Hao Li, MD
(He/Him/His)
Rank
Fellow or Postdoc
Department
Surgery
Thoracic Surgery
Authors
Hao Li*, MD, Fatemeh Hooshmand, MSc, Fatemehsadat Pezeshkian,MD, Yue Xie, MSPH, Emanuele Mazzola, PhD, Rafael Ribeiro Barcelos, MD, Sanna Laaksonen, MD, Lynette Sholl, MD, Raphael Bueno, MD, Paula Ugalde Figueroa, MD, Scott Swanson, MD.
Principal Investigator
Scott Swanson
Twitter / Website
Categories
Objectives: Neoadjuvant immunotherapy (Neo-IO), often combined with chemotherapy, has revolutionized the neoadjuvant treatment paradigm for non-small cell lung cancer (NSCLC). This study aims to investigate the risk factors for recurrence following Neo-IO.
Methods: We conducted a retrospective analysis of resectable NSCLC patients who underwent lung resection followed by Neo-IO, using data from a prospectively collected clinical database of thoracic surgery department. The percentage of residual viable tumor (%RVT) of the primary tumor (PT) were quantified (0-100%) in the tumor bed, following pan-tumor immune-related pathologic response criteria (irPRC). The optimal %RVT cutoff, as a continuous covariate for recurrence-free survival (RFS), was determined using the Rhier function from the rolr R package.
Results: A total of 104 patients were included from October 2017 and Aprill 2024. Baseline invasive mediastinal staging was performed in 95.2% (99/104) of patients. Pathological complete response (pCR) and major pathological response (MPR) rates were 21.2% (22/104) and 45.2% (47/104), respectively. The average %RVT was 20% (range: 5%–60%). With optimal %RVT cutoffs of 5% and 40%, patients with less than 5% %RVT exhibited the best RFS compared to those in the intermediate group (5%–40%, P = 0.098) and the worst-responsive group (≥40%, P = 0.001). Multivariate analyses identified %RVT as an independent risk factor for RFS (HR, 3.61; 95% CI, 1.13-11.55; P=0.03).
Conclusions: The percentage of residual viable tumor in the primary tumor is an independent risk factor for lung cancer recurrence following neoadjuvant immunotherapy, with optimal cutoffs identified at 5% and 40%.