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Background: The Extended Prostate Cancer Index Composite (EPIC) instrument is a commonly used patient reported outcome (PRO) tool in prostate cancer clinical trials. Summary scores for EPIC subscales are calculated by averaging patient scores for attributes (e.g., side effects), implying equal weighting of the attributes in the absence of evidence showing otherwise. Methods: We estimated patient preferences for each of the attributes included in the bowel subscale of the EPIC instrument using best-worst (B-W) scaling among a cohort of men with prostate cancer. Patients were presented with multiple tasks in which they were asked to indicate which attribute they would find most and least bothersome at different levels of severity. Analysis utilized both (simple) B-W counts and scores to estimate patient preferences for each attribute as well as attribute levels. Results: A total of 174 respondents from two institutions participated in the survey. Preference estimates for each of the five attributes included in the EPIC-26 bowel subscale showed wide variation preferences: 'losing control of bowel movements' was found to be the most bothersome attribute, with a B-W score of -0.48, followed by bowel urgency which also had negative B-W score (-0.04). Increased frequency of bowel movements was the least bothersome attribute, with a B-W score of +0.33, followed by bloody stools (+0.12), and pelvic/rectal pain (+0.06). Analysis of preference weights for attribute bother levels showed preference estimates be linear. Conclusions: We provide novel evidence on patient preferences for side effect reduction following prostate radiotherapy. Within the bowel sub-scale of the EPIC-26 short form, we found that bowel incontinence was perceived to be the most bothersome treatment effect, while increased bowel frequency was least bothersome to patients. [ABSTRACT FROM AUTHOR]

Objectives:Qualitative research aimed at identifying patient acceptance of active surveillance (AS) has been identified as a public health research priority. The primary objective of this study was to determine if analysis of a large-sample of anonymous internet conversations (ICs) could be utilized to identify unmet public needs regarding AS. Methods:English-language ICs regarding prostate cancer (PC) treatment with AS from 2002–12 were identified using a novel internet search methodology. Web spiders were developed to mine, aggregate, and analyze content from the world-wide-web for ICs centered on AS. Collection of ICs was not restricted to any specific geographic region of origin. NLP was used to evaluate content and perform a sentiment analysis. Conversations were scored as positive, negative, or neutral. A sentiment index (SI) was subsequently calculated according to the following formula to compare temporal trends in public sentiment towards AS: [(# Positive IC/#Total IC) - (#Negative IC/#Total IC) x 100]. Results:A total of 464 ICs were identified. Sentiment increased from -13 to +2 over the study period. The increase sentiment has been driven by increased patient emphasis on quality-of-life factors and endorsement of AS by national medical organizations. Unmet needs identified in these ICs include: a gap between quantitative data regarding long-term outcomes with AS vs. conventional treatments, desire for treatment information from an unbiased specialist, and absence of public role models managed with AS. Conclusions:This study demonstrates the potential utility of online patient communications to provide insight into patient preferences and decision-making. Based on our findings, we recommend that multidisciplinary clinics consider including an unbiased specialist to present treatment options and that future decision tools for AS include quantitative data regarding outcomes after AS. [ABSTRACT FROM AUTHOR]

Purpose: The Expanded Prostate Cancer Index Composite (EPIC) is the most commonly used patient reported outcome (PRO) tool in prostate cancer (PC) clinical trials, but health utilities associated with the different health states assessed with this tool are unknown, limiting our ability to perform cost-utility analyses. This study aimed to map EPIC tool to EuroQoL-5D-3L (EQ5D) to generate EQ5D health utilities., Methods and Materials: This is a secondary analysis of a prospective, randomized non-inferiority clinical trial, conducted between 04/2006 and 12/2009 at cancer centers across the United States, Canada, and Switzerland. Eligible patients included men >18 years with a known diagnosis of low-risk PC. Patient HRQoL data were collected using EPIC and health utilities were obtained using EQ5D. Data were divided into an estimation sample (n = 765, 70%) and a validation sample (n = 327, 30%). The mapping algorithms that capture the relationship between the instruments were estimated using ordinary least squares (OLS), Tobit, and two-part models. Five-fold cross-validation (in-sample) was used to compare the predictive performance of the estimated models. Final models were selected based on root mean square error (RMSE)., Results: A total of 565 patients in the estimation sample had complete information on both EPIC and EQ5D questionnaires at baseline. Mean observed EQ5D utility was 0.90±0.13 (range: 0.28-1) with 55% of patients in full health. OLS models outperformed their counterpart Tobit and two-part models for all pre-determined model specifications. The best model fit was: "EQ5D utility = 0.248541 + 0.000748*(Urinary Function) + 0.001134*(Urinary Bother) + 0.000968*(Hormonal Function) + 0.004404*(Hormonal Bother)- 0.376487*(Zubrod) + 0.003562*(Urinary Function*Zubrod)"; RMSE was 0.10462., Conclusions: This is the first study to identify a comprehensive set of mapping algorithms to generate EQ5D utilities from EPIC domain/ sub-domain scores. The study results will help estimate quality-adjusted life-years in PC economic evaluations., Competing Interests: Drs. Khairnar, Albert, Bentzen, Bruner, Chen, Currey, Dayes, DeNittis, Horwitz, Lee, Michalski, Mullins, Palumbo, Pisansky, Seaward, Shah, Shaya, and Villalonga have nothing to disclose. Dr. Feng reports personal fees from Janssen Oncology, Sanofi, Bayer, Celgene, and Blue Earth Diagnostics, grants from Zenith Epigenetics, and other from PFS Genomics, outside the submitted work; Dr. Malone reports personal fees from Sanofi, and honoraria from Amgen, Abbvie, Astellas, Janssen, Tersara, Astra Zeneca, Knight Therapeutics, and Bayer, outside the submitted work; Dr. Mishra reports grants from American Society of Radiation Oncology (ASTRO), during the conduct of the study and other from Varian Medical Systems, outside the submitted work; Dr. Sandler reports grants from ACR/NRG Oncology, during the conduct of the study; personal fees from Janssen, other from Radiogel, outside the submitted work; Dr. Pugh reports other from Millennium, other from Pfizer, outside the submitted work. This does not alter our adherence to PLOS ONE policies on sharing data and materials.