Prognostic nutritional index combined with NLR to construct a survival prediction model and decision analysis of patients with muscle-invasive bladder cancer after surgery.

OBJECTIVES: To build a nomogram prediction model, assess its predictive ability, and perform a survival decision analysis on patients with muscle-invasive bladder cancer (MIBC) to study risk factors affecting overall survival (OS). METHODS: A retrospective analysis was performed on the clinical information of 262 patients with MIBC who underwent radical cystectomy (RC) at the Urology Department of the Second Affiliated Hospital of Kunming Medical University between July 2015 and August 2021. The final model variables that were included were chosen using single-factor stepwise Cox regression, optimal subset regression, and LASSO regression + cross-validation with the minimum AIC value. The next step was to do a multivariate Cox regression analysis. The establishment of a nomogram model by fitting and the screening out of independent risk factors impacting the survival of patients with MIBC having radical resection. Receiver Activity Characteristic curves, C-index, and a calibration plot evaluated the prediction accuracy, validity, and clinical benefit of the model. The 1-, 3-, and 5-year survival rates were then computed for each risk factor using a Kaplan-Meier survival analysis. RESULTS: 262 eligible patients in total were enrolled. With a median follow-up of 32 months, the follow-up period ranged from 2 to 83 months. 171 cases (65.27%) survived while 91 cases (34.73%) perished. Age (HR = 1.06 [1.04; 1.08], p = 0.001), preoperative hydronephrosis (HR = 0.69 [0.46, 1.05], p = 0.087), T stage (HR = 2.06 [1.09, 3.93], p = 0.027), lymphovascular invasion (LVI, HR = 1.73 [1.12, 2.67], p = 0.013), prognostic nutritional index (PNI, HR = 1.70 [1.09, 2.63], p = 0.018), and neutrophil-to-lymphocyte ratio (NLR, HR = 0.52 [0.29, 0.93)], p = 0.026) were independent risk factor for the survival of bladder cancer patients. Create a nomogram based on the aforementioned findings, and then draw the 1-year, 3-year, and 5-year OS receiver operating characteristic curves by the nomogram. The AUC values were 0.811 (95% CI [0.752, 0.869]), 0.814 (95% CI [0.755, 0.873]), and 0.787 (95% CI [0.708, 0.865]), respectively, and the calibration plot matched the predicted value well. The 1-year, 3-year, and 5-year decision curve analyses were higher than the ALL line and None line at threshold values of >5%, 5%-70%, and 20%-70% indicating that the model has good clinical applicability. The calibration plot for the Bootstrap 1000-time resampled validation model was similar to the actual value. Patients with preoperative combination hydronephrosis, higher T-stage, combined LVI, low PNI, and high NLR had worse survival, according to Kaplan-Meier survival analysis for each variable. CONCLUSIONS: This study might conclude that PNI and NLR were separate risk factors that affect a patient's OS after RC for MIBC. The prognosis of bladder cancer may be predicted by PNI and NLR, but additional confirmation in randomized controlled trials is required.

Fracture risk assessment in children with benign bone lesions of long bones.

BACKGROUND: Fracture risk assessment in children with benign bone lesions of long bones remains poorly investigated. AIM: To investigate the risk factors for pathological fracture in children with benign bone lesions and to propose a modified scoring system for quantitative analysis of the pathologic fracture risk. METHODS: We retrospectively reviewed 96 pediatric patients with benign bone lesions. We compared radiographic and clinical features between 40 patients who had fractures through a benign bone lesion and 56 who had no fracture. Information including histological diagnosis, anatomical site, radiographic appearance, severity of pain, and lesion size was recorded for the patients. A modified scoring system was proposed to predict the risk of fracture. RESULTS: The univariate comparisons showed a significant difference between the fracture and non-fracture groups in terms of lesion type, pain, lesion-to-bone width, and axial cortical involvement of the patients (P < 0.05). Lesion type, pain, lesion-to-bone width, and axial cortical involvement were independently correlated with an increased risk of fracture. The mean score of the fracture group was 7.89, whereas the mean score of the non-fracture group was 6.01. The optimum cut-off value of the score to predict pathological fracture was 7. The scoring system had a sensitivity of 70% and a specificity of 80% for detecting patients with fractures. The Youden index was 0.5, which was the maximum value. The area under the receiver operator characteristic was 0.814. CONCLUSION: Lesion type, pain, lesion-to-bone width, and axial cortical involvement are risk factors for pathological fracture. The modified scoring system can provide evidence for clinical decision-making in children with benign bone lesions. A bone lesion with a total score > 7 indicates a high risk of a pathologic fracture and is an indication for prophylactic internal fixation.