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A Bayesian CUSUM plot: Diagnosing quality of treatment
Steen Rosthøj1, Rikke-Line Jacobsen2
1Pediatric Oncology Section, Pediatric Department, Aalborg University Hospital, Aalborg, Denmark.
Journal of Evaluation in Clinical Practice
|September 8, 2017
Summary
This study introduces a Bayesian CUSUM plot to assess quality of treatment (QOT) in small patient groups. The method effectively evaluates treatment effectiveness, even with ongoing patient follow-up.
Area of Science:
- Biostatistics
- Clinical Trial Methodology
- Health Services Research
Background:
- Assessing quality of treatment (QOT) in small patient series presents statistical challenges.
- Traditional methods may be insufficient for ongoing trials with incomplete follow-up data.
Purpose of the Study:
- To introduce a novel Bayesian Cumulative Sum (CUSUM) plot for evaluating QOT.
- To demonstrate its application in case series, including those with ongoing follow-up.
- To provide a method for diagnostic reasoning favoring "healthy" over "sick" treatment quality.
Main Methods:
- Utilized Bayesian diagnostic reasoning and likelihood ratios (LR) to quantify evidence for QOT.
- Converted LRs to weights (log base 2) and sequentially plotted cumulative evidence.
- Adapted Kaplan-Meier survival curves for analyzing series with ongoing follow-up.
Main Results:
- Retrospective analysis of 39 acute lymphoblastic leukemia cases showed equal odds between good and poor QOT.
- In an ongoing trial with 37 patients (22 at risk), odds favored good QOT 2:1 based on survival curves.
Conclusions:
- A Bayesian CUSUM plot is effective for assessing QOT in small patient series.
- The method is applicable retrospectively with complete outcomes and prospectively in ongoing trials.
- This technique enhances the evaluation of treatment quality in clinical practice.
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