Comparison of aggregate and individual participant data approaches to meta-analysis of randomised trials: An observational study

TC-325 Superiority in Malignant Gastrointestinal Bleeding: An Individual Patient Data Meta-Analysis of Randomized Trials

INTRODUCTION

The efficacy of topical hemostatic agents, recommended for peptic ulcer bleeding, remains poorly characterized in malignant gastrointestinal bleeding (GIB).

METHODS

We performed an individual patient data meta-analysis assessing the efficacy of topical hemostatic agents in malignant GIB. The literature was searched using OVID MEDLINE, EMBASE, and ISI Web of Science databases (database inception to November 2023). Only randomized controlled trials (RCTs) comparing topical hemostatic agents with conventional endoscopic modalities in malignant GIB were included. Original RCT patient-level data were obtained. Preferred Reporting Items for Systematic Review and Meta-Analyses guidelines were followed. Quality of the evidence was evaluated using the revised Cochrane risk-of-bias tool and certainty of evidence with the Grading of Recommendations Assessment, Development, and Evaluation approach. The primary outcome was immediate hemostasis; secondary outcomes were 30-day rebleeding and the composite measure of further bleeding (persistent bleeding or 30-day rebleeding). Other outcomes were all-cause mortality, adverse events, and need for additional nonendoscopic treatment. Odds ratios (ORs) from endpoint comparisons were pooled using logistic regression models.

RESULTS

Overall, 985 citations were identified; 3 RCTs (n = 160 patients) were included with all assessing TC-325 (Hemospray). TC-325 achieved immediate hemostasis more often than conventional endoscopic modalities (OR 46.6, 95% confidence interval [CI] 5.89-369.1) (low-level certainty). Thirty-day rebleeding (OR 0.28, 95% CI 0.11-0.70) and further bleeding (OR 0.11, 95% CI 0.05-0.26) were both significantly lower with TC-325 (very-low-level certainty). All-cause mortality and need for additional nonendoscopic treatment did not differ between groups. No adverse events were reported. Subgroup analysis confirmed TC-325 superiority in patients with upper GIB.

DISCUSSION

TC-325 seems superior to conventional endoscopic therapy in managing patients with malignant GIB. TC-325 results in improvements in immediate hemostasis, 30-day rebleeding, and further bleeding, based on very low-to-low certainties of evidence.

Neoadjuvant therapy versus upfront surgery in resectable pancreatic cancer: reconstructed patient-level meta-analysis of randomized clinical trials

BACKGROUND

Neoadjuvant treatment has shown promising results in patients with borderline resectable pancreatic ductal adenocarcinoma. The potential benefits of neoadjuvant treatment on long-term overall survival in patients with resectable pancreatic ductal adenocarcinoma have not yet been established. The aim of this study was to compare long-term overall survival of patients with resectable pancreatic ductal adenocarcinoma based on whether they received neoadjuvant treatment or underwent upfront surgery.

METHODS

A systematic review including randomized clinical trials on the overall survival outcomes between neoadjuvant treatment and upfront surgery in patients with resectable pancreatic ductal adenocarcinoma was conducted up to 1 August 2023 from PubMed, MEDLINE and Web of Science databases. Patient-level survival data was extracted and reconstructed from available Kaplan-Meier curves. A frequentist one-stage meta-analysis was employed, using Cox-based models and a non-parametric method (restricted mean survival time), to assess the difference in overall survival between groups. A Bayesian meta-analysis was also conducted.

RESULTS

Five randomized clinical trials comprising 625 patients were included. Among patients with resectable pancreatic ductal adenocarcinoma, neoadjuvant treatment was not significantly associated with a reduction in the hazard of death compared with upfront surgery (shared frailty HR 0.88, 95% c.i. 0.72 to 1.08, P = 0.223); this result was consistent in the non-parametric restricted mean survival time model (+2.41 months, 95% c.i. -1.22 to 6.04, P < 0.194), in the sensitivity analysis that excluded randomized clinical trials with a high risk of bias (shared frailty HR 0.91 (95% c.i. 0.72 to 1.15; P = 0.424)) and in the Bayesian analysis with a posterior shared frailty HR of 0.86 (95% c.i. 0.70 to 1.05).

CONCLUSION

Neoadjuvant treatment does not demonstrate a survival advantage over upfront surgery for patients with resectable pancreatic ductal adenocarcinoma.

Application of causal inference methods in individual-participant data meta-analyses in medicine: addressing data handling and reporting gaps with new proposed reporting guidelines

Observational data provide invaluable real-world information in medicine, but certain methodological considerations are required to derive causal estimates. In this systematic review, we evaluated the methodology and reporting quality of individual-level patient data meta-analyses (IPD-MAs) conducted with non-randomized exposures, published in 2009, 2014, and 2019 that sought to estimate a causal relationship in medicine. We screened over 16,000 titles and abstracts, reviewed 45 full-text articles out of the 167 deemed potentially eligible, and included 29 into the analysis. Unfortunately, we found that causal methodologies were rarely implemented, and reporting was generally poor across studies. Specifically, only three of the 29 articles used quasi-experimental methods, and no study used G-methods to adjust for time-varying confounding. To address these issues, we propose stronger collaborations between physicians and methodologists to ensure that causal methodologies are properly implemented in IPD-MAs. In addition, we put forward a suggested checklist of reporting guidelines for IPD-MAs that utilize causal methods. This checklist could improve reporting thereby potentially enhancing the quality and trustworthiness of IPD-MAs, which can be considered one of the most valuable sources of evidence for health policy.

Reduced incidence of diabetes during the COVID-19 pandemic in Alberta: A time-segmented longitudinal study of Alberta's Tomorrow Project

AIM

To characterize the impact of the COVID-19 pandemic on diabetes diagnosis using data from Alberta's Tomorrow Project (ATP), a population-based cohort study of chronic diseases in Alberta, Canada.

MATERIALS AND METHODS

The ATP participants who were free of diabetes on 1 April 2018 were included in the study. A time-segmented regression model was used to compare incidence rates of diabetes before the COVID-19 pandemic, during the first two COVID-19 states of emergency, and in the period when the state of emergency was relaxed, after adjusting for seasonality, sociodemographic factors, socioeconomic status, and lifestyle behaviours.

RESULTS

Among 43 705 ATP participants free of diabetes (65.5% females, age 60.4 ± 9.5 years in 2018), the rate of diabetes was 4.75 per 1000 person-year (PY) during the COVID-19 pandemic (up to 31 March 2021), which was 32% lower (95% confidence interval [CI] 21%, 42%; p < 0.001) than pre-pandemic (6.98 per 1000 PY for the period 1 April 2018 to 16 March 2020). In multivariable regression analysis, the first COVID-19 state of emergency (first wave) was associated with an 87.3% (95% CI -98.6%, 13.9%; p = 0.07) reduction in diabetes diagnosis; this decreasing trend was sustained to the second COVID-19 state of emergency and no substantial rebound (increase) was observed when the COVID-19 state of emergency was relaxed.

CONCLUSIONS

The COVID-19 public health emergencies had a negative impact on diabetes diagnosis in Alberta. The reduction in diabetes diagnosis was likely due to province-wide health service disruptions during the COVID-19 pandemic. Systematic plans to close the post-COVID-19 diagnostic gap are required in diabetes to avoid substantial downstream sequelae of undiagnosed disease.

Which is Better for Individual Participant Data Meta-Analysis of Zero-Inflated Count Outcomes, One-Step or Two-Step Analysis? A Simulation Study

Meta-analysis using individual participant data (IPD) is an important methodology in intervention research because it (a) increases accuracy and precision of estimates, (b) allows researchers to investigate mediators and moderators of treatment effects, and (c) makes use of extant data. IPD meta-analysis can be conducted either via a one-step approach that uses data from all studies simultaneously, or a two-step approach, which aggregates data for each study and then combines them in a traditional meta-analysis model. Unfortunately, there are no evidence-based guidelines for how best to approach IPD meta-analysis for count outcomes with many zeroes, such as alcohol use. We used simulation to compare the performance of four hurdle models (3 one-step and 1 two-step models) for zero-inflated count IPD, under realistic data conditions. Overall, all models yielded adequate coverage and bias for the treatment effect in the count portion of the model, across all data conditions. However, in the zero portion, the treatment effect was underestimated in most models and data conditions, especially when there were fewer studies. The performance of both one- and two-step approaches depended on the formulation of the treatment effects, suggesting a need to carefully consider model assumptions and specifications when using IPD.

Application of Causal Inference Methods to Pooled Longitudinal Non- Randomized Studies: A Methodological Systematic Review

Observational data provide invaluable real-world information in medicine, but certain methodological considerations are required to derive causal estimates. In this systematic review, we evaluated the methodology and reporting quality of individual-level patient data meta-analyses (IPD-MAs) published in 2009, 2014, and 2019 that sought to estimate a causal relationship in medicine. We screened over 16,000 titles and abstracts, reviewed 45 full-text articles out of the 167 deemed potentially eligible, and included 29 into the analysis. Unfortunately, we found that causal methodologies were rarely implemented, and reporting was generally poor across studies. Specifically, only three of the 29 articles used quasi-experimental methods, and no study used G-methods to adjust for time-varying confounding. To address these issues, we propose stronger collaborations between physicians and methodologists to ensure that causal methodologies are properly implemented in IPD-MAs. In addition, we put forward a suggested checklist of reporting guidelines for IPD-MAs that utilize causal methods. This checklist could improve reporting thereby potentially enhancing the quality and trustworthiness of IPD-MAs, which can be considered one of the most valuable sources of evidence for health policy.

Prognostic value of HER2-low status in breast cancer: a systematic review and meta-analysis

BACKGROUND

Human epidermal growth factor receptor 2 (HER2)-low expression in breast cancer has been recently identified as a new therapeutic target. However, it is unclear if HER2-low status has an independent impact on prognosis.

MATERIALS AND METHODS

A systematic literature research was carried out to identify studies comparing survival outcomes of patients affected by HER2-low versus HER2-zero breast cancer. Using random-effects models, pooled hazard ratios (HRs) and odds ratios (ORs) with 95% confidence intervals (CIs) were calculated for progression-free survival (PFS) and overall survival (OS) in the metastatic setting as well as disease-free survival (DFS), OS and pathological complete response (pCR) in the early setting. Subgroup analyses by hormone receptor (HoR) status were carried out. The study protocol is registered on PROSPERO (n.CRD42023390777).

RESULTS

Among 1916 identified records, 42 studies including 1 797 175 patients were eligible. In the early setting, HER2-low status was associated with significant improved DFS (HR 0.86, 95% CI 0.79-0.92, P < 0.001) and OS (HR 0.90, 95% CI 0.85-0.95, P < 0.001) when compared to HER2-zero status. Improved OS was observed for both HoR-positive and HoR-negative HER2-low populations, while DFS improvement was observed only in the HoR-positive subgroup. HER2-low status was significantly associated with a lower rate of pCR as compared to HER2-zero status both in the overall population (OR 0.74, 95% CI 0.62-0.88, P = 0.001) and in the HoR-positive subgroup (OR 0.77, 95% CI 0.65-0.90, P = 0.001). In the metastatic setting, patients with HER2-low breast cancers showed better OS when compared with those with HER2-zero tumours in the overall population (HR 0.94, 95% CI 0.89-0.98, P = 0.008), regardless of HoR status. No significant PFS differences were found.

CONCLUSIONS

Compared with HER2-zero status, HER2-low status appears to be associated with a slightly increased OS both in the advanced and early settings, regardless of HoR expression. In the early setting, HER2-low tumours seem to be associated to lower pCR rates, especially if HoR-positive.

Individual participant data systematic review and meta-analysis of randomised controlled trials assessing adult mindfulness-based programmes for mental health promotion in non-clinical settings

Introduction

Mindfulness-based programmes (MBPs) are widely used to prevent mental ill-health that is becoming the leading global cause of morbidity. Evidence suggests beneficial average effects but wide variability. We aimed to confirm the effect of MBPs on psychological distress, and to understand whether and how baseline distress, gender, age, education, and dispositional mindfulness modify the effect of MBPs on distress among adults in non-clinical settings.

Methods

We conducted a pre-registered systematic review and individual participant data (IPD) meta-analysis (PROSPERO CRD42020200117). Thirteen databases were searched in December 2020 for randomised controlled trials satisfying a quality threshold and comparing in-person, expert-defined MBPs in non-clinical settings with passive control groups. Two researchers independently selected, extracted, and appraised trials using the revised Cochrane Risk-of-Bias Tool (RoB2). Anonymised IPD of eligible trials were sought from collaborating authors. The primary outcome was psychological distress (unpleasant mental or emotional experiences including anxiety and depression) at 1 to 6 months after programme completion. Data were checked and imputed if missing. Pairwise, random-effects, two-stage IPD meta-analyses were conducted. Effect modification analyses followed a within-studies approach. Public and professional stakeholders were involved in the planning, conduct and dissemination of this study.

Results

Fifteen trials were eligible, 13 trialists shared IPD (2,371 participants representing 8 countries, median age 34 years-old, 71% women, moderately distressed on average, 20% missing outcome data). In comparison with passive control groups, MBPs reduced average distress between one- and six-months post-intervention with a small to moderate effect size (standardised mean difference (SMD) -0.32; 95% confidence interval (CI) -0.41 to -0.24; p-value < 0.001; 95% prediction interval (PI) -0.41 to -0.24 (no heterogeneity)). Results were robust to sensitivity analyses, and similar for the other psychological distress time point ranges. Confidence in the primary outcome result is high. We found no clear indication that this effect is modified by baseline psychological distress, gender, age, education level, or dispositional mindfulness.

Conclusions

Group-based teacher-led MBPs generally reduce psychological distress among community adults who volunteer to receive this type of intervention. More research is needed to identify sources of variability in outcomes at an individual level.

Using individual participant data to improve network meta-analysis projects

A network meta-analysis combines the evidence from existing randomised trials about the comparative efficacy of multiple treatments. It allows direct and indirect evidence about each comparison to be included in the same analysis, and provides a coherent framework to compare and rank treatments. A traditional network meta-analysis uses aggregate data (eg, treatment effect estimates and standard errors) obtained from publications or trial investigators. An alternative approach is to obtain, check, harmonise and meta-analyse the individual participant data (IPD) from each trial. In this article, we describe potential advantages of IPD for network meta-analysis projects, emphasising five key benefits: (1) improving the quality and scope of information available for inclusion in the meta-analysis, (2) examining and plotting distributions of covariates across trials (eg, for potential effect modifiers), (3) standardising and improving the analysis of each trial, (4) adjusting for prognostic factors to allow a network meta-analysis of conditional treatment effects and (5) including treatment-covariate interactions (effect modifiers) to allow relative treatment effects to vary by participant-level covariate values (eg, age, baseline depression score). A running theme of all these benefits is that they help examine and reduce heterogeneity (differences in the true treatment effect between trials) and inconsistency (differences in the true treatment effect between direct and indirect evidence) in the network. As a consequence, an IPD network meta-analysis has the potential for more precise, reliable and informative results for clinical practice and even allows treatment comparisons to be made for individual patients and targeted populations conditional on their particular characteristics.

The incidence of new mental health disorders after acute pancreatitis: A large, propensity-matched, observational study

INTRODUCTION

The prevalence of acute pancreatitis (AP) and mental health disorders (MHDs) are rising. While the association between chronic pancreatitis (CP) and MHDs is established, it is unknown whether there is a risk of MHDs after an index episode of AP. The aim of this study was to evaluate the incidence of MHDs and pharmacotherapy use after an episode of AP.

METHODS

This was a large observational study using the TriNetX research network, an electronic health record dataset containing inpatient and outpatient data from more than 50 healthcare organizations. Patients with AP from 2015-2020 were identified. Four cohorts were created: acute necrotizing pancreatitis (ANP), acute pancreatitis without necrosis (AP-WON), acute appendicitis, and healthy controls without pancreatitis. The cohorts were matched by age, sex, race, ethnicity, and nicotine and alcohol use. The primary outcome was new composite MHDs at one-year. Secondary outcomes included stratified MHDs, psychiatric medication use, opioid analgesic use, and all-cause mortality.

RESULTS

The ANP, AP-WON, appendicitis, and healthy control cohorts contained 11,806, 177,266, 27,187, and 561,833 patients, respectively. Patients with AP-WON had significantly higher rates of composite MHDs compared with those hospitalized for appendicitis (9.7% vs 4.7%, HR 1.9, 95% CI 1.7-1.9). This association was augmented when comparing ANP to appendicitis (12.8% vs 5.2%, HR 2.4, 95% CI 2.1-2.7). All secondary outcomes were observed at significantly higher rates in the AP-WON cohort when compared to appendicitis. Again, these associations were augmented comparing ANP to appendicitis.

CONCLUSION

Compared with controls, patients with AP had significantly higher rates of new MHDs and their associated pharmacotherapies at one-year, suggesting that a single episode of AP may independently place patients at risk for developing MHDs irrespective of whether they go on to develop CP.

Comparison of different treatments for HPV+ oropharyngeal carcinoma: a network meta-analysis

INTRODUCTION

Treatment of human papillomavirus (HPV)-related head and neck squamous cell carcinoma (HNSCC) is rapidly evolving. Despite either surgery or radiotherapy (RT), with or without chemotherapy (CT), being acceptable in intermediate and locally advanced diseases, there is uncertainty regarding the best treatment option for these patients. Therefore, we performed a network meta-analysis (NMA) to compare the relative efficacy of different treatments for HPV+ oropharyngeal carcinoma.

MATERIAL AND METHODS

Randomized clinical trials that enrolled adults with non-metastatic HPV+ oropharynx cancer and provided data about overall survival (OS) and/or progression-free survival (PFS) and/or locoregional control and distant metastases (LRC and DM) were included. Fixed- or random-effects models were fit using a Bayesian approach to NMA. Between-group comparisons were estimated using hazard ratios (HRs) with 95% credible intervals (CrIs). The primary outcome was OS.

RESULTS

A total of 844 citations were screened; 11 randomized clinical trials were included (HPV+ stage III-IV cancer, mainly oropharynx carcinomas). Nine treatment arms were compared. Radiotherapy (altered or standard fractionation) + triweekly cisplatin (HR 3.8; 95% CrIs 0.29-65 and 0.3; 95% CrIs 0.03-2.51) was superior to RT in term of OS (P score = 0.42 and 0.16). Radiotherapy with low and high cisplatin doses appeared similar (HR 1.57; 95% CrIs 0.19-12.72). Altered fractionation or standard RT + 3-weekly cisplatin are the 2 highest-ranked options in terms of PFS (P score = 0.35 and 0.34).

CONCLUSIONS

This meta-analysis confirms the role of cisplatin added to RT as the best option for HPV+ oropharyngeal carcinoma. RT+ 3-weekly cisplatin is likely to be the best radical treatment in terms of OS and PFS.

Estimating interactions and subgroup-specific treatment effects in meta-analysis without aggregation bias: A within-trial framework

Estimation of within-trial interactions in meta-analysis is crucial for reliable assessment of how treatment effects vary across participant subgroups. However, current methods have various limitations. Patients, clinicians and policy-makers need reliable estimates of treatment effects within specific covariate subgroups, on relative and absolute scales, in order to target treatments appropriately-which estimation of an interaction effect does not in itself provide. Also, the focus has been on covariates with only two subgroups, and may exclude relevant data if only a single subgroup is reported. Therefore, in this article we further develop the "within-trial" framework by providing practical methods to (1) estimate within-trial interactions across two or more subgroups; (2) estimate subgroup-specific ("floating") treatment effects that are compatible with the within-trial interactions and make maximum use of available data; and (3) clearly present this data using novel implementation of forest plots. We described the steps involved and apply the methods to two examples taken from previously published meta-analyses, and demonstrate a straightforward implementation in Stata based upon existing code for multivariate meta-analysis. We discuss how the within-trial framework and plots can be utilised with aggregate (or "published") source data, as well as with individual participant data, to effectively demonstrate how treatment effects differ across participant subgroups.

Hydroxychloroquine/chloroquine for the treatment of hospitalized patients with COVID-19: An individual participant data meta-analysis

BACKGROUND

Results from observational studies and randomized clinical trials (RCTs) have led to the consensus that hydroxychloroquine (HCQ) and chloroquine (CQ) are not effective for COVID-19 prevention or treatment. Pooling individual participant data, including unanalyzed data from trials terminated early, enables more detailed investigation of the efficacy and safety of HCQ/CQ among subgroups of hospitalized patients.

METHODS

We searched ClinicalTrials.gov in May and June 2020 for US-based RCTs evaluating HCQ/CQ in hospitalized COVID-19 patients in which the outcomes defined in this study were recorded or could be extrapolated. The primary outcome was a 7-point ordinal scale measured between day 28 and 35 post enrollment; comparisons used proportional odds ratios. Harmonized de-identified data were collected via a common template spreadsheet sent to each principal investigator. The data were analyzed by fitting a prespecified Bayesian ordinal regression model and standardizing the resulting predictions.

RESULTS

Eight of 19 trials met eligibility criteria and agreed to participate. Patient-level data were available from 770 participants (412 HCQ/CQ vs 358 control). Baseline characteristics were similar between groups. We did not find evidence of a difference in COVID-19 ordinal scores between days 28 and 35 post-enrollment in the pooled patient population (odds ratio, 0.97; 95% credible interval, 0.76-1.24; higher favors HCQ/CQ), and found no convincing evidence of meaningful treatment effect heterogeneity among prespecified subgroups. Adverse event and serious adverse event rates were numerically higher with HCQ/CQ vs control (0.39 vs 0.29 and 0.13 vs 0.09 per patient, respectively).

CONCLUSIONS

The findings of this individual participant data meta-analysis reinforce those of individual RCTs that HCQ/CQ is not efficacious for treatment of COVID-19 in hospitalized patients.

Hydroxychloroquine/chloroquine for the treatment of hospitalized patients with COVID-19: An individual participant data meta-analysis

Background

Results from observational studies and randomized clinical trials (RCTs) have led to the consensus that hydroxychloroquine (HCQ) and chloroquine (CQ) are not effective for COVID-19 prevention or treatment. Pooling individual participant data, including unanalyzed data from trials terminated early, enables more detailed investigation of the efficacy and safety of HCQ/CQ among subgroups of hospitalized patients.

Methods

We searched ClinicalTrials.gov in May and June 2020 for US-based RCTs evaluating HCQ/CQ in hospitalized COVID-19 patients in which the outcomes defined in this study were recorded or could be extrapolated. The primary outcome was a 7-point ordinal scale measured between day 28 and 35 post enrollment; comparisons used proportional odds ratios. Harmonized de-identified data were collected via a common template spreadsheet sent to each principal investigator. The data were analyzed by fitting a prespecified Bayesian ordinal regression model and standardizing the resulting predictions.

Results

Eight of 19 trials met eligibility criteria and agreed to participate. Patient-level data were available from 770 participants (412 HCQ/CQ vs 358 control). Baseline characteristics were similar between groups. We did not find evidence of a difference in COVID-19 ordinal scores between days 28 and 35 post-enrollment in the pooled patient population (odds ratio, 0.97; 95% credible interval, 0.76-1.24; higher favors HCQ/CQ), and found no convincing evidence of meaningful treatment effect heterogeneity among prespecified subgroups. Adverse event and serious adverse event rates were numerically higher with HCQ/CQ vs control (0.39 vs 0.29 and 0.13 vs 0.09 per patient, respectively).

Conclusions

The findings of this individual participant data meta-analysis reinforce those of individual RCTs that HCQ/CQ is not efficacious for treatment of COVID-19 in hospitalized patients.

The limited efficacy of psychological interventions for depression in people with Type 1 or Type 2 diabetes: An Individual Participant Data Meta-Analysis (IPD-MA)

BACKGROUND

People with either Type 1/Type 2 diabetes experiencing anxiety or depression experience worse clinical and social outcomes. Efficacy of available psychological and pharmacological treatments for anxiety and depression is unclear. Aggregate data meta-analyses (AD-MAs) have failed to consider the clinical relevance of any change these treatments elicit. Thus, we sought to complete an individual participant data meta-analysis (IPD-MA) to evaluate this.

METHODS

Eligible RCTs of psychological treatments (PTs) and pharmacological treatments (PhTs) were systematically identified and assessed using the Cochrane Risk of Bias Tool-2. IPD was requested and Jacobson's methodology was used to determine the clinical relevance of symptom-change. Traditional effect sizes were calculated to permit comparison of trials providing and not providing IPD and to compare with AD-MAs.

RESULTS

Sufficient data was obtained to conduct an IPD-MA for PTs (12/25) but not PhTs (1/5). Across PT trials, rates of 'recovery' for depression post-intervention were low. Whilst significantly more treated patients did recover (17% [95% CI 0.10, 0.25]) than controls (9% [95% CI 0.03, 0.17]), the difference was small (6% [95% CI 0.02, 0.10]).

LIMITATIONS

Only 50% of eligible trials provided IPD; we were also only able to examine outcomes immediately following the end of an intervention.

CONCLUSION

Current psychological interventions offer limited benefit in treating anxiety and depression in people with Type 1 or Type 2 diabetes (83% remain depressed). More efficacious interventions are urgently needed.

Stereotactic Body Radiation Therapy versus Conventional External Beam Radiation Therapy for Painful Bone Metastases: A Systematic Review and Meta-analysis of Randomized Trials

PURPOSE

To compare the efficacy and safety of stereotactic body radiation therapy (SBRT) and conventional external beam radiation therapy (cEBRT) in patients with previously unirradiated painful bone metastases (BM).

METHODS

We searched biomedical databases for eligible randomized trials (RCTs). The outcomes of interest were pain response, local progression, overall survival (OS) and adverse events. We used established tools to assess the quality of the individual trials and certainty of the pooled evidence. We performed meta-analyses using random effects models.

RESULTS

Six RCTs were identified. SBRT improved complete pain response rates at 3 months (OR, 3.38; 95% CI, 1.88-6.07; high certainty), reduced local progression rates (OR, 0.19; 95% CI, 0.06-0.62; high certainty) and increase pain flare rates. There were no differences for other outcomes.

CONCLUSION

Among patients with previously unirradiated painful BM, SBRT significantly improved complete pain response rates at 3 months, delayed local progression and increase pain flare rates.

Exercise and Cardiovascular Disease Risk Factors in Children and Adolescents With Obesity: A Systematic Review With Meta-Analysis of Randomized Controlled Trials

The purpose of this study was to examine the effects of exercise on cardiovascular disease (CVD) risk factors in children and adolescents with obesity. Randomized controlled trials (RCTs) of exercise ≥4 weeks in children and adolescents with obesity were included if one or more CVD risk factors were included as an outcome. Studies were retrieved by searching 7 electronic databases, cross-referencing, and expert review. Data were pooled using the inverse-variance heterogeneity (IVhet) model and strength of evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) instrument. Thirty-nine studies representing 1548 participants (847 exercise, 701 control) met the inclusion criteria. Aerobic exercise improved 10 of 12 (83.3%) outcomes (P < .05 for all) while combined aerobic and strength training improved 5 of 8 (62.5%) outcomes (P < .05 for all). The strength of evidence ranged from "very low" to "moderate." It was concluded that aerobic exercise, as well as combined aerobic and strength training, is associated with improvements in multiple CVD risk factors among children and adolescents with obesity. However, the generally low strength of evidence suggests a need for future well-designed and conducted RCTs on the effects of exercise, especially strength training, in children and adolescents with obesity.

Mindfulness-based programmes for mental health promotion in adults in non-clinical settings: protocol of an individual participant data meta-analysis of randomised controlled trials

INTRODUCTION

With mental ill health listed as a top cause of global disease burden, there is an urgent need to prioritise mental health promotion programmes. Mindfulness-based programmes (MBPs) are being widely implemented to reduce stress in non-clinical settings. In a recent aggregate-level meta-analysis we found that, compared with no intervention, these MBPs reduce average psychological distress. However, heterogeneity between studies impedes generalisation of effects across every setting. Study-level effect modifiers were insufficient to reduce heterogeneity; studying individual-level effect modifiers is warranted. This requires individual participant data (IPD) and larger samples than those found in existing individual trials.

METHODS AND ANALYSIS

We propose an IPD meta-analysis. Our primary aim is to see if, and how, baseline psychological distress, gender, age, education and dispositional mindfulness moderate the effect of MBPs on distress. We will search 13 databases for good-quality randomised controlled trials comparing in-person, expert-defined MBPs in non-clinical settings with passive controls. Two researchers will independently select, extract and appraise trials using the revised Cochrane risk-of-bias tool. Anonymised IPD of eligible trials will be sought from authors, who will be invited to collaborate.The primary outcome will be psychological distress measured using psychometrically validated questionnaires at 1-6 months after programme completion. Pairwise random-effects two-stage IPD meta-analyses will be conducted. Moderator analyses will follow a 'deft' approach. We will estimate subgroup-specific intervention effects. Secondary outcomes and sensitivity analyses are prespecified. Multiple imputation strategies will be applied to missing data.

ETHICS AND DISSEMINATION

The findings will refine our knowledge on the effectiveness of MBPs and help improve the targeting of MBPs in non-clinical settings. They will be shared in accessible formats with a range of stakeholders. Public and professional stakeholders are being involved in the planning, conduct and dissemination of this project.

PROSPERO REGISTRATION NUMBER

CRD42020200117.

Methodology to standardize heterogeneous statistical data presentations for combining time-to-event oncologic outcomes

Survival analysis following oncological treatments require specific analysis techniques to account for data considerations, such as failure to observe the time of event, patient withdrawal, loss to follow-up, and differential follow up. These techniques can include Kaplan-Meier and Cox proportional hazard analyses. However, studies do not always report overall survival (OS), disease-free survival (DFS), or cancer recurrence using hazard ratios, making the synthesis of such oncologic outcomes difficult. We propose a hierarchical utilization of methods to extract or estimate the hazard ratio to standardize time-to-event outcomes so that study inclusion into meta-analyses can be maximized. We also provide proof-of concept results from a statistical analysis that compares OS, DFS, and cancer recurrence for robotic surgery to open and non-robotic minimally invasive surgery. In our example, use of the proposed methodology would allow for the increase in data inclusion from 108 hazard ratios reported to 240 hazard ratios reported or estimated, resulting in an increase of 122%. While there are publications summarizing the motivation for these analyses, and comprehensive papers describing strategies to obtain estimates from published time-dependent analyses, we are not aware of a manuscript that describes a prospective framework for an analysis of this scale focusing on the inclusion of a maximum number of publications reporting on long-term oncologic outcomes incorporating various presentations of statistical data.

Is meta-analysis of RCTs assessing the efficacy of interventions a reliable source of evidence for therapeutic decisions?

Literature-based meta-analysis is a standard technique applied to pool results of individual studies used in medicine and social sciences. It has been criticized for being too malleable to constrain results, averaging incomparable values, lacking a measure of evidence's strength, and problems with a systematic bias of individual studies. We argue against using literature-based meta-analysis of RCTs to assess treatment efficacy and show that therapeutic decisions based on meta-analytic average are not optimal given the full scope of existing evidence. The argument proceeds with discussing examples and analyzing the properties of some standard meta-analytic techniques. First, we demonstrate that meta-analysis can lead to reporting statistically significant results despite the treatment's limited efficacy. Second, we show that meta-analytic confidence intervals are too narrow compared to the variability of treatment outcomes reported by individual studies. Third, we argue that literature-based meta-analysis is not a reliable measurement instrument. Finally, we show that meta-analysis averages out the differences among studies and leads to a loss of information. Despite these problems, literature-based meta-analysis is useful for the assessment of harms. We support two alternative approaches to evidence amalgamation: meta-analysis of individual patient data (IPD) and qualitative review employing mechanistic evidence.

Transforming Obesity Prevention for CHILDren (TOPCHILD) Collaboration: protocol for a systematic review with individual participant data meta-analysis of behavioural interventions for the prevention of early childhood obesity

INTRODUCTION

Behavioural interventions in early life appear to show some effect in reducing childhood overweight and obesity. However, uncertainty remains regarding their overall effectiveness, and whether effectiveness differs among key subgroups. These evidence gaps have prompted an increase in very early childhood obesity prevention trials worldwide. Combining the individual participant data (IPD) from these trials will enhance statistical power to determine overall effectiveness and enable examination of individual and trial-level subgroups. We present a protocol for a systematic review with IPD meta-analysis to evaluate the effectiveness of obesity prevention interventions commencing antenatally or in the first year after birth, and to explore whether there are differential effects among key subgroups.

METHODS AND ANALYSIS

Systematic searches of Medline, Embase, Cochrane Central Register of Controlled Trials, Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsycInfo and trial registries for all ongoing and completed randomised controlled trials evaluating behavioural interventions for the prevention of early childhood obesity have been completed up to March 2021 and will be updated annually to include additional trials. Eligible trialists will be asked to share their IPD; if unavailable, aggregate data will be used where possible. An IPD meta-analysis and a nested prospective meta-analysis will be performed using methodologies recommended by the Cochrane Collaboration. The primary outcome will be body mass index z-score at age 24±6 months using WHO Growth Standards, and effect differences will be explored among prespecified individual and trial-level subgroups. Secondary outcomes include other child weight-related measures, infant feeding, dietary intake, physical activity, sedentary behaviours, sleep, parenting measures and adverse events.

ETHICS AND DISSEMINATION

Approved by The University of Sydney Human Research Ethics Committee (2020/273) and Flinders University Social and Behavioural Research Ethics Committee (HREC CIA2133-1). Results will be relevant to clinicians, child health services, researchers, policy-makers and families, and will be disseminated via publications, presentations and media releases.

PROSPERO REGISTRATION NUMBER

CRD42020177408.

Systematic Review Reveals Lack of Causal Methodology Applied to Pooled Longitudinal Observational Infectious Disease Studies

OBJECTIVES

Among ID studies seeking to make causal inferences and pooling individual-level longitudinal data from multiple infectious disease cohorts, we sought to assess what methods are being used, how those methods are being reported, and whether these factors have changed over time.

STUDY DESIGN AND SETTING

Systematic review of longitudinal observational infectious disease studies pooling individual-level patient data from 2+ studies published in English in 2009. 2014, or 2019. This systematic review protocol is registered with PROSPERO (CRD42020204104).

RESULTS

Our search yielded 1,462 unique articles. Of these, 16 were included in the final review. Our analysis showed a lack of causal inference methods and of clear reporting on methods and the required assumptions.

CONCLUSION

There are many approaches to causal inference which may help facilitate accurate inference in the presence of unmeasured and time-varying confounding. In observational ID studies leveraging pooled, longitudinal IPD, the absence of these causal inference methods and gaps in the reporting of key methodological considerations suggests there is ample opportunity to enhance the rigor and reporting of research in this field. Interdisciplinary collaborations between substantive and methodological experts would strengthen future work.

Analyzing Data of a Multilab Replication Project With Individual Participant Data Meta-Analysis

Abstract. Multilab replication projects such as Registered Replication Reports (RRR) and Many Labs projects are used to replicate an effect in different labs. Data of these projects are usually analyzed using conventional meta-analysis methods. This is certainly not the best approach because it does not make optimal use of the available data as a summary rather than participant data are analyzed. I propose to analyze data of multilab replication projects with individual participant data (IPD) meta-analysis where the participant data are analyzed directly. The prominent advantages of IPD meta-analysis are that it generally has larger statistical power to detect moderator effects and allows drawing conclusions at the participant and lab level. However, a disadvantage is that IPD meta-analysis is more complex than conventional meta-analysis. In this tutorial, I illustrate IPD meta-analysis using the RRR by McCarthy and colleagues, and I provide R code and recommendations to facilitate researchers to apply these methods.

Individual Participant Data Meta-Analysis versus Aggregate Data Meta-Analysis: a case study in eczema and food allergy prevention

Introduction

Meta‐analysis traditionally uses aggregate data from published reports. Individual Participant Data (IPD) meta‐analysis, which obtains and synthesizes participant‐level data, is potentially more informative, but resource‐intensive. The impact on the findings of meta‐analyses using IPD in comparison with aggregate data has rarely been formally evaluated.

Methods

We conducted a secondary analysis of a Cochrane systematic review of skincare interventions for preventing eczema and food allergy in infants to identify the impact of the analytical choice on the review's findings. We used aggregate data meta‐analysis only and contrasted the results against those of the originally published IPD meta‐analysis. All meta‐analysis used random effects inverse variance models. Certainty of evidence was evaluated using GRADE.

Results

The pooled treatment effects for the Cochrane systematic review's co‐primary outcomes of eczema and food allergy were similar in IPD meta‐analysis (eczema RR 1.03, 95% CI 0.81, 1.31; I²41%, 7 studies 3075 participants), and aggregate meta‐analysis (eczema RR 1.01 95% CI 0.77, 1.33; I²53%, 7 studies, 3089 participants). In aggregate meta‐analysis, the statistical heterogeneity could not be explained but using IPD it was explained by one trial which used a different, bathing intervention. For IPD meta‐analysis, risk of bias was assessed as lower and more adverse event data were available compared with aggregate meta‐analysis. This resulted in higher certainty of evidence, especially for adverse events. IPD meta‐analysis enabled analysis of treatment interactions by age and hereditary eczema risk; and analysis of the effect of treatment adherence using pooled complier‐adjusted‐causal‐effect analysis, none of which was possible in aggregate meta‐analysis.

Conclusions

For this systematic review, IPD did not significantly change primary outcome risk ratios compared with aggregate data meta‐analysis. However, certainty of evidence, safety outcomes, subgroup and adherence analyses were significantly different using IPD. This demonstrates benefits of adopting an IPD approach to meta‐analysis.

Current trends in the application of causal inference methods to pooled longitudinal non-randomised data: a protocol for a methodological systematic review

INTRODUCTION

Causal methods have been adopted and adapted across health disciplines, particularly for the analysis of single studies. However, the sample sizes necessary to best inform decision-making are often not attainable with single studies, making pooled individual-level data analysis invaluable for public health efforts. Researchers commonly implement causal methods prevailing in their home disciplines, and how these are selected, evaluated, implemented and reported may vary widely. To our knowledge, no article has yet evaluated trends in the implementation and reporting of causal methods in studies leveraging individual-level data pooled from several studies. We undertake this review to uncover patterns in the implementation and reporting of causal methods used across disciplines in research focused on health outcomes. We will investigate variations in methods to infer causality used across disciplines, time and geography and identify gaps in reporting of methods to inform the development of reporting standards and the conversation required to effect change.

METHODS AND ANALYSIS

We will search four databases (EBSCO, Embase, PubMed, Web of Science) using a search strategy developed with librarians from three universities (Heidelberg University, Harvard University, and University of California, San Francisco). The search strategy includes terms such as 'pool*', 'harmoniz*', 'cohort*', 'observational', variations on 'individual-level data'. Four reviewers will independently screen articles using Covidence and extract data from included articles. The extracted data will be analysed descriptively in tables and graphically to reveal the pattern in methods implementation and reporting. This protocol has been registered with PROSPERO (CRD42020143148).

ETHICS AND DISSEMINATION

No ethical approval was required as only publicly available data were used. The results will be submitted as a manuscript to a peer-reviewed journal, disseminated in conferences if relevant, and published as part of doctoral dissertations in Global Health at the Heidelberg University Hospital.

Effect of dietary nitrate on human muscle power: a systematic review and individual participant data meta-analysis

BACKGROUND

Previous narrative reviews have concluded that dietary nitrate (NO3-) improves maximal neuromuscular power in humans. This conclusion, however, was based on a limited number of studies, and no attempt has been made to quantify the exact magnitude of this beneficial effect. Such information would help ensure adequate statistical power in future studies and could help place the effects of dietary NO3- on various aspects of exercise performance (i.e., endurance vs. strength vs. power) in better context. We therefore undertook a systematic review and individual participant data meta-analysis to quantify the effects of NO3- supplementation on human muscle power.

METHODS

The literature was searched using a strategy developed by a health sciences librarian. Data sources included Medline Ovid, Embase, SPORTDiscus, Scopus, Clinicaltrials.gov , and Google Scholar. Studies were included if they used a randomized, double-blind, placebo-controlled, crossover experimental design to measure the effects of dietary NO3- on maximal power during exercise in the non-fatigued state and the within-subject correlation could be determined from data in the published manuscript or obtained from the authors.

RESULTS

Nineteen studies of a total of 268 participants (218 men, 50 women) met the criteria for inclusion. The overall effect size (ES; Hedge's g) calculated using a fixed effects model was 0.42 (95% confidence interval (CI) 0.29, 0.56; p = 6.310 × 10- 11). There was limited heterogeneity between studies (i.e., I2 = 22.79%, H2 = 1.30, p = 0.3460). The ES estimated using a random effects model was therefore similar (i.e., 0.45, 95% CI 0.30, 0.61; p = 1.064 × 10- 9). Sub-group analyses revealed no significant differences due to subject age, sex, or test modality (i.e., small vs. large muscle mass exercise). However, the ES in studies using an acute dose (i.e., 0.54, 95% CI 0.37, 0.71; p = 6.774 × 10- 12) was greater (p = 0.0211) than in studies using a multiple dose regimen (i.e., 0.22, 95% CI 0.01, 0.43; p = 0.003630).

CONCLUSIONS

Acute or chronic dietary NO3- intake significantly increases maximal muscle power in humans. The magnitude of this effect-on average, ~ 5%-is likely to be of considerable practical and clinical importance.

A framework for prospective, adaptive meta-analysis (FAME) of aggregate data from randomised trials

BACKGROUND

The vast majority of systematic reviews are planned retrospectively, once most eligible trials have completed and reported, and are based on aggregate data that can be extracted from publications. Prior knowledge of trial results can introduce bias into both review and meta-analysis methods, and the omission of unpublished data can lead to reporting biases. We present a collaborative framework for prospective, adaptive meta-analysis (FAME) of aggregate data to provide results that are less prone to bias. Also, with FAME, we monitor how evidence from trials is accumulating, to anticipate the earliest opportunity for a potentially definitive meta-analysis.

METHODOLOGY

We developed and piloted FAME alongside 4 systematic reviews in prostate cancer, which allowed us to refine the key principles. These are to: (1) start the systematic review process early, while trials are ongoing or yet to report; (2) liaise with trial investigators to develop a detailed picture of all eligible trials; (3) prospectively assess the earliest possible timing for reliable meta-analysis based on the accumulating aggregate data; (4) develop and register (or publish) the systematic review protocol before trials produce results and seek appropriate aggregate data; (5) interpret meta-analysis results taking account of both available and unavailable data; and (6) assess the value of updating the systematic review and meta-analysis. These principles are illustrated via a hypothetical review and their application to 3 published systematic reviews.

CONCLUSIONS

FAME can reduce the potential for bias, and produce more timely, thorough and reliable systematic reviews of aggregate data.

Current trends in the application of causal inference methods to pooled longitudinal observational infectious disease studies-A protocol for a methodological systematic review

INTRODUCTION

Pooling (or combining) and analysing observational, longitudinal data at the individual level facilitates inference through increased sample sizes, allowing for joint estimation of study- and individual-level exposure variables, and better enabling the assessment of rare exposures and diseases. Empirical studies leveraging such methods when randomization is unethical or impractical have grown in the health sciences in recent years. The adoption of so-called "causal" methods to account for both/either measured and/or unmeasured confounders is an important addition to the methodological toolkit for understanding the distribution, progression, and consequences of infectious diseases (IDs) and interventions on IDs. In the face of the Covid-19 pandemic and in the absence of systematic randomization of exposures or interventions, the value of these methods is even more apparent. Yet to our knowledge, no studies have assessed how causal methods involving pooling individual-level, observational, longitudinal data are being applied in ID-related research. In this systematic review, we assess how these methods are used and reported in ID-related research over the last 10 years. Findings will facilitate evaluation of trends of causal methods for ID research and lead to concrete recommendations for how to apply these methods where gaps in methodological rigor are identified.

METHODS AND ANALYSIS

We will apply MeSH and text terms to identify relevant studies from EBSCO (Academic Search Complete, Business Source Premier, CINAHL, EconLit with Full Text, PsychINFO), EMBASE, PubMed, and Web of Science. Eligible studies are those that apply causal methods to account for confounding when assessing the effects of an intervention or exposure on an ID-related outcome using pooled, individual-level data from 2 or more longitudinal, observational studies. Titles, abstracts, and full-text articles, will be independently screened by two reviewers using Covidence software. Discrepancies will be resolved by a third reviewer. This systematic review protocol has been registered with PROSPERO (CRD42020204104).

Poly (ADP-ribose) polymerase inhibitors in solid tumours: Systematic review and meta-analysis

BACKGROUND

Poly (ADP-ribose) polymerase-inhibitors (PARPis) showed antitumour activity in BRCA1/2-mutated cancers, with more heterogeneous outcomes in tumours harbouring mutations that impair other genes involved in the DNA homologous recombination repair (HRR) or wild-type (wt).

METHODS

We conducted a systematic review and meta-analysis to better assess the role of PARPis in the treatment of metastatic solid tumours, with and without BRCA1/2 mutations. The primary end-point was progression-free survival (PFS). The secondary end-points were overall response rate (ORR) and overall survival (OS). A random-effects model was applied.

RESULTS

Twenty-nine studies (8,839 patients) were included. PFS was significantly improved (hazard ratio [HR]: 0.59, 95% confidence interval [CI]: 0.51-0.68, p < 0.001), without being affected by BRCA mutational status (p = 0.65). Significant subgroup differences were observed with regard to the tumour site (p = 0.001), line of therapy (p = 0.002), control arm (p < 0.001), type of PARPi (p < 0.001) and trials' phase (p = 0.006). PARPis were associated with ORR (relative risk: 1.35, 95% CI: 1.16-1.56, p < 0.001), with significant subgroup differences observed with regard to treatment line (p = 0.03), control arm (p = 0.04) and PARPis (p < 0.001) and independent of mutational status (p = 0.44), tumour site (p = 0.86) and trials' phase (p = 0.09). OS was significantly improved by PARPis (HR: 0.86, 95% CI: 0.80-0.92, p < 0.001), regardless of mutational status (p = 0.57), tumour site (p = 0.82), treatment line (p = 0.22), control arm (p = 0.21), PARPis (p = 0.30) and trials' phase (p = 0.26). Finally, an exploratory subgroup analysis showed a significant PFS improvement (HR: 0.51, 95% CI: 0.43-0.60, p < 0.001) with PARPis in BRCA-wt/HRR-deficient tumours.

CONCLUSION

Our results confirm the efficacy of already approved PARPi-based treatments in BRCA1/2-mutant solid tumours, support their role also in BRCA-independent HRR-deficient tumours and suggest a potentially broader efficacy in some wt tumours, perhaps with appropriate therapeutic partners. Prospective studies are warranted.

Bayesian Methods for Meta-Analyses of Binary Outcomes: Implementations, Examples, and Impact of Priors

Bayesian methods are an important set of tools for performing meta-analyses. They avoid some potentially unrealistic assumptions that are required by conventional frequentist methods. More importantly, meta-analysts can incorporate prior information from many sources, including experts’ opinions and prior meta-analyses. Nevertheless, Bayesian methods are used less frequently than conventional frequentist methods, primarily because of the need for nontrivial statistical coding, while frequentist approaches can be implemented via many user-friendly software packages. This article aims at providing a practical review of implementations for Bayesian meta-analyses with various prior distributions. We present Bayesian methods for meta-analyses with the focus on odds ratio for binary outcomes. We summarize various commonly used prior distribution choices for the between-studies heterogeneity variance, a critical parameter in meta-analyses. They include the inverse-gamma, uniform, and half-normal distributions, as well as evidence-based informative log-normal priors. Five real-world examples are presented to illustrate their performance. We provide all of the statistical code for future use by practitioners. Under certain circumstances, Bayesian methods can produce markedly different results from those by frequentist methods, including a change in decision on statistical significance. When data information is limited, the choice of priors may have a large impact on meta-analytic results, in which case sensitivity analyses are recommended. Moreover, the algorithm for implementing Bayesian analyses may not converge for extremely sparse data; caution is needed in interpreting respective results. As such, convergence should be routinely examined. When select statistical assumptions that are made by conventional frequentist methods are violated, Bayesian methods provide a reliable alternative to perform a meta-analysis.

Endocrine-Based Treatments in Clinically-Relevant Subgroups of Hormone Receptor-Positive/HER2-Negative Metastatic Breast Cancer: Systematic Review and Meta-Analysis

A precise assessment of the efficacy of first-/second-line endocrine therapies (ET) ± target therapies (TT) in clinically-relevant subgroups of hormone receptor-positive (HR+)/HER2-negative metastatic breast cancer (MBC) has not yet been conducted. To improve our current knowledge and support clinical decision-making, we thus conducted a systematic literature search to identify all first-/second-line phase II/III randomized clinical trials (RCT) of currently approved or most promising ET ± TT. Then, we performed a meta-analysis to assess progression-free (PFS) and/or overall survival (OS) benefit in several clinically-relevant prespecified subgroups. Thirty-five RCT were included (17,595 patients). Pooled results show significant reductions in the risk of relapse or death of 26-41% and 12-27%, respectively, depending on the clinical subgroup. Combination strategies proved to be more effective than single-agent ET (PFS hazard ratio (HR) range for combinations: 0.60-0.65 vs. HR range for single agent ET: 0.59-1.37; OS HR range for combinations: 0.74-0.87 vs. HR range for single agent ET: 0.68-0.98), with CDK4/6-inhibitors(i) + ET being the most effective regimen. Single agent ET showed comparable efficacy with ET+TT combinations in non-visceral (p = 0.63) and endocrine sensitive disease (p = 0.79), while mTORi-based combinations proved to be a valid therapeutic option in endocrine-resistant tumors, as well as PI3Ki + ET in PIK3CA-mutant tumors. These results strengthen international treatment guidelines and can aid therapeutic decision-making.

Clinical Trial Data Sharing for COVID-19-Related Research

This paper aims to provide a perspective on data sharing practices in the context of the COVID-19 pandemic. The scientific community has made several important inroads in the fight against COVID-19, and there are over 2500 clinical trials registered globally. Within the context of the rapidly changing pandemic, we are seeing a large number of trials conducted without results being made available. It is likely that a plethora of trials have stopped early, not for statistical reasons but due to lack of feasibility. Trials stopped early for feasibility are, by definition, statistically underpowered and thereby prone to inconclusive findings. Statistical power is not necessarily linear with the total sample size, and even small reductions in patient numbers or events can have a substantial impact on the research outcomes. Given the profusion of clinical trials investigating identical or similar treatments across different geographical and clinical contexts, one must also consider that the likelihood of a substantial number of false-positive and false-negative trials, emerging with the increasing overall number of trials, adds to public perceptions of uncertainty. This issue is complicated further by the evolving nature of the pandemic, wherein baseline assumptions on control group risk factors used to develop sample size calculations are far more challenging than those in the case of well-documented diseases. The standard answer to these challenges during nonpandemic settings is to assess each trial for statistical power and risk-of-bias and then pool the reported aggregated results using meta-analytic approaches. This solution simply will not suffice for COVID-19. Even with random-effects meta-analysis models, it will be difficult to adjust for the heterogeneity of different trials with aggregated reported data alone, especially given the absence of common data standards and outcome measures. To date, several groups have proposed structures and partnerships for data sharing. As COVID-19 has forced reconsideration of policies, processes, and interests, this is the time to advance scientific cooperation and shift the clinical research enterprise toward a data-sharing culture to maximize our response in the service of public health.

Evaluation of various estimators for standardized mean difference in meta-analysis

Meta-analyses of a treatment's effect compared with a control frequently calculate the meta-effect from standardized mean differences (SMDs). SMDs are usually estimated by Cohen's d or Hedges' g. Cohen's d divides the difference between sample means of a continuous response by the pooled standard deviation, but is subject to nonnegligible bias for small sample sizes. Hedges' g removes this bias with a correction factor. The current literature (including meta-analysis books and software packages) is confusingly inconsistent about methods for synthesizing SMDs, potentially making reproducibility a problem. Using conventional methods, the variance estimate of SMD is associated with the point estimate of SMD, so Hedges' g is not guaranteed to be unbiased in meta-analyses. This article comprehensively reviews and evaluates available methods for synthesizing SMDs. Their performance is compared using extensive simulation studies and analyses of actual datasets. We find that because of the intrinsic association between point estimates and standard errors, the usual version of Hedges' g can result in more biased meta-estimation than Cohen's d. We recommend using average-adjusted variance estimators to obtain an unbiased meta-estimate, and the Hartung-Knapp-Sidik-Jonkman method for accurate estimation of its confidence interval.

Pre-pregnancy obesity and risk of congenital abnormalities of the kidney and urinary tract (CAKUT)-systematic review, meta-analysis and ecological study

BACKGROUND

There is increasing evidence that maternal obesity is associated with several structural birth defects. Congenital abnormalities of the kidney and urinary tract (CAKUT) account for 30 to 50% of children starting kidney replacement therapy (KRT). We conducted a systematic review, meta-analysis and ecological study to explore the relationship between maternal obesity and CAKUT.

METHODS

A systematic literature search was conducted in EMBASE, MEDLINE, Global Health, The Cochrane Library, Scopus and Web of Science. Study quality was assessed for bias and confounding. A meta-analysis using a random effect model was carried out to obtain a summary odds ratio (OR) and 95% confidence interval (CI). In the ecological study, country-level data were used to examine the correlation of secular trends in female obesity, CAKUT incidence and incidence of KRT.

RESULTS

Eight epidemiological studies were included in the review-4 cohort studies and 4 case-control studies-7 of which were included in the meta-analysis. There was evidence of a positive association between obesity during pregnancy and the risk of CAKUT, with a summary OR = 1.14 (1.02-1.27). No association was seen with overweight, nor a dose response with increasing obesity. There was an increasing trend in countries' proportion of female obesity and an increasing trend in reported CAKUT incidence with specific rises seen in congenital hydronephrosis (CH) and multicystic kidney dysplasia (MCKD).

CONCLUSIONS

Our findings suggest that pre-pregnancy obesity may be associated with increased risk of CAKUT at population level. Graphical abstract.

Dopamine and Neuroinflammation in Schizophrenia - Interpreting the Findings from Translocator Protein (18kDa) PET Imaging

Schizophrenia is a complex disease whose pathophysiology is not yet fully understood. In addition to the long prevailing dopaminergic hypothesis, the evidence suggests that neuroinflammation plays a role in the pathophysiology of the disease. Recent studies using positron emission tomography (PET) that target a 18kDa translocator protein (TSPO) in activated microglial cells in an attempt to measure neuroinflammation in patients have shown a decrease or a lack of an increase in TSPO binding. Many biological and methodological considerations have been formulated to explain these findings. Although dopamine has been described as an immunomodulatory molecule, its potential role in neuroinflammation has not been explored in the aforementioned studies. In this review, we discuss the interactions between dopamine and neuroinflammation in psychotic states. Dopamine may inhibit neuroinflammation in activated microglia. Proinflammatory molecules released from microglia may decrease dopaminergic transmission. This could potentially explain why the levels of neuroinflammation in the brain of patients with schizophrenia seem to be unchanged or decreased compared to those in healthy subjects. However, most data are indirect and are derived from animal studies or from studies performed outside the field of schizophrenia. Further studies are needed to combine TSPO and dopamine imaging to study the association between microglial activation and dopamine system function.

ECMO for severe ARDS: systematic review and individual patient data meta-analysis

PURPOSE

To assess the effect of venovenous extracorporeal membrane oxygenation (ECMO) compared to conventional management in patients with severe acute respiratory distress syndrome (ARDS).

METHODS

We conducted a systematic review and individual patient data meta-analysis of randomised controlled trials (RCTs) performed after Jan 1, 2000 comparing ECMO to conventional management in patients with severe ARDS. The primary outcome was 90-day mortality. Primary analysis was by intent-to-treat.

RESULTS

We identified two RCTs (CESAR and EOLIA) and combined data from 429 patients. On day 90, 77 of the 214 (36%) ECMO-group and 103 of the 215 (48%) control group patients had died (relative risk (RR), 0.75, 95% confidence interval (CI) 0.6-0.94; P = 0.013; I2 = 0%). In the per-protocol and as-treated analyses the RRs were 0.75 (95% CI 0.6-0.94) and 0.86 (95% CI 0.68-1.09), respectively. Rescue ECMO was used for 36 (17%) of the 215 control patients (35 in EOLIA and 1 in CESAR). The RR of 90-day treatment failure, defined as death for the ECMO-group and death or crossover to ECMO for the control group was 0.65 (95% CI 0.52-0.8; I2 = 0%). Patients randomised to ECMO had more days alive out of the ICU and without respiratory, cardiovascular, renal and neurological failure. The only significant treatment-covariate interaction in subgroups was lower mortality with ECMO in patients with two or less organs failing at randomization.

CONCLUSIONS

In this meta-analysis of individual patient data in severe ARDS, 90-day mortality was significantly lowered by ECMO compared with conventional management.

Trials number, funding support, and intervention type associated with IPDMA data retrieval: a cross-sectional study

OBJECTIVES

This study aimed to investigate the predictors for high data retrieval and the reporting of individual participant data meta-analyses (IPDMAs).

STUDY DESIGN AND SETTING

We searched EMBASE, MEDLINE, and the Cochrane Library for articles pertaining to IPDMA from 2011 to 2019. Only IPDMA assessing treatment effects, including randomized controlled trials (RCTs), were included. Adherence to the PRISMA-IPD guideline was checked.

RESULTS

A total of 210 IPDMA covering 18 diseases were sampled; 80 (38.1%) and 123 (58.6%) of the IPDMA retrieved IPD from all and ≥80% RCTs, respectively. Non-Cochrane reviews, IPDMA on nonpharmacological interventions, analyses of smaller numbers of RCTs, and having funding supports were predictors of complete IPD retrieval. Owners of RCTs had an increased probability of obtaining IPD. Only 4.3% described the eligibility criteria covering all the PICO components, 11.0% reported the methods for assessing risk of bias across studies, 11.4% mentioned the IPD integrity, and 9.0% presented detailed results of syntheses.

CONCLUSION

IPD retrieval and reporting was not satisfactory among the published IPDMA. Encouraging RCT owners to conduct or join in the IPDMA is a potential strategy to maximize the IPD retrieval. IPDMA are suggested to adhere to the PRISMA-IPD guideline during reporting.

Adaptive platform trials using multi-arm, multi-stage protocols: getting fast answers in pandemic settings

Global health pandemics, such as coronavirus disease 2019 (COVID-19), require efficient and well-conducted trials to determine effective interventions, such as treatments and vaccinations. Early work focused on rapid sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), subsequent in-vitro and in-silico work, along with greater understanding of the different clinical phases of the infection, have helped identify a catalogue of potential therapeutic agents requiring assessment. In a pandemic, there is a need to quickly identify efficacious treatments, and reject those that are non-beneficial or even harmful, using randomised clinical trials. Whilst each potential treatment could be investigated across multiple, separate, competing two-arm trials, this is a very inefficient process. Despite the very large numbers of interventional trials for COVID-19, the vast majority have not used efficient trial designs. Well conducted, adaptive platform trials utilising a multi-arm multi-stage (MAMS) approach provide a solution to overcome limitations of traditional designs. The multi-arm element allows multiple different treatments to be investigated simultaneously against a shared, standard-of-care control arm. The multi-stage element uses interim analyses to assess accumulating data from the trial and ensure that only treatments showing promise continue to recruitment during the next stage of the trial. The ability to test many treatments at once and drop insufficiently active interventions significantly speeds up the rate at which answers can be achieved. This article provides an overview of the benefits of MAMS designs and successes of trials, which have used this approach to COVID-19. We also discuss international collaboration between trial teams, including prospective agreement to synthesise trial results, and identify the most effective interventions. We believe that international collaboration will help provide faster answers for patients, clinicians, and health care systems around the world, including for future waves of COVID-19, and enable preparedness for future global health pandemics.

Adaptive platform trials using multi-arm, multi-stage protocols: getting fast answers in pandemic settings

Global health pandemics, such as coronavirus disease 2019 (COVID-19), require efficient and well-conducted trials to determine effective interventions, such as treatments and vaccinations. Early work focused on rapid sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), subsequent in-vitro and in-silico work, along with greater understanding of the different clinical phases of the infection, have helped identify a catalogue of potential therapeutic agents requiring assessment. In a pandemic, there is a need to quickly identify efficacious treatments, and reject those that are non-beneficial or even harmful, using randomised clinical trials. Whilst each potential treatment could be investigated across multiple, separate, competing two-arm trials, this is a very inefficient process. Despite the very large numbers of interventional trials for COVID-19, the vast majority have not used efficient trial designs. Well conducted, adaptive platform trials utilising a multi-arm multi-stage (MAMS) approach provide a solution to overcome limitations of traditional designs. The multi-arm element allows multiple different treatments to be investigated simultaneously against a shared, standard-of-care control arm. The multi-stage element uses interim analyses to assess accumulating data from the trial and ensure that only treatments showing promise continue to recruitment during the next stage of the trial. The ability to test many treatments at once and drop insufficiently active interventions significantly speeds up the rate at which answers can be achieved. This article provides an overview of the benefits of MAMS designs and successes of trials, which have used this approach to COVID-19. We also discuss international collaboration between trial teams, including prospective agreement to synthesise trial results, and identify the most effective interventions. We believe that international collaboration will help provide faster answers for patients, clinicians, and health care systems around the world, including for each further wave of COVID-19, and enable preparedness for future global health pandemics.

Clinical Trials [and Tribulations]: The Immediate Effects of COVID-19 on IBD Clinical Research Activity in the UK

There have been immediate and profound impacts of SARS-CoV-2 and COVID-19 on health care services worldwide, with major consequences for non COVID-19 related health care. Alongside efforts to reconfigure services and enable continued delivery of safe clinical care for patients with IBD, consideration must also be given to management of IBD research activity. In many centres there has been an effective shutdown of IBD clinical trial activity as research sites have switched focus to either COVID-19 related research or clinical care only. As a result, the early termination of trial programmes, and loss of potentially effective therapeutic options for IBD, has become a real and worrying prospect. Moreover, in many countries research activity has become embedded into clinical care-with clinical trials often providing access to new therapies or strategies-which would otherwise not have been available in standard clinical pathways. This pandemic has significant implications for the design, conduct, analysis, and reporting of clinical trials in IBD. In this Viewpoint, we share our experiences from a clinical and academic perspective in the UK, highlighting the early challenges encountered, and consider implications for patients and staff at research sites, sponsors, research ethics committees, funders, and regulators. We also offer potential solutions both for now and for when we enter a recovery phase from the pandemic.