Figure 1.

Workflow of the proposed integrated predictive model and study design. The patients with ES-SCLC treated with combined atezolizumab or durvalumab with standard chemotherapy are included and one training cohort and two independent external validation cohorts are created. Cox regression is employed to screen for therapeutic efficacy associated clinical features. Radiomics Score is constructed using machine learning from the radiomics features extracted in the regions of interest delineated on the chest CT before treatment. Clinical features are further combined with the radiomics score to devise the integrated model, whose outputs create the treatment outcome prediction. AUC, area under the curve; DCA, decision curve analysis; ES-SCLC, extensive-stage small cell lung cancer; K-M, Kaplan-Meier.