Coping with Information Loss and the Use of Auxiliary Sources of Data: A Report from the NISS Ingram Olkin Forum Series on Unplanned Clinical Trial Disruptions (preprint)

Clinical trials disruption has always represented a non negligible part of the ending of interventional studies. While the SARS-CoV-2 (COVID-19) pandemic has led to an impressive and unprecedented initiation of clinical research, it has also led to considerable disruption of clinical trials in other disease areas, with around 80% of non-COVID-19 trials stopped or interrupted during the pandemic. In many cases the disrupted trials will not have the planned statistical power necessary to yield interpretable results. This paper describes methods to compensate for the information loss arising from trial disruptions by incorporating additional information available from auxiliary data sources. The methods described include the use of auxiliary data on baseline and early outcome data available from the trial itself and frequentist and Bayesian approaches for the incorporation of information from external data sources. The methods are illustrated by application to the analysis of artificial data based on the Primary care pediatrics Learning Activity Nutrition (PLAN) study, a clinical trial assessing a diet and exercise intervention for overweight children, that was affected by the COVID-19 pandemic. We show how all of the methods proposed lead to an increase in precision relative to use of complete case data only.

Impact of Early Corticosteroids on 60-day Mortality in Critically Ill Patients with COVID-19: A Multicenter Cohort Study of the OUTCOMEREA Network (preprint)

ObjectivesIn severe COVID-19 pneumonia, the appropriate timing and dosing of corticosteroids(CS) is not known. Patient subgroups for which CS could be more beneficial also need appraisal. The aim of this study was to assess the effect of early CS in COVID-19 pneumonia patients admitted to the ICU on the occurrence of 60-day mortality, ICU-acquired-bloodstream infections(ICU-BSI), and hospital-acquired pneumonia and ventilator-associated pneumonia(HAP-VAP).MethodsWe included patients with COVID-19 pneumonia admitted to 11 ICUs belonging to the French OutcomeReaTM network from January to May 2020. We used survival models with ponderation with inverse probability of treatment weighting (IPTW). Inflammation was defined as Ferritin >1000 µg/l or D-Dimers >1000 µg/l or C-Reactive Protein >100 mg/dL.ResultsThe study population comprised 302 patients having a median age of 61.6(53-70) years of whom 78.8% were male and 58.6% had at least one comorbidity. The median SAPS II was 33(25-44). Invasive mechanical ventilation was required in 34.8% of the patients. Sixty-six (21.8%) patients were in the Early-CS-subgroup. Most of them (n=55, 83.3%) received high doses of steroids. Overall, 60-day mortality was 29.4%. The risks of 60-day mortality (IPTWHR =0.88;95% CI 0.55 to 1.39, p=0.58), ICU-BSI and HAP-VAP were similar in the two groups. Importantly, early CS treatment was associated with a lower mortality rate in patients aged 60 years or more (IPTWHR, 0.51;95% CI, 0.29 – 0.91; p=0.02). But, CS was associated with an increased risk of death for the patients younger than 60 years without inflammation on admission (IPTWHR =8.17;95% CI, 1.76, 37.85; p=0.01).ConclusionFor patients with COVID-19 pneumonia, early CS treatment was not associated with patient survival. Interestingly, inflammation and age can significantly influence the effect of CS.