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.