Meta-analysis of few small studies in orphan diseases

Stress and Multiple Sclerosis - Systematic review and meta-analysis of the association with disease onset, relapse risk and disability progression

OBJECTIVE

This systematic review and meta-analysis address the evidence on the association of psychological stressors with onset of multiple sclerosis, inflammatory disease activity (relapses or new disease activity on magnetic resonance imaging, MRI) and disability progression.

METHODS

PubMed was searched from 1946 to 15 July 2022. Studies and certain stressors were selected when they assessed stressors independent from stress elicited by the disease process itself. Risk of bias was assessed by the CASP Case Control Study Checklist and the CASP Cohort Study Checklist. Normal-Normal Hierarchical Model (NNHM) for random-effects meta-analysis was used in the Bayesian framework.

RESULTS

30 studies reporting data from 26 cohorts reporting on 24.781 cases could be identified. Ten studies addressed stressors and MS disease onset showing a weak to modest effect of psychological stressors. A meta-analysis of three studies investigating diagnosed stress disorders and MS risk showed a 1.87-fold (CI 1.061 to 3.429) increased MS risk. Stress and MS relapse risk were addressed in 19 heterogeneous studies. Meta-analyses from two independent cohorts investigating the same military threat of a population showed a threefold increased risk for relapses in association with war (relapse rate: 3.0, CI 1.56 to 5.81). In addition, two studies confirmed an association of stressful life events and MRI activity. Three studies of stressors and disease progression were included indicating some effect on disease progression.

CONCLUSIONS

Taken together studies indicate a minor to modest impact of psychological stressors on disease onset, inflammatory activity and progression of MS. Possible case-selection bias and lack of confounder analysis were present in many studies.

How trace plots help interpret meta-analysis results

The trace plot is seldom used in meta-analysis, yet it is a very informative plot. In this article, we define and illustrate what the trace plot is, and discuss why it is important. The Bayesian version of the plot combines the posterior density of τ , the between-study standard deviation, and the shrunken estimates of the study effects as a function of τ . With a small or moderate number of studies, τ is not estimated with much precision, and parameter estimates and shrunken study effect estimates can vary widely depending on the correct value of τ . The trace plot allows visualization of the sensitivity to τ along with a plot that shows which values of τ are plausible and which are implausible. A comparable frequentist or empirical Bayes version provides similar results. The concepts are illustrated using examples in meta-analysis and meta-regression; implementation in R is facilitated in a Bayesian or frequentist framework using the bayesmeta and metafor packages, respectively.

Short-term Outcomes of Different Techniques for Gastric Ischemic Preconditioning Before Esophagectomy: A Network Meta-analysis

BACKGROUND

Ischemia at the anastomotic site plays a critical role determinant in the development of anastomosis-related complications after esophagectomy. Gastric ischemic conditioning (GIC) before esophagectomy has been described to improve the vascular perfusion at the tip of the gastric conduit with a potential effect on anastomotic leak (AL) and stenosis (AS) risk minimization. Laparoscopic (LapGIC) and angioembolization (AngioGIC) techniques have been reported.

PURPOSE

Compare short-term outcomes among different GIC techniques.

MATERIALS AND METHODS

Systematic review and network meta-analysis. One-step esophagectomy (noGIC), LapGIC, and AngioGIC were compared. Primary outcomes were AL, AS, and gastric conduit necrosis (GCN). Risk ratio (RR) and weighted mean difference (WMD) were used as pooled effect size measures, whereas 95% credible intervals (CrIs) were used to assess relative inference.

RESULTS

Overall, 1760 patients (14 studies) were included. Of those, 1028 patients (58.4%) underwent noGIC, 593 (33.6%) LapGIC, and 139 (8%) AngioGIC. AL was reduced for LapGIC versus noGIC (RR=0.68; 95% CrI 0.47-0.98) and AngioGIC versus noGIC (RR=0.52; 95% CrI 0.31-0.93). Similarly, AS was reduced for LapGIC versus noGIC (RR=0.32; 95% CrI 0.12-0.68) and AngioGIC versus noGIC (RR=1.30; 95% CrI 0.65-2.46). The indirect comparison, assessed with the network methodology, did not show any differences for LapGIC versus AngioGIC in terms of postoperative AL and AS risk. No differences were found for GCN, pulmonary complications, overall complications, hospital length of stay, and 30-day mortality among different treatments.

CONCLUSIONS

Compared to noGIC, both LapGIC and AngioGIC before esophagectomy seem equivalent and associated with a reduced risk for postoperative AL and AS.

Bayesian random-effects meta-analysis with empirical heterogeneity priors for application in health technology assessment with very few studies

In Bayesian random-effects meta-analysis, the use of weakly informative prior distributions is of particular benefit in cases where only a few studies are included, a situation often encountered in health technology assessment (HTA). Suggestions for empirical prior distributions are available in the literature but it is unknown whether these are adequate in the context of HTA. Therefore, a database of all relevant meta-analyses conducted by the Institute for Quality and Efficiency in Health Care (IQWiG, Germany) was constructed to derive empirical prior distributions for the heterogeneity parameter suitable for HTA. Previously, an extension to the normal-normal hierarchical model had been suggested for this purpose. For different effect measures, this extended model was applied on the database to conservatively derive a prior distribution for the heterogeneity parameter. Comparison of a Bayesian approach using the derived priors with IQWiG's current standard approach for evidence synthesis shows favorable properties. Therefore, these prior distributions are recommended for future meta-analyses in HTA settings and could be embedded into the IQWiG evidence synthesis approach in the case of very few studies.

Robust variance estimation in small meta-analysis with the standardized mean difference

Conventional random-effects models in meta-analysis rely on large sample approximations instead of exact small sample results. While random-effects methods produce efficient estimates and confidence intervals for the summary effect have correct coverage when the number of studies is sufficiently large, we demonstrate that conventional methods result in confidence intervals that are not wide enough when the number of studies is small, depending on the configuration of sample sizes across studies, the degree of true heterogeneity and number of studies. We introduce two alternative variance estimators with better small sample properties, investigate degrees of freedom adjustments for computing confidence intervals, and study their effectiveness via simulation studies.

Efficacy of ferric carboxymaltose in heart failure with iron deficiency: an individual patient data meta-analysis

BACKGROUND AND AIMS

Whereas a beneficial effect of intravenous ferric carboxymaltose (FCM) on symptoms and exercise capacity among patients with iron deficiency and heart failure (HF) has been consistently demonstrated, the effects of treatment on clinical events remain the subject of research. This meta-analysis aimed to characterize the effects of FCM therapy on hospitalizations and mortality.

METHODS

Patient-level data from randomized, placebo-controlled FCM trials including adults with HF and iron deficiency with ≥52 weeks follow-up were analysed. The co-primary efficacy endpoints were (i) composite of total/recurrent cardiovascular hospitalizations and cardiovascular death and (ii) composite of total HF hospitalizations and cardiovascular death, through 52 weeks. Key secondary endpoints included individual composite endpoint components. Event rates were analysed using a negative binomial model. Treatment-emergent adverse events were also examined.

RESULTS

Three FCM trials with a total of 4501 patients were included. Ferric carboxymaltose was associated with a significantly reduced risk of co-primary endpoint 1 (rate ratio 0.86; 95% confidence interval 0.75-0.98; P = .029; Cochran Q: 0.008), with a trend towards a reduction of co-primary endpoint 2 (rate ratio 0.87; 95% confidence interval 0.75-1.01; P = .076; Cochran Q: 0.024). Treatment effects appeared to result from reduced hospitalization rates, not improved survival. Treatment appeared to have a good safety profile and was well tolerated.

CONCLUSIONS

In iron-deficient patients with HF with reduced left ventricular ejection fraction, intravenous FCM was associated with significantly reduced risk of hospital admissions for HF and cardiovascular causes, with no apparent effect on mortality.

Systematic Review and Meta-Analysis of Dietary Interventions and Microbiome in Phenylketonuria

Inborn errors of metabolism (IEMs) comprise a diverse group of monogenic disorders caused by enzyme deficiencies that result either in a toxic accumulation of metabolic intermediates or a shortage of essential end-products. Certain IEMs, like phenylketonuria (PKU), necessitate stringent dietary intervention that could lead to microbiome dysbiosis, thereby exacerbating the clinical phenotype. The objective of this systematic review was to examine the impact of PKU therapies on the intestinal microbiota. This research was conducted following the PRISMA Statement, with data from PubMed, Scopus, ScienceDirect, and Web of Science. A total of 18 articles meeting the inclusion criteria were published from 2011 to 2022. Significant reductions in several taxonomic groups in individuals with PKU when compared to the control group were detected in a quantitative analysis conducted across seven studies. The meta-analysis synthesis indicates a contrast in biodiversity between PKU subjects and the control population. Additionally, the meta-regression results, derived from the Bacillota/Bacteroidota ratio data, suggest a potential influence of diet in adult PKU populations (p = 0.004). It is worth noting that the limited number of studies calls for further research and analysis in this area. Our findings indicate the necessity of enhancing understanding of microbiota variability in reaction to treatments among PKU subjects to design tailored therapeutic and nutritional interventions to prevent complications resulting from microbiota disruption.

A comparison of surgical techniques for perineal wound closure following perineal excision: a systematic review and network meta-analysis

BACKGROUND

To mitigate pelvic wound issues following perineal excision of rectal or anal cancer, a number of techniques have been suggested as an alternative to primary closure. These methods include the use of a biological/dual mesh, omentoplasty, muscle flap, and/or pelvic peritoneum closure. The aim of this network analysis was to compare all the available surgical techniques used in the attempt to mitigate issues associated with an empty pelvis.

METHODS

An electronic systematic search using MEDLINE databases (PubMed), EMBASE, and Web of Science was performed (Last date of research was March 15th, 2023). Studies comparing at least two of the aforementioned surgical techniques for perineal wound reconstruction during abdominoperineal resection, pelvic exenteration, or extra levator abdominoperineal excision were included. The incidence of primary healing, complication, and/or reintervention for perineal wound were evaluated. In addition, the overall incidence of perineal hernia was assessed.

RESULTS

Forty-five observational studies and five randomized controlled trials were eligible for inclusion reporting on 146,398 patients. All the surgical techniques had a comparable risk ratio (RR) in terms of primary outcomes. The pooled network analysis showed a lower RR for perineal wound infection when comparing primary closure (RR 0.53; Crl 0.33, 0.89) to muscle flap. The perineal wound dehiscence RR was lower when comparing both omentoplasty (RR 0.59; Crl 0.38, 0.95) and primary closure (RR 0.58; Crl 0.46, 0.77) to muscle flap.

CONCLUSIONS

Surgical options for perineal wound closure have evolved significantly over the last few decades. There remains no clear consensus on the "best" option, and tailoring to the individual remains a critical factor.

Rare events meta-analysis using the Bayesian beta-binomial model

In meta-analyses of rare events, it can be challenging to obtain a reliable estimate of the pooled effect, in particular when the meta-analysis is based on a small number of studies. Recent simulation studies have shown that the beta-binomial model is a promising candidate in this situation, but have thus far only investigated its performance in a frequentist framework. In this study, we aim to make the beta-binomial model for meta-analysis of rare events amenable to Bayesian inference by proposing prior distributions for the effect parameter and investigating the models' robustness to different specifications of priors for the scale parameter. To evaluate the performance of Bayesian beta-binomial models with different priors, we conducted a simulation study with two different data generating models in which we varied the size of the pooled effect, the degree of heterogeneity, the baseline probability, and the sample size. Our results show that while some caution must be exercised when using the Bayesian beta-binomial in meta-analyses with extremely sparse data, the use of a weakly informative prior for the effect parameter is beneficial in terms of mean bias, mean squared error, and coverage. For the scale parameter, half-normal and exponential distributions are identified as candidate priors in meta-analysis of rare events using the Bayesian beta-binomial model.

Improved methods to construct prediction intervals for network meta-analysis

Network meta-analysis has played an important role in evidence-based medicine for assessing the comparative effectiveness of multiple available treatments. The prediction interval has been one of the standard outputs in recent network meta-analysis as an effective measure that enables simultaneous assessment of uncertainties in treatment effects and heterogeneity among studies. To construct the prediction interval, a large-sample approximating method based on the t-distribution has generally been applied in practice; however, recent studies have shown that similar t-approximation methods for conventional pairwise meta-analyses can substantially underestimate the uncertainty under realistic situations. In this article, we performed simulation studies to assess the validity of the current standard method for network meta-analysis, and we show that its validity can also be violated under realistic situations. To address the invalidity issue, we developed two new methods to construct more accurate prediction intervals through bootstrap and Kenward-Roger-type adjustment. In simulation experiments, the two proposed methods exhibited better coverage performance and generally provided wider prediction intervals than the ordinary t-approximation. We also developed an R package, PINMA (https://cran.r-project.org/web/packages/PINMA/), to perform the proposed methods using simple commands. We illustrate the effectiveness of the proposed methods through applications to two real network meta-analyses.

Adherence enhancing interventions for pharmacological and oxygen therapy in patients with COPD: protocol for a systematic review and component network meta-analyses

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is characterised by hyperinflation and expiratory airflow limitation due to long-term exposure to irritants. The variety and complexity of COPD treatment and the possible added comorbidities may make the patients find it difficult to cope with the required medications. That is why supporting patients' adherence is critical because not taking medications correctly increases the risk of complications and creates an additional financial burden. A range of interventions aiming to improve patient adherence were used, and most of them are complex since they involve a mix of elements. Furthermore, despite the variety of available tools, assessing adherence is challenging because clinicians usually do not get a concrete judgement if their patients followed their treatment plan reliably. We aim to evaluate the effectiveness of adherence-enhancing interventions for COPD patients, explore which intervention (component) works for which patients and check the factors influencing the implementation and participant responses.

METHODS

We will perform a comprehensive literature search (Medline, Embase, Cochrane Library, trial registries) without restrictions on language and publication status, and we will include all controlled studies investigating the effect of adherence-enhancing intervention on patients with COPD. We plan to involve COPD patients in the systematic review development through two patient interviews (one before and one after the systematic review). Two reviewers will perform the screening, data extraction and risk of bias (ROB) assessment. For ROB, we will use ROB 2.0 to assess randomised controlled trials, and ROBINS-I to assess non-randomised studies. We will perform pair-wise random-effects meta-analyses and component network meta-analyses to identify the most effective components and combinations of components. We will use the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach to assess the quality of evidence. To determine the degree of complexity, we will use the iCAT_SR checklist, and then, following a logical model, we will group the interventions according to prespecified criteria.

DISCUSSION

This systematic review aims to point out the most effective and implementable adherence-enhancing interventions by using methods for synthesising evidence on complex interventions and involving COPD patients all along with the review process.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42022353977.

Postpartum relapse risk in multiple sclerosis: a systematic review and meta-analysis

The influence of pregnancy on the course of multiple sclerosis (MS) has long been controversial. While historical evidence suggests a substantial decline in relapse rates during pregnancy followed by a rebound in the postpartum period, more recent work yielded equivocal results. We performed a systematic review and meta-analysis on data from cohort studies to determine whether women with MS experience increased relapse rates after delivery. A systematic literature search was conducted in the databases MEDLINE and Epistemonikos on the topic 'motherhood choice in MS' in March 2022. We included cohort studies assessing the association between pregnancy and MS relapse activity defined by the annualised relapse rate after 3, 6, 9 and 12 months post partum. Furthermore, information about disease-modifying therapies (DMT) and breast feeding was considered, if available. 5369 publications were identified. Of these, 93 full-text articles on MS relapse activity during the postpartum period were screened. 11 studies including 2739 pregnancies were eligible. Women with MS showed a significantly increased relapse rate in the first 6 months post partum, compared with preconception with the incidence rate ratio (IRR) almost doubled in the first 3 months post partum (1.87, 95% CI 1.40 to 2.50). However, at 10-12 months post partum, the IRR decreased significantly (0.81, 95% CI 0.67 to 0.98). Subanalysis on influencing parameters suggested that preconceptional DMTs (IRR for highly-effective DMTs 2.76, 95% CI 1.34 to 5.69) and exclusive breast feeding (risk ratio 0.39, 95% CI 0.18 to 0.86) significantly influenced postpartum relapse risk. Increased postpartum annualised relapse rate and possible modifiers should be considered in counselling women with MS who are considering pregnancy.

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.

Adjusting for publication bias in meta-analysis via inverse probability weighting using clinical trial registries

Publication bias is a major concern in conducting systematic reviews and meta-analyses. Various sensitivity analysis or bias-correction methods have been developed based on selection models, and they have some advantages over the widely used trim-and-fill bias-correction method. However, likelihood methods based on selection models may have difficulty in obtaining precise estimates and reasonable confidence intervals, or require a rather complicated sensitivity analysis process. Herein, we develop a simple publication bias adjustment method by utilizing the information on conducted but still unpublished trials from clinical trial registries. We introduce an estimating equation for parameter estimation in the selection function by regarding the publication bias issue as a missing data problem under the missing not at random assumption. With the estimated selection function, we introduce the inverse probability weighting (IPW) method to estimate the overall mean across studies. Furthermore, the IPW versions of heterogeneity measures such as the between-study variance and the I2 measure are proposed. We propose methods to construct confidence intervals based on asymptotic normal approximation as well as on parametric bootstrap. Through numerical experiments, we observed that the estimators successfully eliminated bias, and the confidence intervals had empirical coverage probabilities close to the nominal level. On the other hand, the confidence interval based on asymptotic normal approximation is much wider in some scenarios than the bootstrap confidence interval. Therefore, the latter is recommended for practical use.

Considerations for pooling real-world data as a comparator cohort to a single arm trial: a simulation study on assessment of heterogeneity

BACKGROUND

Novel precision medicine therapeutics target increasingly granular, genomically-defined populations. Rare sub-groups make it challenging to study within a clinical trial or single real-world data (RWD) source; therefore, pooling from disparate sources of RWD may be required for feasibility. Heterogeneity assessment for pooled data is particularly complex when contrasting a pooled real-world comparator cohort (rwCC) with a single-arm clinical trial (SAT), because the individual comparisons are not independent as all compare a rwCC to the same SAT. Our objective was to develop a methodological framework for pooling RWD focused on the rwCC use case, and simulate novel approaches of heterogeneity assessment, especially for small datasets.

METHODS

We present a framework with the following steps: pre-specification, assessment of dataset eligibility, and outcome analyses (including assessment of outcome heterogeneity). We then simulated heterogeneity assessments for a binary response outcome in a SAT compared to two rwCCs, using standard methods for meta-analysis, and an Adjusted Cochran's Q test, and directly comparing the individual participant data (IPD) from the rwCCs.

RESULTS

We found identical power to detect a true difference for the adjusted Cochran's Q test and the IPD method, with both approaches superior to a standard Cochran's Q test. When assessing the impact of heterogeneity in the null scenario of no difference between the SAT and rwCCs, a lack of statistical power led to Type 1 error inflation. Similarly, in the alternative scenario of a true difference between SAT and rwCCs, we found substantial Type 2 error, with underpowered heterogeneity testing leading to underestimation of the treatment effect.

CONCLUSIONS

We developed a methodological framework for pooling RWD sources in the context of designing a rwCC for a SAT. When testing for heterogeneity during this process, the adjusted Cochran's Q test matches the statistical power of IPD heterogeneity testing. Limitations of quantitative heterogeneity testing in protecting against Type 1 or Type 2 error indicate these tests are best used descriptively, and after careful selection of datasets based on clinical/data considerations. We hope these findings will facilitate the rigorous pooling of RWD to unlock insights to benefit oncology patients.

Short-term outcomes of different esophagojejunal anastomotic techniques during laparoscopic total gastrectomy: a network meta-analysis

BACKGROUND

Different techniques have been described for esophagojejunostomy (EJ) during laparoscopic total gastrectomy (LTG) for gastric cancer. Linear stapled techniques include overlap (OL) and functional end-to-end anastomosis (FEEA) while single staple technique (SST), hemi-double staple technique (HDST), and OrVil® are circular stapled approaches. Nowadays, the choice among techniques for EJ depends on operating surgeon personal preference.

PURPOSE

To compare short-term outcomes of different EJ techniques during LTG.

METHODS

Systematic review and network meta-analysis. OL, FEEA, SST, HDST, and OrVil® were compared. Primary outcomes were anastomotic leak (AL) and stenosis (AS). Risk ratio (RR) and weighted mean difference (WMD) were used as pooled effect size measures, whereas 95% credible intervals (CrI) were used to measure relative inference.

RESULTS

Overall, 3177 patients (20 studies) were included. The technique for EJ was SST (n = 1026; 32.9%), OL (n = 826; 26.5%), FEEA (n = 752; 24.1%), OrVil® (n = 317; 10.1%), and HDST (n = 196; 6.4%). AL was comparable for OL vs. FEEA (RR = 0.82; 95% CrI 0.47-1.49), OL vs. SST (RR = 0.55; 95% CrI 0.27-1.21), OL vs. OrVil® (RR = 0.54; 95% CrI 0.32-1.22), and OL vs. HDST (RR = 0.65; 95% CrI 0.28-1.63). Similarly, AS was similar for OL vs. FEEA (RR = 0.46; 95% CrI 0.18-1.28), OL vs. SST (RR = 0.89; 95% CrI 0.39-2.15), OL vs. OrVil® (RR = 0.36; 95% CrI 0.14-1.02), and OL vs. HDST (RR = 0.61; 95% CrI 0.31-1.21). Anastomotic bleeding, time to soft diet resumption, pulmonary complications, hospital length of stay, and mortality were comparable while operative time was reduced for FEEA.

CONCLUSIONS

This network meta-analysis shows similar postoperative AL and AS risk when comparing OL, FEEA, SST, HDST, and OrVil® techniques. Similarly, no differences were found for anastomotic bleeding, operative time, soft diet resumption, pulmonary complications, hospital length of stay and 30-day mortality.

Effect of intravenous iron replacement on recurrent heart failure hospitalizations and cardiovascular mortality in patients with heart failure and iron deficiency: A Bayesian meta-analysis

AIMS

Iron deficiency is common in patients with heart failure (HF) and reduced ejection fraction (HFrEF) and is associated with a poor prognosis. Whether intravenous iron replacement improves recurrent HF hospitalizations and cardiovascular mortality of these patients is uncertain although several trials were conducted. Moreover, none of the trials were powered to assess the effect of intravenous iron in clinically important subgroups. Therefore, we conducted a Bayesian analysis to derive precise estimates of the effect of intravenous iron replacement on recurrent HF hospitalizations and cardiovascular mortality in iron-deficient HFrEF patients using consistent subgroup definitions across trials.

METHODS AND RESULTS

Individual participant data were used from the FAIR-HF (n = 459), CONFIRM-HF (n = 304) and AFFIRM-AHF (n = 1108) trials. These data were re-analysed following as closely as possible the approach taken in the analyses of IRONMAN (n = 1137), for which study level data were used. Definitions of outcomes and subgroups from the FAIR-HF, CONFIRM-HF and AFFIRM-AHF were matched with those used in IRONMAN. The primary endpoint was recurrent HF hospitalizations and cardiovascular mortality. The analysis of recurrent events was based on rate ratios (RR) derived from the Lin-Wei-Yang-Ying model, and the data were pooled using Bayesian random-effects meta-analysis. Compared with placebo, intravenous iron significantly reduced the rates of recurrent HF hospitalizations and cardiovascular mortality (RR 0.73, 95% credible interval [CI] 0.48-0.99; between-trial heterogeneity tau = 0.16). The pooled treatment effects did not provide evidence for any differential effects for subgroups based on sex (ratio of rate ratios [RRR] 1.49 [95% CI 0.95-2.37], age <69.4 vs. ≥69.4 years) (RRR 0.68 [0.40-1.15]), ischaemic versus non-ischaemic aetiology of HF (RRR 0.73 [0.42-1.33]), transferrin saturation <20% vs. ≥20% (RRR 0.75 [0.40-1.34]), estimated glomerular filtration rate ≤60 versus >60 ml/min/1.73 m2 (RRR 0.97 [0.56-1.68]), haemoglobin <11.8 versus ≥11.8 (RRR 0.95 [0.53-1.60]), ferritin <35 versus ≥35 μg/L (RRR 1.26 [0.72-2.48]) and New York Heart Association class II versus III/IV (RRR 0.91 [0.54-1.56]).

CONCLUSIONS

Treatment of iron-deficient HFrEF patients with intravenous iron - namely with ferric carboxymaltose or ferric derisomaltose - results in significant reduction in recurrent HF hospitalizations and cardiovascular mortality. Results were nominally consistent across the subgroups studied, but for several of these subgroups uncertainty remains present.

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.

Quality of life of pediatric and adult individuals with osteogenesis imperfecta: a meta-analysis

BACKGROUND

Osteogenesis imperfecta (OI) is a group of rare inheritable disorders of connective tissue. The cardinal manifestations of OI are low bone mass and reduced bone mineral strength, leading to increased bone fragility and deformity that may lead to significant impairment in daily life. The phenotypic manifestations show a broad range of severity, ranging from mild or moderate to severe and lethal. The here presented meta-analysis aimed to analyze existing findings on quality of life (QoL) in children and adults with OI.

METHODS

Nine databases were searched with predefined key words. The selection process was executed by two independent reviewers and was based on predetermined exclusion and inclusion criteria. The quality of each study was assessed using a risk of bias tool. Effect sizes were calculated as standardized mean differences. Between-study heterogeneity was calculated with the I² statistic.

RESULTS

Among the studies included two featured children and adolescents (N = 189), and four adults (N = 760). Children with OI had significantly lower QoL on the Pediatric quality of life inventory (PedsQL) with regards to the total score, emotional, school, and social functioning compared to controls and norms. The data was not sufficient to calculate differences regarding OI-subtypes. In the adult sample assessed with Short Form Health Survey Questionnaire, 12 (SF-12) and 36 items (SF-36), all OI types showed significantly lower QoL levels across all physical component subscales compared to norms. The same pattern was found for the mental component subscales namely vitality, social functioning, and emotional role functioning. The mental health subscale was significantly lower for OI type I, but not for type III and IV. All of the included studies exhibited a low risk of bias.

CONCLUSIONS

QoL was significantly lower in children and adults with OI compared to norms and controls. Studies in adults comparing OI subtypes showed that the clinical severity of the phenotype is not related to worse mental health QoL. Future research is needed to examine QoL in children and adolescents in more sophisticated ways and to better understand the association between clinical severity of an OI-phenotype/severity and mental health in adults.

Bayesian estimation and testing in random-effects meta-analysis of rare binary events allowing for flexible group variability

Rare binary events data arise frequently in medical research. Due to lack of statistical power in individual studies involving such data, meta-analysis has become an increasingly important tool for combining results from multiple independent studies. However, traditional meta-analysis methods often report severely biased estimates in such rare-event settings. Moreover, many rely on models assuming a pre-specified direction for variability between control and treatment groups for mathematical convenience, which may be violated in practice. Based on a flexible random-effects model that removes the assumption about the direction, we propose new Bayesian procedures for estimating and testing the overall treatment effect and inter-study heterogeneity. Our Markov chain Monte Carlo algorithm employs Pólya-Gamma augmentation so that all conditionals are known distributions, greatly facilitating computational efficiency. Our simulation shows that the proposed approach generally reports less biased and more stable estimates compared to existing methods. We further illustrate our approach using two real examples, one using rosiglitazone data from 56 studies and the other using stomach ulcers data from 41 studies.

What is the ideal mesh location for incisional hernia prevention during elective laparotomy? A network meta-analysis of randomized trials

BACKGROUND

Incisional hernia (IH) represents an important complication after surgery. Prophylactic mesh reinforcement (PMR) with different mesh locations [onlay (OL), retromuscular (RM), preperitoneal (PP), and intraperitoneal (IP)] has been described to possibly reduce the risk of postoperative IH. However, data reporting the 'ideal' mesh location are sparse. The aim of this study was to evaluate the optimal mesh location for IH prevention during elective laparotomy.

METHODS

Systematic review and network meta-analysis of randomized controlled trials (RCTs). OL, RM, PP, IP, and no mesh (NM) were compared. The primary aim was postoperative IH. Risk ratio (RR) and weighted mean difference (WMD) were used as pooled effect size measures, whereas 95% credible intervals (CrI) were used to assess relative inference.

RESULTS

Fourteen RCTs (2332 patients) were included. Overall, 1052 (45.1%) had no mesh (NM) while 1280 (54.9%) underwent PMR stratified in IP ( n =344 pts), PP ( n =52 pts), RM ( n =463 pts), and OL ( n =421 pts) placement. Follow-up ranged from 12 months to 67 months. RM (RR=0.34; 95% CrI: 0.10-0.81) and OL (RR=0.15; 95% CrI: 0.044-0.35) were associated with significantly reduced IH RR compared to NM. A tendency toward reduced IH RR was noticed for PP versus NM (RR=0.16; 95% CrI: 0.018-1.01), while no differences were found for IP versus NM (RR=0.59; 95% CrI: 0.19-1.81). Seroma, hematoma, surgical site infection, 90-day mortality, operative time and hospital length of stay were comparable among treatments.

CONCLUSIONS

RM or OL mesh placement seems associated with reduced IH RR compared to NM. PP location appears promising; however, future studies are warranted to corroborate this preliminary indication.

Peripheral blood cellular immunophenotype in depression: a systematic review and meta-analysis

INTRODUCTION

Meta-analyses implicate immune dysfunction in depression confirming increased levels of circulating immune proteins (e.g., cytokines) in depression cases compared to controls. White blood cells (WBC) both produce and are influenced by cytokines, and play key roles in orchestrating innate and adaptive immune responses, but their role in depression remains unclear. Therefore, a systematic review of studies of various WBC subsets in depression is required for a greater understanding of the nature of immune dysfunction in this illness.

METHODS

We searched PubMed and PsycINFO databases (inception to 5th April 2022) and conducted a systematic review and meta-analysis of identified studies comparing absolute count and/or relative percentage of flow cytometry-derived WBC subsets between depression cases and controls. Selected studies were quality assessed. Random-effect meta-analysis was performed.

RESULTS

Thirty-three studies were included and 27 studies (n = 2277) were meta-analysed. We report an increase in mean absolute counts of WBC (seven studies; standardised mean difference [SMD] = 1.07; 95% CI, 0.61-1.53; P < 0.01; I2 = 64%), granulocytes (two studies; SMD = 2.07; 95% CI, 1.45-2.68; P < 0.01; I2 = 0%), neutrophils (four studies; SMD = 0.91; 95% CI, 0.23-1.58; P < 0.01; I2 = 82%), monocytes (seven studies; SMD = 0.60; 95% CI, 0.19-1.01; P < 0.01; I2 = 66%), CD4+ helper T cells (11 studies; SMD = 0.30; 95% CI, 0.15-0.45; P < 0.01; I2 = 0%), natural killer cells (11 studies; SMD = 1.23; 95% CI, 0.38-2.08; P < 0.01; I2 = 95%), B cells (10 studies; SMD = 0.30; 95% CI, 0.03-0.57; P = 0.03; I2 = 56%), and activated T cells (eight studies; SMD = 0.45; 95% CI, 0.24-0.66; P < 0.01; I2 = 0%) in depression, compared to controls. Fewer studies reported relative percentage, indicating increased neutrophils and decreased total lymphocytes, Th1, and Th2 cells in depression.

CONCLUSIONS

Depression is characterised by widespread alterations in circulating myeloid and lymphoid cells, consistent with dysfunction in both innate and adaptive immunity. Immune cells could be useful biomarkers for illness subtyping and patient stratification in future immunotherapy trials of depression, along with cytokines, other biomarkers, and clinical measures.

Methods for the Inclusion of Real-World Evidence in a Rare Events Meta-Analysis of Randomized Controlled Trials

BACKGROUND

Many rare events meta-analyses of randomized controlled trials (RCTs) have lower statistical power, and real-world evidence (RWE) is becoming widely recognized as a valuable source of evidence. The purpose of this study is to investigate methods for including RWE in a rare events meta-analysis of RCTs and the impact on the level of uncertainty around the estimates.

METHODS

Four methods for the inclusion of RWE in evidence synthesis were investigated by applying them to two previously published rare events meta-analyses: the naïve data synthesis (NDS), the design-adjusted synthesis (DAS), the use of RWE as prior information (RPI), and the three-level hierarchical models (THMs). We gauged the effect of the inclusion of RWE by varying the degree of confidence placed in RWE.

RESULTS

This study showed that the inclusion of RWE in a rare events meta-analysis of RCTs could increase the precision of the estimates, but this depended on the method of inclusion and the level of confidence placed in RWE. NDS cannot consider the bias of RWE, and its results may be misleading. DAS resulted in stable estimates for the two examples, regardless of whether we placed high- or low-level confidence in RWE. The results of the RPI approach were sensitive to the confidence level placed in RWE. The THM was effective in allowing for accommodating differences between study types, while it had a conservative result compared with other methods.

CONCLUSION

The inclusion of RWE in a rare events meta-analysis of RCTs could increase the level of certainty of the estimates and enhance the decision-making process. DAS might be appropriate for inclusion of RWE in a rare event meta-analysis of RCTs, but further evaluation in different scenarios of empirical or simulation studies is still warranted.

Chemsex and chemsex associated substance use among men who have sex with men in Asia: A systematic review and meta-analysis

BACKGROUND

The prevalence of chemsex has been reported by multiple systematic reviews among men who have sex with men (MSM) focussing predominantly on the Global North. An Asian perspective with meta-analytical evidence is missing. This meta-analysis summarised the prevalence of substance use associated with chemsex, and chemsex activity among MSM and MSM sub-populations in Asia, as well as the likelihood for chemsex among MSM living with or without HIV.

METHODS

We utilized PubMed, Web of Science and medRxiv to search for literature describing chemsex and its associated substance use among MSM and MSM sub-populations in Asia from January 1, 2010 to November 1, 2021 to conduct three meta-analyses with both frequentist and Bayesian approaches.

RESULTS

We identified 219 studies and included 23 in the meta-analysis. Based on the frequentist models, methamphetamine was the default substance associated with chemsex among MSM in Asia (prevalence = 0.16, 95 %CI:0.09-0.22), followed by GHB/GBL (prevalence = 0.15, 95 %CI:0.03-0.27) and ketamine (prevalence = 0.08, 95 %CI:0.04-0.12), but hardly any cocaine (prevalence = 0.01, 95 %CI:0.00-0.03). Compared to a general MSM population (prevalence = 0.19, 95 %CI:0.15-0.23), MSM engaging in transactional sex showed a higher prevalence of chemsex (MSM sex work clients [prevalence = 0.28, 95 %CI:0.11-0.45]; MSM sex worker [prevalence = 0.28, 95 %CI:0.17-0.26]). MSM living with HIV also showed higher odds of chemsex activity (OR = 3.35, 95 %CI:1.57-7.10), compared to MSM living without HIV. Both meta-analytic models converged, indicating robust evidence.

CONCLUSIONS

Our meta-analyses showed that chemsex is not uncommon among MSM, and MSM engaging in transactional sex in Asia. We confirmed that MSM living with HIV have a higher likelihood of engaging in chemsex, too. Chemsex prevention and management strategies in Asia should be adjusted accordingly.

Using the bayesmeta R package for Bayesian random-effects meta-regression

BACKGROUND

Random-effects meta-analysis within a hierarchical normal modeling framework is commonly implemented in a wide range of evidence synthesis applications. More general problems may even be tackled when considering meta-regression approaches that in addition allow for the inclusion of study-level covariables.

METHODS

We describe the Bayesian meta-regression implementation provided in the bayesmetaR package including the choice of priors, and we illustrate its practical use.

RESULTS

A wide range of example applications are given, such as binary and continuous covariables, subgroup analysis, indirect comparisons, and model selection. Example R code is provided.

CONCLUSIONS

The bayesmeta package provides a flexible implementation. Due to the avoidance of MCMC methods, computations are fast and reproducible, facilitating quick sensitivity checks or large-scale simulation studies.

Efficacy of laparoscopic Toupet fundoplication compared to endoscopic and surgical procedures for GERD treatment: a randomized trials network meta-analysis

PURPOSE

We aim to review and quantitatively compare laparoscopic Toupet fundoplication (LTF), Nissen fundoplication (LNF), anterior partial fundoplication (APF), magnetic augmentation sphincter (MSA), radiofrequency ablation (RFA), transoral incisionless fundoplication (TIF), proton pump inhibitor (PPI), and placebo for the treatment of GERD. A number of meta-analyses compared the efficacy of surgical and endoscopic procedures for recalcitrant GERD, but considerable debate on the effectiveness of operative strategies remains.

METHODS

A systematic review of MEDLINE databases, EMBASE, and Web of Science for randomized controlled trials (RCTs) comparing the aforementioned surgical and endoscopic GERD treatments was performed. Risk ratio and weighted mean difference were used as pooled effect size measures, whereas 95% credible intervals (CrI) were used to assess relative inference.

RESULTS

Thirty-three RCTs were included. Surgical and endoscopic treatments have similar RR for heartburn, regurgitation, bloating. LTF has a lower RR of post-operative dysphagia when compared to APF (RR 3.3; Crl 1.4-7.1) and LNF (RR 2.5; Crl 1.3-4.4). The pooled network meta-analysis did not observe any significant improvement regarding LES pressure and pH < from baseline. LTF, APF, LNF, MSA, RFA, and TIF had have a similar post-operative PPI discontinuation rate.

CONCLUSION

LTF has a lower rate of post-operative dysphagia when compared to APF and LNF. The pre-post effects, such as GERD-HQRL, LES pressure, and pH <4, should be avoided in meta-analyses because results may be biased. Last, a consensus about the evaluation of GERD treatments' efficacy and their outcomes is needed.

Micropolitics of Rare Diseases in Italy

Many stakeholders are involved in knowledge production regarding rare diseases. However, disputes and contentions can arise in this field. In this article, I analyze how professionals and afflicted people mobilized the category of "rare diseases" within a hospital center in Italy. By exploring the micropolitics performed there, I observe how practitioners produced inclusion in the Italian health care system or exclusion from it. I then show how users of the health care service challenged such practices, through their own interpretations of "rare diseases," while even the refusal to participate in patients' organizations emerged sometimes as a form of resistance.

Postpartum hemorrhage drills or simulations and adverse outcomes: a systematic review and Bayesian meta-analysis

OBJECTIVE

To compare the rates of adverse outcomes with postpartum hemorrhage (PPH) before and after implementation of drills or simulation exercises.

STUDY ELIGIBILITY CRITERIA

We included all English studies that reported on rates of PPH and associated complications during the pre- and post-implementation of interventional exercises.

STUDY APPRASIAL AND SYNTHESIS METHODS

Two investigators independently reviewed the abstracts, and full articles for eligibility of all studies. Inconsistencies related to study evaluation or data extraction were resolved by a third author. The co-primary outcomes were the rate of PPH and of any transfusion; the secondary outcomes included admission to the intensive care unit (ICU), transfusion ≥ 4 units of packed red blood cells, hysterectomy, or maternal death. Study effects were combined by Bayesian meta-analysis and reported as risk ratios (RR) and 95% credible intervals (Cr).

RESULTS

We reviewed 142 full length articles. Of these, 18 publications, with 355,060 deliveries-150,562 (42%) deliveries during the pre-intervention and 204,498 (57.6%) deliveries in the post-interventional period-were included in the meta-analysis. Using the Newcastle-Ottawa Scale, only three studies were considered good quality, and none of them were done in the US. The rate of PPH prior to intervention was 5.06% and 5.46% afterwards (RR 1.09, 95% CI 0.87-1.36; probability of reduction in the diagnosis being 21%). The likelihood of transfusion decreased from 1.68% in the pre-intervention to 1.27% in the post-intervention period (RR 0.80, 95% Cr 0.57-1.09). The overall probability of reduction in transfusion was 93%, albeit it varied among studies done in non-US countries (96%) versus in the US (23%). Transfusion of 4 units or more of blood occurred in 0.44% of deliveries before intervention and 0.37% afterwards (RR of 0.85, 95% CI 0.50-1.52), with the overall probability of reduction being 72% (76% probability of reduction in studies from non-US countries and 49% reduction with reports from the US). Surgical interventions to manage PPH, which was not reported in any US studies, occurred in 0.14% before intervention and 0.28% afterwards (RR 1.29; 95% CI 0.56-3.06; probability of reduction 27%). Admission to the ICU occurred in 0.10% before intervention and 0.08% subsequently (RR 0.92, 95% CI 0.58-1.43), with the overall probability of reduction being 65% (81% in studies from non-US countries and 27% from the study done in the US). Maternal death occurred in 0.17% in the pre-intervention period and 0.09% during the post-intervention (RR 0.62, 95% CI 0.33-1.05; probability of reduction 93% in studies from non-US countries and 82% in one study from the US).

CONCLUSIONS

Interventions to reduce the sequelae of PPH are associated with decrease in adverse outcomes. The conclusion, however, ought not to be accepted reflexively for the US population. All of the studies on the topic done in the US are of poor quality and the associated probability of reduction in sequelae are consistently lower than those done in other countries.

SYNOPSIS

Since the putative benefits of PPH drills or simulation exercises are based on poor quality pre- and post-intervention trials, policies recommending them ought to be revisited.

Generating evidence for diagnosis and therapy of RarE LIVEr disease: the RELIVE Initiative for systematic reviews and meta-analyses

BACKGROUND

Rare liver lesions and diseases have seldomly aroused major interest of researchers. For most guidelines, presumably similar clinical conditions are pooled without detailed investigations of singularities that they present.

MAIN TEXT

A multidisciplinary project aiming to establish evidence-based therapies for rare liver diseases has been founded. A series of systematic reviews and meta-analyses will be the starting point for a structured development of guidelines for rare conditions of the liver affecting pediatric and adult populations. The novel approach will be focusing on case reports and small patient series with distinct rare liver diseases without pooling several presumably acceptably similar conditions. Thus, a vital resource of information will be utilized, which has been largely neglected hitherto.

CONCLUSION

Highly specific recommendations based on highest available evidence will therefore be developed for specific conditions, advancing the individualized medicine approach for the afflicted patients.

Innovations in Clinical Development in Rare Diseases of Children and Adults: Small Populations and/or Small Patients

Many of the afflictions of children are rare diseases. This creates numerous drug development challenges related to small populations, including limited information about the disease state, enrollment challenges, and diminished incentives for pediatric development of novel therapies by pharmaceutical and biotechnology sponsors. We review selected innovations in clinical development that may partially mitigate some of these difficulties, starting with the concept of development efficiency for individual clinical trials, clinical programs (involving multiple trials for a single drug), and clinical portfolios of multiple drugs, and decision analysis as a tool to optimize efficiency. Development efficiency is defined as the ability to reach equally rigorous or more rigorous conclusions in less time, with fewer trial participants, or with fewer resources. We go on to discuss efficient methods for matching targeted therapies to biomarker-defined subgroups, methods for eliminating or reducing the need for natural history data to guide rare disease development, the use of basket trials to enhance efficiency by grouping multiple similar disease applications in a single clinical trial, and the use of alternative data sources including historical controls to augment or replace concurrent controls in clinical studies. Greater understanding and broader application of these methods could lead to improved therapies and/or more widespread and rapid access to novel therapies for rare diseases in both children and adults.

Incorporating historical control information in ANCOVA models using the meta-analytic-predictive approach

The meta-analytic-predictive (MAP) approach is a Bayesian meta-analytic method to synthesize and incorporate information from historical controls in the analysis of a new trial. Classically, only a single parameter, typically the intercept or rate, is assumed to vary across studies, which may not be realistic in more complex models. Analysis of covariance (ANCOVA) is often used to analyze trials with a pretest-posttest design, where both the intercept and the baseline effect (coefficient of the outcome at baseline) affect the estimated treatment effect. We extended the MAP approach to ANCOVA, to allow for variation in the intercept and the baseline effect across studies, and possibly also correlation between these parameters. The method was illustrated using data from the Alzheimer's Disease Cooperative Study (ADCS) and assessed with a simulation study. In the ADCS data, the proposed multivariate MAP approach yielded a prior effective sample size of 79 and 58 for the intercept and the baseline effect respectively and reduced the posterior standard deviation of the treatment effect by 12.6%. The result was robust to the choice of prior for the between-study variation. In the simulations, the proposed approach yielded power gains with a good control of the type I error rate. Ignoring the between-study correlation of the parameters or assuming no variation in the baseline effect generally led to less power gain. In conclusion, the MAP approach can be extended to a multivariate version for ANCOVA, which may improve the estimation of the treatment effect.

Effects of physical exercise on blood pressure during pregnancy

Objective

Effect of physical exercise on pregnant women currently has become a hot topic in prenatal health care. In this study, A meta-analysis was conducted on account of Randomized Controlled Trial (RCT). It focused on evaluating the effect of physical exercise intervention on blood pressure so that could provide certain evidence for health care during pregnancy.

Methods

Results of relevant studies were retrieved from PubMed, Embase, Web of Science and the Cochrane Library, and all of these included studies were evaluated according to the Cochrane collaboration’s tool for assessing the risk of bias. Stata 15.1 was used for meta-analysis, and mean difference (MD) was used as statistic for pooled analysis. The effect values were combined by conventional meta-analysis and Bayesian meta-analysis respectively, and the consistency of pooled results was considered as well.

Results

A total of 18 RCT studies were included in the quantitative analysis. The conventional meta-analysis showed differences in blood pressure between intervention group and control group (P < 0.05). Systolic and diastolic blood pressures of intervention group were 3.19 mmHg (95% CI: -5.13, -1.25) and 2.14 mmHg (95% CI: -4.26, -0.03) lower than that of control group, respectively. Bayesian meta-analysis showed that both systolic and diastolic pressure among intervention group decreased by 3.34 mmHg (95% CrI: -5.15, -1.56) and 2.14 mmHg (95% CrI: -3.79, − 0.50), respectively. Subgroup analysis supported that as long as healthy pregnant women participated in exercises, their blood pressure could be slightly regulated, while hypertension susceptible pregnant women significantly lowered blood pressure.

Conclusion

Exercise intervention during pregnancy is beneficial to lower or normalize blood pressure, and this research provides clues for follow-up studies.

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.

Improving pediatric multiple sclerosis interventional phase III study design: a meta-analysis

Background:

To support innovative trial designs in a regulatory setting for pediatric-onset multiple sclerosis (MS), the study aimed to perform a systematic literature review and meta-analysis of relapse rates with interferon β (IFN β), fingolimod, and natalizumab and thereby demonstrate potential benefits of Bayesian and non-inferiority designs in this population.

Methods:

We conducted a literature search in MEDLINE and EMBASE from inception until 17 June 2020 of all studies reporting annualized relapse rates (ARR) in IFN β-, fingolimod-, or natalizumab-treated patients with pediatric-onset relapsing–remitting MS. These interventions were chosen because the literature was mainly available for these treatments, and they are currently used for the treatment of pediatric MS. Two researchers independently extracted data and assessed study quality using the Cochrane Effective Practice and Organization of Care – Quality Assessment Tool. The meta-analysis estimates were obtained by Bayesian random effects model. Data were summarized as ARR point estimates and 95% credible intervals.

Results:

We found 19 articles, including 2 randomized controlled trials. The baseline ARR reported was between 1.4 and 3.7. The meta-analysis-based ARR was significantly higher in IFN β-treated patients (0.69, 95% credible interval: 0.51–0.91) versus fingolimod (0.11, 0.04–0.27) and natalizumab (0.17, 0.09–0.31). Based on the meta-analysis results, an appropriate non-inferiority margin versus fingolimod could be in the range of 2.29–2.67 and for natalizumab 1.72–2.29 on the ARR ratio scale. A Bayesian design, which uses historical information for a fingolimod or natalizumab control arm, could reduce the sample size of a new trial by 18 or 14 patients, respectively.

Conclusion:

This meta-analysis provides evidence that relapse rates are considerably higher with IFNs versus fingolimod or natalizumab. The results support the use of innovative Bayesian or non-inferiority designs to avoid exposing patients to less effective comparators in trials and bringing new medications to patients more efficiently.

Staple Line Reinforcement During Laparoscopic Sleeve Gastrectomy: Systematic Review and Network Meta-analysis of Randomized Controlled Trials

Purpose

Staple line reinforcement (SLR) during laparoscopic sleeve gastrectomy (LSG) is controversial. The purpose of this study was to perform a comprehensive evaluation of the most commonly utilized techniques for SLR.

Materials and Methods

Network meta-analysis of randomized controlled trials (RCTs) to compare no reinforcement (NR), suture oversewing (SR), glue reinforcement (GR), bioabsorbable staple line reinforcement (Gore® Seamguard®) (GoR), and clips reinforcement (CR). Risk Ratio (RR), weighted mean difference (WMD), and 95% credible intervals (CrI) were used as pooled effect size measures.

Results

Overall, 3994 patients (17 RCTs) were included. Of those, 1641 (41.1%) underwent NR, 1507 (37.7%) SR, 689 (17.2%) GR, 107 (2.7%) GoR, and 50 (1.3%) CR. SR was associated with a significantly reduced risk of bleeding (RR=0.51; 95% CrI 0.31–0.88), staple line leak (RR=0.56; 95% CrI 0.32–0.99), and overall complications (RR=0.50; 95% CrI 0.30–0.88) compared to NR while no differences were found vs. GR, GoR, and CR. Operative time was significantly longer for SR (WMD=16.2; 95% CrI 10.8–21.7), GR (WMD=15.0; 95% CrI 7.7–22.4), and GoR (WMD=15.5; 95% CrI 5.6–25.4) compared to NR. Among treatments, there were no significant differences for surgical site infection (SSI), sleeve stenosis, reoperation, hospital length of stay, and 30-day mortality.

Conclusions

SR seems associated with a reduced risk of bleeding, leak, and overall complications compared to NR while no differences were found vs. GR, GoR, and CR. Data regarding GoR and CR are limited while further trials reporting outcomes for these techniques are warranted.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s11695-022-05950-z.

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.

Innovative Pediatric Development for Secukinumab in Psoriasis: Faster Patient Access, Reduction of Patients on Control

This manuscript describes the innovative pediatric development strategy of secukinumab in psoriasis. Initially, this pediatric development had been planned early during the adult development program. This is common for most development programs as it is required by law in major regions worldwide. At that time, only limited experience with secukinumab's mechanism of action was available, especially in the pediatric population for which no data had been collected yet. Pediatric extrapolation frameworks were not in use. As a result, a standard pediatric program had initially been proposed requiring two relatively large placebo-controlled pivotal trials. However, as experience with the use of secukinumab grew, so did experience with - and regulatory openness to - innovative quantitative approaches such as extrapolation. It became clear that the pediatric development of secukinumab could be substantially accelerated by these novel ideas. Here we report how these concepts were implemented in the pediatric development program of secukinumab in psoriasis, using a wide range of innovative quantitative techniques. This strategy led to the removal of the placebo arm from one trial, a substantial reduction of the overall sample size in this program, and a significantly faster approval of secukinumab for the pediatric psoriasis population.

Improving the assessment of the probability of success in late stage drug development

There are several steps to confirming the safety and efficacy of a new medicine. A sequence of trials, each with its own objectives, is usually required. Quantitative risk metrics can be useful for informing decisions about whether a medicine should transition from one stage of development to the next. To obtain an estimate of the probability of regulatory approval, pharmaceutical companies may start with industry-wide success rates and then apply to these subjective adjustments to reflect program-specific information. However, this approach lacks transparency and fails to make full use of data from previous clinical trials. We describe a quantitative Bayesian approach for calculating the probability of success (PoS) at the end of phase II which incorporates internal clinical data from one or more phase IIb studies, industry-wide success rates, and expert opinion or external data if needed. Using an example, we illustrate how PoS can be calculated accounting for differences between the phase II data and future phase III trials, and discuss how the methods can be extended to accommodate accelerated drug development pathways.

Combining cox regressions across a heterogeneous distributed research network facing small and zero counts

Studies of the effects of medical interventions increasingly take place in distributed research settings using data from multiple clinical data sources including electronic health records and administrative claims. In such settings, privacy concerns typically prohibit sharing of individual patient data, and instead, cross-network analyses can only utilize summary statistics from the individual databases such as hazard ratios and standard errors. In the specific but very common context of the Cox proportional hazards model, we show that combining such per site summary statistics into a single network-wide estimate using standard meta-analysis methods leads to substantial bias when outcome counts are small. This bias derives primarily from the normal approximations of the per site likelihood that the methods utilized. Here we propose and evaluate methods that eschew normal approximations in favor of three more flexible approximations: a skew-normal, a one-dimensional grid, and a custom parametric function that mimics the behavior of the Cox likelihood function. In extensive simulation studies, we demonstrate how these approximations impact bias in the context of both fixed-effects and (Bayesian) random-effects models. We then apply these approaches to three real-world studies of the comparative safety of antidepressants, each using data from four observational health care databases.

The likelihood of severe COVID-19 outcomes among PLHIV with various comorbidities: a comparative frequentist and Bayesian meta-analysis approach

Introduction

The SARS‐CoV‐2 virus can currently pose a serious health threat and can lead to severe COVID‐19 outcomes, especially for populations suffering from comorbidities. Currently, the data available on the risk for severe COVID‐19 outcomes due to an HIV infection with or without comorbidities paint a heterogenous picture. In this meta‐analysis, we summarized the likelihood for severe COVID‐19 outcomes among people living with HIV (PLHIV) with or without comorbidities.

Methods

Following PRISMA guidelines, we utilized PubMed, Web of Science and medRxiv to search for studies describing COVID‐19 outcomes in PLHIV with or without comorbidities up to 25 June 2021. Consequently, we conducted two meta‐analyses, based on a classic frequentist and Bayesian perspective of higher quality studies.

Results and discussion

We identified 2580 studies (search period: January 2020–25 June 2021, data extraction period: 1 January 2021–25 June 2021) and included nine in the meta‐analysis. Based on the frequentist meta‐analytical model, PLHIV with diabetes had a seven times higher risk of severe COVID‐19 outcomes (odd ratio, OR = 6.69, 95% CI: 3.03–19.30), PLHIV with hypertension a four times higher risk (OR = 4.14, 95% CI: 2.12–8.17), PLHIV with cardiovascular disease an odds ratio of 4.75 (95% CI: 1.89–11.94), PLHIV with respiratory disease an odds ratio of 3.67 (95% CI: 1.79–7.54) and PLHIV with chronic kidney disease an OR of 9.02 (95% CI: 2.53–32.14) compared to PLHIV without comorbidities. Both meta‐analytic models converged, thereby providing robust summative evidence. The Bayesian meta‐analysis produced similar effects overall, with the exclusion of PLHIV with respiratory diseases who showed a non‐significant higher risk to develop severe COVID‐19 outcomes compared to PLHIV without comorbidities.

Conclusions

Our meta‐analyses show that people with HIV, PLHIV with coexisting diabetes, hypertension, cardiovascular disease, respiratory disease and chronic kidney disease are at a higher likelihood of developing severe COVID‐19 outcomes. Bayesian analysis helped to estimate small sample biases and provided predictive likelihoods. Clinical practice should take these risks due to comorbidities into account and not only focus on the HIV status alone, vaccination priorities should be adjusted accordingly.

Interventions to decrease complications after shoulder dystocia: a systematic review and Bayesian meta-analysis

OBJECTIVE

This study aimed to evaluate the outcomes associated with the implementation of simulation exercises to reduce the sequela of shoulder dystocia.

DATA SOURCES

Electronic databases (Ovid MEDLINE, Embase, the Cumulative Index to Nursing and Allied Health Literature database, and Scopus) were initially queried in June 2020 and updated in November 2020. The following 3 concepts were introduced and refined using the controlled vocabulary of the database: vaginal birth, shoulder dystocia, and simulation training. There were no limitations to the year of publication as part of the search strategy.

STUDY ELIGIBILITY CRITERIA

We included all studies that reported on the frequency of shoulder dystocia and the associated complications before and after the implementation of interventional exercises to improve outcomes.

METHODS

Two authors independently assessed the abstracts and full-text articles of all studies for eligibility and evaluated the quality of the included studies using the Newcastle-Ottawa Scale. Any inconsistencies related to study evaluation or data extraction were resolved by a third author. The coprimary outcomes of this systematic review and meta-analysis were neonatal brachial plexus palsy diagnosed following deliveries complicated by shoulder dystocia and persistence of brachial palsy at 12 months or later. The secondary outcomes were the frequency of shoulder dystocia and cesarean delivery. Study effects were combined using a Bayesian meta-analysis and were reported as risk ratios and 95% credible intervals (Crs).

RESULTS

Of the 372 articles reviewed, 16 publications, which included 428,552 deliveries with 217,713 (50.8%) deliveries during the preintervention and 210,839 (49.2%) deliveries during the postinterventional period, were included in the meta-analysis. The incidence of neonatal brachial plexus palsy after shoulder dystocia decreased from 12.1% to 5.7% (risk ratio, 0.37; 95% Cr, 0.26-0.57; probability of reduction 100%). The overall proportion of neonatal brachial plexus palsy decreased, but with less precision, from 0.3% to 0.1% (risk ratio, 0.53; 95% Cr, 0.21-1.26; probability of reduction 94%). Two studies followed newborns with brachial plexus palsy for at least 12 months. One study that reported on persistent neonatal brachial plexus palsy at 12 months among 1148 shoulder dystocia cases noted a reduction in persistent neonatal brachial plexus palsy from 1.9% to 0.2% of shoulder dystocia cases (risk ratio, 0.13; 95% confidence interval, 0.04-0.49). In contrast, the study that reported on persistent neonatal brachial plexus palsy at 12 months for all deliveries noted that it did not change significantly, namely from 0.3 to 0.2 per 1000 births (risk ratio, 0.77; 95% confidence interval, 0.31-1.90). Following the implementation of shoulder dystocia interventional exercises, the diagnosis of shoulder dystocia increased significantly from 1.2% to 1.7% of vaginal deliveries (risk ratio, 1.39; 95% Cr, 1.19-1.65; probability of increase 100%). Compared with the preimplementation period, the cesarean delivery rate increased postimplementation from 21.2% to 25.9% (risk ratio, 1.22; 95% Cr, 0.93-1.59; probability of increase 93%). We created an online tool (https://ccrebm-bell.shinyapps.io/sdmeta/) that permits calculation of the absolute risk reduction and absolute risk increase attributable to the intervention vis-à-vis the incidence of shoulder dystocia, neonatal brachial plexus palsy, and cesarean deliveries.

CONCLUSION

Introduction of shoulder dystocia interventional exercises decreased the rate of neonatal brachial plexus palsy per shoulder dystocia case; the data on persistence of neonatal brachial plexus palsy beyond 12 months is limited and contradictory. Implementation of the interventions was associated with an increase in the diagnosis of shoulder dystocia and rate of cesarean deliveries.

Meta-analyses of deflazacort versus prednisone/prednisolone in patients with nonsense mutation Duchenne muscular dystrophy

Aim: Compare efficacies of deflazacort and prednisone/prednisolone in providing clinically meaningful delays in loss of physical milestones in patients with nonsense mutation Duchenne muscular dystrophy. Materials & methods: Placebo data from Phase IIb (ClinicalTrials.gov Identifier: NCT00592553) and ACT DMD (ClinicalTrials.gov Identifier: NCT01826487) ataluren nonsense mutation Duchenne muscular dystrophy clinical trials were retrospectively combined in meta-analyses (intent-to-treat population; for change from baseline to week 48 in 6-min walk distance [6MWD] and timed function tests). Results: Significant improvements in change in 6-min walk distance with deflazacort versus prednisone/prednisolone (least-squares mean difference 39.54 m [95% CI: 13.799, 65.286; p = 0.0026]). Significant and clinically meaningful improvements in 4-stair climb and 4-stair descend for deflazacort versus prednisone/prednisolone. Conclusion: Deflazacort provides clinically meaningful delays in loss of physical milestones over 48 weeks compared with prednisone/prednisolone for patients with nonsense mutation Duchenne muscular dystrophy.

Subgroup identification in individual participant data meta-analysis using model-based recursive partitioning

Model-based recursive partitioning (MOB) can be used to identify subgroups with differing treatment effects. The detection rate of treatment-by-covariate interactions and the accuracy of identified subgroups using MOB depend strongly on the sample size. Using data from multiple randomized controlled clinical trials can overcome the problem of too small samples. However, naively pooling data from multiple trials may result in the identification of spurious subgroups as differences in study design, subject selection and other sources of between-trial heterogeneity are ignored. In order to account for between-trial heterogeneity in individual participant data (IPD) meta-analysis random-effect models are frequently used. Commonly, heterogeneity in the treatment effect is modelled using random effects whereas heterogeneity in the baseline risks is modelled by either fixed effects or random effects. In this article, we propose metaMOB, a procedure using the generalized mixed-effects model tree (GLMM tree) algorithm for subgroup identification in IPD meta-analysis. Although the application of metaMOB is potentially wider, e.g. randomized experiments with participants in social sciences or preclinical experiments in life sciences, we focus on randomized controlled clinical trials. In a simulation study, metaMOB outperformed GLMM trees assuming a random intercept only and model-based recursive partitioning (MOB), whose algorithm is the basis for GLMM trees, with respect to the false discovery rates, accuracy of identified subgroups and accuracy of estimated treatment effect. The most robust and therefore most promising method is metaMOB with fixed effects for modelling the between-trial heterogeneity in the baseline risks.

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.

A systematic review and meta-analysis of the association between expressive suppression and positive affect

People differ in their self-reported propensities to experience positive affect (PA). Even those prone to internalizing symptoms show varied proclivities to PA; social anxiety (SA), for instance, unlike other types of anxiety, shows a strong negative association with PA that cannot be explained by diminished reward sensitivity. Heightened reliance on suppression of emotional displays (expressive suppression; ES) may be an alternate contributor to attenuated PA among people with elevated SA, relative to people with other types of anxiety. A first step toward testing this hypothesis is clarifying the ES-PA association and examining whether it varies as a function of anxiety type (social anxiety vs. other types of anxiety). This meta-analysis (k = 41; n = 11,010) revealed a significant, negative association between ES and PA (r = -0.158); however, this relationship was not significant for individuals with social or other anxiety disorders. Moreover, two moderators (sample culture-Western: r = -0.16; Eastern: r = 0.003; type of emotion suppressed-Negative: r = 0.18; Positive: r = -0.12) accounted for significant heterogeneity in effect sizes. This review synthesizes the literature on ES and PA in healthy and anxious samples; findings suggest moderating variables merit closer attention in future studies.

Exploring consequences of simulation design for apparent performance of methods of meta-analysis

Contemporary statistical publications rely on simulation to evaluate performance of new methods and compare them with established methods. In the context of random-effects meta-analysis of log-odds-ratios, we investigate how choices in generating data affect such conclusions. The choices we study include the overall log-odds-ratio, the distribution of probabilities in the control arm, and the distribution of study-level sample sizes. We retain the customary normal distribution of study-level effects. To examine the impact of the components of simulations, we assess the performance of the best available inverse-variance-weighted two-stage method, a two-stage method with constant sample-size-based weights, and two generalized linear mixed models. The results show no important differences between fixed and random sample sizes. In contrast, we found differences among data-generation models in estimation of heterogeneity variance and overall log-odds-ratio. This sensitivity to design poses challenges for use of simulation in choosing methods of meta-analysis.

Systematic review and updated network meta-analysis of randomized controlled trials comparing open, laparoscopic-assisted, and robotic distal gastrectomy for early and locally advanced gastric cancer

BACKGROUND

The role of minimally invasive surgery for the treatment of early and locally advanced gastric cancer remains controversial. The purpose of this study was to perform a comprehensive evaluation of major surgical approaches for operable distal gastric cancer.

METHODS

Systematic review and network meta-analyses of randomized controlled trials were performed to compare open distal gastrectomy, laparoscopic-assisted distal gastrectomy, and robotic distal gastrectomy. Risk ratio, weighted mean difference, and 95% credible intervals were used as pooled effect size measures.

RESULTS

Seventeen randomized controlled trials (5,909 patients) were included. Overall, 2,776 (46.8%) underwent open distal gastrectomy, 2,964 (50.1%) laparoscopic-assisted distal gastrectomy, and 141 (3.1%) robotic distal gastrectomy. Among these 3 groups, there were no significant differences in 30-day mortality, anastomotic leak, and overall complications. Compared to open distal gastrectomy, laparoscopic-assisted distal gastrectomy was associated with significantly reduced intraoperative blood loss, early postoperative pain, time to first flatus, and hospital length of stay. Similarly, robotic distal gastrectomy was associated with significantly reduced blood loss and time to first flatus compared to open distal gastrectomy. No differences were found in the total number of harvested lymph nodes, tumor-free resection margins, 5-year overall, and disease-free survival. The subgroup analysis in locally advanced gastric cancer showed trends toward reduced blood loss, time to first flatus, and hospital length of stay with minimally invasive approaches but similar overall and disease-free survival.

CONCLUSION

Laparoscopic-assisted distal gastrectomy and robotic distal gastrectomy performed by well-trained experienced surgeons, even in the setting of locally advanced gastric cancer, seem associated with improved short-term outcomes with similar overall and disease-free survival compared with open distal gastrectomy.