Dataset Information

Dynamic prediction of risk of liver-related outcomes in chronic hepatitis C using routinely collected data.

ABSTRACT: Accuracy of risk assessments for clinical outcomes in patients with chronic liver disease has been limited given the nonlinear nature of disease progression. Longitudinal prediction models may more accurately capture this dynamic risk. The aim of this study was to construct accurate models of short- and long-term risk of disease progression in patients with chronic hepatitis C by incorporating longitudinal clinical data. Data from the Hepatitis C Antiviral Long-term Treatment Against Cirrhosis trial were analysed (n = 533 training cohort; n = 517 validation cohort). Outcomes included a composite liver outcome (liver-related death, decompensation, hepatocellular carcinoma (HCC) or liver transplant), decompensation, HCC and overall mortality. Longitudinal models were constructed for risk of outcomes at 1, 3 and 5 years and compared with models using data at baseline only or baseline and a single follow-up time point. A total of 25.1% of patients in the training and 20.8% in the validation cohort had an outcome during a median follow-up of 6.5 years (range 0.5-9.2). The most important predictors were as follows: albumin, aspartate aminotransferase/alanine aminotransferase ratio, bilirubin, alpha-fetoprotein and platelets. Longitudinal models outperformed baseline models with higher true-positive rates and negative predictive values. The areas under the receiver-operating characteristic curve for the composite longitudinal model were 0.89 (0.80-0.96), 0.83 (0.76-0.88) and 0.81 (0.75-0.87) for 1-, 3-, and 5-year risk prediction, respectively. Model performance was retained for decompensation and overall mortality but not HCC. Longitudinal prediction models provide accurate risk assessments and identify patients in need of intensive monitoring and care.

SUBMITTER: Konerman MA

PROVIDER: S-EPMC5809174 | biostudies-other | 2016 Jun

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Dynamic prediction of risk of liver-related outcomes in chronic hepatitis C using routinely collected data.

Konerman M A MA Brown M M Zheng Y Y Lok A S F AS

Journal of viral hepatitis 20160219 6

Accuracy of risk assessments for clinical outcomes in patients with chronic liver disease has been limited given the nonlinear nature of disease progression. Longitudinal prediction models may more accurately capture this dynamic risk. The aim of this study was to construct accurate models of short- and long-term risk of disease progression in patients with chronic hepatitis C by incorporating longitudinal clinical data. Data from the Hepatitis C Antiviral Long-term Treatment Against Cirrhosis t ...[more]

PMID: 26893198

Similar Datasets

Project description:Background and objectivesDefining the optimal moment to start renal replacement therapy (RRT) in acute kidney injury (AKI) remains challenging. Multiple randomized controlled trials (RCTs) addressed this question whilst using absolute criteria such as pH or serum potassium. However, there is a need for identification of the most optimal cut-offs of these criteria. We conducted a causal analysis on routinely collected data (RCD) to compare the impact of different pre-specified dynamic treatment regimes (DTRs) for RRT initiation based on time-updated levels of potassium, pH, and urinary output on 30-day ICU mortality.Design, setting, participants, and measurementsPatients in the ICU of Ghent University Hospital were included at the time they met KDIGO-AKI-stage ≥ 2. We applied inverse-probability-of-censoring-weighted Aalen-Johansen estimators to evaluate 30-day survival under 81 DTRs prescribing RRT initiation under different thresholds of potassium, pH, or persisting oliguria.ResultsOut of 13,403 eligible patients (60.8 ± 16.8 years, SOFA 7.0 ± 4.1), 5622 (63.4 ± 15.3 years, SOFA 8.2 ± 4.2) met KDIGO-AKI-stage ≥ 2. The DTR that delayed RRT until potassium ≥ 7 mmol/l, persisting oliguria for 24-36 h, and/or pH < 7.0 (non-oliguric) or < 7.2 (oliguric) despite maximal conservative treatment resulted in a reduced 30-day ICU mortality (from 12.7% [95% CI 11.9-13.6%] under current standard of care to 10.5% [95% CI 9.5-11.7%]; risk difference 2.2% [95% CI 1.3-3.8%]) with no increase in patients starting RRT (from 471 [95% CI 430-511] to 475 [95% CI 342-572]). The fivefold cross-validation benchmark for the optimal DTR resulted in 30-day ICU mortality of 10.7%.ConclusionsOur causal analysis of RCD to compare RRT initiation at different thresholds of refractory low pH, high potassium, and persisting oliguria identified a DTR that resulted in a decrease in 30-day ICU mortality without increase in number of RRTs. Our results suggest that the current criteria to start RRT as implemented in most RCTs may be suboptimal. However, as our analysis is hypothesis generating, this optimal DTR should ideally be validated in a multicentric RCT.

Project description:ObjectiveAntipsychotics are licensed for psychosis and are also prescribed for behavior control. This study aims to examine characteristics and outcomes of children prescribed antipsychotics.MethodsA cohort study using general practice and hospital records linked with education records for 1,488,936 children living in Wales between 1999 and 2015. The characteristics of the children who were prescribed antipsychotics are presented using descriptive statistics and outcomes such as respiratory illness, diabetes, and injury were analyzed using multilevel logistic regression and the prior event rate ratio (PERR).ResultsChildren with intellectual difficulty/autism were more likely to be prescribed antipsychotics (2.8% have been prescribed an antipsychotic [75% with autism] compared with 0.15% of children without intellectual difficulty). Those with intellectual disabilities/autism were prescribed antipsychotics at a younger age and for a longer period. Antipsychotic use was associated with a higher rate of respiratory illness for all (PERR of hospital admission: 1.55 [95% CI: 1.51-1.598] or increase in rate of 2 per 100 per year in those treated), and for those with intellectual difficulty/autism, there was a higher rate of injury and hospitalized depression. However, among those without intellectual difficulty/autism, there were lower rates of depression (PERR: 0.55 [95% CI: 0.51-0.59]).ConclusionsThis work shows real-world use of antipsychotics and provides information on the rate of possible adverse events in children treated. Antipsychotics are predominantly used for those with intellectual difficulty/autism rather than those with a psychotic diagnosis. There is evidence that rates of respiratory disease, epilepsy, and diabetes are also higher postantipsychotic use for all. In those with intellectual difficulty/autism, hospital-admitted depression and injury are higher postantipsychotic use. The use of antipsychotics for behavioral management is likely to have increased cost implications to the healthcare system.

Dataset Information

Dynamic prediction of risk of liver-related outcomes in chronic hepatitis C using routinely collected data.

Publications

Dynamic prediction of risk of liver-related outcomes in chronic hepatitis C using routinely collected data.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets