ObjectiveTo investigate the correlation between spread through air space (STAS) of sub-centimeter non-small cell lung cancer and clinical characteristics and radiological features, constructing a nomogram risk prediction model to provide a reference for the preoperative planning of sub-centimeter lung cancer patients. MethodsThe data of patients with sub-centimeter non-small cell lung cancer who underwent surgical treatment in Nanjing Drum Tower Hospital from January 2022 to October 2023 were retrospectively collected. According to the pathological diagnosis of whether the tumor was accompanied with STAS, it was divided into two groups, a STAS positive group and a STAS negative group. The clinical and radiological data of the two groups were collected for univariate logistic regression analysis, and the variables with statistically significant differences were included in the multivariate analysis. Finally, independent risk factors for STAS were screened out and nomogram models were constructed. The sensitivity and specificity were calculated based on the Youden index, and area under the curve (AUC), calibration plots and decision curve analysis (DCA) were used to evaluate the performance of the model. ResultsA total of 112 patients were collected, which included 17 patients in the STAS positive group, consisting of 11 males and 6 females, with a mean age of 59.0±10.3 years. The STAS negative group included 95 patients, with 30 males and 65 females, and a mean age of 56.8±10.3 years. Univariate logistic regression analysis showed that male, anti-GAGE7 antibody positive, mean CT value and spiculation were associated with the occurrence of STAS. Multivariate regression analysis showed that associations between STAS and male (OR=5.974, 95%CI 1.495 to 23.872), anti-GAGE7 antibody (OR=11.760, 95%CI 1.619 to 85.408) and mean CT value (OR=1.008, 95%CI 1.004 to 1.013) were still significant, while the association between STAS and spiculation was not significant anymore. Based on the above three independent predictors, a nomogram model of STAS in sub-centimeter lung cancer was constructed. The AUC value of the model was 0.890, the sensitivity was 76.5%, and the specificity was 91.6%. The calibration curve was well fitted, suggesting that the model had good prediction efficiency for STAS. The DCA plot showed that the model had good clinically utility. ConclusionMale, anti-GAGE7 antibody positive and mean CT value are independent predictors of STAS positivity of sub-centimeter non-small cell lung cancer, the nomogram model established in this study had good predictive value, and provide reference significance for preoperative planning of patients.
Evidence-based research in traditional Chinese medicine (TCM) has made many important achievements and promoted the modernization and internationalization of TCM. The ability to produce research evidence to guide clinical practice in an emergency treatment situation is a major test of the development of evidence-based Chinese medicine (EBCM) when emerging infectious diseases outbreaks. Along with the development of EBCM, TCM has experienced emerging infectious disease events such as atypical pneumonia (SARS), influenza A (HIN1), and corona virus disease 2019 (COVID-19), and the ability of TCM to conduct clinical research in emergency treatment work has been continuously improved. This article provides an overview of the clinical research conducted in TCM to resist emerging infectious diseases in the past, focusing on the clinical research results obtained in the present time of COVID-19 rescue and treatment, and discusses the role of EBCM development to enhance the clinical research capacity of TCM in emerging infectious diseases.