1 Department of Obstetrics and Gynaecology, 2 Department of Epidemiology and Biostatistics, Radboud University Nijmegen Medical Centre, 3 TNO Nutrition and Food Research, Department of Food & Chemical Risk Analysis, Zeist, 4 Erasmus Medical Centre Rotterdam, Department of Gynaecology and Obstetrics, Rotterdam, 5 Diaconessenhuis, Department of Gynaecology, Reinier de Graaf Groep, Voorburg, 6 Netherlands Cancer Institute, Department of Epidemiology, Amsterdam, The Netherlands
7 To whom correspondence should be addressed. Email: a.lintsen{at}obgyn.umcn.nl
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Abstract |
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Key words: body mass index/IVF/live birth rate/smoking/subfertility diagnosis
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Introduction |
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The main goal of the present analyses was to explore possible predictive factors such as duration of subfertility, and female age, for subfertile couples with different causes of subfertility. As there is evidence of an overall detrimental effect of female smoking on natural and assisted fecundity in the literature (Hughes and Brennan, 1996; Feightinger et al., 1997
; Augood et al.., 1998
; Hassan and Killick, 2004
) and indication for an unfavourable effect of extremes of body mass index (BMI) on the outcome of fertility treatment (Norman and Clark, 1998
; Wang et al., 2000
, 2002
; Nichols et al., 2003
), we also studied smoking and BMI as possible prognostic factors. Like the Templeton model we distinguished the major causes of subfertility, and added male subfertility and lifestyle factors. We executed this study with data from a large Dutch nationwide retrospective cohort study (the so called OMEGA study) including 19 840 women who underwent IVF treatment between 1983 and 1995.
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Materials and methods |
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In The Netherlands, three IVF cycles were covered by health cost insurances in the period under study, leading to a low drop-out rate in the first three cycles. Eighty-seven per cent of the women completed at least three cycles, or became pregnant in the first two cycles. As continuation of IVF depends on predictors of success observed in the first cycle, such as number of oocytes, fertilization rate and embryo morphology (Stolwijk et al., 1996), we restricted all analyses to the first attempt, leaving 8457 first cycles for analysis.
Definition of variables
Subfertility diagnosis was based on medical record information and divided into four categories: tubal pathology, male subfertility, unexplained subfertility and other known subfertility causes, mainly women with polycystic ovarian syndrome (PCOS) or endometriosis. Each woman was only categorized once, the one assumed to contribute most to the subfertility. For 831 first cycles there was no cause of subfertility known and these were therefore not analysed in detail. Duration of subfertility was determined by the period between the start of the involuntary childlessness, as reported by the woman, and the date of first IVF attempt. Primary subfertility was defined as having no pregnancy before the IVF treatment. Education level was divided into low (those without completed vocational training), middle (with vocational training) and high (with high vocational training or academic degrees). Women were defined as smokers when they smoked more than one cigarette a day for 1 year at the time of the first oocyte retrieval. Underweight was defined as having a BMI <20 kg/m2, normal weight as a BMI of 2027 kg/m2 and overweight as a BMI
27 kg/m2, as there were not enough women with a BMI
30 kg/m2 for analysis. The BMI was calculated with the women's weight at the time of first visit to the gynaecologist for her fertility problem. The woman's age at the IVF attempt was computed by subtracting the date of birth from the IVF attempt date. IVF attempts obtained from the medical records were linked with live births as reported by the women on the questionnaire. Conception dates were calculated by subtracting the reported duration of pregnancy from the delivery date, as reported by the women. If an IVF attempt had started within 4 weeks of the estimated conception date, the pregnancy was considered to be the result of the IVF attempt, unless the medical record stated that a spontaneous pregnancy followed the IVF attempt. The implantation rate was defined as the number of live born children per embryo transferred. The live birth rate was the delivery rate with at least one live born child per cycle. Total fertilization failure (TFF) was defined when none of the oocytes was fertilized after IVF. An abortion was defined as a pregnancy loss between 6 and 16 weeks of amenorrhoea. The following complications were registered: ovarian hyperstimulation syndrome (OHSS) leading to hospitalization, other medical problems resulting in admission and ectopic pregnancies.
Statistical analyses
The statistical program SAS: The SAS system for window 8.2, SAS Institute Inc. Cary NC, USA, was used for statistical analyses. Univariate frequencies and means were calculated to describe the women and their first IVF cycles. The results are given in Tables I and II. All analyses were done first on all women, including those with unknown cause of subfertility, and then by cause of subfertility.
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Results |
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Cycles
The characteristics of the first IVF cycles of our population are described in Table II. The outcome of the first cycles in women with a main diagnosis of tubal pathology (3008 cycles), male subfertility (2179 cycles) and unexplained subfertility (1828 cycles) were analysed, using various outcome measures. Cycles with other known causes of subfertility (611) were also examined. The proportion of first cycles with TFF was 27.1% in the male subfertility group. This was significantly higher than for unexplained subfertility and tubal pathology, (10.6 and 7.3% respectively). The abortion rate was significantly lower in the male subfertility group compared to both other indication categories. The overall proportion of first cycles with complications after IVF treatment (excluding TFF) was 4.9%. Ectopic pregnancies occurred significantly more often in the group with tubal pathology, compared to the other groups. The percentage of cycles with OHSS leading to hospitalization was significantly higher in the other known indication group (including PCOS) compared to the main indication categories.
The average number of embryos per transfer was 2.2 (range 07, median 2). The overall live birth rate per cycle was 15.2%. The live birth rate per first cycle for the unexplained subfertile couples was higher (17.8%) in comparison with tubal pathology (14.6%) and male subfertility (13.6%). The live birth rates according to age and diagnostic categories are shown in Table III. For male subfertility there was no significant difference in the live birth rate per embryo transfer, in comparison with the unexplained subfertile couple (21.3 and 22.7%). Tubal pathology was associated with the lowest live birth rate per embryo transfer (18.4%). The overall implantation rate per cycle was 10.7%.
For the three major subfertility causes analysed, we found evidence of a clear and significant (P<0.0001) trend of declining live birth rates with increasing female age (Figure 2). The overall live birth rate per cycle decreased with 2% (P=0.03) for each additional year of the female age.
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Table V shows the results of multivariate analyses of predictors of the live birth rate as a result of the first IVF cycle, after successful oocyte retrieval and after embryo transfer. The first row gives the intercept, and the corresponding live birth rate for those with reference values for all variables. In the other rows, OR are presented. These can be interpreted as follows: the live birth rate of smokers decreased with 28% compared with the live birth rate of non-smokers, adjusted for the following confounders: age, BMI, indication for IVF, previous pregnancies, duration of subfertility and calendar period in which IVF took place. There was only a significantly lower live birth rate per treatment cycle by cause of subfertility for couples with male subfertility. We found that the adjusted effect of smoking on the live birth rate was even stronger than an increase in female age with >10 years, from age 20 to 30 years, with an OR of 0.78 (95% CI 0.630.96). The strength of the association with smoking differed between the subfertility groups. As in the univariate analyses, smoking was most deleterious to the couples with unexplained subfertility, and least to those with tubal pathology (Table IV). Overweight women (BMI >27 kg/m2) had a 33% reduced chance of a live birth in their first IVF cycle. As for smoking, the association with overweight was strongest in women with unexplained subfertility. BMI and age were also both included as continuous variables. The effect estimates were similar for live birth rate per cycle, per oocyte retrieval and per embryo transfer: BMI per unit OR = 0.98 (0.951.00) and age per year OR = 0.98 (0.961.00). Women with primary subfertility had the same live birth rate as women with secondary subfertility. The duration of subfertility did not influence the live birth rate for the three major subfertility categories. Even after 8 years of subfertility, no significant decrease in live birth rate could be detected.
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Discussion |
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When interpreting our results, the strengths and limitations of our study must be considered. Advantages of our analyses include the large size of the study population and the availability of nearly complete information on details of IVF treatment from the medical records and outcome of all pregnancies from the women themselves. A limitation of our study is that the analyses had to be based on women who responded to the questionnaire (a 71% response rate). Women who had a live birth after IVF were possibly more likely to participate to the OMEGA project than those who remained childless. From two participating hospitals, a non-responder analysis to the questionnaire was performed. Indeed, we observed a higher response rate among women who had a live birth rate after IVF, compared to women who did not (response rates of 73 and 64% respectively). This might have resulted in a slight overestimation of live birth rates after IVF in Tables IIIV. However, assuming that non-response was not associated with lifestyle factors, the estimate of the OR is unbiased. For 3227 IVF-treated women who returned the questionnaire, data from the medical files could not yet be obtained. Since this was due to limited project funding resulting in a random sample of records not yet completed, it is highly unlikely that this has led to selection bias. Another restriction of our study is that we should take into account that the success rates in these older data might differ from the success rates today (Kremer et al., 2002). One unique feature of our analyses is that we were able to study the separate and combined influences of smoking and BMI for a very large number of IVF treatments.
Most of our results correspond with the results of the study by Templeton et al. (1996). We found that only male subfertility was associated with a significantly lower delivery rate per cycle compared with tubal pathology and unexplained subfertility. If we considered the delivery rates per embryo transfer, i.e. after fertilization had occurred, we did not observe a difference between unexplained subfertility and male subfertility. The abortion rate was significantly lower in the male subfertile group. These results imply that the receptiveness of the women with unexplained subfertility and male subfertility was at least the same, and probably better in the male subfertile group. For tubal pathology the delivery rate was significantly lower given an embryo transfer, compared to unexplained subfertility and male subfertility. The explanation for this difference could be the negative effect of tubal pathology on the implantation processes and the embryotoxicity of hydrosalpinx fluid (Johnson et al., 2002
).
Individual studies comparing smoking and non-smoking women undergoing IVF treatment do not always indicate a decreased live birth rate with smoking. A meta-analysis (Augood et al., 1998) showed that women who smoked had significantly lower pregnancy rates per IVF treatment compared to non-smokers. However, in none of these studies was a subdivision made according to the indication for IVF, and each of the studies reported different confounding factors and calculated OR using different statistical methods. In a review (Zenzes, 2000
) on the genetic damaging effects from smoking and its components on germinal cells, evidence was found that smoking affected the quantity and quality of oocytes and that it leads to an early age of menopause. Our results show a lower live birth rate and higher abortion rate for smoking women unless they had a higher mean number of embryos transferred. This might explain the lower quality of these embryos.
We studied the effects of both smoking and age on the live birth rate and found a trend of decreasing live birth rates with increasing age, which was consistently lower for smokers. Among women with tubal pathology, the diagnostic group with significantly more smokers than in the other subfertility causes, we found that the deteriorating effect of smoking on the live birth rate per embryo transfer was not as strong as among women in the other diagnostic categories. The difference in influence of smoking on the outcome of pregnancy per indication category was not statistically significant (BreslowDay test for homogeneity of odds ratios, P=0.19).
There is a clear association of an increased BMI, risk of complications during pregnancy and a higher chance of abortion and subfertility (Norman and Clark, 1998; Wang et al., 2000
, 2002
). After multivariable logistic regression modelling, we also found a significant effect of overweight (BMI
27 kg/m2) on the live birth rate per cycle, with an OR of 0.67 (95% CI 0.480.94).
Besides dependency on calendar period, prognostic models for IVF depend on the success rate of the treating hospital (Haan et al., 1991a; Templeton et al., 1996
; Kremer et al., 2002
), patient characteristics and the number of previous IVF cycles (Tan et al., 1996
; Templeton et al.., 1996
; De Mouzon et al., 1998
). Publications suggest constant success rates for each of the first three cycles (Haan et al., 1991b
; De Vries et al., 1999
). Some attribute this to active censoring, which leads to withdrawal of couples with poor prognosis (Land et al., 1997
). In our study, continuation of IVF treatment depended on indication, due to the differences in fertilization rate. Twenty-five per cent of the couples diagnosed with male subfertility did not complete three cycles and remained childless as compared with 13% of couples with unexplained subfertility and 5% of couples with tubal pathology. For reasons of comparability we therefore restricted our analyses in the present study to the first IVF treatment cycle only.
Our historical cohort study enables us to assess the differences in success rates of IVF between the various subfertility causes. However, to study the efficacy of IVF in various diagnostic categories, a long-term clinical trial will be the best option, comparing the pregnancy rates of IVF or ICSI treatments with no treatment. A second-best option is the comparison of the spontaneous pregnancy rate in subfertile couples on the waiting list for IVF or ICSI, with the results of IVF- or ICSI-treated couples. We are expecting results from such a study in The Netherlands in the near future.
In conclusion, we observed differences in success rate between subfertility causes in favour of unexplained subfertility. Smoking had an unfavourable effect on the outcome of IVF and was comparable with an increase in female age of >10 years from age 20 to 30 years. Overweight had a strong harmful effect on the live birth rate after IVF. The effect of smoking and overweight was largest among women with unexplained subfertility. These results suggest that women, and in particular those with unexplained subfertility, may be able to improve the outcome of subfertility treatment by quitting smoking and losing weight.
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Acknowledgements |
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References |
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Submitted on November 19, 2004; resubmitted on February 1, 2005; accepted on March 7, 2005.