Journal of Endocrinological Investigation

Androgens in endometrial carcinoma: the killer or helper?

Abstract Purpose The aim of this review is to discuss the role of androgens in the progression of endometrial carcinoma (EC) with particular focus on the different kinds of androgenic hormones, androgen receptor (AR) and intracrine androgen metabolism. Methods A comprehensive literature search within PubMed was performed. Selected publications related to androgens and EC were reviewed. Results There are different kinds of androgenic hormones, and different kinds of androgens may have different effects. Elevated androgens (especially testosterone) have been associated with an increased EC risk in postmenopausal women. 5α-reductases (5α-Reds) and 17β-hydroxysteroid dehydrogenase type 2 (17βHSD2) pathway may inhibit the progression of EC mediated by dihydrotestosterone (DHT), but aromatases stimulate further progression of EC. The most of studies accessing the prognostic value of AR have found that AR expression may be a favorable prognostic indicator. Conclusion Androgens may have both oncogenic and tumor suppressive roles. Androgen-specific biases in metabolism and the expression of AR may contribute to the different prognosis of patients with EC.

Postmenopausal onset of androgen excess: a diagnostic and therapeutic algorithm based on extensive clinical experience

Abstract Purpose Postmenopausal hyperandrogenism is a rare condition that requires identifying those women bearing a life-threatening tumor. We aimed to study diagnostic work-up and management of postmenopausal androgen excess, proposing an algorithm for clinical decision supporting. Methods We conducted an observational cross-sectional study and longitudinal follow-up including 51 consecutive menopausal patients reported for hyperandrogenism between 2003 and 2023 to our clinics. We assessed diagnostic testing accuracy and performance by receiver operating characteristic curves, their respective areas under the curve (AUCROC), and 95% confidence intervals (95%CI), for distinguishing between benign and malignant conditions, and androgen excess source. Results Most commonly, postmenopausal hyperandrogenism derived from benign conditions such as ovarian hyperthecosis (n = 9). However, four (8%) patients had borderline/malignant tumors arising at the ovaries (n = 3) or adrenals (n = 1). These latter were more likely to develop virilization than those with benign disorders [specificity(95%CI)]: 0.87 (0.69; 0.92)]. Circulating total testosterone [AUCROC(95%CI): 0.899 (0.795; 1.000)] and estradiol [AUCROC(95%CI): 0.912 (0.812; 1.000)] concentrations showed good performances for discriminating between both conditions. Transvaginal-ultrasonography found two out of three potentially malignant ovarian neoplasms, and another was apparent on a pelvic computed tomography scan. An adrenal computed tomography scan also located an androgen-secreting carcinoma. Conclusions Clinical or biochemical features of an aggressive androgen-secreting tumor should lead to urgently obtaining a targeted imaging. At first, an abdominal-pelvic CT scan represents the best choice to perceive adrenal malignancy, and may identify aggressive ovarian tumors. When warning signs are lacking, a calm and orderly work-up allows properly addressing the diagnostic challenge of postmenopausal hyperandrogenism.

Association between SGLT2 inhibitors and genital cancer: a meta-analysis and mendelian randomization study

Competing risk nomogram and risk classification system for evaluating overall and cancer-specific survival in neuroendocrine carcinoma of the cervix: a population-based retrospective study

Abstract Objective Neuroendocrine carcinoma of the cervix (NECC) is a rare malignancy with poor clinical prognosis due to limited therapeutic options. This study aimed to establish a risk-stratification score and nomogram models to predict prognosis in NECC patients. Methods Data on individuals diagnosed with NECC between 2000 and 2019 were retrieved from the Surveillance Epidemiology and End Results (SEER) database and then randomly classified into training and validation cohorts (7:3). Univariate and multivariate Cox regression analyses evaluated independent indicators of prognosis. Least absolute shrinkage and selection operator (LASSO) regression analysis further assisted in confirming candidate variables. Based on these factors, cancer-specific survival (CSS) and overall survival (OS) nomograms that predict survival over 1, 3, and 5 years were constructed. The receiver operating characteristic (ROC) curve, the concordance index (C-index), and the calibration curve estimated the precision and discriminability of the competing risk nomogram for both cohorts. Finally, we assessed the clinical value of the nomograms using decision curve analysis (DCA). Results Data from 2348 patients were obtained from the SEER database. Age, tumor stage, T stage, N stage, chemotherapy, radiotherapy, and surgery predicted OS. Additionally, histological type was another standalone indicator of CSS prognosis. For predicting CSS, the C-index was 0.751 (95% CI 0.731 ~ 0.770) and 0.740 (95% CI 0.710 ~ 0.770) for the training and validation cohorts, respectively. Furthermore, the C-index in OS prediction was 0.757 (95% CI 0.738 ~ 0.776) and 0.747 (95% CI 0.718 ~ 0.776) for both cohorts. The proposed model had an excellent discriminative ability. Good accuracy and discriminability were also demonstrated using the AUC and calibration curves. Additionally, DCA demonstrated the high clinical potential of the nomograms for CSS and OS prediction. We constructed a corresponding risk classification system using nomogram scores. For the whole cohort, the median CSS times for the low-, moderate-, and high-risk groups were 59.3, 19.5, and 7.4 months, respectively. Conclusion New competing risk nomograms and a risk classification system were successfully developed to predict the 1-, 3-, and 5-year CSS and OS of NECC patients. The models are internally accurate and reliable and may guide clinicians toward better clinical decisions and the development of personalized treatment plans.