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1879 Mathematical Models for Early Detection of Relapse in Multiple Myeloma Patients Treated with Bortezomib/Lenalidomide/Dexamethasone

Program: Oral and Poster Abstracts
Session: 652. Multiple Myeloma and Plasma Cell Dyscrasias: Clinical and Epidemiological: Poster I
Hematology Disease Topics & Pathways:
Research, Clinical Research, Plasma Cell Disorders, Combination therapy, Diseases, real-world evidence, Therapies, Lymphoid Malignancies, Technology and Procedures, Serologic Tests
Saturday, December 10, 2022, 5:30 PM-7:30 PM

Yuki Otani, MD, PhD1*, Dean Bottino, PhD2*, Neeraj Gupta3*, Majid Vakilynejad, PhD4* and Yusuke Tanigawara, PhD5*

1Department of Anesthesiology and Perioperative Medicine, University of Pittsburgh, Pittsburgh, PA
2Takeda Development Center Americas Inc. (TDCA), Lexington, MA
3Takeda Development Center Americas, Inc. (TDCA), Lexington, MA
4Takeda Deveopment Center Americas Inc. (TDCA), Lexington, MA
5Keio Frontier Research & Education Collaborative Square (K-FRECS), Tokyo, Japan

Background: Multiple Myeloma (MM, an incurable bone marrow plasma cell malignancy, is the second most common hematological malignancy in the United States. The introduction of novel triplet-based induction therapy with bortezomib (Bor), lenalidomide (Len), and dexamethasone (Dex) has shown excellent results in several large, randomized phase III trials and is considered a standard of care for newly diagnosed MM (1-3). The question lies at which timing a clinician should move from VRd combination therapy to auto-HCT and sequential second-line therapy. Guidelines recommend waiting for International Myeloma Working Group Uniform Response Criteria (IMWG Criteria) to be met before proceeding to the next line of therapy. A tool to anticipate progression before IMWG Criteria may allow early switch to the next line therapy while the disease burden is relatively low (4). We aimed to evaluate predictive accuracy of a mathematical model to anticipate relapse 6 months before the IMWG Criteria are met.

Methods: Four hundred seventy patients initially treated with a subset of VRd and with ≥ 3 serum M-protein values prior to auto-HCT, including one baseline value ≥ 0.5g/dL in the CoMMpass study (IA16) and were randomly split 2:1 into training and testing sets. A model of M-protein dynamics was developed using the training set. By fitting the model to each observation window in the testing set, distribution of future response trajectories was created for the whole population utilizing Bayesian parameter estimation, and by combining all the M-protein estimated trajectories, Receiver Operating Characteristics (ROC) curve was generated. As a comparator, we also tested most M-protein “velocity” through the two most recent time points as a predictor.

Results: The two-population tumor growth inhibition model with additive drug effect and transit model for cell killing was identified to be the best model for both training and testing set. The model identified baseline R-ISS staging on M-protein baseline (M0), 1st response treatment outcome of first 2 cycles, which we will gain information before 3 months protein value data are gained, on frequency of resistant cell population (ϕ), and existence of t(4;14) mutation-positive cells on resistant cell function (dRes/dt) as the best predictor of serum M-protein kinetics. The ROC area under the curve (AUC) value of relapse prediction 180 days ahead of observed relapse by FPC was 0.829 with sensitivity and specificity both of 78% using an observation time of least 360 days, which was superior to the M-protein velocity ROC score of 0.713 under the same conditions (Fig 1B). ROC AUC continues to improve, and maintains its advantage over M-protein velocity, with each additional 90 days of observation time.

Conclusion: The individualized model-based approach from data within the first 9 or more months of VRd treatment could provide prospective and reasonable predictions of future M-protein trajectories in individuals with MM. It allowed predictions for personalized “progression free” curve under various treatment scenarios. This model may enable a future study testing the difference in patient outcomes when treatment is switched when relapse is imminent versus already occurred.


(1) Rosiñol, L. et al. Bortezomib, lenalidomide, and dexamethasone as induction therapy prior to autologous transplant in multiple myeloma. Blood 134, 1337-45 (2019).

(2) Durie, B.G.M. et al. Bortezomib with lenalidomide and dexamethasone versus lenalidomide and dexamethasone alone in patients with newly diagnosed myeloma without intent for immediate autologous stem-cell transplant (SWOG S0777): a randomised, open-label, phase 3 trial. Lancet 389, 519-27 (2017).

(3) Attal, M. et al. Lenalidomide, Bortezomib, and Dexamethasone with Transplantation for Myeloma. N Engl J Med 376, 1311-20 (2017).

(4) Jackson, G. et al. Response-adapted intensification with cyclophosphamide, bortezomib, and dexamethasone versus no intensification in patients with newly diagnosed multiple myeloma (Myeloma XI): a multicentre, open-label, randomised, phase 3 trial. Lancet Haematol. 6, e616-29 (2019).

Disclosures: Otani: Takeda Development Center Americas Inc.: Research Funding. Bottino: Takeda Development Center Americas Inc.: Current Employment, Current equity holder in publicly-traded company. Gupta: Takeda Development Center Americas, Inc.: Current Employment, Current equity holder in publicly-traded company. Vakilynejad: Takeda Development Center Americas Inc.: Current Employment, Current equity holder in publicly-traded company. Tanigawara: Takeda Development Center Americas Inc.: Research Funding.

*signifies non-member of ASH