Objective: To analyze the risk factors for testicular atrophy (TA) in children with testicular torsion (TT) following emergent orchiopexy. Methods: Clinical data of patients with TT undergoing orchiopexy were retrospectively reviewed, including age at surgery, affected side, delayed surgery (12–24 h and more than 24 h), echogenicity of testicular parenchyma on ultrasonography (ETPU), testicular blood flow on Color Doppler ultrasonography (CDUS), surgical findings (intraoperative blood supply, the degree of torsion, and surgical approaches), and follow-up. The primary outcome was the rate of TA after orchiopexy. The secondary outcome was the testicular volume loss (TVL) between the affected testis and the contralateral. Results: A total of 113 patients were enrolled in this study with a median age of 11 years. The median follow-up was 21 months. Patients had a median TVL of 51.02% and 44 (38.94%) of them developed severe TA during follow-up. TA was significantly associated with age at surgery ( P < 0.0001), delayed surgery ( P = 0.0003), ETPU ( P = 0.0001), and intraoperative blood supply ( P = 0.0005). Multivariate logistic regression analysis showed that school-age children (OR = 0.069, P < 0.001) and puberty (OR = 0.177, P = 0.007) had a decreased risk of TA compared with preschool children, and that heterogeneous ETPU (OR = 14.489, P = 0.0279) and delayed surgery >24 h (OR = 3.921, P = 0.040) increased the risk of TA. Multivariate analysis demonstrated that ETPU ( F = 16.349, P < 0.001) and delayed surgery ( F = 6.016, P = 0.003) were independent risk factors for TVL. Conclusions: Age at surgery, delayed surgery, and ETPU may play a crucial role in predicting the TA in children with TT following emergent orchiopexy. Moreover, blood flow measured by CDUS could not predict the outcome properly.
BackgroundWilms tumor (WT) is the most common tumor in children. We aim to construct a nomogram to predict the cancer-specific survival (CSS) of WT in children and externally validate in China.MethodsWe downloaded the clinicopathological data of children with WT from 2004 to 2018 in the SEER database. At the same time, we used the clinicopathological data collected previously for all children with WT between 2013 and 2018 at Children's Hospital of Chongqing Medical University (Chongqing, China). We analyzed the difference in survival between the patients in the SEER database and our hospital. Cox regression analysis was used to screen for significant risk factors. Based on these factors, a nomogram was constructed to predict the CSS of children with WT. Calibration curve, concordance index (C-index), the area under the receiver operating curve (AUC) and decision curve analysis (DCA) was used to evaluate the accuracy and reliability of the model.ResultsWe included 1,045 children with WT in the SEER database. At the same time, we collected 112 children with WT in our hospital. The Kaplan-Meier curve suggested that children in China with WT had a higher mortality rate than those in the United States. Cox regression analysis revealed that age, lymph node density (LND), and tumor stage were significant prognostic factors for the patients in the SEER database. However, the patients in our hospital only confirmed that the tumor stage and the number of positive regional lymph nodes were significant factors. The prediction model established by the SEER database had been validated internally and externally to prove that it had good accuracy and reliability.ConclusionWe have constructed a survival prognosis prediction model for children with WT, which has been validated internally and externally to prove accuracy and reliability.
ObjectiveProstate cancer (PC) is the most common non-cutaneous malignancy in men worldwide. Accurate predicting the survival of elderly PC patients can help reduce mortality in patients. We aimed to construct nomograms to predict cancer-specific survival (CSS) and overall survival (OS) in elderly PC patients.MethodsInformation on PC patients aged 65 years and older was downloaded from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox regression models were used to determine independent risk factors for PC patients. Nomograms were developed to predict the CSS and OS of elderly PC patients based on a multivariate Cox regression model. The accuracy and discrimination of the prediction model were tested by the consistency index (C-index), the area under the subject operating characteristic curve (AUC), and the calibration curve. Decision curve analysis (DCA) was used to test the clinical value of the nomograms compared with the TNM staging system and D’Amico risk stratification system.Results135183 elderly PC patients in 2010-2018 were included. All patients were randomly assigned to the training set (N=94764) and the validation set (N=40419). Univariate and multivariate Cox regression model analysis revealed that age, race, marriage, histological grade, TNM stage, surgery, chemotherapy, radiotherapy, biopsy Gleason score (GS), and prostate-specific antigen (PSA) were independent risk factors for predicting CSS and OS in elderly patients with PC. The C-index of the training set and the validation set for predicting CSS was 0.883(95%CI:0.877-0.889) and 0.887(95%CI:0.877-0.897), respectively. The C-index of the training set and the validation set for predicting OS was 0.77(95%CI:0.766-0.774)and 0.767(95%CI:0.759-0.775), respectively. It showed that the proposed model has excellent discriminative ability. The AUC and the calibration curves also showed good accuracy and discriminability. The DCA showed that the nomograms for CSS and OS have good clinical potential value.ConclusionsWe developed new nomograms to predict CSS and OS in elderly PC patients. The models have been internally validated with good accuracy and reliability and can help doctors and patients to make better clinical decisions.
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