Measuring and predicting prostate cancer related quality of life changes using EPIC for clinical practice.
OBJECTIVE
We expanded the clinical usefulness of EPIC-CP (Expanded Prostate Cancer Index Composite for Clinical Practice) by evaluating its responsiveness to health related quality of life changes, defining the minimally important differences for an individual patient change in each domain and applying it to a sexual outcome prediction model.


METHODS
In 1,201 subjects from a previously described multicenter longitudinal cohort we modeled the EPIC-CP domain scores of each treatment group before treatment, and at short-term and long-term followup. We considered a posttreatment domain score change from pretreatment of 0.5 SD or greater clinically significant and p ≤ 0.01 statistically significant. We determined the domain minimally important differences using the pooled 0.5 SD of the 2, 6, 12 and 24-month posttreatment changes from pretreatment values. We then recalibrated an EPIC-CP based nomogram model predicting 2-year post-prostatectomy functional erection from that developed using EPIC-26.


RESULTS
For each health related quality of life domain EPIC-CP was sensitive to similar posttreatment health related quality of life changes with time, as was observed using EPIC-26. The EPIC-CP minimally important differences in changes in the urinary incontinence, urinary irritation/obstruction, bowel, sexual and vitality/hormonal domains were 1.0, 1.3, 1.2, 1.6 and 1.0, respectively. The EPIC-CP based sexual prediction model performed well (AUC 0.76). It showed robust agreement with its EPIC-26 based counterpart with 10% or less predicted probability differences between models in 95% of individuals and a mean ± SD difference of 0.0 ± 0.05 across all individuals.


CONCLUSIONS
EPIC-CP is responsive to health related quality of life changes during convalescence and it can be used to predict 2-year post-prostatectomy sexual outcomes. It can facilitate shared medical decision making and patient centered care.
Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts.
Jonathan J
JJ
Chipman
Department of Urology, Emory University, Atlanta, Georgia.
Martin G
MG
Sanda
Department of Urology, University of Michigan School of Medicine, Ann Arbor, Michigan.
Rodney L
RL
Dunn
Department of Urology, University of Michigan School of Medicine, Ann Arbor, Michigan.
John T
JT
Wei
David Geffen School of Medicine and Fielding School of Public Health, University of California-Los Angeles, Los Angeles, California.
Mark S
MS
Litwin
Division of Urology, Department of Surgery, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
Catrina M
CM
Crociani
Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts.
Meredith M
MM
Regan
Division of Urology, Department of Surgery, Beth Israel Deaconess Medical Center, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts. Electronic address: pchang@bidmc.harvard.edu.
Peter
P
Chang
D006801:Humans; D007410:Intestinal Diseases / Q000503:physiopathology* / Q000523:psychology*; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D011183:Postoperative Complications / Q000503:physiopathology* / Q000523:psychology*; D011237:Predictive Value of Tests; D011446:Prospective Studies; D011468:Prostatectomy; D011471:Prostatic Neoplasms / Q000532:radiotherapy / Q000601:surgery*; D011788:Quality of Life; D012735:Sexual Dysfunction, Physiological / Q000503:physiopathology* / Q000523:psychology*; D011795:Surveys and Questionnaires; D014570:Urologic Diseases / Q000503:physiopathology* / Q000523:psychology*
outcome assessment (health care); prostate; prostatic neoplasms; quality of life; questionnaires