Nomogram for predicting pathological complete response to neoadjuvant chemoimmunotherapy in patients with resectable...

Neoadjuvant chemoimmunotherapy is increasingly employed in resectable non-small cell lung cancer (NSCLC), with variable pathological complete response (pCR) rates. Currently, no reliable preoperative tool is available for predicting pCR. This study develops a nomogram based on clinical variables to predict pCR and guide individualized surgical decisions.

We retrospectively analyzed data from 179 NSCLC patients (stages IIB-IIIB) who received neoadjuvant chemoimmunotherapy followed by resection (2019-2022). Variables included demographics, smoking history, comorbidities, treatment details, and pathology. Univariate and multivariate logistic regression identified pCR predictors, which were incorporated to build a nomogram. Performance was assessed via area under the curve (AUC), calibration, and decision curve analysis (DCA).

Of 179 patients, 92 (51.4%) achieved pCR. Multivariate analysis identified independent predictors: non-squamous histology (OR 0.344 (non-squamous vs. squamous), 95% CI 0.151-0.707, p = 0.006), positive family history (OR 10.76 (positive vs. negative), 95% CI 1.903-203.3, p = 0.027), shorter smoking cessation duration (defined as time in days from last cigarette to treatment start) (OR 0.999 (per day), 95% CI 0.999-0.999, p = 0.033), older age (OR 1.053 (per year), 95% CI 1.005-1.106, p = 0.032), and more treatment cycles (OR 1.621 (per cycle), 95% CI 1.007-2.661, p = 0.049). The nomogram showed modest discrimination (AUC 0.709, 95% CI 0.633-0.785), good calibration, and net benefit on DCA, though it has not been externally validated and is limited by single-center data, small sample size, high pCR rate, and skewed demographics (95.5% male, 92.7% smokers), potentially limiting generalizability to diverse populations such as females or non-smokers.

This nomogram, derived from routine clinical data, predicts pCR after neoadjuvant chemoimmunotherapy in NSCLC, offering a tool for thoracic surgeons to optimize treatment and surgical planning, despite its modest discriminative power, by serving as a complementary aid in resource-limited settings where biomarkers may not be readily available. External validation in larger, multi-center cohorts is essential.