Heavy menstrual bleeding (HMB) is an excessive menstrual blood loss, which interferes with a woman’s quality of life. It is estimated that about 1 woman of childbearing age in every 3 seeks medical assistance for HMB. A wide range of drugs are available for the treatment of HMB in the UK, and the National Institute for Health and Care Excellence has published a guidance to help healthcare professionals investigate the cause of HMB and offer the right treatments, taking into account the woman's priorities and preferences. In severe cases invasive treatment may be required (including surgical removal of the uterus), which may impair the woman´s fertility. Still, despite the availability of non-invasive therapeutic options, HMB is often not recognised and treated timely, potentially delaying access to therapeutic options. Studies show that HMB has not been recognized or treated in about 1 in every 2 women. The objective of this study is to observe how often HMB is diagnosed in women of childbearing age and how it is treated in clinical practice in several countries including the UK, France, Germany and the USA.
Aim: The overarching aim is to describe the proportion and incidence of diagnosed Heavy Menstrual Bleeding (HMB) and real-world treatment in recent decades and across countries with different health care systems and HMB guidelines.
Objectives: Study objectives are to describe:
1. The proportion and incidence rate of diagnosed HMB
2. Characteristics of women diagnosed with HMB i.e. demographics, reproductive history, comorbidities and underlying causes of HMB, use of medications and procedures,
3. Treatment pathways of therapeutic options including Levonorgestrel-releasing Intra Uterine Device (LNG-IUD)
4. The proportion of women receiving first line treatment guideline-compliant and the incidence of invasive treatment among, respectively, women with and without first line treatment guideline-compliant.
The population of interest is women of childbearing age with a diagnosis of HMB. Exposure for objective 4 is first line treatment compliant to country-specific HMB guidelines. Methods: This multi-national network retrospective cohort study will use 5 healthcare databases standardized to the Observational Medical Outcomes Partnerships (OMOP) common data model: CPRD Gold (UK), IQVIA Longitudinal Patient Database (LPD) (France) and Disease Analyzer (DA) (Germany), OPTUM Clinformatics and IBM MarketScan (US). The cohort will include women with a diagnosis of HMB identified among all women aged 11 to 55 years, with at least 365 days of continuous enrolment in each database and without history of hysterectomy nor menopause (natural or iatrogenic). Women will be followed up from the date of first HMB diagnosis until the earliest of the following occurrences: natural or medical menopause, hysterectomy or bilateral ovariectomy, age 55, or death. The study period is 01.01.2000 to 31.12.2020. Data analysis: descriptive statistics will be calculated for the number and proportion of women with HMB, incidence rate of HMB per 1,000 person-years, number and frequency of women with HMB and specific characteristics, treatment pathways and duration of use of LNG-IUD.
1. Incidence rates of HMB and proportion of women receiving a diagnosis of HMB
2. Frequency of baseline characteristics of women diagnosed with HMB in terms of demographics, parity and reproductive history, comorbidities and underlying causes of HMB, comedications and procedures.
3. Treatment pathways of multiple therapeutic options, including but not limited to Levonorgestrel-releasing Intra Uterine Device (LNG-IUD), among women with HMB, and the pattern of use of LNG-IUD
4. Frequency of real-world adherence to medical guidelines for first line treatment and incidence of invasive treatment (such as endometrial ablation and hysterectomy) in women with first treatment guideline-compliant and in those without first treatment guideline compliant treatment, respectively.
Federica Pisa - Chief Investigator - Bayer AG
Federica Pisa - Corresponding Applicant - Bayer AG
Ronald Herrera - Collaborator - Bayer AG