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1.  The use of older studies in meta-analyses of medical interventions: a survey 
Open Medicine  2009;3(2):e62-e68.
Evidence for medical interventions sometimes derives from data that are no longer up to date. These data can influence the outcomes of meta-analyses, yet do not always reflect current clinical practice. We examined the age of the data used in meta-analyses contained within systematic reviews of medical interventions, and investigated whether authors consider the age of these data in their interpretations.
From Issue 4, 2005, of the Cochrane Database of Systematic Reviews we randomly selected 10% of systematic reviews containing at least 1 meta-analysis. From this sample we extracted 1 meta-analysis per primary outcome. We calculated the number of years between the study’s publication and 2005 (the year that the systematic review was published), as well as the number of years between the study’s publication and the year of the literature search conducted in the study. We assessed whether authors discussed the implications of including less recent data, and, for systematic reviews containing meta-analyses of studies published before 1996, we calculated whether excluding the findings of those studies changed the significance of the outcomes. We repeated these calculations and assessments for 22 systematic reviews containing meta-analyses published in 6 high-impact general medical journals in 2005.
For 157 meta-analyses (n = 1149 trials) published in 2005, the median year of the most recent literature search was 2003 (interquartile range [IQR] 2002-04). Two-thirds of these meta-analyses (103/157, 66%) involved no trials published in the preceding 5 years (2001-05). Forty-seven meta-analyses (30%) included no trials published in the preceding 10 years (1996-2005). In another 16 (10%), the statistical significance of the outcomes would have been different had the studies been limited to those published between 1996 and 2005, although in some cases this change in significance would have been due to loss of power. Only 12 (8%) of the meta-analyses discussed the potential implications of including older studies. Among the 22 meta-analyses considered in high-impact general medical journals, 2 included no studies published in the 5 years prior to the reference year (2005), and 18 included at least 1 study published before 1996. Only 4 meta-analyses discussed the implications of including older studies.
In most systematic reviews containing meta-analyses of evidence for health care interventions, very recent studies are rare. Researchers who conduct systematic reviews with meta-analyses, and clinicians who read the outcomes of these studies, should be made aware of the potential implications of including less recent data.
PMCID: PMC2765773  PMID: 19946395
2.  Systematic evaluation of environmental and behavioural factors associated with all-cause mortality in the United States National Health and Nutrition Examination Survey 
Background Environmental and behavioural factors are thought to contribute to all-cause mortality. Here, we develop a method to systematically screen and validate the potential independent contributions to all-cause mortality of 249 environmental and behavioural factors in the National Health and Nutrition Examination Survey (NHANES).
Methods We used Cox proportional hazards regression to associate 249 factors with all-cause mortality while adjusting for sociodemographic factors on data in the 1999–2000 and 2001–02 surveys (median 5.5 follow-up years). We controlled for multiple comparisons with the false discovery rate (FDR) and validated significant findings in the 2003–04 survey (median 2.8 follow-up years). We selected 249 factors from a set of all possible factors based on their presence in both the 1999–2002 and 2003–04 surveys and linkage with at least 20 deceased participants. We evaluated the correlation pattern of validated factors and built a multivariable model to identify their independent contribution to mortality.
Results We identified seven environmental and behavioural factors associated with all-cause mortality, including serum and urinary cadmium, serum lycopene levels, smoking (3-level factor) and physical activity. In a multivariable model, only physical activity, past smoking, smoking in participant’s home and lycopene were independently associated with mortality. These three factors explained 2.1% of the variance of all-cause mortality after adjusting for demographic and socio-economic factors.
Conclusions Our association study suggests that, of the set of 249 factors in NHANES, physical activity, smoking, serum lycopene and serum/urinary cadmium are associated with all-cause mortality as identified in previous studies and after controlling for multiple hypotheses and validation in an independent survey. Whereas other NHANES factors may be associated with mortality, they may require larger cohorts with longer time of follow-up to detect. It is possible to use a systematic association study to prioritize risk factors for further investigation.
PMCID: PMC3887569  PMID: 24345851
All-cause mortality; exposure; behaviour; environment-wide association study
3.  A test for reporting bias in trial networks: simulation and case studies 
Networks of trials assessing several treatment options available for the same condition are increasingly considered. Randomized trial evidence may be missing because of reporting bias. We propose a test for reporting bias in trial networks.
We test whether there is an excess of trials with statistically significant results across a network of trials. The observed number of trials with nominally statistically significant p-values across the network is compared with the expected number. The performance of the test (type I error rate and power) was assessed using simulation studies under different scenarios of selective reporting bias. Examples are provided for networks of antidepressant and antipsychotic trials, where reporting biases have been previously demonstrated by comparing published to Food and Drug Administration (FDA) data.
In simulations, the test maintained the type I error rate and was moderately powerful after adjustment for type I error rate, except when the between-trial variance was substantial. In all, a positive test result increased moderately or markedly the probability of reporting bias being present, while a negative test result was not very informative. In the two examples, the test gave a signal for an excess of statistically significant results in the network of published data but not in the network of FDA data.
The test could be useful to document an excess of significant findings in trial networks, providing a signal for potential publication bias or other selective analysis and outcome reporting biases.
Electronic supplementary material
The online version of this article (doi:10.1186/1471-2288-14-112) contains supplementary material, which is available to authorized users.
PMCID: PMC4193287  PMID: 25262204
Publication bias; Selective outcome reporting; Test of bias; Randomized controlled trials; Comparative effectiveness research
4.  Meta-Analysis of Genome-Wide Scans Provides Evidence for Sex- and Site-Specific Regulation of Bone Mass 
Several genome-wide scans have been performed to detect loci that regulate BMD, but these have yielded inconsistent results, with limited replication of linkage peaks in different studies. In an effort to improve statistical power for detection of these loci, we performed a meta-analysis of genome-wide scans in which spine or hip BMD were studied. Evidence was gained to suggest that several chromosomal loci regulate BMD in a site-specific and sex-specific manner.
BMD is a heritable trait and an important predictor of osteoporotic fracture risk. Several genome-wide scans have been performed in an attempt to detect loci that regulate BMD, but there has been limited replication of linkage peaks between studies. In an attempt to resolve these inconsistencies, we conducted a collaborative meta-analysis of genome-wide linkage scans in which femoral neck BMD (FN-BMD) or lumbar spine BMD (LS-BMD) had been studied.
Materials and Methods
Data were accumulated from nine genome-wide scans involving 11,842 subjects. Data were analyzed separately for LS-BMD and FN-BMD and by sex. For each study, genomic bins of 30 cM were defined and ranked according to the maximum LOD score they contained. While various densitometers were used in different studies, the ranking approach that we used means that the results are not confounded by the fact that different measurement devices were used. Significance for high average rank and heterogeneity was obtained through Monte Carlo testing.
For LS-BMD, the quantitative trait locus (QTL) with greatest significance was on chromosome 1p13.3-q23.3 (p = 0.004), but this exhibited high heterogeneity and the effect was specific for women. Other significant LS-BMD QTLs were on chromosomes 12q24.31-qter, 3p25.3-p22.1, 11p12-q13.3, and 1q32-q42.3, including one on 18p11-q12.3 that had not been detected by individual studies. For FN-BMD, the strongest QTL was on chromosome 9q31.1-q33.3 (p = 0.002). Other significant QTLs were identified on chromosomes 17p12-q21.33, 14q13.1-q24.1, 9q21.32-q31.1, and 5q14.3-q23.2. There was no correlation in average ranks of bins between men and women and the loci that regulated BMD in men and women and at different sites were largely distinct.
This large-scale meta-analysis provided evidence for replication of several QTLs identified in previous studies and also identified a QTL on chromosome 18p11-q12.3, which had not been detected by individual studies. However, despite the large sample size, none of the individual loci identified reached genome-wide significance.
PMCID: PMC4016811  PMID: 17228994
osteoporosis; BMD; linkage; meta-analysis; genome search; genome scan
5.  The Hartung-Knapp-Sidik-Jonkman method for random effects meta-analysis is straightforward and considerably outperforms the standard DerSimonian-Laird method 
The DerSimonian and Laird approach (DL) is widely used for random effects meta-analysis, but this often results in inappropriate type I error rates. The method described by Hartung, Knapp, Sidik and Jonkman (HKSJ) is known to perform better when trials of similar size are combined. However evidence in realistic situations, where one trial might be much larger than the other trials, is lacking. We aimed to evaluate the relative performance of the DL and HKSJ methods when studies of different sizes are combined and to develop a simple method to convert DL results to HKSJ results.
We evaluated the performance of the HKSJ versus DL approach in simulated meta-analyses of 2–20 trials with varying sample sizes and between-study heterogeneity, and allowing trials to have various sizes, e.g. 25% of the trials being 10-times larger than the smaller trials. We also compared the number of “positive” (statistically significant at p < 0.05) findings using empirical data of recent meta-analyses with > = 3 studies of interventions from the Cochrane Database of Systematic Reviews.
The simulations showed that the HKSJ method consistently resulted in more adequate error rates than the DL method. When the significance level was 5%, the HKSJ error rates at most doubled, whereas for DL they could be over 30%. DL, and, far less so, HKSJ had more inflated error rates when the combined studies had unequal sizes and between-study heterogeneity. The empirical data from 689 meta-analyses showed that 25.1% of the significant findings for the DL method were non-significant with the HKSJ method. DL results can be easily converted into HKSJ results.
Our simulations showed that the HKSJ method consistently results in more adequate error rates than the DL method, especially when the number of studies is small, and can easily be applied routinely in meta-analyses. Even with the HKSJ method, extra caution is needed when there are = <5 studies of very unequal sizes.
PMCID: PMC4015721  PMID: 24548571
Meta-analysis; Clinical trial; Trial size; Heterogeneity; Type I error; Random effects; Cochrane Database of Systematic Reviews
6.  There are no randomized controlled trials that support the United States Preventive Services Task Force guideline on screening for depression in primary care: a systematic review 
BMC Medicine  2014;12:13.
The United States Preventive Services Task Force (USPSTF) recommends screening adults for depression in primary care settings when staff-assisted depression management programs are available. This recommendation, however, is based on evidence from depression management programs conducted with patients already identified as depressed, even though screening is intended to identify depressed patients not already recognized or treated. The objective of this systematic review was to evaluate whether there is evidence from randomized controlled trials (RCTs) that depression screening benefits patients in primary care, using an explicit definition of screening.
We re-evaluated RCTs included in the 2009 USPSTF evidence review on depression screening, including only trials that compared depression outcomes between screened and non-screened patients and met the following three criteria: determined patient eligibility and randomized prior to screening; excluded patients already diagnosed with a recent episode of depression or already being treated for depression; and provided the same level of depression treatment services to patients identified as depressed in the screening and non-screening trial arms. We also reviewed studies included in a recent Cochrane systematic review, but not the USPSTF review; conducted a focused search to update the USPSTF review; and reviewed trial registries.
Of the nine RCTs included in the USPSTF review, four fulfilled none of three criteria for a test of depression screening, four fulfilled one of three criteria, and one fulfilled two of three criteria. There were two additional RCTs included only in the Cochrane review, and each fulfilled one of three criteria. No eligible RCTs were found via the updated review.
The USPSTF recommendation to screen adults for depression in primary care settings when staff-assisted depression management programs are available is not supported by evidence from any RCTs that are directly relevant to the recommendation. The USPSTF should re-evaluate this recommendation.
Please see related article:
PROSPERO (#CRD42013004276)
PMCID: PMC3922694  PMID: 24472580
Depression; Primary care; Screening; Systematic review
7.  Evidence-based de-implementation for contradicted, unproven, and aspiring healthcare practices 
Abandoning ineffective medical practices and mitigating the risks of untested practices are important for improving patient health and containing healthcare costs. Historically, this process has relied on the evidence base, societal values, cultural tensions, and political sway, but not necessarily in that order. We propose a conceptual framework to guide and prioritize this process, shifting emphasis toward the principles of evidence-based medicine, acknowledging that evidence may still be misinterpreted or distorted by recalcitrant proponents of entrenched practices and other biases.
PMCID: PMC3892018  PMID: 24398253
Evidence-based medicine; Reversals; Divestment; De-implementation; Contradiction; Bias
8.  Estimating the contribution of genetic variants to difference in incidence of disease between population groups 
Genome-wide association studies have identified multiple genetic susceptibility variants to several complex human diseases. However, risk-genotype frequency at loci showing robust associations might differ substantially among different populations. In this paper, we present methods to assess the contribution of genetic variants to the difference in the incidence of disease between different population groups for different scenarios. We derive expressions for the contribution of a single genetic variant, multiple genetic variants, and the contribution of the joint effect of a genetic variant and an environmental factor to the difference in the incidence of disease. The contribution of genetic variants to the difference in incidence increases with increasing difference in risk-genotype frequency, but declines with increasing difference in incidence between the two populations. The contribution of genetic variants also increases with increasing relative risk and the contribution of joint effect of genetic and environmental factors increases with increasing relative risk of the gene–environmental interaction. The contribution of genetic variants to the difference in incidence between two populations can be expressed as a function of the population attributable risks of the genetic variants in the two populations. The contribution of a group of genetic variants to the disparity in incidence of disease could change considerably by adding one more genetic variant to the group. Any estimate of genetic contribution to the disparity in incidence of disease between two populations at this stage seems to be an elusive goal.
PMCID: PMC3400729  PMID: 22333905
difference in incidence; genetic variants; gene–environmental interaction; population attributable risks
10.  Sex-specific differences in effect size estimates at established complex trait loci 
Background Genetic differences between men and women may contribute to sex differences in prevalence and progression of many common complex diseases.
Using the WTCCC GWAS, we analysed whether there are sex-specific differences in effect size estimates at 142 established loci for seven complex diseases: rheumatoid arthritis, type 1 diabetes (T1D), Crohn’s disease, type 2 diabetes (T2D), hypertension, coronary artery disease and bipolar disorder.
Methods For each Single nucleotide polymorphism (SNP), we calculated the per-allele odds ratio for each sex and the relative odds ratios (RORs; the effect size is higher in men with ROR greater than one). RORs were then meta-analysed across loci within each disease and across diseases.
Results For each disease, summary RORs were not different from one, but there was between-SNP heterogeneity in the RORs for T1D and T2D. Four loci in T1D, three in Crohn’s disease and three in T2D showed differences in the genetic effect between men and women (P < 0.05). We probed these differences in additional independent replication samples for T1D and T2D. The differences remained for the T1D loci CTSH, 17q21 and 20p13 and the T2D locus BCL11A, when WTCCC data and replication data were meta-analysed. Only CTSH showed different genetic effect between men and women in the replication data alone.
Conclusion Our results exclude the presence of large and frequent differences in the effect size estimates between men and women for the established loci in the seven common diseases explored. Documenting small differences in genetic effects between men and women requires large studies and systematic evaluation.
PMCID: PMC3465768  PMID: 22825589
Genetic Predisposition to Disease; Genome-Wide Association Study; Odds ratio; Sex
11.  Systematic evaluation of environmental factors: persistent pollutants and nutrients correlated with serum lipid levels 
Background Both genetic and environmental factors contribute to triglyceride, low-density lipoprotein-cholesterol (LDL-C), and high-density lipoprotein-cholesterol (HDL-C) levels. Although genome-wide association studies are currently testing the genetic factors systematically, testing and reporting one or a few factors at a time can lead to fragmented literature for environmental chemical factors. We screened for correlation between environmental factors and lipid levels, utilizing four independent surveys with information on 188 environmental factors from the Centers of Disease Control, National Health and Nutrition Examination Survey, collected between 1999 and 2006.
Methods We used linear regression to correlate each environmental chemical factor to triglycerides, LDL-C and HDL-C adjusting for age, age2, sex, ethnicity, socio-economic status and body mass index. Final estimates were adjusted for waist circumference, diabetes status, blood pressure and survey. Multiple comparisons were controlled for by estimating the false discovery rate and significant findings were tentatively validated in an independent survey.
Results We identified and validated 29, 9 and 17 environmental factors correlated with triglycerides, LDL-C and HDL-C levels, respectively. Findings include hydrocarbons and nicotine associated with lower HDL-C and vitamin E (γ-tocopherol) associated with unfavourable lipid levels. Higher triglycerides and lower HDL-C were correlated with higher levels of fat-soluble contaminants (e.g. polychlorinated biphenyls and dibenzofurans). Nutrients and vitamin markers (e.g. vitamins B, D and carotenes), were associated with favourable triglyceride and HDL-C levels.
Conclusions Our systematic association study has enabled us to postulate about broad environmental correlation to lipid levels. Although subject to confounding and reverse causality bias, these findings merit evaluation in additional cohorts.
PMCID: PMC3396318  PMID: 22421054
Lipids; cholesterol; environment; pollutants; nutrients; GWAS; EWAS
12.  Strengthening the reporting of genetic risk prediction studies: the GRIPS statement 
The rapid and continuing progress in gene discovery for complex diseases is fueling interest in the potential application of genetic risk models for clinical and public health practice. The number of studies assessing the predictive ability is steadily increasing, but the quality and completeness of reporting varies. A multidisciplinary workshop sponsored by the Human Genome Epidemiology Network developed a checklist of 25 items recommended for strengthening the reporting of Genetic RIsk Prediction Studies, building on the principles established by previous reporting guidelines. These recommendations aim to enhance the transparency of study reporting, and thereby to improve the synthesis and application of information from multiple studies that might differ in design, conduct, or analysis. A detailed Explanation and Elaboration document is published on the EJHG website.
PMCID: PMC3172920  PMID: 21407265
13.  Strengthening the reporting of genetic risk prediction studies (GRIPS): explanation and elaboration 
The rapid and continuing progress in gene discovery for complex diseases is fueling interest in the potential application of genetic risk models for clinical and public health practice. The number of studies assessing the predictive ability is steadily increasing, but they vary widely in completeness of reporting and apparent quality. Transparent reporting of the strengths and weaknesses of these studies is important to facilitate the accumulation of evidence on genetic risk prediction. A multidisciplinary workshop sponsored by the Human Genome Epidemiology Network developed a checklist of 25 items recommended for strengthening the reporting of Genetic RIsk Prediction Studies (GRIPS), building on the principles established by previous reporting guidelines. These recommendations aim to enhance the transparency, quality and completeness of study reporting, and thereby to improve the synthesis and application of information from multiple studies that might differ in design, conduct or analysis.
PMCID: PMC3083630  PMID: 21407270
14.  Strengthening the reporting of genetic risk prediction studies: the GRIPS statement 
Genome Medicine  2011;3(3):16.
The rapid and continuing progress in gene discovery for complex diseases is fueling interest in the potential application of genetic risk models for clinical and public health practice. The number of studies assessing the predictive ability is steadily increasing, but the quality and completeness of reporting varies. A multidisciplinary workshop sponsored by the Human Genome Epidemiology Network developed a checklist of 25 items recommended for strengthening the reporting of genetic risk prediction studies (the GRIPS statement), building on the principles established by prior reporting guidelines. These recommendations aim to enhance the transparency of study reporting, and thereby to improve the synthesis and application of information from multiple studies that might differ in design, conduct, or analysis. A detailed Explanation and Elaboration document is published at
PMCID: PMC3092101  PMID: 21410995
15.  Assessing and reporting heterogeneity in treatment effects in clinical trials: a proposal 
Trials  2010;11:85.
Mounting evidence suggests that there is frequently considerable variation in the risk of the outcome of interest in clinical trial populations. These differences in risk will often cause clinically important heterogeneity in treatment effects (HTE) across the trial population, such that the balance between treatment risks and benefits may differ substantially between large identifiable patient subgroups; the "average" benefit observed in the summary result may even be non-representative of the treatment effect for a typical patient in the trial. Conventional subgroup analyses, which examine whether specific patient characteristics modify the effects of treatment, are usually unable to detect even large variations in treatment benefit (and harm) across risk groups because they do not account for the fact that patients have multiple characteristics simultaneously that affect the likelihood of treatment benefit. Based upon recent evidence on optimal statistical approaches to assessing HTE, we propose a framework that prioritizes the analysis and reporting of multivariate risk-based HTE and suggests that other subgroup analyses should be explicitly labeled either as primary subgroup analyses (well-motivated by prior evidence and intended to produce clinically actionable results) or secondary (exploratory) subgroup analyses (performed to inform future research). A standardized and transparent approach to HTE assessment and reporting could substantially improve clinical trial utility and interpretability.
PMCID: PMC2928211  PMID: 20704705
16.  Primary open angle glaucoma due to T377M MYOC: Population mapping of a Greek founder mutation in Northwestern Greece 
Mutations in the MYOC gene have been shown to explain 5% of unrelated primary open angle glaucoma (POAG) in different populations. In particular, the T377M MYOC mutation has arisen at least three separate times in history, in Great Britain, India, and Greece. The purpose of this study is to investigate the distribution of the mutation among different population groups in the northwestern region of Greece.
Materials and methods:
We explored the distribution of the “Greek” T377M founder mutation in the Epirus region in Northwestern Greece, which could be its origin. Genotyping was performed in POAG cases and controls by PCR amplification of the MYOC gene, followed by digestion with restriction enzyme. Statistical analyses were performed by an exact test, the Kaplan–Meier method and the t-test.
In the isolated Chrysovitsa village in the Pindus Mountains, a large POAG family demonstrated the T377M mutation in 20 of 66 family members while no controls from the Epirus region (n = 124) carried this mutation (P < 0.001). Among other POAG cases from Epirus, 2 out of 14 familial cases and 1 out of 80 sporadic cases showed the mutation (P = 0.057). The probability of POAG diagnosis with advancing age among mutation carriers was 23% at age 40, and reached 100% at age 75. POAG patients with the T377M mutation were diagnosed at a mean age of 51 years (SD ± 13.9), which is younger than the sporadic or familial POAG cases: 63.1 (SD ± 11) and 66.8 (SD ± 9.8) years, respectively.
The T377M mutation was found in high proportion in members of the Chrysovitsa family (30.3%), in lower proportion in familial POAG cases (14.2%) and seems rare in sporadic POAG cases (1.2%), while no controls (0%) from the Epirus region carried the mutation. Historical and geographical data may explain the distribution of this mutation within Greece and worldwide.
PMCID: PMC2850831  PMID: 20390039
primary open angle glaucoma; GLC1C; myocilin; MYOC; founder mutation
17.  Association of RGS4 variants with schizotypy and cognitive endophenotypes at the population level 
While association studies on schizophrenia show conflicting results regarding the importance of the regulator of the G-protein signaling 4 (RGS4) gene, recent work suggests that RGS4 may impact on the structural and functional integrity of the prefrontal cortex. We aimed to study associations of common RGS4 variants with prefrontal dependent cognitive performance and schizotypy endophenotypes at the population level.
Four RGS4 single nucleotide polymorphisms (SNP1 [rs10917670], SNP4 [rs951436], SNP7 [rs951439], and SNP18 [rs2661319]) and their haplotypes were selected. Their associations with self-rated schizotypy (SPQ), vigilance, verbal, spatial working memory and antisaccade eye performance were tested with regressions in a representative population of 2,243 young male military conscripts.
SNP4 was associated with negative schizotypy (higher SPQ negative factor for common T allele, p = 0.009; p = 0.031 for differences across genotypes) and a similar trend was seen also for common A allele of SNP18 (p = 0.039 for allele-load model; but p = 0.12 for genotype differences). Haplotype analyses showed a similar pattern with a dose-response for the most common haplotype (GGGG) on the negative schizotypy score with or without adjustment for age, IQ and their interaction (p = 0.011 and p = 0.024, respectively). There was no clear evidence for any association of the RGS4 variants with cognitive endophenotypes, except for an isolated effect of SNP18 on antisaccade error rate (p = 0.028 for allele-load model).
Common RGS4 variants were associated with negative schizotypal personality traits amongst a large cohort of young healthy individuals. In accordance with recent findings, this may suggest that RGS4 variants impact on the functional integrity of the prefrontal cortex, thus increasing susceptibility for psychotic spectrum disorders.
PMCID: PMC2572614  PMID: 18834502
18.  Effectiveness of antidepressants: an evidence myth constructed from a thousand randomized trials? 
Antidepressants, in particular newer agents, are among the most widely prescribed medications worldwide with annual sales of billions of dollars. The introduction of these agents in the market has passed through seemingly strict regulatory control. Over a thousand randomized trials have been conducted with antidepressants. Statistically significant benefits have been repeatedly demonstrated and the medical literature is flooded with several hundreds of "positive" trials (both pre-approval and post-approval). However, two recent meta-analyses question this picture. The first meta-analysis used data that were submitted to FDA for the approval of 12 antidepressant drugs. While only half of these trials had formally significant effectiveness, published reports almost ubiquitously claimed significant results. "Negative" trials were either left unpublished or were distorted to present "positive" results. The average benefit of these drugs based on the FDA data was of small magnitude, while the published literature suggested larger benefits. A second meta-analysis using also FDA-submitted data examined the relationship between treatment effect and baseline severity of depression. Drug-placebo differences increased with increasing baseline severity and the difference became large enough to be clinically important only in the very small minority of patient populations with severe major depression. In severe major depression, antidepressants did not become more effective, simply placebo lost effectiveness. These data suggest that antidepressants may be less effective than their wide marketing suggests. Short-term benefits are small and long-term balance of benefits and harms is understudied. I discuss how the use of many small randomized trials with clinically non-relevant outcomes, improper interpretation of statistical significance, manipulated study design, biased selection of study populations, short follow-up, and selective and distorted reporting of results has built and nourished a seemingly evidence-based myth on antidepressant effectiveness and how higher evidence standards, with very large long-term trials and careful prospective meta-analyses of individual-level data may reach closer to the truth and clinically useful evidence.
PMCID: PMC2412901  PMID: 18505564
19.  Reporting of Human Genome Epidemiology (HuGE) association studies: An empirical assessment 
Several thousand human genome epidemiology association studies are published every year investigating the relationship between common genetic variants and diverse phenotypes. Transparent reporting of study methods and results allows readers to better assess the validity of study findings. Here, we document reporting practices of human genome epidemiology studies.
Articles were randomly selected from a continuously updated database of human genome epidemiology association studies to be representative of genetic epidemiology literature. The main analysis evaluated 315 articles published in 2001–2003. For a comparative update, we evaluated 28 more recent articles published in 2006, focusing on issues that were poorly reported in 2001–2003.
During both time periods, most studies comprised relatively small study populations and examined one or more genetic variants within a single gene. Articles were inconsistent in reporting the data needed to assess selection bias and the methods used to minimize misclassification (of the genotype, outcome, and environmental exposure) or to identify population stratification. Statistical power, the use of unrelated study participants, and the use of replicate samples were reported more often in articles published during 2006 when compared with the earlier sample.
We conclude that many items needed to assess error and bias in human genome epidemiology association studies are not consistently reported. Although some improvements were seen over time, reporting guidelines and online supplemental material may help enhance the transparency of this literature.
PMCID: PMC2413261  PMID: 18492284
20.  HIV: prevention of opportunistic infections 
BMJ Clinical Evidence  2006;2006:0908.
Opportunistic infections can occur in up to 40% of people with HIV infection and a CD4 count less than 250/mm3, although the risks are much lower with use of highly active antiretroviral treatment.
Methods and outcomes
We conducted a systematic review and aimed to answer the following clinical questions: What are the effects of prophylaxis for P carinii pneumonia (PCP) and toxoplasmosis? What are the effects of antituberculosis prophylaxis in people with HIV infection? What are the effects of prophylaxis for disseminated M avium complex (MAC) disease for people with, and without, previous MAC disease? What are the effects of prophylaxis for cytomegalovirus (CMV), herpes simplex virus (HSV), and varicella zoster virus (VZV)? What are the effects of prophylaxis for invasive fungal disease in people with, and without, previous fungal disease? What are the effects of discontinuing prophylaxis against opportunistic pathogens in people on highly active antiretroviral treatment (HAART)? We searched: Medline, Embase, The Cochrane Library and other important databases up to December 2004 (BMJ Clinical Evidence reviews are updated periodically, please check our website for the most up-to-date version of this review). We included harms alerts from relevant organisations such as the US Food and Drug Administration (FDA) and the UK Medicines and Healthcare products Regulatory Agency (MHRA).
We found 61 systematic reviews, RCTs, or observational studies that met our inclusion criteria.
In this systematic review we present information relating to the effectiveness and safety of the following interventions: acyclovir; antituberculosis prophylaxis; atovaquone; azithromycin (alone or plus rifabutin); clarithromycin (alone, or plus rifabutin and ethambutol, or plus clofazimine); clofazimine plus ethambutol; discontinuing prophylaxis for CMV, MAC, and PCP; ethambutol added to clarithromycin plus clofazimine; famciclovir; fluconazole; isoniazid; itraconazole; oral ganciclovir; rifabutin (alone or plus macrolides); trimethoprim-sulfamethoxazole; and valaciclovir.
Key Points
Opportunistic infections can occur in up to 40% of people with HIV infection and a CD4 count < 250/mm3, although the risks are much lower with use of highly active antiretroviral treatment.
Trimethoprim-sulfamethoxazole or azithromycin may reduce the risk of PCP, but have not been shown to reduce toxoplasmosis infection. Atovaquone may prevent PCP and toxoplasmosis in people who cannot take trimethoprim−sulfamethoxazole, although we don't know this for sure.
Tuberculosis can be prevented by standard prophylaxis in people who are tuberculin skin test positive, but not in those who are tuberculin skin test negative. Short-term combination treatment has similar efficacy to long-term isoniazid monotherapy, but has greater risk of adverse effects.
Azithromycin or clarithromycin may reduce the risk of disseminated Microbacterium avium complex (MAC) disease in people without prior MAC disease. Adding rifabutin may reduce the risk of MAC disease, while adding ethambutol decreases the risk of relapse, compared with other antibiotic regimens.Combination treatment with clarithromycin plus clofazimine may increase mortality and is usually avoided.
Aciclovir reduces the risk of herpes simplex virus (HSV) and varicella zoster virus infection and overall mortality, but has not been shown to reduce cytomegalovirus (CMV) infection. Valaciclovir and ganciclovir may reduce the risk of CMV infection, but may be associated with serious adverse effects.
Fluconazole and itraconazole may reduce the risk of invasive fungal infections or their relapse, but can cause serious adverse effects.
In people with a CD4 cell count above 100−200/mm3, discontinuation of prophylactic treatment may not increase the risk of PCP, toxoplasmosis or MAC infection.
PMCID: PMC2907634
21.  International ranking systems for universities and institutions: a critical appraisal 
BMC Medicine  2007;5:30.
Ranking of universities and institutions has attracted wide attention recently. Several systems have been proposed that attempt to rank academic institutions worldwide.
We review the two most publicly visible ranking systems, the Shanghai Jiao Tong University 'Academic Ranking of World Universities' and the Times Higher Education Supplement 'World University Rankings' and also briefly review other ranking systems that use different criteria. We assess the construct validity for educational and research excellence and the measurement validity of each of the proposed ranking criteria, and try to identify generic challenges in international ranking of universities and institutions.
None of the reviewed criteria for international ranking seems to have very good construct validity for both educational and research excellence, and most don't have very good construct validity even for just one of these two aspects of excellence. Measurement error for many items is also considerable or is not possible to determine due to lack of publication of the relevant data and methodology details. The concordance between the 2006 rankings by Shanghai and Times is modest at best, with only 133 universities shared in their top 200 lists. The examination of the existing international ranking systems suggests that generic challenges include adjustment for institutional size, definition of institutions, implications of average measurements of excellence versus measurements of extremes, adjustments for scientific field, time frame of measurement and allocation of credit for excellence.
Naïve lists of international institutional rankings that do not address these fundamental challenges with transparent methods are misleading and should be abandoned. We make some suggestions on how focused and standardized evaluations of excellence could be improved and placed in proper context.
PMCID: PMC2174504  PMID: 17961208
22.  Materializing research promises: opportunities, priorities and conflicts in translational medicine 
There is considerable evidence that the translation rate of major basic science promises to clinical applications has been inefficient and disappointing. The deficiencies of translational science have often been proposed as an explanation for this failure. An alternative explanation is that until recently basic science advances have made oversimplified assumptions that have not matched the true etiological complexity of most common diseases; while clinical science has suffered from poor research practices, overt biases and conflicts of interest. The advent of molecular medicine and the recasting of clinical science along the principles of evidence-based medicine provide a better environment where translational research may now materialize its goals. At the same time, priority issues need to be addressed in order to exploit the new opportunities. Translational research should focus on diseases with global impact, if true progress is to be made against human suffering. The health outcomes of interest for translational efforts need to be carefully defined and a balance must be struck between the subjective needs of healthcare consumers and objective health outcomes. Development of more simple, practical and safer interventions may be as important a target for translational research as the development of cures for diseases where no effective interventions are available at all. Moreover, while the role of the industry is catalytic in translating research advances to licensed interventions, academic independence needs to be sustained and strengthened at a global level. Conflicts of interest may stifle translational research efforts internationally. The profit motive is unlikely to be sufficient alone to advance biomedical research towards genuine progress.
PMCID: PMC343300  PMID: 14754464
23.  Evidence on Interventions to Reduce Medical Errors 
To critically review the existing evidence on interventions aimed at reducing errors in health care delivery.
Systematic review of randomized trials on behavioral, educational, informational and management interventions relating to medical errors. Pertinent studies were identified from MEDLINE, EMBASE, the Cochrane Clinical Trials Registry, and communications with experts.
Both inpatients and outpatients qualified. No age or disease restrictions were set.
Outcomes were medical errors, including medication, prescription, and diagnostic errors, and excluding preventive medicine errors and simple ordering of redundant tests.
Thirteen randomized studies qualified for evaluation. The trials varied extensively in their patient populations (mean age, 2 weeks to 83 years), study setting, definition of errors, and interventions. Most studies could not afford masking and rigorous allocation concealment. In 9 of 13 studies, error rates in the control arms were very high (10% to 63%), and large treatment benefits from the studied interventions were demonstrated for the main outcome. Interventions were almost always effective in a sample of 24 nonrandomized studies evaluated for comparison. Actual patient harm from serious errors was rarely recorded.
Medical errors were very frequent in the studies we identified, arising sometimes in more than half of the cases where there is an opportunity for error. Relatively simple interventions may achieve large reductions in error rates. Evidence on reduction of medical errors needs to be better categorized, replicated, and tested in study designs maximizing protection from bias. Emphasis should be placed on serious errors.
PMCID: PMC1495210  PMID: 11359552
medical errors; meta-analysis; behavioral interventions; randomized trials; study design
24.  Appendicectomies in Albanians in Greece: outcomes in a highly mobile immigrant patient population 
Albanian immigrants in Greece comprise a highly mobile population with unknown health care profile. We aimed to assess whether these immigrants were more or less likely to undergo laparotomy for suspected appendicitis with negative findings (negative appendicectomy), by performing a controlled study with individual (1:4) matching. We used data from 6 hospitals in the Greek prefecture of Epirus that is bordering Albania.
Among a total of 2027 non-incidental appendicectomies for suspected appendicitis performed in 1994-1999, 30 patients with Albanian names were matched (for age, sex, time of operation and hospital) to 120 patients with Greek names. The odds for a negative appendicectomy were 3.4-fold higher (95% confidence interval [CI], 1.24-9.31, p = 0.02) in Albanian immigrants than in matched Greek-name subjects. The difference was most prominent in men (odds ratio 20.0, 95% CI, 1.41-285, p = 0.02) while it was not formally significant in women (odds ratio 1.56, 95% CI, 0.44-5.48). The odds for perforation were 1.25-fold higher in Albanian-name immigrants than in Greek-name patients (95% CI 0.44- 3.57).
Albanian immigrants in Greece are at high risk for negative appendicectomies. Socioeconomic, cultural and language parameters underlying health care inequalities in highly mobile immigrant populations need better study.
PMCID: PMC35286  PMID: 11472640
25.  Determinants of patient recruitment in a multicenter clinical trials group: trends, seasonality and the effect of large studies 
We examined whether quarterly patient enrollment in a large multicenter clinical trials group could be modeled in terms of predictors including time parameters (such as long-term trends and seasonality), the effect of large trials and the number of new studies launched each quarter. We used the database of all clinical studies launched by the AIDS Clinical Trials Group (ACTG) between October 1986 and November 1999. Analyses were performed in two datasets: one included all studies and substudies (n = 475, total enrollment 69,992 patients) and the other included only main studies (n = 352, total enrollment 57,563 patients).
Enrollment differed across different months of the year with peaks in spring and late fall. Enrollment accelerated over time (+27 patients per quarter for all studies and +16 patients per quarter for the main studies, p < 0.001) and was affected by the performance of large studies with target sample size > 1,000 (p < 0.001). These relationships remained significant in multivariate autoregressive modeling. A time series based on enrollment during the first 32 quarters could forecast adequately the remaining 21 quarters.
The fate and popularity of large trials may determine the overall recruitment of multicenter groups. Modeling of enrollment rates may be used to comprehend long-term patterns and to perform future strategic planning.
PMCID: PMC33393  PMID: 11423002

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