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[Published Journal] Using Observational Studies to Investigate the Relationship Between Fatigue and Work Disability

Statistical Consultancy Team

Our Statistical Consultancy Team recently collaborated on a study to investigate the long-term relationship between fatigue and work disability in patients initiating treatment with etanercept for rheumatoid arthritis (RA) or ankylosing spondylitis (AS); and this work has now been published. (https://arthritis-research.biomedcentral.com/articles/10.1186/s13075-018-1598-8)

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Topics: Statistical Consultancy, Observation Longitudinal Database, Observational Studies, Inflammatory Rheumatic Diseases, Rheumatoid Arthritis (RA)

Outcomes Research Programming vs Traditional Clinical Trial Programming

Clinical Programming Team

Outcomes research aka health outcomes research, is the study of the end results of particular health care practices and interventions, in other words it is the study of what happens in the real world to patients when they are given a certain treatment or a certain method of care. Outcomes research studies are used to improve the quality and value of healthcare for patients.

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Topics: Statistical Programming, Clinical Study Design, Clinical Programming, Accessible Data, Big Data, Outcomes Research, Real World Data, Teradata SQL, Observation Longitudinal Database

Longitudinal Observational Data in a Paediatric Disease Registry

Statistical Consultancy Team

The use of population-based disease registries to support ongoing data collection for long-term safety and clinical outcomes is becoming increasingly common. Data collection methods within registries can vary in terms of completeness and quality. This particular example arose from support to a post-registration commitment for marketing authorisation of a paediatric drug and aims to provide some insight to the techniques and strategies used to monitor paediatric development (growth, sexual maturation) and clinical outcomes of varying severity. The challenges of accounting for irregular follow-up and associated biases are illustrated, and potential statistical solutions described. Recommendations for future reporting are presented as part of the conclusions. 

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Topics: Statistical Programming, Randomization, Paediatric Disease Registry, Outcomes Research, Real World Data, Observation Longitudinal Database

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