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Published on: July 24, 2016
Use and misuse of waterfall plots
Tiffany Shao1, Lisa Wang1, Arnoud J Templeton1
1Divisions of Medical Oncology and Hematology (TS, AJT, RWJ, FVB, MGM, IFT) and Biostatistics (LW), Princess Margaret Cancer Center, Department of Medicine, University of Toronto, Toronto, Canada; Joint Department of Medical Imaging, University Health Network, Toronto, Canada (MM, TKK, MS, HS).
Waterfall plots assessing tumor size changes show significant variability due to inconsistent criteria and measurement errors. Trained radiologists should generate these plots for reliable clinical trial interpretation.
Area of Science:
- Oncology
- Radiology
- Clinical Trials
Background:
- Waterfall plots are commonly used to visualize tumor size changes in clinical studies.
- Assessing the criteria for generating waterfall plots and the impact of measurement error is crucial for accurate interpretation.
Purpose of the Study:
- To evaluate the variability in criteria used for generating waterfall plots.
- To assess the impact of interobserver variability and measurement error on waterfall plot generation.
Main Methods:
- Reviewed published waterfall plots to identify criteria variability.
- Compared waterfall plots generated by radiologists and oncologists using CT scans from a phase I solid tumor study.
- Quantified interobserver variability based on Response Evaluation Criteria in Solid Tumors 1.1.
Main Results:
- Substantial variability was found in the criteria used to generate published waterfall plots.
- Statistically significant differences in results were observed between all readers and between oncologists, but not radiologists.
- Observer variability led to differing classifications of patient response (e.g., partial response, stable disease).
Conclusions:
- Waterfall plots exhibit significant variability due to definition criteria and measurement errors.
- Trained radiologists are recommended for generating waterfall plots to ensure consistency.
- Caution is advised when interpreting waterfall plot results in clinical trial contexts.
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