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The assessment and management of cancer pain is a complex enterprise. This chapter will describe key elements of assessment and management, critique the emerging supportive evidence base, and discuss the basis for future studies of the underlying science.
Assessing cancer pain
Aspects of clinical practice
The goals of cancer pain assessment include characterization of the pain complaint and integration of information in a manner that leads to inferences about underlying pathophysiology and syndrome recognition. Th is understanding is the foundation for diverse management strategies that often rely on multiple modalities to relieve pain while minimizing side eff ects and treatment burden.
Pain measurement
Pain may be evaluated in terms of severity, location, quality, and other aspects. Among the most salient elements is measurement of pain intensity, which may be viewed as the cutting edge of the longstanding effort to develop a scientific foundation to assessment.
The scientifi c basis of patient ratings of pain intensity began more than half a century ago with the early development of clinical trials methodology for the evaluation of analgesics. These studies confirmed that a subjective experience like pain can be validly measured using self-reported rating scales. In the clinical setting, however, the measurement of cancer pain intensity often is beset by practical problems. Some patients are not able to respond with numerical descriptors. Other patients may have an impaired cognitive status or are simply unable to answer questions. This is an area where much work still needs to be done.
Objectives: The purposes of this study were to study symptomatic metastatic cancer patients' knowledge and attitudes toward end-of-life (EOL) care and to examine how patient-perceived health status affects attitudes toward EOL care and survival.
Methods: From 1999 to 2002, 254 symptomatic metastatic cancer patients at the VA New Jersey Health Care System completed the Vermont Voices on Care of the Dying Questionnaire. Survival status and location of death were obtained. Descriptive statistics and the chi square method were used to assess the differences between African Americans (N = 109) and Caucasians (N = 135), and between different patient-perceived health status groups. A log-rank test was performed to assess for differences in median survival length between different patient-perceived health-status groups.
Results: Veterans' responses to the Vermont questionnaire showed knowledge deficits regarding EOL care. There was wide variation in self-rankings of health status: 45.6% of patients rated their illness as serious and life threatening, 18.9% considered their health problem significant but not life threatening, 2.8% thought they were in good health, and one-third of patients were unsure about their health status. Most patients (86.2%) preferred physician frankness when communicating bad news and 61.8% preferred family involvement in EOL discussions. African American patients were less likely to have completed advance directives (p < 0.0001), to have knowledge about hospice programs (p < 0.00001), and to feel capable of assessing their health situation (p = 0.04). Patient-rated health status affected completion rates of advance directives and survival.
Significance of the research: These findings demonstrate knowledge deficits and racial differences in attitudes and values toward EOL care in veterans with cancer. The Vermont questionnaire enables patients to state their EOL preferences but may not be detailed enough for clinical applications. Patient-rated health status may be an important explanatory variable for EOL preferences and length of survival.
Objectives: Caregiver outcomes among those caring for symptomatic advanced cancer patients at VA Medical Centers have not been well reported. The purposes of this study were (1) to identify the caregiver characteristics and their unmet needs; (2) to examine the association between caregiver unmet needs, caregiver burden, and caregiver satisfaction; and (3) to identify the independent predictors of different caregiver outcomes.
Methods: One hundred caregivers completed three caregiver outcomes instruments: Family Inventory of Needs (FIN), Care Strain Index (CSI), and Family Satisfaction with Advanced Cancer Care (FAMCARE). The caregivers' demographics and their function, depression, health status, and social support status as well as the caregivers' perception of the patients' unmet needs (PPUN) were obtained. Principal component analysis was performed to examine the underlying dimensions of caregiver outcome measures. Pearson correlation and stepwise multivariate regression analyses were performed.
Results: The median number of unmet needs was 2 and the median CSI score was 4. Most of unmet needs were related to information needs (needing more information related to home care, finding help with the problems at home, and disease prognosis) and symptom management. The majority of caregivers were satisfied or very satisfied by the care patients received. Spouse caregivers (N = 60, 60%) were significantly older (p = 0.006) with higher unemployment rates (p = 0.001), higher depression scores (p = 0.04), and lower social support scores (p < 0.0001) than nonspouse caregivers (N = 40, 40%). The PPUN predicted caregiver burden and the presence of caregiver unmet needs independently. The presence of caregiver unmet needs was the only independent predictor of caregiver satisfaction. Caregivers with a high PPUN and higher depression score experienced a higher burden.
Significance of the research: The caregiver outcome model is proposed and needs to be further validated in a new cohort of caregivers.
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