Subgroup analysis and other (mis)uses of baseline data in clinical trials

The effectiveness of a nurse-led exercise and health education informatics program on exercise capacity and quality of life among cancer survivors after esophagectomy: A randomized controlled trial

BACKGROUND

Esophagectomy is the primary surgical treatment for esophageal cancer. However, patients often experience a decrease in physical activity, poor nutrition, and a reduction in quality of life following surgery.

OBJECTIVES

The aim of this study was to examine the effects of an exercise and nursing education health informatics program on quality of life, exercise capacity, and nutrition among patients following esophagectomy for esophageal cancer.

DESIGN

A randomized controlled trial.

SETTINGS AND METHODS

Patients who had undergone an esophagectomy for cancer were recruited by purposive sampling from a medical center in Taiwan. Patients who met inclusion criteria and agreed to participate (N = 88) were randomly assigned to an exercise informatics program (intervention group, n = 44) or usual post-surgery care (control group, n = 44). Quality of life was assessed at baseline and 1, 3, and 6 months after discharge. Secondary outcomes of nutrition (albumin, body mass index), and exercise capacity (maximal oxygen uptake, the six-minute walking test) were conducted at baseline and 3 months following discharge. Differences in quality of life, nutrition and exercise capacity between the two groups were analyzed using generalized estimating equations.

RESULTS

Analysis demonstrated significant improvements in outcome measures following hospital discharge for the intervention group compared to controls. Measures of quality of life were significantly better for the intervention group and varied with time following discharge. Functional scores for physical (1 and 3 months), role (1, 3, and 6 months), emotional (1 month), social (3 months) and global health (3 months) were significantly higher than controls. Cancer-related subscales improved for insomnia (1 and 3 months) and nausea/vomiting (3 and 6 months). Esophageal cancer-specific symptoms improved for dry mouth (1 month), dysphagia (3 months), and loss of taste (1 and 6 months). Three months following discharge, levels of albumin were significantly higher for the intervention group compared to controls (β=0.32, 95% CI 0.09, 0.54, p < .01); body mass index did not differ between groups. Exercise capacity was also significantly better; the intervention group had higher maximal oxygen consumption (β=2.61, 95% CI 1.54, 3.69, p < .001) and greater distance on the six-minute walking test (β=83.30, 95% CI 52.60, 113.99, p < .001).

CONCLUSION

The intervention group experienced significant improvements in nutrition, exercise capacity, and variables related to quality of life. These findings suggest a nurse-led exercise and health education informatics program should be implemented for survivors of esophagectomy prior to hospital discharge.

Guidance from key organisations on exploring, confirming and interpreting subgroup effects of medical treatments: a scoping review

OBJECTIVES

With the increasing interest in personalised medicine, the use of subgroup analyses is likely to increase. Subgroup analyses are challenging and often misused, possibly leading to false interpretations of the effect. It remains unclear to what extent key organisations warn for such pitfalls and translate current methodological research to detect these effects into research guidelines. The aim of this scoping review is to determine and evaluate the current guidance used by organisations for exploring, confirming and interpreting subgroup effects.

DESIGN

Scoping review.

ELIGIBILITY CRITERIA

We identified four types of key stakeholder organisations: industry, health technology assessment organisations (HTA), academic/non-profit research organisations and regulatory bodies. After literature search and expert consultation, we identified international and national organisations of each type. For each organisation that was identified, we searched for official research guidance documents and contacted the organisation for additional guidance.

RESULTS

Twenty-seven (45%) of the 60 organisations that we included had relevant research guidance documents. We observed large differences between organisation types: 18% (n=2) of the industry organisations, 64% (n=9) of the HTA organisations, 38% (n=8) of academic/non-profit research organisations and 57% (n=8) of regulatory bodies provided guidance documents. The majority of the documents (n=33, 63%) mentioned one or more challenges in subgroup analyses, such as false positive findings or ecological bias with variations across the organisation types. Statistical recommendations were less common (n=19, 37%) and often limited to a formal test of interaction.

CONCLUSIONS

Almost half of the organisations included in this scoping review provided guidance on subgroup effect research in their guidelines. However, there were large differences between organisations in the amount and level of detail of their guidance. Effort is required to translate and integrate research findings on subgroup analysis to practical guidelines for decision making and to reduce the differences between organisations and organisation types.

Bayesian adaptive randomization trial of intravenous ketamine for veterans with late-life, treatment-resistant depression

More than eleven million U.S. Veterans are at least 65 years of age, an age group of which almost 20% suffers from clinically significant depressive symptoms. Available pharmacological treatments are suboptimal for patients, including veterans, with late-life depression. Ketamine has emerged as a potentially promising rapid-acting therapy for treatment-resistant depression (TRD). However, few studies have examined the safety, tolerability and efficacy of ketamine therapy for older adults with late-life TRD (LL-TRD). This study uses an adaptive randomization design to test the safety, tolerability, efficacy, and durability of three distinct, single sub-anesthetic doses of intravenous (IV) ketamine versus a single dose of active placebo (midazolam) in older depressed veterans. As the study progresses, Bayesian adaptive randomization recalibrates randomization ratios to allocate more participants to conditions demonstrating greater promise and fewer participants to conditions with less promise. Secondary analyses explore clinical and biological moderating and mediating factors of rapid treatment response. Results are expected to inform both the viability of ketamine treatment and optimal dosing strategies for patients with LL-TRD.

IMI - Clinical Myopia Control Trials and Instrumentation Report

The evidence-basis based on existing myopia control trials along with the supporting academic literature were reviewed; this informed recommendations on the outcomes suggested from clinical trials aimed at slowing myopia progression to show the effectiveness of treatments and the impact on patients. These outcomes were classified as primary (refractive error and/or axial length), secondary (patient reported outcomes and treatment compliance), and exploratory (peripheral refraction, accommodative changes, ocular alignment, pupil size, outdoor activity/lighting levels, anterior and posterior segment imaging, and tissue biomechanics). The currently available instrumentation, which the literature has shown to best achieve the primary and secondary outcomes, was reviewed and critiqued. Issues relating to study design and patient selection were also identified. These findings and consensus from the International Myopia Institute members led to final recommendations to inform future instrumentation development and to guide clinical trial protocols.

Understanding of interaction (subgroup) analysis in clinical trials

BACKGROUND

When the treatment effect on the outcome of interest is influenced by a baseline/demographic factor, investigators say that an interaction is present. In randomized clinical trials (RCTs), this type of analysis is typically referred to as subgroup analysis. Although interaction (or subgroup) analyses are usually stated as a secondary study objective, it is not uncommon that these results lead to changes in treatment protocols or even modify public health policies. Nonetheless, recent reviews have indicated that their proper assessment, interpretation and reporting remain challenging.

RESULTS

Therefore, this article provides an overview of these challenges, to help investigators find the best strategy for application of interaction analyses on binary outcomes in RCTs. Specifically, we discuss the key points of formal interaction testing, including the estimation of both additive and multiplicative interaction effects. We also provide recommendations that, if adhered to, could increase the clarity and the completeness of reports of RCTs.

CONCLUSION

Altogether, this article provides a brief non-statistical guide for clinical investigators on how to perform, interpret and report interaction (subgroup) analyses in RCTs.

Baseline resting heart rate variability predicts post-traumatic stress disorder treatment outcomes in adults with co-occurring substance use disorders and post-traumatic stress

Post-traumatic stress disorder (PTSD) symptoms are highly prevalent among individuals with substance use disorders (SUD), presenting a difficult-to-treat, complex comorbidity. Prognostic factors for treatment outcomes may characterize heterogeneity of the treated population and/or implicate mechanisms of action that are salient for improving treatments. High frequency heart rate variability (HF-HRV) is a suggested biomarker for emotion regulation-the ability to generate appropriate emotional responses via the influence of the parasympathetic nervous system on the heart. This initial study investigated the utility of baseline resting HF-HRV for predicting PTSD symptoms and substance use outcomes following treatment of 37 SUD participants with comorbid PTSD symptoms. Participants completed either standard cognitive- behavioral therapy (CBT) for SUD or a novel treatment of integrated post-traumatic stress and substance use that combined CBT for SUD with cognitive processing therapy for PTSD. Analyses demonstrated that higher HF-HRV predicted greater reduction in PTSD symptoms following both types of treatment. This suggests prognostic value of HF-HRV as a predictor of PTSD treatment outcomes; those with poorer autonomic emotional regulation may not respond as well to psychotherapy in general. This hypothesis-generating analysis identifies a putative biomarker that might have utility in treatment prediction.

Approaches to treatment effect heterogeneity in the presence of confounding

The literature on causal effect estimation tends to focus on the population mean estimand, which is less informative as medical treatments are becoming more personalized and there is increasing awareness that subpopulations of individuals may experience a group-specific effect that differs from the population average. In fact, it is possible that there is underlying systematic effect heterogeneity that is obscured by focusing on the population mean estimand. In this context, understanding which covariates contribute to this treatment effect heterogeneity (TEH) and how these covariates determine the differential treatment effect (TE) is an important consideration. Towards such an understanding, this paper briefly reviews three approaches used in making causal inferences and conducts a simulation study to compare these approaches according to their performance in an exploratory evaluation of TEH when the heterogeneous subgroups are not known a priori. Performance metrics include the detection of any heterogeneity, the identification and characterization of heterogeneous subgroups, and unconfounded estimation of the TE within subgroups. The methods are then deployed in a comparative effectiveness evaluation of drug-eluting versus bare-metal stents among 54 099 Medicare beneficiaries in the continental United States admitted to a hospital with acute myocardial infarction in 2008.

A Pilot Randomized Controlled Trial of a Web-Based Growth Mindset Intervention to Enhance the Effectiveness of a Smartphone App for Smoking Cessation

BACKGROUND

Although smartphone apps have shown promise for smoking cessation, there is a need to enhance their low engagement rates. This study evaluated the application of the growth mindset theory, which has demonstrated the potential to improve persistence in behavior change in other domains, as a means to improve engagement and cessation.

OBJECTIVE

This study aimed to explore the feasibility, utility, and efficacy of a Web-based growth mindset intervention for addiction when used alongside a smoking cessation app.

METHODS

Daily smokers (N=398) were all recruited on the Web and randomly assigned to receive either a cessation app alone or the app plus a Web-delivered growth mindset intervention. The primary outcome was engagement, that is, the number of log-ins to the smoking cessation app. The secondary outcome was 30-day point prevalence abstinence at 2-month follow-up collected through a Web-based survey.

RESULTS

The 2-month outcome data retention rate was 91.5% (364/398). In addition, 77.9% (310/398) of the participants in the experimental arm viewed at least 1 page of their growth mindset intervention, and 21.1% (84/398) of the group viewed all the growth mindset intervention. The intention-to-treat analysis did not show statistically significant differences between the experimental and comparison arms on log-ins to the app (19.46 vs 21.61; P=.38). The experimental arm had cessation rates, which trended higher than the comparison arm (17% vs 13%; P=.10). The modified intent-to-treat analysis, including only participants who used their assigned intervention at least once (n=115 in experimental group and n=151 in the control group), showed that the experimental arm had a similar number of log-ins (32.31 vs 28.48; P=.55) but significantly higher cessation rates (21% vs 13%; P=.03) than the comparison arm.

CONCLUSIONS

A growth mindset intervention for addiction did not increase engagement rates, although it may increase cessation rates when used alongside a smartphone app for smoking cessation. Future research is required to refine the intervention and assess efficacy with long-term follow-up to evaluate the efficacy of the mindset intervention.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03174730; https://clinicaltrials.gov/ct2/show/NCT03174730.

Impact of mobile health applications on self-management in patients with type 2 diabetes mellitus: protocol of a systematic review

INTRODUCTION

The emergence of mobile health (mHealth) solutions, particularly mHealth applications (apps), has shown promise in self-management of chronic diseases including type 2 diabetes mellitus (T2DM). While majority of the previous systematic reviews have focused on the effectiveness of mHealth apps in improving treatment outcomes in patients with T2DM, there is a need to also understand how mHealth apps influence self-management of T2DM. This is crucial to ensure improvement in the design and use of mHealth apps for T2DM. This protocol describes how a systematic review will be conducted to determine in which way(s) mHealth apps might impact on self-management of T2DM.

METHODS

The following electronic databases will be searched from inception to April 2019: PubMed, MEDLINE, EMBASE, Global Health, PsycINFO, CINAHL, The Cochrane Central Register of Controlled Trials, Scopus, Web of Science, ProQuest Dissertations & Theses Global, Health Management Information Consortium database, Google Scholar and ClinicalTrials.gov. The Cochrane risk of bias tool will be used to assess methodological quality. The primary outcome measures to be assessed will be 'change in blood glucose'. The secondary outcomes measures will be 'changes in cardiovascular risk markers' (including blood pressure, body mass index and blood lipids), and self-management practices. Others will include: health-related quality of life, economic data, social support, harms (eg, death or complications leading to hospital admissions or emergency unit attendances), death from any cause, anxiety or depression and adverse events (eg, hypoglycaemic episodes).

ETHICS AND DISSEMINATION

This study will not involve the collection of primary data and will not require ethical approval. The review will be published in a peer-reviewed journal and a one-page summary of the findings will be shared with relevant organisations. Presentation of findings will be made at appropriate conferences.

TRIAL REGISTRATION NUMBER

CRD42017071106.

A Simulation Study Comparing Different Statistical Approaches for the Identification of Predictive Biomarkers

Identification of relevant biomarkers that are associated with a treatment effect is one requirement for adequate treatment stratification and consequently to improve health care by administering the best available treatment to an individual patient. Various statistical approaches were proposed that allow assessing the interaction between a continuous covariate and treatment. Nevertheless, categorization of a continuous covariate, e.g., by splitting the data at the observed median value, appears to be very prevalent in practice. In this article, we present a simulation study considering data as observed in a randomized clinical trial with a time-to-event outcome performed to compare properties of such approaches, namely, Cox regression with linear interaction, Multivariable Fractional Polynomials for Interaction (MFPI), Local Partial-Likelihood Bootstrap (LPLB), and the Subpopulation Treatment Effect Pattern Plot (STEPP) method, and of strategies based on categorization of continuous covariates (splitting the covariate at the median, splitting at quartiles, and using an "optimal" split by maximizing a corresponding test statistic). In different scenarios with no interactions, linear interactions or nonlinear interactions, type I error probability and the power for detection of a true covariate-treatment interaction were estimated. The Cox regression approach was more efficient than the other methods for scenarios with monotonous interactions, especially when the number of observed events was small to moderate. When patterns of the biomarker-treatment interaction effect were more complex, MFPI and LPLB performed well compared to the other approaches. Categorization of data generally led to a loss of power, but for very complex patterns, splitting the data into multiple categories might help to explore the nature of the interaction effect. Consequently, we recommend application of statistical methods developed for assessment of interactions between continuous biomarkers and treatment instead of arbitrary or data-driven categorization of continuous covariates.

A systematic survey identified 36 criteria for assessing effect modification claims in randomized trials or meta-analyses

OBJECTIVE

The objective of the study was to systematically survey the methodological literature and collect suggested criteria for assessing the credibility of effect modification and associated rationales.

STUDY DESIGN AND SETTING

We searched MEDLINE, Embase, and WorldCat up to March 2018 for publications providing guidance for assessing the credibility of effect modification identified in randomized trials or meta-analyses. Teams of two investigators independently identified eligible publications and extracted credibility criteria and authors' rationale, reaching consensus through discussion. We created a taxonomy of criteria that we iteratively refined during data abstraction.

RESULTS

We identified 150 eligible publications that provided 36 criteria and associated rationales. Frequent criteria included significant test for interaction (n = 54), a priori hypothesis (n = 49), providing a causal explanation (n = 47), accounting for multiplicity (n = 45), testing a small number of effect modifiers (n = 38), and prespecification of analytic details (n = 39). For some criteria, we found more than one rationale; some criteria were connected through a common rationale. For some criteria, experts disagreed regarding their suitability (e.g., added value of stratified randomization; trustworthiness of biologic rationales).

CONCLUSION

Methodologists have expended substantial intellectual energy providing criteria for critical appraisal of apparent effect modification. Our survey highlights popular criteria, expert agreement and disagreement, and where more work is needed, including testing criteria in practice.

Baseline testing in cluster randomised controlled trials: should this be done?

BACKGROUND

Comparisons of baseline covariates in randomised controlled trials whilst often undertaken is regarded by many as an exercise in futility. Because of randomisation the null hypothesis is true for baseline comparisons and therefore any differences will occur by chance. However, this is only the case if allocations are not known in advance of recruitment. If this occurs then selection bias at randomisation may be present and it is possible that the statistical testing of covariates may unveil selection bias. In this paper we show that this is particularly the case for cluster randomised trials when post-randomised recruitment often occurs and can lead to selection bias.

MAIN TEXT

We take a recently published cluster randomised trial that has suffered from selection bias due to differential recruitment and calculate baseline p values. We show that statistically significant imbalances of p < 0.0001 occurred in 5 of the 10 covariates. In comparison for an individually randomised trial that had no evidence of selection bias only 1 p value of p < 0.05 out of 20 tests was observed. Had baseline p values for the cluster trial been presented to journal editors, reviewers and readers then the results of the trial might have been treated with more caution.

CONCLUSION

We argue that the blanket ban of baseline testing as advocated by some may reduce the chance of identifying deficient cluster randomised trials and this opposition should be reconsidered for cluster trials.

Effects of valsartan, benazepril and their combination in overt nephropathy of type 2 diabetes: A prospective, randomized, controlled trial

AIMS

To evaluate whether angiotensin-converting enzyme (ACE) inhibitor and angiotensin II receptor blocker (ARB) combination therapy is more nephroprotective than ACE inhibitor or ARB monotherapy in people with type 2 diabetes and overt nephropathy.

MATERIALS AND METHODS

In this prospective, randomized, open, blind-endpoint phase III trial sponsored by the Italian Drug Agency, 103 consenting patients with type 2 diabetes, aged >40 years, with serum creatinine levels 159 to 309 μmol/L, spot morning urinary albumin-creatinine ratio > 1000 mg/g (or > 500 mg/g in those on ACE inhibitor or ARB therapy at inclusion) were stratified by centre and randomized to 4.5-year treatment with valsartan 320 mg/d (n = 36), benazepril 20 mg/d (n = 34) or halved doses of both medications (n = 33). The primary endpoint was end-stage renal disease (ESRD). Modified intention-to-treat analyses were performed.

RESULTS

Recruitment took place between June 2007 and February 2013 at 10 centres in Italy and one in Slovenia. A total of 77 participants completed the study and 26 were prematurely withdrawn. During a median (interquartile range) of 41 (18-54) months, 12 participants on benazepril (35.3%) and nine on combination therapy (27.3%) progressed to ESRD, versus five on valsartan (13.9%). Differences between benazepril (hazard ratio [HR] 3.59, 95% confidence interval [CI] 1.25-10.30; P = 0.018) or combination therapy (HR 3.28, 95% CI 1.07-10.0; P = 0.038) and valsartan were significant, even after adjustment for age, gender and baseline serum creatinine, systolic blood pressure and 24-hour proteinuria (HR 5.16, 95% CI 1.50-17.75, P = 0.009 and HR 4.75, 95% CI 1.01-22.39, P = 0.049, respectively). Adverse events were distributed similarly among the groups.

CONCLUSIONS

In people with type 2 diabetes with nephropathy, valsartan (320 mg/d) safely postponed ESRD more effectively than benazepril (20 mg/d) or than halved doses of both medications.

Evaluation of dental trials comparing baseline differences using p values

INTRODUCTION

Significance testing for comparison of the baseline differences between the intervention arms has received a strong condemnation. The goal of this study was to assess the prevalence of randomized controlled trials (RCTs) comparing the baseline characteristics between intervention groups using significance tests in top ten impact factor dental journals.

MATERIALS AND METHODS

RCTs published in 10 high impact factor dental journals were searched in PubMed database. Literature search was limited to time duration of 5 years from September 2012 to August 2017.

RESULTS

We analysed 521 RCTs after excluding 47 non-RCT articles from the total of 568 articles. Baseline demographic characteristics table was not reported in 45.9% of the RCTs and 26.2% of the RCTs did not report table of baseline clinical characteristics. In 38.9% of the studies, significance testing was employed to compare baseline differences between the intervention arms.

CONCLUSIONS

Many trials published in the reputed dental journals failed to follow the recommendations of CONSORT statement regarding reporting of baseline tables and avoiding comparison of baseline differences with significance test.

Protocol for a quasi-experimental study of the effectiveness and cost-effectiveness of mother and baby units compared with general psychiatric inpatient wards and crisis resolution team services (The ESMI study) in the provision of care for women in the postpartum period

INTRODUCTION

Research into what constitutes the best and most effective care for women with an acute severe postpartum mental disorder is lacking. The effectiveness and cost-effectiveness of psychiatric mother and baby units (MBUs) has not been investigated systematically and there has been no direct comparison of the outcomes of mothers and infants admitted to these units, compared with those accessing generic acute psychiatric wards or crisis resolution teams (CRTs). Our primary hypothesis is that women with an acute psychiatric disorder, in the first year after giving birth, admitted to MBUs are significantly less likely to be readmitted to acute care (an MBU, CRTs or generic acute ward) in the year following discharge than women admitted to generic acute wards or cared for by CRTs.

METHODS AND ANALYSIS

Quasi-experimental study of women accessing different types of acute psychiatric services in the first year after childbirth. Analysis of the primary outcome will be compared across the three service types, at 1-year postdischarge. Cost-effectiveness will be compared across the three service types, at 1-month and 1-year postdischarge; explored in terms of quality-adjusted life years. Secondary outcomes include unmet needs, service satisfaction, maternal adjustment, quality of mother-infant interaction. Outcomes will be analysed using propensity scoring to account for systematic differences between MBU and non-MBU participants. Analyses will take place separately within strata, defined by the propensity score, and estimates pooled to produce an average treatment effect with weights to account for cohort attrition.

ETHICS AND DISSEMINATION

The study has National Health Service (NHS) Ethics Approval and NHS Trust Research and Development approvals. The study has produced protocols on safeguarding maternal/child welfare. With input from our lived experience group, we have developed a dissemination strategy for academics/policy-makers/public.

Using Bayesian modeling in frequentist adaptive enrichment designs

Our increased understanding of the mechanistic heterogeneity of diseases has pushed the development of targeted therapeutics. We do not expect all patients with a given disease to benefit from a targeted drug; only those in the target population. That is, those with sufficient dysregulation in the biomolecular pathway targeted by treatment. However, due to complexity of the pathway, and/or technical issues with our characterizing assay, it is often hard to characterize the target population until well into large-scale clinical trials. This has stimulated the development of adaptive enrichment trials; clinical trials in which the target population is adaptively learned; and enrollment criteria are adaptively updated to reflect this growing understanding. This paper proposes a framework for group-sequential adaptive enrichment trials. Building on the work of Simon & Simon (2013). Adaptive enrichment designs for clinical trials. Biostatistics 14(4), 613-625), it includes a frequentist hypothesis test at the end of the trial. However, it uses Bayesian methods to optimize the decisions required during the trial (regarding how to restrict enrollment) and Bayesian methods to estimate effect size, and characterize the target population at the end of the trial. This joint frequentist/Bayesian design combines the power of Bayesian methods for decision making with the use of a formal hypothesis test at the end of the trial to preserve the studywise probability of a type I error.

Efficient design and analysis of randomized controlled trials in rare neurological diseases: An example in Guillain-Barré syndrome

BACKGROUND

Randomized controlled trials (RCTs) pose specific challenges in rare and heterogeneous neurological diseases due to the small numbers of patients and heterogeneity in disease course. Two analytical approaches have been proposed to optimally handle these issues in RCTs: covariate adjustment and ordinal analysis. We investigated the potential gain in efficiency of these approaches in rare and heterogeneous neurological diseases, using Guillain-Barré syndrome (GBS) as an example.

METHODS

We analyzed two published GBS trials with primary outcome 'at least one grade improvement' on the GBS disability scale. We estimated the treatment effect using logistic regression models with and without adjustment for prognostic factors. The difference between the unadjusted and adjusted estimates was disentangled in imbalance (random differences in baseline covariates between treatment arms) and stratification (change of the estimate due to covariate adjustment). Second, we applied proportional odds regression, which exploits the ordinal nature of the GBS disability score. The standard error of the estimated treatment effect indicated the statistical efficiency.

RESULTS

Both trials were slightly imbalanced with respect to baseline characteristics, which was corrected in the adjusted analysis. Covariate adjustment increased the estimated treatment effect in the two trials by 8% and 18% respectively. Proportional odds analysis resulted in lower standard errors indicating more statistical power.

CONCLUSION

Covariate adjustment and proportional odds analysis most efficiently use the available data and ensure balance between the treatment arms to obtain reliable and valid treatment effect estimates. These approaches merit application in future trials in rare and heterogeneous neurological diseases like GBS.

The effect of individual and mixed rewards on diabetes management: A feasibility randomized controlled trial

Background: Incentives play a role in introducing health-related benefits, but no interventions using mixed incentives, i.e. a combination of individual and group incentives, have been tested in individuals with type 2 diabetes mellitus (T2DM). We evaluated the feasibility of implementing individual- and mixed-incentives, with and without a supportive partner, on glycated haemoglobin (HbA1c) control and weight loss among patients with T2DM. Methods: This is a feasibility, sex-stratified, single-blinded, randomized controlled study in individuals with T2DM. All participants received diabetes education and tailored goal setting for weight and glycated haemoglobin (HbA1c). Participants were randomly assigned into three arms: individual incentives (Arm 1), mixed incentives-altruism (Arm 2), and mixed incentives-cooperation (Arm 3). Participants were accompanied by a diabetes educator every other week to monitor targets, and the intervention period lasted 3 months. The primary outcome was the change in HbA1c at 3 months from baseline. Weight and change body mass index (BMI) were considered as secondary outcomes. Results: Out of 783 patients screened, a total of 54 participants, 18 per study arm, were enrolled and 44 (82%) completed the 3-month follow-up. Mean baseline HbA1c values were 8.5%, 7.9% and 8.2% in Arm 1, Arm 2, and Arm 3, respectively. At 3 months, participants in all three study arms showed reductions in HbA1c ranging from -0.9% in Arm 2 to -1.4% in Arm 1. Weight and BMI also showed reductions. Conclusions: Individual and mixed cash incentives show important reductions in HbA1c, weight and BMI in patients with type 2 diabetes mellitus after 3 months.  Recruitment and uptake of the intervention were successfully accomplished demonstrating feasibility to conduct larger effectiveness studies to test individual and mixed economic incentives for diabetes management. Registration: ClinicalTrials.gov Identifier NCT02891382.

Assessing the Evidence in Evidence-Based Medicine

Evidence-based medicine (EBM) has become a fixture in today's medical practice. Evidence consists of memorialized observations and should be contrasted with dogmatic pronouncements and/or hypotheses. Evidence has varying degrees of reliability. The randomized clinical trial (RCT) or a systematic review of RCTs is accorded the highest level of credibility and expert opinion the lowest. This ranking reflects the internal validity (degree to which factors in the study interfere with the gathering or interpretation of the observations) of the study design; more valid designs are more credible. The provision of healthcare requires an almost constant assessment of evidence. In so doing, there are a number of principles of EBM that need to be kept in mind: Association can never prove causation. Various methodologic biases can influence conclusions made in both RCTs and observational studies. The strength of RCTs is in the elimination of confounding bias. Surrogate outcomes must be validated in RCTs assessing how they are changed compared with the clinical outcomes. Subgroup analyses cannot prove hypotheses although they can generate them. P < 0.05 is not the same as truth. Type I errors are more likely to occur when multiple analyses are performed, when trials are prematurely stopped for perceived benefit when there was no a priori plan to do so, or in small papers with dramatic results that are selectively published. The failure to find a difference does not mean that no difference exists (type II error).

The Influence of Baseline Characteristics on Response to a Laser Acupuncture Intervention: An Exploratory Analysis

Objectives

In clinical practice it is known that subjects vary in their response to acupuncture, but there is little data on what predicts the outcome. The aim of this study was to identify such predictors.

Method

A secondary analysis was performed on data from 100 participants in a trial of laser and sham laser acupuncture for chronic non-specific low back pain. Multiple regression analysis was used to identify which baseline characteristics predicted pain change in the immediate, short and intermediate term. An analysis of covariance was performed based on these results to re-examine the primary result of the trial.

Results

Strong predictors of poor response were receipt of disability support pension, headache, the regular use of analgesics or previous failed back surgery. Higher pain scores or exacerbation of pain at baseline predicted a greater proportionate pain relief after the intervention. Adjusted analysis suggested a clinically important effect of laser compared to sham (p<0.05), at short term follow-up only.

Conclusion

The findings of this study suggest which characteristics of patients with chronic low back pain are more likely to respond to laser acupuncture treatment, but require replication in other studies. The findings may not apply in other acupuncture interventions and treatment of different conditions. They may also be used to set selection criteria for future studies, and to aid interpreting the effect of baseline imbalances on trial results.

Personalized evidence based medicine: predictive approaches to heterogeneous treatment effects

The use of evidence from clinical trials to support decisions for individual patients is a form of "reference class forecasting": implicit predictions for an individual are made on the basis of outcomes in a reference class of "similar" patients treated with alternative therapies. Evidence based medicine has generally emphasized the broad reference class of patients qualifying for a trial. Yet patients in a trial (and in clinical practice) differ from one another in many ways that can affect the outcome of interest and the potential for benefit. The central goal of personalized medicine, in its various forms, is to narrow the reference class to yield more patient specific effect estimates to support more individualized clinical decision making. This article will review fundamental conceptual problems with the prediction of outcome risk and heterogeneity of treatment effect (HTE), as well as the limitations of conventional (one-variable-at-a-time) subgroup analysis. It will also discuss several regression based approaches to "predictive" heterogeneity of treatment effect analysis, including analyses based on "risk modeling" (such as stratifying trial populations by their risk of the primary outcome or their risk of serious treatment-related harms) and analysis based on "effect modeling" (which incorporates modifiers of relative effect). It will illustrate these approaches with clinical examples and discuss their respective strengths and vulnerabilities.

Assessment of P values for demographic data in randomized controlled trials

In a large number of randomized controlled trials, researchers provide P values for demographic data, which are commonly reported in table 1 of the article for the purpose of emphasizing the lack of differences between or among groups. As such, the authors intend to demonstrate that statistically insignificant P values in the demographic data confirm that group randomization was adequately performed. However, statistically insignificant P values do not necessarily reflect successful randomization. It is more important to rigorously establish a plan for statistical analysis during the design and planning stage of the study, and to consider whether any of the variables included in the demographic data could potentially affect the research results. If a researcher rigorously designed and planned a study, and performed it accordingly, the conclusions drawn from the results would not be influenced by P values, regardless of whether they were significant. In contrasts, imbalanced variables could affect the results after variance controlling, even though whole study process are well planned and executed. In this situation, the researcher can provide results with both the initial method and a second stage of analysis including such variables. Otherwise, for brief conclusions, it would be pointless to report P values in a table simply listing baseline data of the participants.

A comparative study of subgroup identification methods for differential treatment effect: Performance metrics and recommendations

Subgroup identification with differential treatment effects serves as an important step towards precision medicine, as it provides evidence regarding how individuals with specific characteristics respond to a given treatment. This knowledge not only supports the tailoring of treatment strategies but also prompts the development of new treatments. This manuscript provides a brief overview of the issues associated with the methodologies aimed at identifying subgroups with differential treatment effects, and studies in depth the operational characteristics of five data-driven methods that have appeared recently in the literature. The performance of the methods under study to identify correctly the covariates affecting treatment effects is evaluated via simulation and under various conditions. Two clinical trial data sets are also used to illustrate the application of these methods. Discussion and recommendations pertaining to the use of these methods are provided, with emphasis on the relative performance of the methods under the conditions studied.

A simulation study on estimating biomarker–treatment interaction effects in randomized trials with prognostic variables

Background

To individualize treatment decisions based on patient characteristics, identification of an interaction between a biomarker and treatment is necessary. Often such potential interactions are analysed using data from randomized clinical trials intended for comparison of two treatments. Tests of interactions are often lacking statistical power and we investigated if and how a consideration of further prognostic variables can improve power and decrease the bias of estimated biomarker–treatment interactions in randomized clinical trials with time-to-event outcomes.

Methods

A simulation study was performed to assess how prognostic factors affect the estimate of the biomarker–treatment interaction for a time-to-event outcome, when different approaches, like ignoring other prognostic factors, including all available covariates or using variable selection strategies, are applied. Different scenarios regarding the proportion of censored observations, the correlation structure between the covariate of interest and further potential prognostic variables, and the strength of the interaction were considered.

Results

The simulation study revealed that in a regression model for estimating a biomarker–treatment interaction, the probability of detecting a biomarker–treatment interaction can be increased by including prognostic variables that are associated with the outcome, and that the interaction estimate is biased when relevant prognostic variables are not considered. However, the probability of a false-positive finding increases if too many potential predictors are included or if variable selection is performed inadequately.

Conclusions

We recommend undertaking an adequate literature search before data analysis to derive information about potential prognostic variables and to gain power for detecting true interaction effects and pre-specifying analyses to avoid selective reporting and increased false-positive rates.

Electronic supplementary material

The online version of this article (doi:10.1186/s13063-018-2491-0) contains supplementary material, which is available to authorized users.

The effect of individual and mixed rewards on diabetes management: A feasibility randomized controlled trial

Background: Incentives play a role in introducing health-related benefits, but no interventions using mixed incentives, i.e. a combination of individual and group incentives, have been tested in individuals with type 2 diabetes mellitus (T2DM). We evaluated the feasibility of implementing individual- and mixed-incentives, with and without a supportive partner, on glycated haemoglobin (HbA1c) control and weight loss among patients with T2DM. Methods: This is a feasibility, sex-stratified, single-blinded, randomized controlled study in individuals with T2DM. All participants received diabetes education and tailored goal setting for weight and glycated haemoglobin (HbA1c). Participants were randomly assigned into three arms: individual incentives (Arm 1), mixed incentives-altruism (Arm 2), and mixed incentives-cooperation (Arm 3). Participants were accompanied by a diabetes educator every other week to monitor targets, and the intervention period lasted 3 months. The primary outcome was the change in HbA1c at 3 months from baseline. Weight and change body mass index (BMI) were considered as secondary outcomes. Results: Out of 783 patients screened, a total of 54 participants, 18 per study arm, were enrolled and 44 (82%) completed the 3-month follow-up. Mean baseline HbA1c values were 8.5%, 7.9% and 8.2% in Arm 1, Arm 2, and Arm 3, respectively. At 3 months, participants in all three study arms showed reductions in HbA1c ranging from -0.9% in Arm 2 to -1.4% in Arm 1. Weight and BMI also showed reductions. Conclusions: Individual and mixed cash incentives show important reductions in HbA1c, weight and BMI in patients with type 2 diabetes mellitus after 3 months.  Recruitment and uptake of the intervention were successfully accomplished demonstrating feasibility to conduct larger effectiveness studies to test individual and mixed economic incentives for diabetes management. Registration: ClinicalTrials.gov Identifier NCT02891382.

The effect of individual and mixed rewards on diabetes management: A feasibility randomized controlled trial

Background: Incentives play a role in introducing health-related benefits, but no interventions using mixed incentives, i.e. a combination of individual and group incentives, have been tested in individuals with type 2 diabetes mellitus (T2DM). We evaluated the feasibility of implementing individual- and mixed-incentives, with and without a supportive partner, on glycated haemoglobin (HbA1c) control and weight loss among patients with T2DM. Methods: This is a feasibility, sex-stratified, single-blinded, randomized controlled study in individuals with T2DM. All participants received diabetes education and tailored goal setting for weight and glycated haemoglobin (HbA1c). Participants were randomly assigned into three arms: individual incentives (Arm 1), mixed incentives-altruism (Arm 2), and mixed incentives-cooperation (Arm 3). Participants were accompanied by a diabetes educator every other week to monitor targets, and the intervention period lasted 3 months. The primary outcome was the change in HbA1c at 3 months from baseline. Weight and change body mass index (BMI) were considered as secondary outcomes. Results: Out of 783 patients screened, a total of 54 participants, 18 per study arm, were enrolled and 44 (82%) completed the 3-month follow-up. Mean baseline HbA1c values were 8.5%, 7.9% and 8.2% in Arm 1, Arm 2, and Arm 3, respectively. At 3 months, participants in all three study arms showed reductions in HbA1c ranging from -0.9% in Arm 2 to -1.4% in Arm 1. Weight and BMI also showed reductions. Conclusions: Individual and mixed cash incentives show important reductions in HbA1c, weight and BMI in patients with type 2 diabetes mellitus after 3 months.  Recruitment and uptake of the intervention were successfully accomplished demonstrating feasibility to conduct larger effectiveness studies to test individual and mixed economic incentives for diabetes management. Registration: ClinicalTrials.gov Identifier NCT02891382.

Melancholic Symptoms in Bipolar II Depression and Responsiveness to Lamotrigine in an Exploratory Pilot Study

BACKGROUND

In this exploratory pilot study we reanalyzed data from a previous randomized, double-blind, placebo-controlled trial of lamotrigine for bipolar II depression in which lamotrigine was not superior to placebo to determine if splitting the sample into melancholic and nonmelancholic subgroups revealed a significant treatment effect.

METHODS

Adult outpatients (n = 150) in an acute bipolar II depressive episode completed 8 weeks of treatment with lamotrigine (titrated to 200 mg/d) or placebo. Depressive symptoms were assessed at baseline and weekly with the 17-item Hamilton Depression Rating Scale (HAMD-17) and the Montgomery-Åsberg Depression Rating Scale (MADRS). The presence of melancholic depression was determined by baseline responses to the HAMD-17 and MADRS according to the Diagnostic and Statistical Manual of Mental Disorders criteria. Cox regression models stratified by melancholic status were used to predict HAMD-17 and MADRS treatment response. Analysis-of-variance models were used to compare HAMD-17 and MADRS change scores between lamotrigine and placebo groups while testing for interactions by melancholic status.

RESULTS

Lamotrigine was associated with higher odds of treatment response compared with placebo in the melancholic subgroup but not in the nonmelancholic subgroup. However, the melancholic subgroup-treatment interactions from the analysis-of-variance models were nonsignificant.

CONCLUSIONS

Further research is warranted to test the hypothesis that bipolar depression with melancholic symptoms is more responsive to lamotrigine over placebo than nonmelancholic bipolar depression.

Differential intervention effectiveness of a universal school-based resilience intervention in reducing adolescent substance use within student subgroups: exploratory assessment within a cluster-randomised controlled trial

OBJECTIVES

Interventions addressing the individual and environmental protective factors of adolescents are suggested to have potential for reducing adolescent substance use. While universally delivered school-based substance use prevention interventions are common, previous studies have suggested variable effectiveness by subgroups of students. An exploratory study was undertaken to examine the differential effectiveness of a universal school-based resilience intervention on adolescent substance use and protective factors according to their sociodemographic and previous substance use.

DESIGN

Secondary analysis of data from a cluster-randomised controlled trial.

SETTING

32 Australian secondary schools.

PARTICIPANTS

Cohort of grade 7 students (n=3155) followed up in grade 10 (aged 15-16 years; 2014; n=2105).

INTERVENTION

Three-year universal school-based intervention implemented by school staff that targeted a range of student resilience protective factors (2012-2014).

MEASUREMENTS

Primary outcomes included: tobacco (recent, number of cigarettes) and alcohol (recent, 'risk' and number of drinks) use, and secondary outcomes included: marijuana (recent) and other illicit substance (recent) use, and aggregate individual and environmental protective factor scores. Generalised and linear mixed models examined interactions between treatment and student subgroups (gender; socioeconomic disadvantage (low/high); geographic location (major city/inner regional/outer regional-remote); and previous substance use (non-user/user)) at follow-up (36 models).

RESULTS

Analysis of student follow-up data showed no differential intervention effect for any substance use or protective factor outcome for any subgroup, with the exception of one differential effect found by socioeconomic status for the outcome of mean number of cigarettes smoked by recent smokers (p=0.003). There was no evidence of an intervention effect within the low (mean difference (MD) -12.89, 95% CI -26.00 to 0.23) or high (MD 16.36, 95% CI -1.03 to 33.76) socioeconomic subgroups.

CONCLUSIONS

No evidence of an intervention effect on substance use and protective factors was found according to student subgroups defined by sociodemographic characteristics or previous substance use.

TRIAL REGISTRATION NUMBER

ACTRN12611000606987.

Transcatheter Versus Surgical Aortic Valve Replacement in Patients With Prior Cardiac Surgery in the Randomized PARTNER 2A Trial

OBJECTIVES

The aim of this study was to further evaluate clinical outcomes in patients with and without PCS.

BACKGROUND

Prior cardiac surgery (PCS) is associated with increased surgical risk and post-operative complications following surgical aortic valve replacement (SAVR), but whether this risk is similar in transcatheter aortic valve replacement (TAVR) is unclear.

METHODS

In the PARTNER 2A (Placement of Aortic Transcatheter Valve) trial, 2,032 patients with severe aortic stenosis at intermediate surgical risk were randomized to TAVR with the SAPIEN XT valve or SAVR. Adverse clinical outcomes at 30 days and 2 years were compared using Kaplan-Meier event rates and multivariate Cox proportional hazards regression models. The primary endpoint of the PARTNER 2 trial was all-cause death and disabling stroke.

RESULTS

Five hundred nine patients (25.1%) had PCS, mostly (98.2%) coronary artery bypass grafting. There were no significant differences between TAVR and SAVR in patients with or without PCS in the rates of the primary endpoint at 30 days or 2 years. Nevertheless, an interaction was observed between PCS and treatment arm; whereas no-PCS patients treated with TAVR had higher rates of 30-day major vascular complications than patients treated with SAVR (adjusted hazard ratio: 2.66; 95% confidence interval: 1.68 to 4.22), the opposite was true for patients with PCS (adjusted hazard ratio: 0.27; 95% confidence interval: 0.11 to 0.66) (p_interaction <0.0001). A similar interaction was observed for life-threatening or disabling bleeding.

CONCLUSIONS

In the PARTNER 2A trial of intermediate-risk patients with severe aortic stenosis undergoing SAVR versus TAVR, the relative risk for 2-year adverse clinical outcomes was similar between TAVR and SAVR in patients with or without PCS.

Multi-modal Analgesic Strategies for Trauma (MAST): protocol for a pragmatic randomized trial

BACKGROUND

Pain management after injury is critically important for functional recovery. Although opioids have been a mainstay for treatment of pain, they are associated with adverse events and may contribute to long-term use or abuse. Opioid-minimizing multimodal pain regimens have the potential to reduce exposure to opioids without compromising pain control. This article details an ongoing clinical trial comparing two pill-based, opioid-minimizing, multimodal pain strategies.

METHODS

This is a single-center, parallel-group, randomized, controlled comparative effectiveness trial comparing two multimodal pain regimens in adult trauma patients. All patients 16 years and older admitted to the Red Duke Trauma Institute are eligible unless they are pregnant, a prisoner, under observation status, or a non-acute trauma patient. At admission to the trauma service, patients are enrolled and randomized to one of two multimodal pain regimens. The primary outcome is opioid use, measured by morphine milligram equivalents per patient per day. The secondary outcomes include pain scores, ventilator days, hospital and intensive care unit lengths of stay, occurrence of opioid-related complications, hospital and pharmacy costs, and incidence of hospital discharge with opioid prescription. Outcomes will be compared using Bayesian methods.

DISCUSSION

This trial will determine the effectiveness of two multimodal pain treatment strategies on reducing in-hospital opioid exposure in adult trauma patients. Furthermore, it will compare the two strategies on pain control and patient safety. Knowledge gained in this study can improve quality of care at this hospital and other trauma centers regardless of which medication regimen proves superior.

Sex and Gender Differences Research Design for Basic, Clinical, and Population Studies: Essentials for Investigators

A sex- and gender-informed perspective increases rigor, promotes discovery, and expands the relevance of biomedical research. In the current era of accountability to present data for males and females, thoughtful and deliberate methodology can improve study design and inference in sex and gender differences research. We address issues of motivation, subject selection, sample size, data collection, analysis, and interpretation, considering implications for basic, clinical, and population research. In particular, we focus on methods to test sex/gender differences as effect modification or interaction, and discuss why some inferences from sex-stratified data should be viewed with caution. Without careful methodology, the pursuit of sex difference research, despite a mandate from funding agencies, will result in a literature of contradiction. However, given the historic lack of attention to sex differences, the absence of evidence for sex differences is not necessarily evidence of the absence of sex differences. Thoughtfully conceived and conducted sex and gender differences research is needed to drive scientific and therapeutic discovery for all sexes and genders.

Prognostic and predictive signatures for treatment decisions

AIM

We develop a subgroup selection procedure using both prognostic and predictive biomarkers to identify four patient subpopulations: low- and high-risk responders, and low- and high-risk nonresponders.

METHODS

We utilize three regression models to identify three sets of biomarkers: S, prognostic biomarkers; T, predictive biomarkers; and U, prognostic and predictive biomarkers. The prognostic signature C(S) combines with a predictive signature, either C(T) or C(U), to develop two procedures C(S,T) and C(S,U) for identification of four subgroups.

RESULTS

Simulation experiment showed that proposed models for identifying the biomarker sets S and U performed well, as did the procedure C(S,U) for subgroup identification.

CONCLUSION

The proposed model provides more comprehensive characterization of patient subpopulations, and better accuracy in patient treatment assignment.

Prevention of haematoma progression by tranexamic acid in intracerebral haemorrhage patients with and without spot sign on admission scan: a statistical analysis plan of a pre-specified sub-study of the TICH-2 trial

OBJECTIVE

We present the statistical analysis plan of a prespecified Tranexamic Acid for Hyperacute Primary Intracerebral Haemorrhage (TICH)-2 sub-study aiming to investigate, if tranexamic acid has a different effect in intracerebral haemorrhage patients with the spot sign on admission compared to spot sign negative patients. The TICH-2 trial recruited above 2000 participants with intracerebral haemorrhage arriving in hospital within 8 h after symptom onset. They were included irrespective of radiological signs of on-going haematoma expansion. Participants were randomised to tranexamic acid versus matching placebo. In this subgroup analysis, we will include all participants in TICH-2 with a computed tomography angiography on admission allowing adjudication of the participants' spot sign status.

RESULTS

Primary outcome will be the ability of tranexamic acid to limit absolute haematoma volume on computed tomography at 24 h (± 12 h) after randomisation among spot sign positive and spot sign negative participants, respectively. Within all outcome measures, the effect of tranexamic acid in spot sign positive/negative participants will be compared using tests of interaction. This sub-study will investigate the important clinical hypothesis that spot sign positive patients might benefit more from administration of tranexamic acid compared to spot sign negative patients. Trial registration ISRCTN93732214 ( http://www.isrctn.com ).

Comparison of effectiveness and cost-effectiveness of an intensive community supported discharge service versus treatment as usual for adolescents with psychiatric emergencies: a randomised controlled trial

BACKGROUND

Intensive community treatment to reduce dependency on adolescent psychiatric inpatient care is recommended in guidelines but has not been assessed in a randomised controlled trial in the UK. We designed a supported discharge service (SDS) provided by an intensive community treatment team and compared outcomes with usual care.

METHODS

Eligible patients for this randomised controlled trial were younger than 18 years and had been admitted for psychiatric inpatient care in the South London and Maudsley NHS Foundation Trust. Patients were assigned 1:1 to either the SDS or to usual care by use of a computer-generated pseudorandom code with random permuted blocks of varying sizes. The primary outcome was number of inpatient bed-days, change in Strengths and Difficulties Questionnaire (SDQ) scores, and change in Children's Global Assessment Scale (CGAS) scores at 6 months, assessed by intention to treat. Cost-effectiveness was explored with acceptability curves based on CGAS scores and quality-adjusted life-years (QALYs) calculated from the three-level EuroQol measure of health-related quality of life (EQ-5D-3L), taking a health and social care perspective. This study is registered with the ISRCTN Registry, number ISRCTN82129964.

FINDINGS

Hospital use at 6 months was significantly lower in the SDS group than in the usual care group (unadjusted median 34 IQR 17-63 vs 50 days, 19-125, p=0·04). The ratio of mean total inpatient days for usual care to SDS was 1·67 (95% CI 1·02-2·81, p=0·04), which decreased to 1·65 (0·99-2·77, p=0·057) when adjusted for differences in hospital use before randomisation. Scores for SDQ and CGAS did not differ between groups. The cost-effectiveness acceptability curve based on QALYs showed that the probability of SDS being cost-effective compared with usual care was around 60% with a willingness-to-pay threshold of £20 000-30 000 per QALY, and that based on CGAS showed at least 58% probability of SDS being cost-effective compared with usual care irrespective of willingness to pay. We recorded no adverse events attributable to SDS or usual care.

INTERPRETATION

SDS provided by an intensive community treatment team reduced bed usage at 6 months' follow-up but had no effect on functional status and symptoms of mental health disorders compared with usual care. The possibility of preventing admissions, particularly through features such as reduced self-harm and improved reintegration into school, with intensive community treatment should be investigated in future studies.

FUNDING

South London and Maudsley NHS Trust.

The Risk of Acute Pancreatitis After Initiation of Dipeptidyl Peptidase 4 Inhibitors: Testing a Hypothesis of Subgroup Differences in Older U.S. Adults

OBJECTIVE

To examine whether dipeptidyl peptidase 4 inhibitors (DPP-4I) increase acute pancreatitis risk in older patients and whether the association varies by age, sex, and history of cardiovascular disease (CVD).

RESEARCH DESIGN AND METHODS

We conducted a cohort study of DPP-4I initiators versus thiazolidinedione (TZD) or sulfonylurea initiators using U.S. Medicare beneficiaries, 2007-2014. Eligible initiators were aged 66 years or older without history of pancreatic disease or alcohol-related diseases. Patients were followed up for hospitalization due to acute pancreatitis and censored at 90 days after treatment changes. Weighted Cox models were used to estimate the hazard ratio (HR) for acute pancreatitis. Analyses were performed overall as well as within subgroups defined by age, sex, and CVD history.

RESULTS

We found no increased risk of acute pancreatitis comparing 49,374 DPP-4I initiators to 132,223 sulfonylurea initiators (weighted HR 1.01; 95% CI 0.83-1.24) and comparing 57,301 DPP-4I initiators to 32,612 TZD initiators (weighted HR 1.11; 95% CI 0.76-1.62). Age and sex did not modify the association. Among patients with CVD, acute pancreatitis incidence was elevated in initiators of DPP-4I and sulfonylurea (2.3 and 2.4 per 1,000 person-years, respectively) but not in TZD initiators (1.5). Among patients with CVD, higher risk of acute pancreatitis was observed with DPP-4I compared with TZD (weighted HR 1.84; 95% CI 1.02-3.35) but not compared with sulfonylurea.

CONCLUSIONS

Our study provides evidence that DPP-4I is not associated with an increased risk of acute pancreatitis in older adults overall. The positive association observed in patients with CVD could be due to chance or bias but merits further investigation.

Imbalance p values for baseline covariates in randomized controlled trials: a last resort for the use of p values? A pro and contra debate

Background

Results of randomized controlled trials (RCTs) are usually accompanied by a table that compares covariates between the study groups at baseline. Sometimes, the investigators report p values for imbalanced covariates. The aim of this debate is to illustrate the pro and contra of the use of these p values in RCTs.

Pro

Low p values can be a sign of biased or fraudulent randomization and can be used as a warning sign. They can be considered as a screening tool with low positive-predictive value. Low p values should prompt us to ask for the reasons and for potential consequences, especially in combination with hints of methodological problems.

Contra

A fair randomization produces the expectation that the distribution of p values follows a flat distribution. It does not produce an expectation related to a single p value. The distribution of p values in RCTs can be influenced by the correlation among covariates, differential misclassification or differential mismeasurement of baseline covariates. Given only a small number of reported p values in the reports of RCTs, judging whether the realized p value distribution is, indeed, a flat distribution becomes difficult. If p values ≤0.005 or ≥0.995 were used as a sign of alarm, the false-positive rate would be 5.0% if randomization was done correctly, and five p values per RCT were reported.

Conclusion

Use of a low p value as a warning sign that randomization is potentially biased can be considered a vague heuristic. The authors of this debate are obviously more or less enthusiastic with this heuristic and differ in the consequences they propose.

Meta-Research on Oncology Trials: A Toolkit for Researchers with Limited Resources

"Meta-research" is a discipline that investigates research practices. Meta-research on clinical trials is an attempt to summarize descriptive and methodological features of published or ongoing clinical trials, including aspects of their implementation, design, analysis, reporting, and interpretation. In this type of investigation, the unit of analysis is a primary source of information about a clinical trial (e.g., published reports, study protocols, or abstracts), with meta-research being a second layer of information that summarizes what is known from various primary sources. After the formulation of the primary research question, the methodology of meta-research resembles that of other research projects, with predefined eligibility criteria, exposure variables, primary and secondary outcomes of interest, and an analysis plan. This type of study usually provides a high-level picture of the literature on a specific topic, always accompanied by a critical evaluation of the methodology and/or the quality of reporting of the studies included. Because relatively few resources are consumed to produce meta-research, these studies offer a great opportunity for clinical scientists working in settings with limited resources. In this article, we present the principles of designing and conducting meta-research and use our experience to suggest recommendations on how to perform and how to report this type of potentially very creative study. IMPLICATIONS FOR PRACTICE: The term meta-research pertains to a type of study in which the unit of analysis is, in most cases, the publication of a clinical trial. This type of study usually provides a high-level picture of the literature on a specific topic, always accompanied by a critical evaluation of the methodology, design, and/or the quality of reporting of the studies included. Because relatively few resources are consumed to produce meta-research, these studies offer a great opportunity for clinical scientists who work in low-income countries. This article presents the principles of designing and conducting meta-research and proposes practical recommendations on how to perform and report this type of potentially very creative study.

Exploring synergistic effects of aerobic exercise and mindfulness training on cognitive function in older adults: Protocol for a pilot randomized controlled trial

INTRODUCTION

Despite increasing evidence that aerobic exercise and cognitive training improve cognitive function among patients with cognitive impairment and dementia, few studies have focused on the effect of a combination of these approaches. This study will explore whether combining aerobic training (AT) with mindfulness training (MT), an intervention promoting the moment-to-moment awareness of physical sensations, affective states, and thoughts, improves cognitive function in individuals at risk of dementia. The primary objective is to determine the feasibility and acceptability of the intervention(s). The secondary objective is to obtain estimates of effect sizes on cognitive function and on possible mediators.

METHODS AND ANALYSIS

Forty participants with at least 2 risk factors for dementia will be randomized (2 × 2 factorial design) to either AT (3 sessions/week for 12 weeks), MT (1 session/week for 8 weeks), both, or usual care. Assessments of cognitive function (attention, executive function, episodic, and working memory); physical activity (accelerometry), aerobic capacity (6-minute walk test), waist-to-hip ratio, blood pressure, social support (Multidimensional Scale of Perceived Social Support), depression (Hospital Anxiety and Depression Scale), and mindfulness (Five Facets of Mindfulness) will be conducted at baseline, end of treatment, and 6-months postbaseline. Rates of retention, attendance, and program satisfaction will be calculated for each of the 4 groups to determine the feasibility and acceptability of each intervention.

ETHICS AND DISSEMINATION

This study has full ethical approval by The Miriam Hospital Institutional Review Board and adheres to the Standard Protocol Items: Recommendations for Interventional Trials reporting recommendations. If results from this exploratory, proof-of-concept study support our hypotheses, we will conduct a large randomized controlled trial (RCT) to determine the efficacy of combined MT and AT in improving cognitive function in individuals at risk of dementia. Results from the study will be disseminated through peer-reviewed journals and conference presentations. REGISTRATION DETAILS:: http://www.clinicalstrials.gov identifier NCT03289546.