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1.
J R Stat Soc Ser A Stat Soc ; 181(1): 277-297, 2018 01.
Artigo em Inglês | MEDLINE | ID: mdl-29353967

RESUMO

In randomized controlled trials with treatment non-compliance, instrumental variable approaches are used to estimate complier average causal effects. We extend these approaches to cost-effectiveness analyses, where methods need to recognize the correlation between cost and health outcomes. We propose a Bayesian full likelihood approach, which jointly models the effects of random assignment on treatment received and the outcomes, and a three-stage least squares method, which acknowledges the correlation between the end points and the endogeneity of the treatment received. This investigation is motivated by the REFLUX study, which exemplifies the setting where compliance differs between the randomized controlled trial and routine practice. A simulation is used to compare the methods' performance. We find that failure to model the correlation between the outcomes and treatment received correctly can result in poor confidence interval coverage and biased estimates. By contrast, Bayesian full likelihood and three-stage least squares methods provide unbiased estimates with good coverage.

2.
Eur J Vasc Endovasc Surg ; 51(6): 838-45, 2016 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-27026391

RESUMO

BACKGROUND: Up to 50% of patients develop post-thrombotic syndrome (PTS) following their first proximal deep vein thrombosis (DVT). This meta-analysis aims to evaluate the effectiveness of graduated compression stockings (GCS) in preventing PTS. METHOD: Medline, Embase, Cochrane Database of Systematic Reviews, and ClinicalTrials.gov were electronically searched from inception to January 2015 for studies investigating the effect of GCS in preventing PTS. All randomised control trials were considered for inclusion if they compared the efficacy of GCS (30-40 mmHg at the ankle) with either placebo or no stockings in adults with new proximal lower limb DVT. Methodological assessment, using the Cochrane Risk of Bias Tool, and data extraction was performed by two independent reviewers. The effect of GCS was expressed as the risk difference (RD). RESULTS: A total of 686 articles were screened. Three randomised controlled trials inclusive of 1,177 patients were eligible for inclusion. PTS developed in 49-70% of control patients at 5 years. High statistical heterogeneity was observed between trials (all PTS: I(2) = 0.94; severe PTS: I(2) = 0.79). The risk difference in PTS incidence between control and GCS arms varied from 0% to 39% between trials. In trials with a higher baseline prevalence of PTS, a visual trend towards more benefit with GCS was noted. CONCLUSION: Uncertainty because of sampling variability and heterogeneity was too high to conclude in favour or against an effect of wearing compression stockings in preventing PTS. An effect may be present for higher values of baseline risk. Further evidence is needed. Article history.


Assuntos
Síndrome Pós-Trombótica/epidemiologia , Síndrome Pós-Trombótica/prevenção & controle , Meias de Compressão , Trombose Venosa/epidemiologia , Trombose Venosa/cirurgia , Bases de Dados Factuais , Humanos , Incidência , Ensaios Clínicos Controlados Aleatórios como Assunto , Incerteza
3.
Res Synth Methods ; 3(2): 142-60, 2012 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-26062087

RESUMO

Multi-arm trials (trials with more than two arms) are particularly valuable forms of evidence for network meta-analysis (NMA). Trial results are available either as arm-level summaries, where effect measures are reported for each arm, or as contrast-level summaries, where the differences in effect between arms compare with the control arm chosen for the trial. We show that likelihood-based inference in both contrast-level and arm-level formats is identical if there are only two-arm trials, but that if there are multi-arm trials, results from the contrast-level format will be incorrect unless correlations are accounted for in the likelihood. We review Bayesian and frequentist software for NMA with multi-arm trials that can account for this correlation and give an illustrative example of the difference in estimates that can be introduced if the correlations are not incorporated. We discuss methods of imputing correlations when they cannot be derived from the reported results and urge trialists to report the standard error for the control arm even if only contrast-level summaries are reported. Copyright © 2012 John Wiley & Sons, Ltd.

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