BACKGROUND After an initial recommendation from the World Health Organisation, trials of patients hospitalised with COVID-19 often include an ordinal clinical status outcome, which comprises a series of ordered categorical variables, typically ranging from 'Alive and discharged from hospital' to 'Dead'. These ordinal outcomes are often analysed using a proportional odds model, which provides a common odds ratio as an overall measure of effect, which is generally interpreted as the odds ratio for being in a higher category. The common odds ratio relies on the assumption of proportional odds, which implies an identical odds ratio across all ordinal categories; however, there is generally no statistical or biological basis for which this assumption should hold; and when violated, the common odds ratio may be a biased representation of the odds ratios for particular categories within the ordinal outcome. In this study, we aimed to evaluate to what extent the common odds ratio in published COVID-19 trials differed to simple binary odds ratios for clinically important outcomes. METHODS We conducted a systematic review of randomised trials evaluating interventions for patients hospitalised with COVID-19, which used a proportional odds model to analyse an ordinal clinical status outcome, published between January 2020 and May 2021. We assessed agreement between the common odds ratio and the odds ratio from a standard logistic regression model for three clinically important binary outcomes: 'Alive', 'Alive without mechanical ventilation', and 'Alive and discharged from hospital'. RESULTS Sixteen randomised clinical trials, comprising 38 individual comparisons, were included in this study; of these, only 6 trials (38%) formally assessed the proportional odds assumption. The common odds ratio differed by more than 25% compared to the binary odds ratios in 55% of comparisons for the outcome 'Alive', 37% for 'Alive without mechanical ventilation', and 24% for 'Alive and discharged from hospital'. In addition, the common odds ratio systematically underestimated the odds ratio for the outcome 'Alive' by -16.8% (95% confidence interval: -28.7% to -2.9%, p = 0.02), though differences for the other outcomes were smaller and not statistically significant (-8.4% for 'Alive without mechanical ventilation' and 3.6% for 'Alive and discharged from hospital'). The common odds ratio was statistically significant for 18% of comparisons, while the binary odds ratio was significant in 5%, 16%, and 3% of comparisons for the outcomes 'Alive', 'Alive without mechanical ventilation', and 'Alive and discharged from hospital', respectively. CONCLUSION The common odds ratio from proportional odds models often differs substantially to odds ratios from clinically important binary outcomes, and similar to composite outcomes, a beneficial common OR from a proportional odds model does not necessarily indicate a beneficial effect on the most important categories within the ordinal outcome.

中文翻译：

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评估用于分析 COVID-19 临床试验中顺序结果的比例优势模型是否提供了临床上可解释的治疗效果：系统评价。

背景 根据世界卫生组织的初步建议，对因 COVID-19 住院的患者进行的试验通常包括顺序临床状态结果，其中包括一系列有序的分类变量，通常范围从“活着并出院”到“死亡” 。这些顺序结果通常使用比例优势模型进行分析，该模型提供了一个共同的优势比作为效果的总体衡量标准，通常被解释为处于较高类别的优势比。共同优势比依赖于比例优势的假设，这意味着所有序数类别的优势比相同；然而，通常没有统计或生物学基础来支持这一假设；当违反时，共同优势比可能是序数结果中特定类别的优势比的有偏差的表示。在本研究中，我们旨在评估已发表的 COVID-19 试验中的常见比值比与临床重要结果的简单二元比值比有何不同。方法 我们对评估 COVID-19 住院患者干预措施的随机试验进行了系统回顾，该试验使用比例优势模型来分析顺序临床状态结果，发表于 2020 年 1 月至 2021 年 5 月之间。我们评估了常见优势比和标准逻辑回归模型对三个临床上重要的二元结果的比值比：“活着”、“在没有机械通气的情况下活着”和“活着并出院”。结果 本研究纳入了 16 项随机临床试验，其中包括 38 项个体比较；其中，只有 6 项试验 (38%) 正式评估了比例优势假设。与二元比值比相比，常见比值比相差超过 25%，结果“存活”的比较结果为 55%，“没有机械通气时存活”的比较为 37%，“存活并出院”的比较为 24%。此外，常见比值比系统性地低估了“活着”结果的比值比 -16.8%（95% 置信区间：-28.7% 至 -2.9%，p = 0.02），尽管其他结果的差异较小，并且不具有统计学意义（“没有机械通气时仍存活”为-8.4%，“存活并出院”为 3.6%）。18% 的比较中，共同比值比具有统计显着性，而“存活”、“无需机械通气时存活”和“存活且无机械通气”结果的二元比值比在 5%、16% 和 3% 的比较中显着。分别出院”。结论 比例优势模型的常见优势比通常与临床重要的二元结果的优势比有很大不同，并且与复合结果相似，