Confronting Hysteria: A Reply to Fairman and Curtiss

Shah, Mayur R.; Wegh, Arnold; Rosenberg, Stephen; Juster, Iver A.; Rosen, Allison B.; Fendrick, A. Mark

doi:10.18553/jmcp.2008.14.3.324

JMCP

2008

DOI: 10.18553/jmcp.2008.14.3.324

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Confronting Hysteria: A Reply to Fairman and Curtiss

Mayur R. Shah

Arnold Wegh

Stephen Rosenberg

et al.

Abstract: * affiliation when research was conducted DISCLOSURESMichael Chernew and Mark Fendrick provide consulting services to Hewitt Associates LLC and ActiveHealth Management related to value-based insurance design, and accept consulting fees and speaking honoraria related to value-based insurance design. Allison Rosen is employed by the University of Michigan's Center for Value-Based Insurance Design. Wegh, Rosenberg, and Juster are employed by ActiveHealth Management, which provides consulting services to employers… Show more

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Still Looking for Health Outcomes in All the Wrong Places? Misinterpreted Observational Evidence, Medication Adherence Promotion, and Value-Based Insurance Design

Fairman¹,

Curtiss²

2009

JMCP

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Above all, the right question needs to be framed."1 To those who would argue that sophisticated statistical modeling obviates the need to consider confounding factors and alternative explanations when interpreting observational associations, Freedman's answer was simple: "The technology is relatively easy to use. … However, the appearance of methodological rigor can be deceptive."1 More contemporary guidelines for research reporting acknowledge the same understanding: when interpreting associations, multivariate modeling is often appropriate and valuable, but is still potentially vulnerable to the effects of confounding and bias and is therefore no substitute for a randomized design. 2,3,4 Lessons Learned From Confusing Association With Causation in Chasing BiomarkersCurtiss and Fairman observed in the July/August 2008 issue of JMCP that "evidence-based" interventions targeted to biomarkers frequently do not produce the end point "outcomes we love," such as reductions in hospitalization rates or mortality.5 Notably, most of the instances cited were characterized by a single common pattern: the usurping of lower-quality evidence based on observational associations with higher-quality evidence garnered from experimental testing of hypothesized causal factors.For example, the Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation (ADVANCE) trial was conducted because observational research had documented associations of blood glucose and HbA1c (A1c) levels with cardiovascular events. Researchers randomized 11,140 patients with type 2 diabetes to standard glucose control or intensive glucose control, targeted to achieve an A1c level of 6.5% or less.6 During a median 5 years of follow-up, the patients randomized to the intensive glucose control intervention did not have a significantly lower risk of major macrovascular events (hazard ratio [HR] = 0.94, 95% confidence interval [CI] = 0.84-1.06), cardiovascular mortality (HR = 0.88, 95% CI = 0.74-1.04), or all-cause mortality (HR = 0.93, 95% CI = 0.83-1.06), but did have an increased risk of severe hypoglycemia (2.7% intensive control vs. 1.5% standard control; HR = 1.86, 95% CI = 1.42-2.40). Similarly, the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial was initiated because of high-quality prospective observational evidence suggesting that after "adjusting for other risk factors," each 1% decrease in A1c was associated with a 21% decrease in the risk of diabetes-related mortality, a 14% decrease Naturally, there is a strong desire to substitute intellectual capital for labor. That is why investigators often try to base causal inference on statistical models.

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Still Looking for Health Outcomes in All the Wrong Places? Misinterpreted Observational Evidence, Medication Adherence Promotion, and Value-Based Insurance Design

Fairman¹,

Curtiss²

2009

JMCP

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show abstract

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Confronting Hysteria: A Reply to Fairman and Curtiss

Cited by 1 publication

References 8 publications

Still Looking for Health Outcomes in All the Wrong Places? Misinterpreted Observational Evidence, Medication Adherence Promotion, and Value-Based Insurance Design

Still Looking for Health Outcomes in All the Wrong Places? Misinterpreted Observational Evidence, Medication Adherence Promotion, and Value-Based Insurance Design

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