Dataset Information

Estimating Minimally Important Differences for the Bladder Cancer Index Using Distribution and Anchor Based Approaches.

ABSTRACT:

Purpose

The BCI (Bladder Cancer Index) is a validated, condition specific health questionnaire assessing urinary, bowel and sexual function and quality of life among patients with bladder cancer. We aimed to establish minimally important difference score thresholds that signal clinical importance.

Materials and methods

For 1 year after surgery we followed a prospective cohort of 150 patients who underwent radical cystectomy between 2013 and 2016. Usable data on 138 patients were analyzed. The BCI and the Medical Outcomes Study SF-36 (36-Item Short Form Health Survey) questionnaires were completed prior to cystectomy, and 3, 6 and 12 months postoperatively. Distribution based, minimally important differences were estimated at ⅓ and ½ SD for each index domain across time points. Changes in index domain scores anchored to changes in a SF-36 overall health assessment question were used to estimate anchor based, minimally important differences. Pooled averages are reported between time points and methods.

Results

The distribution based, minimally important difference of ⅓ SDs for urinary, bowel and sexual domains ranged between 5.3 and 7.3, 4.6 and 5.6, and 6.0 and 8.9 points, respectively. Ranges of ½ SDs were 8.8 and 10.9, 6.8 and 8.4, and 8.9 and 13.5 points, respectively. The anchor based approach resulted in minimally important difference estimates of 6.2, 7.3 and 6.8 points, respectively. Aggregated results across the 2 approaches resulted in minimally important differences of 6 to 9, 5 to 8 and 7 to 11 points for urinary, bowel and sexual domains, respectively.

Conclusions

Using 2 independent approaches to our knowledge we established the first minimally important difference estimates for the BCI. Defining patient reported outcome thresholds is important to interpret changes or differences in BCI scores.

SUBMITTER: Peyton CC

PROVIDER: S-EPMC7811779 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Publications

Estimating Minimally Important Differences for the Bladder Cancer Index Using Distribution and Anchor Based Approaches.

Peyton Charles C CC Henriksen Carl C Reich Richard R RR Azizi Mounsif M Gilbert Scott M SM

The Journal of urology 20190401 4

<h4>Purpose</h4>The BCI (Bladder Cancer Index) is a validated, condition specific health questionnaire assessing urinary, bowel and sexual function and quality of life among patients with bladder cancer. We aimed to establish minimally important difference score thresholds that signal clinical importance.<h4>Materials and methods</h4>For 1 year after surgery we followed a prospective cohort of 150 patients who underwent radical cystectomy between 2013 and 2016. Usable data on 138 patients were a ...[more]

PMID: 30342063

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Project description:IntroductionAs 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 analysisData 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 disseminationAll 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.

Project description:BackgroundInterpretation of differences or changes in patient-reported outcome scores should not only consider statistical significance, but also clinical relevance. Accordingly, accurate determination of the minimally important difference (MID) is crucial to assess the effectiveness of health care interventions, as well as for sample size calculation. Several methods have been proposed to determine the MID. Our aim was to review the statistical methods used to determine MID in patient-reported outcome (PRO) questionnaires in cancer patients, focusing on the distribution- and anchor-based approaches and to present the variability of criteria used as well as possible limitations.MethodsWe performed a systematic search using PubMed. We searched for all cancer studies related to MID determination on a PRO questionnaire. Two reviewers independently screened titles and abstracts to identify relevant articles. Data were extracted from eligible articles using a predefined data collection form. Discrepancies were resolved by discussion and the involvement of a third reviewer.ResultsSixty-three articles were identified, of which 46 were retained for final analysis. Both distribution- and anchor-based approaches were used to assess the MID in 37 studies (80.4%). Different time points were used to apply the distribution-based method and the most frequently reported distribution was the 0.5 standard deviation at baseline. A change in a PRO external scale (N = 13, 30.2%) and performance status (N = 15, 34.9%) were the most frequently used anchors. The stability of the MID over time was rarely investigated and only 28.2% of studies used at least 3 assessment timepoints. The robustness of anchor-based MID was questionable in 37.2% of the studies where the minimal number of patients by anchor category was less than 20.ConclusionEfforts are needed to improve the quality of the methodology used for MID determination in PRO questionnaires used in oncology. In particular, increased attention to the sample size should be paid to guarantee reliable results. This could increase the use of these specific thresholds in future studies.

Project description:BackgroundIn network meta-analysis (NMA), the magnitude of difference between treatment effects is typically ignored in the calculation of ranking metrics, such as probability best and surface under the cumulative ranking curve (SUCRAs). This leads to treatment rankings which may not reflect clinically meaningful differences. Minimally important differences (MIDs) represent the smallest value in a given outcome that is considered by patients or clinicians to represent a meaningful difference between treatments. There is a lack of literature on how MIDs can be incorporated into common NMA ranking metrics such as SUCRAs to give more clinically oriented treatment rankings.MethodsAnalogues to commonly available NMA ranking metrics that account for minimally important differences (MIDs) are provided. In particular, definitions are provided for MID-adjusted median ranks, MID-adjusted probability j th best, MID-adjusted cumulative probability j th best, and MID-adjusted SUCRA values. Since adjustment for MIDs allows for ties between treatments in a network, methods for handling ties in ranking are discussed, with it shown that the midpoint method for handling ties retains the property that the average value of all SUCRA values in a network is one half. Comparability of MID-adjusted P-scores and MID-adjusted SUCRA values is discussed, and a Bayesian software implementation of the MID-adjusted ranking metrics is provided.ResultsTwo real-world applications of MID-adjusted ranking metrics are presented to illustrate their use. Specifically, NMAs are conducted based on published networks on treatments for diabetes and Parkinson's disease. To present the results, MIDs are selected from relevant literature to interpret MID-adjusted ranking metrics for these networks.ConclusionsFailure to consider MIDs when ranking treatments can lead to ranking metrics which are not clinically relevant. Our proposed MID-adjusted Bayesian ranking metrics address this challenge. Further, we show that the use of the midpoint method for addressing ties ensures comparability between standard ranking metrics and MID-adjusted ranking metrics. The methods are easily applied in a Bayesian framework using the R package mid.nma.rank.

Dataset Information

Estimating Minimally Important Differences for the Bladder Cancer Index Using Distribution and Anchor Based Approaches.

Purpose

Materials and methods

Results

Conclusions

Publications

Estimating Minimally Important Differences for the Bladder Cancer Index Using Distribution and Anchor Based Approaches.

Similar Datasets

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