Nutritional and Metabolic Diseases

Gland and Hormone Related Diseases

All Conditions

Behaviors and Mental Disorders

Nervous System Diseases

Urinary Tract, Sexual Organs, and Pregnancy Conditions

Respiratory Tract (Lung and Bronchial) Diseases

Symptoms and General Pathology

Heart and Blood Diseases

Immune System Diseases

Musculoskeletal Diseases

Skin and Connective Tissue Diseases

Rare Diseases

Diabetes Mellitus

Depressive Disorder

Dementia

Kidney Diseases

Mental Disorders

Lung Diseases, Obstructive

Pulmonary Disease, Chronic Obstructive

Depression

Obesity

Heart Failure

Asthma

Stroke

Atrial Fibrillation

Coronary Artery Disease

Myocardial Ischemia

Coronary Disease

Hypertension

Heart Diseases

Ischemia

Arthritis

Epilepsy

Lung Diseases

Peripheral Arterial Disease

Peripheral Vascular Diseases

Arthritis, Rheumatoid

Ischemic Stroke

Renal Insufficiency, Chronic

Renal Insufficiency

Vascular Diseases

Psychotic Disorders

Arrhythmias, Cardiac

Urologic Diseases

Urogenital Diseases

Female Urogenital Diseases

Pregnancy Complications

Female Urogenital Diseases and Pregnancy Complications

Male Urogenital Diseases

Respiratory Tract Diseases

Brain Diseases

Central Nervous System Diseases

Chronic Disease

Disease Attributes

Atherosclerosis

Arteriosclerosis

Arterial Occlusive Diseases

Cerebrovascular Disorders

Chronic Graft Versus Host Disease

There are 19 disease areas under investigation. Enrolled patients are segmented into cohorts based on data collected through questionnaires and medical histories. This data-driven approach does not allow for precisely predefined cohorts for the diseases under investigation. Therefore, as a default, the two general predefined cohorts are set as either displaying or not displaying a trait that would form the basis of an investigation.

Dr Mohammed Kamran

Mohammed Kamran, PhD

Health inequality and genetic disparity are a significant issue in the United Kingdom (UK).

This study focuses on diseases that are associated with significant morbidity and mortality in the UK, and specifically examines the extent and basis of treatment failure in different patient populations.

The vast majority of drug registration clinical trials have under-representation of ethnic minority populations. In addition, the wider Caucasian populations have reasonably different clinical characteristics to the population that participated in the drug licencing clinical trials. A consequence of this is that drugs are licensed for use in real-world general patient populations where the clinical trial results are simply not statistically significant to specifically demonstrate efficacy or safety in populations that were either absent or under-represented in the drug registration clinical trials. When these facts are considered alongside data that supports significant under-reporting of adverse events in the real-world setting within the UK (and globally, e.g the USA and Europe), it highlights that pharmacovigilance systems are unable to capture drug effectiveness and safety data in a manner that can reasonably assure appropriate prescribing in the wider patient populations.

This large real-world research study aims to identify whether commonly prescribed drugs are effective in treating illnesses that cause significant poor health and death in the different patient populations that represent the UK.

The goal of this study is to generate large quantitative data-sets that may inform clinical practice to reduce the existing health inequality and genetic disparity in the UK.

This multi-centre real-world study will recruit patients across different National Health Service (NHS) sites based in England, where the overall patient population demographic profile is sufficiently variable to allow for meaningful representation of different ethnicities in the analysis of pooled data-sets.

The study addresses the issue of health inequality and genetic disparity in the United Kingdom (UK) by recruiting up to 200,000 patients primarily from the three main ethnic groups in the UK; namely White (Caucasian), African-Caribbean (Black), and South Asian (Asian) populations on a 1:1:1 ratio.

Biological samples, medical records, alongside specific questionnaires will be used in data analyses to help identify treatment failures in different populations for the 19 disease areas under investigation, which are a significant cause of morbidity and mortality in the UK.

Analysis of patient populations may provide real-world evidence around disease prevalence between and within different ethnic groups. The data may also support hypothesis driven genetic analysis to identify putative bio-markers associated with treatment failure.

Data from this study will be published, and findings could better inform clinical practice in the management of diseases that cause significant poor health and death in the different populations that represent the UK.

Saliva. Where practical, blood or other biological samples may also be voluntarily provided by the patient.

EMPOWER-1: A Multi-site Clinical Cohort Research Study to Reduce Health Inequality

EMPOWER-1: A Multi-site Clinical Cohort Study to Reduce Health Inequality: Identifying Ethnic Disparities in Treatment Failures for Medicines Prescribed to Treat Diseases That Cause Significant Mortality and Morbidity in the UK Population

Identify ethnic disparities in treatment failures for any of the 19 disease states under investigation. The primary outcome is treatment failure, as measured by the discontinuation of a treatment regimen by a clinician in the absence of the cure of the disease, for the most common treatment in each of the 19 diseases.

Identifying ethnic disparities in disease incidence. The corresponding secondary outcome measure for this is, for each of the 19 diseases under consideration, the diagnosis of the disease. We will use time to diagnosis to examine ethnic disparities in incidence.

Another secondary outcome is identifying candidate genetic variants that may underpin observed disparities in treatment failure, for treatments in the 19 diseases under consideration. The corresponding secondary outcome measures used for this are genotypes as identified through whole genome sequencing (WGS) of patient saliva or peripheral blood that are associated with the phenotypes corresponding to the treatment failure previously described as the primary outcome measure.

Future Genetics Limited

Spots Global Cancer Trial Database for equality

Every month we try and update this database with for equality cancer trials from around the world to help patients and their families find trials that might be right for them.
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Spots Global Cancer Trial Database for equality

Every month we try and update this database with for equality cancer trials from around the world to help patients and their families find trials that might be right for them. We offer this 100% free of charge and do not endorse any of the trials listed here, we hope it helps you or a loved one.

Every month we try and update this database with for equality cancer trials from around the world to help patients and their families find trials that might be right for them.
We offer this 100% free of charge and do not endorse any of the trials listed here, we hope it helps you or a loved one.