Establishment and validation of serum lipid-based nomogram for predicting the risk of prostate cancer.

BACKGROUND: This study aimed to explore the value of combined serum lipids with clinical symptoms to diagnose prostate cancer (PCa), and to develop and validate a Nomogram and prediction model to better select patients at risk of PCa for prostate biopsy. METHODS: Retrospective analysis of 548 patients who underwent prostate biopsies as a result of high serum prostate-specific antigen (PSA) levels or irregular digital rectal examinations (DRE) was conducted. The enrolled patients were randomly assigned to the training groups (n = 384, 70%) and validation groups (n = 164, 30%). To identify independent variables for PCa, serum lipids (TC, TG, HDL, LDL, apoA-1, and apoB) were taken into account in the multivariable logistic regression analyses of the training group, and established predictive models. After that, we evaluated prediction models with clinical markers using decision curves and the area under the curve (AUC). Based on training group data, a Nomogram was developed to predict PCa. RESULTS: 210 (54.70%) of the patients in the training group were diagnosed with PCa. Multivariate regression analysis showed that total PSA, f/tPSA, PSA density (PSAD), TG, LDL, DRE, and TRUS were independent risk predictors of PCa. A prediction model utilizing a Nomogram was constructed with a cut-off value of 0.502. The training and validation groups achieved area under the curve (AUC) values of 0.846 and 0.814 respectively. According to the decision curve analysis (DCA), the prediction model yielded optimal overall net benefits in both the training and validation groups, which is better than the optimal net benefit of PSA alone. After comparing our developed prediction model with two domestic models and PCPT-RC, we found that our prediction model exhibited significantly superior predictive performance. Furthermore, in comparison with clinical indicators, our Nomogram's ability to predict prostate cancer showed good estimation, suggesting its potential as a reliable tool for prognostication. CONCLUSIONS: The prediction model and Nomogram, which utilize both blood lipid levels and clinical signs, demonstrated improved accuracy in predicting the risk of prostate cancer, and consequently can guide the selection of appropriate diagnostic strategies for each patient in a more personalized manner.

Identifying stage-associated hub genes in bladder cancer via weighted gene co-expression network and robust rank aggregation analyses.

BACKGROUND: Bladder cancer (BC) is among the most frequent cancers globally. Although substantial efforts have been put to understand its pathogenesis, its underlying molecular mechanisms have not been fully elucidated. METHODS: The robust rank aggregation approach was adopted to integrate 4 eligible bladder urothelial carcinoma microarray datasets from the Gene Expression Omnibus. Differentially expressed gene sets were identified between tumor samples and equivalent healthy samples. We constructed gene co-expression networks using weighted gene co-expression network to explore the alleged relationship between BC clinical characteristics and gene sets, as well as to identify hub genes. We also incorporated the weighted gene co-expression network and robust rank aggregation to screen differentially expressed genes. RESULTS: CDH11, COL6A3, EDNRA, and SERPINF1 were selected from the key module and validated. Based on the results, significant downregulation of the hub genes occurred during the early stages of BC. Moreover, receiver operating characteristics curves and Kaplan-Meier plots showed that the genes exhibited favorable diagnostic and prognostic value for BC. Based on gene set enrichment analysis for single hub gene, all the genes were closely linked to BC cell proliferation. CONCLUSIONS: These results offer unique insight into the pathogenesis of BC and recognize CDH11, COL6A3, EDNRA, and SERPINF1 as potential biomarkers with diagnostic and prognostic roles in BC.

[Diagnosis and treatment of congenital submandibular duct dilatation].

OBJECTIVE: To study the clinical features and treatments of congenital submandibular duct dilatation. METHODS: Seven children with congenital submandibular duct dilatation from January 2008 to March 2018 were included in this study, whose average age was 5 months and 22 days. The clinical manifestations are unilateral swelling of the mouth floor. All seven children underwent sublingual gland resection, submandibular gland dilatation catheter resection, and catheter reroute under general anesthesia. Intraoperatively, the orifice of the submandibular gland was constricted and part of the catheter was dilated. RESULTS: All seven patients had good healing without swelling or cyst formation. CONCLUSIONS: Congenital submandibular duct dilatation occurs at a young age. Early diagnosis and treatment can help prevent further expansion of the catheter and avoid gland atrophy, feeding difficulty, and breathing obstruction. Simultaneous excision of the sublingual gland can avoid the formation of postoperative sublingual cyst.

[Logistic regression analysis of risk factors of serious complications related with double-J ureteral stenting following percutaneous nephrolithotomy].

OBJECTIVE: To investigate the risk factors of the serious complications related with double-J ureteral stent placement following percutaneous nephrolithotomy (PCNL). METHODS: Clinical data were reviewed for 272 patients treated with PCNL and indwelling double-J stents between January, 2014 and April, 2016. The risk factors of serious complications were identified using univariate and multivariate logistic regression analysis. RESULTS: Serious complications of double-J ureteral stenting occurred in 63 patients (23.1%). Univariate and multivariate logistic regression analysis indicated that the ureter abnormalities (ß=1.735, P=0.000, OR=5.670), stent indwelling duration (ß=1.206, P=0.028, OR=3.340), gender (ß=0.895, P=0.016, OR=2.446), preoperative urinary tract infection (ß=0.849, P=0.020 , OR=2.338) and stent size (ß=0.847, P=0.011, OR=2.333) were all risk factors of serious complications related with the procedure. CONCLUSION: Male patients are exposed to a higher risk of serious complications following PCNL. Effective management of urinary tract infection and choice of appropriate stent size in cases of ureteral abnormalities help to reduce these complications. The double-J stent should be withdrawn as soon as possible in patients with good postoperative recovery.