Dataset Information

Predicting long-term renal and patient survival by clinicopathological features in elderly patients undergoing a renal biopsy in a UK cohort.

ABSTRACT:

Background

Several publications have demonstrated the use of renal biopsy in elderly patients in establishing a diagnosis and enabling directed therapy. However, evidence on the long-term outcomes following biopsies is lacking. The aim of this study is to describe the renal and patient outcomes in elderly patients according to indication for biopsy, clinical parameters and the histological diagnosis.

Methods

We performed a retrospective cohort study of 463 patients >70?years old who underwent a renal biopsy at our centre between 2006 and 2015.

Results

The median age of the patients was 74.8 (range 70.0-89.6) years. The most frequent primary diagnoses were pauci-immune crescentic glomerulonephritis (GN; 12%), acute interstitial nephritis (10.8%) and membranous GN (7.1%). Death-censored renal survival at 1 and 5 years following the index biopsy was 85.2 and 75.9%, respectively, and patient survival at 1 and 5 years was 92.2 and 71.6%, respectively. Patients who progressed to end-stage renal disease (ESRD) were at higher risk of dying compared with patients who did not require dialysis [hazard ratio 2.41 (95% confidence interval 1.58-3.68; P?ConclusionsThis study demonstrates that renal biopsies in the elderly not only enable directed therapy, but also provide prognostic information on renal and patient survival.

SUBMITTER: Navaratnarajah A

PROVIDER: S-EPMC6672059 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Publications

Predicting long-term renal and patient survival by clinicopathological features in elderly patients undergoing a renal biopsy in a UK cohort.

Navaratnarajah Arunraj A Sambasivan Khrishanthne K Cook Terry H TH Pusey Charles C Roufosse Candice C Willicombe Michelle M

Clinical kidney journal 20190228 4

<h4>Background</h4>Several publications have demonstrated the use of renal biopsy in elderly patients in establishing a diagnosis and enabling directed therapy. However, evidence on the long-term outcomes following biopsies is lacking. The aim of this study is to describe the renal and patient outcomes in elderly patients according to indication for biopsy, clinical parameters and the histological diagnosis.<h4>Methods</h4>We performed a retrospective cohort study of 463 patients >70 years old w ...[more]

PMID: 31384442

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Project description:BackgroundRenal cell carcinoma (RCC) is a common malignant tumor in the elderly, with an increasing trend in recent years. We aimed to construct a nomogram of cancer-specific survival (CSS) and overall survival (OS) in elderly patients with nonmetastatic renal cell carcinoma (nmRCC).MethodsClinicopathological information was downloaded from the Surveillance, Epidemiology, and End Results (SEER) program in elderly patients with nmRCC from 2010 to 2015. All patients were randomly assigned to a training cohort (70%) or a validation cohort (30%). Univariate and multivariate Cox regression analyses were used to identify independent risk factors for patient outcomes in the training cohort. A nomogram was constructed based on these independent risk factors to predict the 1-, 3-, and 5-year CSS and OS in elderly patients with nmRCC. We used a range of methods to validate the accuracy and reliability of the model, including the calibration curve, consistency index (C-index), and the area under the receiver operating curve (AUC). Decision curve analysis (DCA) was used to test the clinical utility of the model.ResultsA total of 12,116 patients were enrolled in the study. Patients were randomly assigned to the training cohort (N = 8,514) and validation cohort (N = 3,602). In the training cohort, univariate and multivariate Cox regression analysis showed that age, marriage, tumor histological type, histological tumor grade, TN stage, tumor size, and surgery are independent risk factors for prognosis. A nomogram was constructed based on independent risk factors to predict CSS and OS at 1-, 3-, and 5- years in elderly patients with nmRCC. The C-index of the training and validation cohorts in CSS were 0.826 and 0.831; in OS, they were 0.733 and 0.734, respectively. The AUC results of the training and validation cohort were similar to the C-index. The calibration curve indicated that the observed value is highly consistent with the predicted value, meaning the model has good accuracy. DCA results suggest that the clinical significance of the nomogram is better than that of traditional TNM staging.ConclusionsWe built a nomogram prediction model to predict the 1-, 3- and 5-year CSS and OS of elderly nmRCC patients. This model has good accuracy and discrimination and can help doctors and patients make clinical decisions and active monitoring.

Project description:Background: Primary renal leiomyosarcoma (LMS) is an exceedingly rare entity with a poor prognosis. We summarized the clinicopathological characteristics, treatment choice, and survival outcomes of LMS from the Surveillance, Epidemiology, and End Results (SEER) database. Methods: Renal LMS and kidney renal clear cell carcinoma (KIRC) data from 1998 to 2016 were collected from the SEER database. The continuous variables were analyzed using t-tests, while the categorical variables were analyzed using Pearson's chi-squared or Fisher's exact tests. Propensity score matching (PSM) was also performed. The cancer-specific survival (CSS) and overall survival (OS) curves were estimated using Kaplan-Meier analyses and compared by log-rank tests. The risk factors for CSS and OS were estimated using univariable and multivariable Cox proportional hazard regression models. Results: A total of 140 patients with renal LMS and 75,401 patients with KIRC were enrolled. These groups differed significantly in sex, race, tumor size, grade, SEER stage, surgery, radiation, and chemotherapy. Renal LMS exhibited poorer CSS and OS compared with KIRC before and after PSM. For renal LMS, the univariate Cox proportional hazard regression model indicated that larger tumor size, higher tumor grade, higher SEER stage, and chemotherapy were risk factors for CSS and OS, while surgery appeared to be a protective factor. However, only tumor grade, SEER stage, and receiving surgery remained independent prognostic factors in the multivariable Cox proportional hazard regression model. In addition, subgroup analyses indicated that surgery remained a protective factor for advanced renal LMS. However, there was no survival benefit for patients receiving chemotherapy. Conclusions: Primary renal LMS is an exceedingly rare entity with distinct clinicopathological features and a poor prognosis. A higher tumor grade and late stage may indicate a poor prognosis. Complete tumor resection remains to be the first treatment choice, while chemotherapy may be a palliative treatment for patients with advanced disease.

Dataset Information

Predicting long-term renal and patient survival by clinicopathological features in elderly patients undergoing a renal biopsy in a UK cohort.

Background

Methods

Results

Publications

Predicting long-term renal and patient survival by clinicopathological features in elderly patients undergoing a renal biopsy in a UK cohort.

Similar Datasets

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