POSB301 Development of a Sequencing Model Using Patient-Level Data to Optimize Patient Outcomes in Multiple Myeloma

Mendes, J. Pinto; Boer, JH; Casamassima, G; Willis, Anna; Matthijsse, Suzette M.; Armeni, Patrizio

doi:10.1016/j.jval.2021.11.985

Value in Health

2022

DOI: 10.1016/j.jval.2021.11.985

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POSB301 Development of a Sequencing Model Using Patient-Level Data to Optimize Patient Outcomes in Multiple Myeloma

J. Pinto Mendes¹,

JH Boer²,

G Casamassima

et al.

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2024

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Improving Health Outcomes Through Treatment Sequencing Optimization in Multiple Myeloma: A Simulation Model in Transplant‐Ineligible Patients

Geraldes,

Neves,

Bergantim

et al. 2024

Cancer Reports

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ObjectivesPatients with multiple myeloma often require multiple treatment lines. The order in which treatments are sequenced has impact on clinical outcomes. This study aimed to estimate progression‐free survival (PFS) and overall survival (OS) with common treatment sequences used in Portugal and the incremental benefit of an optimal sequence in transplant‐ineligible patients with multiple myeloma.MethodsA state‐transition sequential model with a five‐health state conceptual structure was developed to simulate and compare survival outcomes between treatment sequences up to four lines of treatments. Data sources included randomized clinical trials and indirect treatment comparisons. A panel of Portuguese hematologists listed four most common treatment sequences and optimal sequence of choice in transplant‐ineligible patients.ResultsOur simulation estimated an OS between 6.1 and 7.8 years using the most common sequences, with VMP + DRd + Pd + Kd as the most effective (7.8 years). Optimal sequence of choice (DRd + PVd + Kd + Vd) achieved OS of 9.8 years and may extend OS in 2.0–3.7 years vs. most common sequences (26%–61% increase). This benefit was mostly explained by extended PFS in the first line of treatment.ConclusionModel results demonstrate that choosing the most effective treatment upfront is crucial in delaying disease progression thus yielding better survival outcomes in transplant‐ineligible patients. There was a clear survival benefit in using daratumumab‐based regimens in first line. This modelling exercise highlights the need to raise awareness around the impact of sequencing strategies to improve patient's outcomes.

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Improving Health Outcomes Through Treatment Sequencing Optimization in Multiple Myeloma: A Simulation Model in Transplant‐Ineligible Patients

Geraldes,

Neves,

Bergantim

et al. 2024

Cancer Reports

View full text Add to dashboard Cite

show abstract

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POSB301 Development of a Sequencing Model Using Patient-Level Data to Optimize Patient Outcomes in Multiple Myeloma

Cited by 1 publication

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Improving Health Outcomes Through Treatment Sequencing Optimization in Multiple Myeloma: A Simulation Model in Transplant‐Ineligible Patients

Improving Health Outcomes Through Treatment Sequencing Optimization in Multiple Myeloma: A Simulation Model in Transplant‐Ineligible Patients

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