Predictive markers of response and toxicity to tarlatamab in patients with extensive stage small cell lung cancer: a multi-institutional real-world analysis
Fenton, G.; Guo, W.; Hess, D. L.; Zhang, A. L.; Tatsuoka, C.; Green, A. L.; Sittig, M.; Mehra, R.; Simms, A.; Dowlati, A.; Owonikoko, T. K.; Hsu, M.; Alder, L.; Rosner, S.
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Purpose Tarlatamab, a bispecific T-cell engager, has generated favorable response and survival outcomes in relapsed small cell lung cancer (SCLC). Factors influencing tarlatamab-associated treatment outcomes and toxicity have yet to be established. We performed a multivariate analysis to identify biomarkers associated with cytokine release syndrome (CRS) and immune effector cell associated neurotoxicity syndrome (ICANS) and integrated these variables into a novel risk stratification tool to identify patients at high risk of clinically significant toxicity. Patients and Methods Logistic and ordinal regression analyses evaluated the predictive value of variables contributing to the presence and severity, respectively, of CRS and ICANS in 115 patients with ES-SCLC receiving tarlatamab. Selected variables were then tuned using 5-fold cross-validation and incorporated into novel elastic net-based prediction models. Results Rates of observed CRS, ICANS, and dysgeusia were 46%, 28%, and 47%, respectively. ORR (overall response rate) and DCR (disease control rate) were 44% and 58.2%, while 6-month PFS (progression free survival) and OS (overall survival) rates were 30.4% and 54.9%, respectively. Excluding patients on tarlatamab <30 days, presence of dysgeusia was associated with a lower rate of disease progression (HR 0.44, p=0.00691) and death (HR 0.34, p=0.0145). The presence of, increased size and number of extracranial metastases as well as elevated baseline LDH were significantly associated with increased likelihood of CRS. Increased ECOG performance status, increased volume of brain metastases, development of CRS, and elevated baseline LDH were all associated with increased risk of developing ICANS. Our cross-validated risk model successfully predicted CRS grade [≥]2 and ICANS events with 90.9% and 75% sensitivity, respectively. Conclusions This exploratory analysis identified several predictive biomarkers of toxicity that successfully stratified low and high-risk populations as part of an internally validated novel risk scoring tool.
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