Estimating and testing an index of bias attributable to composite outcomes in comparative studies

Díaz-Quijano, Fredi Alexander

doi:10.1016/j.jclinepi.2020.12.003

Cited by 9 publications

(8 citation statements)

References 45 publications

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“…We included randomized clinical trials where the primary outcome was a binary composite outcome that included all-cause mortality among its components [6].…”

Section: Inclusion Criteriamentioning

confidence: 99%

“…In this context, the Bias Attributable to Composite Outcome (BACO) Index is a recently developed strategy that aids in interpreting the effects on a composite outcome [6]. This index corresponds to the ratio of the logarithms of the measures of association between the composite outcome and mortality.…”

Section: Introductionmentioning

confidence: 99%

“…This index corresponds to the ratio of the logarithms of the measures of association between the composite outcome and mortality. BACO index values different from one indicate that using a composite outcome affects the prognosis as follows: overestimated (BACO index > 1), underestimated (BACO index between 0 and < 1), or inverted (BACO index < 0), using the effect on mortality as the reference point [6].…”

Section: Introductionmentioning

confidence: 99%

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Prevalence of bias attributable to composite outcome in clinical trials: a systematic review

Silva,

Conceição,

Ramírez

et al. 2024

Preprint

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ObjectiveTo investigate the prevalence of bias attributable to composite outcome (BACO) in clinical trials.Study design and settingWe searched PubMed for randomized clinical trials where the primary outcome was a binary composite that included all-cause mortality among its components from January 1, 2019, to December 31, 2020. For each trial, the BACO index was calculated to assess the correspondence between effects on the composite outcome and that on mortality. This systematic review was registered in PROSPERO (CRD42021229554).ResultsAfter screening 1,076 citations and 171 full-text articles, 91 studies were included from 13 different medical areas. The prevalence of significant or suggestive BACO among the 91 included articles was 25.2% (n=23), including 12 with p<0.005 and 11 with p between 0.005 and <0.05. We observed that in 17 (73.9%) of these 23 studies, the BACO index value was between zero and <1, indicating an underestimation of the effect. The other six studies showed negative values (26.1%), indicating an inversion of the association with mortality. None of the studies showed significant overestimation of the association attributable to the composite outcome.ConclusionThese findings highlight the need to predefine guidelines for interpreting effects on composite endpoints based on objective criteria such as the BACO index.What is new?Key FindingsThe study found that 25.2% of the included clinical trials exhibited significant or suggestive bias attributable to composite outcomes (BACO).In 73.9% of these cases, the BACO index was less than 1, indicating an underestimation of the effect. 26.1% of the studies showed an inversion of the association with mortality.No significant overestimation of the association due to composite outcomes was observed.What This Adds to What Was Known?This study contributes to the existing knowledge by quantifying the prevalence of bias attributable to composite outcomes in clinical trials.It highlights that a significant proportion of trials may underestimate the effect or even show an inversion of the association with mortality when composite outcomes are used.This finding emphasizes the need for careful consideration and objective criteria, like the BACO index, in the design and interpretation of clinical trials involving composite outcomes.What Is the Implication and What Should Change Now?Researchers and clinicians should be cautious about relying solely on composite outcomes without assessing the potential biases they introduce.The study suggests a need for predefined guidelines and objective criteria, such as the BACO index, for interpreting the effects of composite outcomes.

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“…We included randomized clinical trials where the primary outcome was a binary composite outcome that included all-cause mortality among its components [6].…”

Section: Inclusion Criteriamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Prevalence of bias attributable to composite outcome in clinical trials: a systematic review

Silva,

Conceição,

Ramírez

et al. 2024

Preprint

Self Cite

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“…The BACO index <0, 0 to <1, and >1 indicated that the composite endpoints were inverted, underestimated, and overestimated, respectively. A BACO index of 1 indicates that the composite endpoint usage resulted in unbiased results [40]. The composite endpoint in a clinical trial means the use of multiple endpoints.…”

Section: Composite Endpointsmentioning

confidence: 99%

Research Question, Objectives, and Endpoints in Clinical and Oncological Research: A Comprehensive Review

singh¹,

Shahapur²,

Vadakedath³

et al. 2022

Cureus

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Clinical research is a systematic process of conducting research work to find solutions for human healthrelated problems. It is applied to understand the disease process and assist in the diagnosis, treatment, and prevention. Currently, we are experiencing global unrest caused by the coronavirus disease (COVID-19) pandemic. The novel severe acute respiratory syndrome coronavirus (SARS-CoV-2) has been responsible for the deaths of more than 50 million people worldwide. Also, it has resulted in severe morbidity among the affected population. The cause of such a huge amount of influence on human health by the pandemic was the unavailability of drugs and therapeutic interventions to treat and manage the disease. Cancer is a disease condition wherein the normal cell function is deranged, and the cells multiply in an uncontrolled manner. Based on recent reports by the World Health Organization (WHO), cancer is the second leading cause of death globally. Moreover, the rates of cancers have shown an increasing trend in the past decade. Therefore, it is essential to improve the understanding concerning clinical research to address the health concerns of humans. In this review, we comprehensively discuss critical aspects of clinical research that include the research question, research objectives, patient-reported outcome measures (PROMs), intentionto-treat and per-protocol analysis, and endpoints in clinical and oncological research.

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“…They are designed to capture a greater number of outcome events, and thus increase a trial’s ability to demonstrate a statistically significant treatment effect [ 8 ]. Other proposed methodological benefits include reduced sample size requirements, avoidance of the need to choose a single primary outcome, reduced use of multiple statistical comparisons [ 9 , 10 ] and to account for competing risks [ 11 ]. However, significant limitations have been identified regarding the implementation [ 11 , 12 ] and interpretation [ 8 , 10 ] of COM.…”

Section: Introductionmentioning

confidence: 99%

Composite outcome measures in high-impact critical care randomised controlled trials: a systematic review

Walker,

Brown,

Vaz

et al. 2024

Crit Care

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Background The use of composite outcome measures (COM) in clinical trials is increasing. Whilst their use is associated with benefits, several limitations have been highlighted and there is limited literature exploring their use within critical care. The primary aim of this study was to evaluate the use of COM in high-impact critical care trials, and compare study parameters (including sample size, statistical significance, and consistency of effect estimates) in trials using composite versus non-composite outcomes. Methods A systematic review of 16 high-impact journals was conducted. Randomised controlled trials published between 2012 and 2022 reporting a patient important outcome and involving critical care patients, were included. Results 8271 trials were screened, and 194 included. 39.1% of all trials used a COM and this increased over time. Of those using a COM, only 52.6% explicitly described the outcome as composite. The median number of components was 2 (IQR 2–3). Trials using a COM recruited fewer participants (409 (198.8–851.5) vs 584 (300–1566, p = 0.004), and their use was not associated with increased rates of statistical significance (19.7% vs 17.8%, p = 0.380). Predicted effect sizes were overestimated in all but 6 trials. For studies using a COM the effect estimates were consistent across all components in 43.4% of trials. 93% of COM included components that were not patient important. Conclusions COM are increasingly used in critical care trials; however effect estimates are frequently inconsistent across COM components confounding outcome interpretations. The use of COM was associated with smaller sample sizes, and no increased likelihood of statistically significant results. Many of the limitations inherent to the use of COM are relevant to critical care research.

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Estimating and testing an index of bias attributable to composite outcomes in comparative studies

Cited by 9 publications

References 45 publications

Prevalence of bias attributable to composite outcome in clinical trials: a systematic review

Prevalence of bias attributable to composite outcome in clinical trials: a systematic review

Research Question, Objectives, and Endpoints in Clinical and Oncological Research: A Comprehensive Review

Composite outcome measures in high-impact critical care randomised controlled trials: a systematic review

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