Bayesian pairwise meta-analysis of time-to-event outcomes in the presence of non-proportional hazards: A simulation study of flexible parametric, piecewise exponential and fractional polynomial models.

BACKGROUND: Traditionally, meta-analysis of time-to-event outcomes reports a single pooled hazard ratio assuming proportional hazards (PH). For health technology assessment evaluations, hazard ratios are frequently extrapolated across a lifetime horizon. However, when treatment effects vary over time, an assumption of PH is not always valid. The Royston-Parmar (RP), piecewise exponential (PE), and fractional polynomial (FP) models can accommodate non-PH and provide plausible extrapolations of survival curves beyond observed data. METHODS: Simulation study to assess and compare the performance of RP, PE, and FP models in a Bayesian framework estimating restricted mean survival time difference (RMSTD) at 50 years from a pairwise meta-analysis with evidence of non-PH. Individual patient data were generated from a mixture Weibull distribution. Twelve scenarios were considered varying the amount of follow-up data, number of trials in a meta-analysis, non-PH interaction coefficient, and prior distributions. Performance was assessed through bias and mean squared error. Models were applied to a metastatic breast cancer example. RESULTS: FP models performed best when the non-PH interaction coefficient was 0.2. RP models performed best in scenarios with complete follow-up data. PE models performed well on average across all scenarios. In the metastatic breast cancer example, RMSTD at 50-years ranged from -14.6 to 8.48 months. CONCLUSIONS: Synthesis of time-to-event outcomes and estimation of RMSTD in the presence of non-PH can be challenging and computationally intensive. Different approaches make different assumptions regarding extrapolation and sensitivity analyses varying key assumptions are essential to check the robustness of conclusions to different assumptions for the underlying survival function.

The development and internal pilot trial of a digital physical activity and emotional well-being intervention (Kidney BEAM) for people with chronic kidney disease.

This trial assessed the feasibility and acceptability of Kidney BEAM, a physical activity and emotional well-being self-management digital health intervention (DHI) for people with chronic kidney disease (CKD), which offers live and on-demand physical activity sessions, educational blogs and videos, and peer support. In this mixed-methods, multicentre randomised waitlist-controlled internal pilot, adults with established CKD were recruited from five NHS hospitals and randomised 1:1 to Kidney BEAM or waitlist control. Feasibility outcomes were based upon a priori progression criteria. Acceptability was primarily explored via individual semi-structured interviews (n = 15). Of 763 individuals screened, n = 519 (68%, 95% CI 65 to 71%) were eligible. Of those eligible, n = 303 (58%, 95% CI 54-63%) did not respond to an invitation to participate by the end of the pilot period. Of the 216 responders, 50 (23%, 95% CI 18-29%) consented. Of the 42 randomised, n = 22 (10 (45%) male; 49 ± 16 years; 14 (64%) White British) were allocated to Kidney BEAM and n = 20 (12 (55%) male; 56 ± 11 years; 15 (68%) White British) to the waitlist control group. Overall, n = 15 (30%, 95% CI 18-45%) withdrew during the pilot phase. Participants completed a median of 14 (IQR 5-21) sessions. At baseline, 90-100% of outcome data (patient reported outcome measures and a remotely conducted physical function test) were completed and 62-83% completed at 12 weeks follow-up. Interview data revealed that remote trial procedures were acceptable. Participants' reported that Kidney BEAM increased their opportunity and motivation to be physically active, however, lack of time remained an ongoing barrier to engagement with the DHI. An randomised controlled trial of Kidney BEAM is feasible and acceptable, with adaptations to increase recruitment, retention and engagement.Trial registration NCT04872933. Date of first registration 05/05/2021.

Evaluating the effect of a digital health intervention to enhance physical activity in people with chronic kidney disease (Kidney BEAM): a multicentre, randomised controlled trial in the UK.

BACKGROUND: Remote digital health interventions to enhance physical activity provide a potential solution to improve the sedentary behaviour, physical inactivity, and poor health-related quality of life that are typical of chronic conditions, particularly for people with chronic kidney disease. However, there is a need for high-quality evidence to support implementation in clinical practice. The Kidney BEAM trial evaluated the clinical effect of a 12-week physical activity digital health intervention on health-related quality of life. METHODS: In a single-blind, randomised controlled trial conducted at 11 centres in the UK, adult participants (aged ≥18 years) with chronic kidney disease were recruited and randomly assigned (1:1) to the Kidney BEAM physical activity digital health intervention or a waiting list control group. Randomisation was performed with a web-based system, in randomly permuted blocks of six. Outcome assessors were masked to treatment allocation. The primary outcome was the difference in the Kidney Disease Quality of Life Short Form version 1.3 Mental Component Summary (KDQoL-SF1.3 MCS) between baseline and 12 weeks. The trial was powered to detect a clinically meaningful difference of 3 arbitrary units (AU) in KDQoL-SF1.3 MCS. Outcomes were analysed by an intention-to-treat approach using an analysis of covariance model, with baseline measures and age as covariates. The trial was registered with ClinicalTrials.gov, NCT04872933. FINDINGS: Between May 6, 2021, and Oct 30, 2022, 1102 individuals were assessed for eligibility, of whom 340 participants were enrolled and randomly assigned to the Kidney BEAM intervention group (n=173) or the waiting list control group (n=167). 268 participants completed the trial (112 in the Kidney BEAM group and 156 in the waiting list control group). All 340 randomly assigned participants were included in the intention-to treat population. At 12 weeks, there was a significant improvement in KDQoL-SF.13 MCS score in the Kidney BEAM group (from mean 44·6 AU [SD 10·8] at baseline to 47·0 AU [10·6] at 12 weeks) compared with the waiting list control group (from 46·1 AU [10·5] to 45·0 AU [10·1]; between-group difference of 3·1 AU [95% CI 1·8-4·4]; p<0·0001). INTERPRETATION: The Kidney BEAM physical activity platform is an efficacious digital health intervention to improve mental health-related quality of life in patients with chronic kidney disease. These findings could facilitate the incorporation of remote digital health interventions into clinical practice and offer a potential intervention worthy of investigation in other chronic conditions. FUNDING: Kidney Research UK.

New horizons in evidence synthesis for older adults.

Evidence synthesis, embedded within a systematic review of the literature, is a well-established approach for collating and combining all the relevant information on a particular research question. A robust synthesis can establish the evidence base, which underpins best practice guidance. Such endeavours are frequently used by policymakers and practitioners to inform their decision making. Traditionally, an evidence synthesis of interventions consisted of a meta-analysis of quantitative data comparing two treatment alternatives addressing a specific and focussed clinical question. However, as the methods in the field have evolved, especially in response to the increasingly complex healthcare questions, more advanced evidence synthesis techniques have been developed. These can deal with extended data structures considering more than two treatment alternatives (network meta-analysis) and complex multicomponent interventions. The array of questions capable of being answered has also increased with specific approaches being developed for different evidence types including diagnostic, prognostic and qualitative data. Furthermore, driven by a desire for increasingly up-to-date evidence summaries, living systematic reviews have emerged. All of these methods can potentially have a role in informing older adult healthcare decisions. The aim of this review is to increase awareness and uptake of the increasingly comprehensive array of newer synthesis methods available and highlight their utility for answering clinically relevant questions in the context of older adult research, giving examples of where such techniques have already been effectively applied within the field. Their strengths and limitations are discussed, and we suggest user-friendly software options to implement the methods described.

Data visualisation approaches for component network meta-analysis: visualising the data structure.

BACKGROUND: Health and social care interventions are often complex and can be decomposed into multiple components. Multicomponent interventions are often evaluated in randomised controlled trials. Across trials, interventions often have components in common which are given alongside other components which differ across trials. Multicomponent interventions can be synthesised using component NMA (CNMA). CNMA is limited by the structure of the available evidence, but it is not always straightforward to visualise such complex evidence networks. The aim of this paper is to develop tools to visualise the structure of complex evidence networks to support CNMA. METHODS: We performed a citation review of two key CNMA methods papers to identify existing published CNMA analyses and reviewed how they graphically represent intervention complexity and comparisons across trials. Building on identified shortcomings of existing visualisation approaches, we propose three approaches to standardise visualising the data structure and/or availability of data: CNMA-UpSet plot, CNMA heat map, CNMA-circle plot. We use a motivating example to illustrate these plots. RESULTS: We identified 34 articles reporting CNMAs. A network diagram was the most common plot type used to visualise the data structure for CNMA (26/34 papers), but was unable to express the complex data structures and large number of components and potential combinations of components associated with CNMA. Therefore, we focused visualisation development around representing the data structure of a CNMA more completely. The CNMA-UpSet plot presents arm-level data and is suitable for networks with large numbers of components or combinations of components. Heat maps can be utilised to inform decisions about which pairwise interactions to consider for inclusion in a CNMA model. The CNMA-circle plot visualises the combinations of components which differ between trial arms and offers flexibility in presenting additional information such as the number of patients experiencing the outcome of interest in each arm. CONCLUSIONS: As CNMA becomes more widely used for the evaluation of multicomponent interventions, the novel CNMA-specific visualisations presented in this paper, which improve on the limitations of existing visualisations, will be important to aid understanding of the complex data structure and facilitate interpretation of the CNMA results.

The NightLife study - the clinical and cost-effectiveness of thrice-weekly, extended, in-centre nocturnal haemodialysis versus daytime haemodialysis using a mixed methods approach: study protocol for a randomised controlled trial.

BACKGROUND: In-centre nocturnal haemodialysis (INHD) offers extended-hours haemodialysis, 6 to 8 h thrice-weekly overnight, with the support of dialysis specialist nurses. There is increasing observational data demonstrating potential benefits of INHD on health-related quality of life (HRQoL). There is a lack of randomised controlled trial (RCT) data to confirm these benefits and assess safety. METHODS: The NightLife study is a pragmatic, two-arm, multicentre RCT comparing the impact of 6 months INHD to conventional haemodialysis (thrice-weekly daytime in-centre haemodialysis, 3.5-5 h per session). The primary outcome is the total score from the Kidney Disease Quality of Life tool at 6 months. Secondary outcomes include sleep and cognitive function, measures of safety, adherence to dialysis and impact on clinical parameters. There is an embedded Process Evaluation to assess implementation, health economic modelling and a QuinteT Recruitment Intervention to understand factors that influence recruitment and retention. Adults (≥ 18 years old) who have been established on haemodialysis for > 3 months are eligible to participate. DISCUSSION: There are 68,000 adults in the UK that need kidney replacement therapy (KRT), with in-centre haemodialysis the treatment modality for over a third of cases. HRQoL is an independent predictor of hospitalisation and mortality in individuals on maintenance dialysis. Haemodialysis is associated with poor HRQoL in comparison to the general population. INHD has the potential to improve HRQoL. Vigorous RCT evidence of effectiveness is lacking. The NightLife study is an essential step in the understanding of dialysis therapies and will guide patient-centred decisions regarding KRT in the future. TRIAL REGISTRATION: Trial registration number: ISRCTN87042063. Registered: 14/07/2020.

Exercise training and resting blood pressure: a large-scale pairwise and network meta-analysis of randomised controlled trials.

OBJECTIVE: To perform a large-scale pairwise and network meta-analysis on the effects of all relevant exercise training modes on resting blood pressure to establish optimal antihypertensive exercise prescription practices. DESIGN: Systematic review and network meta-analysis. DATA SOURCES: PubMed (Medline), the Cochrane library and Web of Science were systematically searched. ELIGIBILITY CRITERIA: Randomised controlled trials published between 1990 and February 2023. All relevant work reporting reductions in systolic blood pressure (SBP) and/or diastolic blood pressure (DBP) following an exercise intervention of ≥2 weeks, with an eligible non-intervention control group, were included. RESULTS: 270 randomised controlled trials were ultimately included in the final analysis, with a pooled sample size of 15 827 participants. Pairwise analyses demonstrated significant reductions in resting SBP and DBP following aerobic exercise training (-4.49/-2.53 mm Hg, p<0.001), dynamic resistance training (-4.55/-3.04 mm Hg, p<0.001), combined training (-6.04/-2.54 mm Hg, p<0.001), high-intensity interval training (-4.08/-2.50 mm Hg, p<0.001) and isometric exercise training (-8.24/-4.00 mm Hg, p<0.001). As shown in the network meta-analysis, the rank order of effectiveness based on the surface under the cumulative ranking curve (SUCRA) values for SBP were isometric exercise training (SUCRA: 98.3%), combined training (75.7%), dynamic resistance training (46.1%), aerobic exercise training (40.5%) and high-intensity interval training (39.4%). Secondary network meta-analyses revealed isometric wall squat and running as the most effective submodes for reducing SBP (90.4%) and DBP (91.3%), respectively. CONCLUSION: Various exercise training modes improve resting blood pressure, particularly isometric exercise. The results of this analysis should inform future exercise guideline recommendations for the prevention and treatment of arterial hypertension.

The economic burden of antibiotic resistance: A systematic review and meta-analysis.

INTRODUCTION: Antibiotic resistance (ABR) has substantial global public health concerns. This systematic review aimed to synthesise recent evidence estimating the economic burden of ABR, characterised by study perspectives, healthcare settings, study design, and income of the countries. METHODS: This systematic review included peer-reviewed articles from PubMed, Medline, and Scopus databases, and grey literature on the topic of the economic burden of ABR, published between January 2016 and December 2021. The study was reported in line with 'Preferred Reporting Items for Systematic Review and Meta-Analysis' (PRISMA). Two reviewers independently screened papers for inclusion first by title, then abstract, and then the full text. Study quality was assessed using appropriate quality assessment tools. Narrative synthesis and meta-analyses of the included studies were conducted. RESULTS: A total of 29 studies were included in this review. Out of these studies, 69% (20/29) were conducted in high-income economies and the remainder were conducted in upper-and-middle income economies. Most of the studies were conducted from a healthcare or hospital perspective (89.6%, 26/29) and 44.8% (13/29) studies were conducted in tertiary care settings. The available evidence indicates that the attributable cost of resistant infection ranges from -US$2,371.4 to +US$29,289.1 (adjusted for 2020 price) per patient episode; the mean excess length of stay (LoS) is 7.4 days (95% CI: 3.4-11.4), the odds ratios of mortality for resistant infection is 1.844 (95% CI: 1.187-2.865) and readmission is 1.492 (95% CI: 1.231-1.807). CONCLUSION: Recent publications show that the burden of ABR is substantial. There is still a lack of studies on the economic burden of ABR from low-income economies, and lower-middle-income economies, from a societal perspective, and in relation to primary care. The findings of this review may be of value to researchers, policymakers, clinicians, and those who are working in the field of ABR and health promotion. SYSTEMATIC REVIEW REGISTRATION: CRD42020193886.

MetaBayesDTA: codeless Bayesian meta-analysis of test accuracy, with or without a gold standard.

BACKGROUND: The statistical models developed for meta-analysis of diagnostic test accuracy studies require specialised knowledge to implement. This is especially true since recent guidelines, such as those in Version 2 of the Cochrane Handbook of Systematic Reviews of Diagnostic Test Accuracy, advocate more sophisticated methods than previously. This paper describes a web-based application - MetaBayesDTA - that makes many advanced analysis methods in this area more accessible. RESULTS: We created the app using R, the Shiny package and Stan. It allows for a broad array of analyses based on the bivariate model including extensions for subgroup analysis, meta-regression and comparative test accuracy evaluation. It also conducts analyses not assuming a perfect reference standard, including allowing for the use of different reference tests. CONCLUSIONS: Due to its user-friendliness and broad array of features, MetaBayesDTA should appeal to researchers with varying levels of expertise. We anticipate that the application will encourage higher levels of uptake of more advanced methods, which ultimately should improve the quality of test accuracy reviews.

Non-opioid analgesics for the prevention of chronic postsurgical pain: a systematic review and network meta-analysis.

BACKGROUND: Chronic postsurgical pain is common after surgery. Identification of non-opioid analgesics with potential for preventing chronic postsurgical pain is important, although trials are often underpowered. Network meta-analysis offers an opportunity to improve power and to identify the most promising therapy for clinical use and future studies. METHODS: We conducted a PRISMA-NMA-compliant systematic review and network meta-analysis of randomised controlled trials of non-opioid analgesics for chronic postsurgical pain. Outcomes included incidence and severity of chronic postsurgical pain, serious adverse events, and chronic opioid use. RESULTS: We included 132 randomised controlled trials with 23 902 participants. In order of efficacy, i.v. lidocaine (odds ratio [OR] 0.32; 95% credible interval [CrI] 0.17-0.58), ketamine (OR 0.64; 95% CrI 0.44-0.92), gabapentinoids (OR 0.67; 95% CrI 0.47-0.92), and possibly dexmedetomidine (OR 0.36; 95% CrI 0.12-1.00) reduced the incidence of chronic postsurgical pain at ≤6 months. There was little available evidence for chronic postsurgical pain at >6 months, combinations agents, chronic opioid use, and serious adverse events. Variable baseline risk was identified as a potential violation to the network meta-analysis transitivity assumption, so results are reported from a fixed value of this, with analgesics more effective at higher baseline risk. The confidence in these findings was low because of problems with risk of bias and imprecision. CONCLUSIONS: Lidocaine (most effective), ketamine, and gabapentinoids could be effective in reducing chronic postsurgical pain ≤6 months although confidence is low. Moreover, variable baseline risk might violate transitivity in network meta-analysis of analgesics; this recommends use of our methods in future network meta-analyses. SYSTEMATIC REVIEW PROTOCOL: PROSPERO CRD42021269642.

A multifaceted graphical display, including treatment ranking, was developed to aid interpretation of network meta-analysis.

OBJECTIVES: Network meta-analysis (NMA) is becoming a popular statistical tool for analyzing a network of evidence comparing more than two interventions. A particular advantage of NMA over pairwise meta-analysis is its ability to simultaneously compare multiple interventions including comparisons not previously trialed together, permitting intervention hierarchies to be created. Our aim was to develop a novel graphical display to aid interpretation of NMA to clinicians and decision-makers that incorporates ranking of interventions. STUDY DESIGN AND SETTING: Current literature was searched, scrutinized, and provided direction for developing the novel graphical display. Ranking results were often found to be misinterpreted when presented alone and, to aid interpretation and effective communication to inform optimal decision-making, need to be displayed alongside other important aspects of the analysis including the evidence networks and relative intervention effect estimates. RESULTS: Two new ranking visualizations were developed-the 'Litmus Rank-O-Gram' and the 'Radial SUCRA' plot-and embedded within a novel multipanel graphical display programmed within the MetaInsight application, with user feedback gained. CONCLUSION: This display was designed to improve the reporting, and facilitate a holistic understanding, of NMA results. We believe uptake of the display would lead to better understanding of complex results and improve future decision-making.

Incidence of adult primary immune thrombocytopenia in England-An update.

BACKGROUND: Adult primary immune thrombocytopenia (ITP) is a rare bleeding disorder of unknown cause. Recent estimates of its incidence and trend over time were acquired for England. METHOD: The primary ITP population (using ICD 10 code D693 and excluding secondary ITP cases; positive predictive value: 82.6%) was sourced from NHS Digital inpatient and outpatient. Incidence rate (IR) for England and by age groups, sex, and regions were calculated and trends were assessed using average annual percent change (AAPC). RESULTS: A total of 25 805 patients (mean age 59 years; females 57.8%) diagnosed between 2003 and 2014 was identified. IRs increased from 4.2/100 000 to 6.4/100 000 over this period (AAPC:4.3%). For all sex-specific age groups, the IRs significantly increased over time, except 18-29 years males. The greatest increase was among females aged 30-39 (AAPC:8.7%). In contrast, among ≥70 years, ITP was more common in males (highest IR among ≥80 years males: 23.9/100 000). England's average annual IR was 6.1/100 000 for 2010-14. An estimated 2.5/100 000 (based on UKITP Registry data) was estimated to require 1st line treatment whereas 2.4/100 000 would have 1st and 2nd line treatments within 6 months from diagnosis. IRs for London and East Midlands were the highest (6.5/100 000). CONCLUSIONS: This study found a rising incidence of primary ITP, with sharp increases among young women and elderly men. These findings put in context the impact of ITP on patients' lives and the healthcare services in England, especially with 17%-50% who may develop chronic ITP and require long-term care.

Measuring quality of life in trials including patients on haemodialysis: methodological issues surrounding the use of the Kidney Disease Quality of Life Questionnaire.

BACKGROUND: Haemodialysis (HD) treatment causes a significant decrease in quality of life (QoL). When enrolled in a clinical trial, some patients are lost prior to follow-up because they die or they receive a kidney transplant. It is unclear how these patients are dealt with in the analysis of QoL data. There are questions surrounding the consistency of how QoL measures are used, reported and analysed. METHODS: A systematic search of electronic databases for trials measuring QoL in HD patients using any variation of the Kidney Disease Quality of Life (KDQoL) Questionnaire was conducted. The review was conducted in Covidence version 2. Quantitative analysis was conducted in Stata version 16. RESULTS: We included 61 trials in the review, of which 82% reported dropouts. The methods to account for missing data due to dropouts include imputation (7%) and complete case analysis (72%). Few trials (7%) conducted a sensitivity analysis to assess the impact of missing data on the study results. Single imputation techniques were used, but are only valid under strong assumptions regarding the type and pattern of missingness. There was inconsistency in the reporting of the KDQoL, with many articles (70%) amending the validated questionnaires or reporting only statistically significant results. CONCLUSIONS: Missing data are not dealt with according to the missing data mechanism, which may lead to biased results. Inconsistency in the use of patient-reported outcome measures raises questions about the validity of these trials. Methodological issues in nephrology trials could be a contributing factor to why there are limited effective interventions to improve QoL in this patient group. PROSPERO REGISTRATION: CRD42020223869.

Timing of invasive strategy in non-ST-elevation acute coronary syndrome: a meta-analysis of randomized controlled trials.

AIMS: The optimal timing of an invasive strategy (IS) in non-ST-elevation acute coronary syndrome (NSTE-ACS) is controversial. Recent randomized controlled trials (RCTs) and long-term follow-up data have yet to be included in a contemporary meta-analysis. METHODS AND RESULTS: A systematic review of RCTs that compared an early IS vs. delayed IS for NSTE-ACS was conducted by searching MEDLINE, Embase, and Cochrane Central Register of Controlled Trials. A meta-analysis was performed by pooling relative risks (RRs) using a random-effects model. The primary outcome was all-cause mortality. Secondary outcomes included myocardial infarction (MI), recurrent ischaemia, admission for heart failure (HF), repeat re-vascularization, major bleeding, stroke, and length of hospital stay. This study was registered with PROSPERO (CRD42021246131). Seventeen RCTs with outcome data from 10 209 patients were included. No significant differences in risk for all-cause mortality [RR: 0.90, 95% confidence interval (CI): 0.78-1.04], MI (RR: 0.86, 95% CI: 0.63-1.16), admission for HF (RR: 0.66, 95% CI: 0.43-1.03), repeat re-vascularization (RR: 1.04, 95% CI: 0.88-1.23), major bleeding (RR: 0.86, 95% CI: 0.68-1.09), or stroke (RR: 0.95, 95% CI: 0.59-1.54) were observed. Recurrent ischaemia (RR: 0.57, 95% CI: 0.40-0.81) and length of stay (median difference: -22 h, 95% CI: -36.7 to -7.5 h) were reduced with an early IS. CONCLUSION: In all-comers with NSTE-ACS, an early IS does not reduce all-cause mortality, MI, admission for HF, repeat re-vascularization, or increase major bleeding or stroke when compared with a delayed IS. Risk of recurrent ischaemia and length of stay are significantly reduced with an early IS.

Meta-analysis of dichotomous and ordinal tests with an imperfect gold standard.

Standard methods for the meta-analysis of medical tests, without assuming a gold standard, are limited to dichotomous data. Multivariate probit models are used to analyse correlated dichotomous data, and can be extended to model ordinal data. Within the context of an imperfect gold standard, they have previously been used for the analysis of dichotomous and ordinal test data from a single study, and for the meta-analysis of dichotomous tests. However, they have not previously been used for the meta-analysis of ordinal tests. In this article, we developed a Bayesian multivariate probit latent class model for the simultaneous meta-analysis of ordinal and dichotomous tests without assuming a gold standard, which also allows one to obtain summary estimates of joint test accuracy. We fitted the models using the software Stan, which uses a state-of-the-art Hamiltonian Monte Carlo algorithm, and we applied the models to a dataset in which studies evaluated the accuracy of tests, and test combinations, for deep vein thrombosis. We demonstrate the issues with dichotomising ordinal test accuracy data in the presence of an imperfect gold standard, before applying and comparing several variations of our proposed model which do not require the data to be dichotomised. The models proposed will allow researchers to more appropriately meta-analyse ordinal and dichotomous tests without a gold standard, potentially leading to less biased estimates of test accuracy. This may lead to a better understanding of which tests, and test combinations, should be used for any given medical condition.

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.

Feasibility study for interactive reporting of network meta-analysis: experiences from the development of the MetaInsight COVID-19 app for stakeholder exploration, re-analysis and sensitivity analysis from living systematic reviews.

BACKGROUND: Network meta-analysis (NMA) has been increasingly adopted worldwide by Cochrane reviews, guideline developers and decision-making bodies to identify optimal treatment choices. However, NMA results are often produced statically, not allowing stakeholders to 'dig deeper' and interrogate with their own judgement. Additionally, amid the COVID-19 pandemic, unnecessary or duplicated reviews have been proposed which analyse from the same pool of evidence. We developed the 'MetaInsight COVID-19' app as a prototype for an interactive platform to eliminate such duplicated efforts, by empowering users to freely analyse the data and improve scientific transparency. METHODS: MetaInsight COVID-19 ( https://crsu.shinyapps.io/metainsightcovid/ ) was developed to conduct NMA with the evolving evidence on treatments for COVID-19. It was updated weekly between 19th May - 19th Oct 2020, incorporating new evidence identified from a living systematic review. RESULTS: The app includes embedded functions to facilitate study selection based on study characteristics, and displays the synthesised results in real time. It allows both frequentist and Bayesian NMA to be conducted as well as consistency and heterogeneity assessments. A demonstration of the app is provided and experiences of building such a platform are discussed. CONCLUSIONS: MetaInsight COVID-19 allows users to take control of the evidence synthesis using the analytic approach they deem appropriate to ascertain how robust findings are to alternative analysis strategies and study inclusion criteria. It is hoped that this app will help avoid many of the duplicated efforts when reviewing and synthesising the COVID-19 evidence, and, in addition, establish the desirability of an open platform format such as this for interactive data interrogation, visualisation, and reporting for any traditional or 'living' NMA.

Genetic testing in motor neuron disease and frontotemporal dementia: a 5-year multicentre evaluation.

INTRODUCTION: Motor neuron disease (MND) and frontotemporal dementia (FTD) comprise a neurodegenerative disease spectrum. Genetic testing and counselling is complex in MND/FTD owing to incomplete penetrance, variable phenotype and variants of uncertain significance. Affected patients and unaffected relatives are commonly referred to clinical genetics to consider genetic testing. However, no consensus exists regarding how such genetic testing should best be undertaken and on which patients. OBJECTIVE: We sought to ascertain UK clinical genetics testing practice in MND/FTD referrals, with the aim of helping inform guideline development. METHODS: MND/FTD clinical genetics referrals comprising both affected patients and unaffected relatives between 2012 and 2016 were identified and a standardised proforma used to collate data from clinical records. RESULTS: 301 referrals (70 affected, 231 unaffected) were reviewed across 10 genetics centres. Previously identified familial variants were known in 107 cases and 58% subsequently underwent testing (8 of 8 diagnostic and 54 of 99 predictive). The median number of genetic counselling appointments was 2 for diagnostic and 4 for predictive testing. Importantly, application of current UK Genomic Test Directory eligibility criteria would not have resulted in detection of all pathogenic variants observed in this cohort. CONCLUSION: We propose pragmatic MND/FTD genetic testing guidelines based on appropriate genetic counselling.