On-treatment lung immune prognostic index is predictive for first-line PD-1 inhibitor combined with chemotherapy in patients with non-small cell lung cancer

Early Changes in LIPI Score Predict Immune-Related Adverse Events: A Propensity Score Matched Analysis in Advanced Non-Small Cell Lung Cancer Patients on Immune Checkpoint Blockade

In advanced cancer patients undergoing immune checkpoint blockade, the burden of immune-related adverse events (irAEs) is high. The need for reliable biomarkers for irAEs remains unfulfilled in this expanding therapeutic field. The lung immune prognostic index (LIPI) is a noninvasive measure of systemic inflammation that has consistently shown a correlation with survival in various cancer types when assessed at baseline. This study sought to determine whether early changes in the LIPI score could discriminate the risk of irAEs and different survival outcomes in advanced non-small cell lung cancer (NSCLC) patients receiving PD-(L)1 blockade-based therapies. We included consecutive patients diagnosed with metastatic NSCLC who received pembrolizumab, nivolumab, or atezolizumab as second-line therapy following platinum-based chemotherapy, or first-line pembrolizumab either alone or in combination with platinum-based chemotherapy. The LIPI score relied on the combined values of derived neutrophil/lymphocyte ratio (dNLR) and lactate dehydrogenase. Their assessment at baseline and after two cycles of treatment allowed us to categorize the population into three subgroups with good (LIPI-0), intermediate (LIPI-1), and poor (LIPI-2) prognosis. Between April 2016 and May 2023, we enrolled a total of 345 eligible patients, 165 (47.8%) and 180 (52.2%) of whom were treated as first- and second-line at our facility, respectively. After applying propensity score matching, we considered 83 relevant patients in each cohort with a homogeneous distribution of all characteristics across the baseline LIPI subgroups. There was a noticeable change in the distribution of LIPI categories due to a significant decrease in dNLR values during treatment. Although no patients shifted to a worse prognosis category, 20 (24.1%) transitioned from LIPI-1 to LIPI-0, and 7 (8.4%) moved from LIPI-2 to LIPI-1 (p < 0.001). Throughout a median observation period of 7.3 (IQR 3.9-15.1) months, a total of 158 irAEs (63.5%) were documented, with 121 (48.6%) and 39 (15.7%) patients experiencing mild to moderate and severe adverse events, respectively. Multivariate logistic regression analysis showed that the classification and changes in the LIPI score while on treatment were independent predictors of irAEs. The LIPI-0 group was found to have significantly increased odds of experiencing irAEs. Following a median follow-up period of 21.1 (95% CI 17.9-25.8) months, the multivariable Cox model confirmed LIPI categorization at any given time point as a significant covariate with influence on overall survival, irrespective of the treatment line. These findings suggest that reassessing the LIPI score after two cycles of treatment could help pinpoint patients particularly prone to immune-related toxicities. Those who maintain a good LIPI score or move from the intermediate to good category would be more likely to develop irAEs. The continuous assessment of LIPI provides prognostic insights and could be useful for predicting the benefit of PD-(L)1 checkpoint inhibitors.