Immune checkpoint inhibitors (ICI) are a significant advance to the treatment arsenal for advanced non-small cell lung cancer (NSCLC), however, there initiation is still associated with significant heterogeneity in survival outcomes. This study aimed to develop and validate a pre-treatment prognostic tool of survival outcomes in advanced NSCLC patients treated with ICIs.
Time-to-event modelling techniques, including decision-tree, Cox proportional hazard and random forest analysis were evaluated to determine the optimal pre-treatment prognostic model using commonly available clinicopathological data. Model development data consisted of advanced NSCLC patients treated with atezolizumab from the randomised clinical trials OAK and POPLAR (n = 751). Data from the single-arm atezolizumab trials BIRCH and FIR (n = 797) were used for external validation. Overall survival (OS) was the primary outcome and progression-free survival (PFS) was assessed as a secondary outcome.
Based upon pre-treatment C-reactive protein, lactate dehydrogenase, derived neutrophil-to-lymphocyte ratio, albumin, PDL1 expression, performance status, time since metastatic diagnosis, and metastatic sites count an optimal prognostic tool was defined. The tool allows the calculation of a personalised Immunotherapy Prognostic Score (IPS). The OS discriminative performance of the IPS was consistent with a well-performing model in both the development and validation cohorts (c-index > 0.73). The IPS discriminated significantly different OS probabilities (P < 0.001), with median OS ranging from 3.4 to greater than 24 months for the upper and lower 15th risk percentiles, from the OAK and POPLAR trials. Similar findings were identified for PFS (P < 0.001), with median PFS ranging from 1.4 to 4.7 months for the upper and lower 15th risk percentiles.
A pre-treatment prognostic tool was developed and validated to identify patient groups with distinctly different survival probabilities following the initiation of atezolizumab treatment for advanced NSCLC.