scholarly journals Revisiting and expanding the meta-analysis of variation: The log coefficient of variation ratio, lnCVR

Author(s):  
Alistair M. Senior ◽  
Wolfgang Viechtbauer ◽  
Shinichi Nakagawa

AbstractMeta-analyses are frequently used to quantify the difference in the average values of two groups (e.g., control and experimental treatment groups), but examine the difference in the variability (variance) of two groups. For such comparisons, the two relatively new effect size statistics, namely the log-transformed ‘variability ratio’ (the ratio of two standard deviations; lnVR) and the log-transformed ‘CV ratio’ (the ratio of two coefficients of variation; lnCVR) are useful. In practice, lnCVR may be of most use because a treatment may affect the mean and the variance simultaneously. We review current, and propose new, estimators for lnCVR and lnVR. We also present methods for use when the two groups are dependent (e.g., for cross-over and pre-test-post-test designs). A simulation study evaluated the performance of these estimators and we make recommendations about which estimators one should use to minimise bias. We also present two worked examples that illustrate the importance of accounting for the dependence of the two groups. We found that the degree to which dependence is accounted for in the sampling variance estimates can impact heterogeneity parameters such as τ2 (i.e., the between-study variance) and I2 (i.e., the proportion of the total variability due to between-study variance), and even the overall effect, and in turn qualitative interpretations. Meta-analytic comparison of the variability between two groups enables us to ask completely new questions and to gain fresh insights from existing datasets. We encourage researchers to take advantage of these convenient new effect size measures for the meta-analysis of variation.

2016 ◽  
Vol 26 (4) ◽  
pp. 364-368 ◽  
Author(s):  
P. Cuijpers ◽  
E. Weitz ◽  
I. A. Cristea ◽  
J. Twisk

AimsThe standardised mean difference (SMD) is one of the most used effect sizes to indicate the effects of treatments. It indicates the difference between a treatment and comparison group after treatment has ended, in terms of standard deviations. Some meta-analyses, including several highly cited and influential ones, use the pre-post SMD, indicating the difference between baseline and post-test within one (treatment group).MethodsIn this paper, we argue that these pre-post SMDs should be avoided in meta-analyses and we describe the arguments why pre-post SMDs can result in biased outcomes.ResultsOne important reason why pre-post SMDs should be avoided is that the scores on baseline and post-test are not independent of each other. The value for the correlation should be used in the calculation of the SMD, while this value is typically not known. We used data from an ‘individual patient data’ meta-analysis of trials comparing cognitive behaviour therapy and anti-depressive medication, to show that this problem can lead to considerable errors in the estimation of the SMDs. Another even more important reason why pre-post SMDs should be avoided in meta-analyses is that they are influenced by natural processes and characteristics of the patients and settings, and these cannot be discerned from the effects of the intervention. Between-group SMDs are much better because they control for such variables and these variables only affect the between group SMD when they are related to the effects of the intervention.ConclusionsWe conclude that pre-post SMDs should be avoided in meta-analyses as using them probably results in biased outcomes.


Author(s):  
Pim Cuijpers ◽  
Eirini Karyotaki ◽  
Marketa Ciharova ◽  
Clara Miguel ◽  
Hisashi Noma ◽  
...  

AbstractMeta-analyses show that psychotherapies are effective in the treatment of depression in children and adolescents. However, these effects are usually reported in terms of effect sizes. For patients and clinicians, it is important to know whether patients achieve a clinically significant improvement or deterioration. We conducted such a meta-analysis to examine response, clinically significant change, clinically significant deterioration and recovery as outcomes. We searched four bibliographic databases and included 40 randomised trials comparing psychotherapy for youth depression against control conditions. We used a validated method to estimate outcome rates, based on means, standard deviation and N at baseline and post-test. We also calculated numbers-need-to- treat (NNT). The overall response rate in psychotherapies at 2 (±1) months after baseline was 39% (95% CI: 34–45) and 24% (95% CI: 0.19–28) in control conditions (NNT: 6.2). The difference between therapy and control was still significant at 6–12 months after baseline (NNT=7.8). Clinically significant improvement was found in 54% of youth in therapy, compared with 32% in control groups (NNT=5.3); clinically significant deterioration was 6% in therapy, 13% in controls (NNT=5.1); recovery was 58% in therapy, 36% in controls (NNT=3.3). Smaller effects were found in studies with low risk of bias. Psychotherapies for depression in youth are effective compared to control conditions, but more than 60% of youth receiving therapy do not respond. More effective treatments and treatment strategies are clearly needed. Trial registrationhttps://osf.io/84xka


2021 ◽  
pp. 146531252110272
Author(s):  
Despina Koletsi ◽  
Anna Iliadi ◽  
Theodore Eliades

Objective: To evaluate all available evidence on the prediction of rotational tooth movements with aligners. Data sources: Seven databases of published and unpublished literature were searched up to 4 August 2020 for eligible studies. Data selection: Studies were deemed eligible if they included evaluation of rotational tooth movement with any type of aligner, through the comparison of software-based and actually achieved data after patient treatment. Data extraction and data synthesis: Data extraction was done independently and in duplicate and risk of bias assessment was performed with the use of the QUADAS-2 tool. Random effects meta-analyses with effect sizes and their 95% confidence intervals (CIs) were performed and the quality of the evidence was assessed through GRADE. Results: Seven articles were included in the qualitative synthesis, of which three contributed to meta-analyses. Overall results revealed a non-accurate prediction of the outcome for the software-based data, irrespective of the use of attachments or interproximal enamel reduction (IPR). Maxillary canines demonstrated the lowest percentage accuracy for rotational tooth movement (three studies: effect size = 47.9%; 95% CI = 27.2–69.5; P < 0.001), although high levels of heterogeneity were identified (I2: 86.9%; P < 0.001). Contrary, mandibular incisors presented the highest percentage accuracy for predicted rotational movement (two studies: effect size = 70.7%; 95% CI = 58.9–82.5; P < 0.001; I2: 0.0%; P = 0.48). Risk of bias was unclear to low overall, while quality of the evidence ranged from low to moderate. Conclusion: Allowing for all identified caveats, prediction of rotational tooth movements with aligner treatment does not appear accurate, especially for canines. Careful selection of patients and malocclusions for aligner treatment decisions remain challenging.


2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Liansheng Larry Tang ◽  
Michael Caudy ◽  
Faye Taxman

Multiple meta-analyses may use similar search criteria and focus on the same topic of interest, but they may yield different or sometimes discordant results. The lack of statistical methods for synthesizing these findings makes it challenging to properly interpret the results from multiple meta-analyses, especially when their results are conflicting. In this paper, we first introduce a method to synthesize the meta-analytic results when multiple meta-analyses use the same type of summary effect estimates. When meta-analyses use different types of effect sizes, the meta-analysis results cannot be directly combined. We propose a two-step frequentist procedure to first convert the effect size estimates to the same metric and then summarize them with a weighted mean estimate. Our proposed method offers several advantages over existing methods by Hemming et al. (2012). First, different types of summary effect sizes are considered. Second, our method provides the same overall effect size as conducting a meta-analysis on all individual studies from multiple meta-analyses. We illustrate the application of the proposed methods in two examples and discuss their implications for the field of meta-analysis.


Author(s):  
C Dandurand ◽  
AA Sepehry ◽  
MH Asadi Lari ◽  
R Akagami ◽  
PA Gooderham

Background: The optimal therapeutic approach for adult craniopharyngioma remains controversial. Some advocate for gross total resection (GTR), while others support subtotal resection followed by adjuvant radiotherapy (STR + XRT). Methods: MEDLINE (1946 to July 1st 2016) and EMBASE (1980 to June 30th 2016) were systematically reviewed. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline was followed. At our institution, from 1975 to 2013, 33 patients were treated with initial surgical resection for adult onset craniopharyngioma. 22 patients were included in the present case series. Results: Eligible studies (n=21) were identified from the literature in addition to a case series of our institutional experience. Three groups were available for analysis: GTR, STR + XRT, and STR. The rates of recurrence were 17 %, 27 % and 45%, respectively. This differs from childhood population. The difference in risk of recurrence after GTR vs. STR + XRT did not reach significance (OR: 0.63, 95% confidence interval: 0.33-1.24, P=0.18). This maybe because of low pooled sample size (n=99) who underwent STR+XRT. Conclusions: This is the first and largest meta-analysis examining rate of recurrence in adult craniopharyngioma. Thus, when safe and feasible, a goal of gross total resection should be favored. Each patient should be considered on a case-by-case basis.


2021 ◽  
Author(s):  
Megha Joshi ◽  
James E Pustejovsky ◽  
S. Natasha Beretvas

The most common and well-known meta-regression models work under the assumption that there is only one effect size estimate per study and that the estimates are independent. However, meta-analytic reviews of social science research often include multiple effect size estimates per primary study, leading to dependence in the estimates. Some meta-analyses also include multiple studies conducted by the same lab or investigator, creating another potential source of dependence. An increasingly popular method to handle dependence is robust variance estimation (RVE), but this method can result in inflated Type I error rates when the number of studies is small. Small-sample correction methods for RVE have been shown to control Type I error rates adequately but may be overly conservative, especially for tests of multiple-contrast hypotheses. We evaluated an alternative method for handling dependence, cluster wild bootstrapping, which has been examined in the econometrics literature but not in the context of meta-analysis. Results from two simulation studies indicate that cluster wild bootstrapping maintains adequate Type I error rates and provides more power than extant small sample correction methods, particularly for multiple-contrast hypothesis tests. We recommend using cluster wild bootstrapping to conduct hypothesis tests for meta-analyses with a small number of studies. We have also created an R package that implements such tests.


2018 ◽  
Vol 33 (1) ◽  
pp. 84
Author(s):  
José Valladares-Neto

OBJECTIVE: Effect size (ES) is the statistical measure which quantifies the strength of a phenomenon and is commonly applied to observational and interventional studies. The aim of this review was to describe the conceptual basis of this measure, including its application, calculation and interpretation.RESULTS: As well as being used to detect the magnitude of the difference between groups, to verify the strength of association between predictor and outcome variables, to calculate sample size and power, ES is also used in meta-analysis. ES formulas can be divided into these categories: I – Difference between groups, II – Strength of association, III – Risk estimation, and IV – Multivariate data. The d value was originally considered small (0.20 > d ≤ 0.49), medium (0.50 > d≤ 0.79) or large (d ≥ 0.80); however, these cut-off limits are not consensual and could be contextualized according to a specific field of knowledge. In general, a larger score implies that a larger difference was detected.CONCLUSION: The ES report, in conjunction with the confidence interval and P value, aims to strengthen interpretation and prevent the misinterpretation of data, and thus leads to clinical decisions being based on scientific evidence studies.


2020 ◽  
Vol 19 (1) ◽  
Author(s):  
Kwuntida Uthaisar Kotepui ◽  
Manas Kotepui

Abstract Background Plasmodium spp. and hepatitis B virus (HBV) are among the most common infectious diseases in underdeveloped countries. This study aimed to determine the prevalence of Plasmodium spp. and HBV co-infection in people living in endemic areas of both diseases and to assess the risk factors related to this co-infection. Methods The PubMed, Web of Science, and Scopus databases were searched. Observational cross-sectional studies and retrospective studies assessing the prevalence of Plasmodium species and HBV co-infection were examined. The methodological quality of the included studies was assessed with the Newcastle-Ottawa Scale (NOS), a tool for assessing the quality of nonrandomized studies in meta-analyses, and heterogeneity among the included studies was assessed with Cochran's Q test and the I2 (inconsistency) statistic. The pooled prevalence of the co-infection and its 95% confidence interval (CI) were estimated using the random-effects model, depending on the amount of heterogeneity there was among the included studies. The pooled odds ratio (OR) represented the difference in qualitative variables, whereas the pooled mean difference (MD) represented the difference in quantitative variables. Meta-analyses of the potential risk factors for Plasmodium spp. and HBV co-infection, including patient age and gender, were identified and represented as pooled odds ratios (OR) and 95% CIs. Publication bias among the included studies was assessed by visual inspection of a funnel plot to search for asymmetry. Results Twenty-two studies were included in the present systematic review and meta-analysis. Overall, the pooled prevalence estimate of Plasmodium spp. and HBV co-infection was 6% (95% CI 4–7%, Cochran's Q statistic < 0.001, I2: 95.8%), with prevalences of 10% in Gambia (95% CI: 8–12%, weight: 4.95%), 8% in Italy (95% CI 5–12%, weight: 3.8%), 7% in Nigeria (95% CI 4–10%, weight: 53.5%), and 4% in Brazil (95% CI 2–5%, weight: 19.9%). The pooled prevalence estimate of Plasmodium spp. and HBV co-infection was higher in studies published before 2015 (7%, 95% CI 4–9%, Cochran's Q statistic < 0.001, I2: 96%) than in those published since 2015 (3%, 95% CI 1–5%, Cochran's Q statistic < 0.001, I2: 81.3%). No difference in age and risk of Plasmodium spp. and HBV co-infection group was found between the Plasmodium spp. and HBV co-infection and the Plasmodium monoinfection group (p: 0.48, OR: 1.33, 95% CI 0.60–2.96). No difference in gender and risk of Plasmodium spp. and HBV co-infection group was found between the Plasmodium spp. and HBV co-infection and HBV co-infection group and the Plasmodium monoinfection group (p: 0.09, OR: 2.79, 95% CI 0.86–9.10). No differences in mean aspartate aminotransferase (AST), mean alanine aminotransferase (ALT), or mean total bilirubin levels were found (p > 0.05) between the Plasmodium spp. and HBV co-infection group and the Plasmodium monoinfection group. Conclusions The present study revealed the prevalence of Plasmodium spp. and HBV co-infection, which will help in understanding co-infection and designing treatment strategies. Future studies assessing the interaction between Plasmodium spp. and HBV are recommended.


2020 ◽  
pp. 019459982095796
Author(s):  
Claudia I. Cabrera ◽  
Alexander Joseph Jones ◽  
Noah Philleo Parker ◽  
Amy Emily Lynn Blevins ◽  
Mark S. Weidenbecher

Objective To evaluate the difference in pharygocutaneous fistula (PCF) development between pectoralis major flap onlay and interpositional reconstructions after salvage total laryngectomy (STL). Data Sources Medline, Cochrane, Embase, Web of Science, CINAHL, and ClinicalTrials.gov. Review Methods A systematic review was performed during January 2020. English articles were included that described minor and major PCF rates after STL reconstructed with pectoralis major onlay or interposition. PCFs were classified as major when conservative therapy was unsuccessful and/or revision surgery was needed. Articles describing total laryngopharyngectomies were excluded. Meta-analyses of the resulting data were performed. Results Twenty-four articles met final criteria amassing 1304 patients. Three articles compared onlay with interposition, and 18 compared onlay with primary closure. Pectoralis interposition demonstrated elevated odds ratio (OR) of PCF formation as compared with onlay (OR, 2.34; P < .001). Onlay reconstruction reduced overall (OR, 0.32; P < .001) and major (OR, 0.21; P < .001) PCF development as compared with primary pharyngeal closure alone. Data were insufficient to compare interposition against primary closure. Conclusions This research shows evidence that pectoralis onlay after STL diminishes the odds of total and major PCF development. Pectoralis interposition reconstruction showed elevated odds of PCF formation as compared with pectoralis onlay.


BMJ Open ◽  
2019 ◽  
Vol 9 (6) ◽  
pp. e024886 ◽  
Author(s):  
Klaus Munkholm ◽  
Asger Sand Paludan-Müller ◽  
Kim Boesen

ObjectivesTo investigate whether the conclusion of a recent systematic review and network meta-analysis (Ciprianiet al) that antidepressants are more efficacious than placebo for adult depression was supported by the evidence.DesignReanalysis of a systematic review, with meta-analyses.Data sources522 trials (116 477 participants) as reported in the systematic review by Ciprianiet aland clinical study reports for 19 of these trials.AnalysisWe used the Cochrane Handbook’s risk of bias tool and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach to evaluate the risk of bias and the certainty of evidence, respectively. The impact of several study characteristics and publication status was estimated using pairwise subgroup meta-analyses.ResultsSeveral methodological limitations in the evidence base of antidepressants were either unrecognised or underestimated in the systematic review by Ciprianiet al. The effect size for antidepressants versus placebo on investigator-rated depression symptom scales was higher in trials with a ‘placebo run-in’ study design compared with trials without a placebo run-in design (p=0.05). The effect size of antidepressants was higher in published trials compared with unpublished trials (p<0.0001). The outcome data reported by Ciprianiet aldiffered from the clinical study reports in 12 (63%) of 19 trials. The certainty of the evidence for the placebo-controlled comparisons should be very low according to GRADE due to a high risk of bias, indirectness of the evidence and publication bias. The mean difference between antidepressants and placebo on the 17-item Hamilton depression rating scale (range 0–52 points) was 1.97 points (95% CI 1.74 to 2.21).ConclusionsThe evidence does not support definitive conclusions regarding the benefits of antidepressants for depression in adults. It is unclear whether antidepressants are more efficacious than placebo.


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