scholarly journals A sensitivity analysis framework for the treatment effect measure used in the meta‐analysis of comparative binary data from randomised controlled trials

2012 ◽  
Vol 32 (6) ◽  
pp. 931-940 ◽  
Author(s):  
Dan Jackson ◽  
Rose Baker ◽  
Jack Bowden
Keyword(s):  
Sensitivity Analysis ◽  
Treatment Effect ◽  
Binary Data ◽  
Randomised Controlled Trials ◽  
Meta Analysis ◽  
Controlled Trials ◽  
Analysis Framework ◽  
Effect Measure ◽  
Randomised Controlled

Treating depression with physical activity in adolescents and young adults: a systematic review and meta-analysis of randomised controlled trials

2017 ◽  
Vol 48 (7) ◽  
pp. 1068-1083 ◽  
Author(s):  
A. P. Bailey ◽  
S. E. Hetrick ◽  
S. Rosenbaum ◽  
R. Purcell ◽  
A. G. Parker
Keyword(s):  
Physical Activity ◽  
Young Adults ◽  
Treatment Effect ◽  
Randomised Controlled Trials ◽  
Meta Analysis ◽  
Risk Of Bias ◽  
Adolescents And Young Adults ◽  
Controlled Trials ◽  
Randomised Controlled

AbstractWe aimed to establish the treatment effect of physical activity for depression in young people through meta-analysis. Four databases were searched to September 2016 for randomised controlled trials of physical activity interventions for adolescents and young adults, 12–25 years, experiencing a diagnosis or threshold symptoms of depression. Random-effects meta-analysis was used to estimate the standardised mean difference (SMD) between physical activity and control conditions. Subgroup analysis and meta-regression investigated potential treatment effect modifiers. Acceptability was estimated using dropout. Trials were assessed against risk of bias domains and overall quality of evidence was assessed using GRADE criteria. Seventeen trials were eligible and 16 provided data from 771 participants showing a large effect of physical activity on depression symptoms compared to controls (SMD = −0.82, 95% CI = −1.02 to −0.61, p < 0.05, I2 = 38%). The effect remained robust in trials with clinical samples (k = 5, SMD = −0.72, 95% CI = −1.15 to −0.30), and in trials using attention/activity placebo controls (k = 7, SMD = −0.82, 95% CI = −1.05 to −0.59). Dropout was 11% across physical activity arms and equivalent in controls (k = 12, RD = −0.01, 95% CI = −0.04 to 0.03, p = 0.70). However, the quality of RCT-level evidence contributing to the primary analysis was downgraded two levels to LOW (trial-level risk of bias, suspected publication bias), suggesting uncertainty in the size of effect and caution in its interpretation. While physical activity appears to be a promising and acceptable intervention for adolescents and young adults experiencing depression, robust clinical effectiveness trials that minimise risk of bias are required to increase confidence in the current finding. The specific intervention characteristics required to improve depression remain unclear, however best candidates given current evidence may include, but are not limited to, supervised, aerobic-based activity of moderate-to-vigorous intensity, engaged in multiple times per week over eight or more weeks. Further research is needed. (Registration: PROSPERO-CRD 42015024388).

scholarly journals Effect Measures in Meta-Analysis

2015 ◽  
Vol 62 (2) ◽  
pp. 75-80
Author(s):  
Md Belal Hossain
Keyword(s):  
Fixed Effects ◽  
Randomised Controlled Trials ◽  
Individual Patient Data ◽  
Meta Analysis ◽  
Controlled Trials ◽  
Random Effects Model ◽  
Fixed Effects Model ◽  
Randomised Trials ◽  
Effect Measure ◽  
Randomised Controlled

When conducting a meta-analysis of randomised controlled trials outcomes, appropriate choice of the effect measure is important. This article demonstrates on various types of effect measures in meta-analysis, for example, binary, continuous and ordinal outcomes. A general fixed effects model and a random effects model are employed for combining these outcomes in meta-analysis. Six trials totaling 1876 patients from a meta-analysis of randomised controlled trials evaluating the efficacy and drawbacks of limited (D1) versus extended lymphadenectomy (D2) for proven gastric adenocarcinoma are analysed for binary and continuous outcomes. An individual patient data consisting of five randomised trials of anti-cholinesterase drug tacrine in patients with Alzheimer's disease is also discussed for ordinal outcomes. DOI: http://dx.doi.org/10.3329/dujs.v62i2.21969 Dhaka Univ. J. Sci. 62(2): 75-80, 2014 (July)

scholarly journals Iron deficiency without anaemia is a potential cause of fatigue: meta-analyses of randomised controlled trials and cross-sectional studies

2017 ◽  
Vol 117 (10) ◽  
pp. 1422-1431 ◽  
Author(s):  
Katsuhiko Yokoi ◽  
Aki Konomi
Keyword(s):  
Sensitivity Analysis ◽  
Therapeutic Effect ◽  
Effect Size ◽  
Randomised Controlled Trials ◽  
Meta Analysis ◽  
Controlled Trials ◽  
Cross Sectional ◽  
Cross Sectional Studies ◽  
Randomised Controlled ◽  
Meta Analyses

AbstractFe deficiency is a prevalent nutritional disease, and fatigue is a common complaint in the general and patient population. The association between Fe deficiency without anaemia (IDNA) and fatigue is unclear. Here, we performed a meta-analysis to evaluate the therapeutic effect of Fe on fatigue in patients with IDNA and the association between IDNA and fatigue in the population. Articles from the PubMed database up to 19 January 2016 were systematically searched. A total of six relevant randomised controlled trials (RCT) and six relevant cross-sectional studies were identified. All outcomes were converted into effect sizes. In the meta-analysis of the six RCT, we identified a significant therapeutic effect of Fe in fatigue patients with IDNA (pooled effect size 0·33; 95 % CI 0·17, 0·48;I2=0·0 %;P<0·0001). A sensitivity analysis found that the overall results (i.e. significant association) were robust. In the meta-analysis of the six cross-sectional studies, the association between IDNA and fatigue was not significant (pooled effect size 0·10; 95 % CI −0·11, 0·31;I2=57·4 %;P=0·362). A sensitivity analysis found that the overall results (i.e. no significant association) were not robust; removal of one study made the outcomes significant. These meta-analyses suggest that improving Fe status may decrease fatigue. Further research is necessary to identify diagnostic criteria for selecting fatigue patients who might benefit from Fe therapy and to assess the prevalence of IDNA with fatigue in the general population.

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