Interventions to prevent obesity in children aged 12 to 18 years old.

BACKGROUND: Prevention of obesity in adolescents is an international public health priority. The prevalence of overweight and obesity is over 25% in North and South America, Australia, most of Europe, and the Gulf region. Interventions that aim to prevent obesity involve strategies that promote healthy diets or 'activity' levels (physical activity, sedentary behaviour and/or sleep) or both, and work by reducing energy intake and/or increasing energy expenditure, respectively. There is uncertainty over which approaches are more effective, and numerous new studies have been published over the last five years since the previous version of this Cochrane Review. OBJECTIVES: To assess the effects of interventions that aim to prevent obesity in adolescents by modifying dietary intake or 'activity' levels, or a combination of both, on changes in BMI, zBMI score and serious adverse events. SEARCH METHODS: We used standard, extensive Cochrane search methods. The latest search date was February 2023. SELECTION CRITERIA: Randomised controlled trials in adolescents (mean age 12 years and above but less than 19 years), comparing diet or 'activity' interventions (or both) to prevent obesity with no intervention, usual care, or with another eligible intervention, in any setting. Studies had to measure outcomes at a minimum of 12 weeks post baseline. We excluded interventions designed primarily to improve sporting performance. DATA COLLECTION AND ANALYSIS: We used standard Cochrane methods. Our outcomes were BMI, zBMI score and serious adverse events, assessed at short- (12 weeks to < 9 months from baseline), medium- (9 months to < 15 months) and long-term (≥ 15 months) follow-up. We used GRADE to assess the certainty of the evidence for each outcome. MAIN RESULTS: This review includes 74 studies (83,407 participants); 54 studies (46,358 participants) were included in meta-analyses. Sixty studies were based in high-income countries. The main setting for intervention delivery was schools (57 studies), followed by home (nine studies), the community (five studies) and a primary care setting (three studies). Fifty-one interventions were implemented for less than nine months; the shortest was conducted over one visit and the longest over 28 months. Sixty-two studies declared non-industry funding; five were funded in part by industry. Dietary interventions versus control The evidence is very uncertain about the effects of dietary interventions on body mass index (BMI) at short-term follow-up (mean difference (MD) -0.18, 95% confidence interval (CI) -0.41 to 0.06; 3 studies, 605 participants), medium-term follow-up (MD -0.65, 95% CI -1.18 to -0.11; 3 studies, 900 participants), and standardised BMI (zBMI) at long-term follow-up (MD -0.14, 95% CI -0.38 to 0.10; 2 studies, 1089 participants); all very low-certainty evidence. Compared with control, dietary interventions may have little to no effect on BMI at long-term follow-up (MD -0.30, 95% CI -1.67 to 1.07; 1 study, 44 participants); zBMI at short-term (MD -0.06, 95% CI -0.12 to 0.01; 5 studies, 3154 participants); and zBMI at medium-term (MD 0.02, 95% CI -0.17 to 0.21; 1 study, 112 participants) follow-up; all low-certainty evidence. Dietary interventions may have little to no effect on serious adverse events (two studies, 377 participants; low-certainty evidence). Activity interventions versus control Compared with control, activity interventions do not reduce BMI at short-term follow-up (MD -0.64, 95% CI -1.86 to 0.58; 6 studies, 1780 participants; low-certainty evidence) and probably do not reduce zBMI at medium- (MD 0, 95% CI -0.04 to 0.05; 6 studies, 5335 participants) or long-term (MD -0.05, 95% CI -0.12 to 0.02; 1 study, 985 participants) follow-up; both moderate-certainty evidence. Activity interventions do not reduce zBMI at short-term follow-up (MD 0.02, 95% CI -0.01 to 0.05; 7 studies, 4718 participants; high-certainty evidence), but may reduce BMI slightly at medium-term (MD -0.32, 95% CI -0.53 to -0.11; 3 studies, 2143 participants) and long-term (MD -0.28, 95% CI -0.51 to -0.05; 1 study, 985 participants) follow-up; both low-certainty evidence. Seven studies (5428 participants; low-certainty evidence) reported data on serious adverse events: two reported injuries relating to the exercise component of the intervention and five reported no effect of intervention on reported serious adverse events. Dietary and activity interventions versus control Dietary and activity interventions, compared with control, do not reduce BMI at short-term follow-up (MD 0.03, 95% CI -0.07 to 0.13; 11 studies, 3429 participants; high-certainty evidence), and probably do not reduce BMI at medium-term (MD 0.01, 95% CI -0.09 to 0.11; 8 studies, 5612 participants; moderate-certainty evidence) or long-term (MD 0.06, 95% CI -0.04 to 0.16; 6 studies, 8736 participants; moderate-certainty evidence) follow-up. They may have little to no effect on zBMI in the short term, but the evidence is very uncertain (MD -0.09, 95% CI -0.2 to 0.02; 3 studies, 515 participants; very low-certainty evidence), and they may not reduce zBMI at medium-term (MD -0.05, 95% CI -0.1 to 0.01; 6 studies, 3511 participants; low-certainty evidence) or long-term (MD -0.02, 95% CI -0.05 to 0.01; 7 studies, 8430 participants; low-certainty evidence) follow-up. Four studies (2394 participants) reported data on serious adverse events (very low-certainty evidence): one reported an increase in weight concern in a few adolescents and three reported no effect. AUTHORS' CONCLUSIONS: The evidence demonstrates that dietary interventions may have little to no effect on obesity in adolescents. There is low-certainty evidence that activity interventions may have a small beneficial effect on BMI at medium- and long-term follow-up. Diet plus activity interventions may result in little to no difference. Importantly, this updated review also suggests that interventions to prevent obesity in this age group may result in little to no difference in serious adverse effects. Limitations of the evidence include inconsistent results across studies, lack of methodological rigour in some studies and small sample sizes. Further research is justified to investigate the effects of diet and activity interventions to prevent childhood obesity in community settings, and in young people with disabilities, since very few ongoing studies are likely to address these. Further randomised trials to address the remaining uncertainty about the effects of diet, activity interventions, or both, to prevent childhood obesity in schools (ideally with zBMI as the measured outcome) would need to have larger samples.

Interventions to prevent obesity in children aged 5 to 11 years old.

BACKGROUND: Prevention of obesity in children is an international public health priority given the prevalence of the condition (and its significant impact on health, development and well-being). Interventions that aim to prevent obesity involve behavioural change strategies that promote healthy eating or 'activity' levels (physical activity, sedentary behaviour and/or sleep) or both, and work by reducing energy intake and/or increasing energy expenditure, respectively. There is uncertainty over which approaches are more effective and numerous new studies have been published over the last five years, since the previous version of this Cochrane review. OBJECTIVES: To assess the effects of interventions that aim to prevent obesity in children by modifying dietary intake or 'activity' levels, or a combination of both, on changes in BMI, zBMI score and serious adverse events. SEARCH METHODS: We used standard, extensive Cochrane search methods. The latest search date was February 2023. SELECTION CRITERIA: Randomised controlled trials in children (mean age 5 years and above but less than 12 years), comparing diet or 'activity' interventions (or both) to prevent obesity with no intervention, usual care, or with another eligible intervention, in any setting. Studies had to measure outcomes at a minimum of 12 weeks post baseline. We excluded interventions designed primarily to improve sporting performance. DATA COLLECTION AND ANALYSIS: We used standard Cochrane methods. Our outcomes were body mass index (BMI), zBMI score and serious adverse events, assessed at short- (12 weeks to < 9 months from baseline), medium- (9 months to < 15 months) and long-term (≥ 15 months) follow-up. We used GRADE to assess the certainty of the evidence for each outcome. MAIN RESULTS: This review includes 172 studies (189,707 participants); 149 studies (160,267 participants) were included in meta-analyses. One hundred forty-six studies were based in high-income countries. The main setting for intervention delivery was schools (111 studies), followed by the community (15 studies), the home (eight studies) and a clinical setting (seven studies); one intervention was conducted by telehealth and 31 studies were conducted in more than one setting. Eighty-six interventions were implemented for less than nine months; the shortest was conducted over one visit and the longest over four years. Non-industry funding was declared by 132 studies; 24 studies were funded in part or wholly by industry. Dietary interventions versus control Dietary interventions, compared with control, may have little to no effect on BMI at short-term follow-up (mean difference (MD) 0, 95% confidence interval (CI) -0.10 to 0.10; 5 studies, 2107 participants; low-certainty evidence) and at medium-term follow-up (MD -0.01, 95% CI -0.15 to 0.12; 9 studies, 6815 participants; low-certainty evidence) or zBMI at long-term follow-up (MD -0.05, 95% CI -0.10 to 0.01; 7 studies, 5285 participants; low-certainty evidence). Dietary interventions, compared with control, probably have little to no effect on BMI at long-term follow-up (MD -0.17, 95% CI -0.48 to 0.13; 2 studies, 945 participants; moderate-certainty evidence) and zBMI at short- or medium-term follow-up (MD -0.06, 95% CI -0.13 to 0.01; 8 studies, 3695 participants; MD -0.04, 95% CI -0.10 to 0.02; 9 studies, 7048 participants; moderate-certainty evidence). Five studies (1913 participants; very low-certainty evidence) reported data on serious adverse events: one reported serious adverse events (e.g. allergy, behavioural problems and abdominal discomfort) that may have occurred as a result of the intervention; four reported no effect. Activity interventions versus control Activity interventions, compared with control, may have little to no effect on BMI and zBMI at short-term or long-term follow-up (BMI short-term: MD -0.02, 95% CI -0.17 to 0.13; 14 studies, 4069 participants; zBMI short-term: MD -0.02, 95% CI -0.07 to 0.02; 6 studies, 3580 participants; low-certainty evidence; BMI long-term: MD -0.07, 95% CI -0.24 to 0.10; 8 studies, 8302 participants; zBMI long-term: MD -0.02, 95% CI -0.09 to 0.04; 6 studies, 6940 participants; low-certainty evidence). Activity interventions likely result in a slight reduction of BMI and zBMI at medium-term follow-up (BMI: MD -0.11, 95% CI -0.18 to -0.05; 16 studies, 21,286 participants; zBMI: MD -0.05, 95% CI -0.09 to -0.02; 13 studies, 20,600 participants; moderate-certainty evidence). Eleven studies (21,278 participants; low-certainty evidence) reported data on serious adverse events; one study reported two minor ankle sprains and one study reported the incident rate of adverse events (e.g. musculoskeletal injuries) that may have occurred as a result of the intervention; nine studies reported no effect. Dietary and activity interventions versus control Dietary and activity interventions, compared with control, may result in a slight reduction in BMI and zBMI at short-term follow-up (BMI: MD -0.11, 95% CI -0.21 to -0.01; 27 studies, 16,066 participants; zBMI: MD -0.03, 95% CI -0.06 to 0.00; 26 studies, 12,784 participants; low-certainty evidence) and likely result in a reduction of BMI and zBMI at medium-term follow-up (BMI: MD -0.11, 95% CI -0.21 to 0.00; 21 studies, 17,547 participants; zBMI: MD -0.05, 95% CI -0.07 to -0.02; 24 studies, 20,998 participants; moderate-certainty evidence). Dietary and activity interventions compared with control may result in little to no difference in BMI and zBMI at long-term follow-up (BMI: MD 0.03, 95% CI -0.11 to 0.16; 16 studies, 22,098 participants; zBMI: MD -0.02, 95% CI -0.06 to 0.01; 22 studies, 23,594 participants; low-certainty evidence). Nineteen studies (27,882 participants; low-certainty evidence) reported data on serious adverse events: four studies reported occurrence of serious adverse events (e.g. injuries, low levels of extreme dieting behaviour); 15 studies reported no effect. Heterogeneity was apparent in the results for all outcomes at the three follow-up times, which could not be explained by the main setting of the interventions (school, home, school and home, other), country income status (high-income versus non-high-income), participants' socioeconomic status (low versus mixed) and duration of the intervention. Most studies excluded children with a mental or physical disability. AUTHORS' CONCLUSIONS: The body of evidence in this review demonstrates that a range of school-based 'activity' interventions, alone or in combination with dietary interventions, may have a modest beneficial effect on obesity in childhood at short- and medium-term, but not at long-term follow-up. Dietary interventions alone may result in little to no difference. Limited evidence of low quality was identified on the effect of dietary and/or activity interventions on severe adverse events and health inequalities; exploratory analyses of these data suggest no meaningful impact. We identified a dearth of evidence for home and community-based settings (e.g. delivered through local youth groups), for children living with disabilities and indicators of health inequities.

Using Risk of Bias 2 to assess results from randomised controlled trials: guidance from Cochrane.

A systematic review identifies, appraises and synthesises all the empirical evidence from studies that meet prespecified eligibility criteria to answer a specific research question. As part of the appraisal, researchers use explicit methods to assess risk of bias in the results' from included studies that contribute to the review's findings, to improve our confidence in the review's conclusions. Randomised controlled trials included in Cochrane Reviews have used a specific risk of bias tool to assess these included studies since 2008. In 2019, a new version of this tool, Risk of Bias 2 (RoB 2), was launched to improve its usability and to reflect current understanding of how the causes of bias can influence study results. Cochrane implemented RoB 2 in a phased approach, with users of the tool informing guidance development. This paper highlights learning for all systematic reviewers (Cochrane and non-Cochrane) from the phased implementation, highlighting differences between the original version of the tool and RoB 2, consideration of reporting systematic review protocols or full review reports that have used RoB 2, and some tips shared by authors during the pilot phase of the implementation.

Does testosterone mediate the relationship between vitamin D and prostate cancer progression? A systematic review and meta-analysis.

PURPOSE: Observational studies and randomized controlled trials (RCTs) have shown an association between vitamin D levels and prostate cancer progression. However, evidence of direct causality is sparse and studies have not examined biological mechanisms, which can provide information on plausibility and strengthen the evidence for causality. METHODS: We used the World Cancer Research Fund International/University of Bristol two-stage framework for mechanistic systematic reviews. In stage one, both text mining of published literature and expert opinion identified testosterone as a plausible biological mechanism. In stage two, we performed a systematic review and meta-analysis to assess the evidence from both human and animal studies examining the effect of vitamin D on testosterone, and testosterone on advanced prostate cancer (diagnostic Gleason score of ≥ 8, development of metastasis) or prostate cancer-specific mortality. RESULTS: A meta-analysis of ten human RCTs showed evidence of an effect of vitamin D on total testosterone (standardised mean difference (SMD) = 0.133, 95% CI = - 0.003-0.269, I2 = 0.0%, p = 0.056). Five human RCTs showed evidence of an effect of vitamin D on free testosterone (SMD = 0.173, 95% CI = - 0.104-0.450, I2 = 52.4%, p = 0.220). Three human cohort studies of testosterone on advanced prostate cancer or prostate cancer-specific mortality provided inconsistent results. In one study, higher levels of calculated free testosterone were positively associated with advanced prostate cancer or prostate cancer-specific mortality. In contrast, higher levels of dihydrotestosterone were associated with lowering prostate cancer-specific mortality in another study. No animal studies met the study eligibility criteria. CONCLUSION: There is some evidence that vitamin D increases levels of total and free testosterone, although the effect of testosterone levels within the normal range on prostate cancer progression is unclear. The role of testosterone as a mechanism between vitamin D and prostate cancer progression remains inconclusive.

Diagnostic test accuracy and cost-effectiveness of tests for codeletion of chromosomal arms 1p and 19q in people with glioma.

BACKGROUND: Complete deletion of both the short arm of chromosome 1 (1p) and the long arm of chromosome 19 (19q), known as 1p/19q codeletion, is a mutation that can occur in gliomas. It occurs in a type of glioma known as oligodendroglioma and its higher grade counterpart known as anaplastic oligodendroglioma. Detection of 1p/19q codeletion in gliomas is important because, together with another mutation in an enzyme known as isocitrate dehydrogenase, it is needed to make the diagnosis of an oligodendroglioma. Presence of 1p/19q codeletion also informs patient prognosis and prediction of the best drug treatment. The main two tests in use are fluorescent in situ hybridisation (FISH) and polymerase chain reaction (PCR)-based loss of heterozygosity (LOH) assays (also known as PCR-based short tandem repeat or microsatellite analysis). Many other tests are available. None of the tests is perfect, although PCR-based LOH is expected to have very high sensitivity. OBJECTIVES: To estimate the sensitivity and specificity and cost-effectiveness of different deoxyribonucleic acid (DNA)-based techniques for determining 1p/19q codeletion status in glioma. SEARCH METHODS: We searched MEDLINE, Embase and BIOSIS up to July 2019. There were no restrictions based on language or date of publication. We sought economic evaluation studies from the results of this search and using the National Health Service Economic Evaluation Database. SELECTION CRITERIA: We included cross-sectional studies in adults with glioma or any subtype of glioma, presenting raw data or cross-tabulations of two or more DNA-based tests for 1p/19q codeletion. We also sought economic evaluations of these tests. DATA COLLECTION AND ANALYSIS: We followed procedures outlined in the Cochrane Handbook for Diagnostic Test Accuracy Reviews. Two review authors independently screened titles/abstracts/full texts, performed data extraction, and undertook applicability and risk of bias assessments using QUADAS-2. Meta-analyses used the hierarchical summary ROC model to estimate and compare test accuracy. We used FISH and PCR-based LOH as alternate reference standards to examine how tests compared with those in common use, and conducted a latent class analysis comparing FISH and PCR-based LOH. We constructed an economic model to evaluate cost-effectiveness. MAIN RESULTS: We included 53 studies examining: PCR-based LOH, FISH, single nucleotide polymorphism (SNP) array, next-generation sequencing (NGS), comparative genomic hybridisation (CGH), array comparative genomic hybridisation (aCGH), multiplex-ligation-dependent probe amplification (MLPA), real-time PCR, chromogenic in situ hybridisation (CISH), mass spectrometry (MS), restriction fragment length polymorphism (RFLP) analysis, G-banding, methylation array and NanoString. Risk of bias was low for only one study; most gave us concerns about how patients were selected or about missing data. We had applicability concerns about many of the studies because only patients with specific subtypes of glioma were included. 1520 participants contributed to analyses using FISH as the reference, 1304 participants to analyses involving PCR-based LOH as the reference and 262 participants to analyses of comparisons between methods from studies not including FISH or PCR-based LOH. Most evidence was available for comparison of FISH with PCR-based LOH (15 studies, 915 participants): PCR-based LOH detected 94% of FISH-determined codeletions (95% credible interval (CrI) 83% to 98%) and FISH detected 91% of codeletions determined by PCR-based LOH (CrI 78% to 97%). Of tumours determined not to have a deletion by FISH, 94% (CrI 87% to 98%) had a deletion detected by PCR-based LOH, and of those determined not to have a deletion by PCR-based LOH, 96% (CrI 90% to 99%) had a deletion detected by FISH. The latent class analysis suggested that PCR-based LOH may be slightly more accurate than FISH. Most other techniques appeared to have high sensitivity (i.e. produced few false-negative results) for detection of 1p/19q codeletion when either FISH or PCR-based LOH was considered as the reference standard, although there was limited evidence. There was some indication of differences in specificity (false-positive rate) with some techniques. Both NGS and SNP array had high specificity when considered against FISH as the reference standard (NGS: 6 studies, 243 participants; SNP: 6 studies, 111 participants), although we rated certainty in the evidence as low or very low. NGS and SNP array also had high specificity when PCR-based LOH was considered the reference standard, although with much more uncertainty as these results were based on fewer studies (just one study with 49 participants for NGS and two studies with 33 participants for SNP array). G-banding had low sensitivity and specificity when PCR-based LOH was the reference standard. Although MS had very high sensitivity and specificity when both FISH and PCR-based LOH were considered the reference standard, these results were based on only one study with a small number of participants. Real-time PCR also showed high specificity with FISH as a reference standard, although there were only two studies including 40 participants. We found no relevant economic evaluations. Our economic model using FISH as the reference standard suggested that the resource-optimising test depends on which measure of diagnostic accuracy is most important. With FISH as the reference standard, MLPA is likely to be cost-effective if society was willing to pay GBP 1000 or less for a true positive detected. However, as the value placed on a true positive increased, CISH was most cost-effective. Findings differed when the outcome measure changed to either true negative detected or correct diagnosis. When PCR-based LOH was used as the reference standard, MLPA was likely to be cost-effective for all measures of diagnostic accuracy at lower threshold values for willingness to pay. However, as the threshold values increased, none of the tests were clearly more likely to be considered cost-effective. AUTHORS' CONCLUSIONS: In our review, most techniques (except G-banding) appeared to have good sensitivity (few false negatives) for detection of 1p/19q codeletions in glioma against both FISH and PCR-based LOH as a reference standard. However, we judged the certainty of the evidence low or very low for all the tests. There are possible differences in specificity, with both NGS and SNP array having high specificity (fewer false positives) for 1p/19q codeletion when considered against FISH as the reference standard. The economic analysis should be interpreted with caution due to the small number of studies.

Ten questions to consider when interpreting results of a meta-epidemiological study-the MetaBLIND study as a case.

Randomized clinical trials underpin evidence-based clinical practice, but flaws in their conduct may lead to biased estimates of intervention effects and hence invalid treatment recommendations. The main approach to the empirical study of bias is to collate a number of meta-analyses and, within each, compare the results of trials with and without a methodological characteristic such as blinding of participants and health professionals. Estimated within-meta-analysis differences are combined across meta-analyses, leading to an estimate of mean bias. Such "meta-epidemiological" studies are published in increasing numbers and have the potential to inform trial design, assessment of risk of bias, and reporting guidelines. However, their interpretation is complicated by issues of confounding, imprecision, and applicability. We developed a guide for interpreting meta-epidemiological studies, illustrated using MetaBLIND, a large study on the impact of blinding. Applying generally accepted principles of research methodology to meta-epidemiology, we framed 10 questions covering the main issues to consider when interpreting results of such studies, including risk of systematic error, risk of random error, issues related to heterogeneity, and theoretical plausibility. We suggest that readers of a meta-epidemiological study reflect comprehensively on the research question posed in the study, whether an experimental intervention was unequivocally identified for all included trials, the risk of misclassification of the trial characteristic, and the risk of confounding, i.e the adequacy of any adjustment for the likely confounders. We hope that our guide to interpretation of results of meta-epidemiological studies is helpful for readers of such studies.

GRADE guidelines: 18. How ROBINS-I and other tools to assess risk of bias in nonrandomized studies should be used to rate the certainty of a body of evidence.

OBJECTIVE: To provide guidance on how systematic review authors, guideline developers, and health technology assessment practitioners should approach the use of the risk of bias in nonrandomized studies of interventions (ROBINS-I) tool as a part of GRADE's certainty rating process. STUDY DESIGN AND SETTING: The study design and setting comprised iterative discussions, testing in systematic reviews, and presentation at GRADE working group meetings with feedback from the GRADE working group. RESULTS: We describe where to start the initial assessment of a body of evidence with the use of ROBINS-I and where one would anticipate the final rating would end up. The GRADE accounted for issues that mitigate concerns about confounding and selection bias by introducing the upgrading domains: large effects, dose-effect relations, and when plausible residual confounders or other biases increase certainty. They will need to be considered in an assessment of a body of evidence when using ROBINS-I. CONCLUSIONS: The use of ROBINS-I in GRADE assessments may allow for a better comparison of evidence from randomized controlled trials (RCTs) and nonrandomized studies (NRSs) because they are placed on a common metric for risk of bias. Challenges remain, including appropriate presentation of evidence from RCTs and NRSs for decision-making and how to optimally integrate RCTs and NRSs in an evidence assessment.

Screening strategies for atrial fibrillation: a systematic review and cost-effectiveness analysis.

BACKGROUND: Atrial fibrillation (AF) is a common cardiac arrhythmia that increases the risk of thromboembolic events. Anticoagulation therapy to prevent AF-related stroke has been shown to be cost-effective. A national screening programme for AF may prevent AF-related events, but would involve a substantial investment of NHS resources. OBJECTIVES: To conduct a systematic review of the diagnostic test accuracy (DTA) of screening tests for AF, update a systematic review of comparative studies evaluating screening strategies for AF, develop an economic model to compare the cost-effectiveness of different screening strategies and review observational studies of AF screening to provide inputs to the model. DESIGN: Systematic review, meta-analysis and cost-effectiveness analysis. SETTING: Primary care. PARTICIPANTS: Adults. INTERVENTION: Screening strategies, defined by screening test, age at initial and final screens, screening interval and format of screening {systematic opportunistic screening [individuals offered screening if they consult with their general practitioner (GP)] or systematic population screening (when all eligible individuals are invited to screening)}. MAIN OUTCOME MEASURES: Sensitivity, specificity and diagnostic odds ratios; the odds ratio of detecting new AF cases compared with no screening; and the mean incremental net benefit compared with no screening. REVIEW METHODS: Two reviewers screened the search results, extracted data and assessed the risk of bias. A DTA meta-analysis was perfomed, and a decision tree and Markov model was used to evaluate the cost-effectiveness of the screening strategies. RESULTS: Diagnostic test accuracy depended on the screening test and how it was interpreted. In general, the screening tests identified in our review had high sensitivity (> 0.9). Systematic population and systematic opportunistic screening strategies were found to be similarly effective, with an estimated 170 individuals needed to be screened to detect one additional AF case compared with no screening. Systematic opportunistic screening was more likely to be cost-effective than systematic population screening, as long as the uptake of opportunistic screening observed in randomised controlled trials translates to practice. Modified blood pressure monitors, photoplethysmography or nurse pulse palpation were more likely to be cost-effective than other screening tests. A screening strategy with an initial screening age of 65 years and repeated screens every 5 years until age 80 years was likely to be cost-effective, provided that compliance with treatment does not decline with increasing age. CONCLUSIONS: A national screening programme for AF is likely to represent a cost-effective use of resources. Systematic opportunistic screening is more likely to be cost-effective than systematic population screening. Nurse pulse palpation or modified blood pressure monitors would be appropriate screening tests, with confirmation by diagnostic 12-lead electrocardiography interpreted by a trained GP, with referral to a specialist in the case of an unclear diagnosis. Implementation strategies to operationalise uptake of systematic opportunistic screening in primary care should accompany any screening recommendations. LIMITATIONS: Many inputs for the economic model relied on a single trial [the Screening for Atrial Fibrillation in the Elderly (SAFE) study] and DTA results were based on a few studies at high risk of bias/of low applicability. FUTURE WORK: Comparative studies measuring long-term outcomes of screening strategies and DTA studies for new, emerging technologies and to replicate the results for photoplethysmography and GP interpretation of 12-lead electrocardiography in a screening population. STUDY REGISTRATION: This study is registered as PROSPERO CRD42014013739. FUNDING: The National Institute for Health Research Health Technology Assessment programme.

Oral anticoagulants for primary prevention, treatment and secondary prevention of venous thromboembolic disease, and for prevention of stroke in atrial fibrillation: systematic review, network meta-analysis and cost-effectiveness analysis.

BACKGROUND: Warfarin is effective for stroke prevention in atrial fibrillation (AF), but anticoagulation is underused in clinical care. The risk of venous thromboembolic disease during hospitalisation can be reduced by low-molecular-weight heparin (LMWH): warfarin is the most frequently prescribed anticoagulant for treatment and secondary prevention of venous thromboembolism (VTE). Warfarin-related bleeding is a major reason for hospitalisation for adverse drug effects. Warfarin is cheap but therapeutic monitoring increases treatment costs. Novel oral anticoagulants (NOACs) have more rapid onset and offset of action than warfarin, and more predictable dosing requirements. OBJECTIVE: To determine the best oral anticoagulant/s for prevention of stroke in AF and for primary prevention, treatment and secondary prevention of VTE. DESIGN: Four systematic reviews, network meta-analyses (NMAs) and cost-effectiveness analyses (CEAs) of randomised controlled trials. SETTING: Hospital (VTE primary prevention and acute treatment) and primary care/anticoagulation clinics (AF and VTE secondary prevention). PARTICIPANTS: Patients eligible for anticoagulation with warfarin (stroke prevention in AF, acute treatment or secondary prevention of VTE) or LMWH (primary prevention of VTE). INTERVENTIONS: NOACs, warfarin and LMWH, together with other interventions (antiplatelet therapy, placebo) evaluated in the evidence network. MAIN OUTCOME MEASURES: Efficacy Stroke, symptomatic VTE, symptomatic deep-vein thrombosis and symptomatic pulmonary embolism. Safety Major bleeding, clinically relevant bleeding and intracranial haemorrhage. We also considered myocardial infarction and all-cause mortality and evaluated cost-effectiveness. DATA SOURCES: MEDLINE and PREMEDLINE In-Process & Other Non-Indexed Citations, EMBASE and The Cochrane Library, reference lists of published NMAs and trial registries. We searched MEDLINE and PREMEDLINE In-Process & Other Non-Indexed Citations, EMBASE and The Cochrane Library. The stroke prevention in AF review search was run on the 12 March 2014 and updated on 15 September 2014, and covered the period 2010 to September 2014. The search for the three reviews in VTE was run on the 19 March 2014, updated on 15 September 2014, and covered the period 2008 to September 2014. REVIEW METHODS: Two reviewers screened search results, extracted and checked data, and assessed risk of bias. For each outcome we conducted standard meta-analysis and NMA. We evaluated cost-effectiveness using discrete-time Markov models. RESULTS: Apixaban (Eliquis®, Bristol-Myers Squibb, USA; Pfizer, USA) [5 mg bd (twice daily)] was ranked as among the best interventions for stroke prevention in AF, and had the highest expected net benefit. Edoxaban (Lixiana®, Daiichi Sankyo, Japan) [60 mg od (once daily)] was ranked second for major bleeding and all-cause mortality. Neither the clinical effectiveness analysis nor the CEA provided strong evidence that NOACs should replace postoperative LMWH in primary prevention of VTE. For acute treatment and secondary prevention of VTE, we found little evidence that NOACs offer an efficacy advantage over warfarin, but the risk of bleeding complications was lower for some NOACs than for warfarin. For a willingness-to-pay threshold of > £5000, apixaban (5 mg bd) had the highest expected net benefit for acute treatment of VTE. Aspirin or no pharmacotherapy were likely to be the most cost-effective interventions for secondary prevention of VTE: our results suggest that it is not cost-effective to prescribe NOACs or warfarin for this indication. CONCLUSIONS: NOACs have advantages over warfarin in patients with AF, but we found no strong evidence that they should replace warfarin or LMWH in primary prevention, treatment or secondary prevention of VTE. LIMITATIONS: These relate mainly to shortfalls in the primary data: in particular, there were no head-to-head comparisons between different NOAC drugs. FUTURE WORK: Calculating the expected value of sample information to clarify whether or not it would be justifiable to fund one or more head-to-head trials. STUDY REGISTRATION: This study is registered as PROSPERO CRD42013005324, CRD42013005331 and CRD42013005330. FUNDING: The National Institute for Health Research Health Technology Assessment programme.

A general framework for the use of logistic regression models in meta-analysis.

Where individual participant data are available for every randomised trial in a meta-analysis of dichotomous event outcomes, "one-stage" random-effects logistic regression models have been proposed as a way to analyse these data. Such models can also be used even when individual participant data are not available and we have only summary contingency table data. One benefit of this one-stage regression model over conventional meta-analysis methods is that it maximises the correct binomial likelihood for the data and so does not require the common assumption that effect estimates are normally distributed. A second benefit of using this model is that it may be applied, with only minor modification, in a range of meta-analytic scenarios, including meta-regression, network meta-analyses and meta-analyses of diagnostic test accuracy. This single model can potentially replace the variety of often complex methods used in these areas. This paper considers, with a range of meta-analysis examples, how random-effects logistic regression models may be used in a number of different types of meta-analyses. This one-stage approach is compared with widely used meta-analysis methods including Bayesian network meta-analysis and the bivariate and hierarchical summary receiver operating characteristic (ROC) models for meta-analyses of diagnostic test accuracy.

The Use of Bayesian Networks to Assess the Quality of Evidence from Research Synthesis: 2. Inter-Rater Reliability and Comparison with Standard GRADE Assessment.

BACKGROUND: The grades of recommendation, assessment, development and evaluation (GRADE) approach is widely implemented in systematic reviews, health technology assessment and guideline development organisations throughout the world. We have previously reported on the development of the Semi-Automated Quality Assessment Tool (SAQAT), which enables a semi-automated validity assessment based on GRADE criteria. The main advantage to our approach is the potential to improve inter-rater agreement of GRADE assessments particularly when used by less experienced researchers, because such judgements can be complex and challenging to apply without training. This is the first study examining the inter-rater agreement of the SAQAT. METHODS: We conducted two studies to compare: a) the inter-rater agreement of two researchers using the SAQAT independently on 28 meta-analyses and b) the inter-rater agreement between a researcher using the SAQAT (who had no experience of using GRADE) and an experienced member of the GRADE working group conducting a standard GRADE assessment on 15 meta-analyses. RESULTS: There was substantial agreement between independent researchers using the Quality Assessment Tool for all domains (for example, overall GRADE rating: weighted kappa 0.79; 95% CI 0.65 to 0.93). Comparison between the SAQAT and a standard GRADE assessment suggested that inconsistency was parameterised too conservatively by the SAQAT. Therefore the tool was amended. Following amendment we found fair-to-moderate agreement between the standard GRADE assessment and the SAQAT (for example, overall GRADE rating: weighted kappa 0.35; 95% CI 0.09 to 0.87). CONCLUSIONS: Despite a need for further research, the SAQAT may aid consistent application of GRADE, particularly by less experienced researchers.

A checklist designed to aid consistency and reproducibility of GRADE assessments: development and pilot validation.

BACKGROUND: The grading of recommendation, assessment, development and evaluation (GRADE) approach is widely implemented in health technology assessment and guideline development organisations throughout the world. GRADE provides a transparent approach to reaching judgements about the quality of evidence on the effects of a health care intervention, but is complex and therefore challenging to apply in a consistent manner. METHODS: We developed a checklist to guide the researcher to extract the data required to make a GRADE assessment. We applied the checklist to 29 meta-analyses of randomised controlled trials on the effectiveness of health care interventions. Two reviewers used the checklist for each paper and used these data to rate the quality of evidence for a particular outcome. RESULTS: For most (70%) checklist items, there was good agreement between reviewers. The main problems were for items relating to indirectness where considerable judgement is required. CONCLUSIONS: There was consistent agreement between reviewers on most items in the checklist. The use of this checklist may be an aid to improving the consistency and reproducibility of GRADE assessments, particularly for inexperienced users or in rapid reviews without the resources to conduct assessments by two researchers independently.

Protocol for a systematic review and individual participant data meta-analysis of B-type natriuretic peptide-guided therapy for heart failure.

BACKGROUND: Several aggregate data meta-analyses suggest that treatment guided by the serum concentration of natriuretic peptides (B-type natriuretic peptide (BNP) or its derivative N-terminal pro-B-type natriuretic peptide (NT-BNP)) reduces all-cause mortality compared with usual care in patients with heart failure (HF). We propose to conduct a meta-analysis using individual participant data (IPD) to estimate the effect of BNP-guided therapy on clinical outcomes, and estimate the extent of effect modification for clinically important subgroups. METHODS: We will use standard systematic review methods to identify relevant trials and assess study quality. We will include all randomized controlled trials (RCTs) of BNP-guided treatment for HF that report a clinical outcome. The primary outcome will be time to all-cause mortality. We will collate anonymized, individual patient data into a single database, and carry out appropriate data checks. We will use fixed-effects and random-effects meta-analysis methods to combine hazard ratios (HR) estimated within each RCT, across all RCTs. We will also include a meta-analysis and meta-regression analyses based on aggregate data, and combine IPD with aggregate data if we obtain IPD for a subset of trials. DISCUSSION: The IPD meta-analysis will allow us to estimate how patient characteristics modify treatment benefit, and to identify relevant subgroups of patients who are likely to benefit most from BNP-guided therapy. This is important because aggregate meta-analyses have suggested that clinically relevant subgroup effects exist, but these analyses have been unable to quantify the effects reliably or precisely. TRIALS REGISTRATION: PROSPERO 2013: CRD42013005335.

Evaluating the impact of imputations for missing participant outcome data in a network meta-analysis.

BACKGROUND: In a meta-analysis of trials with missing outcome data, a parameter known as informative missing odds ratio (IMOR) can be used to quantify the relationship between informative missingness and a binary outcome. IMORs also account for the increased uncertainty due to missingness in the meta-analysis results. PURPOSE: To extend the idea of IMOR into a network meta-analysis (NMA) setting in order to explore the impact of missing outcome data on the inferences about the relative effectiveness of several competing treatments in psychiatric trials. METHODS: IMORs were estimated in two datasets comparing anti-manic treatments and antidepressants. The outcome was response to treatments. In the original meta-analyses, missing participants were assumed to have failed regardless the treatment they were allocated to. To evaluate the robustness of this assumption in each dataset, several imputations of the missing outcomes were studied by an IMOR parameter in the NMA model. By comparing the odds ratios for efficacy under the initial analysis and under several assumptions about the missingness, we assessed the consistency of the conclusions. The missing data mechanism was studied by comparing the prior with the posterior IMOR distribution. Models were fitted using Markov chain Monte Carlo (MCMC) in WinBUGS. RESULTS: In both datasets, the relative effectiveness of the treatments seems to be affected only by the two extreme imputation scenarios of worst- and best-case analyses. Moreover, heterogeneity increases in both datasets under these two extreme scenarios. Overall, there is a non-significant change on the ranking of the anti-manic and antidepressant treatments. The posterior and prior IMOR distributions are very similar showing that the data do not provide any information about the true outcome in missing participants. There is a very weak indication that missing participants tend to fail in placebo and paroxetine, while the opposite occurs for sertraline, fluoxetine, and fluvoxamine. LIMITATIONS: Investigation of informative missingness was limited two classes of treatments and for dichotomous outcome measures. The proportion of missing outcomes was very low overall, and hence, the power of detecting any differences in effectiveness estimated under the various imputation methods is small. CONCLUSIONS: Sensitivity analysis to account for missing outcome data and their uncertainty in the NMA can be undertaken by extending the idea of IMOR. In two case examples, we found no differences between the various models due to low missing data rate. In line with previous observations, data carry little information about the reason of missingness.

Issues relating to study design and risk of bias when including non-randomized studies in systematic reviews on the effects of interventions.

Non-randomized studies may provide valuable evidence on the effects of interventions. They are the main source of evidence on the intended effects of some types of interventions and often provide the only evidence about the effects of interventions on long-term outcomes, rare events or adverse effects. Therefore, systematic reviews on the effects of interventions may include various types of non-randomized studies. In this second paper in a series, we address how review authors might articulate the particular non-randomized study designs they will include and how they might evaluate, in general terms, the extent to which a particular non-randomized study is at risk of important biases. We offer guidance for describing and classifying different non-randomized designs based on specific features of the studies in place of using non-informative study design labels. We also suggest criteria to consider when deciding whether to include non-randomized studies. We conclude that a taxonomy of study designs based on study design features is needed. Review authors need new tools specifically to assess the risk of bias for some non-randomized designs that involve a different inferential logic compared with parallel group trials. Copyright © 2012 John Wiley & Sons, Ltd.

Checklists of methodological issues for review authors to consider when including non-randomized studies in systematic reviews.

BACKGROUND: There is increasing interest from review authors about including non-randomized studies (NRS) in their systematic reviews of health care interventions. This series from the Ottawa Non-Randomized Studies Workshop consists of six papers identifying methodological issues when doing this. AIM: To format the guidance from the preceding papers on study design and bias, confounding and meta-analysis, selective reporting, and applicability/directness into checklists of issues for review authors to consider when including NRS in a systematic review. CHECKLISTS: Checklists were devised providing frameworks to describe/assess: (1) study designs based on study design features; (2) risk of residual confounding and when to consider meta-analysing data from NRS; (3) risk of selective reporting based on the Cochrane framework for detecting selective outcome reporting in trials but extended to selective reporting of analyses; and (4) directness of evidence contributed by a study to aid integration of NRS findings into summary of findings tables. SUMMARY: The checklists described will allow review groups to operationalize the inclusion of NRS in systematic reviews in a more consistent way. The next major step is extending the existing Cochrane Risk of Bias tool so that it can assess the risk of bias to NRS included in a review. Copyright © 2013 John Wiley & Sons, Ltd.