Background: In this study, we aimed to propose a validated prediction model for disease-free survival (DFS) after radical nephroureterectomy (RNU) in a Korean population with upper urinary tract urothelial carcinoma (UTUC).
Methods: We performed a retrospective review of 1561 cases of UTUC who underwent either open RNU (ONU, n = 906) or laparoscopic RNU (LNU, n = 615) from five tertiary Korean institutions between January 2000 and December 2012. Data were used to develop a prediction model using the Cox proportional hazards model. Prognostic factors were selected using the backward variable selection method. The prediction model performance was investigated using Harrell's concordance index (C-index) and Hosmer-Lemeshow type 2 statistics. Internal validation was performed using a bootstrap approach, and the National Cancer Center data set (n = 128) was used for external validation.
Results: A best-fitting prediction model with seven significant factors was developed. The C-index and two Hosmer-Lemeshow type statistics of the prediction model were 0.785 (95% CI, 0.755-0.815), 4.810 (P = 0.8506), and 5.285 (P = 0.8088). The optimism-corrected estimate through the internal validation was 0.774 (95% CI, 0.744-0.804) and the optimism-corrected calibration curve was close to the ideal line with mean absolute error = 0.012. In external validation, the discrimination was 0.657 (95% CI, 0.560-0.755) and the two calibration statistics were 0.790 (P = 0.9397) and 3.103 (P = 0.5408), respectively.
Conclusion: A validated prediction model based on a large Korean RNU cohort was developed with acceptable performance to estimate DFS in patients with UTUC.
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http://dx.doi.org/10.1002/cam4.2382 | DOI Listing |
J Health Organ Manag
January 2025
University of Malta, Msida, Malta.
Purpose: This study explores how corporate social responsibility (CSR) and artificial intelligence (AI) can be combined in the healthcare industry during the post-COVID-19 recovery phase. The aim is to showcase how this fusion can help tackle healthcare inequalities, enhance accessibility and support long-term sustainability.
Design/methodology/approach: Adopting a viewpoint approach, the study leverages existing literature and case studies to analyze the intersection of CSR and AI.
Diabetes Obes Metab
January 2025
Department of Hypertension and Vascular Disease, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Aims: Previous studies have shown that eGDR and TyG, as indicators of insulin resistance (IR), were key risk factors for cardiovascular disease (CVD). Our study further explored the relationship between eGDR change and new-onset CVD, and compared the predictive value of eGDR change, eGDR and TyG.
Materials And Methods: A total of 2895 participants without CVD at baseline from the China Health and Retirement Longitudinal Study (CHARLS) were included, using K-means clustering and cumulative eGDR to measure eGDR change between 2012 and 2015.
Acta Neuropathol Commun
January 2025
Hopp Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany.
Recent genomic studies have allowed the subdivision of intracranial ependymomas into molecularly distinct groups with highly specific clinical features and outcomes. The majority of supratentorial ependymomas (ST-EPN) harbor ZFTA-RELA fusions which were designated, in general, as an intermediate risk tumor variant. However, molecular prognosticators within ST-EPN ZFTA-RELA have not been determined yet.
View Article and Find Full Text PDFAlzheimers Res Ther
January 2025
UK Dementia Research Institute at Cardiff, Cardiff University, Hadyn Ellis Building, Maindy Road, Cardiff, CF24 4HQ, UK.
Background: The success of selecting high risk or early-stage Alzheimer's disease individuals for the delivery of clinical trials depends on the design and the appropriate recruitment of participants. Polygenic risk scores (PRS) show potential for identifying individuals at risk for Alzheimer's disease (AD). Our study comprehensively examines AD PRS utility using various methods and models.
View Article and Find Full Text PDFDiabetol Metab Syndr
January 2025
The International Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, No. 910, Hengshan Rd., Shanghai, 200030, China.
Background: Triglyceride-glucose (TyG) index was suggested as a possible surrogate for insulin resistance and a predictor for cardiovascular diseases and diabetes in the non-pregnant population. However, the relationship between TyG index in early pregnancy and adverse pregnancy outcomes (APOs), and the contribution of pre-pregnancy body mass index (BMI) was still illusive.
Methods: A large retrospective cohort study involving 67,936 pregnant Chinese women between 2017 and 2022 was conducted.
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