Natural menopause is the process by which women stop having periods due to aging and is the result of decline in specific hormones within the body. Menopausal women can experience a variety of symptoms that impact their daily routine, the most bothersome reported to be hot flashes (termed vasomotor symptoms [VMS]) and sleep disturbances. Effective treatment options include hormone therapy (HT) however, many women cannot use HT due to certain other conditions, such as breast cancer or history of heart attack. Some choose not to take HT because of concerns around the safety of the treatment.
It is important to quantify the number of patients with menopausal symptoms who might benefit from treatments that don’t contain hormones in order to manage their symptoms and maintain regular activities. However, women who are experiencing menopause may not always be categorized under a menopause diagnosis in medical records.
This study will use different criteria to define women likely experiencing menopause, including those not able to use HT, and describe them in terms of age, use of medications and other diseases they may experience before/after menopause using healthcare databases in five countries (including UK), before and after the start of the COVID-19 pandemic (given known differences in healthcare use widely reported after the pandemic start). The number of women who experienced VMS or sleep disturbances will be assessed. Differences seen between these definitions will provide foundations for development of a consistent definition of menopause and symptoms that can be used in future database studies.
This study aims to understand potential sources of variability that has previously led to diverse estimates of prevalence of menopausal symptoms.
Primary objective - to understand differences in characteristics of menopausal women as the result of differing cohort inclusion and exclusion criteria to be applied.
Secondary objective - to understand how different cohort and case definitions impact epidemiological estimates of vasomotor symptoms (VMS) and sleep disturbances.
Exploratory objective - to explore characteristics of menopausal women, and incidence and prevalence rates of VMS and sleep disturbances before (2010-2019) and after the start of the COVID-19 pandemic (2020+).
This is a multi-national retrospective cohort study to be executed against 6 observational healthcare databases, including CPRD, mapped to the Observational Medical Outcomes Partnership Common Data Model across five countries (UK, US, Japan, France, Germany).
Multiple target cohort definitions are proposed. Patient characteristics (age, BMI) will be assessed along with comorbidities and medication use characterized within multiple time periods relative to cohort entry. Prevalence and incidence rates of VMS and sleep disturbances in each cohort will be calculated. Kaplan-Meier analyses will assess time from cohort entry to VMS and sleep disturbances.
Women experience a variety of physical and psychological menopausal symptoms that impact quality of life, work productivity and daily routine. VMS, along with sleep disturbances are the most frequent and bothersome reported. Studies of menopause utilizing healthcare databases are scarce and in the few published, inclusion criterion vary substantially with no standard algorithm for identifying menopause or its symptoms. This study provides a mechanism for generating foundational evidence to understand differences in patient characteristics and epidemiological estimates in the absence of a gold standard clinical definition. Outputs are intended to be used in the development of a reproducible definition of menopause and symptoms to be used in analysis of healthcare databases going forward.
Patient characteristics: age; body mass index; comorbidities; medication use; Prevalence of vasomotor symptoms; Prevalence of sleep disturbances; Incidence of vasomotor symptoms; Incidence of sleep disturbances
Victoria Banks - Chief Investigator - Bayer AG
Victoria Banks - Corresponding Applicant - Bayer AG
Cecile Janssenswillen - Collaborator - Bayer AG
Ronald Herrera - Collaborator - Bayer AG
Siir Su Saydam - Collaborator - Bayer AG