A novel nomogram based on inflammatory-nutritional biomarkers for gallbladder cancer after surgical resection.

PURPOSE: Systemic inflammation and nutrition are vital for tumor progression. This study aimed to identify prognostic inflammation nutrition markers and develop a predictive nomogram for gallbladder cancer (GBC). METHODS: A total of 123 patients with GBC who underwent surgical resection at the First Affiliated Hospital of Soochow University and Suzhou Kowloon Hospital were included in our study. The final prognostic variables were identified using univariate and multivariate analyses. A nomogram model was then established, and the consistency index (C-index), calibration curves, and Kaplan-Meier analysis were performed to evaluate the accuracy and discrimination of the nomogram. The area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA) suggested that our nomogram had better predictive ability and clinical feasibility than a published model. RESULTS: The cox regression analysis showed that carcinoembryonic antigen (CEA) > 4.580, albumin-bilirubin (ALBI) > -2.091, geriatric nutritional risk index (GNRI) < 90.83, T3-T4, and N2 are independent prognostic factors. A predictive nomogram was constructed with a C-index of 0.793. In the calibration curves, the nomogram-predicted 1-, 3-, and 5-year survival matched well with the actual survival. Kaplan-Meier analysis showed that the high-risk group had worse survival than the low-risk group (P < 0.001). Finally, our nomogram achieved better 1-, 3- and 5-year AUCs than an established model (0.871, 0.844, and 0.781 vs. 0.753, 0.750, and 0.693). DCA also confirmed that our model outperformed the established model. CONCLUSIONS: In conclusion, our study revealed that CEA > 4.580, GNRI < 90.83, ALBI > -2.091, T3-T4 stage, and N2 were related to clinical outcomes of patients with GBC after surgical resection. The constructed nomogram has superior predictive ability and clinical practicality.

A novel nomogram integrating body composition and inflammatory-nutritional markers for predicting postoperative complications in patients with adhesive small bowel obstruction.

Background: Postoperative complications in adhesive small bowel obstruction (ASBO) significantly escalate healthcare costs and prolong hospital stays. This study endeavors to construct a nomogram that synergizes computed tomography (CT) body composition data with inflammatory-nutritional markers to forecast postoperative complications in ASBO. Methods: The study's internal cohort consisted of 190 ASBO patients recruited from October 2017 to November 2021, subsequently partitioned into training (n = 133) and internal validation (n = 57) groups at a 7:3 ratio. An additional external cohort comprised 52 patients. Body composition assessments were conducted at the third lumbar vertebral level utilizing CT images. Baseline characteristics alongside systemic inflammatory responses were meticulously documented. Through univariable and multivariable regression analyses, risk factors pertinent to postoperative complications were identified, culminating in the creation of a predictive nomogram. The nomogram's precision was appraised using the concordance index (C-index) and the area under the receiver operating characteristic (ROC) curve. Results: Postoperative complications were observed in 65 (48.87%), 26 (45.61%), and 22 (42.31%) patients across the three cohorts, respectively. Multivariate analysis revealed that nutrition risk score (NRS), intestinal strangulation, skeletal muscle index (SMI), subcutaneous fat index (SFI), neutrophil-lymphocyte ratio (NLR), and lymphocyte-monocyte ratio (LMR) were independently predictive of postoperative complications. These preoperative indicators were integral to the nomogram's formulation. The model, amalgamating body composition and inflammatory-nutritional indices, demonstrated superior performance: the internal training set exhibited a 0.878 AUC (95% CI, 0.802-0.954), 0.755 accuracy, and 0.625 sensitivity; the internal validation set displayed a 0.831 AUC (95% CI, 0.675-0.986), 0.818 accuracy, and 0.812 sensitivity. In the external cohort, the model yielded an AUC of 0.886 (95% CI, 0.799-0.974), 0.808 accuracy, and 0.909 sensitivity. Calibration curves affirmed a strong concordance between predicted outcomes and actual events. Decision curve analysis substantiated that the model could confer benefits on patients with ASBO. Conclusion: A rigorously developed and validated nomogram that incorporates body composition and inflammatory-nutritional indices proves to be a valuable tool for anticipating postoperative complications in ASBO patients, thus facilitating enhanced clinical decision-making.

Reporting perioperative complications of radical cystectomy: the influence of using standard methodology based on ICARUS and EAU quality criteria.

PURPOSE: We aimed to evaluate perioperative complications of radical cystectomy (RC) by using standardized methodology. Additionally, we identified independent risk factors associated with perioperative complications. MATERIALS AND METHODS: We retrospectively analyzed 30-day and 90-day perioperative complications of 211 consecutive RC patients. The intraoperative and postoperative complications were defined according to Clavien-Dindo classification (CDC) and reported based on the ICARUS criteria, Martin, and EAU quality criteria. Age-adjusted Charlson comorbidity index (ACCI), systemic inflammatory response index (SIRI), body mass index (BMI) ≥ 25 kg/m2, and neoadjuvant chemotherapy (NAC) were also evaluated. Multivariable regression models according to severe (CDC ≥ IIIb grade) complications were tested. RESULTS: Overall, 88.6% (187/211) patients experienced at least one intraoperative complication. Bleeding during cystectomy was the most common complication observed (81.5% [172/211]). Severe intraoperative complications (EAUiaiC grade > 2) were recorded in 8 patients. Overall, 521 postoperative complications were recorded. Overall, 69.6% of the patients experienced complications. Thirty-nine patients suffered from most severe (CDC ≥ IIIb grade) complications. ACCI (OR: 1.492 [1.144-1.947], p = 0.003), SIRI (OR: 1.279 [1.029-1.575], p = 0.031), BMI (OR: 3.62 [1.58-8.29], p = 0.002), and NAC (OR: 0.342 [0.133-0.880], p = 0.025) were significant independent predictive factors for 90-day most severe complications (CDC ≥ IIIb grade). CONCLUSIONS: RC complications were reported within a standardized manner, concordant with the ICARUS and Martin criteria and EAU guideline recommendations. Complication reporting seems to be improved with the use of standard methodology. Our results showed that ACCI, SIRI, and BMI ≥ 25 kg/m2 and the absence of NAC were significant predictive factors for most severe complications.