Development and validation of a prognostic nomogram for predicting cancer-specific survival in advanced endometrial carcinoma after surgery: a retrospective analysis of the SEER Database.

OBJECTIVE: We aimed to construct and validate a prognostic nomogram to predict cancer-specific survival (CSS) after surgery in patients with advanced endometrial carcinoma (EC). DESIGN: Retrospective cohort study. SETTING AND PARTICIPANTS: The Surveillance, Epidemiology, and End Results (SEER) Database contains cancer incidence and survival data from population-based cancer registries in the USA. A total of 5445 patients from the SEER Database diagnosed with advanced EC between 2004 and 2015 were included and randomised 7:3 into a training cohort (n=3812) and a validation cohort (n=1633). OUTCOME MEASURE: CSS. RESULTS: The nomograms for CSS included 10 variables (positive regional nodes, age, tumour size, International Federation of Gynecology and Obstetrics (FIGO) stage, grade, ethnicity, income, radiation, chemotherapy and historical stage) based on the forward stepwise regression results. They revealed discrimination and calibration using the concordance index (C-index) and area under the time-dependent receiver operating characteristic curve, with a C-index value of 0.7324 (95% CI=0.7181 to 0.7468) and 0.7511 (95% CI=0.7301 to 0.7722) for the training and validation cohorts, respectively. Using calibration plots, a high degree of conformance was shown between the predicted and observed results. Additionally, a comparison of the nomogram and FIGO staging based on changes in the C-index, net reclassification index and integrated discrimination improvement demonstrated that the nomogram had better accuracy and efficacy. CONCLUSIONS: We successfully constructed an accurate and effective nomogram to predict CSS in patients with advanced EC, which may help clinicians determine optimal individualised treatment strategies for patients with advanced EC. The predictive performance of the nomogram was evaluated thoroughly, but only internally. Therefore, further validation using different data sources is warranted in future related studies.

Association of blood metals with serum sex hormones in adults: A cross-sectional study.

Heavy metals such as lead, mercury, and cadmium have been identified to have negative impacts on human health. Although the individual effects of these metals have been extensively researched, the present study aims to explore their combined effects and their association with serum sex hormones among adults. Data for this study were obtained from the general adult population of the 2013-2016 National Health and Nutrition Survey (NHANES) and included five metal (mercury, cadmium, manganese, lead, and selenium) exposures and three sex hormones (total testosterone [TT], estradiol [E2], and sex hormone-binding globulin [SHBG]) levels. The free androgen index (FAI) and TT/E2 ratio were also calculated. The relationships between blood metals and serum sex hormones were analysed using linear regression and restricted cubic spline regression. The effect of blood metal mixtures on sex hormone levels was examined using the quantile g-computation (qgcomp) model. There were 3,499 participants in this study, including 1,940 males and 1,559 females. In males, positive relationships between blood cadmium and serum SHBG (ß=0.049 [0.006, 0.093]), lead and SHBG (ß=0.040 [0.002, 0.079]), manganese and FAI (ß=0.080 [0.016, 0.144]), and selenium and FAI (ß=0.278 [0.054, 0.502]) were observed. In contrast, manganese and SHBG (ß=-0.137 [-0.237, -0.037]), selenium and SHBG (ß=-0.281 [-0.533, -0.028]), and manganese and TT/E2 ratio (ß=-0.094 [-0.158, -0.029]) were negative associations. In females, blood cadmium and serum TT (ß=0.082 [0.023, 0.141]), manganese and E2 (ß=0.282 [0.072, 0.493]), cadmium and SHBG (ß=0.146 [0.089, 0.203]), lead and SHBG (ß=0.163 [0.095, 0.231]), and lead and TT/E2 ratio (ß=0.174 [0.056, 0.292]) were positive relationships, while lead and E2 (ß=-0.168 [-0.315, -0.021]) and FAI (ß=-0.157 [-0.228, -0.086]) were negative associations. This correlation was stronger among elderly women (>50 years old). The qgcomp analysis revealed that the positive effect of mixed metals on SHBG was mainly driven by cadmium, while the negative effect of mixed metals on FAI was mainly driven by lead. Our findings indicate that exposure to heavy metals may disrupt hormonal homeostasis in adults, particularly in older women.