Dataset Information

Joint Modeling of Repeated Measures and Competing Failure Events In a Study of Chronic Kidney Disease.

ABSTRACT: We are motivated by the Chronic Renal Insufficiency Cohort (CRIC) study to identify risk factors for renal progression in patients with chronic kidney diseases. The CRIC study collects two types of renal outcomes: glomerular filtration rate (GFR) estimated annually and end stage renal disease (ESRD). A related outcome of interest is death which is a competing event for ESRD. A joint modeling approach is proposed to model a longitudinal outcome and two competing survival outcomes. We assume multivariate normality on the joint distribution of the longitudinal and survival outcomes. Specifically, a mixed effects model is fit on the longitudinal outcome and a linear model is fit on each survival outcome. The three models are linked together by having the random terms of the mixed effects model as covariates in the survival models. EM algorithm is used to estimate the model parameters and the non-parametric bootstrap is used for variance estimation. A simulation study is designed to compare the proposed method with an approach that models the outcomes sequentially in two steps. We fit the proposed model to the CRIC data and show that the protein-to-creatinine ratio is strongly predictive of both estimated GFR and ESRD but not death.

SUBMITTER: Yang W

PROVIDER: S-EPMC5793948 | biostudies-other | 2017 Dec

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Joint Modeling of Repeated Measures and Competing Failure Events In a Study of Chronic Kidney Disease.

Yang Wei W Xie Dawei D Pan Qiang Q Feldman Harold I HI Guo Wensheng W

Statistics in biosciences 20161227 2

We are motivated by the Chronic Renal Insufficiency Cohort (CRIC) study to identify risk factors for renal progression in patients with chronic kidney diseases. The CRIC study collects two types of renal outcomes: glomerular filtration rate (GFR) estimated annually and end stage renal disease (ESRD). A related outcome of interest is death which is a competing event for ESRD. A joint modeling approach is proposed to model a longitudinal outcome and two competing survival outcomes. We assume multi ...[more]

PMID: 29399206

Similar Datasets

Project description:ImportanceKidney failure risk prediction has implications for disease management, including advance care planning in adults with severe (ie, estimated glomerular filtration rate [eGFR] category 4, [G4]) chronic kidney disease (G4-CKD). Existing prediction tools do not account for the competing risk of death.ObjectiveTo compare predictions of kidney failure (defined as estimated glomerular filtration rate [eGFR] <10 mL/min/1.73 m2 or initiation of kidney replacement therapy) from models that do and do not account for the competing risk of death in adults with G4-CKD.Design, setting, and participantsThis prognostic study linked population-based laboratory and administrative data (2002-2017) from 2 Canadian provinces (Alberta and Manitoba) to compare 3 kidney risk models: the standard Cox regression, cause-specific Cox regression, and Fine-Gray subdistribution hazard model. Participants were adults with incident G4-CKD (eGFR 15-29 mL/min/1.73 m2). Data analysis occurred between July and December 2020.Main outcomes and measuresThe performance of kidney risk models at prespecified times and across categories of baseline characteristics, using calibration, reclassification, and discrimination (for competing risks). Predictive characteristics were age, sex, albuminuria, eGFR, diabetes, and cardiovascular disease.ResultsThe development and validation cohorts included 14 619 (7070 [48.4%] men; mean [SD] age, 74.1 [12.8] years) and 2295 (1152 [50.2] men; mean [SD] age, 71.9 [14.0] years) adults, respectively. The 3 models had comparable calibration up to 2 years from entry. Beyond 2 years, the standard Cox regression overestimated the risk of kidney failure. At 4 years, for example, risks predicted from standard Cox were 40% for people whose observed risks were less than 30%. At 2 years (risk cutoffs 10%-20%) and 5 years (risk cutoffs 15%-30%), 788 (5.4%) and 2162 (14.8%) people in the development cohort were correctly reclassified into lower- or higher-risk categories by the Fine-Gray model and incorrectly reclassified by standard Cox regression (the opposite was observed in 272 patients [1.9%] and 0 patients, respectively). In the validation cohort, 115 (5.0%) individuals and 389 (16.9%) individuals at 2 and 5 years, respectively, were correctly reclassified into lower- or higher-risk categories by the Fine-Gray model and incorrectly reclassified by the standard Cox regression; the opposite was observed in 98 (4.3%) individuals and 0 individuals, respectively. Differences in discrimination emerged at 4 to 5 years in the development cohort and at 1 to 2 years in the validation cohort (0.85 vs 0.86 and 0.78 vs 0.8, respectively). Performance differences were minimal during the entire follow-up in people at lower risk of death (ie, aged ≤65 years or without cardiovascular disease or diabetes) and greater in those with a higher risk of death. At 5 years, for example, in people aged 65 years or older, predicted risks from standard Cox were 50% where observed risks were less than 30%. Similar miscalibration was observed at 5 years in people with albuminuria greater than 30 mg/mmol, diabetes, or cardiovascular disease.Conclusions and relevanceIn this study, predictions about the risk of kidney failure were minimally affected by consideration of competing risks during the first 2 years after developing G4-CKD. However, traditional methods increasingly overestimated the risk of kidney failure with longer follow-up time, especially among older patients and those with more comorbidity.

Project description:BackgroundHypothyroidism and low free triiodothyronine (FT3) syndrome [low FT3 levels with normal thyroid-stimulating hormone (TSH)] have been associated with reduced kidney function cross-sectionally in chronic kidney disease (CKD) patients with severely reduced estimated glomerular filtration rate (eGFR) or end-stage kidney disease (ESKD). Results on the prospective effects of impaired thyroid function on renal events and mortality for patients with severely reduced eGFR or from population-based cohorts are conflicting. Here we evaluated the association between thyroid and kidney function with eGFR (cross-sectionally) as well as renal events and mortality (prospectively) in a large, prospective cohort of CKD patients with mild to moderately reduced kidney function.MethodsThyroid markers were measured among CKD patients from the German Chronic Kidney Disease study. Incident renal endpoints (combined ESKD, acute kidney injury and renal death) and all-cause mortality were abstracted from hospital records and death certificates. Time to first event analysis of complete data from baseline to the 4-year follow-up (median follow-up time 4.04 years) of 4600 patients was conducted. Multivariable linear regression and Cox proportional hazards models were fitted for single and combined continuous thyroid markers [TSH, free thyroxine (FT4), FT3] and thyroid status.ResultsCross-sectionally, the presence of low-FT3 syndrome showed a significant inverse association with eGFR and continuous FT3 levels alone showed a significant positive association with eGFR; in combination with FT4 and TSH, FT3 levels also showed a positive association and FT4 levels showed a negative association with eGFR. Prospectively, higher FT4 and lower FT3 levels were significantly associated with a higher risk of all-cause mortality (N events = 297). Per picomole per litre higher FT3 levels the risk of reaching the composite renal endpoint was 0.73-fold lower (95% confidence interval 0.65-0.82; N events = 615). Compared with euthyroid patients, patients with low-FT3 syndrome had a 2.2-fold higher risk and patients with hypothyroidism had a 1.6-fold higher risk of experiencing the composite renal endpoint.ConclusionsPatients with mild to moderate CKD suffering from thyroid function abnormalities are at an increased risk of adverse renal events and all-cause mortality over time.

Dataset Information

Joint Modeling of Repeated Measures and Competing Failure Events In a Study of Chronic Kidney Disease.

Publications

Joint Modeling of Repeated Measures and Competing Failure Events In a Study of Chronic Kidney Disease.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure