Table_1_Development and Validation of a Nomogram for Predicting Prognosis to Immune Checkpoint Inhibitors Plus Chemotherapy in Patients With Non-Small Cell Lung Cancer.docx

BackgroundImmune checkpoint inhibitors (ICIs) plus chemotherapy improved the prognosis of patients with non-small cell lung cancer (NSCLC); however, reliable prognostic biomarkers are lacking. We explored factors associated with prognosis and developed a predictive model.MethodsWe retrospectively analyzed 130 consecutive stage IIIA–IVB NSCLC patients treated with ICIs combined with chemotherapy. Cox univariate and multivariate proportional hazards regression analyses were used to identify prognostic factors associated with progression-free survival (PFS). A nomogram was developed based on key factors in the training cohort (n = 86) and evaluated in the validation cohort (n = 44). According to the nomogram-based total point scores, we divided patients into low- and high-risk groups.ResultsIn the training cohort, bone metastases (p = 0.017) and an increased derived neutrophil-to-lymphocyte ratio (p = 0.018) were significantly associated with poor PFS, while smoking (p = 0.007) and programmed death-ligand 1 (PD-L1) ≥50% (p = 0.001) were associated with improved PFS. A nomogram based on these factors was developed to predict PFS at 3, 6, and 12 months. The C-index of the nomogram to predict PFS was 0.725 (95% CI: 0.711–0.739) in the training cohort and 0.688 (95% CI: 0.665–0.711) in the validation cohort. The area under the curve (AUC) exhibited an acceptable discriminative ability, and calibration curves demonstrated a consistency between the actual results and predictions. In the training cohort, the median PFS (mPFS) was 12.3 and 5.7 months in the low- and high-risk groups, respectively (p ConclusionsA predictive nomogram was developed to help clinicians assess prognosis early for advanced NSCLC patients who received ICI plus chemotherapy.