Underpinning the vision of precision medicine is the concept that causative mutations in a patient's cancer drive its biology and, by extension, its clinical features and treatment response. However, considerable between-patient heterogeneity in driver mutations complicates evidence-based personalization of cancer care. Here, by reanalyzing data from 1,540 patients with acute myeloid leukemia (AML), we explore how large knowledge banks of matched genomic–clinical data can support clinical decision-making. Inclusive, multistage statistical models accurately predicted likelihoods of remission, relapse and mortality, which were validated using data from independent patients in The Cancer Genome Atlas. Comparison of long-term survival probabilities under different treatments enables therapeutic decision support, which is available in exploratory form online. Personally tailored management decisions could reduce the number of hematopoietic cell transplants in patients with AML by 20–25% while maintaining overall survival rates. Power calculations show that databases require information from thousands of patients for accurate decision support. Knowledge banks facilitate personally tailored therapeutic decisions but require sustainable updating, inclusive cohorts and large sample sizes.
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We thank C. Holmes for stimulating discussions. We gratefully acknowledge D. Weber for clinical data managing, V. Teleanu for assistance in cytogenetics data classification and S. Kayser for assistance in morphological evaluation. This work was supported by grants from the Wellcome Trust (077012/Z/05/Z; P.J.C.), the Bloodwise charity (P.J.C.), the Leukemia and Lymphoma Society (P.J.C.) and the Deutsche Krebshilfe (109675; K.D.), in part by grants from the German Bundesministerium für Bildung und Forschung (BMBF) (01GI9981 (H.D.) and 01KG0605 (R.F.S. and H.D.)), by a Wellcome Trust Senior Clinical Research Fellowship (WT088340MA; P.J.C.), by an EHA early career fellowship (E.P.), and by the Deutsche Forschungsgemeinschaft (project B3, Sonderforschungsbereich (SFB) 1074; K.D. and L.B.); H.D. is coordinating investigator. L.B. is a Heisenberg Professor of the DFG (BU 1339/3-1). We are grateful to all members of the German–Austrian AML Study Group (AMLSG) for their participation in this study and for providing patient samples; a list of participating institutions and investigators appears in the Appendix of Papaemmanuil et al.5. AMLSG treatment trials were in part supported by Amgen and DKH grant 109675.
Integrated supplementary information
Supplementary Tables 1–6