Background of the study: With a prevalence up to 15%, polycystic ovary syndrome (PCOS) is the most common endocrine disorder in women of reproductive age. Women with PCOS present with diverse features, including reproductive features such as irregular menstrual cycles, subfertility, hirsutism and pregnancy complications, metabolic features such as obesity, insulin resistance, metabolic syndrome, pre-diabetes, type 2 diabetes and cardiovascular factors, and psychological features such as anxiety and depression. Because of the reproductive, metabolic and cardiovascular risk factors it is important to screen and inform these women. However, up to 70% of the affected women remain undiagnosed. In academic hospitals (tertiary care) the diagnosis PCOS will rarely be missed by gynecologists. However, in peripheral hospitals or for internal medicine physicians, PCOS and its criteria are less well known. Therefore, the PCOS risk algorithm (PriskA), a digital tool to use in the assessment of PCOS in patients with signs and symptoms of PCOS, is developed. To exclude patients with a WHO I status, the tool exclude women with low Luteinizing Hormone (LH) and low Follicle-Stimulating Hormone (FSH) in advance. Women with LH and FSH within the normal range will be used in the algorithm for further assessment. The algorithm uses clinical data including age, BMI and information about irregular menstrual cycle in combination with anti-Mullerian hormone (AMH), testosterone and Sex Hormone Binding Globulin (SHBG) to generate a risk score ranging from 0-1. Women having a risk score below 0.2 are considered having a low risk of having PCOS, women with a risk score 0.2-0.8 are considered having a moderate risk of having PCOS and women with a risk score above 0.8 have a high risk of having PCOS. Objective of the study: In this study we aim to assess the validity of the PriskA algorithm to diagnose PCOS in a pilot study with patients presenting with signs and symptoms of PCOS. The study also aims to collect information on the user experience from the clinicians and to provide useful information to support the design of a validation study. Study design: This study will be a prospective, mono-center observational pilot study and it will be conducted at the Department of Reproductive Endocrinology at the Erasmus University Medical Center Rotterdam, the Netherlands. We estimate that the study will be completed within one year. Study population: Women with symptoms of PCOS who are referred to the Department of Reproductive Endocrinology at the Erasmus University Medical Center Rotterdam, and are undergoing a standardized screening (COLA screening, which stands for: (menstrual) Cycle problems, Oligomenorrhea and Amenorrhea). The COLA screening is part of standard clinical care. Women with one or more symptoms of PCOS will be included in the study. Women who eventually getting the diagnosis PCOS by standard screening will be labelled as cases and women who have one PCOS symptom and did not get the diagnosis PCOS will be labelled as controls. Primary study parameters/outcome of the study: The validity of the PriskA tool to diagnose PCOS, by assessing the sensitivity and specificity of the risk probabilities of 0.2 and 0.8.Parameters that will be used: * Testosterone level in serum (using Elecsys using Cobas 6000) * SHBG level in serum (using Elecsys using Cobas 6000). * AMH level in serum (using Elecsys using Cobas 6000). * LH level in serum (using Elecsys using Cobas 6000) * FSH level in serum (using Elecsys using Cobas 6000) * Cycle information * Age * BMI Secondary study parameters/outcome of the study: A secondary study parameter is to assess the number (percentage) and characteristics of patients with a PriskA score between 0.2-0.8. Characteristics will include: menstrual cycle information, age, BMI, serum LH, serum FSH, serum AMH, serum testosterone, serum SHBG, serum progesterone, serum estradiol, total follicle count, PCOS phenotype (if applicable), WHO diagnosis or other endocrinological diagnosis. Another secondary parameter is the user experience of the PriskA tool. This will be collected from every user by a questionnaire. Questionnaires will be collected from every used when he/she completed 20 patients during the study.
Study Type
OBSERVATIONAL
Enrollment
150
PriskA tool is an algorithm that generates a risk score of having PCOS.
Erasmus University Medical Center
Rotterdam, Netherlands
Sensitivity and specificity of the risk probabilities (<0.2 and >0.8) of the PriskA tool
The PriskA tool generates a risk score ranging from 0-1. Women having a risk score below 0.2 are considered having a low risk of having PCOS, women with a risk score 0.2-0.8 are considered having a moderate risk of having PCOS and women with a risk score above 0.8 have a high risk of having PCOS.
Time frame: Through study completion, an average of 1 year.
Number of patiens with a PriskA score between 0.2 and 0.8.
A secondary study parameter is to assess the number (percentage) of patients with a PriskA score between 0.2-0.8.
Time frame: Through study completion, an average of 1 year.
Diagnosis of patients with a PriskA score between 0.2 and 0.8.
The official diagnosis of patients with a PriskA score between 0.2 and 0.8, including WHO I or III, or other endocrinological diagnosis.
Time frame: Through study completion, an average of 1 year.
PCOS phenotype of patients with a PriskA score between 0.2 and 0.8 and PCOS diagnosis.
A secondary study parameter is to investigate the phenotype of women who receive the diagnosis PCOS but have PriskA score between 0.2 and 0.8. This will be stratified in phenotype A, B, C or D.
Time frame: Through study completion, an average of 1 year.
User experience of PriskA tool
Another secondary parameter is the user experience of the PriskA tool. This will be collected from every user by a questionnaire. Questionnaires will be collected from every user when he/she completed 20 patients during the study.
Time frame: Through study completion, an average of 1 year.
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