In the hierarchy of research designs, the results of randomized, controlled trials are considered to be evidence of the highest grade, whereas observational studies are viewed as having less validity because they reportedly overestimate treatment effects. We used published meta-analyses to identify randomized clinical trials and observational studies that examined the same clinical topics. We then compared the results of the original reports according to the type of research design. A search of the Medline data base for articles published in five major medical journals from 1991 to 1995 identified meta-analyses of randomized, controlled trials and meta-analyses of either cohort or case–control studies that assessed the same intervention. For each of five topics, summary estimates and 95 percent confidence intervals were calculated on the basis of data from the individual randomized, controlled trials and the individual observational studies. For the five clinical topics and 99 reports evaluated, the average results of the observational studies were remarkably similar to those of the randomized, controlled trials. For example, analysis of 13 randomized, controlled trials of the effectiveness of bacille Calmette–Guérin vaccine in preventing active tuberculosis yielded a relative risk of 0.49 (95 percent confidence interval, 0.34 to 0.70) among vaccinated patients, as compared with an odds ratio of 0.50 (95 percent confidence interval, 0.39 to 0.65) from 10 case–control studies. In addition, the range of the point estimates for the effect of vaccination was wider for the randomized, controlled trials (0.20 to 1.56) than for the observational studies (0.17 to 0.84). The results of well-designed observational studies (with either a cohort or a case–control design) do not systematically overestimate the magnitude of the effects of treatment as compared with those in randomized, controlled trials on the same topic.

Obesity is a serious disease that is associated with an increased risk of diabetes, hypertension, heart disease, stroke, and cancer, among other diseases. The United States Centers for Disease Control and Prevention (CDC) estimates a 20% obesity rate in the 50 states, with 12 states having rates of over 30%. Currently, the body mass index (BMI) is most commonly used to determine adiposity. However, BMI presents as an inaccurate obesity classification method that underestimates the epidemic and contributes to failed treatment. In this study, we examine the effectiveness of precise biomarkers and duel-energy x-ray absorptiometry (DXA) to help diagnose and treat obesity. A cross-sectional study of adults with BMI, DXA, fasting leptin and insulin results were measured from 1998–2009. Of the participants, 63% were females, 37% were males, 75% white, with a mean age = 51.4 (SD = 14.2). Mean BMI was 27.3 (SD = 5.9) and mean percent body fat was 31.3% (SD = 9.3). BMI characterized 26% of the subjects as obese, while DXA indicated that 64% of them were obese. 39% of the subjects were classified as non-obese by BMI, but were found to be obese by DXA. BMI misclassified 25% men and 48% women. Meanwhile, a strong relationship was demonstrated between increased leptin and increased body fat. Our results demonstrate the prevalence of false-negative BMIs, increased misclassifications in women of advancing age, and the reliability of gender-specific revised BMI cutoffs. BMI underestimates obesity prevalence, especially in women with high leptin levels (>30 ng/mL). Clinicians can use leptin-revised levels to enhance the accuracy of BMI estimates of percentage body fat when DXA is unavailable.

OBJECTIVE: To systematically review evidence of the treatment benefits of selective serotonin reuptake inhibitors (SSRIs) for symptoms related to severe premenstrual syndrome (PMS) and premenstrual dysphoric disorder. DATA SOURCES: We conducted electronic database searches of MEDLINE, Web of Science, Cochrane Library, Embase, PsycINFO, and Cinahl through March 2007, and hand-searched reference lists and pertinent journals. METHODS OF STUDY SELECTION: Studies included in the review were double-blind, randomized, controlled trials comparing an SSRI with placebo that reported a change in a validated score of premenstrual symptomatology. Studies had to report follow-up for any duration longer than one menstrual cycle among premenopausal women who met clinical diagnostic criteria for PMS or premenstrual dysphoric disorder. From 2,132 citations identified, we pooled results from 29 studies (in 19 citations) using random-effects meta-analyses and present results as odds ratios (ORs). TABULATION, INTEGRATION, AND RESULTS: Our meta- analysis, which included 2,964 women, demonstrates that SSRIs are effective for treating PMS and premenstrual dysphoric disorder (OR 0.40, 95% confidence interval [CI] 0.31–0.51). Intermittent dosing regimens were found to be less effective (OR 0.55, 95% CI 0.45–0.68) than continuous dosing regimens (OR 0.28, 95% CI 0.18–0.42). No SSRI was demonstrably better than another. The choice of outcome measurement instrument was associated with effect size estimates. The overall effect size is smaller than reported previously. CONCLUSION: Selective serotonin reuptake inhibitors were found to be effective in treating premenstrual symptoms, with continuous dosing regimens favored for effectiveness.

The concept of the medical home has existed since the 1960s, but has recently become a focus for discussion and innovation in the health care system. The most prominent definitions of the medical home are those presented by the Patient-Centered Primary Care Collaborative, the National Committee for Quality Assurance, and the Commonwealth Fund. These definitions share: adoption of health information technology and decision support systems, modification of clinical practice patterns, and ensuring continuity of care. Each of these components is a complex undertaking, and there is scant evidence to guide assessment of diverse strategies for achieving their integration into a medical home. Without a shared vocabulary and common definitions, policy-makers seeking to encourage the development of medical homes, providers seeking to improve patient care, and payers seeking to develop appropriate systems of reimbursement will face challenges in evaluating and disseminating the medical home model.