Direct and indirect effects of the COVID-19 pandemic on mortality: an individual-level population-scale analysis using linked electronic health records, Wales, United Kingdom, 2016 to 2022.

BackgroundThe COVID-19 pandemic resulted in increased mortality directly and indirectly associated with COVID-19.AimTo assess the impact of the COVID-19 pandemic on all-cause and disease-specific mortality and explore potential health inequalities associated with area-level deprivation in Wales.MethodsTwo population-based cohort studies were derived from multi-sourced, linked demographic, administrative and electronic health record data from 2016 to 2019 (n = 3,113,319) and 2020 to 2022 (n = 3,571,471).

Factors Associated With Early Motor Function Trajectories in DMD After Glucocorticoid Initiation: Post Hoc Analysis of the FOR-DMD Trial.

Background And Objectives: Clinical trials in Duchenne muscular dystrophy (DMD) require 3-6 months of stable glucocorticoids, and the primary outcome is explored at 48-52 weeks. The factors that influence the clinical outcome assessment (COA) trajectories soon after glucocorticoid initiation are relevant for the design and analysis of clinical trials of novel drugs. We describe early COA trajectories, associated factors, and the time from glucocorticoid initiation to COA peak.

Clustering long-term health conditions among 67728 people with multimorbidity using electronic health records in Scotland.

There is still limited understanding of how chronic conditions co-occur in patients with multimorbidity and what are the consequences for patients and the health care system. Most reported clusters of conditions have not considered the demographic characteristics of these patients during the clustering process. The study used data for all registered patients that were resident in Fife or Tayside, Scotland and aged 25 years or more on 1st January 2000 and who were followed up until 31st December 2018.

Natural history of Duchenne muscular dystrophy in the United Kingdom: A descriptive study using the Clinical Practice Research Datalink.

Background: Duchenne muscular dystrophy (DMD) is a rare, muscle-degenerative disease predominantly affecting males. Natural history models capture the full disease pathway under current care and combine with estimates of new interventions' effects to assess cost-effectiveness by health technology decision-makers. These models require mortality estimates throughout a patient's lifetime, but rare disease datasets typically contain relatively few patients with short follow-ups.

Modeling the multi-state natural history of rare diseases with heterogeneous individual patient data: A simulation study.

Multi-state survival models are used to represent the natural history of a disease, forming the basis of a health technology assessment comparing a novel treatment to current practice. Constructing such models for rare diseases is problematic, since evidence sources are typically much sparser and more heterogeneous. This simulation study investigated different one-stage and two-stage approaches to meta-analyzing individual patient data (IPD) in a multi-state survival setting when the number and size of studies being meta-analyzed are small.

Individual participant data from digital sources informed and improved precision in the evaluation of predictive biomarkers in Bayesian network meta-analysis.

Objectives: We aimed to develop a network meta-analytic model for the evaluation of treatment effectiveness within predictive biomarker subgroups, by combining evidence from individual participant data (IPD) from digital sources (in the absence of randomized controlled trials) and aggregate data (AD).

Study Design And Setting: A Bayesian framework was developed for modeling time-to-event data to evaluate predictive biomarkers. IPD were sourced from electronic health records, using a target trial emulation approach, or digitized Kaplan-Meier curves.

Transporting Comparative Effectiveness Evidence Between Countries: Considerations for Health Technology Assessments.

Internal validity is often the primary concern for health technology assessment agencies when assessing comparative effectiveness evidence. However, the increasing use of real-world data from countries other than a health technology assessment agency's target population in effectiveness research has increased concerns over the external validity, or "transportability", of this evidence, and has led to a preference for local data. Methods have been developed to enable a lack of transportability to be addressed, for example by accounting for cross-country differences in disease characteristics, but their consideration in health technology assessments is limited.

Trajectories in chronic disease accrual and mortality across the lifespan in Wales, UK (2005-2019), by area deprivation profile: linked electronic health records cohort study on 965,905 individuals.

Background: Understanding and quantifying the differences in disease development in different socioeconomic groups of people across the lifespan is important for planning healthcare and preventive services. The study aimed to measure chronic disease accrual, and examine the differences in time to individual morbidities, multimorbidity, and mortality between socioeconomic groups in Wales, UK.

Methods: Population-wide electronic linked cohort study, following Welsh residents for up to 20 years (2000-2019).

Prognostic Value of Neurotrophic Tyrosine Receptor Kinase Gene Fusions in Solid Tumors for Overall Survival: A Systematic Review and Meta-Analysis.

Purpose: Evidence suggests that neurotrophic tyrosine receptor kinase () gene fusions in solid tumors are predictive biomarkers for targeted inhibition across a number of adult and pediatric tumor types. However, despite robust clinical response to tyrosine receptor kinase (TRK) inhibitors, the natural history and prognostic implications of fusions in solid tumors are poorly understood. It is important to evaluate their prognostic significance on survival to provide some context to the clinical effectiveness observed in clinical trials of TRK-targeted therapies.

Cost-Effectiveness Analysis of Siltuximab for Australian Public Investment in the Rare Condition Idiopathic Multicentric Castleman Disease.

Objectives: This paper presents an Australian model that formed part of the health technology assessment for public investment in siltuximab for the rare condition of idiopathic Multicentric Castleman Disease (iMCD) in Australia.

Methods: Two literature reviews were conducted to identify the appropriate comparator and model structure. Survival gain based on available clinical trial data were modelled using an Excel-based model semi-Markov model including time-varying transition probabilities, an adjustment for trial crossover and long-term data.

Hierarchical network meta-analysis models for synthesis of evidence from randomised and non-randomised studies.

Background: With the increased interest in the inclusion of non-randomised data in network meta-analyses (NMAs) of randomised controlled trials (RCTs), analysts need to consider the implications of the differences in study designs as such data can be prone to increased bias due to the lack of randomisation and unmeasured confounding. This study aims to explore and extend a number of NMA models that account for the differences in the study designs, assessing their impact on the effect estimates and uncertainty.

Methods: Bayesian random-effects meta-analytic models, including naïve pooling and hierarchical models differentiating between the study designs, were extended to allow for the treatment class effect and accounting for bias, with further extensions allowing for bias terms to vary depending on the treatment class.

Double-counting of populations in evidence synthesis in public health: a call for awareness and future methodological development.

Background: There is a growing interest in the inclusion of real-world and observational studies in evidence synthesis such as meta-analysis and network meta-analysis in public health. While this approach offers great epidemiological opportunities, use of such studies often introduce a significant issue of double-counting of participants and databases in a single analysis. Therefore, this study aims to introduce and illustrate the nuances of double-counting of individuals in evidence synthesis including real-world and observational data with a focus on public health.

Comparative review of pharmacological therapies in individuals with HER2-positive advanced breast cancer with focus on hormone receptor subgroups.

Breast cancer is the fifth leading cause of cancer-related deaths worldwide. The randomized controlled trials (RCTs) of targeted therapies in human epidermal receptor 2 (HER2)-positive advanced breast cancer (ABC) have provided an evidence base for regulatory and reimbursement agencies to appraise the use of cancer therapies in clinical practice. However, a subset of these patients harbor additional biomarkers, for example, a positive hormone receptor status that may be more amenable to therapy and improve overall survival (OS).

Use of copula to model within-study association in bivariate meta-analysis of binomial data at the aggregate level: A Bayesian approach and application to surrogate endpoint evaluation.

Bivariate meta-analysis provides a useful framework for combining information across related studies and has been utilized to combine evidence from clinical studies to evaluate treatment efficacy on two outcomes. It has also been used to investigate surrogacy patterns between treatment effects on the surrogate endpoint and the final outcome. Surrogate endpoints play an important role in drug development when they can be used to measure treatment effect early compared to the final outcome and to predict clinical benefit or harm.

Bridging disconnected networks of first and second lines of biologic therapies in rheumatoid arthritis with registry data: bayesian evidence synthesis with target trial emulation.

Objectives: We aim to use real-world data in evidence synthesis to optimize an evidence base for the effectiveness of biologic therapies in rheumatoid arthritis to allow for evidence on first-line therapies to inform second-line effectiveness estimates.

Study Design And Setting: We use data from the British Society for Rheumatology Biologics Register for Rheumatoid Arthritis to supplement randomized controlled trials evidence obtained from the literature, by emulating target trials of treatment sequences to estimate treatment effects in each line of therapy. Treatment effects estimates from the target trials inform a bivariate network meta-analysis (NMA) of first-line and second-line treatments.

Bayesian network meta-analysis methods for combining individual participant data and aggregate data from single arm trials and randomised controlled trials.

Background: Increasingly in network meta-analysis (NMA), there is a need to incorporate non-randomised evidence to estimate relative treatment effects, and in particular in cases with limited randomised evidence, sometimes resulting in disconnected networks of treatments. When combining different sources of data, complex NMA methods are required to address issues associated with participant selection bias, incorporating single-arm trials (SATs), and synthesising a mixture of individual participant data (IPD) and aggregate data (AD). We develop NMA methods which synthesise data from SATs and randomised controlled trials (RCTs), using a mixture of IPD and AD, for a dichotomous outcome.

The association between frailty risk and COVID-19-associated all-mortality in hospitalised older people: a national cohort study.

Introduction: Frailty has emerged as an important construct to support clinical decision-making during the COVID-19 pandemic. However, doubts remain related to methodological limitations of published studies.

Methods: Retrospective cohort study of all people aged 75 + admitted to hospital in England between 1 March 2020 and 31 July 2021.

Risk factors associated with SARS-CoV-2 infection in a multiethnic cohort of United Kingdom healthcare workers (UK-REACH): A cross-sectional analysis.

Background: Healthcare workers (HCWs), particularly those from ethnic minority groups, have been shown to be at disproportionately higher risk of infection with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) compared to the general population. However, there is insufficient evidence on how demographic and occupational factors influence infection risk among ethnic minority HCWs.

Methods And Findings: We conducted a cross-sectional analysis using data from the baseline questionnaire of the United Kingdom Research study into Ethnicity and Coronavirus Disease 2019 (COVID-19) Outcomes in Healthcare workers (UK-REACH) cohort study, administered between December 2020 and March 2021.

Effect of Transcatheter Aortic Valve Implantation vs Surgical Aortic Valve Replacement on All-Cause Mortality in Patients With Aortic Stenosis: A Randomized Clinical Trial.

Importance: Transcatheter aortic valve implantation (TAVI) is a less invasive alternative to surgical aortic valve replacement and is the treatment of choice for patients at high operative risk. The role of TAVI in patients at lower risk is unclear.

Objective: To determine whether TAVI is noninferior to surgery in patients at moderately increased operative risk.

How does risdiplam compare with other treatments for Types 1-3 spinal muscular atrophy: a systematic literature review and indirect treatment comparison.

To conduct indirect treatment comparisons between risdiplam and other approved treatments for spinal muscular atrophy (SMA). Individual patient data from risdiplam trials were compared with aggregated data from published studies of nusinersen and onasemnogene abeparvovec, accounting for heterogeneity across studies. In Type 1 SMA, studies of risdiplam and nusinersen included similar populations.

Treatments for Chronic Kidney Disease: A Systematic Literature Review of Randomized Controlled Trials.

Delaying disease progression and reducing the risk of mortality are key goals in the treatment of chronic kidney disease (CKD). New drug classes to augment renin-angiotensin-aldosterone system (RAAS) inhibitors as the standard of care have scarcely met their primary endpoints until recently. This systematic literature review explored treatments evaluated in patients with CKD since 1990 to understand what contemporary data add to the treatment landscape.