Looking to the Future in the Era of Personalized Medicine

More Info in the ASH Press release

 

Webcasts at the bottom

793 A Personalized Prediction Model to Risk Stratify Patients with Myelodysplastic Syndromes

Aziz Nazha, et al.

Conclusion

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.

https://ash.confex.com/ash/2018/webprogram/Paper114774.html

 

811 Multicenter Microbiota Analysis Indicates That Pre-HCT Microbiota Injury Is Prevalent across Geography and Predicts Poor Overall Survival

Jonathan U. Peled, et al.

Conclusion

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.

https://ash.confex.com/ash/2018/webprogram/Paper116967.html

 

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.

Conclusion

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.

https://ash.confex.com/ash/2018/webprogram/Paper118494.html