A Crowdsourcing Approach to Developing and Assessing Prediction Algorithms for AML Prognosis.

ABSTRACT: Acute Myeloid Leukemia (AML) is a fatal hematological cancer. The genetic abnormalities underlying AML are extremely heterogeneous among patients, making prognosis and treatment selection very difficult. While clinical proteomics data has the potential to improve prognosis accuracy, thus far, the quantitative means to do so have yet to be developed. Here we report the results and insights gained from the DREAM 9 Acute Myeloid Prediction Outcome Prediction Challenge (AML-OPC), a crowdsourcing effort designed to promote the development of quantitative methods for AML prognosis prediction. We identify the most accurate and robust models in predicting patient response to therapy, remission duration, and overall survival. We further investigate patient response to therapy, a clinically actionab

SUBMITTER: Noren DP 

PROVIDER: S-EPMC4924788 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature