A simple multivariate score could predict ovarian reserve, as well as pregnancy rate, in infertile women

A simple multivariate score could predict ovarian reserve, as well as pregnancy rate, in infertile women Johnny S. Younis, M.D.,a,b Jimmy Jadaon, M.D.,a Ido Izhaki, Ph.D.,c Sami Haddad, M.D.,a Orit Radin, M.Sc.,a Shalom Bar-Ami, Ph.D.,a and Moshe Ben-Ami, M.D.a,b a

Reproductive Medicine Unit, Department of Obstetrics and Gynecology, Poriya Medical Center, Tiberias; b Faculty of Medicine, the Technion, Haifa; and c Department of Evolutionary and Environmental Biology, Haifa University, Haifa, Israel

Objective: To find a simple multivariate score that has the potential to predict ovarian reserve, as well as pregnancy rate, in infertile women. Design: A prospective study. Setting: A university-affiliated reproductive medicine unit. Patient(s): One hundred sixty-eight consecutive women undergoing their first IVF-ET treatment at our unit. Intervention(s): Basal ovarian reserve studies, endocrine and sonographic, were performed before starting therapy. After completion of treatment, a logistic regression analysis was performed to examine which parameters significantly determined low ovarian reserve. These parameters were incorporated thereafter in a multivariate score to predict ovarian reserve, as well as clinical pregnancy rate. Main Outcome Measure(s): Low ovarian reserve defined as %3 oocytes on retrieval day and clinical implantation and pregnancy rates. Result(s): Logistic regression analysis revealed that age, antral follicle count, basal FSH, FSH/LH ratio, mean ovarian volume, infertility duration, number of previous cycle cancellations, and body mass index were all, in decreasing significance, independent factors that determine low ovarian reserve. The multivariate score was shown to have a distinctive prediction of ovarian reserve. A cumulative score of >14 was shown to be more accurate in predicting low ovarian reserve than age, day 3 FSH, or antral follicle count separately. Moreover, a score of >14 was shown to have a sensitivity of 88% and a specificity of 69% in predicting low ovarian reserve. More important, women with a score of >14 had significantly lower clinical implantation and pregnancy rates relative to women with a score of %14, corresponding to 6.7% versus 22.4%, and 11.3% versus 38.6%, respectively. Conclusion(s): A novel and simple multivariate score using clinical and basal endocrine and sonographic parameters has a distinctive prediction of low ovarian reserve in infertile women undergoing assisted reproductive technology treatment. Moreover, it has the potential to predict clinical implantation and pregnancy rates in women with low and good ovarian reserve. (Fertil Steril 2010;94:655–61. 2010 by American Society for Reproductive Medicine.) Key Words: Low ovarian reserve, multivariate score, basal endocrine studies, basal sonographic studies, age

The functional life span of the female gonad is defined by the number and rate of depletion of oocytes enclosed within follicles in the ovaries. The size of the oocyte pool set forth at birth, as well as the rate of oocyte loss in the ovaries throughout postnatal life, may have substantial consequences on the reproductive life span and may affect the overall well-being of women as they age (1). The continuous loss of oocytes throughout life appears to be determined by a genetic program of cell death. The involvement of apoptosis and its regulatory molecules seems to play a prominent role in development of the fetal ovaries and in the postnatal ovarian cycle. This concept has been largely investigated during the last few years (2). However, Received February 15, 2009; revised March 1, 2009; accepted March 4, 2009; published online April 14, 2009. J.S.Y. has nothing to disclose. J.J. has nothing to disclose. I.I. has nothing to disclose. S.H. has nothing to disclose. O.R. has nothing to disclose. S.B.-A. has nothing to disclose. M.B.-A. has nothing to disclose. Reprint requests: Johnny S. Younis, M.D., Assisted Reproduction Unit, Department of Obstetrics and Gynecology, Poriya Medical Center, Tiberias, 15208, Israel (FAX: 972-4-6080405; E-mail: jsy@netvision. net.il).

0015-0282/$36.00 doi:10.1016/j.fertnstert.2009.03.036

until now, it did not produce clinical markers of ovarian reserve that could be incorporated into the routine clinical practice in an assisted reproductive technology (ART) setting. Recent publications have suggested that antim€ullerian hormone (AMH) (3), and possibly inhibin-B (4), could be the most ‘‘physiologically’’ available predictors of ovarian reserve in infertile women. Both AMH and inhibin-B are produced by the ovarian pool of follicular granulosa cells. Antim€ullerian hormone is produced by recruited follicles until they become sensitive to FSH (resting pool), whereas inhibin-B is generated by growing follicles responsive to FSH (active pool). Despite the initial enthusiasm concerning their clinical use in the ART setting, it has been shown that when compared with other available tests, they have a limited potential for predicting pregnancy (5–8). Moreover, a large part of ART units have no direct access to perform these tests on a regular routine basis. On the other hand, endocrine and sonographic ovarian reserve tests are readily available in every ART unit. They are not expensive and could be used easily before initiating ART therapy. These tests include basal endocrine serum FSH and

Fertility and Sterility Vol. 94, No. 2, July 2010 Copyright ª2010 American Society for Reproductive Medicine, Published by Elsevier Inc.

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E2, as well as sonographic ovarian volume and antral follicle count. However, basal endocrine levels and sonographic parameters are usually considered to have low specificity and sensitivity when used to predict low ovarian reserve in infertile women (9). Moreover, their ability to predict pregnancy and implantation rates in an ART setting is very limited and therefore inadequate (9, 10). Although these simple tests have been extensively investigated in the past they have seldom been looked into in combination (11). Therefore, our objective was to find a simple multivariate score that uses both basal sonographic and endocrine ovarian reserve parameters conjoined. A further objective was to find a multivariate score that has the potential to predict ovarian reserve, as well as pregnancy rate, in infertile women undergoing ART treatment.

MATERIALS AND METHODS Study Population We prospectively included a large unselected IVF population in our study. A total of 168 consecutive women, aged 19 to 44 years, were referred to our IVF center for treatment. All women were menstruating spontaneously with two intact ovaries and with no evidence of thyroid disease, diabetes mellitus, significant hyperprolactinemia, or hypogonadotropic hypogonadism. All of the women were determined to have normal uterine cavities by hysterosalpingography and/ or hysteroscopy. Conventional IVF and/or intracytoplasmic sperm injection (ICSI) were performed according to the cause of infertility. Informed written consent was obtained from all patients. The study was exempt from Institutional Review Board approval because no additional interventions were used besides the routine and standard IVF preparation and treatment in our unit.

Basal Ovarian Reserve Studies All women in the study underwent a primary assessment of basal ovarian reserve studies before starting treatment. Ovarian reserve assessment, endocrine levels, and sonographic tests were carried out on the same day. We performed the evaluation on days 2 through 4 of a natural cycle 1 month before initiating IVF-ET treatment and following at least a 3-month period without hormonal therapy. Endocrine studies included serum FSH, LH, E2, and P levels. In addition, we evaluated the FSH/LH ratio. One clinician, who was blinded to the clinical and endocrine data, carried out all sonographic studies. Ovarian volume and antral follicle count were performed with use of a two-dimensional endovaginal probe of 5 to 9 MHz frequency (Voluson 730 expert; General Electric Medical System, Zipf, Austria). Ovarian volume was calculated as the volume of an ellipsoid, that is, Length  Width  Depth  p/6. Total and mean basal volume of both ovaries was evaluated in each patient. Antral follicle count 2- to 10-mm diameter in both ovaries was also recorded (12). 656

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Hormonal Assays Sera obtained for basal FSH and LH measurements were analyzed by microparticle enzyme immunoassay (AxSYM; Abbott, Abbott Park, IL). The intra-assay and interassay coefficients of variation were <5% and <11%, respectively, for FSH and <7% and <8%, respectively, for LH. Serum E2 and P levels were assayed by solid-phase, competitive chemiluminescent enzyme immunoassay (Immulite 2000; DPC, Los Angeles, CA). The intra-assay and interassay coefficients of variation were <10% and <16%, respectively, for E2 and <18% and <22%, respectively, for P.

Study Protocol The long protocol, starting on day 21 of the cycle, with GnRH agonist for IVF-ET was similarly used in each patient. Downregulation was achieved after IM administration of GnRH agonist (Decapeptyl CR 3.75 mg; Ferring, Malmo, Sweden) and was assured by serum E2 levels of %30 pg/mL. Superovulation was commenced with four ampules (300 IU) per day for the first 5 days of IM hMG (Menogon; Ferring). The following gonadotropin dosages in each patient were tailored in accordance with transvaginal scanning of follicular development and serum E2 levels. Human chorionic gonadotropin (Pregnyl; NV Organon, Oss, The Netherlands) 10,000 IU was administered when the transvaginal scan showed two or more follicles with diameter of 18 to 20 mm and serum E2 level R400 pg/mL. Transvaginal oocyte retrieval was performed 34 to 36 hours after hCG administration under ultrasound guidance. The treatments of oocytes, sperm, and embryos, as well as the ET technique, were performed as is carried out routinely in our unit (13). Luteal support was administered in all patients with use of transvaginal micronized P treatment (Utrogestan; Besins International Laboratories, Paris, France) 800 mg/day.

Study Conduct The study was performed in a prospective manner in a university-affiliated reproductive medicine unit. Biologists in the IVF laboratory, technicians in the endocrine laboratory, and the ovarian ultrasound operator were all blinded to the clinical data. Only first cycles of treatment performed in our unit in the 168 women enrolled were evaluated. After completion of IVF-ET treatment a linear logistic regression analysis was performed to examine which clinical parameters significantly determined low ovarian reserve. Low ovarian reserve was defined as three or fewer oocytes achieved on the day of retrieval. This strict definition of low ovarian reserve was chosen in view of previous publications (14). The parameters studied included age, body mass index (BMI), infertility duration, number of previous IVF cycles, and number of previous IVF cancellations (due to low ovarian response). In addition, basal endocrine and sonographic ovarian reserve parameters including FSH, E2, FSH/LH ratio, Vol. 94, No. 2, July 2010

total and mean ovarian volume, and antral follicle count also were included. Parameters that were found significant by the linear logistic regression analysis thereafter were incorporated in a new multivariate score to predict low ovarian reserve. Women in the study were then divided into two groups in accordance with the optimal cutoff value found of the new score. The two groups were compared regarding their clinical characteristics, ovarian response, IVF results, and their clinical implantation and pregnancy rates. Statistical Analysis Our data were analyzed with use of the Statistical Package for the Social Sciences for Windows (version 15.0; SPSS, Inc., Chicago, IL). Descriptive procedure was used to evaluate patients’ characteristics, and each variable is presented as mean  SD and range. Univariate linear logistic regressions were used for each independent variable to evaluate significant factors that could predict the number of retrieved oocytes. The regression was performed in a forward pattern. The area under the receiver operating characteristic curve (ROC AUC) then was computed to assess the predictive accuracy of the logistic model. The yielded values were from 0.5 (no predictive power) to 1.0 (perfect prediction). After the new score buildup, a ROC AUC analysis was performed once more to determine the optimal value of the new score to predict low ovarian reserve. Diagnostic sensitivity and specificity were calculated, and the ROC curve was constructed by plotting the sensitivity against the false-positive rate (1  Specificity) of various cutoff values. The value with the optimal combination of sensitivity and specificity was chosen as the optimal cutoff value. Independent sample t-test was used to compare means between groups. Categorical variables were analyzed with use of the c2 test. A P value of < .05 was considered as statistically significant. RESULTS The study included 168 patients undergoing their first IVF treatment cycle in our unit. Of these women, 116 underwent an ICSI procedure, 31 underwent a conventional IVF procedure, and another 20 women underwent a combined IVF and ICSI in the same cycle. One case did not reach oocyte pickup because of low ovarian response. All of the remaining 167 women underwent oocyte pickup. Twenty-eight women did not perform ET during the same cycle. Twelve of them achieved embryos; however, embryos were cryopreserved, 11 of them because of the risk of development of ovarian hyperstimulation syndrome and one of them because of cervical stenosis precluding the performance of the transfer. In one case the couple got divorced and the embryos were discarded. In the other 15 cases, no embryos developed. Two of these were cases of nonobstructive azoospermia in which it was planned to perform testicular fine Fertility and Sterility

needle aspiration, but sperm was not found and the 2 couples refused donor insemination. In 4 cases no oocytes were achieved during retrieval. The other 9 cases were fertilization or cleavage failure. Patients’ characteristics including basal endocrine and sonographic basal ovarian reserve parameters are presented in Table 1 as mean  SD and range. A linear logistic univariate analysis showed that age, infertility duration, previous IVF cancelation cycles, BMI, basal FSH, FSH/LH ratio, antral follicle count, and mean ovarian volume were all independent factors that predicted low ovarian reserve, that is, three or fewer retrieved oocytes. The number of previous IVF cycles, basal LH, E2, and P serum levels were not found to affect ovarian reserve prediction. The ROC AUC of each of the predictive independent variables is presented in Table 2. As noted, three groups of independent variables to predict low ovarian reserve were found with high, moderate, and low prediction ability, respectively. The first group comprised the best independent variables including age, antral follicle count, and basal FSH with a ROC AUC of 0.81, 0.80, and 0.78, respectively. The second group of independent variables with moderate prediction ability was basal FSH/LH ratio, mean ovarian volume, and infertility duration with a ROC AUC of 0.73, 0.67, and 0.64, respectively. The third group of independent factors with low prediction ability was the number of previous IVF cancellations and the patient’s BMI with a ROC AUC of 0.58 and 0.54, respectively. All of these variables then were incorporated into a new scoring system as shown in Table 3. The high predictive factors: age, antral follicle count, and basal FSH received a score of 1 to 5 as described in Table 3. Each of the moderate

TABLE 1 Patients’ characteristics in the study.

No. of women Age (y) BMI (kg/m2) Infertility duration (y) No. of previous cycles No. of previous cancellations Basal FSH (mIU/mL) Basal E2 (pg/mL) Basal P (ng/mL) Basal LH (mIU/mL) Basal FSH/LH ratio Antral follicle count Mean ovarian volume (cm3) Total ovarian volume (cm3)

Mean ± SD

Range

168 30.4  5.4 26.2  6.4 5.2  3.8 1.8  3.4 0.1  0.3

19–44 18–41 1–26 0–15 0–2

6.9  2.4 48  22 0.8  0.6 5.1  2.4 1.7  1.1 8.5  5.5 9.1  4.1

1.8–16.1 8–98 0.1–2.9 0.5–13.3 0.4–8.6 2–32 2.9–30.6

17.8  8.3

4.0–61.3

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significantly younger, had a lower BMI, had shorter duration of infertility, and had fewer IVF cancellations in the past as compared with the >14 score group. Moreover, basal FSH and antral follicle count were significantly better in the %14 score versus the >14 score group. In addition, the low score group performed superiorly during the controlled ovarian hyperstimulation and IVF treatment. Most important, although a similar number of embryos were transferred to the uterus in both groups, the low score group had a significantly better clinical implantation rate compared with the high score group, corresponding to 22.4% and 6.7%, respectively. Also, the clinical pregnancy rate per cycle was significantly superior in the low versus the high score group, corresponding to 38.6% and 11.3%, respectively.

TABLE 2 Prediction factors of low ovarian reserve (N [ 168). Predictor

ROC AUC

BMI No. of previous cancellations Infertility duration Mean ovarian volume Basal FSH/LH ratio Basal FSH Antral follicle count Age The new multivariate score

r2

r

0.54 0.58

0.217 0.047 0.214 0.046

0.63 0.67 0.73 0.78 0.80 0.81 0.90

0.170 0.163 0.239 0.421 0.354 0.458 0.588

0.029 0.027 0.057 0.177 0.125 0.210 0.346

DISCUSSION Applying a strict definition of low ovarian reserve in a large unselected IVF population and using logistic regression analytic models, our data clearly show that age, basal antral follicle count, and FSH are the most significant independent variables that predict the ovarian reserve of infertile women. The ROC AUC for the three variables was comparable, corresponding to 0.81 to 0.80 and 0.78, respectively. Other less significant independent variables also were found in our study to predict ovarian reserve. These include FSH/LH ratio, mean ovarian volume, infertility duration, number of previous IVF cancellations, and BMI with ROC AUC stepwise decrease from 0.73 to 0.54.

Younis. Ovarian reserve multivariate score. Fertil Steril 2010.

prediction factors received a score of 1 to 3, and those of the low prediction factors received a score of 1 or 2. Age, antral follicle count, and basal FSH got a score of 1 to 5, and other parameters got a score of 1 to 3 or 1 to 2 because the latter were less sensitive to predict low ovarian reserve. The range of the new multivariate score system is therefore 8 to 28. Thus, 8 is the lowest cumulative score (predicts high ovarian reserve) and 28 is the highest cumulative score (predicts low ovarian reserve).

The most significant finding of our study is that incorporating all of these independent variables into one multivariate model resulted in a more accurate parameter to predict low ovarian reserve. The ROC AUC of the new multivariate model was 0.90, significantly superior to all other independent variables. A multivariate score of >14 was shown to have the best sensitivity and specificity to predict low ovarian reserve corresponding to 88% and 69%, respectively. Women with a score of >14 were significantly older, had a longer duration of infertility, had higher BMI, and had more IVF cycles to be cancelled as compared with women with %14 score. Moreover, results of their basal ovarian reserve studies,

This novel cumulative multivariate score was shown to have a distinctive prediction of low ovarian reserve. A cumulative score of >14 was shown to be more accurate in predicting low ovarian reserve than age, basal FSH, or antral follicle count separately with a ROC AUC of 0.90, significantly superior to all other independent variables (Table 2). Additionally, a score of >14 was shown to have a sensitivity of 88% and a specificity of 69% to predict low ovarian reserve. Table 4 summarizes a comparison between the two groups after the introduction of the multivariate new score in relation to the cutoff point of 14. Women with a score of %14 were

TABLE 3 The scoring system used for the multivariate model.

2

BMI (kg/m ) No. of previous cancellations Infertility duration (y) Mean ovarian volume (cm3) Basal FSH/LH ratio Basal FSH (mIU/mL) Antral follicle count Age (y)

1

2

3

4

5

%30 1 %2 >10 %2 %6 >12 %25

>30 2 2–10 5–10 2–4 6–8 10–12 26–30

>10 %5 >4 8–12 7–9 31–35

12–15 4–6 36–40

>15 %3 >41

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TABLE 4 Comparison between patients with good (%14) and low (>14) ovarian reserve with use of the new multivariate score.

No. of women Age (y) BMI (kg/m2) Infertility duration (y) No. of previous cycles No. of previous cancellations Basal FSH (mIU/mL) Basal E2 (pg/mL) Basal P (ng/mL) Basal LH Basal FSH/LH ratio Antral follicle count Mean ovarian volume (cm3) Total ovarian volume (cm3) No. of gonadotropin ampules Duration of gonadotropin treatment (d) E2 on hCG day (pg/mL) P on hCG day (ng/mL) No. of follicles R14 mm on hCG day No. of oocytes retrieved No. of 2PN zygotes No. of cleaved embryos No. of embryos transferred Clinical pregnancy rate per cycle (%) Clinical pregnancy rate per ET (%) Clinical implantation rate per ET (%)

Score % 14

Score > 14

P value

106 27.8  3.8 24.7  4.9 4.2  2.8 1.2  2.1 0.01  0.09 6.0  1.6 48.8  21.3 0.8  0.6 5.2  2.4 1.46  0.99 10.9  5.1 10.0  3.9 19.5  7.9 37.2  11.6 11.9  2.1 2619  1250 1.03  0.63 13.3  6.7 13.2  6.3 8.00  4.8 7.6  4.4 2.1  1.2 38.6 45.0 22.4

61 34.8  4.9 28.7  7.7 6.9  4.7 3.1  4.5 0.18  0.47 8.4  2.8 47.4  22.0 0.8  1.1 4.8  2.5 2.17  1.12 4.4  3.2 7.5  3.8 14.9  8.4 50.5  19.1 11.7  2.5 1480  973 0.79  0.60 7.1  4.5 5.6  4.7 3.3  3.2 3.2  3.1 1.7  1.2 11.3 17.5 6.7

< .001 < .001 < .001 .003 .006 < .001 .702 .778 .364 < .001 < .001 < .001 .001 < .001 .711 < .001 .017 < .001 < .001 < .001 < .001 .098 < .05 < .05 < .05

Notes: Values are presented as mean  SD. 2PN ¼ two pronuclei. Younis. Ovarian reserve multivariate score. Fertil Steril 2010.

including antral follicle count, FSH, and mean ovarian volume, were significantly poorer as compared with the %14 score group. Also, women with a multivariate score of >14 performed inferiorly in their first IVF treatment when compared with the %14 score group. Most important, the new multivariate score was able to distinguish clinical pregnancy rate between the low and good ovarian reserve groups. Infertile women with a score of >14 had significantly lower clinical implantation and pregnancy rates versus women with a score of %14, corresponding to 6.7% versus 22.4% and 11.3% versus 38.6%, respectively. It is well accepted today that the available tests for ovarian reserve do not have enough predictive power to justify their routine clinical use. It is believed also that the studies introduced so far test oocyte quantity and not quality (11). Moreover, none of the available tests have been shown to predict pregnancy or live birth with sufficient accuracy and were concluded to be inadequate (9, 10). Consequently, several research groups in the last decade have explored the idea that a cumulative multivariate model would perform better in preFertility and Sterility

dicting low ovarian reserve and pregnancy achievement (15–22). Looking into these published reports, it can be seen that the multivariate models that have been studied so far are not conclusive. The definition of low ovarian reserve in these studies differed and varied considerably. Moreover, although some of these did find an advantage for the multivariate model over a single ovarian reserve test (18, 22), others did not (17, 20). Also, although some studies used only the static ovarian reserve studies, others incorporated the clearly more demanding dynamic tests into the multivariate model. In a recent meta-analysis a systematic regression analysis showed that the performance of one particular multivariate model was not superior to that of the other. Furthermore, it was concluded that compared with other ovarian reserve tests these multifactor models do not seem to create a definitive improvement in their predictive capacity (9). Notably, all studies published so far reported on prediction of poor response, whereas none revealed usable data on pregnancy prediction. 659

It is interesting to notice that most of the multivariate models published so far have evaluated low ovarian reserve with use of various endocrine or sonographic parameters disjointedly. To the best of our knowledge only three studies have incorporated endocrine and sonographic ovarian reserve studies combined (18, 20, 22). Bancsi et al. (18) in a prospective study of 120 women in their first IVF cycle examined the ovarian reserve by using basal antral follicle count, total ovarian volume, FSH, E2, and inhibin-B. Low ovarian reserve was defined as four or fewer oocytes or cycle cancellation due to three or fewer follicles of 18 mm. The antral follicle count was found to be the best single predictor for ovarian reserve with ROC AUC of 0.87. The addition of FSH and inhibin-B to antral follicle count improved by only a fraction the prediction of low ovarian reserve to ROC AUC of 0.92. However, the results of the analyses for pregnancy were far less promising. Basal antral follicle count, inhibin B, and FSH separately or combined did not have an effect on pregnancy rate. In another conjoined endocrine and sonographic multivariate model reported by Erdem et al. (20), 56 women were studied with use of basal FSH, inhibin-B, clomiphene citrate challenge test, mean ovarian volume, and mean antral follicle count. Low ovarian reserve was defined as five or fewer oocytes or cycle cancellation due to three or fewer follicles of <15 mm. The mean ovarian volume was found to be the best single predictor for ovarian reserve with ROC AUC of 0.82. The addition of other hormonal test or antral follicle count did not improve the prediction of low ovarian reserve. All parameters studied except age did not have an effect on pregnancy prediction. In a similar recent retrospective study by Muttukrishna et al. (22), 81 women were evaluated with use of basal antral follicle count, AMH, inhibin-B, and FSH. Low ovarian reserve was defined as four or fewer collected oocytes. Delta inhibin-B (levels of inhibin-B on day 4 minus day 3) had the best association to the number of oocytes collected followed by basal AMH and antral follicle count. A cumulative score using basal FSH, basal AMH, delta E2, delta inhibin-B, antral follicle count, and age was the best predictor for identifying low ovarian reserve with ROC AUC of 0.91. The parameters studied were not associated with pregnancy achievement. Taken together, three studies (two prospective and one retrospective) have been reported combining endocrine and sonographic tests to predict low ovarian reserve in infertile women. The number of women in each of these studies was undersized, and the definition of low ovarian reserve was liberal. Two studies included a dynamic test, and only one study included age as part of the multivariate model. Eventually, two studies showed an improvement of the multivariate model over a single test, whereas one study did not. All three studies were not able to predict pregnancy. More studies therefore are encouraged to explore the potential of the combined endocrine and sonographic multivariate model in 660

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predicting the reproductive performance of infertile women with low ovarian reserve. Our new score is unique because it is easy and simple to perform, incorporating undemanding clinical (age, infertility duration, previous cycle cancellations, and BMI), basal endocrine (FSH and FSH/LH ratio), and basal ultrasonographic parameters (antral follicle count and ovarian volume). It does not include dynamic tests and does not comprise more expensive ovarian reserve studies such as AMH and inhibin-B that are not available on a regular basis in every ART unit. Evidently the new score increases the predictive value of low ovarian reserve. Above all, our score is closely related to clinical implantation and pregnancy rates in an IVF setting. A good clinical marker should have a high sensitivity for identifying the women with true low ovarian reserve and high specificity for identifying the women with true good ovarian reserve. We have chosen the cutoff of 14 in the new multivariate score that provides a higher sensitivity (88%) rather than a high specificity (69%) to identify more precisely the women with true low ovarian reserve. Our new score enables the identification of women with low ovarian reserve and therefore may assist in counseling and optimizing their superovulation protocol. Moreover, knowing that there is a high chance of a poor outcome may help the patient and the physician to decide to withhold treatment and search for alternatives such as oocyte donation or adoption. This could be the case with infertile women who have repeated IVF failure. On the other hand, our multivariate score does not preclude newly admitted infertile women performing an IVF treatment. The specificity of the new score cutoff, as well as the clinical pregnancy rate achieved in the high score (>14) group, does not justify withholding IVF from these patients. Controversy exists as to whether any of the available endocrine or sonographic parameters are superior to age in assessing reproductive potential. This is especially true for basal FSH level. Although initial studies have shown that basal FSH is a better predictor for IVF performance than age (23), later studies have shown that basal FSH is of less value than age in predicting pregnancy rates (17, 20, 24) especially in younger women (25). No doubt female age is a basic factor that is related to both quantity and quality of ovarian reserve. As such, it is our belief that age should be incorporated into any multivariate model that is trying to evaluate ovarian reserve, as well as pregnancy, in an IVF setting. Pregnancy prediction is a more complicated issue than ovarian reserve appraisal for infertile women. Obviously pregnancy is not related to the ovarian reserve alone, but to many other factors as well. Pregnancy achievement is interrelated to oocyte and embryo quality, ET technique, number of embryos transferred, as well as endometrial receptivity. It is our belief that incorporating clinical criteria, particularly age, has contributed to the ability of our score to be closely related to clinical pregnancy rate. Basal endocrine and Vol. 94, No. 2, July 2010

sonographic parameters primarily represent the quantitative aspect of ovarian reserve. However, it also is believed that there is a relationship between quantity and quality when considering the issue of ovarian reserve (26). It is therefore possible that conjoining age and other clinical parameters to both endocrine and sonographic tests into one multivariate score, as performed in our study, has attributed further to pregnancy appraisal. It should be noted that our study evaluated only one cycle of IVF treatment. It could be claimed that the use of pregnancy as an outcome parameter for the assessment of ovarian reserve status may be insufficient if only one exposure cycle is taken into account because this may not accurately represent a woman’s true reproductive capacity. The recent literature has suggested that singleton live term birth rate per cycle initiated or per defined treatment period may be the most significant outcome variable of all ART treatment cycles (27, 28). It is our belief that prospective targeted studies should be performed to validate our multivariate score as a predictor of low ovarian reserve and to explore whether it could be a good predictor of singleton, term, live birth per cycle started. In conclusion, we present a new simple multivariate score that has a distinctive prediction of low ovarian reserve in infertile women. The score incorporates undemanding clinical, basal endocrine, and ovarian sonographic parameters. The new score increases significantly low ovarian reserve prediction as related to various available single tests. Moreover, it is closely related to clinical implantation and pregnancy rates in low and good responder infertile women.

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