Personalized Timing for Allogeneic Stem-Cell Transplantation in Hematologic Neoplasms: A Target Trial Emulation Approach Using Multistate Modeling and Microsimulation

Author:

Gregorio Caterina123ORCID,Spreafico Marta4ORCID,D'Amico Saverio5ORCID,Sauta Elisabetta5ORCID,Asti Gianluca5ORCID,Lanino Luca56ORCID,Tentori Cristina Astrid56,Platzbecker Uwe7ORCID,Haferlach Torsten8,Diez-Campelo Maria9ORCID,Fenaux Pierre10,Komrokji Rami11ORCID,Della Porta Matteo Giovanni56ORCID,Ieva Francesca112

Affiliation:

1. MOX—Modelling and Scientific Computing Laboratory, Politecnico di Milano, Department of Mathematics, Milan, Italy

2. Biostatistics Unit, Department of Medical Sciences, University of Trieste, Trieste, Italy

3. Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden

4. Mathematical Institute, Leiden University, Leiden, the Netherlands

5. Humanitas Clinical and Research Center—IRCCS, Milan, Italy

6. Department of Biomedical Sciences, Humanitas University, Milan, Italy

7. Medical Clinic and Policlinic 1, Hematology and Cellular Therapy, University Hospital Leipzig, Leipzig, Germany

8. MLL Munich Leukemia Laboratory, Munich, Germany

9. Hematology Department, Hospital Universitario de Salamanca, Salamanca, Spain

10. Department of Hematology and Bone Marrow Transplantation, Hôpital Saint-Louis/Assistance Publique-Hôpitaux de Paris (AP-HP)/University Paris 7, Paris, France

11. Department of Malignant Hematology, H. Lee Moffitt Cancer Center, Tampa, FL

12. HDS, Health Data Science Center, Human Technopole, Milan, Italy

Abstract

PURPOSE Decision about the optimal timing of a treatment procedure in patients with hematologic neoplasms is critical, especially for cellular therapies (most including allogeneic hematopoietic stem-cell transplantation [HSCT]). In the absence of evidence from randomized trials, real-world observational data become beneficial to study the effect of the treatment timing. In this study, a framework to estimate the expected outcome after an intervention in a time-to-event scenario is developed, with the aim of optimizing the timing in a personalized manner. METHODS Retrospective real-world data are leveraged to emulate a target trial for treatment timing using multistate modeling and microsimulation. This case study focuses on myelodysplastic syndromes, serving as a prototype for rare cancers characterized by a heterogeneous clinical course and complex genomic background. A cohort of 7,118 patients treated according to conventional available treatments/evidence across Europe and United States is analyzed. The primary clinical objective is to determine the ideal timing for HSCT, the only curative option for these patients. RESULTS This analysis enabled us to identify the most appropriate time frames for HSCT on the basis of each patient's unique profile, defined by a combination relevant patients' characteristics. CONCLUSION The developed methodology offers a structured framework to address a relevant clinical issue in the field of hematology. It makes several valuable contributions: (1) novel insights into how to develop decision models to identify the most favorable HSCT timing, (2) evidence to inform clinical decisions in a real-world context, and (3) the incorporation of complex information into decision making. This framework can be applied to provide medical insights for clinical issues that cannot be adequately addressed through randomized clinical trials.

Publisher

American Society of Clinical Oncology (ASCO)

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