2024 World Conference on Lung Cancer (WCLC) - ePosters-EP.07C.17 A Nomogram Prediction Model for Assessing the Risk of Recurrence in NSCLC Patients Underwent Neoadjuvant Immunotherapy: A Retrospective Study

EP.07C.17 A Nomogram Prediction Model for Assessing the Risk of Recurrence in NSCLC Patients Underwent Neoadjuvant Immunotherapy: A Retrospective Study

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This study focuses on the development of a nomogram prediction model designed to assess the risk of recurrence in non-small cell lung cancer (NSCLC) patients who have undergone neoadjuvant immunotherapy. The research was conducted by a team from the Guangdong Lung Cancer Institute and examined the efficacy of using specific blood markers alongside clinical characteristics to predict recurrence.<br /><br />Neoadjuvant immunotherapy has shown promise in enhancing the prognosis of NSCLC by modifying the tumor microenvironment. However, recurrence remains a concern for some patients post-treatment. This retrospective study investigates blood markers collected at the start of treatment and before surgery for IB-IIIB stage patients.<br /><br />A total of 296 patients from Guangdong Provincial People's Hospital, who underwent neoadjuvant immunotherapy followed by surgery, were included in the study. These patients were split into a training group (70%) and a validation group (30%). The researchers employed a least absolute shrinkage and selection operator (LASSO)-derived Cox regression to identify risk factors and construct a nomogram model. The performance of the model was evaluated using the area under the curve (AUC), C-index, calibration plot, and decision curve analysis.<br /><br />NSE and PCR emerged as significant blood markers for the nomogram. The model demonstrated good calibration for both the training and validation groups. Specifically, the AUC score was 0.87 for the training group over three years, suggesting strong predictive capability, although it fell to 0.525 in the validation group. The C-index was 0.757 in the training group and dropped to 0.55 in the test group, reflecting some decline in predictive performance outside the training cohort.<br /><br />The study concludes that the nomogram model is a useful tool for identifying recurrence risk in NSCLC patients who have undergone neoadjuvant immunotherapy, although further validation is needed. Acknowledgments are extended to the patients and their families involved in the study.

Asset Subtitle

Lishan Peng

Meta Tag

Speaker Lishan Peng

Topic Early-Stage Non-small Cell Lung Cancer

Keywords

nomogram prediction model

non-small cell lung cancer

NSCLC recurrence risk

neoadjuvant immunotherapy

blood markers

LASSO Cox regression

Guangdong Lung Cancer Institute

NSE and PCR markers

predictive model evaluation

tumor microenvironment