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Impact of musculoskeletal degradation on cancer outcomes and strategies for management in clinical practice

Published online by Cambridge University Press:  03 November 2020

Aoife M. Ryan*
Affiliation:
School of Food & Nutritional Sciences, College of Science, Engineering & Food Science, University College Cork, Cork, Republic of Ireland Cork Cancer Research Centre, University College Cork, Cork, Republic of Ireland
Erin S Sullivan
Affiliation:
School of Food & Nutritional Sciences, College of Science, Engineering & Food Science, University College Cork, Cork, Republic of Ireland
*
*Corresponding author: Aoife M. Ryan, email a.ryan@ucc.ie
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Abstract

The prevalence of malnutrition in patients with cancer is one of the highest of all patient groups. Weight loss (WL) is a frequent manifestation of malnutrition in cancer and several large-scale studies have reported that involuntary WL affects 50–80% of patients with cancer, with the degree of WL dependent on tumour site, type and stage of disease. The study of body composition in oncology using computed tomography has unearthed the importance of both low muscle mass (sarcopenia) and low muscle attenuation as important prognostic indications of unfavourable outcomes including poorer tolerance to chemotherapy; significant deterioration in performance status and quality of life (QoL), poorer post-operative outcomes and shortened survival. While often hidden by excess fat and high BMI, muscle abnormalities are highly prevalent in patients with cancer (ranging from 10 to 90%). Early screening to identify individuals with sarcopenia and decreased muscle quality would allow for earlier multimodal interventions to attenuate adverse body compositional changes. Multimodal therapies (combining nutritional counselling, exercise and anti-inflammatory drugs) are currently the focus of randomised trials to examine if this approach can provide a sufficient stimulus to prevent or slow the cascade of tissue wasting and if this then impacts on outcomes in a positive manner. This review will focus on the aetiology of musculoskeletal degradation in cancer; the impact of sarcopenia on chemotherapy tolerance, post-operative complications, QoL and survival; and outline current strategies for attenuation of muscle loss in clinical practice.

Type
Conference on ‘Diet and Digestive Disease’
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press on behalf of The Nutrition Society.

Involuntary weight loss (WL) is a hallmark feature of cancer-associated malnutrition, the prevalence of which has frequently been shown to be one of the highest of all hospital patient groups(Reference Raja, Lim and Lim1Reference Kruizenga, van Keeken and Weijs3). Several large scale studies over the past 40 years have reported that involuntary WL affects 50–80 % of patients with cancer with the degree of WL dependent on tumour site, type and stage of disease(Reference Bozzetti and Group4Reference Ní Bhuachalla, Daly and Power7).

Malnutrition and involuntary WL at the time of diagnosis and deterioration of nutritional status during treatment, are associated with poor outcomes. A recent large international cohort of 8160 patients with cancer suggesting that WL of as little as 2⋅4 % predicts survival independent of disease, site, stage or performance score(Reference Martin, Senesse and Gioulbasanis6). In addition to the adverse impact on survival, WL has historically been associated with severe chemotherapy-related toxicity(Reference Andreyev, Norman and Oates8Reference Cushen, Power and Teo12); and leads to a significant deterioration in a patients' performance status, psychological well-being and overall quality of life (QoL)(Reference Wheelwright, Darlington and Hopkinson13,Reference Daly, Dolan and Power14) .

Aetiology of malnutrition in cancer

The aetiology of malnutrition in cancer is multifactorial and includes the effect of nutrition impact symptoms (NIS) on oral intake, as well as complex metabolic alterations inherent in the disease process(Reference Argiles, Busquets and Stemmler15). The pathophysiology includes derangement of metabolic and hormonal processes due to inflammatory mediators produced by the tumour microenvironment, which can impair appetite and promote an inflammatory state associated with increased energy requirements and anabolic resistance(Reference Baracos, Martin and Korc16,Reference Baracos17) . Therefore, reduced dietary intake, increased requirements, altered substrate utilisation and anabolic resistance, combined with the reduced anabolic stimulus in the form of exercise, all contribute to malnutrition in cancer.

Nutrition impact symptoms

As well as abnormal metabolism of nutrients, patients with cancer often experience a reduction in oral intake and absorption due to nutrition impact symptoms such as anorexia, dysgeusia, nausea, constipation diarrhoea, dysphagia, malabsorption and early satiety. NIS are caused by both the disease itself and cancer treatments. Underlying causes range from the mass-effect of tumours (in the case of pain and dysphagia), as well as more complex, centrally mediated mechanisms such as attenuated orexigen production (caused by systemic inflammation), to iatrogenic conditions such as radiation enteritis(Reference Schiessel and Baracos18). NIS are strongly associated with malnutrition, specifically anorexia and WL(Reference Del Fabbro, Hui and Dalal19). Most NIS reported are of gastrointestinal origin, for example; nausea, vomiting, constipation, taste and smell changes, dumping syndrome and dysphagia. However, pain, fatigue, reduced functional capacity, financial concerns(Reference Nicolini, Ferrari and Masoni20Reference Omlin, Blum and Wierecky22) and depression are also noted by many patients. These varying symptoms all have a profound impact on QoL(Reference Tong, Isenring and Yates23) and performance status(Reference Attar, Malka and Sabate24). The impact of NIS on performance status is of particular concern as reduced activity levels feed the cycle of cachexia. in that, reduced stimulus to the muscles can lead to muscle atrophy alongside the muscle wasting associated with a lack of substrate and anabolic resistance(Reference Antoun and Raynard25).

Metabolic derangements and increased energy expenditure

While reduced oral intake is a significant contributor to WL in cancer, a recent review showed that in studies where nutritional intake is controlled, WL persists in many patients(Reference Martin and Kubrak26), suggesting that factors such as hypermetabolism and anabolic resistance contribute to cancer-related WL(Reference Vazeille, Jouinot and Durand27). The presence of cancer in the body causes a variety of metabolic and endocrine changes (such as inflammation, anabolic resistance, proteolysis, lipolysis and futile cycling) induced by the tumour and activated immune cells. Complex interactions between inflammation (pro-inflammatory cytokines), neuro-hormonal changes and potential proteolytic and lipolytic factors produced by the host and the tumour, fuel WL and loss of lean mass(Reference Argiles, Busquets and Stemmler15). Hypermetabolism is also thought to be a significant contributor to energy deficits, with resultant WL. Depending on the tumour burden, and the level of anaerobic metabolism, an additional 418–5858 kJ (100–1400 kcals) can be required daily(Reference Friesen, Baracos and Tuszynski28). In addition, significantly increased production of acute-phase proteins and cytokines is an energy-intensive process(Reference Argiles, Busquets and Stemmler15) and receptors for many cytokines are expressed in the feeding centres of the hypothalamus, therefore inflammation-mediated changes in the hypothalamic-pituitary axis result in illness behaviour(Reference Baracos, Martin and Korc16), including aberrations in appetite signalling and inhibition of orexigens resulting in poor oral intake(Reference Grossberg, Scarlett and Marks29). Additional factors such as the browning of adipose tissue(Reference Chu, Bos and Gill30), changes in carbohydrate metabolism (Cori cycle upregulation), changes in fat metabolism (fatty acid cycling), increased insulin resistance(Reference Dev, Bruera and Dalal31) and the demand for amino acids to drive the inflammatory response, results in increased muscle proteolysis and reductions in lean mass, which affects both skeletal muscle and muscular organs, such as the heart(Reference Argiles, Busquets and Stemmler15). Furthermore, upregulation of the ubiquitin-proteasome pathway leads to increased muscle degradation(Reference Muscaritoli, Bossola, Doglietto, Mantovani, Anker, Inui, Morley, Fanelli, Scevola, Schuster and Yeh32).

Increase in sedentary behaviour

A doubly-labelled water study quantifying the physical activity level (PAL) of healthy adults found that the PAL of a sedentary adult is 1⋅4–1⋅5(Reference Black, Coward and Cole33). Compared to this, patients with cancer have been shown in a number of studies to be significantly more inactive that this, with Moses et al. reporting on twenty-four pancreatic cancer patients with cachexia, who had a mean PAL of 1⋅24(Reference Moses, Slater and Preston34) and Gibney et al. who found that lung cancer patients had a PAL of 1⋅36(Reference Gibney, Elia and Jebb35). These values correspond better with the severely disabled than any healthy, sedentary population. Community living spinal cord injury patients have been demonstrated to have a PAL of 1⋅32(Reference Mollinger, Spurr and el Ghatit36) and young patients with cerebral palsy a PAL of 1⋅23(Reference Stallings, Zemel and Davies37). These findings attest to the marked impact of advanced cancer and cachexia on the physical function and QoL of such patients. Levels of physical activity this low may exacerbate muscle wasting and it is well understood in any individual that a lack of physical activity will cause deconditioning and deterioration in muscle mass.

Weight loss and changes in body composition following a cancer diagnosis

The end results of the factors discussed earlier is involuntary WL which is a hallmark feature cancer-associated malnutrition. Often referred to as cancer cachexia, it is now accepted to be a multifactorial syndrome characterised predominantly by the ongoing loss of skeletal muscle mass (with or without loss of fat mass) that cannot be fully reversed by conventional nutrition support(Reference Fearon, Strasser and Anker38). Moderate-to-severe WL is present in 30–70 % of cancer patients(Reference Tangvik, Tell and Guttormsen2,Reference Bozzetti and Group4Reference Ní Bhuachalla, Daly and Power7,Reference Ryan, Power and Daly39) . In the largest study to-date of 8160 patients with locally advanced or metastatic disease, 73 % experienced involuntary WL(Reference Martin, Senesse and Gioulbasanis6). Table 1 summarises the prevalence of >5 % WL (a key component of the diagnostic criteria of cancer cachexia(Reference Fearon, Strasser and Anker38)) according to tumour site in the scientific literature. WL has consistently been shown to be most frequent in patients with cancers in the upper gut and lung(Reference Bachmann, Heiligensetzer and Krakowski-Roosen40Reference Nemer, Krishna and Shah44).

Table 1. Prevalence of patients with >5% weight loss according to primary tumour location in the scientific literature

While involuntary WL is reported by the majority of patients with cancer, a significant proportion remain overweight or obese by international standards, thus appearing well-nourished(Reference Bozzetti45). Recent studies have reported that between 40 and 60 % of cancer patients are overweight or obese (BMI >25 kg/m2) even in the setting of metastatic disease(Reference Martin, Senesse and Gioulbasanis6,Reference Ní Bhuachalla, Daly and Power7,Reference Gioulbasanis, Martin and Baracos46Reference Ramos Chaves, Boleo-Tome and Monteiro-Grillo48) . In a recent pooled analysis of twenty-two randomised trials that included 11 724 patients with cancer, 67 % were shown to be overweight or obese at the time of their cancer diagnosis(Reference Greenlee, Unger and LeBlanc49). As a result, many patients with cancer-related malnutrition are diagnosed with malnutrition late in the course of their disease as nutritional screening instruments such as the Malnutrition Universal Screening Tool, and others, are primarily based on BMI and do not identify these patients as malnourished until they have lost significant weight. Neither BMI nor percentage WL can capture changes in body composition and specifically changes in muscle mass(Reference Bozzetti45). Muscle loss is the most clinically relevant phenotypic feature of cancer cachexia and identifying those with muscle loss can become a huge challenge in overweight and obese patients(Reference Ryan, Power and Daly39). It is also important to note that although muscle loss is commonly associated with cancer, cancer is a disease associated with ageing, and therefore the aetiology of muscle loss in patients with cancer can be 2-fold, first resulting from the age-related decline in muscle mass and second due to cytokine-mediated degradation of muscle and adipose depots, hypermetabolism and anorexia associated with cancer cachexia(Reference Argiles, Busquets and Stemmler15). Distinguishing the exact cause of muscle loss can be difficult.

Lean mass

Computed tomography is now considered a gold standard method of body composition assessment and is of particular convenience in oncology research as these scans are readily available because they are used as part of routine medical care. Axial computed tomography images at the level of L3 are analysed to determine muscle mass, muscle radiodensity and adipose tissue mass (total, subcutaneous and visceral) and excellent inter-observer reliability has been shown(Reference Aubrey, Esfandiari and Baracos50). Regression formulae are available to estimate whole-body compartments using these data. Computed tomography allows the precise quantification of both muscle and adipose tissue and has led to a large volume of research which has increased our understanding of the importance of abnormal body composition phenotypes, such as low muscle mass (sarcopenia), and more recently low muscle attenuation (MA) as important prognostic indicators of unfavourable outcomes in patients with cancer(Reference Martin, Senesse and Gioulbasanis6,Reference Daly, Power and O'Reilly11,Reference Cespedes Feliciano, Kroenke and Bradshaw51,Reference van Vugt, Braam and van Oudheusden52) .

Sarcopenia

Sarcopenia is defined by The European Working Group on Sarcopenia in Older People as ‘a syndrome of progressive and generalised loss of skeletal muscle mass and strength with a risk of adverse outcomes such as physical disability, poor quality of life and death’(Reference Cruz-Jentoft, Baeyens and Bauer53,Reference Cruz-Jentoft, Bahat and Bauer54) . While muscle loss is a normal part of ageing, this syndrome can also occur in association with disease, such as cancer. A generally accepted cut-point is skeletal muscle mass 2 standard deviations below that of a healthy, young population(Reference Baumgartner, Koehler and Gallagher55).

Sarcopenia is now known to relate to asthenia, fatigue, impaired physical function, increased chemotherapy toxicity, impaired QoL and reduced survival(Reference Martin, Senesse and Gioulbasanis6,Reference Wheelwright, Darlington and Hopkinson13,Reference Bozzetti45,Reference Prado, Cushen and Orsso56) . Recent studies have shown that cancer, and its treatment, exacerbate muscle loss and that patients continually lose muscle mass while on treatment(Reference Daly, Power and O'Reilly11,Reference Daly, Ní Bhuachalla and Power57,Reference Rutten, van Dijk and Kruitwagen58) . While healthy adults over the age of 40 years have been shown to lose muscle at a rate of 1–1⋅4 %/year(Reference Frontera, Zayas and Rodriguez59), cancer patients have been shown to have a 24-fold higher rate of muscle loss than that observed in healthy ageing adults(Reference Daly, Ní Bhuachalla and Power57,Reference Blauwhoff-Buskermolen, Versteeg and de van der Schueren60) . In studies examining the rate of muscle loss in cancer patients, rates of 3⋅9 %/100 days have been reported in foregut cancer(Reference Daly, Ní Bhuachalla and Power57), 3⋅1 %/100 days in pancreatic cancer(Reference Tan, Birdsell and Martin61) 3⋅3 %/100 days in metastatic melanoma(Reference Daly, Power and O'Reilly11) and 5⋅2 %/100 days in ovarian cancer(Reference Rutten, van Dijk and Kruitwagen58).

Prevalence of cancer cachexia and sarcopenia in oncology

The prevalence of cancer cachexia and sarcopenia can vary widely depending on the method of assessment and diagnostic criteria used(Reference Daly, Prado and Ryan62). From the literature, it can be estimated that the prevalence of cancer cachexia (based on WL >5 % as per the recent consensus definition(Reference Fearon, Strasser and Anker38)) can vary between 13 and 61 % depending on the tumour site (Table 1), and between 38 and 70 % of patients are considered to have sarcopenia (based on three of the most commonly used diagnostic criteria) (see Fig. 1). The prevalence of sarcopenia is highest in the lung (median 70 %, range 47–79 %)(Reference Baracos, Reiman and Mourtzakis63Reference Kim, Kim and Park66) and pancreatic cancer (median 56 %, range 44–89 %)(Reference Wesseltoft-Rao, Hjermstad and Ikdahl41,Reference Tan, Birdsell and Martin61,Reference Sandini, Patino and Ferrone67Reference Carrara, Pecorelli and De Cobelli73) however, it is noteworthy that the majority of studies report a prevalence of above 40 % at most other sites in the body.

Fig. 1. Prevalence of sarcopenia in patients with cancer according to the primary tumour location in the literature (all stages).(Reference Baracos, Reiman and Mourtzakis63Reference El Amrani, Vermersch and Fulbert68,Reference Fattouh, Chang and Ow136,Reference Wesseltoft-Rao, Hjermstad and Ikdahl41,Reference Tan, Birdsell and Martin61,Reference Di Sebastiano, Yang and Zbuk69Reference Carrara, Pecorelli and De Cobelli73,Reference Mir, Coriat and Blanchet111,Reference Elliott, Doyle and Murphy180,Reference Harimoto, Shirabe and Yamashita256Reference Black, Mackay and Ramsay260,Reference Tan, Brammer and Randhawa90,Reference Yip, Goh and Davies94,Reference Anandavadivelan, Brismar and Nilsson261Reference Awad, Tan and Cui264,Reference Cushen, Power and Teo12,Reference Antoun, Lanoy and Albiges-Sauvin113,Reference Paireder, Asari and Kristo265Reference Psutka, Boorjian and Moynagh270,Reference Auclin, Bourillon and De Maio95,Reference Huillard, Mir and Peyromaure271Reference Mason, Boorjian and Bhindi275,Reference van Vugt, Braam and van Oudheusden52,Reference Blauwhoff-Buskermolen, Versteeg and de van der Schueren60,Reference Camus, Lanic and Kraut149,Reference Lanic, Kraut-Tauzia and Modzelewski150,Reference Xiao, Luo and O'Brian276,Reference Thoresen, Frykholm and Lydersen277,Reference Lieffers, Bathe and Fassbender185,Reference Black, Mackay and Ramsay260,Reference van Roekel, Bours and Te Molder278Reference Chemama, Bayar and Lanoy280,Reference Kurk, Peeters and Dorresteijn86Reference van der Kroft, Bours and Janssen-Heijnen88,Reference McSorley, Black and Horgan281,Reference Reisinger, van Vugt and Tegels282,Reference Broughman, Williams and Deal283Reference Barret, Antoun and Dalban287,Reference Palmela, Velho and Agostinho91,Reference Jarvinen, Ilonen and Kauppi288Reference Psutka, Carrasco and Schmit293,Reference Daly, Power and O'Reilly11,Reference Martin, Birdsell and Macdonald47,Reference Daly, Ní Bhuachalla and Power57,Reference Rutten, van Dijk and Kruitwagen58,Reference Prado, Lieffers and McCargar92,Reference Ataseven, Luengo and du Bois162,Reference Hayashi, Ando and Gyawali164,Reference Nishigori, Okabe and Tanaka268,Reference Kumar, Moynagh and Multinu294,Reference Valentine, François and Nora295,Reference Ní Bhuachalla, Daly and Power7,Reference Shachar, Deal and Weinberg93,Reference Veasey Rodrigues, Baracos and Wheler96,Reference Prado, Baracos and McCargar100,Reference Rier, Jager and Sleijfer165,Reference Del Fabbro, Parsons and Warneke296Reference Deluche, Leobon and Desport299) .

Prevalence of sarcopenia defined using three of the most common definitions for defining low muscle mass is displayed in Table 1. These definitions are as follows; Prado et al.(Reference Prado, Lieffers and McCargar92): Skeletal muscle index (SMI)<52⋅4 cm2/m2 in men and <38⋅5 cm2/m2 in women; Martin et al.(Reference Martin, Birdsell and Macdonald47): SMI <43⋅0 cm2/m2 in men with a BMI <25 kg/m2 and <53⋅0 cm2/m2 in men with a BMI >25 kg/m2 and SMI <41⋅0 cm2/m2 in women; Baumgartner et al.(Reference Baumgartner, Koehler and Gallagher55) converted dual-energy X-ray absorptiometry cut points by Mourtzakis et al.(Reference Mourtzakis, Prado and Lieffers300) as SMI <55 4 cm2/m2 in men and <38⋅9 cm2/m2 in women.

Our group recently estimated the incidence and prevalence of cachexia and sarcopenia in the UK and Ireland(Reference Sullivan, Daly and Power74). We estimated that across the Republic of Ireland and UK at least 128 892 cancer patients are affected by WL >5 % annually (34 %) and that there are 716 124 cancer survivors who have suffered >5 % WL at some point in their disease trajectory. Furthermore, we estimated that there are at least 133 707 annual cases of cancer patients with sarcopenia (35 %) and 771 589 cancer survivors alive who have been affected by sarcopenia during their disease trajectory.

The rates of muscle wasting seen in cancer populations are of huge public health importance, given that cancer cachexia and sarcopenia have been reported to be unequivocally associated with negative clinical outcomes in patients with cancer including poorer tolerance to anti-cancer treatment, poorer overall QoL, increased risk of post-operative complications and poorer overall survival(Reference Martin, Senesse and Gioulbasanis6,Reference Wheelwright, Darlington and Hopkinson13,Reference Prado, Cushen and Orsso56,Reference Daly, Prado and Ryan62) .

Skeletal degradation in cancer treatment

As well as the ongoing loss of muscle mass, several anti-cancer therapies (both hormonal and non-hormonal) promote bone loss through direct dysregulation of bone turnover and indirectly through hypogonadism and nephrotoxicity. The rate of bone loss from cancer therapy can be ten times higher than in the general population(Reference Sturgeon, Mathis and Rogers75Reference Maillefert, Sibilia and Michel79) but is highest in breast and prostate cancer(Reference Sturgeon, Mathis and Rogers75) due to commonly administered therapies such as endocrine therapy (breast cancer) and androgen deprivation therapy (prostate cancer). Chemotherapy drugs (cisplatin, doxorubicin, cyclophosphamide, ifosfamide, FOLFIRI, carboplatin, methotrexate and targeted therapies) cause reduced bone volume and radiation therapy, orchiectomy and oophorectomy also result in bone loss. The onset of bone loss from premature menopause is sudden (within 6 months of treatment) and significant (21 % decreased density v. age-matched menstruating women(Reference Cann, Martin and Genant80)). For men with prostate cancer on androgen deprivation therapy loss of bone starts within 6–9 months with annual declines of between 2 and 8 %(Reference Berruti, Dogliotti and Terrone81Reference Diamond, Higano and Smith83). Reduction in bone quality is also further exacerbated by inactivity. Muscle weakness and exercise intolerance can persist from months to years after remission(Reference Winters-Stone, Bennett and Nail84,Reference Nicolson and Conklin85) . Excess bone resorption can lead to fractures and spinal cord compression(Reference Sturgeon, Mathis and Rogers75).

Why malnutrition matters: impact on tolerance to systemic chemotherapy

Chemotherapy can often be associated with severe toxicity that can result in dose delays, dose reductions and treatment termination, referred to as dose limiting toxicities. Moderate to severe toxicities can lead to interruption, deferral or even cessation of treatment. Severe toxic events can result in hospitalisations and can even be life-threatening. Recent evidence suggest that variability in body composition of cancer patients may be a source of disparities in the metabolism of cytotoxic agents resulting in increased toxicity(Reference Kurk, Peeters and Dorresteijn86Reference van der Kroft, Bours and Janssen-Heijnen88).

To date, in excess of forty studies have examined the relationship between low lean mass (sarcopenia) and the prevalence of dose limiting toxicity in patients with cancer (we have previously reviewed these(Reference Ryan, Prado and Sullivan89)). The relationship between sarcopenia and increased chemotherapy toxicity has been reported in both early and late-stage disease, at almost all cancer sites and with many modalities of cytotoxic agents (cytotoxic single agents, regimens, targeted agents and immunotherapies)(Reference Tan, Brammer and Randhawa90Reference Shachar, Deal and Weinberg93). Although the relationship between low lean mass and poorer tolerance to treatment has been observed in the majority of studies, a few smaller studies have reported no association(Reference Blauwhoff-Buskermolen, Versteeg and de van der Schueren60,Reference Rollins, Tewari and Ackner71,Reference Yip, Goh and Davies94Reference Versteeg, Blauwhoff-Buskermolen and Buffart99) .

Low lean mass can lead to increased toxic side effects to chemotherapy through alterations in the distribution, metabolism and clearance of chemotherapy drugs(Reference Prado, Baracos and McCargar100). The widespread use of body surface area (BSA), relying on height and weight alone(Reference Du Bois and Du Bois101), in dosing chemotherapy drugs presents a problem as there are large discrepancies in muscle mass between people of the same BSA, resulting in potential under or over-dosing when calculations are based on a simple BSA formula(Reference Stobäus, Küpferling and Lorenz102Reference Prado, Antoun and Sawyer104). A 4–10-fold variation in drug clearance is possible in individuals with a similar BSA and there is concern that this approach to dosing is invalid(Reference Takimoto105,Reference Baker, Verweij and Rowinsky106) . Bodyweight comprises two major components (lean and fat mass) then these are the two major sites of distribution of hydrophilic and lipophilic drugs(Reference Prado, Baracos and McCargar107,Reference Prado, Baracos and Xiao108) . Therefore, variability in individual lean mass or fat mass may lead to changes in the volume of distribution of drugs and therefore adversely affect the tolerance of cytotoxic drugs(Reference Daly, Prado and Ryan62). In sarcopenic obesity, tolerance is further compromised in individuals where the combination of excessive fat mass and low lean mass may significantly impact the tolerance of hydrophilic drugs by resulting in a disproportionally small volume of drug distribution in relation to their body weight or BSA(Reference Prado, Baracos and McCargar100,Reference Prado, Baracos and McCargar107) . Variations in lean and fat mass can therefore lead to considerable variation in the milligram of chemotherapy drug per kilogram lean mass with higher doses per kilogram lean mass shown to be associated with more frequent and severe toxic side effects(Reference Prado, Baracos and McCargar107,Reference Sjøblom, Benth and Grønberg109,Reference Sjøblom, Grønberg and Benth110) . This hypothesis is supported by pharmacokinetic data, with sarcopenic patients experiencing higher plasma concentrations of antineoplastic drugs and experiencing more toxicity(Reference Mir, Coriat and Blanchet111,Reference Massicotte, Borget and Broutin112) . For lipophilic drugs such as doxorubicin or trabectedin, individuals with a low-fat mass may also present with toxicity due to a reduced volume of distribution(Reference Prado, Baracos and Xiao108).

It is also important to note that sarcopenic patients are excessively fragile and highly susceptible to acute medical events that exacerbate chemotherapy-related toxicity(Reference Antoun, Lanoy and Albiges-Sauvin113). In addition, for those patients with systemic inflammation, this has been shown to decrease liver cytochrome activities and drug clearance and may modify drug exposure. Low concentrations of circulation plasma proteins (e.g. albumin), which is commonly seen in those with malnutrition or systemic inflammation (or both) may also affect the distribution of highly protein-bound drugs such as vandetanib, sorafenib and epirubicin(Reference Prado, Baracos and Xiao108,Reference Mir, Coriat and Blanchet111,Reference Massicotte, Borget and Broutin112) . As imaging techniques in body composition become more widely used, this may represent an opportunity for a more personalised approach to chemotherapy dosing.

Why malnutrition matters: impact on performance status and quality of life

The adverse impact of WL on QoL has long been recognised in patients with cancer and WL has been associated with deterioration in patients' performance status and psychosocial well-being(Reference Bachmann, Heiligensetzer and Krakowski-Roosen40,Reference Blum, Omlin and Baracos114,Reference Ravasco, Monteiro-Grillo and Vidal115) . In a recent systematic review examining the impact of WL and QoL, a negative relationship between %WL and QoL was reported in twenty-three of twenty-seven studies included in the analysis(Reference Wheelwright, Darlington and Hopkinson13). However, the mode by which WL exerts its influence on QoL is not fully understood but may relate to muscle atrophy associated with cachexia and WL leading to fatigue or reduced functional capacity(Reference Fearon, Voss and Hustead116). The negative impact on QoL is unsurprising, considering cancer-related malnutrition is a major cause of fatigue(Reference Evans and Lambert117,Reference Ryan, Carroll and Ryan118) , reduced functional ability(Reference Fearon, Voss and Hustead116) and a source of emotional distress(Reference Evans and Lambert117,Reference Hopkinson, Brown and Okamoto119) . Our group recently reported on a cohort of 1027 patients with advanced cancer and showed that WL >10 % was associated with poorer QoL in almost all functional and symptom domains(Reference Daly, Dolan and Power14). In particular, WL in excess of 10 % in the preceding 3 months was independently associated with poorer physical function, fatigue and appetite loss and overall poorer QoL summary scores.

While there is no doubt that WL impacts negatively on QoL, inconsistent reports on the relationship between muscle parameters and QoL have been published in the literature(Reference Parsons, Tsimberidou and Pontikos97,Reference Neefjes, van den Hurk and Blauwhoff-Buskermolen120Reference Bye, Sjøblom and Wentzel-Larsen122) . Parsons and colleagues reported no significant associations between low Skeletal muscle index and symptom burden or functional life domains assessed by the MD Anderson Symptom Inventory, in a cohort of 104 patients with advanced cancer(Reference Parsons, Tsimberidou and Pontikos97). However, in a study of 734 advanced lung cancer patients, low Skeletal muscle index was non-linearly associated with lower global QoL, physical function and role function, and associated with more symptoms (fatigue and pain), while low MA was associated with poor physical function and more dyspnoea(Reference Bye, Sjøblom and Wentzel-Larsen122). Sarcopenia has also been associated with greater depression symptoms and more fatigue in patients with advanced cancer(Reference Neefjes, van den Hurk and Blauwhoff-Buskermolen120,Reference Nipp, Fuchs and El-Jawahri121) . It may be that low Skeletal muscle index, at a single time point, is not reflective of a dynamic measure of loss and may be influenced by a patient's intrinsic level of muscularity. Perhaps the loss of muscle over time may better reflect poor QoL and further research is needed in this area.

The mode by which WL exerts its influence on QoL is not fully understood but may relate to muscle atrophy associated with cachexia and WL leading to fatigue or reduced functional capacity. Recent work has suggested that the complex interplay between metabolic disruption and pro-inflammatory cytokines (i.e. IL-6, IL-8 and TNF-α) in cancer cachexia often leads to physical, biochemical and nutritional deterioration which subsequently leads to poor QoL(Reference Aapro, Arends and Bozzetti123). It is thought that the systemic inflammatory response has a direct role in the development of cancer-associated symptom clusters, including pain, fatigue, mood, anorexia and physical function(Reference McSorley, Dolan and Roxburgh124). Systemic inflammation and loss of lean mass are also thought to drive cancer-related fatigue, which is thought to affect up to 80 % of cancer patients(Reference Baguley, Skinner and Wright125) both during and after treatment cessation(Reference Baguley, Skinner and Wright125Reference Wang, Zhao and Fisch128). Severe and persistent fatigue, along with muscle mass wasting has been shown to inhibit QoL by considerably reducing functional capacity to fully participate in daily living tasks(Reference Baguley, Skinner and Wright125). Individual proinflammatory cytokines have been associated with clinical symptoms, e.g., IL-6 and C-reactive protein with anorexia(Reference Paulsen, Laird and Aass129), IL-1ra with fatigue(Reference Paulsen, Laird and Aass129) and IL-6 with major depression(Reference Du, Zhang and Li130,Reference Breitbart, Rosenfeld and Tobias131) . Our group recently reported that systemic inflammation has a negative impact on QoL that is independent of Eastern Cooperative Oncology Group performance status(Reference Daly, Dolan and Power14) which is consistent with previous reports indicating that the systemic inflammatory response is associated with poorer QoL, even in those with a good performance score(Reference Laird, Fallon and Hjermstad132).

Importantly, interventions aimed at targeting nutritional status and attenuating weight have proven successful in improving aspects QoL in patients with cancer(Reference Baldwin, Spiro and Ahern133). In addition, novel cachexia treatments, such as Anamorelin, an oral ghrelin-receptor agonist with appetite enhancing and anabolic activity have shown a favourable clinical response in alleviating anorexia-cachexia symptoms(Reference Temel, Abernethy and Currow134). Research is warranted to determine if attenuating the systemic inflammatory response is capable of producing clinically relevant improvements in symptoms that may represent a new therapeutic approach to symptom management in patients with advanced cancer.

Impact on survival

The impact of sarcopenia on survival in cancer has been extensively studied over the past decade. Most studies report a significant decrease in overall survival in patients with sarcopenia compared with those without sarcopenia, irrespective of the primary cancer site and stage (see Fig. 2). Figure 1 displays a forest plot depicting the summary results of meta-analyses examining the role of sarcopenia in survival in cancer. To-date sarcopenia (diagnosed by computed tomography) has been shown to be independently associated with poorer survival in all those sites included in the meta-analysis in Fig. 2 as well as in head and neck(Reference Cho, Kim and Keum135Reference Stone, Olson and Mowery140), prostate cancer(Reference Ohtaka, Aoki and Nagata141), cholangiocarcinoma(Reference Coelen, Wiggers and Nio142Reference Okumura, Kaido and Hamaguchi146), lymphoma(Reference Go, Park and Kang147Reference Nakamura, Hara and Shibata151) and leukaemia(Reference Nakamura, Ninomiya and Matsumoto152). In a recent systematic review and meta-analysis of thirty-eight studies that included 7843 patients with solid tumours, low muscle cross-sectional area was observed in 27⋅7 % of patients with cancer and associated with poorer overall survival (hazard ratio (HR) 1⋅44, 95 % CI 1⋅32, 1⋅56), cancer-specific survival (HR 1⋅93, 95 % CI 1⋅38, 2⋅70), as well as disease-free survival (HR 1⋅16, 95 % CI 1⋅00, 1⋅30) but not with progression-free survival (HR 1⋅54, 95 % CI 0⋅90, 2⋅64)(Reference Shachar, Williams and Muss153). This meta-analysis demonstrated that the adverse effects of low lean mass on overall survival were similar in both metastatic (HR 1⋅37, 95 % CI 1⋅21, 1⋅56) and non-metastatic disease (HR 1⋅54, 95 % CI 1⋅31, 1⋅79), and this relationship was observed across different primary tumour sites. Recently, in two of the largest observational cohort studies to date, Caan and colleagues(Reference Caan, Meyerhardt and Kroenke154,Reference Caan, Cespedes Feliciano and Prado155) demonstrated the prognostic value of low muscle mass in non-metastatic breast (n 3241) and colorectal cancer (n 3262). Low lean mass was present in 34 and 42 % of patients, respectively, and was independently associated with a 27–41 % higher risk of overall mortality (colon: HR 1⋅24, (95 % CI 1⋅09, 1⋅48); Breast: HR 1⋅41 (95 % CI 1⋅18, 1⋅69)](Reference Caan, Meyerhardt and Kroenke154,Reference Caan, Cespedes Feliciano and Prado155) .

Fig. 2. (Colour online) Forest Plot depicting summary results of meta-analyses examining the role of sarcopenia in survival in cancer. Asterisks denote studies which did not confirm the inclusion of multivariate data in the meta-analysis(Reference Shachar, Williams and Muss153,Reference Hu, Dou and Shao301Reference Zhang, Meng and Li304,Reference Yang, Shen and Tan305Reference Aleixo, Williams and Nyrop310,Reference Mintziras, Miligkos and Wachter170,Reference Bundred, Kamarajah and Roberts311Reference Borggreve, den Boer and van Boxel315) .

In addition to low muscle area (sarcopenia), low MA (density; indicative of fatty infiltration of muscle tissue) is also associated with poorer survival in a variety of tumours including non-small cell lung cancer(Reference Sjøblom, Grønberg and Wentzel-Larsen156), colorectal(Reference Kroenke, Prado and Meyerhardt157Reference van Baar, Beijer and Bours159), endometrial(Reference de Paula, Rodrigues and Chaves160), renal(Reference Antoun, Lanoy and Iacovelli161), ovarian cancer(Reference Ataseven, Luengo and du Bois162) and melanoma(Reference Sabel, Lee and Cai163). Importantly, in some cases, low MA appears to superior in predicting mortality compared with low lean mass alone(Reference Sjøblom, Grønberg and Wentzel-Larsen156,Reference Hayashi, Ando and Gyawali164Reference Van Rijssen, van Huijgevoort and Coelen167) . However, it has also been demonstrated that the risk of mortality associated with low lean mass and low MA can be independent of each other(Reference Okumura, Kaido and Hamaguchi146,Reference Charette, Vandeputte and Ameye168,Reference Sueda, Takahasi and Nishimura169) .

Lastly, the combination of sarcopenia and obesity has been shown to have particularly poor clinical outcomes. This may be related to the combined negative effects of both conditions or may be related to poor detection of sarcopenia in a cohort whose muscle loss is masked by excess adiposity. Sarcopenic obesity specifically has been associated with poorer survival in a number of cohorts(Reference Prado, Lieffers and McCargar92,Reference Mintziras, Miligkos and Wachter170) .

Why malnutrition matters: impact of muscle loss during treatment and survival

Notwithstanding the impact of sarcopenia on survival, several studies have emphasised that patients continually lose muscle mass while on treatment and that this is associated with an increased risk of mortality in a number of cancers. Patients with advanced pancreatic cancer (n 97) who experienced the early loss of skeletal muscle (>10 % within 3 months of diagnosis) were at increased risk of poorer overall survival and progression-free survival compared to patients who did not experience muscle loss to the same degree (HR 2⋅16 (95 % CI 1⋅23, 3⋅78), P = 0⋅007 and HR 2⋅31 (95 % CI 1⋅30, 4⋅09), P = 0⋅004)(Reference Basile, Parnofiello and Vitale171). In patients with surgically resected stage I-III colorectal cancer (n 1924), those who experienced the largest decrease in muscle mass (≥2 standard deviations or the equivalent to ≥11⋅4 % loss) and the largest decline in mean MA (≥2 sd; ≥20⋅2 % loss) from baseline were at a significantly increased risk of mortality (HR 2⋅15, 95 % CI 1⋅59, 2⋅92), P < 0⋅001 and HR 1⋅61 95 % CI 1⋅20, 2⋅15, P = 0⋅002, respectively), and these findings were independent of changes in body mass or other body composition parameters(Reference Brown, Caan and Meyerhardt158). To date, losses in muscle have been shown to be prognostic of reduced survival in pancreatic(Reference Dalal, Hui and Bidaut72,Reference Basile, Parnofiello and Vitale171) , oesophageal(Reference Yoon, Oh and Ahn172), gastric(Reference Park, Kim and Beom173), lung(Reference Nattenmuller, Wochner and Muley174), colorectal(Reference Blauwhoff-Buskermolen, Versteeg and de van der Schueren60,Reference Takeda, Akiyoshi and Matsueda175,Reference Miyamoto, Baba and Sakamoto176) , ovarian(Reference Rutten, van Dijk and Kruitwagen58), melanoma(Reference Daly, Power and O'Reilly11) and foregut cancers(Reference Daly, Ní Bhuachalla and Power57).

Why malnutrition matters: impact on surgical outcomes

In cancer patients undergoing surgery, length of stay and post-operative complications are important indicators of surgical morbidity. Sarcopenia has been independently associated with adverse post-operative outcomes including infections, complications, the longer length of hospital stay and risk of readmission following gastrectomy(Reference Lou, Chi and Chen177,Reference Zhang, Wang and Wang178) , pancreatectomy(Reference Cao, Xiong and Zhong179), oesophagectomy(Reference Elliott, Doyle and Murphy180,Reference Ida, Watanabe and Yoshida181) , cystectomy(Reference Mao, Ma and Wang182)pneumonectomy(Reference Madariaga, Troschel Cand Med and Best Cand Med183,Reference Kawaguchi, Hanaoka and Ohshio184) and colectomy(Reference Lieffers, Bathe and Fassbender185Reference Zhang, Tan and Jiang187). Even in those without complications, length of stay has been shown to be significantly longer in patients with muscle abnormalities(Reference Martin, Hopkins and Malietzis188Reference Gani, Buettner and Margonis190).

Potential therapies for malnutrition in cancer

Despite much evidence that impaired nutritional status is associated with poor outcomes, the evidence-base regarding the optimal management of malnutrition in cancer and the ability to improve nutritional status to improve clinical outcomes is lacking(Reference Arends, Bachmann and Baracos191). While the treatment of malignancy is the primary method of reversing the metabolic environment which perpetuates cachexia, supportive care is required while this process ensues. In the early stages of cancer cachexia, malnutrition may be reversible; however, in later stages of the disease, it has been difficult to attain significant improvements in nutritional status, although it has been suggested that with the right combination of therapies, even patients with advanced disease may exhibit anabolic potential.

Dietetic management

Nutritional interventions have been a mainstay of cachexia management to date. Nutritional counselling, consisting of dietary advice and ongoing education is the first line for treatment of malnutrition(Reference Arends, Bachmann and Baracos191). While a food-first approach to a high-protein, high-energy diet is recommended, nutrition support, starting with the use of oral nutritional supplements is frequently required to augment volitional intake where appetite is limited. Furthermore, artificial nutrition in the form of enteral or parenteral nutrition may be required due to dysphagia, obstruction of the gastrointestinal tract or severe malabsorption(Reference Arends192). The European Society for Clinical Nutrition and Metabolism (ESPEN) released consensus guidelines in 2017 for the nutritional management of cancer patients(Reference Arends, Bachmann and Baracos191). Despite limited evidence that nutritional interventions improve clinical outcomes, ESPEN strongly recommends, with moderate evidence, that nutritional interventions be employed in those at risk of malnutrition, aiming to increase oral intake, by providing dietary advice, management of metabolic derangements and nutrition impact symptoms, as well as the provision of oral nutritional supplementation where needed. ESPEN recommend that patients' total energy expenditure be assumed as 105–126 kJ/kg (25–30 kcal/kg) body weight daily, unless the direct measurement is available. Given that cancer patients can be hypo-, normo- or hypermetabolic, and displaying varying levels of anabolic resistance, it seems reasonable, in the absence of direct measurements, to take a pragmatic approach, and adjust requirements according to clinical response to the initial estimation.

Apart from energy requirements, meeting protein needs is also a priority in order to maintain lean mass and support recovery throughout the cancer journey. ESPEN recommend 1–1⋅5 g protein/kg body weight in cancer patients but suggest that research is necessary to determine whether a higher level such as 2 g/kg may be beneficial(Reference Arends, Bachmann and Baracos191). PRIMe (ClinicalTrials.gov ID: NCT 02788955) is a feasibility study (n 40) comparing isoenergetic diets in colorectal cancer with either 1 g protein/kg body weight or 2 g protein/kg body weight and assessing the impact of the varying protein intakes on muscle mass and physical functioning.

A number of individual studies have demonstrated positive impacts of nutritional interventions on relevant outcomes. A number of studies have demonstrated that dietitian-led clinics and intensive dietary counselling can reduce nutrition-related admissions(Reference Kiss, Krishnasamy and Loeliger193,Reference Hall, Englehart and Blaseg194) and reduce the length of stay(Reference De Waele, Mattens and Honore195). Improved energy and protein intake(Reference Uster, Ruefenacht and Ruehlin196,Reference Poulsen, Pedersen and Osterlind197) and weight(Reference Isenring, Capra and Bauer198,Reference Isenring, Capra and Bauer199) were noted in some studies and these increases led to improved QoL, functioning and nutritional status(Reference Ravasco, Monteiro-Grillo and Vidal200).

A recent national survey led by our research group in Ireland examined the attitudes and experiences of patients with cancer (n 1085) to nutrition(Reference Sullivan, Rice and Kingston201). Overall 45 % reported problems with diet and eating, 44 % had experienced involuntary WL (mean loss reported 10⋅4 kg, range 1–44 kg) and 52 % reported they had noticed muscle loss. The majority (67 %) wanted more information on diet with 51 % reported they were concerned about their nutritional status and confused by what to eat. Worryingly one in three with involuntary WL had not been able to access a registered dietitian (RD) for individual advice. Despite ESPEN recommendation that all patients receive routine nutritional screening and intervention early in the course of malnutrition(Reference Arends, Bachmann and Baracos191), access to RD for cancer patients is poor. For example, evidence-based guidelines from Australia recommend that all patients receiving radiotherapy to the gastrointestinal tract or head and neck area are routinely referred to dietitians(Reference Isenring, Zabel and Bannister202), however, a service provision audit in the UK found that only 69 % of head and neck cancer patients see a dietitian, with those having oral tumours the most likely to be referred(Reference Bradley, Zutshi and Nutting203). Generally speaking, there is a lack of dietitians providing care to those affected by cancer. In Ireland, as of 2016, there were thirty-six RD working in cancer care, of which only five are practising outside the capital city of Dublin, which provides only one dietitian to every 1389 active cancer patients(204). This represents all dietitians who cover oncology as part of their role and does not constitute the number of dedicated oncology dietitians. In the USA, there are approximately 1⋅7 full-time equivalent dietitians per outpatient cancer centre, corresponding to 1 RD to 1202 patients(Reference Trujillo, Claghorn and Dixon205). In Ontario, Canada, there are few dietitians practising in oncology and palliative care, with 1⋅1–1⋅6 full-time equivalent full-time equivalent RD per 100 inpatient beds and 0⋅2–1⋅4 full-time equivalent/100 patients in the outpatient setting(206). There is also a lack of specialist dietitians in oncology, with only 370 board-certified oncology specialist dietitians in the USA(Reference O'Sullivan Maillet, Brody and Skipper207).

When malnourished patients are seen by dietitians the mainstay dietary treatment, particularly for those with poor appetite is a ‘little and often, high protein high energy diet’. This diet constitutes a food-first approach which involves counselling patients and their carers on foods that are naturally high in protein and energy and providing meal and snack options to achieve this. Our group has developed several cookbooks to bring this advice to life over the past number of years and these are available as free downloadable e-books at www.breakthroughcancerresearch.ie/books. These resources are written in lay language and provide simple high protein high energy meal options. For some patients with continued problems with poor appetite and early satiety, oral nutritional supplements and/or enteral feeding will be necessary to support their nutritional status during cancer treatment.

Systemic inflammation

As observed by Sir David Cuthbertson in 1942(Reference Cuthbertson208) in reference to the post-shock metabolic response ‘it is doubtful whether, during the early catabolic phase, any dietary measure can effectively suppress the catabolic destruction of protein’. One could argue the same is true for cancer where systemic inflammation is present. Systemic inflammation is present in 30–50 % of advanced cancer populations(Reference Shinko, Diakos and Clarke209) and is an independent factor reducing survival(Reference McMillan210). Over the years several pharmaceutical and dietary factors have been examined to reduce inflammation including corticosteroids, non-steroidal inflammatory drugs, statins and n-3 fatty acids. Corticosteriods appear to increase appetite and QoL for a limited period of time but the optimal dose, duration or timing of intervention is not clear. There is good evidence that non-steroidal anti-inflammatory drugs can lead to increases in body weight in cachexia and a plausible mechanism is the attenuation of cachexia-related inflammation and subsequent modulation of the anabolic resistance associated with cancer cachexia. However, non-steroidal anti-inflammatory drugs do have some risks, such as gastrointestinal bleeding, and so further evidence is needed to prove efficacy and safety in cancer cachexia management(Reference Solheim, Fearon and Blum211). n-3 Fatty acids have been associated with weight stabilisation(Reference Ryan, Reynolds and Healy212,Reference Persson, Glimelius and Ronnelid213) , improved QoL(Reference Lewis, Xun and Fly214,Reference Werner, Kullenberg de Gaudry and Taylor215) and increased chemo-sensitivity(Reference Camargo, Mocellin and Brunetta216) in some studies.

Physical activity

Physical activity and more specifically, structured exercise, has been suggested as part of the management of cancer cachexia(Reference Maddocks, Murton and Wilcock217). Exercise has been shown to be safe in individuals living with and beyond cancer(Reference Turner, Steed and Quirk218) and can promote QoL in patients on active treatment(Reference Mishra, Scherer and Snyder219) and during the survivorship period(Reference Mishra, Scherer and Geigle220). Moreover, the specific QoL domains impacted by exercise are those which are commonly impaired in cancer cachexia (physical functioning, role functioning, fatigue and body image/self-esteem)(Reference Mishra, Scherer and Snyder219,Reference Mishra, Scherer and Geigle220) . Of note, it has been shown that the most QoL benefit is gained from supervised exercise programmes(Reference Sweegers, Altenburg and Chinapaw221) and that those patients with the lowest baselines experience the most improvement in fatigue, QoL, aerobic fitness and physical function, indicating that the patients who are most inactive could benefit from any increase in exercise(Reference Buffart, Sweegers and May222).

Based on the current evidence, the American College of Sports Medicine position is that exercise is safe and beneficial for cancer patients and their guidelines provide evidence-based recommendations in terms of safety measures, and exercise prescription specifics across many tumour types, with a focus on the prescription of physical activity using the frequency, intensity, time, type framework. The recommended target to achieve the documented benefits of exercise programmes in cancer is ≥30 min moderate-intensity aerobic exercise ≥3 times per week for at least 8–12 weeks and resistance training ≥2 times per week (≥2 sets of eight–fifteen repetitions ≥60 % one-repetition maximum)(Reference Campbell, Winters-Stone and Wiskemann223,Reference Schmitz, Courneya and Matthews224) . Likewise, the Clinical Oncology Society of Australia has a position statement, as of 2018, which states that all members of the multidisciplinary team should promote physical activity amongst cancer patients and that patients should be encouraged to return to normal levels of activity as soon as possible after diagnosis and that they should aim for ≥150 min moderate-intensity or 75 min vigorous-intensity aerobic exercise per week and 2–3 sessions of resistance exercise per week (moderate to vigorous-intensity exercises targeting the major muscle groups)(Reference Cormie, Atkinson and Bucci225).

Multimodal approaches

When the multifactorial nature of malnutrition in cancer is considered, it seems reasonable that a multimodal approach to treatment may fare better than a unimodal approach. By targeting multiple aetiologies, there is some evidence that multimodal therapies may have a better chance of attenuating the progression of cachexia(Reference Solheim, Vagnildhaug and Laird226). Multimodal management of cancer cachexia should incorporate general interventions such as nutrition counselling, symptom management and exercise as well as focused interventions that address specific aetiological components of the cancer cachexia syndrome, such as fish oil or non-steroidal anti-inflammatory drug to address increased inflammation or corticosteroids to improve appetite(Reference Del Fabbro227).

Early intervention is of the utmost importance as refractory cachexia remains a challenge, still considered irreversible and associated with a terminal prognosis(Reference Fearon, Strasser and Anker38). The European School of Oncology Task Force's official position is that research should focus on the identification and management of cachexia early in the disease course when it is amenable to treatment(Reference Aapro, Arends and Bozzetti123). Furthermore, it has been suggested that a ‘parallel pathway’ approach should be adopted to ensure that cachexia is managed alongside cancer itself, recognising their inherent connection and avoiding the sentiment that cachexia is an inevitable endpoint associated with advanced disease, but rather focusing on optimising clinical outcomes by preventing the development of malnutrition(Reference Muscaritoli, Molfino and Gioia228).

A systematic review by Hall et al. showed that the current literature base for combined nutrition and exercise programmes in advanced cancer is lacking in strong evidence. While studies to date have shown variable improvements in QoL, overall function, fatigue, endurance/strength, depression and nutritional status, the results are inconsistent across studies and they are often underpowered(Reference Hall, Cook and Maddocks229). The strongest evidence in favour of these trials is only of moderate quality and it suggests that physical endurance and strength, as well as mood, can be improved by these interventions. Further well-designed studies are needed in order to verify the utility of multimodal approaches.

MENAC, a large multi-centre phase III trial (A randomised, open-label trial of a multimodal intervention (exercise, nutrition and anti-inflammatory medication) plus standard care v. standard care alone to prevent/attenuate cachexia in advanced cancer patients undergoing chemotherapy) is currently underway (ClinicalTrials.gov ID: NCT02330926)(Reference Solheim, Laird and Balstad230). Identification of a successful cachexia treatment would mark significant progress in the field of oncology nutrition, and given the impact of nutrition of survival and tolerance to treatment, the oncology field as a whole.

Conclusions

WL and abnormalities of body composition are common across all cancer sites and stages and the aetiology of malnutrition in cancer is multifactorial and complex. It is associated with poorer QoL as well as increased morbidity and mortality and is often considered an inevitable part of the cancer trajectory. Irrespective of baseline BMI, muscle and fat wasting are associated with poorer outcomes; however, simple screening tools using weight and BMI alone miss a large proportion of patients with altered body composition who are at risk nutritionally and therefore, techniques to adequately identify patients at risk of malnutrition must be developed and widely implemented in order to facilitate early-intervention and a parallel pathway.

Despite the widespread fatalism with respect to cancer cachexia, patients do retain anabolic potential and although nutritional interventions, to date, have not been shown to increase survival, it may be that these interventions have not been successful in addressing the malnutrition as a primary outcome and thus, the benefit of survival has not been borne out. With more successful therapies, including multimodal and interdisciplinary approaches, it may be that nutritional interventions can improve not only QoL but also the length of life. Management of cancer-related malnutrition must focus on early-intervention with multimodal approaches in order to tackle the multifactorial nature of cachexia pathophysiology.

Further research into the pathogenesis and consequences of cancer-related malnutrition may lead to a better understanding of potential targets for treatment. However, while a number of promising therapies for cachexia are under investigation, the field lacks currently licensed treatments and so interventional research must be prioritised in order to provide an evidence base for the treatment of the condition which is now well documented as causing poor outcomes.

In conclusion, prompt identification of patients with cancer-related malnutrition must be optimised and development of an effective, evidence-based treatment strategy is of the utmost importance as it stands to improve longevity and QoL for cancer survivors.

Acknowledgements

The authors would like to acknowledge the Health Research Board Clinical Research Facility at Mercy University Hospital Cork where a lot of the research mentioned in the article was conducted and their statistician Dr Darren Dahly for his ongoing help and support of our research.

Financial Support

The free cookbooks for cancer patients mentioned in this article received financial support from Breakthrough Cancer Research (Irish Registered Charity). The national survey mentioned in this article on attitudes of Irish cancer patients to nutrition was in part supported by the Irish Society of Clinical Nutrition & Metabolism (IrSPEN)

Conflict of Interest

None

Authorship

A. R. delivered the Cuthbertson Medal Lecture. A. R. and E. S. co-wrote the paper.

References

Raja, R, Lim, AV, Lim, YP et al. (2004) Malnutrition screening in hospitalised patients and its implication on reimbursement. Intern Med J 34, 176181.CrossRefGoogle ScholarPubMed
Tangvik, RJ, Tell, GS, Guttormsen, AB et al. (2015) Nutritional risk profile in a university hospital population. Clin Nutr 34, 705711.CrossRefGoogle Scholar
Kruizenga, H, van Keeken, S, Weijs, P et al. (2016) Undernutrition screening survey in 564,063 patients: patients with a positive undernutrition screening score stay in hospital 1⋅4 d longer. Am J Clin Nutr 103, 10261032.CrossRefGoogle ScholarPubMed
Bozzetti, F & Group, SW (2009) Screening the nutritional status in oncology: a preliminary report on 1,000 outpatients. Support Care Cancer 17, 279284.CrossRefGoogle ScholarPubMed
Dewys, WD, Begg, C, Lavin, PT et al. (1980) Prognostic effect of weight loss prior to chemotherapy in cancer patients. Eastern Cooperative Oncology Group. Am J Med 69, 491497.CrossRefGoogle ScholarPubMed
Martin, L, Senesse, P, Gioulbasanis, I et al. (2015) Diagnostic criteria for the classification of cancer-associated weight loss. J Clin Oncol 33, 9099.CrossRefGoogle ScholarPubMed
Ní Bhuachalla, É, Daly, LE, Power, DG et al. (2018) Computed tomography diagnosed cachexia and sarcopenia in 725 oncology patients: is nutritional screening capturing hidden malnutrition? J Cachexia Sarcopenia Muscle 9, 295305.CrossRefGoogle ScholarPubMed
Andreyev, HJ, Norman, AR, Oates, J et al. (1998) Why do patients with weight loss have a worse outcome when undergoing chemotherapy for gastrointestinal malignancies? Eur J Cancer 34, 503509.CrossRefGoogle ScholarPubMed
Ross, PJ, Ashley, S, Norton, A et al. (2004) Do patients with weight loss have a worse outcome when undergoing chemotherapy for lung cancers? Br J Cancer 90, 19051911.CrossRefGoogle ScholarPubMed
Di Fiore, F, Lecleire, S, Pop, D et al. (2007) Baseline nutritional status is predictive of response to treatment and survival in patients treated by definitive chemoradiotherapy for a locally advanced esophageal cancer. Am J Gastroenterol 102, 25572563.CrossRefGoogle ScholarPubMed
Daly, LE, Power, DG, O'Reilly, Á et al. (2017) The impact of body composition parameters on ipilimumab toxicity and survival in patients with metastatic melanoma. Br J Cancer 116, 310317.Google ScholarPubMed
Cushen, SJ, Power, DG, Teo, MY et al. (2017) Body composition by computed tomography as a predictor of toxicity in patients with renal cell carcinoma treated with Sunitinib. Am J Clin Oncol 40, 4752.CrossRefGoogle ScholarPubMed
Wheelwright, S, Darlington, AS, Hopkinson, JB et al. (2013) A systematic review of health-related quality of life instruments in patients with cancer cachexia. Support Care Cancer 21, 26252636.CrossRefGoogle ScholarPubMed
Daly, LE, Dolan, RD, Power, DG et al. (2020) Determinants of quality of life in patients with incurable cancer. Cancer 126, 28722882.CrossRefGoogle ScholarPubMed
Argiles, JM, Busquets, S, Stemmler, B et al. (2015) Cachexia and sarcopenia: mechanisms and potential targets for intervention. Curr Opin Pharmacol 22, 100106.CrossRefGoogle ScholarPubMed
Baracos, VE, Martin, L, Korc, M et al. (2018) Cancer-associated cachexia. Nat Rev Dis Primers 4, 17105.CrossRefGoogle ScholarPubMed
Baracos, VE (2018) Cancer-associated malnutrition. Eur J Clin Nutr 72, 12551259.CrossRefGoogle ScholarPubMed
Schiessel, DL & Baracos, VE (2018) Barriers to cancer nutrition therapy: excess catabolism of muscle and adipose tissues induced by tumour products and chemotherapy. Proc Nutr Soc 77, 394402.CrossRefGoogle ScholarPubMed
Del Fabbro, E, Hui, D, Dalal, S et al. (2011) Clinical outcomes and contributors to weight loss in a cancer cachexia clinic. J Palliat Med 14, 10041008.CrossRefGoogle Scholar
Nicolini, A, Ferrari, P, Masoni, MC et al. (2013) Malnutrition, anorexia and cachexia in cancer patients: a mini-review on pathogenesis and treatment. Biomed Pharmacother 67, 807817.CrossRefGoogle ScholarPubMed
Kubrak, C, Olson, K, Jha, N et al. (2010) Nutrition impact symptoms: key determinants of reduced dietary intake, weight loss, and reduced functional capacity of patients with head and neck cancer before treatment. Head Neck 32, 290300.Google ScholarPubMed
Omlin, A, Blum, D, Wierecky, J et al. (2013) Nutrition impact symptoms in advanced cancer patients: frequency and specific interventions, a case-control study. J Cachexia Sarcopenia Muscle 4, 5561.CrossRefGoogle Scholar
Tong, H, Isenring, E & Yates, P (2009) The prevalence of nutrition impact symptoms and their relationship to quality of life and clinical outcomes in medical oncology patients. Support Care Cancer 17, 8390.CrossRefGoogle ScholarPubMed
Attar, A, Malka, D, Sabate, JM et al. (2012) Malnutrition is high and underestimated during chemotherapy in gastrointestinal cancer: an AGEO prospective cross-sectional multicenter study. Nutr Cancer 64, 535542.CrossRefGoogle ScholarPubMed
Antoun, S & Raynard, B (2018) Muscle protein anabolism in advanced cancer patients: response to protein and amino acids support, and to physical activity. Ann Oncol: Official J Euro Soc Medical Oncol/ESMO 29, ii10ii17.Google ScholarPubMed
Martin, L & Kubrak, C (2018) How much does reduced food intake contribute to cancer-associated weight loss? Curr Opin Support Palliat Care 12, 410419.CrossRefGoogle ScholarPubMed
Vazeille, C, Jouinot, A, Durand, JP et al. (2017) Relation between hypermetabolism, cachexia, and survival in cancer patients: a prospective study in 390 cancer patients before initiation of anticancer therapy. Am J Clin Nutr 105, 11391147.CrossRefGoogle ScholarPubMed
Friesen, DE, Baracos, VE & Tuszynski, JA (2015) Modeling the energetic cost of cancer as a result of altered energy metabolism: implications for cachexia. Theor Biol Med Model 12, 17.CrossRefGoogle ScholarPubMed
Grossberg, AJ, Scarlett, JM & Marks, DL (2010) Hypothalamic mechanisms in cachexia. Physiol Behav 100, 478489.CrossRefGoogle ScholarPubMed
Chu, K, Bos, SA, Gill, CM et al. (2019) Brown adipose tissue and cancer progression. Skeletal Radiol 49, 635639.CrossRefGoogle ScholarPubMed
Dev, R, Bruera, E & Dalal, S (2018) Insulin resistance and body composition in cancer patients. Ann Oncol: Official J Euro Soc Medical Oncol/ESMO 29, ii18ii26.CrossRefGoogle ScholarPubMed
Muscaritoli, M, Bossola, M, Doglietto, GB et al. (2006) The ubiquitin/proteasome system in cancer cachexia. In Cachexia and Wasting: A Modern Approach, pp. 503508 [Mantovani, G, Anker, SD, Inui, A, Morley, JE, Fanelli, FR, Scevola, D, Schuster, MW and Yeh, S-S, editors]. Milano: Springer Milan.CrossRefGoogle Scholar
Black, AE, Coward, WA, Cole, TJ et al. (1996) Human energy expenditure in affluent societies: an analysis of 574 doubly-labelled water measurements. Eur J Clin Nutr 50, 7292.Google ScholarPubMed
Moses, AW, Slater, C, Preston, T et al. (2004) Reduced total energy expenditure and physical activity in cachectic patients with pancreatic cancer can be modulated by an energy and protein dense oral supplement enriched with n-3 fatty acids. Br J Cancer 90, 9961002.CrossRefGoogle ScholarPubMed
Gibney, E, Elia, M, Jebb, SA et al. (1997) Total energy expenditure in patients with small-cell lung cancer: results of a validated study using the bicarbonate-urea method. Metab, Clin Exp 46, 14121417.CrossRefGoogle ScholarPubMed
Mollinger, LA, Spurr, GB, el Ghatit, AZ et al. (1985) Daily energy expenditure and basal metabolic rates of patients with spinal cord injury. Arch Phys Med Rehabil 66, 420426.Google ScholarPubMed
Stallings, VA, Zemel, BS, Davies, JC et al. (1996) Energy expenditure of children and adolescents with severe disabilities: a cerebral palsy model. Am J Clin Nutr 64, 627634.CrossRefGoogle ScholarPubMed
Fearon, K, Strasser, F, Anker, SD et al. (2011) Definition and classification of cancer cachexia: an international consensus. Lancet Oncol 12, 489495.CrossRefGoogle Scholar
Ryan, AM, Power, DG, Daly, L et al. (2016) Cancer-associated malnutrition, cachexia and sarcopenia: the skeleton in the hospital closet 40 years later. Proc Nutr Soc 75, 199211.CrossRefGoogle ScholarPubMed
Bachmann, J, Heiligensetzer, M, Krakowski-Roosen, H et al. (2008) Cachexia worsens prognosis in patients with resectable pancreatic cancer. J Gastrointest Surg 12, 11931201.CrossRefGoogle ScholarPubMed
Wesseltoft-Rao, N, Hjermstad, MJ, Ikdahl, T et al. (2015) Comparing two classifications of cancer cachexia and their association with survival in patients with unresected pancreatic cancer. Nutr Cancer 67, 472480.CrossRefGoogle ScholarPubMed
Krishnan, S, Rana, V, Janjan, NA et al. (2006) Prognostic factors in patients with unresectable locally advanced pancreatic adenocarcinoma treated with chemoradiation. Cancer 107, 25892596.CrossRefGoogle ScholarPubMed
Olson, SH, Xu, Y, Herzog, K et al. (2016) Weight loss, diabetes, fatigue, and depression preceding pancreatic cancer. Pancreas 45, 986991.CrossRefGoogle ScholarPubMed
Nemer, L, Krishna, SG, Shah, ZK et al. (2017) Predictors of pancreatic cancer-associated weight loss and nutritional interventions. Pancreas 46, 11521157.CrossRefGoogle ScholarPubMed
Bozzetti, F (2017) Forcing the vicious circle: sarcopenia increases toxicity, decreases response to chemotherapy and worsens with chemotherapy. Ann Oncol: Official J Euro Soc Medical Oncol/ESMO 28, 21072118.CrossRefGoogle ScholarPubMed
Gioulbasanis, I, Martin, L, Baracos, VE et al. (2015) Nutritional assessment in overweight and obese patients with metastatic cancer: does it make sense? Ann Oncol 26, 217221.Google ScholarPubMed
Martin, L, Birdsell, L, Macdonald, N et al. (2013) Cancer cachexia in the age of obesity: skeletal muscle depletion is a powerful prognostic factor, independent of body mass index. J Clin Oncol 31, 15391547.CrossRefGoogle ScholarPubMed
Ramos Chaves, M, Boleo-Tome, C, Monteiro-Grillo, I et al. (2010) The diversity of nutritional status in cancer: new insights. Oncologist 15, 523530.CrossRefGoogle ScholarPubMed
Greenlee, H, Unger, JM, LeBlanc, M et al. (2017) Association between body mass index and cancer survival in a pooled analysis of 22 clinical trials. Cancer Epidemiol Biomarkers Prev: Pub Am Assoc Cancer Res cosponsored Am Soc Prev Oncol 26, 2129.CrossRefGoogle Scholar
Aubrey, J, Esfandiari, N, Baracos, VE et al. (2014) Measurement of skeletal muscle radiation attenuation and basis of its biological variation. Acta Physiol (Oxf) 210, 489497.CrossRefGoogle ScholarPubMed
Cespedes Feliciano, EM, Kroenke, CH, Bradshaw, PT et al. (2017) Postdiagnosis weight change and survival following a diagnosis of early-stage breast cancer. Cancer Epidemiol Biomarkers Prev: Pub Am Assoc Cancer Res cosponsored Am Soc Prev Oncol 26, 4450.CrossRefGoogle ScholarPubMed
van Vugt, JL, Braam, HJ, van Oudheusden, TR et al. (2015) Skeletal muscle depletion is associated with severe postoperative complications in patients undergoing cytoreductive surgery with hyperthermic intraperitoneal chemotherapy for peritoneal carcinomatosis of colorectal cancer. Ann Surg Oncol 22, 36253631.CrossRefGoogle ScholarPubMed
Cruz-Jentoft, AJ, Baeyens, JP, Bauer, JM et al. (2010) Sarcopenia: European consensus on definition and diagnosis: report of the European Working Group on sarcopenia in older people. Age Ageing 39, 412423.CrossRefGoogle ScholarPubMed
Cruz-Jentoft, AJ, Bahat, G, Bauer, J et al. (2019) Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing 48, 1631.CrossRefGoogle ScholarPubMed
Baumgartner, RN, Koehler, KM, Gallagher, D et al. (1998) Epidemiology of sarcopenia among the elderly in New Mexico. Am J Epidemiol 147, 755763.CrossRefGoogle ScholarPubMed
Prado, CM, Cushen, SJ, Orsso, CE et al. (2016) Sarcopenia and cachexia in the era of obesity: clinical and nutritional impact. Proc Nutr Soc 75, 188198.CrossRefGoogle ScholarPubMed
Daly, LE, Ní Bhuachalla, É, Power, DG et al. (2018) Loss of skeletal muscle during systemic chemotherapy is prognostic of poor survival in patients with foregut cancer. J Cachexia Sarcopenia Muscle 9, 315325.CrossRefGoogle ScholarPubMed
Rutten, IJ, van Dijk, DP, Kruitwagen, RF et al. (2016) Loss of skeletal muscle during neoadjuvant chemotherapy is related to decreased survival in ovarian cancer patients. J Cachexia Sarcopenia Muscle 7, 458466.CrossRefGoogle ScholarPubMed
Frontera, WR, Zayas, AR & Rodriguez, N (2012) Aging of human muscle: understanding sarcopenia at the single muscle cell level. Phys Med Rehabil Clin N Am 23, 201207, xiii.Google ScholarPubMed
Blauwhoff-Buskermolen, S, Versteeg, KS, de van der Schueren, MA et al. (2016) Loss of muscle mass during chemotherapy Is predictive for poor survival of patients with metastatic colorectal cancer. J Clin Oncol 34, 13391344.CrossRefGoogle ScholarPubMed
Tan, BH, Birdsell, LA, Martin, L et al. (2009) Sarcopenia in an overweight or obese patient is an adverse prognostic factor in pancreatic cancer. Clin Cancer Res 15, 69736979.CrossRefGoogle ScholarPubMed
Daly, LE, Prado, CM & Ryan, AM (2018) A window beneath the skin: how computed tomography assessment of body composition can assist in the identification of hidden wasting conditions in oncology that profoundly impact outcomes. Proc Nutr Soc 77, 135151.CrossRefGoogle ScholarPubMed
Baracos, VE, Reiman, T, Mourtzakis, M et al. (2010) Body composition in patients with non-small cell lung cancer: a contemporary view of cancer cachexia with the use of computed tomography image analysis. Am J Clin Nutr 91, 1133S1137S.CrossRefGoogle ScholarPubMed
Arrieta, O, De la Torre-Vallejo, M, López-Macías, D et al. (2015) Nutritional status, body surface, and low lean body mass/body mass index are related to dose reduction and severe gastrointestinal toxicity induced by Afatinib in patients with non-small cell lung cancer. Oncologist 20, 967974.CrossRefGoogle ScholarPubMed
Stene, GB, Helbostad, JL, Amundsen, T et al. (2014) Changes in skeletal muscle mass during palliative chemotherapy in patients with advanced lung cancer. Acta Oncol 54, 340348.CrossRefGoogle ScholarPubMed
Kim, EY, Kim, YS, Park, I et al. (2015) Prognostic significance of CT-determined sarcopenia in patients with small-cell lung cancer. J Thorac Oncol 10, 17951799.CrossRefGoogle ScholarPubMed
Sandini, M, Patino, M, Ferrone, CR et al. (2018) Association between changes in body composition and neoadjuvant treatment for pancreatic cancer. JAMA Surg 153, 809815.CrossRefGoogle ScholarPubMed
El Amrani, M, Vermersch, M, Fulbert, M et al. (2018) Impact of sarcopenia on outcomes of patients undergoing pancreatectomy: a retrospective analysis of 107 patients. Medicine 97, e12076.CrossRefGoogle ScholarPubMed
Di Sebastiano, KM, Yang, L, Zbuk, K et al. (2013) Accelerated muscle and adipose tissue loss may predict survival in pancreatic cancer patients: the relationship with diabetes and anaemia. Br J Nutr 109, 302312.CrossRefGoogle ScholarPubMed
Cooper, AB, Slack, R, Fogelman, D et al. (2015) Characterization of anthropometric changes that occur during neoadjuvant therapy for potentially resectable pancreatic cancer. Ann Surg Oncol 22, 24162423.CrossRefGoogle ScholarPubMed
Rollins, KE, Tewari, N, Ackner, A et al. (2015) The impact of sarcopenia and myosteatosis on outcomes of unresectable pancreatic cancer or distal cholangiocarcinoma. Clin Nutr 35, 11031109.CrossRefGoogle ScholarPubMed
Dalal, S, Hui, D, Bidaut, L et al. (2012) Relationships among body mass index, longitudinal body composition alterations, and survival in patients with locally advanced pancreatic cancer receiving chemoradiation: a pilot study. J Pain Symptom Manage 44, 181191.CrossRefGoogle ScholarPubMed
Carrara, G, Pecorelli, N, De Cobelli, F et al. (2017) Preoperative sarcopenia determinants in pancreatic cancer patients. Clin Nutr 36, 16491653.CrossRefGoogle ScholarPubMed
Sullivan, ES, Daly, LE, Power, DG et al. (2020) Epidemiology of cancer-related weight loss and sarcopenia in the UK and Ireland: incidence, prevalence, and clinical impact. JCSM Rapid Commun 3, 91102.CrossRefGoogle Scholar
Sturgeon, KM, Mathis, KM, Rogers, CJ et al. (2019) Cancer- and chemotherapy-induced musculoskeletal degradation. JBMR Plus 3, e10187.CrossRefGoogle ScholarPubMed
Higano, C, Shields, A, Wood, N et al. (2004) Bone mineral density in patients with prostate cancer without bone metastases treated with intermittent androgen suppression. Urology 64, 11821186.CrossRefGoogle ScholarPubMed
Eastell, R, Adams, JE, Coleman, RE et al. (2008) Effect of anastrozole on bone mineral density: 5-year results from the anastrozole, tamoxifen, alone or in combination trial 18233230. J Clin Oncol 26, 10511057.CrossRefGoogle ScholarPubMed
Shapiro, CL, Manola, J & Leboff, M (2001) Ovarian failure after adjuvant chemotherapy is associated with rapid bone loss in women with early-stage breast cancer. J Clin Oncol 19, 33063311.CrossRefGoogle ScholarPubMed
Maillefert, JF, Sibilia, J, Michel, F et al. (1999) Bone mineral density in men treated with synthetic gonadotropin-releasing hormone agonists for prostatic carcinoma. J Urol 161, 12191222.CrossRefGoogle ScholarPubMed
Cann, CE, Martin, MC, Genant, HK et al. (1984) Decreased spinal mineral content in amenorrheic women. JAMA: J Am Medical Assoc 251, 626629.CrossRefGoogle ScholarPubMed
Berruti, A, Dogliotti, L, Terrone, C et al. (2002) Changes in bone mineral density, lean body mass and fat content as measured by dual energy x-ray absorptiometry in patients with prostate cancer without apparent bone metastases given androgen deprivation therapy. J Urol 167, 23612367; discussion 2367.CrossRefGoogle ScholarPubMed
Diamond, TH, Bucci, J, Kersley, JH et al. (2004) Osteoporosis and spinal fractures in men with prostate cancer: risk factors and effects of androgen deprivation therapy. J Urol 172, 529532.CrossRefGoogle ScholarPubMed
Diamond, TH, Higano, CS, Smith, MR et al. (2004) Osteoporosis in men with prostate carcinoma receiving androgen-deprivation therapy: recommendations for diagnosis and therapies. Cancer 100, 892899.CrossRefGoogle ScholarPubMed
Winters-Stone, KM, Bennett, JA, Nail, L et al. (2008) Strength, physical activity, and age predict fatigue in older breast cancer survivors. Oncol Nurs Forum 35, 815821.CrossRefGoogle ScholarPubMed
Nicolson, GL & Conklin, KA (2008) Reversing mitochondrial dysfunction, fatigue and the adverse effects of chemotherapy of metastatic disease by molecular replacement therapy. Clin Exp Metastasis 25, 161169.CrossRefGoogle ScholarPubMed
Kurk, SA, Peeters, PHM, Dorresteijn, B et al. (2018) Impact of different palliative systemic treatments on skeletal muscle mass in metastatic colorectal cancer patients. J Cachexia Sarcopenia Muscle 9, 909919.CrossRefGoogle ScholarPubMed
van Vugt, JLA, Coebergh van den Braak, RRJ, Lalmahomed, ZS et al. (2018) Impact of low skeletal muscle mass and density on short and long-term outcome after resection of stage I-III colorectal cancer. Eur J Surg Oncol 44, 13541360.CrossRefGoogle Scholar
van der Kroft, G, Bours, DMJL, Janssen-Heijnen, DM et al. (2018) Value of sarcopenia assessed by computed tomography for the prediction of postoperative morbidity following oncological colorectal resection: a comparison with the malnutrition screening tool. Clin Nutr ESPEN 24, 114119.CrossRefGoogle ScholarPubMed
Ryan, AM, Prado, CM, Sullivan, ES et al. (2019) Effects of weight loss and sarcopenia on response to chemotherapy, quality of life, and survival. Nutrition 67–68, 110539.CrossRefGoogle ScholarPubMed
Tan, BH, Brammer, K, Randhawa, N et al. (2015) Sarcopenia is associated with toxicity in patients undergoing neo-adjuvant chemotherapy for oesophago-gastric cancer. Eur J Surg Oncol 41, 333338.CrossRefGoogle ScholarPubMed
Palmela, C, Velho, S, Agostinho, L et al. (2017) Body composition as a prognostic factor of neoadjuvant chemotherapy toxicity and outcome in patients with locally advanced gastric cancer. J Gastric Cancer 17, 7487.CrossRefGoogle ScholarPubMed
Prado, CM, Lieffers, JR, McCargar, LJ et al. (2008) Prevalence and clinical implications of sarcopenic obesity in patients with solid tumours of the respiratory and gastrointestinal tracts: a population-based study. Lancet Oncol 9, 629635.CrossRefGoogle ScholarPubMed
Shachar, SS, Deal, AM, Weinberg, M et al. (2017) Skeletal muscle measures as predictors of toxicity, hospitalization, and survival in patients with metastatic breast cancer receiving taxane-based chemotherapy. Clin Cancer Res 23, 658665.CrossRefGoogle ScholarPubMed
Yip, C, Goh, V, Davies, A et al. (2014) Assessment of sarcopenia and changes in body composition after neoadjuvant chemotherapy and associations with clinical outcomes in oesophageal cancer. Eur Radiol 24, 9981005.CrossRefGoogle ScholarPubMed
Auclin, E, Bourillon, C, De Maio, E et al. (2017) Prediction of everolimus toxicity and prognostic value of skeletal muscle index in patients with metastatic renal cell carcinoma. Clin Genitourin Cancer 15, 350355.CrossRefGoogle ScholarPubMed
Veasey Rodrigues, H, Baracos, VE, Wheler, JJ et al. (2013) Body composition and survival in the early clinical trials setting. Eur J Cancer 49, 30683075.CrossRefGoogle ScholarPubMed
Parsons, HA, Tsimberidou, AM, Pontikos, M et al. (2012) Evaluation of the clinical relevance of body composition parameters in patients with cancer metastatic to the liver treated with hepatic arterial infusion chemotherapy. Nutr Cancer 64, 206217.CrossRefGoogle ScholarPubMed
Srdic, D, Plestina, S, Sverko-Peternac, A et al. (2016) Cancer cachexia, sarcopenia and biochemical markers in patients with advanced non-small cell lung cancer-chemotherapy toxicity and prognostic value. Support Care Cancer 24, 44954502.CrossRefGoogle ScholarPubMed
Versteeg, KS, Blauwhoff-Buskermolen, S, Buffart, LM et al. (2018) Higher muscle strength Is associated with prolonged survival in older patients with advanced cancer. Oncologist 23, 580585.CrossRefGoogle ScholarPubMed
Prado, CM, Baracos, VE, McCargar, LJ et al. (2009) Sarcopenia as a determinant of chemotherapy toxicity and time to tumor progression in metastatic breast cancer patients receiving capecitabine treatment. Clin Cancer Res 15, 29202926.Google ScholarPubMed
Du Bois, D & Du Bois, EF (1989) A formula to estimate the approximate surface area if height and weight be known. 1916. Nutrition 5, 303311; discussion 312–303.Google ScholarPubMed
Stobäus, N, Küpferling, S, Lorenz, ML et al. (2013) Discrepancy between body surface area and body composition in cancer. Nutr Cancer 65, 11511156.CrossRefGoogle ScholarPubMed
McLeay, SC, Morrish, GA, Kirkpatrick, CMJ et al. (2012) The relationship between drug clearance and body size systematic review and meta-analysis of the literature published from 2000 to 2007. Clin Pharmacokinet 51, 319330.CrossRefGoogle ScholarPubMed
Prado, CM, Antoun, S, Sawyer, MB et al. (2011) Two faces of drug therapy in cancer: drug-related lean tissue loss and its adverse consequences to survival and toxicity. Curr Opin Clin Nutr Metab Care 14, 250254.CrossRefGoogle ScholarPubMed
Takimoto, CH (2009) Maximum tolerated dose: clinical endpoint for a bygone era? Target Oncol 4, 143147.Google ScholarPubMed
Baker, SD, Verweij, J, Rowinsky, EK et al. (2002) Role of body surface area in dosing of investigational anticancer agents in adults, 1991–2001. J Natl Cancer Inst 94, 18831888.CrossRefGoogle Scholar
Prado, CM, Baracos, VE, McCargar, LJ et al. (2007) Body composition as an independent determinant of 5-fluorouracil-based chemotherapy toxicity. Clin Cancer Res 13, 32643268.CrossRefGoogle ScholarPubMed
Prado, CM, Baracos, VE, Xiao, J et al. (2014) The association between body composition and toxicities from the combination of Doxil and trabectedin in patients with advanced relapsed ovarian cancer. Appl Physiol Nutr Metab 39, 693698.CrossRefGoogle ScholarPubMed
Sjøblom, B, Benth, J, Grønberg, BH et al. (2017) Drug dose per kilogram lean body mass predicts hematologic toxicity from carboplatin-doublet chemotherapy in advanced non-small-cell lung cancer. Clin Lung Cancer 18, e129e136.CrossRefGoogle ScholarPubMed
Sjøblom, B, Grønberg, BH, Benth, J et al. (2015) Low muscle mass is associated with chemotherapy-induced haematological toxicity in advanced non-small cell lung cancer. Lung Cancer 90, 8591.CrossRefGoogle ScholarPubMed
Mir, O, Coriat, R, Blanchet, B et al. (2012) Sarcopenia predicts early dose-limiting toxicities and pharmacokinetics of sorafenib in patients with hepatocellular carcinoma. PLoS ONE 7, e37563.CrossRefGoogle ScholarPubMed
Massicotte, MH, Borget, I, Broutin, S et al. (2013) Body composition variation and impact of low skeletal muscle mass in patients with advanced medullary thyroid carcinoma treated with vandetanib: results from a placebo-controlled study. J Clin Endocrinol Metab 98, 24012408.CrossRefGoogle ScholarPubMed
Antoun, S, Lanoy, E, Albiges-Sauvin, L et al. (2014) Clinical implications of body composition assessment by computed tomography in metastatic renal cell carcinoma. Expert Rev Anticancer Ther 14, 279288.CrossRefGoogle ScholarPubMed
Blum, D, Omlin, A, Baracos, VE et al. (2011) Cancer cachexia: a systematic literature review of items and domains associated with involuntary weight loss in cancer. Crit Rev Oncol Hematol 80, 114144.CrossRefGoogle ScholarPubMed
Ravasco, P, Monteiro-Grillo, I, Vidal, PM et al. (2004) Cancer: disease and nutrition are key determinants of patients' quality of life. Support Care Cancer 12, 246252.Google ScholarPubMed
Fearon, KC, Voss, AC, Hustead, DS et al. (2006) Definition of cancer cachexia: effect of weight loss, reduced food intake, and systemic inflammation on functional status and prognosis. Am J Clin Nutr 83, 13451350.CrossRefGoogle ScholarPubMed
Evans, WJ & Lambert, CP (2007) Physiological basis of fatigue. Am J Phys Med Rehabil 86, S2946.CrossRefGoogle Scholar
Ryan, JL, Carroll, JK, Ryan, EP et al. (2007) Mechanisms of cancer-related fatigue. Oncologist 12, Suppl. 1, 2234.CrossRefGoogle ScholarPubMed
Hopkinson, JB, Brown, JC, Okamoto, I et al. (2012) The effectiveness of patient-family carer (couple) intervention for the management of symptoms and other health-related problems in people affected by cancer: a systematic literature search and narrative review. J Pain Symptom Manage 43, 111142.CrossRefGoogle ScholarPubMed
Neefjes, ECW, van den Hurk, RM, Blauwhoff-Buskermolen, S et al. (2017) Muscle mass as a target to reduce fatigue in patients with advanced cancer. J Cachexia Sarcopenia Muscle 8, 623629.CrossRefGoogle ScholarPubMed
Nipp, RD, Fuchs, G, El-Jawahri, A et al. (2017) Sarcopenia is associated with quality of life and depression in patients with advanced cancer. Oncologist 23, 97104.CrossRefGoogle ScholarPubMed
Bye, A, Sjøblom, B, Wentzel-Larsen, T et al. (2017) Muscle mass and association to quality of life in non-small cell lung cancer patients. J Cachexia Sarcopenia Muscle 8, 759767.CrossRefGoogle ScholarPubMed
Aapro, M, Arends, J, Bozzetti, F et al. (2014) Early recognition of malnutrition and cachexia in the cancer patient: a position paper of a European school of oncology task force. Ann Oncol 25, 14921499.CrossRefGoogle ScholarPubMed
McSorley, S, Dolan, R, Roxburgh, C et al. (2017) How and why systemic inflammation worsens quality of life in patients with advanced cancer. Expert Rev Quality of life in Cancer Care 2, 167175.CrossRefGoogle Scholar
Baguley, BJ, Skinner, TL & Wright, ORL (2018) Nutrition therapy for the management of cancer-related fatigue and quality of life: a systematic review and meta-analysis. Br J Nutr 122, 527541.CrossRefGoogle Scholar
Bower, JE, Ganz, PA, Tao, ML et al. (2009) Inflammatory biomarkers and fatigue during radiation therapy for breast and prostate cancer. Clin Cancer Res 15, 55345540.CrossRefGoogle ScholarPubMed
Bower, JE & Lamkin, DM (2013) Inflammation and cancer-related fatigue: mechanisms, contributing factors, and treatment implications. Brain Behav Immun 30, Suppl, S4857.CrossRefGoogle ScholarPubMed
Wang, XS, Zhao, F, Fisch, MJ et al. (2014) Prevalence and characteristics of moderate to severe fatigue: a multicenter study in cancer patients and survivors. Cancer 120, 425432.CrossRefGoogle ScholarPubMed
Paulsen, O, Laird, B, Aass, N et al. (2017) The relationship between pro-inflammatory cytokines and pain, appetite and fatigue in patients with advanced cancer. PLoS ONE 12, e0177620.CrossRefGoogle ScholarPubMed
Du, YJ, Zhang, HY, Li, B et al. (2013) Sputum interleukin-6, tumor necrosis factor-alpha and Salivary cortisol as new biomarkers of depression in lung cancer patients. Prog Neuro-Psychopharmacol Biol Psychiatry 47, 6976.CrossRefGoogle ScholarPubMed
Breitbart, W, Rosenfeld, B, Tobias, K et al. (2014) Depression, cytokines, and pancreatic cancer. Psycho-oncology 23, 339345.CrossRefGoogle ScholarPubMed
Laird, BJ, Fallon, M, Hjermstad, MJ et al. (2016) Quality of life in patients with advanced cancer: differential association with performance Status and systemic inflammatory response. J Clin Oncol 34, 27692775.CrossRefGoogle ScholarPubMed
Baldwin, C, Spiro, A, Ahern, R et al. (2012) Oral nutritional interventions in malnourished patients with cancer: a systematic review and meta-analysis. J Natl Cancer Inst 104, 371385.CrossRefGoogle ScholarPubMed
Temel, JS, Abernethy, AP, Currow, DC et al. (2016) Anamorelin in patients with non-small-cell lung cancer and cachexia (ROMANA 1 and ROMANA 2): results from two randomised, double-blind, phase 3 trials. Lancet Oncol 17, 519531.CrossRefGoogle ScholarPubMed
Cho, Y, Kim, JW, Keum, KC et al. (2018) Prognostic significance of sarcopenia with inflammation in patients with head and neck cancer who underwent definitive chemoradiotherapy. Front Oncol 8, 457.CrossRefGoogle ScholarPubMed
Fattouh, M, Chang, GY, Ow, TJ et al. (2018) Association between pretreatment obesity, sarcopenia, and survival in patients with head and neck cancer. Head Neck 41, 707714.CrossRefGoogle ScholarPubMed
Chargi, N, Bril, SI, Emmelot-Vonk, MH et al. (2019) Sarcopenia is a prognostic factor for overall survival in elderly patients with head-and-neck cancer. Eur Arch Otorhinolaryngol 276, 14751486.CrossRefGoogle ScholarPubMed
Jung, AR, Roh, JL, Kim, JS et al. (2019) Prognostic value of body composition on recurrence and survival of advanced-stage head and neck cancer. Eur J Cancer 116, 98106.CrossRefGoogle ScholarPubMed
Ganju, RG, Morse, R, Hoover, A et al. (2019) The impact of sarcopenia on tolerance of radiation and outcome in patients with head and neck cancer receiving chemoradiation. Radiother Oncol 137, 117124.CrossRefGoogle ScholarPubMed
Stone, L, Olson, B, Mowery, A et al. (2019) Association between sarcopenia and mortality in patients undergoing surgical excision of head and neck cancer. JAMA Otolaryngol--Head & Neck Surg 145, 647654.CrossRefGoogle ScholarPubMed
Ohtaka, A, Aoki, H, Nagata, M et al. (2019) Sarcopenia is a poor prognostic factor of castration-resistant prostate cancer treated with docetaxel therapy. Prostate Int 7, 914.CrossRefGoogle ScholarPubMed
Coelen, RJ, Wiggers, JK, Nio, CY et al. (2015) Preoperative computed tomography assessment of skeletal muscle mass is valuable in predicting outcomes following hepatectomy for perihilar cholangiocarcinoma. HPB (Oxford) 17, 520528.CrossRefGoogle ScholarPubMed
Kitano, Y, Yamashita, YI, Saito, Y et al. (2019) Sarcopenia affects systemic and local immune system and impacts postoperative outcome in patients with extrahepatic cholangiocarcinoma. World J Surg 43, 22712280.CrossRefGoogle ScholarPubMed
Hahn, F, Muller, L, Stohr, F et al. (2019) The role of sarcopenia in patients with intrahepatic cholangiocarcinoma: prognostic marker or hyped parameter? Liver Int 39, 13071314.CrossRefGoogle ScholarPubMed
Yugawa, K, Itoh, S, Kurihara, T et al. (2019) Skeletal muscle mass predicts the prognosis of patients with intrahepatic cholangiocarcinoma. Am J Surg 218, 952958.CrossRefGoogle ScholarPubMed
Okumura, S, Kaido, T, Hamaguchi, Y et al. (2017) Impact of skeletal muscle mass, muscle quality, and visceral adiposity on outcomes following resection of intrahepatic cholangiocarcinoma. Ann Surg Oncol 24, 10371045.CrossRefGoogle ScholarPubMed
Go, SI, Park, S, Kang, MH et al. (2019) Clinical impact of prognostic nutritional index in diffuse large B cell lymphoma. Ann Hematol 98, 401411.CrossRefGoogle ScholarPubMed
Go, SI, Park, MJ, Song, HN et al. (2016) Prognostic impact of sarcopenia in patients with diffuse large B-cell lymphoma treated with rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone. J Cachexia Sarcopenia Muscle 7, 567576.CrossRefGoogle ScholarPubMed
Camus, V, Lanic, H, Kraut, J et al. (2014) Prognostic impact of fat tissue loss and cachexia assessed by computed tomography scan in elderly patients with diffuse large B-cell lymphoma treated with immunochemotherapy. Eur J Haematol 93, 918.CrossRefGoogle ScholarPubMed
Lanic, H, Kraut-Tauzia, J, Modzelewski, R et al. (2014) Sarcopenia is an independent prognostic factor in elderly patients with diffuse large B-cell lymphoma treated with immunochemotherapy. Leuk Lymphoma 55, 817823.CrossRefGoogle ScholarPubMed
Nakamura, N, Hara, T, Shibata, Y et al. (2015) Sarcopenia is an independent prognostic factor in male patients with diffuse large B-cell lymphoma. Ann Hematol 94, 20432053.CrossRefGoogle ScholarPubMed
Nakamura, N, Ninomiya, S, Matsumoto, T et al. (2019) Prognostic impact of skeletal muscle assessed by computed tomography in patients with acute myeloid leukemia. Ann Hematol 98, 351359.CrossRefGoogle ScholarPubMed
Shachar, SS, Williams, GR, Muss, HB et al. (2016) Prognostic value of sarcopenia in adults with solid tumours: a meta-analysis and systematic review. Eur J Cancer 57, 5867.CrossRefGoogle ScholarPubMed
Caan, BJ, Meyerhardt, JA, Kroenke, CH et al. (2017) Explaining the obesity paradox: the association between body composition and colorectal cancer survival (C-SCANS study). Cancer Epidemiol, Biomarkers Prev: Pub Am Assoc Cancer Res, Cosponsored Am Soc Preventive Oncol 26, 10081015.CrossRefGoogle Scholar
Caan, BJ, Cespedes Feliciano, EM, Prado, CM et al. (2018) Association of muscle and adiposity measured by computed tomography with survival in patients with nonmetastatic breast cancer. JAMA Oncol 4, 798804.CrossRefGoogle ScholarPubMed
Sjøblom, B, Grønberg, BH, Wentzel-Larsen, T et al. (2016) Skeletal muscle radiodensity is prognostic for survival in patients with advanced non-small cell lung cancer. Clin Nutr 35, 13861393.CrossRefGoogle ScholarPubMed
Kroenke, CH, Prado, CM, Meyerhardt, JA et al. (2018) Muscle radiodensity and mortality in patients with colorectal cancer. Cancer 124, 30083015.CrossRefGoogle ScholarPubMed
Brown, JC, Caan, BJ, Meyerhardt, JA et al. (2018) The deterioration of muscle mass and radiodensity is prognostic of poor survival in stage I-III colorectal cancer: a population-based cohort study (C-SCANS). J Cachexia Sarcopenia Muscle 9, 664672.CrossRefGoogle Scholar
van Baar, H, Beijer, S, Bours, MJL et al. (2018) Low radiographic muscle density is associated with lower overall and disease-free survival in early-stage colorectal cancer patients. J Cancer Res Clin Oncol 144, 21392147.CrossRefGoogle ScholarPubMed
de Paula, NS, Rodrigues, CS & Chaves, GV (2018) Comparison of the prognostic value of different skeletal muscle radiodensity parameters in endometrial cancer. Eur J Clin Nutr 73, 524530.CrossRefGoogle ScholarPubMed
Antoun, S, Lanoy, E, Iacovelli, R et al. (2013) Skeletal muscle density predicts prognosis in patients with metastatic renal cell carcinoma treated with targeted therapies. Cancer 119, 33773384.CrossRefGoogle ScholarPubMed
Ataseven, B, Luengo, TG, du Bois, A et al. (2018) Skeletal muscle attenuation (Sarcopenia) predicts reduced overall survival in patients with advanced epithelial ovarian cancer undergoing primary debulking surgery. Ann Surg Oncol 25, 33723379.CrossRefGoogle ScholarPubMed
Sabel, MS, Lee, J, Cai, S et al. (2011) Sarcopenia as a prognostic factor among patients with stage III melanoma. Ann Surg Oncol 18, 35793585.CrossRefGoogle ScholarPubMed
Hayashi, N, Ando, Y, Gyawali, B et al. (2016) Low skeletal muscle density is associated with poor survival in patients who receive chemotherapy for metastatic gastric cancer. Oncol Rep 35, 17271731.CrossRefGoogle ScholarPubMed
Rier, HN, Jager, A, Sleijfer, S et al. (2017) Low muscle attenuation is a prognostic factor for survival in metastatic breast cancer patients treated with first line palliative chemotherapy. Breast 31, 915.CrossRefGoogle ScholarPubMed
Chu, MP, Lieffers, J, Ghosh, S et al. (2017) Skeletal muscle density is an independent predictor of diffuse large B-cell lymphoma outcomes treated with rituximab-based chemoimmunotherapy. J Cachexia Sarcopenia Muscle 8, 298304.CrossRefGoogle ScholarPubMed
Van Rijssen, LB, van Huijgevoort, NC, Coelen, RJ et al. (2017) Skeletal muscle quality is associated with worse survival after pancreatoduodenectomy for periampullary, nonpancreatic cancer. Ann Surg Oncol 24, 272280.CrossRefGoogle ScholarPubMed
Charette, N, Vandeputte, C, Ameye, L et al. (2019) Prognostic value of adipose tissue and muscle mass in advanced colorectal cancer: a post hoc analysis of two non-randomized phase II trials. BMC Cancer 19, 134.CrossRefGoogle ScholarPubMed
Sueda, T, Takahasi, H, Nishimura, J et al. (2018) Impact of low muscularity and myosteatosis on long-term outcome after curative colorectal cancer surgery: a propensity score-matched analysis. Dis Colon Rectum 61, 364374.CrossRefGoogle ScholarPubMed
Mintziras, I, Miligkos, M, Wachter, S et al. (2018) Sarcopenia and sarcopenic obesity are significantly associated with poorer overall survival in patients with pancreatic cancer: systematic review and meta-analysis. Int J Surg 59, 1926.CrossRefGoogle ScholarPubMed
Basile, D, Parnofiello, A, Vitale, MG et al. (2019) The IMPACT study: early loss of skeletal muscle mass in advanced pancreatic cancer patients. J Cachexia Sarcopenia Muscle 10, 368377.CrossRefGoogle ScholarPubMed
Yoon, HG, Oh, D, Ahn, YC et al. (2020) Prognostic impact of sarcopenia and skeletal muscle loss during neoadjuvant chemoradiotherapy in esophageal cancer. Cancers (Basel) 12, 925.CrossRefGoogle ScholarPubMed
Park, HS, Kim, HS, Beom, SH et al. (2018) Marked loss of muscle, visceral Fat, or subcutaneous Fat after gastrectomy predicts poor survival in advanced gastric cancer: single-center study from the CLASSIC trial. Ann Surg Oncol 25, 32223230.CrossRefGoogle ScholarPubMed
Nattenmuller, J, Wochner, R, Muley, T et al. (2017) Prognostic impact of CT-quantified muscle and fat distribution before and after first-line-chemotherapy in lung cancer patients. PLoS ONE 12, e0169136.CrossRefGoogle ScholarPubMed
Takeda, Y, Akiyoshi, T, Matsueda, K et al. (2018) Skeletal muscle loss is an independent negative prognostic factor in patients with advanced lower rectal cancer treated with neoadjuvant chemoradiotherapy. PLoS ONE 13, e0195406.CrossRefGoogle ScholarPubMed
Miyamoto, Y, Baba, Y, Sakamoto, Y et al. (2015) Negative impact of skeletal muscle loss after systemic chemotherapy in patients with unresectable colorectal cancer. PLoS ONE 10, e0129742.CrossRefGoogle ScholarPubMed
Lou, N, Chi, CH, Chen, XD et al. (2017) Sarcopenia in overweight and obese patients is a predictive factor for postoperative complication in gastric cancer: a prospective study. Eur J Surg Oncol 43, 188195.CrossRefGoogle ScholarPubMed
Zhang, Y, Wang, JP, Wang, XL et al. (2018) Computed tomography-quantified body composition predicts short-term outcomes after gastrectomy in gastric cancer. Curr Oncol 25, e411e422.CrossRefGoogle ScholarPubMed
Cao, Q, Xiong, Y, Zhong, Z et al. (2019) Computed tomography-assessed sarcopenia indexes predict major complications following surgery for hepatopancreatobiliary malignancy: a meta-analysis. Ann Nutr Metab 74, 2434.CrossRefGoogle ScholarPubMed
Elliott, JA, Doyle, SL, Murphy, CF et al. (2017) Sarcopenia: prevalence, and impact on operative and oncologic outcomes in the multimodal management of locally advanced esophageal cancer. Ann Surg 266, 822830.CrossRefGoogle ScholarPubMed
Ida, S, Watanabe, M, Yoshida, N et al. (2015) Sarcopenia is a predictor of postoperative respiratory complications in patients with esophageal cancer. Ann Surg Oncol 22, 44324437.CrossRefGoogle ScholarPubMed
Mao, W, Ma, B, Wang, K et al. (2020) Sarcopenia predicts prognosis of bladder cancer patients after radical cystectomy: a study based on the Chinese population. Clin Transl Med 10, e105.CrossRefGoogle ScholarPubMed
Madariaga, MLL, Troschel Cand Med, FM, Best Cand Med, TD et al. (2019) Low thoracic skeletal muscle area predicts morbidity after pneumonectomy for lung cancer. Ann Thorac Surg 109, 907913.CrossRefGoogle ScholarPubMed
Kawaguchi, Y, Hanaoka, J, Ohshio, Y et al. (2019) Sarcopenia predicts poor postoperative outcome in elderly patients with lung cancer. Gen Thorac Cardiovasc Surg 67, 949954.CrossRefGoogle ScholarPubMed
Lieffers, JR, Bathe, OF, Fassbender, K et al. (2012) Sarcopenia is associated with postoperative infection and delayed recovery from colorectal cancer resection surgery. Br J Cancer 107, 931936.CrossRefGoogle ScholarPubMed
Tsaousi, G, Kokkota, S, Papakostas, P et al. (2017) Body composition analysis for discrimination of prolonged hospital stay in colorectal cancer surgery patients. Eur J Cancer Care (Engl) 26 [Epublication].CrossRefGoogle ScholarPubMed
Zhang, S, Tan, S, Jiang, Y et al. (2018) Sarcopenia as a predictor of poor surgical and oncologic outcomes after abdominal surgery for digestive tract cancer: a prospective cohort study. Clin Nutr 38, 28812888.CrossRefGoogle ScholarPubMed
Martin, L, Hopkins, J, Malietzis, G et al. (2018) Assessment of Computed Tomography (CT)-defined muscle and adipose tissue features in relation to short-term outcomes after elective surgery for colorectal cancer: a multicenter approach. Ann Surg Oncol 25, 26692680.CrossRefGoogle ScholarPubMed
van Vugt, JLA, Buettner, S, Levolger, S et al. (2017) Low skeletal muscle mass is associated with increased hospital expenditure in patients undergoing cancer surgery of the alimentary tract. PLoS ONE 12, e0186547.CrossRefGoogle ScholarPubMed
Gani, F, Buettner, S, Margonis, GA et al. (2016) Sarcopenia predicts costs among patients undergoing major abdominal operations. Surgery 160, 11621171.CrossRefGoogle ScholarPubMed
Arends, J, Bachmann, P, Baracos, V et al. (2017) ESPEN Guidelines on nutrition in cancer patients. Clin Nutr 36, 1148.CrossRefGoogle ScholarPubMed
Arends, J (2018) Struggling with nutrition in patients with advanced cancer: nutrition and nourishment-focusing on metabolism and supportive care. Ann Oncol: Official J Euro Soc Medical Oncol/ESMO 29, ii27ii34.CrossRefGoogle ScholarPubMed
Kiss, NK, Krishnasamy, M, Loeliger, J et al. (2012) A dietitian-led clinic for patients receiving (chemo)radiotherapy for head and neck cancer. Support Care Cancer 20, 21112120.CrossRefGoogle ScholarPubMed
Hall, BT, Englehart, MS, Blaseg, K et al. (2014) Implementation of a dietitian-led enteral nutrition support clinic results in quality improvement, reduced readmissions, and cost savings. Nutr Clin Pract 29, 649655.CrossRefGoogle ScholarPubMed
De Waele, E, Mattens, S, Honore, PM et al. (2015) Nutrition therapy in cachectic cancer patients. The Tight Caloric Control (TiCaCo) pilot trial. Appetite 91, 298301.CrossRefGoogle ScholarPubMed
Uster, A, Ruefenacht, U, Ruehlin, M et al. (2013) Influence of a nutritional intervention on dietary intake and quality of life in cancer patients: a randomized controlled trial. Nutrition 29, 13421349.CrossRefGoogle ScholarPubMed
Poulsen, GM, Pedersen, LL, Osterlind, K et al. (2014) Randomized trial of the effects of individual nutritional counseling in cancer patients. Clin Nutr 33, 749753.CrossRefGoogle ScholarPubMed
Isenring, E, Capra, S, Bauer, J et al. (2003) The impact of nutrition support on body composition in cancer outpatients receiving radiotherapy. Acta Diabetol 40, Suppl. 1, S162164.CrossRefGoogle ScholarPubMed
Isenring, EA, Capra, S & Bauer, JD (2004) Nutrition intervention is beneficial in oncology outpatients receiving radiotherapy to the gastrointestinal or head and neck area. Br J Cancer 91, 447452.CrossRefGoogle ScholarPubMed
Ravasco, P, Monteiro-Grillo, I, Vidal, PM et al. (2005) Dietary counseling improves patient outcomes: a prospective, randomized, controlled trial in colorectal cancer patients undergoing radiotherapy. J Clin Oncol 23, 14311438.CrossRefGoogle ScholarPubMed
Sullivan, ES, Rice, N, Kingston, E et al. (2019) The patient voice: An Irish survey of nutrition attitudes & access to dietetic care throughout the cancer journey. Annals of Oncology 30 (suppl 5), v718 v746CrossRefGoogle Scholar
Isenring, E, Zabel, R, Bannister, M et al. (2013) Updated evidence-based practice guidelines for the nutritional management of patients receiving radiation therapy and/or chemotherapy. Nutr Diet 70, 312324.CrossRefGoogle Scholar
Bradley, PJ, Zutshi, B & Nutting, CM (2005) An audit of clinical resources available for the care of head and neck cancer patients in England. Clin Oncol (R Coll Radiol) 17, 604609.CrossRefGoogle ScholarPubMed
Irish Nutrition & Dietetic Institute (2015) Irish Nutrition & Dietetic Institute Submission to the National Cancer Strategy 2016-2025. Available at: https://www.indi.ie/34-members/special-interest-groups/haematology-and-oncology/568-indi-submission-to-the-national-cancer-control-programme-the-role-of-nutrition-dietetics-in-cancer-services.htmlGoogle Scholar
Trujillo, E, Claghorn, K, Dixon, S et al. (2019) Inadequate nutrition services in outpatient cancer centers: Results of a National Survey. J Oncol 2019, 7462940.CrossRefGoogle ScholarPubMed
Dietitians of Canada Ontario Clinical Nutrition Leaders Action group (CNLAG) (2018) Dietitian staffing levels in Ontario Hospitals. Available at: https://www.dietitians.ca/DietitiansOfCanada/media/Documents/Resources/2018-12-18-2018-Dietitian-staffing-levels-in-Ontario-hospitals_Executive-Summary.pdfGoogle Scholar
O'Sullivan Maillet, J, Brody, RA, Skipper, A et al. (2012) Framework for analyzing supply and demand for specialist and advanced practice registered dietitians. J Acad Nutr Diet 112, S4755.CrossRefGoogle ScholarPubMed
Cuthbertson, D (1942) Post-shock metabolic response. The Lancet 239, 433437.CrossRefGoogle Scholar
Shinko, D, Diakos, CI, Clarke, SJ et al. (2017) Cancer-Related systemic inflammation: the challenges and therapeutic opportunities for personalized medicine. Clin Pharmacol Ther 102, 599610.CrossRefGoogle ScholarPubMed
McMillan, DC (2013) The systemic inflammation-based Glasgow prognostic score: a decade of experience in patients with cancer. Cancer Treat Rev 39, 534540.CrossRefGoogle ScholarPubMed
Solheim, TS, Fearon, KC, Blum, D et al. (2013) Non-steroidal anti-inflammatory treatment in cancer cachexia: a systematic literature review. Acta Oncol 52, 617.CrossRefGoogle ScholarPubMed
Ryan, AM, Reynolds, JV, Healy, L et al. (2009) Enteral nutrition enriched with eicosapentaenoic acid (EPA) preserves lean body mass following esophageal cancer surgery: results of a double-blinded randomized controlled trial. Ann Surg 249, 355363.CrossRefGoogle ScholarPubMed
Persson, C, Glimelius, B, Ronnelid, J et al. (2005) Impact of fish oil and melatonin on cachexia in patients with advanced gastrointestinal cancer: a randomized pilot study. Nutrition 21, 170178.CrossRefGoogle ScholarPubMed
Lewis, C, Xun, P, Fly, AD et al. (2015) Fish oil supplementation and quality of life in stage II colorectal cancer patients: a 24-month follow-up study. Nutr Cancer 67, 12391246.CrossRefGoogle ScholarPubMed
Werner, K, Kullenberg de Gaudry, D, Taylor, LA et al. (2017) Dietary supplementation with n-3-fatty acids in patients with pancreatic cancer and cachexia: marine phospholipids versus fish oil - a randomized controlled double-blind trial. Lipids Health Dis 16, 104.CrossRefGoogle ScholarPubMed
Camargo, CQ, Mocellin, MC, Brunetta, HS et al. (2019) Fish oil decreases the severity of treatment-related adverse events in gastrointestinal cancer patients undergoing chemotherapy: a randomized, placebo-controlled, triple-blind clinical trial. Clin Nutr ESPEN 31, 6170.CrossRefGoogle ScholarPubMed
Maddocks, M, Murton, AJ & Wilcock, A (2012) Therapeutic exercise in cancer cachexia. Crit Rev Oncog 17, 285292.CrossRefGoogle ScholarPubMed
Turner, RR, Steed, L, Quirk, H et al. (2018) Interventions for promoting habitual exercise in people living with and beyond cancer. Cochrane Database Syst Rev 9, CD010192.Google ScholarPubMed
Mishra, SI, Scherer, RW, Snyder, C et al. (2012) Exercise interventions on health-related quality of life for people with cancer during active treatment. Cochrane Database Syst Rev 8, CD008465.Google Scholar
Mishra, SI, Scherer, RW, Geigle, PM et al. (2012) Exercise interventions on health-related quality of life for cancer survivors. Cochrane Database Syst Rev 8, CD007566.Google Scholar
Sweegers, MG, Altenburg, TM, Chinapaw, MJ et al. (2018) Which exercise prescriptions improve quality of life and physical function in patients with cancer during and following treatment? A systematic review and meta-analysis of randomised controlled trials. Br J Sports Med 52, 505513.CrossRefGoogle ScholarPubMed
Buffart, LM, Sweegers, MG, May, AM et al. (2018) Targeting exercise interventions to patients with cancer in need: an individual patient data meta-analysis. J Natl Cancer Inst 110, 11901200.CrossRefGoogle ScholarPubMed
Campbell, KL, Winters-Stone, KM, Wiskemann, J et al. (2019) Exercise guidelines for cancer survivors: consensus statement from international multidisciplinary roundtable. Med Sci Sports Exerc 51, 23752390.CrossRefGoogle ScholarPubMed
Schmitz, KH, Courneya, KS, Matthews, C et al. (2010) American college of sports medicine roundtable on exercise guidelines for cancer survivors. Med Sci Sports Exerc 42, 14091426.CrossRefGoogle ScholarPubMed
Cormie, P, Atkinson, M, Bucci, L et al. (2018) Clinical oncology society of Australia position statement on exercise in cancer care. Med J Aust 209, 184187.CrossRefGoogle ScholarPubMed
Solheim, TS, Vagnildhaug, OM, Laird, BJ et al. (2019) Combining optimal nutrition and exercise in a multimodal approach for patients with active cancer with risk of losing weight rationale and practical approach. Nutrition [Epublication 27 Jun 2019].CrossRefGoogle Scholar
Del Fabbro, E (2015) Current and Future Care of Patients with the Cancer Anorexia-Cachexia Syndrome. Am Soc Clin Oncol Educ Book 2015, e299-237.CrossRefGoogle Scholar
Muscaritoli, M, Molfino, A, Gioia, G et al. (2011) The “parallel pathway”: a novel nutritional and metabolic approach to cancer patients. Intern Emerg Med 6, 105112.CrossRefGoogle ScholarPubMed
Hall, CC, Cook, J, Maddocks, M et al. (2019) Combined exercise and nutritional rehabilitation in outpatients with incurable cancer: a systematic review. Support Care Cancer 27, 23712384.CrossRefGoogle ScholarPubMed
Solheim, TS, Laird, BJA, Balstad, TR et al. (2018) Cancer cachexia: rationale for the MENAC (Multimodal-Exercise, Nutrition and Anti-Inflammatory Medication for Cachexia) trial. BMJ Support Palliat Care 8, 258265.CrossRefGoogle ScholarPubMed
Climent, M, Munarriz, M, Blazeby, JM et al. (2017) Weight loss and quality of life in patients surviving 2 years after gastric cancer resection. Eur J Surg Oncol 43, 13371343.CrossRefGoogle ScholarPubMed
Gavazzi, C, Colatruglio, S, Sironi, A et al. (2011) Importance of early nutritional screening in patients with gastric cancer. Br J Nutr 106, 17731778.CrossRefGoogle ScholarPubMed
Pacelli, F, Bossola, M, Rosa, F et al. (2008) Is malnutrition still a risk factor of postoperative complications in gastric cancer surgery? Clin Nutr 27, 398407.CrossRefGoogle Scholar
Correia, M, Cravo, M, Marques-Vidal, P et al. (2007) Serum concentrations of TNF-alpha as a surrogate marker for malnutrition and worse quality of life in patients with gastric cancer. Clin Nutr 26, 728735.CrossRefGoogle ScholarPubMed
Berstad, P, Haugum, B, Helgeland, M et al. (2013) Preoperative body size and composition, habitual diet, and post-operative complications in elective colorectal cancer patients in Norway. J Hum Nutr Diet 26, 359368.CrossRefGoogle ScholarPubMed
Burden, ST, Hill, J, Shaffer, JL et al. (2010) Nutritional status of preoperative colorectal cancer patients. J Hum Nutr Diet 23, 402407.CrossRefGoogle ScholarPubMed
Zacharakis, M, Xynos, ID, Lazaris, A et al. (2010) Predictors of survival in stage IV metastatic colorectal cancer. Anticancer Res 30, 653660.Google ScholarPubMed
van der Werf, A, van Bokhorst, QNE, de van der Schueren, MAE et al. (2018) Cancer cachexia: identification by clinical assessment versus international consensus criteria in patients with metastatic colorectal cancer. Nutr Cancer 70, 13221329.CrossRefGoogle ScholarPubMed
Pressoir, M, Desné, S, Berchery, D et al. (2010) Prevalence, risk factors and clinical implications of malnutrition in French comprehensive cancer centres. Br J Cancer 102, 966971.CrossRefGoogle ScholarPubMed
van der Schaaf, MK, Tilanus, HW, van Lanschot, JJ et al. (2014) The influence of preoperative weight loss on the postoperative course after esophageal cancer resection. J Thorac Cardiovasc Surg 147, 490495.CrossRefGoogle ScholarPubMed
Martin, L, Jia, C, Rouvelas, I et al. (2008) Risk factors for malnutrition after oesophageal and cardia cancer surgery. Br J Surg 95, 13621368.CrossRefGoogle ScholarPubMed
Hynes, O, Anandavadivelan, P, Gossage, J et al. (2017) The impact of pre- and post-operative weight loss and body mass index on prognosis in patients with oesophageal cancer. Eur J Surg Oncol 43, 15591565.CrossRefGoogle ScholarPubMed
Lakenman, P, Ottens-Oussoren, K, Witvliet-van Nierop, J et al. (2017) Handgrip strength is associated with treatment modifications during neoadjuvant chemoradiation in patients with esophageal cancer. Nutr Clin Pract 32, 652657.CrossRefGoogle ScholarPubMed
Deans, DA, Tan, BH, Wigmore, SJ et al. (2009) The influence of systemic inflammation, dietary intake and stage of disease on rate of weight loss in patients with gastro-oesophageal cancer. Br J Cancer 100, 6369.CrossRefGoogle ScholarPubMed
Shen, S, Araujo, JL, Altorki, NK et al. (2017) Variation by stage in the effects of prediagnosis weight loss on mortality in a prospective cohort of esophageal cancer patients. Dis Esophagus 30, 17.CrossRefGoogle Scholar
Morio, K, Minami, T, Sozu, T et al. (2016) Weight loss associated with platinum-based chemotherapy in patients with advanced lung cancer. Chemotherapy 61, 256261.CrossRefGoogle ScholarPubMed
Sanders, KJ, Hendriks, LE, Troost, EG et al. (2016) Early weight loss during chemoradiotherapy Has a detrimental impact on outcome in NSCLC. J Thorac Oncol 11, 873879.CrossRefGoogle Scholar
Alexander, M, Evans, SM, Stirling, RG et al. (2016) The influence of comorbidity and the simplified comorbidity score on overall survival in non-small cell lung cancer-A prospective cohort study. J Thorac Oncol 11, 748757.CrossRefGoogle ScholarPubMed
Alexander, M, Wolfe, R, Ball, D et al. (2017) Lung cancer prognostic index: a risk score to predict overall survival after the diagnosis of non-small-cell lung cancer. Br J Cancer 117, 744751.CrossRefGoogle Scholar
Kawai, H, Saito, Y & Suzuki, Y (2017) Gender differences in the correlation between prognosis and postoperative weight loss in patients with non-small cell lung cancer. Interact Cardiovasc Thorac Surg 25, 272277.CrossRefGoogle ScholarPubMed
Colinet, B, Jacot, W, Bertrand, D et al. (2005) A new simplified comorbidity score as a prognostic factor in non-small-cell lung cancer patients: description and comparison with the Charlson's index. Br J Cancer 93, 10981105.CrossRefGoogle ScholarPubMed
Kiss, N, Isenring, E, Gough, K et al. (2014) The prevalence of weight loss during (chemo)radiotherapy treatment for lung cancer and associated patient- and treatment-related factors. Clin Nutr 33, 10741080.CrossRefGoogle ScholarPubMed
Russell, K, Healy, B, Pantarotto, J et al. (2014) Prognostic factors in the radical nonsurgical treatment of stage IIIB non-small-cell lung cancer. Clin Lung Cancer 15, 237243.CrossRefGoogle ScholarPubMed
Caan, BJ, Kwan, ML, Hartzell, G et al. (2008) Pre-diagnosis body mass index, post-diagnosis weight change, and prognosis among women with early stage breast cancer. Cancer Causes & Control: CCC 19, 13191328.CrossRefGoogle ScholarPubMed
Bradshaw, PT, Ibrahim, JG, Stevens, J et al. (2012) Postdiagnosis change in bodyweight and survival after breast cancer diagnosis. Epidemiology 23, 320327.CrossRefGoogle ScholarPubMed
Harimoto, N, Shirabe, K, Yamashita, YI et al. (2013) Sarcopenia as a predictor of prognosis in patients following hepatectomy for hepatocellular carcinoma. Br J Surg 100, 15231530.CrossRefGoogle ScholarPubMed
Voron, T, Tselikas, L, Pietrasz, D et al. (2015) Sarcopenia impacts on short- and long-term results of Hepatectomy for Hepatocellular Carcinoma. Ann Surg 261, 11731183.CrossRefGoogle Scholar
Kamachi, S, Mizuta, T, Otsuka, T et al. (2016) Sarcopenia is a risk factor for the recurrence of hepatocellular carcinoma after curative treatment. Hepatol Res: the official J Japan Soc Hepatol 46, 201208.CrossRefGoogle ScholarPubMed
Nault, JC, Pigneur, F, Nelson, AC et al. (2015) Visceral fat area predicts survival in patients with advanced hepatocellular carcinoma treated with tyrosine kinase inhibitors. Dig Liver Dis 47, 869876.CrossRefGoogle ScholarPubMed
Black, D, Mackay, C, Ramsay, G et al. (2017) Prognostic value of computed tomography: measured parameters of body composition in primary operable gastrointestinal cancers. Ann Surg Oncol 24, 22412251.CrossRefGoogle ScholarPubMed
Anandavadivelan, P, Brismar, TB, Nilsson, M et al. (2016) Sarcopenic obesity: a probable risk factor for dose limiting toxicity during neo-adjuvant chemotherapy in oesophageal cancer patients. Clin Nutr 35, 724730.CrossRefGoogle ScholarPubMed
Grotenhuis, B, Shapiro, J, van Adrichem, S et al. (2016) Sarcopenia/muscle mass is not a prognostic factor for short- and long-term outcome after esophagectomy for cancer. World J Surg 40, 26982704.CrossRefGoogle ScholarPubMed
Reisinger, KW, Bosmans, JW, Uittenbogaart, M et al. (2015) Loss of skeletal muscle mass during neoadjuvant chemoradiotherapy predicts postoperative mortality in esophageal cancer surgery. Ann Surg Oncol 22, 44454452.CrossRefGoogle ScholarPubMed
Awad, S, Tan, BH, Cui, H et al. (2012) Marked changes in body composition following neoadjuvant chemotherapy for oesophagogastric cancer. Clin Nutr 31, 7477.CrossRefGoogle ScholarPubMed
Paireder, M, Asari, R, Kristo, I et al. (2017) Impact of sarcopenia on outcome in patients with esophageal resection following neoadjuvant chemotherapy for esophageal cancer. Eur J Surg Oncol 43, 478484.CrossRefGoogle ScholarPubMed
Tamandl, D, Paireder, M, Asari, R et al. (2016) Markers of sarcopenia quantified by computed tomography predict adverse long-term outcome in patients with resected oesophageal or gastro-oesophageal junction cancer. Eur Radiol 26, 13591367.CrossRefGoogle ScholarPubMed
Sato, S, Kunisaki, C, Suematsu, H et al. (2018) Impact of sarcopenia in patients with unresectable locally advanced esophageal cancer receiving chemoradiotherapy. In vivo 32, 603610.Google ScholarPubMed
Nishigori, T, Okabe, H, Tanaka, E et al. (2016) Sarcopenia as a predictor of pulmonary complications after esophagectomy for thoracic esophageal cancer. J Surg Oncol 113, 678684.CrossRefGoogle ScholarPubMed
Sharma, P, Zargar-Shoshtari, K, Caracciolo, JT et al. (2015) Sarcopenia as a predictor of overall survival after cytoreductive nephrectomy for metastatic renal cell carcinoma. Urol Oncol 33, 339.e317323.CrossRefGoogle ScholarPubMed
Psutka, SP, Boorjian, SA, Moynagh, MR et al. (2016) Decreased skeletal muscle mass is associated with an increased risk of mortality after radical nephrectomy for localized renal cell cancer. J Urol 195, 270276.CrossRefGoogle ScholarPubMed
Huillard, O, Mir, O, Peyromaure, M et al. (2013) Sarcopenia and body mass index predict sunitinib-induced early dose-limiting toxicities in renal cancer patients. Br J Cancer 108, 10341041.CrossRefGoogle ScholarPubMed
Antoun, S, Birdsell, L, Sawyer, MB et al. (2010) Association of skeletal muscle wasting with treatment with sorafenib in patients with advanced renal cell carcinoma: results from a placebo-controlled study. J Clin Oncol 28, 10541060.CrossRefGoogle ScholarPubMed
Fukushima, H, Nakanishi, Y, Kataoka, M et al. (2016) Prognostic significance of sarcopenia in patients with metastatic renal cell carcinoma. J Urol 195, 2632.CrossRefGoogle ScholarPubMed
Cushen, SJ, Power, DG, Murphy, KP et al. (2016) Impact of body composition parameters on clinical outcomes in patients with metastatic castrate-resistant prostate cancer treated with docetaxel. Clin Nutr 13, e39e45.Google ScholarPubMed
Mason, RJ, Boorjian, SA, Bhindi, B et al. (2018) The association between sarcopenia and oncologic outcomes after radical prostatectomy. Clin Genitourin Cancer 16, e629e636.CrossRefGoogle ScholarPubMed
Xiao, DY, Luo, S, O'Brian, K et al. (2016) Impact of sarcopenia on treatment tolerance in United States veterans with diffuse large B-cell lymphoma treated with CHOP-based chemotherapy. Am J Hematol 91, 10021007.CrossRefGoogle ScholarPubMed
Thoresen, L, Frykholm, G, Lydersen, S et al. (2012) The association of nutritional assessment criteria with health-related quality of life in patients with advanced colorectal carcinoma. Eur J Cancer Care (Engl) 21, 505516.CrossRefGoogle ScholarPubMed
van Roekel, EH, Bours, MJL, Te Molder, MEM et al. (2017) Associations of adipose and muscle tissue parameters at colorectal cancer diagnosis with long-term health-related quality of life. Qual Life Res 26, 17451759.CrossRefGoogle ScholarPubMed
Thoresen, L, Frykholm, G, Lydersen, S et al. (2013) Nutritional status, cachexia and survival in patients with advanced colorectal carcinoma. Different assessment criteria for nutritional status provide unequal results. Clin Nutr 32, 6572.CrossRefGoogle ScholarPubMed
Chemama, S, Bayar, MA, Lanoy, E et al. (2016) Sarcopenia is associated with chemotherapy toxicity in patients undergoing cytoreductive surgery with hyperthermic intraperitoneal chemotherapy for peritoneal carcinomatosis from colorectal cancer. Ann Surg Oncol 23, 38913898.CrossRefGoogle ScholarPubMed
McSorley, ST, Black, DH, Horgan, PG et al. (2017) The relationship between tumour stage, systemic inflammation, body composition and survival in patients with colorectal cancer. Clin Nutr 37, 12791285.CrossRefGoogle ScholarPubMed
Reisinger, KW, van Vugt, JL, Tegels, JJ et al. (2015) Functional compromise reflected by sarcopenia, frailty, and nutritional depletion predicts adverse postoperative outcome after colorectal cancer surgery. Ann Surg 261, 345352.CrossRefGoogle ScholarPubMed
Broughman, JR, Williams, GR, Deal, AM et al. (2015) Prevalence of sarcopenia in older patients with colorectal cancer. J Geriatr Oncol 6, 442445.CrossRefGoogle ScholarPubMed
Nakanishi, R, Oki, E, Sasaki, S et al. (2018) Sarcopenia is an independent predictor of complications after colorectal cancer surgery. Surg Today 48, 151157.CrossRefGoogle ScholarPubMed
Malietzis, G, Johns, N, Al-Hassi, HO et al. (2016) Low muscularity and myosteatosis Is related to the host systemic inflammatory response in patients undergoing surgery for colorectal cancer. Ann Surg 263, 320325.CrossRefGoogle ScholarPubMed
Eriksson, S, Nilsson, JH, Strandberg Holka, P et al. (2017) The impact of neoadjuvant chemotherapy on skeletal muscle depletion and preoperative sarcopenia in patients with resectable colorectal liver metastases. HPB (Oxford) 19, 331337.CrossRefGoogle ScholarPubMed
Barret, M, Antoun, S, Dalban, C et al. (2014) Sarcopenia is linked to treatment toxicity in patients with metastatic colorectal cancer. Nutr Cancer 66, 583589.CrossRefGoogle ScholarPubMed
Jarvinen, T, Ilonen, I, Kauppi, J et al. (2018) Loss of skeletal muscle mass during neoadjuvant treatments correlates with worse prognosis in esophageal cancer: a retrospective cohort study. World J Surg Oncol 16, 27.CrossRefGoogle ScholarPubMed
Mayr, R, Fritsche, HM, Zeman, F et al. (2018) Sarcopenia predicts 90-day mortality and postoperative complications after radical cystectomy for bladder cancer. World J Urol 36, 12011207.CrossRefGoogle ScholarPubMed
Kocher, NJ, Jafri, S, Balabhadra, S et al. (2018) Is sarcopenia and sarcopenic obesity associated with clinical and pathological outcomes in patients undergoing radical nephroureterectomy? Urol Oncol 36, 156.e117156.e122.CrossRefGoogle ScholarPubMed
Hirasawa, Y, Nakashima, J, Yunaiyama, D et al. (2016) Sarcopenia as a novel preoperative prognostic predictor for survival in patients with bladder cancer undergoing radical cystectomy. Ann Surg Oncol 23, 10481054.CrossRefGoogle ScholarPubMed
Fukushima, H, Yokoyama, M, Nakanishi, Y et al. (2015) Sarcopenia as a prognostic biomarker of advanced urothelial carcinoma. PLoS ONE 10, e0115895.CrossRefGoogle ScholarPubMed
Psutka, SP, Carrasco, A, Schmit, GD et al. (2014) Sarcopenia in patients with bladder cancer undergoing radical cystectomy: impact on cancer-specific and all-cause mortality. Cancer 120, 29102918.CrossRefGoogle ScholarPubMed
Kumar, A, Moynagh, MR, Multinu, F et al. (2016) Muscle composition measured by CT scan is a measurable predictor of overall survival in advanced ovarian cancer. Gynecol Oncol 142, 311316.CrossRefGoogle ScholarPubMed
Valentine, H, François, G, Nora, K et al. (2017) Sarcopenic overweight is associated with early acute limiting toxicity of anti-PD1 checkpoint inhibitors in melanoma patients. Invest New Drugs 35, 436441.Google Scholar
Del Fabbro, E, Parsons, H, Warneke, CL et al. (2012) The relationship between body composition and response to neoadjuvant chemotherapy in women with operable breast cancer. Oncologist 17, 12401245.CrossRefGoogle ScholarPubMed
Weinberg, MS, Shachar, SS, Muss, HB et al. (2018) Beyond sarcopenia: characterization and integration of skeletal muscle quantity and radiodensity in a curable breast cancer population. Breast J 24, 278284.CrossRefGoogle Scholar
Mazzuca, F, Onesti, CE, Roberto, M et al. (2018) Lean body mass wasting and toxicity in early breast cancer patients receiving anthracyclines. Oncotarget 9, 2571425722.CrossRefGoogle ScholarPubMed
Deluche, E, Leobon, S, Desport, JC et al. (2018) Impact of body composition on outcome in patients with early breast cancer. Support Care Cancer 26, 861868.CrossRefGoogle ScholarPubMed
Mourtzakis, M, Prado, CM, Lieffers, JR et al. (2008) A practical and precise approach to quantification of body composition in cancer patients using computed tomography images acquired during routine care. Appl Physiol Nutr Metab 33, 9971006.CrossRefGoogle ScholarPubMed
Hu, X, Dou, WC, Shao, YX et al. (2019) The prognostic value of sarcopenia in patients with surgically treated urothelial carcinoma: a systematic review and meta-analysis. Eur J Surg Oncol 45, 747754.CrossRefGoogle ScholarPubMed
Li, J, Deng, Y, Zhang, M et al. (2019) Prognostic value of radiologically determined sarcopenia prior to treatment in urologic tumors: a meta-analysis. Medicine 98, e17213.CrossRefGoogle ScholarPubMed
Deng, HY, Zha, P, Peng, L et al. (2019) Preoperative sarcopenia is a predictor of poor prognosis of esophageal cancer after esophagectomy: a comprehensive systematic review and meta-analysis. Dis Esophagus 32.CrossRefGoogle ScholarPubMed
Zhang, G, Meng, S, Li, R et al. (2017) Clinical significance of sarcopenia in the treatment of patients with primary hepatic malignancies, a systematic review and meta-analysis. Oncotarget 8, 102474102485.CrossRefGoogle ScholarPubMed
Yang, M, Shen, Y, Tan, L et al. (2019) Prognostic value of sarcopenia in lung cancer: a systematic review and meta-analysis. Chest 156, 101111.CrossRefGoogle ScholarPubMed
Chang, KV, Chen, JD, Wu, WT et al. (2018) Association between loss of skeletal muscle mass and mortality and tumor recurrence in hepatocellular carcinoma: a systematic review and meta-analysis. Liver Cancer 7, 90103.CrossRefGoogle ScholarPubMed
Sun, G, Li, Y, Peng, Y et al. (2018) Can sarcopenia be a predictor of prognosis for patients with non-metastatic colorectal cancer? A systematic review and meta-analysis. Int J Colorectal Dis 33, 14191427.CrossRefGoogle ScholarPubMed
Su, H, Ruan, J, Chen, T et al. (2019) CT-assessed sarcopenia is a predictive factor for both long-term and short-term outcomes in gastrointestinal oncology patients: a systematic review and meta-analysis. Cancer Imaging 19, 82.CrossRefGoogle ScholarPubMed
Vrieling, A, Kampman, E, Knijnenburg, NC et al. (2018) Body composition in relation to clinical outcomes in renal cell cancer: a systematic review and meta-analysis. Eur Urol Focus 4, 420434.CrossRefGoogle ScholarPubMed
Aleixo, GFP, Williams, GR, Nyrop, KA et al. (2019) Muscle composition and outcomes in patients with breast cancer: meta-analysis and systematic review. Breast Cancer Res Treat 177, 569579.CrossRefGoogle ScholarPubMed
Bundred, J, Kamarajah, SK & Roberts, KJ (2019) Body composition assessment and sarcopenia in patients with pancreatic cancer: a systematic review and meta-analysis. HPB: Official J Int Hepato Pancreato Biliary Assoc 21, 16031612.CrossRefGoogle ScholarPubMed
Rinninella, E, Cintoni, M, Raoul, P et al. (2019) Muscle mass, assessed at diagnosis by L3-CT scan as a prognostic marker of clinical outcomes in patients with gastric cancer: a systematic review and meta-analysis. Clin Nutr 39, 20452054.CrossRefGoogle ScholarPubMed
Buentzel, J, Heinz, J, Bleckmann, A et al. (2019) Sarcopenia as prognostic factor in lung cancer patients: a systematic review and meta-analysis. Anticancer Res 39, 46034612.CrossRefGoogle ScholarPubMed
Ubachs, J, Ziemons, J, Minis-Rutten, IJG et al. (2019) Sarcopenia and ovarian cancer survival: a systematic review and meta-analysis. J Cachexia Sarcopenia Muscle 10, 11651174.CrossRefGoogle ScholarPubMed
Borggreve, AS, den Boer, RB, van Boxel, GI, et al. (2020) The predictive value of low muscle mass as measured on CT scans for postoperative complications and mortality in gastric cancer patients: a systematic review and meta-analysis. J Clin Med 9, 199.CrossRefGoogle Scholar
Figure 0

Table 1. Prevalence of patients with >5% weight loss according to primary tumour location in the scientific literature

Figure 1

Fig. 1. Prevalence of sarcopenia in patients with cancer according to the primary tumour location in the literature (all stages).(63–68,136,41,61,69–73,111,180,256–260,90,94,261–264,12,113,265–270,95,271–275,52,60,149,150,276,277,185,260,278–280,86–88,281,282,283–287,91,288–293,11,47,57,58,92,162,164,268,294,295,7,93,96,100,165,296–299).Prevalence of sarcopenia defined using three of the most common definitions for defining low muscle mass is displayed in Table 1. These definitions are as follows; Prado et al.(92): Skeletal muscle index (SMI)<52⋅4 cm2/m2 in men and <38⋅5 cm2/m2 in women; Martin et al.(47): SMI <43⋅0 cm2/m2 in men with a BMI <25 kg/m2 and <53⋅0 cm2/m2 in men with a BMI >25 kg/m2 and SMI <41⋅0 cm2/m2 in women; Baumgartner et al.(55) converted dual-energy X-ray absorptiometry cut points by Mourtzakis et al.(300) as SMI <55 4 cm2/m2 in men and <38⋅9 cm2/m2 in women.

Figure 2

Fig. 2. (Colour online) Forest Plot depicting summary results of meta-analyses examining the role of sarcopenia in survival in cancer. Asterisks denote studies which did not confirm the inclusion of multivariate data in the meta-analysis(153,301–304,305–310,170,311–315).