Fatemehsadat Pezeshkian, MD

Rank

Fellow or Postdoc

Department

Surgery

Thoracic Surgery

Authors

Fatemehsadat Pezeshkian MD, Fatemeh Hooshmand MS, Yue Xie PhD, Emanuele Mazzola PhD, Anupama Singh MD, Miles McAllister BA, Mohammad Abdallat MD, Rafael Ribeiro Barcelos MD, Abby White MD, Paula Ugalde MD, Raphael Bueno MD, Michael T. Jaklitsch MD, Scott J. Swanson MD

Principal Investigator

Michael T. Jaklitsch and Scott J. Swanson

Twitter / Website

Categories

Tailored Approaches: Decision Support Model for Predicting Complete Response to neoadjuvant treatment in Stage III N2 Lung Cancer

Abstract

Objective: Lung cancer management has evolved significantly, presenting physicians with many treatment options. We developed a predictive model to facilitate patient-tailored stage III N2 lung cancer decision-making.

Methods: A single-institutional cohort of patients who received definitive surgical resection of stage III N2 lung cancer from 2006-2023 was reviewed. The cohort was weighted using propensity score weighting built with age and radiologic lesion size. A predictive nomogram was constructed using preoperative data to predict the complete response to neoadjuvant treatment.

Results: A total of 495 patients with a median follow-up of 32.6 months were included. The median age was 65 (IQR 58-72), comprising 286 (58%) women and 209 (42%) men. Neoadjuvant therapy was administered to 307 (62%), which were chemoradiation in 273 (55%) and chemoimmunotherapy in 34(7%). Disease recurrence was observed in 250 (51%) patients, and the 5-year overall survival rate was 57.2%. After propensity score weighting, nomograms were developed to predict the complete response to neoadjuvant treatment with an AUC of 71%. (Figure 1)

Conclusions: Our nomogram, with validation, has the potential to outline the probability of complete response to neoadjuvant therapy. Our prediction model supports robust, tailored plans for treatment and follow-up strategies in stage III N2 lung cancer.