3 results
OP22 Benchmarking Of Population-Based Childhood Cancer Survival By Toronto Stage: Know The Differences To Propose Effective Interventions
- Rosalia Ragusa, Dott Fabio Didonè, Laura Botta, Antonina Torrisi, Maria Alessandra Bellia, Gemma Gatta, BENCHISTA Italy working group
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- Journal:
- International Journal of Technology Assessment in Health Care / Volume 39 / Issue S1 / December 2023
- Published online by Cambridge University Press:
- 14 December 2023, p. S7
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Introduction
Pediatric cancers are rare tumors, heterogeneous in location and biologically very different from adult cancers. Documented survival variation across European countries and Italian regions shows that there is still room for further improvement by reducing inequalities. We aim to understand why there are differences in survival. The BENCHISTA-ITA project (National Benchmarking of Childhood Cancer Survival by Stage at diagnosis), that is the Italian twin project of the International BENCHISTA, collects stage at diagnosis of solid pediatric tumors, according to the Toronto Guidelines. We will compare how far the cancer has spread at diagnosis and test if differences in tumor stage explain any survival differences between Italian regions.
MethodsThe project study involved the stage distribution and the survival of 9 pediatric solid tumors diagnosed between 2013 and 2017 in Italy. All patients therefore had at least 3 years of follow-up in 2021 for life-stage definition. The study involves the identification of all new diagnoses of cancer, evaluation of the clinical documentation of cases eligible for research, and international classification and coding. Analyses of stage distribution and survival rates for each tumor type will be described.
ResultsData from 35 population-based cancer registries from 18 out of 20 Italian regions were collected covering about 84 percent of the Italian child population. In particular, data on: imaging/examination performed before any treatment; source used for staging; primary treatment defined as given within one year from diagnosis; relapse/ recurrence/ progression; follow up and status of life. The study tested the applicability of the Toronto Guidelines as a tool to obtain population-level comparable stage information for childhood cancers. There were 1,343 cases collected (242 Neuroblastoma, 124 Wilms Tumour, 145 Medulloblastoma, 148 Osteosarcoma, 135 Ewing sarcoma, 115 Rhabdomyososarcoma, 54 Ependymoma, 47 Retinoblastoma, 333 Astrocytoma). Toronto stage could be assigned in more than 90 percent in the majority of tumors. Tumors in which it was more difficult to assign the stage using the Toronto staging guidelines were ependymoma, astrocytoma, and retinoblastoma. It was easier to retrieve data for patients in the 0-14 years of age range than adolescents (14-18 years). Differences in stage distribution and survival differences between regional grouping were presented.
ConclusionsThe Italian BENCHISTA project, improving the connection between pediatric cancer registries, aims to improve care of children with cancer across the nation, reducing possible disparities.
The wide adoption of the Toronto Guidelines will facilitate international comparative incidence studies, strengthen the interpretation of survival data, and contribute to more appropriate solutions to improve childhood cancer outcomes.
OP135 Machine Learning And Cancer Registry: Evaluation Of The Effectiveness Of Case Coding
- Carmelo Ettore Viscosi, Alessia Anna Di Prima, Antonina Torrisi, Antonietta Alfia Torrisi, Margherita Ferrante, Rosalia Ragusa
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- Journal:
- International Journal of Technology Assessment in Health Care / Volume 39 / Issue S1 / December 2023
- Published online by Cambridge University Press:
- 14 December 2023, p. S39
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Introduction
Machine learning (ML) algorithms are computational procedures that use pattern recognition and inference by learning from previously categorized documents to predict the category to which a new document belongs. The role of machine learning within cancer registries remains unclear given the lack of in-depth testing and guidance from health technology assessment (HTA) agencies. We evaluated the effectiveness of coding new cases through machine learning at the Integrated Cancer Registry.
MethodsThe Integrated Cancer Registry covers the eastern area of Sicily in Italy, which has an annual average incidence of about 10,000 cases of malignant neoplasm. Potential new cancer cases were retrieved from pathology services and processed by pathologists who confirmed the neoplastic nature of supposed cases and specified the morphological type and location of the tumors. The current method involves identification by reading the free-text report when International Classification Diseases for Oncology information was not provided. We used the new Microsoft ML.Net Library, a framework developed in response to the challenge of facilitating machine learning pipeline utilization in large software applications. A total of 1,050,952 free-text pathology reports published from 2003 to 2018 were selected separately from all Sicilian pathology services and uploaded to machine learning software that explored eight binary classification algorithms.
ResultsWe evaluated each algorithm’s performance by calculating metrics (the number of true positives, true negatives, false positives, and false negatives) from the classification procedure applied to the test dataset. The metrics used were accuracy, F1 score, and area under the receiver operating characteristic curve. With a test set of around 210,000 text diagnoses, each algorithm reached an F1 score of up to 95 percent.
ConclusionsMachine learning algorithms capture relevant information about tumors from free-text pathology reports, optimizing the process and reducing waste. With the help of machine learning systems, cancer registries can provide more timely data for research and evaluation of all types of new cancer technologies (drugs, devices, radiology and radiotherapy equipment, diagnostic devices, robotic surgery, and vaccines).
OP45 HTA And Gender Medicine: Time To Take Action!
- Rosalia Ragusa, Vincenzo Guardabasso, Maria Alessandra Bellia, Filippo Piana, Rosalba Quattrocchi
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- Journal:
- International Journal of Technology Assessment in Health Care / Volume 39 / Issue S1 / December 2023
- Published online by Cambridge University Press:
- 14 December 2023, p. S12
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Introduction
Gender medicine responds to the need for a reassessment of the medical-scientific approach in a gender perspective, to increase knowledge of the different aspects underlying gender differences and the appropriateness/ effectiveness of health interventions.
MethodsA policy review of documents prepared by the Italian Ministry of Health on gender medicine was carried out, to investigate the possible areas of intervention of health technology assessment in the development of this interdisciplinary dimension. The areas of highest priority for action have been identified.
ResultsIn Italy, the Ministry of Health, with the support of the National Institute of Health, issued a Plan for Application and Dissemination of Gender Medicine in June 2019. Our review shows that for the development of research on the mechanisms of pathogenesis the Italian Plan gives indications on the identification of diagnostic markers, prognostic and predictive response in a gender perspective, but there are no formalized rules that constitute a constraint or an obligation to do so. In Horizon Europe calls, for example, “Pragmatic trials on minimally invasive diagnostics” (HORIZON-MISS-2023-CANCER-01-03) on the other hand, it is required that gender and gender issues should be taken into account in all projects and all data should be disaggregated by gender, socio-economic status and ethnicity. Separating subjects into two groups in the analysis leads to greater complexity. This is even more true when considering the different types of gender. The total number of subjects to be included must likely increase to maintain statistical power in evaluating effects in subgroups. This increase leads to an increase in time and cost, if one needs to provide separate data by sex and even more so by gender. Different statistical tests to be used, according to the type of variables of the primary endpoint, should be considered in the study protocols.
ConclusionsIt seems appropriate to suggest reviewing upcoming health technology assessments with an eye to gender medicine. Gender medicine should become a strategic goal of prevention in public health and will strengthen the concept of the patient centrality until the personalization of therapies is achieved.