A clinicopathologic prediction model for postoperative recurrence in stage Ia non-small cell lung cancer

Abstract

Objective: Controversy remains over the appropriate postoperative management for patients with stage Ia non-small cell lung cancer who underwent complete surgical resection as a result of a heterogeneous prognosis. We aimed to identify the predictive factors for recurrence in these patients to aid in the decision making.

Methods: We reviewed 344 patients with stage Ia non-small cell lung cancer to analyze the associations between recurrence-free survival and the following clinicopathologic variables: age, gender, smoking history, family history, preoperative serum carcinoembryonic antigen level, type of surgical resection, tumor location, tumor histology, lymphovascular invasion, tumor differentiation, and pathologic T status.

Results: Cox multivariate survival analysis revealed that central tumor location (P=.019), stage T1b (P=.006), high histologic grade (including large cell carcinoma, solid predominant, micropapillary predominant, and invasive mucinous adenocarcinoma, P=.007), poor differentiation (P=.022), and lymphovascular invasion (P=.035) were independently associated with recurrence-free survival. A nomogram for predicting the probability of 3-year recurrence-free survival was developed using the 5 variables. This model shows good calibration, reasonable discrimination (concordance index=0.733), and small overfitting (2.6%) demonstrated by bootstrapping.

Conclusions: We developed a clinicopathologic prediction model for postoperative recurrence in stage Ia non-small cell lung cancer. This model can help with the selection of appropriate postoperative therapeutic strategies for these patients.