Prognostic risk integration for survival modeling (PRISM) in newly diagnosed acute myeloid leukemia treated with venetoclax: a multinational retrospective cohort study
Abstract
Abstract Background: The 4-gene molecular prognostic risk score (mPRS) improves overall survival (OS) prediction in patients (pts) with newly diagnosed AML (ND-AML) treated with hypomethylating agents (HMA) and venetoclax (VEN). Yet given the broad clinical and molecular heterogeneity of AML, risk stratification remains suboptimal. We consolidated a large international cohort of ND-AML pts treated with lower-intensity regimens including HMA or low-dose cytarabine (LDAC) plus VEN to improve OS prognostication. Methods: We analyzed 2,273 ND-AML adult pts who received frontline VEN with HMA (n=2,222) or LDAC (n=51) at an academic medical center in the US, UK, France, Germany, or Italy who had complete clinical, cytogenetic, and molecular data. An initial set of 1,974 patients were split into a training (TC, N=1,339) and internal validation (VC, N=635) cohorts, stratifying on key clinical variables (de novo vs. secondary AML, TP53 and IDH2 mutations, hematopoietic cell transplantation [HCT], death). An additional N=299 patients, acquired later, were utilized as an external validation set. OS was measured from therapy start, estimated with Kaplan-Meier curves, and compared across risk groups using the log-rank test. HCT was considered a time-dependent covariate. OS discrimination was estimated by Harrell's C-index (C). Clinical and genomic features (with a frequency ≥ 4% required for nominal features) were included in model development. Cox L1-penalized regression of OS applied to 1,000 bootstrap samples from the TC was used to identify stable features (selected with a consistent direction in ≥75% of bootstrap iterations). These features were entered into a robust Cox model. Non-significant genes “ResMut” were grouped according to their directional effect on OS to create “ResMut-fav” denoting the presence of ≥1 mutation in a favorable set of residual genes. The final robust Cox model beta coefficients were added to calculate patient-specific risk PRISM scores. Quartiles of PRISM scores defined four clinical PRISM risk groups: low (L), moderate (M), high (H), and very-high (VH). Results: In the TC, median pt age was 74 years; 61% were male. 41% had secondary AML (sAML), arising from an antecedent hematologic disorder (sAML-AHD) in 33% (11% with treated AHD) and from prior therapy in 8%. The mPRS distribution was 56% higher-, 22% intermediate-, and 22% lower-benefit. HCT rate was 12%. The final PRISM model included age, sex, sAML-AHD, ELN 2022 complex karyotype and other adverse-risk cytogenetic abnormalities, and adverse mutations in KRAS, PTPN11, FLT3-ITD, JAK2, ASXL1, and TP53. Favorable features included diploid karyotype, mutations in RUNX1 or IDH2, and ResMut-fav (comprising CEBPA, BCOR, IDH1, SF3B1). For TC pts, at median follow-up of 20.8 months (mo), median OS (mOS) was 12.2 mo (95% CI: 10.9–13.6). Higher PRISM scores were associated with worse OS (1-unit increase HR: 2.50; 95% CI: 2.21–2.82; C: 0.654). Median OS by PRISM risk group L/M/H/VH was 29.6, 17.6, 11.3, and 5.6 mo (C: 0.641; p<0.001). PRISM risk groups improved OS discrimination vs. mPRS (C: 0.641 vs. 0.583, p<0.001), with similar benefit after adjusting for HCT (C: 0.650 vs. 0.594, p<0.001). There were no significant differences in considered variables between the TC and VC. In the VC, median follow-up was 24.4 mo and mOS 13.0 mo (95% CI: 11.5–14.8). The PRISM score was significantly associated with OS (1-unit increase HR: 2.28; 95% CI: 1.91–2.71; C: 0.653). Median OS by PRISM group L/M/H/VH was 24.4, 15.0, 11.7, and 5.8 mo, similar to rates observed in the TC. PRISM risk groups outperformed mPRS (C: 0.648 vs. 0.613, p=0.002), including after adjusting for HCT (C: 0.659 vs. 0.629, p=0.018). The external validation cohort was marginally older (median age 75 years) with fewer HCT recipients (8%) compared to the initial TC/VC. Higher PRISM scores remained highly associated with OS (1-unit increase HR: 2.49, 95% CI: 1.92-3.24; C: 0.661). Median OS by PRISM group L/M/H/VH was 28.8, 13.9, 12.5, and 6.3 mo. PRISM risk groups had better OS discrimination than mPRS (C: 0.648 vs. 0.584, p=0.010), including after adjusting for HCT (C:0.662 vs. 0.607, p=0.004). Conclusions: Integration of prognostically relevant clinical and genomic features into the PRISM score and subsequent PRISM risk groups enables improved discrimination of survival following lower-intensity HMA/LDAC+VEN therapy in patients with ND-AML compared to current risk classification frameworks.
Article Details
Authors (48)
Curtis Lachowiez
1Oregon Health and Science University, Portland, United States
Andy Kaempf
1Oregon Health & Science University, Division of Hematologic Malignancies, Knight Cancer Institute, Portland, United States
Jad Othman
3The University of Sydney, Sydney, Australia
Seongseok Yun
Moffitt Cancer Cancer and Research Institute, Tampa, Florida, United States
Maël Heiblig
9Department of Hematology, Centre Hospitalier Universitaire de Lyon, Lyon, France
Michael Heuser
Rabia Shahswar
4Hannover Medical School, Department for Hematology, Hemostasis, Oncology and Stem Cell Transplantation, Hannover, Germany
Anand Patel
Rafael Madero-Marroquin
1University of Chicago, Chicago, United States
Joseph Cannova
Irene Zacheo
1919. IRST IRCCS, Meldola, Forlì-Cesena, forlì cesena, Italy
Federica Monaco
11Department of Hematology, Ospedali Infermi, AUSLROMAGNA, Rimini, Italy
Dimitrios Drekolias
Moffitt Cancer Cancer and Research Institute, Tampa, Florida, United States
Fatima Tuz Zahra
1H. Lee Moffitt Cancer Center, Tampa, United States
Amine Belhabri
19Service d’Hématologie, Centre Léon-Bérard, Lyon, France
Urbain Tauveron-Jalenques
3Centre Hospitalier Universitaire Clermont-Ferrand, Service d'hématologie et thérapie cellulaire, Clermont-Ferrand, France
Emmanuelle Tavernier
Martin Carré
Gaspar Aspas Requena
8CHU Clermont-Ferrand, Department of Hematology, Clermont-Ferrand, France
Nicola Long
1Oregon Health & Science University, Division of Hematologic Malignancies, Knight Cancer Institute, Portland, United States
Rachel Cook
1Oregon Health and Science University, Portland, United States
Elie Traer
Oregon Health & Science University, Portland, Oregon, United States
Ronan Swords
OHSU Knight Cancer Institute Center for Hematologic Malignancies, Portland, Oregon, United States
Jennifer Saultz
1Oregon Health and Science University, Portland, United States
Jenny O'Nions
13Department of Hematology, University College London Hospital NHS Foundation Trust, London, United Kingdom
Faisal Basheer
13Addenbrooke's Hospital, Department of Haematology, Cambridge, United Kingdom
John Laurie
14University Hospitals Sussex NHS Foundation Trust, Worthing, United Kingdom
Shivani Handa
The Ohio State University, Columbus, Ohio, United States
Eytan Stein
3Memorial Sloan Kettering Cancer Center, Medicine, New York, United States
Maria Baer
3University of Maryland Marlene and Stewart Greenebaum Cancer Center, Baltimore, United States
Wendy Stock
Rebecca Olin
1University of California, San Francisco, Hematology, Blood and Marrow Transplantation, and Cellular Therapy Program, San Francisco, United States
William Blum
Emory University, Atlanta, Georgia, United States
Gary Schiller
7David Geffen School of Medicine at UCLA, Los Angeles, United States
Tara Lin
20University of Kansas Cancer Center, Westwood, United States
Emily Curran
University of Cincinnati College of Medicine, Cincinnati, Ohio, United States
Ying Huang
Rina Welkie
1The Ohio State University, James Comprehensive Cancer Center, Columbus, United States
Ashley Yocum
14Blood Cancer United, Washington, United States
Giovanni Marconi
31Hematology Unit, Ospedale S. Maria delle Croci, University of Bologna, Ravenna, Italy
Ellen Madarang
2University of Miami Miller School of Medicine, Leukemia Service, Department of Medicine, Miami, United States
Justin Watts
2Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Medicine, Miami, United States
Yazan Madanat
Richard Dillon
5King's College London, London, United Kingdom
Sanam Loghavi
Joshua Zeidner
5University of North Carolina, Chapel Hill, United States
Daniel Pollyea
2University of Colorado School of Medicine, Division of Hematology, Aurora, United States
Elsa Bernard
2Institut Gustave Roussy, Computational Clinical Oncology Lab, UMR 981, Villejuif, France