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Introduction: The Fragility Index (FI) and the FI family are statistical tools that measure the robustness of randomized controlled trials (RCT) by examining how many patients would need a different outcome to change the statistical significance of the main results of a trial. These tools have recently gained popularity in assessing the robustness or fragility of clinical trials in many clinical areas and analyzing the strength of the trial outcomes underpinning guideline recommendations. However, it has not been applied to perioperative care Clinical Practice Guidelines (CPG). Objectives: This study aims to survey clinical practice guidelines in anesthesiology to determine the Fragility Index of RCTs supporting the recommendations, and to explore trial characteristics associated with fragility. Methods and analysis: A methodological survey will be conducted using the targeted population of RCT referenced in the recommendations of the CPG of the North American and European societies from 2012 to 2022. FI will be assessed for statistically significant and non-significant trial results. A Poisson regression analysis will be used to explore factors associated with fragility. Discussion: This methodological survey aims to estimate the Fragility Index of RCTs supporting perioperative care guidelines published by North American and European societies of anesthesiology between 2012 and 2022. The results of this study will inform the methodological quality of RCTs included in perioperative care guidelines and identify areas for improvement. [ABSTRACT FROM AUTHOR]

Background: Subgroup analyses are widely used to evaluate the heterogeneity of treatment effects in randomized clinical trials. However, there is a limited investigation of the quality of prespecified and reported subgroup analyses in stroke trials. This study evaluated the credibility of subgroup analyses in stroke trials. Methods and analysis: We searched Medline/PubMed, Embase, the Cochrane Central Register of Controlled Trials, and the Web of Science from inception to 24 March 2021. Three reviewers screened, extracted, and analyzed the data from the publications. Primary publications of stroke trials that reported at least one subgroup effect and had published corresponding study protocols were included. The Instrument for Assessing the Credibility of Effect Modification Analyses (ICEMAN) was used to examine the quality of the subgroup effects reported, with each subgroup effect assigned a credibility rating ranging from very low to high. Subgroup effects with two or more "definitely no" responses received a low credibility rating. The risk of bias was assessed using the Cochrane Risk-of-Bias tool for randomized trials version 2. Results: Seventy-four articles met the inclusion criteria and reported a combined total of 647 subgroup effects. The median sample size was 1264 (interquartile range (IQR): 380–3876), and the median number of subgroups prespecified in the protocol was 6 (IQR: 2–10). Sixty-one (82%) studies used the univariate test of interaction. Of the total 647 subgroup effects reported in these studies, 319 (49%) were reported in acute stroke trials, while 423 (65%) had low credibility. Conclusion: The quality of subgroup analysis reporting in stroke trials remains poor. More effort is needed to train trialists on the best methods for designing and performing subgroup analyses, and how to report the results. Trial registration number: We prospectively registered the review with International Prospective Register for Systematic Reviews (registration number: CRD42020223133) [ABSTRACT FROM AUTHOR]

Background: Extremely preterm infants have a high mortality and morbidity. Here, we present a statistical analysis plan for secondary Bayesian analyses of the pragmatic, sufficiently powered multinational, trial—SafeBoosC III—evaluating the benefits and harms of cerebral oximetry monitoring plus a treatment guideline versus usual care for such infants. Methods: The SafeBoosC-III trial is an investigator-initiated, open-label, randomised, multinational, pragmatic, phase III clinical trial with a parallel-group design. The trial randomised 1601 infants, and the frequentist analyses were published in April 2023. The primary outcome is a dichotomous composite outcome of death or severe brain injury. The exploratory outcomes are major neonatal morbidities associated with neurodevelopmental impairment later in life: (1) bronchopulmonary dysplasia; (2) retinopathy of prematurity; (3) late-onset sepsis; (4) necrotising enterocolitis; and (5) number of major neonatal morbidities (count of bronchopulmonary dysplasia, retinopathy of prematurity, and severe brain injury). The primary Bayesian analyses will use non-informed priors including all plausible effects. The models will use a Hamiltonian Monte Carlo sampler with 1 chain, a sampling of 10,000, and at least 25,000 iterations for the burn-in period. In Bayesian statistics, such analyses are referred to as 'posteriors' and will be presented as point estimates with 95% credibility intervals (CrIs), encompassing the most probable results based on the data, model, and priors selected. The results will be presented as probability of any benefit or any harm, Bayes factor, and the probability of clinical important benefit or harm. Two statisticians will analyse the blinded data independently following this protocol. Discussion: This statistical analysis plan presents a secondary Bayesian analysis of the SafeBoosC-III trial. The analysis and the final manuscript will be carried out and written after we publicise the primary frequentist trial report. Thus, we can interpret the findings from both the frequentists and Bayesian perspective. This approach should provide a better foundation for interpreting of our findings. Trial registration: ClinicalTrials.org, NCT03770741. Registered on 10 December 2018. [ABSTRACT FROM AUTHOR]

The evidence base to support reimbursement decision making for oncology drugs is often based on short-term follow-up trial data, and attempts to address this uncertainty are not typically undertaken once a reimbursement decision is made. To address this gap, we sought to conduct a reassessment of an oncology drug (pembrolizumab) for patients with advanced melanoma which was approved based on interim data with a median 7.9 months of follow-up and for which long-term data have since been published. We developed a three-health-state partitioned survival model based on the phase 3 KEYNOTE-006 clinical trial data using patient-level data reconstruction techniques based on an interim analysis. We used a standard survival analysis and parametric curve fitting techniques to extrapolate beyond the trial follow-up time, and the model structure and inputs were derived from the literature. Five-year long-term follow-up data from the trial were then used to re-evaluate the cost-effectiveness of pembrolizumab versus ipilimumab for treatment of advanced melanoma. The best fitting parametric curves and corresponding survival extrapolations for reconstructed interim data and long-term data reconstructed from KEYNOTE-006 were different. An analysis of the 5 year long-term follow-up data generated a base case incremental cost-effectiveness ratio (ICER) that was 28% higher than the ICER based on interim trial data. Our findings suggest that there may be a trade-off between certainty and the ICER. Conducting health technology re-assessments of certain oncology products on the basis of longer-term data availability, especially for those health technology adoption decisions made based on immature clinical data, may be of value to decision makers. [ABSTRACT FROM AUTHOR]

Participants enrolled in cardiovascular disease (CVD) randomized controlled trials are not often representative of the population living with the disease. Older adults, children, women, Black, Indigenous and People of Color, and people living in low- and middle-income countries are typically under-enrolled in trials relative to disease distribution. Treatment effect estimates of CVD therapies have been largely derived from trial evidence generated in White men without complex comorbidities, limiting the generalizability of evidence. This review highlights barriers and facilitators of trial enrollment, temporal trends, and the rationale for representativeness. It proposes strategies to increase representativeness in CVD trials, including trial designs that minimize the research burden on participants, inclusive recruitment practices and eligibility criteria, diversification of clinical trial leadership, and research capacity-building in under-represented regions. Implementation of such strategies could generate better and more generalizable evidence to reduce knowledge gaps and position the cardiovascular trial enterprise as a vehicle to counter existing healthcare inequalities. [ABSTRACT FROM AUTHOR]

Nearly half of adult fracture patients are vitamin D deficient (serum 25‐hydroxyvitamin D [25(OH)D] levels <20 ng/mL). Many surgeons advocate prescribing vitamin D supplements to improve fracture healing outcomes; however, data supporting the effectiveness of vitamin D3 supplements to improve acute fracture healing are lacking. We tested the effectiveness of vitamin D3 supplementation for improving tibia and femur fracture healing. We conducted a single‐center, double‐blinded phase II screening randomized controlled trial with a 12‐month follow‐up. Patients aged 18–50 years receiving an intramedullary nail for a tibia or femoral shaft fracture were randomized 1:1:1:1 to receive (i) 150,000 IU loading dose vitamin D3 at injury and 6 weeks (n = 27); (ii) 4000 IU vitamin D3 daily (n = 24); (iii) 600 IU vitamin D3 daily (n = 24); or (iv) placebo (n = 27). Primary outcomes were clinical fracture healing (Function IndeX for Trauma [FIX‐IT]) and radiographic fracture healing (Radiographic Union Score for Tibial fractures [RUST]) at 3 months. One hundred two patients with a mean age of 29 years (standard deviation 8) were randomized. The majority were male (69%), and 56% were vitamin D3 deficient at baseline. Ninety‐nine patients completed the 3‐month follow‐up. In our prespecified comparisons, no clinically important or statistically significant differences were detected in RUST or FIX‐IT scores between groups when measured at 3 months and over 12 months. However, in a post hoc comparison, high doses of vitamin D3 were associated with improved clinical fracture healing relative to placebo at 3 months (mean difference [MD] 0.90, 80% confidence interval [CI], 0.08 to 1.79; p = 0.16) and within 12 months (MD 0.89, 80% CI, 0.05 to 1.74; p = 0.18). The study was designed to identify potential evidence to support the effectiveness of vitamin D3 supplementation in improving acute fracture healing. Vitamin D3 supplementation, particularly high doses, might modestly improve acute tibia or femoral shaft fracture healing in healthy adults, but confirmatory studies are required. The Vita‐Shock trial was awarded the Orthopaedic Trauma Association's (OTA) Bovill Award in 2020. This award is presented annually to the authors of the most outstanding OTA Annual Meeting scientific paper. © 2022 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research. [ABSTRACT FROM AUTHOR]

Background: COVID-19 is rapidly spreading causing extensive burdens across the world. Effective vaccines to prevent COVID-19 are urgently needed. Methods and findings: Our objective was to assess the effectiveness and safety of COVID-19 vaccines through analyses of all currently available randomized clinical trials. We searched the databases CENTRAL, MEDLINE, Embase, and other sources from inception to June 17, 2021 for randomized clinical trials assessing vaccines for COVID-19. At least two independent reviewers screened studies, extracted data, and assessed risks of bias. We conducted meta-analyses, network meta-analyses, and Trial Sequential Analyses (TSA). Our primary outcomes included all-cause mortality, vaccine efficacy, and serious adverse events. We assessed the certainty of evidence with GRADE. We identified 46 trials; 35 trials randomizing 219 864 participants could be included in our analyses. Our meta-analyses showed that mRNA vaccines (efficacy, 95% [95% confidence interval (CI), 92% to 97%]; 71 514 participants; 3 trials; moderate certainty); inactivated vaccines (efficacy, 61% [95% CI, 52% to 68%]; 48 029 participants; 3 trials; moderate certainty); protein subunit vaccines (efficacy, 77% [95% CI, −5% to 95%]; 17 737 participants; 2 trials; low certainty); and viral vector vaccines (efficacy 68% [95% CI, 61% to 74%]; 71 401 participants; 5 trials; low certainty) prevented COVID-19. Viral vector vaccines decreased mortality (risk ratio, 0.25 [95% CI 0.09 to 0.67]; 67 563 participants; 3 trials, low certainty), but comparable data on inactivated, mRNA, and protein subunit vaccines were imprecise. None of the vaccines showed evidence of a difference on serious adverse events, but observational evidence suggested rare serious adverse events. All the vaccines increased the risk of non-serious adverse events. Conclusions: The evidence suggests that all the included vaccines are effective in preventing COVID-19. The mRNA vaccines seem most effective in preventing COVID-19, but viral vector vaccines seem most effective in reducing mortality. Further trials and longer follow-up are necessary to provide better insight into the safety profile of these vaccines. [ABSTRACT FROM AUTHOR]

Background: Despite the expectations regarding the effectiveness of chloroquine (CQ) and hydroxychloroquine (HCQ) for coronavirus disease (COVID-19) management, concerns about their adverse events have remained. Objectives: The objective of this systematic review was to evaluate the safety of CQ and HCQ from malarial and non-malarial randomized clinical trials (RCTs). Methods: The primary outcomes were the frequencies of serious adverse events (SAEs), retinopathy, and cardiac complications. Search strategies were applied to MEDLINE, EMBASE, LILACS, CENTRAL, Scopus, and Trip databases. We used a random-effects model to pool results across studies and Peto's one-step odds ratio (OR) for event rates below 1%. Both-armed zero-event studies were excluded from the meta-analyses. We used the Grading of Recommendations Assessment, Development, and Evaluation system to evaluate the certainty of evidence. Results: One hundred and six RCTs were included. We found no significant difference between CQ/HCQ and control (placebo or non-CQ/HCQ) in the frequency of SAEs (OR: 0.98, 95% confidence interval [CI]: 0.76–1.26, 33 trials, 15,942 participants, moderate certainty of evidence). However, there was a moderate certainty of evidence that CQ/HCQ increases the incidence of cardiac complications (RR: 1.62, 95% CI: 1.10–2.38, 16 trials, 9908 participants). No clear relationship was observed between CQ/HCQ and retinopathy (OR: 1.63, 95% CI: − 0.4–6.57, 5 trials, 344 participants, very low certainty of evidence). Conclusions: CQ and HCQ probably do not increase SAEs, with low frequency of these adverse events on malarial and non-malarial conditions. However, they may increase cardiac complications especially in patients with COVID-19. No clear effect of their use on the incidence of retinopathy was observed. Systematic review registration: PROSPERO CRD42020177818 [ABSTRACT FROM AUTHOR]

Background: Sub-Saharan Africa continues to carry a high burden of communicable diseases such as TB and HIV and non-communicable diseases such as hypertension and other cardiovascular conditions. Although investment in research has led to advances in improvements in outcomes, a lot still remains to be done to build research capacity in health. Like many other regions in the world, Sub-Saharan Africa suffers from a critical shortage of biostatisticians and clinical trial methodologists.Methods: Funded through a Fogarty Global Health Training Program grant, the Faculty of Medicine and Health Sciences at Stellenbosch University in South Africa established a new Masters Program in Biostatistics which was launched in January 2017. In this paper, we describe the development of a biostatistical and clinical trials collaboration Module, adapted from a similar course offered in the Health Research Methodology program at McMaster University.Discussion: Guided by three core principles (experiential learning; multi-/inter-disciplinary approach; and formal mentorship), the Module aims to advance biostatistical collaboration skills of the trainees by facilitating learning in how to systematically apply fundamental statistical and trial methodological knowledge in practice while strengthening some soft skills which are necessary for effective collaborations with other healthcare researchers to solve health problems. We also share some preliminary findings from the first four cohorts that took the Module in January-November 2018 to 2021. We expect that this Module can provide an example of how to improve biostatistical and clinical trial collaborations and accelerate research capacity building in low-resource settings.Funding Source: Fogarty International Center of the National Institutes of Health. [ABSTRACT FROM AUTHOR]

Background: COVID-19 is a rapidly spreading disease that has caused extensive burden to individuals, families, countries, and the world. Effective treatments of COVID-19 are urgently needed. This is the second edition of a living systematic review of randomized clinical trials assessing the effects of all treatment interventions for participants in all age groups with COVID-19. Methods and findings: We planned to conduct aggregate data meta-analyses, trial sequential analyses, network meta-analysis, and individual patient data meta-analyses. Our systematic review was based on PRISMA and Cochrane guidelines, and our eight-step procedure for better validation of clinical significance of meta-analysis results. We performed both fixed-effect and random-effects meta-analyses. Primary outcomes were all-cause mortality and serious adverse events. Secondary outcomes were admission to intensive care, mechanical ventilation, renal replacement therapy, quality of life, and non-serious adverse events. According to the number of outcome comparisons, we adjusted our threshold for significance to p = 0.033. We used GRADE to assess the certainty of evidence. We searched relevant databases and websites for published and unpublished trials until November 2, 2020. Two reviewers independently extracted data and assessed trial methodology. We included 82 randomized clinical trials enrolling a total of 40,249 participants. 81 out of 82 trials were at overall high risk of bias. Meta-analyses showed no evidence of a difference between corticosteroids versus control on all-cause mortality (risk ratio [RR] 0.89; 95% confidence interval [CI] 0.79 to 1.00; p = 0.05; I2 = 23.1%; eight trials; very low certainty), on serious adverse events (RR 0.89; 95% CI 0.80 to 0.99; p = 0.04; I2 = 39.1%; eight trials; very low certainty), and on mechanical ventilation (RR 0.86; 95% CI 0.55 to 1.33; p = 0.49; I2 = 55.3%; two trials; very low certainty). The fixed-effect meta-analyses showed indications of beneficial effects. Trial sequential analyses showed that the required information size for all three analyses was not reached. Meta-analysis (RR 0.93; 95% CI 0.82 to 1.07; p = 0.31; I2 = 0%; four trials; moderate certainty) and trial sequential analysis (boundary for futility crossed) showed that we could reject that remdesivir versus control reduced the risk of death by 20%. Meta-analysis (RR 0.82; 95% CI 0.68 to 1.00; p = 0.05; I2 = 38.9%; four trials; very low certainty) and trial sequential analysis (required information size not reached) showed no evidence of difference between remdesivir versus control on serious adverse events. Fixed-effect meta-analysis showed indications of a beneficial effect of remdesivir on serious adverse events. Meta-analysis (RR 0.40; 95% CI 0.19 to 0.87; p = 0.02; I2 = 0%; two trials; very low certainty) showed evidence of a beneficial effect of intravenous immunoglobulin versus control on all-cause mortality, but trial sequential analysis (required information size not reached) showed that the result was severely underpowered to confirm or reject realistic intervention effects. Meta-analysis (RR 0.63; 95% CI 0.35 to 1.14; p = 0.12; I2 = 77.4%; five trials; very low certainty) and trial sequential analysis (required information size not reached) showed no evidence of a difference between tocilizumab versus control on serious adverse events. Fixed-effect meta-analysis showed indications of a beneficial effect of tocilizumab on serious adverse events. Meta-analysis (RR 0.70; 95% CI 0.51 to 0.96; p = 0.02; I2 = 0%; three trials; very low certainty) showed evidence of a beneficial effect of tocilizumab versus control on mechanical ventilation, but trial sequential analysis (required information size not reached) showed that the result was severely underpowered to confirm of reject realistic intervention effects. Meta-analysis (RR 0.32; 95% CI 0.15 to 0.69; p < 0.00; I2 = 0%; two trials; very low certainty) showed evidence of a beneficial effect of bromhexine versus standard care on non-serious adverse events, but trial sequential analysis (required information size not reached) showed that the result was severely underpowered to confirm or reject realistic intervention effects. Meta-analyses and trial sequential analyses (boundary for futility crossed) showed that we could reject that hydroxychloroquine versus control reduced the risk of death and serious adverse events by 20%. Meta-analyses and trial sequential analyses (boundary for futility crossed) showed that we could reject that lopinavir-ritonavir versus control reduced the risk of death, serious adverse events, and mechanical ventilation by 20%. All remaining outcome comparisons showed that we did not have enough information to confirm or reject realistic intervention effects. Nine single trials showed statistically significant results on our outcomes, but were underpowered to confirm or reject realistic intervention effects. Due to lack of data, it was not relevant to perform network meta-analysis or possible to perform individual patient data meta-analyses. Conclusions: No evidence-based treatment for COVID-19 currently exists. Very low certainty evidence indicates that corticosteroids might reduce the risk of death, serious adverse events, and mechanical ventilation; that remdesivir might reduce the risk of serious adverse events; that intravenous immunoglobin might reduce the risk of death and serious adverse events; that tocilizumab might reduce the risk of serious adverse events and mechanical ventilation; and that bromhexine might reduce the risk of non-serious adverse events. More trials with low risks of bias and random errors are urgently needed. This review will continuously inform best practice in treatment and clinical research of COVID-19. Systematic review registration: PROSPERO CRD42020178787. [ABSTRACT FROM AUTHOR]

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19) which has rapidly spread worldwide. Several human randomized clinical trials assessing potential vaccines are currently underway. There is an urgent need for a living systematic review that continuously assesses the beneficial and harmful effects of all available vaccines for COVID-19. Methods/design: We will conduct a living systematic review based on searches of major medical databases (e.g., MEDLINE, EMBASE, CENTRAL) and clinical trial registries from their inception onwards to identify relevant randomized clinical trials. We will update the literature search once a week to continuously assess if new evidence is available. Two review authors will independently extract data and conduct risk of bias assessments. We will include randomized clinical trials comparing any vaccine aiming to prevent COVID-19 (including but not limited to messenger RNA; DNA; non-replicating viral vector; replicating viral vector; inactivated virus; protein subunit; dendritic cell; other vaccines) with any comparator (placebo; "active placebo;" no intervention; standard care; an "active" intervention; another vaccine for COVID-19) for participants in all age groups. Primary outcomes will be all-cause mortality; a diagnosis of COVID-19; and serious adverse events. Secondary outcomes will be quality of life and non-serious adverse events. The living systematic review will include aggregate data meta-analyses, trial sequential analyses, network meta-analyses, and individual patient data meta-analyses. Within-study bias will be assessed using Cochrane risk of bias tool. The Grading of Recommendations, Assessment, Development and Evaluations (GRADE) and Confidence in Network Meta-Analysis (CINeMA) approaches will be used to assess certainty of evidence. Observational studies describing harms identified during the search for trials will also be included and described and analyzed separately. Discussion: COVID-19 has become a pandemic with substantial mortality. A living systematic review assessing the beneficial and harmful effects of different vaccines is urgently needed. This living systematic review will regularly inform best practice in vaccine prevention and clinical research of this highly prevalent disease. Systematic review registration: PROSPERO CRD42020196492 [ABSTRACT FROM AUTHOR]

Background: Clinical trials change practice in cardiology, and leading them requires research training, mentorship, sponsorship, and networking. Women report challenges in obtaining these opportunities.Objectives: The purpose of this review was to evaluate temporal trends in representation of women as authors in heart failure (HF) randomized controlled trials (RCTs) published in high-impact medical journals and explore RCT characteristics associated with women as lead authors.Methods: We searched MEDLINE, EMBASE, and CINAHL for HF RCTs published in journals with an impact factor ≥10 between January 1, 2000, and May 7, 2019. We assessed temporal trends in the gender distribution of authors, and used multivariable logistic regression to determine characteristics associated with women as lead authors.Results: We identified 10,596 unique articles, of which 403 RCTs met inclusion criteria. Women represented 15.6% (95% confidence interval [CI]: 12.2% to 19.6%), 12.9% (95% CI: 9.8% to 16.6%), and 11.4% (95% CI: 8.5% to 14.9%) of lead, senior, and corresponding authors, respectively. The proportion of women authors has not changed over time. Women had lower odds of lead authorship in RCTs that were multicenter (odds ratio [OR]: 0.58; 95% CI: 0.18 to 0.96; p = 0.037), were coordinated in North America (OR: 0.21; 95% CI: 0.08 to 0.70; p = 0.011) or Europe (OR: 0.33; 95% CI: 0.09 to 0.91; p = 0.039), tested drug interventions (OR: 0.42; 95% CI: 0.16 to 0.97; p = 0.043), or had men as the senior author (OR: 0.50; 95% CI: 0.21 to 0.93; p = 0.043).Conclusions: Women are under-represented as authors of HF RCTs, with no change in temporal trends. Women had lower odds of lead authorship in RCTs that were multicenter, were coordinated in North America or Europe, tested drug interventions, or had men as senior authors. [ABSTRACT FROM AUTHOR]

Background: Most randomized controlled trials (RCTs) and meta-analyses of RCTs examine effect modification (also called a subgroup effect or interaction), in which the effect of an intervention varies by another variable (e.g., age or disease severity). Assessing the credibility of an apparent effect modification presents challenges; therefore, we developed the Instrument for assessing the Credibility of Effect Modification Analyses (ICEMAN).Methods: To develop ICEMAN, we established a detailed concept; identified candidate credibility considerations in a systematic survey of the literature; together with experts, performed a consensus study to identify key considerations and develop them into instrument items; and refined the instrument based on feedback from trial investigators, systematic review authors and journal editors, who applied drafts of ICEMAN to published claims of effect modification.Results: The final instrument consists of a set of preliminary considerations, core questions (5 for RCTs, 8 for meta-analyses) with 4 response options, 1 optional item for additional considerations and a rating of credibility on a visual analogue scale ranging from very low to high. An accompanying manual provides rationales, detailed instructions and examples from the literature. Seventeen potential users tested ICEMAN; their suggestions improved the user-friendliness of the instrument.Interpretation: The Instrument for assessing the Credibility of Effect Modification Analyses offers explicit guidance for investigators, systematic reviewers, journal editors and others considering making a claim of effect modification or interpreting a claim made by others. [ABSTRACT FROM AUTHOR]

Background: COVID-19 is a rapidly spreading virus infection that has quickly caused extensive burden to individual, families, countries, and the globe. No intervention has yet been proven effective for the treatment of COVID-19. Some randomized clinical trials assessing the effects of different drugs have been published, and more are currently underway. There is an urgent need for a living, dynamic systematic review that continuously evaluates the beneficial and harmful effects of all available interventions for COVID-19. Methods/design: We will conduct a living systematic review based on searches of major medical databases (e.g., MEDLINE, EMBASE, CENTRAL) and clinical trial registries from their inception onwards to identify relevant randomized clinical trials. We will update the literature search once a week to continuously assess if new evidence is available. Two review authors will independently extract data and perform risk of bias assessment. We will include randomized clinical trials comparing any intervention for the treatment of COVID-19 (e.g., pharmacological interventions, fluid therapy, invasive or noninvasive ventilation, or similar interventions) with any comparator (e.g., an "active" comparator, standard care, placebo, no intervention, or "active placebo") for participants in all age groups with a diagnosis of COVID-19. Primary outcomes will be all-cause mortality and serious adverse events. Secondary outcomes will be admission to intensive care, mechanical ventilation, renal replacement therapy, quality of life, and non-serious adverse events. The living systematic review will include aggregate data meta-analyses, Trial Sequential Analyses, network meta-analysis, and individual patient data meta-analyses. Risk of bias will be assessed with domains, an eight-step procedure will be used to assess if the thresholds for clinical significance are crossed, and the certainty of the evidence will be assessed by Grading of Recommendations, Assessment, Development and Evaluations (GRADE). Discussion: COVID-19 has become a pandemic with substantial mortality. A living systematic review evaluating the beneficial and harmful effects of pharmacological and other interventions is urgently needed. This review will continuously inform best practice in treatment and clinical research of this highly prevalent disease. Systematic review registration: PROSPERO CRD42020178787 [ABSTRACT FROM AUTHOR]

Background: Frequent users of emergency medical services for issues that could be more appropriately managed through non-urgent care deplete the limited resources of the health-care system. Community paramedicine is an emerging field that extends the role of paramedics beyond the traditional emergency response. The goal of the current study is to evaluate the impact of a community paramedicine home-visit intervention with frequent users on reducing ambulance calls, hospital visits, and admissions. The study will also provide a cross-sectional description of the characteristics of frequent users of emergency medical services.Methods/design: An open-label, pragmatic, randomized controlled trial with parallel intervention and control groups will be conducted in four paramedic services in Ontario. The sample size has been calculated as 261 per group for a 25% reduction in ambulance calls. Eligible participants will be frequent callers (three or more calls in 6 months), individuals who call for at least one lift assist, or individuals referred to the program by a paramedic. Individuals will be randomly allocated to receive either the Community Paramedicine at Home (CP@home) program intervention or their usual care (control). Intervention participants will receive up to three visits from a community paramedic, who will conduct health risk assessments, provide health promotion and education, provide referrals to local resources, and fax reports back to the family physician. Data will be collected from administrative databases (e.g., paramedic services), a custom CP@home program database, participant surveys, and key informant interviews. An intention-to-treat analysis will be conducted, including descriptive statistics and multi-level modeling to find factors predictive of primary and secondary outcomes. A thematic analysis will be used to analyze the qualitative outcomes. An economic analysis will consider the cost-effectiveness of the program.Discussion: CP@home has the potential to reduce the health-care system burden significantly by targeting current frequent users of emergency medical services. By targeting this population, CP@home aims to decrease ambulance calls and emergency department visits, reducing health-care costs and improving the quality of life of a vulnerable population. If successful, CP@home will inform the development of community paramedicine policies and the expanding role of paramedics in regions across Canada.Trial Registration: ClinicalTrials.gov, NCT02835989 . Registered on July 14 2016. [ABSTRACT FROM AUTHOR]

Purpose: Reporting guidelines (eg, Consolidated Standards of Reporting Trials [CONSORT] statement) are intended to improve reporting standards and enhance the transparency and reproducibility of research findings. Despite accessibility of such guidelines, researchers are not required to adhere to them. Our goal was to determine the current status of reporting quality in the medical literature and examine whether adherence of reporting guidelines has improved since the inception of reporting guidelines. Materials and methods: Eight reporting guidelines, such as CONSORT, Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), STrengthening the Reporting of OBservational studies in Epidemiology (STROBE), Quality of Reporting of Meta-analysis (QUOROM), STAndards for Reporting of Diagnostic accuracy (STARD), Animal Research: Reporting In Vivo Experiments (ARRIVE), Consolidated Health Economic Evaluation Reporting Standards (CHEERS), and Meta-analysis of Observational Studies in Epidemiology (MOOSE) were examined. Our inclusion criteria included reviews published between January 1996 to September 2016 which investigated the adherence to reporting guidelines in the literature that addressed clinical trials, systematic reviews, observational studies, meta-analysis, diagnostic accuracy, economic evaluations, and preclinical animal studies that were in English. All reviews were found on Web of Science, Excerpta Medical Database (EMBASE), MEDLINE, and Cumulative Index to Nursing and Allied Health Literature (CINAHL). Results: Among the general searching of 26,819 studies by using the designed searching method, 124 studies were included post screening. We found that 87.9% of the included studies reported suboptimal adherence to reporting guidelines. Factors associated with poor adherence included non-pharmacological interventions, year of publication, and trials concluding with significant results. Improved adherence was associated with better study designs such as allocation concealment, random sequence, large sample sizes, adequately powered studies, multiple authorships, and being published in journals endorsing guidelines. Conclusion: We conclude that the level of adherence to reporting guidelines remains suboptimal. Endorsement of reporting guidelines by journals is important and recommended. [ABSTRACT FROM AUTHOR]

Background: The pragmatic-explanatory continuum indicator summary version 2 (PRECIS-2) tool has recently been developed to classify randomized clinical trials (RCTs) as pragmatic or explanatory based on their design characteristics. Given that treatment effects in explanatory trials may be greater than those obtained in pragmatic trials, conventional meta-analytic approaches may not accurately account for the heterogeneity among the studies and may result in biased treatment effect estimates. This study investigates if the incorporation of PRECIS-2 classification of published trials can improve the estimation of overall intervention effects in meta-analysis. Methods: Using data from 31 published trials of intervention aimed at reducing obesity in children, we evaluated the utility of incorporating PRECIS-2 ratings of published trials into meta-analysis of intervention effects in clinical trials. Specifically, we compared random-effects meta-analysis, stratified meta-analysis, random-effects meta-regression, and mixture random-effects meta-regression methods for estimating overall pooled intervention effects. Results: Our analyses revealed that mixture meta-regression models that incorporate PRECIS-2 classification as covariate resulted in a larger pooled effect size (ES) estimate (ES = - 1.01, 95%CI = [- 1.52, - 0.43]) than conventional random-effects meta-analysis (ES = - 0.15, 95%CI = [- 0.23, - 0.08]). Conclusions: In addition to the original intent of PRECIS-2 tool of aiding researchers in their choice of trial design, PRECIS-2 tool is useful for explaining between study variations in systematic review and meta-analysis of published trials. We recommend that researchers adopt mixture meta-regression methods when synthesizing evidence from explanatory and pragmatic trials. [ABSTRACT FROM AUTHOR]

Aim: Article retraction is a measure taken by journals or authors where there is evidence of research misconduct or error, redundancy, plagiarism or unethical research. Recently, the retraction of scientific publications has been on the rise. In this survey, we aimed to describe the characteristics and distribution of retracted articles and the reasons for retractions. Methods: We searched retracted articles on the PubMed database and Retraction Watch website from 1980 to February 2016. The primary outcomes were the characteristics and distribution of retracted articles and the reasons for retractions. The secondary outcomes included how article retractions were handled by journals and how to improve the journal practices toward article retractions. Results: We included 1,339 retracted articles. Most retracted articles had six authors or fewer. Article retraction was most common in the USA (26%), Japan (11%) and Germany (10%). The main reasons for article retraction were misconduct (51%, n = 685) and error (14%, n = 193). There were 66% (n = 889) of retracted articles having male senior or corresponding authors. Of the articles retracted after August 2010, 63% (n = 567) retractions were reported on Retraction Watch. Large discrepancies were observed in the ways that different journals handled article retractions. For instance, articles were completely withdrawn from some journals, while in others, articles were still available with no indication of retraction. Likewise, some retraction notices included a detailed account of the events that led to article retraction, while others only consisted of a statement indicating the article retraction. Conclusion: The characteristics, geographic distribution and reasons for retraction of published articles involving human research participants were examined in this survey. More efforts are needed to improve the consistency and transparency of journal practices toward article retractions. [ABSTRACT FROM AUTHOR]

In clinical trials it is not uncommon to face a multiple testing problem which can have an impact on both type I and type II error rates, leading to inappropriate interpretation of trial results. Multiplicity issues may need to be considered at the design, analysis and interpretation stages of a trial. The proportion of trial reports not adequately correcting for multiple testing remains substantial. The purpose of this article is to provide an introduction to multiple testing issues in clinical trials, and to reduce confusion around the need for multiplicity adjustments. We use a tutorial, question-and-answer approach to address the key issues of why, when and how to consider multiplicity adjustments in trials. We summarize the relevant circumstances under which multiplicity adjustments ought to be considered, as well as options for carrying out multiplicity adjustments in terms of trial design factors including Population, Intervention/Comparison, Outcome, Time frame and Analysis (PICOTA). Results are presented in an easy-to-use table and flow diagrams. Confusion about multiplicity issues can be reduced or avoided by considering the potential impact of multiplicity on type I and II errors and, if necessary pre-specifying statistical approaches to either avoid or adjust for multiplicity in the trial protocol or analysis plan. [ABSTRACT FROM AUTHOR]

Background: Sharing interim data, results or result extrapolations is an important issue that can affect trial integrity. The different ways in which Data Safety Monitoring Boards (DSMBs) share interim results with non-DSMB members and the acceptability of such practices are poorly understood. Our objective was to undertake a narrative review specifically on what kind of interim results, if any, should be shared by the DSMB with non-DSMB members and why.Methods: We conducted a narrative review using a systematic search strategy of several databases and major health research stakeholders. Literature was included if there was some discussion within the full text about sharing interim trial results with non-DSMB members.Results: About 79.6% (129/162) of included citations were based on author's views, 16.7% (27/162) on research guidelines and 3.7% (6/162) on surveys. The largest group of citations, 73/162 (45%), expresses the opinion or argument against sharing interim results with exceptions. Trailing closely, 71/162 (43.8%) of the included citations support the opinion or argument that interim results should not be shared and should remain confidential with the DSMB. Half of the six surveys support sharing in some capacity, while the other three do not. Eleven circumstances were found that potentially warrant interim result sharing by the DSMB; they relate to (1) usual practices by DSMBs, (2) trial completion threatened, (3) patient safety, (4) regulatory approval and (5) other circumstances. Dominant risks for sharing under these conditions are associated with introducing trial bias.Discussion/conclusion: There was no majority view in the literature. However, the largest group of citations included express the idea that interim results should remain confidential with the DSMB but also acknowledge circumstances when they could be shared with non-DSMB members. Limitations of this review are that (1) the included literature predominately provides personal perspectives, not evidence, and (2) surveys found globally focus on trial monitoring practices lacking detailed information on what specifically to share, with whom and why. More research is needed with the use of a detailed survey of the clinical trial community focused on DSMB sharing interim results, to better understand and guide DSMB interim result sharing practices. [ABSTRACT FROM AUTHOR]

Lessons learned from Integrated Management Program Advancing Community Treatment of Atrial Fibrillation (IMPACT-AF): a pragmatic clinical trial of computerized decision support in primary care. B Correction: Trials 22, 531 (2021) b https://doi.org/10.1186/s13063-021-05488-y Following the publication of the original article [[1]], we were notified that Fig. [Extracted from the article]

In the article, the authors present their study on the temporal trends of enrolling Black, Indigenous and other people of color (BIPOC) in randomized controlled trials (RCT) of diabetes in North America and Europe. Topics include the importance of representativeness in clinical trials as per the U.S. Food and Drug Administration (FDA) and the National Institutes of Health, and the use of resources like the Cochrane Library in the diabetes RTC studies.

We describe a framework for defining pilot and feasibility studies focusing on studies conducted in preparation for a randomised controlled trial. To develop the framework, we undertook a Delphi survey; ran an open meeting at a trial methodology conference; conducted a review of definitions outside the health research context; consulted experts at an international consensus meeting; and reviewed 27 empirical pilot or feasibility studies. We initially adopted mutually exclusive definitions of pilot and feasibility studies. However, some Delphi survey respondents and the majority of open meeting attendees disagreed with the idea of mutually exclusive definitions. Their viewpoint was supported by definitions outside the health research context, the use of the terms ‘pilot’ and ‘feasibility’ in the literature, and participants at the international consensus meeting. In our framework, pilot studies are a subset of feasibility studies, rather than the two being mutually exclusive. A feasibility study asks whether something can be done, should we proceed with it, and if so, how. A pilot study asks the same questions but also has a specific design feature: in a pilot study a future study, or part of a future study, is conducted on a smaller scale. We suggest that to facilitate their identification, these studies should be clearly identified using the terms ‘feasibility’ or ‘pilot’ as appropriate. This should include feasibility studies that are largely qualitative; we found these difficult to identify in electronic searches because researchers rarely used the term ‘feasibility’ in the title or abstract of such studies. Investigators should also report appropriate objectives and methods related to feasibility; and give clear confirmation that their study is in preparation for a future randomised controlled trial designed to assess the effect of an intervention. [ABSTRACT FROM AUTHOR]

Background: Eligibility criteria that result in the exclusion of a substantial number of patients from randomized trials jeopardize the generalizability of treatment effect to much of the clinical population. This is important when evaluating opioid substitution and antagonist therapies (OSATs), especially given the challenges associated with treating the opioid-dependent population. We aimed to identify OSAT trials' eligibility criteria, quantify the percentage of the clinical population excluded by these criteria, and determine how OSAT guidelines incorporate evidence from these trials.Methods: We performed a systematic review to identify the eligibility criteria used across trials. We searched Medline, EMBASE, PsycINFO, Web of Science, Cochrane Library, Cochrane Clinical Trials Registry (CTR), World Health Organization International CTR Platform Search Portal, and the National Institutes of Health CTR databases from inception to January 1, 2014. To quantify the effect of trials' eligibility criteria on generalizability, we applied these criteria to data from an observational study of opioid-dependent patients (n = 394). We then accessed the Canadian, American, British, and World Health Organization (WHO) OSAT guidelines to evaluate how evidence is used in the recommendations.Results: Among the 60 trials identified the majority (≥50 % of trials) exclude patients with psychiatric (60 %) and physical comorbidity (51.7 %). Additionally, we found 19 trials exclude patients with current alcohol/substance-use problems (31.7 %), and 29 (48.3 %) exclude patients taking psychotropic medications. These criteria were restrictive and in some cases rendered 70 % of the observational sample ineligible. North American OSAT guidelines made strong recommendations supported by evidence with poor generalizability. National Institute of Health and Care Excellence (NICE) and WHO guidelines for opioid misuse provide a critical assessment of the literature used to inform their recommendations.Conclusions: Trials assessing OSATs often exclude patients with concurrent disorders. If the excluded patients respond differently to treatment, results from these trials are likely to overestimate the true effectiveness of OSATs. North American guidelines should consider these limitations when drafting clinical recommendations. [ABSTRACT FROM AUTHOR]

Knowledge translation (KT) involves implementation of evidence-based strategies and guidelines into practice to improve the process of care and health outcomes for patients. Findings from pragmatic trials may be used in KT to provide patients, healthcare providers and policymakers with information to optimize healthcare decisions based on how a given strategy or intervention performs under the real world conditions. However, pragmatic trials have been criticized for having the following problems: i) high rates of loss to follow-up; ii) nonadherence to study intervention; iii) unblinded treatment and patient self-assessment, which can potentially create bias; iv) being less perfect experiments than efficacy trials; v) sacrificing internal validity to achieve generalizability; and vi) often requiring large sample sizes to detect small treatment effects in heterogeneous populations. In this paper, we discuss whether these criticisms hold merit, or if they are simply driven by confusion about the purpose of pragmatic trials. We use the Cardiovascular Health Awareness Program (CHAP) trial - a community randomized pragmatic trial designed to assess whether offering a highly organized, community-based CHAP intervention compared to usual care can reduce cardiovascular disease-related outcomes - to address these specific criticisms and illustrate how to reduce this confusion. [ABSTRACT FROM AUTHOR]

Focus of Presentation A randomized clinical trial is considered the best experimental study design for comparing the effect of an intervention against a control. Selecting a trial design depends on the trial objective, a better choice would be a design that provides optimal estimation of the intervention effect, i.e. a design that yields smaller variance for the estimated intervention effect and giving stable estimates. The choice of analysis method depends on trial design aspects, reasonable assumption on the underlying probabilistic model generating the data and the credibility of findings depend on the appropriateness of the analysis method used. Here, we describe a planned randomized standard of care-controlled trial on interactive weekly mobile text messaging added to a motivational interviewing intervention aimed at sustaining continued breastfeeding among women living with HIV in South Africa. Under the "findings" heading, we highlight some of the trial design and statistical issues for discussion at the early career workshop, to gain insights on possible approaches to address the methods issues. Methods and trial design: Women from peri-urban informal settlements and a rural setting will be invited to participate within 24 hours of giving birth at selected primary healthcare facilities. Eligible women will be individually randomized to intervention or control arm after providing written informed consent. The intervention will consist of a weekly text message encouraging women to exclusively breastfeed and inquiring if they have any problems breastfeeding their infants. In addition to text messaging, women assigned to the intervention arm must visit the research site where a research nurse or counsellor will conduct an individual motivational interview, at weeks 2, 6, and 10 post-delivery. Women assigned to the control arm will be counselled by the standard of care service, i.e. primary healthcare nurses and trained counsellors will counsel women to exclusively breastfeed for the first six months through group educational infant feeding counselling sessions. Study participation will not change standard of care of participants, so women assigned to the intervention arm will receive the standard of care service, in line with provincial guidelines applicable in the sector during the study period. The primary outcomes are 1) number of women who are exclusively breastfeeding at week 24 post-delivery and 2) number of women reporting any breastfeeding at week 24 post-delivery. Findings or trial design and statistical issues Although women are individually randomly assigned to intervention and control arms, the standard of care at the primary health care facility may induce a dependency between these participants, also called the group therapy effect. For example, promotion of exclusive breastfeeding in HIV-infected women may be enhanced through positive feedback from women who follow this practice or vice versa. The standard of care will be clustered within group infant feeding counselling session, where participants (both assigned to the control and intervention arm) will receive the standard of care in groups. Women assigned to the intervention arm will receive individual motivational interview and the text messages will be send separately, to each woman's mobile phone. Implications The trial objective will be to determine whether at week 24 following delivery, weekly text message added to motivational interview leads to better adherence to exclusive breastfeeding and leads to extended breastfeeding than standard of care. Trial design and statistical issues to discuss during the workshop will include a discussion around: 1) the appropriateness of invoking the standard experimental design to address the study objectives, and possible alternatives 2) Sample size estimation for a trial comparing group and individual treatments? 3) Reasonable assumption on the underlying probabilistic model generating the outcome data and 4) Candidate statistical models. Key messages Use of sound statistical principles of experimental design established for clinical trials allow objective and unbiased comparisons. [ABSTRACT FROM AUTHOR]

Background: No proof of efficacy, in the form of a randomized controlled trial (RCT), exists to support pulsed radiofrequency (PRF) treatment of the dorsal root ganglion (DRG) for chronic lumbar radicular (CLR) pain. We determined the feasibility of a larger trial (primary objective), and also explored the efficacy of PRF in decreasing pain on a visual analog scale (VAS) and improving the Oswestry Disability Index. Methods: This was a single-center, placebo-controlled, triple-blinded RCT. Patients were randomized to a placebo group (needle placement) or a treatment group (PRF at 42°C for 120 seconds to the DRG). Patients were followed up for 3 months post procedure. Outcomes with regard to pain, Oswestry Disability Index score, and side effects were analyzed on an intention-to-treat basis. Results: Over 15 months, 350 potential patients were identified and 56 were assessed for eligibility. Fifteen of them did not meet the selection criteria. Of the 41 eligible patients, 32 (78%) were recruited. One patient opted out before intervention. Three patients were lost to follow-up at 3 months. Mean VAS differences were not significantly different at 4 weeks (-0.36, 95% confidence interval [CI], -2.29, 1.57) or at 3 months (-0.76, 95% CI, -3.14, 1.61). The difference in mean Oswestry Disability Index score was also not significantly different at 4 weeks (-2%, 95% CI, -14%, 10%) or 3 months (-7%, 95% CI, -21%, 6%). There were no major side effects. Six of 16 patients in the PRF group and three of 15 in the placebo group showed a .50% decrease in VAS score. Conclusion: The recruitment rate was partially successful. At 3 months, the relative success of PRF-DRG was small. A large-scale trial to establish efficacy is not practically feasible considering the small effect size, which would necessitate recruitment of a challengingly large number of participants over a number of years. Until clear parameters for application of PRF are established, clinicians will need to use their individual judgment regarding its clinical applicability, given the present evidence. [ABSTRACT FROM AUTHOR]

Background Patients, identified to be at risk for but who have never experienced a potentially lethal cardiac arrhythmia, have the option of receiving an implantable cardioverter defibrillator (ICD) as prophylaxis against sudden cardiac death - a primary prevention indication. In Canada, there is no clear framework to support patients' decision-making for these devices. Decision support, using a decision aid, could moderate treatment-related uncertainty and prepare patients to make well-informed decisions. Patient decision aids provide information on treatment options, risks, and benefits, to help patients clarify their values for outcomes of treatment options. The objectives of this research are: 1) develop a decision aid, 2) evaluate the decision aid, and 3) determine the feasibility of conducting a trial. Methods/design A development panel comprised of the core investigative team, health service researchers, decision science experts, cardiovascular healthcare practitioners, and ICD patient representatives will collaborate to provide input on the content and format of the aid. To generate probabilities to include in the aid, we will synthesize primary prevention ICD evidence. To obtain anonymous input about the facts and content, we will employ a modified Delphi process. To evaluate the draft decision aid will invite ICD patients and their families (n = 30) to rate its acceptability. After we evaluate the aid, to determine the feasibility, we will conduct a feasibility pilot randomized controlled trial (RCT) in new ICD candidates (n = 80). Participants will be randomized to receive a decision aid prior to specialist consultation versus usual care. Results from the pilot RCT will determine the feasibility of research processes; inform sample size calculation, measure decision quality (knowledge, values, decision conflict) and the influence of health related quality of life on decision-making. Discussion Our study seeks to develop a decision aid, for patients offered their first ICD for prophylaxis against sudden cardiac death. This paper outlines the background and methods of a pilot randomized trial which will inform a larger multicenter trial. Ultimately, decision support prior to specialist consultation could enhance the decision-making process between patients, physicians, and families, associated with life-prolonging medical devices like the ICD. [ABSTRACT FROM AUTHOR]

Background: Most HIV prevention strategies assume beneficiaries can act on their prevention decisions. But some people are unable to do so. They are 'choice-disabled'. Economic and educational interventions can reduce sexual violence, but there is less evidence that they can reduce HIV. There is little research on complex interventions in HIV prevention, yet all countries in southern Africa implement combination prevention programmes. Methods/Design: The primary objective is to reduce HIV infections among women aged 15 to 29 years. Secondary objectives are reduction in gender violence and improvement in HIV-related knowledge, attitudes and practices among youth aged 15 to 29 years. A random sample of 77 census enumeration areas in three countries (Botswana, Namibia and Swaziland) was allocated randomly to three interventions, alone or in combination, in a factorial design stratified by country, HIV rates (above or below average for country), and urban/rural location. A baseline survey of youth aged 15 to 29 years provided cluster specific rates of HIV. All clusters continue existing prevention efforts and have a baseline and follow-up survey. Cluster is the unit of allocation, intervention and analysis, using generalised estimating equations, on an intention-to-treat basis. One intervention discusses evidence about choice disability with local HIV prevention services, to help them to serve the choice-disabled. Another discusses an eight-episode audio-docudrama with community groups, of all ages and both sexes, to generate endogenous strategies to reduce gender violence and develop an enabling environment. A third supports groups of women aged 18 to 25 years to build self-esteem and life skills and to set up small enterprises to generate income. A survey in all clusters after 3 years will measure outcomes, with interviewers unaware of group assignment of the clusters. The primary outcome is HIV infection in women aged 15 to 29 years. Secondary outcomes in youth aged 15 to 29 years are gender violence and protective knowledge, attitudes, subjective norms, intention to change, agency, discussion of prevention and practices related to HIV and gender violence. Trial registration: Trial registration number: ISRCTN28557578 [ABSTRACT FROM AUTHOR]

Background: Sensitivity analyses play a crucial role in assessing the robustness of the findings or conclusions based on primary analyses of data in clinical trials. They are a critical way to assess the impact, effect or influence of key assumptions or variations-such as different methods of analysis, definitions of outcomes, protocol deviations, missing data, and outliers-on the overall conclusions of a study. The current paper is the second in a series of tutorial-type manuscripts intended to discuss and clarify aspects related to key methodological issues in the design and analysis of clinical trials. Discussion: In this paper we will provide a detailed exploration of the key aspects of sensitivity analyses including: 1) what sensitivity analyses are, why they are needed, and how often they are used in practice; 2) the different types of sensitivity analyses that one can do, with examples from the literature; 3) some frequently asked questions about sensitivity analyses; and 4) some suggestions on how to report the results of sensitivity analyses in clinical trials. Summary: When reporting on a clinical trial, we recommend including planned or posthoc sensitivity analyses, the corresponding rationale and results along with the discussion of the consequences of these analyses on the overall findings of the study. [ABSTRACT FROM AUTHOR]

In order to improve the generation and use of high quality health research evidence among Cameroonian researchers, the Centre for Development of Best Practices in Health (CDBPH) located in the Yaounde Central Hospital organised a three day workshop on clinical trials from the 29th April to the 1st May 2013. Sixteen participants form the Faculty of Medicine and Biomedical Science of the University of Yaounde 1 and the Ministry of Health attended this workshop. This report includes the material covered in the workshop, the readings and supplementary resources for clinical trials. The workshop was well received by the participants and resulted in significant gains in knowledge on clinical trials. [ABSTRACT FROM AUTHOR]

Background: Subjects with breast cancer enrolled in trials may experience multiple events such as local recurrence, distant recurrence or death. These events are not independent; the occurrence of one may increase the risk of another, or prevent another from occurring. The most commonly used Cox proportional hazards (Cox-PH) model ignores the relationships between events, resulting in a potential impact on the treatment effect and conclusions. The use of statistical methods to analyze multiple time-to-event events has mainly been focused on superiority trials. However, their application to non-inferiority trials is limited. We evaluate four statistical methods for multiple time-to-event endpoints in the context of a non-inferiority trial. Methods: Three methods for analyzing multiple events data, namely, i) the competing risks (CR) model, ii) the marginal model, and iii) the frailty model were compared with the Cox-PH model using data from a previouslyreported non-inferiority trial comparing hypofractionated radiotherapy with conventional radiotherapy for the prevention of local recurrence in patients with early stage breast cancer who had undergone breast conserving surgery. These methods were also compared using two simulated examples, scenario A where the hazards for distant recurrence and death were higher in the control group, and scenario B. where the hazards of distant recurrence and death were higher in the experimental group. Both scenarios were designed to have a non-inferiority margin of 1.50. Results: In the breast cancer trial, the methods produced primary outcome results similar to those using the Cox-PH model: namely, a local recurrence hazard ratio (HR) of 0.95 and a 95% confidence interval (CI) of 0.62 to 1.46. In Scenario A, non-inferiority was observed with the Cox-PH model (HR = 1.04; CI of 0.80 to 1.35), but not with the CR model (HR = 1.37; CI of 1.06 to 1.79), and the average marginal and frailty model showed a positive effect of the experimental treatment. The results in Scenario A contrasted with Scenario B with non-inferiority being observed with the CR model (HR = 1.10; CI of 0.87 to 1.39), but not with the Cox-PH model (HR = 1.46; CI of 1.15 to 1.85), and the marginal and frailty model showed a negative effect of the experimental treatment. Conclusion: When subjects are at risk for multiple events in non-inferiority trials, researchers need to consider using the CR, marginal and frailty models in addition to the Cox-PH model in order to provide additional information in describing the disease process and to assess the robustness of the results. In the presence of competing risks, the Cox-PH model is appropriate for investigating the biologic effect of treatment, whereas the CR models yields the actual effect of treatment in the study. [ABSTRACT FROM AUTHOR]

Background: Venous thromboembolism (VTE) is a common preventable cause of mortality in hospitalized medical patients. Despite rigorous randomized trials generating strong recommendations for anticoagulant use to prevent VTE, nearly 40% of medical patients receive inappropriate thromboprophylaxis. Knowledge-translation strategies are needed to bridge this gap. Methods: We conducted a 16-week pilot cluster randomized controlled trial (RCT) to determine the proportion of medical patients that were appropriately managed for thromboprophylaxis (according to the American College of Chest Physician guidelines) within 24 hours of admission, through the use of a multicomponent knowledgetranslation intervention. Our primary goal was to determine the feasibility of conducting this study on a larger scale. The intervention comprised clinician education, a paper-based VTE risk assessment algorithm, printed physicians' orders, and audit and feedback sessions. Medical wards at six hospitals (representing clusters) in Ontario, Canada were included; three were randomized to the multicomponent intervention and three to usual care (i.e., no active strategies for thromboprophylaxis in place). Blinding was not used. Results: A total of 2,611 patients (1,154 in the intervention and 1,457 in the control group) were eligible and included in the analysis. This multicomponent intervention did not lead to a significant difference in appropriate VTE prophylaxis rates between intervention and control hospitals (appropriate management rate odds ratio = 0.80; 95% confidence interval: 0.50, 1.28; p = 0.36; intra-class correlation coefficient: 0.022), and thus was not considered feasible. Major barriers to effective knowledge translation were poor attendance by clinical staff at education and feedback sessions, difficulty locating preprinted orders, and lack of involvement by clinical and administrative leaders. We identified several factors that may increase uptake of a VTE prophylaxis strategy, including local champions, support from clinical and administrative leaders, mandatory use, and a simple, clinically relevant risk assessment tool. Conclusions: Hospitals allocated to our multicomponent intervention did not have a higher rate of medical inpatients appropriately managed for thromboprophylaxis than did hospitals that were not allocated to this strategy. [ABSTRACT FROM AUTHOR]

Mentoring plays an important role in learning and career development. Mentored researchers are more productive and more likely to publish their work. However, mentorship programs are not universally used in most settings or disciplines. Furthermore, successful and mutually beneficial mentoring relationships are not always easy to arrange. Long-distance mentoring relationships are even more difficult to handle and may break down for a wide variety of reasons. Drawing from our experiences with the first Canadian Institutes of Health Research - Canadian HIV Trials Network international postdoctoral fellowship program, we describe the roles of the context, the key mentor and the mentee attributes; goals and expectations; environments, local support, a communication plan, funding, face-to-face contact, multidisciplinary collaboration, co-mentoring, and evaluation as they apply to the successful implementation of a long-distance mentoring program. [ABSTRACT FROM AUTHOR]

Background: Assessment of heterogeneity is essential in systematic reviews and meta-analyses of clinical trials. The most commonly used heterogeneity measure, I2, provides an estimate of the proportion of variability in a meta-analysis that is explained by differences between the included trials rather than by sampling error. Recent studies have raised concerns about the reliability of I2 estimates, due to their dependence on the precision of included trials and time-dependent biases. Authors have also advocated use of 95% confidence intervals (CIs) to express the uncertainty associated with I2 estimates. However, no previous studies have explored how many trials and events are required to ensure stable and reliable I2 estimates, or how 95% CIs perform as evidence accumulates. Methodology/Principal Findings: To assess the stability and reliability of I2 estimates and their 95% CIs, in relation to the cumulative number of trials and events in meta-analysis, we looked at 16 large Cochrane meta-analyses - each including a sufficient number of trials and events to reliably estimate I2 - and monitored the I2 estimates and their 95% CIs for each year of publication. In 10 of the 16 meta-analyses, the I2 estimates fluctuated more than 40% over time. The median number of events and trials required before the cumulative I2 estimates stayed within +/220% of the final I2 estimate was 467 and 11. No major fluctuations were observed after 500 events and 14 trials. The 95% confidence intervals provided good coverage over time. Conclusions/Significance: I2 estimates need to be interpreted with caution when the meta-analysis only includes a limited number of events or trials. Confidence intervals for I2 estimates provide good coverage as evidence accumulates, and are thus valuable for reflecting the uncertainty associated with estimating I2. [ABSTRACT FROM AUTHOR]

Background: Multicentre randomized controlled trials (RCTs) routinely use randomization and analysis stratified by centre to control for differences between centres and to improve precision. No consensus has been reached on how to best analyze correlated continuous outcomes in such settings. Our objective was to investigate the properties of commonly used statistical models at various levels of clustering in the context of multicentre RCTs. Methods: Assuming no treatment by centre interaction, we compared six methods (ignoring centre effects, including centres as fixed effects, including centres as random effects, generalized estimating equation (GEE), and fixed- and random-effects centre-level analysis) to analyze continuous outcomes in multicentre RCTs using simulations over a wide spectrum of intraclass correlation (ICC) values, and varying numbers of centres and centre size. The performance of models was evaluated in terms of bias, precision, mean squared error of the point estimator of treatment effect, empirical coverage of the 95% confidence interval, and statistical power of the procedure. Results: While all methods yielded unbiased estimates of treatment effect, ignoring centres led to inflation of standard error and loss of statistical power when within centre correlation was present. Mixed-effects model was most efficient and attained nominal coverage of 95% and 90% power in almost all scenarios. Fixed-effects model was less precise when the number of centres was large and treatment allocation was subject to chance imbalance within centre. GEE approach underestimated standard error of the treatment effect when the number of centres was small. The two centre-level models led to more variable point estimates and relatively low interval coverage or statistical power depending on whether or not heterogeneity of treatment contrasts was considered in the analysis. Conclusions: All six models produced unbiased estimates of treatment effect in the context of multicentre trials. Adjusting for centre as a random intercept led to the most efficient treatment effect estimation across all simulations under the normality assumption, when there was no treatment by centre interaction. [ABSTRACT FROM AUTHOR]

The Biostatistics and Methodological Innovation Working (BMIW) Group is one of several working groups within the CANadian Network and Centre for Trials INternationally (CANNeCTIN). This programme received funding from the Canadian Institutes of Health Research and the Canada Foundation for Innovation beginning in 2008, to enhance the infrastructure and build capacity for large Canadian-led clinical trials in cardiovascular diseases (CVD) and diabetes mellitus (DM). The overall aims of the BMIW Group's programme within CANNeCTIN, are to advance biostatistical and methodological research, and to build biostatistical capacity in CVD and DM. Our program of research and training includes: monthly videoconferences on topical biostatistical and methodological issues in CVD/DM clinical studies; providing presentations on methods issues at the annual CANNeCTIN meetings; collaborating with clinician investigators on their studies; training young statisticians in biostatistics and methods in CVD/DM trials and organizing annual symposiums on topical methodological issues. We are focused on the development of new biostatistical methods and the recruitment and training of highly qualified personnel - who will become leaders in the design and analysis of CVD/DM trials. The ultimate goal is to enhance global health by contributing to efforts to reduce the burden of CVD and DM. [ABSTRACT FROM AUTHOR]

Background: Attrition, which leads to missing data, is a common problem in cluster randomized trials (CRTs), where groups of patients rather than individuals are randomized. Standard multiple imputation (MI) strategies may not be appropriate to impute missing data from CRTs since they assume independent data. In this paper, under the assumption of missing completely at random and covariate dependent missing, we compared six MI strategies which account for the intra-cluster correlation for missing binary outcomes in CRTs with the standard imputation strategies and complete case analysis approach using a simulation study. Method: We considered three within-cluster and three across-cluster MI strategies for missing binary outcomes in CRTs. The three within-cluster MI strategies are logistic regression method, propensity score method, and Markov chain Monte Carlo (MCMC) method, which apply standard MI strategies within each cluster. The three across-cluster MI strategies are propensity score method, random-effects (RE) logistic regression approach, and logistic regression with cluster as a fixed effect. Based on the community hypertension assessment trial (CHAT) which has complete data, we designed a simulation study to investigate the performance of above MI strategies. Results: The estimated treatment effect and its 95% confidence interval (CI) from generalized estimating equations (GEE) model based on the CHAT complete dataset are 1.14 (0.76 1.70). When 30% of binary outcome are missing completely at random, a simulation study shows that the estimated treatment effects and the corresponding 95% CIs from GEE model are 1.15 (0.76 1.75) if complete case analysis is used, 1.12 (0.72 1.73) if within-cluster MCMC method is used, 1.21 (0.80 1.81) if across-cluster RE logistic regression is used, and 1.16 (0.82 1.64) if standard logistic regression which does not account for clustering is used. Conclusion: When the percentage of missing data is low or intra-cluster correlation coefficient is small, different approaches for handling missing binary outcome data generate quite similar results. When the percentage of missing data is large, standard MI strategies, which do not take into account the intra-cluster correlation, underestimate the variance of the treatment effect. Within-cluster and across-cluster MI strategies (except for random-effects logistic regression MI strategy), which take the intra-cluster correlation into account, seem to be more appropriate to handle the missing outcome from CRTs. Under the same imputation strategy and percentage of missingness, the estimates of the treatment effect from GEE and RE logistic regression models are similar. [ABSTRACT FROM AUTHOR]

Data sharing from clinical trials is one way of promoting fair and transparent conduct of clinical trials. It would maximise the use of data and permit the exploration of additional hypotheses. On the other hand, the quality of secondary analyses cannot always be ascertained, and it may be unfair to investigators who have expended resources to collect data to bear the additional burden of sharing. As the discussion on the best modalities of sharing data evolves, some of the practical issues that may arise need to be addressed. In this paper, we discuss issues which impede the use of data even when sharing should be possible: (1) multicentre studies requiring consent from all the investigators in each centre; (2) remote access platforms with software limitations and Internet requirements; (3) on-site data analysis when data cannot be moved; (4) governing bodies for data generated in one jurisdiction and analysed in another; (5) using programmatic data collected as part of routine care; (6) data collected in multiple languages; (7) poor data quality. We believe these issues apply to all primary data and cause undue difficulties in conducting analysis even when there is some willingness to share. They can be avoided by anticipating the possibility of sharing any clinical data and pre-emptively removing or addressing restrictions that limit complete sharing. These issues should be part of the data sharing discussion. [ABSTRACT FROM AUTHOR]

Background: Investigators designing clinical trials often use composite outcomes to overcome many statistical issues. Trialists want to maximize power to show a statistically significant treatment effect and avoid inflation of Type I error rate due to evaluation of multiple individual clinical outcomes. However, if the treatment effect is not similar among the components of this composite outcome, we are left not knowing how to interpret the treatment effect on the composite itself. Given significant heterogeneity among these components, a composite outcome may be judged as being invalid or un-interpretable for estimation of the treatment effect. This paper compares the power of different tests to detect heterogeneity of treatment effect across components of a composite binary outcome. Methods: Simulations were done comparing four different models commonly used to analyze correlated binary data. These models included: logistic regression for ignoring correlation, logistic regression weighted by the intra cluster correlation coefficient, population average logistic regression using generalized estimating equations (GEE), and random effects logistic regression. Results: We found that the population average model based on generalized estimating equations (GEE) had the greatest power across most scenarios. Adequate power to detect possible composite heterogeneity or variation between treatment effects of individual components of a composite outcome was seen when the power for detecting the main study treatment effect for the composite outcome was also reasonably high. Conclusions: It is recommended that authors report tests of composite heterogeneity for composite outcomes and that this accompany the publication of the statistically significant results of the main effect on the composite along with individual components of composite outcomes. [ABSTRACT FROM AUTHOR]

Pilot studies for phase III trials - which are comparative randomized trials designed to provide preliminary evidence on the clinical efficacy of a drug or intervention - are routinely performed in many clinical areas. Also commonly know as "feasibility" or "vanguard" studies, they are designed to assess the safety of treatment or interventions; to assess recruitment potential; to assess the feasibility of international collaboration or coordination for multicentre trials; to increase clinical experience with the study medication or intervention for the phase III trials. They are the best way to assess feasibility of a large, expensive full-scale study, and in fact are an almost essential pre-requisite. Conducting a pilot prior to the main study can enhance the likelihood of success of the main study and potentially help to avoid doomed main studies. The objective of this paper is to provide a detailed examination of the key aspects of pilot studies for phase III trials including: 1) the general reasons for conducting a pilot study; 2) the relationships between pilot studies, proof-of-concept studies, and adaptive designs; 3) the challenges of and misconceptions about pilot studies; 4) the criteria for evaluating the success of a pilot study; 5) frequently asked questions about pilot studies; 7) some ethical aspects related to pilot studies; and 8) some suggestions on how to report the results of pilot investigations using the CONSORT format. [ABSTRACT FROM AUTHOR]

Background: Patients with early stage papillary thyroid carcinoma (PTC), are faced with the decision to either to accept or reject adjuvant radioactive iodine (RAI) treatment after thryroidectomy. This decision is often difficult because of conflicting reports of RAI treatment benefit and medical evidence uncertainty due to the lack of long-term randomized controlled trials. Methods: We report the protocol for a parallel, 2-arm, randomized trial comparing an intervention group exposed to a computerized decision aid (DA) relative to a control group receiving usual care. The DA explains the options of adjuvant radioactive iodine or no adjuvant radioactive iodine, as well as associated potential benefits, risks, and follow-up implications. Potentially eligible adult PTC patient participants will include: English-speaking individuals who have had recent thyroidectomy, and whose primary tumor was 1 to 4 cm in diameter, with no known metastases to lymph nodes or distant sites, with no other worrisome features, and who have not received RAI treatment for thyroid cancer. We will measure the effect of the DA on the following patient outcomes: a) knowledge about PTC and RAI treatment, b) decisional conflict, c) decisional regret, d) client satisfaction with information received about RAI treatment, and e) the final decision to accept or reject adjuvant RAI treatment and rationale. Discussion: This trial will provide evidence of feasibility and efficacy of the use of a computerized DA in explaining complex issues relating to decision making about adjuvant RAI treatment in early stage PTC. Trial registration: Clinical Trials.gov Identifier: NCT01083550 [ABSTRACT FROM AUTHOR]