GetReal in network meta-analysis: a review of the methodology

Mortality and bleeding associated with the management of sub-massive pulmonary embolism: a systematic review and Bayesian network meta-analysis

Current guidelines recommend anticoagulation (AC) for low and intermediate-risk pulmonary embolism (PE) and systemic thrombolysis (tPA) for high risk (massive) PE. How these treatment options compare with other modalities of treatment such as catheter directed thrombolysis (CDT), ultrasound assisted catheter thrombolysis (USAT), and administering lower dose of thrombolytics (LDT) is unclear. There is no study that has compared all these treatment options. We conducted a systematic review and Bayesian network meta-analysis of randomized controlled trials in patients with submassive (intermediate risk) PE. Fourteen randomized controlled trials were included, comprising 2132 patients. On Bayesian network meta-analysis, a significant decrease in mortality was noted in tPA versus AC. There was no significant difference between USAT versus CDT. For risk of major bleeding, there was no significant difference in relative risk of major bleeding between tPA versus AC and USAT versus CDT. tPA was found to have a significantly higher risk of minor bleeding and a lower risk of recurrent PE compared to AC. Systemic thrombolysis is associated with a significant reduction in mortality and recurrent PE compared to anticoagulation but an increased risk of minor bleeding. There was no difference in risk of major bleeding. Our study also shows that while the newer modalities of treatment for pulmonary embolism are promising, there is lack of data to comment on the purported advantages.

Measuring the performance of prediction models to personalize treatment choice

When data are available from individual patients receiving either a treatment or a control intervention in a randomized trial, various statistical and machine learning methods can be used to develop models for predicting future outcomes under the two conditions, and thus to predict treatment effect at the patient level. These predictions can subsequently guide personalized treatment choices. Although several methods for validating prediction models are available, little attention has been given to measuring the performance of predictions of personalized treatment effect. In this article, we propose a range of measures that can be used to this end. We start by defining two dimensions of model accuracy for treatment effects, for a single outcome: discrimination for benefit and calibration for benefit. We then amalgamate these two dimensions into an additional concept, decision accuracy, which quantifies the model's ability to identify patients for whom the benefit from treatment exceeds a given threshold. Subsequently, we propose a series of performance measures related to these dimensions and discuss estimating procedures, focusing on randomized data. Our methods are applicable for continuous or binary outcomes, for any type of prediction model, as long as it uses baseline covariates to predict outcomes under treatment and control. We illustrate all methods using two simulated datasets and a real dataset from a trial in depression. We implement all methods in the R package predieval. Results suggest that the proposed measures can be useful in evaluating and comparing the performance of competing models in predicting individualized treatment effect.

Surgical treatment of patellar dislocation: A network meta-analysis of randomized control trials and cohort studies

Background

Currently, there are many surgical options for patellar dislocation. The purpose of this study is to perform a network meta-analysis of the randomized controlled trials (RCTs) and cohort studies to determine the better treatment.

Method

We searched the Pubmed, Embase, Cochrane Central Register of Controlled Trials, Web of Science, clinicaltrials.gov and who.int/trialsearch. Clinical outcomes included Kujala score, Lysholm score, International Knee Documentation Committee (IKDC) score, redislocation or recurrent instability. We conducted pairwise meta-analysis and network meta-analysis respectively using the frequentist model to compare the clinical outcomes.

Results

There were 10 RCTs and 2 cohort studies with a total of 774 patients included in our study. In network meta-analysis, double-bundle medial patellofemoral ligament reconstruction (DB-MPFLR) achieved good results on functional scores. According to the surface under the cumulative ranking (SUCRA), DB-MPFLR had the highest probabilities of their protective effects on outcomes of Kujala score (SUCRA 96.5 %), IKDC score (SUCRA 100.0%) and redislocation (SUCRA 67.8%). However, DB-MPFLR (SUCRA 84.6%) comes second to SB-MPFLR (SUCRA 90.4%) in Lyshlom score. It is (SUCRA 70%) also inferior to vastus medialis plasty (VM-plasty) (SUCRA 81.9%) in preventing Recurrent instability. The results of subgroup analysis were similar.

Conclusion

Our study demonstrated that MPFLR showed better functional scores than other surgical options.

Accuracies of various types of spinal robot in robot-assisted pedicle screw insertion: a Bayesian network meta-analysis

BACKGROUND

With the popularization of robot-assisted spinal surgeries, it is still uncertain whether robots with different designs could lead to different results in the accuracy of pedicle screw placement. This study aimed to compare the pedicle screw inserting accuracies among the spinal surgeries assisted by various types of robot and estimate the rank probability of each robot-assisted operative technique involved.

METHODS

The electronic literature database of PubMed, Web of Science, EMBASE, CNKI, WANFANG and the Cochrane Library was searched in November 2021. The primary outcome was the Gertzbein-Robbins classification of pedicle screws inserted with various operative techniques. After the data extraction and direct meta-analysis process, a network model was established in the Bayesian framework and further analyses were carried out.

RESULTS

Among all the 15 eligible RCTs, 4 types of robot device, namely Orthbot, Renaissance, SpineAssist and TiRobot, were included in this study. In the network meta-analysis, the Orthbot group (RR 0.27, 95% CI 0.13-0.58), the Renaissance group (RR 0.33, 95% CI 0.14-0.86), the SpineAssist group (RR 0.14, 95% CI 0.06-0.34) and the conventional surgery group (RR 0.21, 95% CI 0.13-0.31) were inferior to the TiRobot group in the proportion of grade A pedicle screws. Moreover, the results of rank probabilities revealed that in terms of accuracy, the highest-ranked robot was TiRobot, followed by Renaissance and Orthbot.

CONCLUSIONS

In general, current RCT evidence indicates that TiRobot has an advantage in the accuracy of the pedicle screw placement, while there is no significant difference among the Orthbot-assisted technique, the Renaissance-assisted technique, the conventional freehand technique, and the SpineAssist-assisted technique in accuracy.

Comparative effectiveness of different types of exercise in reducing arterial stiffness in children and adolescents: a systematic review and network meta-analysis

OBJECTIVE

Arterial stiffness is an early and detectable marker of vascular changes leading to atherosclerotic cardiovascular disease (ACVD). Our objective was to compare the effectiveness of different types of exercise in reducing arterial stiffness in children and adolescents.

DESIGN

A systematic review and network meta-analysis (NMA) was conducted including experimental studies reporting the effects of exercise interventions on pulse wave velocity (PWV) in children and adolescents.

DATA SOURCES

Cochrane Central Register of Controlled Trials, EMBASE (via Scopus), PubMed (via Medline) and Web of Science from database inception to 25 March 2022.

ELIGIBILITY CRITERIA

Experimental studies reporting the effects of exercise interventions on PWV in children and adolescents.

RESULTS

Fourteen studies were included in the NMA, all of them were randomised controlled trials except one quasi-experimental study, with an overall risk of bias of some concern. Regarding PWV reduction, all exercise modalities were more effective than control, with standardised mean difference ranging from -1.93 (95% CI: -2.84 to -1.02) and -1.11 (95% CI: -2.01 to -0.21) for aerobic exercise and high intensity interval training (HIIT), respectively, to -0.59 (95% CI: -1.39 to 0.22) for combined exercise. Only sensorimotor training was not superior to the control group 0.11 (95% CI: -1.10 to 1.32).

CONCLUSION

Our results support that exercise interventions, especially aerobic exercise or HIIT, can improve arterial stiffness at early ages. The potential to address ACVD early and mitigate long-term consequences via exercise interventions in children and adolescents with higher arterial stiffness requires further investigation.

PROSPERO REGISTRATION NUMBER

CRD42022322536.

Cardiovascular disease and type 2 diabetes in older adults: a combined protocol for an individual participant data analysis for risk prediction and a network meta-analysis of novel anti-diabetic drugs

Introduction

Older and multimorbid adults with type 2 diabetes (T2D) are at high risk of cardiovascular disease (CVD) and chronic kidney disease (CKD). Estimating risk and preventing CVD is a challenge in this population notably because it is underrepresented in clinical trials. Our study aims to (1) assess if T2D and haemoglobin A1c (HbA1c) are associated with the risk of CVD events and mortality in older adults, (2) develop a risk score for CVD events and mortality for older adults with T2D, (3) evaluate the comparative efficacy and safety of novel antidiabetics.

Methods and analysis

For Aim 1, we will analyse individual participant data on individuals aged ≥65 years from five cohort studies: the Optimising Therapy to Prevent Avoidable Hospital Admissions in Multimorbid Older People study; the Cohorte Lausannoise study; the Health, Aging and Body Composition study; the Health and Retirement Study; and the Survey of Health, Ageing and Retirement in Europe. We will fit flexible parametric survival models (FPSM) to assess the association of T2D and HbA1c with CVD events and mortality. For Aim 2, we will use data on individuals aged ≥65 years with T2D from the same cohorts to develop risk prediction models for CVD events and mortality using FPSM. We will assess model performance, perform internal-external cross validation, and derive a point-based risk score. For Aim 3, we will systematically search randomized controlled trials of novel antidiabetics. Network meta-analysis will be used to determine comparative efficacy in terms of CVD, CKD, and retinopathy outcomes, and safety of these drugs. Confidence in results will be judged using the CINeMA tool.

Ethics and dissemination

Aims 1 and 2 were approved by the local ethics committee (Kantonale Ethikkommission Bern); no approval is required for Aim 3. Results will be published in peer-reviewed journals and presented in scientific conferences.

Synthesizing cross-design evidence and cross-format data using network meta-regression

In network meta-analysis (NMA), we synthesize all relevant evidence about health outcomes with competing treatments. The evidence may come from randomized clinical trials (RCT) or non-randomized studies (NRS) as individual participant data (IPD) or as aggregate data (AD). We present a suite of Bayesian NMA and network meta-regression (NMR) models allowing for cross-design and cross-format synthesis. The models integrate a three-level hierarchical model for synthesizing IPD and AD into four approaches. The four approaches account for differences in the design and risk of bias (RoB) in the RCT and NRS evidence. These four approaches variously ignoring differences in RoB, using NRS to construct penalized treatment effect priors and bias-adjustment models that control the contribution of information from high RoB studies in two different ways. We illustrate the methods in a network of three pharmacological interventions and placebo for patients with relapsing-remitting multiple sclerosis. The estimated relative treatment effects do not change much when we accounted for differences in design and RoB. Conducting network meta-regression showed that intervention efficacy decreases with increasing participant age. We also re-analysed a network of 431 RCT comparing 21 antidepressants, and we did not observe material changes in intervention efficacy when adjusting for studies' high RoB. We re-analysed both case studies accounting for different study RoB. In summary, the described suite of NMA/NMR models enables the inclusion of all relevant evidence while incorporating information on the within-study bias in both observational and experimental data and enabling estimation of individualized treatment effects through the inclusion of participant characteristics.

Bias propagation in network meta-analysis models

Network meta-analysis combines direct and indirect evidence to compare multiple treatments. As direct evidence for one treatment contrast may be indirect evidence for other treatment contrasts, biases in the direct evidence for one treatment contrast may affect not only the estimate for this particular treatment contrast but also estimates of other treatment contrasts. Because network structure determines how direct and indirect evidence are combined and weighted, the impact of biased evidence will be determined by the network geometry. Thus, this study's aim was to investigate how the impact of biased evidence spreads across the whole network and how the propagation of bias is influenced by the network structure. In addition to the popular Lu & Ades model, we also investigate bias propagation in the baseline model and arm-based model to compare the effects of bias in the different models. We undertook extensive simulations under different scenarios to explore how the impact of bias may be affected by the location of the bias, network geometry and the statistical model. Our results showed that the structure of a network has an important impact on how the bias spreads across the network, and this is especially true for the Lu & Ades model. The impact of bias is more likely to be diluted by other unbiased evidence in a well-connected network. We also used a real network meta-analysis to demonstrate how to use the new knowledge about bias propagation to explain questionable results from the original analysis.

Bayesian hierarchical model-based network meta-analysis to overcome survival extrapolation challenges caused by data immaturity

Aim: This research evaluated standard Weibull mixture cure (WMC) network meta-analysis (NMA) with Bayesian hierarchical (BH) WMC NMA to inform long-term survival of therapies. Materials & methods: Four trials in previously treated metastatic non-small-cell lung cancer with PD-L1 >1% were used comparing docetaxel with nivolumab, pembrolizumab and atezolizumab. Cure parameters related to a certain treatment class were assumed to share a common distribution. Results: Standard WMC NMA predicted cure rates were 0.03 (0.01; 0.07), 0.18 (0.12; 0.24), 0.07 (0.02; 0.15) and 0.03 (0.00; 0.09) for docetaxel, nivolumab, pembrolizumab and atezolizumab, respectively, with corresponding incremental life years (LY) of 3.11 (1.65; 4.66), 1.06 (0.41; 2.37) and 0.42 (-0.57; 1.68). The Bayesian hierarchical-WMC-NMA rates were 0.06 (0.03; 0.10), 0.17 (0.11; 0.23), 0.12 (0.05; 0.20) and 0.12 (0.03; 0.23), respectively, with incremental LY of 2.35 (1.04; 3.93), 1.67 (0.68; 2.96) and 1.36 (-0.05; 3.64). Conclusion: BH-WMC-NMA impacts incremental mean LYs and cost-effectiveness ratios, potentially affecting reimbursement decisions.

Two Intramedullary and 1 Extramedullary Cortical Button, With or Without Interference Screw, Show Biomechanical Properties Superior to Native Tendon in Repair of the Distal Biceps Tendon: A Systematic Review and Network Meta-analysis of Biomechanical Performance

PURPOSE

The aim of this study was to use a systematic review and network meta-analysis (NMA) to compare the failure strength, maximum strength, stiffness, and displacement of available constructs for distal biceps repair.

METHODS

An NMA was conducted to determine the performance of 2 all-suture suture anchors (2x ASA), 2 intramedullary cortical buttons (2x IM CB), 2 suture anchors (2x SA), extramedullary cortical buttons (EM CB), extramedullary cortical button plus interference screw (EM CB+IFS), interference screw (IFS), single intramedullary cortical button (IM CB), single suture anchor (SA), transosseous suture (TOS), tension slide technique (TST), and tension slide technique plus suture tape (TST+ST). Analysis consisted of arm-based network meta-analysis under Bayesian random-effects model with Markov Chain Monte Carlo (MCMC) sampling. Biomechanical outcomes were summarized as treatment effects and their corresponding 95% confidence intervals (CI). Rank probabilities were calculated and used to generate each treatment's surface under the cumulative ranking (SUCRA) curve. Biomechanical properties were compared to native tendon. Displacement >10 mm was defined as clinical failure.

RESULTS

Twenty-one studies were included. For failure strength, no construct outperformed the native tendon but 2× SA, IFS, SA, and TOS demonstrated poorer failure strength. For the maximum load to failure, EM CB+IFS outperformed the native tendon. Compared to native tendon, EM CB+IFS, EM CB, and 2×IM CB were stiffer, while 2x SA and IFS were less stiff. No construct demonstrated >10 mm of displacement, but constructs with displacement above the mean (3.5 mm) included 2× ASA, 2xIM CB, and TOS.

CONCLUSIONS

The fixation constructs that consistently demonstrated comparable or better biomechanical properties (failure strength, maximum strength, and stiffness) to native tendon in distal biceps tendon repair were the extramedullary cortical button with or without interference screw and two intramedullary cortical buttons. No construct demonstrated displacement beyond standard definitions for clinical failure.

CLINICAL RELEVANCE

This network meta-analysis of biomechanical studies suggests that extramedullary cortical button and two intramedullary cortical buttons may be the most stable construct for distal biceps repair fixation, with equivalent or better biomechanical properties compared to native tendon.

Crossroads of methodological choices in research synthesis: insights from two network meta-analyses on preventing relapse in schizophrenia

In recent years, network meta-analyses have been increasingly carried out to inform clinical guidelines and policy. This approach is under constant development, and a broad consensus on how to carry out several of its methodological and statistical steps is still lacking. Therefore, different working groups might often make different methodological choices based on their clinical and research experience, with possible advantages and shortcomings. In this contribution, we will critically assess two network meta-analyses on the topic of pharmacological prevention of relapse in schizophrenia, carried out by two different research groups. We will highlight the implications of different methodological choices on the analysis results and their clinical-epidemiological interpretation. Moreover, we will discuss some of the most relevant technical issues of network meta-analyses for which there is not a broad methodological agreement, including the assessment of transitivity.

The Association between Baseline Proton Pump Inhibitors, Immune Checkpoint Inhibitors, and Chemotherapy: A Systematic Review with Network Meta-Analysis

(1) Although emerging evidence suggests that proton pump inhibitor (PPI)-induced dysbiosis negatively alters treatment response to immune checkpoint inhibitors (ICIs) in cancer patients, no study systematically investigates the association between PPIs, ICIs, and chemotherapy; (2) Cochrane Library, Embase, Medline, and PubMed were searched from inception to 20 May 2022, to identify relevant studies involving patients receiving ICIs or chemotherapy and reporting survival outcome between PPI users and non-users. Survival outcomes included overall survival (OS) and progression-free survival (PFS). Network meta-analyses were performed using random-effects models. p-scores, with a value between 0 and 1, were calculated to quantify the treatment ranking, with a higher score suggesting a higher probability of greater effectiveness. We also conducted pairwise meta-analyses of observational studies to complement our network meta-analysis; (3) We identified 62 studies involving 26,484 patients (PPI = 8834; non-PPI = 17,650), including non-small cell lung cancer (NSCLC), urothelial carcinoma (UC), melanoma, renal cell carcinoma (RCC), hepatocellular carcinoma (HCC), and squamous cell carcinoma (SCC) of the neck and head. Eight post-hoc analyses from 18 randomized-controlled trials were included in our network, which demonstrated that, in advanced NSCLC and UC, patients under ICI treatment with concomitant PPI (p-score: 0.2016) are associated with both poorer OS (HR, 1.49; 95% CI, 1.37 to 1.67) and poorer PFS (HR, 1.41; 95% CI, 1.25 to 1.61) than those without PPIs (p-score: 1.000). Patients under ICI treatment with concomitant PPI also had poorer OS (HR, 1.18; 95% CI, 1.07 to 1.31) and poorer PFS (HR, 1.30; 95% CI, 1.14 to 1.48) in comparison with those receiving chemotherapy (p-score: 0.6664), implying that PPIs may compromise ICI's effectiveness, making it less effective than chemotherapy. Our pairwise meta-analyses also supported this association. Conversely, PPI has little effect on patients with advanced melanoma, RCC, HCC, and SCC of the neck and head who were treated with ICIs; (4) "PPI-induced dysbiosis" serves as a significant modifier of treatment response in both advanced NSCLC and UC that are treated with ICIs, compromising the effectiveness of ICIs to be less than that of chemotherapy. Thus, clinicians should avoid unnecessary PPI prescription in these patients. "PPI-induced dysbiosis", on the other hand, does not alter the treatment response to ICIs in advanced melanoma, RCC, HCC, and SCC of the head and neck.

Management of Chronic Subdural Hematoma: A Systematic Review and Component Network Meta-analysis of 455 Studies With 103 645 Cases

BACKGROUND

Chronic subdural hematoma (CSDH) is a common neurosurgical condition with a high risk of recurrence after treatment.

OBJECTIVE

To assess and compare the risk of recurrence, morbidity, and mortality across various treatments for CSDH.

METHODS

A systematic review and meta-analysis was performed. PubMed/MEDLINE, EMBASE, SCOPUS, and Web of Science were searched from January 01, 2000, to July 07, 2021. The primary outcome was recurrence, and secondary outcomes were morbidity and mortality. Component network meta-analyses (CNMAs) were performed for surgical and medical treatments, assessing recurrence and morbidity. Incremental risk ratios (iRRs) with 95% CIs were estimated for each component.

RESULTS

In total, 12 526 citations were identified, and 455 studies with 103 645 cases were included. Recurrence occurred in 11 491/93 525 (10.8%, 95% CI 10.2-11.5, 418 studies) cases after surgery. The use of a postoperative drain (iRR 0.53, 95% CI 0.44-0.63) and middle meningeal artery embolization (iRR 0.19, 95% CI 0.05-0.83) reduced recurrence in the surgical CNMA. In the pharmacological CNMA, corticosteroids (iRR 0.47, 95% CI 0.36-0.61) and surgical intervention (iRR 0.11, 95% CI 0.07-0.15) were associated with lower risk. Corticosteroids were associated with increased morbidity (iRR 1.34, 95% CI 1.05-1.70). The risk of morbidity was equivalent across surgical treatments.

CONCLUSION

Recurrence after evacuation occurs in approximately 10% of cSDHs, and the various surgical interventions are approximately equivalent. Corticosteroids are associated with reduced recurrence but also increased morbidity. Drains reduce the risk of recurrence, but the position of drain (subdural vs subgaleal) did not influence recurrence. Middle meningeal artery embolization is a promising treatment warranting further evaluation in randomized trials.

Precision rehabilitation for aphasia by patient age, sex, aphasia severity, and time since stroke? A prespecified, systematic review-based, individual participant data, network, subgroup meta-analysis

BACKGROUND

Stroke rehabilitation interventions are routinely personalized to address individuals' needs, goals, and challenges based on evidence from aggregated randomized controlled trials (RCT) data and meta-syntheses. Individual participant data (IPD) meta-analyses may better inform the development of precision rehabilitation approaches, quantifying treatment responses while adjusting for confounders and reducing ecological bias.

AIM

We explored associations between speech and language therapy (SLT) interventions frequency (days/week), intensity (h/week), and dosage (total SLT-hours) and language outcomes for different age, sex, aphasia severity, and chronicity subgroups by undertaking prespecified subgroup network meta-analyses of the RELEASE database.

METHODS

MEDLINE, EMBASE, and trial registrations were systematically searched (inception-Sept2015) for RCTs, including ⩾ 10 IPD on stroke-related aphasia. We extracted demographic, stroke, aphasia, SLT, and risk of bias data. Overall-language ability, auditory comprehension, and functional communication outcomes were standardized. A one-stage, random effects, network meta-analysis approach filtered IPD into a single optimal model, examining SLT regimen and language recovery from baseline to first post-intervention follow-up, adjusting for covariates identified a-priori. Data were dichotomized by age (⩽/> 65 years), aphasia severity (mild-moderate/ moderate-severe based on language outcomes' median value), chronicity (⩽/> 3 months), and sex subgroups. We reported estimates of means and 95% confidence intervals. Where relative variance was high (> 50%), results were reported for completeness.

RESULTS

959 IPD (25 RCTs) were analyzed. For working-age participants, greatest language gains from baseline occurred alongside moderate to high-intensity SLT (functional communication 3-to-4 h/week; overall-language and comprehension > 9 h/week); older participants' greatest gains occurred alongside low-intensity SLT (⩽ 2 h/week) except for auditory comprehension (> 9 h/week). For both age-groups, SLT-frequency and dosage associated with best language gains were similar. Participants ⩽ 3 months post-onset demonstrated greatest overall-language gains for SLT at low intensity/moderate dosage (⩽ 2 SLT-h/week; 20-to-50 h); for those > 3 months, post-stroke greatest gains were associated with moderate-intensity/high-dosage SLT (3-4 SLT-h/week; ⩾ 50 hours). For moderate-severe participants, 4 SLT-days/week conferred the greatest language gains across outcomes, with auditory comprehension gains only observed for ⩾ 4 SLT-days/week; mild-moderate participants' greatest functional communication gains were associated with similar frequency (⩾ 4 SLT-days/week) and greatest overall-language gains with higher frequency SLT (⩾ 6 days/weekly). Males' greatest gains were associated with SLT of moderate (functional communication; 3-to-4 h/weekly) or high intensity (overall-language and auditory comprehension; (> 9 h/weekly) compared to females for whom the greatest gains were associated with lower-intensity SLT (< 2 SLT-h/weekly). Consistencies across subgroups were also evident; greatest overall-language gains were associated with 20-to-50 SLT-h in total; auditory comprehension gains were generally observed when SLT > 9 h over ⩾ 4 days/week.

CONCLUSIONS

We observed a treatment response in most subgroups' overall-language, auditory comprehension, and functional communication language gains. For some, the maximum treatment response varied in association with different SLT-frequency, intensity, and dosage. Where differences were observed, working-aged, chronic, mild-moderate, and male subgroups experienced their greatest language gains alongside high-frequency/intensity SLT. In contrast, older, moderate-severely impaired, and female subgroups within 3 months of aphasia onset made their greatest gains for lower-intensity SLT. The acceptability, clinical, and cost effectiveness of precision aphasia rehabilitation approaches based on age, sex, aphasia severity, and chronicity should be evaluated in future clinical RCTs.

Network meta-analysis of rare events using penalized likelihood regression

Network meta-analysis (NMA) of rare events has attracted little attention in the literature. Until recently, networks of interventions with rare events were analyzed using the inverse-variance NMA approach. However, when events are rare the normal approximations made by this model can be poor and effect estimates are potentially biased. Other methods for the synthesis of such data are the recent extension of the Mantel-Haenszel approach to NMA or the use of the noncentral hypergeometric distribution. In this article, we suggest a new common-effect NMA approach that can be applied even in networks of interventions with extremely low or even zero number of events without requiring study exclusion or arbitrary imputations. Our method is based on the implementation of the penalized likelihood function proposed by Firth for bias reduction of the maximum likelihood estimate to the logistic expression of the NMA model. A limitation of our method is that heterogeneity cannot be taken into account as an additive parameter as in most meta-analytical models. However, we account for heterogeneity by incorporating a multiplicative overdispersion term using a two-stage approach. We show through simulation that our method performs consistently well across all tested scenarios and most often results in smaller bias than other available methods. We also illustrate the use of our method through two clinical examples. We conclude that our "penalized likelihood NMA" approach is promising for the analysis of binary outcomes with rare events especially for networks with very few studies per comparison and very low control group risks.

Coronary perforation incidence, outcomes and temporal trends (COPIT): a systematic review and meta-analysis

Coronary perforation is a potentially life-threatening complication of percutaneous coronary intervention (PCI). We studied incidence, outcomes and temporal trends following PCI-related coronary artery perforation (CAP).

METHODS

Prospective systematic review and meta-analysis including meta-regression using MEDLINE and EMBASE to November 2020. We included 'all-comer' PCI cohorts including large PCI registries and randomised controlled trials and excluding registries or trials limited to PCI in high-risk populations such as chronic total occlusion PCI or cohorts treated only with atheroablative devices. Regression analysis and corresponding correlation coefficients were performed comparing perforation incidence, mortality rate, tamponade rate and the rate of Ellis III perforations against the midpoint (year) of data collection to determine if a significant temporal relationship was present.

RESULTS

3997 studies were screened for inclusion. 67 studies met eligibility criteria with a total of 5 568 191 PCIs included over a 38-year period (1982-2020). The overall pooled incidence of perforation was 0.39% (95% CI 0.34% to 0.45%) and remained similar throughout the study period. Around 1 in 5 coronary perforations led to tamponade (21.1%). Ellis III perforations are increasing in frequency and account for 43% of all perforations. Perforation mortality has trended lower over the years (7.5%; 95% CI 6.7% to 8.4%). Perforation risk factors derived using meta-regression were female sex, hypertension, chronic kidney disease and previous coronary bypass grafting. Coronary perforation was most frequently caused by distal wire exit (37%) followed by balloon dilation catheters (28%). Covered stents were used to treat 25% of perforations, with emergency cardiac surgery needed in 17%.

CONCLUSION

Coronary perforation complicates approximately 1 in 250 PCIs. Ellis III perforations are increasing in incidence although it is unclear whether this is due to reporting bias. Despite this, the overall perforation mortality rate (7.5%) has trended lower in recent years. Limitations of our findings include bias that may be introduced through analysis of multidesign studies and registries without pre-specified standardised perforation reporting CMore research into coronary perforation management including the optimal use of covered stents seems warranted.

PROSPERO REGISTRATION NUMBER

CRD42020207881.

Comparison of six risk scores for stroke-associated pneumonia in patients with acute ischemic stroke: A systematic review and Bayesian network meta-analysis

Background

Stroke-associated pneumonia (SAP) is one of the major causes of death after suffering a stroke. Several scoring systems have been developed for the early prediction of SAP. However, it is unclear which scoring system is more suitable as a risk prediction tool. We performed this Bayesian network meta-analysis to compare the prediction accuracy of these scoring systems.

Methods

Seven databases were searched from their inception up to April 8, 2022. The risk of bias assessment of included study was evaluated by the QUADAS-C tool. Then, a Bayesian network meta-analysis (NMA) was performed by R 4.1.3 and STATA 17.0 software. The surface under the cumulative ranking curve (SUCRA) probability values were applied to rank the examined scoring systems.

Results

A total of 20 cohort studies involving 42,236 participants were included in this analysis. The results of the NMA showed that AIS-APS had excellent performance in prediction accuracy for SAP than Chumbler (MD = 0.030, 95%CI: 0.004, 0.054), A2DS2 (MD = 0.041, 95% CI: 0.023, 0.059), ISAN (MD = 0.045, 95% CI: 0.022, 0.069), Kwon (MD = 0.077, 95% CI: 0.055, 0.099) and PANTHERIS (MD = 0.082, 95% CI: 0.049, 0.114). Based on SUCRA values, AIS-APS (SUCRA: 99.8%) ranked the highest.

Conclusion

In conclusion, the study found that the AIS-APS is a validated clinical tool for predicting SAP after the onset of acute ischemic stroke.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=292375, identifier: CRD42021292375.

Comparative Effectiveness of Physical Activity Intervention Programs on Motor Skills in Children and Adolescents: A Systematic Review and Network Meta-Analysis

Objective: To evaluate how different physical activity (PA) interventions (traditional, exergaming, and teacher/parent education) impacted children's motor skills (object control, locomotor, and gross motor). Design: Systematic review and network meta-analysis. Data sources: PubMed, Medline, Scopus, Web of Science, EMBASE, and PsycINFO. Eligibility criteria: (1) Participants comprised 1708 children 3-12 years; (2) PA or exercise-based interventions were investigated; (3) only studies using a Test of Gross Motor Skills assessment were included; (4) RCT were chosen as the study design to assess the impact of PA interventions on children's motor skills; and (5) culture-based PA studies with English language only were included. Data were analyzed using a Bayesian network meta-analysis. Results: The results were reported as standardized mean differences (SMDs) with associated 95% credible intervals (CrIs). For object control, aerobic intervention (SMD 6.90, 95% Crl 1.39 to 13.50); for locomotor, exergaming intervention (SMD 12.50, 95% Crl 0.28 to 24.50); and for gross motor, aerobic intervention (SMD 7.49, 95% Crl 0.11 to 15.70) were the most effective treatments. Conclusion: Children's FMSs have been improved through different PA interventions. Among them, aerobic interventions seem to be the most effective intervention in enhancing object control skills and overall gross motor skills.

Comparative effectiveness and acceptability of different ACT delivery formats to treat depression: A systematic review and network meta-analysis of randomized controlled trials

BACKGROUND

Acceptance and Commitment Therapy (ACT) has been shown to be effective in the treatment of acute depression. However, whether ACT can be effectively delivered in individual, group, internet, and combined delivery format remain unclear. We aimed to examine the most effective delivery format for ACT via a network meta-analysis (NMA).

METHODS

An electronic literature search was conducted by two reviewers in the Pubmed, Cochrane library, Embase, PsycINFO, CINAHL, CNKI, Wangfang databases to identify relevant studies that were published up to March 21th, 2021. We conducted pairwise and NMA to evaluate the relative effectiveness and rank the probability of different ACT delivery formats. A series of analyses and assessments, such as the risk of bias, and GRADE were performed concurrently.

RESULTS

A total of 23 studies were included in our analysis based on a series of rigorous screenings, which comprised 690 depressed patients. The effectiveness of individual, group, internet, and combine ACT did not differ statistically significantly from each other. Compared with control group, individual delivery format (standardized mean difference [SMD] = -1.44, confidence interval (CI) = -2.11 to -0.76 GRADE low), group delivery format (SMD = -1.34, 95 % CI = -1.91 to -0.78 GRADE moderate), and internet delivery format (SMD = -0.66, 95 % CI = -1.25 to -0.06 GRADE low) showed the largest improvement on depressive symptoms, whereas the combined group and individual ACT was less effective. In terms of acceptability (dropout for any reason), all delivery formats did not differ statistically significantly from each other.

CONCLUSIONS

For depression symptoms, individual, group, and internet treatment formats appeared to be effective interventions. Applying effective and acceptable ACT in a range of different formats will make ACT easier to implement, disseminate, and deliver across different settings and diverse patient populations. More research is needed to verify the ACT in telephone and combined formats for the management of depression.

Comparative efficacy and acceptability of psychotherapies, pharmacotherapies, and their combination for the treatment of adult insomnia: A systematic review and network meta-analysis

This study aims to explore the comparative efficacy and acceptability of psychotherapies, pharmacotherapies, and their combinations for insomnia. MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, PsycINFO, CINAHL, and ClinicalTrials.gov were searched for randomized clinical trials (RCTs) examining the comparative efficacy in which a psychotherapy and a pharmacotherapy for insomnia were directly compared with each other, or in which a combination of psychotherapy and pharmacotherapy was compared with either alone. The analysis included data from 23 RCTs. In 18 of 23 studies, cognitive behavior therapy for insomnia (CBT-I) was the psychotherapy. At post-treatment, CBT-I showed higher subjective sleep efficiency (SE), and lower subjective wake time after sleep onset (WASO) and insomnia severity index (ISI) score. Compared with CBT-I plus pharmacotherapy, pharmacotherapy showed lower subjective SE, and higher subjective sleep latency (SL), PSG measured SL, subjective WASO, and ISI score. Overall, the findings derived from post-treatment data suggested that CBT-I is more beneficial in treating insomnia compared with pharmacotherapy. CBT-I combined with pharmacotherapy is beneficial in improving some sleep parameters (i.e., subjective SE, SL, WASO, and PSG measured SL) compared with pharmacotherapy alone. Daily clinical decisions should consider these findings on the relative efficacy of the principal approaches to insomnia treatment.

Comparative effects of pharmacological interventions for the acute and long-term management of insomnia disorder in adults: a systematic review and network meta-analysis

BACKGROUND

Behavioural, cognitive, and pharmacological interventions can all be effective for insomnia. However, because of inadequate resources, medications are more frequently used worldwide. We aimed to estimate the comparative effectiveness of pharmacological treatments for the acute and long-term treatment of adults with insomnia disorder.

METHODS

In this systematic review and network meta-analysis, we searched the Cochrane Central Register of Controlled Trials, MEDLINE, PubMed, Embase, PsycINFO, WHO International Clinical Trials Registry Platform, ClinicalTrials.gov, and websites of regulatory agencies from database inception to Nov 25, 2021, to identify published and unpublished randomised controlled trials. We included studies comparing pharmacological treatments or placebo as monotherapy for the treatment of adults (≥18 year) with insomnia disorder. We assessed the certainty of evidence using the confidence in network meta-analysis (CINeMA) framework. Primary outcomes were efficacy (ie, quality of sleep measured by any self-rated scale), treatment discontinuation for any reason and due to side-effects specifically, and safety (ie, number of patients with at least one adverse event) both for acute and long-term treatment. We estimated summary standardised mean differences (SMDs) and odds ratios (ORs) using pairwise and network meta-analysis with random effects. This study is registered with Open Science Framework, https://doi.org/10.17605/OSF.IO/PU4QJ.

FINDINGS

We included 170 trials (36 interventions and 47 950 participants) in the systematic review and 154 double-blind, randomised controlled trials (30 interventions and 44 089 participants) were eligible for the network meta-analysis. In terms of acute treatment, benzodiazepines, doxylamine, eszopiclone, lemborexant, seltorexant, zolpidem, and zopiclone were more efficacious than placebo (SMD range: 0·36-0·83 [CINeMA estimates of certainty: high to moderate]). Benzodiazepines, eszopiclone, zolpidem, and zopiclone were more efficacious than melatonin, ramelteon, and zaleplon (SMD 0·27-0·71 [moderate to very low]). Intermediate-acting benzodiazepines, long-acting benzodiazepines, and eszopiclone had fewer discontinuations due to any cause than ramelteon (OR 0·72 [95% CI 0·52-0·99; moderate], 0·70 [0·51-0·95; moderate] and 0·71 [0·52-0·98; moderate], respectively). Zopiclone and zolpidem caused more dropouts due to adverse events than did placebo (zopiclone: OR 2·00 [95% CI 1·28-3·13; very low]; zolpidem: 1·79 [1·25-2·50; moderate]); and zopiclone caused more dropouts than did eszopiclone (OR 1·82 [95% CI 1·01-3·33; low]), daridorexant (3·45 [1·41-8·33; low), and suvorexant (3·13 [1·47-6·67; low]). For the number of individuals with side-effects at study endpoint, benzodiazepines, eszopiclone, zolpidem, and zopiclone were worse than placebo, doxepin, seltorexant, and zaleplon (OR range 1·27-2·78 [high to very low]). For long-term treatment, eszopiclone and lemborexant were more effective than placebo (eszopiclone: SMD 0·63 [95% CI 0·36-0·90; very low]; lemborexant: 0·41 [0·04-0·78; very low]) and eszopiclone was more effective than ramelteon (0.63 [0·16-1·10; very low]) and zolpidem (0·60 [0·00-1·20; very low]). Compared with ramelteon, eszopiclone and zolpidem had a lower rate of all-cause discontinuations (eszopiclone: OR 0·43 [95% CI 0·20-0·93; very low]; zolpidem: 0·43 [0·19-0·95; very low]); however, zolpidem was associated with a higher number of dropouts due to side-effects than placebo (OR 2·00 [95% CI 1·11-3·70; very low]).

INTERPRETATION

Overall, eszopiclone and lemborexant had a favorable profile, but eszopiclone might cause substantial adverse events and safety data on lemborexant were inconclusive. Doxepin, seltorexant, and zaleplon were well tolerated, but data on efficacy and other important outcomes were scarce and do not allow firm conclusions. Many licensed drugs (including benzodiazepines, daridorexant, suvorexant, and trazodone) can be effective in the acute treatment of insomnia but are associated with poor tolerability, or information about long-term effects is not available. Melatonin, ramelteon, and non-licensed drugs did not show overall material benefits. These results should serve evidence-based clinical practice.

FUNDING

UK National Institute for Health Research Oxford Health Biomedical Research Centre.

Theory and practice of Bayesian and frequentist frameworks for network meta-analysis

Network meta-analysis (NMA) is an increasingly popular statistical method of synthesising evidence to assess the comparative benefits and harms of multiple treatments in a single analysis. Several automated software packages facilitate conducting NMA using either of two alternative approaches, Bayesian or frequentist frameworks. Researchers must choose a framework for conducting NMA (Bayesian or frequentist) and select appropriate model(s), and those conducting NMA need to understand the assumptions and limitations of different approaches. Bayesian models are more frequently used and can be more flexible but require checking additional assumptions and greater statistical expertise that are often ignored. The present paper describes the important theoretical aspects of Bayesian and frequentist models for NMA and the applications and considerations of contrast-synthesis and arm-synthesis NMAs. In addition, we present evidence from a limited number of simulation and empirical studies that compared different frequentist and Bayesian models and provide an overview of available automated software packages to perform NMA. We will conclude that when analysts choose appropriate models, there are seldom important differences in the results of Bayesian and frequentist approaches and that network meta-analysts should therefore focus on model features rather than the statistical framework.

Assessing and visualizing fragility of clinical results with binary outcomes in R using the fragility package

With the growing concerns about research reproducibility and replicability, the assessment of scientific results' fragility (or robustness) has been of increasing interest. The fragility index was proposed to quantify the robustness of statistical significance of clinical studies with binary outcomes. It is defined as the minimal event status modifications that can alter statistical significance. It helps clinicians evaluate the reliability of the conclusions. Many factors may affect the fragility index, including the treatment groups in which event status is modified, the statistical methods used for testing for the association between treatments and outcomes, and the pre-specified significance level. In addition to assessing the fragility of individual studies, the fragility index was recently extended to both conventional pairwise meta-analyses and network meta-analyses of multiple treatment comparisons. It is not straightforward for clinicians to calculate these measures and visualize the results. We have developed an R package called "fragility" to offer user-friendly functions for such purposes. This article provides an overview of methods for assessing and visualizing the fragility of individual studies as well as pairwise and network meta-analyses, introduces the usage of the "fragility" package, and illustrates the implementations with several worked examples.

Efficacy and acceptability of psychotherapeutic and pharmacological interventions for trauma-related nightmares: A systematic review and network meta-analysis

This network meta-analysis compares the efficacy and acceptability of all published psychotherapeutic and pharmacological interventions for trauma-related nightmares (TRN) in adults. The analysis included data from 29 randomized clinical trials involving 14 psychotherapeutic and pharmacological interventions and involved 2214 trauma survivors. Prazosin and image rehearsal therapy (IRT) were found to be the two effective interventions for TRN. Other interventions such as risperidone, paroxetine, cognitive behavioral therapy for insomnia (CBT-I), CBT-I+IRT, prolonged exposure (PE), and IRT+PE, did not show significantly greater efficacy compared with control conditions. The rates of all-cause discontinuations were comparable among majority of the interventions and did not show significant differences compared with control conditions. Prazosin and IRT should be considered as the initial choice of pharmacological and psychotherapeutic interventions for TRN. The efficacy of other pharmacological and psychotherapeutic interventions remains to be demonstrated. Future guidelines and daily clinical decision making on the choice of interventions for TRN should consider these findings.

Comparative Efficacy of Three Minimally Invasive Procedures for Kümmell’s Disease: A Systematic Review and Network Meta-Analysis

Background

Percutaneous vertebroplasty (PVP), percutaneous kyphoplasty (PKP), and bone-filling mesh containers(BFC) are three viable minimally invasive techniques that have been used to treat Kümmell’s disease(KD). However, there is still debate as to which is safer and more effective. This study summarized the pros and cons of the three techniques in the treatment of KD through network meta-analysis(NMA).

Methods

All eligible published clinical control studies comparing PVP, PKP, and BFC for KD up to December 2021 were collected by online search of Cochrane Library, PubMed, Embase, CNKI, Wanfang Database, and Chinese biomedical literature database. Data were extracted after screening, and Stata 16.0 software was used to perform the network meta-analysis.

Results

Four randomized controlled trials (RCTs) and 16 retrospective case-control studies (CCTs) with a total of 1114 patients were included. The NMA results showed no statistical difference between the 3 procedures in terms of improving patients’ clinical symptoms. PKP was most likely to be the most effective in correcting kyphosis, while BFC was likely to be the most effective in managing the occurrence of cement leakage. No statistical differences were found in the incidence of new vertebral fractures in adjacent segments.

Conclusions

Ranking analysis showed that BFC has the highest likelihood of being the optimal procedure for the treatment of KD, based on a combined assessment of effectiveness in improving patients’ symptoms and safety in the occurrence of adverse events.

Oral pharmacological treatments for chronic prostatitis/chronic pelvic pain syndrome: A systematic review and network meta-analysis of randomised controlled trials

BACKGROUND

Pharmacological treatments for chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) are empirically used. However, the quantitative comparative effectiveness and safety of multiple pharmacological treatments is lacking.

METHODS

PubMed, Embase, Cochrane Central Register of Controlled Trials, and Web of Science were searched from inception to March 22, 2022. Randomised controlled trials comparing two or more oral pharmacological treatments for patients with CP/CPPS were included. Title, abstract, and full-text screening were independently screened by four reviewers. Primary outcomes were efficacy (the National Institutes of Health Chronic Prostatitis Symptom Index [NIH-CPSI] total score, pain score, urinary score, and quality of life score [QoL]) and safety (adverse events). This study was registered with PROSPERO, CRD42020184106.

FINDINGS

25 studies (3514 patients) assessed 26 treatments. Low to very low quality evidence indicated that doxazosin (Mean difference [MD], -11.4, 95% Credible interval [CrI], -17.5 to -5.1) and the doxazosin, ibuprofen, and thiocolchicoside combination (MD, -11.6, CrI, -18.1 to -5.3) were significantly more effective than placebo in the NIH-CPSI total score. Other NIH-CPSI relative outcomes (pain, urinary, and QoL scores) showed a similar pattern. Low and very low quality evidence suggested that combination treatment including doxazosin, ibuprofen, and thiocolchicoside (odds ratios [OR], 3.2, CrI, 0.5 to 19.3) and the tamsulosin and dapoxetine combination (OR, 6.0, CrI, 0.7 to 67.3) caused more adverse events. In half of all comparisons regarding NIH-CPSI pain scores and quality of life scores, heterogeneity was minimal or low. Heterogeneity was high in both NIH-CPSI total symptom scores (I²  = 78.0%) and pain scores (I²  = 87. 0%) for tamsulosin versus placebo. There was also high heterogeneity in NIH-CPSI urine scores for the combination of tamsulosin and ciprofloxacin versus tamsulosin (I²  = 66.8%), tamsulosin and levofloxacin versus tamsulosin (I²  = 93.3%), and tamsulosin versus placebo (I²  = 83%).

INTERPRETATION

Pharmacological treatments have little evidence supporting efficacy in CP/CPPS. Future studies could personalise therapy for individuals according to specific symptoms and identify non-pharmacological targets for CP/CPPS.

FUNDING

Dr Jiani Wu received funding for this project from the China Association for Science and Technology (2017QNRC001), the China Academy of Chinese Medical Sciences (ZZ13-YQ-027), and the National Natural Science Foundation of China (82105037).

Algorithm-based individualization methodology of the starting gonadotropin dose in IVF/ICSI and the freeze-all strategy prevent OHSS equally in normal responders: a systematic review and network meta-analysis of the evidence

PURPOSE

Ovarian hyperstimulation syndrome (OHSS) represents a rare but dangerous condition associated with controlled ovarian stimulation (COS) in IVF/ICSI. Over the last decades, many strategies have been introduced into clinical practice with the objective of preventing this potentially life-threatening condition. Among these, the freeze-all policy has gained great popularity, thanks to improvements in vitrification. Nevertheless, not all clinics have adequate skills in vitrification procedures and patients may be dissatisfied with a longer time to pregnancy.

METHODS

This study is a systematic review and network meta-analysis of randomized controlled trials comparing different strategies of ovarian stimulation in IVF/ICSI cycles (freeze-all policy, algorithm-based individualization of the starting dose, experience-based individualization of the starting dose, standard dose) in terms of reduction of OHSS, in normal responders.

RESULTS

The results indicate that only the algorithm-based individualization of the starting gonadotropin dose reduces OHSS similarly to the freeze-all strategy.

CONCLUSION

Albeit in the era of the freeze-all policy, the personalization of the starting gonadotropin dose obtained by the use of algorithms should be pursued as a valid and safe option for IVF.

Strategies to reduce limb ischemia in peripheral venoarterial extracorporeal membrane oxygenation: A systematic review and Meta-analysis

Venoarterial extracorporeal membrane oxygenation (VA-ECMO) provides cardiovascular and respiratory support for patients in cardiogenic shock; yet, complications are a frequent source of morbidity and mortality. Limb ischemia can be potentially mitigated by limp perfusion protection strategies (LPPS). We performed a systematic review and meta-analysis to evaluate the safety and efficacy of two LPPS in patients treated with peripheral VA-ECMO - prophylactic insertion of a distal perfusion catheter (DPC) and small bore (<17 Fr) arterial return cannula. Among 22 included studies, limb ischemia was reduced in patients receiving a small arterial cannula (OR 0.40, 95% CI 0.24-0.65; p < 0.001) and in patients receiving a prophylactic DPC (OR 0.31, 95% CI 0.21-0.47; p < 0.001). Mortality was not significantly reduced with either a small arterial cannula (OR 0.70, 95% CI 0.23-2.18; p = 0.54) or prophylactic DPC strategy (OR 0.89, 95% CI 0.67-1.17; p = 0.40). As such, prophylactic insertion of a DPC or smaller bore arterial return cannula appear to reduce the risk of lower limb ischemia in this analysis. Further data are needed to confirm these findings. Registration: Registered in PROSPERO Database (Registration CRD42020215677).

Challenges of modelling approaches for network meta-analysis of time-to-event outcomes in the presence of non-proportional hazards to aid decision making: Application to a melanoma network

BACKGROUND

Synthesis of clinical effectiveness from multiple trials is a well-established component of decision-making. Time-to-event outcomes are often synthesised using the Cox proportional hazards model assuming a constant hazard ratio over time. However, with an increasing proportion of trials reporting treatment effects where hazard ratios vary over time and with differing lengths of follow-up across trials, alternative synthesis methods are needed.

OBJECTIVES

To compare and contrast five modelling approaches for synthesis of time-to-event outcomes and provide guidance on key considerations for choosing between the modelling approaches.

METHODS

The Cox proportional hazards model and five other methods of estimating treatment effects from time-to-event outcomes, which relax the proportional hazards assumption, were applied to a network of melanoma trials reporting overall survival: restricted mean survival time, generalised gamma, piecewise exponential, fractional polynomial and Royston-Parmar models.

RESULTS

All models fitted the melanoma network acceptably well. However, there were important differences in extrapolations of the survival curve and interpretability of the modelling constraints demonstrating the potential for different conclusions from different modelling approaches.

CONCLUSION

The restricted mean survival time, generalised gamma, piecewise exponential, fractional polynomial and Royston-Parmar models can accommodate non-proportional hazards and differing lengths of trial follow-up within a network meta-analysis of time-to-event outcomes. We recommend that model choice is informed using available and relevant prior knowledge, model transparency, graphically comparing survival curves alongside observed data to aid consideration of the reliability of the survival estimates, and consideration of how the treatment effect estimates can be incorporated within a decision model.

Combining individual patient data from randomized and non-randomized studies to predict real-world effectiveness of interventions

Meta-analysis of randomized controlled trials is generally considered the most reliable source of estimates of relative treatment effects. However, in the last few years, there has been interest in using non-randomized studies to complement evidence from randomized controlled trials. Several meta-analytical models have been proposed to this end. Such models mainly focussed on estimating the average relative effects of interventions. In real-life clinical practice, when deciding on how to treat a patient, it might be of great interest to have personalized predictions of absolute outcomes under several available treatment options. This paper describes a general framework for developing models that combine individual patient data from randomized controlled trials and non-randomized study when aiming to predict outcomes for a set of competing medical interventions applied in real-world clinical settings. We also discuss methods for measuring the models' performance to identify the optimal model to use in each setting. We focus on the case of continuous outcomes and illustrate our methods using a data set from rheumatoid arthritis, comprising patient-level data from three randomized controlled trials and two registries from Switzerland and Britain.

Network meta-analysis and random walks

Network meta-analysis (NMA) is a central tool for evidence synthesis in clinical research. The results of an NMA depend critically on the quality of evidence being pooled. In assessing the validity of an NMA, it is therefore important to know the proportion contributions of each direct treatment comparison to each network treatment effect. The construction of proportion contributions is based on the observation that each row of the hat matrix represents a so-called "evidence flow network" for each treatment comparison. However, the existing algorithm used to calculate these values is associated with ambiguity according to the selection of paths. In this article, we present a novel analogy between NMA and random walks. We use this analogy to derive closed-form expressions for the proportion contributions. A random walk on a graph is a stochastic process that describes a succession of random "hops" between vertices which are connected by an edge. The weight of an edge relates to the probability that the walker moves along that edge. We use the graph representation of NMA to construct the transition matrix for a random walk on the network of evidence. We show that the net number of times a walker crosses each edge of the network is related to the evidence flow network. By then defining a random walk on the directed evidence flow network, we derive analytically the matrix of proportion contributions. The random-walk approach has none of the associated ambiguity of the existing algorithm.

Bayesian models for aggregate and individual patient data component network meta-analysis

Network meta-analysis can synthesize evidence from studies comparing multiple treatments for the same disease. Sometimes the treatments of a network are complex interventions, comprising several independent components in different combinations. A component network meta-analysis (CNMA) can be used to analyze such data and can in principle disentangle the individual effect of each component. However, components may interact with each other, either synergistically or antagonistically. Deciding which interactions, if any, to include in a CNMA model may be difficult, especially for large networks with many components. In this article, we present two Bayesian CNMA models that can be used to identify prominent interactions between components. Our models utilize Bayesian variable selection methods, namely the stochastic search variable selection and the Bayesian LASSO, and can benefit from the inclusion of prior information about important interactions. Moreover, we extend these models to combine data from studies providing aggregate information and studies providing individual patient data (IPD). We illustrate our models in practice using three real datasets, from studies in panic disorder, depression, and multiple myeloma. Finally, we describe methods for developing web-applications that can utilize results from an IPD-CNMA, to allow for personalized estimates of relative treatment effects given a patient's characteristics.

Pharmacological and dietary-supplement treatments for autism spectrum disorder: a systematic review and network meta-analysis

Background

There is still no approved medication for the core symptoms of autism spectrum disorder (ASD). This network meta-analysis investigated pharmacological and dietary-supplement treatments for ASD.

Methods

We searched for randomized-controlled-trials (RCTs) with a minimum duration of seven days in ClinicalTrials.gov, EMBASE, MEDLINE, PsycINFO, WHO-ICTRP (from inception up to July 8, 2018), CENTRAL and PubMed (up to November 3, 2021). The co-primary outcomes were core symptoms (social-communication difficulties-SCD, repetitive behaviors-RB, overall core symptoms-OCS) measured by validated scales and standardized-mean-differences (SMDs). Associated symptoms, e.g., irritability/aggression and attention-deficit/hyperactivity disorder (ADHD) symptoms, dropouts and important side-effects, were investigated as secondary outcomes. Studies in children/adolescents and adults were analyzed separately in random-effects pairwise and network meta-analyses.

Results

We analyzed data for 41 drugs and 17 dietary-supplements, from 125 RCTs (n = 7450 participants) in children/adolescents and 18 RCTs (n = 1104) in adults. The following medications could improve at least one core symptom domain in comparison with placebo: aripiprazole (k = 6 studies in analysis, SCD: SMD = 0.27 95% CI [0.09, 0.44], RB: 0.48 [0.26, 0.70]), atomoxetine (k = 3, RB:0.49 [0.18, 0.80]), bumetanide (k = 4, RB: 0.35 [0.09, 0.62], OCS: 0.61 [0.31, 0.91]), and risperidone (k = 4, SCM: 0.31 [0.06, 0.55], RB: 0.60 [0.29, 0.90]; k = 3, OCS: 1.18 [0.75, 1.61]) in children/adolescents; fluoxetine (k = 1, RB: 1.20 [0.45, 1.96]), fluvoxamine (k = 1, RB: 1.04 [0.27, 1.81]), oxytocin (k = 6, RB:0.41 [0.16, 0.66]) and risperidone (k = 1, RB: 0.97 [0.21,1.74]) in adults. There were some indications of improvement by carnosine, haloperidol, folinic acid, guanfacine, omega-3-fatty-acids, probiotics, sulforaphane, tideglusib and valproate, yet imprecise and not robust. Confidence in these estimates was very low or low, except moderate for oxytocin. Medications differed substantially in improving associated symptoms, and in their side-effect profiles.

Limitations

Most of the studies were inadequately powered (sample sizes of 20–80 participants), with short duration (8–13 weeks), and about a third focused on associated symptoms. Networks were mainly star-shaped, and there were indications of reporting bias. There was no optimal rating scale measuring change in core symptoms.

Conclusions

Some medications could improve core symptoms, although this could be likely secondary to the improvement of associated symptoms. Evidence on their efficacy and safety is preliminary; therefore, routine prescription of medications for the core symptoms cannot be recommended.

Trial registration PROSPERO-ID CRD42019125317.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13229-022-00488-4.

Cross-roads for meta-analysis and network meta-analysis of H. pylori therapy

Helicobacter pylori infections are responsible for tremendous morbidity and mortality worldwide, leading to efforts to eradicate the organism. However, the effectiveness of antimicrobial therapy has been undermined by the progressive development of antimicrobial resistance. Treatments and treatment guidelines have been based on traditional pairwise meta-analyses of randomised controlled trials. More recently, network meta-analyses have also been used in an attempt to provide useful information to the clinician regarding which therapies appear best and which to avoid as the least efficacious. However, both forms of meta-analysis have been undermined by the same problems including the poor quality of the clinical trials using unoptimised regimens and incomparable comparisons related to marked geographic and ethnic genotypic and phenotypic heterogeneity. In addition, the comparator regimens often consist of invalid strawman comparisons. New approaches concerning H. pylori treatment and analysis of therapies are needed. H. pylori therapies should be based on antimicrobial stewardship, as in other infectious diseases. This approach requires the use of only optimised therapies proven to be reliably highly effective in the local population (eg, a cure rate of >90%) for both the study and the comparator regimens. Meta-analyses should be restricted to regimens that meet these criteria and must take into account the presence of marked geographical and host genetic and phenotypic heterogeneity. In addition, to provide clinically relevant results, treatment outcomes should focus on, and present, actual cure rates in addition to odd ratios.

Oral Antihypertensives for Nonsevere Pregnancy Hypertension: Systematic Review, Network Meta- and Trial Sequential Analyses

BACKGROUND

We aimed to address which antihypertensives are superior to placebo/no therapy or another antihypertensive for controlling nonsevere pregnancy hypertension and provide future sample size estimates for definitive evidence.

METHODS

Randomized trials of antihypertensives for nonsevere pregnancy hypertension were identified from online electronic databases, to February 28, 2021 (registration URL: https://www.crd.york.ac.uk/PROSPERO/; unique identifier: CRD42020188725). Our outcomes were severe hypertension, proteinuria/preeclampsia, fetal/newborn death, small-for-gestational age infants, preterm birth, and admission to neonatal care. A Bayesian random-effects model generated estimates of direct and indirect treatment comparisons. Trial sequential analysis informed future trials needed.

RESULTS

Of 1246 publications identified, 72 trials were included; 61 (6923 women) were informative. All commonly prescribed antihypertensives (labetalol, other β-blockers, methyldopa, calcium channel blockers, and mixed/multi-drug therapy) versus placebo/no therapy reduced the risk of severe hypertension by 30% to 70%. Labetalol decreased proteinuria/preeclampsia (odds ratio, 0.73 [95% credible interval, 0.54-0.99]) and fetal/newborn death (odds ratio, 0.54 [0.30-0.98]) compared with placebo/no therapy, and proteinuria/preeclampsia compared with methyldopa (odds ratio, 0.66 [0.44-0.99]) and calcium channel blockers (odds ratio, 0.63 [0.41-0.96]). No other differences were identified, but credible intervals were wide. Trial sequential analysis indicated that 2500 to 10 000 women/arm (severe hypertension or safety outcomes) to >15 000/arm (fetal/newborn death) would be required to provide definitive evidence.

CONCLUSIONS

In summary, all commonly prescribed antihypertensives in pregnancy reduce the risk of severe hypertension, but labetalol may also decrease proteinuria/preeclampsia and fetal/newborn death. Evidence is lacking for many other safety outcomes. Prohibitive sample sizes are required for definitive evidence. Real-world data are needed to individualize care.

A dose-effect network meta-analysis model with application in antidepressants using restricted cubic splines

Network meta-analysis has been used to answer a range of clinical questions about the preferred intervention for a given condition. Although the effectiveness and safety of pharmacological agents depend on the dose administered, network meta-analysis applications typically ignore the role that drugs dosage plays in the results. This leads to more heterogeneity in the network. In this paper, we present a suite of network meta-analysis models that incorporate the dose-effect relationship using restricted cubic splines. We extend existing models into a dose-effect network meta-regression to account for study-level covariates and for groups of agents in a class-effect dose-effect network meta-analysis model. We apply our models to a network of aggregate data about the efficacy of 21 antidepressants and placebo for depression. We find that all antidepressants are more efficacious than placebo after a certain dose. Also, we identify the dose level at which each antidepressant's effect exceeds that of placebo and estimate the dose beyond which the effect of antidepressants no longer increases. When covariates were introduced to the model, we find that studies with small sample size tend to exaggerate antidepressants efficacy for several of the drugs. Our dose-effect network meta-analysis model with restricted cubic splines provides a flexible approach to modelling the dose-effect relationship in multiple interventions. Decision-makers can use our model to inform treatment choice.

Network Meta-Analysis for Single-Case Design Studies: An Illustration

Single-case designs (SCDs) are used to evaluate the effects of interventions on individual participants. By repeatedly measuring participants under different conditions, SCD studies focus on individual effects rather than on group summaries. The main limitation of SCDs remains its generalisability to wider populations, reducing the relevance of their findings for practice and policy making. With this limitation in mind, methodological developments for synthesising SCD data from different studies that investigate the same research question have intensified in the past decades (e.g. multilevel modelling). However, these techniques are restricted to comparing two interventions at a time and can only incorporate evidence from studies that directly compare the two treatments of interest. These limitations could be addressed by using network meta-analysis that incorporates both direct and indirect evidence to simultaneously compare multiple interventions. Despite its potential, network meta-analytical techniques have yet to be applied to SCD data. Thus, in this paper, we argue that network meta-analysis can be a valuable tool to synthesise SCD data. We demonstrate the use of network meta-analysis in SCD data using a real dataset, and we conclude by reflecting on the challenges that SCD researchers might face when applying network meta-analysis methods to their data.

Neuropsychological Interventions for Cancer-Related Cognitive Impairment: A Network Meta-Analysis of Randomized Controlled Trials

The aim of this network meta-analysis was to evaluate the comparative effects of neuropsychological interventions for cancer-related cognitive impairment (CRCI), and to rank the best intervention options for adult cancer patients with CRCI. Twenty-seven eligible randomized controlled trials (RCTs) were searched, and a total of six interventions identified: cognitive behavioral therapies (CBT), cognitive rehabilitation (CR), cognitive training (CT), meditation/mindfulness-based interventions, psychoeducation, and supportive care. In terms of effectiveness, the relative effect size of CBT, CR, and CT in managing subjective cognition had statistically significant differences - 0.94 (0.43-1.44), 0.54 (0.03-1.05), and 0.47 (0.13-0.81), respectively. The most effective interventions to manage the objective cognition of attention were meditation or mindfulness-based interventions: intervention effect size was 0.58 (0.24-0.91). The relative effect size of CT had a statistically significant difference in managing verbal memory, and the intervention effect size was 1.16 (0.12-2.20). The relative effect size of psychoeducation in managing executive function compared with control had a statistically significant difference, which was 0.56 (0.26-0.86). For managing information processing speed, the most effective intervention was CT and the effect size was -0.58 (-1.09--0.06). This network meta-analysis found that CT is the most effective intervention for managing the objective cognition of verbal memory and processing speed; meditation/mindfulness-based interventions may be the best option for enhancing attention; psychoeducation is the most effective intervention for managing executive function; CT may be the best option for managing verbal fluency as the intervention ranking probability. For the management of subjective cognition, CBT may be the most effective intervention.

Software to Conduct a Meta-Analysis and Network Meta-Analysis

Statistical software for meta-analysis (MA) and network meta-analysis (NMA) have become indispensable for researchers. The aim of this chapter is to introduce key features of MA and NMA software to compare the effectiveness of interventions. Commonly used or routinely maintained statistical software are reviewed, including commercial and open-sourced programs such as Stata, R and Excel plug-ins. It does not provide a comprehensive overview of all features available in the software covered. Rather, it focuses on the essential features required to carry out an MA or NMA . This chapter begins with a review of key considerations when implementing an MA or NMA , then presents a summary of the software. Key features of each software option are discussed.

Contrast-Based and Arm-Based Models for Network Meta-Analysis

Network meta-analysis is used to synthesize evidence from a network of treatments. The models used in a network meta-analysis are more complex than those used for pairwise meta-analysis. Two types of models are available to undertake a network meta-analysis: contrast-based and arm-based models. Contrast-based models have been used in most published network meta-analyses. Arm-based models offer greater flexibility and handle treatments symmetrically, but risk compromising randomization. In this chapter, we (1) present the contrast-based and arm-based statistical models; (2) describe the theoretical differences between the models (noting when the estimates from the models are expected to diverge); (3) summarize the evidence comparing the two models from simulation studies and empirical investigations; and (4) provide a worked example applying the two models to a network using the R software package.

A Revised Framework to Evaluate the Consistency Assumption Globally in a Network of Interventions

Background

The unrelated mean effects (UME) model has been proposed for evaluating the consistency assumption globally in the network of interventions. However, the UME model does not accommodate multiarm trials properly and omits comparisons between nonbaseline interventions in the multiarm trials not investigated in 2-arm trials.

Methods

We proposed a refinement of the UME model that tackles the limitations mentioned above. We also accompanied the scatterplots on the posterior mean deviance contributions of the trial arms under the network meta-analysis (NMA) and UME models with Bland-Altman plots to detect outlying trials contributing to poor model fit. We applied the refined and original UME models to 2 networks with multiarm trials.

Results

The original UME model omitted more than 20% of the observed comparisons in both networks. The thorough inspection of the individual data points’ deviance contribution using complementary plots in conjunction with the measures of model fit and the estimated between-trial variance indicated that the refined and original UME models revealed possible inconsistency in both examples.

Conclusions

The refined UME model allows proper accommodation of the multiarm trials and visualization of all observed evidence in complex networks of interventions. Furthermore, considering several complementary plots to investigate deviance helps draw informed conclusions on the possibility of global inconsistency in the network.

Highlights

Hypofractionated radiotherapy for newly diagnosed elderly glioblastoma patients: A systematic review and network meta-analysis

OBJECTIVE

To evaluate different hypofractionated radiotherapy (HRT) regimens for newly diagnosed elderly glioblastoma (GBM) patients.

METHODS

We performed a systematic review with network meta-analysis (NMA), including searches on CENTRAL, Medline, EMBASE, CINAHL, clinical trial databases and manual search. Only randomized clinical trials (RCTs) were included. Primary outcomes: overall survival (OS) and adverse events (AE). Secondary outcomes: progression-free-survival (PFS) and quality of life (QoL). We used the Cochrane Risk of Bias (RoB) table for assessing individual studies and CINeMA for evaluating the certainty of the final body of evidence.

RESULTS

Four RCTs (499 patients) were included. For OS, the estimates from NMA did not provide strong evidence of a difference between the HRTs: 40 Gray (Gy) versus 45 Gy (HR: 0.89; CI 95%: 0.42, 1.91); 34 Gy versus 45 Gy (HR: 0.85; CI 95% 0.43, 1.70); 25 Gy versus 45 Gy (HR: 0.81; CI 95% 0.32, 2.02); 34 Gy versus 40 Gy (HR: 0.95; CI 95% 0.57, 1.61); and 25 Gy versus 34 Gy (HR: 0.95; CI 95% 0.46, 1.97). We performed qualitative synthesis for AE and QoL due to data scarcity and clinical heterogeneity among studies. The four studies reported a similar QoL (assessed by different methods) between arms. One RCT reported grade ≥ 3 AE, with no evidence of a difference between arms. PFS was reported in one study (25 Gy versus 40 Gy), with no evidence of a difference between arms.

CONCLUSION

This review found no evidence of a difference between the evaluated HRTs for efficacy and safety.

A frequentist one-step model for a simple network meta-analysis of time-to-event data in presence of an effect modifier

INTRODUCTION

Individual patient data (IPD) present particular advantages in network meta-analysis (NMA) because interactions may lead an aggregated data (AD)-based model to wrong a treatment effect (TE) estimation. However, fewer works have been conducted for IPD with time-to-event contrary to binary outcomes. We aimed to develop a general frequentist one-step model for evaluating TE in the presence of interaction in a three-node NMA for time-to-event data.

METHODS

One-step, frequentist, IPD-based Cox and Poisson generalized linear mixed models were proposed. We simulated a three-node network with or without a closed loop with (1) no interaction, (2) covariate-treatment interaction, and (3) covariate distribution heterogeneity and covariate-treatment interaction. These models were applied to the NMA (Meta-analyses of Chemotherapy in Head and Neck Cancer [MACH-NC] and Radiotherapy in Carcinomas of Head and Neck [MARCH]), which compared the addition of chemotherapy or modified radiotherapy (mRT) to loco-regional treatment with two direct comparisons. AD-based (contrast and meta-regression) models were used as reference.

RESULTS

In the simulated study, no IPD models failed to converge. IPD-based models performed well in all scenarios and configurations with small bias. There were few variations across different scenarios. In contrast, AD-based models performed well when there were no interactions, but demonstrated some bias when interaction existed and a larger one when the modifier was not distributed evenly. While meta-regression performed better than contrast-based only, it demonstrated a large variability in estimated TE. In the real data example, Cox and Poisson IPD-based models gave similar estimations of the model parameters. Interaction decomposition permitted by IPD explained the ecological bias observed in the meta-regression.

CONCLUSION

The proposed general one-step frequentist Cox and Poisson models had small bias in the evaluation of a three-node network with interactions. They performed as well or better than AD-based models and should also be undertaken whenever possible.

Predictive P-score for treatment ranking in Bayesian network meta-analysis

Background

Network meta-analysis (NMA) is a widely used tool to compare multiple treatments by synthesizing different sources of evidence. Measures such as the surface under the cumulative ranking curve (SUCRA) and the P-score are increasingly used to quantify treatment ranking. They provide summary scores of treatments among the existing studies in an NMA. Clinicians are frequently interested in applying such evidence from the NMA to decision-making in the future. This prediction process needs to account for the heterogeneity between the existing studies in the NMA and a future study.

Methods

This article introduces the predictive P-score for informing treatment ranking in a future study via Bayesian models. Two NMAs were used to illustrate the proposed measure; the first assessed 4 treatment strategies for smoking cessation, and the second assessed treatments for all-grade treatment-related adverse events. For all treatments in both NMAs, we obtained their conventional frequentist P-scores, Bayesian P-scores, and predictive P-scores.

Results

In the two examples, the Bayesian P-scores were nearly identical to the corresponding frequentist P-scores for most treatments, while noticeable differences existed for some treatments, likely owing to the different assumptions made by the frequentist and Bayesian NMA models. Compared with the P-scores, the predictive P-scores generally had a trend to converge toward a common value of 0.5 due to the heterogeneity. The predictive P-scores’ numerical estimates and the associated plots of posterior distributions provided an intuitive way for clinicians to appraise treatments for new patients in a future study.

Conclusions

The proposed approach adapts the existing frequentist P-score to the Bayesian framework. The predictive P-score can help inform medical decision-making in future studies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-021-01397-5.

Reporting of Cochrane systematic review protocols with network meta-analyses-A scoping review

Publishing systematic review protocols is a fundamental part of systematic reviews to ensure transparency and reproducibility. In this scoping review, we aimed to evaluate reporting of Cochrane systematic review protocols with network meta-analyses (NMA). We searched all Cochrane NMA protocols published in 2018 and 2019, and assessed the characteristics and reporting of methodologies relevant to NMA. We reported frequencies for each reporting item. Forty-five protocols were assessed, including two for overviews and 43 for intervention reviews. Thirty-three (73%) were labelled as NMA protocols in the title. Forty-two (95%) justified the need of an NMA and 40 (89%) used appropriate search strategies to identify potential eligible studies. About half (24, 53%) considered the transitivity assumption when reporting inclusion criteria and 35 (78%) specified potential effect modifiers. Forty-three (96%) reported statistical software for NMA, 25 (56%) reported NMA model choice, 32 (71%) reported framework choice and 32 (71%) reported assumption about heterogeneity variances. Protocols varied in whether they reported methods for relative ranking (35, 78%), statistical inconsistency (40, 89%), reporting bias (44, 98%) and sources of heterogeneity (39, 87%). In conclusion, Cochrane NMA protocols reported multiple NMA-specific items well, but could be further improved, especially regarding transitivity assumptions. Our recommendations for NMA protocol reporting based on this scoping review could assist authors, reviewers, and editors to improve NMA protocols.