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Statistical controversies in cancer research: using standardized effect size graphs to enhance interpretability of cancer-related clinical trials with patient-reported outcomes.


ABSTRACT: Patient reported outcomes (PROs) are becoming increasingly important in cancer studies, particularly with the emphasis on patient centered outcome research. However, multiple PROs, using different scales, with different directions of favorability are often used within a trial, making interpretation difficult. To enhance interpretability, we propose the use of a standardized effect size graph, which shows all PROs from a study on the same figure, on the same scale. Plotting standardized effects with their 95% confidence intervals (CIs) on a single graph clearly showing the null value conveys a comprehensive picture of trial results. We demonstrate how to create such a graph using data from a randomized controlled trial that measured 12 PROs at two time points. The 24 effect sizes and CIs are shown on one graph and clearly indicate that the intervention is effective and sustained.

SUBMITTER: Bell ML 

PROVIDER: S-EPMC5834129 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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Statistical controversies in cancer research: using standardized effect size graphs to enhance interpretability of cancer-related clinical trials with patient-reported outcomes.

Bell M L ML   Fiero M H MH   Dhillon H M HM   Bray V J VJ   Vardy J L JL  

Annals of oncology : official journal of the European Society for Medical Oncology 20170801 8


Patient reported outcomes (PROs) are becoming increasingly important in cancer studies, particularly with the emphasis on patient centered outcome research. However, multiple PROs, using different scales, with different directions of favorability are often used within a trial, making interpretation difficult. To enhance interpretability, we propose the use of a standardized effect size graph, which shows all PROs from a study on the same figure, on the same scale. Plotting standardized effects w  ...[more]

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