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PurposePatient-reported outcome (PRO) data from clinical trials can promote valuable patient-clinician communication and aid the decision-making process regarding treatment options. Despite these benefits, both patients and doctors face challenges in interpreting PRO scores. The purpose of this study was to identify best practices for presenting PRO results expressed as proportions of patients with changes from baseline (improved/stable/worsened) for use in patient educational materials and decision aids.MethodsWe electronically surveyed adult cancer patients/survivors, oncology clinicians, and PRO researchers, and conducted one-on-one cognitive interviews with patients/survivors and clinicians. Participants saw clinical trial data comparing two treatments as proportions changed using three different formats: pie charts, bar graphs, icon arrays. Interpretation accuracy, clarity, and format preference were analyzed quantitatively and online survey comments and interviews, qualitatively.ResultsThe internet sample included 629 patients, 139 clinicians, and 249 researchers; 10 patients and 5 clinicians completed interviews. Bar graphs were less accurately interpreted than pie charts (OR 0.39; p

Purpose: As patient-reported outcome measures (PROMs) are increasingly used in clinical practice for screening, monitoring, and management, the potential for response bias has been raised (e.g., over-reporting problems for attention, under-reporting to avoid treatment changes/discontinuation). We investigated whether patients systematically bias their responses when they know clinicians will review their PROM results. Methods: We conducted secondary analyses of three experimental studies evaluating PROMs in adult and pediatric care. Prior to PROM completion, intervention group patients were informed that the results would be shown to their clinicians ("feedback" arm), whereas control group patients were told that their clinicians would not see their responses ("no feedback" arm). Independent sample t-tests compared the "feedback" and "no feedback" arms' PROM scores at baseline. Effect sizes and 95% confidence intervals were estimated using Cohen's d statistics with Hedges' g correction, and effect sizes > 0.50 were considered clinically relevant. Results: Across the 29 domains assessed in the three studies, no between-arm differences reached an effect size of ± 0.50. Only 3/29 effect sizes exceeded ± 0.30. The confidence intervals for 14 domains included ± 0.50, with 4 favoring the "no feedback" arm and 10 favoring the "feedback" arm. Two domains reached statistical significance, one favoring the "no feedback" arm and one favoring the "feedback" arm. Conclusion: This study does not support the hypothesis that patients systematically bias their PROM responses if they know that clinicians will see their results. These findings support using PROMs in clinical practice as a valid mechanism to promote patient-centered care. [ABSTRACT FROM AUTHOR]