Validation of user-friendly models predicting extracapsular extension in prostate cancer patients

Objective: There are many models to predict extracapsular extension (ECE) in patients with prostate cancer. We aimed to externally validate several models in a Japanese cohort. Methods: We included patients treated with robotic-assisted radical prostatectomy for prostate cancer. The risk of ECE was calculated for each patient in several models (prostate side-specific and non-side-specific). Model performance was assessed by calculating the receiver operating curve and the area under the curve (AUC), calibration plots, and decision curve analyses. Results: We identified ECE in 117 (32.9%) of the 356 prostate lobes included. Patients with ECE had a statistically significant higher prostate-specific antigen level, percentage of positive digital rectal examination, percentage of hypoechoic nodes, percentage of magnetic resonance imaging nodes or ECE suggestion, percentage of biopsy positive cores, International Society of Urological Pathology grade group, and percentage of core involvement. Among the side-specific models, the Soeterik, Patel, Sayyid, Martini, and Steuber models presented AUC of 0.81, 0.78, 0.77, 0.75, and 0.73, respectively. Among the non-side-specific models, the memorial Sloan Kettering Cancer Center web calculator, the Roach formula, the Partin tables of 2016, 2013, and 2007 presented AUC of 0.74, 0.72, 0.64, 0.61, and 0.60, respectively. However, the 95% confidence interval for most of these models overlapped. The side-specific models presented adequate calibration. In the decision curve analyses, most models showed net benefit, but it overlapped among them. Conclusion: Models predicting ECE were externally validated in Japanese men. The side-specific models predicted better than the non-side-specific models. The Soeterik and Patel models were the most accurate performing models

Simple screening method for the diagnosis of nonB-nonC hepatocellular carcinoma

Aim: The incidence of non-virus-related nonB-nonC hepatocellular carcinoma (NBNC-HCC) is on the rise. However, screening at-risk individuals using imaging methods is complicated by the large size of the at-risk patient pool. The aim of this study is to develop an effective simple screening method, using blood tests.Methods: The diagnostic value of aspartate aminotransferase (AST), alpha-fetoprotein (AFP), and des-gamma-carboxy prothrombin (DCP) was analyzed using sera from 203 NBNB-HCC patients and 106 diabetes mellitus patients.Results: Areas under receiver operating characteristic curves for AST, AFP, and DCP were 0.844, 0.901, and 0.914, respectively. The optimal cut-offs for diagnosing NBNC-HCC based on Youden indices were 30 IU/L, 3.6 ng/mL, and 25 mAU/mL, respectively. On selecting patients who were positive at least one parameter (AST, AFP, or DCP), the sensitivity was 97.5%. This high sensitivity was preserved (98.0%) even in cases of non-advanced HCC (≤ 3 cm, ≤ 3 nodules). Specificity was 72.6%.Conclusion: This simple triple screen for AST, AFP, and DCP appears to have diagnostic value in NBNC-HCC and could be used to select candidates for further testing using imaging

Effect of butyrate‐producing enterobacteria on advanced hepatocellular carcinoma treatment with atezolizumab and bevacizumab

Abstract Aim Multiple studies have revealed the correlation between gut microbiome and the response to checkpoint inhibitors (CPIs) in patients with cancer, and oral administration of butyrate‐producing enterobacteria has been reported to enhance the efficacy of CPIs. However, the effects of enterobacteria on patients with hepatocellular carcinoma (HCC) are not well understood. Methods In this retrospective multicenter study, we enrolled 747 patients with advanced HCC, treated with atezolizumab and bevacizumab combination therapy. Tumor response, survival, and adverse effects were compared between 99 patients who ingested drugs containing butyric acid‐producing enterobacteria (butyric acid group) and the remaining patients (control group). Results Objective response and disease control rates in butyric acid group (29.7% and 77.8%, respectively) were higher than those in the control group (26.4% and 72.7%, respectively). However, the differences were not statistically significant (p = 0.543 and p = 0.222, respectively). No difference in median survival time was observed between the two groups (20.0 months and 21.4 months, respectively; p = 0.789), even after matching the backgrounds of the patients with propensity scores (p = 0.714). No adverse effects occurred upon the administration of butyrate‐producing bacteria. However, proteinuria (41.4% vs. 30.9%; p = 0.041), fever (17.2% vs. 10.2%, p = 0.036), and diarrhea (15.2% vs. 6.2%; p = 0.001) occurred more frequently in the butyric acid group. Conclusion Butyrate‐producing bacteria does not enhance the efficacy of atezolizumab–bevacizumab combination therapy in patients with HCC