MRC Clinical Trials Unit at UCL, London, UK.
School of Dentistry, University of Leeds, Leeds, UK.
Clin Trials. 2024 Jun;21(3):363-370. doi: 10.1177/17407745231211272. Epub 2023 Nov 20.
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.
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'.
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%, = 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.
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.
世界卫生组织最初建议后，对因 COVID-19 住院的患者进行的试验通常包括一个有序的临床状态结局，该结局由一系列有序的分类变量组成，通常范围从“存活并出院”到“死亡”。这些有序结局通常使用比例优势模型进行分析，该模型提供了一个整体效应的常用优势比，通常被解释为处于较高类别中的优势比。常用优势比依赖于比例优势的假设，这意味着所有有序类别之间的优势比相同；然而，通常没有统计或生物学依据支持这一假设；并且在违反假设的情况下，常用优势比可能是有序结局中特定类别的优势比的有偏差的表示。在这项研究中，我们旨在评估已发表的 COVID-19 试验中常用优势比与临床重要结局的简单二项优势比差异程度。
我们对 2020 年 1 月至 2021 年 5 月期间发表的使用比例优势模型分析 COVID-19 住院患者的有序临床状态结局的随机试验进行了系统评价。我们评估了常用优势比与标准逻辑回归模型的二项优势比之间的一致性，用于三个临床重要的二项结局：“存活”、“存活且无需机械通气”和“存活且出院”。
本研究共纳入了 16 项随机临床试验，包括 38 项独立比较；其中，只有 6 项试验（38%）正式评估了比例优势假设。对于“存活”结局，55%的比较中常用优势比与二项优势比相差超过 25%，37%的比较中为“存活且无需机械通气”，24%的比较中为“存活且出院”。此外，常用优势比系统地低估了“存活”结局的优势比，为-16.8%（95%置信区间：-28.7%至-2.9%，=0.02），而对于其他结局，差异较小且无统计学意义（“存活且无需机械通气”为-8.4%，“存活且出院”为 3.6%）。常用优势比在 18%的比较中具有统计学意义，而二项优势比在“存活”、“存活且无需机械通气”和“存活且出院”结局的 5%、16%和 3%的比较中具有统计学意义。
比例优势模型中的常用优势比通常与临床重要的二项结局的优势比有很大差异，与复合结局类似，比例优势模型中的有益常用 OR 并不一定表明对有序结局中最重要的类别有有益的影响。
