A Meta-Analysis of Observational Studies on Prolactin Levels in Women with Polycystic Ovary Syndrome

2. Materials and Methods

This study was conducted in accordance with the PRISMA statement (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) [21].

2.1. Search Strategy

A comprehensive search was conducted up to 30 August 2022, in PubMed and Web of Science. The search terms used were (“Polycystic Ovary Syndrome” OR “Ovary Syndrome, Polycystic” OR “Syndrome, Polycystic Ovary” OR “Stein-Leventhal Syndrome” OR “Stein Leventhal Syndrome” OR “Syndrome, Stein-Leventhal” OR “Polycystic Ovarian Syndrome” OR “Ovarian Syndrome, Polycystic” OR “PCOS”) AND (“Hyperprolactinemia” OR “Prolactin, Inappropriate Secretion” OR “Inappropriate Secretion Prolactin” OR “Secretion Prolactin, Inappropriate” OR “Prolactin Hypersecretion Syndrome” OR “Hypersecretion Syndrome, Prolactin” OR “Syndrome, Prolactin Hypersecretion” OR “Inappropriate Prolactin Secretion” OR “Prolactin Secretion, Inappropriate” OR “Prolactinoma” OR “HPRL” OR “Prolactin” OR “PRL”). We restricted our search to the English language. An additional manual retrieval was conducted through reference lists of the selected studies to detect other relevant studies.

2.2. Inclusion Criteria

Studies meeting the following inclusion criteria were included: (1) observational studies, including cross-sectional, case-control, and cohort studies with data on confirmed PCOS patients according to Rotterdam diagnosis criteria and non-PCOS controls. (2) Studies with data on serum PRL levels in both PCOS women and controls after excluding the other causes of hyperprolactinemia (including pituitary tumours, hypothyroidism, pregnancy, thyroid disorder, and Cushing syndrome, etc.).

2.3. Data Extraction

Two independent authors (M.S.G and F.R.T) extracted the following information from the eligible studies: first author, the date of publication, country, study design, sample size, diagnostic criteria, detection method, the mean and standard deviation/median and interquartile range/median and range of serum PRL concentrations.If a study presented serum PRL levels through other means of central tendency (quartile, percentile, and median), the values were converted to mean ± SD using proper formulas [22]. The different reported measurement units of PRL in different studies were all converted to a single unit, which was ng/mL.

2.4. Quality Assessment

The quality of included articles was assessed and scored by two investigators independently (F.M. and MSG), by applying the Newcastle–Ottawa scale (NOS), to improve the interpretation of the results and reduce the review bias. Scoring the NOS grade was carried out according to three aspects: selection, comparability, and exposure. According to the quality score assessment, each item on the scale is scored from one point, except for comparability, which can be adapted to the specific topic of interest to score up to two points [23]. NOS score categories of 0–3, 4–6, and 7–9 were considered as low, moderate, and high quality, respectively. Disagreements were resolved by discussion with the third reviewer (FRT).

2.5. Statistical Analysis

The combined mean difference and the corresponding 95% confidence interval (95% CI) of PRL levels in the PCOS and non-PCOS participants of all included studies were calculated. The statistical significance of pooled mean difference was estimated with the Z test. The graphical results were displayed by forest plot.The chi-squared test and I2 statistic were calculated to evaluate statistical heterogeneity among studies. A random-effects model was performed when significant heterogeneity (I2 > 50% or p < 0.05) was detected. Further subgroup analysis was conducted to assess the potential sources of heterogeneity. To examine possible heterogeneities in the meta-analysis, a meta-regression analysis was performed using the following variables: age, continent of origin, and BMI. Publication bias was evaluated using Begg’s funnel plot and Egger’s regression test. STATA software version 14.0 (StataCorp LP, College Station, TX, USA) was used to conduct the meta-analysis, and p < 0.05 was considered as statistically significant.

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Abstract

Infertility, defined as the inability to conceive after 12 months of regular unprotected intercourse (1), affects ~7% to 15.5% of reproductive-aged women in the United States (2). Although a cause for infertility is identified in the majority of couples, ~10% to 30% have unexplained or idiopathic infertility, which is defined as infertility in the setting of regular ovulation, tubal patency, a normal uterine cavity, and normal semen analysis (3–6). Unexplained infertility (UI) is associated with high emotional and economic costs; annual US expenditures for all forms of infertility total $3 to $4 billion/y (7), and couples with UI have higher conception rates with in vitro fertilization (IVF), one of the most expensive forms of treatment (8). Therefore, gaining a greater understanding of potential hormonal factors that may contribute to UI may lead to more economical and effective treatment strategies for these couples.

Known causes of infertility include hyperprolactinemia and thyroid dysfunction (9, 10). Hyperprolactinemia is a common cause of amenorrhea and infertility, due to impaired gonadotropin secretion and pulsatility, likely caused by impaired gonadotropin-releasing hormone secretion (11, 12). Treatment with dopamine agonist therapy has been shown to restore ovulation and fertility in women with hyperprolactinemia (13–16). Importantly, even hyperprolactinemic women with regular menstrual cycles may experience decreased fertility because of a shortened luteal phase (17–19), but whether high-normal levels of prolactin in women with no known history of hyperprolactinemia may affect fertility remains unknown.

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Murine and in vitro studies suggest that thyrotropin (TSH) and thyroid hormone are important factors during oocyte development and implantation (20–23). In humans, an in vivo model also suggests the importance of TSH for oocyte development, as TSH levels ≥2.5 mIU/L in oocyte donors inversely predict clinical pregnancy independent of the recipient’s TSH level (24). Both hyperthyroidism (25) and hypothyroidism are associated with menstrual irregularity (26), and rates of infertility have been reported to approach 50% in women with Hashimoto thyroiditis and Graves disease (27). A higher percentage of women with infertility have also been shown to have frankly abnormal TSH levels as compared with controls (28), and the recent American Thyroid Association Thyroid and Pregnancy Guidelines recommend checking TSH in all women seeking evaluation for infertility (29). However, whether higher TSH levels in a population of women with a normal TSH and no known history of thyroid disease are part of the UI phenotype remains an unanswered question.

Methods

Study population

Using the patient database registry at a large academic health system (the Research Patient Data Registry of Partners HealthCare system), we obtained data on female patients between 18 and 39 years of age who presented to the Partners HealthCare system with the diagnosis of infertility and without a disorder of menstruation between 1 January 2000 and 31 December 2012. All electronic records were then individually reviewed to ensure that the women met our inclusion and exclusion criteria. Women were included who did not conceive after ≥1 year with appropriate exposure to sperm (UI group) or who had inadequate exposure to sperm due to a male partner with azoospermia (n = 39) or severe oligospermia (n = 13) with a sperm count <1 millionml (severe male factor). inclusion criteria for all women included regular menstrual cycles every 21 to 35 days with ≤5 of intercycle variability, normal uterine cavity evaluation, cycle day 3 follicle-stimulating hormone (fsh) ≤10 iu concomitant estradiollevel ≤80 pg (34), tsh within the rangeassay and miu l, prolactin ≤20 ng ml. partners ui had semen concentration ≥15ml, motility ≥40%, forms ≥4% (wherestrict tygerberg analysis was available), based on world health organization 2010 (35),regardless year evaluation. if (36) evaluation sperm not available, subjects were excluded percentage abnormal forms. in severe factor group concentrations <1 at least two occasions. we history hypothyroidism or hyperthyroidism (including postpartum thyroiditis an level), a high level, body mass index (bmi) <18.5 kg m2 or ≥40 kg/m2, women with recurrent pregnancy loss (three or more miscarriages), women with abnormalities that may be associated with reproduction (e.g., complex ovarian cysts, previous ovarian surgery, cervical stenosis, endometriosis, or endometritis), or a strong suspicion by the evaluating physician of an endocrine disorder, including polycystic ovary syndrome. This study was approved by the Partners HealthCare institutional review board.

Laboratory assessment

Statistical analysis

Statistical analysis was performed using JMP Pro 11.0 (SAS Institute, Cary, NC) software. Means and standard deviation measurements are reported and compared using the Student’s t test unless the data were nonnormally distributed, in which case medians and first and third quartile ranges are presented and compared via the Wilcoxon rank-sum test. Percentages were compared using the Fisher exact test or the Pearson χ2 test. Least-squares linear regression modeling was performed to control for clinically relevant covariates. TSH was log transformed for the regression analyses due to nonnormality. P <0.05 on a two-tailed test was used to indicate statistical significance.

Results

Clinical characteristics

A total of 239 women met our inclusion and exclusion criteria: 187 women with UI and 52 with severe male factor infertility. Subjects in the two groups were similarly distributed across the 13-year study period (P = 0.69). Characteristics of the study participants are listed in Table 1. Subjects in the UI group were slightly older than subjects in the severe male factor group (mean age ± standard deviation: UI, 31.5 ± 2.7 years; severe male factor, 30.1 ± 3.7 years; P = 0.01). Median BMI was lower in the UI group as compared with the severe male factor group [UI median BMI 23.0 kg/m2, interquartile range: (20.9, 26.2); severe male factor median BMI 24.4 kg/m2, interquartile range: (22.2, 27.0); P < 0.04], and the percentage of women with a BMI ≥25 kg/m2 was lower in the UI group than in the severe male factor group, although this difference was not statistically significant (P = 0.24). Median duration of infertility and mean day 3 FSH levels were similar in both groups.

TSH and prolactin levels

TSH

Median TSH levels were significantly greater in the UI group than in the severe male factor group [UI median TSH 1.95 mIU/L, interquartile range: (1.54, 2.61); severe male factor TSH 1.66 mIU/L, interquartile range: (1.25, 2.17); P = 0.003] (Fig. 1). TSH levels remained significantly higher in the UI group when we controlled for both BMI (P < 0.02) and age (P < 0.01), variables that have been positively associated with TSH in previous studies (37–41). Although smoking status was not significantly different between the groups, both past and a current history of cigarette smoking are associated with lower TSH levels (42). Therefore, we also controlled for both current history of smoking and past or current history of smoking, and TSH remained significantly higher in the UI group than in the severe male factor group (P < 0.01 for both).

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After we excluded women from the UI group whose partner had a low morphology based on methods that did not use strict (Tygerberg) criteria (n = 19), TSH levels remained significantly higher in the UI group than in the severe male factor group [UI TSH 1.96 mIU/L, interquartile range: (1.54, 2.61); severe male factor TSH 1.66 mIU/L, interquartile range: (1.25, 2.17); P < 0.01] and regression analyses similarly remained significant (P ≤ 0.01 for all).

Significantly more women in the UI group had TSH values ≥2.5 mIU/L as compared with women in the severe male factor group (Fig. 2). The percentage of women in the UI group with a TSH ≥2.5 mIU/L was nearly twice the percentage in the severe male factor group (UI 26.9%, severe male factor 13.5%; P < 0.05). Of the 57 total patients who had a TSH ≥2.5 mIU/L, 22.8% (13 patients) were started on thyroid hormone replacement therapy after their initial evaluation, although it is not known whether patients were initiated on thyroid hormone replacement to prevent adverse obstetrical outcomes if they were to conceive or in an attempt to improve the likelihood of conception.

To exclude the possibility that the observed differences were due to changes in assay methods or laboratory procedures, we divided patients into groups depending on where their TSH level was measured (which hospital or laboratory) and which assay was used. In one case, two laboratories used the same TSH assay, but patients who had their TSH measured with this assay were divided into two separate groups because there may have been systematic differences between the hospital laboratories that could have led to differences in TSH levels. Table 2 shows the percentage of women with UI and severe male factor in each of the laboratory and assay groupings. Although the overall χ2 test did not detect a difference between the groups with respect to where and how TSH was measured (P = 0.48), we performed individual significance testing to ensure that we were not missing differences. With individual testing, we found that a significantly higher percentage of subjects in the severe male factor group had a TSH level measured in one laboratory/assay (group 4) compared with subjects with UI (P = 0.04). When we excluded patients from laboratory/assay group 4 and those who had their TSH measured with an unknown assay, the observed differences in TSH levels remained significant; the TSH level in the UI group (n = 130) was significantly higher than that of the severe male factor group (n = 30) [UI TSH 1.94 mIU/L, interquartile range: (1.52, 2.54); severe male factor TSH 1.72 mIU/L, interquartile range: (1.32, 2.00); P = 0.01], and a significantly higher percentage of women with UI had a TSH ≥2.5 mIU/L compared with those with severe male factor infertility (25.4% vs 6.7%, P < 0.03).

Thyroid peroxidase antibodies

Only 19 of the 239 women in the study had thyroid peroxidase (TPO) antibodies assessed around the time of their infertility evaluation. Of these 19 women, 6 had an elevated TPO antibody level (3 in the UI group and 3 in the severe male factor group). Median TPO antibody levels were significantly higher in the severe male factor group than in the UI group [UI TPO antibody 13.3 IU/mL, interquartile range: (10.2, 18); severe male factor TPO antibody 90.4 IU/mL, interquartile range: (18.4, 2994.3); P = 0.03]. When the six subjects with a positive TPO antibody were excluded from the TSH analyses, the results remained significant, with a higher median TSH level in the UI group [1.95 mIU/L, interquartile range: (1.52, 2.58)] as compared with the severe male factor group [1.69 mIU/L, interquartile range: (1.22, 2.16); P < 0.01] and a significantly higher percentage of subjects with a TSH ≥2.5 mIU/L in the UI group (26%) than in the severe male factor group (12%; P < 0.04).

Prolactin

Prolactin levels were similar in the UI group and the severe male factor group [UI prolactin 10.4 ng/mL, interquartile range: (7.7, 13.4); severe male factor prolactin 11 ng/mL, interquartile range: (8.5, 13.7); P = 0.36]. Because prolactin levels may vary during the menstrual cycle (43, 44), we performed an analysis including only women who had prolactin measured on day 3 of their menstrual cycle (n = 180), and the results were similar [UI prolactin 10.8 ng/mL, interquartile range: (8.1, 13.7); severe male factor prolactin 12.5 ng/mL, interquartile range: (9.2, 14.5); P = 0.20]. There were no significant differences between the groups with respect to method of prolactin measurement (P = 0.82; Supplemental Table 1).

Discussion

We have shown that women with UI have significantly higher TSH levels than a control group of women with a comparatively normal fertility evaluation except for an azoospermic or severely oligospermic partner. Similarly, nearly twice as many women with UI have TSH levels ≥2.5 mIU/L as compared with the control group. Importantly, all subjects in this study had TSH levels within the normal, prepregnancy reference range, suggesting that even mild variations of thyroid dysfunction within the normal range may be an important factor in fertility in women who have no known cause for their infertility.

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Thyroid disease is a known cause of menstrual irregularity and infertility (9). A number of previous studies have investigated the relationship between TSH and conception rates or time to pregnancy with conflicting results; a TSH ≥2.5 mIU/L has not been associated with increased time to pregnancy in women with proven fecundity (and without a history of infertility) (45) or with adverse intrauterine insemination outcomes (46), whereas in a large population-based study including women with thyroid dysfunction, higher TSH levels were associated with fewer total pregnancies (47).

Because we did not require proven fecundity as a criterion for the severe male factor group, our choice of control group probably biased our result toward the null hypothesis, because it is possible that some of the women in the severe male factor group would have been classified as having UI had they been with a partner with a normal semen profile. Therefore, the fact that we found a difference in TSH levels, despite this choice of control group, only adds to the strength of our findings. We also did not use a population of couples with less severe forms of male factor infertility as our control group, which would have yielded a much larger number of controls. The definition of male factor infertility has changed over the years, with the lower limit of most semen parameters being lower in current as compared with previous reference ranges (35). Therefore, including a population of couples over a span of 13 years, with a changing definition of male infertility, would have been problematic. Second, a previous study found that in a population of couples who underwent IVF, TSH levels were significantly higher in women with a male partner with male factor infertility as compared with other types of infertility, including ovulatory and tubal factors (49). The authors hypothesized that this is likely due to the fact that in couples diagnosed with mild male factor infertility, female factors also contribute to the diagnosis of infertility, supported by previous studies demonstrating that female partners of men with poor semen factors have lower fertilization rates using donor sperm as compared with female partners of azoospermic men (49–51). Given the complicated relationship between mild male factor infertility and female hormonal status, we included only couples with azoospermia or severe oligospermia in our analysis.

We also hypothesized that women with UI would have higher prolactin levels (within the normal range) as compared with the control group. A previous study demonstrated higher prolactin levels in ovulating women with infertility of an unknown cause as compared with a control group of fertile women, and treatment with a dopamine agonist resulted in conception in 16 of the 40 infertile women during the 10 months of follow-up (52). On the other hand, a more recent Cochrane review combining data from three double-blind, randomized trials of 127 women with UI treated with bromocriptine or placebo found no benefit in conception rates in the bromocriptine-treated group (53). In our study, we did not find a significant difference in prolactin levels in women with UI as compared with severe male factor infertility. Importantly, prolactin levels are exquisitely sensitive to environmental influences including stress (54) and food intake (55) and have been shown to be highest during the ovulatory and luteal phases of the menstrual cycle (43, 44). We attempted to control for some of this potential variability by including only prolactin levels measured on day 3 of the menstrual cycle, but it is possible that even if there was a difference between groups, we did not detect it because of the variability we were not able to control for. To determine whether prolactin levels contribute to the phenotype of UI, future studies will need to measure prolactin levels in a carefully controlled setting.

Strengths of our study include our very strict inclusion and exclusion criteria, which allowed us to control for other possible factors contributing to infertility. Importantly, our control group consisted of a population of women who had a similarly rigorous fertility evaluation compared with the UI group. The main limitation of this study is that we relied on health records and therefore we were limited to laboratory tests that were drawn for clinical purposes. Therefore, we could not measure thyroid antibody levels or thyroid hormone levels in our subjects, and a previous meta-analysis demonstrated an increased rate of infertility in women who were thyroid antibody positive (56). Of the 239 women included in our study, only 19 had TPO antibodies checked around the time of their infertility evaluation.

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Acknowledgments

Financial Support: This work is supported by National Institutes of Health Grants K23 DK094820 (to P.K.F.; National Institute of Diabetes and Digestive and Kidney Diseases, http://dx.doi.org/10.13039/100000062) and 1UL1TR001102 and the Claflin Distinguished Scholar Award (to P.K.F.; Massachusetts General Hospital, http://dx.doi.org/10.13039/100005294). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Disclosure Summary: The authors have nothing to disclose.

References

Author notes

References

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