1229P - Precision patient selection for postoperative therapy in resectable NSCLC: A comprehensive postoperative-risk model incorporating genetic and histological features

Background

To develop a novel postoperative-risk model integrating genetic alterations with histological grading systems for resectable non-small cell lung cancer (NSCLC), and to evaluate its performance against established grading systems in identifying high-risk patients requiring adjuvant therapy.

Methods

404 patients with resectable invasive non-mucinous lung adenocarcinoma (stage IA-IIIB according to the 8th edition of the AJCC Cancer Staging Manual) between October 2018 and December 2021 were included, with follow-up until September 2023. The predominant subtype-based grading system (p-GS) and the IASLC grading system (I-GS) were assessed. Enrichment-based targeted DNA sequencing was performed for all specimens. The primary clinical endpoint was disease-free survival (DFS), defined as the interval from surgery to recurrence, progression, or death from any cause.

Results

At a median follow-up of 32 months (range from 1.1 to 47.7 months), 82/404 patients relapsed. Co-mutation adversely impacted DFS (univariable: HR[95%CI]=2.74[1.66-4.52], p<0.001; multivariable: HR[95%CI]=2.04[1.23-3.40], p=0.006). Postoperative-risk models based on P-GS, I-GS and I-GS + co-mutation exhibited robust predictive performance. Integration of co-mutation with I-GS improved prognostic discrimination, reducing AIC from 884.08 to 875.82 and enhancing C-index to 0.794 for DFS. Among EGFR-mutant patients (stage IIA-IIIB, n=79), both EGFR tyrosine kinase inhibitor monotherapy and combination chemotherapy significantly improved DFS (HR[95%CI]=0.21[0.09-0.51], p<0.001; and HR[95%CI]=0.10[0.03-0.40], p=0.001; respectively), increasing median survival from 13.4 to 40.1 months compared to untreated patients.

Conclusions

Integrating co-mutation status with histological grading systems enhances the prognostic accuracy of the postoperative risk model for resectable NSCLC, potentially facilitating improved identification of high-risk patients who may benefit from adjuvant therapy.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

The authors.

Funding

National Natural Science Foundation of China (Grant No. 82002449, 81702954), Natural Science Foundation of Anhui Province of China (Grant No. 2008085QH350, 2208085MH250).

Disclosure

All authors have declared no conflicts of interest.