Introduction: The European Organisation for Research and Treatment of Cancer Quality of Life Core Questionnaire (EORTC QLQ-C30) measures 15 health-related quality of life (HRQoL) scales relevant to... Show moreIntroduction: The European Organisation for Research and Treatment of Cancer Quality of Life Core Questionnaire (EORTC QLQ-C30) measures 15 health-related quality of life (HRQoL) scales relevant to the disease and treatment of patients with cancer. A study by Martinelli (2011) demonstrated that these scales could be grouped into three main clusters: physical, psychological and gastrointestinal. This study aims to validate Martinelli's findings in an independent dataset and evaluate whether these clusters are consistent across cancer types and patient characteristics. Methods: Pre-defined criteria for successful validation were three main clusters should emerge with a minimum R-squared value of 0.51 using pooled baseline-data. A cluster analysis was performed on the 15 QLQ-C30 HRQoL-scales in the overall dataset, as well as by cancer type and selected patient characteristics to examine the robustness of the results. Results: The dataset consisted of 20,066 patients pooled across 17 cancer types. Overall, three main clusters were identified (R-2 = 0.61); physical-cluster included role-functioning, physical functioning, social-functioning, fatigue, pain, and global-health status; psychological-cluster included emotional-functioning, cognitive-functioning, and insomnia; gastro-intestinal-cluster included nausea/vomiting and appetite loss. The results were consistent across different levels of disease severity, socio-demographic and clinical characteristics with minor variations by cancer type. Global-health status was found to be strongly linked to the scales included in the physical-functioning-related cluster. Conclusion: This study successfully validated prior findings by Martinelli (2011): the QLQC30 scales are interrelated and can be grouped into three main clusters. Knowing how these multidimensional HRQoL scales are related to each other can help clinicians and patients with cancer in managing symptom burden, guide policymakers in defining social-support plans and inform selection of HRQoL scales in future clinical trials. (C)2022 Elsevier Ltd. All rights reserved. Show less
Coens, C.; Pe, M.; Dueck, A.C.; Sloan, J.; Basch, E.; Calvert, M.; ... ; Setting Int Stand Analyzing Patien 2020
Patient-reported outcomes (PROs), such as symptoms, function, and other health-related quality-of-life aspects, are increasingly evaluated in cancer randomised controlled trials (RCTs) to provide... Show morePatient-reported outcomes (PROs), such as symptoms, function, and other health-related quality-of-life aspects, are increasingly evaluated in cancer randomised controlled trials (RCTs) to provide information about treatment risks, benefits, and tolerability. However, expert opinion and critical review of the literature showed no consensus on optimal methods of PRO analysis in cancer RCTs, hindering interpretation of results. The Setting International Standards in Analyzing Patient-Reported Outcomes and Quality of Life Endpoints Data Consortium was formed to establish PRO analysis recommendations. Four issues were prioritised: developing a taxonomy of research objectives that can be matched with appropriate statistical methods, identifying appropriate statistical methods for PRO analysis, standardising statistical terminology related to missing data, and determining appropriate ways to manage missing data. This Policy Review presents recommendations for PRO analysis developed through critical literature reviews and a structured collaborative process with diverse international stakeholders, which provides a foundation for endorsement; ongoing developments of these recommendations are also discussed. Show less
Bottomley, A.; Reijneveld, J.C.; Koller, M.; Flechtner, H.; Tomaszewski, K.A.; Greimel, E.; ... ; 5th EORTC Quality Life Canc 2019