Meta-analysis of two studies in the presence of heterogeneity with applications in rare diseases

Acute Anterior Cruciate Ligament Reconstruction Performed Within 10 Days of Injury Does Not Increase Risk of Postoperative Arthrofibrosis: A Systematic Review and Meta-analysis

BACKGROUND

The optimal timing of anterior cruciate ligament (ACL) reconstruction (ACLR) remains a controversial topic. Previous reviews have demonstrated that there are no differences between early and delayed ACLR; however, these studies have been limited by heterogeneous definitions of acute ACL injury.

PURPOSE

To evaluate postoperative patient functional outcomes and risk for arthrofibrosis after acute arthroscopic ACLR performed ≤10 days after injury.

STUDY DESIGN

Systematic review; Level of evidence, 4.

METHODS

A systematic review was performed according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines using multiple medical databases. Inclusion criteria were studies that evaluated postoperative range of motion outcomes for patients undergoing ACLR ≤10 days after initial ACL injury. For included comparative studies comparing patient groups undergoing ACLR ≤10 days and patients undergoing "delayed" ACLR after ≥3 weeks of initial injury, quantitative analysis was performed to assess for differences in postoperative arthrofibrosis, reoperation rates, and patient-reported outcomes between groups. DerSimonian-Laird binary random-effects models were constructed to quantitatively describe the association between the ACLR time period and patient outcomes by generating effect estimates in the form of odds ratios with 95% CIs. Qualitative analysis was performed to describe variably reported patient outcomes and the risk of arthrofibrosis after ACLR for noncomparative studies.

RESULTS

Screening yielded 6 full-text articles with 448 patients who underwent ACLR (296 ACLR <10 days, 152 ACLR >3 weeks), with a pooled mean age of 28.1 years. For studies amenable to quantitative analysis, there were no significant differences between ACLR performed ≤10 days and ACLR performed at the 3-week point or after in terms of postoperative stiffness (3 studies; odds ratio, 1.27; P = .508), Tegner scores (2 studies; mean difference, -0.056; P = .155), or reoperation for stiffness (3 studies; odds ratio, 0.869; P = .462). The overall incidence of postoperative arthrofibrosis after 12 months of follow-up was 11 of 296 (3.7%) for ACLRs performed ≤10 days versus 6 of 152 (3.9%) for those performed at the 3-week point or after.

CONCLUSION

ACLR performed ≤10 days after the inciting injury does not increase the risk of postoperative arthrofibrosis and demonstrates similar patient-reported outcomes compared with ACLR performed at the 3-week point or after.

Clinical Results of Primary Repair Versus Reconstruction of the Anterior Cruciate Ligament: A Systematic Review and Meta-analysis of Contemporary Trials

Background

Primary anterior cruciate ligament (ACL) repair has gained renewed interest in select centers for patients with proximal or midsubstance ACL tears. Therefore, it is important to reassess contemporary clinical outcomes of ACL repair to determine whether a clinical benefit exists over the gold standard of ACL reconstruction (ACLR).

Purpose

To (1) perform a meta-analysis of comparative trials to determine whether differences in clinical outcomes and adverse events exist between ACL repair versus ACLR and (2) synthesize the midterm outcomes of available trials.

Study Design

Systematic review; Level of evidence, 3.

Methods

The PubMed, OVID/Medline, and Cochrane databases were queried in August 2023 for prospective and retrospective clinical trials comparing ACL repair and ACLR. Data pertaining to tear location, surgical technique, adverse events, and clinical outcome measures were recorded. DerSimonian-Laird random-effects models were constructed to quantitatively evaluate the association between ACL repair/ACLR, adverse events, and clinical outcomes. A subanalysis of minimum 5-year outcomes was performed.

Results

Twelve studies (893 patients; 464 ACLR and 429 ACL repair) were included. Random-effects models demonstrated a higher relative risk (RR) of recurrent instability/clinical failure (RR = 1.64; 95% confidence interval [CI], 1.04-2.57; P = .032), revision ACLR (RR = 1.63; 95% CI, 1.03-2.59; P = .039), and hardware removal (RR = 4.94; 95% CI, 2.10-11.61; P = .0003) in patients who underwent primary ACL repair versus ACLR. The RR of reoperations and complications (knee-related) were not significantly different between groups. No significant differences were observed when comparing patient-reported outcome scores. In studies with minimum 5-year outcomes, no significant differences in adverse events or Lysholm scores were observed.

Conclusion

In contemporary comparative trials of ACL repair versus ACLR, the RR of clinical failure, revision surgery due to ACL rerupture, and hardware removal was greater for primary ACL repair compared with ACLR. There were no observed differences in patient-reported outcome scores, reoperations, or knee-related complications between approaches. In the limited literature reporting on minimum 5-year outcomes, significant differences in adverse events or the International Knee Documentation Committee score were not observed.

The optimal threshold of PD-L1 combined positive score to predict the benefit of PD-1 antibody plus chemotherapy for patients with HER2-negative gastric adenocarcinoma: a meta-analysis

BACKGROUND

Immune checkpoint inhibitors (ICIs) combined with chemotherapy have become the first-line treatment of metastatic gastric and gastroesophageal adenocarcinomas (GEACs). This study aims to figure out the optimal combined positive score (CPS) cutoff value.

METHODS

We searched for randomized phase III trials to investigate the efficacy of ICIs plus chemotherapy for metastatic GEACs compared with chemotherapy alone. Pooled analyses of hazard ratios (HRs) based on PD-L1 expression were performed.

RESULTS

A total of six trials (KEYNOTE-062, KEYNOTE-590, KEYNOTE-859, ATTRACTION-04, CheckMate 649, and ORIENT-16) were included, comprising 5,242 patients. ICIs plus chemotherapy significantly improved OS (HR: 0.79, 95% CI 0.72-0.86 in global patients; HR: 0.75, 95% CI 0.57-0.98 in Asian patients) and PFS (HR: 0.74, 95% CI 0.68-0.82 in global patients; HR: 0.64, 95% CI 0.56-0.73 in Asian patients) compared with chemotherapy alone. The differences in OS (ratio of HR: 1.05, 95% CI 0.79-1.40; predictive value: - 5.1%) and PFS (ratio of HR: 1.16, 95% CI 0.98-1.36; predictive value: - 13.5%) were not statistically significant between the global and Asian patients. Subgroup analyses indicated that the optimal CPS threshold was at ≥ 5 for OS and ≥ 10 for PFS with the highest predictive values.

CONCLUSIONS

The benefit derived from ICIs plus chemotherapy is similar between Asian and global GEAC patients. However, those with a PD-L1 CPS < 5 or CPS < 10 may not have significant benefits from ICIs therapy. Therefore, it is advisable to routinely assess PD-L1 expression in GEAC patients considered for ICIs treatment.

Weil's osteotomy versus distal metatarsal metaphyseal osteotomy for the treatment of metatarsalgia. A metaanalysis of outcome and complications

BACKGROUND

Weil's osteotomy (WO) and distal metatarsal metaphyseal osteotomy (DMMO) are considered to be the gold standard of managing metatarsalgia. Stiffness and floating toe are the main disadvantages of the WO, whereas delayed union or malunion and prolonged swelling are the main complications of the DMMO. The purpose of this study is to compare these two methods, in terms of outcome and complications, through a metaanalysis of the literature.

MATERIALS AND METHODS

Pubmed, Google Scholar and Mendeley databases were searched for studies comparing directly the outcome of DMMO and Weil's osteotomy, with a minimum follow up of six months. The random effects model was used for the metaanalysis. The quality of studies was assessed using the MINORS criteria.

RESULTS

Four studies were eligible for the analysis including 211 patients in total. The mean difference of the postoperative American Orthopaedic Foot and Ankle Society (AOFAS) score and the visual analogue scale (VAS) among the two techniques was - 1,04 (C.I.: -3,50 - 1,43) and - 0,39 (CI: -0,83 - 0,08) respectively. The risk difference regarding postoperative stiffness, swelling and residual metatarsalgia was - 0,09 (95% C.I.: -0,23 - 0,06), - 0,17 (95% C.I.: -0,62 - 0,29) and - 0,06 (95% C.I.: -0,20 - 0,08) respectively.

CONCLUSION

Based on the existing literature, Weil's osteotomy and DMMO are equally safe and effective for the treatment of metatarsalgia. More studies of better quality are required, in order to extract safer and absolute conclusions regarding this topic.

Better together against genetic heterogeneity: A sex-combined joint main and interaction analysis of 290 quantitative traits in the UK Biobank

Genetic effects can be sex-specific, particularly for traits such as testosterone, a sex hormone. While sex-stratified analysis provides easily interpretable sex-specific effect size estimates, the presence of sex-differences in SNP effect implies a SNP×sex interaction. This suggests the usage of the often overlooked joint test, testing for an SNP's main and SNP×sex interaction effects simultaneously. Notably, even without individual-level data, the joint test statistic can be derived from sex-stratified summary statistics through an omnibus meta-analysis. Utilizing the available sex-stratified summary statistics of the UK Biobank, we performed such omnibus meta-analyses for 290 quantitative traits. Results revealed that this approach is robust to genetic effect heterogeneity and can outperform the traditional sex-stratified or sex-combined main effect-only tests. Therefore, we advocate using the omnibus meta-analysis that captures both the main and interaction effects. Subsequent sex-stratified analysis should be conducted for sex-specific effect size estimation and interpretation.

Lead exposure from honey: meta-analysis and risk assessment for the Arab region

The Codex Alimentarius Commission has adopted a maximum level for lead in honey (0.1 mg/kg). Despite representing a population of more than half a billion, exposure and risk assessments for lead specific to the Arab region are lacking. The aim of this work was to collect analytical data for lead in honey available in Arab countries and to assess the risk caused by exposure to lead from these samples for local consumers. A regional mean lead concentration in honey, obtained through a meta-analysis of 57 studies, was used in deterministic risk assessments for adults (nephrotoxicity and cardiovascular effects) and young children (developmental neurotoxicity). A regional pooled mean concentration of 0.12 mg/kg [95%CI: 0.07-0.21] (0.13 mg/kg, if non-detects are considered at their highest possible value) was obtained. Margins of exposure of 363 [71-17182] and 865 [168-40909] were calculated for adults, and of 48 [9-2273] for children, indicating potential concern for the latter population subset. These values were produced using GEMS consumption data, and considering the same intake for both children and adults, potentially overestimating the risk for children. Nevertheless, food competent authorities should consider measures to reduce lead concentration in honey available for sale in the region to prevent trade constraints and to better protect vulnerable populations.

Mind-body therapies adjuvant to chemotherapy improve quality of life and fatigue in top cancers: A systematic review and meta-analysis

BACKGROUND

Breast, lung and colorectal cancers are 3 of the top 4 most common cancers worldwide. Their treatment with chemotherapy often results in adverse effects on quality of life, fatigue and functional exercise capacity amongst patients. Mind-body therapies, including yoga, Tai chi and Qigong, are commonly used as complementary and alternative therapies in cancer. This meta-analysis evaluates the effects of yoga, Tai chi and Qigong in alleviating the adverse effects of chemotherapy.

METHODS

Various databases were systematically interrogated using specific search terms, returning 1901 manuscripts. Removal of duplicates, irrelevant studies, those lacking available data and applying inclusion/exclusion criteria reduced this number to 9 manuscripts for inclusion in the final meta-analyses. Mean differences were calculated to determine pooled effect sizes using RStudio.

RESULTS

This is the first systematic review and meta-analysis to demonstrate significant improvements in fatigue for colorectal cancer patients undergoing chemotherapy with a reduction of -1.40 (95 % CI: -2.24 to -0.56; p = 0.001) observed in mind-body therapy intervention groups.

CONCLUSION

Yoga, Tai chi and Qigong could all be implemented alongside adjuvant therapies to alleviate the adverse effects on colorectal cancer patient fatigue during chemotherapy treatment.

REVIEW REGISTRATION

This systematic review and meta-analysis is registered on InPlasy: registration number INPLASY202390035; doi: https://doi.org/10.37766/inplasy2023.9.0035.

Clinical outcome post treatment of anemia in pregnancy with intravenous versus oral iron therapy: a systematic review and meta-analysis

Oral iron therapy is often the most common way of treating anaemia; however intravenous iron is considered effective due to rapid iron replenishment. We have dearth of evidence on clinical outcomes post treatment of anaemia. We have searched studies published in English in PubMed, Cochrane, Scopus, ProQuest, and Google Scholar. Our study analysed the clinical outcomes amongst neonates and mother and the adverse events post treatment and assessed the mean change in maternal haemoglobin concentration in both the groups. Forest plots for the clinical outcomes are presented. From a total of 370 studies, 34 Randomized and quasi experimental studies comparing clinical outcomes post-treatment of anaemia in pregnancy were included for quantitative evidence synthesis. Pooled results of maternal clinical outcomes using random effect model [OR: 0.79 (95% CI 0.66; 0.95); 10 outcomes; 17 studies] showed statistically significant difference among both the groups [Moderate quality evidence]; however no significant difference [OR: 0.99 (95% CI 0.86; 1.14); 7 outcomes; 8 studies] have been observed for neonatal complications [Low quality evidence]. The study found that pregnant women receiving IV iron were significantly less likely to experience adverse events as compared with those receiving oral iron [OR 0.39;  (95% CI 0.26-0.60)]; 34 studies; 13,909 women; [Low quality evidence]. Findings from meta-regression analysis showed that IV iron is more likely to reduce maternal complications by 21% compared to oral iron. Increase in odds of adverse maternal outcomes was observed due to increase in gestational age and publication year but no effect for the type of drug used. IV iron increases Hb more and at a higher pace than oral iron. Intravenous iron is more likely to avert adverse maternal outcomes and adverse reactions. However, there is no conclusive evidence on its effectiveness on individual maternal outcome or neonatal outcome/s. Protocol registered with PROSPERO CRD42022368346).

Extraction vs nonextraction orthodontic treatment: a systematic review and meta-analysis

OBJECTIVES

To compare four first premolar extraction and nonextraction treatment effects on intra-arch width, profile, treatment duration, occlusal outcomes, smile aesthetics and stability.

MATERIALS AND METHODS

An electronic search of the literature to June 2, 2023 was conducted using health science databases, with additional search of gray literature, unpublished material, and hand searching, for studies reporting nonsurgical patients with fixed appliances regarding sixteen sub-outcomes. Data extraction used customized forms, quality assessed with ROBINS-I (Risk Of Bias In Non-randomized Studies-of Interventions) and Cochrane RoB 2 (risk-of-bias) tool. GRADE (Grading of Recommendations Assessment, Development and Evaluation) assessed certainty of evidence.

RESULTS

Thirty (29 retrospective studies, 1 randomized controlled trial) studies were included. Random-effect meta-analysis (95% CI) demonstrated maxillary (MD: -2.03 mm; [-2.97, -1.09]; P < .0001) and mandibular inter-first molar width decrease (MD: -2.00 mm; [-2.71, -1.30]; P < .00001) with four first premolar extraction; mandibular intercanine width increase (MD: 0.68 mm; [0.36, 0.99]; P < .0001) and shorter treatment duration (MD: 0.36 years; [0.10, 0.62]; P = .007) in the nonextraction group. Narrative synthesis included three and five studies for upper and lower lip-E plane, respectively. For American Board of Orthodontics Objective Grading System and maxillary/mandibular anterior alignment (Little's irregularity index), each included two studies with inconclusive evidence. There were no eligible studies for UK Peer Assessment Rating (PAR) score. Class I subgroup/sensitivity analyses favored the same results. Prediction interval indicated no significant difference for all outcomes.

CONCLUSIONS

Four first premolar extraction results in maxillary and mandibular inter-first molar width decrease and retraction of upper/lower lips. Nonextraction treatment results in mandibular intercanine width increase and shorter treatment duration. There was no significant difference between the two groups regarding maxillary intercanine width, US PAR score, and posttreatment smile esthetics. Further high-quality focused research is recommended.

Bayesian hierarchical model for dose-finding trial incorporating historical data

The Multiple Comparison Procedure and Modelling (MCPMod) approach has been shown to be a powerful statistical technique that can significantly improve the design and analysis of dose-finding studies under model uncertainty. Due to its frequentist nature, however, it is difficult to incorporate information into MCPMod from historical trials on the same drug. BMCPMod, a recently introduced Bayesian version of MCPMod, is designed to take into account historical information on the placebo dose group. We introduce a Bayesian hierarchical framework capable of incorporating historical information on an arbitrary number of dose groups, including both placebo and active ones, taking into account the relationship between responses of these dose groups. Our approach can also model both prognostic and predictive between-trial heterogeneity and is particularly useful in situations where the effect sizes of two trials are different. Our goal is to reduce the necessary sample size in the dose-finding trial while maintaining its target power.

Comparison of statistical methods for integrating real-world evidence in a rare events meta-analysis of randomized controlled trials

Rare events meta-analyses of randomized controlled trials (RCTs) are often underpowered because the outcomes are infrequent. Real-world evidence (RWE) from non-randomized studies may provide valuable complementary evidence about the effects of rare events, and there is growing interest in including such evidence in the decision-making process. Several methods for combining RCTs and RWE studies have been proposed, but the comparative performance of these methods is not well understood. We describe a simulation study that aims to evaluate an array of alternative Bayesian methods for including RWE in rare events meta-analysis of RCTs: the naïve data synthesis, the design-adjusted synthesis, the use of RWE as prior information, the three-level hierarchical models, and the bias-corrected meta-analysis model. The percentage bias, root-mean-square-error, mean 95% credible interval width, coverage probability, and power are used to measure performance. The various methods are illustrated using a systematic review to evaluate the risk of diabetic ketoacidosis among patients using sodium/glucose co-transporter 2 inhibitors as compared with active-comparators. Our simulations show that the bias-corrected meta-analysis model is comparable to or better than the other methods in terms of all evaluated performance measures and simulation scenarios. Our results also demonstrate that data solely from RCTs may not be sufficiently reliable for assessing the effects of rare events. In summary, the inclusion of RWE could increase the certainty and comprehensiveness of the body of evidence of rare events from RCTs, and the bias-corrected meta-analysis model may be preferable.

Summarizing empirical information on between-study heterogeneity for Bayesian random-effects meta-analysis

In Bayesian meta-analysis, the specification of prior probabilities for the between-study heterogeneity is commonly required, and is of particular benefit in situations where only few studies are included. Among the considerations in the set-up of such prior distributions, the consultation of available empirical data on a set of relevant past analyses sometimes plays a role. How exactly to summarize historical data sensibly is not immediately obvious; in particular, the investigation of an empirical collection of heterogeneity estimates will not target the actual problem and will usually only be of limited use. The commonly used normal-normal hierarchical model for random-effects meta-analysis is extended to infer a heterogeneity prior. Using an example data set, we demonstrate how to fit a distribution to empirically observed heterogeneity data from a set of meta-analyses. Considerations also include the choice of a parametric distribution family. Here, we focus on simple and readily applicable approaches to then translate these into (prior) probability distributions.

Effect of intraoperative PEEP with recruitment maneuvers on the occurrence of postoperative pulmonary complications during general anesthesia--protocol for Bayesian analysis of three randomized clinical trials of intraoperative ventilation

Background: Using the frequentist approach, a recent meta-analysis of three randomized clinical trials in patients undergoing intraoperative ventilation during general anesthesia for major surgery failed to show the benefit of ventilation that uses high positive end-expiratory pressure with recruitment maneuvers when compared to ventilation that uses low positive end-expiratory pressure without recruitment maneuvers. Methods: We designed a protocol for a Bayesian analysis using the pooled dataset. The multilevel Bayesian logistic model will use the individual patient data. Prior distributions will be prespecified to represent a varying level of skepticism for the effect estimate. The primary endpoint will be a composite of postoperative pulmonary complications (PPC) within the first seven postoperative days, which reflects the primary endpoint of the original studies. We preset a range of practical equivalence to assess the futility of the intervention with an interval of odds ratio (OR) between 0.9 and 1.1 and assess how much of the 95% of highest density interval (HDI) falls between the region of practical equivalence. Ethics and dissemination: The used data derive from approved studies that were published in recent years. The findings of this current analysis will be reported in a new manuscript, drafted by the writing committee on behalf of the three research groups. All investigators listed in the original trials will serve as collaborative authors.

Risk Factors for Graft Failure After Meniscal Allograft Transplantation: A Systematic Review and Meta-analysis

Background

Graft failure after meniscal allograft transplantation (MAT) may necessitate revision surgery or conversion to arthroplasty. A comprehensive understanding of the risk factors for failure after MAT of the knee may facilitate more informed shared decision-making discussions before surgery and help determine whether MAT should be performed based on patient risk.

Purpose

To perform a systematic review and meta-analysis of risk factors associated with graft failure after MAT of the knee.

Study Design

Systematic review; Level of evidence, 4.

Methods

The PubMed, OVID/Medline, and Cochrane databases were queried in October 2021. Data pertaining to study characteristics and risk factors associated with failure after MAT were recorded. DerSimonian-Laird binary random-effects models were constructed to quantitatively evaluate the association between risk factors and MAT graft failure by generating effect estimates in the form of odds ratios (ORs) with 95% CIs. Qualitative analysis was performed to describe risk factors that were variably reported.

Results

In total, 17 studies including 2184 patients were included. The overall pooled prevalence of failure at the latest follow-up was 17.8% (range, 3.3%-81.0%). In 10 studies reporting 5-year failure rates, the pooled prevalence of failure was 10.9% (range, 4.7%-23%). In 4 studies reporting 10-year failure rates, the pooled prevalence was 22.7% (range, 8.1%-55.0%). A total of 39 risk factors were identified, although raw data presented in a manner amenable to meta-analysis only allowed for 3 to be explored quantitatively. There was strong evidence to support that an International Cartilage Regeneration & Joint Preservation Society grade >3a (OR, 5.32; 95% CI, 2.75-10.31; P < .001) was a significant risk factor for failure after MAT. There was no statistically significant evidence to incontrovertibly support that patient sex (OR, 2.16; 95% CI, 0.83-5.64; P = .12) or MAT laterality (OR, 1.11; 95% CI, 0.38-3.28; P = .85) was associated with increased risk of failure after MAT.

Conclusion

Based on the studies reviewed, there was strong evidence to suggest that degree of cartilage damage at the time of MAT is associated with graft failure; however, the evidence was inconclusive on whether laterality or patient sex is associated with graft failure.

Vitamin D status and risk of rheumatoid arthritis: systematic review and meta-analysis

BACKGROUND

Vitamin D is important for immunomodulation and may play a role in autoimmune diseases. Studies have reported a high prevalence of vitamin D deficiency in rheumatoid arthritis (RA) patients, and vitamin D status, assessed by circulating 25-hydroxyvitamin D [25(OH)D] concentration, is inversely associated with RA disease activity. However, it is unclear whether vitamin D deficiency increases the risk of later developing RA. We conducted a systematic review and meta-analysis of pre-diagnostic 25(OH)D concentrations and risk of RA.

METHODS

Medline and Embase databases were searched in December 2021 using various keywords for 'vitamin D', 'rheumatoid arthritis', and 'prospective study'. Publications identified from the search were screened for eligibility, studies were excluded if vitamin D status was measured at or after RA diagnosis, and data were extracted from relevant articles. Bayesian meta-analysis was used to estimate the summary relative risk (RR) and 95% credible interval (CrI) for risk of RA in relation to circulating 25(OH)D concentrations, as well as the between-study heterogeneity.

RESULTS

The search strategy yielded 908 records, of which 4 publications reporting on 7 studies, involving a total of 15,604 participants and 1049 incident RA cases, were included in the meta-analysis. There was no suggestion of an association between 25(OH)D concentration and subsequent risk of RA. The pooled RR per 25 nmol/L increment in 25(OH)D was 0.96 (95% CrI 0.82-1.13; I² = 52%). No associations were evident in men (RR = 1.02, 95% CrI 0.65-1.61; I² = 77%, 2 studies) or women (RR = 0.94, 95% CrI 0.73-1.22; I² = 71%, 4 studies).

CONCLUSIONS

This systematic review and meta-analysis did not identify evidence of an association between 25(OH)D and RA risk, but there was notable between-study heterogeneity and a lack of precision. Investigations in large-scale prospective studies with long follow-up or suitably designed Mendelian randomisation studies with consideration of potential non-linear relationships are needed to determine whether vitamin D is involved in RA aetiology.

Random-effects meta-analysis models for the odds ratio in the case of rare events under different data-generating models: A simulation study

Meta-analysis of binary data is challenging when the event under investigation is rare, and standard models for random-effects meta-analysis perform poorly in such settings. In this simulation study, we investigate the performance of different random-effects meta-analysis models in terms of point and interval estimation of the pooled log odds ratio in rare events meta-analysis. First and foremost, we evaluate the performance of a hypergeometric-normal model from the family of generalized linear mixed models (GLMMs), which has been recommended, but has not yet been thoroughly investigated for rare events meta-analysis. Performance of this model is compared to performance of the beta-binomial model, which yielded favorable results in previous simulation studies, and to the performance of models that are frequently used in rare events meta-analysis, such as the inverse variance model and the Mantel-Haenszel method. In addition to considering a large number of simulation parameters inspired by real-world data settings, we study the comparative performance of the meta-analytic models under two different data-generating models (DGMs) that have been used in past simulation studies. The results of this study show that the hypergeometric-normal GLMM is useful for meta-analysis of rare events when moderate to large heterogeneity is present. In addition, our study reveals important insights with regard to the performance of the beta-binomial model under different DGMs from the binomial-normal family. In particular, we demonstrate that although misalignment of the beta-binomial model with the DGM affects its performance, it shows more robustness to the DGM than its competitors.

Depth of anaesthesia and mortality after cardiac or noncardiac surgery: a systematic review and meta-analysis of randomised controlled trials

BACKGROUND

Recent randomised controlled trials have failed to show a benefit in mortality by using processed electroencephalography (pEEG) to guide lighter anaesthesia. We performed a meta-analysis of mortality data from randomised trials of pEEG monitoring to assess the evidence of any protective effect of pEEG-guided light anaesthesia compared with deep anaesthesia in adults aged ≥18 yr.

METHODS

Our study followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. In February 2022, we searched three databases (Cochrane CENTRAL, OVID Medline, EMBASE) for RCTs of pEEG monitoring that provided mortality data at 30 days, 90 days, and/or 1 yr or longer.

RESULTS

We included 16 articles from 12 RCTs with 48 827 total participants. We observed no statistically significant mortality reduction with light anaesthesia compared with deep anaesthesia in patients aged ≥18 yr when all studies were pooled (odds ratio [OR]=0.99; 95% confidence interval (CI), 0.92-1.08). This result did not change significantly when analysing mortality at 30 days, 90 days, 1 yr or longer. We observed no mortality benefit for pEEG monitoring compared with usual care (OR=1.02; 95% CI, 0.89-1.18), targeting higher pEEG index values compared with lower values (OR=0.89; 95% CI, 0.60-1.32), or low pEEG index value alerts compared with no alerts (OR=1.02; 95% CI, 0.41-2.52).

CONCLUSIONS

pEEG-guided lighter anaesthesia does not appear to reduce the risk of postoperative mortality. The absence of a plausible rationale for why deeper anaesthesia should increase mortality has hampered appropriate design of definitive clinical trials.

CLINICAL TRIAL REGISTRATION

CRD42022285195 (PROSPERO).

Efficacy and safety associated with immune checkpoint inhibitors in unresectable hepatocellular carcinoma: A re-analysis of a meta-analysis

We identified analytic limitations in a recent meta-analysis and re-examined the efficacy and safety associated with immune checkpoint inhibitors (ICIs) in unresectable hepatocellular carcinoma (HCC) compared with standard therapies. Our findings mostly contradict conclusions from the previous study, suggesting the need for continuing the investigation of ICIs in HCC with additional clinical evidence.

Should the two-trial paradigm still be the gold standard in drug assessment?

Two significant pivotal trials are usually required for a new drug approval by a regulatory agency. This standard requirement is known as the two-trial paradigm. However, several authors have questioned why we need exactly two pivotal trials, what statistical error the regulators are trying to protect against, and potential alternative approaches. Therefore, it is important to investigate these questions to better understand the regulatory decision-making in the assessment of drugs' effectiveness. It is common that two identically designed trials are run solely to adhere to the two-trial rule. Previous work showed that combining the data from the two trials into a single trial (one-trial paradigm) would increase the power while ensuring the same level of type I error protection as the two-trial paradigm. However, this is true only under a specific scenario and there is little investigation on the type I error protection over the whole null region. In this article, we compare the two paradigms by considering scenarios in which the two trials are conducted in identical or different populations as well as with equal or unequal size. With identical populations, the results show that a single trial provides better type I error protection and higher power. Conversely, with different populations, although the one-trial rule is more powerful in some cases, it does not always protect against the type I error. Hence, there is the need for appropriate flexibility around the two-trial paradigm and the appropriate approach should be chosen based on the questions we are interested in.

Association of Vitamin D Polygenic Risk Scores and Disease Outcome in People With Multiple Sclerosis

Background and Objectives

Observational studies suggest low levels of 25-hydroxyvitamin D (25[OH]D) may be associated with increased disease activity in people with multiple sclerosis (PwMS). Large-scale genome-wide association studies (GWAS) suggest 25(OH)D levels are partly genetically determined. The resultant polygenic scores (PGSs) could serve as a proxy for 25(OH)D levels, minimizing potential confounding and reverse causation in analyses with outcomes. Herein, we assess the association of genetically determined 25(OH)D and disease outcomes in MS.

Methods

We generated 25(OH)D PGS for 1,924 PwMS with available genotyping data pooled from 3 studies: the CombiRx trial (n = 575), Johns Hopkins MS Center (n = 1,152), and Immune-Mediated Inflammatory Diseases study (n = 197). 25(OH)D-PGS were derived using summary statistics (p < 5 × 10−8) from a large GWAS including 485,762 individuals with circulating 25(OH)D levels measured. We included clinical and imaging outcomes: Expanded disability status scale (EDSS), timed 25-foot walk (T25FW), nine-hole peg test (9HPT), radiologic activity, and optical coherence tomography-derived ganglion cell inner plexiform layer (GCIPL) thickness. A subset (n = 935) had measured circulating 25(OH)D levels. We fitted multivariable models based on the outcome of interest and pooled results across studies using random effects meta-analysis. Sensitivity analyses included a modifiedpvalue threshold for inclusion in the PGS (5 × 10−5) and applying Mendelian randomization (MR) rather than using PGS.

Results

Initial analyses demonstrated a positive association between generated 25(OH)D-PGS and circulating 25(OH)D levels (per 1SD increase in 25[OH]D PGS: 3.08%, 95% CI: 1.77%, 4.42%;p= 4.33e-06; R2= 2.24%). In analyses with outcomes, we did not observe an association between 25(OH)D-PGS and relapse rate (per 1SD increase in 25[OH]D-PGS: 0.98; 95% CI: 0.87–1.10), EDSS worsening (per 1SD: 1.05; 95% CI: 0.87–1.28), change in T25FW (per 1SD: 0.07%; 95% CI: −0.34 to 0.49), or change in 9HPT (per 1SD: 0.09%; 95% CI: −0.15 to 0.33). 25(OH)D-PGS was not associated with new lesion accrual, lesion volume or other imaging-based outcomes (whole brain, gray, white matter volume loss or GCIPL thinning). The results were similarly null in analyses using otherpvalue thresholds or those applying MR.

Discussion

Genetically determined lower 25(OH)D levels were not associated with worse disease outcomes in PwMS and raises questions about the plausibility of a treatment effect of vitamin D in established MS.

The effectiveness of compassion-based interventions among cancer patients: A systematic review and meta-analysis

Objectives

This study examined the effects of compassion-based intervention on mental health in cancer patients by using systematic review and meta-analysis of randomized controlled trials (RCTs).

Methods

Eleven bibliographic databases were searched from their earliest data available date up to March 1, 2022. The databases were PubMed, CINAHL, MEDLINE, PsycINFO, WOS, Cochrane, Embase, Scopus, ProQuest Dissertations, Airiti Library, and the National Digital Library of Theses and Dissertations in Taiwan.

Results

Ten studies from 2015 to 2021 were included with a total of 771 cancer patients. Most were targeted at women with breast cancer. Brief compassion-based interventions of approximately 30 minutes were conducted by audio file, paper, and web-based self-guided writing prompts. Most were conducted after the completion of active treatment. Anxiety was the most measured outcome. Constructive compassion-based interventions with 4- to 12-week sessions were conducted by a trained facilitator. Most were conducted for patients who had undergone treatment, and depression was the most measured outcome. The meta-analysis indicated that compassion-based interventions had a significant effect of reducing depression and increasing self-compassion. Moderation analysis indicated that constructive intervention showed more benefits of increased self-compassion than brief intervention. Both face-to-face and non-face-to-face web-delivered formats had benefits for increasing self-compassion compared with the control condition.

Significance of results

Compassion-based interventions might provide an effective strategy for improving self-compassion and depression among patients with breast cancer. Suggestions for further research and health-care providers follow.

Primary surgery versus primary rehabilitation for treating anterior cruciate ligament injuries: a living systematic review and meta-analysis

OBJECTIVE

Compare the effectiveness of primarily surgical versus primarily rehabilitative management for anterior cruciate ligament (ACL) rupture.

DESIGN

Living systematic review and meta-analysis.

DATA SOURCES

Six databases, six trial registries and prior systematic reviews. Forward and backward citation tracking was employed.

ELIGIBILITY CRITERIA

Randomised controlled trials that compared primary reconstructive surgery and primary rehabilitative treatment with or without optional reconstructive surgery.

DATA SYNTHESIS

Bayesian random effects meta-analysis with empirical priors for the OR and standardised mean difference and 95% credible intervals (CrI), Cochrane RoB2, and the Grading of Recommendations Assessment, Development and Evaluation approach to judge the certainty of evidence.

RESULTS

Of 9514 records, 9 reports of three studies (320 participants in total) were included. No clinically important differences were observed at any follow-up for self-reported knee function (low to very low certainty of evidence). For radiological knee osteoarthritis, we found no effect at very low certainty of evidence in the long term (OR (95% CrI): 1.45 (0.30 to 5.17), two studies). Meniscal damage showed no effect at low certainty of evidence (OR: 0.85 (95% CI 0.45 to 1.62); one study) in the long term. No differences were observed between treatments for any other secondary outcome. Three ongoing randomised controlled trials were identified.

CONCLUSIONS

There is low to very low certainty of evidence that primary rehabilitation with optional surgical reconstruction results in similar outcome measures as early surgical reconstruction for ACL rupture. The findings challenge a historical paradigm that anatomic instability should be addressed with primary surgical stabilisation to provide optimal outcomes.

PROSPERO REGISTRATION NUMBER

CRD42021256537.

Bayesian heterogeneity in a meta-analysis with two studies and binary data

The meta-analysis of two trials is valuable in many practical situations, such as studies of rare and/or orphan diseases focussed on a single intervention. In this context, additional concerns, like small sample size and/or heterogeneity in the results obtained, might make standard frequentist and Bayesian techniques inappropriate. In a meta-analysis, moreover, the presence of between-sample heterogeneity adds model uncertainty, which must be taken into consideration when drawing inferences. We suggest that the most appropriate way to measure this heterogeneity is by clustering the samples and then determining the posterior probability of the cluster models. The meta-inference is obtained as a mixture of all the meta-inferences for the cluster models, where the mixing distribution is the posterior model probability. We present a simple two-component form of Bayesian model averaging that is unaffected by characteristics such as small study size or zero-cell counts, and which is capable of incorporating uncertainties into the estimation process. Illustrative examples are given and analysed, using real sparse binomial data.

A straightforward meta-analysis approach for oncology phase I dose-finding studies

Phase I early-phase clinical studies aim at investigating the safety and the underlying dose-toxicity relationship of a drug or combination. While little may still be known about the compound's properties, it is crucial to consider quantitative information available from any studies that may have been conducted previously on the same drug. A meta-analytic approach has the advantages of being able to properly account for between-study heterogeneity, and it may be readily extended to prediction or shrinkage applications. Here we propose a simple and robust two-stage approach for the estimation of maximum tolerated dose(s) utilizing penalized logistic regression and Bayesian random-effects meta-analysis methodology. Implementation is facilitated using standard R packages. The properties of the proposed methods are investigated in Monte Carlo simulations. The investigations are motivated and illustrated by two examples from oncology.

A comparison of methods for enriching network meta-analyses in the absence of individual patient data

During drug development, a biomarker is sometimes identified as separating a patient population into those with more and those with less benefit from evaluated treatments. Consequently, later studies might be targeted, while earlier ones are performed in mixed patient populations. This poses a challenge in evidence synthesis, especially if only aggregated data are available. Starting from this scenario, we investigate three commonly used network meta-analytic estimation methods, the naive estimation approach, the stand-alone analysis, and the network meta-regression. Additionally, we adapt and modify two methods which are used in evidence synthesis to combine randomized controlled trials with observational studies, the enrichment-through-weighting approach and the informative prior estimation. We evaluate all five methods in a simulation study with 32 scenarios using bias, RMSE, coverage, precision, and power. Additionally, we re-visit a clinical data set to exemplify and discuss the application. In the simulation study, none of the methods was observed to be clearly favorable over all investigated scenarios. However, the stand-alone analysis and the naive estimation performed comparably or worse than the other methods in all evaluated performance measures and simulation scenarios and are therefore not recommended. While substantial between-trial heterogeneity is challenging for all estimation approaches, the performance of the network meta-regression, the enriching-through weighting approach and the informative prior approach was dependent on the simulation scenario and the performance measure of interest. Furthermore, as these estimation methods are drawing slightly different assumptions, some of which require the presence of additional information for estimation, we recommend sensitivity-analyses wherever possible. This article is protected by copyright. All rights reserved.

Comparison of Socioeconomic Disparities in Pump Uptake Among Children With Type 1 Diabetes in 2 Canadian Provinces With Different Payment Models

IMPORTANCE

Insulin pumps improve glycemic control and quality of life in children with type 1 diabetes (T1D). Canada's provinces have implemented universal pediatric programs to improve access. However, these programs provide differing financial coverage, allowing for unique cross-jurisdictional comparisons.

OBJECTIVE

To evaluate possible socioeconomic status (SES) disparities in pump uptake in Québec, where pumps are fully funded, with those in Manitoba, where pumps are partially funded.

DESIGN, SETTING, AND PARTICIPANTS

Using health administrative databases and a clinical registry, parallel, population-based cohort studies of children with diabetes were conducted from April 1, 2011, in Québec, and April 1, 2012, in Manitoba, until March 31, 2017. In analysis conducted from July 1, 2019, to November 30, 2021, multivariable Cox proportional hazards regression models were applied to study the association between pump uptake and SES, defined using validated area-based material and social deprivation indices. Children aged 1 to 17 years with T1D were identified using a validated definition in administrative data (Québec) and a clinical registry (Manitoba). Those using pumps before the initiation of provincial programs were excluded.

EXPOSURES

Socioeconomic status.

MAIN OUTCOMES AND MEASURES

Insulin pump uptake.

RESULTS

A total of 2919 children with T1D were identified in Québec: 1550 male (53.1%), mean (SD) age at diagnosis, 8.3 (4.4) years, and 1067 (36.6%) were using a pump. In Manitoba, 636 children were identified: 364 male (57.2%), mean (SD) age at diagnosis, 8.8 (4.4) years, and 106 (16.7%) were using a pump. In Québec, the mean age at diagnosis of T1D was lower in children using the pump compared with those not using a pump (7.6 [4.1] vs 8.7 [4.5] years); sex distribution was similar (562 [52.7%] vs 988 [53.3%] male). No differences in mean (SD) age at diagnosis (8.8 [4.4] vs 8.8 [4.3] years) or sex (57 [53.8%] vs 307 [57.9%] male) were noted in both groups in Manitoba. Increasing material deprivation was associated with decreased pump uptake in both Québec (adjusted hazard ratio [aHR] 0.89; 95% CI, 0.85-0.93) and Manitoba (aHR, 0.70; 95% CI, 0.60-0.82). Inclusion of ethnic concentration did not change this association. Socioeconomic disparities in pump uptake were greater in Manitoba than Québec (P = .006 by t test; Cochran Q, 8.15; P = .004; I2 = 87.7%; 95% CI, 52.5%-96.8%).

CONCLUSIONS AND RELEVANCE

The results of this study suggest that the program of full coverage for pumps available in Québec partially mitigates observed SES disparities in uptake and may be a model to improve access for all children with T1D.

Risk Factors for Failure After Osteochondral Allograft Transplantation of the Knee: A Systematic Review and Exploratory Meta-analysis

BACKGROUND

Graft failure after osteochondral allograft transplantation (OCA) of the knee is a devastating outcome, often necessitating subsequent interventions. A comprehensive understanding of the risk factors for failure after OCA of the knee may provide enhanced prognostic data for the knee surgeon and facilitate more informed shared decision-making discussions before surgery.

PURPOSE

To perform a systematic review and meta-analysis of risk factors associated with graft failure after OCA of the knee.

STUDY DESIGN

Systematic review and meta-analysis; Level of evidence, 4.

METHODS

The PubMed, Ovid/MEDLINE, and Cochrane databases were queried in April 2021. Data pertaining to study characteristics and risk factors associated with failure after OCA were recorded. DerSimonian-Laird binary random-effects models were constructed to quantitatively evaluate the association between risk factors and graft failure by generating effect estimates in the form of odds ratios (ORs) with 95% CIs, while mean differences (MDs) were calculated for continuous data. Qualitative analysis was performed to describe risk factors that were variably reported.

RESULTS

A total of 16 studies consisting of 1401 patients were included. The overall pooled prevalence of failure was 18.9% (range, 10%-46%). There were 44 risk factors identified, of which 9 were explored quantitatively. There was strong evidence to support that the presence of bipolar chondral defects (OR, 4.20 [95% CI, 1.17-15.08]; P = .028) and male sex (OR, 2.04 [95% CI, 1.17-3.55]; P = .012) were significant risk factors for failure after OCA. Older age (MD, 5.06 years [95% CI, 1.44-8.70]; P = .006) and greater body mass index (MD, 1.75 kg/m² [95% CI, 0.48-3.03]; P = .007) at the time of surgery were also significant risk factors for failure after OCA. There was no statistically significant evidence to incontrovertibly support that concomitant procedures, chondral defect size, and defect location were associated with an increased risk of failure after OCA.

CONCLUSION

Bipolar chondral defects, male sex, older age, and greater body mass index were significantly associated with an increased failure rate after OCA of the knee. No statistically significant evidence presently exists to support that chondral defect size and location or concomitant procedures are associated with an increased graft failure rate after OCA of the knee. Additional studies are needed to evaluate these associations.

Performing Meta-analyses with Very Few Studies

This chapter contains a methodological framework for choosing a model for the meta-analysis of very few studies and selecting an estimation method for the chosen model by means of study characteristics and by comparing results yielded by different approaches. When the results are inconclusive between different estimation methods, it might be the best solution to refrain from a quantitative meta-analysis but to summarize the study results by means of a qualitative evidence synthesis.

Risk Factors for Ramp Lesions of the Medial Meniscus: A Systematic Review and Meta-analysis

BACKGROUND

Failure to appropriately identify and repair medial meniscal ramp lesions at the time of anterior cruciate ligament (ACL) reconstruction (ACLR) may result in increased anterior tibial translation and internal rotation, increasing the risk for graft failure. Knowledge of the risk factors leading to the development of ramp lesions may enhance clinicians' vigilance in specific ACL-deficient populations and subsequently repair of these lesions at the time of ACLR.

PURPOSE

To perform a systematic review and meta-analysis of factors tested for associations with ramp lesions and to determine which were significantly associated with the presence of ramp lesions.

STUDY DESIGN

Systematic review and meta-analysis; Level of evidence, 4.

METHODS

PubMed, OVID/Medline, and Cochrane databases were queried in April 2020. Data pertaining to study characteristics and reported risk factors for ramp lesions were recorded. DerSimonian-Laird binary random-effects models were constructed to quantitatively evaluate the association between risk factors and ramp lesions by generating effect estimates in the form of odds ratios (ORs) with 95% CIs. Qualitative analysis was performed to describe risk factors that were variably reported.

RESULTS

The review included 12 studies with 8410 patients. The overall pooled prevalence of ramp lesions was 21.9% (range, 9.0%-41.7%). A total of 45 risk factors were identified, of which 8 were explored quantitatively. There was strong evidence to support that posteromedial tibial edema on magnetic resonance imaging (MRI) (OR, 2.12; 95% CI, 1.27-3.56; P = .004), age <30 years (OR, 2.02; 95% CI, 1.23-3.22; P = .002), and complete ACL tears (OR, 3.0; 95% CI, 1.41-6.20; P = .004) were risk factors for ramp lesions. There was moderate evidence to support that male sex (OR, 1.58; 95% CI, 1.36-1.83; P < .001) and concomitant lateral meniscal tears (OR, 1.54; 95% CI, 1.11-2.13; P = .009) were risk factors for ramp lesions. Chronic ACL injury (≥24 months) demonstrated minimal evidence as a risk factor (OR, 1.41; 95% CI, 1.14-1.74; P = .001). No significant associations were determined between contact injury or revision ACLR and the presence of ramp lesions.

CONCLUSION

Significant associations between male sex, age <30 years, posteromedial tibial edema on MRI, concomitant lateral meniscal tears, complete ACL tears, injury chronicity, and the presence of ramp lesions were found. Contact injury and revision ACLR were not significantly associated with the presence of ramp lesions.

Investigating the association of CD36 gene polymorphisms (rs1761667 and rs1527483) with T2DM and dyslipidemia: Statistical analysis, machine learning based prediction, and meta-analysis

CD36 (cluster of differentiation 36) is a membrane protein involved in lipid metabolism and has been linked to pathological conditions associated with metabolic disorders, such as diabetes and dyslipidemia. A case-control study was conducted and included 177 patients with type-2 diabetes mellitus (T2DM) and 173 control subjects to study the involvement of CD36 gene rs1761667 (G>A) and rs1527483 (C>T) polymorphisms in the pathogenesis of T2DM and dyslipidemia among Jordanian population. Lipid profile, blood sugar, gender and age were measured and recorded. Also, genotyping analysis for both polymorphisms was performed. Following statistical analysis, 10 different neural networks and machine learning (ML) tools were used to predict subjects with diabetes or dyslipidemia. Towards further understanding of the role of CD36 protein and gene in T2DM and dyslipidemia, a protein-protein interaction network and meta-analysis were carried out. For both polymorphisms, the genotypic frequencies were not significantly different between the two groups (p > 0.05). On the other hand, some ML tools like multilayer perceptron gave high prediction accuracy (≥ 0.75) and Cohen's kappa (κ) (≥ 0.5). Interestingly, in K-star tool, the accuracy and Cohen's κ values were enhanced by including the genotyping results as inputs (0.73 and 0.46, respectively, compared to 0.67 and 0.34 without including them). This study confirmed, for the first time, that there is no association between CD36 polymorphisms and T2DM or dyslipidemia among Jordanian population. Prediction of T2DM and dyslipidemia, using these extensive ML tools and based on such input data, is a promising approach for developing diagnostic and prognostic prediction models for a wide spectrum of diseases, especially based on large medical databases.

Sac transection versus sac reduction during laparoscopic herniorrhaphy: A systematic review and meta-analysis

Hernia repair techniques have evolved recently; however sac handling remains a critical step. Transection of the herniated sac as opposed to total sac reduction may simplify the procedure. However, residual sac tissue may increase the risk for seroma formation. We performed a systemic review and meta-analysis to evaluate the safety and feasibility of transecting the hernia sac during laparoscopic herniorrhaphy. Relevant literature search was performed in PubMed, EMBASE, SCORPUS, and the Cochrane Library databases. Relevant studies that compared total reduction with transection of the herniated sac during laparoscopic herniorrhaphy were included. The primary outcome measure was the incidence of seromas. We also analyzed secondary outcomes including operative duration, postoperative pain scores, complications, and hernia recurrence rate. Of the 330 studies identified, four studies published between 2002 and 2020, with sample sizes ranging from 70 to 520 patients, met the inclusion criteria. Overall, 848 hernias were evaluated. We observed a high incidence of seroma formation in the sac transection group compared to that in the sac reduction group (OR 2.41; 95% CI 1.39 to 4.17, P = 0.002), but the groups did not differ significantly with respect to factor such as operative duration, postoperative complications, and pain score. Herniated sac transection during laparoscopic herniorrhaphy might be associated with a higher risk of seroma formation than that observed with sac reduction. The former approach did not show any significant benefits compared to the latter approach with respect to operative duration and postoperative complications.

Sensitivity and identification quantification by a relative latent model complexity perturbation in Bayesian meta-analysis

In recent years, Bayesian meta‐analysis expressed by a normal–normal hierarchical model (NNHM) has been widely used for combining evidence from multiple studies. Data provided for the NNHM are frequently based on a small number of studies and on uncertain within‐study standard deviation values. Despite the widespread use of Bayesian NNHM, it has always been unclear to what extent the posterior inference is impacted by the heterogeneity prior (sensitivity S) and by the uncertainty in the within‐study standard deviation values (identification I). Thus, to answer this question, we developed a unified method to simultaneously quantify both sensitivity and identification (S‐I) for all model parameters in a Bayesian NNHM, based on derivatives of the Bhattacharyya coefficient with respect to relative latent model complexity (RLMC) perturbations. Three case studies exemplify the applicability of the method proposed: historical data for a conventional therapy, data from which one large study is first included and then excluded, and two subgroup meta‐analyses specified by their randomization status. We analyzed six scenarios, crossing three RLMC targets with two heterogeneity priors (half‐normal, half‐Cauchy). The results show that S‐I explicitly reveals which parameters are affected by the heterogeneity prior and by the uncertainty in the within‐study standard deviation values. In addition, we compare the impact of both heterogeneity priors and quantify how S‐I values are affected by omitting one large study and by the randomization status. Finally, the range of applicability of S‐I is extended to Bayesian NtHM. A dedicated R package facilitates automatic S‐I quantification in applied Bayesian meta‐analyses.

Surgical and laser interventions for pseudoexfoliation glaucoma systematic review of randomized controlled trials

To assess the comparative effectiveness and safety of different surgical and laser techniques in people with pseudoexfoliation glaucoma (PXFG). We conducted a systematic review including randomized controlled trials (RCT) that compared any pair of surgical or laser treatment versus other type of intervention in PXFG. RCT were identified by a highly sensitive search of electronic databases and two individuals independently assessed trial eligibility, abstracted data and assessed risk of bias. We performed Bayesian Meta-Analysis when outcomes were comparable. The search strategy identified 6171 records. Six studies (262 subjects) were included. Two trials analyzed the same pair of surgical interventions comparing phacoemulsification as solo procedure or combined with trabecular aspiration and we performed meta-analysis. Other RCTs compared the following interventions: trabecular aspiration associated with phacoemulsification versus phacotrabeculectomy, non-penetrating deep sclerectomy associated or not with phacoemulsification, selective versus argon laser trabeculoplasty and one-site versus two-site phacotrabeculectomy. For IOP data, none of the trials reported a difference between pairs of surgical techniques, nor changes in visual acuity or number of post-operative medications. The overall risk of bias is moderate to high. There are no apparent differences in efficacy and safety, although with large uncertainty, between surgical or laser techniques for PXFG. Based on the low-quality evidence from the six studies included in this review, it is not possible to justify the preferential use of non-penetrating surgery, MIGS or trabecular aspiration (with or without cataract surgery) in PXFG. Further research is needed to determine the optimal management of this condition.

How vague is vague? How informative is informative? Reference analysis for Bayesian meta-analysis

Meta-analysis provides important insights for evidence-based medicine by synthesizing evidence from multiple studies which address the same research question. Within the Bayesian framework, meta-analysis is frequently expressed by a Bayesian normal-normal hierarchical model (NNHM). Recently, several publications have discussed the choice of the prior distribution for the between-study heterogeneity in the Bayesian NNHM and used several "vague" priors. However, no approach exists to quantify the informativeness of such priors, and thus, we develop a principled reference analysis framework for the Bayesian NNHM acting at the posterior level. The posterior reference analysis (post-RA) is based on two posterior benchmarks: one induced by the improper reference prior, which is minimally informative for the data, and the other induced by a highly anticonservative proper prior. This approach applies the Hellinger distance to quantify the informativeness of a heterogeneity prior of interest by comparing the corresponding marginal posteriors with both posterior benchmarks. The post-RA is implemented in the freely accessible R package ra4bayesmeta and is applied to two medical case studies. Our findings show that anticonservative heterogeneity priors produce platykurtic posteriors compared with the reference posterior, and they produce shorter 95% credible intervals (CrI) and optimistic inference compared with the reference prior. Conservative heterogeneity priors produce leptokurtic posteriors, longer 95% CrI and cautious inference. The novel post-RA framework could support numerous Bayesian meta-analyses in many research fields, as it determines how informative a heterogeneity prior is for the actual data as compared with the minimally informative reference prior.

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.

Bounds for the weight of external data in shrinkage estimation

Shrinkage estimation in a meta-analysis framework may be used to facilitate dynamical borrowing of information. This framework might be used to analyze a new study in the light of previous data, which might differ in their design (e.g., a randomized controlled trial and a clinical registry). We show how the common study weights arise in effect and shrinkage estimation, and how these may be generalized to the case of Bayesian meta-analysis. Next we develop simple ways to compute bounds on the weights, so that the contribution of the external evidence may be assessed a priori. These considerations are illustrated and discussed using numerical examples, including applications in the treatment of Creutzfeldt-Jakob disease and in fetal monitoring to prevent the occurrence of metabolic acidosis. The target study's contribution to the resulting estimate is shown to be bounded below. Therefore, concerns of evidence being easily overwhelmed by external data are largely unwarranted.

A confidence interval robust to publication bias for random-effects meta-analysis of few studies

In meta-analyses including only few studies, the estimation of the between-study heterogeneity is challenging. Furthermore, the assessment of publication bias is difficult as standard methods such as visual inspection or formal hypothesis tests in funnel plots do not provide adequate guidance. Previously, Henmi and Copas (Statistics in Medicine 2010, 29: 2969-2983) proposed a confidence interval for the overall effect in random-effects meta-analysis that is robust to publication bias to some extent. As is evident from their simulations, the confidence intervals have improved coverage compared with standard methods. To our knowledge, the properties of their method have never been assessed for meta-analyses including fewer than five studies. In this manuscript, we propose a variation of the method by Henmi and Copas employing an improved estimator of the between-study heterogeneity, in particular when dealing with few studies only. In a simulation study, the proposed method is compared to several competitors. Overall, we found that our method outperforms the others in terms of coverage probabilities.

On weakly informative prior distributions for the heterogeneity parameter in Bayesian random-effects meta-analysis

The normal-normal hierarchical model (NNHM) constitutes a simple and widely used framework for meta-analysis. In the common case of only few studies contributing to the meta-analysis, standard approaches to inference tend to perform poorly, and Bayesian meta-analysis has been suggested as a potential solution. The Bayesian approach, however, requires the sensible specification of prior distributions. While noninformative priors are commonly used for the overall mean effect, the use of weakly informative priors has been suggested for the heterogeneity parameter, in particular in the setting of (very) few studies. To date, however, a consensus on how to generally specify a weakly informative heterogeneity prior is lacking. Here we investigate the problem more closely and provide some guidance on prior specification.

Bayesian Approaches for Confirmatory Trials in Rare Diseases: Opportunities and Challenges

The aim of this narrative review is to introduce the reader to Bayesian methods that, in our opinion, appear to be the most important in the context of rare diseases. A disease is defined as rare depending on the prevalence of the affected patients in the considered population, for example, about 1 in 1500 people in U.S.; about 1 in 2500 people in Japan; and fewer than 1 in 2000 people in Europe. There are between 6000 and 8000 rare diseases and the main issue in drug development is linked to the challenge of achieving robust evidence from clinical trials in small populations. A better use of all available information can help the development process and Bayesian statistics can provide a solid framework at the design stage, during the conduct of the trial, and at the analysis stage. The focus of this manuscript is to provide a review of Bayesian methods for sample size computation or reassessment during phase II or phase III trial, for response adaptive randomization and of for meta-analysis in rare disease. Challenges regarding prior distribution choice, computational burden and dissemination are also discussed.

Interval estimation of the overall treatment effect in random-effects meta-analyses: Recommendations from a simulation study comparing frequentist, Bayesian, and bootstrap methods

There exists a variety of interval estimators for the overall treatment effect in a random-effects meta-analysis. A recent literature review summarizing existing methods suggested that in most situations, the Hartung-Knapp/Sidik-Jonkman (HKSJ) method was preferable. However, a quantitative comparison of those methods in a common simulation study is still lacking. Thus, we conduct such a simulation study for continuous and binary outcomes, focusing on the medical field for application. Based on the literature review and some new theoretical considerations, a practicable number of interval estimators is selected for this comparison: the classical normal-approximation interval using the DerSimonian-Laird heterogeneity estimator, the HKSJ interval using either the Paule-Mandel or the Sidik-Jonkman heterogeneity estimator, the Skovgaard higher-order profile likelihood interval, a parametric bootstrap interval, and a Bayesian interval using different priors. We evaluate the performance measures (coverage and interval length) at specific points in the parameter space, that is, not averaging over a prior distribution. In this sense, our study is conducted from a frequentist point of view. We confirm the main finding of the literature review, the general recommendation of the HKSJ method (here with the Sidik-Jonkman heterogeneity estimator). For meta-analyses including only two studies, the high length of the HKSJ interval limits its practical usage. In this case, the Bayesian interval using a weakly informative prior for the heterogeneity may help. Our recommendations are illustrated using a real-world meta-analysis dealing with the efficacy of an intramyocardial bone marrow stem cell transplantation during coronary artery bypass grafting.

Nutritional interventions for the management of frailty in older adults: systematic review and meta-analysis of randomized clinical trials

CONTEXT

Although nutrition is considered an important intervention for the management of frailty, the actual effectiveness of interventions addressing nutrition in frail older people remains unclear.

OBJECTIVE

The aim for this systematic review was to appraise the evidence regarding the effectiveness of nutritional interventions for the management of frailty in older adults.

DATA EXTRACTION

We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The MEDLINE, Embase, Cumulative Index to Nursing and Allied Health Literature, Cochrane Central Register of Controlled Trials, Web of Science, and Latin American and Caribbean Health Sciences Literature databases were searched from January 2001 to November 2019. Two independent reviewers extracted relevant data. From 2370 initial records, 19 publications presenting data from 17 studies (1564 individuals; follow-up: 7-96 weeks) were included.

DATA ANALYSIS

None of the Bayesian random-effects meta-analyses comparing nutritional supplements with placebo regarding mortality, body mass index, weight, frailty status, muscle strength, gait speed, body composition, and cognitive function showed statistically significant differences. The same applies to a single meta-analysis comparing nutritional education with general health advice regarding muscle strength.

CONCLUSION

Our results suggest, mostly with low to very low degrees of certainty, that nutritional supplements or nutritional education delivered in isolation may not be effective for the management of frailty in older people.

REVIEW REGISTRATION NUMBER

CRD42018111510 (PROSPERO).

Meta-Analysis with Few Studies and Binary Data: A Bayesian Model Averaging Approach

In meta-analysis, the existence of between-sample heterogeneity introduces model uncertainty, which must be incorporated into the inference. We argue that an alternative way to measure this heterogeneity is by clustering the samples and then determining the posterior probability of the cluster models. The meta-inference is obtained as a mixture of all the meta-inferences for the cluster models, where the mixing distribution is the posterior model probabilities. When there are few studies, the number of cluster configurations is manageable, and the meta-inferences can be drawn with BMA techniques. Although this topic has been relatively neglected in the meta-analysis literature, the inference thus obtained accurately reflects the cluster structure of the samples used. In this paper, illustrative examples are given and analysed, using real binary data.

Secondary caries risk of different adhesive strategies and restorative materials in permanent teeth: Systematic review and network meta-analysis

OBJECTIVES

Secondary caries is a major long-term complication of dental restorations. Different adhesive strategies and restorative materials may affect secondary caries risk. We aimed to systematically review and synthesize the secondary caries risk of different adhesive strategies and restorative materials.

SOURCES

Medline via PubMed 01/2005-10/2019.

STUDY SELECTION

Randomized controlled studies with minimum 2 years follow-up, comparing different adhesive strategies and/or restorative materials in permanent teeth were included. Our outcome was the occurrence of secondary caries. Bayesian pairwise and network-meta-analysis were conducted.

DATA

We included 50 trials; 19 assessing secondary caries depending on different adhesive strategies, 31 on restorative materials. Studies were published between 2005 and 2017, largely of unclear risk of bias, and included a mean of 40 (range: 8-90) participants and 46 (range: 14-200) placed restorations. Mean follow-up was 43 (range: 24-180) months. Secondary caries was a rare event; the majority of studies did not find any lesions. Network meta-analysis found great uncertainty. 3-step etch-and-rinse adhesives showed the lowest risk of secondary caries, 2-step etch-and-rinse the highest. For restorative materials, resin-modified glass ionomer showed the lowest risk of secondary caries. Most resin composites showed similar risks.

CONCLUSION

Data from randomized trials comparing different adhesive strategies or restorative materials are extremely scarce. The differences between materials were limited over the observational period of the included studies. The yielded rankings should be interpreted with caution.

CLINICAL SIGNIFICANCE

Despite often claimed to be a major complication of restorations, there is surprisingly little data on secondary caries from randomized trials. Longer-term studies may be needed to identify differences in secondary caries risk between materials.

Zero-cell corrections in random-effects meta-analyses

The standard estimator for the log odds ratio (the unconditional maximum likelihood estimator) and the delta-method estimator for its standard error are not defined if the corresponding 2 × 2 table contains at least one "zero cell". This is also an issue when estimating the overall log odds ratio in a meta-analysis. It is well known that correcting for zero cells by adding a small increment should be avoided. Nevertheless, these zero-cell corrections continue to be used. With this Brief Method Note, we want to warn of a particularly bad zero-cell correction. For this, we conduct a simulation study comparing the following two zero-cell corrections under the ordinary random-effects model: (a) adding 1 2 to all cells of all the individual studies' 2 × 2 tables independently of any zero-cell occurrences and (b) adding 1 2 to all cells of only those 2 × 2 tables containing at least one zero cell. The main finding is that correction (a) performs worse than correction (b). Thus, we strongly discourage the use of correction (a).

Approaches for combining primary care electronic health record data from multiple sources: a systematic review of observational studies

OBJECTIVE

To identify observational studies which used data from more than one primary care electronic health record (EHR) database, and summarise key characteristics including: objective and rationale for using multiple data sources; methods used to manage, analyse and (where applicable) combine data; and approaches used to assess and report heterogeneity between data sources.

DESIGN

A systematic review of published studies.

DATA SOURCES

Pubmed and Embase databases were searched using list of named primary care EHR databases; supplementary hand searches of reference list of studies were retained after initial screening.

STUDY SELECTION

Observational studies published between January 2000 and May 2018 were selected, which included at least two different primary care EHR databases.

RESULTS

6054 studies were identified from database and hand searches, and 109 were included in the final review, the majority published between 2014 and 2018. Included studies used 38 different primary care EHR data sources. Forty-seven studies (44%) were descriptive or methodological. Of 62 analytical studies, 22 (36%) presented separate results from each database, with no attempt to combine them; 29 (48%) combined individual patient data in a one-stage meta-analysis and 21 (34%) combined estimates from each database using two-stage meta-analysis. Discussion and exploration of heterogeneity was inconsistent across studies.

CONCLUSIONS

Comparing patterns and trends in different populations, or in different primary care EHR databases from the same populations, is important and a common objective for multi-database studies. When combining results from several databases using meta-analysis, provision of separate results from each database is helpful for interpretation. We found that these were often missing, particularly for studies using one-stage approaches, which also often lacked details of any statistical adjustment for heterogeneity and/or clustering. For two-stage meta-analysis, a clear rationale should be provided for choice of fixed effect and/or random effects or other models.

Limitations and Challenges of Conducting Budget Impact Analyses in Rare Diseases: A Case Study of Alpha-1 Antitrypsin Deficiency

OBJECTIVES

There are challenges in conducting a budget impact analysis (BIA) for rare disorders. Through this case study, we present some challenges and limitations of a BIA of managing patients affected with alpha-1 antitrypsin deficiency (AATD). We explored a conceptual basis and barriers for health services researchers interested in quantifying budget impacts of rare disease management program (DMP).

METHODS

We developed a static budget impact cost calculator model in Microsoft Excel, obtaining the clinical impact of a DMP from the literature and translating it into costs using OLDW. Cost inputs and resource use was obtained from 2010 to 2015 claims data using the OLDW. Insurers' payments were calculated and categorized into the following cost buckets: physician visits, emergency room visits, inpatients stays, augmentation therapy, other prescription drugs costs, and other costs.

RESULTS

Data were based on 6832 patients with alpha-1 antitrypsin deficiency identified among over 21 million OLDW enrollees observed between January 1, 2010, and December 31, 2015. The introduction of a DMP was estimated to decrease costs of the management of patients with alpha-1 antitrypsin deficiency by $13.5 million over 5 years. The savings attributed to the program over the 5-year time horizon are due to 2555 exacerbations, 5180 emergency room visits, 9342 specialist visits, and 105 358 general practitioner visits avoided.

CONCLUSIONS

A comprehensive DMP for a rare condition might provide cost savings to a health plan. BIAs for rare disease may be more informative if they focus on DMPs rather than on individual drugs.

European perspective of perampanel response in people with Intellectual Disability

BACKGROUND

Epilepsy prevalence is over 20% for those with ID. It is difficult to diagnose and treat and more likely to be treatment resistant. The evidence informing prescribing is sparse, particularly for new drugs such as perampanel (PMP).

AIMS OF THE STUDY

This study seeks to strengthen the research evidence regarding PMP for people with ID by pooling information from two isolated and separately conducted studies: the UK-based Epilepsy Database Register (Ep-ID) and the data from the Kempenhaeghe clinic in the Netherlands.

METHODS

A single data set of comparable data was created and analysed under agreement and supervision of a UK statistician.

RESULTS

Seizure reduction within twelve months was evident in 62% of Dutch and 47% of UK patients. Retention rates were higher for those in the UK (P = .01) and for patients with moderate to profound ID, whilst side effects were more prominent in the Dutch cohort.

CONCLUSIONS

Comparable rates of seizure reduction are in line with estimates for non-ID patients, adding to the evidence suggesting that PMP has a similar impact on those with ID. Taking a European perspective and sharing data across centres can help strengthen the evidence for prescribing antiepileptic drugs in the ID population.

Clinical Trials Impacted by the COVID-19 Pandemic: Adaptive Designs to the Rescue?

Very recently the new pathogen severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was identified and the coronavirus disease 2019 (COVID-19) declared a pandemic by the World Health Organization. The pandemic has a number of consequences for ongoing clinical trials in non-COVID-19 conditions. Motivated by four current clinical trials in a variety of disease areas we illustrate the challenges faced by the pandemic and sketch out possible solutions including adaptive designs. Guidance is provided on (i) where blinded adaptations can help; (ii) how to achieve Type I error rate control, if required; (iii) how to deal with potential treatment effect heterogeneity; (iv) how to use early read-outs; and (v) how to use Bayesian techniques. In more detail approaches to resizing a trial affected by the pandemic are developed including considerations to stop a trial early, the use of group-sequential designs or sample size adjustment. All methods considered are implemented in a freely available R shiny app. Furthermore, regulatory and operational issues including the role of data monitoring committees are discussed.