Statistical inference and effect measures in abstracts of randomized controlled trials, 1975-2021. A systematic review

1975-2021年随机对照试验摘要中的统计推断和效应指标:一项系统评价

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Abstract

OBJECTIVE: To examine the time trend of statistical inference, statistical reporting style of results, and effect measures from the abstracts of randomized controlled trials (RCTs). STUDY DESGIN AND SETTINGS: We downloaded 385,867 PubMed abstracts of RCTs from 1975 to 2021. We used text-mining to detect reporting of statistical inference (p-values, confidence intervals, significance terminology), statistical reporting style of results, and effect measures for binary outcomes, including time-to-event measures. We validated the text mining algorithms by random samples of abstracts. RESULTS: A total of 320 676 abstracts contained statistical inference. The percentage of abstracts including statistical inference increased from 65% (1975) to 87% (2006) and then decreased slightly. From 1975 to 1990, the sole reporting of language regarding statistical significance was predominant. Since 1990, reporting of p-values without confidence intervals has been the most common reporting style. Reporting of confidence intervals increased from 0.5% (1975) to 29% (2021). The two most common effect measures for binary outcomes were hazard ratios and odds ratios. Number needed to treat and number needed to harm are reported in less than 5% of abstracts with binary endpoints. CONCLUSIONS: Reporting of statistical inference in abstracts of RCTs has increased over time. Increasingly, p-values and confidence intervals are reported rather than just mentioning the presence of "statistical significance". The reporting of odds ratios comes with the liability that the untrained reader will interpret them as risk ratios, which is often not justified, especially in RCTs.

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