Background The threshold for statistical significance (p < 0.05) has been debated in recent years, with proposals to lower it to p < 0.005 to reduce the frequency of papers concluding with false-positive results, which can result in patients receiving overtreatment, and potentiating the problem of nonreplicable results in medical research. However, to our knowledge the impact of modeling that suggestion—in terms of how many studies might be reclassified as no-difference studies and how much larger studies would need to become to implement that suggestion—has not been assessed in orthopaedic surgery. Questions/purposes We used randomized trials in foot and ankle research to answer the question: If the threshold for statistical significance were lowered from p < 0.05 to p < 0.005, (1) what proportion of foot and ankle RCTs would be reclassified as no-difference trials under a stricter p value threshold, and (2) how much larger would studies have needed to be to retain or obtain 80% power at the p < 0.005 level? Methods We manually reviewed all articles published between 2019 and 2024 in the top 10 ranked orthopaedic journals and the top three foot and ankle–specific journals, both selected based on their 2023 two-year journal Impact Factor, focusing on foot and ankle studies. Studies were included if they met the following criteria: (1) RCT design, (2) focus on foot and ankle conditions or interventions, (3) published in English, and (4) reported p values for primary outcomes. After screening, a total of 123 RCTs met these criteria and were included in the final analysis. Those studies’ p values for primary endpoints were extracted and analyzed under both thresholds. If a study had multiple primary endpoints or evaluated the primary endpoint from multiple domains, all p values were included. We categorized p values into three groups based on the classification proposed by Ioannidis: (1) p < 0.005 as “statistically significant,” (2) 0.005 ≤ p < 0.05 as “suggestive,” and (3) p ≥ 0.05 as “nonsignificant.” For studies with sufficient power analysis data, we calculated the required sample size increase needed to maintain 80% statistical power (1 – beta) at an alpha level of 0.005, using the variance reported in the source studies. The effect size (delta) was inferred from the between-group differences reported in each study. Additionally, multivariable logistic regression analysis was performed to identify factors associated with maintaining statistical significance under the p < 0.005 threshold. Results Among 281 primary endpoints identified from 123 trials, 44% (124 of 281) were statistically significant using the threshold defined in those articles (p < 0.05). Of these significant endpoints, only 42% (52 of 124) of endpoints met the proposed threshold (p < 0.005), whereas 58% (72 of 124) fell between 0.005 and 0.05. Following the classification proposed by Benjamin et al., these endpoints would be reclassified as “suggestive” rather than statistically significant. Overall, only 19% (52 of 281) of all endpoints remained statistically significant under the threshold of 0.005 proposed. Twenty-five percent (31 of 123) of trials maintained statistically significant primary endpoints. Among the 123 trials, 54% (66 of 123) had sufficient power analysis data. Assuming an alpha of 0.005, power of 80%, and effect sizes derived from reported between-group differences, maintaining statistical power under the new threshold would require a mean increase of 69% in the sample size. Logistic regression analysis revealed that extracorporeal shock wave therapy (OR 6.8; p < 0.001) and injection therapy (OR 3.3; p = 0.008) were associated with maintaining significance under the stricter threshold. Conclusion Adopting a threshold of p < 0.005 would substantially impact the interpretation of published foot and ankle RCTs; using that threshold, more than one-half of published RCTs in foot and ankle surgery would have been reclassified as having only “suggestive” or no-difference findings on one or more primary study endpoints. Clinical Relevance Lowering the p value threshold to 0.005 would require larger sample sizes, posing feasibility challenges in foot and ankle surgery because of smaller patient populations. While this shift aims to reduce false-positives, it risks excluding meaningful findings from underpowered studies. More importantly, this debate highlights that no single p value threshold is universally appropriate. Instead of rigidly applying 0.05 or 0.005, researchers should adjust thresholds based on study context—allowing more relaxed thresholds for exploratory studies and stricter ones for high-risk interventions.
Shimozono et al. (2025) studied this question.