Conducting proportional meta-analysis in different types of systematic reviews: a guide for synthesisers of evidence

Barker, Timothy Hugh; Migliavaca, Celina Borges; Stein, Cinara; Colpani, Verônica; Falavigna, Maicon; Aromataris, Edoardo; Munn, Zachary

doi:10.1186/s12874-021-01381-z

Cited by 352 publications

(263 citation statements)

References 45 publications

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“…Finally, we conducted meta-regression 55,56 using a mixed effects model using the formula: where is the observed effect-size with k studies, is the intercept, is the regression coefficient, εk is the sampling error through which the effect size of a study deviates from its true effect, and ζk is the heterogeneity. We built a multiple regression model by hierarchical addition of the following predictors: region, period of study (2001-‘10 vs 2011-’20), and sex after excluding studies involving multiple regions.…”

Section: Meta-regressionmentioning

confidence: 99%

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Population-level hypertension control rate in India: A systematic review and meta-analysis of community based non-interventional studies, 2001-2020

Koya

Pilakkadavath

Wilson³

et al. 2022

Preprint

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Background: Hypertension is a significant contributor to mortality in India. This systematic review and meta-analysis aimed to understand the overall hypertension control rate in India, differences across sex and regions, and changes over time. Methods: Community-based, non-interventional studies published between 2001 and 2020 were searched in PubMed, Embase, and Web of Science. Modified New Castle-Ottawa scales was used to assess the risk of bias. We conducted a random-effects meta-analysis to provide summary estimates by including 29 studies that had a minimum sample size of 100 each. We also conducted subgroup analysis and meta-regression to explore changes in control rates over years and to explain the heterogeneity. Results: The systematic review included 170,631 hypertensive patients. The overall control rate was 33.2% (95% CI-27.9,38.6) with substantial heterogeneity, I2=99.1 % (95% CI-98.9,99.2; p <0.001). Subgroup analysis showed that hypertension control rates did not improve over the years (35.8% in 2011-2020 versus 29.6% in 2001-2010, p=0.23) and did not vary between males and females (34.2% for females and 28.2% for males, p=0.23). Control rates were significantly higher in the south region compared to other regions. Meta-regression model with sex, region, study period, and an interaction term for region and period of the study explained 76.5% of heterogeneity. Very few studies analyzed relevant factors that are associated with adequate control. Conclusion: Hypertension is adequately controlled only among one-third of patients in India. India needs more studies at community levels to understand the health system and socioeconomic factors that determine uncontrolled hypertension in India. PROSPERO registration: CRD42021267973

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Section: Meta-regressionmentioning

confidence: 99%

“…To control rate for differences in region, period of study, and sex, we conducted a mixed-effects meta-regression 55,56 using the model equation:…”

Section: Meta-regressionmentioning

confidence: 99%

Population-level hypertension control rate in India: A systematic review and meta-analysis of community based non-interventional studies, 2001-2020

Koya

Pilakkadavath

Wilson³

et al. 2022

Preprint

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“…However, as recently noted by Barker et al ., the assumption of positive results being more often published is not necessarily true for proportional studies, as there is no clear definition or consensus about what a positive result in a meta‐analysis of proportion is 34 . In our view, more plausible explanations for the absence of publications are that the studies had a small sample size or general poor quality.…”

Section: Resultsmentioning

confidence: 86%

Prevalence and correlates of obesity among the oldest old. A systematic review, meta‐analysis and meta‐regression

Hajek

Kretzler

König

2022

Geriatrics Gerontology Int

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Thus far, the prevalence and correlates of obesity among the oldest have been identified in several studies. Nevertheless, there is a lack of a systematic review, meta-analysis and metaregression synthesizing the existing observational studies. Consequently, our aim was to fill this knowledge gap. Three electronic databases were searched (Medline, PsycINFO, CINAHL) and an additional hand search was performed. Observational studies (both, cross-sectional and longitudinal) determining the prevalence and (preferably) the correlates of obesity in the oldest old (≥80 years) were included. Data extraction covered study design, measurement of obesity, analytical approach, sample characteristics and main results. In total, 19 studies were included. Reported prevalence of obesity in the community varied greatly (range 0.7%-71.5%). The pooled prevalence of obesity was 17.8% (95% CI: 13.3%À22.2%), with significant heterogeneity between studies (I 2 = 99.7%, P < 0.001). There is evidence of a publication bias. Meta-regressions showed that some of the heterogeneity was explained by the types of measures of obesity and country of the respective sample. In conclusion, obesity remains a key challenge among the oldest old. Future research in this age bracket is urgently required in regions mostly neglected thus far (e.g., South America, Africa or Asia). Moreover, studies based on longitudinal data are required to clarify the determinants of obesity among the oldest old. Furthermore, studies based on objectively recorded obesity (e.g., waist circumference) are also required.

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“…Where possible, data on antibiotic consumption and appropriateness of antibiotic prescribing were pooled using a random-effects model meta-analysis, due to the likeliness of unexplained heterogeneity. 15 Data on antibiotic consumption were pooled with meta-analyses of rates using the generic inverse variance method, with DDD/100 patient-days as the rate and sample sizes as the denominator. Data on the appropriateness of antibiotic prescribing, separate for Gyssens method and reference guidelines, were pooled with meta-analyses of proportions using the generalised linear mixed model (GLMM) with the logit transformation to retain studies with extreme proportions.…”

Section: Methodsmentioning

confidence: 99%

Optimizing antibiotic use in Indonesia: a systematic review and synthesis of current evidence to inform opportunities for intervention

Limato

Lazarus

Dernison

et al. 2022

Preprint

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Introduction A major driver of antimicrobial resistance (AMR) and poor clinical outcomes is suboptimal antibiotic use, although data are lacking in low-resource settings. We reviewed studies on systemic antibiotic use (WHO ATC/DDD category J01) for human health in Indonesia, and synthesized available evidence to identify opportunities for intervention. Methods We systematically searched five international and national databases for eligible peer-reviewed articles, in English and Indonesian, published between 1 January 2000 and 1 June 2021 including: 1) antibiotic consumption; 2) prescribing appropriateness; 3) antimicrobial stewardship (AMS); 4) perceptions among consumers and providers. Two independent reviewers included studies and extracted data. Study-level data were summarized using random-effects model meta-analysis for consumption and prescribing appropriateness, effect direction analysis for AMS interventions, and qualitative synthesis for perception surveys. (PROSPERO CRD42019134641) Results Of 9323 search hits, we included 100 reports on antibiotic consumption (20), prescribing appropriateness (49), AMS (13), and/or perception (25) (8 categorized in >1 domain). The pooled estimate of overall antibiotic consumption was 110.1 DDD/100 patient-days (95%CI98.5-121.6), with ceftriaxone, ampicillin and levofloxacin being most consumed. Pooled estimates for overall appropriate prescribing (according to Gyssens method) were 33.5% (95%CI18.1-53.4%) in hospitals and 49.4% (95%CI23.7-75.4%) in primary care. Pooled estimates for appropriate prescribing (according to reference guidelines) were, in hospitals, 99.7% (95%CI97.4-100%) for indication, 84.9% (95%CI38.5-98.0%) for drug choice, and 6.1% (95%CI0.2-63.2%) for overall appropriateness, and, in primary care, 98.9% (95%CI60.9-100%) for indication, 82.6% (95%CI50.5%-95.7%) for drug choice and 10.5% (95%CI0.8-62.6%) for overall appropriateness. The few AMS intervention studies conducted to date suggested potential to reduce antibiotic consumption and improve prescribing appropriateness. Key themes identified in perception surveys were lack of antibiotic knowledge among consumers and non-prescription antibiotic self-medication. Conclusions Context-specific strategies are urgently needed to improve rational antibiotic use in Indonesian hospitals and communities, with critical evidence gaps concerning private and informal health providers.

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Conducting proportional meta-analysis in different types of systematic reviews: a guide for synthesisers of evidence

Cited by 352 publications

References 45 publications

Population-level hypertension control rate in India: A systematic review and meta-analysis of community based non-interventional studies, 2001-2020

Population-level hypertension control rate in India: A systematic review and meta-analysis of community based non-interventional studies, 2001-2020

Prevalence and correlates of obesity among the oldest old. A systematic review, meta‐analysis and meta‐regression

Optimizing antibiotic use in Indonesia: a systematic review and synthesis of current evidence to inform opportunities for intervention

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