The predictive value of machine learning and nomograms for lymph node metastasis of prostate cancer: a systematic review and meta-analysis.

BACKGROUND: In clinical practice, there are currently a variety of nomograms for predicting lymph node metastasis (LNM) of prostate cancer. At the same time, some scholars have introduced machine learning (ML) into the prediction of LNM of prostate cancer. However, the predictive value of nomograms and ML remains controversial. Based on this situation, this systematic review and meta-analysis was performed to explore the predictive value of various nomograms currently recommended and newly-developed ML models for LNM in prostate cancer patients. EVIDENCE ACQUISITION: Cochrane, PubMed, Embase, and Web of Science were searched up to November 1, 2022. The risk of bias in the included studies was evaluated using the Prediction model Risk of Bias Assessment Tool (PROBAST). The concordance index (C-index), sensitivity, and specificity were adopted to evaluate the predictive accuracy of the models. RESULTS: Thirty-one studies (18,803 patients) were included. Seven kinds of nomograms currently recommended, dominated by Briganti nomogram or MSKCC nomogram, were covered in the included studies. For newly-developed ML models, the C-index for LNM prediction in the training set and validation set was 0.846 [95%CI (0.818, 0.873)] and 0.862 [95%CI (0.819-0.905)] respectively. Most ML models in the training set were based on Logistic Regression (LR), which had a sensitivity of 0.78 [95%CI (0.70, 0.85)] and a specificity of 0.85 [95%CI (0.77, 0.90)] in the training set, and a sensitivity of 0.81 [95%CI (0.67, 0.89)] and a specificity of 0.82 [95%CI (0.75, 0.88)] in the validation set. For the recommended nomograms, the C-index in the validation set was 0.745 [95%CI (0.701, 0.790)] for the Briganti nomogram and 0.714 [95%CI (0.662, 0.765)] for the MSKCC nomogram. CONCLUSION: The predictive accuracy of ML is superior to existing clinically recommended nomograms, and appropriate updates can be conducted to existing nomograms according to special situations.

Prognostic value of pretreatment serum albumin-globulin ratio in urothelial carcinoma: A systematic review and meta-analysis.

Objective: To evaluate whether pretreatment albumin-globulin ratio (AGR) can be used as a biomarker for predicting the prognosis of patients with urothelial carcinoma (UC). Methods: We systematically searched PubMed, Web of Science, China National Knowledge Infrastructure (CNKI), Google Scholar and Cochrane Library; the search time was up to May 2022. Stata 16.0 was used for data processing and statistical analysis. Results: We identified 12 studies with 5,727 patients from 317 unique citations during the meta-analysis. Our results suggested that a low AGR before treatment was significantly associated with poor overall survival (OS) [hazard ratio (HR) = 1.99, 95% confidence interval (CI) = 1.45-2.75, P < 0.001], cancer-specific survival (CSS) [HR=2.01, 95% CI = 1.50-2.69, P < 0.001] and recurrence-free survival (RFS) [HR=1.39, 95% CI = 1.12-1.72, P = 0.002]. Furthermore, we defined different subgroups according to ethnicity, cancer type, cut-off value, sample size and stage. Similar prognostic outcomes for OS and CSS were observed in most subgroups. However, for subgroup of stage, the low pretreatment AGR only predicted the poor survival of patients with non-metastatic UC. Conclusion: Our meta-analysis revealed that the AGR before treatment could be used as a predictive biomarker to indicate the prognosis of UC patients during clinical practice, especially in patients with non-metastatic UC.

Comparison of Perioperative Outcomes of Robotic-Assisted vs Laparoscopic Adrenalectomy for Pheochromocytoma: A Meta-Analysis.

OBJECTIVE: To compare the efficacy and safety of robotic-assisted adrenalectomy (RA) and standard laparoscopic adrenalectomy (LA) for pheochromocytoma (PHEO). METHODS: We systematically searched the Cochrane Library, PubMed, Embase, and Science databases for studies published through January 2021. Controlled trials on RA and LA for PHEOs were included. The meta-analysis was conducted with the Review Manager 5.4 software. RESULTS: Four studies with 386 patients were included in the analysis. There were no significant differences in OT (WMD: 0.16; 95% CI: -28.50 to 28.82; I2 = 89%; P = 0.99), transfusion rate (OR: 0.70; 95% CI: 0.07 to 7.07; I2 = 64%; P = 0.77), conversion rate (OR: 0.44; 95% CI: 0.07 to 2.88; I2 = 0%; P = 0.39), complication rate (OR: 1.06; 95% CI: 0.62 to 1.82; I2 = 0%; P = 0.84) among patients undergoing RA and LA. However, compared with patients who underwent LA, patients who underwent RA had a shorter LOS (OR: -0.50; 95% CI: -0.55 to 0.45; I2 = 31%; P<0.01), less EBL (WMD: -0.85; 95% CI: -13.56 to -2.54; I2 = 44%; P<0.01), and fewer IHD (OR: 0.34; 95% CI: 0.17 to 0.70; I2 = 0%; P<0.01). CONCLUSION: The RA for pheochromocytoma achieve better outcomes over LA in terms of safety and efficacy.

Frictional Wear and Corrosion Behavior of AlCoCrFeNi High-Entropy Alloy Coatings Synthesized by Atmospheric Plasma Spraying.

High-entropy alloy coatings (HEAC) exhibit good frictional wear and corrosion resistances, which are of importance for structure materials. In this study, the microstructure, surface morphology, hardness, frictional wear and corrosion resistance of an AlCoCrFeNi high-entropy alloy coating synthesized by atmospheric plasma spraying (APS) were investigated. The frictional wear and corrosion resistance of the coating are simultaneously improved with an increase of the power of APS. The influence of the APS process on the microstructure and mechanical behavior is elucidated. The mechanisms of frictional wear and corrosion behavior of the AlCoCrFeNi HEAC are discussed in detail.