Bradley C. Johnston

Probiotics for the Prevention of Clostridium difficile–Associated Diarrhea: A Systematic Review and Meta-analysis

66% (pooled relative risk, 0.34 [95% CI, 0.24 to 0.49]; I 2 0%). In a population with a 5% incidence of antibiotic-associated CDAD (median control group risk), probiotic prophylaxis would prevent 33 episodes (CI, 25 to 38 episodes) per 1000 persons. Of probiotictreated patients, 9.3% experienced adverse events, compared with 12.6% of control patients (relative risk, 0.82 [CI, 0.65 to 1.05]; I 2 17%). Limitations: In 13 trials, data on CDAD were missing for 5% to 45% of patients. The results were robust to worst-plausible assumptions regarding event rates in studies with missing outcome data. Conclusion: Moderate-quality evidence suggests that probiotic prophylaxis results in a large reduction in CDAD without an increase in clinically important adverse events.

GRADE guidelines: 13. Preparing Summary of Findings tables and evidence profiles—continuous outcomes

Presenting continuous outcomes in Summary of Findings tables presents particular challenges to interpretation. When each study uses the same outcome measure, and the units of that measure are intuitively interpretable (e.g., duration of hospitalization, duration of symptoms), presenting differences in means is usually desirable. When the natural units of the outcome measure are not easily interpretable, choosing a threshold to create a binary outcome and presenting relative and absolute effects become a more attractive alternative. When studies use different measures of the same construct, calculating summary measures requires converting to the same units of measurement for each study. The longest standing and most widely used approach is to divide the difference in means in each study by its standard deviation and present pooled results in standard deviation units (standardized mean difference). Disadvantages of this approach include vulnerability to varying degrees of heterogeneity in the underlying populations and difficulties in interpretation. Alternatives include presenting results in the units of the most popular or interpretable measure, converting to dichotomous measures and presenting relative and absolute effects, presenting the ratio of the means of intervention and control groups, and presenting the results in minimally important difference units. We outline the merits and limitations of each alternative and provide guidance for meta-analysts and guideline developers.

Comparison of Weight Loss Among Named Diet Programs in Overweight and Obese Adults: A Meta-analysis

IMPORTANCE Many claims have been made regarding the superiority of one diet or another for inducing weight loss. Which diet is best remains unclear. OBJECTIVE To determine weight loss outcomes for popular diets based on diet class (macronutrient composition) and named diet. DATA SOURCES Search of 6 electronic databases: AMED, CDSR, CENTRAL, CINAHL, EMBASE, and MEDLINE from inception of each database to April 2014. STUDY SELECTION Overweight or obese adults (body mass index ≥25) randomized to a popular self-administered named diet and reporting weight or body mass index data at 3-month follow-up or longer. DATA EXTRACTION AND SYNTHESIS Two reviewers independently extracted data on populations, interventions, outcomes, risk of bias, and quality of evidence. A Bayesian framework was used to perform a series of random-effects network meta-analyses with meta-regression to estimate the relative effectiveness of diet classes and programs for change in weight and body mass index from baseline. Our analyses adjusted for behavioral support and exercise. MAIN OUTCOMES AND MEASURES Weight loss and body mass index at 6- and 12-month follow-up (±3 months for both periods). RESULTS Among 59 eligible articles reporting 48 unique randomized trials (including 7286 individuals) and compared with no diet, the largest weight loss was associated with low-carbohydrate diets (8.73 kg [95% credible interval {CI}, 7.27 to 10.20 kg] at 6-month follow-up and 7.25 kg [95% CI, 5.33 to 9.25 kg] at 12-month follow-up) and low-fat diets (7.99 kg [95% CI, 6.01 to 9.92 kg] at 6-month follow-up and 7.27 kg [95% CI, 5.26 to 9.34 kg] at 12-month follow-up). Weight loss differences between individual diets were minimal. For example, the Atkins diet resulted in a 1.71 kg greater weight loss than the Zone diet at 6-month follow-up. Between 6- and 12-month follow-up, the influence of behavioral support (3.23 kg [95% CI, 2.23 to 4.23 kg] at 6-month follow-up vs 1.08 kg [95% CI, -1.82 to 3.96 kg] at 12-month follow-up) and exercise (0.64 kg [95% CI, -0.35 to 1.66 kg] vs 2.13 kg [95% CI, 0.43 to 3.85 kg], respectively) on weight loss differed. CONCLUSIONS AND RELEVANCE Significant weight loss was observed with any low-carbohydrate or low-fat diet. Weight loss differences between individual named diets were small. This supports the practice of recommending any diet that a patient will adhere to in order to lose weight.

Credibility of claims of subgroup effects in randomised controlled trials: systematic review

Objective To investigate the credibility of authors’ claims of subgroup effects using a representative sample of recently published randomised controlled trials. Design Systematic review. Data source Core clinical journals, as defined by the National Library of Medicine, in Medline. Study selection Randomised controlled trials published in 2007. Using prespecified criteria, teams of trained reviewers independently judged whether authors claimed subgroup effects and the strength of their claims. Reviewers assessed each of these claims against 10 predefined criteria, developed through a search of existing criteria and a consensus process. Results Of 207 randomised controlled trials reporting subgroup analyses, 64 (31%) made claims for the primary outcome. Of those, 20 were strong claims and 28 claims of a likely effect. Authors included subgroup variables measured at baseline in 60 (94%) trials, used subgroup variable as a stratification factor at randomisation in 13 (20%), clearly prespecified their hypotheses in 26 (41%), correctly prespecified direction in 4 (6%), tested a small number of hypotheses in 28 (44%), carried out a test of interaction that proved statistically significant in 6 (9%), documented replication of a subgroup effect with previous related studies in 21 (33%), identified consistency of a subgroup effect across related outcomes in 19 (30%), and provided a compelling indirect evidence for the effect in 14 (22%). In the 19 trials making more than one claim, only one (5%) checked the independence of the interaction. Of the 64 claims, 54 (84%) met four or fewer of the 10 criteria. For strong claims, more than 50% failed each of the individual criteria, and only three (15%) met more than five criteria. Conclusion Authors often claim subgroup effects in their trial report. However, the credibility of subgroup effects, even when claims are strong, is usually low. Users of the information should treat claims that fail to meet most criteria with scepticism. Trial researchers should report the conduct of subgroup analyses and provide sufficient evidence when claiming a subgroup effect or suggesting a possible effect.

Probiotics for pediatric antibiotic-associated diarrhea: a meta-analysis of randomized placebo-controlled trials

Background: Antibiotic treatment is known to disturb gastrointestinal microflora, which results in a range of clinical symptoms — most notably, diarrhea. This is especially important in children, for whom antibiotics are prescribed frequently. Although meta-analyses have been conducted to evaluate the ability of probiotics to prevent antibiotic-induced diarrhea in the general population, little is known about which probiotic strains and doses might be of most benefit to children. Our objective in this study was to assess the efficacy of probiotics (of any specified strain or dose) for the prevention of antibiotic-associated diarrhea in children and to assess adverse events associated with the use of probiotics when coadministered with antibiotics to children. Methods: A comprehensive search was performed of the major electronic databases (e.g., CENTRAL, MEDLINE, EMBASE, CINAHL, AMED) from their inception to January 2005. We also contacted experts and searched registries and meeting abstracts for additional relevant articles. Randomized controlled trials that compared probiotic treatment with placebo or no treatment, involving pediatric subjects less than 19 years of age were included. Two reviewers independently applied eligibility criteria and assessed the studies for methodological quality. Data were independently extracted by 2 reviewers and analyzed via the standard Cochrane methodology. Results: Six studies were included (total n = 707 patients). The combined results, analyzed with a per-protocol method that reported on the incidence of diarrhea during antibiotic treatment, showed significant benefit for the use of probiotics over placebo (relative risk [RR] 0.43, 95% confidence interval [CI] 0.25–0.75, Ι2 = 70.1%). In contrast, results from intention-to-treat analysis were nonsignificant overall (RR 1.01, 95% CI 0.64–1.61). Subgroup analysis on 4 studies that provided at least 5 billion single-strain colony-forming units (CFUs) daily (range 5.5–40 × 109 Lactobacillus GG, L. sporogens or Saccharomyces boulardii) showed strong evidence with narrow CIs for the preventative effects of probiotics for antibiotic-associated diarrhea (RR 0.36, 95% CI 0.25–0.53, Ι2 = 3.5%). No serious adverse events were reported. Interpretation: The potential protective effects of probiotics to prevent antibiotic-associated diarrhea in children do not withstand intention-to-treat analysis. Before routine use is recommended, further studies (with limited losses of subjects to follow-up) are merited. Trials should involve those probiotic strains and doses with the most promising evidence (i.e., Lactobacillus GG, L. sporogens or S. boulardii at 5–40 × 109 CFUs daily).

Potential impact on estimated treatment effects of information lost to follow-up in randomised controlled trials (LOST-IT): systematic review

Objective To assess the reporting, extent, and handling of loss to follow-up and its potential impact on the estimates of the effect of treatment in randomised controlled trials. Design Systematic review. We calculated the percentage of trials for which the relative risk would no longer be significant under a number of assumptions about the outcomes of participants lost to follow-up. Data sources Medline search of five top general medical journals, 2005-07. Eligibility criteria Randomised controlled trials that reported a significant binary primary patient important outcome. Results Of the 235 eligible reports identified, 31 (13%) did not report whether or not loss to follow-up occurred. In reports that did give the relevant information, the median percentage of participants lost to follow-up was 6% (interquartile range 2-14%). The method by which loss to follow-up was handled was unclear in 37 studies (19%); the most commonly used method was survival analysis (66, 35%). When we varied assumptions about loss to follow-up, results of 19% of trials were no longer significant if we assumed no participants lost to follow-up had the event of interest, 17% if we assumed that all participants lost to follow-up had the event, and 58% if we assumed a worst case scenario (all participants lost to follow-up in the treatment group and none of those in the control group had the event). Under more plausible assumptions, in which the incidence of events in those lost to follow-up relative to those followed-up is higher in the intervention than control group, results of 0% to 33% trials were no longer significant. Conclusion Plausible assumptions regarding outcomes of patients lost to follow-up could change the interpretation of results of randomised controlled trials published in top medical journals.

Prevalence, Characteristics, and Publication of Discontinued Randomized Trials

IMPORTANCE The discontinuation of randomized clinical trials (RCTs) raises ethical concerns and often wastes scarce research resources. The epidemiology of discontinued RCTs, however, remains unclear. OBJECTIVES To determine the prevalence, characteristics, and publication history of discontinued RCTs and to investigate factors associated with RCT discontinuation due to poor recruitment and with nonpublication. DESIGN AND SETTING Retrospective cohort of RCTs based on archived protocols approved by 6 research ethics committees in Switzerland, Germany, and Canada between 2000 and 2003. We recorded trial characteristics and planned recruitment from included protocols. Last follow-up of RCTs was April 27, 2013. MAIN OUTCOMES AND MEASURES Completion status, reported reasons for discontinuation, and publication status of RCTs as determined by correspondence with the research ethics committees, literature searches, and investigator surveys. RESULTS After a median follow-up of 11.6 years (range, 8.8-12.6 years), 253 of 1017 included RCTs were discontinued (24.9% [95% CI, 22.3%-27.6%]). Only 96 of 253 discontinuations (37.9% [95% CI, 32.0%-44.3%]) were reported to ethics committees. The most frequent reason for discontinuation was poor recruitment (101/1017; 9.9% [95% CI, 8.2%-12.0%]). In multivariable analysis, industry sponsorship vs investigator sponsorship (8.4% vs 26.5%; odds ratio [OR], 0.25 [95% CI, 0.15-0.43]; P < .001) and a larger planned sample size in increments of 100 (-0.7%; OR, 0.96 [95% CI, 0.92-1.00]; P = .04) were associated with lower rates of discontinuation due to poor recruitment. Discontinued trials were more likely to remain unpublished than completed trials (55.1% vs 33.6%; OR, 3.19 [95% CI, 2.29-4.43]; P < .001). CONCLUSIONS AND RELEVANCE In this sample of trials based on RCT protocols from 6 research ethics committees, discontinuation was common, with poor recruitment being the most frequently reported reason. Greater efforts are needed to ensure the reporting of trial discontinuation to research ethics committees and the publication of results of discontinued trials.

Adverse Events Associated With Pediatric Spinal Manipulation: A Systematic Review

BACKGROUND. Spinal manipulation is a noninvasive manual procedure applied to specific body tissues with therapeutic intent. Although spinal manipulation is commonly used in children, there is limited understanding of the pediatric risk estimates. OBJECTIVE. Our goal was to systematically identify and synthesize available data on adverse events associated with pediatric spinal manipulation. METHODS. A comprehensive search was performed of 8 major electronic databases (eg, Medline, AMED, MANTIS) from inception to June 2004 irrespective of language. Reports were included if they (1) were a primary investigation of spinal manipulation (eg, observation studies, controlled trials, surveys), (2) included a study population of children who were aged 18 years or younger, and (3) reported data on adverse events. Data were summarized to demonstrate the nature and severity of adverse events that may result rather than their incidence. RESULTS. Thirteen studies (2 randomized trials, 11 observational reports) were identified for inclusion. We identified 14 cases of direct adverse events involving neurologic or musculoskeletal events. Nine cases involved serious adverse events (eg, subarachnoidal hemorrhage, paraplegia), 2 involved moderately adverse events that required medical attention (eg, severe headache), and 3 involved minor adverse events (eg, midback soreness). Another 20 cases of indirect adverse events involved delayed diagnosis (eg, diabetes, neuroblastoma) and/or inappropriate provision of spinal manipulation for serious medical conditions (ie, meningitis, rhabdomyosarcoma). CONCLUSIONS. Serious adverse events may be associated with pediatric spinal manipulation; neither causation nor incidence rates can be inferred from observational data. Conduct of a prospective population-based active surveillance study is required to properly assess the possibility of rare, yet serious, adverse events as a result of spinal manipulation on pediatric patients.

Evolution of Heterogeneity (I2) Estimates and Their 95% Confidence Intervals in Large Meta-Analyses

Background Assessment of heterogeneity is essential in systematic reviews and meta-analyses of clinical trials. The most commonly used heterogeneity measure, I2, provides an estimate of the proportion of variability in a meta-analysis that is explained by differences between the included trials rather than by sampling error. Recent studies have raised concerns about the reliability of I2 estimates, due to their dependence on the precision of included trials and time-dependent biases. Authors have also advocated use of 95% confidence intervals (CIs) to express the uncertainty associated with I2 estimates. However, no previous studies have explored how many trials and events are required to ensure stable and reliable I2 estimates, or how 95% CIs perform as evidence accumulates. Methodology/Principal Findings To assess the stability and reliability of I2 estimates and their 95% CIs, in relation to the cumulative number of trials and events in meta-analysis, we looked at 16 large Cochrane meta-analyses - each including a sufficient number of trials and events to reliably estimate I2 - and monitored the I2 estimates and their 95% CIs for each year of publication. In 10 of the 16 meta-analyses, the I2 estimates fluctuated more than 40% over time. The median number of events and trials required before the cumulative I2 estimates stayed within +/−20% of the final I2 estimate was 467 and 11. No major fluctuations were observed after 500 events and 14 trials. The 95% confidence intervals provided good coverage over time. Conclusions/Significance I2 estimates need to be interpreted with caution when the meta-analysis only includes a limited number of events or trials. Confidence intervals for I2 estimates provide good coverage as evidence accumulates, and are thus valuable for reflecting the uncertainty associated with estimating I2.

Pooling health‐related quality of life outcomes in meta‐analysis—a tutorial and review of methods for enhancing interpretability

BACKGROUND - Meta-analyses of health-related quality of life (HRQL) outcomes present difficulties in interpretation when studies use different instruments to measure the same construct. Presentation of results in standard deviation units (standardized mean difference) is widely used but is limited by vulnerability to differential variability in populations enrolled and interpretational challenges. OBJECTIVE - The objective of this study is to identify and describe the available approaches for enhancing interpretability of meta-analyses involving HRQL outcomes. FINDINGS - We identified 12 approaches in three categories: Summary estimates derived from the pooled standardized mean difference: conversion to units of the most familiar instrument or to risk difference or odds ratio. These approaches remain vulnerable to differential variability in populations. Summary estimates derived from the individual trial summary statistics: conversion to units of the most familiar instrument or to ratio of means. Both are appropriate complementary approaches to measures derived from converted probabilities. Summary estimates derived from the individual trial summary statistics and established minimally important differences for all instruments: presentation in minimally important difference units or conversion to risk difference or odds ratio. Risk differences are ideal for balancing desirable and undesirable consequences of alternative interventions. CONCLUSION - The use of these approaches may enhance the interpretability and the usefulness of systematic reviews involving HRQL outcomes. Copyright