John Maringwa

Patient Self-Reports of Symptoms and Clinician Ratings as Predictors of Overall Cancer Survival

BACKGROUND The National Cancer Institutes Common Terminology Criteria for Adverse Events (NCI-CTCAE) reporting system is widely used by clinicians to measure patient symptoms in clinical trials. The European Organization for Research and Treatment of Cancers Quality of Life core questionnaire (EORTC QLQ-C30) enables cancer patients to rate their symptoms related to their quality of life. We examined the extent to which patient and clinician symptom scoring and their agreement could contribute to the estimation of overall survival among cancer patients. METHODS We analyzed baseline data regarding six cancer symptoms (pain, fatigue, vomiting, nausea, diarrhea, and constipation) from a total of 2279 cancer patients from 14 closed EORTC randomized controlled trials. In each trial that was selected for retrospective pooled analysis, both clinician and patient symptom scoring were reported simultaneously at study entry. We assessed the extent of agreement between clinician vs patient symptom scoring using the Spearman and kappa correlation statistics. After adjusting for age, sex, performance status, cancer severity, and cancer site, we used Harrell concordance index (C-index) to compare the potential for clinician-reported and/or patient-reported symptom scores to improve the accuracy of Cox models to predict overall survival. All P values are from two-sided tests. RESULTS Patient-reported scores for some symptoms, particularly fatigue, did differ from clinician-reported scores. For each of the six symptoms that we assessed at baseline, both clinician and patient scorings contributed independently and positively to the predictive accuracy of survival prognostication. Cox models of overall survival that considered both patient and clinician scores gained more predictive accuracy than models that considered clinician scores alone for each of four symptoms: fatigue (C-index = .67 with both patient and clinician data vs C-index = .63 with clinician data only; P <.001), vomiting (C-index = .64 vs .62; P = .01), nausea (C-index = .65 vs .62; P < .001), and constipation (C-index = .62 vs .61; P = .01). CONCLUSION Patients provide a subjective measure of symptom severity that complements clinician scoring in predicting overall survival.

A global analysis of multitrial data investigating quality of life and symptoms as prognostic factors for survival in different tumor sites.

The objective of this study was to examine the prognostic value of baseline health‐related quality of life (HRQOL) for survival with regard to different cancer sites using 1 standardized and validated patient self‐assessment tool.

Minimal clinically meaningful differences for the EORTC QLQ-C30 and EORTC QLQ-BN20 scales in brain cancer patients

BACKGROUND We aimed to determine the smallest changes in health-related quality of life (HRQoL) scores in the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire core 30 and the Brain Cancer Module (QLQ-BN20), which could be considered as clinically meaningful in brain cancer patients. MATERIALS AND METHODS World Health Organisation performance status (PS) and mini-mental state examination (MMSE) were used as clinical anchors appropriate to related subscales to determine the minimal clinically important differences (MCIDs) in HRQoL change scores (range 0-100) in the QLQ-C30 and QLQ-BN20. A threshold of 0.2 standard deviation (SD) (small effect) was used to exclude anchor-based MCID estimates considered too small to inform interpretation. RESULTS Based on PS, our findings support the following integer estimates of the MCID for improvement and deterioration, respectively: physical (6, 9), role (14, 12), and cognitive functioning (8, 8); global health status (7, 4*), fatigue (12, 9), and motor dysfunction (4*, 5). Anchoring with MMSE, cognitive functioning MCID estimates for improvement and deterioration were (11, 2*) and for communication deficit were (9, 7). Estimates with asterisks were <0.2 SD and were excluded from our MCID range of 5-14. CONCLUSION These estimates can help clinicians evaluate changes in HRQoL over time, assess the value of a health care intervention and can be useful in determining sample sizes in designing future clinical trials.

Minimal important differences for interpreting health-related quality of life scores from the EORTC QLQ-C30 in lung cancer patients participating in randomized controlled trials

BackgroundThe aim of this study was to determine the smallest changes in health-related quality of life (HRQOL) scores in a subset of the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire core 30 (EORTC QLQ-C30) scales, which could be considered as clinically meaningful in patients with non-small-cell lung cancer (NSCLC).MethodsWHO performance status (PS) and weight change were used as clinical anchors to determine minimal important differences (MIDs) in HRQOL change scores (range, 0–100) in the EORTC QLQ-C30 scales. Selected distribution-based methods were used for comparison.FindingsIn a pooled dataset of 812 NSCLC patients undergoing treatment, the values determined to represent the MID depended on whether patients were improving or deteriorating. MID estimates for improvement (based on a one-category change in PS, 5 − <20% weight gain) were physical functioning (9, 5); role functioning (14, 7); social functioning (5, 7); global health status (9, 4); fatigue (14, 5); and pain (16, 2). The respective MID estimates for deterioration (based on PS, weight loss) were physical (4, 6); role (5, 5); social (7, 9); global health status (4, 4); fatigue (6, 11); and pain (3, 7).InterpretationBased on the selected QLQ-C30 scales, the MID may depend upon whether the patients’ PS is improving or worsening, but our results are not definitive. The MID estimates for the specified scales can help clinicians and researchers evaluate the significance of changes in HRQOL and assess the value of a health care intervention or compare treatments. The estimates also can be useful in determining sample sizes in the design of future clinical trials.

Examining the relationships among health-related quality-of-life indicators in cancer patients participating in clinical trials: a pooled study of baseline EORTC QLQ-C30 data.

Aims: Cancer patients experience multiple and concurrent health-related problems and symptoms due to their illness and therapies. The first objective of this analysis was to identify how health-related quality-of-life (HRQoL) indicators cluster among cancer patients and how possible clusters change across patients with different sociodemographic and clinical characteristics. The second objective of this study was to identify which HRQoL indicators are linked to patients’ perception of overall quality of life. Methods: Retrospective pooling of 30 closed randomized European Organisation for Research and Treatment of Cancer (EORTC) clinical trials yielded baseline EORTC Quality of Life Core Questionnaire (QLQ-C30) HRQoL data for a total of 7417 patients. A cluster analysis was performed to determine how the 15 HRQoL indicators obtained with the QLQ-C30 cluster overall and by patient characteristics. Results: Three main clusters emerged from the overall dataset: a physical cluster, a psychological cluster and a gastrointestinal cluster. The same clusters were found in subgroups defined according to sociodemographic and clinical characteristics, while some differences emerged among cancer sites. The Global Health scale was found to be part of the physical cluster in the overall dataset. This result was consistent across different levels of disease severity, while divergent results were seen across some cancer sites. Conclusion: Our findings suggest that HRQoL indicators are interrelated. Understanding these relationships may aid clinicians in managing the symptom burden experienced by patients, as well as policy-makers, in defining psychosocial support plans.

Establishing anchor-based minimally important differences (MID) with the EORTC quality-of-life measures: a meta-analysis protocol

Introduction As patient assessment of health-related quality of life (HRQOL) in cancer clinical trials has increased over the years, so has the need to attach meaningful interpretations to differences in HRQOL scores between groups and changes within groups. Determining what represents a minimally important difference (MID) in HRQOL scores is useful to clinicians, patients and researchers, and can be used as a benchmark for assessing the success of a healthcare intervention. Our objective is to provide an evidence-based protocol to determine MIDs for the European Organisation for Research and Treatment for Cancer Quality of life Questionnaire core 30 (EORTC QLQ-C30). We will mainly focus on MID estimation for group-level comparisons. Responder thresholds for individual-level change will also be estimated. Methods and analysis Data will be derived from published phase II and III EORTC trials that used the QLQ-C30 instrument, covering several cancer sites. We will use individual patient data to estimate MIDs for different cancer sites separately. Focus is on anchor-based methods. Anchors will be selected per disease site from available data. A disease-oriented and methodological panel will provide independent guidance on anchor selection. We aim to construct multiple clinical anchors per QLQ-C30 scale and also to compare with several anchor-based methods. The effects of covariates, for example, gender, age, disease stage and so on, will also be investigated. We will examine how our estimated MIDs compare with previously published guidelines, hence further contributing to robust MID guidelines for the EORTC QLQ-C30. Ethics and dissemination All patient data originate from completed clinical trials with mandatory written informed consent, approved by local ethical committees. Our findings will be presented at scientific conferences, disseminated via peer-reviewed publications and also compiled in a MID ‘blue book’ which will be made available online on the EORTC Quality of Life Group website as a free guideline document.