The maximum tumor growth rate predicts clinical outcomes of patients with small-cell lung cancer undergoing first-line chemotherapy plus immune-checkpoint inhibitor therapy.

Abstract

Currently, no biomarkers can accurately predict survival outcomes in patients with SCLC undergoing treatment. Tumor growth rate (TGR; percent size change per month [%/m]) is suggested as an imaging predictor of response to anti-cancer treatment. We aimed to evaluate the predictive role of the maximum TGR (TGRmax) for outcomes of small-cell lung cancer (SCLC) patients undergoing first-line chemotherapy plus immune-checkpoint inhibitor (ICI) treatment. Patients with SCLC receiving first-line chemotherapy plus immunotherapy were analyzed within this retrospective study. The X-tile program was used to identify the cut-off value of TGRmax based on maximum progression-free survival (PFS) stratification. The Kaplan-Meier methods and Cox regression models were used to evaluate the effect of the presence of TGRmax on PFS and overall survival (OS). In total, 104 patients were evaluated. Median (range) TGRmax was -33.9 (-65.2 to 21.6) %/m and the optimal cut-off value of TGRmax was -34.3%/m. Multivariate Cox regression analysis revealed that patients with TGRmax > -34.3%/m was associated with shorter PFS (hazard ratio [HR], 2.81; 95% CI, 1.71-4.63; p < 0.001) and OS (HR, 3.17; 95% CI, 1.41-7.08; p=0.005). In patients who received partial response (PR), Kaplan-Meier survival analyses showed that superior PFS and OS (p=0.005 and p=0.009, respectively) benefit was observed when TGRmax ≤-34.3%/m. SCLC patients with TGRmax > -34.3%/m had worse PFS and OS in first-line ICI plus platin-based chemotherapy. TGRmax could independently serve as an early biomarker to predict the benefit from chemoimmunotherapy.