Heterogeneity of treatment effect of stress ulcer prophylaxis in ICU patients: A secondary analysis protocol

Agents intervening against delirium in the intensive care unit trial-Protocol for a secondary Bayesian analysis

BACKGROUND

Delirium is highly prevalent in the intensive care unit (ICU) and is associated with high morbidity and mortality. The antipsychotic haloperidol is the most frequently used agent to treat delirium although this is not supported by solid evidence. The agents intervening against delirium in the intensive care unit (AID-ICU) trial investigates the effects of haloperidol versus placebo for the treatment of delirium in adult ICU patients.

METHODS

This protocol describes the secondary, pre-planned Bayesian analyses of the primary and secondary outcomes up to day 90 of the AID-ICU trial. We will use Bayesian linear regression models for all count outcomes and Bayesian logistic regression models for all dichotomous outcomes. We will adjust for stratification variables (site and delirium subtype) and use weakly informative priors supplemented with sensitivity analyses using sceptical priors. We will present results as absolute differences (mean differences and risk differences) and relative differences (ratios of means and relative risks). Posteriors will be summarised using median values as point estimates and percentile-based 95% credibility intervals. Probabilities of any benefit/harm, clinically important benefit/harm and clinically unimportant differences will be presented for all outcomes.

DISCUSSION

The results of this secondary, pre-planned Bayesian analysis will complement the primary frequentist analysis of the AID-ICU trial and facilitate a nuanced and probabilistic interpretation of the trial results.

Conservative vs. liberal fluid therapy in septic shock - Protocol for secondary Bayesian analyses of the CLASSIC trial

BACKGROUND

Clinical equipoise exists regarding intravenous (IV) fluid volumes in sepsis. The Conservative vs. Liberal Approach to fluid therapy of Septic Shock in Intensive Care (CLASSIC) trial investigates the effect of restricted vs. standard IV fluid therapy in 1554 adult intensive care unit patients with septic shock.

METHODS

This protocol describes secondary Bayesian analyses of the primary outcome (90-day all-cause mortality) and three secondary outcomes at day 90. We will analyse all binary outcomes with adjusted Bayesian logistic regressions and present results as conditional relative risks and risk differences with 95% credibility intervals (CrIs). The secondary count outcome will be analysed using adjusted Bayesian linear regression with results summarised as conditional mean differences and ratios of means with 95% Crls. We will use weakly informative priors for the primary analyses, and sceptical and evidence-based priors in the sensitivity analyses. Exact probabilities will be presented for any benefit/harm, clinically important benefit/harm and no clinically important difference. We will assess whether heterogeneity of treatment effects on mortality is present using Bayesian hierarchical models in subgroups and on the continuous scale using models with interactions according to five baseline variables assessing the overall severity of illness and the degree of circulatory and renal impairment.

DISCUSSION

The outlined analyses will supplement the primary analysis of the CLASSIC trial by describing probabilities of beneficial and harmful effects and evaluating heterogeneity of treatment effects in a framework that may be easier to interpret for researchers and clinicians.

Lower versus higher oxygenation targets in critically ill patients with severe hypoxaemia: secondary Bayesian analysis to explore heterogeneous treatment effects in the Handling Oxygenation Targets in the Intensive Care Unit (HOT-ICU) trial

BACKGROUND

In the Handling Oxygenation Targets in the Intensive Care Unit (HOT-ICU) trial, a lower (8 kPa) vs a higher (12 kPa) PaO2 target did not affect mortality amongst critically ill adult patients. We used Bayesian statistics to evaluate any heterogeneity in the effect of oxygenation targets on mortality between different patient groups within the HOT-ICU trial.

METHODS

We analysed 90-day all-cause mortality using adjusted Bayesian logistic regression models, and assessed heterogeneous treatment effects according to four selected baseline variables using both hierarchical models of subgroups and models with interactions on the continuous scales. Results are presented as mortality probability (%) and relative risk (RR) with 95% credibility intervals (CrI).

RESULTS

All 2888 patients in the intention-to-treat cohort of the HOT-ICU trial were included. The adjusted 90-day mortality rates were 43.0% (CrI: 38.3-47.8%) and 42.3% (CrI: 37.7-47.1%) in the lower and higher oxygenation groups, respectively (RR 1.02 [CrI: 0.93-1.11]), with 36.5% probability of an RR <1.00. Analyses of heterogeneous treatment effects suggested a dose-response relationship between baseline norepinephrine dose and increased mortality with the lower oxygenation target, with 95% probability of increased mortality associated with the lower oxygenation target as norepinephrine doses increased.

CONCLUSIONS

A lower oxygenation target was unlikely to affect overall mortality amongst critically ill adult patients with acute hypoxaemic respiratory failure. However, our results suggest an increasing mortality risk for patients with a lower oxygen target as the baseline norepinephrine dose increases. These findings warrant additional investigation.

CLINICAL TRIAL REGISTRATION

NCT03174002.

Higher vs Lower Doses of Dexamethasone in Patients with COVID-19 and Severe Hypoxia (COVID STEROID 2) trial: Protocol for a secondary Bayesian analysis

BACKGROUND

Coronavirus disease 2019 (COVID-19) can lead to severe hypoxic respiratory failure and death. Corticosteroids decrease mortality in severely or critically ill patients with COVID-19. However, the optimal dose remains unresolved. The ongoing randomised COVID STEROID 2 trial investigates the effects of higher vs lower doses of dexamethasone (12 vs 6 mg intravenously daily for up to 10 days) in 1,000 adult patients with COVID-19 and severe hypoxia.

METHODS

This protocol outlines the rationale and statistical methods for a secondary, pre-planned Bayesian analysis of the primary outcome (days alive without life support at day 28) and all secondary outcomes registered up to day 90. We will use hurdle-negative binomial models to estimate the mean number of days alive without life support in each group and present results as mean differences and incidence rate ratios with 95% credibility intervals (CrIs). Additional count outcomes will be analysed similarly and binary outcomes will be analysed using logistic regression models with results presented as probabilities, relative risks and risk differences with 95% CrIs. We will present probabilities of any benefit/harm, clinically important benefit/harm and probabilities of effects smaller than pre-defined clinically minimally important differences for all outcomes analysed. Analyses will be adjusted for stratification variables and conducted using weakly informative priors supplemented by sensitivity analyses using sceptic priors.

DISCUSSION

This secondary, pre-planned Bayesian analysis will supplement the primary, conventional analysis and may help clinicians, researchers and policymakers interpret the results of the COVID STEROID 2 trial while avoiding arbitrarily dichotomised interpretations of the results.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT04509973; EudraCT: 2020-003363-25.

Bayesian and heterogeneity of treatment effect analyses of the HOT-ICU trial-A secondary analysis protocol

BACKGROUND

The Handling Oxygenation Targets in the Intensive Care Unit (HOT-ICU) trial is an ongoing randomised clinical trial exploring the benefits and harms of targeting a lower (8 kPa) versus a higher (12 kPa) arterial oxygenation target in adult patients acutely admitted to the intensive care unit (ICU) with hypoxaemic respiratory failure.

METHODS

This protocol describes a secondary analysis of the primary trial outcome, 90-day all-cause mortality. We will analyse the primary outcome using Bayesian methods, which allows quantification of probabilities of all effect sizes. We will explore the presence of heterogeneity of treatment effects (HTE) using Bayesian hierarchical models in subgroups based on baseline parameters: (a) severity of illness (Sequential Organ Failure Assessment (SOFA) score), (b) severity of hypoxaemic respiratory failure (partial pressure of arterial oxygen (PaO₂ )/fraction of inspired oxygen (FiO₂ ) ratio), (c) vasopressor requirement (highest noradrenaline dose in the 24 hours prior to randomisation), and (d) plasma lactate concentration (latest prior to randomisation). Additionally, we will perform separate assessments of the treatment effect interaction with each of the baseline parameters above on the continuous scale and present these using conditional effects plots.

CONCLUSIONS

This secondary analysis will aid the interpretation of the HOT-ICU trial by evaluating probabilities of all effect sizes. In addition, we will evaluate whether HTE is present, thus, further evaluating benefits and harms of a lower versus a higher oxygenation target in adult ICU patients with acute hypoxaemic respiratory failure.