Incorporating patient-reported outcome data into a predictive calculator for allogeneic hematopoietic cell transplantation recipients.

BACKGROUND: The Center for International Blood and Marrow Transplant Research (CIBMTR) provides a 1-year overall survival calculator to estimate outcomes for individual patients before they undergo allogeneic hematopoietic cell transplantation (HCT) to inform risk. The calculator considers pre-HCT clinical and demographic characteristics, but not patient-reported outcomes (PROs). Because pre-HCT PRO scores have been associated with post-HCT outcomes, the authors hypothesized that adding PRO scores to the calculator would enhance its predictive power. METHODS: Clinical data were obtained from the CIBMTR and the Blood and Marrow Transplant Clinical Trials Network. The PRO measures used were the 36-Item Short Form Survey (SF-36) and the Functional Assessment of Cancer Therapy-Bone Marrow Transplantation. One thousand thirty-three adult patients were included. RESULTS: When adjusted for clinical characteristics, the SF-36 physical component score was significantly predictive of 1-year survival (hazard ratio [HR], 0.88; 95% confidence interval [CI], 0.81-0.95; p = .0015), whereas the mental component score was not (HR, 1.02; 95% CI, 0.95-1.10; p = 0.6396). The baseline single general health question on the SF-36 was also significantly associated with mortality (HR, 1.91 for those reporting fair/poor health vs. good, very good, or excellent health; 95% CI, 1.33-2.76; p = .0005). The addition of PRO scores to the calculator did not result in a significant change in the model's predictive ability. Self-reported pre-HCT scores were strongly predictive of self-reported health status (odds ratio, 3.35; 95% CI, 1.66-6.75; p = .0007) and quality of life (odds ratio, 3.24; 95% CI, 1.93-5.41; p < .0001) after HCT. CONCLUSIONS: The authors confirmed the significant, independent association of pre-HCT PRO scores with overall survival, although adding PRO scores to the survival calculator did not improve its performance. They also demonstrated that a single general health question was as accurate as the full measure for predicting survival, an important finding that may reduce respondent burden and promote its inclusion in routine clinical practice. Validation of these findings should be performed.

Duke Scholars

Author Kathryn Eve Flynn Population Health Sciences