¿Ensayos clínicos de superioridad, equivalencia o no inferioridad? / ¿Clinical trials of superiority, non-inferiority or equivalence?

La eficacia de una nueva intervención se establece generalmente a través de ensayos clínicos (EC) con asignación aleatoria (AA). Sin embargo, entre otros tantos desafíos metodológicos, el especificar la hipótesis de un EC con AA, sigue siendo un problema complejo de resolver para los investigadores clínicos. En este manuscrito discutimos las características de tres variantes de los EC con AA: EC de superioridad (ECS), EC de no-inferioridad (ECNI), y EC de equivalencia (ECE). Estos tres tipos de EC tienen supuestos diferentes sobre los efectos de una intervención, por lo que plantear hipótesis y definir objetivos requiere conocer algunos supuestos subyacentes a estos EC, incluso hasta elementos relacionados con la estimación del tamaño de muestra para cada cual. El objetivo de este manuscrito fue describir las diferencias metodológicas entre ECS, ECNI y ECE.

Efficacy and effectivity of new interventions are generally established through randomized clinical trials (RCTs). However, among many other methodological challenges, specifying the hypothesis of a RCT remains complex problem for clinical researchers. In this manuscript we discuss the characteristics of three variants of RCTs: superiority RCT (SRCT), non-inferiority RCT (NIRCT), and equivalence RCT (ERCT). These three types of RCT have different assumptions about the effects of an intervention, so setting hypotheses and defining objectives requires knowing some assumptions underlying these RCTs, including elements related to the estimation of the sample size for each one. The aim of this manuscript was to describe methodological differences between SRCT, NIRCT and ERCT.

More Than a Decade Since the Latest CONSORT Non-inferiority Trials Extension: Do Infectious Diseases Trials Do Enough?

More than a decade after the Consolidated Standards of Reporting Trials group released a reporting items checklist for non-inferiority randomized controlled trials, the infectious diseases literature continues to underreport these items. Trialists, journals, and peer reviewers should redouble their efforts to ensure infectious diseases studies meet these minimum reporting standards.

Non-inferiority trials with time-to-event data: clarifying the impact of censoring.

In non-inferiority (NI) trials with time-to-event data, different types and patterns of censoring may occur, but their impact on trial results is not entirely clear. We investigated the influence of informative and non-informative censoring by conducting extensive simulation studies under the assumption that the NI margin is defined as a maximum acceptable hazard ratio and scenarios typically observed in recent NI trials. We found that while non-informative censoring tends to only affect the power, informative censoring can impact the treatment effect estimates, type I error rate, and power. The magnitude of these effects depends on the between-group differences in the failure and informative censoring risks, as well as the correlation between censoring and failure times, among other factors. The adverse impact of informative censoring was generally decreased with larger NI margins.

Magnetic Waves vs. Electric Shocks: A Non-Inferiority Study of Magnetic Seizure Therapy and Electroconvulsive Therapy in Treatment-Resistant Depression.

Treatment-resistant depression (TRD), characterized by the failure to achieve symptomatic remission despite multiple pharmacotherapeutic treatments, poses a significant challenge for clinicians. Electroconvulsive therapy (ECT) is an effective but limited option due to its cognitive side effects. In this context, magnetic seizure therapy (MST) has emerged as a promising alternative, offering comparable antidepressant efficacy with better cognitive outcomes. However, the clinical outcomes and cognitive effects of MST require further investigation. This double-blinded, randomized, non-inferiority study aims to compare the efficacy, tolerability, cognitive adverse effects, and neurophysiological biomarkers of MST with bilateral ECT (BT ECT) in patients with TRD. This study will employ multimodal nuclear magnetic resonance imaging (MRI) and serum neurotrophic markers to gain insight into the neurobiological basis of seizure therapy. Additionally, neurophysiological biomarkers will be evaluated as secondary outcomes to predict the antidepressant and cognitive effects of both techniques. The study design, recruitment methods, ethical considerations, eligibility criteria, interventions, and blinding procedures are described. The expected outcomes will advance the field by offering a potential alternative to ECT with improved cognitive outcomes and a better understanding of the underlying pathophysiology of depression and antidepressant therapies.

Increasing the use of experimental methods in nursing and midwifery education research.

AIM: To consider how more use could be made of experimental research in nursing and midwifery education. BACKGROUND: Much use has been made in nursing and midwifery educational research of pre- and post-, within-subjects research. While this has its place and has been a valuable design for testing educational interventions, there has been a distinct lack of more rigorous experimental designs. DESIGN: Discussion paper to consider the use of experimental designs in nursing and midwifery education research. METHODS: A review of within-subjects designs, between-subjects designs and new approaches to experimental research such as pragmatic designs, non-inferiority designs and the framework offered by complex interventions. RESULTS: Recommendations for implementing experimental designs in nursing and midwifery education research have been drawn. CONCLUSIONS: Within-subjects designs have dominated experimental research in nursing and midwifery education. While suitable for preliminary studies, they should be augmented by more rigorous designs based on between-subjects designs. These do not have to be strictly randomised controlled trials and there are many reasons why these are hard to implement in nursing and midwifery education research. However, a range of alternatives is available.

Practical approaches to Bayesian sample size determination in non-inferiority trials with binary outcomes.

Bayesian analysis of a non-inferiority trial is advantageous in allowing direct probability statements to be made about the relative treatment difference rather than relying on an arbitrary and often poorly justified non-inferiority margin. When the primary analysis will be Bayesian, a Bayesian approach to sample size determination will often be appropriate for consistency with the analysis. We demonstrate three Bayesian approaches to choosing sample size for non-inferiority trials with binary outcomes and review their advantages and disadvantages. First, we present a predictive power approach for determining sample size using the probability that the trial will produce a convincing result in the final analysis. Next, we determine sample size by considering the expected posterior probability of non-inferiority in the trial. Finally, we demonstrate a precision-based approach. We apply these methods to a non-inferiority trial in antiretroviral therapy for treatment of HIV-infected children. A predictive power approach would be most accessible in practical settings, because it is analogous to the standard frequentist approach. Sample sizes are larger than with frequentist calculations unless an informative analysis prior is specified, because appropriate allowance is made for uncertainty in the assumed design parameters, ignored in frequentist calculations. An expected posterior probability approach will lead to a smaller sample size and is appropriate when the focus is on estimating posterior probability rather than on testing. A precision-based approach would be useful when sample size is restricted by limits on recruitment or costs, but it would be difficult to decide on sample size using this approach alone.

Multiple assessments of non-inferiority trials with ordinal endpoints.

Non-inferiority (NI) trials are implemented when there is a practical demand to search for alternatives to standard therapies, such as to reduce side effects. An experimental treatment is considered non-inferior to the standard treatment when it exhibits clinically non-significant loss of efficacy. Ordinal categorical responses are frequently observed in clinical trials. It has been reported that responses measured using an ordinal scale produce more informative analysis than when responses collapse into binary outcomes. We study the NI trials using ordinal endpoints. We propose a latent variable model for ordinal categorical responses. Based on the proposed latent variable model, the mean efficacy of the different treatments is denoted by the corresponding mean parameter of the underlying continuous distributions. A two-step procedure is proposed for model identification and parameter estimation. A non-inferiority analysis can then be conducted based on the latent variable model and the corresponding estimation procedure. We also develop a method and an algorithm to produce an optimal sample size configuration based on the proposed testing procedure. Two clinical examples are provided for demonstrative purposes.

How do we know a treatment is good enough? A survey of non-inferiority trials.

BACKGROUND: Non-inferiority and equivalence trials aim to determine whether a new treatment is good enough (non-inferior) or as good as (equivalent to) another treatment. To inform the decision about non-inferiority or equivalence, a margin is used. We aimed to identify the current methods used to determine non-inferiority or equivalence margins, as well as the main challenges and suggestions from trialists. METHODS: We developed an online questionnaire that included both closed and open-ended questions about methods to elicit non-inferiority or equivalence margins, underlying principles, and challenges and suggestions for improvement. We recruited trialists with experience of determining a margin by contacting corresponding authors for non-inferiority or equivalence trials. We used descriptive statistics and content analysis to identify categories in qualitative data. RESULTS: We had forty-one responses, all from non-inferiority trials. More than half of the trials were non-pharmacological (n = 21, 51%), and the most common primary outcome was clinical (n = 29, 71%). The two most used methods to determine the margin were as follows: a review of the evidence base (n = 27, 66%) and opinion seeking methods (n = 24, 59%). From those using reviews, the majority used systematic reviews or reviews of multiple RCTs to determine the margin (n = 17, 63%). From those using opinion seeking methods, the majority involved clinicians with or without other professionals (n = 19, 79%). Respondents reported that patients' opinions on the margin were sought in four trials (16%). Median confidence in overall quality of the margin was 5 out of 7 (maximum confidence); however, around a quarter of the respondents were "completely unconfident" that the margin reflected patient's views. We identified "stakeholder involvement" as the most common category to determine respondent's confidence in the quality of the margins and whether it reflected stakeholder's views. The most common suggestion to improve the definition of margins was "development of methods to involve stakeholders," and the most common challenge identified was "communication of margins." CONCLUSIONS: Responders highlighted the need for clearer guidelines on defining a margin, more and better stakeholder involvement in its selection, and better communication tools that enable discussions about non-inferiority trials with stakeholders. Future research should focus on developing best practice recommendations.

Methodological and reporting quality of non-inferiority randomized controlled trials comparing antifungal therapies: a systematic review.

BACKGROUND: Detailed reporting is essential in non-inferiority randomized controlled trials (NI-RCTs) to assess evidence quality, as these trials inform standards of care. OBJECTIVES: The primary objective was to evaluate the methodological and reporting quality of antifungal NI-RCTs. DATA SOURCES: Medline, EMBASE, the Cochrane CENTRAL and the United States Federal Drug Administration (FDA) drugs database were searched to 9 September 2020. STUDY ELIGIBILITY CRITERIA: NI-RCTs differing by antifungal formulation, type, dose, administration and/or duration were included. Articles were independently assessed in duplicate using quality indicators developed by the Consolidated Standards of Reporting Trials (CONSORT) group. PARTICIPANTS: Patients enrolled in antifungal trials for prophylactic and therapeutic use. METHODS: The Cochrane RoB 2.0 tool was used to assess risk of bias. Descriptive statistics were used; all statistical tests were two sided. RESULTS: Of 32 included studies, 22 (68.7%) did not justify the NIM. Handling of missing data was not described in 20 (62.5%). Intention-to-treat (ITT) and per-protocol (PP) analyses were both reported in 12/32 (37.5%) studies. Eleven of 32 studies (34.3%) reported potentially misleading conclusions. Industry-financed studies were more likely to report only the ITT analysis (n = 14/27, 51.9%). Methodological and reporting quality was unaffected by publication year; risk of bias from missing data changed over time. Overall risk of bias across included studies was moderate to high, with high risk in randomization process (n = 8/32, 25%), missing outcome data (n = 5/32, 15.6%), and selection of reported result (n = 9/32, 28.1%). CONCLUSIONS: Justification of the non-inferiority margin, reporting of ITT and PP analyses, missing data handling description, and ensuring conclusions are consistent with reported data is necessary to improve CONSORT adherence. Small sample size and overall risk of bias are study limitations. (Systematic Review Registration Number PROSPERO CRD42020219497).

Confidence interval of risk difference by different statistical methods and its impact on the study conclusion in antibiotic non-inferiority trials.

BACKGROUND: Numerous statistical methods can be used to calculate the confidence interval (CI) of risk differences. There is consensus in previous literature that the Wald method should be discouraged. We compared five statistical methods for estimating the CI of risk difference in terms of CI width and study conclusion in antibiotic non-inferiority trials. METHODS: In a secondary analysis of a systematic review, we included non-inferiority trials that compared different antibiotic regimens, reported risk differences for the primary outcome, and described the number of successes and/or failures as well as patients in each arm. For each study, we re-calculated the risk difference CI using the Wald, Agresti-Caffo, Newcombe, Miettinen-Nurminen, and skewness-corrected asymptotic score (SCAS) methods. The CIs by different statistical methods were compared in terms of CI width and conclusion on non-inferiority. A wider CI was considered to be more conservative. RESULTS: The analysis included 224 comparisons from 213 studies. The statistical method used to calculate CI was not reported in 134 (59.8%) cases. The median (interquartile range IQR) for CI width by Wald, Agresti-Caffo, Newcombe, Miettinen-Nurminen, and SCAS methods was 13.0% (10.8%, 17.4%), 13.3% (10.9%, 18.5%), 13.6% (11.1%, 18.9%), 13.6% (11.1% and 19.0%), and 13.4% (11.1%, 18.9%), respectively. In 216 comparisons that reported a non-inferiority margin, the conclusion on non-inferiority was the same across the five statistical methods in 211 (97.7%) cases. The differences in CI width were more in trials with a sample size of 100 or less in each group and treatment success rate above 90%. Of the 18 trials in this subgroup with a specified non-inferiority margin, non-inferiority was shown in 17 (94.4%), 16 (88.9%), 14 (77.8%), 14 (77.8%), and 15 (83.3%) cases based on CI by Wald, Agresti-Caffo, Newcombe, Miettinen-Nurminen, and SCAS methods, respectively. CONCLUSIONS: The statistical method used to calculate CI was not reported in the majority of antibiotic non-inferiority trials. Different statistical methods for CI resulted in different conclusions on non-inferiority in 2.3% cases. The differences in CI widths were highest in trials with a sample size of 100 or less in each group and a treatment success rate above 90%. TRIAL REGISTRATION: PROSPERO CRD42020165040 . April 28, 2020.

Subgroup discovery in non-inferiority trials.

Approaches and guidelines for performing subgroup analysis to assess heterogeneity of treatment effect in clinical trials have been the topic of numerous papers in the statistical and clinical literature, but have been discussed predominantly in the context of conventional superiority trials. Concerns about treatment heterogeneity are the same if not greater in non-inferiority (NI) trials, especially since overall similarity between two treatment arms in a successful NI trial could be due to the existence of qualitative interactions that are more likely when comparing two active therapies. Even in unsuccessful NI trials, subgroup analyses can yield important insights about the potential reasons for failure to demonstrate non-inferiority of the experimental therapy. Recent NI trials have performed a priori subgroup analyses using standard statistical tests for interaction, but there is increasing interest in more flexible machine learning approaches for post-hoc subgroup discovery. The performance and practical application of such methods in NI trials have not been systematically explored, however. We considered the Virtual Twin method for the NI setting, an algorithm for subgroup identification that combines random forest with classification and regression trees, and conducted extensive simulation studies to examine its performance under different NI trial conditions and to devise decision rules for selecting the final subgroups. We illustrate the utility of the method with data from a NI trial that was conducted to compare two acupuncture treatments for chronic musculoskeletal pain.

Intention-to-treat analysis may be more conservative than per protocol analysis in antibiotic non-inferiority trials: a systematic review.

BACKGROUND: In non-inferiority trials, there is a concern that intention-to-treat (ITT) analysis, by including participants who did not receive the planned interventions, may bias towards making the treatment and control arms look similar and lead to mistaken claims of non-inferiority. In contrast, per protocol (PP) analysis is viewed as less likely to make this mistake and therefore preferable in non-inferiority trials. In a systematic review of antibiotic non-inferiority trials, we compared ITT and PP analyses to determine which analysis was more conservative. METHODS: In a secondary analysis of a systematic review, we included non-inferiority trials that compared different antibiotic regimens, used absolute risk reduction (ARR) as the main outcome and reported both ITT and PP analyses. All estimates and confidence intervals (CIs) were oriented so that a negative ARR favored the control arm, and a positive ARR favored the treatment arm. We compared ITT to PP analyses results. The more conservative analysis between ITT and PP analyses was defined as the one having a more negative lower CI limit. RESULTS: The analysis included 164 comparisons from 154 studies. In terms of the ARR, ITT analysis yielded the more conservative point estimate and lower CI limit in 83 (50.6%) and 92 (56.1%) comparisons respectively. The lower CI limits in ITT analysis favored the control arm more than in PP analysis (median of - 7.5% vs. -6.9%, p = 0.0402). CIs were slightly wider in ITT analyses than in PP analyses (median of 13.3% vs. 12.4%, p < 0.0001). The median success rate was 89% (interquartile range IQR 82 to 93%) in the PP population and 44% (IQR 23 to 60%) in the patients who were included in the ITT population but excluded from the PP population (p < 0.0001). CONCLUSIONS: Contrary to common belief, ITT analysis was more conservative than PP analysis in the majority of antibiotic non-inferiority trials. The lower treatment success rate in the ITT analysis led to a larger variance and wider CI, resulting in a more conservative lower CI limit. ITT analysis should be mandatory and considered as either the primary or co-primary analysis for non-inferiority trials. TRIAL REGISTRATION: PROSPERO registration number CRD42020165040 .

Non-inferiority trials using a surrogate marker as the primary endpoint: An increasing phenotype in cardiovascular trials.

BACKGROUND/AIMS: Non-inferiority trials are increasing in cardiovascular medicine, with approval of many drugs and devices on the basis of such studies. Surrogate markers as primary endpoints have been also more frequently used for efficient assessment of cardiovascular interventions. However, there is uncertainty about their concordance with clinical outcomes. Non-inferiority design using a surrogate marker as a primary endpoint may pose particular challenges in clinical interpretation. We sought to explore the publication trends, methodology, and reporting features of non-inferiority cardiovascular trials that used a primary surrogate marker as the primary endpoint. METHODS: We searched six high-impact journals (The New England Journal of Medicine, The Journal of the American Medical Association, The Lancet, The Journal of the American College of Cardiology, Circulation, and European Heart Journal) from 1 January 1990 to 31 December 2018 and identified non-inferiority cardiovascular trials that used a surrogate marker as the primary endpoint. We assessed the non-inferiority margin reported in the manuscript and other publicly available platforms (e.g. protocol, clinicaltrials.gov). We also determined whether the included non-inferiority trials with surrogate markers as primary endpoints were followed by clinical outcome trials. RESULTS: We screened 15,553 publications and identified 247 cardiovascular trials that used a non-inferiority design. Of these, 37 had a surrogate marker as a primary endpoint (18 drug trials, 13 device trials, 6 others). All of these non-inferiority trials with surrogate outcomes were published after 2000, mostly in cardiology journals (13 in The Journal of the American College of Cardiology, 9 in European Heart Journal, 8 in Circulation, 6 in The Lancet, 1 in The New England Journal of Medicine), and their publication rate increased over time (p < 0.001 for linear trend). The median number of patients in the primary analysis was 300 (interquartile range: 202-465). The study protocol or a methods paper was publicly available for only 13 (35.1%) trials, of which the non-inferiority margin was not reported in 4 trials. In 16 studies (43.2%), the manuscript did not acknowledge the limitations of using a surrogate endpoint or the need for a definitive clinical outcome trial. Thirty-four trials (91.9%) concluded that the tested intervention met non-inferiority criteria. However, only five (13.5%) were followed by clinical outcomes trials the results of which did not always confirm non-inferiority. CONCLUSION: Non-inferiority trials that use a surrogate marker as the primary endpoint are being increasingly performed. However, these trials pose particular challenges with design, reporting, and interpretation, which are not systematically and consistently addressed or reported.

Overview of randomised controlled trials in orthopaedic research: search for significant findings.

BACKGROUND: The majority of recent orthopaedics randomised controlled trials (RCTs) have been non-inferiority trials with no significant clinical or statistical differences between treatment groups. The aim of this study was to evaluate randomised trials for significant findings in the orthopaedic literature based on the main elective procedures undertaken across different subspecialties. METHODS: We evaluated the following procedures: anterior cervical discectomy and fusion (ACDF), subacromial decompression (SAD), carpal tunnel decompression (CTD), total hip replacement (THR), anterior cruciate ligament reconstruction (ACLR), total knee replacement (TKR) and hallux valgus correction (HVC). Following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, we searched the Cochrane Central Register of Controlled Trials (CENTRAL, 2018, Issue 1), Ovid MEDLINE (1946 to 12 January 2018) and Embase (1980 to 12 January 2018). Trials that met our inclusion criteria were assessed using a binary outcome measure of whether they reported statistically significant findings. RESULTS: We included 1078 RCTs across seven most commonly performed elective procedures. Of those, only 16% (172/1078) reported significant findings [ACDF 26/77 (33.8%); SAD 2/22 (9%); CTD 11/72 (15.3%); THR 52/281 (18.5%); ACLR 21/239 (8.8%); TKR 55/357 (15.4%); HVC 5/30 (16.7%)]. The number of RCTs per year of publication has increased dramatically particularly since early 2000s-with over 100 RCTs of those seven procedures published in 2017 alone. CONCLUSIONS: This is the first study to undertake a comprehensive review of orthopaedic RCTs in elective practice. The number of RCTs in orthopaedic research is steadily increasing. However, only 16% of trials reports significant differences between interventions. CLINICAL RELEVANCE: For trials comparing different surgical techniques, this evidence provides treating surgeons with the flexibility to utilise available resources and infrastructure to deliver patients care without compromising clinical outcomes. Further, for trials comparing different treatment modalities, this study helps to inform the shared decision-making process when counselling patients on the effectiveness of surgical interventions.

Statistical considerations in the design and analysis of non-inferiority trials with binary endpoints in the presence of non-adherence: a simulation study.

Protocol non-adherence is common and poses unique challenges in the interpretation of trial outcomes, especially in non-inferiority trials. We performed simulations of a non-inferiority trial with a time-fixed treatment and a binary endpoint in order to: i) explore the impact of various patterns of non-adherence and analysis methods on treatment effect estimates; ii) quantify the probability of claiming non-inferiority when the experimental treatment effect is actually inferior; and iii) evaluate alternative methods such as inverse probability weighting and instrumental variable estimation. We found that the probability of concluding non-inferiority when the experimental treatment is actually inferior depends on whether non-adherence is due to confounding or non-confounding factors, and the actual treatments received by the non-adherent participants. With non-adherence, intention-to-treat analysis has a higher tendency to conclude non-inferiority when the experimental treatment is actually inferior under most patterns of non-adherence. This probability of concluding non-inferiority can be increased to as high as 0.1 from 0.025 when the adherence is relatively high at 90%. The direction of bias for the per-protocol analysis depends on the directions of influence the confounders have on adherence and probability of outcome. The inverse probability weighting approach can reduce bias but will only eliminate it if all confounders can be measured without error and are appropriately adjusted for. Instrumental variable estimation overcomes this limitation and gives unbiased estimates even when confounders are not known, but typically requires large sample sizes to achieve acceptable power. Investigators need to consider patterns of non-adherence and potential confounders in trial designs. Adjusted analysis of the per-protocol population with sensitivity analyses on confounders and other approaches, such as instrumental variable estimation, should be considered when non-compliance is anticipated. We provide an online power calculator allowing for various patterns of non-adherence using the above methods.

The limitations of equivalence and non-inferiority trials.

Equivalence and non-inferiority trials are becoming more and more popular. Typically, they compare the effects of a treatment of interest with the current gold-standard treatment as the comparator. However, for this approach, the definition of equivalence or non-inferiority margins (NIM) is crucial, and no clear rules for their definition exist. We criticized the practice of these trials of being over-inflationary in favor of (erroneous) equivalence, and we outlined our critique with some study examples comparing psychodynamic treatments with current first-line treatments for mental disorders. Here we answer to a commentary of Leichsenring et al. to our paper. Although focusing on our commentary, these authors are less arguing against our conclusions, but they address issues of study conduct, and lack of appreciation of our examples. However, the crucial question is: What is the risk of erroneous equivalence conclusions that we want to accept as responsible clinicians and scientists? We conclude that the scientific community has to define better and clearer criteria for NIMs. We do not believe that it is ethically justifiable to recommend a treatment that is 10 or 20% less effective than the current gold standard interventions.

Tamaño de muestra de protocolos clínicos.

El cálculo del tamaño de muestra en los protocolos clínicos que se revisan en el comité institucional del Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán tiene básicamente tres tipos de problemas: datos insuficientes para recalcular el tamaño de la muestra, uso de ecuaciones obsoletas que no toman en cuenta el error beta y uso de una ecuación que no corresponde al diseño del estudio. En este documento discutimos los cuatro datos que deben ser incluidos en los protocolos de los estudios clínicos aleatorizados que comparan medicamentos versus placebo en los estudios de superioridad y versus control activo en los estudios de no inferioridad.Sample size calculation in clinical protocols submitted to the review board of the Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán frequently has three types of problems: insufficient data for sample size recalculation, use of obsolete equations that do not take the beta error into account, and use of equations that do not correspond to the study design. In this document, we discuss the four data that should be included in the clinical protocols of randomized controlled trials that compare drugs versus placebo in superiority trials, and versus active controls in non-inferiority studies.

Exploring how non-inferiority and equivalence are assessed in paediatrics: a systematic review.

OBJECTIVE: To review characteristics, methodology and reporting of non-inferiority and equivalence trials in the specific context of paediatrics. DESIGN: PubMed and Cochrane databases were searched (up to September 2016) for non-inferiority/equivalence randomised controlled trials conducted in children published in high-impact-factor journals (>5.0 for general/specialist medical journals; >2.2 for paediatric journals). RESULTS: We found that the statistical hypothesis was inconsistent with the objective in 12 (10%) of the 125 reports included. Non-inferiority (n=98) and equivalence trials (n=27) were mostly used to evaluate interventions with easier administration (45%, n=54/120) and/or better safety profile (34%, n=41/120). All the data needed for targeted sample size recalculation were available for 39 reports (31%). The margin-representing the largest difference between arms that would be clinically acceptable-was reported in 119 (95%), and 44/119 (37%) reported the method used for margin determination. The median sample size was 268 (IQR 125-531). Margins were wider in smaller trials (<125 randomised patients) than in larger trials (p=0.04/p<0.01 for binary/continuous outcomes, respectively). We did not agree with the authors' conclusions in 11% (11/103) of the reports that provided sufficient information. CONCLUSIONS: There is still a need to improve the quality of methodology, reporting and interpretation of non-inferiority/equivalence trials in paediatrics. In particular, the margins were often not justified and the conclusion was often not supported by the design and/or the results. As researchers have to cope with small sample size and with lack of evidence, methods for non-inferiority/equivalence trials need to be used and/or developed in this vulnerable population.

Do non-inferiority trials of reduced intensity therapies show reduced effects? A descriptive analysis.

OBJECTIVES: To identify non-inferiority trials within a cohort where the experimental therapy is the same as the active control comparator but at a reduced intensity and determine if these non-inferiority trials of reduced intensity therapies have less favourable results than other non-inferiority trials in the cohort. Such a finding would provide suggestive evidence of biocreep in these trials. DESIGN: This metaresearch study used a cohort of non-inferiority trials published in the five highest impact general medical journals during a 5-year period. Data relating to the characteristics and results of the trials were abstracted. PRIMARY OUTCOME MEASURES: Proportions of trials with a declaration of superiority, non-inferiority and point estimates favouring the experimental therapy and mean absolute risk differences for trials with outcomes expressed as a proportion. RESULTS: Our search yielded 163 trials reporting 182 non-inferiority comparisons; 36 comparisons from 31 trials were between the same therapy at reduced and full intensity. Compared with trials not evaluating reduced intensity therapies, fewer comparisons of reduced intensity therapies demonstrated a favourable result (non-inferiority or superiority) (58.3%vs82.2%; P=0.002) and fewer demonstrated superiority (2.8%vs18.5%; P=0.019). Likewise, point estimates for reduced intensity therapies more often favoured active control than those for other trials (77.8%vs39.7%; P<0.001) as did mean absolute risk differences (+2.5% vs -0.7%; P=0.018). CONCLUSIONS: Non-inferiority trials comparing a therapy at reduced intensity to the same therapy at full intensity showed reduced effects compared with other non-inferiority trials. This suggests these trials may have a high rate of type 1 errors and biocreep, with significant implications for the design and interpretation of future non-inferiority trials.