The use of one-stage meta-analytic method based on individual participant data for binary adverse events under the rule of three: a simulation study

Cheng, Liang; Ju, Ke; Cai, Ruilie; Xu, Chang

doi:10.7717/peerj.6295

Cited by 11 publications

(12 citation statements)

References 30 publications

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“…An advantage of the Peto OR for such studies is that it does not need a continuity correction to estimate the relative effect and variance. Several simulation studies have shown it to be a more robust effect estimator than the classic OR with continuity correction when the events are rare [15, 28, 32]. We, however, demonstrated no advantage for the Peto ORs in the situation of rare events with large studies; indeed it may lead to less conservative error estimation.…”

Section: Discussionmentioning

confidence: 60%

Peto odds ratios demonstrate no advantage over classic odds ratios in meta-analysis of binary rare outcomes

Furuya‐Kanamori

Lin

et al. 2020

Preprint

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In this study, we examined the discrepancy between large studies and small studies in meta-analyses of rare event outcomes and the impact of Peto versus the classic odds ratios (ORs) through empirical data from the Cochrane Database of Systematic Reviews that collected from January 2003 to May 2018. Meta-analyses of binary outcomes with rare events (event rate <=5%), with at least 5 studies, and with at least one large study (N>=1000) were extracted. The Peto and classic ORs were used as the effect sizes in the meta-analyses, and the magnitude and direction of the ORs of the meta-analyses of large studies versus small studies were compared. The p-values of the meta-analyses of small studies were examined to assess if the Peto and the classic OR methods gave similar results. Totally, 214 meta-analyses were included. Over the total 214 pairs of pooled ORs of large studies versus pooled small studies, 66 (30.84%) had a discordant direction (kappa=0.33) when measured by Peto OR and 69 (32.24%) had a discordant direction (kappa=0.22) when measured by classic OR. The Peto ORs resulted in smaller p-values compared to classic ORs in a substantial (83.18%) number of cases. In conclusion, there is considerable discrepancy between large studies and small studies among the results of meta-analyses of sparse data. The use of Peto odds ratios does not improve this situation and is not recommended as it may result in less conservative error estimation.

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Section: Discussionmentioning

confidence: 60%

Peto odds ratios demonstrate no advantage over classic odds ratios in meta-analysis of binary rare outcomes

Furuya‐Kanamori

Lin

et al. 2020

Preprint

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“…These three were actually the most commonly used methods for rare events in practice. The Peto's OR and MH methods generally perform better than the continuity correction [19,28]. However, the Peto's OR could be only used to deal with studies with single-armed zero-events; for studies with both-arm zero-events, most software programs would remove such studies directly [26].…”

Section: Discussionmentioning

confidence: 99%

Protocols for meta-analysis of intervention safety seldom specified methods to deal with rare events

Zhou

Zhu

Lin

et al. 2020

Journal of Clinical Epidemiology

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Objectives: Meta-analyses of rare events often generate unstable results, and selective reporting of the results may mislead the health care decision. Developing a synthesis plan for rare events in protocol may help to formulate the reporting. We aim to investigate whether existing protocols specified methods to deal with rare events. Study Design and Setting: Protocols (not including Cochrane protocols) for systematic reviews of health care interventions focused on the safety registered in PROSPERO were included. The proportion of protocols that specified methods to deal with rare events and the detailed methods were summarized. We compared the difference of proportions (PD) across different settings. Results: We identified 1,004 eligible protocols, of which, 119 (11.85%, 95% confidence interval (CI): 9.92%, 14.01%) specified methods to deal with rare events. The three most commonly planned methods were the ManteleHaenszel, Peto's odds ratio, and continuity correction. Protocols planned a quantitative analysis (PD 5 0.07, 95% CI: 0.02, 0.12; P 5 0.004) and listed safety as a primary outcome (PD 5 0.07, 95% CI: 0.01, 0.12; P 5 0.018) were more likely to specify methods to deal with rare events. Conclusion: Protocols for systematic reviews of intervention safety seldom specified methods to deal with rare events. Future systematic reviewers should provide a detailed and rigorous synthesis plan for rare events in their protocols.

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“…We concentrate here on MAs of study-level summaries, which is far more common in the assessment of adverse events, though patient-level analysis is to be preferred when data are available. 3 The methods used when performing MAs of binary data are frequently done using the standard inversevariance fixed-effects model which is based on large-sample normal approximation, or fixed-effects methods based on exact distributional theory such as the Mantel-Haenszel (MH) 4 or Peto model, 5 or the standard random-effects DerSimonian-Laird (DL) model. 6 Because these methods lack power to investigate the incidence of rare events and are mostly based on large sample normal approximation particularly inverse-variance, 7,8 their statistical properties for estimating treatment effects are often judged as suboptimal either through results being biased, confidence intervals being inappropriately wide or statistical power being too low to detect any true differences.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Applications of simple and accessible methods for meta-analysis involving rare events: A simulation study

Hodkinson

Kontopantelis²

2021

Stat Methods Med Res

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Meta-analysis of clinical trials targeting rare events face particular challenges when the data lack adequate number of events and are susceptible to high levels of heterogeneity. The standard meta-analysis methods (DerSimonian Laird (DL) and Mantel–Haenszel (MH)) often lead to serious distortions because of such data sparsity. Applications of the methods suited to specific incidence and heterogeneity characteristics are lacking, thus we compared nine available methods in a simulation study. We generated 360 meta-analysis scenarios where each considered different incidences, sample sizes, between-study variance (heterogeneity) and treatment allocation. We include globally recommended methods such as inverse-variance fixed/random-effect (IV-FE/RE), classical-MH, MH-FE, MH-DL, Peto, Peto-DL and the two extensions for MH bootstrapped-DL (bDL) and Peto-bDL. Performance was assessed on mean bias, mean error, coverage and power. In the absence of heterogeneity, the coverage and power when combined revealed small differences in meta-analysis involving rare and very rare events. The Peto-bDL method performed best, but only in smaller sample sizes involving rare events. For medium-to-larger sample sizes, MH-bDL was preferred. For meta-analysis involving very rare events, Peto-bDL was the best performing method which was sustained across all sample sizes. However, in meta-analysis with 20% or more heterogeneity, the coverage and power were insufficient. Performance based on mean bias and mean error was almost identical across methods. To conclude, in meta-analysis of rare binary outcomes, our results suggest that Peto-bDL is better in both rare and very rare event settings in meta-analysis with limited sample sizes. However, when heterogeneity is large, the coverage and power to detect rare events are insufficient. Whilst this study shows that some of the less studied methods appear to have good properties under sparse data scenarios, further work is needed to assess them against the more complex distributional-based methods to understand their overall performances.

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The use of one-stage meta-analytic method based on individual participant data for binary adverse events under the rule of three: a simulation study

Cited by 11 publications

References 30 publications

Peto odds ratios demonstrate no advantage over classic odds ratios in meta-analysis of binary rare outcomes

Peto odds ratios demonstrate no advantage over classic odds ratios in meta-analysis of binary rare outcomes

Protocols for meta-analysis of intervention safety seldom specified methods to deal with rare events

Applications of simple and accessible methods for meta-analysis involving rare events: A simulation study

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