Validation of a Hematopoietic Cell Transplant-Composite Risk (HCT-CR) Model for Post-Transplant Survival Prediction in Patients with Hematologic Malignancies.

PURPOSE

Allogeneic hematopoietic stem cell transplantation (AHCT) outcomes depend on disease and patient characteristics. We previously developed a novel prognostic model, hematopoietic cell transplant composite-risk (HCT-CR) by incorporating the refined disease risk index (DRI-R) and hematopoietic cell transplant-comorbidity/age index (HCT-CI/Age) to predict post-transplant survival in patients with acute myeloid leukemia and myelodysplastic syndrome. Here we aimed to validate and prove the generalizability of the HCT-CR model in an independent cohort of patients with hematologic malignancies receiving AHCT.

EXPERIMENTAL DESIGN

Data of consecutive adult patients receiving AHCT for various hematologic malignancies were analyzed. Patients were stratified into four HCT-CR risk groups. The discrimination, calibration performance, and clinical net benefit of the HCT-CR model were tested.

RESULTS

The HCT-CR model stratified patients into four risk groups with significantly different overall survival (OS). Three-year OS was 67.4%, 50%, 37.5%, and 29.9% for low, intermediate, high, and very high-risk group, respectively ( < 0.001). The HCT-CR model had better discrimination on OS prediction when compared with the DRI-R and HCT-CI/Age (C-index was 0.69 vs. 0.59 and 0.56, respectively, < 0.001). The decision curve analysis showed that HCT-CR model provided better clinical utility for patient selection for post-transplant clinical trial than the "treat all" or "treat none" strategy and the use of the DRI-R and HCT-CI/Age model separately.

CONCLUSIONS

The HCT-CR can be effectively used to predict post-transplant survival in patients with various hematologic malignancies. This composite model can identify patients who will benefit the most from transplantation and helps physicians in making decisions regarding post-transplant therapy to improve outcomes.