Statistical controversies in cancer research: using standardized effect size graphs to enhance interpretability of cancer-related clinical trials with patient-reported outcomes.
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.
Department of Epidemiology and Biostatistics, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson.
M L
ML
Bell
Office of Biostatistics, U.S. Food and Drug Administration, Silver Spring, USA.
M H
MH
Fiero
Centre for Medical Psychology and Evidence-Based Decision-Making, School of Psychology, University of Sydney, Camperdown.
H M
HM
Dhillon
University of Sydney, Liverpool Hospital, Liverpool.
V J
VJ
Bray
Concord Cancer Centre, Concord Repatriation General Hospital, Concord.|Sydney Medical School, University of Sydney, Sydney, Australia.
J L
JL
Vardy
D035843:Biomedical Research; D002986:Clinical Trials as Topic; D003627:Data Interpretation, Statistical; D006801:Humans; D009369:Neoplasms / Q000628:therapy*; D016896:Treatment Outcome
cancer; effect size; graphs; patient-reported outcomes; quality of life