Combining randomized trial data to estimate heterogeneous treatment effects

Authors  Hatfield, Laura; Kramer, Daniel;  Normand, Sharon-Lise
Year Published 2015
Link to white paper

Abstract

Heart failure arises, progresses, and responds to therapy differently in different people. Yet clinical trials often lack power to estimate treatment effects for subgroups, or enforce eligibility criteria that exclude some patients entirely. Combining information across trials increases power for subgroup estimates and expands generalizibility. However, naively pooling patient-level data sacrifices the benefits of randomization, and pooling study-level estimates must consider trial heterogeneity.We develop and illustrate approaches for combining information across trials to estimate effects in men and women with heart failure who are treated with implantable cardioverter-defibrilliator (ICD) alone or in combination with cardiac resynchronization therapy (CRT-D). We consider individual- and trial-level factors that may confound or mediate subgroup treatment effects. For example, ischemic disease is more common in men; could this explain why women appear to benefit more from CRT-D than men?Our Bayesian models estimate sex-specific treatment effects across trials, accounting for uncertainty, confounding, and mediation. We find that with a very small number of heterogeneous studies, hierarchical modeling offers few benefits over conventional effect pooling,producing wider credible intervals but little shrinkage. We also find little evidence for residual confounding within subgroups, but some evidence of interactions between left bundle branch blockage and ischemic etiology in the sex-specific treatment effects, suggesting further study.

Acknowledgments

LAH and SLN are supported by contract DHHS/FDA-223201110172C and grant 1U01FD004493-01 from the Center for Devices and Radiological Health, US Food and Drug Administration.DBK is supported by a Paul B. Beeson Career Development Award (NIA K23AG045963).

Multiple Outcomes and Multiple Sources of Evidence

Journal  Circulation: Cardiovascular Quality Outcomes
Authors Normand, Sharon-Lise T.
Year Published 2011
Link to Publication

 

Background

This issue contains 2 articles in our planned Statistical Primer on Methods or Interpretation Series. The goals of our series are to (1) familiarize cardiovascular outcomes researchers with design and analytic problems encountered in outcomes research, (2) point to potential solutions, and (3) introduce modern analytic approaches. The series’ inaugural article discussed approaches for handling missing data—approaches that have existed for several decades but have not been fully embraced by outcomes researchers. The second article focused on the “landmark analysis, an analytic approach in which patients having treatment-censoring events before a “landmark” time are excluded from analysis. In this issue, Teixeira-Pinto and Mauri address the problem of multiple outcomes, and Kwok and Lewis discuss the use of Bayesian hierarchical models.

Automated surveillance to detect post-procedure safety signals of approved cardiovascular devices

Journal JAMA (Journal of the American Medical Association)
Authors Resnic FS; Gross TP; Marinac-Dabic D; Loyo-Berríos N; Donnelly S; Normand SL; Matheny ME
Year Published 2010
Link to Publication – (PDF)

Context

Ensuring the safety of medical devices challenges current surveillance approaches, which rely heavily on voluntary reporting of adverse events. Automated surveillance of clinical registries may provide early warnings in the postmarket evaluation of medical device safety.

Objective

To determine whether automated safety surveillance of clinical registries using a computerized tool can provide early warnings regarding the safety of new cardiovascular devices.

PATIENTS:

Prospective propensity-matched cohort analysis of 7 newly introduced cardiovascular devices, using clinical data captured in the Massachusetts implementation of the National Cardiovascular Data Repository CathPCI Registry for all adult patients undergoing percutaneous coronary intervention from April 2003 through September 2007 in Massachusetts.

MAIN OUTCOME MEASURE:

Presence of any safety alert, triggered if the cumulative observed risk for a given device exceeded the upper 95% confidence interval (CI) of comparator control device. Predefined sensitivity analyses assessed robustness of alerts when triggered.

RESULTS:

We evaluated 74,427 consecutive interventional coronary procedures. Three of 21 safety analyses triggered sustained alerts in 2 implantable devices. Patients receiving Taxus Express2 drug-eluting stents experienced a 1.28-fold increased risk of postprocedural myocardial infarction (2.87% vs 2.25%; absolute risk increase, 0.62% [95% CI, 0.25%-0.99%]) and a 1.21-fold increased risk of major adverse cardiac events (4.24% vs 3.50%; absolute increase, 0.74% [95% CI, 0.29%-1.19%]) compared with those receiving alternative drug-eluting stents. Patients receiving Angio-Seal STS vascular closure devices experienced a 1.51-fold increased risk of major vascular complications (1.09% vs 0.72%; absolute increased risk, 0.37% [95% CI, 0.03%-0.71%]) compared with those receiving alternative vascular closure devices. Sensitivity analyses confirmed increased risk following use of the Taxus Express2 stent but not the Angio-Seal STS device.

CONCLUSION:

Automated prospective surveillance of clinical registries is feasible and can identify low-frequency safety signals for new cardiovascular devices.