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Diagnosis and management of polycystic ovary syndrome in the United Kingdom, 2004-2014

Journal: BMJ Open

Manuscript ID bmjopen-2016-012461

Article Type: Research

Date Submitted by the Author: 29-Apr-2016

Complete List of Authors: Ding, Tao; University College London, Statistical Science Baio, Gianluca; UCL, Statistical Science Hardiman, Paul ; University College London Medical School Petersen, Irene; University College London Medical School, Department of Primary Care and Population health Sammon, Cormac; University College London, Department of Primary Care and Population Health

<b>Primary Subject

Heading</b>: Epidemiology

Secondary Subject Heading: Diabetes and endocrinology

Keywords: EPIDEMIOLOGY, Polycystic Ovary Syndrome, prescription

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Title: Diagnosis and management of polycystic ovary syndrome in the United Kingdom, 2004-2014

Corresponding author:

Name: Tao Ding

Postal address: Department of Statistical Science, University College London, 1-19 Torrington

Place, London WC1E 6BT, UK

Email: [email protected]

Telephone number: 07522127150

Co-authors:

Name: Gianluca Baio

Department: Department of Statistical Science

Institution: University College London

Country: London, United Kingdom

Name: Paul J. Hardiman

Department: Department of Women’s Institute of Health



Name: Irene Petersen

Department: Department of Primary Care and Population Health



Name: Cormac Sammon




Keywords: epidemiology/PCOS/prescription

Word count: 2787

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Diagnosis and management of polycystic ovary syndrome in the United

Kingdom, 2004-2014

Tao Ding1, Gianluca Baio1, Paul J.Hardiman2, Irene Petersen3, Cormac Sammon3

1Department of Statistical Science, University College London, London, UK,

2Institute for Women's Health, University

College London Medical School, London, UK, 3Department of Primary Care and Population Health, University College

London, London, UK

Correspondence to Tao Ding; [email protected]

Abstract (293/300)

Objective: To estimate the incidence and prevalence of PCOS in UK primary care and investigate

prescribing patterns before and after a PCOS diagnosis.

Design: Retrospective cohort study

Setting: UK primary care (2004 - 2014)

Participants: Women aged 15 to 45

Primary and secondary outcome measures: The incidence and prevalence of diagnosed PCOS and

probable PCOS (i.e. those without a confirmed diagnosis but with at least two PCOS features

recorded within 3 years). Among women with diagnosed or probable PCOS, the prevalence of

prescribing of drugs typically used in the treatment of PCOS was calculated both prior to and in the

24 months after the diagnosis of PCOS.

Results: We identified 7,233 women with PCOS diagnoses and 7,057 women with records

suggestive of probable PCOS, corresponding to incidence rates of 0.93 and 0.91 per 1000 person

years at risk (PYAR) and an overall rate of 1.84 per 1000 PYAR. Women aged 20-24 years and

women living in deprived areas had the highest incidence of PCOS. The prevalence of PCOS in 2014

was approximately 2%. The proportion of women with a prescription in the 24 months after their

PCOS index date varied by drug type: 10.2% metformin, 15.2% combined oral contraceptives,

18.8% acne related treatments, 1.93% clomiphene, 1.0% spironolactone, 0.28% cyproterone and

3.11% eflornithine. Acne related treatments were more commonly used to treat probable (28.3%)

than diagnosed cases (12.3%) while the other drugs were prescribed more commonly in diagnosed

than probable cases.

Conclusion: In conclusion, compared to rates estimated in community samples, the incidence of

women presenting in primary care with PCOS diagnoses and features is low. Among the women

that do present, only 50% were observed to have a PCOS diagnosis recorded. There is considerable

variation observed in treatments prescribed to women with PCOS.

Key words: epidemiology/PCOS/prescription

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Article summary

Strengths and limitations of this study

1. The current study is the first to investigate the incidence and prevalence of PCOS in the primary

care setting in the UK and the longitudinal nature of the database allowed us to examine trends

over a long time period, which has not been captured by previous epidemiological studies.

2. Under-diagnosis was the main concern for the current study as only data considered relevant at

the time of a consultation are recorded by clinicians although we attempted to include women

with two or more features of PCOS as potential cases.

3. Our study investigated the prescribing patterns of PCOS in the UK primary care, which has not

been well explored in previous studies. These findings reflected the current management of PCOS

in the clinical practices and provide important indications for general practitioners.

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Background

Polycystic ovary syndrome (PCOS) is associated with a wide range of reproductive,

cardiometabolic and dermatological abnormalities. One of the most prominent symptoms in PCOS

patients is oligo-menorrhea. Consequently, women with PCOS are highly likely to be infertile and

potentially develop endometrial hyperplasia due to continuing secretion of oestrogen without

ovulation [1,2]. Furthermore, emerging evidence has suggested that approximately 50-70% of

PCOS patients have insulin resistance regardless of their body weight or body mass index (BMI)

[3]. Consequently, women with PCOS are at an elevated risk of developing various common

metabolic disorders compared with the general population [4]. In addition, many PCOS patients

are observed to have an elevated androgen level, which leads to hirsutism, alopecia and acne [1].

While the epidemiology of PCOS in the community has been well studied [5-8], the proportion of

women who present in routine clinical practice with PCOS features and the extent to which these

women are subsequently diagnosed is less clear. Similarly, while a range of treatments have been

suggested for the management of PCOS [9], there is very little information regarding which of

these drugs are actually prescribed in routine clinical practice. Such ‘read world evidence’ can help

identify priority areas for research, training and health promotion efforts. The current study

sought to provide such evidence by investigating the recording of PCOS features and diagnoses in

UK general practice between 2004 and 2014 and the subsequent prescribing of pharmacological

treatments.

Methods

Data source

The Health Improvement Network (THIN) is one of the largest primary care data sources in the UK,

including data from over 500 general practices, covering approximately 6.2% of the total

population in the UK. Available data include patient demographics, medical history, test results,

drug prescriptions and social deprivation as measured by quintiles of the Townsend score [10].

The symptoms and diagnoses are recorded using a hierarchical clinical coding system (Read codes)

[11]. In our study, data were included from each practice that met minimum quality criteria, for

example, acceptable computer usage (ACU) (a time point when a practice is considered to use

their computer system adequately, i.e. at least one medical record, one AHD record and two

therapy records are computerized annually for a practice) and acceptable mortality reporting

(AMR) (a time point which the observed death rate for a practice reach the standard predicted

numbers of deaths derived from National statistics given the practice’s demographics) [12-14].

Study population

Women aged 15-45, who were permanently registered for at least one year were included in the

study population. Women with conditions that can cause similar symptoms to PCOS were

identified and excluded. These conditions include prolactinoma, Cushing’s syndrome, Nelson’s

syndrome, adrenal related disorders (i.e. adrenal tumours, adrenal hyperplasia), and pituitary

disorders.

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Case definition

PCOS cases were identified using two methods. First, Read codes for ‘polycystic ovary syndrome’

(C165.00), ‘Stein-Leventhal syndrome’ (C164.12) and ‘endoscopic drilling of ovary’ (7E25300) were

used to identify those women who had been clinically diagnosed as PCOS cases (diagnosed cases).

Women with two or more Read codes indicative of PCOS features (menstrual/ovarian dysfunction,

clinical and biochemical hyperandrogenism, polycystic ovaries) recorded in a three year period

were then selected and we considered these as probable cases. These women were considered as

those who were likely to meet at least one of the 3 major definitions of PCOS [15-18] but who may

not have been clinically diagnosed as having the condition. The index date for probable cases was

considered to be the date the second PCOS feature was recorded. A full list of the codes used to

define cases is provided in Table SI.

Covariates and prescription indicators

We extracted data on each woman’s year of birth, ethnicity and deprivation level of the area in

which the woman lived [5]; data on prescriptions of interest (i.e. combined oral contraceptives,

progestin oral contraceptives, intrauterine devices, clomiphene, metformin, spironolactone,

gonadotrophins, cyproterone, flutamide, eflornithine, weight control/loss drugs, lipid regulators,

acne-related drugs) were also included and information on prescribing of these drugs before and

in the 24 months after each PCOS case index data was extracted.

Statistical Analysis

For incidence estimation, the rate was computed as the total number of new PCOS cases recorded

between 2004 and 2014 divided by the total number of person years of follow-up. Person-time for

the denominator was estimated by summing each woman’s follow-up from the latest among (i)

their 15th birthday, (ii) one year after registration, (iii) the date at which their practice met

minimum quality criteria and (iv) the 1st January 2004, to the earliest of the date among (i) their

first incident diagnosis, (ii) their date of death, (iii) the date they left the practice, (iv) the date data

were last collected from their practice and (v) the 31st December 2014. All incidence rates were

reported per 1000 person years at risk (PYAR).

Hierarchical (patients were considered to be nested in each practice) multivariate Poisson

regression models were used to estimate incidence rate ratios (IRR) and 95% confidence intervals

(95% CI) comparing the incidence of first PCOS diagnoses across 5-year age bands, Townsend

score quintiles and calendar period (i.e. 2004-2007, 2008-2011, 2012-2014).

The period prevalence of the diagnosis of PCOS was evaluated for the calendar year 2014. The

denominator for the prevalence calculation consisted of any women with at least one year of post-

registration follow-up, of which at least 6 months must have occurred in 2014. The prevalence of

PCOS was also estimated within 5-year age bands. Secondary analysis was carried out to assess

the sensitivity of the prevalence estimate to the length of the post-registration period (i.e. 1 year,

2 years) and the minimum period registered within 2014 (i.e. 3, 6, 9 months).

Among the women with a diagnosis of PCOS, we calculated the number and proportion with a

prescription for one of the drugs of interest at any point prior to their PCOS index date. Among the

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women without prescription for each drug of interest prior to the index date, we then calculated

the proportion of women with a prescription for that drug within 2 years after the PCOS index

date. We used cumulative incidence plots to describe how the proportion initiating different drugs

increased over the two years following the PCOS index date for the time period 2004-2012.

All analyses were performed using STATA 13.0 and were carried out for all PCOS cases and

stratified by case definition (diagnosed PCOS versus probable PCOS).

Results

In total, 7,233 diagnosed and 7,057 probable PCOS cases were identified amongst 2,087,107

female individuals aged 15-45 years old between 2004 and 2014. Table I describes the number of

PCOS features identified in each group. The incidence rate of diagnosed PCOS cases was 0.93 per

1000 PYAR (95% CI: 0.91-0.96) whereas the rate for probable cases was 0.91 per 1000 PYAR (95%

CI: 0.89-0.93). This equated to an overall combined incidence rate of 1.84 PYAR (95% CI: 1.81-

1.87).

Table I Number and proportion of diagnosed and probable cases with major PCOS features

Features

No. (%)

Diagnosed cases

(n=7233)

Probable cases

(n=7057)

Menstrual dysfunction 2055 (28.4) 6265 (88.8) Hyperandrogenism 2836 (39.2) 6221 (88.2) PCO 199 (2.8) 1636 (23.2) ≥ 2 features 597 (8.3) 7057 (100)

The overall incidence of PCOS increased from 1.67 (95% CI: 1.58-1.77) per 1000 PYAR in 2004 to

2.00 (95% CI: 1.89-2.10) per 1000 PYAR in 2010, after which the rate remained relatively constant

at approximately 2 per 1000 PYAR (Figure I). The incidence was the highest for those in the 20-24

year age group (3.59 per 1000 PYAR, 95% CI: 3.47-3.70) whereas the 40-44 year age group had the

lowest incidence (0.62 per 1000 PYAR, 95% CI: 0.58-0.66). The age-specific trend of PCOS

diagnoses was similar for both diagnosed and probable cases. After adjusting for the effects of

year and social deprivation, significant differences still remained in the incidence of PCOS (Table

II). In terms of social deprivation, the incidence of PCOS for individuals who were least deprived

was 1.59 (95% CI: 1.53-1.65) per 1000 PYAR whereas among the most deprived, a rate of 2.23

(95% CI: 2.15-2.32) per 1000 PYAR was estimated. This difference in rates remained statistically

significant after adjusting for effects of other covariates (i.e. age, year) and after stratifying by case

definition (Table II).

The overall prevalence of PCOS in 2014 was approximately 2.27% (95% CI: 2.23-2.31%), with a

prevalence of 1.34% and 0.93% in diagnosed and probable cases, respectively. The age-specific

prevalence peaked in the 30-34 year age group, and decreased for older age groups (Figure II).

Prevalence estimates were not sensitive to varying the post-registration period and the time

period registered within 2014, remaining consistently around 2%.

The proportion of women using one of the PCOS related drugs before or after their index date

varied widely across drugs groups (see Table III). At the time of their PCOS index date, over 40% of

women had previously been prescribed combined oral contraceptive (COC), approximately 30%

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had been prescribed acne-related drugs before diagnosis, greater than 18% had been prescribed

progestin oral contraceptives (POC) and about 18% had previously been prescribed at least one of

the other drugs (Table III). Acne-related drugs, COC and metformin were the most commonly used

drugs in the 24 months after a PCOS record (Table III). Plots describing the cumulative incidence of

women with a prescription for each drug type over the 24 months following their index date are

provided in figure SI. The plots show that while all drugs show an initial surge in prescribing on or

just after the PCOS index date, this is greater for some drugs (e.g. metformin, acne related drugs)

than for us (COCs and POCs)

Prescription results stratified according to whether PCOS cases were diagnosed or probable are

provided in Table SII. These results indicate that acne-related treatments and POCs were more

commonly used to treat probable than diagnosed cases while COCs, metformin, clomiphene,

cyproterone, elflornithine and weight loss drugs were prescribed more commonly in diagnosed

than probable cases. Cumulative incidence plots stratified according to whether a case was

diagnosed or probable (Figure II) illustrate the differences listed in table SII and further to this

show that these differences are typically established on or immediately after the index date.

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Table II. Recorded rate of PCOS diagnoses by social and demographical characteristics

*IRR from multilevel Poisson distribution accounted for practice-level variability and adjusted for other variables considered

Diagnosed PCOS Probable PCOS Overall

Rate per 1000 PYAR (95% CI)

Adjusted* IRR (95% CI)

P Rate per 1000 PYAR (95% CI)




P

Townsend quintile <0.001 <0.001 <0.001

1 0.80 (0.76-0.84) 1 0.80 (0.76-0.84) 1 1.59 (1.53-1.65) 1

2 0.90 (0.85-0.95) 1.14 (1.06-1.23) 0.79 (0.75-0.84) 0.99 (0.92-1.07) 1.69 (1.62-1.75) 1.08 (1.02-1.14)

3 0.94 (0.90-0.99) 1.12 (1.04-1.21) 0.91 (0.86-0.96) 1.07 (0.99-1.15) 1.85 (1.78-1.92) 1.10 (1.05-1.16)

4 1.02 (0.97-1.07) 1.15 (1.06-1.24) 0.97 (0.92-1.02) 1.06 (0.98-1.15) 1.98 (1.91-2.05) 1.11 (1.05-1.17)

5 1.07 (1.01-1.13) 1.15 (1.05-1.25) 1.17 (1.11-1.23) 1.21 (1.11-1.32) 2.23 (2.15-2.32) 1.19 (1.11-1.26)

Age, years <0.001 <0.001 <0.001

15-19 1.20 (1.14-1.27) 0.69 (0.64-0.74) 0.54 (0.50-0.59) 0.29 (0.27-0.32) 1.75 (1.67-1.83) 0.49 (0.46-0.51)

20-24 1.72 (1.64-1.80) 1 1.87 (1.79-1.96) 1 3.59 (3.47-3.70) 1

25-29 1.51 (1.44-1.58) 0.86 (0.80-0.91) 1.49 (1.42-1.56) 0.78 (0.73-0.83) 2.98 (2.88-3.08) 0.81 (0.78-0.85)

30-34 1.03 (0.98-1.09) 0.58 (0.54-0.62) 0.86 (0.81-0.91) 0.46 (0.42-0.49) 1.88 (1.81-1.96) 0.51 (0.49-0.54)

35-39 0.45 (0.42-0.49) 0.26 (0.24-0.28) 0.55 (0.51-0.59) 0.30 (0.27-0.32) 0.99 (0.94-1.05) 0.27 (0.26-0.29)

40-44 0.17 (0.15-0.19) 0.10 (0.08-0.11) 0.45 (0.42-0.48) 0.24 (0.22-0.26) 0.62 (0.58-0.66) 0.17 (0.16-0.18)

Year <0.001 <0.001 <0.001

2004-2007 0.91 (0.87-0.94) 1 0.82 (0.79-0.86) 1 1.73 (1.68-1.78) 1

2008-2011 0.94 (0.91-0.98) 1.00 (0.95-1.06) 0.95 (0.92-0.99) 1.13 (1.07-1.19) 1.89 (1.84-1.94) 1.06 (1.02-1.10)

2012-2014 0.96 (0.92-1.01) 0.98 (0.92-1.04) 0.98 (0.93-1.02) 1.13 (1.07-1.20) 1.92 (1.86-1.98) 1.04 (1.00-1.09)

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Table III Number and percentage of PCOS women prescribed relevant drugs for PCOS both prior to and following the diagnosis of PCOS

Types of drugs

No. (%)

Before diagnosis of PCOS After diagnosis of PCOS

2004-2007 2008-2011 2012-2014

Combined oral

contraceptives

(COC)

12349 (40.22) 901 (17.01) 912 (18.87) 459 (17.88)

Progestin oral

contraceptives

(POC)

5806 (18.91) 474 (6.45) 691 (10.22) 272 (7.80)

Intrauterine

devices (IUDs)

728 (2.37) 43 (0.50) 64 (0.75) 25 (0.52)

Clomiphene 518 (1.69) 210 (2.46) 165 (1.92) 70 (1.43)

Metformin 1278 (4.16) 1212 (14.77) 1102 (13.25) 495 (10.52)

Gonadotrophins 435 (1.42) 29 (0.34) 13 (0.15) 13 (0.26)

Spironolactone 235 (0.77) 109 (1.26) 111 (1.28) 43 (0.87)

Cyproterone 91 (0.30) 28 (0.32) 19 (0.22) 3 (0.06)

Flutamide 6 (0.02) 4 (0.05) 1 (0.01) 0

Eflornithine 550 (1.79) 354 (4.10) 407 (4.81) 172 (3.58)

Weight

control/loss drugs

1330 (4.33) 403 (4.84) 364 (4.43) 91 (1.95)

Lipid regulators 194 (0.63) 69 (0.79) 46 (0.53) 8 (0.16)

Acne-related drugs 9000 (29.31) 1182 (19.52) 1234 (20.78) 582 (18.32)

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Discussion

Summary

We present data on more than 14,000 potential PCOS cases among women aged 15 to 45 in primary

care across the UK between 2004 and 2014. 51.2% of these women had a PCOS diagnosis recorded,

while 49.9% did not, corresponding to incidence rates of 0.93 per 1000 PYAR (95% CI: 0.91-0.96) and

0.91 per 1000 PYAR (95% CI: 0.89-0.93) respectively. The prevalence of PCOS in 2014 was

approximately 2.27%. There was considerable variation in the type of drug prescribed on the day of,

or in the 24 months after a PCOS diagnosis and prescribing differed between diagnosed and

probable cases.

Strengths and limitations

Our study is the first to investigate the diagnosis and management of PCOS in the primary care

setting in the UK. As THIN contains over 10 million patient records, our study is robust in terms of

sample size. The longitudinal nature of the database also allowed us to examine trends over a ten

year study period which, to our knowledge, has not been captured by previous epidemiological

studies where individuals were often sampled at a single time point.

As our data were collected in routine clinical practice our results reflect the true burden of PCOS on

the healthcare system. However, this also means that only data considered relevant at the time of a

consultation are recorded by clinicians. Consequently, under-diagnosis was the main concern in the

current study and underestimation of PCOS rates was anticipated. We attempted to address under-

reporting by allowing women with two or more features of PCOS (inter-feature period within 3

years) to count as a PCOS case. However, the inclusion of probable cases may introduce case

misclassification as some probable cases may not be true PCOS cases. For example, some probable

cases were included with a record of acne which may not be as strong an indictor as hirsutism and

elevated androgen level, especially for young women aged below 25. Incomplete patient history is a

concern as women with prevalent PCOS diagnoses at the time of registration with a practice may not

be identified, resulting in the underestimation of prevalence rates and the overestimation of

incidence rates. Additionally, the lack of information on ethnicity is also an issue as the trends in

incidence observed over age, deprivation and calendar year categories may be influenced by

unobserved differences in ethnicity distributions across these covariates.

As we lack information on the indication for prescriptions we cannot be certain that prescriptions

issued after, or even on the date of a PCOS record were prescribed for the treatment of PCOS. For

example, approximately 30% of the PCOS cases prescribed metformin had a prior diagnosis of type 2

diabetes, the approved indication for this drug. However, by excluding those ever prescribed

metformin prior to their PCOS diagnosis from our calculations, we can be relatively confident that

prescriptions for metformin issued on the date of a PCOS diagnosis are likely to be at least partly for

the treatment of PCOS. Our confidence that the drug was prescribed for PCOS then decreases with

increasing time after the PCOS diagnosis such that we expect the proportion of diagnosed cases

prescribed metformin for PCOS to lie somewhere between the 8% with a prescription on the date of

diagnosis and the 20% with a prescription on or in the 24 months after the date of diagnosis.

The proportion of women with PCOS who had been prescribed combined oral contraceptives (COC)

before their PCOS diagnosis is similar to that reported by other studies [19,20]. The proportion of

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women with PCOS who initiated metformin after their diagnosis in our study (over 10%) is

comparable to a Danish study where 11.8% of the women with PCOS were identified as having

received metformin [20]. These comparisons support the validity of our prescribing data.

Interpretation

The prevalence of recorded PCOS in UK primary care in 2014 is comparable to that obtained from

studies using databases in the United States (0.56% to 2.22%) [21-23]. However, the rates are

significantly lower than those from community-based studies where rates as high as 22.5% have

been obtained using systematic screening to identify diagnosed and probable cases from selected

populations [24]. This suggests that a small proportion of the total number of women with PCOS

present in primary care. However, it is notable that prevalence estimates as low as 2.2% have been

observed in a community based sample of Chinese women identified according to the 2006

Androgen Excess Society definition [25].

The fact that the incidence of probable PCOS cases was as high as the incidence of diagnosed cases

indicates that there are a large group of women who present in primary care exhibiting two features

of PCOS within a 3 year period but who do not have a subsequent PCOS diagnosis. While for some of

these women a PCOS diagnosis may not be relevant, it is likely that a considerable proportion of the

women may meet the diagnostic criteria for PCOS and should therefore be referred for further

assessment. Failure to refer such women may mean they are not offered the lifestyle advice or

medications which could reduce their risk of long term PCOS-related complications.

Variation was observed in the treatments prescribed to diagnosed and probable PCOS cases, in

particular, a greater proportion of diagnosed women received metformin prescriptions while a

greater proportion of the probable cases received treatment for the PCOS feature they presented

with. This suggests that the diagnosed and probable cases are indeed receiving different care for

their condition, with some probable cases not receiving potentially effective treatments such as

metformin.

It is notable that even among diagnosed PCOS cases there is much variation in treatments prescribed

following diagnosis. This suggests there may be a lack of consensus on the ideal treatment for the

condition. This is supported by a recent survey of European endocrinologists which found variation

in the treatments most commonly prescribed for PCOS [26]. Further research into the comparative

efficacy and effectiveness of the various PCOS treatment options may therefore be warranted.

Conclusions

In conclusion, compared to rates estimated in community samples, the incidence of women

presenting in primary care with PCOS diagnoses and features is low. Among the women that do

present, only 50% were observed to have a PCOS diagnosis recorded. Further work may therefore be

needed to inform women and healthcare professionals about the condition. The variation observed

in treatments prescribed following a PCOS diagnosis suggests further work is needed to identify the

most effective treatment for the condition.

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Contributors

TD, CS, IP were involved in the design of the study. TD and CS performed the analysis, while GB, IP,

PJH helped with the interpretation. TD prepared the manuscript, and CS, GB, IP, PJH revised it as

needed. All authors have read and approved the final manuscript.

Funding: This research received no specific grant from any funding agency in the public, commercial

or not-for-profit sectors.

Competing interests: We have read and understood BMJ policy on declaration of interests and

declare that we have no competing interests.

Ethics: THIN has overall ethical approval from the South East Multicentre Research Ethics Committee

(reference number: 07/H1102/103).

Data sharing statement: No additional data are available.

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21. Okoroh EM, Hooper WC, Atrash HK, Yusuf HR, Boulet SL. 2012 Prevalence of polycystic ovary syndrome among the

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22. Christensen SB, Black MH, Smith N, Martinez MM, Jacobsen SJ, Porter AH, Koebnick C. 2013 Prevalence of polycystic

ovary syndrome in adolescents. Fertil Steril 100:470-477.

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25. Chen X, Yang D, Mo Y, Li L, Chen Y, Huang Y. 2008 Prevalence of polycystic ovary syndrome in unselected women

from southern China. Eur J Obstet Gynecol Reprod Biol 139:59-64.

26. Conway G, Dewailly D, Diamanti-Kandarakis E, Escobar-Morreale HF, Franks S, Gambineri A, Kelestimur F, Macut D,

Micic D, Pasquali R, Pfeifer M, Pignatelli D, Pugeat M, Yildiz B, ESE PCOS Special Interest Group. European survey of

diagnosis and management of the polycystic ovary syndrome: results of the ESE PCOS Special Interest Group's

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Time trends in PCOS diagnosis recorded (for diagnosed, probable and total cases).

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Plots describing the cumulative incidence of women with a prescription for each drug type over the 24 months following their index date stratified according to whether the case was diagnosed (dashed line) or

probable (solid line). Results shown for the eight most commonly prescribed drugs.

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Data supplement

Table SI Code lists used to identify study variables

medcode description

Codes for polycystic ovary syndrome

C164.12 Stein - Leventhal syndrome

C165.00 Polycystic ovarian syndrome

7E25300 Endoscopic drilling of ovary

K591100 Oligomenorrhoea

K591200 Primary oligomenorrhoea

K591300 Secondary oligomenorrhoea

K594.00 Irregular menstrual cycle

K594z00 Irregular menstrual cycle NOS

C161000 Hypersecretion of ovarian androgen

M240.00 Alopecia

M240000 Alopecia unspecified

M240200 Male pattern alopecia

M240300 Frontal alopecia of women

M240400 Premature alopecia

M240z00 Alopecia NOS

M241.00 Hirsutism - hypertrichosis

M260.00 Acne varioliformis

M260000 Acne frontalis

M260z00 Acne varioliformis NOS

M261.00 Other acne

M261000 Acne vulgaris

M261100 Acne conglobata

M261600 Cystic acne

M261A00 Pustular acne

M261E00 Acne excoriee des jeunes filles

M261F00 Acne fulminans

M261G00 Acne agminata

M261J00 Acne necrotica

M261K00 Acne keloidalis

M261X00 Acne, unspecified

M261z00 Other acne NOS

Myu6300 [X]Other androgenic alopecia

Myu6800 [X]Other acne

Myu6F00 [X]Acne, unspecified

4473 Serum testosterone

4473100 Serum testosterone level abnormal

4474 Free androgen index

4474100 Free androgenic index abnormal

447G.00 Plasma testosterone level

447H.00 Androgen level

4Q26.00 Dihydrotestosterone level

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4Q2E.00 Free testosterone level

4Q2F.00 Calculated free testosterone

ZRBs.00 Ferriman and Galwey score

K53..11 Ovarian cysts

K532.00 Other ovarian cysts

K532z00 Ovarian cyst NOS

Kyu9500 [X]Other and unspecified ovarian cysts

Codes for diseases for exclusion

B540.00 Malignant neoplasm of adrenal gland

B540000 Malignant neoplasm of adrenal cortex

B540100 Malignant neoplasm of adrenal medulla

B540z00 Malignant neoplasm of adrenal gland NOS

B587.00 Secondary malignant neoplasm of adrenal gland

B7H0.00 Benign neoplasm of adrenal gland

B8yy100 Carcinoma in situ of adrenal gland

B922.00 Neoplasm of uncertain behaviour of adrenal gland

BB5h.00 [M]Adrenal cortical tumours

BB5h000 [M]Adrenal cortical adenoma NOS

BB5h100 [M]Adrenal cortical carcinoma

BB5h300 [M]Adrenal cortical adenoma, heavily pigmented variant

BB5h400 [M]Adrenal cortical adenoma, clear cell type

BB5h500 [M]Adrenal cortical adenoma, glomerulosa cell type

BB5h600 [M]Adrenal cortical adenoma, mixed cell type

BB5hz00 [M]Adrenal cortical tumours NOS

BBCF.00 [M]Adrenal rest tumour

BBD7.00 [M]Extra-adrenal paraganglioma, NOS

C15..00 Disorders of adrenal glands

C153.00 Other corticoadrenal overactivity

C155000 Adrenal medullary insufficiency

C15y.00 Other specified adrenal disorders

C15yz00 Other specified adrenal disorder NOS

C15z.00 Adrenal gland disorder NOS

Cyu4A00 [X]Other specified disorders of adrenal gland

PK1..00 Anomalies of adrenal gland

PK10.00 Aberrant adrenal gland

PK12.00 Accessory adrenal gland

PK13.00 Hypoplasia of adrenal gland

PK14.00 Ectopic adrenal gland

PK1y.00 Other specified anomalies of adrenal gland

PK1y000 Congenital cyst of adrenal gland

PK1yz00 Other congenital anomaly of adrenal gland NOS

PK1z.00 Anomalies of adrenal gland NOS

2226.11 O/E - cushingoid facies

C150.00 Cushing's syndrome

C150000 Idiopathic Cushing's syndrome

C150100 Iatrogenic Cushing's syndrome

C150111 Drug-induced Cushings syndrome

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C150200 Pituitary dependent Cushing's syndrome

C150300 Ectopic ACTH secretion causing Cushing's syndrome

C150500 Alcohol-induced pseudo-Cushing's syndrome

C150z00 Cushing's syndrome NOS

Cyu4500 [X]Other Cushing's syndrome

F395100 Myopathy due to Cushing's syndrome

C150400 Nelson's syndrome

BB5y400 [M]Prolactinoma

B542.00 Malignant neoplasm pituitary gland and craniopharyngeal duct

B542000 Malignant neoplasm of pituitary gland

B542z00 Malig neop pituitary gland or craniopharyngeal duct NOS

B7H2.00 Benign neoplasm of pituitary gland and craniopharyngeal duct

B7H2.11 Pituitary adenoma

B7H2000 Benign neoplasm of pituitary gland

B7H2z00 Benign neoplasm of pituitary and craniopharyngeal duct NOS

B8yy300 Carcinoma in situ of pituitary gland

B920.00 Neop uncertain behaviour pituitary and craniopharyngeal duct

B920000 Neoplasm of uncertain behaviour of pituitary gland

B920z00 Neop uncertain behaviour pituitary and craniopharyngeal NOS

BB5V.00 [M]Pituitary adenomas and carcinomas

BB5Vz00 [M]Pituitary adenoma or carcinoma NOS

C13..00 Disorders of pituitary gland and its hypothalamic control

C131.00 Other anterior pituitary hyperfunction

C134.00 Other anterior pituitary disorder

C134z00 Other anterior pituitary disorder NOS

C134z11 Anterior pituitary hormone deficiency NEC

C137.00 Iatrogenic pituitary disorders

C137z00 Iatrogenic pituitary disorder NOS

C13z.00 Pituitary disorders NOS

Cyu4400 [X]Other disorders of pituitary gland

Cyu4M00 [X]Hyperfunction of pituitary gland, unspecified

K5B1.00 Female infertility of pituitary - hypothalamic origin

K5B1000 Primary pituitary - hypothalamic infertility

K5B1z00 Female infertility of pituitary - hypothalamic cause NOS

PK24.00 Anomalies of pituitary gland

PK24000 Aberrant pituitary gland

PK24z00 Anomaly of pituitary gland NOS

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Table SII Number and percentage of PCOS women prescribed relevant drugs for PCOS both prior to and following the diagnosis of PCOS stratified by case

definition

Types of drugs

No. (%)

Before After

2004-2007 2008-2011 2012-2014

Diagnosed Probable Diagnosed Probable Diagnosed Probable Diagnosed Probable

Combined oral

contraceptives

(COC)

5136 (31.35) 7213 (50.37) 601 (16.68) 291 (17.19) 611 (20.57) 311 (16.51) 290 (20.52) 179 (14.90)

Progestin oral

contraceptives

(POC)

2067 (12.62) 3739 (26.11) 260 (5.48) 212 (8.11) 377 (9.18) 312 (11.58) 163 (8.29) 115 (7.24)

Intrauterine

devices (IUDs)

191 (1.17) 537 (3.75) 21 (0.40) 23 (0.69) 31 (0.64) 33 (0.88) 13 (0.51) 13 (0.54)

Clomiphene 332 (2.03) 186 (1.30) 164 (3.18) 45 (1.34) 129 (2.69) 38 (0.98) 61 (2.41) 10 (0.41)

Metformin 1084 (6.62) 194 (1.35) 1125 (23.27) 88 (2.62) 991 (21.87) 112 (2.92) 459 (19.44) 51 (2.11)

Gonadotrophins 126 (0.77) 309 (2.16) 17 (0.32) 12 (0.36) 7 (0.14) 6 (0.16) 5 (0.20) 8 (0.33)

Spironolactone 174 (1.06) 61 (0.43) 101 (1.94) 9 (0.26) 101 (2.08) 10 (0.26) 37 (1.45) 7 (0.28)

Cyproterone 72 (0.44) 19 (0.13) 27 (0.51) 4 (0.12) 17 (0.35) 2 (0.05) 2 (0.08) 1 (0.04)

Flutamide 6 (0.04) 0 4 (0.08) 0 0 1 (0.03) 0 0

Eflornithine 415 (2.53) 135 (0.94) 279 (5.33) 73 (2.14) 292 (6.22) 112 (2.93) 129 (5.27) 47 (1.94)

Weight

control/loss

drugs

849 (5.18) 481 (3.36) 320 (6.39) 84 (2.53) 284 (6.22) 82 (2.21) 72 (3.02) 23 (0.98)

Lipid regulators 93 (0.57) 101 (0.71) 48 (0.91) 22 (0.65) 25 (0.52) 21 (0.55) 5 (0.20) 3 (0.12)

Acne-related

drugs

3547 (21.64) 5453 (38.08) 600 (14.99) 585 (28.63) 583 (15.95) 664 (28.53) 226 (12.67) 373 (25.92)

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Figure SI. Plots describing the cumulative incidence of women with a prescription for each drug type over the 24 months following their index date.

Results shown for the eight most commonly prescribed drugs.

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STROBE 2007 (v4) checklist of items to be included in reports of observational studies in epidemiology*

Checklist for cohort, case-control, and cross-sectional studies (combined)

Section/Topic Item # Recommendation Reported on page #

Title and abstract 1 (a) Indicate the study’s design with a commonly used term in the title or the abstract 2

(b) Provide in the abstract an informative and balanced summary of what was done and what was found 2

Introduction

Background/rationale 2 Explain the scientific background and rationale for the investigation being reported 4

Objectives 3 State specific objectives, including any pre-specified hypotheses 4

Methods

Study design 4 Present key elements of study design early in the paper 4

Setting 5 Describe the setting, locations, and relevant dates, including periods of recruitment, exposure, follow-up, and data

collection 4

Participants 6 (a) Cohort study—Give the eligibility criteria, and the sources and methods of selection of participants. Describe

methods of follow-up

Case-control study—Give the eligibility criteria, and the sources and methods of case ascertainment and control

selection. Give the rationale for the choice of cases and controls

Cross-sectional study—Give the eligibility criteria, and the sources and methods of selection of participants

5-6

(b) Cohort study—For matched studies, give matching criteria and number of exposed and unexposed

Case-control study—For matched studies, give matching criteria and the number of controls per case NA

Variables 7 Clearly define all outcomes, exposures, predictors, potential confounders, and effect modifiers. Give diagnostic

criteria, if applicable 5

Data sources/ measurement 8* For each variable of interest, give sources of data and details of methods of assessment (measurement). Describe

comparability of assessment methods if there is more than one group 4-5

Bias 9 Describe any efforts to address potential sources of bias 4-5

Study size 10 Explain how the study size was arrived at NA

Quantitative variables 11 Explain how quantitative variables were handled in the analyses. If applicable, describe which groupings were chosen

and why 4-5

Statistical methods 12 (a) Describe all statistical methods, including those used to control for confounding 5-6

(b) Describe any methods used to examine subgroups and interactions NA

(c) Explain how missing data were addressed NA

(d) Cohort study—If applicable, explain how loss to follow-up was addressed

Case-control study—If applicable, explain how matching of cases and controls was addressed 5-6

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Cross-sectional study—If applicable, describe analytical methods taking account of sampling strategy

(e) Describe any sensitivity analyses 5-6

Results

Participants 13* (a) Report numbers of individuals at each stage of study—eg numbers potentially eligible, examined for eligibility,

confirmed eligible, included in the study, completing follow-up, and analysed 6

(b) Give reasons for non-participation at each stage NA

(c) Consider use of a flow diagram NA

Descriptive data 14* (a) Give characteristics of study participants (eg demographic, clinical, social) and information on exposures and

potential confounders

(b) Indicate number of participants with missing data for each variable of interest NA

(c) Cohort study—Summarise follow-up time (eg, average and total amount) 6

Outcome data 15* Cohort study—Report numbers of outcome events or summary measures over time 6-7

Case-control study—Report numbers in each exposure category, or summary measures of exposure NA

Cross-sectional study—Report numbers of outcome events or summary measures 6-7

Main results 16 (a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates and their precision (eg, 95%

confidence interval). Make clear which confounders were adjusted for and why they were included 6-7

(b) Report category boundaries when continuous variables were categorized 6-8

(c) If relevant, consider translating estimates of relative risk into absolute risk for a meaningful time period 6-8

Other analyses 17 Report other analyses done—eg analyses of subgroups and interactions, and sensitivity analyses 6

Discussion

Key results 18 Summarise key results with reference to study objectives 10

Limitations 19 Discuss limitations of the study, taking into account sources of potential bias or imprecision. Discuss both direction

and magnitude of any potential bias 10-11

Interpretation 20 Give a cautious overall interpretation of results considering objectives, limitations, multiplicity of analyses, results

from similar studies, and other relevant evidence 11

Generalisability 21 Discuss the generalisability (external validity) of the study results 11

Other information

Funding 22 Give the source of funding and the role of the funders for the present study and, if applicable, for the original study on

which the present article is based 12

*Give information separately for cases and controls in case-control studies and, if applicable, for exposed and unexposed groups in cohort and cross-sectional studies.

Note: An Explanation and Elaboration article discusses each checklist item and gives methodological background and published examples of transparent reporting. The STROBE

checklist is best used in conjunction with this article (freely available on the Web sites of PLoS Medicine at http://www.plosmedicine.org/, Annals of Internal Medicine at

http://www.annals.org/, and Epidemiology at http://www.epidem.com/). Information on the STROBE Initiative is available at www.strobe-statement.org.

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Diagnosis and management of polycystic ovary syndrome in the United Kingdom (2004-2014), a retrospective cohort

study

Journal: BMJ Open

Manuscript ID bmjopen-2016-012461.R1

Article Type: Research

Date Submitted by the Author: 09-Jun-2016

Complete List of Authors: Ding, Tao; University College London, Statistical Science Baio, Gianluca; UCL, Statistical Science Hardiman, Paul ; University College London Medical School

Petersen, Irene; University College London Medical School, Department of Primary Care and Population health Sammon, Cormac; University College London, Department of Primary Care and Population Health

<b>Primary Subject Heading</b>:

Epidemiology

Secondary Subject Heading: Diabetes and endocrinology

Keywords: EPIDEMIOLOGY, Polycystic Ovary Syndrome, prescription


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Title: Diagnosis and management of polycystic ovary syndrome in the United Kingdom (2004-

2014), a retrospective cohort study

Corresponding author:

Name: Tao Ding

Postal address: Department of Statistical Science, University College London, 1-19 Torrington

Place, London WC1E 6BT, UK

Email: [email protected] Telephone number: 07522127150

Co-authors:

Name: Gianluca Baio

Department: Department of Statistical Science



Name: Paul J. Hardiman

Department: Department of Women’s Institute of Health



Name: Irene Petersen




Name: Cormac Sammon




Keywords: epidemiology/PCOS/prescription

Word count: 2787

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Diagnosis and management of polycystic ovary syndrome in the United

Kingdom (2004-2014), a retrospective cohort study

Tao Ding1, Gianluca Baio1, Paul J.Hardiman2, Irene Petersen3, Cormac Sammon3

1Department of Statistical Science, University College London, London, UK,

2Institute for Women's Health, University

College London Medical School, London, UK, 3Department of Primary Care and Population Health, University College

London, London, UK

Correspondence to Tao Ding; [email protected]

Abstract (298/300)

Objective: To estimate the incidence and prevalence of PCOS in UK primary care and investigate

prescribing patterns before and after a PCOS diagnosis.

Design: Retrospective cohort study

Setting: UK primary care (2004 - 2014)

Participants: Women aged 15 to 45

Primary and secondary outcome measures: The incidence and prevalence of diagnosed PCOS and

probable PCOS (i.e. those without a confirmed diagnosis but with at least two PCOS features

recorded within 3 years). Among women with diagnosed or probable PCOS, the prevalence of

prescribing of drugs typically used to treat PCOS was calculated both prior to and in the 24 months

after the diagnosis of PCOS.

Results: We identified 7,233 women with PCOS diagnoses and 7,057 women with records

suggestive of probable PCOS, corresponding to incidence rates of 0.93 and 0.91 per 1000 person

years at risk (PYAR) and an overall rate of 1.84 per 1000 PYAR. Women aged 20-24 years and

women living in deprived areas had the highest incidence of PCOS. The prevalence of PCOS in 2014

was approximately 2%. The proportion of women with a prescription in the 24 months after their

PCOS index date varied by drug type: 10.2% metformin, 15.2% combined oral contraceptives,

18.8% acne related treatments, 1.93% clomiphene, 1.0% spironolactone, 0.28% cyproterone and

3.11% eflornithine. Acne related treatments were more commonly used to treat probable (28.3%)

than diagnosed cases (12.3%) while metformin were prescribed much more commonly in

diagnosed cases.

Conclusion: In conclusion, compared to rates estimated in community samples, the incidence and

prevalence of women presenting in primary care with PCOS diagnoses and features are low,

indicating that PCOS is an under-recognised condition. Although considerable variation is observed

in treatments prescribed to women with PCOS, the treatments initiated following a confirmed

diagnosis generally reflect the long-term prognostic concerns raised in PCOS consensuses.

Key words: epidemiology/PCOS/prescription

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Article summary

Strengths and limitations of this study

1. The current study is the first to investigate the incidence and prevalence of PCOS in the primary

care setting in the UK and the longitudinal nature of the database allowed us to examine trends

over a long time period, which has not been captured by previous epidemiological studies.

2. Under-diagnosis was the main concern for the current study as only data considered relevant at

the time of a consultation are recorded by clinicians although we attempted to include women

with two or more features of PCOS as potential cases.

3. Our study investigated the prescribing patterns of PCOS in the UK primary care, which has not

been well explored in previous studies. These findings reflected the current management of PCOS

in the clinical practices and provide important indications for general practitioners.

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Background

Polycystic ovary syndrome (PCOS) is associated with a wide range of reproductive,

cardiometabolic and dermatological abnormalities. One of the most prominent symptoms in PCOS

patients is oligo-menorrhea. Consequently, women with PCOS are highly likely to be infertile and

potentially develop endometrial hyperplasia due to continuing secretion of oestrogen without

ovulation [1,2]. Furthermore, emerging evidence has suggested that approximately 50-70% of

PCOS patients have insulin resistance regardless of their body weight or body mass index (BMI)

[3]. Consequently, women with PCOS are at an elevated risk of developing various common

metabolic disorders compared with the general population [4]. In addition, many PCOS patients

are observed to have an elevated androgen level, which leads to hirsutism, alopecia and acne [1].

While the epidemiology of PCOS in the community has been well studied [5-8], the proportion of

women who present in routine clinical practice with PCOS features and the extent to which these

women are subsequently diagnosed is less clear. Similarly, while a range of treatments have been

suggested for the management of PCOS [9], there is very little information regarding which of

these drugs are actually prescribed in routine clinical practice. Such ‘real world evidence’ can help

identify priority areas for research, training and health promotion efforts. The current study

sought to provide such evidence by investigating the recording of PCOS features and diagnoses in

UK general practice between 2004 and 2014 and the subsequent prescribing of pharmacological

treatments.

Methods

Data source

The Health Improvement Network (THIN) is one of the largest primary care data sources in the UK,

including data from over 500 general practices, covering approximately 6.2% of the total

population in the UK. Available data include patient demographics, medical history, test results,

drug prescriptions and social deprivation as measured by quintiles of the Townsend score [10].

Symptoms and diagnoses are recorded using a hierarchical clinical coding system (Read codes)

[11], with additional information recorded as unstructured text. The information stored as

unstructured text was not available in this study. Notably, as the data are collected in routine

clinical practice, only information deemed clinically relevant is entered in a patient’s record.

In our study, data were included from each practice that met minimum quality criteria, for

example, acceptable computer usage (ACU) (a time point when a practice is considered to use

their computer system adequately, i.e. at least one medical record, one additional health data

record such as body mass index, lab test results and two therapy records are computerized

annually for a practice) and acceptable mortality reporting (AMR) (a time point which the

observed death rates for a practice reach the standard predicted numbers of deaths derived from

National statistics given the practice’s demographics) [12-14].

Study population

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Women aged 15-45, who were permanently registered for at least one year were included in the

study population. Women with conditions that can cause similar symptoms to PCOS were

identified and excluded. These conditions include prolactinoma, Cushing’s syndrome, Nelson’s

syndrome, adrenal related disorders (i.e. adrenal tumours, adrenal hyperplasia), and pituitary

disorders.

Case definition

PCOS cases were identified using two methods. First, Read codes for ‘polycystic ovary syndrome’

(C165.00), ‘Stein-Leventhal syndrome’ (C164.12) and ‘endoscopic drilling of ovary’ (7E25300) were

used to identify those women who had been clinically diagnosed as PCOS cases (diagnosed cases).

Women with two or more Read codes indicative of PCOS features (menstrual/ovarian dysfunction,

clinical and biochemical hyperandrogenism, polycystic ovaries) recorded in a three year period

were then selected and we considered these as probable cases. These women were considered as

those who were likely to meet at least one of the 3 major definitions of PCOS [15-18] but who may

not have been clinically diagnosed as having the condition. The index date for probable cases was

considered to be the date the second PCOS feature was recorded. A full list of the codes used to

define cases is provided in Table SI.

Covariates and prescription indicators

We extracted data on each woman’s year of birth, ethnicity and deprivation level of the area in

which the woman lived [10]; data on prescriptions of interest (i.e. combined oral contraceptives,

progestin oral contraceptives, intrauterine devices, clomiphene, metformin, spironolactone,

gonadotrophins, cyproterone, flutamide, eflornithine, weight control/loss drugs, lipid regulators,

acne-related drugs) were also included and information on prescribing of these drugs before and

in the 24 months after each PCOS case index data was extracted.

Statistical Analysis

For incidence estimation, the rate was computed as the total number of new PCOS cases recorded

between 2004 and 2014 divided by the total number of person years of follow-up. Person-time for

the denominator was estimated by summing each woman’s follow-up from the latest among (i)

their 15th birthday, (ii) one year after registration, (iii) the date at which their practice met

minimum quality criteria and (iv) the 1st January 2004, to the earliest of the date among (i) their

first incident diagnosis, (ii) their date of death, (iii) the date they left the practice, (iv) the date data

were last collected from their practice and (v) the 31st December 2014. All incidence rates were

reported per 1000 person years at risk (PYAR).

Hierarchical (patients were considered to be nested in each practice) multivariate Poisson

regression models were used to estimate incidence rate ratios (IRR) and 95% confidence intervals

(95% CI) comparing the incidence of first PCOS diagnoses across 5-year age bands, Townsend

score quintiles and calendar period (i.e. 2004-2007, 2008-2011, 2012-2014).

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The period prevalence of the diagnosis of PCOS was evaluated for the calendar year 2014. The

denominator for the prevalence calculation consisted of any women with at least one year of post-

registration follow-up, of which at least 6 months must have occurred in 2014. The prevalence of

PCOS was also estimated within 5-year age bands. Secondary analysis was carried out to assess

the sensitivity of the prevalence estimate to the length of the post-registration period (i.e. 1 year,

2 years) and the minimum period registered within 2014 (i.e. 3, 6, 9 months).

Among the women with a diagnosis of PCOS, we calculated the number and proportion with a

prescription for one of the drugs of interest at any point prior to their PCOS index date. Among the

women without prescription for each drug of interest prior to the index date, we then calculated

the proportion of women with a prescription for that drug within 2 years after the PCOS index

date. We used cumulative incidence plots to describe how the proportion initiating different drugs

increased over the two years following the PCOS index date for the time period 2004-2012.

All analyses were performed using STATA 13.0 and were carried out for all PCOS cases and

stratified by case definition (diagnosed PCOS versus probable PCOS).

Results

In total, 7,233 diagnosed and 7,057 probable PCOS cases were identified amongst 2,087,107

female individuals aged 15-45 years old between 2004 and 2014. Table I describes the number of

PCOS features identified in each group. The incidence rate of diagnosed PCOS cases was 0.93 per

1000 PYAR (95% CI: 0.91-0.96) whereas the rate for probable cases was 0.91 per 1000 PYAR (95%

CI: 0.89-0.93). This equated to an overall combined incidence rate of 1.84 PYAR (95% CI: 1.81-

1.87).

Table I Number and proportion of diagnosed and probable cases with major PCOS features

Features

No. (%)

Diagnosed cases

(n=7233)

Probable cases

(n=7057)

Menstrual dysfunction 2055 (28.4) 6265 (88.8) Hyperandrogenism 2836 (39.2) 6221 (88.2) PCO 199 (2.8) 1636 (23.2) ≥ 2 features 597 (8.3) 7057 (100)

The overall incidence of PCOS increased from 1.67 (95% CI: 1.58-1.77) per 1000 PYAR in 2004 to

2.00 (95% CI: 1.89-2.10) per 1000 PYAR in 2010, after which the rate remained relatively constant

at approximately 2 per 1000 PYAR (Figure I). The incidence was the highest for those in the 20-24

year age group (3.59 per 1000 PYAR, 95% CI: 3.47-3.70) whereas the 40-44 year age group had the

lowest incidence (0.62 per 1000 PYAR, 95% CI: 0.58-0.66). The age-specific trend of PCOS

diagnoses was similar for both diagnosed and probable cases. After adjusting for the effects of

year and social deprivation, significant differences still remained in the incidence of PCOS (Table

II). In terms of social deprivation, the incidence of PCOS for individuals who were least deprived

was 1.59 (95% CI: 1.53-1.65) per 1000 PYAR whereas among the most deprived, a rate of 2.23

(95% CI: 2.15-2.32) per 1000 PYAR was estimated. This difference in rates remained statistically

significant after adjusting for effects of other covariates (i.e. age, year) and after stratifying by case

definition (Table II).

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The overall prevalence of PCOS in 2014 was approximately 2.27% (95% CI: 2.23-2.31%), with a

prevalence of 1.34% and 0.93% in diagnosed and probable cases, respectively. The age-specific

prevalence peaked in the 30-34 year age group, and decreased for older age groups. Prevalence

estimates were not sensitive to varying the post-registration period and the time period registered

within 2014, remaining consistently around 2%.

The proportion of women using one of the PCOS related drugs before or after their index date

varied widely across drugs groups (see Table III). At the time of their PCOS index date, over 40% of

women had previously been prescribed combined oral contraceptive (COC), approximately 30%

had been prescribed acne-related drugs before diagnosis, greater than 18% had been prescribed

progestin oral contraceptives (POC) and about 18% had previously been prescribed at least one of

the other drugs (Table III). Acne-related drugs, COC and metformin were the most commonly used

drugs in the 24 months after a PCOS record (Table III). Plots describing the cumulative incidence of

women with a prescription for each drug type over the 24 months following their index date are

provided in Figure SI. The plots show that while all drugs show an initial surge in prescribing on or

just after the PCOS index date, this is greater for some drugs (e.g. metformin, acne related drugs)

than for others (COCs and POCs).

Prescription results stratified according to whether PCOS cases were diagnosed or probable are

provided in Table SII. These results indicate that acne-related treatments and POCs were more

commonly used to treat probable than diagnosed cases while COCs, metformin, clomiphene,

cyproterone, elflornithine and weight loss drugs were prescribed more commonly in diagnosed

than probable cases. Cumulative incidence plots stratified according to whether a case was

diagnosed or probable illustrate the differences listed in table SII and further to this show that

these differences are typically established on or immediately after the index date (Figure II).

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Table II. Recorded rate of PCOS diagnoses by social and demographical characteristics

*IRR from multilevel Poisson distribution accounted for practice-level variability and adjusted for other variables considered

Diagnosed PCOS Probable PCOS Overall

Rate per 1000 PYAR (95% CI)






P

Townsend quintile <0.001 <0.001 <0.001

1 0.80 (0.76-0.84) 1 0.80 (0.76-0.84) 1 1.59 (1.53-1.65) 1

2 0.90 (0.85-0.95) 1.14 (1.06-1.23) 0.79 (0.75-0.84) 0.99 (0.92-1.07) 1.69 (1.62-1.75) 1.08 (1.02-1.14)

3 0.94 (0.90-0.99) 1.12 (1.04-1.21) 0.91 (0.86-0.96) 1.07 (0.99-1.15) 1.85 (1.78-1.92) 1.10 (1.05-1.16)

4 1.02 (0.97-1.07) 1.15 (1.06-1.24) 0.97 (0.92-1.02) 1.06 (0.98-1.15) 1.98 (1.91-2.05) 1.11 (1.05-1.17)

5 1.07 (1.01-1.13) 1.15 (1.05-1.25) 1.17 (1.11-1.23) 1.21 (1.11-1.32) 2.23 (2.15-2.32) 1.19 (1.11-1.26)

Age, years <0.001 <0.001 <0.001

15-19 1.20 (1.14-1.27) 0.69 (0.64-0.74) 0.54 (0.50-0.59) 0.29 (0.27-0.32) 1.75 (1.67-1.83) 0.49 (0.46-0.51)

20-24 1.72 (1.64-1.80) 1 1.87 (1.79-1.96) 1 3.59 (3.47-3.70) 1

25-29 1.51 (1.44-1.58) 0.86 (0.80-0.91) 1.49 (1.42-1.56) 0.78 (0.73-0.83) 2.98 (2.88-3.08) 0.81 (0.78-0.85)

30-34 1.03 (0.98-1.09) 0.58 (0.54-0.62) 0.86 (0.81-0.91) 0.46 (0.42-0.49) 1.88 (1.81-1.96) 0.51 (0.49-0.54)

35-39 0.45 (0.42-0.49) 0.26 (0.24-0.28) 0.55 (0.51-0.59) 0.30 (0.27-0.32) 0.99 (0.94-1.05) 0.27 (0.26-0.29)

40-44 0.17 (0.15-0.19) 0.10 (0.08-0.11) 0.45 (0.42-0.48) 0.24 (0.22-0.26) 0.62 (0.58-0.66) 0.17 (0.16-0.18)

Year <0.001 <0.001 <0.001

2004-2007 0.91 (0.87-0.94) 1 0.82 (0.79-0.86) 1 1.73 (1.68-1.78) 1

2008-2011 0.94 (0.91-0.98) 1.00 (0.95-1.06) 0.95 (0.92-0.99) 1.13 (1.07-1.19) 1.89 (1.84-1.94) 1.06 (1.02-1.10)

2012-2014 0.96 (0.92-1.01) 0.98 (0.92-1.04) 0.98 (0.93-1.02) 1.13 (1.07-1.20) 1.92 (1.86-1.98) 1.04 (1.00-1.09)

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Table III Number and percentage of PCOS women prescribed relevant drugs for PCOS both prior to and following the diagnosis of PCOS

Types of drugs

No. (%)

Before diagnosis of PCOS After diagnosis of PCOS

2004-2007 2008-2011 2012-2014

Combined oral

contraceptives

(COC)

12349 (40.22) 901 (17.01) 912 (18.87) 459 (17.88)

Progestin oral

contraceptives

(POC)

5806 (18.91) 474 (6.45) 691 (10.22) 272 (7.80)

Intrauterine

devices (IUDs)

728 (2.37) 43 (0.50) 64 (0.75) 25 (0.52)

Clomiphene 518 (1.69) 210 (2.46) 165 (1.92) 70 (1.43)

Metformin 1278 (4.16) 1212 (14.77) 1102 (13.25) 495 (10.52)

Gonadotrophins 435 (1.42) 29 (0.34) 13 (0.15) 13 (0.26)

Spironolactone 235 (0.77) 109 (1.26) 111 (1.28) 43 (0.87)

Cyproterone 91 (0.30) 28 (0.32) 19 (0.22) 3 (0.06)

Flutamide 6 (0.02) 4 (0.05) 1 (0.01) 0

Eflornithine 550 (1.79) 354 (4.10) 407 (4.81) 172 (3.58)

Weight

control/loss drugs

1330 (4.33) 403 (4.84) 364 (4.43) 91 (1.95)

Lipid regulators 194 (0.63) 69 (0.79) 46 (0.53) 8 (0.16)

Acne-related drugs 9000 (29.31) 1182 (19.52) 1234 (20.78) 582 (18.32)

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Discussion

Summary

We present data on more than 14,000 potential PCOS cases among women aged 15 to 45 in primary

care across the UK between 2004 and 2014. 51.2% of these women had a PCOS diagnosis recorded,

while 49.9% did not, corresponding to incidence rates of 0.93 per 1000 PYAR (95% CI: 0.91-0.96) and

0.91 per 1000 PYAR (95% CI: 0.89-0.93) respectively. The prevalence of PCOS in 2014 was

approximately 2.27%. There was considerable variation in the type of drug prescribed on the day of,

or in the 24 months after a PCOS diagnosis and prescribing differed between diagnosed and

probable cases.

Strengths and limitations

To the best of our knowledge, this study is the first to investigate the diagnosis and management of

PCOS in the primary care setting in the UK. As THIN contains over 10 million patient records, our

study is robust in terms of sample size. The longitudinal nature of the database also allowed us to

examine trends over a ten year study period which, has not been captured by previous

epidemiological studies where individuals were often sampled at a single time point.

As our data were collected in routine clinical practice our results reflect the true burden of PCOS on

the healthcare system. However, this also means that only data considered relevant at the time of a

consultation are recorded by clinicians. Consequently, it is unsurprising that only 8% of diagnosed

cases had ≥2 PCOS features recorded as, while the initial feature prompting referral is likely to be

noted by the general practitioner (GP), once a PCOS diagnosis has been made by a specialist a GP is

unlikely to record anything other than the confirmed diagnosis in the coded record. The routine

nature of data collection also meant that under-diagnosis was a concern in the current study and

underestimation of PCOS rates was anticipated. We attempted to address under-reporting by

allowing women with two or more features of PCOS (inter-feature period within 3 years) to count as

a PCOS case. However, the inclusion of probable cases may introduce case misclassification as some

probable cases may not be true PCOS cases. For example, while we considered women with a raised

testosterone level to have hyperandrogenism there are concerns surrounding the accuracy of

testosterone testing [19]. On the contrary, it is also possible that many probable cases are true cases

but do not have a diagnosis recorded in their medical records for some reason.

Incomplete patient history is a concern as women with prevalent PCOS diagnoses at the time of

registration with a practice may not be identified, resulting in the underestimation of prevalence

rates and the overestimation of incidence rates. Additionally, the lack of information on ethnicity is

also an issue as the trends in incidence observed over age, deprivation and calendar year categories

may be influenced by unobserved differences in ethnicity distributions across these covariates.

As we lack information on the indication for prescriptions we cannot be certain that prescriptions

issued after, or even on the date of a PCOS record were prescribed for the treatment of PCOS. For

example, approximately 30% of the PCOS cases prescribed metformin had a prior diagnosis of type 2

diabetes, the approved indication for this drug. However, by excluding those ever prescribed

metformin prior to their PCOS diagnosis from our calculations, we can be relatively confident that

prescriptions for metformin issued on the date of a PCOS diagnosis are likely to be at least partly for

the treatment of PCOS. Our confidence that the drug was prescribed for PCOS then decreases with

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increasing time after the PCOS diagnosis such that we expect the proportion of diagnosed cases

prescribed metformin for PCOS to lie somewhere between the 8% with a prescription on the date of

diagnosis and the 20% with a prescription on or in the 24 months after the date of diagnosis.

While we lacked information on prescribing outside primary care, the responsibility for prescribing

treatments which have been initiated by specialists is likely to be transferred to an individual’s GP a

number of months after diagnosis. The use of a 24 month window to assess prescribing therefore

allowed us to capture initiation of drugs prescribed in secondary care. This is reflected in the

cumulative incidence curves shown in Figure S1 where the drugs that are commonly initiated outside

primary care (e.g. spironolactone, clomiphene) are initiated further after the index date than the

drugs typically initiated in primary care (e.g. COCs, acne drugs). However, prescribing rates may be

underestimated if care is not transferred to the GP within 24 months (e.g. for budgetary reasons).

The proportion of women with PCOS who had been prescribed combined oral contraceptives (COC)

before their PCOS diagnosis is similar to that reported by other studies [20,21]. The proportion of

women with PCOS who initiated metformin after their diagnosis in our study (over 10%) is

comparable to a Danish study where 11.8% of the women with PCOS were identified as having

received metformin [21]. These comparisons support the validity of our prescribing data.

Interpretation

The prevalence of recorded PCOS in UK primary care in 2014 is comparable to that obtained from

studies using databases in the United States (0.56% to 2.22%) [22-24]. However, the rates are

significantly lower than those from epidemiological surveys in the Europe where systematic

screening were often provided to identify cases from selected populations [25-28]. This gap

highlights the importance for improving public and GPs’ awareness of PCOS.

The incidence of PCOS increased slightly over the study period however no significant changes in

yearly rates were observed. This might reflect the increasing awareness of the syndrome after the

establishment of the Rotterdam and AES criteria during the study period. However, it could also be

due to the improvement of the database, i.e. the completeness of medical recordings has improved

over time.

It should be noted that the Townsend score represents the deprivation level of the area in which a

woman lives. Women who lived in more deprived areas had a higher incidence of PCOS than those

living in the less deprived areas. A possible explanation is that obesity (a factor strongly associated

with PCOS) is more prevalent among women living in more deprived areas. Alternatively, these

women may consult their GP more frequently than those in less deprived areas, for other

morbidities (i.e. type 2 diabetes), and therefore have more opportunity for PCOS to be diagnosed

and recorded.

The fact that the incidence of probable PCOS cases was as high as the incidence of diagnosed cases

indicates that there are a large group of women who present in primary care exhibiting two features

of PCOS within a 3 year period but who do not have a subsequent PCOS diagnosis. While for some of

these probable cases a PCOS diagnosis may not be relevant, it is likely that a considerable proportion

of the women may meet the diagnostic criteria for PCOS and should therefore be referred for further

assessment. Failure to refer such women may mean they are not offered the lifestyle advice or

medications which could reduce their risk of long term PCOS-related complications.

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Variation was observed in the treatments prescribed to diagnosed and probable PCOS cases, in

particular, a greater proportion of diagnosed women received metformin prescriptions while a

greater proportion of the probable cases received treatment for the PCOS feature they presented

with. This suggests that the diagnosed and probable cases are indeed receiving different care for

their condition, with some probable cases not receiving potentially effective treatments such as

metformin. The wide variation in prescribing patterns may also be due to the varied nature of clinical

presentations of PCOS not only by individuals but also by age. For example, young women consulting

their GPs are more likely to ask for drugs to regulate their menses or to treat acne whereas more

elderly women may initiate anti-diabetic drugs to prevent rapid conversion to diabetes.

Metformin and oral contraceptives were the two drugs most commonly initiated in women with

diagnosed PCOS, possibly reflecting the major concerns of long-term metabolic risks of this

syndrome stated by the three PCOS consensuses. However, it is notable that even among the

diagnosed PCOS cases there is some variation in treatments prescribed following a diagnosis. This

suggests that there may be a lack of consensus on the ideal treatment for the condition. This is

supported by a recent survey of European endocrinologists which found variation in the treatments

most commonly prescribed for PCOS [29]. Further research into the comparative efficacy and

effectiveness of the various PCOS treatment options may therefore be warranted.

Conclusions

In conclusion, compared to rates estimated in community samples, the incidence of women

presenting in primary care with PCOS diagnoses and features is low compared with most

epidemiological surveys. Among the women that do present, only 50% were observed to have a

PCOS diagnosis recorded. Further work is therefore needed to inform women and healthcare

professionals about the condition to avoid any worsening of the disease or rapid conversion into

other metabolic disorders considering the relatively low cost of diagnosis and high cost of care for

the associated diseases suggested by Azziz et al. [30]. There is much potential for these treatments

to prove cost-effective alternatives, which should be carefully considered by public health care

providers, such as the NHS in the UK.

Although there is much variation in the treatments prescribed following a PCOS diagnosis, the

widespread prescribing of oral contraceptives and metformin generally reflects the prognostic

concerns raised in PCOS consensuses, aiming to reduce the future metabolic risks of PCOS patients

or treat PCOS patients who may already have developed metabolic disorders. Further work is

needed to identify the most effective treatment for the condition.

Contributors

TD, CS, IP were involved in the design of the study. TD and CS performed the analysis, while GB, IP,

PJH helped with the interpretation. TD prepared the manuscript, and CS, GB, IP, PJH revised it as

needed. All authors have read and approved the final manuscript.

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Funding: This research received no specific grant from any funding agency in the public, commercial

or not-for-profit sectors.

Competing interests: We have read and understood BMJ policy on declaration of interests and

declare that we have no competing interests.

Ethics: THIN has overall ethical approval from the South East Multicentre Research Ethics Committee

(reference number: 07/H1102/103).

Data sharing statement: No additional data are available.

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criteria and long-term health risks related to polycystic ovary syndrome (PCOS). Hum Reprod 19:41-47.

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RS, Norman RJ, Taylor AE et al. 2006 Positions statement: criteria for defining polycystic ovary syndrome as a

predominantly hyperandrogenic syndrome: an Androgen Excess Society guideline. J Clin Endocrinol Metab 91:4237-4245.

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review: guide to the best practices in the evaluation and treatment of polycystic ovary syndrome – Part 1. Endocr Pract.

2015 Nov;21(11):1291-300.

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profile of diagnosed polycystic ovary syndrome. J Clin Endocrinol Metab 91:1357-1363.

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privately insured, United States, 2003-2008. Am J Obstet Gynecol 207:299.

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indigent population. J Investig Med 62:868-74.

25. Michelmore KF, Balen AH, Dunger DB, Vessey MP. Polycystic ovaries and associated clinical and biochemical features

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26. Asunción M, Calvo RM, San Millán JL, Sancho J, Avila S, Escobar-Morreale HF. A prospective study of the prevalence

of the polycystic ovary syndrome in unselected Caucasian women from Spain. J Clin Endocrinol Metab. 2000

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27. Diamanti-Kandarakis E, Kouli CR, Bergiele AT, Filandra FA, Tsianateli TC, Spina GG, Zapanti ED, Bartzis MI. A survey of

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1999 Nov;84(11):4006-11.

28. Lauritsen MP, Bentzen JG, Pinborg A, Loft A, Forman JL, Thuesen LL, Cohen A, Hougaard DM, Nyboe Andersen A The

prevalence of polycystic ovary syndrome in a normal population according to the Rotterdam criteria versus revised

criteria including anti-Mullerian hormone.Hum Reprod. 2014 Apr;29(4):791-801.

29. Conway G, Dewailly D, Diamanti-Kandarakis E, Escobar-Morreale HF, Franks S, Gambineri A, Kelestimur F, Macut D,

Micic D, Pasquali R, Pfeifer M, Pignatelli D, Pugeat M, Yildiz B, ESE PCOS Special Interest Group. European survey of

diagnosis and management of the polycystic ovary syndrome: results of the ESE PCOS Special Interest Group's

Questionnaire. Eur J Endocrinol. 2014 Oct;171(4):489-98.

30. Azziz R, Marin C, Hoq L, Badamgarav E, Song P. Health care-related economic burden of the polycystic ovary

syndrome during the reproductive life span.J Clin Endocrinol Metab. 2005 Aug;90(8):4650-8.

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Time trends in PCOS diagnosis recorded (for diagnosed, probable and total cases). 338x246mm (300 x 300 DPI)

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Plots describing the cumulative incidence of women with a prescription for each drug type over the 24 months following their index date stratified according to whether the case was diagnosed (dashed line) or

probable (solid line). Results shown for the eight most commonly prescribed drugs.

326x244mm (300 x 300 DPI)

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Data supplement

Table SI Code lists used to identify study variables

medcode description

Codes for polycystic ovary syndrome

C164.12 Stein - Leventhal syndrome

C165.00 Polycystic ovarian syndrome

7E25300 Endoscopic drilling of ovary

K591100 Oligomenorrhoea

K591200 Primary oligomenorrhoea

K591300 Secondary oligomenorrhoea

K594.00 Irregular menstrual cycle

K594z00 Irregular menstrual cycle NOS

C161000 Hypersecretion of ovarian androgen

M240.00 Alopecia

M240000 Alopecia unspecified

M240200 Male pattern alopecia

M240300 Frontal alopecia of women

M240400 Premature alopecia

M240z00 Alopecia NOS

M241.00 Hirsutism - hypertrichosis

M260.00 Acne varioliformis

M260000 Acne frontalis

M260z00 Acne varioliformis NOS

M261.00 Other acne

M261000 Acne vulgaris

M261100 Acne conglobata

M261600 Cystic acne

M261A00 Pustular acne

M261E00 Acne excoriee des jeunes filles

M261F00 Acne fulminans

M261G00 Acne agminata

M261J00 Acne necrotica

M261K00 Acne keloidalis

M261X00 Acne, unspecified

M261z00 Other acne NOS

Myu6300 [X]Other androgenic alopecia

Myu6800 [X]Other acne

Myu6F00 [X]Acne, unspecified

4473 Serum testosterone

4473100 Serum testosterone level abnormal

4474 Free androgen index

4474100 Free androgenic index abnormal

447G.00 Plasma testosterone level

447H.00 Androgen level

4Q26.00 Dihydrotestosterone level

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4Q2E.00 Free testosterone level

4Q2F.00 Calculated free testosterone

ZRBs.00 Ferriman and Galwey score

K53..11 Ovarian cysts

K532.00 Other ovarian cysts

K532z00 Ovarian cyst NOS

Kyu9500 [X]Other and unspecified ovarian cysts

Codes for diseases for exclusion

B540.00 Malignant neoplasm of adrenal gland

B540000 Malignant neoplasm of adrenal cortex

B540100 Malignant neoplasm of adrenal medulla

B540z00 Malignant neoplasm of adrenal gland NOS

B587.00 Secondary malignant neoplasm of adrenal gland

B7H0.00 Benign neoplasm of adrenal gland

B8yy100 Carcinoma in situ of adrenal gland

B922.00 Neoplasm of uncertain behaviour of adrenal gland

BB5h.00 [M]Adrenal cortical tumours

BB5h000 [M]Adrenal cortical adenoma NOS

BB5h100 [M]Adrenal cortical carcinoma

BB5h300 [M]Adrenal cortical adenoma, heavily pigmented variant

BB5h400 [M]Adrenal cortical adenoma, clear cell type

BB5h500 [M]Adrenal cortical adenoma, glomerulosa cell type

BB5h600 [M]Adrenal cortical adenoma, mixed cell type

BB5hz00 [M]Adrenal cortical tumours NOS

BBCF.00 [M]Adrenal rest tumour

BBD7.00 [M]Extra-adrenal paraganglioma, NOS

C15..00 Disorders of adrenal glands

C153.00 Other corticoadrenal overactivity

C155000 Adrenal medullary insufficiency

C15y.00 Other specified adrenal disorders

C15yz00 Other specified adrenal disorder NOS

C15z.00 Adrenal gland disorder NOS

Cyu4A00 [X]Other specified disorders of adrenal gland

PK1..00 Anomalies of adrenal gland

PK10.00 Aberrant adrenal gland

PK12.00 Accessory adrenal gland

PK13.00 Hypoplasia of adrenal gland

PK14.00 Ectopic adrenal gland

PK1y.00 Other specified anomalies of adrenal gland

PK1y000 Congenital cyst of adrenal gland

PK1yz00 Other congenital anomaly of adrenal gland NOS

PK1z.00 Anomalies of adrenal gland NOS

2226.11 O/E - cushingoid facies

C150.00 Cushing's syndrome

C150000 Idiopathic Cushing's syndrome

C150100 Iatrogenic Cushing's syndrome

C150111 Drug-induced Cushings syndrome

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C150200 Pituitary dependent Cushing's syndrome

C150300 Ectopic ACTH secretion causing Cushing's syndrome

C150500 Alcohol-induced pseudo-Cushing's syndrome

C150z00 Cushing's syndrome NOS

Cyu4500 [X]Other Cushing's syndrome

F395100 Myopathy due to Cushing's syndrome

C150400 Nelson's syndrome

BB5y400 [M]Prolactinoma

B542.00 Malignant neoplasm pituitary gland and craniopharyngeal duct

B542000 Malignant neoplasm of pituitary gland

B542z00 Malig neop pituitary gland or craniopharyngeal duct NOS

B7H2.00 Benign neoplasm of pituitary gland and craniopharyngeal duct

B7H2.11 Pituitary adenoma

B7H2000 Benign neoplasm of pituitary gland

B7H2z00 Benign neoplasm of pituitary and craniopharyngeal duct NOS

B8yy300 Carcinoma in situ of pituitary gland

B920.00 Neop uncertain behaviour pituitary and craniopharyngeal duct

B920000 Neoplasm of uncertain behaviour of pituitary gland

B920z00 Neop uncertain behaviour pituitary and craniopharyngeal NOS

BB5V.00 [M]Pituitary adenomas and carcinomas

BB5Vz00 [M]Pituitary adenoma or carcinoma NOS

C13..00 Disorders of pituitary gland and its hypothalamic control

C131.00 Other anterior pituitary hyperfunction

C134.00 Other anterior pituitary disorder

C134z00 Other anterior pituitary disorder NOS

C134z11 Anterior pituitary hormone deficiency NEC

C137.00 Iatrogenic pituitary disorders

C137z00 Iatrogenic pituitary disorder NOS

C13z.00 Pituitary disorders NOS

Cyu4400 [X]Other disorders of pituitary gland

Cyu4M00 [X]Hyperfunction of pituitary gland, unspecified

K5B1.00 Female infertility of pituitary - hypothalamic origin

K5B1000 Primary pituitary - hypothalamic infertility

K5B1z00 Female infertility of pituitary - hypothalamic cause NOS

PK24.00 Anomalies of pituitary gland

PK24000 Aberrant pituitary gland

PK24z00 Anomaly of pituitary gland NOS

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Table SII Number and percentage of PCOS women prescribed relevant drugs for PCOS both prior to and following the diagnosis of PCOS stratified by case

definition

Types of drugs No. (%)

Before After

2004-2007 2008-2011 2012-2014

Diagnosed Probable Diagnosed Probable Diagnosed Probable Diagnosed Probable

Combined oral contraceptives (COC)

5136 (31.35) 7213 (50.37) 601 (16.68) 291 (17.19) 611 (20.57) 311 (16.51) 290 (20.52) 179 (14.90)

Progestin oral contraceptives (POC)

2067 (12.62) 3739 (26.11) 260 (5.48) 212 (8.11) 377 (9.18) 312 (11.58) 163 (8.29) 115 (7.24)

Intrauterine devices (IUDs)

191 (1.17) 537 (3.75) 21 (0.40) 23 (0.69) 31 (0.64) 33 (0.88) 13 (0.51) 13 (0.54)

Clomiphene 332 (2.03) 186 (1.30) 164 (3.18) 45 (1.34) 129 (2.69) 38 (0.98) 61 (2.41) 10 (0.41)

Metformin 1084 (6.62) 194 (1.35) 1125 (23.27) 88 (2.62) 991 (21.87) 112 (2.92) 459 (19.44) 51 (2.11)

Gonadotrophins 126 (0.77) 309 (2.16) 17 (0.32) 12 (0.36) 7 (0.14) 6 (0.16) 5 (0.20) 8 (0.33)

Spironolactone 174 (1.06) 61 (0.43) 101 (1.94) 9 (0.26) 101 (2.08) 10 (0.26) 37 (1.45) 7 (0.28)

Cyproterone 72 (0.44) 19 (0.13) 27 (0.51) 4 (0.12) 17 (0.35) 2 (0.05) 2 (0.08) 1 (0.04)

Flutamide 6 (0.04) 0 4 (0.08) 0 0 1 (0.03) 0 0

Eflornithine 415 (2.53) 135 (0.94) 279 (5.33) 73 (2.14) 292 (6.22) 112 (2.93) 129 (5.27) 47 (1.94)

Weight control/loss drugs

849 (5.18) 481 (3.36) 320 (6.39) 84 (2.53) 284 (6.22) 82 (2.21) 72 (3.02) 23 (0.98)

Lipid regulators 93 (0.57) 101 (0.71) 48 (0.91) 22 (0.65) 25 (0.52) 21 (0.55) 5 (0.20) 3 (0.12)

Acne-related drugs

3547 (21.64) 5453 (38.08) 600 (14.99) 585 (28.63) 583 (15.95) 664 (28.53) 226 (12.67) 373 (25.92)

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Figure SI. Plots describing the cumulative incidence of women with a prescription for each drug type over the 730 days following their index date.

Results shown for the eight most commonly prescribed drugs.

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STROBE 2007 (v4) checklist of items to be included in reports of observational studies in epidemiology*

Checklist for cohort, case-control, and cross-sectional studies (combined)

Section/Topic Item # Recommendation Reported on page #

Title and abstract 1 (a) Indicate the study’s design with a commonly used term in the title or the abstract 2

(b) Provide in the abstract an informative and balanced summary of what was done and what was found 2

Introduction

Background/rationale 2 Explain the scientific background and rationale for the investigation being reported 4

Objectives 3 State specific objectives, including any pre-specified hypotheses 4

Methods

Study design 4 Present key elements of study design early in the paper 4

Setting 5 Describe the setting, locations, and relevant dates, including periods of recruitment, exposure, follow-up, and data

collection 4

Participants 6 (a) Cohort study—Give the eligibility criteria, and the sources and methods of selection of participants. Describe

methods of follow-up

Case-control study—Give the eligibility criteria, and the sources and methods of case ascertainment and control

selection. Give the rationale for the choice of cases and controls

Cross-sectional study—Give the eligibility criteria, and the sources and methods of selection of participants

5-6

(b) Cohort study—For matched studies, give matching criteria and number of exposed and unexposed

Case-control study—For matched studies, give matching criteria and the number of controls per case NA

Variables 7 Clearly define all outcomes, exposures, predictors, potential confounders, and effect modifiers. Give diagnostic

criteria, if applicable 5

Data sources/ measurement 8* For each variable of interest, give sources of data and details of methods of assessment (measurement). Describe

comparability of assessment methods if there is more than one group 4-5

Bias 9 Describe any efforts to address potential sources of bias 4-5

Study size 10 Explain how the study size was arrived at NA

Quantitative variables 11 Explain how quantitative variables were handled in the analyses. If applicable, describe which groupings were chosen

and why 4-5

Statistical methods 12 (a) Describe all statistical methods, including those used to control for confounding 5-6

(b) Describe any methods used to examine subgroups and interactions NA

(c) Explain how missing data were addressed NA

(d) Cohort study—If applicable, explain how loss to follow-up was addressed

Case-control study—If applicable, explain how matching of cases and controls was addressed 5-6

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Cross-sectional study—If applicable, describe analytical methods taking account of sampling strategy

(e) Describe any sensitivity analyses 5-6

Results

Participants 13* (a) Report numbers of individuals at each stage of study—eg numbers potentially eligible, examined for eligibility,

confirmed eligible, included in the study, completing follow-up, and analysed 6

(b) Give reasons for non-participation at each stage NA

(c) Consider use of a flow diagram NA

Descriptive data 14* (a) Give characteristics of study participants (eg demographic, clinical, social) and information on exposures and

potential confounders

(b) Indicate number of participants with missing data for each variable of interest NA

(c) Cohort study—Summarise follow-up time (eg, average and total amount) 6

Outcome data 15* Cohort study—Report numbers of outcome events or summary measures over time 6-7

Case-control study—Report numbers in each exposure category, or summary measures of exposure NA

Cross-sectional study—Report numbers of outcome events or summary measures 6-7

Main results 16 (a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates and their precision (eg, 95%

confidence interval). Make clear which confounders were adjusted for and why they were included 6-7

(b) Report category boundaries when continuous variables were categorized 6-8

(c) If relevant, consider translating estimates of relative risk into absolute risk for a meaningful time period 6-8

Other analyses 17 Report other analyses done—eg analyses of subgroups and interactions, and sensitivity analyses 6

Discussion

Key results 18 Summarise key results with reference to study objectives 10

Limitations 19 Discuss limitations of the study, taking into account sources of potential bias or imprecision. Discuss both direction

and magnitude of any potential bias 10-11

Interpretation 20 Give a cautious overall interpretation of results considering objectives, limitations, multiplicity of analyses, results

from similar studies, and other relevant evidence 11-12

Generalisability 21 Discuss the generalisability (external validity) of the study results 11-12

Other information

Funding 22 Give the source of funding and the role of the funders for the present study and, if applicable, for the original study on

which the present article is based 13

*Give information separately for cases and controls in case-control studies and, if applicable, for exposed and unexposed groups in cohort and cross-sectional studies.

Note: An Explanation and Elaboration article discusses each checklist item and gives methodological background and published examples of transparent reporting. The STROBE

checklist is best used in conjunction with this article (freely available on the Web sites of PLoS Medicine at http://www.plosmedicine.org/, Annals of Internal Medicine at

http://www.annals.org/, and Epidemiology at http://www.epidem.com/). Information on the STROBE Initiative is available at www.strobe-statement.org.

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bmj open · furthermore, emerging evidence has suggested that approximately 50-70% of pcos patients...

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