Dataset Information

Minimal important differences of EORTC QLQ-C30 for metastatic breast cancer patients: Results from a randomized clinical trial.

ABSTRACT:

Purpose

To establish minimal important differences (MIDs) for the European Organisation for Research and Treatment for Cancer Quality of life Questionnaire core 30 (EORTC QLQ-C30) in patients with metastatic breast cancer.

Methods

The dataset was obtained from the SELECT BC-CONFIRM randomized clinical trial. Anchors obtained from patients (transition items) and clinicians (performance status) were used for anchor-based methods. Anchors obtained through 6 months after starting treatment were used for this analysis. Correlation coefficients of anchor and change in QLQ-C30 and effect size were used to qualify for estimating MIDs. Mean change method and generalized estimating equation were applied to estimate MIDs. Distribution-based methods were used for comparison.

Results

We analyzed a dataset of 154 metastatic breast cancer patients. MIDs were estimated in 8 of 15 scales of QLQ-C30. Estimated MIDs for within-group improvement varied from 7 to 15 and those for deterioration varied from - 7 to - 17. Estimated MIDs for between-group improvement varied from 5 to 11 and those for deterioration varied from - 5 to - 8 across QLQ-C30 scales. Patient-reported anchors were more susceptible to early changes in health status than clinician-reported anchors.

Conclusion

We provided the MIDs of the QLQ-C30 using both patient- and clinicians-reported anchors measured in a randomized trial of Japanese patients with metastatic breast cancer. We recommend patient-reported anchors for anchor-based estimation of MID. Our results can aid patients and clinicians, as well as researchers, in the interpretation of QLQ-C30.

SUBMITTER: Kawahara T

PROVIDER: S-EPMC9098551 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Publications

Minimal important differences of EORTC QLQ-C30 for metastatic breast cancer patients: Results from a randomized clinical trial.

Kawahara Takuya T Taira Naruto N Shiroiwa Takeru T Hagiwara Yasuhiro Y Fukuda Takashi T Uemura Yukari Y Mukai Hirofumi H

Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation 20220104 6

<h4>Purpose</h4>To establish minimal important differences (MIDs) for the European Organisation for Research and Treatment for Cancer Quality of life Questionnaire core 30 (EORTC QLQ-C30) in patients with metastatic breast cancer.<h4>Methods</h4>The dataset was obtained from the SELECT BC-CONFIRM randomized clinical trial. Anchors obtained from patients (transition items) and clinicians (performance status) were used for anchor-based methods. Anchors obtained through 6 months after starting trea ...[more]

PMID: 34982354

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Project description:IntroductionWhen determining if changes on patient-reported outcome (PRO) scores in clinical trials convey a meaningful treatment benefit, statistical significance tests alone may not communicate the patient perspective. Appraising within-patient changes on PRO scores against established thresholds can determine if improvements or deteriorations experienced by individuals are meaningful. To evaluate the appropriateness of thresholds for interpreting meaningful improvements and deterioration within individuals on the European Organisation for Research and Treatment of Cancer (EORTC) 30-item core instrument (QLQ-C30) and 13-item lung cancer module (QLQ-LC13), a series of psychometric methods were applied to data from a phase III randomized controlled clinical trial in non-small cell lung cancer.MethodsAnchor-based methods of empirical cumulative distribution functions and classification statistics were employed using change scores from Baseline to Week 7 using changes on the QLQ-C30 Global Health Status item as an anchor. Distribution-based methods of one-half standard deviation and standard error of measurement identified the minimum amount of change each domain score can reliably measure.ResultsWhile the correlations between the domain scores and the anchor item were modest in size (i.e., r ≥ 0.30 for only 5 of 24 domains), consideration of multiple methods along with the magnitude of possible step changes on the score allowed for patterns to emerge. The triangulation process planned a priori resulted in different methods being the source for different domain scores. Absolute values of the proposed thresholds ranged from 11.11 to 33.33, and all resulted in the same classifications for all EORTC domains, except QLQ-C30 Fatigue, as would the 10-point threshold that is traditionally used.ConclusionThis study confirms the appropriateness of the 10-point EORTC score threshold generally used by the field for interpreting within-patient changes, but the thresholds proposed from this study enhance interpretability by corresponding to only observable locations along the domain score scale.

Project description:BackgroundThe minimal important difference (MID) is a useful tool to interpret changes in patients' health-related quality of life. This study aims to estimate MIDs for interpreting within-patient change for both components of the EQ-5D-5L questionnaire [EQ-Visual Analogue Scale (EQ-VAS) and utility index] and domains of the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30) for cancer patients.MethodsData were obtained from the Cancer 2015 dataset, a longitudinal cohort of Australian cancer patients. Anchor-based approaches were used to estimate MIDs for the EQ-5D-5L index-based utility index [Australia and the United States (US) tariff sets], EQ-VAS scores, and the EORTC QLQ-C30. Clinical [Eastern Cooperative Oncology Group (ECOG) performance status] and patient-reported (items 29 and 30 of the EORTC QLQ-C30 and the EQ-VAS) anchors were assessed for appropriateness by their correlation strength. Clinical change groups (CCGs) were defined a priori for improvement and deterioration based on estimates used in previous literature. MIDs were estimated via linear regression and distribution-based methods.ResultsFor the index-based utility scores in Australia, the anchor-defined MID estimates were 0.01 to 0.06 for improvement and - 0.04 to -0.03 for deterioration, with a weighted value of 0.03 for improvement and deterioration. The EQ-VAS MID estimate was 5 points for both improvement and deterioration. For the EORTC QLQ-C30, changes of at least 3.64 (improvement) and - 4.28 (deterioration) units on the physical functioning scale, 6.31 (improvement) and - 7.11 (deterioration) units on the role functioning scale, 4.65 (improvement) and - 3.41 (deterioration) units on the emotional functioning scale, and 5.41 (improvement) and - 5.56 (deterioration) units on the social functioning scale were estimated to be meaningful.ConclusionThis study identified lower MIDs for the EQ-5D-5L utility index, EQ-VAS, and EORTC QLQ-C30 domain scores, than those reported previously. The use of a real-world cancer-specific panel dataset may reflect smaller MID estimates that are more applicable to cancer patients in the clinical practice, rather than using MIDs that have been estimated from clinical trials.

Project description:BackgroundThe types of outcomes measured collected in clinical studies and those required for cost-effectiveness analysis often differ. Decision makers routinely use quality adjusted life years (QALYs) to compare the benefits and costs of treatments across different diseases and treatments using a common metric. QALYs can be calculated using preference-based measures (PBMs) such as EQ-5D-3L, but clinical studies often focus on objective clinician or laboratory measured outcomes and non-preference-based patient outcomes, such as QLQ-C30. We model the relationship between the generic, preference-based EQ-5D-3L and the cancer specific quality of life questionnaire, QLQ-C30 in patients with breast cancer. This will result in a mapping that allows users to convert QLQ-C30 scores into EQ-5D-3L scores for the purposes of cost-effectiveness analysis or economic evaluation.MethodsWe use data from a randomized trial of 602 patients with HER2-positive advanced breast cancer provided 3766 EQ-5D-3L observations. Direct mapping using adjusted, limited dependent variable mixture models (ALDVMM) is compared to a random effects linear regression and indirect mapping using seemingly unrelated ordered probit models. EQ-5D-3L was estimated as a function of the summary scales of the QLQ-C30 and other patient characteristics.ResultsA four component mixture model outperformed other models in terms of summary fit statistics. A close fit to the observed data was observed across the range of disease severity. Simulated data from the model closely aligned to the original data and showed that mapping did not significantly underestimate uncertainty. In the simulated data, 22.15% were equal to 1 compared to 21.93% in the original data. Variance was 0.0628 in the simulated data versus 0.0693 in the original data. The preferred mapping is provided in Excel and Stata files for the ease of users.ConclusionA four component adjusted mixture model provides reliable, non-biased estimates of EQ-5D-3L from the QLQ-C30, to link clinical studies to economic evaluation of health technologies for breast cancer. This work adds to a growing body of literature demonstrating the appropriateness of mixture model based approaches in mapping.

Project description:BackgroundThe European Organization for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire Core 30 Physical Functioning subscale is a widely used patient-reported outcome measure that quantifies cancer patients' physical functioning. Strong floor/ceiling effects can affect a scale's sensitivity to change. The aim of this study was to characterize floor/ceiling effects of the physical functioning domain in patients with advanced/metastatic breast cancer enrolled in commercial clinical trials and a community-based trial.MethodsThe clinical trial cohort comprised patients from 5 registrational trials submitted to the Food and Drug Administration for review (2010-2017). The community cohort comprised a subgroup of patients from the Alliance Patient Reported Outcomes to Enhance Cancer Treatment (PRO-TECT) trial. The distribution of patient responses to Physical Functioning items and the summed score were assessed at the baseline and 3-month follow-up for both cohorts. Descriptive statistics were used to determine floor/ceiling effects at the item and scale levels.ResultsThe clinical trial cohort and the community cohort consisted of 2407 and 178 patients, respectively. Twenty-four percent or more of the respondents reported "not at all" for having trouble/needing help with each Physical Functioning item across both cohorts and measurement time points. Fourteen to twenty percent of the patients scored perfectly (100 of 100) on the Physical Functioning subscale summary measure (where higher scores indicated better physical functioning) across both cohorts and time points.ConclusionsMinor floor effects and notable ceiling effects were found at the item and scale levels of the Physical Functioning subscale, regardless of cohort, and this creates some uncertainty about its ability to detect changes in physical functioning among high-functioning patients. Investigators may consider adding additional high-functioning items from the EORTC's item library to more accurately describe the impact of anticancer treatment on patients' physical functioning.

Project description:BackgroundIn oncology, health-related quality of life (HRQoL) data are often collected using disease-specific patient questionnaires while generic, patient-level utility data required for health economic modeling are often not collected.MethodsWe developed a mapping algorithm for multiple myeloma that relates HRQoL scores from the European Organization for Research and Treatment of Cancer (EORTC) questionnaires QLQ-C30 and QLQ-MY20 to a utility value from the European QoL-5 Dimensions (EQ-5D) questionnaire. Data were obtained from 154 multiple myeloma patients who had participated in a multicenter cohort study in the UK or Germany. All three questionnaires were administered at a single time point. Scores from all 19 domains of the QLQ-C30 and QLQ-MY20 instruments were univariately tested against EQ-5D values and retained in a multivariate regression model if statistically significant. A 10-fold cross-validation model selection method was also used as an alternative testing means. Two models were developed: one based on QLQ-C30 plus QLQ-MY20 scores and one based on QLQ-C30 scores alone. Adjusted R-squared, correlation coefficients, and plots of observed versus predicted EQ-5D values were presented for both models.ResultsMapping revealed that Global Health Status/QoL, Physical Functioning, Pain, and Insomnia were significant predictors of EQ-5D utility values. Similar results were observed when QLQ-MY20 scores were excluded from the model, except that Emotional Functioning and became a significant predictor and Insomnia was no longer a significant predictor. Adjusted R-squared values were of similar magnitude with or without inclusion of QLQ-MY20 scores (0.70 and 0.69, respectively), suggesting that the EORTC QLQ-MY20 adds little in terms of predicting utility values in multiple myeloma.ConclusionsThis algorithm successfully mapped EORTC HRQoL data onto EQ-5D utility in patients with multiple myeloma. Current mapping will aid in the analysis of cost-effectiveness of novel therapies for this indication.

Dataset Information

Minimal important differences of EORTC QLQ-C30 for metastatic breast cancer patients: Results from a randomized clinical trial.

Purpose

Methods

Results

Conclusion

Publications

Minimal important differences of EORTC QLQ-C30 for metastatic breast cancer patients: Results from a randomized clinical trial.

Similar Datasets

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