Delta inflation: a bias in the design of randomized controlled trials in critical care medicine

Patient-important outcomes in randomized controlled trials in critically ill patients: a systematic review

Background

Intensivists’ clinical decision making pursues two main goals for patients: to decrease mortality and to improve quality of life and functional status in survivors. Patient-important outcomes are gaining wide acceptance in most fields of clinical research. We sought to systematically review how well patient-important outcomes are reported in published randomized controlled trials (RCTs) in critically ill patients.

Methods

Literature search was conducted to identify eligible trials indexed from January to December 2013. Articles were eligible if they reported an RCT involving critically ill adult patients. We excluded phase II, pilot and physiological crossover studies. We assessed study characteristics. All primary and secondary outcomes were collected, described and classified using six categories of outcomes including patient-important outcomes (involving mortality at any time on the one hand and quality of life, functional/cognitive/neurological outcomes assessed after ICU discharge on the other).

Results

Of the 716 articles retrieved in 2013, 112 RCTs met the inclusion criteria. Most common topics were mechanical ventilation (27%), sepsis (19%) and nutrition (17%). Among the 112 primary outcomes, 27 (24%) were patient-important outcomes (mainly mortality, 21/27) but only six (5%) were patient-important outcomes besides mortality assessed after ICU discharge (functional disability = 4; quality of life = 2). Among the 598 secondary outcomes, 133 (22%) were patient-important outcomes (mainly mortality, 92/133) but only 41 (7%) were patient-important outcomes besides mortality assessed after ICU discharge (quality of life = 20, functional disability = 14; neurological/cognitive performance = 5; handicap = 1; post-traumatic stress = 1). Seventy-three RCTs (65%) reported at least one patient-important outcome but only 11 (10%) reported at least one patient-important outcome besides mortality assessed after ICU discharge.

Conclusion

Patient-important outcomes are rarely primary outcomes in RCTs in critically ill patients published in 2013. Among them, mortality accounted for the majority. We promote the use of patient-important outcomes in critical care trials.

Electronic supplementary material

The online version of this article (doi:10.1186/s13613-017-0243-z) contains supplementary material, which is available to authorized users.

Sample size determination for a binary response in a superiority clinical trial using a hybrid classical and Bayesian procedure

BACKGROUND

When designing studies that have a binary outcome as the primary endpoint, the hypothesized proportion of patients in each population experiencing the endpoint of interest (i.e., π ₁,π ₂) plays an important role in sample size and power calculations. Point estimates for π ₁ and π ₂ are often calculated using historical data. However, the uncertainty in these estimates is rarely addressed.

METHODS

This paper presents a hybrid classical and Bayesian procedure that formally integrates prior information on the distributions of π ₁ and π ₂ into the study's power calculation. Conditional expected power (CEP), which averages the traditional power curve using the prior distributions of π ₁ and π ₂ as the averaging weight conditional on the presence of a positive treatment effect (i.e., π ₂>π ₁), is used, and the sample size is found that equates the pre-specified frequentist power (1-β) and the conditional expected power of the trial.

RESULTS

Notional scenarios are evaluated to compare the probability of achieving a target value of power with a trial design based on traditional power and a design based on CEP. We show that if there is uncertainty in the study parameters and a distribution of plausible values for π ₁ and π ₂, the performance of the CEP design is more consistent and robust than traditional designs based on point estimates for the study parameters. Traditional sample size calculations based on point estimates for the hypothesized study parameters tend to underestimate the required sample size needed to account for the uncertainty in the parameters. The greatest marginal benefit of the proposed method is achieved when the uncertainty in the parameters is not large.

CONCLUSIONS

Through this procedure, we are able to formally integrate prior information on the uncertainty and variability of the study parameters into the design of the study while maintaining a frequentist framework for the final analysis. Solving for the sample size that is necessary to achieve a high level of CEP given the available prior information helps protect against misspecification of hypothesized treatment effect and provides a substantiated estimate that forms the basis for discussion about the study's feasibility during the design phase.

Olfactory Ensheathing Cell Transplantation in Experimental Spinal Cord Injury: Effect size and Reporting Bias of 62 Experimental Treatments: A Systematic Review and Meta-Analysis

Olfactory ensheathing cell (OEC) transplantation is a candidate cellular treatment approach for human spinal cord injury (SCI) due to their unique regenerative potential and autologous origin. The objective of this study was, through a meta-epidemiologic approach, (i) to assess the efficacy of OEC transplantation on locomotor recovery after traumatic experimental SCI and (ii) to estimate the likelihood of reporting bias and/or missing data. A study protocol was finalized before data collection. Embedded into a systematic review and meta-analysis, we conducted a literature research of databases including PubMed, EMBASE, and ISI Web of Science from 1949/01 to 2014/10 with no language restrictions, screened by two independent investigators. Studies were included if they assessed neurobehavioral improvement after traumatic experimental SCI, administrated no combined interventions, and reported the number of animals in the treatment and control group. Individual effect sizes were pooled using a random effects model. Details regarding the study design were extracted and impact of these on locomotor outcome was assessed by meta-regression. Missing data (reporting bias) was determined by Egger regression and Funnel-plotting. The primary study outcome assessed was improvement in locomotor function at the final time point of measurement. We included 49 studies (62 experiments, 1,164 animals) in the final analysis. The overall improvement in locomotor function after OEC transplantation, measured using the Basso, Beattie, and Bresnahan (BBB) score, was 20.3% (95% CI 17.8–29.5). One missing study was imputed by trim and fill analysis, suggesting only slight publication bias and reducing the overall effect to a 19.2% improvement of locomotor activity. Dose-response ratio supports neurobiological plausibility. Studies were assessed using a 9-point item quality score, resulting in a median score of 5 (interquartile range [IQR] 3–5). In conclusion, OEC transplantation exerts considerable beneficial effects on neurobehavioral recovery after traumatic experimental SCI. Publication bias was minimal and affirms the translational potential of efficacy, but safety cannot be adequately assessed. The data justify OECs as a cellular substrate to develop and optimize minimally invasive and safe cellular transplantation paradigms for the lesioned spinal cord embedded into state-of-the-art Phase I/II clinical trial design studies for human SCI.

This meta-analysis study examines the effects of transplanting olfactory ensheathing cells in rodents with experimental spinal cord injury, finding evidence for significant recovery and identifying aspects of the procedure that influence the effect size.

Spinal cord injury converts into a debilitating disease affecting millions of chronic patients worldwide. Despite increased molecular knowledge over the last decades, no causal pharmacological or cellular therapy has proven effective so far. Due to their unique regenerative capabilities and their autologous origin, olfactory ensheathing cells (OECs) constitute an appealing candidate for topical cell transplantation. In contrast to few and heterogeneous experimental reports of OEC transplantation after spinal cord injury in humans, a considerable number of preclinical studies have been conducted applying OEC transplantation in rodent models. We set out to conduct a systematic review and meta-analysis to assess preclinical efficacy of OEC transplantation. We detected a significant overall increase of functional neurological recovery in animals after OEC transplantation compared to the control group. This effect was not distorted by publication bias. We identified several specific hallmarks of the cell transplantation procedure that determine the effect size of the transplantation. Our findings delineate conditions for optimized OEC transplantation into lesioned spinal cords and its relevance for effective translation to human trials.

Worldwide Opinion on Multicenter Randomized Interventions Showing Mortality Reduction in Critically Ill Patients: A Democracy-Based Medicine Approach

OBJECTIVES

Democracy-based medicine is a combination of evidence-based medicine (systematic review), expert assessment, and worldwide voting by physicians to express their opinions and self-reported practice via the Internet. The authors applied democracy-based medicine to key trials in critical care medicine.

DESIGN AND SETTING

A systematic review of literature followed by web-based voting on findings of a consensus conference.

PARTICIPANTS

A total of 555 clinicians from 61 countries.

INTERVENTIONS

The authors performed a systematic literature review (via searching MEDLINE/PubMed, Scopus, and Embase) and selected all multicenter randomized clinical trials in critical care that reported a significant effect on survival and were endorsed by expert clinicians. Then they solicited voting and self-reported practice on such evidence via an interactive Internet questionnaire. Relationships among trial sample size, design, and respondents' agreement were investigated. The gap between agreement and use/avoidance and the influence of country origin on physicians' approach to interventions also were investigated.

MEASUREMENTS AND MAIN RESULTS

According to 24 multicenter randomized controlled trials, 15 interventions affecting mortality were identified. Wide variabilities in both the level of agreement and reported practice among different interventions and countries were found. Moreover, agreement and reported practice often did not coincide. Finally, a positive correlation among agreement, trial sample size, and number of included centers was found. On the contrary, trial design did not influence clinicians' agreement.

CONCLUSIONS

Physicians' clinical practice and agreement with the literature vary among different interventions and countries. The role of these interventions in affecting survival should be further investigated to reduce both the gap between evidence and clinical practice and transnational differences.

Event-rate and delta inflation when evaluating mortality as a primary outcome from randomized controlled trials of nutritional interventions during critical illness: a systematic review

BACKGROUND

There is a lack of high-quality evidence that proves that nutritional interventions during critical illness reduce mortality.

OBJECTIVES

We evaluated whether power calculations for randomized controlled trials (RCTs) of nutritional interventions that used mortality as the primary outcome were realistic, and whether overestimation was systematic in the studies identified to determine whether this was due to overestimates of event rate or delta.

DESIGN

A systematic review of the literature between 2005 and 2015 was performed to identify RCTs of nutritional interventions administered to critically ill adults that had mortality as the primary outcome. Predicted event rate (predicted mortality during the control), predicted mortality during intervention, predicted delta (predicted difference between mortality during the control and intervention), actual event rate (observed mortality during control), observed mortality during intervention, and actual delta (difference between observed mortality during the control and intervention) were recorded. The event-rate gap (predicted event rate minus observed event rate), the delta gap (predicted delta minus observed delta), and the predicted number needed to treat were calculated. Data are shown as median (range).

RESULTS

Fourteen articles were extracted, with power calculations provided for 10 studies. The predicted event rate was 29.9% (20.0–52.4%), and the predicted delta was 7.9% (3.0–20.0%). If the study hypothesis was proven correct then, on the basis of the power calculations, the number needed to treat would have been 12.7 (5.0–33.3) patients. The actual event rate was 25.3% (6.1–50.0%), the observed mortality during the intervention was 24.4% (6.3–39.7%), and the actual delta was 0.5% (−10.2–10.3%), such that the event-rate gap was 2.6% (−3.9–23.7%) and delta gap was 7.5% (3.2–25.2%).

CONCLUSIONS

Overestimates of delta occur frequently in RCTs of nutritional interventions in the critically ill that are powered to determine a mortality benefit. Delta inflation may explain the number of "negative" studies in this field of research.

Selection of the treatment effect for sample size determination in a superiority clinical trial using a hybrid classical and Bayesian procedure

Specification of the treatment effect that a clinical trial is designed to detect (θA) plays a critical role in sample size and power calculations. However, no formal method exists for using prior information to guide the choice of θA. This paper presents a hybrid classical and Bayesian procedure for choosing an estimate of the treatment effect to be detected in a clinical trial that formally integrates prior information into this aspect of trial design. The value of θA is found that equates the pre-specified frequentist power and the conditional expected power of the trial. The conditional expected power averages the traditional frequentist power curve using the conditional prior distribution of the true unknown treatment effect θ as the averaging weight. The Bayesian prior distribution summarizes current knowledge of both the magnitude of the treatment effect and the strength of the prior information through the assumed spread of the distribution. By using a hybrid classical and Bayesian approach, we are able to formally integrate prior information on the uncertainty and variability of the treatment effect into the design of the study, mitigating the risk that the power calculation will be overly optimistic while maintaining a frequentist framework for the final analysis. The value of θA found using this method may be written as a function of the prior mean μ0 and standard deviation τ0, with a unique relationship for a given ratio of μ0/τ0. Results are presented for Normal, Uniform, and Gamma priors for θ.

Comparing alternative design options for chronic disease prevention interventions

BACKGROUND

While the randomized clinical trial is considered to provide the highest level of evidence in clinical medicine, its superiority to other study designs in the context of prevention studies is debated. The purpose of this review was (i) to gather evidence about challenges facing both randomized controlled trials and observational designs for the conduct of population-based chronic disease prevention interventions and (ii) to consider the suitability of recently proposed hybrid designs for population-based prevention intervention studies.

METHODS

Rapid review methods were employed for this study. Articles published within 2007-2012, were included if they: (i) discussed challenges or benefits related to any intervention study design, (ii) compared randomized controlled trials (RCT) and observational designs or (iii) introduced a new study design potentially applicable to population-based interventions. After initial screening, papers retained for inclusion were subjected to content analysis and synthesis.

RESULTS

A total of 35 included articles were reviewed and used for synthesis. Both RCTs and observational studies are subject to multiple challenges, the main being external and internal validity for RCTs and observational designs, respectively. Four new hybrid designs identified.

CONCLUSION

Although any high quality design can produce high level of evidence, multiple challenges with prevention intervention RCTs or observational studies identified. New hybrid designs that carry benefits of randomized and observational methods may be the road ahead for to assess the effects of population-based interventions.

Cluster randomised crossover trials with binary data and unbalanced cluster sizes: application to studies of near-universal interventions in intensive care

BACKGROUND

Cluster randomised crossover trials have been utilised in recent years in the health and social sciences. Methods for analysis have been proposed; however, for binary outcomes, these have received little assessment of their appropriateness. In addition, methods for determination of sample size are currently limited to balanced cluster sizes both between clusters and between periods within clusters. This article aims to extend this work to unbalanced situations and to evaluate the properties of a variety of methods for analysis of binary data, with a particular focus on the setting of potential trials of near-universal interventions in intensive care to reduce in-hospital mortality.

METHODS

We derive a formula for sample size estimation for unbalanced cluster sizes, and apply it to the intensive care setting to demonstrate the utility of the cluster crossover design. We conduct a numerical simulation of the design in the intensive care setting and for more general configurations, and we assess the performance of three cluster summary estimators and an individual-data estimator based on binomial-identity-link regression.

RESULTS

For settings similar to the intensive care scenario involving large cluster sizes and small intra-cluster correlations, the sample size formulae developed and analysis methods investigated are found to be appropriate, with the unweighted cluster summary method performing well relative to the more optimal but more complex inverse-variance weighted method. More generally, we find that the unweighted and cluster-size-weighted summary methods perform well, with the relative efficiency of each largely determined systematically from the study design parameters. Performance of individual-data regression is adequate with small cluster sizes but becomes inefficient for large, unbalanced cluster sizes. When outcome prevalences are 6% or less and the within-cluster-within-period correlation is 0.05 or larger, all methods display sub-nominal confidence interval coverage, with the less prevalent the outcome the worse the coverage.

LIMITATIONS

As with all simulation studies, conclusions are limited to the configurations studied. We confined attention to detecting intervention effects on an absolute risk scale using marginal models and did not explore properties of binary random effects models.

CONCLUSION

Cluster crossover designs with binary outcomes can be analysed using simple cluster summary methods, and sample size in unbalanced cluster size settings can be determined using relatively straightforward formulae. However, caution needs to be applied in situations with low prevalence outcomes and moderate to high intra-cluster correlations.

Outcomes and statistical power in adult critical care randomized trials

RATIONALE

Intensive care unit (ICU)-based randomized clinical trials (RCTs) among adult critically ill patients commonly fail to detect treatment benefits.

OBJECTIVES

Appraise the rates of success, outcomes used, statistical power, and design characteristics of published trials.

METHODS

One hundred forty-six ICU-based RCTs of diagnostic, therapeutic, or process/systems interventions published from January 2007 to May 2013 in 16 high-impact general or critical care journals were studied.

MEASUREMENT AND MAIN RESULTS

Of 146 RCTs, 54 (37%) were positive (i.e., the a priori hypothesis was found to be statistically significant). The most common primary outcomes were mortality (n = 40 trials), infection-related outcomes (n = 33), and ventilation-related outcomes (n = 30), with positive results found in 10, 58, and 43%, respectively. Statistical power was discussed in 135 RCTs (92%); 92 cited a rationale for their power parameters. Twenty trials failed to achieve at least 95% of their reported target sample size, including 11 that were stopped early due to insufficient accrual/logistical issues. Of 34 superiority RCTs comparing mortality between treatment arms, 13 (38%) accrued a sample size large enough to find an absolute mortality reduction of 10% or less. In 22 of these trials the observed control-arm mortality rate differed from the predicted rate by at least 7.5%.

CONCLUSIONS

ICU-based RCTs are commonly negative and powered to identify what appear to be unrealistic treatment effects, particularly when using mortality as the primary outcome. Additional concerns include a lack of standardized methods for assessing common outcomes, unclear justifications for statistical power calculations, insufficient patient accrual, and incorrect predictions of baseline event rates.

Registration and design alterations of clinical trials in critical care: a cross-sectional observational study

PURPOSE

In 2005 the International Committee of Medical Journal Editors issued a requirement that all randomized controlled trials (RCTs) be registered primarily to prevent selective reporting (publication bias). However, registries allow for alterations in study protocol. Changes occurring before (or after) study completion could invalidate the original study intent, leading to publication of misleading conclusions. In RCTs involving critically ill patients, these concerns may be particularly acute because mortality is high and conditions investigated are usually syndromes rather than specific diseases. This study was conducted to estimate the registration rate of RCTs in critical care; and, among registered RCTs, to determine timing of registration and whether sample size or primary outcome were altered.

METHODS

We searched the MEDLINE database for RCTs that began after or continued through July 2005. We determined whether each trial had been registered and, for registered trials, compared registry data to data in the published manuscript.

RESULTS

Approximately two-thirds (66%) of trials were registered. Of these, 66% of registrations occurred after enrolment had commenced. Overall, 6% (5/90) of trials appropriately registered a sample size which was unchanged from the interval between registration and publication, and only 12% (11/90) reported primary outcomes that were both appropriately registered and unchanged.

CONCLUSIONS

Non-registration, or registration after trial initiation, are common in RCTs of critically ill patients. Among registered trials important protocol changes are often made between trial commencement and publication. This study identifies and quantifies the extent of this serious-but correctable-problem for RCTs in critically ill patients.

Harmonizing international trials of early goal-directed resuscitation for severe sepsis and septic shock: methodology of ProCESS, ARISE, and ProMISe

PURPOSE

To describe and compare the design of three independent but collaborating multicenter trials of early goal-directed resuscitation for severe sepsis and septic shock.

METHODS

We reviewed the three current trials, one each in the USA (ProCESS: protocolized care for early septic shock), Australasia (ARISE: Australasian resuscitation in sepsis evaluation), and the UK (ProMISe: protocolised management in sepsis). We used the 2010 CONSORT (consolidated standards of reporting trials) statement and the 2008 CONSORT extension for trials assessing non-pharmacologic treatments to describe and compare the underlying rationale, commonalities, and differences.

RESULTS

All three trials conform to CONSORT guidelines, address the same fundamental questions, and share key design elements. Each trial is a patient-level, equal-randomized, parallel-group superiority trial that seeks to enroll emergency department patients with inclusion criteria that are consistent with the original early goal-directed therapy (EGDT) trial (suspected or confirmed infection, two or more systemic inflammatory response syndrome criteria, and refractory hypotension or elevated lactate), is powered to detect a 6–8 % absolute mortality reduction (hospital or 90-day), and uses trained teams to deliver EGDT. Design differences appear to primarily be driven by between-country variation in health care context. The main difference between the trials is the inclusion of a third, alternative resuscitation strategy arm in ProCESS.

CONCLUSIONS

Harmonization of study design and methods between severe sepsis trials is feasible and may facilitate pooling of data on completion of the trials.

Quality of reporting of randomized controlled trials published in Intensive Care Medicine from 2001 to 2010

PURPOSE

To evaluate the methodological quality of randomized controlled trials (RCTs) published in Intensive Care Medicine from 2001 to 2010, and to compare it with a previous review of RCTs published from 1975 to 2000.

METHODS

We assessed the quality of reporting of randomization, blinding and participant flow, both individually and combined within the Jadad scale, and compared them with findings from our previous review. For RCTs published from 2001 to 2010, we also evaluated the frequency of distorted finding presentation (spin) and inflated predicted treatment effect (delta inflation).

RESULTS

In the 221 RCTs from 2001 to 2010, the sample size was significantly larger than in the older series, and there was a higher proportion of studies with negative findings. Reporting of the rationale for sample size estimation and allocation concealment increased significantly, but reporting of other important individual methodological components did not change substantially compared with the previous period and remained low. Among RCTs from 2001 to 2010, a spin strategy was used in 69 of 111 RCTs with statistically negative results, while delta inflation was present in 7 of 11 RCTs evaluating survival as a primary outcome. Papers with higher Jadad scores were cited more often than the others.

CONCLUSIONS

Quality of reporting of RCTs published in Intensive Care Medicine has only partly improved over time, and spin and delta bias are of frequent occurrence. There is a need for stronger adherence to CONSORT recommendations, with special emphasis on accurate description of randomization and blindness, and correct reporting of statistically non-significant results.

Covariate adjustment increased power in randomized controlled trials: an example in traumatic brain injury

OBJECTIVE

We aimed to determine to what extent covariate adjustment could affect power in a randomized controlled trial (RCT) of a heterogeneous population with traumatic brain injury (TBI).

STUDY DESIGN AND SETTING

We analyzed 14-day mortality in 9,497 participants in the Corticosteroid Randomization After Significant Head Injury (CRASH) RCT of corticosteroid vs. placebo. Adjustment was made using logistic regression for baseline covariates of two validated risk models derived from external data (International Mission on Prognosis and Analysis of Clinical Trials in Traumatic Brain Injury [IMPACT]) and from the CRASH data. The relative sample size (RESS) measure, defined as the ratio of the sample size required by an adjusted analysis to attain the same power as the unadjusted reference analysis, was used to assess the impact of adjustment.

RESULTS

Corticosteroid was associated with higher mortality compared with placebo (odds ratio=1.25, 95% confidence interval=1.13-1.39). RESS of 0.79 and 0.73 were obtained by adjustment using the IMPACT and CRASH models, respectively, which, for example, implies an increase from 80% to 88% and 91% power, respectively.

CONCLUSION

Moderate gains in power may be obtained using covariate adjustment from logistic regression in heterogeneous conditions such as TBI. Although analyses of RCTs might consider covariate adjustment to improve power, we caution against this approach in the planning of RCTs.

Understanding health economic analysis in critical care: insights from recent randomized controlled trials

PURPOSE OF REVIEW

The article reviews the methods of health economic analysis (HEA) in clinical trials of critically ill patients. Emphasis is placed on the usefulness of HEA in the context of positive and 'no effect' studies, with recent examples.

RECENT FINDINGS

The need to control costs and promote effective spending in caring for the critically ill has garnered considerable attention due to the high cost of critical illness. Many clinical trials focus on short-term mortality, ignoring costs and quality of life, and fail to change clinical practice or promote efficient use of resources. Incorporating HEA into clinical trials is a possible solution. Such studies have shown some interventions, although expensive, provide good value, whereas others should be withdrawn from clinical practice. Incorporating HEA into randomized controlled trials (RCTs) requires careful attention to collect all relevant costs. Decision trees, modeling assumptions and methods for collecting costs and measuring outcomes should be planned and published beforehand to minimize bias.

SUMMARY

Costs and cost-effectiveness are potentially useful outcomes in RCTs of critically ill patients. Future RCTs should incorporate parallel HEA to provide both economic outcomes, which are important to the community, alongside patient-centered outcomes, which are important to individuals.

Vasopressors and the search for the optimal trial design

Despite several advances in the care of critically ill patients, sepsis and septic shock continue to carry the largest burden of mortality and morbidity. Trials comparing vasopressors in shock have been disappointing and several key issues in methodology may need to be explored. There has been substantial progress in evolving adaptive trial methodology, however these have seldom been translated to clinical trials. This paper discusses some of the issues relevant to critical illness. To illustrate the potential contribution of adaptive trials we discuss fixed sample size design including event and time to event studies. We then explore group sequential and adaptive trial design, enrichment strategies and sample size re-estimation. An attractive feature of responsive adaptive designs is the flexibility to deal with unanticipated treatment effect size. If the observed effect size is larger than expected, early stopping is permitted. If the effect size is smaller than expected, sample size recalculation would be a reasonable choice in the face of an underpowered study. This allows for optimal efficiency in trial design. Reservations about adaptive trial design centre on issues of validity, feasibility and integrity of the study and are discussed in this paper.

The added value of ordinal analysis in clinical trials: an example in traumatic brain injury

Introduction

In clinical trials, ordinal outcome measures are often dichotomized into two categories. In traumatic brain injury (TBI) the 5-point Glasgow outcome scale (GOS) is collapsed into unfavourable versus favourable outcome. Simulation studies have shown that exploiting the ordinal nature of the GOS increases chances of detecting treatment effects. The objective of this study is to quantify the benefits of ordinal analysis in the real-life situation of a large TBI trial.

Methods

We used data from the CRASH trial that investigated the efficacy of corticosteroids in TBI patients (n = 9,554). We applied two techniques for ordinal analysis: proportional odds analysis and the sliding dichotomy approach, where the GOS is dichotomized at different cut-offs according to baseline prognostic risk. These approaches were compared to dichotomous analysis. The information density in each analysis was indicated by a Wald statistic. All analyses were adjusted for baseline characteristics.

Results

Dichotomous analysis of the six-month GOS showed a non-significant treatment effect (OR = 1.09, 95% CI 0.98 to 1.21, P = 0.096). Ordinal analysis with proportional odds regression or sliding dichotomy showed highly statistically significant treatment effects (OR 1.15, 95% CI 1.06 to 1.25, P = 0.0007 and 1.19, 95% CI 1.08 to 1.30, P = 0.0002), with 2.05-fold and 2.56-fold higher information density compared to the dichotomous approach respectively.

Conclusions

Analysis of the CRASH trial data confirmed that ordinal analysis of outcome substantially increases statistical power. We expect these results to hold for other fields of critical care medicine that use ordinal outcome measures and recommend that future trials adopt ordinal analyses. This will permit detection of smaller treatment effects.

The acute management of trauma hemorrhage: a systematic review of randomized controlled trials

Introduction

Worldwide, trauma is a leading cause of death and disability. Haemorrhage is responsible for up to 40% of trauma deaths. Recent strategies to improve mortality rates have focused on optimal methods of early hemorrhage control and correction of coagulopathy. We undertook a systematic review of randomized controlled trials (RCT) which evaluated trauma patients with hemorrhagic shock within the first 24 hours of injury and appraised how the interventions affected three outcomes: bleeding and/or transfusion requirements; correction of trauma induced coagulopathy and mortality.

Methods

Comprehensive searches were performed of MEDLINE, EMBASE, CENTRAL (The Cochrane Library Issue 7, 2010), Current Controlled Trials, ClinicalTrials.gov, the World Health Organization International Clinical Trials Registry Platform (ICTRP) and the National Health Service Blood and Transplant Systematic Review Initiative (NHSBT SRI) RCT Handsearch Database.

Results

A total of 35 RCTs were identified which evaluated a wide range of clinical interventions in trauma hemorrhage. Many of the included studies were of low methodological quality and participant numbers were small. Bleeding outcomes were reported in 32 studies; 7 reported significantly reduced transfusion use following a variety of clinical interventions, but this was not accompanied by improved survival. Minimal information was found on traumatic coagulopathy across the identified RCTs. Overall survival was improved in only three RCTs: two small studies and a large study evaluating the use of tranexamic acid.

Conclusions

Despite 35 RCTs there has been little improvement in outcomes over the last few decades. No clear correlation has been demonstrated between transfusion requirements and mortality. The global trauma community should consider a coordinated and strategic approach to conduct well designed studies with pragmatic endpoints.