European Organisation for Research and Treatment of Cancer
Citations 7
Establishing the content validity of patient-reported outcome measures used in neuro-oncology based on the WHO ICF framework: Part of the RANO-PRO initiative
Abstract Background Instruments to assess patient-reported outcomes (PRO) should generate high-quality evidence. Reliable PRO evidence is essential to policymakers, in conjunction with outcomes such as survival and radiological response, to understand the net clinical benefit of antitumor treatments. This study aimed to establish the content validity of 215 identified PRO measures used in patients with brain tumors. Methods A survey (n = 148 items) was developed reflecting aspects of the WHO International Classification of Functioning, Disability, and Health (ICF) framework. Patients with brain tumors, their proxies, and healthcare professionals (HCPs) were asked to rate each survey item on relevance. An item was considered a relevant issue if ≥25% of the patients or proxies or ≥50% of the HCPs considered that item to be an issue. Next, all items in the identified PRO measures were linked to ICF and relevant items in the survey, and the percentage of content coverage was calculated. Results In total, 114 patients, 71 proxies, and 65 HCPs from different countries completed the survey. Fifty-six of 148 (37.8%) items in the survey were considered relevant. The most important aspects mentioned by both patients and proxies were difficulty concentrating, difficulty remembering, multitasking, and handling stress. Depending on the definition, between 35% and 49% of PRO measures were considered to have sufficient content validity (≥80% coverage). Conclusion The content validity was insufficient in more than half of the identified PRO measures, particularly multidimensional measures. Future research should investigate whether different approaches to PRO assessment better meet the needs of all stakeholders.
Quality of Life in Male Breast Cancer: Prospective Study of the International Male Breast Cancer Program (EORTC10085/TBCRC029/BIG2-07/NABCG)
Abstract Introduction Prospective data about quality of life (QoL) in men with breast cancer (BC) are lacking. A prospective registry (EORTC10085) of men with all BC stages, including a QoL correlative study, was performed as part of the International Male Breast Cancer Program. Methods Questionnaires at BC diagnosis included the EORTC QLQ-C30 and BR23 (BC specific module), adapted for men. High functioning and global health/QoL scores indicate high functioning levels/high QoL; high symptom-focused measures scores indicate high symptoms/problems levels. EORTC reference data for healthy men and women with BC were used for comparisons. Results Of 422 men consenting to participate, 363 were evaluable. Median age was 67 years, and median time between diagnosis and survey was 1.1 months. A total of 114 men (45%) had node-positive early disease, and 28 (8%) had advanced disease. Baseline mean global health status score was 73 (SD: 21), better than in female BC reference data (62, SD: 25). Common symptoms in male BC were fatigue (22, SD: 24), insomnia (21, SD: 28), and pain (16, SD: 23), for which women’s mean scores indicated more burdensome symptoms at 33 (SD: 26), 30 (SD: 32), and 29 (SD: 29). Men’s mean sexual activity score was 31 (SD: 26), with less sexual activity in older patients or advanced disease. Conclusions QoL and symptom burden in male BC patients appears no worse (and possibly better) than that in female patients. Future analyses on impact of treatment on symptoms and QoL over time, may support tailoring of male BC management.
Systematic review on the use of patient-reported outcome measures in brain tumor studies: part of the Response Assessment in Neuro-Oncology Patient-Reported Outcome (RANO-PRO) initiative
Abstract Background The Response Assessment in Neuro-Oncology Patient-Reported Outcome (RANO-PRO) working group aims to provide guidance on the use of PROs in brain tumor patients. PRO measures should be of high quality, both in terms of relevance and other measurement properties. This systematic review aimed to identify PRO measures that have been used in brain tumor studies to date. Methods A systematic literature search for articles published up to June 25, 2020 was conducted in several electronic databases. Pre-specified inclusion criteria were used to identify studies using PRO measures assessing symptoms, (instrumental) activities of daily living [(I)ADL] or health-related quality of life (HRQoL) in adult patients with glioma, meningioma, primary central nervous system lymphoma, or brain metastasis. Results A total of 215 different PRO measures were identified in 571 published and 194 unpublished studies. The identified PRO measures include brain tumor-specific, cancer-specific, and generic instruments, as well as instruments designed for other indications or multi- or single-item study-specific questionnaires. The most frequently used instruments were the EORTC QLQ-C30 and QLQ-BN20 (n = 286 and n = 247), and the FACT-Br (n = 167), however, the majority of the instruments were used only once or twice (150/215). Conclusion Many different PRO measures assessing symptoms, (I)ADL or HRQoL have been used in brain tumor studies to date. Future research should clarify whether these instruments or their scales/items exhibit good content validity and other measurement properties for use in brain tumor patients.
Calculating the net clinical benefit in neuro-oncology clinical trials using two methods: quality-adjusted survival effect sizes and joint modeling
Abstract Background Two methods combining survival and health-related quality of life (HRQoL) data in glioma trials to calculate the “net clinical benefit” were evaluated: Quality-adjusted effect sizes (QASES) and joint modeling (JM). Methods The net clinical benefit in two trials was calculated as proof of concept for other trials. With the QASES method, effect sizes for differences in progression-free survival (PFS) or overall survival (OS) and HRQoL between the experimental arm and standard treatment arm were calculated, while the relative emphasis placed on survival/HRQoL varied. JM allows simultaneous modeling of HRQoL and OS/PFS. Results In the EORTC 26951 trial, combined radiochemotherapy significantly prolonged OS (difference 11.7 months), but also resulted in more patients experiencing clinically relevant worsening (≥10 points) in appetite loss and nausea/vomiting shortly after treatment. Using QASES, the survival benefit of additional procarbazine, lomustine, and vincristine (PCV) decreased from 42.3 months to 29.5 and 28.2 months when accounting for appetite loss and nausea/vomiting, respectively. JM analyses resulted in a loss of the beneficial effect of additional PCV between 13% and 24% when adjusting for different HRQoL parameters. The EORTC 22033 trial showed no significant PFS difference between radiotherapy or temozolomide alone (46 vs 39 months), nor clinically relevant differences in HRQoL. JM analyses also showed no significant association between PFS and HRQoL scales/items, whereas QASES showed that temozolomide alone was more favorable when considering symptom burden (47–49 instead of 39 months). Conclusions Both methods resulted in different outcomes, but adjusting for the impact of treatment on HRQoL resulted in theoretically reduced survival benefits.
QOLP-04. CALCULATING THE NET CLINICAL BENEFIT IN BRAIN TUMOR TRIALS BY COMBINING SURVIVAL AND HEALTH-RELATED QUALITY OF LIFE DATA USING TWO METHODS: QUALITY ADJUSTED SURVIVAL EFFECT SIZES AND JOINT MODELLING
Abstract INTRODUCTION The impact of treatment on both the quality and the quantity of life, i.e. the ‘net clinical benefit’, should be considered to facilitate shared decision making. Two methods that combine survival and health-related quality of life (HRQoL) data: Quality Adjusted Effect Sizes (QASES) and Joint Modelling (JM) were applied to gain insight in the net clinical benefit. METHODS The net clinical benefit in one RCT (EORTC 26951 comparing radiotherapy (RT) + PCV chemotherapy versus RT alone) was calculated as a proof of concept for other trials. With the QASES method, effect sizes for differences in survival and HRQoL between treatment arms were calculated. JM allows simultaneous modeling of a longitudinal outcome (HRQoL), and a time-to event outcome (survival). HRQoL scales/items that were selected for primary analysis in the main study were also selected for this analysis: fatigue, global health, social functioning, communication deficit, seizures, physical functioning, and nausea/vomiting. RESULTS 288/386 patients completed baseline HRQoL forms and were included in the analysis. Overall survival (OS) was significantly longer with combined treatment (42.3 vs. 30.6 months). The percentage of patients who experienced a clinically relevant deterioration (≥10 points) in nausea/vomiting, fatigue, social functioning and global health up to one year after treatment compared to baseline was larger in the RT+PCV arm. QASES corresponded to a reduction in the median OS difference from 9.7 months up till 5.5 months, given equal weights to OS and HRQoL. JM analyses resulted in a theoretical loss of treatment effect in OS of 2–6% when adjusting for HRQoL. CONCLUSION Both methods showed that adjusting for the impact of treatment on a relevant HRQoL parameter reduced the survival benefit in the experimental treatment arm compared to standard treatment arm. Applying these methods may facilitate communicating the impact of treatment to patients in clinical practice.
OS7.4 Calculating the net clinical benefit in brain tumor clinical trials by combining survival and health-related quality of life data using two methods: quality adjusted survival effect sizes (QASES) and joint modelling (JM)
Abstract BACKGROUND The impact of treatment on both the quality and the quantity of life, i.e. the ‘net clinical benefit’, should be considered to inform glioma patients and facilitate shared decision making. We applied two methods (i.e. Quality Adjusted Effect Sizes (QASES) and Joint Modelling (JM)) that combine survival and health-related quality of life (HRQoL) data into one outcome, to gain insight in the net clinical benefit of a treatment strategy. In addition, we assessed if both methods result in similar interpretations. MATERIAL AND METHODS We calculated the net clinical benefit in one randomized controlled trial, EORTC 26951 comparing radiotherapy (RT) + PCV chemotherapy versus RT alone, as a proof of concept for other trials. With the QASES method, effect sizes for differences in survival and HRQoL between treatment arms were calculated. Next, the combined effect size can be determined by weighing the emphasis put on survival or HRQoL (e.g. survival more important). JM allows simultaneous modeling of a longitudinal outcome (HRQoL), and a time-to event outcome (survival). HRQoL scales/items that were selected for primary analysis in the main study were also selected for this analysis: fatigue, global health, social functioning, communication deficit, seizures, physical functioning, and nausea/vomiting. RESULTS 288/386 patients completed baseline HRQoL forms and were included in the analysis. Overall survival (OS) was significantly longer with combined treatment (difference of 10.8 months). In contrast, the percentage of patients who experienced a clinically relevant deterioration (≥10 points) in nausea/vomiting, fatigue, social functioning and global health up to one year after treatment compared to baseline was larger in the RT+PCV arm. The QASES corresponded to a reduction in the median OS difference from 10.8 months to 6.8 months when adjusted for the HRQoL scales/items, when given equal weights to OS and HRQoL. JM analyses resulted in a theoretical loss of treatment effect in OS of 2–6% when adjusting for HRQoL. CONCLUSION Both methods showed that adjusting for the impact of treatment on a relevant HRQoL parameter reduced the survival benefit in the experimental treatment arm compared to standard treatment arm. Applying these methods may facilitate communicating the impact of treatment to patients in clinical practice.
Moving forward toward standardizing analysis of quality of life data in randomized cancer clinical trials
Background There is currently a lack of consensus on how health-related quality of life and other patient-reported outcome measures in cancer randomized clinical trials are analyzed and interpreted. This makes it difficult to compare results across randomized controlled trials (RCTs) synthesize scientific research, and use that evidence to inform product labeling, clinical guidelines, and health policy. The Setting International Standards in Analyzing Patient-Reported Outcomes and Quality of Life Endpoints Data for Cancer Clinical Trials (SISAQOL) Consortium aims to develop guidelines and recommendations to standardize analyses of patient-reported outcome data in cancer RCTs. Methods and Results Members from the SISAQOL Consortium met in January 2017 to discuss relevant issues. Data from systematic reviews of the current state of published research in patient-reported outcomes in cancer RCTs indicated a lack of clear reporting of research hypothesis and analytic strategies, and inconsistency in definitions of terms, including “missing data,”“health-related quality of life,” and “patient-reported outcome.” Based on the meeting proceedings, the Consortium will focus on three key priorities in the coming year: developing a taxonomy of research objectives, identifying appropriate statistical methods to analyze patient-reported outcome data, and determining best practices to evaluate and deal with missing data. Conclusion The quality of the Consortium guidelines and recommendations are informed and enhanced by the broad Consortium membership which includes regulators, patients, clinicians, and academics.