Ankylosing spondylitis and psychiatric disorders in European population: a Mendelian randomization study.

Background: Epidemiologic evidence has demonstrated a correlation between ankylosing spondylitis and psychiatric disorders. However, little is known about the common genetics and causality of this association. This study aimed to investigate the common genetics and causality between ankylosing spondylitis (AS) and psychiatric disorders. Methods: A two-sample Mendelian Randomization (MR) analysis was carried out to confirm causal relationships between ankylosing spondylitis and five mental health conditions including major depressive disorder (MDD), anxiety disorder (AXD), schizophrenia (SCZ), bipolar disorder (BIP), and anorexia nervosa (AN). Genetic instrumental variables associated with exposures and outcomes were derived from the largest available summary statistics of genome-wide association studies (GWAS). Bidirectional causal estimation of MR was primarily obtained using the inverse variance weighting (IVW) method. Other MR methods include MR-Egger regression, Weighted Median Estimator (WME), Weighted Mode, Simple Mode, and Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO). Sensitivity analyses are conducted to estimate the robustness of MR results. Results: The findings suggest that AS may be causally responsible for the risk of developing SCZ (OR = 1.18, 95% confidence interval = (1.06, 1.31), P = 2.58 × 10-3) and AN (OR = 1.32, 95% confidence interval = (1.07, 1.64), P = 9.43 × 10-3). In addition, MDD, AXD, SCZ, AN, and BIP were not inversely causally related to AS (all p > 0.05). Conclusion: Our study provides fresh insights into the relationship between AS and psychiatric disorders (SCZ and AN). Furthermore, it may provide new clues for risk management and preventive interventions for mental disorders in patients with AS.

Two web-based dynamically interactive nomograms and risk stratification systems for predicting survival outcomes and guiding treatment in non-metastatic nasopharyngeal carcinoma.

BACKGROUND: A nomogram is a valuable and easily accessible tool for individualizing cancer prognosis. This study aims to establish and validate two prognostic nomograms for long-term overall survival (OS) and cancer-specific survival (CSS) in non-metastatic nasopharyngeal carcinoma (NPC) patients and to investigate the treatment options for the nomogram-based risk stratification subgroups. METHODS: A total of 3959 patients with non-metastatic NPC between 2004 and 2015 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. The patients were randomly allocated to the training and validation cohorts in a 7:3 ratio. Prognostic nomograms were constructed to estimate OS and CSS by integrating significant variables from multivariate Cox regression employing a backward stepwise method. We examined the correlation indices (C-index) and areas under the curves (AUC) of time-dependent receiver operating characteristic curves to assess the discriminative ability of our survival models. The comprehensive enhancements of predictive performance were evaluated with net reclassification operating improvement (NRI) and integrated discrimination improvement (IDI). Reliability was validated using calibration plots. Decision curve analysis (DCA) was used to estimate clinical efficacy and capability. Finally, the nomogram-based risk stratification system used Kaplan-Meier survival analysis and log-rank tests to examine differences between subgroups. RESULTS: The following independent parameters were significant predictors for OS: sex, age, race, marital status, histological type, median household income, AJCC stage tumor size, and lymph node size. Except for the race variables mentioned above, the rest were independent prognostic factors for CSS. The C-index, AUC, NRI, and IDI indicated satisfactory discriminating properties. The calibration curves exhibited high concordance with the exact outcomes. Moreover, the DCA demonstrated performed well for net benefits. The prognosis significantly differed between low- and high-risk patients (p < 0.001). In a treatment-based stratified survival analysis in risk-stratified subgroups, chemotherapy benefited patients in the high-risk group compared to radiotherapy alone. Radiotherapy only was recommended in the low-risk group. CONCLUSIONS: Our nomograms have satisfactory performance and have been validated. It can assist clinicians in prognosis assessment and individualized treatment of non-metastatic NPC patients.