High body mass index and pre-existing autoimmune disease are associated with an increased risk of immune-related adverse events in cancer patients treated with PD-(L)1 inhibitors across different solid tumors.

BACKGROUND: Treatment with anti-PD-(L)1 antibodies, approved for several oncology indications, can lead to immune-related adverse events (irAEs). We aimed to investigate risk factors associated with an increased reporting of irAEs in patients treated with PD-(L)1 inhibitors approved for solid tumor indications. PATIENTS AND METHODS: A retrospective review was performed of individual data from patients in phase II/III registrational studies for PD-(L)1 inhibitors in solid tumors. Data on baseline characteristics and adverse events were extracted. Univariate and multivariable logistic regression models were used to identify risk factors. RESULTS: In total, 5123 patients were included from 15 studies reporting on the use of four PD-(L)1 inhibitors for five solid tumor indications. Univariate analysis suggested that type of study drug (P < 0.001), indication (P = 0.003), body mass index (BMI) (P = 0.001), and baseline autoimmune disease (P < 0.001) were associated with an increased occurrence of any irAE. Using logistic regression analyses, three factors were identified as increasing the risk of irAE: BMI ≥ 30 kg/m2 [odds ratio (OR) 1.5, 95% confidence interval (CI) 1.2-1.8] in comparison to normal BMI, having an autoimmune disease at baseline (OR 1.8, 95% CI 1.1-2.7), and use of a PD-L1 inhibitor (OR 1.6, 95% CI 1.2-2.0). The latter finding is probably biased due to the selection of the studies in the dataset with complete information on baseline characteristics. CONCLUSION: This study was conducted using a large dataset of individual patient data from clinical trials comprising multiple solid tumor indications. We demonstrated that patients with obesity and concurrent autoimmune disease were at increased risk of developing irAEs.

Critical appraisal of the PADUA classification and assessment of the R.E.N.A.L. nephrometry score in patients undergoing partial nephrectomy.

PURPOSE: We validated the PADUA classification and assessed the R.E.N.A.L. nephrometry score to predict perioperative complications of partial nephrectomy. In addition, we assessed their interobserver variability, and the ability to predict the use of ischemia and ischemia time. MATERIALS AND METHODS: Data from consecutive cases of partial nephrectomy with or without ischemia from 3 centers were retrospectively collected. Associations between preoperative variables and complications were evaluated in univariate and multivariate analyses. Reproducibility was assessed by determining Fleiss' generalized kappa and intraclass correlation coefficients in a subcohort scored by 3 physicians with different degrees of urological expertise. RESULTS: A total of 134 partial nephrectomies were included in the study and 31 cases (23%) presented with complications. On univariate analyses complications were associated with age (p = 0.02), tumor size on computerized tomography (p = 0.01), pT stage (p = 0.001), and PADUA (p = 0.001) and R.E.N.A.L. scores (p = 0.02). In 3 multivariate models PADUA score 10 or greater (OR 3.98, p = 0.01), R.E.N.A.L. score 9 or greater (OR 4.21, p = 0.02), tumor size in cm (OR 1.35, p = 0.02) and age (OR 1.04, p = 0.04) were independent predictors of complications. The R.E.N.A.L. nephrometry score predicted the use of ischemia (p = 0.03) and both scores predicted ischemia time (both p <0.001). Kappa was 0.37 to 0.80 for PADUA components and 0.23 to 0.73 for R.E.N.A.L. components. The intraclass correlation coefficient was 0.73 for PADUA and 0.70 for R.E.N.A.L. score. CONCLUSIONS: The highest categories of PADUA and R.E.N.A.L. scores as well as clinical tumor size predict the risk of perioperative complications of partial nephrectomy. Both scores can indicate ischemia time. Their reproducibility is substantial but the implementation of these systems in clinical practice needs further refinement.