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Lack of standardization of outcome measures limits the usefulness of clinical trial evidence to inform health care decisions. This can be addressed by agreeing on a minimum core set of outcome measures per health condition, containing measures relevant to patients and decision makers. Since 1992, the Outcome Measures in Rheumatology (OMERACT) consensus initiative has successfully developed core sets for many rheumatologic conditions, actively involving patients since 2002. Its expanding scope required an explicit formulation of its underlying conceptual framework and process. Literature searches and iterative consensus process (surveys and group meetings) of stakeholders including patients, health professionals, and methodologists within and outside rheumatology. To comprehensively sample patient-centered and intervention-specific outcomes, a framework emerged that comprises three core “Areas,” namely Death, Life Impact, and Pathophysiological Manifestations; and one strongly recommended Resource Use. Through literature review and consensus process, core set development for any specific health condition starts by identifying at least one core “Domain” within each of the Areas to formulate the “Core Domain Set.” Next, at least one applicable measurement instrument for each core Domain is identified to formulate a “Core Outcome Measurement Set.” Each instrument must prove to be truthful (valid), discriminative, and feasible. In 2012, 96% of the voting participants (n=125) at the OMERACT 11 consensus conference endorsed this model and process. The OMERACT Filter 2.0 explicitly describes a comprehensive conceptual framework and a recommended process to develop core outcome measurement sets for rheumatology likely to be useful as a template in other areas of health care.

The active-controlled trial with a non-inferiority design has gained popularity in recent years. However, non-inferiority trials present some methodological challenges, especially in determining the non-inferiority margin. Regulatory guidelines provide some general statements on how a non-inferiority trial should be conducted. Moreover, in a scientific advice procedure, regulators give companies the opportunity to discuss critical trial issues prior to the start of the trial. The aim of this study was to identify potential issues that may benefit from more explicit guidance by regulators. To achieve this, we collected and analyzed questions about non-inferiority trials posed by applicants for scientific advice in Europe in 2008 and 2009, as well as the responses given by the European Medicines Agency (EMA). In our analysis we included 156 final letters of advice from 2008 and 2009, addressed to 94 different applicants (manufacturers). Our analysis yielded two major findings: (1) applicants frequently asked questions 'whether' and 'how' to conduct a non-inferiority trial, 26% and 74%, respectively, and (2) the EMA regulators seem mainly concerned about the choice of the non-inferiority margin in non-inferiority trials (36% of total regulatory answers). In 40% of the answers, the EMA recommended using a stricter margin, and in 10% of the answers regarding non-inferiority margins, the EMA questioned the justification of the proposed non-inferiority margin. We conclude that there are still difficulties in selecting the appropriate methodology for non-inferiority trials. Straightforward and harmonized guidance regarding non-inferiority trials is required, for example on whether it is necessary to conduct such a trial and how the non-inferiority margin is determined. It is unlikely that regulatory guidelines can cover all therapeutic areas; therefore, in some cases regulatory scientific advice may be used as an opportunity for tailored advice.

Background While there is some consensus on methods for investigating statistical and methodological heterogeneity, little attention has been paid to clinical aspects of heterogeneity. The objective of this study is to summarize and collate suggested methods for investigating clinical heterogeneity in systematic reviews. Methods We searched databases (Medline, EMBASE, CINAHL, Cochrane Library, and CONSORT, to December 2010) and reference lists and contacted experts to identify resources providing suggestions for investigating clinical heterogeneity between controlled clinical trials included in systematic reviews. We extracted recommendations, assessed resources for risk of bias, and collated the recommendations. Results One hundred and one resources were collected, including narrative reviews, methodological reviews, statistical methods papers, and textbooks. These resources generally had a low risk of bias, but there was minimal consensus among them. Resources suggested that planned investigations of clinical heterogeneity should be made explicit in the protocol of the review; clinical experts should be included on the review team; a set of clinical covariates should be chosen considering variables from the participant level, intervention level, outcome level, research setting, or others unique to the research question; covariates should have a clear scientific rationale; there should be a sufficient number of trials per covariate; and results of any such investigations should be interpreted with caution. Conclusions Though the consensus was minimal, there were many recommendations in the literature for investigating clinical heterogeneity in systematic reviews. Formal recommendations for investigating clinical heterogeneity in systematic reviews of controlled trials are required.

Immunizations are speeding towards approval before clinical trials end, but scientists say this could complicate efforts to study long-term effects. Immunizations are speeding towards approval before clinical trials end, but scientists say this could complicate efforts to study long-term effects.

Background Multi-arm trials enable the evaluation of multiple treatments within a single trial. They provide a way of substantially increasing the efficiency of the clinical development process. However, since multi-arm trials test multiple hypotheses, some regulators require that a statistical correction be made to control the chance of making a type-1 error (false-positive). Several conflicting viewpoints are expressed in the literature regarding the circumstances in which a multiple-testing correction should be used. In this article we discuss these conflicting viewpoints and review the frequency with which correction methods are currently used in practice. Methods We identified all multi-arm clinical trials published in 2012 by four major medical journals. Summary data on several aspects of the trial design were extracted, including whether the trial was exploratory or confirmatory, whether a multiple-testing correction was applied and, if one was used, what type it was. Results We found that almost half (49%) of published multi-arm trials report using a multiple-testing correction. The percentage that corrected was higher for trials in which the experimental arms included multiple doses or regimens of the same treatments (67%). The percentage that corrected was higher in exploratory than confirmatory trials, although this is explained by a greater proportion of exploratory trials testing multiple doses and regimens of the same treatment. Conclusions A sizeable proportion of published multi-arm trials do not correct for multiple-testing. Clearer guidance about whether multiple-testing correction is needed for multi-arm trials that test separate treatments against a common control group is required.

The Affordable Care Act offers strong support for comparative effectiveness research, which entails comparisons among active treatments, to provide the foundation for evidence-based practice. Traditionally, a key form of research into the effectiveness of therapeutic treatments has been placebo-controlled trials, in which a specified treatment is compared to placebo. These trials feature high-contrast comparisons between treatments. Historical trends in placebo-controlled trials have been evaluated to help guide the comparative effectiveness research agenda. We investigated placebo-controlled trials reported in four leading medical journals between 1966 and 2010. We found that there was a significant decline in average effect size or average difference in efficacy (the ability to produce a desired effect) between the active treatment and placebo. On average, recently studied treatments offered only small benefits in efficacy over placebo. A decline in effect sizes in conventional placebo-controlled trials supports an increased emphasis on other avenues of research, including comparative studies on the safety, tolerability, and cost of treatments with established efficacy. [PUBLICATION ABSTRACT]

In phase II platform trials, 'many-to-one' comparisons are performed when K experimental treatments are compared with a common control to identify the most promising treatment(s) to be selected for Phase III trials. However, when sample sizes are limited, such as when the disease of interest is rare, only a single Phase II/III trial addressing both treatment selection and confirmatory efficacy testing may be feasible. In this paper, we suggest a two-step safety selection and testing procedure for such seamless trials. At the end of the study, treatments are first screened on the basis of safety, and those deemed to be sufficiently safe are then taken forwards for efficacy testing against a common control. All safety and efficacy evaluations are therefore performed at the end of the study, when for each patient all safety and efficacy data are available. If confirmatory conclusions are to be drawn from the trial, strict control of the family-wise error rate (FWER) is essential. However, to avoid unnecessary losses in power, no type I error rate should be \"wasted\" on comparisons which are no longer of interest because treatments have been dropped due to safety concerns. We investigate the impact on power and FWER control of multiplicity adjustments which correct efficacy tests only for the number of safe selected treatments instead of adjusting for all K null hypotheses the trial begins testing. We derive conditions under which strict control of the FWER can be achieved. Procedures using the estimated association between safety and efficacy outcomes are developed for the case when the correlation between endpoints is unknown. The operating characteristics of the proposed procedures are assessed via simulation.

Metabolic–bariatric surgery delivers substantial weight loss and can induce remission or improvement of obesity-related risks and complications. However, more robust estimates of its effect on long-term mortality and life expectancy—especially stratified by pre-existing diabetes status—are needed to guide policy and facilitate patient counselling. We compared long-term survival outcomes of severely obese patients who received metabolic–bariatric surgery versus usual care. We did a prespecified one-stage meta-analysis using patient-level survival data reconstructed from prospective controlled trials and high-quality matched cohort studies. We searched PubMed, Scopus, and MEDLINE (via Ovid) for randomised trials, prospective controlled studies, and matched cohort studies comparing all-cause mortality after metabolic–bariatric surgery versus non-surgical management of obesity published between inception and Feb 3, 2021. We also searched grey literature by reviewing bibliographies of included studies as well as review articles. Shared-frailty (ie, random-effects) and stratified Cox models were fitted to compare all-cause mortality of adults with obesity who underwent metabolic–bariatric surgery compared with matched controls who received usual care, taking into account clustering of participants at the study level. We also computed numbers needed to treat, and extrapolated life expectancy using Gompertz proportional-hazards modelling. The study protocol is prospectively registered on PROSPERO, number CRD42020218472. Among 1470 articles identified, 16 matched cohort studies and one prospective controlled trial were included in the analysis. 7712 deaths occurred during 1·2 million patient-years. In the overall population consisting 174 772 participants, metabolic–bariatric surgery was associated with a reduction in hazard rate of death of 49·2% (95% CI 46·3–51·9, p<0·0001) and median life expectancy was 6·1 years (95% CI 5·2–6·9) longer than usual care. In subgroup analyses, both individuals with (hazard ratio 0·409, 95% CI 0·370–0·453, p<0·0001) or without (0·704, 0·588–0·843, p<0·0001) baseline diabetes who underwent metabolic–bariatric surgery had lower rates of all-cause mortality, but the treatment effect was considerably greater for those with diabetes (between-subgroup I2 95·7%, p<0·0001). Median life expectancy was 9·3 years (95% CI 7·1–11·8) longer for patients with diabetes in the surgery group than the non-surgical group, whereas the life expectancy gain was 5·1 years (2·0–9·3) for patients without diabetes. The numbers needed to treat to prevent one additional death over a 10-year time frame were 8·4 (95% CI 7·8–9·1) for adults with diabetes and 29·8 (21·2–56·8) for those without diabetes. Treatment effects did not appear to differ between gastric bypass, banding, and sleeve gastrectomy (I2 3·4%, p=0·36). By leveraging the results of this meta-analysis and other published data, we estimated that every 1·0% increase in metabolic–bariatric surgery utilisation rates among the global pool of metabolic–bariatric candidates with and without diabetes could yield 5·1 million and 6·6 million potential life-years, respectively. Among adults with obesity, metabolic–bariatric surgery is associated with substantially lower all-cause mortality rates and longer life expectancy than usual obesity management. Survival benefits are much more pronounced for people with pre-existing diabetes than those without. None.

After the introduction of selective serotonin reuptake inhibitors (SSRIs), other newer antidepressants with different mechanisms of action have been introduced in clinical practice. Because antidepressants are commonly prescribed in combination with other medications used to treat co-morbid psychiatric or somatic disorders, they are likely to be involved in clinically significant drug interactions. This review examines the drug interaction profiles of the following newer antidepressants: escitalopram, venlafaxine, desvenlafaxine, duloxetine, milnacipran, mirtazapine, reboxetine, bupropion, agomelatine and vilazodone. In general, by virtue of a more selective mechanism of action and receptor profile, newer antidepressants carry a relatively low risk for pharmacodynamic drug interactions, at least as compared with first-generation antidepressants, i.e. monoamine oxidase inhibitors (MAOIs) and tricyclic antidepressants (TCAs). On the other hand, they are susceptible to pharmacokinetic drug interactions. All new antidepressants are extensively metabolized in the liver by cytochrome P450 (CYP) isoenzymes, and therefore may be the target of metabolically based drug interactions. Concomitant administration of inhibitors or inducers of the CYP isoenzymes involved in the biotransformation of specific antidepressants may cause changes in their plasma concentrations. However, due to their relatively wide margin of safety, the consequences of such kinetic modifications are usually not clinically relevant. Conversely, some newer antidepressants may cause pharmacokinetic interactions through their ability to inhibit specific CYPs. With regard to this, duloxetine and bupropion are moderate inhibitors of CYP2D6. Therefore, potentially harmful drug interactions may occur when they are coadministered with substrates of these isoforms, especially compounds with a narrow therapeutic index. The other new antidepressants are only weak inhibitors or are not inhibitors of CYP isoforms at usual therapeutic concentrations and are not expected to affect the disposition of concomitantly administered medications. Although drug interactions with newer antidepressants are potentially, but rarely, clinically significant, the use of antidepressants with a more favourable drug interaction profile is advisable. Knowledge of the interaction potential of individual antidepressants is essential for safe prescribing and may help clinicians to predict and eventually avoid certain drug combinations.

Interval training (IT) may induce physiological adaptations superior to those achieved with conventional moderate-intensity continuous training (MCT) in patients with coronary artery disease (CAD). Our objectives were (1) to systematically review studies which have prescribed IT in CAD, (2) to summarize the findings of this research including the safety and physiological benefits of IT, and (3) to identify areas for further investigation. A systematic review of the literature using computerized databases was performed. The search yielded two controlled trials and five randomized controlled trials (RCTs) enrolling 213 participants. IT prescribed in isolation or in combination with resistance training was shown to induce significant and clinically important physiological adaptations in cardiac patients. IT was also shown to improve cardiorespiratory fitness (e.g. V O 2max , V O 2AT ), endothelial function, left ventricle morphology and function (e.g. ejection fraction) to a significantly greater extent when compared with conventional MCT. No adverse cardiac or other life-threatening events occurred secondary to exercise participation in these studies. However, these findings must be interpreted with caution, as methodological limitations were present in all trials reviewed. In conclusion, robustly designed RCTs with thorough and standardized reporting are required to determine the risk and benefits of IT in the broader cardiac patient population. Further research is required to determine optimal IT protocols for the use in cardiac rehabilitation programmes, potentially contributing to novel exercise prescription guidelines for this patient population.