Artificial Intelligence Methods to Estimate Overall Mortality and Non-Relapse Mortality Following Allogeneic Hct in the Modern Era: An Ebmt-Tcwp Study

Artificial Intelligence Methods to Estimate Overall Mortality and Non-Relapse Mortality Following Allogeneic Hct in the Modern Era: An Ebmt-Tcwp Study Publisher Pubmed

Mussetti A¹ ; Riussansalvador B^{2, 3} ; Moreno V^{2, 3} ; Peczynski C⁴ ; Polge E⁵ ; Galimard JE⁶ ; Kroger N⁷ ; Blaise D⁸ ; Peffault De Latour R^{9, 10} ; Kulagin A¹¹ ; Mousavi A¹² ; Stelljes M¹³ ; Hamladji RM¹⁴ ; Middeke JM¹⁵ Show All Authors

Mussetti A¹
Riussansalvador B^{2, 3}
Moreno V^{2, 3}
Peczynski C⁴
Polge E⁵
Galimard JE⁶
Kroger N⁷
Blaise D⁸
Peffault De Latour R^{9, 10}
Kulagin A¹¹
Mousavi A¹²
Stelljes M¹³
Hamladji RM¹⁴
Middeke JM¹⁵
Salmenniemi U¹⁶
Sengeloev H¹⁷
Forcade E¹⁸
Platzbecker U¹⁹
Remenyi P²⁰
Angelucci E²¹
Chevallier P²²
Yakoubagha I²³
Craddock C²⁴
Ciceri F²⁵
Schroeder T²⁶
Aljurf M²⁷
Ch K²⁸
Moiseev I²⁹
Penack O³⁰
Schoemans H^{31, 32}
Mohty M³³
Glass B³⁴
Sureda A¹
Basak G³⁵
Peric Z³⁶

Show Affiliations

1. Department of Haematology, Institut Catala dâ€™Oncologia - Hospitalet, IDIBELL, University of Barcelona, Barcelona, Spain
2. Biomarkers and Susceptibility Unit (UBS), Oncology Data Analytics Program (ODAP), Catalan Institute of Oncology (ICO), Lâ€™Hospitalet del Llobregat, Barcelona, Spain
3. ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), Lâ€™Hospitalet de Llobregat, Barcelona, Spain
4. EBMT Paris Study Office, Department of Haematology, Saint Antoine Hospital, INSERM Unite Mixte de Recherche (UMR)-S 938, Sorbonne University, Paris, France
5. EBMT Global Committee (Shanghai and Paris Offices) and Acute Leukaemia Working Party, Hospital Saint-Antoine APHP and Sorbonne University, Paris, France
6. EBMT, Statistics Unit, Paris, France
7. Department of Stem Cell Transplantation, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
8. Programme de Transplantation & Therapie Cellulaire, Centre de Recherche en Cancerologie de Marseille, Institut Paoli Calmettes, Marseille, France
9. Service dâ€™Hematologie-Greffe, Hopital Saint-Louis, Assistance Publique-Hopitaux de Paris (APHP), Paris, France
10. Universite Paris Diderot, Institut Universitaire dâ€™Hematologie, Sorbonne Paris Cite, Paris, France
11. Raisa Memorial (RM) Gorbacheva Research Institute, Pavlov University, St. Petersburg, Russian Federation
12. Shariati Hospital, Haematology-Oncology and BMT Research, Tehran, Iran
13. Department of Medicine A, University Hospital Munster, Munster, Germany
14. Centre Pierre et Marie Curie, Service Hematologie Greffe de Moelle, Alger, Algeria
15. Med. Klinik I, University Hospital, TU Dresden, Germany
16. HUCH Comprehensive Cancer Center, Stem Cell Transplantation Unit, Helsinki, Finland
17. Bone Marrow Transplant Unit Copenhagen, Department of Haematology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
18. CHU Bordeaux, Service dâ€™hematologie Clinique et Therapie Cellulaire, Pessac, 33000, France
19. University Hospital Leipzig, Leipzig, Germany
20. Department of Haematology and Stem Cell Transplant, Del-pesti Centrumkorhaz - Orszagos Hematologiai es Infektologiai Intezet, Budapest, Hungary
21. Haematology and Cellular Therapy Unit. IRCCS Ospedale Policlinico San Martino, Genova, Italy
22. CHU Nantes, Nantes, France
23. CHU de Lille LIRIC, INSERM U995, Universite de Lille, Lille, France
24. Department of Haematology, University Hospital Birmingham NHS Trust, Queen Elizabeth Medical Centre, Edgbaston, Birmingham, United Kingdom
25. Haematology & Bone Marrow Transplant, IRCCS San Raffaele Scientific Institute, Milan, Italy
26. Department of Bone Marrow Transplantation, University Hospital, Essen, Germany
27. Oncology Center, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
28. Hannover Medical School, Hannover, Germany
29. R.M.Gorbacheva Memorial Institute of Oncology, Haematology and Transplantation, Pavlov First Saint Petersburg State Medical University, Saint-Petersburg, Russian Federation
30. Department of Haematology, Charite Universitatsmedizin Berlin, Berlin, Germany
31. Department of Haematology, University Hospitals Leuven, Leuven, Belgium
32. Department of Public Health and Primary Care, ACCENT VV, KU Leuven - University of Leuven, Leuven, Belgium
33. Department of Haematology, Saint Antoine Hospital, INSERM UMR 938, Sorbonne University, Paris, France
34. Klinik fur Hamatologie und Stammzelltransplantation, HELIOS Klinikum Berlin-Buch, Berlin, Germany
35. Department of Haematology, Transplantation and Internal Medicine, Medical University of Warsaw, Warsaw, Poland
36. School of medicine, University of Zagreb and University Hospital Centre Zagreb, Zagreb, Croatia

Source: Bone Marrow Transplantation Published:2024

Abstract

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. © The Author(s), under exclusive licence to Springer Nature Limited 2023.

2. The Impact of Malnutrition on Mortality and Complications of Hematopoietic Stem Cell Transplantation in Patients With Acute Leukemia, Clinical Nutrition (2023)

3. A Threshold-Free Summary Index for Quantifying the Capacity of Covariates to Yield Efficient Treatment Rules, Statistics in Medicine (2020)

4. Outcomes of Allogeneic Hematopoietic Stem Cell Transplantation in Patients Aged 70 Years and Older: A Systematic Review and Meta-Analysis, Transplantation and Cellular Therapy (2025)

5. International Retrospective Study of Allogeneic Hematopoietic Cell Transplantation for Activated Pi3k-Delta Syndrome, Journal of Allergy and Clinical Immunology (2022)

6. Comparing Different Propensity Score Estimation Methods for Estimating the Marginal Causal Effect Through Standardization to Propensity Scores, Communications in Statistics: Simulation and Computation (2018)

7. Outcomes of Hematopoietic Stem Cell Transplantation From Unmanipulated Haploidentical Versus Matched Sibling Donor in Patients With Acute Myeloid Leukemia in First Complete Remission With Intermediate or High-Risk Cytogenetics: A Study From the Acute Leukemia Working Party of the European Society for Blood and Marrow Transplantation, Haematologica (2018)

8. Human Milk Fungi: Environmental Determinants and Inter-Kingdom Associations With Milk Bacteria in the Child Cohort Study, BMC Microbiology (2020)

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Style	Citing Format
MLA	Mussetti A, et al.. "Artificial Intelligence Methods to Estimate Overall Mortality and Non-Relapse Mortality Following Allogeneic Hct in the Modern Era: An Ebmt-Tcwp Study." Bone Marrow Transplantation, vol. 59, no. 2, 2024, pp. 232-238.
APA	Mussetti A, Riussansalvador B, Moreno V, Peczynski C, Polge E, Galimard JE, Kroger N, Blaise D, Peffault De Latour R, Kulagin A, Mousavi A, Stelljes M, Hamladji RM, Middeke JM, Salmenniemi U, Sengeloev H, Forcade E, Platzbecker U, Remenyi P, ... Peric Z (2024). Artificial Intelligence Methods to Estimate Overall Mortality and Non-Relapse Mortality Following Allogeneic Hct in the Modern Era: An Ebmt-Tcwp Study. Bone Marrow Transplantation, 59(2), 232-238.
Chicago	Mussetti A, Riussansalvador B, Moreno V, Peczynski C, Polge E, Galimard JE, Kroger N, et al.. "Artificial Intelligence Methods to Estimate Overall Mortality and Non-Relapse Mortality Following Allogeneic Hct in the Modern Era: An Ebmt-Tcwp Study." Bone Marrow Transplantation 59, no. 2 (2024): 232-238.
Harvard	Mussetti A et al. (2024) 'Artificial Intelligence Methods to Estimate Overall Mortality and Non-Relapse Mortality Following Allogeneic Hct in the Modern Era: An Ebmt-Tcwp Study', Bone Marrow Transplantation, 59(2), pp. 232-238.
Vancouver	Mussetti A, Riussansalvador B, Moreno V, Peczynski C, Polge E, Galimard JE, et al.. Artificial Intelligence Methods to Estimate Overall Mortality and Non-Relapse Mortality Following Allogeneic Hct in the Modern Era: An Ebmt-Tcwp Study. Bone Marrow Transplantation. 2024;59(2):232-238.
BibTex	@article{ author = {Mussetti A and Riussansalvador B and Moreno V and Peczynski C and Polge E and Galimard JE and Kroger N and Blaise D and Peffault De Latour R and Kulagin A and Mousavi A and Stelljes M and Hamladji RM and Middeke JM and Salmenniemi U and Sengeloev H and Forcade E and Platzbecker U and Remenyi P and Angelucci E and Chevallier P and Yakoubagha I and Craddock C and Ciceri F and Schroeder T and Aljurf M and Ch K and Moiseev I and Penack O and Schoemans H and Mohty M and Glass B and Sureda A and Basak G and Peric Z}, title = {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}, volume = {59}, number = {2}, pages = {232-238}, year = {2024} }
RIS	TY - JOUR AU - Mussetti A AU - Riussansalvador B AU - Moreno V AU - Peczynski C AU - Polge E AU - Galimard JE AU - Kroger N AU - Blaise D AU - Peffault De Latour R AU - Kulagin A AU - Mousavi A AU - Stelljes M AU - Hamladji RM AU - Middeke JM AU - Salmenniemi U AU - Sengeloev H AU - Forcade E AU - Platzbecker U AU - Remenyi P AU - Angelucci E AU - Chevallier P AU - Yakoubagha I AU - Craddock C AU - Ciceri F AU - Schroeder T AU - Aljurf M AU - Ch K AU - Moiseev I AU - Penack O AU - Schoemans H AU - Mohty M AU - Glass B AU - Sureda A AU - Basak G AU - Peric Z TI - Artificial Intelligence Methods to Estimate Overall Mortality and Non-Relapse Mortality Following Allogeneic Hct in the Modern Era: An Ebmt-Tcwp Study JO - Bone Marrow Transplantation VL - 59 IS - 2 SP - 232 EP - 238 PY - 2024 ER -

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