Age-related natural fertility outcomes in women over 35 years: a systematic review and individual participant data meta-analysis

Full text

Age-related natural fertility outcomes
in women over 35 years: a systematic
review and individual participant data
meta-analysis
S.J. Chua
1,
*, N.A. Danhof
2
, M.H. Mochtar
2
, M. van Wely
2
,
D.J. McLernon
3
, I. Custers
2
, E. Lee
4
, K. Dreyer
5
, D.J. Cahill
6
,
W.R. Gillett
7
, A. Righarts
7
, A. Strandell
8
, T. Rantsi
9
, L. Schmidt
10
,
M.J.C. Eijkemans
11
, B.W.J. Mol
12,13
, and R. van Eekelen
2
1
University of Adelaide, Adelaide, South Australia 5000, Australia
2
Department of Obstetrics and Gynaecology, Center for Reproductive
Medicine, Academic Medical Center, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands
3
Medical Statistics Team, Institute
of Applied Health Sciences, University of Aberdeen, Aberdeen AB24 3FX, UK
4
Western Ultrasound for Women, West Leederville,
Western Australia 6007, Australia
5
Department of Reproductive Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV
Amsterdam, The Netherlands
6
Academic Unit of Obstetrics and Gynaecology, University of Bristol, St Michael’s Hospital, Bristol BS8
1TH, UK
7
Women’s and Children’s Health, Dunedin School of Medicine, The University of Otago, Dunedin 9016, New Zealand
8
Department of Obstetrics and Gynecology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg and
Sahlgrenska University Hospital, 413 45 Go¨teborg, Sweden
9
Department of Obstetrics and Gynecology, University of Helsinki and
Helsinki University Hospital, FI-00029 HUS, Helsinki, Finland
10
Department of Public Health, University of Copenhagen, 1014
Copenhagen K, Denmark
11
Department of Biostatistics and Research Support, Julius Centre, University Medical Centre, 3584 CX
Utrecht, The Netherlands
12
Discipline of Obstetrics and Gynaecology, Robinson Research Institute, University of Adelaide, South
Australia 5006, Australia
13
Department of Obstetrics and Gynaecology, Monash Medical Centre, Monash Health and Monash University,
Clayton 3800, Victoria, Australia
*Correspondence address. University of Adelaide, North Terrace, South Australia 5000, Australia. E-mail: chua.sujen@gmail.com
Submitted on December 31, 2019; resubmitted on April 30, 2020; editorial decision on May 9, 2020
STUDY QUESTION: What is the rate of natural conception leading to ongoing pregnancy or livebirth over 6–12 months for infertile
women of age 35 years?
SUMMARY ANSWER: Natural conception rates were still clinically relevant in women aged 35 years and above and were significantly
higher in women with unexplained infertility compared to those with other diagnoses.
WHAT IS KNOWN ALREADY: In recent years, increasing numbers of women have attempted to conceive at a later age, resulting in a
commensurate increase in the need for ART. However, there is a lack of data on natural fertility outcomes (i.e. no interventions) in
women with increasing age.
STUDY DESIGN, SIZE, DURATION: A systematic review with individual participant data (IPD) meta-analysis was carried out.
PubMed, MEDLINE, EMBASE, the Cochrane Library, clinicaltrials.gov were searched until 1 July 2018 including search terms ‘fertility ser-
vice’, ‘waiting list’, ‘treatment-independent’ and ‘spontaneous conception’. Language restrictions were not imposed.
PARTICIPANTS/MATERIALS, SETTING, METHODS: Inclusion criteria were studies (at least partly) reporting on infertile couples
with female partner of age 35 years who attended fertility services, underwent fertility workup (e.g. history, semen analysis, tubal status
and ovulation status) and were exposed to natural conception (e.g. independent of treatment such as IVF, ovulation induction and tubal
surgery). Studies that exclusively studied only one infertility diagnosis, without including other women presenting to infertility services for
other causes of infertility, were excluded. For studies that met the inclusion criteria, study authors were contacted to provide IPD, after
which fertility outcomes for women of age 35 years were retrieved. Time to pregnancy or livebirth and the effect of increasing age on
fertility outcomes after adjustment for other prognostic factors were analysed. Quality of studies was graded with the Newcastle–Ottawa
Scale (non-randomised controlled trials (RCTs)) or the Cochrane Risk of Bias tool (for RCTs).
V
CThe Author(s) 2020. Published by Oxford University Press on behalf of European Society of Human Reproduction and Embryology. All rights reserved.
For permissions, please email: journals.permissions@oup.com
Human Reproduction, pp. 1–14, 2020
doi:10.1093/humrep/deaa129
ORIGINAL ARTICLE Infertility
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MAIN RESULTS AND THE ROLE OF CHANCE: We included nine studies (seven cohort studies and two RCTs) (n¼4379 women
of at least age 35 years), with the observed composite primary outcome of ongoing pregnancy or livebirth occurring in 429 women (9.8%)
over a median follow-up of 5 months (25th to 75th percentile: 2.5–8.5 months). Studies were of moderate to high quality. The probability
of natural conception significantly decreased with any diagnosis of infertility, when compared with unexplained infertility. We found
non-linear effects of female age and duration of infertility on ongoing pregnancy and tabulated the predicted probabilities for unexplained
infertile women aged 35–42 years with either primary or secondary infertility and with a duration of infertility from 1 to 6 years. For a
35-year-old woman with 2 years of primary unexplained infertility, the predicted probability of natural conception leading to ongoing
pregnancy or livebirth was 0.15 (95% CI 0.11–0.19) after 6 months and 0.24 (95% CI 0.17–0.30) after 12 months. For a 42-year-old
woman, this decreased to 0.08 (95% CI 0.04–0.11) after 6 months and 0.13 (95% CI 0.07–0.18) after 12 months.
LIMITATIONS, REASONS FOR CAUTION: In the studies selected, there were different study designs, recruitment strategies in different
centres, protocols and countries and different methods of assessment of infertility. Data were limited for women above the age of 40 years.
WIDER IMPLICATIONS OF THE FINDINGS: Women attending fertility services should be encouraged to pursue natural conception
while waiting for treatment to commence and after treatment if it is unsuccessful. Our results may aid in counselling women, and, in partic-
ular, for those with unexplained infertility.
STUDY FUNDING/COMPETING INTEREST(S): S.J.C. received funding from the University of Adelaide Summer Research
Scholarship. B.W.M. is supported by a NHMRC Investigator grant (GNT1176437), B.W.M. reports consultancy for ObsEva, Merck, Merck
KGaA, iGenomix and Guerbet. B.W.M. reports research support by Merck and Guerbet.
PROSPERO REGISTRATION NUMBER: CRD42018096552.
Key words: infertility / IVF / ART / waiting lists / time factors / maternal age / time-to-pregnancy / middle-age / aging
Introduction
Sharp declines in fertility occur with increasing female age. These dra-
matic changes are generally in conjunction with a decreasing ovarian
reserve. The mechanisms behind this deterioration in follicle number
and quality, and menstrual cycle changes have yet to be precisely eluci-
dated (Broekmans et al.,2009). In addition, there appears to be con-
siderable natural variation in this decline in fertility, which has been
shown to start at different female ages (De Brucker et al., 2013).
Current trends in high-income societies indicate a postponement of
childbearing in association with accessibility to contraception, eco-
nomic prosperity, increased education and participation of women in
the workforce (Leridon, 2006;Max Planck Institute for Demographic
Research (Germany) and Vienna Institute of Demography (Austria),
2019). Such delays in childbearing naturally result in a heightened aver-
age age of first attempt at conception, a proportional increase in
women above the age of 30 years having their first child and higher
failure rates of natural conception (Lutz et al.,2003). The follow-
through effect can be observed in the disproportionate use of fertility
services among older women (Adamson et al., 2018;Centers for
Disease Control and Prevention ASfRM and Society for Assisted
Reproductive Technology, 2018;Fitzgerald et al., 2019).
Along a similar vein, since the first successful IVF cycle for tubal in-
fertility in 1978, indications for treatment have expanded to include
women of advanced age with unexplained infertility (Steptoe and
Edwards, 1978;Adamson et al., 2018;Centers for Disease Control
and Prevention ASfRM and Society for Assisted Reproductive
Technology, 2018;Fitzgerald et al., 2019). Controversies arise in the
management of these women as IVF success rates are age-dependent,
and the rate of maternal and foetal adverse events also escalates with
increasing age (Adamson et al.,2018;Centers for Disease Control and
Prevention ASfRM and Society for Assisted Reproductive Technology,
2018;Fitzgerald et al., 2019). However, given the accelerated decline
in fecundity in women over the age of 30 years, delaying ART in
favour of pursuing natural conception may result in time-sensitive irre-
versible losses of ovarian reserve, which further jeopardises fertility
outcomes (Habbema et al.,2015). This is the dilemma of female age
in managing infertile couples (Eshre Capri Workshop Group, 2017).
Data on natural fertility outcomes (i.e. no interventions) with in-
creasing age are required in order to empower women to make in-
formed choices when deciding on fertility treatments. The only
available data at present are derived from historical non-contraceptive
natural fertility studies from the late 20th century and it is unknown
whether such fertility outcomes are applicable to women of the 21st
century (Henry, 1965;Leridon, 1977;Eijkemans et al., 2014).
Individual participant data (IPD) meta-analysis is a powerful modern
tool allowing for the extraction, combination and analysis of data from
clinical studies. Such an approach is suited to investigating natural fertil-
ity outcomes for women of older reproductive age since individual
study datasets are generally too small to make accurate predictions for
this subgroup of women.
We aimed to answer the following questions using IPD meta-analysis:
•What is the rate of natural conception leading to livebirth over 6–
12 months for infertile women of age 35 years?
•What are the factors affecting time to conception leading to
livebirth?
Materials and methods
Criteria for considering studies in this
review
Participants.
IPD of studies reporting (fully or partially) on women aged 35 years
attending fertility services. Subfertility was defined as ‘a disease charac-
terised by the failure to establish a clinical pregnancy after 12 months
2Chua et al.
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of regular, unprotected sexual intercourse or due to an impairment of
a person’s capacity to reproduce either as an individual or with his/
her partner’ (Zegers-Hochschild et al.,2017).
Types of studies.
The following study designs were eligible: case-control studies, cohort
studies (prospective and retrospective) and randomised controlled tri-
als (RCTs).
Interventions.
Studies reporting on fertility outcomes independent of ART (e.g. IVF,
surgery, tubal catheterisation or ovulation induction) were included.
These included women undergoing a diagnostic fertility work-up,
women on a waiting list for treatment or women who discontinued
treatment. Studies on women undergoing non-artificial interventions
(e.g. timed intercourse, lifestyle advice) were also eligible. Studies only
reporting on fertility outcomes dependent on ART were excluded.
Studies on women that have undergone interventions that have per-
manently altered their reproductive system (e.g. tubal surgery) were
also excluded.
Outcome measures.
The primary outcome measure was a composite of the cumulative
rate of natural conceptions leading to ongoing pregnancy and the cu-
mulative rate of natural conceptions leading to livebirth. This is be-
cause livebirth was not recorded for all women in all cohorts and, in
absence, ongoing pregnancy was used. We refer to this composite
outcome as (natural conception leading to) ongoing pregnancy.
Time to natural conception leading to ongoing pregnancy or livebirth
was calculated from the date of entry to the fertility service (for cohort
studies) or date of randomisation (for RCTs) to last menstrual period
when pregnancy occurred. If last menstrual period was not available,
this was estimated with the assumption of term delivery at 40 weeks
of gestation. In order to extract the treatment-independent time to
natural conception for all cohorts, women were censored at time of
treatment, natural conception or end of follow-up, with censoring at
whichever of these events occurred first.
Ongoing pregnancy was defined as visualisation of foetal heartbeat
by ultrasound after 20 weeks of gestation per woman. In studies defin-
ing ongoing pregnancy as a sonographic foetal heartbeat beyond 8 or
12 weeks, we used that definition. Livebirth was defined as delivery of
at least one live foetus after 20 weeks of gestation per woman. The
occurrence of multiple pregnancies resulting in the birth of more than
one baby was considered a single event.
Other secondary outcomes were clinical pregnancy defined as preg-
nancy diagnosed by ultrasonographic visualisation of one or more ges-
tational sacs or definitive clinical signs of pregnancy, miscarriage
defined as the spontaneous loss of an intra-uterine pregnancy prior to
22 completed weeks of gestational age, ectopic pregnancy defined as a
pregnancy outside the uterine cavity diagnosed by ultrasound, surgical
visualisation or histopathology, and chemical pregnancy defined as
pregnancy diagnosed only by the detection of beta hCG in serum or
urine (Zegers-Hochschild et al.,2017).
The following other factors known to affect natural fertility were
collected: diagnosis, duration of infertility, referral status, BMI, primary
versus secondary infertility, semen characteristics (volume, morphol-
ogy, motility, concentration), cycle length, basal FSH levels, antral
follicle count, anti-Mu¨llerian hormone (AMH), tubal status and semen
status (Bensdorp et al.,2017).
Data collection and analysis
Search strategy.
The following databases were searched to 1.7.2018: PubMed,
MEDLINE, EMBASE, Cochrane Database of Systematic Reviews,
Cochrane Central Register of Controlled Trials (CENTRAL), the
Cochrane Library, clinicaltrials.gov. Relevant reviews and references
lists of included studies were hand searched. The search strategy was
documented in accordance to the Preferred Reporting Items for
Systematic Reviews and Meta-Analyses (PRISMA) statement. Search
terms included ‘fertility service’, ‘waiting list’, ‘treatment-independent’
and ‘spontaneous conception’. Language restriction was not applied.
Studies prior to the year 2000 were excluded on the basis that the
original authors would likely no longer have access to IPD.
Selection of studies.
Two authors (S.J.C. and N.A.D.) independently assessed the included
studies, in order to ascertain eligibility for inclusion, extract outcomes
of interest and determine the quality of studies. In the event of dis-
crepancies, a third author was introduced (B.W.M.) to form a final
decision.
Assessment of risk of bias.
Two authors (S.J.C. and N.A.D.) independently assessed risk of bias of
included studies using the following tools:
•The risk of bias assessment tool developed by the Cochrane
Collaboration for RCTs (Higgins et al., 2011).
•The Newcastle–Ottawa Scale for cohort studies and case-control
studies (Wells et al., 2008).
Disagreements were resolved by discussion and or by input from a
third author (B.W.M.).
Data collection.
Corresponding authors of identified studies were contacted and invited
to provide IPD. Study protocols were obtained.
Analysis.
All IPD for women aged 35 years were combined into a single data-
base, including all available variables corresponding to studied out-
comes (as above). We used a Kaplan–Meier curve to show the
estimated cumulative natural conception rate per infertility diagnosis
group. Cox proportional hazards analysis was conducted to determine
which factors were related to time-to-pregnancy for women aged
35 years. Scaled Schoenfeld residuals were used to check if the esti-
mated effect of covariates were proportional over time (Grambsch
and Therneau, 1994). Restricted cubic spline analysis was used to as-
sess whether there was a linear association between female age as a
continuous variable and natural conception leading to ongoing preg-
nancy or livebirth (Harrell, 2001). The best fit was preferred, judged
by a Wald test for non-linear terms and the lowest Akaike
Information Criterion (Akaike, 2011). If fits were similar, the simplest
model was preferred (i.e. the model with the lowest number of knots
or parameters estimated).
Natural fertility outcomes in women aged over 35 years 3
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In the case where a non-linear association was discovered, the effect
of different female ages on livebirth rates, ranging from 35 to 43 years,
was visualised in a plot. Using the model with the best fit, absolute
chances of natural conception over 6 and 12 months were tabulated
for all combinations of patient characteristics.
Sensitivity analyses.
Not all studies had collected data on all covariates, most notably FSH,
AMH and semen parameters. Only when data were available from
multiple studies, we considered these detailed covariates for analysis
or to use in imputation. Otherwise, analysis was restricted to covari-
ates that were available in all studies. To account for the fact that we
combined multiple studies using separate study designs, protocols and
recruitment in different countries, we used a gamma frailty random
effects Cox model. Using this model, we calculated the absolute chan-
ces of natural conception over 6 or 12 months and presented these
next to the tabulated chances from the Cox model without random
effects.
Missing data.
Depending on the extent of missing data on relevant covariates, we
used multiple or single imputation.
Software.
Data were prepared in SPSS Statistics (IBM, version 24, Armonk, NY,
USA) and Microsoft Excel (Microsoft Office, version 15.41, Redmond,
WA, USA), and analysed using R (version 3.3.2, Vienna, Austria) with
the rms,survival and frailtyEM packages.
Registration.
The protocol was registered with PROSPERO (CRD42018096552).
Results
Systematic review
The search strategy identified 3191 hits, of which 2224 were left after
duplicates were removed (Supplementary Data). After study screening,
130 studies were deemed eligible, of which 28 were excluded as they
were published prior to the year 2000. Emails were sent to authors of
the remaining studies and authors of 30 studies replied, resulting in 18
unique databases. Upon receipt of the data, nine databases were ex-
cluded. Two did not record natural conception outcome as they were
from RCTs that only performed an intention-to-treat analysis without
recording treatment-independent pregnancies (Steiner et al.,2015),
one database was an RCT embedded in a cohort yielding duplicate
data (Custers et al., 2012), one database was in a file format that
could not be accessed (Mol et al.,2001), and in seven, the treatment-
free follow-up time could not be accurately ascertained
(Osmanagaoglu et al., 2002;Gnoth et al., 2003;Brandes et al.,2009;
Walschaerts et al.,2012;Wynter et al., 2013). This resulted in nine in-
cluded databases (n¼4379 women). The number of women included
and excluded based on study selection criteria was presented accord-
ing to PRISMA guidance (Fig. 1).
Of the included studies, two were RCTs and seven were cohort
studies (six prospective, one retrospective). Of the RCTs, two investi-
gated different contrast methods for hysterosalpingography (Lindborg
et al., 2009;Dreyer et al., 2017). We included all arms, regardless of
contrast used, in the meta-analysis as this was considered part of the
diagnostic work-up. Of the cohort studies, one included women who
discontinued ART (Cahill et al., 2005), one included women on the
waiting list for ART (Eijkemans et al.,2008), and five included all
women presenting for fertility services capturing all treatment-related
and treatment-independent fertility outcomes during a fixed follow-up
interval (van der Steeg et al.,2007;Pinborg et al.,2009;Pearce et al.,
2017;Righarts et al.,2017;Rantsi et al., 2018).
Three studies were subgroup analyses from larger cohort studies or
RCTs, where for the purposes of the meta-analysis the data from the
original study was requested and the related publications were
searched for (van der Steeg et al.,2007;Pinborg et al.,2009;Rantsi
et al., 2018). Of note, based on local guidelines, some women with in-
termediate to good prognosis for natural fertility were preferentially
counselled for initial expectant management (van der Steeg et al.,
2007;Eijkemans et al., 2008;Righarts et al.,2017). Local guidelines
and prognostic models used to calculate natural fertility were de-
scribed, including the Hunault model (Hunault et al., 2004). Women
of age 35 years were smaller subsets of the original studies, ranging
from 29 to 1445 (original study sizes ranged from 120 to 7860
participants).
Of the included studies, half were multicentre (four from the
Netherlands, one from Denmark) (van der Steeg et al.,2007;
Eijkemans et al., 2008;Pinborg et al., 2009;Dreyer et al., 2017), while
the others were single-centre studies. All studies originated from high-
resourced countries. Six studies reported on livebirth while three
reported on pregnancy as the sole primary outcome (van der Steeg
et al., 2007;Eijkemans et al.,2008;Pearce et al.,2017). Data from
these nine studies were used in the composite primary outcome of
livebirth and ongoing pregnancy. Definition of different subgroups of in-
fertility was heterogeneous, including methods described by Hull, as-
sessment according to the guidelines of the Dutch Society of
Obstetrics and Gynaecology, local clinical priority access criteria (Hull
et al., 1985;Dutch Society of Obstetrics and Gynaecology, 2004;
Gillett et al., 2012) and was not described in two studies (Schmidt,
2006;Lindborg et al., 2009).
Of the prognostic factors of interest, all studies with exception of
one (Pearce et al., 2017) reported duration of infertility, types of infer-
tility and whether it was primary or secondary infertility. Secondary
outcomes were reported in four studies (Cahill et al.,2005;Lindborg
et al.,2009;Pinborg et al.,2009;Dreyer et al.,2017
), of which two
studies reported on multiple pregnancy (Cahill et al.,2005;Dreyer
et al.,2017), four reported on rate of miscarriage (Cahill et al.,2005;
Schmidt, 2006;Lindborg et al., 2009;Dreyer et al.,2017) and two
reported on the rate of ectopic pregnancy (Cahill et al.,2005;Dreyer
et al., 2017). Ongoing pregnancy in these studies was defined as foetal
cardiac activity on ultrasound on assessment, either at gestation of at
least 8 weeks (Eijkemans et al., 2008)oratleast12weeks(van der
Steeg et al.,2007). Data for ongoing pregnancy as defined by the pro-
tocol of at least 20 weeks could not be obtained. One study reported
time to delivery, where time to conception was estimated with the as-
sumption of term delivery (Righarts et al., 2017). Methodological char-
acteristics of included studies are presented in table form (Table I).
Studies were generally of moderate to high quality (Tables II and III).
Most cohort studies included all women presenting to fertility services
with a follow-up of up to 13 years for some cohorts and were graded
4Chua et al.
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as high quality. This was particularly true for large cohort studies (van
der Steeg et al., 2007;Eijkemans et al., 2008;Righarts et al., 2017).
RCTs were of high quality with clear method of randomisation and
allocation concealment. Given the objective outcomes livebirth or
ongoing pregnancy, this was graded as unclear risk of bias despite lack
of blinding. A funnel plot could not be used for the detection of publi-
cation bias as not all studies were powered to detect natural
conception.
3190 studies idenfied through database
searching
1 study idenfied through other sources including
contact with researchers
2224 studies aer duplicates removed
2224 studies screened for eligibility
2094 studies excluded
352 study design; 1051 intervenon; 3 <35yo; 6 Low
sample size; 99 Not human; 345 Not inferle; 24 Not
ferlit
y
outcomes; 214 known dia
g
noses
102 studies for which IPD were sought 28 eligible Studies for which IPD were not sought
(published prior to 2000)
30 studies for which IPD were provided (18 unique
cohorts)
9 cohorts excluded (2 natural concepon not
recorded; 1 data not in accessible format; 1 duplicate
study; 5 unclear me to pregnancy)
72 studies for which IPD were not provided
6 no access to data; 8 email addresses not in use; 2
emails could not be located; 2 sample size too small;
54 nil response from authors
15 studies included in analysis (9 unique cohorts)
(4379 parcipants)
Cahill 2005
Original data
(n=150)
IPD data (n=66)
Excluded (n=84)
- <35years (n=84)
van der Steeg 2007
Original data (n=7860)
IPD data (n=1445)
Excluded (n=6415)
- Age <35 (n=5548)
- Missing data (n=867)
Lindborg 2009
Original data (n=334)
IPD data (n=66)
Excluded (n=268)
- Age <35 (n=268)
Pearce 2017
Original data
(n=120)
IPD data (n=29)
Excluded (n=91)
- Age <35 (n=91)
Dreyer 2017
Original data (n=1119)
IPD data (n=312)
Excluded
- Age <35 (n=773)
- Subferle <1 year (n=27)
- No follow-up (n=7)
Eijkemans 2008
Original data (n=5962)
IPD data (n=1802)
Excluded (n=4160)
- Age <35 (n=3948)
- Subferle <1 year
(n=212)
Righarts 2017
Original data (n=1386)
IPD data (n=356)
Excluded (n=1030)
- Age <35 (n=890)
- Subferle <1 year (n=109)
- No follow-up (n=31)
Rantsi 2018
Original data (n=258)
IPD data (n=41)
Excluded (n=217)
- Age <35 (n=204)
- No follow-up (n=13)
Pinborg 2009
Original data (n=2251)
IPD data (n=262)
Excluded (n=1989)
- Age <35 (n =1947)
- No follow-up (n=42)
Figure 1 PRISMA individual participant data flow diagram. PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses;
IPD, individual participant data.
Natural fertility outcomes in women aged over 35 years 5
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...................................................................................................................................................................................................................................................................................................
Table I Study and methodological characteristics.
Study design Setting Inclusion criteria Exclusion criteria Outcomes of
interest
Prognostic factors
Cahill et al. (n¼66) Prospective cohort Single centre (UK), 1987–1991 All couples who attended for fertility
treatment
Severe male factor Livebirth Duration infertile
Multiple pregnancy Diagnoses
Severe tubal factor Ectopic pregnancy Primary/Secondary
Miscarriage
van der Steeg et al. (n¼
1445)
Prospective cohort Multicentre (Dutch, 38 centres),
2002–2004
All couples who attended for
infertility workup
Severe male factor Ongoing pregnancy
(USA 12 weeks)
Duration infertile
Diagnoses
Ovulation disorder Primary/Secondary
Sperm, FSH
Dreyer et al. (n¼312) RCT Multicentre (Dutch, 27 centres),
2012–2014
Age 8–39 years, spontaneous
menstrual cycles, infertile at least 1
year, indication for
hysterosalpingography
Endocrine disorder Livebirth Duration infertile
Severe male factor Multiple pregnancy Diagnoses
Severe tubal factor Ectopic pregnancy Primary/Secondary
Ovulation disorder Miscarriage
Eijkemans et al. (n¼
1802)
Prospective cohort Multicentre (Dutch, nationwide),
2002–2003
All couples who attended for IVF Non-IVF treatment Ongoing pregnancy
(USA 8 weeks)
Duration infertile
Diagnoses
Primary/Secondary
Righarts et al. (n¼356) Prospective cohort Single centre (New Zealand), 1998–
2005
All couples who attended for infertil-
ity workup
Livebirth Duration infertile
Diagnoses
Primary/Secondary
FSH
Lindborg et al. (n¼66) RCT Single centre (Finland), 2001–2006 All couples who attended for
infertility workup,including a HyCoSy
Female age >¼40 Livebirth Duration infertile
Severe male factor Diagnoses
Severe tubal factor Miscarriage Primary/Secondary
Ovulation disorder Sperm
Pearce et al. (n¼29) Retrospective cohort Single centre (Australia), 2013–2016 All couples who attended for infertil-
ity workup,including a HyCoSy
Pregnancy Diagnoses
Rantsi et al. (n¼41) Prospective cohort Single centre (Finland), 2007–2010 All couples who attended for infertil-
ity workup
Livebirth Duration infertile
Diagnoses
Primary/Secondary
Pinborg et al. (n¼262) Prospective cohort Multicentre (Denmark, 5 centres),
2000-ongoing
All couples who attended for fertility
treatment
Livebirth Duration infertile
Miscarriage Diagnoses
Primary/Secondary
HyCoSy, hysterosalpingography; US, ultrasound; RCT, randomised controlled trial.
6Chua et al.
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IPD meta-analysis
Baseline characteristics of the women are in Table IV.Atotalof4379
women from six countries were included of whom median female age
was 37.3 years (25
th
to 75th percentile 36.1–38.9 years). There were
little data (n¼531) for women over 40 years. Median duration of in-
fertility was 2.4 years (25
th
to 75th percentile 1.5–4.0 years), of which
2367 (54%) were primary infertility cases. Unexplained infertility
accounted for the most infertility at 51.0% (n¼2233), followed by
Table III Risk of bias grading of randomised controlled
trials utilising the Cochrane Risk of Bias tool.
.......................................... .............................................. ..............
Table II Risk of bias grading of cohort studies utilising the
Newcastle–Ottawa Scale.
Selection Comparability Outcome
1234 1 1 2 3
Cahill et al. ** * * *
Eijkemans et al. **** * * * *
Righarts et al. **** * * * *
Van der Steeg et al. **** * * * *
Pearce et al. ** * * *
Pinborg et al. ** *
Rantsi et al. **** * * * *
*The Newcastle Ottawa Scale is graded with a star system, if criteria are fulfilled a
star is awarded for each individual question
...................................................................................................................................................................................................................................................................................................
Table IV Characteristics of all included couples by cohort.
Eijkemans et al. Van der Steeg et al. Righarts et al. Dreyer et al. Pinborg et al. Lindborg et al. Cahill et al. Rantsi et al. Pearce et al.
n51802 n51445 n5356 n5312 n5262 n566 n566 n541 n529
Female age, years
[median, 25h–75th percentile]
37.4 [36.2, 39.1] 37.4 [36.1, 38.9] 37.8 [36.1, 40.2] 37.1 [36.0, 38.5] 36.0 [35.0, 38.0] 36.3 [35.7–37.2] 38.0 [36.0, 39.0] 36.9 [36.0, 38.1] 38.0 [36.0–39.0]
Duration of infertility, years
[median, 25th–75th percentile]
3.2 [2.1, 4.7] 1.6 [1.2, 2.5] 2.9 [1.6, 5.0] 1.8 [1.3, 2.3] 4.0 [3.0, 5.0] 2.0 [1.5–2.5] 5.0 [3.0, 7.0] 1.5 [1.0, 3.0] 8.0 [3.0–11.0]
Primary infertile (%) 944 (52.4) 772 (53.4) 230 (64.6) 182 (58.3) 135 (51.5) 27 (40.9) 43 (65.2) 17 (41.5) 20 (69)
Median follow-up, in months 4.1 5.7 7.6 3.5 7.4 6.0 8.5 9.6 7.0
Types of infertility
Unexplained infertility (%) 462 (25.6) 1207 (83.5) 86 (24.2) 275 (88.1) 83 (31.7) 66 (100) 9 (14.3) 19 (46.3) 26 (89.7)
Male factor (%) 581 (32.2) 142 (9.8) 114 (32.0) 74 (28.2) 16 (25.4) 3 (7.3)
Tubal factor (%) 373 (20.7) 96 (6.6) 76 (21.3) 25 (8.0) 64 (24.4) 23 (36.5) 8 (19.5) 2 (6.9)
Endometriosis (%) 106 (5.9) 29 (8.1) 9 (14.3) 6 (14.6) 1 (3.4)
Hormonal/menstrual
cycle infertility (%)
109 (6.0) 38 (10.7) 17 (6.5) 4 (9.8)
Immunological infertility (%) 59 (3.3)
Uncertain/other (%) 112 (6.2) 13 (3.7) 12 (3.8) 24 (9.2) 6 (9.5) 1 (2.4)
Natural fertility outcomes in women aged over 35 years 7
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male factor (21.2%, n¼930), tubal factor (15.2%, n¼667), ovulatory
disorders (3.8%, n¼168), endometriosis (3.4%, n¼151), immunologi-
cal causes (1.3%, n¼59) and other causes of infertility (3.9%,
n¼171). Only one study included detailed covariate data, such as
AMH and FSH, and therefore, these covariates were not used (van
der Steeg et al., 2007). BMI and smoking status were also reported in
four studies (van der Steeg et al.,2007;Lindborg et al., 2009;Righarts
et al.,2017;Rantsi et al., 2018). Data on the most important factors
aside from female age, duration of infertility and primary or secondary
infertility, were missing in n¼32 (0.7%), which was accounted for us-
ing single imputation.
When considering the composite primary outcome of livebirth and
ongoing pregnancy, a total of 429 events were noted (9.8%). Any spe-
cific diagnosis of infertility was associated with a lower hazard ratio
(HR) for natural conception leading to ongoing pregnancy or livebirth
compared to unexplained infertility, except for immunological infertility
which did not reach statistical significance (HR 0.11; 95% CI 0.01–
1.65). HRs for male factor (HR 0.30; 95% CI 0.21–0.43), tubal factor
(HR 0.42; 95% CI 0.30–0.60), endometriosis (HR 0.36; 95% CI 0.17–
0.76) and ovulation disorders (HR 0.409; 95% CI 0.21–0.76) were
significantly lower compared to unexplained infertility. In all infertility
subgroups, the probability of natural conception leading to ongoing
pregnancy increased over follow-up with the exception of immunologi-
cal infertility (Fig. 2).
Given the heterogeneity in method of diagnosis and the large avail-
ability of robust data for women with unexplained infertility, further
analysis of the probability of ongoing pregnancy in these women
(n¼2404) was performed. For women with unexplained infertility, the
Kaplan–Meier estimate of natural conception leading to ongoing preg-
nancy or livebirth was 13.3% (95% CI 11.7–14.9%) within 6 months
and 21.9% (95% CI 19.2–24.5) within 12 months (Fig. 3).
The final Cox model contained female age, duration of infertility and
primary or secondary infertility. In the analysis of those with unexplained
infertility, the model with non-linear effects for female age and duration
of infertility fitted best (using restricted cubic splines with 3 and 4 knots,
respectively). The non-linear effect of female age on natural conception
leading to ongoing pregnancy is shown (Fig. 4), where the probability of
natural conception decreases for women aged 38 years or older. Using
this model, a 35-year-old woman with 2 years of primary unexplained
infertility had a predicted probability of natural conception of 0.15 (95%
CI 0.11–0.19) after 6 months and 0.24 (95% CI 0.17–0.30) after 12
months (Table V). For a woman of age 42 years, this decreased to 0.08
(95% CI 0.04–0.11) after 6 months and 0.13 (95% CI 0.07–0.18) after
12 months. For women with primary unexplained infertility who have
been trying to conceive naturally for 5 years, there was very low (<5%)
probability of natural conception leading to ongoing pregnancy over 12
months when the woman is 41 years old or above (Table V). The
results with the random effects Cox model were more optimistic, esti-
mating higher probabilities of ongoing pregnancy than the Cox model
without random effects, and never reaching below 5% over 12 months.
Figure 3 Kaplan–Meier curve depicting the natural rate of
conception leading to ongoing pregnancy or livebirth for
unexplained infertile couples or unknown diagnoses. Dotted
lines are 95% confidence limits.
Figure 4 Effect of female age on the probability of natural
conception leading to ongoing pregnancy or livebirth
within 12 months. Grey areas indicate 95% confidence limits.
Figure 2 Kaplan–Meier curves depicting the natural rate
of conception leading to ongoing pregnancy or livebirth,
stratified for the different types of infertility.
8Chua et al.
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................................................................................................................................................................................................. ...........................
Table V Predicted probabilities of natural conception over 6 or 12 months for couples with unexplained infertility for various
combinations of female age, duration of infertility and primary or secondary infertility.
Female
age
(years)
Duration of
infertility
(years)
Primary or
secondary
infertility
Predicted probability
over 6 months (95%CI)
Predicted probability
over 12 months (95%CI)
Predicted probability
over 6 months (frailty)*
Predicted probability
over 12 months (frailty)*
35 1 Primary 0.18 (0.12–.24) 0.29 (0.20–0.37) 0.23 0.37
36 1 Primary 0.19 (0.14–0.23) 0.30 (0.23–0.36) 0.24 0.38
37 1 Primary 0.19 (0.14–0.23) 0.30 (0.23–0.36) 0.24 0.38
38 1 Primary 0.17 (0.13–0.22) 0.28 (0.21–0.34) 0.23 0.36
39 1 Primary 0.15 (0.11–0.19) 0.25 (0.19–0.31) 0.20 0.32
40 1 Primary 0.13 (0.09–0.17) 0.22 (0.16–0.27) 0.17 0.28
41 1 Primary 0.11 (0.07–0.15) 0.18 (0.12–0.24) 0.14 0.23
42 1 Primary 0.09 (0.05–0.13) 0.15 (0.09–0.22) 0.12 0.20
35 2 Primary 0.15 (0.11–0.19) 0.24 (0.17–0.30) 0.18 0.29
36 2 Primary 0.15 (0.12–0.18) 0.25 (0.19–0.29) 0.18 0.30
37 2 Primary 0.15 (0.12–0.18) 0.25 (0.19–0.29) 0.18 0.30
38 2 Primary 0.14 (0.11–0.17) 0.23 (0.18–0.28) 0.17 0.28
39 2 Primary 0.13 (0.10–0.16) 0.21 (0.16–0.25) 0.15 0.25
40 2 Primary 0.11 (0.08–0.14) 0.18 (0.13–0.22) 0.13 0.21
41 2 Primary 0.09 (0.06–0.12) 0.15 (0.10–0.20) 0.11 0.18
42 2 Primary 0.08 (0.04–0.11) 0.13 (0.07–0.18) 0.09 0.15
35 3 Primary 0.08 (0.06–0.11) 0.14 (0.09–0.18) 0.11 0.18
36 3 Primary 0.09 (0.06–0.11) 0.14 (0.11–0.17) 0.11 0.19
37 3 Primary 0.08 (0.06–0.11) 0.14 (0.11–0.17) 0.11 0.19
38 3 Primary 0.08 (0.06–0.10) 0.13 (0.10–0.17) 0.10 0.18
39 3 Primary 0.07 (0.05–0.09) 0.12 (0.09–0.15) 0.09 0.16
40 3 Primary 0.06 (0.04–0.08) 0.10 (0.07–0.13) 0.08 0.13
41 3 Primary 0.05 (0.03–0.07) 0.08 (0.05–0.11) 0.06 0.11
42 3 Primary 0.04 (0.02–0.06) 0.07 (0.04–0.10) 0.05 0.09
35 4 Primary 0.06 (0.03–0.08) 0.09 (0.06–0.13) 0.08 0.13
36 4 Primary 0.06 (0.04–0.08) 0.10 (0.06–0.13) 0.08 0.14
37 4 Primary 0.06 (0.04–0.08) 0.10 (0.06–0.13) 0.08 0.14
38 4 Primary 0.05 (0.04–0.07) 0.09 (0.06–0.12) 0.07 0.13
39 4 Primary 0.05 (0.03–0.06) 0.08 (0.05–0.11) 0.06 0.11
40 4 Primary 0.04 (0.02–0.05) 0.07 (0.04–0.09) 0.05 0.09
41 4 Primary 0.03 (0.02–0.05) 0.06 (0.03–0.08) 0.04 0.08
42 4 Primary 0.03 (0.01–0.04) 0.05 (0.02–0.07) 0.04 0.06
35 5 Primary 0.05 (0.03–0.07) 0.08 (0.05–0.11) 0.07 0.11
36 5 Primary 0.05 (0.03–0.07) 0.08 (0.05–0.11) 0.07 0.12
37 5 Primary 0.05 (0.03–0.07) 0.08 (0.05–0.11) 0.07 0.12
38 5 Primary 0.05 (0.03–0.06) 0.08 (0.05–0.10) 0.06 0.11
39 5 Primary 0.04 (0.02–0.05) 0.07 (0.04–0.09) 0.06 0.09
40 5 Primary 0.03 (0.02–0.05) 0.06 (0.03–0.08) 0.05 0.08
41 5 Primary 0.03 (0.02–0.04) 0.05 (0.03–0.07) 0.04 0.07
42 5 Primary 0.02 (0.01–0.04) 0.04 (0.02–0.06) 0.03 0.05
35 6 Primary 0.05 (0.03–0.07) 0.08 (0.04–0.11) 0.06 0.11
36 6 Primary 0.05 (0.03–0.07) 0.08 (0.05–0.11) 0.06 0.11
37 6 Primary 0.05 (0.03–0.07) 0.08 (0.05–0.11) 0.06 0.11
38 6 Primary 0.04 (0.03–0.06) 0.07 (0.05–0.10) 0.06 0.10
39 6 Primary 0.04 (0.02–0.05) 0.07 (0.04–0.09) 0.05 0.09
40 6 Primary 0.03 (0.02–0.05) 0.06 (0.03–0.08) 0.04 0.08
(continued)
Natural fertility outcomes in women aged over 35 years 9
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Table V Continued
Female
age
(years)
Duration of
infertility
(years)
Primary or
secondary
infertility
Predicted probability
over 6 months (95%CI)
Predicted probability
over 12 months (95%CI)
Predicted probability
over 6 months (frailty)*
Predicted probability
over 12 months (frailty)*
41 6 Primary 0.03 (0.01–0.04) 0.05 (0.02–0.07) 0.04 0.06
42 6 Primary 0.02 (0.01–0.03) 0.04 (0.02–0.06) 0.03 0.05
35 1 Secondary 0.22 (0.15–0.29) 0.35 (0.25–0.44) 0.28 0.44
36 1 Secondary 0.23 (0.17–0.28) 0.36 (0.28–0.43) 0.29 0.45
37 1 Secondary 0.23 (0.18–0.28) 0.36 (0.28–0.43) 0.29 0.45
38 1 Secondary 0.22 (0.16–0.26) 0.34 (0.26–0.41) 0.28 0.43
39 1 Secondary 0.19 (0.15–0.23) 0.30 (0.24–0.37) 0.24 0.38
40 1 Secondary 0.16 (0.12–0.20) 0.26 (0.20–0.32) 0.21 0.33
41 1 Secondary 0.14 (0.09–0.18) 0.22 (0.15–0.29) 0.17 0.28
42 1 Secondary 0.12 (0.07–0.16) 0.19 (0.11–0.26) 0.14 0.24
35 2 Secondary 0.18 (0.13–0.23) 0.29 (0.21–0.37) 0.22 0.35
36 2 Secondary 0.19 (0.15–0.23) 0.30 (0.24–0.36) 0.23 0.36
37 2 Secondary 0.19 (0.15–0.23) 0.30 (0.24–0.36) 0.23 0.36
38 2 Secondary 0.18 (0.14–0.21) 0.28 (0.22–0.34) 0.21 0.34
39 2 Secondary 0.16 (0.12–0.19) 0.25 (0.19–0.31) 0.19 0.30
40 2 Secondary 0.13 (0.10–0.17) 0.22 (0.16–0.27) 0.16 0.26
41 2 Secondary 0.11 (0.07–0.15) 0.18 (0.12–0.24) 0.13 0.22
42 2 Secondary 0.09 (0.05–0.13) 0.15 (0.09–0.22) 0.11 0.18
35 3 Secondary 0.10 (0.07–0.13) 0.17 (0.12–0.22) 0.14 0.23
36 3 Secondary 0.11 (0.08–0.13) 0.17 (0.13–0.21) 0.14 0.23
37 3 Secondary 0.11 (0.08–0.13) 0.17 (0.13–0.21) 0.14 0.23
38 3 Secondary 0.10 (0.07–0.12) 0.16 (0.12–0.20) 0.13 0.22
39 3 Secondary 0.09 (0.06–0.11) 0.15 (0.11–0.18) 0.11 0.19
40 3 Secondary 0.07 (0.05–0.09) 0.12 (0.09–0.16) 0.10 0.16
41 3 Secondary 0.06 (0.04–0.08) 0.10 (0.07–0.14) 0.08 0.14
42 3 Secondary 0.05 (0.03–0.07) 0.09 (0.05–0.12) 0.07 0.11
35 4 Secondary 0.07 (0.04–0.10) 0.12 (0.07–0.16) 0.10 0.16
36 4 Secondary 0.07 (0.05–0.10) 0.12 (0.08–0.16) 0.10 0.17
37 4 Secondary 0.07 (0.05–0.10) 0.12 (0.08–0.16) 0.10 0.17
38 4 Secondary 0.07 (0.04–0.09) 0.11 (0.07–0.15) 0.09 0.16
39 4 Secondary 0.06 (0.04–0.08) 0.10 (0.07–0.13) 0.08 0.14
40 4 Secondary 0.05 (0.03–0.07) 0.08 (0.05–0.11) 0.07 0.12
41 4 Secondary 0.04 (0.02–0.06) 0.07 (0.04–0.10) 0.06 0.10
42 4 Secondary 0.03 (0.02–0.05) 0.06 (0.03–0.09) 0.05 0.08
35 5 Secondary 0.06 (0.03–0.08) 0.10 (0.06–0.14) 0.08 0.14
36 5 Secondary 0.06 (0.04–0.08) 0.10 (0.06–0.14) 0.08 0.14
37 5 Secondary 0.06 (0.04–0.08) 0.10 (0.06–0.14) 0.08 0.14
38 5 Secondary 0.06 (0.04–0.08) 0.10 (0.06–0.13) 0.08 0.14
39 5 Secondary 0.05 (0.03–0.07) 0.08 (0.05–0.11) 0.07 0.12
40 5 Secondary 0.04 (0.03–0.06) 0.07 (0.04–0.10) 0.06 0.10
41 5 Secondary 0.04 (0.02–0.05) 0.06 (0.03–0.09) 0.05 0.08
42 5 Secondary 0.03 (0.01–0.04) 0.05 (0.02–0.08) 0.04 0.07
35 6 Secondary 0.06 (0.03–0.08) 0.10 (0.05–0.14) 0.08 0.14
36 6 Secondary 0.06 (0.04–0.08) 0.10 (0.06–0.14) 0.08 0.14
37 6 Secondary 0.06 (0.04–0.08) 0.10 (0.06–0.14) 0.08 0.14
38 6 Secondary 0.06 (0.03–0.08) 0.09 (0.06–0.13) 0.08 0.13
39 6 Secondary 0.05 (0.03–0.07) 0.08 (0.05–0.11) 0.07 0.11
(continued)
10 Chua et al.
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Three studies recorded time to treatment and treatment-related
outcomes (Schmidt, 2006;Righarts et al., 2017;Rantsi et al., 2018).
Given the heterogeneity in types of treatment the women received,
the different starting times of treatment after recruitment that does
not allow a direct comparison and the relatively small numbers in-
volved, the effect of treatment was not estimated, in keeping with the
original protocol.
Discussion
Summary of findings
This study was designed to guide treatment strategies for women of
age 35 years presenting to a fertility service. As expected, natural
fertility declined with female age. This association between female age
and time to natural conception leading to ongoing pregnancy or live-
birth was non-linear. Studies were of moderate to high quality and
mainly derived from high resource settings. Of note, any diagnosis of
infertility conferred a poorer prognosis compared with unexplained
infertility.
Strengths and limitations
The IPD meta-analysis method was used to incorporate all available
data on women aged 35 years or above to estimate more accurately
their probability of a natural conception leading to ongoing pregnancy
or livebirth. The most important limitation in our study is the aggrega-
tion of studies that used different study design, recruitment strategies
in different centres, protocols and countries. In addition, as this was an
undifferentiated population of women, with heterogeneous methods
used in defining tubal status, male infertility and ovulatory status, the
most robust conclusions could only be made for those with unex-
plained infertility. Additionally, only one study reported on outcomes
from immunological infertility (Eijkemans et al.,2008). The frailty model
was utilised in order to account for these differences. This resulted in
higher point estimates and undefined CIs, however, did not change the
relationship between age and time to natural conception.
Limited confounding variables (diagnoses, duration of infertility and
whether infertility was primary or secondary) were included in the
analysis, however, other known variables that could potentially impact
on fertility (e.g. AMH, BMI) were insufficient. Additionally, data on sec-
ondary outcomes, such as multiple pregnancy and ectopic pregnancy,
were negligible.
The effect of treatment was not an area of interest that was ex-
plored in this study. In order to provide the best model for clinical
decision-making, we have elected to study only natural conception in
the absence of treatment. This is because the effect of treatment
would likely act as a competing risk, resulting in a reduction in
detected rates of natural conception. This was addressed by censoring
women at the time when treatment occurred. However, due to this
censorship, follow-up time was significantly truncated for many women
included in this IPD analysis, as some would have commenced treat-
ment at an earlier date before natural conception occurred.
The major contributors to our study came from Dutch data, in
which some patients with intermediate to good prognosis for natural
conception were preferentially counselled for expectant management,
although this did not seem to introduce a strong confounding effect
(van Geloven et al., 2014). Also, addition of the RCTs introduced
strict inclusion and exclusion criteria, where severe male infertility and
tubal pathology were excluded (Lindborg et al., 2009;Dreyer et al.,
2017). Unfortunately, there were little data for women above the age
of 40 years.
Clinical implications
Female age is a strong predictor of infertility, which also is reflected in
the fact that increasing age predicts poorer outcomes for ART
(Malchau et al., 2017;Centers for Disease Control and Prevention
ASfRM and Society for Assisted Reproductive Technology, 2018;
Fitzgerald et al., 2019). In addition, it is unclear whether ART adds any
meaningful increase in livebirth rate on top of natural fertility for cer-
tain diagnoses (McLernon et al.,2016;van Eekelen et al., 2019).
Moreover, the costs and adverse effects, such as multiple livebirth
rate, warrant objective evaluation of ART use/recommendations.
On a global scale, older women account for a significant proportion
of ART usage. In 2011, a study incorporating 2560 centres from 65
countries discovered that women who were at least 35 years old
accounted for 60% of ART usage (Adamson et al., 2018). In 2016, this
percentage remained stable at 61–62% in women from high resource
settings (Centers for Disease Control and Prevention ASfRM and
Society for Assisted Reproductive Technology, 2018;Fitzgerald et al.,
2019). Treatment decisions are also influenced by reimbursement poli-
cies, which may impose age restrictions. In addition, there have been
no RCTs investigating treatment versus no treatment in a cohort of
this age. Existing data tend to report per cycle outcomes and do not
take into account the dropout rate of women attending fertility serv-
ices, which may skew fertility outcomes.
................................................................................................................................................................................................. ...........................
Table V Continued
Female
age
(years)
Duration of
infertility
(years)
Primary or
secondary
infertility
Predicted probability
over 6 months (95%CI)
Predicted probability
over 12 months (95%CI)
Predicted probability
over 6 months (frailty)*
Predicted probability
over 12 months (frailty)*
40 6 Secondary 0.04 (0.02–0.06) 0.07 (0.04–0.10) 0.06 0.09
41 6 Secondary 0.03 (0.02–0.05) 0.06 (0.03–0.08) 0.04 0.08
42 6 Secondary 0.03 (0.01–0.04) 0.05 (0.02–0.07) 0.04 0.06
*The final two columns are average predictions from the Cox model including a random effect (frailty) for cohort. Note that the confid ence limits of the latter are undefined.
Natural fertility outcomes in women aged over 35 years 11
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Women attending fertility services should be encouraged to pursue
natural conception while waiting for treatment commencement, as
well as during treatment, and not give up on their fertility even after
treatment fails (Walschaerts et al.,2012;Wynter et al., 2013).
Women of advanced maternal age with low natural fertility chances as
well as low chances from treatment could potentially be counselled
for donor oocyte treatment (Hogan et al.,2019). Clearly, natural fertil-
ity remains an important source of livebirth and ongoing pregnancy,
and should not be neglected in the context of clinical counselling and
research, especially for women with unexplained infertility.
Supplementary data
Supplementary data are available at Human Reproduction online.
Authors’ roles
S.J.V., R.V.E., M.V.W., D.J.M. and B.W.J.M. were involved in the draft-
ing of the protocol. S.J.C. and N.A.D. were involved in study selection
and risk of bias assessment. S.J.C., R.V.E., M.H.M., D.J.M., I.C., E.L.,
K.D., D.J.C., W.R.G., A.R., A.S., T.R., L.S. and R.M.J.C.E. were in-
volved in data analysis. S.J.C. and R.V.E. were responsible for the final
draft of the manuscript. All authors critically revised the manuscript
and approved the final manuscript.
Funding
S.J.C. received funding from the University of Adelaide Summer
Research Scholarship. B.W.M. is supported by a NHMRC Investigator
grant (GNT1176437).
Conflict of interest
B.W.M. reports consultancy for ObsEva, Merck, Merck KGaA,
iGenomix and Guerbet. B.W.M. reports research support by Merck
and Guerbet. The remaining authors do not declare any conflicts on
interest.
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