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Causal null hypotheses of sustained treatment strategies: What can be tested with an instrumental variable?

Sometimes instrumental variable methods are used to test whether a causal effect is null rather than to estimate the magnitude of a causal effect. However, when instrumental variable methods are applied to time-varying exposures, as in many Mendelian randomization studies, it is unclear what causal null hypothesis is tested. Here, we consider different versions of causal null...

Methods to Estimate the Comparative Effectiveness of Clinical Strategies that Administer the Same Intervention at Different Times

she has no conflict of interest. James M. Robins declares that he has no conflict of interest. Geir Hoff declares that he has no conflict of interest. Miguel A. Hernán declares that he has no

Selecting on Treatment: A Pervasive Form of Bias in Instrumental Variable Analyses

. Hernán 0 1 0 Kresge Building , 9th Floor, Boston, MA 02115 ( 1 Author affiliations: Department of Epidemiology, Harvard School of Public Health , Boston, Massachusetts (Sonja A. Swanson, James M. Robins

Oseltamivir and Risk of Lower Respiratory Tract Complications in Patients With Flu Symptoms: A Meta-analysis of Eleven Randomized Clinical Trials

An independent reanalysis of 11 randomized clinical trials shows that oseltamivir treatment reduces the risk of lower respiratory tract complications requiring antibiotic treatment by 28% overall (95% confidence interval [CI], 11%–42%) and by 37% among patients with confirmed influenza infections (95% CI, 18%–52%).

Results on Differential and Dependent Measurement Error of the Exposure and the Outcome Using Signed Directed Acyclic Graphs

Measurement error in both the exposure and the outcome is a common problem in epidemiologic studies. Measurement errors in the exposure and the outcome are said to be independent of each other if the measured exposure and the measured outcome are statistically independent conditional on the true exposure and true outcome (and dependent otherwise). Measurement error is said to be...

Bias in Observational Studies of Prevalent Users: Lessons for Comparative Effectiveness Research From a Meta-Analysis of Statins

Randomized clinical trials (RCTs) are usually the preferred strategy with which to generate evidence of comparative effectiveness, but conducting an RCT is not always feasible. Though observational studies and RCTs often provide comparable estimates, the questioning of observational analyses has recently intensified because of randomized-observational discrepancies regarding the...

Incidence of Adult-onset Asthma After Hypothetical Interventions on Body Mass Index and Physical Activity: An Application of the Parametric G-Formula

, Carlos A. Camargo, Jr., Miguel A. Hernán); Department of Global Health and Population, Harvard School of Public Health, Boston, Massachusetts (Goodarz Danaei); Channing Division of Network Medicine ... , Massachusetts (Carlos A. Camargo, Jr.); Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts (Miguel A. Hernán); and Harvard-MIT Division of Health Sciences and Technology, Boston

Potential Biases in Estimating Absolute and Relative Case-Fatality Risks during Outbreaks

Estimating the case-fatality risk (CFR)—the probability that a person dies from an infection given that they are a case—is a high priority in epidemiologic investigation of newly emerging infectious diseases and sometimes in new outbreaks of known infectious diseases. The data available to estimate the overall CFR are often gathered for other purposes (e.g., surveillance) in...

Statins and Risk of Diabetes: An analysis of electronic medical records to evaluate possible bias due to differential survival

OBJECTIVE Two meta-analyses of randomized trials of statins found increased risk of type 2 diabetes. One possible explanation is bias due to differential survival when patients who are at higher risk of diabetes survive longer under statin treatment.

Invited Commentary: Causal Diagrams and Measurement Bias

Causal inferences about the effect of an exposure on an outcome may be biased by errors in the measurement of either the exposure or the outcome. Measurement errors of exposure and outcome can be classified into 4 types: independent nondifferential, dependent nondifferential, independent differential, and dependent differential. Here the authors describe how causal diagrams can...

Changes in Fish Consumption in Midlife and the Risk of Coronary Heart Disease in Men and Women

Without data from randomized trials, the long-term effects of fish consumption on coronary heart disease (CHD) need to be inferred from observational studies. We estimated CHD risk under different hypothetical interventions on fish consumption during mid- and later life in 2 prospective US cohorts of 25,797 men in the Health Professionals Follow-Up Study and 53,772 women in the...

Constructing Inverse Probability Weights for Marginal Structural Models

The method of inverse probability weighting (henceforth, weighting) can be used to adjust for measured confounding and selection bias under the four assumptions of consistency, exchangeability, positivity, and no misspecification of the model used to estimate weights. In recent years, several published estimates of the effect of time-varying exposures have been based on weighted...

Association of smoking with amyotrophic lateral sclerosis risk and survival in men and women: a prospective study

Background Previous epidemiologic studies have examined the association of smoking with amyotrophic lateral sclerosis (ALS) incidence, but their results have been inconsistent. Moreover, limited information exists on the association between smoking and survival in ALS patients. We evaluated the association of smoking with ALS incidence and survival in a population-based cohort...

Effectiveness of Patient Adherence Groups as a Model of Care for Stable Patients on Antiretroviral Therapy in Khayelitsha, Cape Town, South Africa

Background Innovative models of care are required to cope with the ever-increasing number of patients on antiretroviral therapy in the most affected countries. This study, in Khayelitsha, South Africa, evaluates the effectiveness of a group-based model of care run predominantly by non-clinical staff in retaining patients in care and maintaining adherence. Methods and Findings...

Invited Commentary: Effect Modification by Time-varying Covariates

Marginal structural models (MSMs) allow estimation of effect modification by baseline covariates, but they are less useful for estimating effect modification by evolving time-varying covariates. Rather, structural nested models (SNMs) were specifically designed to estimate effect modification by time-varying covariates. In their paper, Petersen et al. (Am J Epidemiol 2007;166:985...

The Birth Weight “Paradox” Uncovered?

Low birth weight (LBW) infants have lower infant mortality in groups in which LBW is most frequent. For example, in 1991, US infants born to smokers had higher risks of both LBW and infant mortality than infants born to nonsmokers. However, among LBW infants, infant mortality was lower for infants born to smokers (relative rate = 0.79). There are competing theories regarding this...