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Predicting treatment benefit in multiple myeloma through simulation of alternative treatment effects.

ABSTRACT: Many cancer treatments are associated with serious side effects, while they often only benefit a subset of the patients. Therefore, there is an urgent clinical need for tools that can aid in selecting the right treatment at diagnosis. Here we introduce simulated treatment learning (STL), which enables prediction of a patient's treatment benefit. STL uses the idea that patients who received different treatments, but have similar genetic tumor profiles, can be used to model their response to the alternative treatment. We apply STL to two multiple myeloma gene expression datasets, containing different treatments (bortezomib and lenalidomide). We find that STL can predict treatment benefit for both; a twofold progression free survival (PFS) benefit is observed for bortezomib for 19.8% and a threefold PFS benefit for lenalidomide for 31.1% of the patients. This demonstrates that STL can derive clinically actionable gene expression signatures that enable a more personalized approach to treatment.

SUBMITTER: Ubels J

PROVIDER: S-EPMC6063966 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

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Predicting treatment benefit in multiple myeloma through simulation of alternative treatment effects.

Ubels Joske J Sonneveld Pieter P van Beers Erik H EH Broijl Annemiek A van Vliet Martin H MH de Ridder Jeroen J

Nature communications 20180727 1

Many cancer treatments are associated with serious side effects, while they often only benefit a subset of the patients. Therefore, there is an urgent clinical need for tools that can aid in selecting the right treatment at diagnosis. Here we introduce simulated treatment learning (STL), which enables prediction of a patient's treatment benefit. STL uses the idea that patients who received different treatments, but have similar genetic tumor profiles, can be used to model their response to the a ...[more]

PMID: 30054467

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Project description:Attaining undetectable minimal residual disease (MRD) is the current therapeutic goal for multiple myeloma. But there is a current lack of data regarding the clinical benefit of autologous stem cell transplantation (ASCT) for patients with myeloma achieving early MRD-negative status after induction treatment, in addition to the interaction of longitudinal MRD status with ASCT. The current study included 407 patients with transplant-eligible multiple myeloma with available MRD status from the National Longitudinal Cohort of Hematological Diseases in China (NCT04645199), of whom 147 (34.4%) achieved early undetectable MRD and 182 (44.7%) received ASCT. Early MRD-negative status was associated with a lower risk of disease progression [HR = 0.447; 95% confidence interval (CI), 0.333-0.600; P < 0.001] and death (HR = 0.473; 95% CI, 0.320-0.700; P < 0.001). Of note, patients who achieved undetectable MRD early still benefitted from ASCT, with a remarkable improvement in the median MRD-negative duration (33.5-58.0 months, P < 0.001), progression-free survival (PFS; 46.0-88.3 months, P < 0.001), and overall survival (OS; 76.4 months to not reached, P = 0.003). These clinical benefits were more pronounced in patients with aggressive features (high-risk cytogenetic abnormalities or high tumor burden) compared with standard-risk patients. Similar results were observed in patients with detectable MRD after induction treatment. In addition, we identified four MRD-status transformation patterns following ASCT, which were strongly correlated with diverse survival outcomes (P < 0.001). Our study revealed the enhanced clinical significance of ASCT in patients with transplant-eligible myeloma, regardless of early MRD status, particularly for high-risk patients. Subsequent prospective trials are essential to validate these observations.SignificanceAchieving and maintaining undetectable MRD is the current treatment goal for multiple myeloma. Our results emphasized the remarkable clinical benefit of ASCT on MRD-negative duration, PFS, and OS in patients with multiple myeloma regardless of early MRD status. These favorable impacts were more evident in patients with aggressive features. Importantly, dynamic MRD monitoring among ASCT could facilitate personalized stratification of therapeutic approaches.

Dataset Information

Predicting treatment benefit in multiple myeloma through simulation of alternative treatment effects.

Publications

Predicting treatment benefit in multiple myeloma through simulation of alternative treatment effects.

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