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Epidemiological investigation and economic analysis of Polycystic Ovary Syndrome (PCOS) for women in the UK

Ding, Tao; (2018) Epidemiological investigation and economic analysis of Polycystic Ovary Syndrome (PCOS) for women in the UK. Doctoral thesis (Ph.D), UCL (University College London). Green open access

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Abstract

BACKGROUND: Polycystic ovary syndrome (PCOS) is an endocrine disorder affecting millions of women worldwide. The pathophysiology of this condition is unclear but is believed to be caused by some genetic and environmental factors. PCOS is associated with a range of reproductive, metabolic and dermatological disorders and therefore, the economic burden of this condition can be potentially significant for the public health system in the UK. METHODS: The methodology used for this research includes several parts. Firstly, I conducted literature reviews to identify studies reporting the prevalence of PCOS and morbidities associated PCOS. The Bayesian hierarchical model was then applied to model data from the published studies. This forms the rst part of this research for which the analysis was based on aggregate data. In the second part, I investigated the incidence and prevalence of PCOS under the specific UK context using data from The Health Improvement Network (THIN), a primary care database with over 500 general practices contributing data each year. I then used a multi-state Markov model to simulate the population dynamics of PCOS and evaluated the associated economic burden of care as well as the quality of life for the entire population with this condition in the UK. RESULTS: The prevalence estimates from community studies are generally much higher compared with that from database studies. The prevalence of PCOS varies for different diagnostic criteria and across distinct ethnic groups. Women with PCOS are at higher risk of type 2 diabetes, obesity, cardiovascular diseases and pregnancy complications and are more likely to experience psychological disorders. The prevalence of PCOS in the UK is estimated to be approximately 2% based on the primary care data, with an annual incidence rate of 2 per 1000 person-year. There is wide variation in the prescriptions initiated for the PCOS patients. The prevalence of type 2 diabetes in the PCOS population is estimated to increase to approximately 26% in the next 25 years in the UK, which significantly reduces the quality of life for individual patients and incurs massive amount of healthcare-related costs for the National Health Service (NHS). CONCLUSIONS: The large gap between the prevalence rates estimated from community and database studies suggests that PCOS is a condition without much public awareness and under-reporting is often observed. The differences in prevalence rates estimated according to different diagnostic criteria indicates the potential issue of under- and over-diagnosis of the condition at present. The ethnic variation in terms of the diagnostic criteria, disease monitoring and management may need to be considered carefully. The prescribing patterns of PCOS in the primary care suggest that currently, there is lack of most effective treatment for this condition and patients generally receive treatments tailored to their external symptoms. The prevalence of type 2 diabetes among PCOS patients is estimated to be high, resulting in massive amount of healthcare costs and reduced quality of life for PCOS population in the UK. Early screening is likely to help reduce the adverse outcomes associated with PCOS for this selected population and it may be cost effective to include them in the current Diabetes Prevention Programme. This may help improve the detection of symptoms indicative of diabetes in PCOS patients to allow early interventions and save significant amount of healthcare costs for the NHS from the country perspective.

Type: Thesis (Doctoral)
Qualification: Ph.D
Title: Epidemiological investigation and economic analysis of Polycystic Ovary Syndrome (PCOS) for women in the UK
Event: University College London
Open access status: An open access version is available from UCL Discovery
Language: English
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science
URI: https://discovery.ucl.ac.uk/id/eprint/10045238
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