EBPI-UWZH Musculoskeletal Epidemiology Research Group, University of Zurich and Balgrist University Hospital, Zurich, Switzerland.
Epidemiology, Biostatistics and Prevention Institute (EBPI), University of Zurich, Zurich, Switzerland.
BMC Med Res Methodol. 2024 Nov 15;24(1):281. doi: 10.1186/s12874-024-02359-3.
A Bayesian approach may be useful in the study of possible treatment-related rare serious adverse events, particularly when there are strongly held opinions in the absence of good quality previous data. We demonstrate the application of a Bayesian analysis by integrating expert opinions with population-based epidemiologic data to investigate the association between chiropractic care and acute lumbar disc herniation (LDH) with early surgery.
Experts' opinions were used to derive probability distributions of the incidence rate ratio (IRR) for acute LDH requiring early surgery associated with chiropractic care. A 'community of priors' (enthusiastic, neutral, and skeptical) was built by dividing the experts into three groups according to their perceived mean prior IRR. The likelihood was formed from the results of a population-based epidemiologic study comparing the relative incidence of acute LDH with early surgery after chiropractic care versus primary medical care, with sensitive and specific outcome case definitions and surgery occurring within 8- and 12-week time windows after acute LDH. The robustness of results to the community of priors and specific versus sensitive case definitions was assessed.
The most enthusiastic 25% of experts had a prior IRR of 0.42 (95% credible interval [CrI], 0.03 to 1.27), while the most skeptical 25% of experts had a prior IRR of 1.66 (95% CrI, 0.55 to 4.25). The Bayesian posterior estimates across priors and outcome definitions ranged from an IRR of 0.39 (95% CrI, 0.21 to 0.68) to an IRR of 1.40 (95% CrI, 0.52 to 2.55). With a sensitive definition of the outcome, the analysis produced results that confirmed prior enthusiasts' beliefs and that were precise enough to shift prior beliefs of skeptics. With a specific definition of the outcome, the results were not strong enough to overcome prior skepticism.
A Bayesian analysis integrating expert beliefs highlighted the value of eliciting informative priors to better understand how new evidence ought to update prior existing beliefs. Clinical epidemiologists are encouraged to integrate informative and expert opinions representing the end-user community of priors in Bayesian analyses, particularly when there are strongly held opinions in the absence of definitive scientific evidence.
贝叶斯方法在研究可能与治疗相关的罕见严重不良事件时可能很有用，特别是在缺乏高质量的先前数据但存在强烈观点的情况下。我们通过将专家意见与基于人群的流行病学数据相结合，来研究整脊治疗与早期手术治疗的急性腰椎间盘突出症（LDH）之间的关联，从而展示了贝叶斯分析的应用。
利用专家意见得出与整脊治疗相关的早期手术治疗急性 LDH 的发病率比（IRR）的概率分布。根据其认为的平均先验 IRR，将专家分为三组，建立“先验共识群体”（热情、中立和怀疑）。通过一项基于人群的流行病学研究形成可能性，该研究比较了整脊治疗与初级医疗保健后急性 LDH 早期手术的相对发病率，具有敏感和特异的结果病例定义，并且手术发生在急性 LDH 后 8 至 12 周的时间窗内。评估了结果对先验共识群体和特定与敏感病例定义的稳健性。
最热情的 25%专家的先验 IRR 为 0.42（95%可信区间[CrI]，0.03 至 1.27），而最怀疑的 25%专家的先验 IRR 为 1.66（95% CrI，0.55 至 4.25）。在不同的先验和结果定义下，贝叶斯后验估计值范围从 IRR 0.39（95% CrI，0.21 至 0.68）到 IRR 1.40（95% CrI，0.52 至 2.55）。使用敏感的结果定义，分析结果证实了先前热情支持者的信念，并且足够精确，可以改变怀疑者的先验信念。使用特定的结果定义，结果不足以克服先前的怀疑。
贝叶斯分析综合了专家的信念，强调了得出有信息的先验以更好地了解新证据应该如何更新先前存在的信念的价值。鼓励临床流行病学家在贝叶斯分析中纳入具有信息性和代表最终用户先验共识群体的专家意见，特别是在缺乏明确科学证据但存在强烈观点的情况下。
