Methodologic discussions for using and interpreting composite endpoints are limited, but still identify major concerns

Appropriateness and Quality of Composite Endpoint Use and Reporting in Spine Surgery: A Systematic Review

BACKGROUND

A composite endpoint (CEP) is a measure comprising 2 or more separate component outcomes. The use of these constructs is increasing. We sought to conduct a systematic review on the usage, quality of reporting, and appropriate use of CEPs in spine surgery research.

METHODS

A systematic review was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. Articles reporting randomized controlled trials of a spine surgery intervention using a CEP as a primary outcome were included. We assessed the quality of CEP reporting, appropriateness of CEP use, and correspondence between CEP treatment effect and component outcome treatment effect in the included trials.

RESULTS

Of 2,321 initial titles, 43 citations were included for analysis, which reported on 20 unique trials. All trials reported the CEP construct well. In 85% of trials, the CEP design was driven by US Food and Drug Administration guidance. In the majority of trials, the reporting of CEP results did not adhere to published recommendations: 43% of tests that reported statistically significant results on component outcomes were not statistically significant when adjusted for multiple testing. 67% of trials did not meet appropriateness criteria for CEP use. In addition, CEP treatment effect tended to be 6% higher than the median treatment effect for component outcomes.

CONCLUSION

Given that CEP analysis was not appropriate for the majority of spine surgery trials and the inherent challenges in the reporting and interpretation of CEP analysis, CEP use should not be mandated by regulatory bodies in spine surgery trials.

LEVEL OF EVIDENCE

Level I. See Instructions for Authors for a complete description of levels of evidence.

Impact of functional status on 30-day resource utilization and organ system complications following index bariatric surgery: a cohort study

BACKGROUND

Bariatric surgical procedures carry an appreciable risk profile despite their elective nature. Identified risk factors for procedural complications are often limited to medical comorbidities. This study assesses the impact of functional status on resource utilization and organ system complications following bariatric surgery.

MATERIALS AND METHODS

This retrospective cohort study analyzed patients undergoing elective, index bariatric surgery from American College of Surgeons National Surgical Quality Improvement Program participating hospitals from 2015 to 2019 ( n =65 627). The primary independent variable was functional status. The primary outcome was unplanned resource utilization. Secondary outcomes included composite organ system complications and mortality. The impact of functional status was first investigated with univariate analyses. Survival and multivariate analyses were then performed on select complications with clinically and statistically significant incidence in the dependent cohort.

RESULTS

On univariate analysis, dependent functional status was associated with unplanned resource utilization [12.1% (27/223) vs. 4.1% (2661/65 404)]; relative risk, 2.98 (95% CI, 2.09-4.25); P < 0.001] and haematologic/infectious complications [6.7% (15/223) vs. 2.4% (1540/65 404); relative risk, 2.86 (95% CI, 1.75-4.67); P < 0.001]. Survival analysis demonstrated a significantly shorter time to both events in patients with dependent functional status ( P < 0.001). On multivariate analysis, dependent functional status was an independent predictor of unplanned resource utilization[adjusted odds ratio 2.17 (95% CI, 1.27-3.50); P = 0.003; model c-statistic, 0.572]) and haematologic/infectious complications [adjusted odds ratio, 2.20 ([95% CI, 1.14-3.86); P = 0.011; model c-statistic, 0.579].

CONCLUSION

Patients with dependent functional status are at an elevated risk of unplanned resource utilization and haematologic/infectious complications following index bariatric surgery. The increased risk cannot be explained by medical comorbidities alone.

A paradigm shift for cardiovascular outcome evaluation in diabetes: Major adverse cardiovascular events (MACE) to major adverse vascular events (MAVE)

BACKGROUND AND AIMS

Drugs for diabetes are required to demonstrate cardiovascular safety through CV outcome trials (CVOT). The pre-defined end-points for cardiovascular outcome studies may not be sufficient to capture all clinically relevant atherosclerotic cardio vascular disease (ASCVD) events particularly peripheral arterial disease (PAD).

METHODS

We planned a scoping review and searched database to identify CVOT conducted in population with diabetes measuring lower limb events due to PAD as the primary outcome measure. We also searched CVOT for reported differential cardiovascular outcomes in population with PAD.

RESULTS

We identified that CV outcomes are measured as 3 point major adverse cardiovascular outcomes (3P-MACE) that includes nonfatal MI and nonfatal stroke or 4P-MACE that included additional unstable angina which is further expanded to 5P-MACE by the inclusion of hospitalization for heart failure (HHF). These CV end points are captured as surrogate for CV mortality based on the biological plausibility of relation between the surrogate and final outcome from pathophysiological studies. We found the prevalence of PAD is no lesser than other CV events in people with diabetes. Moreover, PAD contributes to the significant morbidity associated with diabetes as a surrogate for mortality. However, none of the CVOT with anti-diabetic drugs include PAD events as primary outcome measure despite the inclusion of 6-25 % participants with PAD in major CVOT. PAD outcomes are objectively measurable with tibial arterial waveforms and clinical end-point as lower extremity amputation. PAD outcomes do improve with treatment including intensive glycemic control and novel oral anticoagulants. We suggest the inclusion of PAD to MACE as a pre-specified outcome for a comprehensive capture of major adverse vascular event in future studies for people with diabetes.

CONCLUSIONS

MACE should be expanded to include PAD event as major adverse vascular event in cardiovascular outcome studies since PAD is clinically relevant and objectively measurable in diabetes.

Anakinra authorized to treat severe coronavirus disease 2019; Sepsis breakthrough or time to reflect?

Introduction

The European Medicines Agency (EMA) and the United States Food and Drug Administration (FDA) announced conditions for using recombinant human interleukin-1 receptor antagonist (rhIL-1ra) to treat hospitalized patients with Coronavirus disease 2019 (COVID-19) and risk for progression. These decisions followed publication of the suPAR-guided Anakinra treatment for Validation of the risk and early Management OF seveRE respiratory failure by COVID-19 (SAVE- MORE) phase 3 clinical trial that yielded positive results.

Methods

We conducted a literature review and theoretical analysis of IL-1 blockade as a therapy to treat COVID-19. Using a stepwise analysis, we assessed clinical applicability of the SAVE-MORE results and evaluated conceptual support for interleukin-1 suppression as a suitable approach to COVID-19 treatment. This therapeutic approach was then examined as an example of inflammation-suppressing measures used to treat sepsis.

Results

Anakinra use as a COVID-19 therapy seems to rely on a view of pathogenesis that incorrectly reflects human disease. Since COVID-19 is an example of sepsis, COVID-19 benefit due to anti-inflammatory therapy contradicts an extensive history of unsuccessful clinical study. Repurposing rhIL-1ra to treat COVID-19 appears to exemplify a cycle followed by inflammation-suppressing sepsis treatments. A landscape of treatment failures is interrupted by a successful clinical trial. However, subsequent confirmatory study fails to replicate the positive data.

Discussion

We suggest further experimentation is not a promising pathway to discover game-changing sepsis therapies. A different kind of approach may be necessary.

Making Sense of Composite Endpoints in Clinical Research

Multiple drugs currently used in clinical practice have been approved by regulatory agencies based on studies that utilize composite endpoints. Composite endpoints are appealing because they reduce sample size requirements, follow-up periods, and costs. However, interpreting composite endpoints can be challenging, and their misuse is not uncommon. Incorrect interpretation of composite outcomes can lead to misleading conclusions that impact patient care. To correctly interpret composite outcomes, several important questions should be considered. Are the individual components of the composite outcome equally important to patients? Did the more and less important endpoints occur with similar frequency? Do the component endpoints exhibit similar relative risk reductions? If these questions receive affirmative answers, the use and interpretation of the composite endpoint would be appropriate. However, if any component of the composite endpoint fails to satisfy the aforementioned criteria, interpretation can become difficult, necessitating additional steps. Regulatory agencies acknowledge these challenges and have specific considerations when approving drugs based on studies employing composite endpoints. In conclusion, composite endpoints are valuable tools for evaluating the efficacy and net clinical benefit of interventions; however, cautious interpretation is advised.

Redefining Neurodevelopmental Impairment: Perspectives of Very Preterm Birth Stakeholders

Children born very preterm are at risk of severe neurodevelopmental impairment, a composite endpoint that includes cerebral palsy, developmental delay, and hearing and visual impairment defined by medical professionals. We aimed to describe preterm birth stakeholders' perspectives on this classification. Ten clinical scenarios describing 18-month-old children with different components of severe neurodevelopmental impairment and one scenario of a typically developing child (control) were distributed to parents and stakeholders using a snowball sampling technique. For each scenario, participants rated health on a scale from 0 to 10 and whether the scenario represented a severe condition. Results were analyzed descriptively and mean differences from the control scenario were compared using a linear mixed-effects model. Stakeholders (number = 827) completed 4553 scenarios. Median health scores for each scenario varied from 6 to 10. The rating for the cerebral palsy and language delay scenario was significantly lower (mean difference -4.3; 95% confidence interval: -4.4, -4.1) than the control. The proportion of respondents rating a scenario as "severe" ranged from 5% for cognitive delay to 55% for cerebral palsy and language delay. Most participants disagreed with the rating used in research to describe severe neurodevelopmental impairment in preterm children. The term should be redefined to align with stakeholder perceptions.

Should we use composite outcomes in obstetric clinical prediction models?

Clinical prediction models assist clinicians to estimate the natural course of a condition, and thus facilitate treatment decisions. The development of prediction models is increasingly common in obstetric research. Composite outcomes, whereby multiple outcomes are combined into a single endpoint, are frequently used in obstetric prediction models to increase statistical power when predicting rare events. Although existing literature has reviewed the positives and negatives of using composite outcomes in clinical trials, there has been minimal commentary on the implications of their use in the development and reporting of prognostic models. In this article, we review these issues, in particular, highlighting how unequal individual relationships between predictors and individual component outcomes can result in misleading conclusions, which may result in the omission of important but rare predictors or inappropriately inform clinical decisions to implement an intervention. We propose careful use, or where possible avoidance, of composite outcomes in the development of prognostic models in obstetrics. Methodological standards for developing prognostic models should be updated to standardise and appraise composite outcomes when their use is necessary. We also support previous recommendations to report on the accuracy of key components and inconsistencies among predictor variables.

Outcomes in pediatric anesthesia: towards a universal language

PURPOSE OF REVIEW

The identification of valid, well defined and relevant outcomes is fundamental to provide a reliable and replicable measure that can be used to improve quality of clinical care and research output. The purpose of this review is to provide an update on what the pediatric anesthesia research community is pursuing on standardized and validated outcomes.

RECENT FINDINGS

Several initiatives by different research groups have been established during the last years. They all aim to find validated outcomes using the standardized methodology of COMET ( https://www.comet-initiative.org/ ). These initiatives focus on clinical and research outcomes on the field of anesthesia, perioperative medicine, pain and sedation in pediatric age.

SUMMARY

Clinical outcomes are measurements of changes in health, function or quality of life and they help evaluating quality of care. In order for them to be relevant in quantifying quality improvement, they need to be well defined, standardized and consistent across trials. A great effort from researchers has been made towards the identification of set of outcomes with these features.

Evaluation of heart failure admission as a surrogate for mortality in randomized clinical trials: A meta-analysis

BACKGROUND

Heart failure (HF) admission is used as a study endpoint in clinical trials. However, it remains unclear whether it can be a valid surrogate endpoint for mortality.

OBJECTIVES

To validate whether HF admission is a valid surrogate for mortality.

METHODS

In PubMed and EMBASE, randomized controlled trials (RCTs) of interventions to treat patients with heart failure at the enrolment were searched on 13 April 2022. We extracted RCTs in which event numbers of both HF admission and all-cause mortality were reported as either primary or secondary outcomes. Trial-level correlations (R-squared) between HF admission and mortality were assessed. We performed subgroup analyses by study year, follow-up duration, baseline HF with reduced ejection fraction (HFrEF) or HF with preserved ejection fraction (HFpEF), and whether the intervention was pharmacological. We followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses guideline.

RESULTS

A total of 117 RCTs met the criteria for inclusion. Overall, the trial-level R-squared between HF admission and all-cause mortality was 0.39 (95% confidence interval (CI), 0.26 to 0.53). However, in the subgroup analyses, the trial-level R-squared was increased when the follow-up duration was ≥24 months (0.70 [95% CI: 0.55, 0.85]), when intervention was pharmacological (0.51 [95% CI: 0.34, 0.68]) and when the baseline HF type was HFrEF (0.57 [95% CI: 0.42, 0.73]).

CONCLUSIONS

Our findings indicate that HF admission may not always be a valid surrogate for mortality in patients with HF. Rather, the surrogacy of HF admission may be dependent on clinical background and interventions.

Matching the Outcomes to Treatment Targets of Exercise for Low Back Pain: Does it Make a Difference? Results of Secondary Analyses From Individual Patient Data of Randomised Controlled Trials and Pooling of Results Across Trials in Comparative Meta-analysis

OBJECTIVE

To explore whether using a single matched or composite outcome might affect the results of previous randomized controlled trials (RCTs) testing exercise for non-specific low back pain (NSLBP). The first objective was to explore whether a single matched outcome generated greater standardized mean differences (SMDs) when compared with the original unmatched primary outcome SMD. The second objective was to explore whether a composite measure, composed of matched outcomes, generated a greater SMD when compared with the original primary outcome SMD.

DESIGN

We conducted exploratory secondary analyses of data.

SETTING

Seven RCTs were included, of which 2 were based in the USA (University research clinic, Veterans Affairs medical center) and the UK (primary care clinics, nonmedical centers). One each were based in Norway (clinics), Brazil (primary care), and Japan (outpatient clinics).

PARTICIPANTS

The first analysis comprised 1) 5 RCTs (n=1033) that used an unmatched primary outcome but included (some) matched outcomes as secondary outcomes, and the second analysis comprised 2) 4 RCTs (n=864) that included multiple matched outcomes by developing composite outcomes (N=1897).

INTERVENTION

Exercise compared with no exercise.

MAIN OUTCOME MEASURES

The composite consisted of standardized averaged matched outcomes. All analyses replicated the RCTs' primary outcome analyses.

RESULTS

Of 5 RCTs, 3 had greater SMDs with matched outcomes (pooled effect SMD 0.30 [95% confidence interval {CI} 0.04, 0.56], P=.02) compared with an unmatched primary outcome (pooled effect SMD 0.19 [95% CI -0.03, 0.40] P=.09). Of 4 composite outcome analyses, 3 RCTs had greater SMDs in the composite outcome (pooled effect SMD 0.28 [95% CI 0.05, 0.51] P=.02) compared with the primary outcome (pooled effect SMD 0.24 [95% CI -0.04, 0.53] P=.10).

CONCLUSIONS

These exploratory analyses suggest that using an outcome matched to exercise treatment targets in NSLBP RCTs may produce greater SMDs than an unmatched primary outcome. Composite outcomes could offer a meaningful way of investigating superiority of exercise than single domain outcomes.

Investigations of methods for multiple time-to-event endpoints: A chronic myeloid leukemia data analysis

BACKGROUND

In randomized controlled trials, multiple time-to-event endpoints are commonly used to determine treatment effects. However, choosing an appropriate method to address multiple endpoints, according to different purposes of clinical practice, is a challenge for researchers.

METHODS

We applied single endpoint, composite endpoint and win ratio analysis to chronic myeloid leukemia (CML) data to illustrate the distinctions with different multiple endpoints, including relapse, recovery and death after transplantation.

RESULTS

Regarding relapse and death, the hazard ratio in single endpoint analysis (HR_s ) were 1.281 (95% CI: 1.061-1.546) and hazard ratio in composite endpoint analysis (HR_c ) were 1.286 (95% CI: 1.112-1.486) and 1/WR (win ratio) was 1.292 (95% CI: 1.115-1.497) indicated a similar negative effect for non-prophylaxis patients. However, when considering recovery and death, the corresponding HR_s  = 1.280 (95% CI: 1.056-1.552) may not be enough to describe the effect on death with nonproportional hazards (p < 0.05), and for the composite endpoint analysis, the HR_c  = 0.828 (95% CI: 0.740-0.926) cannot quantify and interpret the clinical effect on the composite endpoint with the combination of recovery and death, while the 1/WR = 1.351 (95% CI: 1.207-1.513) showed an unfavourable effect for non-prophylaxis patients CONCLUSIONS: When dealing with multiple endpoints, single endpoints, researchers may choose single endpoints, composite endpoints and WR analysis due to different clinical applications and purposes. However, both single and composite endpoint analyses are hazard-based measures, and thus, the proportional hazards assumption should be considered. Moreover, composite endpoint analysis should be applied for endpoints with similar clinical meanings but not opposing implications. Win ratio analysis can be considered for different clinical importance of multiple endpoints, but the meaning of 'winner' needs to be specified for desired or undesired endpoints.

Range and Consistency of Cardiovascular Outcomes Reported by Clinical Trials in Kidney Transplant Recipients: A Systematic Review

Cardiovascular disease is a major cause of morbidity and mortality in kidney transplant recipients. Trial evidence to improve cardiovascular outcomes is limited by inconsistent reporting of outcomes, which may also lack patient-relevance. This study aimed to assess the range and consistency of cardiovascular outcomes reported by contemporary trials in kidney transplant recipients.

Methods

A systematic review of all randomized controlled trials involving adult kidney transplant recipients that reported at least 1 cardiovascular outcome from January 2012 to December 2019 was performed, including Embase, MEDLINE, Cochrane, and ClinicalTrials.gov electronic databases. Trial characteristics were extracted and all levels of specification of the cardiovascular outcome measures reported were analyzed (the measure definition, metric' and method of aggregation). Measures assessing a similar aspect of cardiovascular disease were categorized into outcomes.

Results

From 93 eligible trials involving 27 609 participants, 490 outcome measures were identified. The outcome measures were grouped into 38 outcomes. A cardiovascular composite was the most common outcome reported (40 trials, 43%) followed by cardiovascular mortality (42%) and acute coronary syndrome (31%). Cardiovascular composite was also the most heterogeneous outcome with 77 measures reported followed by cardiovascular mortality (n = 58) and inflammatory biomarkers (n = 51). The most common cardiovascular composite outcome components reported were major cardiovascular events (18 trials), stroke unspecified (11 trials), and myocardial infarction unspecified (10 trials).

Conclusions

There is substantial heterogeneity in cardiovascular outcome reporting in kidney transplant trials.

Valuing Health Gain from Composite Response Endpoints for Multisystem Diseases

OBJECTIVES

This study aimed to demonstrate how to estimate the value of health gain after patients with a multisystem disease achieve a condition-specific composite response endpoint.

METHODS

Data from patients treated in routine practice with an exemplar multisystem disease (systemic lupus erythematosus) were extracted from a national register (British Isles Lupus Assessment Group Biologics Register). Two bespoke composite response endpoints (Major Clinical Response and Improvement) were developed in advance of this study. Difference-in-differences regression compared health utility values (3-level version of EQ-5D; UK tariff) over 6 months for responders and nonresponders. Bootstrapped regression estimated the incremental quality-adjusted life-years (QALYs), probability of QALY gain after achieving the response criteria, and population monetary benefit of response.

RESULTS

Within the sample (n = 171), 18.2% achieved Major Clinical Response and 49.1% achieved Improvement at 6 months. Incremental health utility values were 0.0923 for Major Clinical Response and 0.0454 for Improvement. Expected incremental QALY gain at 6 months was 0.020 for Major Clinical Response and 0.012 for Improvement. Probability of QALY gain after achieving the response criteria was 77.6% for Major Clinical Response and 72.7% for Improvement. Population monetary benefit of response was £1 106 458 for Major Clinical Response and £649 134 for Improvement.

CONCLUSIONS

Bespoke composite response endpoints are becoming more common to measure treatment response for multisystem diseases in trials and observational studies. Health technology assessment agencies face a growing challenge to establish whether these endpoints correspond with improved health gain. Health utility values can generate this evidence to enhance the usefulness of composite response endpoints for health technology assessment, decision making, and economic evaluation.

Sample size requirement in trials that use the composite endpoint major adverse cardiovascular events (MACE): new insights

BACKGROUND

The real impact of the degree of association (DoA) between endpoint components of a composite endpoint (CE) on sample size requirement (SSR) has not been explored. We estimate the impact of the DoA between death and acute myocardial infarction (AMI) on SSR of trials using use the CE of major adverse cardiac events (MACE).

METHODS

A systematic review and quantitative synthesis of trials that include MACE as the primary outcome through search strategies in MEDLINE and EMBASE electronic databases. We limited to articles published in journals indexed in the first quartile of the Cardiac & Cardiovascular Systems category (Journal Citation Reports, 2015-2020). The authors were contacted to estimate the DoA between death and AMI using joint probability and correlation. We analyzed the SSR variation using the DoA estimated from RCTs.

RESULTS

Sixty-three of 134 publications that reported event rates and the therapy effect in all component endpoints were included in the quantitative synthesis. The most frequent combination was death, AMI, and revascularization (n = 20; 31.8%). The correlation between death and AMI, estimated from 5 trials¸ oscillated between - 0.02 and 0.31. SSR varied from 14,602 in the scenario with the strongest correlation to 12,259 in the scenario with the weakest correlation; the relative impact was 16%.

CONCLUSIONS

The DoA between death and AMI is highly variable and may lead to a considerable SSR variation in a trial including MACE.

Guidelines for Reporting Outcomes in Trial Protocols: The SPIRIT-Outcomes 2022 Extension

IMPORTANCE

Complete information in a trial protocol regarding study outcomes is crucial for obtaining regulatory approvals, ensuring standardized trial conduct, reducing research waste, and providing transparency of methods to facilitate trial replication, critical appraisal, accurate reporting and interpretation of trial results, and knowledge synthesis. However, recommendations on what outcome-specific information should be included are diverse and inconsistent. To improve reporting practices promoting transparent and reproducible outcome selection, assessment, and analysis, a need for specific and harmonized guidance as to what outcome-specific information should be addressed in clinical trial protocols exists.

OBJECTIVE

To develop harmonized, evidence- and consensus-based standards for describing outcomes in clinical trial protocols through integration with the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) 2013 statement.

EVIDENCE REVIEW

Using the Enhancing the Quality and Transparency of Health Research (EQUATOR) methodological framework, the SPIRIT-Outcomes 2022 extension of the SPIRIT 2013 statement was developed by (1) generation and evaluation of candidate outcome reporting items via consultation with experts and a scoping review of existing guidance for reporting trial outcomes (published within the 10 years prior to March 19, 2018) identified through expert solicitation, electronic database searches of MEDLINE and the Cochrane Methodology Register, gray literature searches, and reference list searches; (2) a 3-round international Delphi voting process (November 2018-February 2019) completed by 124 panelists from 22 countries to rate and identify additional items; and (3) an in-person consensus meeting (April 9-10, 2019) attended by 25 panelists to identify essential items for outcome-specific reporting to be addressed in clinical trial protocols.

FINDINGS

The scoping review and consultation with experts identified 108 recommendations relevant to outcome-specific reporting to be addressed in trial protocols, the majority (72%) of which were not included in the SPIRIT 2013 statement. All recommendations were consolidated into 56 items for Delphi voting; after the Delphi survey process, 19 items met criteria for further evaluation at the consensus meeting and possible inclusion in the SPIRIT-Outcomes 2022 extension. The discussions during and after the consensus meeting yielded 9 items that elaborate on the SPIRIT 2013 statement checklist items and are related to completely defining and justifying the choice of primary, secondary, and other outcomes (SPIRIT 2013 statement checklist item 12) prospectively in the trial protocol, defining and justifying the target difference between treatment groups for the primary outcome used in the sample size calculations (SPIRIT 2013 statement checklist item 14), describing the responsiveness of the study instruments used to assess the outcome and providing details on the outcome assessors (SPIRIT 2013 statement checklist item 18a), and describing any planned methods to account for multiplicity relating to the analyses or interpretation of the results (SPIRIT 2013 statement checklist item 20a).

CONCLUSIONS AND RELEVANCE

This SPIRIT-Outcomes 2022 extension of the SPIRIT 2013 statement provides 9 outcome-specific items that should be addressed in all trial protocols and may help increase trial utility, replicability, and transparency and may minimize the risk of selective nonreporting of trial results.

Guidelines for Reporting Outcomes in Trial Reports: The CONSORT-Outcomes 2022 Extension

IMPORTANCE

Clinicians, patients, and policy makers rely on published results from clinical trials to help make evidence-informed decisions. To critically evaluate and use trial results, readers require complete and transparent information regarding what was planned, done, and found. Specific and harmonized guidance as to what outcome-specific information should be reported in publications of clinical trials is needed to reduce deficient reporting practices that obscure issues with outcome selection, assessment, and analysis.

OBJECTIVE

To develop harmonized, evidence- and consensus-based standards for reporting outcomes in clinical trial reports through integration with the Consolidated Standards of Reporting Trials (CONSORT) 2010 statement.

EVIDENCE REVIEW

Using the Enhancing the Quality and Transparency of Health Research (EQUATOR) methodological framework, the CONSORT-Outcomes 2022 extension of the CONSORT 2010 statement was developed by (1) generation and evaluation of candidate outcome reporting items via consultation with experts and a scoping review of existing guidance for reporting trial outcomes (published within the 10 years prior to March 19, 2018) identified through expert solicitation, electronic database searches of MEDLINE and the Cochrane Methodology Register, gray literature searches, and reference list searches; (2) a 3-round international Delphi voting process (November 2018-February 2019) completed by 124 panelists from 22 countries to rate and identify additional items; and (3) an in-person consensus meeting (April 9-10, 2019) attended by 25 panelists to identify essential items for the reporting of outcomes in clinical trial reports.

FINDINGS

The scoping review and consultation with experts identified 128 recommendations relevant to reporting outcomes in trial reports, the majority (83%) of which were not included in the CONSORT 2010 statement. All recommendations were consolidated into 64 items for Delphi voting; after the Delphi survey process, 30 items met criteria for further evaluation at the consensus meeting and possible inclusion in the CONSORT-Outcomes 2022 extension. The discussions during and after the consensus meeting yielded 17 items that elaborate on the CONSORT 2010 statement checklist items and are related to completely defining and justifying the trial outcomes, including how and when they were assessed (CONSORT 2010 statement checklist item 6a), defining and justifying the target difference between treatment groups during sample size calculations (CONSORT 2010 statement checklist item 7a), describing the statistical methods used to compare groups for the primary and secondary outcomes (CONSORT 2010 statement checklist item 12a), and describing the prespecified analyses and any outcome analyses not prespecified (CONSORT 2010 statement checklist item 18).

CONCLUSIONS AND RELEVANCE

This CONSORT-Outcomes 2022 extension of the CONSORT 2010 statement provides 17 outcome-specific items that should be addressed in all published clinical trial reports and may help increase trial utility, replicability, and transparency and may minimize the risk of selective nonreporting of trial results.

Neonatal Morbidities and Feeding Tolerance Outcomes in Very Preterm Infants, before and after Introduction of Probiotic Supplementation

While probiotics are reported to reduce the risks of neonatal morbidities, less is known about probiotics and feeding tolerance. With this retrospective cohort study, we investigate whether introduction of probiotic supplementation as the standard of care was associated with fewer neonatal morbidities and improved feeding tolerance in very preterm infants. Using the Swedish Neonatal Quality Register, 345 live-born very preterm infants (28–31 weeks’ gestation), from January 2019–August 2021, in NICUs in Stockholm, Sweden, either received probiotic supplementation (Bifidobacterium infantis, Bifidobacterium lactis, Streptococcusthermophilus) (139) or no supplementation (206); they were compared regarding a primary composite outcome of death, sepsis, and/or necrotising enterocolitis and secondary outcomes: time to full enteral feeding and antibiotics use. Probiotics seemed associated with a reduced risk of the composite outcome (4.3% versus 9.2%, p = 0.08). In the subgroup of 320 infants without the primary outcome, probiotics were associated with shorter time to full enteral feeding (6.6 days versus 7.2 days) and less use of antibiotics (5.2 days versus 6.1 days). Our findings suggest that probiotics improve feeding tolerance and further support that very preterm infants may benefit from probiotic supplementation.

Assessment of Clinical Worsening End Points as a Surrogate for Mortality in Pulmonary Arterial Hypertension: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

BACKGROUND

Clinical worsening (CW) is a composite end point commonly used in pulmonary arterial hypertension (PAH) trials. We aimed to assess the trial-level surrogacy of CW for mortality in PAH trials, and whether the various CW components were similar in terms of frequency of occurrence, treatment-related relative risk (RR) reduction, and importance to patients.

METHODS

We searched MEDLINE, Embase, and the Cochrane Library (January 1990 to December 2020) for trials evaluating the effects of PAH therapies on CW. The coefficient of determination between the RR for CW and mortality was assessed by regression analysis. The frequency of occurrence, RR reduction, and importance to patients of the CW components were assessed.

RESULTS

We included 35 independent cohorts (9450 patients). PAH therapies significantly reduced CW events (RR, 0.64 [95% CI, 0.55-0.73]), including PAH-related hospitalizations (RR, 0.61 [95% CI, 0.47-0.79]), treatment escalation (RR, 0.57 [95% CI, 0.38-0.84]) and symptomatic progression (RR, 0.58 [95% CI, 0.48-0.69]), and modestly reduced all-cause mortality when incorporating deaths occurring after a primary CW-defining event (RR, 0.860 [95% CI, 0.742-0.997]). However, the effects of PAH-specific therapies on CW only modestly correlated with their effects on mortality (R²_trial, 0.35 [95% CI, 0.10-0.59]; P<0.0001), and the gradient in the treatment effect across component end points was large in the majority of trials. The weighted proportions of CW-defining events were hospitalization (33.5%) and symptomatic progression (32.3%), whereas death (6.7%), treatment escalation (5.6%), and transplantation/atrioseptostomy (0.2%) were infrequent. CW events were driven by the occurrence of events of major (49%) and mild-to-moderate (37%) importance to patients, with 14% of the events valued as critical.

CONCLUSIONS

PAH therapies significantly reduced CW events, but study-level CW is not a surrogate for mortality in PAH trials. Moreover, components of CW largely vary in frequency, response to therapy, and importance to patients and are thus not interchangeable.

REGISTRATION

URL: https://www.crd.york.ac.uk/PROSPERO; Unique identifier: CRD42020178949.

Intravenous Vitamin C in Adults with Sepsis in the Intensive Care Unit

BACKGROUND

Studies that have evaluated the use of intravenous vitamin C in adults with sepsis who were receiving vasopressor therapy in the intensive care unit (ICU) have shown mixed results with respect to the risk of death and organ dysfunction.

METHODS

In this randomized, placebo-controlled trial, we assigned adults who had been in the ICU for no longer than 24 hours, who had proven or suspected infection as the main diagnosis, and who were receiving a vasopressor to receive an infusion of either vitamin C (at a dose of 50 mg per kilogram of body weight) or matched placebo administered every 6 hours for up to 96 hours. The primary outcome was a composite of death or persistent organ dysfunction (defined by the use of vasopressors, invasive mechanical ventilation, or new renal-replacement therapy) on day 28.

RESULTS

A total of 872 patients underwent randomization (435 to the vitamin C group and 437 to the control group). The primary outcome occurred in 191 of 429 patients (44.5%) in the vitamin C group and in 167 of 434 patients (38.5%) in the control group (risk ratio, 1.21; 95% confidence interval [CI], 1.04 to 1.40; P = 0.01). At 28 days, death had occurred in 152 of 429 patients (35.4%) in the vitamin C group and in 137 of 434 patients (31.6%) in the placebo group (risk ratio, 1.17; 95% CI, 0.98 to 1.40) and persistent organ dysfunction in 39 of 429 patients (9.1%) and 30 of 434 patients (6.9%), respectively (risk ratio, 1.30; 95% CI, 0.83 to 2.05). Findings were similar in the two groups regarding organ-dysfunction scores, biomarkers, 6-month survival, health-related quality of life, stage 3 acute kidney injury, and hypoglycemic episodes. In the vitamin C group, one patient had a severe hypoglycemic episode and another had a serious anaphylaxis event.

CONCLUSIONS

In adults with sepsis receiving vasopressor therapy in the ICU, those who received intravenous vitamin C had a higher risk of death or persistent organ dysfunction at 28 days than those who received placebo. (Funded by the Lotte and John Hecht Memorial Foundation; LOVIT ClinicalTrials.gov number, NCT03680274.).

Rating the importance of outcomes from diabetes trials. A survey of patients' and doctors' opinions

Purpose

To investigate and compare how patients with diabetes mellitus and doctors rate the importance of outcomes used as part of composite endpoints in clinical diabetes trials. Secondly, to compare the ratings of outcomes between patients with low and high education.

Methods

Using a pre-piloted questionnaire, patients with diabetes and doctors working with diabetes were asked to rate the importance of 36 different outcomes commonly used in trials assessing intervention effects in patients with diabetes. The respondents were asked to rate individual outcomes as being either critical, of major importance, of moderate importance, or of minor importance.

Results

The study population consisted of 139 patients with a mean age of 56.6 years and an average duration of diabetes for 13.6 years and 45 doctors with a mean time of practice of 19.6 years. There was no difference between patients' and doctors' rating of risk of mortality and non-fatal myocardial infarction, and percutaneous coronary intervention (all p-values > 0.34). Non-fatal stroke, admission for heart failure or angina was perceived more severely by patients compared to doctors (all p-values < 0.03). Patients rated risk of foot-ulcers, amputations and quality of life as more important compared to doctors (p-values < 0.01).

Conclusion

The current study suggest that patients and doctors weigh some diabetic outcomes used as part of composite endpoints in clinical diabetes trials differently. These findings call for more studies on patient reported outcomes and patient education for improved personal care.

Highlights

• We performed this study to assess how patients and practicing physicians rate the importance of outcomes commonly used in diabetes trials.• We found that patients and doctors rate the importance of some outcomes used in clinical diabetes trials differently.• These findings suggest that shared decision making is pivotal when taking clinical decisions and that future diabetes studies incorporate end points relevant to both patients and clinicians and do not combine end points which are not equally important.

Composite outcomes in observational studies of Crohn's disease: a systematic review and meta-analysis

BACKGROUND

This systematic review and meta-analysis aims to assess composite and aggregate outcomes of observational studies in Crohn's disease and to evaluate whether the number and type of variables included affect the frequency of the outcome.

METHODS

MEDLINE [via PubMed], Scopus and Web of Science were searched to identify observational studies that enrolled patients with Crohn's disease and evaluated a composite or aggregate outcome. The proportion of patients achieving the outcome was determined and a random-effects meta-analysis was performed to evaluate how the frequency of each outcome varies according to the reporting of predefined variables.

RESULTS

From 10,257 identified records, 46 were included in the qualitative analysis and 38 in the meta-analysis. The frequency for composite and aggregate outcomes was 0.445 [95% confidence interval (CI): 0.389-0.501] and 0.140 (95% CI: 0.000-0.211), respectively. When comparing composite outcomes by number of included variables, the frequency was 0.271 (95% CI: 0.000-0.405) and 0.698 (95% CI: 0.651-0.746), for one and six variables, respectively. The frequency of the composite outcome varied according to the identity of the variables being reported. Specific pairs of predefined variables had a significant effect in the frequency of composite outcomes.

CONCLUSION

Composite outcomes with increasing number of predefined variables show an increase in frequency. Outcomes including variables such as 'Surgery' and 'Steroids' had higher frequencies when compared with the ones that did not include these variables. These results show that the frequency of composite outcomes is dependent on the number and type of variables being reported.

A Novel Hemodynamic Index of Post-operative Right Heart Dysfunction Predicts Mortality in Cardiac Surgical Patients

INTRODUCTION

This study aimed to investigate whether mortality following cardiac surgery was associated with the pulmonary artery pulsatility index (PAPi): pulmonary artery pulse pressure divided by central venous pressure (CVP), and a novel index: mean pulmonary artery pressure (mPAP) minus CVP.

METHODS

This retrospective analysis investigated all cardiac surgery patients in the Society of Thoracic Surgeons registry at a single academic medical center from January 2017 through March 2020 (n = 1510). The primary and secondary outcomes were mortality at 1 year and serum creatinine increase during index surgical admission, respectively. CVP, mPAP, PAPi, mPAP-CVP gradient, mean arterial pressure (MAP), and cardiac index (CI) were sampled continually from invasive hemodynamic monitors post-operatively. Associations with mortality were tested with univariate and multivariate analyses. The relationship with serum creatinine was investigated with Pearson's correlation at alpha = .05.

RESULTS

One-year mortality was observed in 44/1200 patients (3.7%). On univariate analysis, mortality was associated with minimums for mPAP, MAP, and CI and maximums for CVP, mPAP, PAPi, mPAP-CVP gradient, and CI (all P < .10). Model selection revealed that the only independently predictive parameters were minimum MAP (AOR = .880 [.819-.944]), maximum mPAP-CVP gradient (AOR = 1.082 [1.031-1.133]), and maximum CI (AOR = 1.421 [.928-2.068]), with model c-statistic = .770. A maximum mPAP-CVP gradient >20.5 predicted mortality with 54.5% sensitivity and 79.30% specificity, maintaining significance on survival analysis (P < .001). Peak increase in serum creatinine from baseline demonstrated a weak association with all parameters (max |r| = .33).

CONCLUSIONS

Mortality was not predicted by the post-operative PAPi; rather, it was independently predicted by the mPAP-CVP gradient, MAP, and CI.

Composite Outcomes in Clinical Prediction Modeling: Are We Trying to Predict Apples and Oranges?

Composite outcomes are widely used in clinical research. Existing literature has considered the pros and cons of composite outcomes in clinical trials, but their extensive use in clinical prediction has received much less attention. Clinical prediction assists decision-making by directing patients with higher risks of adverse outcomes toward interventions that provide the greatest benefits to those at the greatest risk. In this article, we summarize our existing understanding of the advantages and disadvantages of composite outcomes, consider how these relate to clinical prediction, and highlight the problem of key predictors having markedly different associations with individual components of the composite outcome. We suggest that a "composite outcome fallacy" may occur when a clinical prediction model is based on strong associations between key predictors and one component of a composite outcome (such as mortality) and used to direct patients toward intervention when these predictors actually have an inverse association with a more relevant component of the composite outcome (such as the use of a lifesaving intervention). We propose that clinical prediction scores using composite outcomes should report their accuracy for key components of the composite outcome and examine for inconsistencies among predictor variables.

Composite outcomes in observational studies of ulcerative colitis: A systematic review and meta-analysis

Background

Ulcerative colitis (UC) has been the focus of numerous observational studies over the years and a common strategy employed in their design is the use of composite and aggregate outcomes.

Objective

This systematic review and meta‐analysis aims to identify composite and aggregate outcomes of observational studies in UC and to evaluate how the number and type of variables included and the length of follow‐up affect the frequency of patients that achieve these outcomes.

Methods

A systematic literature search was carried out using MEDLINE [via PubMed], Scopus, and Web of Science online databases. Observational studies that included UC patients and reported composite or aggregate outcomes were identified. A set of variables considered to be representative of progressive or disabling UC was defined, the proportion of patients attaining the outcomes was determined and a random‐effects meta‐analysis was performed by dividing the identified studies into subgroups according to different criteria of interest.

Results

A total of 10,264 records were identified in the systematic search, of which 33 were retained for qualitative analysis and 20 were included in the meta‐analysis. The mean frequency for composite outcomes was 0.363 [95% confidence interval (CI) 0.323‐0.403]. The frequency of composite outcome for the subgroup of studies that included the variable “Biologics” was significantly higher than for those in which this variable was not reported [0.410; 95% CI 0.364‐0.457 versus 0.298; 95% CI 0.232‐0.364; p = 0.006]. Composite outcomes were also more frequent as the follow‐up duration increased.

Conclusion

The frequency of composite outcomes in observational studies of UC is dependent on the specific identity of the variables being reported. Moreover, longer follow‐up periods are associated with higher frequencies of composite outcomes. The evidence provided here is useful for the design of future observational studies of UC that aim to maximize the frequency of patients that achieve composite outcomes.

Summarize the established knowledge on this subject

Observational studies have become a valuable source of information but also present a remarkable heterogeneity.

The inconsistency on the reported outcomes between individual studies and the potential for reporting biases has led to calls for the development of core outcome sets (COS).

What are the significant and/or new findings of this study?

This is the first systematic review and meta‐analysis of outcomes in observational studies of Ulcerative colitis (UC).

The frequency of composite outcomes in observational studies of UC is dependent on the specific identity of the variables being reported and on the follow‐up duration.

Reporting of the variable “Biologics” significantly increased the frequency of composite outcomes.

These findings may be useful for the design of future observational studies of UC.

Composite outcomes at OMERACT: Multi-outcome domains and composite outcome domains

The OMERACT Technical Advisory Group recognises that working groups during the process of creating a core outcome set may identify an outcome domain that would be best represented as a composite that encapsulates these component outcome domains by bringing them together into a single outcome. A multi-outcome domain (MOD) is a within-patient combination of component outcomes, and an individual patient's evaluation depends on the observation of all of the components in that patient with a single overall rating determined according to a specified rule; which is often applicable when we consider a disease activity score. A composite outcome domain (COD) consists of a number of component outcomes and is defined as the occurrence in a patient of one, some or all of these specified components; which is often applicable when we consider the risk of adverse events or remission criteria. We review the general benefits, challenges, reporting and interpretation of using MODs and CODs. The development of the MOD or COD instrument for an OMERACT core outcome measurement set is considered through four distinct steps: choosing relevant outcome domains; finding high quality instruments for each of these outcome domains; weighting the outcome domain instruments in the MOD/COD instrument; and putting MOD/COD instrument through the OMERACT Filter. Guidance and training are in preparation for working groups who will be completing the OMERACT Instrument Selection Algorithm (OFISA). As for other initiatives in OMERACT, we will seek feedback from OMERACT working groups who complete the development of their MOD/COD, which will then be incorporated into the refinement of the guidance and training.

Days alive out of hospital in heart failure: Insights from the PARADIGM-HF and CHARM trials

BACKGROUND

An endpoint that has received some attention in recent cardiovascular trials is 'days alive and out of hospital' (DAOH). Percent DAOH is a natural extension of DAOH that adjusts for differences in length of follow-up. This endpoint measure incorporates mortality and morbidity together in a way that has the potential to give more insight regarding treatment effects compared to conventional time-to-event endpoints. Other advantages of this measure include the relative ease of collection and interpretation. However, research on how to analyze this measure is still limited.

METHODS

We propose using the one-inflated beta model to analyze percent DAOH. This model is appropriate for highly left-skewed data with a large proportion of boundary values. Data from the Prospective Comparison of ARNI [Angiotensin Receptor-Neprilysin Inhibitor] with ACEI [Angiotensin-Converting-Enzyme Inhibitor] to Determine Impact on Global Mortality and Morbidity in Heart Failure Trial (PARADIGM-HF) and Candesartan in Heart Failure Assessment of Reduction in Mortality and morbidity (CHARM) trials are used to illustrate this method.

RESULTS

Statistically significant differences in percent DAOH were observed for PARADIGM-HF and CHARM in favor of treatment. In PARADIGM-HF, treatment with sacubitril plus valsartan increased DAOH on average by 11 days (95% CI: 1.4-20.9 days) and increased percent DAOH by 1.64% at a fixed follow-up length of 1,000 days (95% CI: 0.61%- 2.67%). For the CHARM overall program, the candesartan group has 1.79% more DAOH (95% CI: 0.91%- 2.68%).

CONCLUSION

DAOH, and especially percent DAOH, can enhance our understanding of treatment effects in future cardiovascular trials, and the one-inflated beta model is an appropriate choice for its analysis.

Statistical models for composite endpoints of death and non-fatal events: a review

The proper analysis of composite endpoints consisting of both death and non-fatal events is an intriguing and sometimes contentious topic. The current practice of analyzing time to the first event often draws criticisms for ignoring the unequal importance between component events and for leaving recurrent-event data unused. Novel methods that address these limitations have recently been proposed. To compare the novel versus traditional approaches, we review three typical models for composite endpoints based on time to the first event, composite event process, and pairwise hierarchical comparisons. The pros and cons of these models are discussed with reference to the relevant regulatory guidelines, such as the recently released ICH-E9(R1) Addendum "Estimands and Sensitivity Analysis in Clinical Trials". We also discuss the impact of censoring when the model assumptions are violated and explore sensitivity analysis strategies. Simulation studies are conducted to assess the performance of the reviewed methods under different settings. As demonstration, we use publicly available R-packages to analyze real data from a major cardiovascular trial.

Methodological Issues in Randomized Clinical Trials for Prodromal Alzheimer's and Parkinson's Disease

Alzheimer's disease (AD) and Parkinson's disease (PD) are the first and second most common neurodegenerative disorders, respectively. Both are proteinopathies with inexorable courses and no approved disease-modifying therapies. A substantial effort has been made to identify interventions that could slow down the progression of AD and PD; to date, with no success. The advances in biomarker research improved the identification of individuals at risk for these disorders before symptom onset, recognizing the pre-clinical stage, in which there is abnormal protein accumulation but no clinical symptoms of the disease, and the prodromal stage, in which mild symptoms are present but the clinical diagnostic criteria for disease cannot be fulfilled. The ability to detect pre-clinical and prodromal stages of these diseases has encouraged clinical trials for disease-modification at earlier phases, seeking to slow or prevent phenoconversion into clinical disease. Clinical trials at these stages have several challenges, such as the identification of the eligible population, the appropriate choice of biomarkers, the definition of clinical endpoints, the duration of follow-up, and the statistical analysis. This article aims to discuss some of the methodological challenges in the design of trials for pre-clinical and prodromal phases of AD and PD, to critically review the recent studies, and to discuss methodological approaches to mitigate these challenges in trial design.

Competing risk of mortality in association studies of non-fatal events

In geriatric research of non-fatal events, participants often die during the study follow-up without having the non-fatal event of interest. Cause-specific (CS) hazard regression and Fine-Gray (FG) subdistribution hazard regression are the two most common estimation approaches addressing such competing risk. We explain how the conventional CS approach and the FG approach differ and why many FG estimates of associations are counter-intuitive. Additionally, we clarify the indirect link between models for hazard and models for cumulative incidence. The methodologies are contrasted on data from the Cardiovascular Health Study, a population-based study in adults aged 65 years and older.

Survival analyses in cardiovascular research, part II: statistical methods in challenging situations

This article is the second of a series of 2 educational articles. In the first article, we described the basic concepts of survival analysis, summarizing the common statistical methods and providing a set of recommendations to guide the strategy of survival analyses in randomized clinical trials and observational studies. Here, we introduce stratified Cox models and frailty models, as well as the immortal time bias arising from a poor assessment of time-dependent variables. To address the issue of multiplicity of outcomes, we provide several modelling strategies to deal with other types of time-to-event data analyses, such as competing risks, multistate models, and recurrent-event methods. This review is illustrated with examples from previous cardiovascular research publications, and each statistical method is discussed alongside its main strengths and limitations. Finally, we provide some general observations about alternative statistical methods with less restrictive assumptions, such as the win ratio method, the restrictive mean survival time, and accelerated failure time model.

Association of Skin Psoriasis and Somatic Comorbidity With the Development of Psychiatric Illness in a Nationwide Swedish Study

Importance

Psoriasis is a complex systemic disease with skin involvement, somatic comorbidity, and psychiatric illness (PI). Although this view of psoriasis is widely accepted, potential synergies within this triad of symptoms have not been adequately investigated.

Objectives

To investigate the independent association of skin psoriasis and somatic comorbidity with the development of PI and to assess whether skin psoriasis and somatic comorbidity act synergistically to produce a risk of PI that is greater than the additive associations.

Design, Setting, and Participants

Participants were enrolled between January 2005 and December 2010, in this retrospective matched case-control study using secondary (ie, administrative), population-based registry data from Swedish patients in routine clinical care. The dates of analysis were March 2017 to December 2019. Participants were patients with skin psoriasis and control participants without psoriasis matched on age, sex, and municipality, who were all free of preexisting PI.

Exposures

Presence of skin psoriasis and somatic comorbidity (captured through the Charlson Comorbidity Index and the Elixhauser Comorbidity Index).

Main Outcomes and Measures

Risk of PI onset (composite of depression, anxiety, and suicidality) is shown using Kaplan-Meier curves stratified by the presence of skin psoriasis and somatic comorbidity. Adjusted associations of skin psoriasis and somatic comorbidity with the development of PI were analyzed using Cox proportional hazards regression models, including interactions to assess synergistic associations. The 3 components of PI were also assessed individually.

Results

A total of 93 239 patients with skin psoriasis (mean [SD] age, 54 [17] years; 47 475 men [51%]) and 1 387 495 control participants (mean [SD] age, 54 [16] years; 702 332 men [51%]) were included in the study. As expected, patients with skin psoriasis were more likely to have somatic comorbidity and PI than control participants. Compared with those without skin psoriasis or somatic comorbidity, patients with psoriasis without somatic comorbidity had a 1.32 times higher risk of PI onset (hazard ratio [HR], 1.32; 95% CI, 1.27-1.36; P < .001), whereas patients with psoriasis with somatic comorbidity had a 2.56 times higher risk of PI onset (HR, 2.56; 95% CI, 2.46-2.66; P < .001). No synergistic associations of skin psoriasis and somatic comorbidity with the development of PI were found (HR, 0.93; 95% CI, 0.81-1.04; P = .21).

Conclusions and Relevance

This study found that somatic comorbidity appeared to alter PI onset even more than skin psoriasis. The observed association of skin psoriasis and somatic comorbidity with the development of PI reinforces the need for proactive, holistic treatment of patients with psoriasis.

Composite adverse outcomes in obstetric studies: a systematic review

BACKGROUND

Composite outcomes are increasingly being used in obstetric trials. The aim of this systematic review is to critically appraise the use of composite outcomes in obstetric RCTs with an intention of identifying limitations and providing potential solutions for future research.

METHODS

The study protocol was prospectively registered. Medline, Embase, Cochrane Databases and www.clinicaltrials.gov were searched for randomized controlled trials (RCTs) published in English between 1999 and 2019, using search terms related to pregnancy and composite outcomes.

STUDY ELIGIBILITY CRITERIA

RCTs involving an obstetric condition that reported on a composite outcome.

STUDY APPRAISAL AND SYNTHESIS METHODS

Screening and data extraction were performed in duplicate, and a descriptive synthesis and critical appraisal of composite obstetric outcomes, is presented.

RESULTS

Of the 4170 results screened, we identified 156 RCTs, reporting on 181 composite outcomes. Of these, 158 composite outcomes related to general morbidity and mortality, either exclusively maternal (n=20), fetal-neonatal [perinatal] (n=116) or maternal and perinatal (n=22) were included in the final analysis. Obstetric composite outcomes included between two and 16 components. Components that comprised these composite outcomes were often dissimilar in terms of severity and frequency of occurrence, unlikely to have similar relative risk reductions and sometimes unrelated to the study's primary objective - important pre-requisites to consider while constructing composite outcomes. In addition, composite adverse obstetric outcomes often do not incorporate the perspectives of pregnant persons, embrace a holistic view of health or consider outcomes related to both members of the mother-fetus dyad.

CONCLUSIONS

Composite outcomes are being increasingly used as primary outcomes in obstetric RCTs, based on which study conclusions are drawn and clinical recommendations made. However, there is a lack of consistency with regard to what components should be included within a composite adverse obstetric outcome and how these components should be measured. The use of novel research methods such as concept mapping may be able to address some of the limitations with the development of composite adverse obstetric outcomes, to inform future research.

Use of Composite Outcomes in Neonatal Trials: An Analysis of the Cochrane Reviews

INTRODUCTION

Composite outcomes are used to increase the power of a study by combining event rates. Many composite outcomes in adult clinical trials have components that differ substantially in patient importance, event rate, and effect size, making interpretation challenging. Little is known about the use of composite outcomes in neonatal randomized controlled trials (RCTs).

METHODS

We assessed the use of composite outcomes in neonatal RCTs included in Cochrane Neonatal reviews published till November 2017. Two authors reviewed the components of the composite outcomes to compare their patient importance and computed the ratios of effect sizes and event rates between the components, with an a priori threshold of 1.5, indicating a substantial difference. Descriptive statistics were presented.

RESULTS

We extracted 7,766 outcomes in 2,134 RCTs in 312 systematic reviews. Among them, 55 composite outcomes (0.7%) were identified in 46 RCTs. The vast majority (92.7%) of composite outcomes had 2 components, with death being the most common component (included 51 times [92.7%]). The components in nearly three-quarters of the composite outcomes (n = 40 [72.7%]) had different patient importance, while the effect sizes and event rates differed substantially between the components in 27 (49.1%) and 35 (63.6%) outcomes, respectively, with up to 43-fold difference in the event rates observed.

CONCLUSIONS

The majority of composite outcomes in neonatal RCTs had different patient importance with contrasting effect sizes and event rates between the components. In patient communication, clinicians should highlight individual components, rather than the composites, with explanation on the relationship between the components, to avoid misleading impression on the effect of the intervention. Future trials should report the estimates of all individual components alongside the composite outcomes presented.

Protocol for a randomized controlled trial evaluating the impact of the Nurse-Family Partnership's home visiting program in South Carolina on maternal and child health outcomes

Background

Policy-makers are increasingly seeking rigorous evidence on the impact of programs that go beyond typical health care settings to improve outcomes for low-income families during the critical period around the transition to parenthood and through early childhood.

Methods

This study is a randomized controlled trial evaluating the impact of the Nurse-Family Partnership’s expansion in South Carolina. The scientific trial was made possible by a “Pay for Success” program embedded within a 1915(b) Waiver from Medicaid secured by the South Carolina Department of Health and Human Services. This protocol describes study procedures and defines primary and secondary health-related outcomes that can be observed during the intervention period (including pregnancy through the child’s first 2 years of life). Primary study outcomes include (1) a composite indicator for adverse birth outcomes including being born small for gestational age, low birth weight (less than 2500 g), preterm birth (less than 37 weeks’ gestation), or perinatal mortality (fetal death at or after 20 weeks of gestation or mortality in the first 7 days of life), (2) a composite outcome indicating health care utilization or mortality associated with major injury or concern for abuse or neglect occurring during the child’s first 24 months of life, and (3) an indicator for an inter-birth interval of < 21 months. Secondary outcomes are defined similarly in three domains: (1) improving pregnancy and birth outcomes, (2) improving child health and development, and (3) altering the maternal life course through changes in family planning.

Discussion

Evidence from this trial on the impact of home visiting services delivered at scale as part of a Medicaid benefit can provide policy-makers and stakeholders with crucial information about the effectiveness of home visiting programs in improving health and well-being for low-income mothers and children and about novel financing mechanisms for cross-silo interventions.

Trial registration

The trial was registered prospectively on the American Economic Association Trial Registry (the primary registry for academic economists doing policy trials) on 16 February 2016 (AEARCTR-0001039). ClinicalTrials.gov NCT03360539. Registered on 28 November 2017.

Survival analysis for AdVerse events with VarYing follow-up times (SAVVY): Rationale and statistical concept of a meta-analytic study

The assessment of safety is an important aspect of the evaluation of new therapies in clinical trials, with analyses of adverse events being an essential part of this. Standard methods for the analysis of adverse events such as the incidence proportion, that is the number of patients with a specific adverse event out of all patients in the treatment groups, do not account for both varying follow-up times and competing risks. Alternative approaches such as the Aalen-Johansen estimator of the cumulative incidence function have been suggested. Theoretical arguments and numerical evaluations support the application of these more advanced methodology, but as yet there is to our knowledge only insufficient empirical evidence whether these methods would lead to different conclusions in safety evaluations. The Survival analysis for AdVerse events with VarYing follow-up times (SAVVY) project strives to close this gap in evidence by conducting a meta-analytical study to assess the impact of the methodology on the conclusion of the safety assessment empirically. Here we present the rationale and statistical concept of the empirical study conducted as part of the SAVVY project. The statistical methods are presented in unified notation, and examples of their implementation in R and SAS are provided.

Management of Diffuse Low-Grade Glioma: The Renaissance of Robust Evidence

The surgical management of diffuse low-grade gliomas (DLGGs) has undergone a paradigm shift toward striving for maximal safe resection when feasible. While extensive observational data supports this transition, unbiased evidence in the form of high quality randomized-controlled trials (RCTs) is lacking. Furthermore, despite a high volume of molecular, genetic, and imaging data, the field of neuro-oncology lacks personalized care algorithms for individuals with DLGGs based on a robust foundation of evidence. In this manuscript, we (1) discuss the logistical and philosophical challenges hindering the development of surgical RCTs for DLGGs, (2) highlight the potential impact of well-designed international prospective observational registries, (3) discuss ways in which cutting-edge computational techniques can be harnessed to generate maximal insight from high volumes of multi-faceted data, and (4) outline a comprehensive plan of action that will enable a multi-disciplinary approach to future DLGG management, integrating advances in clinical medicine, basic molecular research and large-scale data mining.

Prelabor screening at term using the cerebroplacental ratio and placental growth factor: a pragmatic randomized open-label phase 2 trial

BACKGROUND AND OBJECTIVE

In some women placental function may not be adequate to meet fetal growth requirements in late pregnancy or the additional demands during labor, thus predisposing these infants to intrapartum fetal compromise and subsequent serious morbidity and mortality. The objective of this study was to determine if the introduction of a prelabor screening test at term combining the cerebroplacental ratio and maternal placental growth factor level would result in a reduction in a composite of adverse outcomes.

STUDY DESIGN

Single-site, nonblinded, randomized controlled trial conducted at a tertiary hospital in Brisbane, Australia. Eligible women were randomized to either receive the screening test performed between 37-38 weeks or routine obstetric care. Screen-positive women were offered induction of labor. The primary outcome was a composite of emergency cesarean delivery for nonreassuring fetal status (fetal distress) or severe neonatal acidosis or low Apgar score or stillbirth or neonatal death.

RESULTS

Women were recruited and randomized (n = 501) between April 2017 and January 2019. Sixty-three of 249 subjects (25.3%) in the screened group compared to 56 of 252 (22.2%) in the control group experienced the primary outcome (relative risk = 1.14 [95% confidence interval, 0.83-1.56]; P = .418). Women who screened positive were more likely to require operative delivery for fetal distress, have meconium-stained liquor, have pathologic fetal heart rate abnormalities, and have infants with lower birthweight compared to women that screened negative.

CONCLUSION

The introduction of this test did not result in improvements in intrapartum intervention rates or neonatal outcomes. However, it did show discriminatory potential, and future research should focus on refining the thresholds used.

Composite endpoints

Studies often combine several events, for example, death or myocardial infarction or stroke, into a single study outcome. This is called a composite endpoint. Composite endpoints make doing trials easier by reducing the sample size or follow-up period required to demonstrate the effectiveness of an intervention. However, interpreting the results of composite endpoints can be confusing. To avoid misleading conclusions about the effectiveness of an intervention, it is important for readers of studies reporting a composite endpoint to ascertain that the clinical importance, the frequency of events, and the effect of the intervention on each component of the composite endpoint are similar.

Reporting of Organ Support Outcomes in Septic Shock Randomized Controlled Trials: A Methodologic Review-The Sepsis Organ Support Study

OBJECTIVES

Many recent randomized controlled trials in the field of septic shock failed to demonstrate a benefit on mortality. Randomized controlled trials increasingly report organ support duration and organ support-free days as primary or secondary outcomes. We conducted a methodologic systematic review to assess how organ support outcomes were defined and reported in septic shock randomized controlled trials.

DATA SOURCES

MEDLINE via PubMed, Embase, Cochrane Central Register of Controlled Trials, and Web of Science.

STUDY SELECTION

We included randomized controlled trials published between January 2004 and March 2018 that involved septic shock adults and assessed organ support duration and/or organ support-free days for hemodynamic support, respiratory support, or renal replacement therapy.

DATA EXTRACTION

For each randomized controlled trial, we extracted the definitions of organ support duration and organ support-free days. We particularly evaluated how nonsurvivors were accounted for. Study authors were contacted to provide any missing information regarding these definitions.

DATA SYNTHESIS

We included 28 randomized controlled trials. Organ support duration and organ support-free days outcomes were reported in 17 and 15 randomized controlled trials, respectively, for hemodynamic support, 15 and 15 for respiratory support, and five and nine for renal replacement therapy. Nonsurvivors were included in the organ support duration calculation in 13 of 14 randomized controlled trials (93%) for hemodynamic support and nine of 10 (90%) for respiratory support. The organ support-free days definition for hemodynamic support, respiratory support, and renal replacement therapy was reported in six of 15 randomized controlled trials (40%), eight of 15 randomized controlled trials (53%), and six of nine randomized controlled trials (67%) reporting an organ support-free days outcome, respectively. Of these, one half assigned "0" to nonsurvivors, and the other half attributed one point per day alive free of organ support up to a predefined time point.

CONCLUSIONS

This study highlights the heterogeneity and infrequency of organ support duration/organ support-free days outcome reporting in septic shock trials. When reported, the definitions of these outcome measures and methods of calculation are also infrequently reported, in particular how nonsurvivors were accounted for, which may have an important impact on interpretation.

How Accurate Are the Surgical Risk Preoperative Assessment System (SURPAS) Universal Calculators in Total Joint Arthroplasty?

BACKGROUND

Surgical outcome prediction models are useful for many purposes, including informed consent, shared decision making, preoperative mitigation of modifiable risk, and risk-adjusted quality measures. The recently reported Surgical Risk Preoperative Assessment System (SURPAS) universal risk calculators were developed using 2005-2012 American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP), and they demonstrated excellent overall and specialty-specific performance. However, surgeons must assess whether universal calculators are accurate for the small subset of procedures they perform. To our knowledge, SURPAS has not been tested in a subset of patients undergoing lower-extremity total joint arthroplasty (TJA).

QUESTIONS/PURPOSES

How accurate are SURPAS models' predictions for patients undergoing TJA?

METHODS

We identified an internal subset of patients undergoing non-emergency THA or TKA from the 2012 ACS-NSQIP, the most recent year of the SURPAS development dataset. To assess the accuracy of SURPAS prediction models, 30-day postoperative outcomes were defined as in the original SURPAS study: mortality, overall morbidity, and six complication clusters-pulmonary, infectious, cardiac or transfusion, renal, venous thromboembolic, and neurologic. We calculated predicted outcome probabilities by applying coefficients from the published SURPAS logistic regression models to the TJA cohort. Discrimination was assessed with C-indexes, and calibration was assessed with Hosmer-Lemeshow 10-group chi-square tests and decile plots.

RESULTS

The 30-day postoperative mortality rate for TJA was 0.1%, substantially lower than the 1% mortality rate in the SURPAS development dataset. The most common postoperative complications for TJA were intraoperative or postoperative transfusion (16%), urinary tract infection (5%), and vein thrombosis (3%). The C-indexes for joint arthroplasty ranged from 0.56 for venous thromboembolism (95% CI 0.53 to 0.59 versus SURPAS C-index 0.78) to 0.82 for mortality (95% CI 0.76 to 0.88 versus SURPAS C-index 0.94). All joint arthroplasty C-index estimates, including CIs, were lower than those reported in the original SURPAS development study. Decile plots and Hosmer-Lemeshow tests indicated poor calibration. Observed mortality rates were lower than expected for patients in all risk deciles (lowest decile: no observed deaths, 0.0% versus expected 0.1%; highest decile: observed mortality 0.7% versus expected 2%; p < 0.001). Conversely, observed morbidity rates were higher than expected across all risk deciles (lowest decile: observed 12% versus expected 8%; highest decile: observed morbidity 32% versus expected 25%; p < 0.001) CONCLUSIONS: The universal SURPAS risk models have lower accuracy for TJA procedures than they do for the wider range of procedures in which the SURPAS models were originally developed.

CLINICAL RELEVANCE

These results suggest that SURPAS model estimates must be evaluated for individual surgical procedures or within restricted groups of related procedures such as joint arthroplasty. Given substantial variation in patient populations and outcomes across numerous surgical procedures, universal perioperative risk calculators may not produce accurate and reliable results for specific procedures. Surgeons and healthcare administrators should use risk calculators developed and validated for specific procedures most relevant to each decision. Continued work is needed to assess the accuracy of universal risk calculators in more narrow procedural categories based on similarity of outcome event rates and prevalence of predictive variables across procedures.

Alive and Ventilator Free: A Hierarchical, Composite Outcome for Clinical Trials in the Acute Respiratory Distress Syndrome

OBJECTIVES

Survival from acute respiratory distress syndrome is improving, and outcomes beyond mortality may be important for testing new treatments. The "ventilator-free days" score, is an established composite that equates ventilation on day 28 to death. A hierarchical outcome treating death as a worse than prolonged ventilation would enhance face validity, but performance characteristics and reporting of such an outcome are unknown. We therefore evaluated the performance of a novel hierarchical composite endpoint, the Alive and Ventilator Free score.

DESIGN

Using data from four Acute Respiratory Distress Syndrome Network clinical trials, we compared Alive and Ventilator Free to the ventilator-free days score. Alive and Ventilator Free compares each patient with every other patient in a win-lose-tie for each comparison. Duration of mechanical ventilation is only compared if both patients survived. We evaluated power of Alive and Ventilator Free versus ventilator-free days score under various circumstances.

SETTING

ICUs within the Acute Respiratory Distress Syndrome Network.

PATIENTS

Individuals enrolled in four Acute Respiratory Distress Syndrome Network trials.

INTERVENTIONS

None for this analysis.

MEASUREMENTS AND MAIN RESULTS

Within the four trials (n = 2,410 patients), Alive and Ventilator Free and ventilator-free days score had similar power, with Alive and Ventilator Free slightly more powerful when a mortality difference was present, and ventilator-free days score slightly more powerful with a difference in duration of mechanical ventilation. Alive and Ventilator Free less often found in favor of treatments that increased mortality and increased days free of ventilation among survivors.

CONCLUSIONS

A hierarchical composite endpoint, Alive and Ventilator Free, preserves statistical power while improving face validity. Alive and Ventilator Free is less prone to favor a treatment with discordant effects on survival and days free of ventilation. This general approach can support complex outcome hierarchies with multiple constituent outcomes. Approaches to interpretation of differences in Alive and Ventilator Free are also presented.

A patient-centered composite endpoint weighting technique for orthopaedic trauma research

Background

This study aimed to address the current limitations of the use of composite endpoints in orthopaedic trauma research by quantifying the relative importance of clinical outcomes common to orthopaedic trauma patients and use those values to develop a patient-centered composite endpoint weighting technique.

Methods

A Best-Worst Scaling choice experiment was administered to 396 adult surgically-treated fracture patients. Respondents were presented with ten choice sets, each consisting of three out of ten plausible clinical outcomes. Hierarchical Bayesian modeling was used to determine the utilities associated with the outcomes.

Results

Death was the outcome of greatest importance (mean utility = − 8.91), followed by above knee amputation (− 7.66), below knee amputation (− 6.97), severe pain (− 5.90), deep surgical site infection (SSI) (− 5.69), bone healing complications (− 5.20), and moderate pain (− 4.59). Mild pain (− 3.30) and superficial SSI (− 3.29), on the other hand, were the outcomes of least importance to respondents.

Conclusion

This study revealed that patients’ relative importance towards clinical outcomes followed a logical gradient, with distinct and quantifiable preferences for each possible component outcome. These findings were incorporated into a novel composite endpoint weighting technique.

Assessing risk factors of non-fatal outcomes amid a competing risk of mortality: the example of hip fracture

The Fine-Gray method is often used instead of Cox regression to account for competing risks of death in time-to-event analyses for non-fatal outcomes. A series of examples using well-known risk factors of hip fracture in an older cohort with substantial competing mortality demonstrates that the Fine-Gray approach can yield estimates that implausibly contradict long-established associations, while Cox regression preserves them. Cox regression is generally preferred for risk factor-outcome associations even in the presence of competing risk of death.

INTRODUCTION

Factors like age, sex, and race are associated not only with risk of hip fracture but also with mortality. Substantial misunderstanding remains regarding the appropriate statistical approach to account for the competing risk of mortality.

METHODS

In the Cardiovascular Health Study, an ongoing cohort study of 5888 older adults, we followed participants for incident hip fracture from their 1992-1993 visit through June 2014. We contrasted the conventional cause-specific Cox analysis, which censors individuals at the time of death, with the Fine-Gray (FG) approach, which extends participant follow-up even after death, to estimate the association of well-established demographic and clinical factors with incident hip fracture.

RESULTS

For age, current smoking and sex, Cox and FG methods yielded directionally concordant but quantitatively different strengths of association. For example, the Cox hazard ratio (HR) for a 5-year increment in age was 1.74 (95% CI, 1.61-1.87), while the corresponding FG HR was 1.16 (1.09-1.24). In contrast, the FG approach estimated a stronger association of hip fracture with sex. The two approaches yielded nearly identical results for race. For diabetes and kidney function, the estimates were discordant in direction, and the FG HRs suggested effects that were in the opposite direction of well-understood and widely accepted associations.

CONCLUSIONS

Cause-specific Cox models provide appropriate estimates of hazard for non-fatal outcomes like hip fracture even in the presence of competing risk of mortality. The Cox approach estimates hazard in the population of individuals who have not yet had an incident hip fracture and remain alive, which is typically the group of clinical interest. The Fine-Gray method estimates hazard in a hypothetical population that can yield misleading inferences about risk factors in populations of clinical interest.

The age of randomized clinical trials: three important aspects of randomized clinical trials in cardiovascular pharmacotherapy with examples from lipid and diabetes trials

Randomized clinical trials (RCTs) are important and the Gold Standard for drugs in modern cardiovascular (CV) therapy. The cornerstone of RCTs is the recording of hard clinical endpoints instead of surrogates. It is important to select an appropriate endpoint. Efficacy endpoints must be clinically relevant and can be hierarchically divided. A very interesting innovation in endpoint acquisition is the total event paradigm.

Cardiovascular Outcomes Reported in Hemodialysis Trials

Patients on long-term hemodialysis are at very high risk for cardiovascular disease but are usually excluded from clinical trials conducted in the general population or in at-risk populations. There are no universally agreed cardiovascular outcomes for trials conducted specifically in the hemodialysis population. In this review, we highlight that trials reporting cardiovascular outcomes in hemodialysis patients are usually of short duration (median 3 to 6 months) and are small (59% of trials have <100 participants). Overall, the cardiovascular outcomes are very heterogeneous and may not reflect outcomes that are meaningful to patients and clinicians in supporting decision making, as they are often surrogates of uncertain clinical importance. Composite outcomes used in different trials rarely share the same components. In a field in which a single trial is often insufficiently powered to fully assess the clinical and economic impact of interventions, differences in outcome reporting across trials make the task of meta-analysis and interpretation of all the available evidence challenging. Core outcome sets are now being established across many specialties in health care to prevent these problems. Through the global Standardized Outcomes in Nephrology-Hemodialysis initiative, cardiovascular disease was identified as a critically important core domain to be reported in all trials in hemodialysis. Informed by the current state of reporting of cardiovascular outcomes, a core outcome measure for cardiovascular disease is currently being established with involvement of patients, caregivers, and health professionals. Consistent reporting of cardiovascular outcomes that are critically important to hemodialysis patients and clinicians will strengthen the evidence base to inform care in this very high-risk population.

Imputation strategies when a continuous outcome is to be dichotomized for responder analysis: a simulation study

BACKGROUND

In many clinical trials continuous outcomes are dichotomized to compare proportions of patients who respond. A common and recommended approach to handling missing data in responder analysis is to impute as non-responders, despite known biases. Multiple imputation is another natural choice but when a continuous outcome is ultimately dichotomized, the specifications of the imputation model come into question. Practitioners can either impute the missing outcome before dichotomizing or dichotomize then impute. In this study we compared multiple imputation of the continuous and dichotomous forms of the outcome, and imputing responder status as non-response in responder analysis.

METHODS

We simulated four response profiles representing a two-arm randomized controlled trial with a continuous outcome at four time points. We omitted data using six missing at random mechanisms, and imputed missing observations three ways: 1) replacing as non-responder; 2) multiply imputing before dichotomizing; and 3) multiply imputing the dichotomized response. Imputation models included the continuous response at all timepoints, and additional auxiliary variables for some scenarios. We assessed bias, power, coverage of the 95% confidence interval, and type 1 error. Finally, we applied these methods to a longitudinal trial for patients with major depressive disorder.

RESULTS

Both forms of multiple imputation performed better than non-response imputation in terms of bias and type 1 error. When approximately 30% of responses were missing, bias was less than 7.3% for multiple imputation scenarios but when 50% of responses were missing, imputing before dichotomizing generally had lower bias compared to dichotomizing before imputing. Non-response imputation resulted in biased estimates, both underestimates and overestimates. In the example trial data, non-response imputation estimated a smaller difference in proportions than multiply imputed approaches.

CONCLUSIONS

With moderate amounts of missing data, multiply imputing the continuous outcome variable prior to dichotomizing performed similar to multiply imputing the binary responder status. With higher rates of missingness, multiply imputing the continuous variable was less biased and had well-controlled coverage probabilities of the 95% confidence interval compared to imputing the dichotomous response. In general, multiple imputation using the longitudinally measured continuous outcome in the imputation model performed better than imputing missing observations as non-responders.