[Do breast-fed children have a lower risk for later obesity? Discussion of a meta-analysis]

The relationship between breast-feeding and childhood obesity is of great interest. Since 2000, several studies have been published with conflicting data regarding the potential protective effect of breast-feeding on childhood obesity. Meta-analyses suggested a small but significant protective effect of breast-feeding, but a recent study was not able to show such an effect. This paper summarises one of these meta-analyses and discusses the strengths and limitations of the meta-analysis approach.

Meta-analysis in medical research: potentials and limitations

Meta-analysis, the statistical combination of results from several studies to produce a single estimate of a treatment effect or size of an association, continues to attract controversy. We illustrate and discuss the promises and limitations of meta-analysis. Meta-analysis of clinical trials can prevent delays in the introduction of effective treatments or lead to the timely identification of adverse effects. However, meta-analyses are liable to numerous biases, both at the level of the individual study and the selection of studies for inclusion in meta-analysis. The biases and confounding factors that threaten the validity of individual studies will also affect meta-analyses of observational studies. We argue that meta-analyses should only be performed within the framework of systematic reviews that have been prepared using methods that minimize bias and address the combinability of studies.

Multidimensional preventive home visit programs for community-dwelling older adults: a systematic review and meta-analysis of randomized controlled trials

BACKGROUND: Multidimensional preventive home visit programs aim at maintaining health and autonomy of older adults and preventing disability and subsequent nursing home admission, but results of randomized controlled trials (RCTs) have been inconsistent. Our objective was to systematically review RCTs examining the effect of home visit programs on mortality, nursing home admissions, and functional status decline. METHODS: Data sources were MEDLINE, EMBASE, Cochrane CENTRAL database, and references. Studies were reviewed to identify RCTs that compared outcome data of older participants in preventive home visit programs with control group outcome data. Publications reporting 21 trials were included. Data on study population, intervention characteristics, outcomes, and trial quality were double-extracted. We conducted random effects meta-analyses. RESULTS: Pooled effects estimates revealed statistically nonsignificant favorable, and heterogeneous effects on mortality (odds ratio [OR] 0.92, 95% confidence interval [CI], 0.80-1.05), functional status decline (OR 0.89, 95% CI, 0.77-1.03), and nursing home admission (OR 0.86, 95% CI, 0.68-1.10). A beneficial effect on mortality was seen in younger study populations (OR 0.74, 95% CI, 0.58-0.94) but not in older populations (OR 1.14, 95% CI, 0.90-1.43). Functional decline was reduced in programs including a clinical examination in the initial assessment (OR 0.64, 95% CI, 0.48-0.87) but not in other trials (OR 1.00, 95% CI, 0.88-1.14). There was no single factor explaining the heterogenous effects of trials on nursing home admissions. CONCLUSION: Multidimensional preventive home visits have the potential to reduce disability burden among older adults when based on multidimensional assessment with clinical examination. Effects on nursing home admissions are heterogeneous and likely depend on multiple factors including population factors, program characteristics, and health care setting.

Empirical evidence of bias in treatment effect estimates in controlled trials with different interventions and outcomes: meta-epidemiological study

OBJECTIVE: To examine whether the association of inadequate or unclear allocation concealment and lack of blinding with biased estimates of intervention effects varies with the nature of the intervention or outcome. DESIGN: Combined analysis of data from three meta-epidemiological studies based on collections of meta-analyses. DATA SOURCES: 146 meta-analyses including 1346 trials examining a wide range of interventions and outcomes. MAIN OUTCOME MEASURES: Ratios of odds ratios quantifying the degree of bias associated with inadequate or unclear allocation concealment, and lack of blinding, for trials with different types of intervention and outcome. A ratio of odds ratios <1 implies that inadequately concealed or non-blinded trials exaggerate intervention effect estimates. RESULTS: In trials with subjective outcomes effect estimates were exaggerated when there was inadequate or unclear allocation concealment (ratio of odds ratios 0.69 (95% CI 0.59 to 0.82)) or lack of blinding (0.75 (0.61 to 0.93)). In contrast, there was little evidence of bias in trials with objective outcomes: ratios of odds ratios 0.91 (0.80 to 1.03) for inadequate or unclear allocation concealment and 1.01 (0.92 to 1.10) for lack of blinding. There was little evidence for a difference between trials of drug and non-drug interventions. Except for trials with all cause mortality as the outcome, the magnitude of bias varied between meta-analyses. CONCLUSIONS: The average bias associated with defects in the conduct of randomised trials varies with the type of outcome. Systematic reviewers should routinely assess the risk of bias in the results of trials, and should report meta-analyses restricted to trials at low risk of bias either as the primary analysis or in conjunction with less restrictive analyses.

An empirical comparison of methods for meta-analysis of diagnostic accuracy showed hierarchical models are necessary

OBJECTIVE: Meta-analysis of studies of the accuracy of diagnostic tests currently uses a variety of methods. Statistically rigorous hierarchical models require expertise and sophisticated software. We assessed whether any of the simpler methods can in practice give adequately accurate and reliable results. STUDY DESIGN AND SETTING: We reviewed six methods for meta-analysis of diagnostic accuracy: four simple commonly used methods (simple pooling, separate random-effects meta-analyses of sensitivity and specificity, separate meta-analyses of positive and negative likelihood ratios, and the Littenberg-Moses summary receiver operating characteristic [ROC] curve) and two more statistically rigorous approaches using hierarchical models (bivariate random-effects meta-analysis and hierarchical summary ROC curve analysis). We applied the methods to data from a sample of eight systematic reviews chosen to illustrate a variety of patterns of results. RESULTS: In each meta-analysis, there was substantial heterogeneity between the results of different studies. Simple pooling of results gave misleading summary estimates of sensitivity and specificity in some meta-analyses, and the Littenberg-Moses method produced summary ROC curves that diverged from those produced by more rigorous methods in some situations. CONCLUSION: The closely related hierarchical summary ROC curve or bivariate models should be used as the standard method for meta-analysis of diagnostic accuracy.

Individual patient data meta-analysis of diagnostic and prognostic studies in obstetrics, gynaecology and reproductive medicine

BACKGROUND: In clinical practice a diagnosis is based on a combination of clinical history, physical examination and additional diagnostic tests. At present, studies on diagnostic research often report the accuracy of tests without taking into account the information already known from history and examination. Due to this lack of information, together with variations in design and quality of studies, conventional meta-analyses based on these studies will not show the accuracy of the tests in real practice. By using individual patient data (IPD) to perform meta-analyses, the accuracy of tests can be assessed in relation to other patient characteristics and allows the development or evaluation of diagnostic algorithms for individual patients. In this study we will examine these potential benefits in four clinical diagnostic problems in the field of gynaecology, obstetrics and reproductive medicine. METHODS/DESIGN: Based on earlier systematic reviews for each of the four clinical problems, studies are considered for inclusion. The first authors of the included studies will be invited to participate and share their original data. After assessment of validity and completeness the acquired datasets are merged. Based on these data, a series of analyses will be performed, including a systematic comparison of the results of the IPD meta-analysis with those of a conventional meta-analysis, development of multivariable models for clinical history alone and for the combination of history, physical examination and relevant diagnostic tests and development of clinical prediction rules for the individual patients. These will be made accessible for clinicians. DISCUSSION: The use of IPD meta-analysis will allow evaluating accuracy of diagnostic tests in relation to other relevant information. Ultimately, this could increase the efficiency of the diagnostic work-up, e.g. by reducing the need for invasive tests and/or improving the accuracy of the diagnostic workup. This study will assess whether these benefits of IPD meta-analysis over conventional meta-analysis can be exploited and will provide a framework for future IPD meta-analyses in diagnostic and prognostic research.

Lifestyle factors and colorectal cancer risk (1): systematic review and meta-analysis of associations with body mass index

OBJECTIVE: Excess body weight, defined by body mass index (BMI), may increase the risk of colorectal cancer. As a prerequisite to the determination of lifestyle attributable risks, we undertook a systematic review and meta-analysis of prospective observational studies to quantify colorectal cancer risk associated with increased BMI and explore for differences by gender, sub-site and study characteristics. METHOD: We searched MEDLINE and EMBASE (to December 2007), and other sources, selecting reports based on strict inclusion criteria. Random-effects meta-analyses and meta-regressions of study-specific incremental estimates were performed to determine the risk ratio (RR) and 95% confidence intervals (CIs) associated with a 5 kg/m(2) increase in BMI. RESULTS: We analysed 29 datasets from 28 articles, including 67,361 incident cases. Higher BMI was associated with colon (RR 1.24, 95% CIs: 1.20-1.28) and rectal (1.09, 1.05-1.14) cancers in men, and with colon cancer (1.09, 1.04-1.12) in women. Associations were stronger in men than in women for colon (P < 0.001) and rectal (P = 0.005) cancers. Associations were generally consistent across geographic populations. Study characteristics and adjustments accounted for only moderate variations of associations. CONCLUSION: Increasing BMI is associated with a modest increased risk of developing colon and rectal cancers, but this modest risk may translate to large attributable proportions in high-prevalence obese populations. Inter-gender differences point to potentially important mechanistic differences, which merit further research.

The importance of allocation concealment and patient blinding in osteoarthritis trials: a meta-epidemiologic study

OBJECTIVE: To evaluate the association of adequate allocation concealment and patient blinding with estimates of treatment benefits in osteoarthritis trials. METHODS: We performed a meta-epidemiologic study of 16 meta-analyses with 175 trials that compared therapeutic interventions with placebo or nonintervention control in patients with hip or knee osteoarthritis. We calculated effect sizes from the differences in means of pain intensity between groups at the end of followup divided by the pooled SD and compared effect sizes between trials with and trials without adequate methodology. RESULTS: Effect sizes tended to be less beneficial in 46 trials with adequate allocation concealment compared with 112 trials with inadequate or unclear concealment of allocation (difference -0.15; 95% confidence interval [95% CI] -0.31, 0.02). Selection bias associated with inadequate or unclear concealment of allocation was most pronounced in meta-analyses with large estimated treatment benefits (P for interaction < 0.001), meta-analyses with high between-trial heterogeneity (P = 0.009), and meta-analyses of complementary medicine (P = 0.019). Effect sizes tended to be less beneficial in 64 trials with adequate blinding of patients compared with 58 trials without (difference -0.15; 95% CI -0.39, 0.09), but differences were less consistent and disappeared after accounting for allocation concealment. Detection bias associated with a lack of adequate patient blinding was most pronounced for nonpharmacologic interventions (P for interaction < 0.001). CONCLUSION: Results of osteoarthritis trials may be affected by selection and detection bias. Adequate concealment of allocation and attempts to blind patients will minimize these biases.

The effects of excluding patients from the analysis in randomised controlled trials: meta-epidemiological study

OBJECTIVE: To examine whether excluding patients from the analysis of randomised trials are associated with biased estimates of treatment effects and higher heterogeneity between trials. DESIGN: Meta-epidemiological study based on a collection of meta-analyses of randomised trials. DATA SOURCES: 14 meta-analyses including 167 trials that compared therapeutic interventions with placebo or non-intervention control in patients with osteoarthritis of the hip or knee and used patient reported pain as an outcome. METHODS: Effect sizes were calculated from differences in means of pain intensity between groups at the end of follow-up, divided by the pooled standard deviation. Trials were combined by using random effects meta-analysis. Estimates of treatment effects were compared between trials with and trials without exclusions from the analysis, and the impact of restricting meta-analyses to trials without exclusions was assessed. RESULTS: 39 trials (23%) had included all patients in the analysis. In 128 trials (77%) some patients were excluded from the analysis. Effect sizes from trials with exclusions tended to be more beneficial than those from trials without exclusions (difference -0.13, 95% confidence interval -0.29 to 0.04). However, estimates of bias between individual meta-analyses varied considerably (tau(2)=0.07). Tests of interaction between exclusions from the analysis and estimates of treatment effects were positive in five meta-analyses. Stratified analyses indicated that differences in effect sizes between trials with and trials without exclusions were more pronounced in meta-analyses with high between trial heterogeneity, in meta-analyses with large estimated treatment benefits, and in meta-analyses of complementary medicine. Restriction of meta-analyses to trials without exclusions resulted in smaller estimated treatment benefits, larger P values, and considerable decreases in between trial heterogeneity. CONCLUSION: Excluding patients from the analysis in randomised trials often results in biased estimates of treatment effects, but the extent and direction of bias is unpredictable. Results from intention to treat analyses should always be described in reports of randomised trials. In systematic reviews, the influence of exclusions from the analysis on estimated treatment effects should routinely be assessed.

Efficacy pneumococcal vaccination in adults: a meta-analysis

Background: Clinical trials and meta-analyses have produced conflicting results of the efficacy of unconjugated pneumococcal polysaccharide vaccine in adults. We sought to evaluate the vaccine’s efficacy on clinical outcomes as well as the methodologic quality of the trials. Methods: We searched several databases and all bibliographies of reviews and meta-analyses for clinical trials that compared pneumococcal polysaccharide vaccine with a control. We examined rates of pneumonia and death, taking the methodologic quality of the trials into consideration. Results: We included 22 trials involving 101 507 participants: 11 trials reported on presumptive pneumococcal pneumonia, 19 on all-cause pneumonia and 12 on allcause mortality. The current 23-valent vaccine was used in 8 trials. The relative risk (RR) was 0.64 (95% confidence interval [CI] 0.43–0.96) for presumptive pneumococcal pneumonia and 0.73 (95% CI 0.56–0.94) for all-cause pneumonia. There was significant heterogeneity between the trials reporting on presumptive pneumonia (I2 = 74%, p < 0.001) and between those reporting on all-cause pneumonia (I2 = 90%, p < 0.001). The RR for all-cause mortality was 0.97 (95% CI 0.87–1.09), with moderate heterogeneity between trials (I2 = 44%, p = 0.053). Trial quality, especially regarding double blinding, explained a substantial proportion of the heterogeneity in the trials reporting on presumptive pneumonia and all-cause pneumonia. There was little evidence of vaccine protection in trials of higher methodologic quality (RR 1.20, 95% CI 0.75–1.92, for presumptive pneumonia; and 1.19, 95% CI 0.95–1.49, for allcause pneumonia in double-blind trials; p for heterogeneity > 0.05). The results for all-cause mortality in double-blind trials were similar to those in all trials combined. There was little evidence of vaccine protection among elderly patients or adults with chronic illness in analyses of all trials (RR 1.04, 95% CI 0.78–1.38, for presumptive pneumococcal pneumonia; 0.89, 95% CI 0.69–1.14, for all-cause pneumonia; and 1.00, 95% CI 0.87–1.14, for all-cause mortality). Interpretation: Pneumococcal vaccination does not appear to be effective in preventing pneumonia, even in populations for whom the vaccine is currently recommended.

Determinants of Advertising Effectiveness: The Development of an International Advertising Elasticity Database and a Meta-Analysis

Increasing demand for marketing accountability requires an efficient allocation of marketing expenditures. Managers who know the elasticity of their marketing instruments can allocate their budgets optimally. Meta-analyses offer a basis for deriving benchmark elasticities for advertising. Although they provide a variety of valuable insights, a major shortcoming of prior meta-analyses is that they report only generalized results as the disaggregated raw data are not made available. This problem is highly relevant because coding of empirical studies, at least to a certain extent, involves subjective judgment. For this reason, meta-studies would be more valuable if researchers and practitioners had access to disaggregated data allowing them to conduct further analyses of individual, e.g., product-level-specific, interests. We are the first to address this gap by providing (1) an advertising elasticity database (AED) and (2) empirical generalizations about advertising elasticities and their determinants. Our findings indicate that the average current-period advertising elasticity is 0.09, which is substantially smaller than the value 0f 0.12 that was recently reported by Sethuraman, Tellis, and Briesch (2011). Furthermore, our meta-analysis reveals a wide range of significant determinants of advertising elasticity. For example, we find that advertising elasticities are higher (i) for hedonic and experience goods than for other goods; (ii) for new than for established goods; (iii) when advertising is measured in gross rating points (GRP) instead of absolute terms; and (iv) when the lagged dependent or lagged advertising variable is omitted.

Comparative efficacy of seven psychotherapeutic interventions for patients with depression: a network meta-analysis

BACKGROUND Previous meta-analyses comparing the efficacy of psychotherapeutic interventions for depression were clouded by a limited number of within-study treatment comparisons. This study used network meta-analysis, a novel methodological approach that integrates direct and indirect evidence from randomised controlled studies, to re-examine the comparative efficacy of seven psychotherapeutic interventions for adult depression. METHODS AND FINDINGS We conducted systematic literature searches in PubMed, PsycINFO, and Embase up to November 2012, and identified additional studies through earlier meta-analyses and the references of included studies. We identified 198 studies, including 15,118 adult patients with depression, and coded moderator variables. Each of the seven psychotherapeutic interventions was superior to a waitlist control condition with moderate to large effects (range d = -0.62 to d = -0.92). Relative effects of different psychotherapeutic interventions on depressive symptoms were absent to small (range d = 0.01 to d = -0.30). Interpersonal therapy was significantly more effective than supportive therapy (d = -0.30, 95% credibility interval [CrI] [-0.54 to -0.05]). Moderator analysis showed that patient characteristics had no influence on treatment effects, but identified aspects of study quality and sample size as effect modifiers. Smaller effects were found in studies of at least moderate (Δd = 0.29 [-0.01 to 0.58]; p = 0.063) and large size (Δd = 0.33 [0.08 to 0.61]; p = 0.012) and those that had adequate outcome assessment (Δd = 0.38 [-0.06 to 0.87]; p = 0.100). Stepwise restriction of analyses by sample size showed robust effects for cognitive-behavioural therapy, interpersonal therapy, and problem-solving therapy (all d>0.46) compared to waitlist. Empirical evidence from large studies was unavailable or limited for other psychotherapeutic interventions. CONCLUSIONS Overall our results are consistent with the notion that different psychotherapeutic interventions for depression have comparable benefits. However, the robustness of the evidence varies considerably between different psychotherapeutic treatments.

Effects of study precision and risk of bias in networks of interventions: a network meta-epidemiological study

BACKGROUND Empirical research has illustrated an association between study size and relative treatment effects, but conclusions have been inconsistent about the association of study size with the risk of bias items. Small studies give generally imprecisely estimated treatment effects, and study variance can serve as a surrogate for study size. METHODS We conducted a network meta-epidemiological study analyzing 32 networks including 613 randomized controlled trials, and used Bayesian network meta-analysis and meta-regression models to evaluate the impact of trial characteristics and study variance on the results of network meta-analysis. We examined changes in relative effects and between-studies variation in network meta-regression models as a function of the variance of the observed effect size and indicators for the adequacy of each risk of bias item. Adjustment was performed both within and across networks, allowing for between-networks variability. RESULTS Imprecise studies with large variances tended to exaggerate the effects of the active or new intervention in the majority of networks, with a ratio of odds ratios of 1.83 (95% CI: 1.09,3.32). Inappropriate or unclear conduct of random sequence generation and allocation concealment, as well as lack of blinding of patients and outcome assessors, did not materially impact on the summary results. Imprecise studies also appeared to be more prone to inadequate conduct. CONCLUSIONS Compared to more precise studies, studies with large variance may give substantially different answers that alter the results of network meta-analyses for dichotomous outcomes.

Breastfeeding and Childhood Asthma: Systematic Review and Meta-Analysis.

Asthma and wheezing disorders are common chronic health problems in childhood. Breastfeeding provides health benefits, but it is not known whether or how breastfeeding decreases the risk of developing asthma. We performed a systematic review and meta-analysis of studies published between 1983 and 2012 on breastfeeding and asthma in children from the general population. We searched the PubMed and Embase databases for cohort, cross-sectional, and case-control studies. We grouped the outcomes into asthma ever, recent asthma, or recent wheezing illness (recent asthma or recent wheeze). Using random-effects meta-analyses, we estimated pooled odds ratios of the association of breastfeeding with the risk for each of these outcomes. We performed meta-regression and stratified meta-analyses. We included 117 of 1,464 titles identified by our search. The pooled odds ratios were 0.78 (95% confidence interval: 0.74, 0.84) for 75 studies analyzing "asthma ever," 0.76 (95% confidence interval: 0.67, 0.86) for 46 studies analyzing "recent asthma," and 0.81 (95% confidence interval: 0.76, 0.87) for 94 studies analyzing recent wheezing illness. After stratification by age, the strong protective association found at ages 0-2 years diminished over time. We found no evidence for differences by study design or study quality or between studies in Western and non-Western countries. A positive association of breastfeeding with reduced asthma/wheezing is supported by the combined evidence of existing studies.

Comparative genetic analyses point to HCP5 as susceptibility locus for HCV-associated hepatocellular carcinoma

BACKGROUND & AIMS: Recently, genetic variations in MICA (lead single nucleotide polymorphism [SNP] rs2596542) were identified by a genome-wide association study (GWAS) to be associated with hepatitis C virus (HCV)-related hepatocellular carcinoma (HCC) in Japanese patients. In the present study, we sought to determine whether this SNP is predictive of HCC development in the Caucasian population as well. METHODS: An extended region around rs2596542 was genotyped in 1924 HCV-infected patients from the Swiss Hepatitis C Cohort Study (SCCS). Pair-wise correlation between key SNPs was calculated both in the Japanese and European populations (HapMap3: CEU and JPT). RESULTS: To our surprise, the minor allele A of rs2596542 in proximity of MICA appeared to have a protective impact on HCC development in Caucasians, which represents an inverse association as compared to the one observed in the Japanese population. Detailed fine-mapping analyses revealed a new SNP in HCP5 (rs2244546) upstream of MICA as strong predictor of HCV-related HCC in the SCCS (univariable p=0.027; multivariable p=0.0002, odds ratio=3.96, 95% confidence interval=1.90-8.27). This newly identified SNP had a similarly directed effect on HCC in both Caucasian and Japanese populations, suggesting that rs2244546 may better tag a putative true variant than the originally identified SNPs. CONCLUSIONS: Our data confirms the MICA/HCP5 region as susceptibility locus for HCV-related HCC and identifies rs2244546 in HCP5 as a novel tagging SNP. In addition, our data exemplify the need for conducting meta-analyses of cohorts of different ethnicities in order to fine map GWAS signals.