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. Author manuscript; available in PMC: 2012 Jan 1.
Published in final edited form as: Fertil Steril. 2010 Jul 25;95(1):79–84. doi: 10.1016/j.fertnstert.2010.06.043

Fertility Treatments and Outcomes among Couples Seeking Fertility Care: Data from a Prospective Fertility Cohort in the United States

James F Smith 1,4, Michael L Eisenberg 1, Susan G Millstein 3, Robert D Nachtigall 4, Natalia Sadetsky 1, Marcelle I Cedars 4, Patricia P Katz 2; the Infertility Outcomes Program Project Group
PMCID: PMC2966858  NIHMSID: NIHMS216927  PMID: 20659733

Abstract

Objective

To determine the relationship between number of fertility treatment cycles and pregnancy rates.

Design

Prospective cohort study

Setting

Eight community and academic infertility practices

Patients

408 couples presenting for an infertility evaluation

Interventions

Face-to-face and telephone interviews and questionnaires

Main Outcome Measures

Incidence of pregnancy

Materials and Methods

Cox regression analysis compared the efficacy of cycle-based fertility treatments to no cycle-based fertility treatment after multivariable adjustment

Results

Couples using 1–2 medications-only cycles had a significantly higher pregnancy rate (HR 4.7 [95% CI 1.3–16.6]); a benefit that did not persist after 3+ cycles (HR 0.6 [0.1–3.2]). Couples using IUI for one (HR 2.9 [1.4–5.8]), two (HR 2.0 [0.9–4.5]), and three cycles (HR 4.5 [1.8–10.9]) were more likely to achieve a pregnancy. No additional benefit was seen for couples using 4+ IUI cycles (HR 1.0 [0.4–2.6]). IVF was associated with significant benefit for couples using one (HR 2.8 [1.5–5.2]) and two cycles (HR 2.2 [1.2–4.1]). Couples using 3+ IVF cycles had a non-statistically significant higher likelihood of pregnancy (HR 1.3 [0.7–2.4]).

Conclusions

Cycle-based fertility treatments may offer a point of diminishing returns for infertile couples: two cycles of medications only, three cycles of IUI, and two cycles of IVF.

Keywords: Diminishing returns, infertility treatment, prospective cohort, decreasing efficacy, ART

Introduction

Infertility affects 7–17% of all couples seeking to have children in the United States (15). Regardless of the etiology, infertility treatment has become increasingly “cycle-based” whereby ovarian stimulation by oral and/or injectable drugs is combined with a sperm-delivery technique, usually intrauterine insemination (IUI), in-vitro fertilization (IVF), or intracytoplasmic sperm injection (ICSI). Several studies have demonstrated a benefit of IUI compared to ovarian stimulation alone (68), and of IVF compared to IUI (911).

There has been significant debate concerning the number of treatment cycles couples should pursue (12, 13). Reindollar demonstrated that proceeding to IVF after three IUI cycles resulted in a faster time to pregnancy than using up to six IUI cycles before IVF (13). Data from SART demonstrated that cumulative ART pregnancy rates plateau after 3–4 cycles (14). However, the per-cycle pregnancy rate declined slowly from a maximum of 30% for couples using one cycle to ~20% for couples using 6+ cycles. These data were not adjusted for the many factors known to affect fertility success, nor were they compared to couples not using ART.

Despite these observations, no prospective study has compared these cycle-based fertility treatment modalities in the same study population. Further, few studies have addressed whether the pregnancy rates of the most commonly utilized cycle-based treatments diminish with increasing duration of treatment in a broad population of fertility patients (15). The present study reports results from an 18-month prospective observational study of couples pursuing the full range of cycle-based fertility treatments. The aims of the present study were to describe the use, duration, and success of cycle-based treatments over this period while adjusting for infertility risk factors such as maternal age (16), infertility duration and diagnosis (1719), and parity (2022). Such information could be useful in counseling infertile patients as to when they should abandon less intensive treatment for more intensive and potentially more costly therapy.

Methods

Cohort Description

Couples were recruited from eight reproductive endocrinology clinics after the female partner presented for infertility treatment. Study inclusion criteria were: currently trying to get pregnant with a male partner, English-speaking, no prior treatment with IVF, no prior sterilization or hysterectomy, not seeking treatment for recurrent miscarriage, and living in proximity to one of the eight centers. Participants completed baseline questionnaires and face-to-face interviews with highly trained female interviewers and completed three follow-up telephone interviews. Of 809 women who met inclusion criteria, 436 (54%) agreed to participate, and 96% (n=420), 93% (n=405), and 89% (n=390) completed the first (4-month), second (10-month), and third (18-month) follow-up interview, respectively. 408 couples (94%) were followed until pregnancy or study end. The institutional Committee on Human Research approved this protocol and all subjects provided written consent.

Primary Outcome

Pregnancies were ascertained during semi-structured follow-up interviews. Follow-up time was calculated as time between enrollment date and the interview date at which pregnancy was reported. Couples were censored after the interview in which they reported a pregnancy or at 18 months of observation. Pregnancy status at the time of interview or at the conclusion of the study was the “event” for the survival analysis. The unit of time for each of these “events” was the time between study enrollment and interview date or conclusion of the study.

Predictors

Demographic characteristics

Female and male age, parity and gravidity were determined from baseline questionnaires and the medical record

Fertility characteristics

Duration of infertility was calculated as time between the date the couple began trying to achieve pregnancy and the date of the first interview. Etiology of infertility was obtained through medical record abstraction at the end of the 18-month observation period. Male factor diagnoses were combined into one group (“male factor”) while female infertility diagnoses were categorized as tubal (e.g. damaged, blocked, removed Fallopian tubes; ectopic pregnancy; tubal adhesions), uterine (e.g. intrauterine adhesions, fibroids), ovarian (e.g. diminished ovarian reserve, “advanced maternal age,” elevated FSH, premature ovarian failure), or ovulatory (e.g. amenorrhea, luteal phase defect, polycystic ovarian disease). A diagnosis of male factor infertility was determined from a review of the medical record. Diagnoses were further classified into 4 groups: no identified infertility etiology, male factor only, female factor only, or both male and female factors. No identified infertility etiology was chosen as the analytic reference group to maximize the clinical applicability and interpretability of these results.

Infertility treatment(s) used was (were) determined through medical record review and interviews in which participants were asked about treatments used since the previous interview. Couples were classified into one of four treatment groups based on the highest treatment intensity used during the study period: No cycle-based treatment (NO_TX), ovulation induction without IUI (MEDS), IUI with or without ovulation induction (IUI), and IVF with or without preceding IUI (IVF). Couples using donor egg were excluded from the IVF group. The number of treatment cycles used for each cycle-based treatment pathway was tabulated.

Data Analysis

Kaplan-Meier analysis estimated the cumulative probability of ongoing pregnancy after study enrollment (23). The log-rank test assessed bivariate differences between subject characteristics and the likelihood of pregnancy. Pair-wise and overall p-values are reported for each covariate. Multivariable Cox proportional hazards regression analysis estimated the effect of treatment type and number of treatment cycles on the probability of pregnancy after adjustment for age, parity, and infertility duration and diagnosis. We report Hazard Ratios (HR) with 95% confidence intervals to estimate the association between these subject characteristics and the monthly probability of pregnancy. Proportional hazards assumptions were assessed by careful visual inspection of log/antilog survival curves to assess for marked divergences, convergences, or multiple crossings of survival curves. We also applied the Schoenfeld test to all variables in the regression models. All variables listed above met the proportional hazards assumptions.

Initial multivariable Cox proportional hazards models were developed with predictor variables selected a priori. For the three models comparing the number of MEDS, IUI, or IVF cycles to NO_TX, covariates included: male and female age, male factor infertility, female diagnosis, female parity, fertility treatments prior to study enrollment, and infertility duration. The model evaluating the effect of IUI also adjusted for the number of medication-only cycles. The multivariable model characterizing IVF adjusted for the number of medication-only and IUI cycles. Statistical significance was set at p<0.05; all tests were 2-sided. STATA 10 (Statacorp, College Station, TX, USA) was used for all analysis.

Results

Among 408 participants, mean female and male ages were 35.6 (SD 4.7) and 36.9 (SD 5.5), respectively. Female factor infertility was found most commonly (58%, Table 1). Mean infertility duration was 2.1 years (SD 1.7). Fertility treatment prior to enrollment in the study was relatively common and included clomiphene (65%), gonadatropins (25%), and IUI (36%). Female age (p = 0.08), male age (p = 0.38), having prior children (p = 0.10), using oral medications before study entry (p=0.06), duration of infertility (p = 0.39), and uterine factor infertility (p = 0.28) were not significantly associated with treatments used during the study. However, couples who used injection medications (p = 0.01) or IUI (p < 0.001) prior to study entry, overall couple infertility etiology (p = 0.002), tubal factor infertility (p = 0.02), ovarian factor infertility (p = 0.03), and ovulatory dysfunction (p < .001) were significantly associated with subsequent treatment type. During the study period, treatments used were IVF (53%), IUI (22%), and MEDS (4%); 21% used NO_TX. Most couples used three or fewer treatment cycles (47%); however, a substantial minority used 4+ cycles (32%). The cumulative pregnancy rate was lowest for couples using NO_TX (28%) compared to 50–70% for IUI, and 35–60% for IVF (Table 2).

Table 1.

Age and Fertility Characteristics of Cohort (N=408)

N %
Female age <35 162 39.8
35–39 156 38.3
≥40 89 21.9
Male Age <35 126 30.9
35–39 129 31.6
≥40 101 24.8
Unknown 52 12.8
Prior offspring 97 23.9
Prior pregnancy 0 193 49.6
1 92 23.7
2 64 16.5
3+ 40 10.3
Prior fertility treatment Oral medications 251 65.4
Injectable medications 94 24.5
IUI 139 36.2
Duration of infertility < 1 year 69 16.9
1–2 years 158 38.7
≥ 2 years 152 37.3
Unknown 29 7.1
Couple fertility diagnosis Male and female factors 123 30.2
Female factor only 238 58.3
Male factor only 29 7.1
No known infertility factors 18 4.4
Female diagnosis Tubal 57 14.0
Uterine 48 11.8
Ovarian 155 38.0
Ovulatory 109 26.7
Donor Egg 24 5.9
Number of cycles 0 86 21.1
1 68 16.7
2 65 15.9
3 57 14.0
4 38 9.3
5 28 6.9
6 27 6.6
7+ 39 9.6
Highest intensity of fertility treatment No cycle-based treatment 86 21.1
Medications only 15 3.7
Intrauterine insemination only 91 22.3
In vitro fertilization 216 52.9

Table 2.

Cumulative Pregnancy Rate at Eighteen Months by Treatment Type and by Couples Using a Given Number of Cycles

Number of Cycles N Cumulative Pregnancy Rate* 95% CI
No Cycle-Based Treatment 86 0.28 0.20 0.39
Medications Only
 1–2 cycles 9 0.85 0.54 0.99
 3+ cycles 6 0.29 0.08 0.74
Intrauterine Insemination
 1 cycle 33 0.71 0.55 0.85
 2 cycles 23 0.57 0.38 0.77
 3 cycles 15 0.71 0.48 0.90
 4+ cycles 20 0.50 0.28 0.76
In-Vitro Fertilization
 1 cycle 83 0.59 0.48 0.71
 2 cycles 57 0.57 0.44 0.70
 3+ cycles 52 0.35 0.23 0.50
*

Cumulative pregnancy rates for population of couples utilizing each number of cycles. Couples using donor egg were excluded from IVF cycles.

Women > age 40 were 71% less likely to achieve pregnancy (HR 0.29 [95% CI 0.18–0.45]) compared to women < age 35 (Table 3). Couples with men aged 35–39 and those > age 40 were 30% (HR 0.70, [0.51–0.97]) and 44% (HR 0.56 [0.39–0.81]), respectively, less likely to achieve pregnancy relative to men < age 35. Relative to couples with no known infertility factors, couples with isolated female factor infertility were 55% less likely to achieve pregnancy (HR 0.45 [0.3–0.8]). Those with both male and female factors were 64% less likely to become pregnant (HR 0.36 [0.20–0.64]). Isolated male factor infertility was associated with a non-statistically significant 33% reduction in the probability of achieving a pregnancy.

Table 3.

Unadjusted Relationship between Age, Fertility Characteristics, Treatments, and the Monthly Likelihood of Achieving a Pregnancy

N HR 95% CI P-Value Overall P-Value
Female age <35 162 1.00 ref ref
35–39 156 0.78 0.58 1.03 0.08
≥ 40 89 0.29 0.18 0.45 <0.001 <0.001
Male age <35 126 1.00 ref ref
35–39 129 0.70 0.51 0.97 0.03
≥40 101 0.56 0.39 0.81 <0.001
Unknown 52 0.53 0.33 0.84 0.01 0.004
Prior children No 309 1.00 ref ref
Yes 97 1.10 0.81 1.50 0.53 0.53
Prior pregnancy 0 193 1.00 ref ref
1 92 1.15 .82 1.62 .40
2 64 1.22 .83 1.81 .30
3+ 40 .81 .49 1.32 .39 .41
Prior fertility treatment Oral medications 251 1.05 0.79 1.40 0.74 0.74
Injectable medications 94 1.26 0.92 1.71 0.15 0.15
IUI 139 1.04 0.79 1.40 0.74 0.74
Duration of infertility < 1 year 69 1.00 ref ref
1–2 years 158 1.30 0.88 1.92 0.18
≥ 2 years 152 0.89 0.59 1.33 0.56
Unknown 29 0.69 0.35 1.37 0.29 0.03
Couple fertility diagnosis No known infertility factors 18 1.00 ref ref
Male factor only 29 0.67 0.34 1.34 0.26
Female factor only 238 0.45 0.26 0.78 0.01
Male and female factors 123 0.36 0.20 0.64 <0.001 0.002
Female diagnosis Tubal 57 0.94 0.64 1.40 0.77 0.77
Uterine 48 0.77 0.49 1.21 0.26 0.26
Ovarian 155 0.60 0.45 0.81 <0.001 <0.001
Ovulatory 109 1.29 0.96 1.73 0.09 0.09
Any cycle-based treatment No 86 1.00 ref ref
Yes 322 2.28 1.51 3.43 <0.001 <0.001
Medications only No cycle based treatment 86 1.00 ref ref
1–2 cycles 9 5.39 2.39 12.16 <0.001
3+ cycles 6 0.87 0.20 3.67 0.85 <0.001
Intrauterine insemination only No cycle based treatment 86 1.00 ref ref
1 cycle 33 3.14 1.81 5.44 <0.001
2 cycles 23 2.93 1.52 5.62 <0.001
3 cycles 15 3.12 1.53 6.34 <0.001
4+ cycles 20 1.63 0.79 3.39 0.19 <0.001
In vitro fertilization only No cycle based treatment 86 1.00 ref ref
1 cycle 83 2.46 1.52 3.98 <0.001
2 cycles 57 2.45 1.47 4.07 0.001
3+ cycles 52 1.49 0.85 2.59 0.16 <0.001

In unadjusted analyses, cycle-based treatment was associated with a 2.3-fold increase in monthly pregnancy rates (HR 2.3 [1.5–3.4], Table 3) compared to NO_TX. Using MEDS was more effective than NO_TX for 1–2 cycles (HR 5.39 [2.4–12.2]), but not for 3+ cycles (HR 0.9 [0.2–3.7]). IUI was more effective than NO_TX for one (HR 3.1 [1.8–5.4]), two (HR 2.9 [1.5–5.6]), and three (HR 3.1 [1.5–6.3]) cycles; however, no statistical improvement in pregnancy rate occurred after 4+ cycles. IVF was significantly more effective than NO_TX for one (HR 2.5 [1.5–4.0]), two (HR 2.5 [1.5–4.1]), and 3+ cycles (HR 1.5 [0.9–2.6]); however, this difference was not statistically significance for couples using3+ cycles.

After adjustment for infertility diagnosis, male and female age, parity, infertility duration, and fertility treatment used before study enrollment, the MEDS group was associated with a significant increase in the monthly incidence of pregnancy after 1–2 cycles (HR 4.7 [1.3–16.6]; Table 4), but not for 3+ cycles (HR 0.6 [0.1–3.2]). Of the covariates examined, only female age >40 was independently associated with lower success rates (HR 0.06 [0.01–0.4]).

Table 4.

Multivariable Relationship between Number of Fertility Treatments and the Monthly Likelihood of Achieving a Pregnancy

Medication Use* N HR 95% CI P-Value Overall P-Value
Number of cycles No cycle based treatment 86 1.00 ref ref
1–2 cycles 9 4.71 1.34 16.64 0.02
3+ cycles 6 0.63 0.13 3.18 0.58 0.03

Intrauterine Insemination Use**

Number of cycles No cycle based treatment 86 1.00 ref ref
1 cycle 21 2.85 1.40 5.82 0.004
2 cycles 23 2.03 0.93 4.47 0.08
3 cycles 15 4.47 1.83 10.9 0.001
4+ cycles 32 1.04 0.41 2.62 0.94 0.006

In-Vitro Fertilization Use***

Number of cycles No cycle based treatment 86 1.00 ref ref
1 cycle 83 2.78 1.48 5.24 0.001
2 cycles 57 2.21 1.19 4.11 0.01
3+ cycles 52 1.25 0.65 2.41 0.51 0.003
*

Adjusted for male and female age, male factor infertility, female diagnosis (i.e. tubal, uterine, ovarian, ovulatory), parity, prior fertility treatments and duration of infertility. Of note, only female age over 40 compared to under 35 (HR 0.06, p=0.005) was independently associated with lower pregnancy success.

**

Adjusted for male and female age, male factor infertility, female diagnosis (i.e. tubal, uterine, ovarian, ovulatory), parity, number of failed medication cycles, prior fertility treatments (i.e. prior medication use or intrauterine insemination) before study entry, and duration of infertility. Of note, female age over 40 (HR .11, p = 0.001), tubal factor (HR 0.29, p=0.04), and male factor (HR 0.57, p=0.05) were independently associated with lower success.

***

Adjusted for male and female age, male factor infertility, female diagnosis (i.e. tubal, uterine, ovarian, ovulatory), parity, prior fertility treatments (i.e. prior medication use or intrauterine insemination) before study entry, number of failed medication and IUI cycles during the study, and duration of infertility. Couples using donor egg were excluded from IVF cycles. Of note, female age over 40 (HR 0.35, p=0.01) and having a previous child (HR 1.59, p = 0.04) were independently associated with pregnancy success.

A similar pattern was seen for IUI cycles after multivariable adjustment for infertility diagnosis, male and female age, parity, infertility duration, fertility treatment used before study enrollment, and number of failed medication cycles during the study. IUI was better than NO_TX for one (HR 2.85 [1.4–5.8]), two (HR 2.0 [0.9–4.5]), and three (HR 4.5 [1.8–10.9]) cycles; however, this difference was not statistically significance for couples using two cycles. Couples using 4+ cycles were no more likely than the NO_TX group to achieve pregnancy (HR 1.0 [0.4–2.6]). Female age >40 (HR 0.11 [0.03–0.3] tubal diagnosis (HR 0.3 [0.09–0.9]), and male factor infertility (HR 0.57 [0.3–1.0]) were independently associated with lower success rates.

After multivariable adjustment, IVF was more effective than NO_TX for couples using one (HR 2.8 [1.5–5.2]) and two cycles (HR 2.2 [1.2–4.1]). While IVF was associated with a 25% increase in the monthly pregnancy rate for couples using 3+ cycles (HR 1.25 [0.7–2.4]), this increase was not statistically significant. Female age >40 (HR 0.35 [0.2–0.8]) was independently associated with a 65% reduction in the likelihood of achieving a pregnancy relative to couples with women under 35. When the female partner had one or more prior children, her likelihood of achieving a pregnancy also increased significantly (HR 1.6 [1.0–2.5]).

Discussion

To the best of our knowledge, no study in the United States has prospectively determined the incidence of pregnancy among a population of couples seeking infertility consultation who utilized a wide range of fertility options, nor has any prospective study determined the optimal length of time to pursue particular treatment options before considering higher intensity treatment. Data from this study demonstrated a decreasing efficacy of cycle-based infertility treatment over the course of 18 months of follow-up.

Compared to no treatment, the first several cycles of medications, IUI, or IVF increased pregnancy rates. However, there was a point of diminishing returns where additional cycles did not significantly alter pregnancy rates. After adjustment for common infertility risk factors, couples using medications only for one or two cycles had a five-fold higher average monthly pregnancy rate than who did not use cycle-based treatment. This benefit did not persist for couples using three or more such cycles. Couples using IUI had higher pregnancy rates through three cycles but not for 4+ cycles. IVF was associated with more than a doubling in the probability of achieving pregnancy for couples using one or two cycles. Using 3+ cycles of IVF was associated with a non-statistically significant 25% increase in pregnancy rates, supporting a recent U.S. retrospective cohort study that found that pregnancy rates decline with increasing treatment time (12).

The decline in treatment efficacy with repeated cycles was most pronounced for couples using medications or IUI alone. This rapid decline in treatment efficacy over time may reflect more severe underlying fertility problems in couples not achieving pregnancy within the first few cycles of treatment. For IVF, a persistent benefit cannot be ruled out from our data. Estimates from the SART Writing Group (14) demonstrate a cumulative IVF pregnancy rate of ~50% after 3 cycles, increasing to only 56% after 9+ cycles, with a slow decline in per-cycle IVF pregnancy rates from 30% for couples using one cycle to 20% for couples using 9+ cycles.

The choice to forego cycle-based treatment appears to have merits for a short time. An earlier cohort study of 873 untreated infertile couples demonstrated an annual pregnancy rate of ~14% (24), slightly lower than the 22% observed in our no-cycle-based treatment population. The higher rate in our study could be explained by the utilization of non-cycle based treatments, differences in the study population, or statistical variation. A recent large prospective study of couples in the Netherlands demonstrated that 9% of infertile women on an IVF/ICSI waiting list achieved a treatment-independent pregnancy within one year of observation (25). These studies did not characterize the rate at which couples achieved pregnancy. We found that the pregnancy rate was similar between treated and untreated patients for the first 4–6 months, after which time the pregnancy rate began to flatten for the no-cycle-based treatment group and increase for the cycle-based treatment patients. While using no cycle-based treatment may be a reasonable initial approach, particularly for women <age 35, if the couple’s goal continues to be achieving a pregnancy, they may be better served by considering use of cycle-based treatments after six months.

Few prospective cohorts have evaluated the effect of risk factors among a general fertility population. Increasing female age was consistently associated with lower pregnancy rates, while male age became statistically insignificant after adjustment for female age. This likely represents the observation that men and women, on average, marry at similar ages and that female age represents the stronger influence on fertility. Fertility diagnosis was also an important predictor of pregnancy. Couples with no known infertility factors were more likely to achieve a pregnancy, while female factor infertility, particularly ovarian dysfunction (e.g., diminished ovarian reserve), was a significant factor in lower pregnancy success. Tubal infertility was not associated with lower pregnancy success, probably because these couples were more likely to undergo IVF.

We acknowledge that some couples pursued multiple cycles of cycle-based therapy early in observation while others pursued treatment later, leading to variations in time to pregnancy not due to subject characteristics or treatments.. Despite this limitation, a real time cumulative pregnancy rate was calculated as suggested by Daya (23), who advocated this approach as the optimal technique. It was not possible to calculate per-cycle success rates for treatment given the fact of follow-up at 4, 10, and 18 months. Finally, because the sample size for each treatment group was relatively small, extensive inference was not possible for many of these subgroups. We suspect that future, larger prospective studies will demonstrate a similar pattern of decreasing treatment effectiveness but perhaps with different cutoff points for treatment efficacy.

Nevertheless, this study is the largest prospective study performed in the United States comparing outcomes of cycle-based fertility treatments to no-cycle-based treatments. Losses to follow-up were very small, suggesting that informative censoring (e.g. drop-out due to poor prognostic findings or psychological distress) did not threaten the internal validity of this study. Finally, using couple-based (rather than cycle-based) data provides information that may be more relevant to counseling patients considering different treatment pathways.

Our data suggest that while cycle-based fertility treatments offer clinically significant increases in the pregnancy rate; this benefit does not persist indefinitely. Couples not achieving a pregnancy on medications alone after two cycles or IUI after three cycles may be best counseled to pursue a higher level of infertility treatment, consistent with recent work by Reindollar (13). Those failing IVF after two cycles may want to consider other treatment strategies such as donor sperm, donor egg, or further modifications in the IVF or ICSI protocol as additional cycles appear less likely to increase reproductive success as much as earlier cycles.

Acknowledgments

Support: Grant HD37074 from the National Institute for Child Health and Human Development (NICHD/NIH)

We would like to acknowledge the additional members of the Infertility Outcomes Program Project Group: Nancy Adler, PhD; Mary Croughan, PhD; Lauri Pasch, PhD; Steven Gregorich, PhD; and Jonathan Showstack, MPH, PhD.

Footnotes

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References

  • 1.Chandra A, Stephen EH. Impaired fecundity in the United States: 1982–1995. Fam Plann Perspect. 1998;30:34–42. [PubMed] [Google Scholar]
  • 2.Stephen EH, Chandra A. Updated projections of infertility in the United States: 1995–2025. Fertility and Sterility. 1998;70:30–4. doi: 10.1016/s0015-0282(98)00103-4. [DOI] [PubMed] [Google Scholar]
  • 3.Oakley L, Doyle P, Maconochie N. Lifetime prevalence of infertility and infertility treatment in the UK: results from a population-based survey of reproduction. Hum Reprod. 2008;23:447–50. doi: 10.1093/humrep/dem369. [DOI] [PubMed] [Google Scholar]
  • 4.Stephen EH, Chandra A. Declining estimates of infertility in the United States: 1982–2002. Fertil Steril. 2006;86:516–23. doi: 10.1016/j.fertnstert.2006.02.129. [DOI] [PubMed] [Google Scholar]
  • 5.Wyshak G. Infertility in American college alumnae. Int J Gynaecol Obstet. 2001;73:237–42. doi: 10.1016/s0020-7292(01)00381-2. [DOI] [PubMed] [Google Scholar]
  • 6.Hughes EG. The effectiveness of ovulation induction and intrauterine insemination in the treatment of persistent infertility: a meta-analysis. Hum Reprod. 1997;12:1865–72. doi: 10.1093/humrep/12.9.1865. [DOI] [PubMed] [Google Scholar]
  • 7.Guzick DS, Carson SA, Coutifaris C, Overstreet JW, Factor-Litvak P, Steinkampf MP, et al. Efficacy of superovulation and intrauterine insemination in the treatment of infertility. National Cooperative Reproductive Medicine Network. N Engl J Med. 1999;340:177–83. doi: 10.1056/NEJM199901213400302. [DOI] [PubMed] [Google Scholar]
  • 8.Dankert T, Kremer JA, Cohlen BJ, Hamilton CJ, Pasker-de Jong PC, Straatman H, et al. A randomized clinical trial of clomiphene citrate versus low dose recombinant FSH for ovarian hyperstimulation in intrauterine insemination cycles for unexplained and male subfertility. Hum Reprod. 2007;22:792–7. doi: 10.1093/humrep/del441. [DOI] [PubMed] [Google Scholar]
  • 9.Goverde AJ, McDonnell J, Vermeiden JP, Schats R, Rutten FF, Schoemaker J. Intrauterine insemination or in-vitro fertilisation in idiopathic subfertility and male subfertility: a randomised trial and cost-effectiveness analysis. Lancet. 2000;355:13–8. doi: 10.1016/S0140-6736(99)04002-7. [DOI] [PubMed] [Google Scholar]
  • 10.Hughes EG, Beecroft ML, Wilkie V, Burville L, Claman P, Tummon I, et al. A multicentre randomized controlled trial of expectant management versus IVF in women with Fallopian tube patency. Hum Reprod. 2004;19:1105–9. doi: 10.1093/humrep/deh209. [DOI] [PubMed] [Google Scholar]
  • 11.Donderwinkel PF, van der Vaart H, Wolters VM, Simons AH, Kroon G, Heineman MJ. Treatment of patients with long-standing unexplained subfertility with in vitro fertilization. Fertil Steril. 2000;73:334–7. doi: 10.1016/s0015-0282(99)00518-x. [DOI] [PubMed] [Google Scholar]
  • 12.Haagen EC, Hermens RP, Nelen WL, Braat DD, Grol RP, Kremer JA. Subfertility guidelines in Europe: the quantity and quality of intrauterine insemination guidelines. Hum Reprod. 2006;21:2103–9. doi: 10.1093/humrep/del100. [DOI] [PubMed] [Google Scholar]
  • 13.Reindollar RH, Regan MM, Neumann PJ, Levine BS, Thornton KL, Alper MM, et al. A randomized clinical trial to evaluate optimal treatment for unexplained infertility: the fast track and standard treatment (FASTT) trial. Fertil Steril. 2009 doi: 10.1016/j.fertnstert.2009.04.022. S0015-0282(09)00866-8 [pii] [DOI] [PubMed] [Google Scholar]
  • 14.Stern JE, Brown MB, Luke B, Wantman E, Lederman A, Missmer SA, et al. Calculating cumulative live-birth rates from linked cycles of assisted reproductive technology (ART): data from the Massachusetts SART CORS. Fertil Steril. 2009 doi: 10.1016/j.fertnstert.2009.05.052. S0015-0282(09)01244-8 [pii] [DOI] [PubMed] [Google Scholar]
  • 15.Malizia BA, Hacker MR, Penzias AS. Cumulative live-birth rates after in vitro fertilization. N Engl J Med. 2009;360:236–43. doi: 10.1056/NEJMoa0803072. [DOI] [PubMed] [Google Scholar]
  • 16.van der Steeg JW, Steures P, Eijkemans MJ, Habbema JD, Hompes PG, Broekmans FJ, et al. Predictive value and clinical impact of Basal follicle-stimulating hormone in subfertile, ovulatory women. J Clin Endocrinol Metab. 2007;92:2163–8. doi: 10.1210/jc.2006-2399. [DOI] [PubMed] [Google Scholar]
  • 17.Basso O, Olsen J. Subfecundity and neonatal mortality: longitudinal study within the Danish national birth cohort. BMJ. 2005;330:393–4. doi: 10.1136/bmj.38336.616806.8F. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Berube S, Marcoux S, Langevin M, Maheux R. Fecundity of infertile women with minimal or mild endometriosis and women with unexplained infertility. The Canadian Collaborative Group on Endometriosis. Fertil Steril. 1998;69:1034–41. doi: 10.1016/s0015-0282(98)00081-8. [DOI] [PubMed] [Google Scholar]
  • 19.Matorras R, Rodriguez F, Gutierrez de Teran G, Pijoan JI, Ramon O, Rodriguez-Escudero FJ. Endometriosis and spontaneous abortion rate: a cohort study in infertile women. Eur J Obstet Gynecol Reprod Biol. 1998;77:101–5. doi: 10.1016/s0301-2115(97)00181-4. [DOI] [PubMed] [Google Scholar]
  • 20.van der Steeg JW, Steures P, Eijkemans MJ, Habbema JD, Hompes PG, Michgelsen HW, et al. Predictive value of pregnancy history in subfertile couples: results from a nationwide cohort study in the Netherlands. Fertil Steril. 2008;90:521–7. doi: 10.1016/j.fertnstert.2007.07.1301. [DOI] [PubMed] [Google Scholar]
  • 21.Duran EH, Morshedi M, Taylor S, Oehninger S. Sperm DNA quality predicts intrauterine insemination outcome: a prospective cohort study. Hum Reprod. 2002;17:3122–8. doi: 10.1093/humrep/17.12.3122. [DOI] [PubMed] [Google Scholar]
  • 22.van Montfrans JM, Hoek A, van Hooff MH, de Koning CH, Tonch N, Lambalk CB. Predictive value of basal follicle-stimulating hormone concentrations in a general subfertility population. Fertil Steril. 2000;74:97–103. doi: 10.1016/s0015-0282(00)00560-4. [DOI] [PubMed] [Google Scholar]
  • 23.Daya S. Life table (survival) analysis to generate cumulative pregnancy rates in assisted reproduction: are we overestimating our success rates? Hum Reprod. 2005;20:1135–43. doi: 10.1093/humrep/deh889. [DOI] [PubMed] [Google Scholar]
  • 24.Collins JA, Burrows EA, Wilan AR. The prognosis for live birth among untreated infertile couples. Fertil Steril. 1995;64:22–8. [PubMed] [Google Scholar]
  • 25.Eijkemans MJ, Lintsen AM, Hunault CC, Bouwmans CA, Hakkaart L, Braat DD, et al. Pregnancy chances on an IVF/ICSI waiting list: a national prospective cohort study. Hum Reprod. 2008;23:1627–32. doi: 10.1093/humrep/den132. [DOI] [PubMed] [Google Scholar]

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