ArticleCPT: pharmacometrics & systems pharmacology2024
Modeling serum M-protein response for early detection of biochemical relapse in myeloma patients treated with bortezomib, lenalidomide and dexamethasone.
Article in CPT: pharmacometrics & systems pharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01454297 (A Prospective, Longitudinal, Observational Study in Newly Diagnosed Multiple Myeloma), which is not on this map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
A Prospective, Longitudinal, Observational Study in Newly Diagnosed Multiple Myeloma (MM) Patients to Assess the Relationship Between Patient Outcomes, Treatment Regimens and Molecular Profiles
Who cites it
3 citing papers in PubMed.
- PK-PD Modeling Suggests Tumor Heterogeneity Limits Preclinical to Clinical Translation of Enzalutamide in Prostate Cancer.Pharmaceutical research · 2026Article
- Comparative Molecular Insights and Computational Modeling of Multiple Myeloma and Osteosarcoma.International journal of molecular sciences · 2026Review
- Modeling serum M-protein response for early detection of biochemical relapse in myeloma patients treated with bortezomib, lenalidomide and dexamethasone.CPT: pharmacometrics & systems pharmacology · 2024Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Multiple myeloma (MM) treatment guidelines recommend waiting for formal progression criteria (FPC) to be met before proceeding to the next line of therapy. As predicting progression may allow early switching to next-line therapy while the disease burden is relatively low, we evaluated the predictive accuracy of a mathematical model to anticipate relapse 180 days before the FPC is met. A subset of 470/1143 patients from the IA16 dataset who were initially treated with VRd (Velcade (bortezomib), Revlimid (lenalidomide), and dexamethasone) in the CoMMpass study (NCT01454297) were randomly split 2:1 into training and testing sets. A model of M-protein dynamics was developed using the training set and used to predict relapse probability in patients in the testing set given their response histories up to 12 or more months of treatment. The predictive accuracy of this model and M-protein "velocity" were assessed via receiver operating characteristics (ROC) analysis. The final model was a two-population tumor growth inhibition model with additive drug effect and transit delay compartments for cell killing. The ROC area under the curve value of relapse prediction 180 days ahead of observed relapse by FPC was 0.828 using at least 360 days of response data, which was superior to the M-protein velocity ROC score of 0.706 under the same conditions. The model can predict future relapse from early M-protein responses and can be used in a future clinical trial to test whether early switching to second-line therapy results in better outcomes in MM.
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