Missing outcome data is one of the principal threats to the validity of treatment effect estimates from randomized trials. The outcome distributions of participants with missing and observed data are often different, which increases the risk of bias. Causal inference methods may aid in reducing the bias and improving efficiency by incorporating baseline variables into the analysis. In particular, doubly robust estimators incorporate estimates of two nuisance parameters: the outcome regression and the missingness mechanism (i.e., the probability of missingness conditional on treatment assignment and baseline variables), to adjust for differences in the observed and unobserved groups that can be explained by observed covariates. To obtain consistent estimators of the treatment effect, one of these two nuisance parameters mechanism must be consistently estimated. Such nuisance parameters are traditionally estimated using parametric models, which generally preclude consistent estimation, particularly in moderate to high dimensions. Recent research on missing data has focused on data-adaptive estimation of the nuisance parameters in order to achieve consistency, but the large sample properties of such estimators are poorly understood. In this article we discuss a doubly robust estimator that is consistent and asymptotically normal (CAN) under data-adaptive consistent estimation of the outcome regression or the missingness mechanism. We provide a formula for an asymptotically valid confidence interval under minimal assumptions. We show that our proposed estimator has smaller finite-sample bias compared to standard doubly robust estima-tors. We present a simulation study demonstrating the enhanced performance of our estimators in terms of bias, efficiency, and coverage of the confidence intervals. We present the results of an illustrative example: a randomized, double-blind phase II/III trial of antiretroviral therapy in HIV-infected persons, and provide R code implementing our proposed estimators.

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OBJECTIVE -To develop and evaluate clinical rules to predict risk for diabetes in middleaged adults. RESEARCH DESIGN AND METHODS -The Atherosclerosis Risk in Communities isa cohort study conducted from 1987-1989 to 1996 -1998. We studied 7,915 participants 45-64 years of age, free of diabetes at baseline, and ascertained 1,292 incident cases of diabetes by clinical diagnosis or oral glucose tolerance testing.RESULTS -We derived risk functions to predict diabetes using logistic regression in a random half of the sample. Rules based on these risk functions were evaluated in the other half. A risk function based on waist, height, hypertension, blood pressure, family history of diabetes, ethnicity, and age was performed similarly to one based on fasting glucose (area under the receiver-operating characteristic curve [AUC] 0.71 and 0.74, respectively; P ϭ 0.2). Risk functions composed of the clinical variables plus fasting glucose (AUC 0.78) and additionally including triglycerides and HDL cholesterol (AUC 0.80) performed better (P Ͻ 0.001). Evaluation of scores based on the metabolic syndrome as defined by the National Cholesterol Education Program or with slight variations showed AUCs of 0.75 and 0.78, respectively. Rules based on all these approaches, while identifying 20 -56% of the sample as screen positive, achieved sensitivities of 40 -87% and specificities of 50 -86%.CONCLUSIONS -Rules derived from clinical information, alone or combined with simple laboratory measures, can characterize degrees of diabetes risk in middle-aged adults, permitting preventive actions of appropriate intensity. Rules based on the metabolic syndrome are reasonable alternatives to rules derived from risk functions. Diabetes Care 28:2013-2018, 2005P revention of diabetes and its associated burden has become a major health priority worldwide (1). Recent clinical trials demonstrate that lifestyle (2-4) and pharmaceutical (2,5,6) interventions in individuals with impaired glucose tolerance (IGT) can prevent the development of diabetes, providing a rationale for the identification of high-risk subjects so as to institute early lifestyle interventions.Because these trials focused primarily on individuals with IGT, an oral glucose tolerance test (OGTT) was required to identify individuals meriting intervention. The inconveniences and costs associated with this test (7) have stimulated the development of simple rules involving readily available clinical information capable of predicting diabetes with equal or better diagnostic properties than IGT. Currently reported investigations are limited to Mexican Americans and nonHispanic whites (8), Japanese Americans (9), and Finns (10).The purpose of this study is to develop and evaluate rules to predict high risk of developing diabetes in middle-aged, white, and African-American adults using readily available clinical information. -In 1987-In -1989, the Atherosclerosis Risk in Communities (ARIC) study recruited a populationbased cohort of 15,792 men and women 45-64 years of age from four U.S. comm...

Background The optimal time to start antiretroviral therapy (ART) for HIV–infected adults in resource limited settings with a CD4+ T cell count of 200 – 350 cells per mm3 remains uncertain. Methods We conducted a randomized, open label, trial of early versus standard ART initiation in HIV-infected adults with no history of an AIDS illness and a confirmed CD4+ T cell count between 200 and 350 cells per mm3 in Haiti. The primary study end point was survival. Participants in both groups received monthly follow up, isoniazid and trimethoprim-sulfamethoxazole prophylaxis, and nutritional support. The early treatment group initiated zidovudine, lamivudine, and efavirenz within two weeks of enrollment. The standard group started the same ART regimen when participants developed a CD4+ T cell count ≤ 200 cells/mm3 or clinical AIDS. Results Between 2005 and 2008, 816 participants, 408 per group, were enrolled and followed for a median of 21 months. The CD4 T cell count at enrollment was ~ 280 cells per mm3 in both groups. There were 23 deaths in the standard group and 6 in the early group, p=0.0011, hazards ratio 4.0, 95% CI 1.6 to 9.8. There were 36 incident tuberculosis cases in the standard group and 18 in the early group, p = 0.0125, hazard ratio 2.0, 95% CI 1.2 to 3.6. Conclusions Early ART decreased mortality and incident tuberculosis infection. Access to ART should be expanded to all HIV–infected adults with a CD4+ T cell count < 350 cells per mm3, including those from resource limited settings.