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Selecting Treatments During an Infectious Disease Pandemic: Chasing the Evidence
Annals of Internal Medicine ( IF 39.2 ) Pub Date : 2021-08-17 , DOI: 10.7326/m21-3221
Marshall J Glesby 1 , Roy M Gulick 1
Affiliation  

How do clinicians assess and incorporate information on treating a potentially fatal new disease? The COVID-19 pandemic brought this question into focus as rapidly emerging evidence informed decisions on implementing and deimplementing treatments. Traditionally, peer-reviewed, published, randomized clinical trials define the standard of care for treatment. In the setting of COVID-19, a more rapid response evolved: Available drugs were repurposed for treatment on the basis of in vitro data, anecdotal reports, case series, and retrospective observational studies because of desperation to “do something.” This was fueled by colleagues, patients and their families, the popular press, and social media and led to a cacophony of treatment approaches.

An extreme example occurred early in the pandemic (1): The results of a small uncontrolled study of hydroxychloroquine plus azithromycin were initially disseminated on YouTube on 17 March 2020 and then electronically published in the International Journal of Antimicrobial Agents on 20 March 2020 (2). On 21 March 2020, a U.S. political leader tweeted that this drug combination has “a real chance to be one of the biggest game changers in the history of medicine.” On 3 April 2020, the journal posted a statement of concern about the study's methodology, noting that although it is important to help the scientific community by publishing new data fast, this cannot be at the cost of reducing scientific scrutiny and best practices” (3). Ultimately, published randomized clinical trials failed to demonstrate benefit. Of note, several subsequent studies that received considerable attention—published in peer-reviewed journals (4, 5) or as non–peer-reviewed preprints, the latter advocated by some funding agencies and journals for more rapid data dissemination—were retracted because of concerns about data quality or integrity, in a trend that continues (6).

To help bring order to this chaos, within a few months of the first confirmed U.S. case of COVID-19 the National Institutes of Health (7, 8) and some professional societies expeditiously developed online guidelines that could be rapidly updated on the basis of emerging evidence. Over time, the quality of data behind many recommendations changed from “expert opinion” to observational, retrospective data and ultimately to randomized controlled clinical trials.

How have clinicians treated COVID-19 in this rapidly changing landscape? Mehta and colleagues (9) address this by describing temporal trends in the use of 3 drugs for the treatment of COVID-19 in U.S. patients hospitalized over a 13-month period beginning in February 2020. They studied 137 870 adults in the National COVID Cohort Collaborative (N3C), a retrospective cohort constructed from electronic health record data at 43 health centers. They focused on 3 drugs: hydroxychloroquine, remdesivir, and dexamethasone. Hydroxychloroquine was available because it had approval from the U.S. Food and Drug Administration (FDA) for other indications. It demonstrated in vitro activity against SARS-CoV-2, prompting emergency use authorization (EUA) status by the FDA, but it was ultimately found to be ineffective and the emergency use authorization was revoked. Remdesivir, an antiviral agent, improved time to recovery but not survival in randomized clinical trials of hospitalized patients with COVID-19, supporting FDA approval, and these data led to conflicting guideline recommendations. Dexamethasone demonstrated a mortality benefit in hospitalized patients with COVID-19 who required oxygen, particularly those receiving mechanical ventilation. The authors found a rapid increase in hydroxychloroquine use with a reassuringly rapid decline over weeks as evidence emerged of its lack of efficacy. Use of remdesivir and subsequently dexamethasone increased in association with emerging efficacy data and guideline recommendations from the National Institutes of Health. Of note, the authors found considerable variation in use of the 3 drugs across health centers; variation was greatest with remdesivir, and dexamethasone use differed significantly, especially among patients receiving mechanical ventilation.

The authors emphasize their key finding that approximately one fifth of mechanically ventilated patients did not receive corticosteroids despite release of the RECOVERY (Randomised Evaluation of COVID-19 Therapy) trial results in June 2020 that showed a survival benefit in this subgroup. Their data, however, show a remarkably rapid uptake of corticosteroid therapy within a month of the press release from the RECOVERY trial (16 June 2020) and the strong recommendation for use in the COVID-19 treatment guidelines from the National Institutes of Health (25 June 20). The reasons for the plateau in dexamethasone use at approximately 80% of ventilated patients and the variability across centers are unknown. The adoption of corticosteroid use may have been complicated by lack of definitive efficacy data in related infections (such as SARS and Middle East respiratory syndrome); data from other viral respiratory illnesses showing harm; initial guidelines advising against their use; and concerns about the potential for increased viral replication, immunosuppression, and adverse effects (including hyperglycemia). Furthermore, the generalizability of RECOVERY was questioned given a higher mortality rate in the control group than in the United States overall. Of note, the combination of remdesivir and dexamethasone was used commonly with scant available clinical data and only an “expert opinion” recommendation in guidelines.

Strengths of Mehta and colleagues' study include the large sample size, the diverse patient population, and the geographic diversity of the centers that contributed data. These features enabled the authors to characterize interhospital variation in use of the drugs and to superimpose trends in use on the timeline of emerging data. They had few exclusions (<4%) due to data quality issues.

The authors acknowledge several important limitations of their study, such as the inclusion of predominantly academic medical centers. They do not provide specific information on the types of hospitals included but note that their findings may not generalize to community-based hospitals, at which most care in the United States is provided. Although exploration of potential causes of variability across hospitals would be of interest, they did not analyze hospital-level factors and presumably could not address patient-level factors. In this regard, they also acknowledge their lack of patient- level data, such as oxygen use (aside from mechanical ventilation), which limited their analysis of the appropriateness of corticosteroid use to the subset of patients who were ventilated.

Mehta and colleagues clearly showed how rapidly clinicians can navigate a cacophony of data and incorporate important and meaningful results of clinical research into practice during an infectious disease pandemic. Clinicians adopted a drug with a mortality benefit (dexamethasone), abandoned a drug with no benefit and the potential for harm (hydroxychloroquine), and recognized the nuances of a third drug (remdesivir) that had FDA approval based on decreased clinical progression but lacked a demonstrated mortality benefit. There have been and will continue to be refinements in the clinical care of COVID-19 based on new evidence that emerges from other carefully conducted trials, including global platform trials. Real-time updates of online treatment guidelines and recent innovations, such as living systematic reviews (10), will help clinicians keep pace with emerging data and continue to improve clinical outcomes. Lessons learned from COVID-19 will improve how we assess and disseminate emerging data, leading to efficient implementation (or deimplementation) of evidence-based treatments.

References

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  • 9. Mehta HB, An H, Andersen KM, et al; National COVID Cohort Collaborative (N3C). Use of hydroxychloroquine, remdesivir, and dexamethasone among adults hospitalized with COVID-19 in the United States. A retrospective cohort study. Ann Intern Med. 17 August 2021. [Epub ahead of print]. doi:10.7326/M21-0857 Google Scholar
  • 10. Laine C Taichman DB Guallar E et alKeeping up with emerging evidence in (almost) real time. Ann Intern Med2020;173:153-154. [PMID: 32369539] doi:10.7326/M20-2627 LinkGoogle Scholar


中文翻译:

在传染病大流行期间选择治疗方法:寻找证据

临床医生如何评估和整合有关治疗可能致命的新疾病的信息?COVID-19 大流行使这个问题成为焦点,因为迅速出现的证据为实施和取消实施治疗的决策提供了依据。传统上,同行评审的、已发表的、随机临床试验定义了治疗的护理标准。在 COVID-19 的背景下,出现了更快速的反应:由于急于“做某事”,可用药物根据体外数据、轶事报告、病例系列和回顾性观察研究被重新用于治疗。这受到同事、患者及其家人、大众媒体和社交媒体的推动,并导致了治疗方法的不和谐。

一个极端的例子发生在大流行初期 (1):一项关于羟氯喹加阿奇霉素的小型非对照研究的结果最初于 2020 年 3 月 17 日在 YouTube 上传播,然后于 2020 年 3 月 20 日以电子方式发表在国际抗菌药物杂志上 (2) . 2020 年 3 月 21 日,一位美国政治领导人在推特上表示,这种药物组合“真正有机会成为医学史上最大的游戏规则改变者之一”。在2020年4月3,该杂志发布的有关研究关注的一个声明方法,并指出,尽管通过快速发布新数据来帮助科学界很重要,这不能以减少科学审查和最佳实践为代价”(3)。最终,已发表的随机临床试验未能证明获益。值得注意的是,随后几项受到相当关注的研究——发表在同行评审期刊 (4, 5) 或作为非同行评审的预印本,后者被一些资助机构和期刊提倡以加快数据传播——因为对数据质量或完整性的担忧,这种趋势仍在继续 (6)。

为帮助解决这一混乱局面,在美国首例 COVID-19 确诊病例发生后的几个月内,美国国立卫生研究院 (7, 8) 和一些专业协会迅速制定了在线指南,这些指南可以根据新出现的情况快速更新。证据。随着时间的推移,许多建议背后的数据质量从“专家意见”转变为观察性、回顾性数据,最终转变为随机对照临床试验。

在这个瞬息万变的环境中,临床医生如何治疗 COVID-19?Mehta 及其同事 (9) 通过描述从 2020 年 2 月开始的 13 个月内在住院的美国患者中使用 3 种药物治疗 COVID-19 的时间趋势来解决这个问题。他们研究了国家 COVID 队列中的 137 870 名成年人Collaborative (N3C),一个根据 43 个医疗中心的电子健康记录数据构建的回顾性队列。他们专注于 3 种药物:羟氯喹、瑞德西韦和地塞米松。羟氯喹之所以可用,是因为它已获得美国食品和药物管理局 (FDA) 的其他适应症批准。它展示了针对 SARS-CoV-2 的体外活性,促使 FDA 获得紧急使用授权(EUA)状态,但最终被发现无效,紧急使用授权被撤销。Remdesivir 是一种抗病毒药物,在 COVID-19 住院患者的随机临床试验中改善了恢复时间,但没有改善生存率,支持 FDA 批准,这些数据导致指南建议相互矛盾。地塞米松对需要吸氧的 COVID-19 住院患者,尤其是接受机械通气的患者,显示出死亡率获益。作者发现羟氯喹的使用迅速增加,但随着证据表明其缺乏疗效,数周内出现令人欣慰的快速下降。瑞德西韦和随后地塞米松的使用随着来自美国国立卫生研究院的新疗效数据和指南建议的增加而增加。值得注意的是,作者发现各卫生中心使用这 3 种药物的情况存在很大差异;瑞德西韦的变异最大,

作者强调了他们的主要发现,尽管 2020 年 6 月发布的 RECOVERY(COVID-19 治疗随机评估)试验结果显示该亚组的生存获益,但仍有约五分之一的机械通气患者未接受皮质类固醇治疗。然而,他们的数据显示,在 RECOVERY 试验(2020 年 6 月 16 日)发布新闻后的一个月内,皮质类固醇治疗的使用速度非常快,并且强烈建议在美国国立卫生研究院的 COVID-19 治疗指南中使用(25 6 月 20 日)。大约 80% 的机械通气患者使用地塞米松平台期的原因以及各中心之间的差异尚不清楚。由于缺乏相关感染(如 SARS 和中东呼吸综合征)的确切疗效数据,使用皮质类固醇可能变得复杂;来自其他病毒性呼吸道疾病的数据显示出危害;建议不要使用它们的初步指南;以及对增加病毒复制、免疫抑制和不良反应(包括高血糖)的可能性的担忧。此外,鉴于对照组的死亡率高于美国整体,RECOVERY 的普遍性受到质疑。值得注意的是,瑞德西韦和地塞米松的组合通常使用,但可用的临床数据很少,指南中只有“专家意见”建议。以及对增加病毒复制、免疫抑制和不良反应(包括高血糖)的可能性的担忧。此外,鉴于对照组的死亡率高于美国整体,RECOVERY 的普遍性受到质疑。值得注意的是,瑞德西韦和地塞米松的组合通常使用,但可用的临床数据很少,指南中只有“专家意见”建议。以及对增加病毒复制、免疫抑制和不良反应(包括高血糖)的可能性的担忧。此外,鉴于对照组的死亡率高于美国整体,RECOVERY 的普遍性受到质疑。值得注意的是,瑞德西韦和地塞米松的组合通常使用,但可用的临床数据很少,指南中只有“专家意见”建议。

Mehta 及其同事研究的优势包括样本量大、患者人群多样化以及提供数据的中心的地理多样性。这些特征使作者能够表征药物使用的医院间差异,并将使用趋势叠加在新兴数据的时间线上。由于数据质量问题,他们几乎没有排除(<4%)。

作者承认他们的研究有几个重要的局限性,例如主要包括学术医疗中心。他们没有提供关于所包括医院类型的具体信息,但指出他们的研究结果可能无法推广到美国提供大多数护理的社区医院。尽管探索不同医院变异的潜在原因会很有趣,但他们没有分析医院层面的因素,并且可能无法解决患者层面的因素。在这方面,他们也承认他们缺乏患者层面的数据,例如氧气使用(机械通气除外),这限制了他们对使用皮质类固醇的适当性的分析仅限于接受通气的患者。

Mehta 及其同事清楚地表明,在传染病大流行期间,临床医生可以多快地驾驭杂乱无章的数据并将重要且有意义的临床研究结果纳入实践。临床医生采用了一种具有死亡率益处的药物(地塞米松),放弃了一种没有益处但有潜在危害的药物(羟氯喹),并认识到了第三种药物(瑞德西韦)的细微差别,该药物因临床进展减少而获得 FDA 批准,但缺乏证明了死亡率益处。基于来自其他精心进行的试验(包括全球平台试验)的新证据,COVID-19 的临床护理已经并将继续进行改进。实时更新在线治疗指南和最新创新,例如实时系统评价 (10),将帮助临床医生跟上新兴数据的步伐并继续改善临床结果。从 COVID-19 中吸取的教训将改进我们评估和传播新兴数据的方式,从而有效实施(或取消实施)循证治疗。

参考

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更新日期:2021-08-17
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