Keith R Abrams

Keith R Abrams
University of Leicester | LE · Department of Health Sciences

PhD

About

281
Publications
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Publications

Publications (281)
Article
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. COVID-19 an...
Article
Full-text available
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...
Preprint
Multimorbidity is defined as the coexistence of two or more chronic health conditions in an individual. The objective of this study was to examine how diseases in a cluster of physical-mental health multimorbidity with a high all-cause mortality (psychosis, diabetes, and congestive heart failure) develop and coexist over time, and to assess the ass...
Article
Aim: To conduct indirect treatment comparisons between risdiplam and other approved treatments for spinal muscular atrophy (SMA). Patients & methods: Individual patient data from risdiplam trials were compared with aggregated data from published studies of nusinersen and onasemnogene abeparvovec, accounting for heterogeneity across studies. Results...
Preprint
Full-text available
Objective: We aim to utilise real world data in evidence synthesis to optimise an evidence base for the effectiveness of biologic therapies in rheumatoid arthritis in order 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 Biol...
Preprint
Full-text available
Introduction 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 influen...
Article
Full-text available
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 eva...
Article
Introduction The use of real-world data, as an alternative to randomized controlled trials, is becoming increasingly common in the evaluation of new health technologies. With this rise in real-world literature, such data will also enter evidence synthesis models. While it can be beneficial to utilize data from all available sources, this can introd...
Article
Objective: Duchenne Muscular Dystrophy (DMD) is a rare progressive disease, which is often diagnosed in early childhood, and leads to considerably reduced life-expectancy; due to its rarity, research literature and patient numbers are limited. To fully characterise the natural history, it is crucial to obtain appropriate estimates of the life-expe...
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Full-text available
Background Network Meta-Analysis (NMA) is a key component of submissions to reimbursement agencies world-wide, especially when there is limited direct head-to-head evidence for multiple technologies from randomised controlled trials (RCTs). Many NMAs include only data from RCTs. However, real-world evidence (RWE) is also becoming widely recognised...
Article
Full-text available
Background In oncology trials, treatment switching from the comparator to the experimental regimen is often allowed but may lead to underestimating overall survival (OS) of an experimental therapy.Objective This study evaluates the impact of treatment switching from control to olaparib on OS using the final survival data from the PROfound study and...
Article
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Introduction The COVID-19 pandemic has resulted in significant morbidity and mortality and devastated economies globally. Among groups at increased risk are healthcare workers (HCWs) and ethnic minority groups. Emerging evidence suggests that HCWs from ethnic minority groups are at increased risk of adverse COVID-19-related outcomes. To date, there...
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Full-text available
Introduction: COVID-19 has spread rapidly worldwide, causing significant morbidity and mortality. People from ethnic minorities, particularly those working in healthcare settings, have been disproportionately affected. Current evidence of the association between ethnicity and COVID-19 outcomes in people working in healthcare settings is insufficie...
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Full-text available
Background Use of real world data (RWD) from non-randomised studies (e.g. single-arm studies) is increasingly being explored to overcome issues associated with data from randomised controlled trials (RCTs). We aimed to compare methods for pairwise meta-analysis of RCTs and single-arm studies using aggregate data, via a simulation study and applicat...
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Background Gestational Diabetes Mellitus (GDM) is the most prevalent metabolic disorder during pregnancy, however, the association between dyslipidaemia and GDM remains unclear. Methods We searched Medline, Scopus, Web of Science, Cochrane, Maternity and Infant Care database (MIDIRS) and ClinicalTrials.gov up to February 2021 for relevant studies...
Preprint
Full-text available
Introduction The COVID-19 pandemic has resulted in significant morbidity and mortality, and has devastated economies in many countries. Amongst the groups identified as being at increased risk from COVID-19 are healthcare workers (HCWs) and ethnic minority groups. Emerging evidence suggests HCWs from ethnic minority groups are at increased risk of...
Preprint
Full-text available
The role of health technology assessment (HTA) in low- and middle-income countries (LMICs) has become increasingly important in order to inform resource allocation and wider health policy decision-making. Using the case study of Tunisia’s first published HTA on trastuzumab in early and locally advanced HER2 positive breast cancer, we aim to evaluat...
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Background The complexity of public health interventions create challenges in evaluating their effectiveness. There have been huge advancements in quantitative evidence synthesis methods development (including meta-analysis) for dealing with heterogeneity of intervention effects, inappropriate ‘lumping’ of interventions, adjusting for different pop...
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Full-text available
Introduction Multimorbidity is widely recognised as the presence of two or more concurrent long-term conditions, yet remains a poorly understood global issue despite increasing in prevalence. We have created the Wales Multimorbidity e-Cohort (WMC) to provide an accessible research ready data asset to further the understanding of multimorbidity. Our...
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Full-text available
Background Patients from ethnic minority groups are disproportionately affected by Coronavirus disease (COVID-19). We performed a systematic review and meta-analysis to explore the relationship between ethnicity and clinical outcomes in COVID-19. Methods Databases (MEDLINE, EMBASE, PROSPERO, Cochrane library and MedRxiv) were searched up to 31st A...
Article
Background: The aim of this study was to describe outcomes in hospitalised older people with different levels of frailty and COVID-19 infection. Methods: We undertook a single centre, retrospective cohort study examining COVID-19 related mortality using Electronic Health Records, for older people (65 and over) with frailty, hospitalised with or...
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Full-text available
Background: Network meta-analysis synthesises data from a number of clinical trials in order to assess the comparative efficacy of multiple healthcare interventions in similar patient populations. In situations where clinical trial data are heterogeneously reported i.e. data are missing for one or more outcomes of interest, synthesising such data...
Preprint
Bivariate meta-analysis provides a useful framework for combining information across related studies and has been widely utilised to combine evidence from clinical studies in order to evaluate treatment efficacy. Bivariate meta-analysis has also been used to investigate surrogacy patterns between treatment effects on the surrogate and the final out...
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Full-text available
Surrogate endpoints play an important role in drug development when they can be used to measure treatment effect early compared to the final clinical outcome and to predict clinical benefit or harm. Such endpoints are assessed for their predictive value of clinical benefit by investigating the surrogate relationship between treatment effects on the...
Preprint
Full-text available
Background: Network meta-analysis synthesises data from a number of clinical trials in order to assess the comparative efficacy of multiple healthcare interventions in similar patient populations. In situations where clinical trial data are heterogeneously reported i.e. data are missing for one or more outcomes of interest, synthesising such data c...
Preprint
Full-text available
Background: Network meta-analysis synthesises data from a number of clinical trials in order to assess the comparative efficacy of multiple healthcare interventions in similar patient populations. In situations where clinical trial data are heterogeneously reported i.e. data are missing for one or more outcomes of interest, synthesising such data c...
Preprint
Full-text available
Background: Pre-marketing authorisation estimates of survival are generally restricted to those observed directly in randomised controlled trials (RCTs). However, for regulatory and Health Technology Assessment (HTA) decision-making a longer time horizon is often required than is studied in RCTs. Therefore, extrapolation is required to estimate lon...
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Full-text available
Drug development for rare diseases is challenged by small populations and limited data. This makes development of clinical trial protocols difficult and contributes to the uncertainty around whether or not a potential therapy is efficacious. The use of data standards to aggregate data from multiple sources, and the use of such integrated databases...
Article
Electronic health records are being increasingly used in medical research to answer more relevant and detailed clinical questions; however, they pose new and significant methodological challenges. For instance, observation times are likely correlated with the underlying disease severity: Patients with worse conditions utilise health care more and m...
Article
Survival models incorporating random effects to account for unmeasured heterogeneity are being increasingly used in biostatistical and applied research. Specifically, unmeasured covariates whose lack of inclusion in the model would lead to biased, inefficient results are commonly modeled by including a subject‐specific (or cluster‐specific) frailty...
Preprint
Surrogate endpoints play an important role in drug development when they can be used to measure treatment effect early compared to the final clinical outcome and to predict clinical benefit or harm. Therefore, such endpoints must be assessed for their predictive value of clinical benefit by investigating the surrogate relationship between treatment...
Article
Full-text available
Surrogate endpoints are very important in regulatory decision making in healthcare, in particular if they can be measured early compared to the long‐term final clinical outcome and act as good predictors of clinical benefit. Bivariate meta‐analysis methods can be used to evaluate surrogate endpoints and to predict the treatment effect on the final...
Article
Full-text available
Introduction The association between cancer of the esophagus and achalasia has long been recognized. However, it has also been recognized that cancers themselves can give rise to achalasia‐like syndromes. The risk of developing cancer is also a factor in assessing whether there is a potential role for surveillance in this disease. This paper uses p...
Preprint
Full-text available
Electronic health records are being increasingly used in medical research to answer more relevant and detailed clinical questions; however, they pose new and significant methodological challenges. For instance, observation times are likely correlated with the underlying disease severity: patients with worse conditions utilise health care more and m...
Preprint
Full-text available
Survival models incorporating random effects to account for unmeasured heterogeneity are being increasingly used in biostatistical and applied research. Specifically, unmeasured covariates whose lack of inclusion in the model would lead to biased, inefficient results are commonly modelled by including a subject-specific (or cluster-specific) frailt...
Data
DS_10.1177_0272989X18788537 – Supplemental material for Bayesian Multiparameter Evidence Synthesis to Inform Decision Making: A Case Study in Metastatic Hormone-Refractory Prostate Cancer
Article
Full-text available
Background: When designing studies it is common to search the literature to investigate variability estimates to use in sample size calculations. Proprietary data of previously designed trials in a particular indication are also used to obtain estimates of variability. Estimates of treatment effects are typically obtained from randomised controlle...
Preprint
Surrogate endpoints are very important in regulatory decision-making in healthcare, in particular if they can be measured early compared to the long-term final clinical outcome and act as good predictors of clinical benefit. Bivariate meta-analysis methods can be used to evaluate surrogate endpoints and to predict the treatment effect on the final...
Preprint
Full-text available
Background: Network Meta-Analysis (NMA) is a key component of submissions to reimbursement agencies world-wide, especially when there is limited direct head-to-head evidence for multiple technologies from randomised control trials (RCTs). Almost all NMAs include only data from RCTs. However, real-world evidence (RWE) is also becoming widely recogni...
Article
Full-text available
Standard methods for indirect comparisons and network meta-analysis are based on aggregate data, with the key assumption that there is no difference between the trials in the distribution of effect-modifying variables. Methods which relax this assumption are becoming increasingly common for submissions to reimbursement agencies such as NICE. These...
Article
Full-text available
In health technology assessment, decisions are based on complex cost-effectiveness models which, to be implemented, require numerous input parameters. When some of relevant estimates are not available the model may have to be simplified. Multi-parameter evidence synthesis allows to combine data from diverse sources of evidence resulting in obtainin...
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Full-text available
Background Microvascular obstruction (MVO) predicts short- and longer-term outcomes following primary percutaneous coronary intervention (PPCI) treatment of ST-elevation myocardial infarction (STEMI). The evidence base supporting the role of adenosine and sodium nitroprusside (SNP), the most evaluated adjunctive therapies aimed at attenuating MVO a...
Article
Reliance on “real world” observational data undermines evidence base for clinical practice The reforms to the Cancer Drugs Fund implemented in July were an excellent opportunity to generate evidence on the effectiveness of new cancer drugs.1 Unlike under the previous arrangements, data on patients’ outcomes will have to be collected for all drugs...
Article
Background: Human chorionic gonadotrophin (hCG) is a marker of early pregnancy. This study sought to determine the possibility of being able to distinguish between healthy and failing pregnancies by utilising patient-associated risk factors and daily urinary hCG levels. Methods: Data were from a study that collected daily early morning urine sam...
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Full-text available
Background: Patients with atrial fibrillation are at a greater risk of stroke and therefore the main goal for treatment of patients with atrial fibrillation is to prevent stroke from occurring. There are a number of different stroke prevention treatments available to include warfarin and novel oral anticoagulants. Previous network meta-analyses of...
Data
Supporting Information. (DOCX)
Article
Aims: To assess effects of repeat treatment with onabotulinumtoxin A (onaBoNT-A) in women with refractory idiopathic detrusor overactivity (DO). Methods: Analysis of an open-label extension study of a large randomized placebo controlled trial of onaBoNT-A. Participants had been randomized to receive 200 IU onaBoNTA or placebo and were offered up...
Article
In meta-analysis, the random-effects model is often used to account for heterogeneity. The model assumes that heterogeneity has an additive effect on the variance of effect sizes. An alternative model, which assumes multiplicative heterogeneity, has been little used in the medical statistics community, but is widely used by particle physicists. In...
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Full-text available
Background Microvascular obstruction (MVO) following primary percutaneous coronary intervention (PPCI) treatment of ST-segment elevation myocardial infarction (STEMI) contributes to infarct expansion, left ventricular (LV) remodelling, and worse clinical outcomes. The REFLO-STEMI trial tested whether intra-coronary (IC) high-dose adenosine or sodiu...
Article
Full-text available
Trametinib, a selective inhibitor of mitogen-activated protein kinase kinase 1 (MEK1) and MEK2, significantly improves progression-free survival compared with chemotherapy in patients with BRAF V600E/K mutation–positive advanced or metastatic melanoma (MM). However, the pivotal clinical trial permitted randomized chemotherapy control group patients...
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Full-text available
When patients randomised to the control group of a randomised controlled trial are allowed to switch onto the experimental treatment, intention-to-treat analyses of the treatment effect are confounded because the separation of randomised groups is lost. Previous research has investigated statistical methods that aim to estimate the treatment effect...