Intracytoplasmic Sperm injection (ICSI) brings
an operative technology in the fields of assisted
reproduction technology (ART) (
Multiple studies have also showed a higher
risk of congenital abnormalities, cardiovascular,
musculoskeletal defect, low birth weight, preterm
delivery and increase perinatal mortality
in IVF/ ICSI offspring (
Different success rate of ICSI has also been observed in various causes of infertility. Our prediction model has been developed in reproductive medicine to help gynecologists in assessing the chances of pregnancy following ICSI. With these models, gynecologists can calculate the probability of a treatment pregnancy as well as the probability of pregnancy success with ICSI. In this study, we evaluated the relation between ICSI outcome and special cause of infertility. We also aimed to examine parameters that might predict pregnancy success rate following ICSI.
This cross sectional study included 1492 infertile women referred to Infertility Center of Royan Institute between 2010 and 2011.We assigned two groups including pregnant (n=504) and nonpregnant (n=988), while all participants underwent ICSI cycles.
Information about age, menstrual duration, number of previous cycle, endometrial thickness, number of embryo transfer, embryo quality, duration of infertility, type of infertility, cause of infertility (ovulatory factor, unexplained factor, male factor...) were obtained from patient’s file, then the collected data were analyzed and compared between the two groups. Inclusion criteria were as follows: male infertility, ovarian infertility (including polycystic ovary syndrome (PCOS) and diminished ovarian reserve), tubal infertility, unexplained infertility, recurrent abortion, and endometriosis.
The couples with testicular atrophy, anatomical abnormalities, infection, uterine fibroids, systemic disease and history of ICSI/IVF failure more than three times were excluded from the study. In all participants, serum follicle-stimulating hormone (FSH; Pishtaz-Tab, Tehran, Iran) and luteinizing hormone (LH; Pishtaz- Tab, Tehran, Iran) were measured on day 3 of the cycle preceding ovarian stimulation. The ovarian stimulation protocol for all patients was performed according to the standard long protocol. Both groups started with Bucereline acetate (Superfact; Aventis Pharma Deutshlan, Frankfurt, Germany) 500 μg on day 21 of the previous cycle and continued daily until the day of hCG administration. After ovarian stimulation, injection of 10000 IU of human chorionic gonadotropin (hCG; Choriomon; IBSA, Switzerland) was given when at least two follicles ≥18 mm were detected. Transvaginal follicular aspiration was performed under ultrasound guidance, 34-36 hours after the administration of hCG. Afterwards, ICSI cycle was completed. All patients received luteal phase support through daily administration of 100 mg natural progesterone (sterop Laboratories, Brussls, Belgium) and progesterone up to 8 week of gestation. A clinical pregnancy was confirmed by the observation of gestational sac in ultrasonography. This study was approved by the Royan Ethics Committee.
In addition, all subjects agreed to participate in the study were required to sign a consent form approved by the Royan Ethics Committee.
In order to build a prediction model, we used backward logistic regression analysis, in which a p-value of 0.15 was used as an entry criterion, whereas a p-value of 0.10 was the threshold for a variable to stay in the model. The performance of the model was calculated as the area under the receiver operating characteristic (ROC) area under roc curve (AUC). An AUC of 0.5 indicates no discriminative performance, whereas an AUC of 1.0 indicates perfect discrimination.
Calibration of the model was assessed by comparing the predicted probability of pregnancy in a category of patients with the observed percentage of pregnant woman in the same category. We first categorized the predicted probabilities of pregnancy in 10 groups, and then we compared the mean predicted probability of pregnancy within a group with the observed probability of the same group.
All statistical analysis was performed by SPSS program (Version 18; USA). Chi-square and t test were used for analysis. Also, In order to predict the result of ICSI, we used logistic regression. The data were expressed as means ± standard deviation (SD). Odds ratio (OR) and 95% confidence interval (95% CI) were also calculated for each factor. The value of p<0.05 was considered to be statistically significant.
In this study, 1492 women were enrolled. The mean maternal age was 32.3 ± 5.3 years, while the mean duration of infertility was 7.2 ± 5.07 years. Of 1492 women, 1172 (78.5%) individuals were with primary infertility, while 320 (21.5%) individuals were with secondary infertility. Overall, 59.8% of patients had previous treatment for infertility, and we also found a significant reduction of pregnancy rate in the group with previously failed ICSI attempts. The general characteristics of all participants undergoing ICSI, divided into pregnant and non-pregnant groups,are provided in table 1.
Our findings confirmed that the pregnancy
rate reduced when the woman’s age increased
(OR=0.93, 95% CI=0.91-0.95). In addition, our
result revealed that pregnancy rate were lower in
primary infertility than secondary infertility, but it
is n’t significant. Our results also showed no significant
effect of body mass index (BMI) on pregnancy
Characteristics of women undergoing ICSI in two groups of pregnant and non-pregnant
|Pregnant||Non-pregnant||OR (CI 95%)*||Significant|
|31.1 ± 4.8||32.9 ± 5.4||0.93 (0.91-0.95)||<0.0001a|
|Primary-N (%)||396 (33.8%)||776 (66.2%)||1***|
|Secondary-N (%)||109 (34%)||211 (66%)||1.005 (0.774-1.30)||0.969b|
|25.8 ± 3.7||26.03 ± 3.7||0.98 (0.95-1.01)||0.37a|
|0.46 ± 0.75||0.66 ± 0.99||0.76 (0.67-0.87)||<0.0001a|
|6.25 ± 1.5||6 ± 1.3||1.12 (1.04-1.21)||0.002a|
*; OR=Odds ratio, CI=Confidence interval, **; Values are mean ± SD, ***; Reference category, a; Independent sample t test and b; Chi-square test.
Table 2 indicates the different causes of infertility and their likelihood of occurrence, like ovulatory factor (7.4%), tuboperitoneal factor (5.2%), unexplained factor (10%), male factor (59.1%), recurrent abortion (2.1%), uterine factor (0.4%), Mix (14%), and others (impotency, vaginismus, genetic disorder, etc) (1.7%). Furthermore, table 2 shows outcome of ICSI cycles in different causes of infertility, where as there was no statistically significant difference between groups.
Cycle characteristics are depicted in table 3.
We found total dose of gonadotropin of nonpregnant
group to be significantly higher than
that of pregnant group (p<0.0001). Table 3 reveals
that there was statistically significant difference
between the pregnant and non-pregnant
groups in endometrial thickness (p<0.05). The
number of retrieved metaphase II (MII) oocytes
was significantly higher in pregnant group than
that in non-pregnant group. There was no significant
difference between two groups in the
mean serum concentrations on day 3 after application
of the following hormones: FSH (7.04 ±
3.43 IU/ml), LH (5.51 ± 4.06 IU/ml), TSH (2.35
± 1.81 IU/ml), metoclopramide-stimulated prolactin
(PRL) (163.40 ± 264.82 IU/ml) (
Success rate of ICSI outcome in infertile couples with different cause of infertility
|Pregnant % (N)||Non-pregnant % (N)||P value a|
|29.7 (33)||70.3 (79)||0.936|
|32.2 (25)||67.8 (53)|
|34 (50)||66 (99)|
|35 (307)||65 (573)|
|31.2 (10)||68.8 (22)|
|50 (4)||50 (4)|
|32.9 (68)||67.1 (141)|
|37.5 (9)||62.5 (15)|
*; Impotency, vaginismus, genetic disorder and a; Chi-square test.
Table 3: Cycle parameters of the patients undergo ICSI
|Pregnant Non-pregnant||OR* (CI 95%)||Significant a|
|1986.48 ± 941||2240.96 ± 1035||0.9997 (0.9996 ± 0.9998)||<0.0001|
|9.87 ± 1.7||9.57 ± 1.8||1.09 (1.03 - 1.16)||0.002|
|0.4 ± 0.8||0.4 ± 0.8||0.97 (0.85 - 1.11)||0.68|
|8.3 ± 3.9||7.2 ± 4.1||1.06 (1.04 - 1.09)||<0.0001|
|0.71 ± 0.2||0.68 ± 0.3||1.31 (0.92 - 1.89)||0.13|
|2.1 ± 2.9||1.5 ± 2.4||1.08 (1.03 - 1.12)||<0.0001|
|2.50 ± 0.66||2.36 ± 0.79||1.29 (1.11 ± 1.48)||<0.0001|
|6.81 ± 3.5||7.13 ± 3.4||0.97 (0.94 - 1.005)||0.10|
|5.82 ± 4.81||5.35 ± 3.8||1.02 (1 - 1.05)||0.04|
|2.35 ± 1.71||2.37 ± 1.8||0.99 (0.93 - 1.05)||0.85|
|163.42 ± 232.1||162.88 ± 270.3||1.00 (1.00 - 1.00)||0.97|
* ; OR=Odds ratio, CI=Confidence interval, **; Values are mean ± SD and a; Chi-square test.
However, there was statistically significant
difference in the mean serum level on day 3 after
application of LH between the pregnant and
the non-pregnant groups. There were no statistically
significant differences between groups
in number of MII oocytes, embryo transfer and
number of good embryo (grade A, B, AB) (
Finally, in order to build a prediction model and find the most important factors that affect pregnancy rate, we used a logistics regression model in a backward manner. Table 4 shows the result of fitting logistic regression model to the data.
Age, menstrual duration, number of previous
cycle, endometrial thickness, number of embryo
transfer, and embryo quality in the logistic regression
model were significantly associated with
pregnancy outcome. Age and number of previous
cycle were negatively associated with pregnancy
outcome, while menstrual duration, endometrial
thickness, embryo quality and number of embryos
transferred were positively associated with pregnancy
Table 4: Result of logistic regression analysis
|AUC: 0.681 (95% CI 0.653-0.709)|
* OR; Odds ratio and CI; Confidence interval.
AUC shows the discriminative performance of
the logistic model. The AUC of 0.5 shows no discriminative
performance, while AUC of 1.0 indicates
perfect discrimination. The AUC for the fitted
logistic model was 0.681 (95% CI=0.653-0.709)
that shows good predictive performance (
Figure 2 indicates the calibration of the prediction model for pregnancy after ICSI. The predictive performance of the model is acceptable because the 95% confidence intervals of the observed pregnancy rates overlap with the predicted pregnancy rates.
ROC curve for assessment discrimimative preformance of logistic regression.
Calibration plot, showing the relationship between predicted and observed rate of pregnancy after ICSI.
Although ICSI is originally developed to treat
male infertility, it has been used for infertile couples
with different causes of infertility (
In our study, no significant difference was
found in BMI between pregnant and not-pregnant
groups. Usoniene et al. reported the same results
of pregnancy rate for different BMI groups (
In our study, mean LH serum concentration in
pregnant group were significantly higher than
that in non-pregnant group (OR=1.02, CI=1-1.05;
p=0.04). At the beginning of stimulation, high LH
concentration can lead to increased endometrial
maturation at oocyte pick-up (
History of menstrual cycle length (MCL) will be
used as a simple sign of ovarian reserve, which is
primarily determined by the growth rates and quality
of ovarian follicles. Our result showed women
with menstrual duration more than 6 days had more
chance of pregnancy than those with cycles less
than 6 days (OR=1.12, CI=1.04-1.21; p=0.002).
Shortening of MCL causes an abbreviated follicular
phase, but in general, luteal phase length is preserved
Tomas et al. found the influence of embryo
quality in pregnancy prediction (
Esinler et al. showed that larger doses of gonadotropin
are required for overweight and obese
It is evident that various factors may influence
the outcome of ICSI. Kovacs et al. showed, women
who became pregnant after ART showed thicker
endometrium, better quality of embryo, as well
as more follicles, oocytes and embryos (
Undoubtedly, this database was not large enough to allow definite conclusion, and needed further supports to continue the follow-up of pregnancy outcome after ICSI.
Our models can be used reliably as a guide for making decisions for fertility management in infertile patients. The effects of using these models in patient care need further experimental investigation.
ICSI is an important treatment option for various indications of infertility. The present study showed that pregnancy rate affected by the number of previous cycle, total dose gonadotropin, endometrial thickness, number of previous cycle, quality of embryo transferred and menstrual duration. It is required that each infertility center gather enough information about the causes of infertility in order to provide more information and better assistance to patients. Therefore, we suggest that physician sprepare adequate training and required information regarding these procedures for infertile couples in order to improve their knowledge.