Predictive value of ovarian reserve markers in smoking and non-smoking women undergoing IVF

Reproductive BioMedicine Online (2010) 20, 857– 860

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ARTICLE

Predictive value of ovarian reserve markers in smoking and non-smoking women undergoing IVF Thomas Freour Paul Barriere a a b

a,*

, Lionel Dessolle a, Miguel Jean a, Damien Masson b,

´decine de la Reproduction, HME, CHU Nantes, 38 Boulevard Jean Monnet, 44093 Nantes, France; Biologie et Me Laboratoire de Biochimie Specialisee et Hormonologie, Quai Moncousu, CHU Nantes, 44000 Nantes, France

* Corresponding author. E-mail address: [email protected] (T Freour). Thomas Freour is a biologist, specializing in reproductive biology and endocrinology. He is currently working at the Department of Reproductive Medicine at the Centre Hospitalier Universitaire of Nantes, France. His main scientific interests are spermatogenesis, proteomic analysis, and identification of ovarian reserve markers and their usefulness in different subgroups of patients, especially in smokers.

Abstract Ovarian reserve markers are now widely used in IVF centres in order to predict ovarian response and adapt ovarian stim-

ulation protocols. In this study, the respective performance of day-3 FSH, oestradiol and anti-Mu ¨llerian hormone concentrations and antral follicle count for the prediction of poor ovarian response to ovarian stimulation and pregnancy in IVF cycles were compared in women according to their smoking status. The analysis of 384 IVF cycles showed that anti-Mu ¨llerian hormone concentration and antral follicle count were the best predictors of poor ovarian response and performed better in non-smokers than in smokers, for which no parameter could predict pregnancy. RBMOnline ª 2010, Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved. KEYWORDS: anti-Mu ¨llerian hormone, antral follicle count, ovarian response, smoking

Introduction Ovarian reserve tests, such as FSH, oestradiol and, more recently anti-Mu ¨llerian hormone (AMH) concentrations and antral follicle count (AFC), have demonstrated their efficiency in predicting ovarian response in IVF cycles (Broer et al., 2009; Jayaprakasan et al., 2008), but their usefulness in predicting pregnancy remains controversial (Verhagen et al., 2008). Moreover, their respective predictive performance has to be clarified. Smoking has various deleterious effects on reproductive function and has been particularly

thought to alter folliculogenesis and ovarian reserve (Freour et al., 2008), resulting in poor IVF outcome (Waylen et al., 2009). This study compared hormonal reserve markers and AFC in predicting ovarian response and pregnancy in smoking and non-smoking women undergoing IVF.

Materials and methods A total of 384 consecutive women undergoing ovarian stimulation for IVF who had complete ovarian reserve tests

1472-6483/$ - see front matter ª 2010, Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.rbmo.2010.03.006

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screening and whose smoking status was known were included anonymously in this study between January 2007 and January 2009. Ovarian stimulation was performed with recombinant FSH in a standard fashion, after pituitary desensitization with gonadotrophin-releasing hormone (GnRH) agonist or associated with GnRH antagonist. Measurement of FSH and oestradiol concentrations and AFC were performed on day 2 or 3 of one of the three spontaneous cycles preceding the IVF cycle. AMH concentration was measured on any day of one of the three spontaneous cycles preceding the IVF cycle. FSH assays were performed using the Elecsys automated ECL (electrochemiluminescence) system (Roche, Switzerland). Analytical sensitivity for FSH was <0.1 mUI/ml, with a coefficient of variation (CV) <2%. Oestradiol assays were performed with a radioimmunoassay (CisBio, France). Analytical sensitivity was 1.4 pg/ml and intra and inter-assay CV <20%. Beckman Coulter Immunotech ELISA kit (Marseille, France) was used for AMH (sensitivity 0.14 ng/ml, intra-assay CV <12% and inter-assay CV <14%). AFC was performed by the same skilled operator by ultrasound (Titan; Sonosite) and follicle diameters, defined as the arithmetic mean of two or three dimensions of each follicle, were recorded. Total AFC grouped all follicles between 2 and 10 mm. Smoking status was recorded during consultation. Women reporting passive smoking were excluded. Statistical analysis was performed using XLStat version 2009.3 (Addinsoft, USA). Means were compared with the Student’s t or Mann–Whitney U-tests and a P-value <0.05 was considered statistically significant. Age, body mass index (BMI), IVF cycle rank, total dose of FSH injected during ovarian stimulation, intracytoplasmic sperm injection (ICSI) rate, fertilization rate, pregnancy rate and ovarian reserve markers (AMH, FSH and oestradiol concentrations and AFC) were used as continuous variables and are presented as means ± SD. Univariate analysis was first performed in order to compare these variables according to the occurrence of poor ovarian response or pregnancy. Poor ovarian response was defined by cycle cancellation for insufficient follicular development (fewer than three follicles recruited) or less than four oocytes retrieved. Clinical pregnancy was defined by fetal heart activity 5 weeks after embryo transfer. Multi-

Table 1

variate logistic regression analysis was then performed in order to develop a model for predicting poor ovarian response and pregnancy. Receiver operator characteristic (ROC) curves were then constructed.

Results Mean age of female patients was 32.5 years. Long GnRH agonist protocol was used in 45% of the cases and GnRH antagonist protocol in 55% of the cycles. Ovum retrieval was performed in 369 cycles and 25 cycles were cancelled due to poor ovarian follicular recruitment and development. A total of 40 women had poor ovarian response to ovarian stimulation, whereas 344 women had four or more oocytes retrieved. Poor and normal ovarian response groups were compared in univariate analysis. Women with poor ovarian response were older (34.85 ± 3.48 years versus 32.38 ± 4.06, P < 0.001), had lower AMH, lower AFC and lower clinical pregnancy rate than women with normal ovarian response (Table 1). BMI, day-3 oestradiol concentration, ICSI and antagonist protocol proportion, total dose of gonadotrophins used and fertilization rate were comparable in both groups. Multivariate analysis showed that only age (P = 0.001) and AMH concentration (P = 0.03) significantly contributed to the prediction model of poor response. Combination of both did not improve the model. ROC curve analysis showed that AMH concentration and AFC had the best area under the curve (AUC; 0.692 and 0.665, respectively, P < 0.05 for both). Clinical pregnancy was obtained in 88 women after embryo transfer, leading to a clinical pregnancy rate of 22.9% per initiated cycle and 25.6% per ovum retrieval. Pregnant women had higher AMH concentration, AFC, lower smoking prevalence (Table 1), more oocytes retrieved (12.06 ± 5.43 versus 10.29 ± 5.08, P = 0.006), higher fertilization rate (68.19 ± 23.12 versus 55.16 ± 29.65, P = 0.0002) and better embryo quality (i.e. proportion of top-quality embryos on day 3, 65.6 ± 27% versus 44.73 ± 35.15%, P < 0.0001) than women who did not achieve pregnancy. Age, BMI, FSH and oestradiol concentration, ICSI rate and antagonist protocol proportion, total dose of gonadotrophins used, fertilization

Ovarian reserve tests and IVF outcome according to ovarian response, pregnancy or smoking category.

Parameter

No. of patients AMH (ng/ml) AFC Poor response Clinical pregnancy rate Proportion of smokers

Ovarian response

Pregnancy

Smoking status

Poor

Normal

Pregnant

Non-pregnant

Nonsmokers

Smokers

40 2.65 ± 1.49 13.02 ± 6.81 – 7.3

344 4.11 ± 2.68a 17.34 ± 9.23a – 25a

88 4.51 ± 2.63 18.63 ± 10.11 3.4 –

296 3.77 ± 2.59a 16.36 ± 18.62a 12.5a –

274 3.99 ± 1.81 17.17 ± 9.28 11 26.1

110 3.61 ± 1.75 16.18 ± 8.6 9 15.4a

25

29

19.3

31.5a

–

–

Values are mean ± SD or percentage, unless otherwise stated. AFC = antral follicle count; AMH = anti-Mu ¨llerian hormone. a P < 0.05.

Ovarian reserve markers in smokers and non-smokers

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Figure 1 Receiver operating characteristic (ROC) curves for anti-Mu ¨llerian hormone (AMH) and antral follicle count (AFC) for prediction of poor ovarian response in (A) non-smokers and (B) smokers. Area under the curve (AUC) was 0.692 for AMH and 0.665 for AFC in non-smokers and 0.538 for AMH and 0.612 for AFC in smokers.

rate, number of embryos transferred and proportion of blastocysts were comparable in both groups. Multivariate analysis showed that no parameter, alone or in combination, significantly predicted pregnancy. ROC curve analysis confirmed that no parameter significantly predicted pregnancy. The effect of smoking was then studied. Among the 384 women included, 274 were non-smokers and 110 reported current smoking. Univariate analysis showed that age, BMI, FSH, LH, and oestradiol concentration, AFC, fertilization rate, ICSI rate and antagonist protocol proportion, number of embryos transferred and proportion of blastocysts were comparable between smokers and non-smokers (data not shown), whereas ovarian response (9.67 ± 4.28 versus 11.15 ± 5.54 oocytes retrieved, P = 0.01) and pregnancy rate (15.4 versus 26.1%, P = 0.03) (Table 1) were lower in smokers than in non-smokers. There was a trend towards lower AMH in smokers compared with non-smokers, although not statistically significant (Table 1). Concerning the prediction of poor ovarian response, ROC curves showed that the AUC remained high for AMH concentration and AFC in non-smokers (0.751 versus 0.682, respectively, P < 0.05 for both), whereas they both lost their predictive power in smokers (0.538 and 0.618, P = NS) (Figure 1). The AUC obtained in smokers and in non-smokers were compared. AMH concentration and AFC AUC for the prediction of poor ovarian response in non-smokers were higher than in smokers, but the difference did not reach statistical significance.

Discussion This study showed that AFC, AMH concentration and age are superior to basal FSH or oestradiol concentration in predicting poor ovarian response to stimulation, but that no parameter significantly predicted pregnancy. It also showed that AMH concentration and AFC are better predictors of ovarian

response in non-smokers than in smokers. These results are in keeping with numerous recent studies reporting the interest of AMH concentration and/or AFC in predicting poor ovarian response (Broer et al., 2009; Jayaprakasan et al., 2008). The study included AFC and hormonal markers, as there is growing evidence that AMH concentration and AFC are relevant and complementary ovarian reserve markers (Broer et al., 2009). Poor ovarian response was defined as insufficient follicular development (fewer than three follicles recruited) or less than four oocytes retrieved. This cut-off is could seem arbitrary but it is based on the study centre’s clinical experience. As shown in a recent metaanalysis (Verhagen et al., 2008), each article published on this topic reports a different definition of poor ovarian response. Whether AMH concentration and/or AFC can predict pregnancy in IVF cycles still remains controversial. While some authors have reported that AMH concentration could predict pregnancy (Barad et al., 2009; Elgindy et al., 2008; Lekamge et al., 2007), some others have not found any correlation (Jayaprakasan et al., 2008). This study did not find any predictive capability for these two parameters. The deleterious effects of tobacco on ovarian physiology have been evocated suggested for a long time, especially because smoking women experience menopause earlier than non-smokers (Di Prospero et al., 2004; Jick and Porter, 1977). Some recent studies yielded some confluent results concerning decreased ovarian reserve and poorer IVF outcome in smokers (Freour et al., 2008; Waylen et al., 2009). As far as is known, the current study is the first to show that AMH concentration and AFC have far lower predicting predictive power for ovarian response in smokers than in non-smokers. This highlights that smoking status should be taken into account when ovarian reserve tests are considered. As these tests can lead to treatment regimen choice and dose adaptation in women undergoing IVF,

860 physicians might have finely shaded interpretation of these tests according to smoking status and patients could thus benefit from such a cautious strategy. This study also confirms that ovarian response and pregnancy rates are significantly lower in smokers than in nonsmokers. This raises the question of a tobacco-induced impairment of folliculogenesis and ovarian reserve alteration in smoking women undergoing IVF. This also shows (if still needed) the importance of medical information on the deleterious effects of tobacco on fertility. Women should be strongly encouraged to preserve their residual reproductive capital through smoking cessation. Further studies, especially on animal models, should help in deciphering the mechanisms of tobacco-induced ovarian reserve alteration. A recent study conducted in mice showed that exposure to polycyclic aromatic hydrocarbons resulted in accelerated loss of primordial follicles, leading to premature exhaustion of the ovarian pool (Jurisicova et al., 2007). Moreover, this alteration of ovarian reserve was not only present in females exposed to polycyclic aromatic hydrocarbons, but also in the female offspring, raising questions on a potential transgenerational effect of maternal smoking. This study did not ask patients about the smoking status of the mother before or during pregnancy and/or lactation, but this might be considered in further studies. One strength of the present study is the relatively large population, which confers a better statistical power than previous reports (Barad et al., 2009). The study agrees with Barad et al. (2009) that univariate and multivariate analysis, combined with ROC curves leads to relevant statistical analysis and to the identification of clinically useful cut-offs. Even if differences can appear in univariate analysis, only multivariate analysis can evaluate the contribution of each parameter to the prediction model. Despite significantly lower AFC in the poor responders group, AFC was not contributive in the multivariate analysis. No cut-offs were retained in the ROC curve analysis. Indeed, as previously reported (Barad et al., 2009), the choice of a cut-off can vary according to the aim of the investigator, i.e. focus on sensitivity or specificity of the test. Moreover, there is a lack of standardization of both AMH concentration and AFC. AMH serum concentrations can vary according to the assay used (Freour et al., 2007). Concerning AFC, while some authors only measure follicles between 2 and 5 mm in diameter, some others measure follicles between 2 and 10 mm, as recently recommended (Broekmans et al., 2009). In conclusion, the search for a relevant ovarian reserve marker and the way to optimize its clinical use is still going on in several teams. However, AMH measurement has confirmed hopes aroused a few years ago and revealed the best predictor of poor ovarian response to date. The present study adds that smoking status influences its predictive power. Therefore, smoking status should be integrated in future studies in the field of ovarian reserve, in order to improve the relevance of studies conducted on the predictive capability of ovarian reserve tests. This will finally lead to the determination of clinically useful thresholds.

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References Barad, D.H., Weghofer, A., Gleicher, N., 2009. Comparing antiMu ¨llerian hormone (AMH) and follicle-stimulating hormone (FSH) as predictors of ovarian function. Fertil. Steril. 91, 1553–1555. Broekmans, F.J., de Ziegler, D., Howles, C.M., Gougeon, A., Trew, G., Olivennes, F., 2009. The antral follicle count: practical recommendations for better standardization. Fertil. Steril. (Epub ahead of print). Broer, S.L., Mol, B.W., Hendriks, D., Broekmans, F.J., 2009. The role of antimullerian hormone in prediction of outcome after IVF: comparison with the antral follicle count. Fertil. Steril. 91, 705–714. Di Prospero, F., Luzi, S., Iacopini, Z., 2004. Cigarette smoking damages women’s reproductive life. Reprod. Biomed. Online 8, 246–247. Elgindy, E.A., El-Haieg, D.O., El-Sebaey, A., 2008. Anti-Mu ¨llerian hormone: correlation of early follicular, ovulatory and midluteal levels with ovarian response and cycle outcome in intracytoplasmic sperm injection patients. Fertil. Steril. 89, 1670–1676. Freour, T., Mirallie ´, S., Bach-Ngohou, K., Denis, M., Barrie `re, P., Masson, D., 2007. Measurement of serum anti-Mu ¨llerian hormone by Beckman Coulter ELISA and DSL ELISA: comparison and relevance in assisted reproduction technology (ART). Clin. Chim. Acta 375, 162–164. Freour, T., Masson, D., Mirallie, S., et al., 2008. Active smoking compromises IVF outcome and affects ovarian reserve. Reprod. Biomed. Online 16, 96–102. Jayaprakasan, K., Campbell, B., Hopkisson, J., Johnson, I., RaineFenning, N., 2008. A prospective, comparative analysis of antiMu ¨llerian hormone, inhibin-B, and three-dimensional ultrasound determinants of ovarian reserve in the prediction of poor response to controlled ovarian stimulation. Fertil. Steril. (Epub ahead of print). Jick, H., Porter, J., 1977. Relation between smoking and age of natural menopause. Report from the Boston Collaborative Drug Surveillance Program, Boston University Medical Center. Lancet 1, 1354–1355. Jurisicova, A., Taniuchi, A., Li, H., et al., 2007. Maternal exposure to polycyclic aromatic hydrocarbons diminishes murine ovarian reserve via induction of Harakiri. J. Clin. Invest. 117, 3971– 3978. Lekamge, D.N., Barry, M., Kolo, M., Lane, M., Gilchrist, R.B., Tremellen, K.P., 2007. Anti-Mu ¨llerian hormone as a predictor of IVF outcome. Reprod. Biomed. Online 14, 602–610. Verhagen, T.E., Hendriks, D.J., Bancsi, L.F., Mol, B.W., Broekmans, F.J., 2008. The accuracy of multivariate models predicting ovarian reserve and pregnancy after in vitro fertilization: a meta-analysis. Hum. Reprod. Update 14, 95–100. Waylen, A.L., Metwally, M., Jones, G.L., Wilkinson, A.J., Ledger, W.L., 2009. Effects of cigarette smoking upon clinical outcomes of assisted reproduction: a meta-analysis. Hum. Reprod. Update 15, 31–44. Declaration: The authors report no financial or commercial conflicts of interest. Received 30 September 2009; refereed 23 November 2009; accepted 4 February 2010.