Construction and validation of a nomogram to predict the overall survival of small cell lung cancer: a multicenter retrospective study in Shandong province, China.

BACKGROUND: Patients diagnosed with small cell lung cancer (SCLC) typically experience a poor prognosis, and it is essential to predict overall survival (OS) and stratify patients based on distinct prognostic risks. METHODS: Totally 2309 SCLC patients from the hospitals in 15 cities of Shandong from 2010 - 2014 were included in this multicenter, population-based retrospective study. The data of SCLC patients during 2010-2013 and in 2014 SCLC were used for model development and validation, respectively. OS served as the primary outcome. Univariate and multivariate Cox regression were applied to identify the independent prognostic factors of SCLC, and a prognostic model was developed based on these factors. The discrimination and calibration of this model were assessed by the time-dependent C-index, time-dependent receiver operator characteristic curves (ROC), and calibration curves. Additionally, Decision Curve Analysis (DCA) curves, Net Reclassification Improvement (NRI), and Integrated Discriminant Improvement (IDI) were used to assess the enhanced clinical utility and predictive accuracy of the model compared to TNM staging systems. RESULTS: Multivariate analysis showed that region (Southern/Eastern, hazard ratio [HR] = 1.305 [1.046 - 1.629]; Western/Eastern, HR = 0.727 [0.617 - 0.856]; Northern/Eastern, HR = 0.927 [0.800 - 1.074]), sex (female/male, HR = 0.838 [0.737 - 0.952]), age (46-60/≤45, HR = 1.401 [1.104 - 1.778]; 61-75/≤45, HR = 1.500 [1.182 - 1.902]; >75/≤45, HR = 1.869 [1.382 - 2.523]), TNM stage (II/I, HR = 1.119[0.800 - 1.565]; III/I, HR = 1.478 [1.100 - 1.985]; IV/I, HR = 1.986 [1.477 - 2.670], surgery (yes/no, HR = 0.677 [0.521 - 0.881]), chemotherapy (yes/no, HR = 0.708 [0.616 - 0.813]), and radiotherapy (yes/no, HR = 0.802 [0.702 - 0.917]) were independent prognostic factors of SCLC patients and were included in the nomogram. The time-dependent AUCs of this model in the training set were 0.699, 0.683, and 0.683 for predicting 1-, 3-, and 5-year OS, and 0.698, 0.698, and 0.639 in the validation set, respectively. The predicted calibration curves aligned with the ideal curves, and the DCA curves, the IDI, and the NRI collectively demonstrated that the prognostic model had a superior net benefit than the TNM staging system. CONCLUSION: The nomogram using SCLC patients in Shandong surpassed the TNM staging system in survival prediction accuracy and enabled the stratification of patients with distinct prognostic risks based on nomogram scores.

Age at menopause is inversely related to the prevalence of common gynecologic cancers: a study based on NHANES.

Background: The fluctuation or even loss of estrogen level caused by menopause in women, and most gynecological cancers often occur before and after menopause, so the age of menopause may be related to the occurrence of gynecological cancer. Aim: To investigate whether the age at menopause is independently associated with the incidence of gynecological cancers and to analyze the possible influencing factors. Methods: We selected the NHANES public database to conduct the study, and by excluding relevant influencing factors, we finally included 5706 NHANES participants who had full data on age at menopause and the occurrence of gynecologic cancers to analyze the relationship between the amount of age at menopause and gynecologic cancers based on univariate or multifactorial logistic regression analysis. Further, the relationship between age at menopause and the prevalence of different gynecologic cancers was investigated, and changes in the prevalence of different gynecologic cancers by age at menopause subgroups were observed. Finally, other relevant factors affecting the prevalence of gynecologic cancers were further investigated by subgroup analysis as well as subcluster analysis. Results: Univariate logistic regression analysis between age at menopause and gynecologic tumor prevalence revealed a negative association between age at menopause and the prevalence of common gynecologic cancers ovarian and cervical cancer, and after adjusting for the effects of covariates, a higher risk of gynecologic tumors was found with statistically significant differences at earlier age at menopause. The regression results showed a negative association between age at menopause and gynecologic cancer prevalence in cervical and ovarian cancer patients (P<0.01,P<0.01). Cervical cancer (OR: 0.91, 95% CI: 0.87,0.94) and ovarian cancer (OR: 0.90, 95% CI: 0.86, 0.95) were more prevalent among those with younger age at menopause. Conclusion: Age at menopause is negatively associated with the prevalence of cervical and ovarian cancers, and the earlier the age at menopause, the greater the risk of developing gynecological cancers.