Department of Orthodontics and Dentofacial Orthopedics, Dental School/Medical Faculty, University of Bern, Switzerland.
Department of Primary Education, University of Ioannina, Greece.
Eur J Orthod. 2023 Nov 30;45(6):722-730. doi: 10.1093/ejo/cjad031.
In meta-analyses involving a few trials, appropriate measures should be employed to assess between-study heterogeneity. When the number of studies is less than five and heterogeneity is evident, the Hartung and Knapp (HK) correction should be used. The aim of this study was to compare the reported estimates of published orthodontic meta-analyses with the pooled effect size estimates and prediction intervals (PI) calculated using eight heterogeneity estimators and corrected using the HK correction.
Systematic reviews (SRs) published between 2017 and 2022 in four orthodontic journals and the Cochrane Database of Systematic Reviews with a meta-analysis of at least three studies were sourced. Study characteristics were extracted at the SR and the outcome/meta-analysis levels. All selected meta-analyses were re-analysed by fitting a random-effects model using eight different heterogeneity estimators, both with and without the HK correction. For each meta-analysis, the overall estimate, along with its standard error, the P-value, and the corresponding 95% confidence interval (CI), the between-study variance (tau2), the I2 statistic, and the PI were calculated.
One-hundred-six SRs were analysed. The most prevalent type of SR was non-Cochrane (95.3%), and the most used meta-analyses synthesis model was the random effect (83.0%). The median number of primary studies was 6 (interquartile range: 5, range: 3-45). The between-study variance was reported in most of the eligible meta-analyses (91.5%), but the type of heterogeneity estimator was reported in only one of them (0.9%). In 5 of 106 meta-analyses (4.7%), the HK correction was applied to adjust the CI of the pooled estimate. The percentage of statistically significant results, which became statistically non-significant, ranged from 16.7% to 25%, depending on the heterogeneity estimator. As the number of studies in a meta-analysis increased, the difference between corrected and uncorrected CIs reduced. Based on the PIs, more than half of the meta-analyses having statistically significant results are likely to change in the future, suggesting the result of the meta-analysis is not conclusive.
The statistical significance of pooled estimates from meta-analyses with at least three studies is sensitive to the HK correction, the heterogeneity variance estimator, and PIs. Clinicians should be aware of the clinical implications of not appropriately assessing the effect of the small number of studies and the between-study heterogeneity when interpreting results from meta-analyses.
在涉及少数试验的荟萃分析中，应采用适当的措施来评估研究间的异质性。当研究数量少于 5 且存在明显的异质性时，应使用 Hartung 和 Knapp（HK）校正。本研究旨在比较已发表的正畸荟萃分析的报告估计值与使用 8 种异质性估计量计算的合并效应量估计值和预测区间（PI），并使用 HK 校正进行校正。
检索了 2017 年至 2022 年间发表在四家正畸期刊和 Cochrane 系统评价数据库中的系统评价（SR），并纳入至少有三项研究的荟萃分析。在 SR 和结果/荟萃分析层面提取研究特征。所有入选的荟萃分析均使用 8 种不同的异质性估计量重新进行分析，包括使用和不使用 HK 校正的随机效应模型。对于每个荟萃分析，计算总体估计值及其标准误差、P 值及其相应的 95%置信区间（CI）、研究间方差（tau2）、I2 统计量和 PI。
共分析了 106 项 SR。最常见的 SR 类型是非 Cochrane（95.3%），最常用的荟萃分析综合模型是随机效应（83.0%）。纳入的荟萃分析中，中位数为 6 项（四分位距：5，范围：3-45）。大多数合格的荟萃分析都报告了研究间方差（91.5%），但只有 1 项（0.9%）报告了异质性估计量的类型。在 106 项荟萃分析中有 5 项（4.7%）应用了 HK 校正来调整合并估计值的 CI。由于异质性估计量的不同，统计显著结果变为不显著的百分比范围为 16.7%至 25%。随着荟萃分析中研究数量的增加，校正和未校正 CI 之间的差异减少。根据 PI，超过一半的具有统计学意义的荟萃分析在未来可能会发生变化，这表明荟萃分析的结果并不具有结论性。
至少有三项研究的荟萃分析的合并估计值的统计学显著性对 HK 校正、异质性方差估计量和 PI 敏感。临床医生在解释荟萃分析结果时，应注意到不适当评估少数研究的效果和研究间异质性对结果的影响。
