Understanding the Merits and Drawbacks of Noninferiority Trials in Cardiovascular Medicine

Non-inferiority trials in clinical ophthalmology: a systematic review

PURPOSE

To summarize the characteristics and methodology of non-inferiority trials in ophthalmology, aiding researchers in understanding the applications and limitations of such trials in ophthalmic diseases.

METHODS

PubMed, Web of Science, Embase and Scopus were searched for literature on non-inferiority randomized trials in ophthalmology published between 2000 and November 5 2023. Data on the basic characteristics were extracted and summarized. The Risk of Bias 2's was used to assess the bias risk.

RESULTS

A total of 294 papers were included, with 77.6% of the trials conducted in the last 10 years, and more than 2/3 (72.1%) were multicenter studies, and 79.9% were registered on platforms. The majority of trials were applied in the researches of glaucoma, cataract, age macular degeneration, macular edema, dry eye, myopia, or refractive error. Non-inferiority thresholds were reported in 88.4% of the trials. Intent-to-treat analysis was the primary outcome analysis method in only 21.8% of trials, while both intent-to-treat and per-protocol analyses were used in 29.6%. Last observation carried forward method was used to address missing values in 23.5%. However, 56.5% of the articles did not report how missing values were handled, leaving uncertainty regarding whether missing data was considered in the analysis. About 20.7% of the studies were at high risk of bias, mainly due to outcome measures and missing value treatments.

CONCLUSION

Non-inferiority trials are commonly used in ophthalmologic research to assess the effectiveness, safety, cost-effectiveness of treatments or surgical methods, but the quality of implementation and reporting needs to be improved.

Bayesian Analytical Methods in Cardiovascular Clinical Trials: Why, When, and How

The Bayesian analytical framework is clinically intuitive, characterised by the incorporation of previous evidence into the analysis and allowing an estimation of treatment effects and their associated uncertainties. The application of Bayesian statistical inference is not new to the cardiovascular field, as illustrated by various recent randomised trials that have applied a primary Bayesian analysis. Given the guideline-shaping character of trials, a thorough understanding of the concepts and technical details of Bayesian statistical methodology is of utmost importance to the modern practicing cardiovascular physician. This review presents a step-by-step guide to interpreting and performing a Bayesian (re)analysis of cardiovascular clinical trials, while highlighting the main advantages of Bayesian inference for the clinical reader. After an introduction of the concepts of frequentist and Bayesian statistical inference and reasons to apply Bayesian methods, key steps in performing a Bayesian analysis are presented, including verification of the clinical appropriateness of the research question, quality and completeness of the trial design, and adequate elicitation of the prior (ie, one's belief toward a certain treatment before the current evidence becomes available); identification of the likelihood; and their combination into a posterior distribution. Examination of this posterior distribution offers not only the possibility of determining the probability of treatment superiority, but also the probability of exceeding any chosen minimal clinically important difference. Multiple priors should be transparently prespecified, limiting post hoc manipulations. Using this guide, 3 cardiovascular randomised controlled trials are reanalysed, demonstrating the clarity and versatility of Bayesian inference.

Characteristics and Impact of Randomized Trials on Drugs or Devices in Cardiovascular Medicine

INTRODUCTION

Clinical trials, essential for medical advancement, vary significantly in methodology and regulatory pathways depending on the type of therapeutic intervention (i.e., drugs or devices). This study aimed to determine whether the drug or device intervention types influence the impact of randomized trials in cardiovascular medicine.

METHODS

We analyzed late-breaking randomized controlled trials presented at major cardiology conferences from 2015 to 2021. The primary endpoint was the total number of citations obtained. Secondary endpoints included the number of citations at 1 and 2 years, number of total and 1-year mentions, and several metrics of study conduct and publication. Statistical analysis included tests for comparisons of continuous or categorical variables, based on their distribution, as appropriate. To adjust the results for potential confounders, univariable and multivariable regression models were utilized. Additionally, sensitivity analyses were conducted to explore both the effect of neutral or positive study outcomes on the comparative impact of drug versus device trials and the impact of the coronavirus disease 2019 (COVID-19) pandemic on the primary endpoint.

RESULTS

Of 382 eligible randomized trials, 227 (59.4%) were trials of drugs and 155 (40.6%) were trials of devices. Drug trials had a higher median number of total citations compared to device studies (93 [interquartile range {IQR} 48-137] vs. 82 [IQR 39-192]; p = 0.025). This difference was consistent at 1 and 2 years and was also observed in the number of total mentions and mentions at 1 year. All the metrics of study conduct and publication were similar, except for drug studies being more often stopped prematurely (8.8 vs. 1.9%; p = 0.006). After adjusting for multiple potential confounders, the difference in citations and mentions was no longer statistically significant. However, drug trials remained more likely to be stopped prematurely (adjusted odds ratio = 1.15; 95% confidence interval 1.03-1.28; p = 0.009). Positive study outcomes significantly influenced the number of citations and the likelihood of a trial being stopped prematurely.

CONCLUSIONS

Drug trials are often stopped early and receive more citations and mentions than device trials. However, these differences are mainly due to factors other than the treatment itself. Studies published simultaneously tend to get more attention, and drug trials with positive results are cited more often than those with neutral results.

Assessment of Noninferiority Margins in Cardiovascular Medicine Trials

Background

Noninferiority trials are increasingly common in cardiovascular medicine, but their reporting and interpretation are challenging, particularly when an absolute risk difference is used as noninferiority margin.

Objectives

This study aimed to investigate the effect of using absolute rather than relative noninferiority margins in cardiovascular trials.

Methods

We reviewed noninferiority trials presented at major cardiovascular conferences from 2015 to 2022 and published within the same period. Based on the actual versus anticipated event rates in the control group, we recalculated the absolute noninferiority margin and re-assessed the trial results. The primary outcome of interest was the proportion of trials with a different interpretation after recalculation. Additionally, we analyzed the conclusion statements of these trials to determine if cautionary notes for the interpretation of study results were included.

Results

We analyzed a total of 768 trials, of which 88 had a noninferiority design and 66 used an absolute noninferiority margin. Of 48 comparisons from 45 trials qualifying for the analysis, 11 (22.9%) had divergent results after recalculation of the absolute noninferiority margin based on the observed rather than anticipated event rate. Ten trials originally claiming noninferiority, did not meet it after the margin recalculation. All of them did not include statements suggesting cautionary interpretation of the study results in the conclusion section. Compared with the other trials, these displayed a larger median difference between anticipated and recalculated noninferiority margins (44.7% [IQR: 38.6%-56.7%] vs 15.3% [IQR: -1.5% to 28.9%]; P < 0.001).

Conclusions

Recalculating noninferiority margins based on actual event rates, rather than anticipated ones, led to different outcomes in approximately 1 out of 4 cardiovascular trials, with most divergent trials lacking cautionary interpretation. These findings emphasize the importance of using or supplementing the relative noninferiority margin, particularly in studies with significant deviations between observed and expected event rates. This underscores the critical need for enhanced methodological and reporting standards in noninferiority trials, especially those employing absolute margins.

Impact of polyethylene glycol loxenatide on cardiovascular outcomes in patients with type 2 diabetes: study protocol for a multicentre, randomised, double-blind, placebo-controlled trial (BALANCE-3)

INTRODUCTION

Recent cardiovascular outcomes trials have demonstrated that glucagon-like peptide 1 receptor agonist (GLP-1RA) decreases the incidence of major adverse cardiovascular events (MACEs) in individuals with type 2 diabetes mellitus (T2DM). Polyethylene glycol loxenatide (PEG-Loxe) is a once-weekly GLP-1RA obtained by modifying exendin-4. No clinical trials have been designed to assess the impact of PEG-Loxe on cardiovascular (CV) outcomes in individuals with T2DM. This trial aims to test the hypothesis that compared with placebo, PEG-Loxe treatment does not result in an unacceptable increase in CV risk in individuals with T2DM.

METHODS AND ANALYSIS

This study is a multicentre, randomised, double-blind, placebo-controlled trial. Patients with T2DM who fulfilled the inclusion criteria were randomly divided to receive weekly administration of either PEG-Loxe 0.2 mg or placebo (1:1 ratio). The randomisation was stratified according to utilisation of sodium-glucose cotransporter 2 inhibitors, history of CV disease and body mass index. The research period is expected to be 3 years, with a 1-year recruitment period and a 2-year follow-up period. The primary outcome is the occurrence of the first MACE, described as CV death, non-fatal myocardial infarction or non-fatal stroke. The statistical analyses were undertaken on the intent-to-treat patient. The primary outcome was evaluated using a Cox proportional hazards model with treatment and randomisation strata as the covariates.

ETHICS AND DISSEMINATION

The current research has been authorised by the Ethics Committee of Tianjin Medical University Chu Hsien-I Memorial Hospital (approval number: ZXYJNYYhMEC2022-2). Researchers must acquire informed consent from every participant before conducting any protocol-associated procedures. The findings of this study will be published in a peer-reviewed journal.

TRIAL REGISTRATION NUMBER

ChiCTR2200056410.

Long-term use of proton-pump inhibitor on Alzheimer’s disease: a real-world distributed network analysis of six observational Korean databases using a Common Data Model

Background:

Dementia has a crucial impact on the quality of life of elderly patients and their caregivers. Proton-pump inhibitors (PPIs) are the most frequently prescribed treatment, but they have been shown to be associated with dementia. The data are inconsistent, however.

Objective:

To investigate the association between PPIs use and Alzheimer’s disease (AD) or all-cause dementia in six observational Korean databases using a Common Data Model (CDM) and to perform a distributed network analysis.

Methods:

Subjects aged over 18 years between 1 January 2004 and 31 December 2020. Among 7,293,565 subjects from 6 cohorts, 41,670 patients met the eligibility criteria. A total of 2206 patients who were included in both cohorts or with a history of dementia were excluded. After propensity matching, 5699 propensity-matched pairs between the PPIs and histamine-2 receptor antagonist (H₂RA) users were included in this study. The primary outcome was the incidence of AD at least 365 days after drug exposure. The secondary outcome was the incidence of all-cause dementia at least 365 days after drug exposure.

Results:

In the 1:1 propensity score matching, the risk of AD or all-cause dementia was not significantly different between the PPIs and H₂RA groups in all six databases. In the distributed network analysis, the long-term PPI users (⩾365 days) were unassociated with AD [hazard ratio (HR) = 0.92, 95% confidence interval (CI) = 0.68–1.23; I² = 0%] and all-cause dementia (HR =1.04, 95% CI = 0.82–1.31; I² = 0%) compared with H₂RA users.

Conclusion:

In the distributed network analysis of six Korean hospital databases using Observational Medical Outcomes Partnership (OMOP)-CDM data, the long-term use of PPI was not associated with a statistically significantly increased risk of AD or all-cause dementia. Therefore, we suggest that physicians should not avoid these medications because of concern about dementia risk.