Prediction model for stage I NSCLC refines follow-up strategy, personalizes therapy

A prediction model on disease recurrence for low-risk, resected stage I lung adenocarcinoma can classify postoperative patients with available clinical information and may even aid in personalizing a follow-up strategy and future adjuvant therapy, reports a study.

The authors retrospectively assessed the disease-free survival (DFS) of 408 patients with pathologically confirmed low-risk stage I lung adenocarcinoma who had had curative resection from 2013 to 2017. They used a tree-based method to categorize the patients into subgroups with distinct DFS outcome and stepwise risk ratio.

A multivariate analysis was also performed, which included the covariates to create a scoring system that will predict disease recurrence. The 2011‒2012 cohort was used to validate this model.

The following factors were found to be associated with better DFS: nonsmoker status, stage AI disease, epidermal-growth factor receptor mutants, and female gender.

On multivariate analysis, factors such as smoking status, disease stage, and gender were included in the scoring system and identified three distinct risk groups for DFS: 99.4 (95 percent confidence interval [CI], 78.3‒125.3), 62.9 (95 percent CI, 48.2‒82.0), and 33.7 months (95 percent CI, 24.6‒46.1; p<0.005).

Additionally, the external validation yielded an area under the curve by receiver operating characteristic analysis of 0.863 (95 percent CI, 0.755‒0.972).

“Although stage I nonsmall cell lung carcinoma typically carries a good prognosis following complete resection, early disease recurrence can occur,” the authors said. “An accurate survival prediction model would help refine a follow-up strategy and personalize future adjuvant therapy.”