Measuring and predicting prostate cancer related quality of life changes using EPIC for clinical practice.

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Published in J Urol on September 25, 2013

Authors

Jonathan J Chipman1, Martin G Sanda2, Rodney L Dunn3, John T Wei3, Mark S Litwin4, Catrina M Crociani5, Meredith M Regan6, Peter Chang7, PROST-QA Consortium

Author Affiliations

1: Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts.
2: Department of Urology, Emory University, Atlanta, Georgia.
3: Department of Urology, University of Michigan School of Medicine, Ann Arbor, Michigan.
4: David Geffen School of Medicine and Fielding School of Public Health, University of California-Los Angeles, Los Angeles, California.
5: Division of Urology, Department of Surgery, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
6: Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts.
7: Division of Urology, Department of Surgery, Beth Israel Deaconess Medical Center, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts. Electronic address: pchang@bidmc.harvard.edu.

Associated clinical trials:

Initiative to Minimize Disparities in Postoperative Prostate Cancer Care | NCT03755492

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