Hester, Laura

Abstract When using real-world data to construct an external comparator arm for a single-arm trial, there may be differences in how and when patients are assessed for disease between trial and real-world settings. Such differences can generate outcome measurement error when comparing time-to-event endpoints and lead to biased findings. Recent methods have been developed to mitigate measurement error bias in real-world endpoints; however, they rely on the existence of a validation sample, ie, data on a set of patients where both the “true” trial-like and “mis-measured” real-world measures are collected. We demonstrate how novel statistical methods can be leveraged as quantitative bias analyses (QBA) to contextualize real-world evidence findings when outcome measurement error is of concern, but validation samples are infeasible to collect. Quantitative bias analyses allow researchers to set plausible ranges for the amount of error when not directly measurable. We highlight how to conduct QBA with two recent methods, cumulative incidence curve correction and survival regression calibration, and illustrate how to generate plausible parameter values through simulation. We provide an illustrative QBA example in a cohort of real-world patients with newly diagnosed multiple myeloma and provide practical guidance to apply QBA for outcome measurement error and interpret results.

PURPOSE Teclistamab is initiated with a step-up dosing (SUD) schedule to mitigate the risk of cytokine release syndrome (CRS) and immune effector cell–associated neurotoxicity syndrome (ICANS). Early teclistamab users commonly received SUD in a hospital setting. This study aimed to evaluate safety and health care resource utilization (HRU) in real-world patients with multiple myeloma who initiated teclistamab SUD in an outpatient setting. METHODS This was a retrospective study using Mayo Clinic's electronic medical records from October 26, 2022, to October 31, 2023. Patient characteristics were summarized for all patients treated with teclistamab and separately for patients who started SUD outpatient. SUD pattern, safety, HRU, and post-SUD dosing schedule were described in patients with complete SUD. RESULTS At data cutoff, 65 patients received ≥1 teclistamab dose, including 58 patients who initiated SUD outpatient (median age, 69.2 years; male, 63.8%; White, 89.7%). Among 57 patients who completed SUD in an outpatient setting, all received premedications on the days of teclistamab administrations per label recommendation; 18 (31.6%) developed CRS (13 grade 1, four grade 2, and one grade 4) and two developed ICANS (one each with grade 2 and 4). All CRS and ICANS resolved with supportive care and all patients continued treatment. Eighteen patients were admitted to the hospital for CRS treatment, with a median CRS-related hospital stay of 2 days per admission. Most (60%) doses during SUD required <1 hour clinic time between administration and checkout. Post-SUD, clinic time for treatment doses decreased to <30 minutes for most doses (82%). CONCLUSION Outcomes of this study support outpatient administration as a safe and feasible option for teclistamab SUD to potentially reduce HRU and improve patient experiences.

Introduction: Progression-free survival (PFS), a common endpoint used in multiple myeloma (MM) trials, is defined as the time to the earliest occurrence of disease progression or death. Disease progression in MM is determined by the International Myeloma Working Group (IMWG) Uniform Response Criteria based on imaging and biomarkers from blood, urine, and bone marrow biopsy testing. In clinical trials, IMWG-recommended assessments are protocol-based. However, in routine care, they are often performed and recorded differently based on a multitude of factors. Algorithms to ascertain progression events using routinely collected biomarker data are important to classify disease progression and align with trial-defined endpoints. The aim of this study was to construct and evaluate an optimized real-world Progression (rwP) algorithm using real-world data (RWD) and demonstrate how biomarker data are captured and used to derive endpoints in routine practice. Method: A cohort of 270 transplant ineligible newly diagnosed MM (NDMM) patients starting on lenalidomide and dexamethasone (Rd) and meeting select MAIA (NCT02252172) trial eligibility criteria were included from the nationwide Flatiron Health electronic health record-derived deidentified database from 2015 to 2023. A rwP algorithm was developed using key IMWG-recommended biomarkers, including serum protein electrophoresis (SPEP), urine protein electrophoresis (UPEP), and serum free light chains (FLCs). The initial baseline value for each biomarker was identified, if available, during either the pre-treatment period (45 days prior through 7 days after first line treatment (1L) start) or the on-treatment period (8 days after 1L start through 1L end). Available biomarkers were followed for disease assessment. If any subsequent lab value during 1L treatment was less than the initial baseline value, the subsequent “on-treatment baseline” value was adopted as the new lowest value; otherwise, the initial value was used as the “on-treatment baseline” value for assessing progression events. Three hierarchies, which describe the order of utilizing key IMWG-recommended biomarkers to define rwP events, were explored, including: i) strict hierarchy (SH) [SPEP &gt; UPEP &gt; FLCs], ii) partial hierarchy (PH) [SPEP = UPEP &gt; FLCs], and iii) no hierarchy (NH) [SPEP = UPEP = FLCs]. The PH option closely resembles the IMWG criteria, with FLCs only used for rwP assessments when no measurable SPEP/UPEP are identified. The NH approach considers all available biomarkers equally and resembles how they are utilized in real-world clinical practice. The feasibility of requiring confirmatory events following the first suggestion of progression was also explored. Assays following the progression event up to the end of 1L were considered as confirmatory progression events if they met IMWG criteria. Results: We applied the rwP algorithm with each hierarchy to all eligible NDMM patients (N = 270). The SH, PH, and NH approaches respectively identified 106 (39.3%), 106 (39.3%), and 123 (45.6%) patients with progression events. Results from the SH and PH approach are consistent likely due to the rarity of UPEP usage in clinical practice. The NH approach captured more progression events because FLCs are used in the presence of measurable SPEP or UPEP, resulting in 73 progression events captured by FLCs in comparison to 32 from other approaches, potentially increasing false-positive capture due to the volatility of FLC results. Among the 106 PH-identified patients who progressed, 84 (79.2%) had IMWG-recommended tests following their progression event, and 74 (69.8%) had their progression confirmed before the end of 1L, with 35 (33.0%) receiving their confirmatory reading within 2 months after progression. These results suggest that requiring confirmatory testing as part of the rwP is feasible, though it may introduce false negatives for patients receiving clinical progression confirmation instead of getting confirmatory labs in routine clinical practice. Conclusion: We present a comprehensive assessment of important design choices for an rwP algorithm for NDMM, including a hierarchy of key assays and the inclusion of confirmatory testing. Further validation of the algorithm with health care provider assessments and the inclusion of bone marrow biopsy and imaging data is important for evaluating the performance of the algorithm in RWD.

Background Teclistamab, the first-in-class B-cell maturation antigen (BCMA) x CD3 bispecific therapy was recently approved by the FDA for the treatment of triple-class exposed relapsed or refractory multiple myeloma (MM) after ≥ 4 prior lines of therapy. Because of the risk of cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS), the step-up dosing (SUD) of teclistamab is commonly administered in an inpatient setting among early users. Mayo Clinic has a well-established hospital-based outpatient program for novel immunotherapies. Since the FDA approval, teclistamab SUD has been administered as part of this program. Each dose of the SUD is administered in an outpatient setting, and the patient is given a remote monitoring kit to regularly measure vital signs and stay connected with the command center for signs and symptoms of CRS and ICANS throughout the entire SUD period. This study aimed to evaluate early safety outcomes and healthcare resource utilization during SUD in real-world (RW) patients who initiated teclistamab under the outpatient administration model across 3 Mayo Clinic locations (Rochester, MN, Phoenix/Scottsdale, AZ, Jacksonville, FL). Methods This was a retrospective study using Mayo Clinic's electronic medical records from October 26, 2022 to June 12, 2023. Eligible patients were adults diagnosed with MM who had initiated commercial teclistamab at any of the 3 Mayo Clinic locations. Patient characteristics, rates and severity of CRS and ICANS, as well as healthcare resource utilization during SUD were described. Time between teclistamab administration and patient check-out was reported for SUD and treatment doses, respectively. Results At the time of data cutoff, 39 patients received at least 1 teclistamab dose across the 3 locations (median age 67.2 years; male: 74%; White: 87%; non-Hispanic: 92%), including 36 patients who initiated teclistamab SUD directly in an outpatient setting. A total of 8 (21%) patients had MM with high-risk cytogenetics and 14 (36%) had prior exposure to other BCMA-targeted therapies. Prevalent comorbidities prior to receiving teclistamab included anemia (77%), hypertension (56%), lytic bone lesions (51%), neutropenia (49%), and hypogammaglobulinemia (41%). Renal impairment or failure was observed in 31% of the patients (Table 1). Almost all patients received acetaminophen (95%), diphenhydramine (95%), and dexamethasone (92%) as pre-medications on the same day as teclistamab administrations during SUD. Of the teclistamab doses with clinic time data, the majority (62%) of doses during SUD required 30 minutes to 1 hour of clinic time for monitoring between administration and check-out. After SUD, the clinic time for weekly treatment doses decreased to less than 30 minutes for most (79%) doses (Figure 1). In patients who completed SUD by data cutoff (n = 37), most patients (70%) received the SUD on a 3-day dose interval (i.e., day 1, 4, 7). The mean time between the first and third doses was 6.3 days. Among the 37 patients with complete SUD, 12 (32%) developed CRS. The highest CRS grade was grade 1 for 10 patients; 1 patient had a grade 2 CRS, and 1 patient had a grade 4 CRS. The patient with grade 4 CRS concurrently decompensated during a dialysis session and all symptoms were considered for CRS grading. A total of 6 patients had recurrent CRS, including 1 patient with 3 events during SUD. All patients who developed CRS during SUD (n=12) were admitted to the hospital for treatment, with a total of 19 admissions across all patients and a median length of stay of 1.7 days per admission. Among patients who were admitted for CRS (n=12), the majority were treated with acetaminophen (92%), diphenhydramine (83%) and dexamethasone (83%); tocilizumab was given to the 2 patients with CRS grade 2 or higher. Only 1 ICANS event (grade 2) was observed in 1 patient during SUD, after dose 3, and the patient was admitted to the hospital for treatment. Conclusion This study evaluated early RW safety outcomes of teclistamab under an outpatient administration model and found the CRS rate and severity to be comparable with other RW evidence generated from various data sources. Outcomes related to teclistamab SUD from Mayo Clinic supported the safety and feasibility of outpatient administration model as a potential option to reduce healthcare resource utilization and improve treatment experiences.