Artificial intelligence methods to estimate overall mortality and non-relapse mortality following allogeneic HCT in the modern era: an EBMT-TCWP study.

Journal

Bone marrow transplantation

ISSN: 1476-5365

Titre abrégé: Bone Marrow Transplant

Pays: England

ID NLM: 8702459

Informations de publication

Date de publication:
25 Nov 2023

Historique:

received: 25 05 2023

accepted: 03 11 2023

revised: 04 10 2023

medline: 26 11 2023

pubmed: 26 11 2023

entrez: 25 11 2023

Statut: aheadofprint

Résumé

Allogeneic haematopoietic cell transplantation (alloHCT) has curative potential counterbalanced by its toxicity. Prognostic scores fail to include current era patients and alternative donors. We examined adult patients from the EBMT registry who underwent alloHCT between 2010 and 2019 for oncohaematological disease. Our primary objective was to develop a new prognostic score for overall mortality (OM), with a secondary objective of predicting non-relapse mortality (NRM) using the OM score. AI techniques were employed. The model for OM was trained, optimized, and validated using 70%, 15%, and 15% of the data set, respectively. The top models, "gradient boosting" for OM (AUC = 0.64) and "elasticnet" for NRM (AUC = 0.62), were selected. The analysis included 33,927 patients. In the final prognostic model, patients with the lowest score had a 2-year OM and NRM of 18 and 13%, respectively, while those with the highest score had a 2-year OM and NRM of 82 and 93%, respectively. The results were consistent in the subset of the haploidentical cohort (n = 4386). Our score effectively stratifies the risk of OM and NRM in the current era but do not significantly improve mortality prediction. Future prognostic scores can benefit from identifying biological or dynamic markers post alloHCT.

Identifiants

DOI: 10.1038/s41409-023-02147-5 PMID: 38007531

pubmed: 38007531

doi: 10.1038/s41409-023-02147-5

pii: 10.1038/s41409-023-02147-5

doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

Informations de copyright

Références

Cieri N, Maurer K, Wu CJ. 60 Years Young: The Evolving Role of Allogeneic Hematopoietic Stem Cell Transplantation in Cancer Immunotherapy. Cancer Res. 2021;81:4373–84.

doi: 10.1158/0008-5472.CAN-21-0301 pubmed: 34108142 pmcid: 8416782

Snowden JA, Sánchez-Ortega I, Corbacioglu S, Basak GW, Chabannon C, de la Camara R, et al. Indications for haematopoietic cell transplantation for haematological diseases, solid tumours and immune disorders: current practice in Europe, 2022. Bone Marrow Transplant [Internet]. 2022 May [cited 2022 Jul 25]; Available from: https://www.nature.com/articles/s41409-022-01691-w

Passweg JR, Baldomero H, Chabannon C, Basak GW, de la Cámara R, Corbacioglu S, et al. Hematopoietic cell transplantation and cellular therapy survey of the EBMT: monitoring of activities and trends over 30 years. Bone Marrow Transpl. 2021;56:1651–64.

doi: 10.1038/s41409-021-01227-8

McDonald GB, Sandmaier BM, Mielcarek M, Sorror M, Pergam SA, Cheng GS, et al. Survival, Nonrelapse Mortality, and Relapse-Related Mortality After Allogeneic Hematopoietic Cell Transplantation: Comparing 2003–2007 Versus 2013–2017 Cohorts. Ann Intern Med. 2020;172:229.

doi: 10.7326/M19-2936 pubmed: 31958813 pmcid: 7847247

Armand P, Kim HT, Logan BR, Wang Z, Alyea EP, Kalaycio ME, et al. Validation and refinement of the Disease Risk Index for allogeneic stem cell transplantation. Blood. 2014;123:3664–71.

doi: 10.1182/blood-2014-01-552984 pubmed: 24744269 pmcid: 4047501

Papaemmanuil E, Gerstung M, Bullinger L, Gaidzik VI, Paschka P, Roberts ND, et al. Genomic Classification and Prognosis in Acute Myeloid Leukemia. N. Engl J Med. 2016;374:2209–21.

doi: 10.1056/NEJMoa1516192 pubmed: 27276561 pmcid: 4979995

Della Porta MG, Gallì A, Bacigalupo A, Zibellini S, Bernardi M, Rizzo E, et al. Clinical Effects of Driver Somatic Mutations on the Outcomes of Patients With Myelodysplastic Syndromes Treated With Allogeneic Hematopoietic Stem-Cell Transplantation. JCO. 2016;34:3627–37.

doi: 10.1200/JCO.2016.67.3616

Sorror ML, Maris MB, Storb R, Baron F, Sandmaier BM, Maloney DG, et al. Hematopoietic cell transplantation (HCT)-specific comorbidity index: a new tool for risk assessment before allogeneic HCT. Blood. 2005;106:2912–9.

doi: 10.1182/blood-2005-05-2004 pubmed: 15994282 pmcid: 1895304

Gratwohl A. The EBMT risk score. Bone Marrow Transpl. 2012;47:749–56.

doi: 10.1038/bmt.2011.110

Sorror ML, Storb RF, Sandmaier BM, Maziarz RT, Pulsipher MA, Maris MB, et al. Comorbidity-Age Index: A Clinical Measure of Biologic Age Before Allogeneic Hematopoietic Cell Transplantation. JCO. 2014;32:3249–56.

doi: 10.1200/JCO.2013.53.8157

Barba P, Martino R, Pérez-Simón JA, Fernández-Avilés F, Castillo N, Piñana JL, et al. Combination of the Hematopoietic Cell Transplantation Comorbidity Index and the European Group for Blood and Marrow Transplantation Score Allows a Better Stratification of High-Risk Patients Undergoing Reduced-Toxicity Allogeneic Hematopoietic Cell Transplantation. Biol Blood Marrow Transplant. 2014;20:66–72.

doi: 10.1016/j.bbmt.2013.10.011 pubmed: 24141006

Parimon T, Au DH, Martin PJ, Chien JW. A Risk Score for Mortality after Allogeneic Hematopoietic Cell Transplantation. Ann Intern Med. 2006;144:407.

doi: 10.7326/0003-4819-144-6-200603210-00007 pubmed: 16549853

Luft T, Benner A, Terzer T, Jodele S, Dandoy CE, Storb R, et al. EASIX and mortality after allogeneic stem cell transplantation. Bone Marrow Transpl. 2020;55:553–61.

doi: 10.1038/s41409-019-0703-1

Shouval R, Labopin M, Bondi O, Mishan-Shamay H, Shimoni A, Ciceri F, et al. Prediction of Allogeneic Hematopoietic Stem-Cell Transplantation Mortality 100 Days After Transplantation Using a Machine Learning Algorithm: A European Group for Blood and Marrow Transplantation Acute Leukemia Working Party Retrospective Data Mining Study. JCO. 2015;33:3144–51.

doi: 10.1200/JCO.2014.59.1339

Salas MQ, Atenafu EG, Bascom O, Wilson L, Lam W, Law AD, et al. Pilot prospective study of Frailty and Functionality in routine clinical assessment in allogeneic hematopoietic cell transplantation. Bone Marrow Transpl. 2021;56:60–9.

doi: 10.1038/s41409-020-0979-1

Shouval R, Fein JA, Shouval A, Danylesko I, Shem-Tov N, Zlotnik M, et al. External validation and comparison of multiple prognostic scores in allogeneic hematopoietic stem cell transplantation. Blood Adv. 2019;3:1881–90.

doi: 10.1182/bloodadvances.2019032268 pubmed: 31221661 pmcid: 6595255

Bacigalupo A, Ballen K, Rizzo D, Giralt S, Lazarus H, Ho V, et al. Defining the Intensity of Conditioning Regimens: Working Definitions. Biol Blood Marrow Transplant. 2009;151628–33.

doi: 10.1016/j.bbmt.2009.07.004 pubmed: 19896087 pmcid: 2861656

Penack O, Peczynski C, Mohty M, Yakoub-Agha I, de la Camara R, Glass B, et al. Association of pre-existing comorbidities with outcome of allogeneic hematopoietic cell transplantation. A retrospective analysis from the EBMT. Bone Marrow Transpl. 2022;57:183–90.

doi: 10.1038/s41409-021-01502-8

Iacobelli S, On behalf of the EBMT Statistical Committee. Suggestions on the use of statistical methodologies in studies of the European Group for Blood and Marrow Transplantation. Bone Marrow Transpl. 2013;48:S1–37.

doi: 10.1038/bmt.2012.282

Domínguez-Almendros S, Benítez-Parejo N, Gonzalez-Ramirez AR. Logistic regression models. Allergologia et Immunopathologia. 2011;39:295–305.

doi: 10.1016/j.aller.2011.05.002 pubmed: 21820234

Yamashita T, Yamashita K, Kamimura R. A Stepwise AIC Method for Variable Selection in Linear Regression. Commun Stat - Theory Methods. 2007;36:2395–403.

doi: 10.1080/03610920701215639

Cortes C, Vapnik V. Support-vector networks. Mach Learn. 1995;20:273–97.

doi: 10.1007/BF00994018

Chen T, Guestrin C XGBoost: A Scalable Tree Boosting System. In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining [Internet]. San Francisco California USA: ACM; 2016 [cited 2023 Jul 14]. p. 785–94. Available from: https://doi.org/10.1145/2939672.2939785 .

Friedman J, Hastie T, Tibshirani R Regularization Paths for Generalized Linear Models via Coordinate Descent. J Stat Soft [Internet]. 2010 [cited 2023 Jul 14];33. Available from: http://www.jstatsoft.org/v33/i01/ .

R Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2021. http://www.R-project.org/ .

Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. J Chronic Dis. 1987;40:373–83.

doi: 10.1016/0021-9681(87)90171-8 pubmed: 3558716

Sorror ML. How I assess comorbidities before hematopoietic cell transplantation. Blood. 2013;121:2854–63.

doi: 10.1182/blood-2012-09-455063 pubmed: 23355537 pmcid: 3624933

Vaughn JE, Storer BE, Armand P, Raimondi R, Gibson C, Rambaldi A, et al. Design and Validation of an Augmented Hematopoietic Cell Transplantation-Comorbidity Index Comprising Pretransplant Ferritin, Albumin, and Platelet Count for Prediction of Outcomes after Allogeneic Transplantation. Biol Blood Marrow Transplant. 2015;21:1418–24.

doi: 10.1016/j.bbmt.2015.04.002 pubmed: 25862589 pmcid: 4506728

Potdar R, Varadi G, Fein J, Labopin M, Nagler A, Shouval R. Prognostic Scoring Systems in Allogeneic Hematopoietic Stem Cell Transplantation: Where Do We Stand? Biol Blood Marrow Transplant. 2017;23:1839–46.

doi: 10.1016/j.bbmt.2017.07.028 pubmed: 28797781

Luznik L, O’Donnell PV, Symons HJ, Chen AR, Leffell MS, Zahurak M, et al. HLA-haploidentical bone marrow transplantation for hematologic malignancies using nonmyeloablative conditioning and high-dose, posttransplantation cyclophosphamide. Biol Blood Marrow Transpl. 2008;14(Jun):641–50.

doi: 10.1016/j.bbmt.2008.03.005

Holmes HM, Des Bordes JKA, Kebriaei P, Yennu S, Champlin RE, Giralt S, et al. Optimal screening for geriatric assessment in older allogeneic hematopoietic cell transplantation candidates. J Geriatr Oncol. 2014;5:422–30.

doi: 10.1016/j.jgo.2014.04.004 pubmed: 24835889 pmcid: 4232495

Peña M, Salas MQ, Mussetti A, Moreno-Gonzalez G, Bosch A, Patiño B, et al. Pretransplantation EASIX predicts intensive care unit admission in allogeneic hematopoietic cell transplantation. Blood Adv. 2021;5:3418–26.

doi: 10.1182/bloodadvances.2021004812 pubmed: 34495311 pmcid: 8525231

Nitski O, Azhie A, Qazi-Arisar FA, Wang X, Ma S, Lilly L, et al. Long-term mortality risk stratification of liver transplant recipients: real-time application of deep learning algorithms on longitudinal data. Lancet Digital Health. 2021;3:e295–305.

doi: 10.1016/S2589-7500(21)00040-6 pubmed: 33858815