Looking to the Future in the Era of Personalized Medicine
Webcasts at the bottom
793 A Personalized Prediction Model to Risk Stratify Patients with Myelodysplastic Syndromes
Aziz Nazha, et al.
We built a personalized prediction model based on clinical and genomic data that outperformed IPSS and IPSS-R in predicting OS and AML transformation. The new model gives survival probabilities at different time points that are unique for a given pt. Incorporating clinical and mutational data outperformed a mutations only model even when cytogenetics and age were added.
811 Multicenter Microbiota Analysis Indicates That Pre-HCT Microbiota Injury Is Prevalent across Geography and Predicts Poor Overall Survival
Jonathan U. Peled, et al.
We demonstrate that HCT patients at 4 institutions on 3 continents presented with microbiota configurations that were similar to one another and distinct from those of healthy individuals. Severe microbiota injury as revealed by domination is a common event whose development begins before allograft infusion, and pre-HCT microbiota injury predicts poor overall survival. These observations suggest the pre-HCT period as a window of opportunity to (a) assess microbiota injury as part of comorbidity evaluation, (b) inform selection of antibiotic prophylaxis, gut-decontamination, GVHD-prophylaxis, or conditioning regimens, and (c) intervene with microbiota injury-remediation or prevention strategies.
559 Initial Report of the Beat AML Umbrella Study for Previously Untreated AML: Evidence of Feasibility and Early Success in Molecularly Driven Phase 1 and 2 Studies
Amy Burd, et al.
Our data support the feasibility of a rapid precision medicine approach in older pts with previously untreated AML. The Beat AML trial is a model for dynamic, mechanism-based clinical trials in blood cancers where genomic analysis may inform, accelerate, and improve drug development.