Dataset Information

Personalized prediction of lifetime benefits with statin therapy for asymptomatic individuals: a modeling study.

ABSTRACT:

Background

Physicians need to inform asymptomatic individuals about personalized outcomes of statin therapy for primary prevention of cardiovascular disease (CVD). However, current prediction models focus on short-term outcomes and ignore the competing risk of death due to other causes. We aimed to predict the potential lifetime benefits with statin therapy, taking into account competing risks.

Methods and findings

A microsimulation model based on 5-y follow-up data from the Rotterdam Study, a population-based cohort of individuals aged 55 y and older living in the Ommoord district of Rotterdam, the Netherlands, was used to estimate lifetime outcomes with and without statin therapy. The model was validated in-sample using 10-y follow-up data. We used baseline variables and model output to construct (1) a web-based calculator for gains in total and CVD-free life expectancy and (2) color charts for comparing these gains to the Systematic Coronary Risk Evaluation (SCORE) charts. In 2,428 participants (mean age 67.7 y, 35.5% men), statin therapy increased total life expectancy by 0.3 y (SD 0.2) and CVD-free life expectancy by 0.7 y (SD 0.4). Age, sex, smoking, blood pressure, hypertension, lipids, diabetes, glucose, body mass index, waist-to-hip ratio, and creatinine were included in the calculator. Gains in total and CVD-free life expectancy increased with blood pressure, unfavorable lipid levels, and body mass index after multivariable adjustment. Gains decreased considerably with advancing age, while SCORE 10-y CVD mortality risk increased with age. Twenty-five percent of participants with a low SCORE risk achieved equal or larger gains in CVD-free life expectancy than the median gain in participants with a high SCORE risk.

Conclusions

We developed tools to predict personalized increases in total and CVD-free life expectancy with statin therapy. The predicted gains we found are small. If the underlying model is validated in an independent cohort, the tools may be useful in discussing with patients their individual outcomes with statin therapy.

SUBMITTER: Ferket BS

PROVIDER: S-EPMC3531501 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Personalized prediction of lifetime benefits with statin therapy for asymptomatic individuals: a modeling study.

Ferket Bart S BS van Kempen Bob J H BJ Heeringa Jan J Spronk Sandra S Fleischmann Kirsten E KE Nijhuis Rogier L G RL Hofman Albert A Steyerberg Ewout W EW Hunink M G Myriam MG

PLoS medicine 20121227 12

<h4>Background</h4>Physicians need to inform asymptomatic individuals about personalized outcomes of statin therapy for primary prevention of cardiovascular disease (CVD). However, current prediction models focus on short-term outcomes and ignore the competing risk of death due to other causes. We aimed to predict the potential lifetime benefits with statin therapy, taking into account competing risks.<h4>Methods and findings</h4>A microsimulation model based on 5-y follow-up data from the Rotte ...[more]

PMID: 23300388

Similar Datasets

Project description:BackgroundStatins are a class of drugs that lower cholesterol levels in the blood by inhibiting an enzyme called 3-hydroxy-3-methyl-glutaryl-coenzyme A (HMG-CoA) reductase. High cholesterol levels can lead to plaque buildup in the arteries, which can cause Atherosclerotic Cardiovascular Disease(ASCVD). Statins can reduce the risk of ASCVD events by about 25-35% but they might be associated with symptoms such as muscle pain, liver damage, or diabetes. As a result, this leads to a strong reason to discontinue statin therapy, which increases the risk of cardiovascular events and mortality and becomes a public-health problem.To solve this problem, in the previous work, we proposed a framework to produce a proactive strategy, called a personalized statin treatment plan (PSTP) to minimize the risks of statin-associated symptoms and therapy discontinuation when prescribing statin. In our previous PSTP framework, three limitations remain, and they can influence PSTP usability: (1) Not taking the counterfactual predictions and confounding bias into account. (2) The balance between multiple drug-prescribing objectives (especially trade-off objectives), such as tradeoff between benefits and risks. (3) Evaluating PSTP in retrospective data.ObjectivesThis manuscript aimed to provide solutions for the three abovementioned problems to improve PSTP robustness to produce a proactive strategy for statin prescription that can maximize the benefits (low-density lipoprotein cholesterol (LDL-C) reduction) and minimize risks (statin-associated symptoms and therapy discontinuation) at the same time.MethodsWe applied overlapping weighting counterfactual survival risk prediction (CP), multiple objective optimization (MOO), and clinical trial simulation (CTS) which consists of Random Arms, Clinical Guideline arms, PSTP Arms, and Practical Arms to improve the PSTP framework and usability.ResultsIn addition to highly balanced covariates, in the CTS, the revised PSTP showed improvements in lowering the SAS risks overall compared to other arms across all time points by at most 7.5% to at least 1.0% (Fig. 8(a)). It also has the better flexibility of identifying the optimal Statin across all time points within one year.ConclusionWe demonstrated feasibility of robust and trustworthy counterfactual survival risk prediction model. In CTS, we also demonstrated the PSTP with Pareto optimization can personalize optimal balance between Statin benefits and risks.

Project description:BACKGROUND:Recent studies have suggested that statins possess diverse immune modulatory and anti-inflammatory properties. As statins might attenuate inflammation, statin therapy has been hypothesized to reduce mortality in HIV-infected individuals. We therefore used a Danish nationwide cohort of HIV-infected individuals to estimate the impact of statin use on mortality before and after a diagnosis of cardiovascular disease, chronic kidney disease or diabetes. METHODS:We identified all Danish HIV-infected individuals (1,738) who initiated HAART after 1 January 1998, and achieved virological suppression within 180 days. Date of first redemption of a prescription of statin was obtained from the Danish National Prescription Registry. We used Poisson regression analysis to assess adjusted mortality rate ratios (aMRR). First, time was censored at date of virological failure (VL >500 copies/ml). Second, time was not censored at virological failure. All analyses were adjusted for potential confounders. RESULTS:In the analyses confined to observation time without virological failure (+ censoring) statin therapy was associated with a non-statistically significant reduced rate of death (aMRR 0.75; 95% CI: 0.33-1.68). No difference was observed in the analysis with no censoring (aMRR 1.17; 95% CI: 0.66-2.07). Use of statin seemed to reduce mortality in individuals after a diagnosis of comorbidity {(+ censoring: aMRR: 0.34; 95% CI: 0.11-1.04), (-censoring: aMRR: 0.64; 95% CI: 0.32-1.29)}. No difference in rate of death could be detected before first date of diagnosis of comorbidity {(+ censoring: aMRR: 1.12; 95% CI: 0.34-3.62), (-censoring: aMRR: 0.90; 95% CI: 0.28-2.88)}. CONCLUSION:Statin therapy might reduce all-cause mortality in HIV-infected individuals, but the impact on individuals with no comorbidity seems small or absent. An unambiguous proof of a causal relation can only be obtained in a randomized controlled trial, but the sample size predicted may be prohibitive for its conduct.

Project description:ImportanceAscending thoracic aortic disease is an important cause of sudden death in the US, yet most aortic aneurysms are identified incidentally.ObjectiveTo develop and validate a clinical score to estimate ascending aortic diameter.Design, setting, and participantsUsing an ongoing magnetic resonance imaging substudy of the UK Biobank cohort study, which had enrolled participants from 2006 through 2010, score derivation was performed in 30 018 participants and internal validation in an additional 6681. External validation was performed in 1367 participants from the Framingham Heart Study (FHS) offspring cohort who had undergone computed tomography from 2002 through 2005, and in 50 768 individuals who had undergone transthoracic echocardiography in the Community Care Cohort Project, a retrospective hospital-based cohort of longitudinal primary care patients in the Mass General Brigham (MGB) network between 2001-2018.ExposuresDemographic and clinical variables (11 covariates that would not independently prompt thoracic imaging).Main outcomes and measuresAscending aortic diameter was modeled with hierarchical group least absolute shrinkage and selection operator (LASSO) regression. Correlation between estimated and measured diameter and performance for identifying diameter 4.0 cm or greater were assessed.ResultsThe 30 018-participant training cohort (52% women), were a median age of 65.1 years (IQR, 58.6-70.6 years). The mean (SD) ascending aortic diameter was 3.04 (0.31) cm for women and 3.32 (0.34) cm for men. A score to estimate ascending aortic diameter explained 28.2% of the variance in aortic diameter in the UK Biobank validation cohort (95% CI, 26.4%-30.0%), 30.8% in the FHS cohort (95% CI, 26.8%-34.9%), and 32.6% in the MGB cohort (95% CI, 31.9%-33.2%). For detecting individuals with an ascending aortic diameter of 4 cm or greater, the score had an area under the receiver operator characteristic curve of 0.770 (95% CI, 0.737-0.803) in the UK Biobank, 0.813 (95% CI, 0.772-0.854) in the FHS, and 0.766 (95% CI, 0.757-0.774) in the MGB cohorts, although the model significantly overestimated or underestimated aortic diameter in external validation. Using a fixed-score threshold of 3.537, 9.7 people in UK Biobank, 1.8 in the FHS, and 4.6 in the MGB cohorts would need imaging to confirm 1 individual with an ascending aortic diameter of 4 cm or greater. The sensitivity at that threshold was 8.9% in the UK Biobank, 11.3% in the FHS, and 18.8% in the MGB cohorts, with specificities of 98.1%, 99.2%, and 96.2%, respectively.Conclusions and relevanceA prediction model based on common clinically available data was derived and validated to predict ascending aortic diameter. Further research is needed to optimize the prediction model and to determine whether its use is associated with improved outcomes.

Project description:PurposePrevious studies have suggested that cholesterol may influence thyroid function. Since statins are widely used for their cholesterol-lowering effect, we aimed to assess the association between statin use and thyroid function, and also to explore the role of the cholesterol-lowering effect in it.MethodsWe performed a retrospective cohort study derived from REACTION study. Eligible subjects receiving statin therapy were included in the statin group, and sex-, age-, total cholesterol (TC)-, and thyroid function-matched participants without lipid-lowering therapy were included in the control group. The median follow-up time was three years. Outcomes of thyroid function were evaluated at the end of follow-up. We used multivariable regression models to assess the association between statin use and outcomes of thyroid function, and also performed mediation analyses to explore the role of cholesterol in it.ResultsA total of 5,146 participants were screened, and 201 eligible subjects in the statin group and 201 well-matched subjects in the control group were analyzed. At the end of follow-up, TC and thyroid-stimulating hormone (TSH) levels in the statin group were lower than those in the control group (both p < 0.05), and the percentage of euthyroid subjects was higher in the statin group (88.06% vs. 76.12%, p = 0.002). The incidence rate of subclinical hypothyroidism (SCH) in euthyroid subjects was lower in the statin group (6.29% vs. 14.86%, p = 0.009), and the remission rate among subjects with SCH was higher in the statin group (50.00% vs. 15.38%, p = 0.008). In multivariable regression analyses, statin use was independently associated with lower TSH levels and higher odds to be euthyroid (OR 2.335, p = 0.004) at the end of follow-up. Mediation analyses showed the association between statin use and TSH levels were mediated by TC changes during follow-up.ConclusionStatin use was associated with benefits of thyroid function, and TC changes serve as a mediator of the association between statin use and TSH levels. Further studies are needed to clarify the possible underlying mechanism.

Project description:BackgroundCardiovascular disease incidence and mortality have declined across developed economies and granular up-to-date cost-effectiveness evidence is required for treatments targeting large populations. To assess the health benefits and cost-effectiveness of standard and higher intensity statin therapy in the contemporary UK population 40-70 years old.MethodsA cardiovascular disease microsimulation model, developed using the Cholesterol Treatment Trialists' Collaboration data (117,896 participants; 5 years follow-up), and calibrated in the UK Biobank cohort (501,854 participants; 9 years follow-up), projected risks of myocardial infarction, stroke, coronary revascularization, diabetes, cancer and vascular and nonvascular death for all UK Biobank participants without and with statin treatment. Meta-analyses of trials and cohort studies informed statins' relative effects on cardiovascular events, incident diabetes, myopathy and rhabdomyolysis. UK healthcare perspective was taken (2020/2021 UK£) with costs per 28 tablets of £1.10 for standard (35%-45% LDL cholesterol (LDL-C) reduction) and £1.68 for higher intensity (≥45% LDL-C reduction) generic statin.FindingsAcross categories by sex, age, LDL-C, and cardiovascular disease history/10-year cardiovascular risk, lifetime standard statin increased survival by 0.28-1.85 years (0.20-1.09 quality-adjusted life years (QALYs)), and higher intensity statin by further 0.06-0.40 years (0.03-0.20 QALYs) per person. Standard statin was cost-effective across all categories with incremental cost per QALY from £280 to £8530, with higher intensity statin cost-effective at higher cardiovascular risks and higher LDL-C levels. Stopping statin early reduced benefits and was not cost-effective.InterpretationLifetime low-cost statin therapy is cost-effective across all 40-70 years old in UK. Strengthening and widening statin treatment could cost-effectively improve population health.FundingUK NIHR Health Technology Assessment Programme (17/140/02).

Dataset Information

Personalized prediction of lifetime benefits with statin therapy for asymptomatic individuals: a modeling study.

Background

Methods and findings

Conclusions

Publications

Personalized prediction of lifetime benefits with statin therapy for asymptomatic individuals: a modeling study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets