title: Prediction of Hematopoietic Stem Cell Transplantation Related Mortality- Lessons Learned from the In-Silico Approach: A European Society for Blood and Marrow Transplantation Acute Leukemia Working Party Data Mining Study.
abstract: Models for prediction of allogeneic hematopoietic stem transplantation (HSCT) related mortality partially account for transplant risk. Improving predictive accuracy requires understating of prediction limiting factors, such as the statistical methodology used, number and quality of features collected, or simply the population size. Using an in-silico approach (i.e., iterative computerized simulations), based on machine learning (ML) algorithms, we set out to analyze these factors. A cohort of 25,923 adult acute leukemia patients from the European Society for Blood and Marrow Transplantation (EBMT) registry was analyzed. Predictive objective was non-relapse mortality (NRM) 100 days following HSCT. Thousands of prediction models were developed under varying conditions: increasing sample size, specific subpopulations and an increasing number of variables, which were selected and ranked by separate feature selection algorithms. Depending on the algorithm, predictive performance plateaued on a population size of 6,611-8,814 patients, reaching a maximal area under the receiver operator characteristic curve (AUC) of 0.67. AUCs' of models developed on specific subpopulation ranged from 0.59 to 0.67 for patients in second complete remission and receiving reduced intensity conditioning, respectively. Only 3-5 variables were necessary to achieve near maximal AUCs. The top 3 ranking variables, shared by all algorithms were disease stage, donor type, and conditioning regimen. Our findings empirically demonstrate that with regards to NRM prediction, few variables "carry the weight" and that traditional HSCT data has been "worn out". "Breaking through" the predictive boundaries will likely require additional types of inputs.
authors.affiliation: Division of Hematology and Bone Marrow Transplantation, The Chaim Sheba Medical Center, Tel-Hashomer, Ramat-Gan, Israel.|Internal medicine "F" Department and the 2013 Pinchas Borenstein Talpiot Medical Leadership Program, The Chaim Sheba Medical Center, Tel-Hashomer, Ramat-Gan, Israel.|The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan, Israel.
authors.forename: Roni
authors.initials: R
authors.lastname: Shouval
authors.affiliation: EBMT Paris Office, Hospital Saint Antoine, Paris, France.|Sorbonne Universités, UPMC Univ Paris 06, UMR_S 938, CDR Saint-Antoine, F-75012, Paris, France.|INSERM, UMR_S 938, CDR Saint-Antoine, F-75012, Paris, France.|AP-HP, Hématologie Clinique et Thérapie Cellulaire, Hôpital Saint-Antoine, Paris, France.
authors.forename: Myriam
authors.initials: M
authors.lastname: Labopin
authors.affiliation: The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan, Israel.
authors.forename: Ron
authors.initials: R
authors.lastname: Unger
authors.affiliation: Department of Bone Marrow Transplantation and Oncohematology, Maria Sklodowska-Curie Memorial Cancer Center and Institute of Oncology, Gliwice Branch, Gliwice, Poland.
authors.forename: Sebastian
authors.initials: S
authors.lastname: Giebel
authors.affiliation: Hematology and BMT Unit, San Raffaele Scientific Institute, Milan, Italy.
authors.forename: Fabio
authors.initials: F
authors.lastname: Ciceri
authors.affiliation: Department of Hematology and Oncology, Klinikum Augsburg, Ludwig-Maximilians-University, Munich, Germany.
authors.forename: Christoph
authors.initials: C
authors.lastname: Schmid
authors.affiliation: Hematology Department, IDIBAPS, Hospital Clínic, Barcelona, Spain.
authors.forename: Jordi
authors.initials: J
authors.lastname: Esteve
authors.affiliation: Hematology & GIGA research, University of Liège, Liège, Belgium.
authors.forename: Frederic
authors.initials: F
authors.lastname: Baron
authors.affiliation: EBMT Paris Office, Hospital Saint Antoine, Paris, France.
authors.forename: Norbert Claude
authors.initials: NC
authors.lastname: Gorin
authors.affiliation: Hematology & Stem Cell Transplantation Section, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America.
authors.forename: Bipin
authors.initials: B
authors.lastname: Savani
authors.affiliation: Division of Hematology and Bone Marrow Transplantation, The Chaim Sheba Medical Center, Tel-Hashomer, Ramat-Gan, Israel.
authors.forename: Avichai
authors.initials: A
authors.lastname: Shimoni
authors.affiliation: EBMT Paris Office, Hospital Saint Antoine, Paris, France.|Sorbonne Universités, UPMC Univ Paris 06, UMR_S 938, CDR Saint-Antoine, F-75012, Paris, France.|INSERM, UMR_S 938, CDR Saint-Antoine, F-75012, Paris, France.|AP-HP, Hématologie Clinique et Thérapie Cellulaire, Hôpital Saint-Antoine, Paris, France.
authors.forename: Mohamad
authors.initials: M
authors.lastname: Mohty
authors.affiliation: Division of Hematology and Bone Marrow Transplantation, The Chaim Sheba Medical Center, Tel-Hashomer, Ramat-Gan, Israel.|EBMT Paris Office, Hospital Saint Antoine, Paris, France.
authors.forename: Arnon
authors.initials: A
authors.lastname: Nagler
mesh_terms: D000328:Adult; D000465:Algorithms; D019540:Area Under Curve; D003198:Computer Simulation; D003625:Data Collection; D057225:Data Mining; D005060:Europe; D005260:Female; D018380:Hematopoietic Stem Cell Transplantation / Q000009:adverse effects*; D006801:Humans; D015470:Leukemia, Myeloid, Acute / Q000401:mortality* / Q000628:therapy*; D000069550:Machine Learning; D008297:Male; D008875:Middle Aged; D054198:Precursor Cell Lymphoblastic Leukemia-Lymphoma / Q000401:mortality* / Q000628:therapy*; D011237:Predictive Value of Tests; D012008:Recurrence; D012074:Remission Induction; D012189:Retrospective Studies; D012955:Societies, Medical; D019172:Transplantation Conditioning; D014184:Transplantation, Homologous