Development and validation of a predictive model for penile cancer based on the surveillance, epidemiology, and end results database and multi-center cases.

PURPOSE: Penile cancer (PC) is a great impact on the quality of life and psychological status of patients. This study aimed to construct nomograms using data from the Surveillance, Epidemiology, and End Results (SEER) database to predict overall survival (OS) and cancer-specific survival (CSS) in patients with penile cancer (PC). METHODS: Patients were divided into a training cohort (n = 634) and a validation cohort (n = 272) in a 7:3 ratio. Independent risk factors influencing the prognosis of PC were screened using univariate and multivariate Cox analyses, and models for predicting PC were developed. Data from 203 patients with PC in four tertiary hospitals in Gansu Province from 2012 to 2021 were externally validated. RESULTS: Univariate analysis and multivariate analysis showed revealed that the OS-related factors were age, grade, T stage, N stage, M stage and tumor size (p < 0.05); the CSS-related factors were age, mode of surgery, T stage, N stage, M stage and tumor size (p < 0.05). The C-indices of the OS and CSS nomograms in the training cohort were 0.743 [95% confidence interval (CI) (0.714-0.772)] and 0.797 (0.762-0.832), respectively. The C-indices of the OS and CSS nomograms in the internal validation cohort were 0.735 (0.686-0.784) and 0.755 (0.688-0.822), respectively, and those in the external validation cohort were 0.801 (0.746-0.856) and 0.863 (0.812-0.914), respectively. Receiver operating characteristic (ROC) curves, calibration curves, and survival curves all demonstrated good predictive performance of the nomograms. CONCLUSION: The nomograms for PC were developed using the SEER database. The accuracy and clinical usefulness of the model were validated through a combination of internal and external validations.

Association between multiple sclerosis and cancer risk: An extensive review/meta and Mendelian randomization analyses.

BACKGROUND: Observational investigations examining cancer risk among multiple sclerosis (MS) patients have produced contradictory findings. Herein, we performed an extensive review and meta-analysis to evaluate the correlation and causation between MS and cancer incidence. METHODS: We systematically screened for published articles examining cancer incidences among MS patients within the Cochrane Library, PubMed, and Embase databases. Next, we employed STATA v.16.0 for data analysis. Following meta-analysis, we performed a two-sample Mendelian randomization (MR) analysis to uncover the underlying mechanism behind the MS-mediated regulation of certain cancers. RESULTS: Overall, we selected 18 articles encompassing 14 individual cancers incidences and a total of 368,952 patients for meta-analysis. Based on our analysis, there was reduced pancreatic (ES = 0.68; 95% CI: 0.49-0.93; I 2 = 0%) and ovarian cancer (ES = 0.65; 95% CI: 0.53-0.80; I 2 = 86.7%) co-occurrences among MS patients. Meanwhile, the incidences of breast (ES = 1.10; 95% CI: 1.01-1.21; I 2 = 60.9%) and brain cancers (ES = 1.94; 95% CI: 1.12-3.37; I 2 = 56.1%) were elevated among the same population. However, MR analysis revealed the opposite relation between MS and breast cancer risk (OR = 0.94392; 95% CI: 0.91011-0.97900, P = 0.002). Moreover, it revealed strong incidence of lung cancer (OR = 1.0004; 95% CI: 1.0001-1.0083, P = 0.001) among MS patients, as evidenced by the inverse variance weighting estimator. Lastly, MR found that other forms of cancers were not significantly related to MS. CONCLUSIONS: Using meta-analysis, we demonstrated that MS patients exhibited enhanced pancreatic and ovarian cancer risk, and diminished breast and brain cancer risk. However, using MR analysis, we discovered an inverse relation between MS and breast cancer risk, and additionally saw an uptick in lung cancer co-occurrence among MS patients.

Prognostic value of preoperative inflammation-based predictors in patients with bladder carcinoma after radical cystectomy.

AIMS: Emerging evidence has related inflammation-based biomarkers to numerous carcinomas, including bladder carcinoma (BC). However, the role of inflammatory biomarkers in the prognosis of BC remains inconclusive. This study aimed to compare preoperative plasma fibrinogen (PF) and other inflammatory biomarkers such as the platelet-lymphocyte ratio (PLR), neutrophil-lymphocyte ratio (NLR), lymphocyte-monocyte ratio (LMR), C-reactive protein (CRP) level, and serum albumin level to predict the prognosis of patients with BC. METHODS: This article focused on a retrospective analysis of 175 patients with newly diagnosed BC who were admitted to our hospital from March 2005 to March 2016. Of these BC patients, 136 had undergone radical cystectomy (RC). RESULTS: According to multivariate analysis, high PF level was an independent predictor of overall survival (OS) in 136 BC patients receiving RC (HR = 3.759; P = 0.011), but not for all 175 BC patients. Combining the NLR and PF values showed higher predictive accuracy for OS than NLR or PF alone (P < 0.05). Additionally, for 136 BC patients who had undergone RC, a close relationship was found between high PF levels (≥3.39 g/L) and lymph node metastasis (P = 0.011) and clinical T stage (P = 0.015). Furthermore, PF was a superior prognostic factor compared with the LMR, PLR, CRP, and albumin values in 136 BC patients who had undergone RC (P < 0.001). CONCLUSIONS: The preoperative PF level may be a prognostic biomarker; and when combined with the NLR, it can improve the predictive ability of the survival of BC patients, particularly of BC patients who underwent RC.

Screening and identification of specific markers for bladder transitional cell carcinoma from urine urothelial cells with suppressive subtractive hybridization and cDNA microarray.

OBJECTIVE: The objective of this study was to screen and identify differentially expressed genes in invasive bladder transitional cell carcinoma (BTCC). METHODS: Voided urine samples were collected from consecutive patients with BTCC and patients under surveillance for bladder cancer recurrence; voided urine samples from patients with non-malignant diseases served as control. We identified the differentially expressed genes by comparing urine samples of bladder carcinoma to that of the control group with suppressive subtractive hybridization (SSH) and cDNA microarray. The differentially expressed genes were verified by quantitative real-time polymerase chain reaction (QPCR). RESULTS: From the 762 white colonies, a total of 449 positive clones were obtained in which 112 were found to be upregulated in BTCC. Sequencing and homology analysis were performed for these 112 clonies. The detection rates of some known genes (including IGF-1, human telomerase reverse transcriptase [hTERT], bladder cancer specific nuclear matrix protein 4 [BLCA-4] and homeobox A13 [HOXA13]) for BTCC at the Ta, T1 and >T1 stages were 48%, 90% and 100%, respectively, with a specificity of 85%. The test specificity was 80% for the 30 control patients with urinary tract infections. The combination of BLCA-4 and HOXA13 could distinguish between low- and high-grade tumours, with specificity and sensitivity of 80%. CONCLUSION: We successfully constructed a reliable SSH library of BTCC and found that combination detection insulin-like growth factor 1 (IGF-1), hTERT, BLCA-4 and HOXA13 genes could help to evaluate BTCC at different stages.