Abstract
Background: Postoperative prognosis of early stage non-small cell lung cancer (NSCLC) undergoing sublobectomy is heterogeneous. Therefore, we sought to construct a novel survival prediction model for stage IA NSCLC ≤2 cm undergoing sublobectomy.Methods: Based on the data from the Surveillance, Epidemiology, and End Results (SEER) program, we successfully determined and incorporated independent prognostic markers to construct the nomogram. Internal validation of the constructed nomogram was conducted through 1,000 bootstrap resamples. The constructed nomogram was further subjected to external validation with an independent cohort of patients from two Chinese institutions. The performance of the survival prediction model was assessed by concordance index, calibration plots, and risk subgroup classification.Results: A total of 3,238 patients from SEER registries (development cohort), as well as 769 patients from two Chinese institutions (validation cohort) was included. Gender, age, size, histologic type, grade, and examined lymph nodes count were identified as significant prognostic parameters. A novel nomogram was developed and externally validated. Concordance index of constructed nomogram was significantly better than that of the current TNM staging system. Calibration plots demonstrated an optimal consistency between the nomogram predicted and actual observed probability of survival. Survival curves of different risk subgroups within respective TNM stage demonstrated significant distinctions.Conclusion: We developed and externally validated a survival prediction model for patients with stage IA NSCLC ≤2 cm undergoing sublobectomy. This novel nomogram outperforms the conventional TNM staging system and could help clinicians in postoperative surveillance and future clinical trial design.
Highlights
The widespread application of advanced imaging technique for lung cancer screening has witnessed a dramatic increase in the early detection of non-small cell lung cancer (NSCLC) and renewed interests in assessing the optimal surgical procedures for NSCLC ≤2 cm [1, 2]
The eighth edition of the American Joint Committee on Cancer (AJCC) TNM staging has been applied universally, in which stage IA NSCLC ≤2 cm are classified merely based on tumor size (T descriptors) [7]
Postoperative prognosis of cases with the same TNM stage is heterogeneous, and the development of tools based on significant prognosticators such as demographic characters, pathologic features, and surgical procedures may contribute to personalized survival prediction [8]
Summary
The widespread application of advanced imaging technique for lung cancer screening has witnessed a dramatic increase in the early detection of non-small cell lung cancer (NSCLC) and renewed interests in assessing the optimal surgical procedures for NSCLC ≤2 cm [1, 2]. Postoperative prognosis of cases with the same TNM stage is heterogeneous, and the development of tools based on significant prognosticators such as demographic characters, pathologic features, and surgical procedures may contribute to personalized survival prediction [8]. Patients with early stage NSCLC treated with sublobar resection are heterogeneous in distinct physical conditions and therapeutic strategies, which raises difficulty and uncertainty in survival prediction and risk group stratification. The most widely used AJCC TNM classification system stratifies stage IA NSCLC ≤2 cm merely based on tumor size and previously developed nomogram for NSCLC failed to consider tumor size or surgical strategy [11, 12], which necessitate the need to develop individualized survival prediction model for those patients. Postoperative prognosis of early stage non-small cell lung cancer (NSCLC) undergoing sublobectomy is heterogeneous. We sought to construct a novel survival prediction model for stage IA NSCLC ≤2 cm undergoing sublobectomy
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