Comparative Efficacy of Teclistamab Versus Current Treatments in Real-World Clinical Practice in the Prospective LocoMMotion Study in Patients with Triple-Class-Exposed Relapsed and/or Refractory Multiple Myeloma.

INTRODUCTION: Patients with triple-class-exposed relapsed/refractory multiple myeloma (TCE-RRMM) have a poor prognosis and limited treatment options. Teclistamab, a B-cell maturation antigen × CD3 bispecific antibody, was studied in patients with TCE-RRMM in the single-arm MajesTEC-1 study. To assess the relative effectiveness of teclistamab versus real-world physician's choice of therapy (RWPC), adjusted comparisons were performed using individual patient data from MajesTEC-1 and LocoMMotion, a prospective study of patients with TCE-RRMM. METHODS: An external control arm for MajesTEC-1 was created from patients in LocoMMotion (n = 248; clinical cut-off: November 2, 2021) and compared with treated patients (n = 165) from MajesTEC-1 (teclistamab 1.5 mg/kg weekly; clinical cut-off: March 16, 2022). Inverse probability weighting was used to adjust for imbalances in baseline covariates. For binary endpoints [overall response rate (ORR), very good partial response or better (≥ VGPR) rate, complete response or better (≥ CR)], relative effect of teclistamab versus RWPC was estimated with an odds ratio and relative response rate and 95% confidence interval (CI), derived from weighted logistic regression. Weighted Cox proportional hazards model was used to estimate hazard ratios (HR) and 95% CIs for time-to-event endpoints [duration of response (DOR), progression-free survival (PFS), and overall survival (OS)]. RESULTS: After weighting, baseline characteristics were balanced across cohorts. In adjusted comparisons, teclistamab-treated patients were 2.3-fold, 5.2-fold and 148.3-fold, more likely to reach ORR [response-rate ratio (RR) = 2.31, 95% CI 1.77-2.85, p < 0.0001], ≥ VGPR (RR = 5.19, 95% CI 3.26-7.12, p < 0.0001) and ≥ CR (RR = 148.25, 95% CI 20.63-1065.40, p < 0.0001), respectively, versus patients receiving RWPC. Following adjustment, DOR (HR 0.32, 95% CI 0.19-0.54, p < 0.0001) and PFS (HR 0.48, 95% CI 0.35-0.65, p < 0.0001) were significantly longer with teclistamab versus RWPC. OS was numerically better with teclistamab versus RWPC [HR 0.77 (0.55-1.09), p = 0.1419]. CONCLUSION: Teclistamab demonstrated improved effectiveness versus RWPC, highlighting its clinical benefit as a novel and effective treatment for patients with TCE-RRMM. TRIAL REGISTRATION: Majest TEC-1, ClinicalTrials.gov NCT04557098; LocoMMotion, ClinicalTrials.gov NCT04035226.

A registry study of relapsed or refractory multiple myeloma pre-exposed to three or more prior therapies including a proteasome inhibitor, an immunomodulatory agent and CD38-targeted monoclonal antibody therapy in England.

Some patients with multiple myeloma are receiving treatment in clinical practice in England after prior exposure to a proteasome inhibitor, an immunomodulatory agent, and an anti-CD38 monoclonal antibody. We investigated the characteristics of these patients, their outcomes, and the salvage therapies they received using the national cancer registry for England and linked healthcare data. After a median follow-up time of 6.4 months from T 0, median overall survival and time to next treatment were 8.2 and 5.3 months, respectively. This real-world data provide useful clinical insight into a little-studied patient population and highlight the poor outcomes in the UK setting.

Population Adjustment Methods for Indirect Comparisons: A Review of National Institute for Health and Care Excellence Technology Appraisals.

OBJECTIVES: Indirect comparisons via a common comparator (anchored comparisons) are commonly used in health technology assessment. However, common comparators may not be available, or the comparison may be biased due to differences in effect modifiers between the included studies. Recently proposed population adjustment methods aim to adjust for differences between study populations in the situation where individual patient data are available from at least one study, but not all studies. They can also be used when there is no common comparator or for single-arm studies (unanchored comparisons). We aim to characterise the use of population adjustment methods in technology appraisals (TAs) submitted to the United Kingdom National Institute for Health and Care Excellence (NICE). METHODS: We reviewed NICE TAs published between 01/01/2010 and 20/04/2018. RESULTS: Population adjustment methods were used in 7 percent (18/268) of TAs. Most applications used unanchored comparisons (89 percent, 16/18), and were in oncology (83 percent, 15/18). Methods used included matching-adjusted indirect comparisons (89 percent, 16/18) and simulated treatment comparisons (17 percent, 3/18). Covariates were included based on: availability, expert opinion, effective sample size, statistical significance, or cross-validation. Larger treatment networks were commonplace (56 percent, 10/18), but current methods cannot account for this. Appraisal committees received results of population-adjusted analyses with caution and typically looked for greater cost effectiveness to minimise decision risk. CONCLUSIONS: Population adjustment methods are becoming increasingly common in NICE TAs, although their impact on decisions has been limited to date. Further research is needed to improve upon current methods, and to investigate their properties in simulation studies.