Home About us Editorial board Search Ahead of print Current issue Archives Submit article Instructions Subscribe Contacts Login 


 
 Table of Contents  
ORIGINAL ARTICLE
Year : 2014  |  Volume : 27  |  Issue : 4  |  Page : 657-664

Anti-Müllerian hormone, visceral fat, and ovarian stromal Doppler to predict response to ovulation induction in polycystic ovary syndrome


Department of Obstetrics and Gynecology, Faculty of Medicine, Menoufia University, Menoufia, Egypt

Date of Submission23-Oct-2014
Date of Acceptance14-Apr-2014
Date of Web Publication22-Jan-2015

Correspondence Address:
Haitham A Hamza
Department of Obstetrics and Gynecology, Faculty of Medicine, Menoufia University, Menoufia
Egypt
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/1110-2098.149643

Rights and Permissions
  Abstract 

Objective
This study was designed to identify whether visceral adiposity, anti-Mόllerian hormone, and ovarian stromal Doppler assessed during initial screening could predict the response to ovulation induction with clomiphene citrate in patients with polycystic ovary syndrome.
Background
The first choice of drug in women with polycystic ovary syndrome is clomiphene citrate. Three-quarters of women with polycystic ovary syndrome will ovulate with clomiphene citrate. Patients who do not ovulate on the maximum dose of 150 mg are considered to be clomiphene citrate resistant. Several parameters have been used to predict ovarian response in polycystic ovary syndrome patients.
Patients and methods
The study was carried out on 150 patients with polycystic ovary syndrome. Initial clomiphene citrate doses were 50 mg daily for 5 days starting on cycle day 3. In the absence of response, doses were increased to 100 and 150 mg daily in subsequent cycles. First ovulation with clomiphene citrate was used as the endpoint.
Results
At the end of the follow-up period, 110 (73.3%) patients had ovulated. Anti-Mόllerian hormone, visceral fat area assessed with computed tomography, and ovarian stromal pulsatility index were significantly different between responders and nonresponders. The cutoff levels for visceral fat area, anti-Mόllerian hormone, and ovarian stromal pulsatility index for predicting clomiphene citrate resistance were 83.6 cm 2 or more (area under the curve 0.79), 3.2 ng/ml or more (area under the curve 0.79), and 0.92 or less (area under the curve 0.66), respectively. Area under the curve for a multivariate prediction model was 0.87.
Conclusion
Clomiphene citrate-resistant polycystic ovary syndrome patients can be predicted on the basis of initial characteristics such as visceral fat area, anti-Mόllerian hormone levels, and ovarian stromal pulsatility index. This can help in patient selection and counseling regarding the success of ovulation induction.

Keywords: Anti-Müllerian hormone, clomiphene citrate, ovarian stromal pulsatility index, polycystic ovary syndrome, visceral fat area


How to cite this article:
Elsayed MA, Sanad ZF, Emara MA, Hamza HA. Anti-Müllerian hormone, visceral fat, and ovarian stromal Doppler to predict response to ovulation induction in polycystic ovary syndrome. Menoufia Med J 2014;27:657-64

How to cite this URL:
Elsayed MA, Sanad ZF, Emara MA, Hamza HA. Anti-Müllerian hormone, visceral fat, and ovarian stromal Doppler to predict response to ovulation induction in polycystic ovary syndrome. Menoufia Med J [serial online] 2014 [cited 2020 Apr 2];27:657-64. Available from: http://www.mmj.eg.net/text.asp?2014/27/4/657/149643


  Introduction Top


Polycystic ovary syndrome (PCOS) is an endocrine and metabolic disorder with a genetic origin [1],[2] and is influenced by developmental and environmental factors [3]. Biochemical hyperandrogenemia (HA) and clinical manifestations of HA are principal features of PCOS [4]. PCOS accounts for 90-95% of women attending infertility clinics with anovulation [5]. Among those with PCOS and infertility, 90% are overweight [6]. PCOS women are more likely to have upper body fat distribution compared with weight-matched controls. Greater abdominal or visceral adiposity is associated with greater insulin resistance (IR), which could exacerbate the reproductive and metabolic abnormalities in PCOS [7].

Clomiphene citrate (CC) has been the gold standard treatment for induction of ovulation in women with PCOS for many decades because of its simplicity of use, low cost, relative safety, and efficacy [8]. Although 60-85% of patients will ovulate on CC therapy, only about one-half will conceive [9]. If ovulation cannot be achieved with CC administration at doses of 150 mg/day, then the patient is said to be clomiphene citrate resistant (CCR) [10]. If such patients are identified early, they can be administered alternative treatments, resulting in considerable savings in terms of time. Many authors have worked extensively on assessing the possible predictors of treatment outcomes based on initial screening characteristics [11],[12],[13],[14]. The aim of this study was to investigate whether clinical, endocrine, sonographic, and computed tomography (CT) characteristics of anovulatory women with PCOS may predict their ovarian response to CC medication.


  Patients and methods Top


This prospective cross-sectional study was performed at the Obstetrics and Gynecology Department of Menoufia University Hospital between January 2011 and January 2013.The study included 150 infertile women with PCOS diagnosed by the presence of at least two of the following features [15]:

  • Clinical HA: hirsutism or acne vulgaris and/or biochemical HA [total testosterone ≥88 ng/dl or dehydroepiandrosterone sulfate (DHEAS) ≥275 mg/dl] [16].
  • Menstrual and/or ovulatory disturbances, mainly oligomenorrhea (interval between vaginal bleeding >35 days and <6 months) or amenorrhea (bleeding interval >6 months).
  • Polycystic ovaries as visualized by transvaginal ultrasonography (US) (either ≥12 follicles measuring 2-9 mm in diameter or increased ovarian volume >10 cm 3 ).


Exclusion criteria

Patients having one or more of these criteria were excluded: age less than 18 years or greater than 40 years; BMI less than 18.5 kg/m 2 or more than 35 kg/m 2 ; pregnancy; presence of endocrine disorders or systemic disease; current or previous (within the last 3 months) use of oral contraceptives, glucocorticoids, antiandrogens, ovulation induction, or dopaminergic agents; use of antidiabetic or antiobesity drugs; and history of tubal or ovarian surgery.

Clinical evaluation

The aim of the study was explained to the patients and written informed consent was taken. The patients were then subjected to history taking, clinical examination, and anthropometric measurements (body weight, measured with an analog scale and in light clothing; height, measured with the patient barefoot; BMI (weight in kg/height in m 2 ); and waist circumference (WC), obtained as the smallest circumference at the level of the umbilicus).

Laboratory tests

An early-morning blood sample was obtained during the follicular phase (day 3 of the spontaneous cycle or progestin-induced menses in case of amenorrhea) for the measurement of follicle stimulating hormone (FSH), luteinizing hormone (LH), anti-Müllerian hormone (AMH), total testosterone (T), DHEAS, insulin, and glucose.

Blood samples were taken from all women (6 ml) and collected in vaccutainer tubes. All samples were then centrifuged 2 h after withdrawal and were stored at −20°C until assayed. FSH, LH, insulin, total testosterone, and DHEAS were measured using an enzyme immunoassay (DRG Instruments, Marburg, Germany). Fasting blood glucose was measured on an automated autoanalyzer (Roche Diagnostics GmbH, Mannheim, Germany).

IR was calculated using the Homeostasis Model Assessment (HOMA) index as follows:

HOMA-IR = fasting insulinemia (μIU/ml)× fasting glucose (mg/dl)405 [17].

Serum AMH was determined by the quantitative sandwich enzyme-linked immunosorbent assay (ELISA) using a commercial ELISA kit (Immunotech; Beckman-Coulter UK Ltd, Buckinghamshire, UK) according to the manufacturer's protocol.

Ultrasound and Doppler examination

US examination of the uterus and ovaries was performed with a 6.5 MHz transvaginal transducer (Sonata Plus; IBE Technologies, Egypt). Ovarian volume and the number, diameter, and distribution of follicles were recorded. Volume was calculated using the formula V = π/6×DDD3, where D1 is the longitudinal diameter, D2 is the anteroposterior diameter, and D3 is the transverse diameter of the ovary [18]. The average value of both ovaries was used for statistical analysis. Doppler measurements of the uterine and intraovarian vessels were obtained. All patients were in a semirecumbent position and were evaluated between 08.00 and 11.00 a.m. to exclude the effects of circadian rhythmicity on the uterine blood flow [19]. Furthermore, they rested in a waiting room for at least 15 min before being scanned and completely voided the bladder to minimize external effects on the pelvic blood flow [20]. Color signals were sought in the stroma at maximum distance from the ovarian surface [Figure 1]. Color flow images of the ascending branches of the uterine arteries were sampled laterally to the cervix in a longitudinal plane [Figure 2].Pulsatility index (PI), defined as the difference between peak systolic and end diastolic flow divided by the mean maximum flow velocity, was calculated for the ovarian stromal and uterine arteries electronically by the machine. For each examination, the mean value of three consecutive waveforms was obtained. The average value of PIs of the right and left ovarian stromal and uterine arteries was used.
Figure 1: Ovarian stromal flow velocity waveforms in the polycystic ovary on day 3 of the menstrual cycle.

Click here to view
Figure 2: Uterine artery flow velocity waveforms in the polycystic ovary on day 3 of the menstrual cycle.

Click here to view


Visceral fat assessment by computed tomography

CT was performed using SOMATOM Spirit (Siemens, Germany) with all patients in the supine position with their arms above their head and legs elevated with a cushion to reduce the curve in the back. The scans were completed at 120 kV, 50 mA, slice thickness of 10 mm, scanning time of 1 s, field of view of 400 mm, and display matrix of 512´512 pixels [21].

The images that correspond to the level L4-L5 were imported and analyzed by ImageJ software (v1.43) using an IBM personal computer. To identify adipose tissue, the threshold was set for −30 to −190 Hounsfield units, and the visceral area was manually delineated, using tools provided by the software. Finally, pixels within the threshold inside the outlined area were calculated with the software [22] [Figure 3]a and b.
Figure 3: (a) Cross-section of the abdomen on computed tomography at the level of L4-L5 before being processed with the ImageJ program. (b) The same image in (a) after being processed with the ImageJ program. Fat tissue was highlighted by adjusting the threshold of the image to −190 to −30; the visceral area was encircled and the visceral fat area was measured (104.9 cm2).

Click here to view


Treatment schedule and assessment of ovarian response

CC medication was initiated on day 3 after spontaneous or progestagen-induced withdrawal bleeding. The starting dose was 50 mg/day, orally, for five consecutive days. In the case of an absent response, daily doses were increased by 50 mg in the next cycle to a maximum dose of 150 mg/day in the following cycle. The duration of follow-up for all patients included in the study was at least three treatment cycles. Ovulation was assessed by midluteal serum progesterone measurement (progesterone >10 ng/ml indicating ovulation) combined with sonographic monitoring of follicle growth until the appearance of a preovulatory follicle (mean diameter ≥18 mm) and subsequent follicle rupture. Responders were defined as patients who ovulated during CC therapy, independent of the dose administered. Patients with clomiphene-resistant anovulation were defined as those who do not ovulate despite receiving maximum treatment doses of 150 mg/day.

Statistical methods

Distribution of patient characteristics is presented as mean ± SD. We used the Mann-Whitney U-test for exploratory comparison of initial parameters between responders and nonresponders. The univariate and multivariate relationship with response to CC was assessed using logistic regression analysis. We applied binary logistic regression with the enter method with response to CC as a dependent variable and visceral fat area (VFA), AMH, and ovarian stromal PI as covariates [23]. The area under the receiver operating characteristic (ROC) curve (AUC) was used to assess the discriminative ability of the logistic models. SPSS statistical package (version 17; SPSS Inc., Chicago, Illinois, USA) and MedCalc Software (version 12.4; Ostend, Belgium) were used for data analysis.


  Results Top


The study included 150 oligo/anovulatory women with PCOS. The mean age of the studied sample was 23.95 ± 3.26 years (range 19-35 years). All patients were infertile: 113 (75.3%) patients had primary infertility and 37 (24.7%) suffered from secondary infertility. Among the total study group of 150 women, 30 (20%) patients had a normal BMI (18-24.9 kg/m 2 ) and 120 (80%) patients were overweight or obese (BMI 25-34.9 kg/m 2 ). The mean BMI was 27.99 ± 3.4 kg/m 2 . All patients had menstrual irregularities; 28 (18.7%) patients had amenorrhea and 122 (81.3%) had oligomenorrhea. Among the 126 patients with HA (84% of the study group), 66 (52%) patients had both clinical and biochemical HA, 44 (35%) had only clinical HA, and 16 (13%) had only biochemical HA. Eighty (53%) patients had acne vulgaris, 50 (33.3%) had hirsutism, and six (4%) had acanthosis nigricans.

The number of patients who did or did not ovulate after CC medication in increasing doses of 50, 100, and 150 mg daily are shown in [Figure 4].
Figure 4: Distribution of patients who did or did not ovulate after clomiphene citrate induction of ovulation in incremental daily doses of 50, 100, or 150 mg over 5 consecutive days.

Click here to view


Forty (26.67%) patients remaining anovulatory were considered as nonresponders.

There were significant differences between CC responders and nonresponders as regards cycle history (presence of amenorrhea), BMI, WC, serum total testosterone, AMH, fasting insulin, HOMA-IR, mean ovarian volume, OSPI, and VFA. There were no significant differences as regards age, type of infertility, serum FSH, LH, fasting glucose, and DHEAS levels, and uterine artery PI [Table 1].
Table 1: Clinical, endocrine, ultrasonography, and computed tomography characteristics of the overall study group and of patients who did or did not ovulate after clomiphene citrate medication

Click here to view


[Table 2] shows the correlation between clinical, endocrine, US, and CT characteristics of the study group.
Table 2 Correlation between the clinical, endocrine, ultrasonography, and computed tomography characteristics

Click here to view


Statistical significance in univariate analysis with logistic regression analyses and AUC of the initial parameters are shown in [Table 3].
Table 3: Univariate and multivariate logistic regression analyses and area under the receiver operating characteristic curve of clinical, endocrine, sonographic, and computed tomography characteristics in 150 patients with polycystic ovary syndrome for the prediction of patients' response to clomiphene citrate induction of ovulation

Click here to view


The AUCs for total testosterone and BMI were the highest (0.892 and 0.866, respectively).

The cutoff levels for predicting CC resistance for VFA, AMH, and OSPI were 83.6 cm 2 or more (AUC 0.79), 3.2 ng/ml or more (AUC 0.79), and 0.92 or less (AUC 0.66), respectively.

When VFA, AMH, and ovarian stromal Doppler were included in a multivariate logistic regression (using the enter method), the AUC of the resulting prediction model was 0.87. [Figure 5] shows the ROC curve of the prediction model, together with the ROC curve of the three variables that were included in the model.
Figure 5: Receiver operating characteristic curve of anti-Müllerian hormone (AMH), visceral fat area, and ovarian stromal pulsatility index (PI) and the prediction model (involving these three parameters combined) for predicting response to clomiphene citrate ovulation induction in 150 polycystic ovary syndrome patients.

Click here to view



  Discussion Top


PCOS is an endocrine and metabolic disorder with a genetic origin [1],[2] and is influenced by developmental and environmental factors [3]. Biochemical HA and/or clinical manifestations of HA are principal features of PCOS [4]. PCOS accounts for 90-95% of women attending infertility clinics with anovulation [5].

CC has been the gold standard treatment for induction of ovulation in women with PCOS for many decades owing to its simplicity of use, low cost, relative safety, and efficacy [8]. Although 60-85% of patients will ovulate on CC, only about one-half will conceive [9]. If patients remaining anovulatory despite CC therapy could be identified beforehand, ineffective and time-consuming CC treatment can be prevented.

Among those with PCOS and infertility, 90% are overweight [6]. PCOS women are more likely to have upper body fat distribution compared with weight-matched controls. Greater abdominal or visceral adiposity is associated with greater IR, which could exacerbate the reproductive and metabolic abnormalities in PCOS [7]. Previous studies using dual-energy X-ray absorptiometry and single-slice abdominal CT scan to quantify the changes in abdominal fat in women with PCOS undergoing a weight loss program indicated that loss of abdominal fat is associated with resumption of ovulation [24-26]. Douchi et al. [27]studied the effect of body fat distribution (as assessed by dual-energy X-ray absorptiometry scan) as a predictor of the response to CC in patients with PCOS. They found that trunk-leg fat ratio in CC responders (0.9 ± 0.4) was significantly lower than that in CC nonresponders (1.3 ± 0.4) (P < 0.001).

AMH has been shown to be two-fold to three-fold higher in serum from women with PCOS than in women with normal ovaries [28]. AMH has been evaluated as a predictor of response to CC ovulation induction [14] and of success of assisted reproductive techniques [29] in patients with PCOS.

Ovarian stromal PI has been studied in patients with PCOS and has been found to be lower than in controls [30]. The low PI values indicate that ovarian stromal vessels are probably dilated and engorged and more abundant in the ovaries of women with PCOS [31].

In the current study the distribution of PCOS phenotypes was as follows: 75 (50%) patients had classic phenotype [oligo/anovulation (OA)+HA+polycystic ovary (PCO) appearance on US]; 51 (34%) had OA + HA; and 24 (16%) had OA+PCO appearance on US. Yilmaz et al. [32] showed a similar distribution of PCOS phenotypes: the classic phenotype was the most common (44%), followed by OA+HA (23%) and then OA+PCO (18%); the least common phenotype was ovulatory PCOS (HA+PCO) (14%).

In our study the ovulation rate after CC induction was 73.33%. This is consistent with the results found in the literature. Homburg [33] reviewed the published results regarding ovulation and pregnancy rates after CC induction (data from 5268 patients); the ovulation rate was 73%.

In the current study we demonstrated that there were significant differences between responders and nonresponders as regards cycle history (amenorrhea or oligomenorrhea), BMI, WC, total testosterone, fasting insulin, AMH, HOMA-IR, mean ovarian volume, OSPI, and VFA. Patients who did not respond tend to have amenorrhea rather than oligomenorrhea, higher BMI, more abdominal fat (WC and VFA), more IR, HA, higher AMH level, larger ovarian volume, and lower ovarian stromal PI.

In contrast, there were no significant differences between responders and nonresponders as regards age, type of infertility, FSH, LH, DHEAS, and fasting glucose levels, and uterine artery PI.

Our results agree with those of Imani et al. [11] in their study assessing predictors of CC resistance. They found a significant difference between the responder and nonresponder groups as regards cycle history, BMI, total testosterone, and mean ovarian volume and no difference as regards age, FSH, LH, and DHEAS. Mahran et al. [34] recently found that the AMH level is higher in CCR patients than in CC responders.

Imani et al. [11] published the first analysis predicting patients remaining anovulatory after CC medication. In their univariate analysis they found that free androgen index (FAI) (testosterone×100/SHBG), BMI, mean ovarian volume, presence or absence of HA, and cycle history (oligomenorrhea or amenorrhea) were significant predictors, with FAI having the highest AUC (0.76), whereas mean follicle number, bleeding interval in case of oligomenorrhea, and LH were nonsignificant predictors, with LH having the lowest AUC (0.52).

Imani et al. [11] then performed a multivariate analysis using backward stepwise elimination. The resulting model contained four variables: FAI (testosterone×100/SHBG), BMI, mean ovarian volume, and presence or absence of HA; the AUC of the prediction model was 0.82. The observations of Imani et al. [11] suggest that obese hyperandrogenic patients are more likely to be CCR.

In our study we performed univariate regression analysis to predict the response to CC induction of ovulation. We found 10 parameters to be significant predictors; testosterone had the highest AUC (0.892), followed by BMI (0.866), insulin (0.841), HOMA-IR (0.840), VFA (0.828), AMH (0.758), WC (0.745), cycle history (oligomenorrhea or amenorrhea) (0.697), ovarian stromal PI (0.660), and ovarian volume (0.640) in that order. We found that LH, DHEAS, and uterine artery PI are not significant predictors, with LH having the lowest AUC (0.539).

Mahran et al. [34] evaluated the role of AMH as a predictor of ovulation induction with CC therapy in patients with PCOS. They found AMH to be a useful predictor of no ovulation (AUC 0.809, P < 0.001) with a cutoff level of 3.4 ng/ml. Ovulation and pregnancy rates were significantly higher (97%, P < 0.001, and 46%, P = 0.034) in patients with low AMH (<3.4 ng/ml) than in women with AMH 3.4 ng/ml or more (48 and 19%). We showed similar results: we showed a cutoff value of 3.2 ng/ml or more with an AUC of 0.79 to predict CC resistance in those patients.

El-Halawaty et al. [14] evaluated the role of AMH as a predictor of ovulation induction on CC therapy in obese patients with PCOS. They found AMH to be a useful predictor with a cutoff value of 1.2 ng/ml or more to predict ovulation, with AUC 0.71, sensitivity 71%, and specificity 65.7%. However, they did not determine an upper cutoff to predict CC resistance.

In our study, the cutoff value for ovarian stromal PI was 0.92 or less, with sensitivity 57.3% and specificity 72.5%, and the cutoff value for VFA was 83.6 cm 2 or more, with sensitivity 78.2% and specificity 72.5% to predict CC resistance in women with PCOS. To our knowledge, there are no similar studies that have used these two parameters as predictors of response to ovulation induction on CC therapy in PCOS patients.

When VFA, AMH, and OSPI were included in a multivariate logistic regression analysis, the AUC of the resulting prediction model was 0.87.

From a practical point of view, this multivariate logistic model can be interpreted in an equation [35] that can be used for the prediction of response to CC ovulation induction in patients with PCOS as follows:



Thus, if the patient has an AMH of 3 ng/ml, ovarian stromal PI of 0.4, and VFA of 130 cm 2 , P will be 0.90, and thus this patient has a 90% risk of being CCR.


  Conclusion Top


PCOS patients who are less likely to respond to CC can be predicted on the basis of their initial characteristics, such as AMH, ovarian stromal PI, and VFA. This can help in patient selection for treatment and may help with counseling PCOS patients concerning the expected success of ovulation induction.


  Acknowledgements Top


Conflicts of interest

There are no conflicts of interest.

 
  References Top

1.
Ewens KG, Stewart DR, Ankener W, Urbanek M, McAllister JM, Chen C, et al. Family-based analysis of candidate genes for polycystic ovary syndrome. J Clin Endocrinol Metab 2010; 95 :2306-2315.  Back to cited text no. 1
    
2.
Kosova G, Urbanek M. Genetics of the polycystic ovary syndrome. Mol Cell Endocrinol 2013; 373 :29-38.  Back to cited text no. 2
    
3.
Franks S, Berga SL. Does PCOS have developmental origins? Fertil Steril 2012; 97 :2-6.  Back to cited text no. 3
[PUBMED]    
4.
Hoffman B, Schorge J, Schaffer J, Halvorson L, Bradshaw K, Cunningham F. Polycystic ovarian disease and hyperandrogenism. In: editor. Williams gynecology. 2nd ed. New York: McGraw-Hill Education 2012; 461.  Back to cited text no. 4
    
5.
Brassard M, AinMelkY, Baillargeon JP. Basic infertility including polycystic ovary syndrome. Med Clin North Am 2008; 92 :1163-1192, xi  Back to cited text no. 5
    
6.
Lim SS, Norman RJ, Davies MJ, Moran LJ. The effect of obesity on polycystic ovary syndrome: a systematic review and meta-analysis. Obes Rev 2013; 14 :95-109.  Back to cited text no. 6
    
7.
Lord J, Thomas R, Fox B, Acharya U, Wilkin T. The effect of metformin on fat distribution and the metabolic syndrome in women with polycystic ovary syndrome - a randomised, double-blind, placebo-controlled trial. BJOG 2006; 113 :817-824.  Back to cited text no. 7
    
8.
Radosh L. Drug treatments for polycystic ovary syndrome. Am Fam Physician 2009; 79 :671-676.  Back to cited text no. 8
    
9.
Neveu N, Granger L, St-Michel P, Lavoie HB. Comparison of clomiphene citrate, metformin, or the combination of both for first-line ovulation induction and achievement of pregnancy in 154 women with polycystic ovary syndrome. Fertil Steril 2007; 87 :113-120.  Back to cited text no. 9
    
10.
Costello MF, Ledger WL. Evidence-based lifestyle and pharmacological management of infertility in women with polycystic ovary syndrome. Womens Health (Lond Engl) 2012; 8 :277-290.  Back to cited text no. 10
    
11.
Imani B, Eijkemans MJ, te Velde ER, Habbema JD, Fauser BC. Predictors of patients remaining anovulatory during clomiphene citrate induction of ovulation in normogonadotropic oligoamenorrheic infertility. J Clin Endocrinol Metab 1998; 83 :2361-2365.  Back to cited text no. 11
    
12.
Imani B, Eijkemans MJ, de JongFH, Payne NN, Bouchard P, Giudice LC, Fauser BC Free androgen index and leptin are the most prominent endocrine predictors of ovarian response during clomiphene citrate induction of ovulation in normogonadotropic oligoamenorrheic infertility. J Clin Endocrinol Metab 2000; 85 :676-682.  Back to cited text no. 12
    
13.
Rausch ME, Legro RS, Barnhart HX, Schlaff WD, Carr BR, Diamond MP, et al. Reproductive Medicine Network Predictors of pregnancy in women with polycystic ovary syndrome. J Clin Endocrinol Metab 2009; 94 :3458-3466.  Back to cited text no. 13
    
14.
El-Halawaty S, Rizk A, Kamal M, Aboulhassan M, Al-Sawah H, Noah O, Al-Inany H Clinical significance of serum concentration of anti-Müllerian hormone in obese women with polycystic ovary syndrome. Reprod Biomed Online 2007; 15 :495-499.  Back to cited text no. 14
    
15.
The Rotterdam ESHRE/ASRM Sponsored PCOS Consensus Workshop Group. Revised 2003 consensus on diagnostic criteria and long-term health risks related to polycystic ovary syndrome (PCOS). Hum Reprod 2004; 19 :41-47.  Back to cited text no. 15
    
16.
Huang A, Brennan K, Azziz R. Prevalence of hyperandrogenemia in the polycystic ovary syndrome diagnosed by the National Institutes of Health 1990 criteria. Fertil Steril 2010; 93 :1938-1941.  Back to cited text no. 16
    
17.
Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 1985; 28 :412-419.  Back to cited text no. 17
[PUBMED]    
18.
Lass A, Brinsden P. The role of ovarian volume in reproductive medicine. Hum Reprod Update 1999; 5:256-266.  Back to cited text no. 18
    
19.
Zaidi J, Jurkovic D, Campbell S, Okokon E, Tan SL. Circadian variation in uterine artery blood flow indices during the follicular phase of the menstrual cycle. Ultrasound Obstet Gynecol 1995; 5 :406-410.  Back to cited text no. 19
    
20.
Battaglia C, Artini PG, D′Ambrogio G, Galli PA, Genazzani AR. Uterine and ovarian blood flow measurement. Does the full bladder modify the flow resistance? Acta Obstet Gynecol Scand 1994; 73 :716-718.  Back to cited text no. 20
    
21.
Yoshizumi T, Nakamura T, Yamane M, Islam AH, Menju M, Yamasaki K, et al. Abdominal fat: standardized technique for measurement at CT. Radiology 1999; 211:283-286.  Back to cited text no. 21
    
22.
Schneider CA, Rasband WS, Eliceiri KW. NIH Image to ImageJ: 25 years of image analysis. Nat Methods 2012; 9 :671-675.  Back to cited text no. 22
    
23.
Bowers D. Curvy models: logistic regression. In: Bowers D, editor. Medical statistics from scratch, an introduction for health professionals. 2nd ed. Chichester, UK: John Wiley & Sons Ltd; 2008. 213-223.  Back to cited text no. 23
    
24.
Kuchenbecker WK, Groen H, van AsseltSJ, Bolster JH, Zwerver J, Slart RH, et al. In women with polycystic ovary syndrome and obesity, loss of intra-abdominal fat is associated with resumption of ovulation. Hum Reprod 2011; 26 :2505-2512.  Back to cited text no. 24
    
25.
Huber-Buchholz MM, Carey DG, Norman RJ. Restoration of reproductive potential by lifestyle modification in obese polycystic ovary syndrome: role of insulin sensitivity and luteinizing hormone. J Clin Endocrinol Metab 1999; 84 :1470-1474.  Back to cited text no. 25
    
26.
Thomson RL, Buckley JD, Noakes M, Clifton PM, Norman RJ, Brinkworth GD. The effect of a hypocaloric diet with and without exercise training on body composition, cardiometabolic risk profile, and reproductive function in overweight and obese women with polycystic ovary syndrome. J Clin Endocrinol Metab 2008; 93 :3373-3380.  Back to cited text no. 26
    
27.
Douchi T, Oki T, Yamasaki H, Nakae M, Imabayashi A, Nagata Y. Body fat patterning in polycystic ovary syndrome women as a predictor of the response to clomiphene. Acta Obstet Gynecol Scand 2004; 83 :838-841.  Back to cited text no. 27
    
28.
Fallat ME, Siow Y, Marra M, Cook C, Carrillo A. Müllerian-inhibiting substance in follicular fluid and serum: a comparison of patients with tubal factor infertility, polycystic ovary syndrome, and endometriosis. Fertil Steril 1997; 67 :962-965.  Back to cited text no. 28
    
29.
Kaya C, Pabuccu R, Satiroglu H. Serum antimullerian hormone concentrations on day 3 of the in vitro fertilization stimulation cycle are predictive of the fertilization, implantation, and pregnancy in polycystic ovary syndrome patients undergoing assisted reproduction. Fertil Steril 2010; 94 :2202-2207.  Back to cited text no. 29
    
30.
Adali E, Kolusari A, Adali F, Yildizhan R, Kurdoglu M, Sahin HG. Doppler analysis of uterineperfusion and ovarian stromal blood flow in polycystic ovary syndrome. Int J Gynaecol Obstet 2009; 105 :154-157.  Back to cited text no. 30
    
31.
Loverro G, Vicino M, Lorusso F, Vimercati A, Greco P, Selvaggi L. Polycystic ovary syndrome: relationship between insulin sensitivity, sex hormone levels and ovarian stromal blood flow. Gynecol Endocrinol 2001; 15 :142-149.  Back to cited text no. 31
    
32.
Yilmaz M, Isaoglu U, Delibas IB, Kadanali S. Anthropometric, clinical and laboratory comparison of four phenotypes of polycystic ovary syndrome based on Rotterdam criteria. J Obstet Gynaecol Res 2011; 37 :1020-1026.  Back to cited text no. 32
    
33.
Homburg R. Clomiphene citrate - end of an era? A mini-review. Hum Reprod 2005; 20 :2043-2051.  Back to cited text no. 33
    
34.
Mahran A, Abdelmeged A, El-Adawy AR, Eissa MK, Shaw RW, Amer SA. The predictive value of circulating anti-Müllerian hormone in women with polycystic ovarian syndrome receiving clomiphene citrate: a prospective observational study. J Clin Endocrinol Metab 2013; 98 :4170-4175.  Back to cited text no. 34
    
35.
Sullivan LM, Massaro JM, D′AgostinoRBSr. Presentation of multivariate data for clinical use: the Framingham Study risk score functions. Stat Med 2004; 23 :1631-1660.  Back to cited text no. 35
    


    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5]
 
 
    Tables

  [Table 1], [Table 2], [Table 3]



 

Top
 
 
  Search
 
Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
Access Statistics
Email Alert *
Add to My List *
* Registration required (free)

 
  In this article
Abstract
Introduction
Patients and methods
Results
Discussion
Conclusion
Acknowledgements
References
Article Figures
Article Tables

 Article Access Statistics
    Viewed1317    
    Printed14    
    Emailed0    
    PDF Downloaded114    
    Comments [Add]    

Recommend this journal


[TAG2]
[TAG3]
[TAG4]