Published in:
Open Access 01-03-2020 | Original Article – Clinical Oncology
Novel prognostic model for stratifying survival in stage I lung adenocarcinoma patients
Published in: Journal of Cancer Research and Clinical Oncology | Issue 3/2020
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Purpose
We combined conventional clinical and pathological characteristics and pathological architectural grading scores to develop a prognostic model to identify a specific group of patients with stage I lung adenocarcinomas with poor survival following surgery.
Methods
This retrospective study included 198 patients with stage I lung adenocarcinomas recruited from 2004 to 2013. Multivariate analyses were used to confirm independent risk factors, which were checked for internal validity using the bootstrapping method. The prognostic scores, derived from β-coefficients using the Cox regression model, classified patients into high- and low-risk groups. The predictive performance and discriminative ability of the model were assessed by the area under the receiver operating characteristic curve (AUC), concordance index (C-index) and Kaplan–Meier survival analyses.
Results
Three risk factors were identified: T2 (rounding of β-coefficients = 81), necrosis (rounding of β-coefficients = 67), and pathological architectural score of 5–6 (rounding of β-coefficients = 58). The final prognostic score was the sum of points. The derived prognostic scores stratified patients into low- (score ≤ 103) and high- (score > 103) risk groups, with significant differences in 5-year overall survival (high vs. low risk: 49.3% vs. 88.0%, respectively; hazard ratio: 4.55; p < 0.001). The AUC for the proposed model was 0.717. The C-index of the model was 0.693.
Conclusion
An integrated prognostic model was developed to discriminate resected stage I adenocarcinoma patients into low- and high-risk groups, which will help clinicians select individual treatment strategies.