Clinical characteristics analysis and prognostic prediction model construction in multiple primary lung cancer based on the SEER database
10.3760/cma.j.cn115355-20231107-00181
- VernacularTitle:基于SEER数据库的多原发肺癌临床特征分析及预后预测模型构建
- Author:
Linqi WEN
1
;
Shengzhao YANG
;
Zhongshuai WANG
;
Feng LI
;
Yong MA
;
Mingchuang ZHU
;
Jianhong LIAN
Author Information
1. 长治医学院附属和平医院胸外科，长治 046000
- Keywords:
Lung neoplasms;
Neoplasms, multiple primary;
Prognosis;
Neoplasm staging
- From:
Cancer Research and Clinic
2024;36(6):446-453
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the clinical characteristics and prognostic influencing factors of multiple primary lung cancer (MPLC), and to construct a prognostic prediction model.Methods:The clinical data and prognostic information of MPLC patients diagnosed by pathological examination included in the Surveillance, Epidemiology, and End Results (SEER) database from January 2010 to December 2020 were retrospectively analyzed. Patients were randomly divided into training and validation sets according to a 7:3 ratio using R software. Survival curves were plotted by using the Kaplan-Meier method and log-rank test was used for comparison between groups. The independent influencing factors of overall survival (OS) of MPLC patients in the training set were screened using univariate and multivariate Cox proportional hazards models, and accordingly, the nomogram predicting the survival rate of patients at 3, 5 and 8 years were plotted. In the training and validation sets, using the actual survival as the gold standard, the receiver operating characteristic (ROC) curves of the constructed models for predicting the patients' 3-, 5- and 8-year OS rates were plotted, the area under the curve (AUC) was obtained, and C-index of the model was analyzed by using R software. The calibration curves of 3-, 5- and 8-year OS rates predicted by the models and the actual OS rates were plotted.Results:A total of 5 495 MPLC patients were included, 3 846 in the training set and 1 649 in the validation set. The differences in the composition of patients of different ages and AJCC stages between the training and validation sets were statistically significant (both P < 0.05), and the differences in the comparison of other clinicopathological characteristics were not statistically significant (all P > 0.05). The results of multivariate Cox regression analysis showed that males (compared with females, HR = 1.256, 95% CI: 1.144-1.379, P < 0.001), age ≥ 70 years old (compared with 50-59 years old, HR = 1.201, 95% CI: 1.030-1.400, P = 0.019), FPLC with pathological types of squamous cell carcinoma or other types (compared with adenocarcinoma, HR = 1.275, 95% CI: 1.137-1.431, P < 0.001; HR = 1.208, 95% CI: 1.041-1.403, P = 0.013), and SPLC with pathological types of squamous cell carcinoma, small cell lung carcinoma, or other types (compared with adenocarcinoma, HR = 1.270, 95% CI: 1.121-1.440, P < 0.001; HR = 1.978, 95% CI: 1.642-2.384, P < 0.001; HR = 1.246, 95% CI: 1.090-1.424, P = 0.001), and AJCC stage Ⅲ and Ⅳ (compared with stage Ⅰ, HR = 1.645, 95% CI: 1.447-1.869, P < 0.001; HR = 2.078, 95% CI: 1.669-2.587, P < 0.001), FPLC without operation (compared with operation, HR = 1.263, 95% CI: 1.038-1.536, P = 0.020), SPLC without operation (operation vs. no operation, HR = 0.680, 95% CI: 0.579-0.799, P < 0.001), FPLC without lymph node dissection or with clearance of 1-3 regional lymph nodes (compared with clearance of ≥4, HR = 1.225, 95% CI: 1.016-1.477, P = 0.034; HR = 1.314, 95% CI: 1.103-1.566, P = 0.002), FPLC with maximum diameter 3-5 cm or >5 cm (compared with <3 cm, HR = 1.181, 95% CI: 1.053-1.324, P = 0.005; HR = 1.232, 95% CI: 1.069-1.420, P = 0.004), and SPLC with maximum diameter 3-5 cm or >5 cm (compared with <3 cm, HR = 1.560, 95% CI: 1.362-1.786, P < 0.001; HR = 1.727, 95% CI: 1.451-2.054, P < 0.001), and FPLC without chemotherapy (chemotherapy vs. no chemotherapy or unknown, HR = 0.744, 95% CI: 0.655-0.845, P < 0.001) were the independent risk factors of patients' poor OS (all P < 0.05). The results of Kaplan-Meier survival analysis showed that the OS of patients with different gender, race, age, two tumor locations, AJCC staging, pathological type of two lung tumors, maximum diameter of two tumors, and whether two tumors were treated surgically or not, and whether two tumors were treated with chemotherapy or not in the training set were compared, and the differences were all statistically significant (all P < 0.05). Based on the independent factors affecting the OS of MPLC patients screened by the results of multivariate Cox regression analysis, nomogram predicting the 3-, 5- and 8-year OS rates of MPLC were plotted. The results of ROC curve analysis showed that the C-index of the training set's nomogram was 0.679 (95% CI: 0.649-0.701), and the AUC values for predicting the 3-, 5- and 8-year OS rates were 0.601, 0.595 and 0.586, respectively; the C-index of the validation set was 0.678 (95% CI: 0.633-0.720), and the AUC values for predicting 3-, 5- and 8-year OS rates were 0.643, 0.631 and 0.626, respectively. The calibration curves showed that the 3-, 5- and 8-year OS rates of patients predicted by the nomogram models in both the training and validation sets were in good agreement with the actual results with a high goodness-of-fit. Conclusions:The established prognostic model has good predictive value and can effectively assess the prognosis of patients.
