Discussions
NSCLC, tumor
TUMOR, NSCLC
It is important to choose suitable strategy at personalized level on the basis of accurate prediction of prognosis. Considering that the TNM staging system only takes the tumor size and lymph node involvement into considerations, a dedicated nomograms with more prognostic factors may be more accurate in predicting survival than the TNM staging system [In this large population study, six variables including age, sex, laterality, histological classification, pathological T stage, and HI Standard were reviewed [To our knowledge, this is the first dedicated nomogram to predict OS based on the combination of the TNM staging system and other potential prognostic factors, which may benefit the optimal stratified treatment regimens in patients with T1-3N0M0 NSCLC. Accuracy of the nomogram was assessed by discrimination evaluation as well as calibration evaluation. Our nomogram showed perfect discriminative ability (training cohort: C index, 0.671; 95% CI, 0.637–0.705; internal validation cohort: C index, 0.632; 95% CI, 0.581–0.683; external validation cohort: C index, 0.645; 95% CI, 0.617–0.673). Besides, our nomogram showed excellent agreement in calibration plots for 3-/5- year OS of training cohorts, internal validation cohorts, and external validation cohort. DCA curve was performed to ascertain the clinical usefulness of the nomogram and showed good clinical applicability of the nomogram in predicting 3- and 5-year OS of the patients. All the evaluation above confirmed that our nomogram was an excellent model with a powerful prognostic performance to predict OS in patients with T1-3N0M0 NSCLC after curative resection.In our study, 3002 patients at 11 different centers in China were chosen, which is much larger than previous studies concerning the nomogram of T1-3N0M0 NSCLC. In order to simplify the application process and facilitate decision-making, we developed an online version at Although our nomogram showed excellent discrimination and performance, our study still has several limitations. First, considering the retrospective nature of this study, a selection bias might be inevitable although we have included relatively large training, internal validation, and multi-center external validation cohorts to construct the nomogram, which may reduce the bias caused by the retrospective data analysis. Second, our nomograms are based on Chinese population and therefore may not be generalizable to different patient populations in other country. Third, our database only contained some general information but lack more potential factors, such as information about the postoperative adjuvant therapy, which may cause bias in our study. Given these limitations above, our nomogram still need further validation in prospective clinical trials or other patient population. Despite these limitations, our dedicated nomogram represents an important and effective tool to estimate the prognosis of an eligible patient, and thus offering more advice on personalized therapy strategy and follow-up management.