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Fertility trends of women with serious mental illness in the United Kingdom 1992–2017: A primary care cohort study using the clinical practice research datalink
Journal of Affective Disorders 269 (2020) 141–147
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Research paper
Fertility trends of women with serious mental illness in the United Kingdom 1992–2017: A primary care cohort study using the clinical practice research datalink
T
Holly Hopea, , Rosa Parisib,c, Darren M Ashcroftc, Rachael Williamsd, Sonia Cotond, Kyriaki Kosidoue,f, Matthias Piercea,1, Kathryn M Abela,g,1 ⁎
a
Centre for Women’s Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, UK Division of Informatics, Imaging and Data Science, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, UK Centre for Pharmacoepidemiology and Drug Safety, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, UK d Clinical Practice Research Datalink, Medicines and Healthcare products Regulatory Agency, UK e Center for Epidemiology and Community Medicine, Region Stockholm, Sweden f Department of Global Public Health, Karolinska Institute, Stockholm, Sweden g Greater Manchester Mental Health NHS Foundation Trust, UK b c
ARTICLE INFO
ABSTRACT
Keywords: Fertility Women Schizophrenia Bipolar disorder Psychotic disorders Antipsychotics
Background: Changes in care may mean women with serious mental illness (SMI) are more fertile. We investigated 1) the live-birth and pregnancy rate of women with and without SMI over time, 2) the likelihood of pregnancy when using second or first-generation antipsychotics. Method: Retrospective cohort study of women (15–45 years) registered in Clinical Practice Research Datalink (CPRD) general practices between 1992 and 2017. Each analysis year, women with SMI (affective and nonaffective psychotic disorder) were matched with up to four women with no record of SMI on age, calendar year and general practice. Pregnancy and live-birth rates and the rate ratio (RR) comparing women with and without SMI were estimated. The stability of the RR between years was tested. For women with SMI, the pregnancy rates when on or off first or second-generation antipsychotics were calculated and compared using Poisson regression models. Results: In total, 12,524 women with SMI were matched to 50,074 women without SMI, median age 34 [IQR 28–39] years. Between 1992 and 2017 women with SMI had 50% fewer live-births than women without SMI (RR 0..50, 95%CI 0.45–0.55). The pregnancy rate ratio increased from 0.64 (95%CI 0.48–0.86) (1992–1994) to 1.00 (95%CI 0.81–1.22) (2016–2017), (p < 0.0001), but this change was only seen in women with affective disorders. Women are most likely to become pregnant after discontinuing either a second-generation or firstgeneration antipsychotic (RR 1.74, 95%CI 1.42–2.13). Conclusions: Women with SMI are increasingly experiencing pregnancy but not live-birth, which suggests the reproductive health needs of these women are unmet.
1. Introduction Women with serious mental illness (SMI), namely affective and nonaffective psychotic disorders, are less likely to get pregnant and have children than women without SMI, (Howard et al., 2002) and women with common mental illnesses, (Laursen and Munk-Olsen, 2010; Power et al., 2013) and, thus, have considerably lower fertility. This
information potentially highlights an important physical health inequality for women with serious mental illness (SMI) (Abel and Rees, 2010) and one which receives relatively little public health attention compared to cardiovascular, (Goff et al., 2005) or metabolic health (De Hert et al., 2011). In the last two decades, better treatment and community-based care may provide women with SMI more opportunities to develop relationships and start a family. (Naylor et al.,
Corresponding author: Centre for Women's Mental Health, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Room 3.320 Jean McFarlane Building, Oxford Road, Manchester, UK. E-mail address: [email protected] (H. Hope). 1 Shared senior authorship ⁎
https://doi.org/10.1016/j.jad.2020.03.037 Received 13 September 2019; Received in revised form 20 December 2019; Accepted 19 March 2020 Available online 20 March 2020 0165-0327/ © 2020 Elsevier B.V. All rights reserved.
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2014) In addition, since the mid 1990′s, second-generation antipsychotics are increasingly prescribed as first line agents in the treatment of SMI. (Kaye et al., 2003) These drugs were heralded as less likely to induce physical side effects, including hyperprolactinaemia and disruption of fertility. (Jones et al., 2014; Bargiota et al., 2013) However, only one prior study has examined if fertility has changed over time. (Vigod et al., 2012) Vigod et al. 2012 assessed 2473 live-births of women with schizophrenia from 1996 to 2009 in Canada and observed an increase in the relative fertility rate compared to women without schizophrenia from a rate-ratio of 0.30 (95% CI 0.25–0.35) in 1996 to 0.41 (95% CI 0.36–0.47) in 2009. However, to our knowledge, no prior analysis has compared the fertility of women with and without affective and non-affective psychotic disorders and if this has changed over the years where women were switched from first- to second-generation antipsychotics. In addition, our analytical approach will investigate the relative fertility of women with SMI for all years, rather than comparing rates of live births in the entry and end year of study. Nor has the link between first and second antipsychotic exposure and pregnancy in women with SMI been explicitly examined. Women with SMI and their offspring are a vulnerable group (King-Hele et al., 2009; MunkOlsen and Agerbo, 2015) therefore it is a public health imperative to investigate the fertility trends of women with SMI in order to properly resource the required services. Our study uses a large UK cohort identified in a primary care database to investigate trends in both pregnancy and live-births in women with SMI from 1992–2017. Our intention is first to investigate trends in the pregnancy and live-birth rate for women with serious mental illness (affective and non-affective psychoses) using women without SMI as a reference group. Second, and for the first time, we shall quantify the association between first and second-generation antipsychotic exposure and female fertility. We, therefore, test the following hypotheses: 1) Women with SMI relative to women without SMI experience increasing pregnancy and fertility (live-birth) rates from 1992–2017; and 2) second-generation compared to first-generation antipsychotic use associates with an increased likelihood of pregnancy for women with SMI.
resulted in 2680,149 and 2361,107 women available for the analysis of pregnancy and pregnancy outcome respectively (eFigure 1). The proportion of the cohort in each year of the study period diagnosed with SMI was 0.20% in 1992 and 0.23% in 2017 (eTable 1). 2.3. Exposure definitions Serious mental illness included a record of a diagnosis of a nonaffective psychotic disorder (e.g. schizophrenia, schizotypal, delusional, psychosis NOS) or affective psychotic disorder (e.g. bipolar, manic, schizoaffective disorders, or depression with psychosis). Read codes were identified by HH and validated by two psychiatrists (ES and KMA). All prescriptions for antipsychotics were identified by HH and verified by KMA and DMA. A previously developed algorithm cleaned the prescription data, calculated the duration and end date and handled incongruous prescription data. (Pye et al., 2018) The algorithm is further detailed in supplementary material (eFigure 2). Prescriptions were classed as first or second-generation antipsychotics according to the British National Formulary. 2.4. Identifying pregnancies and live-births In the UK, an estimated 83% of women report their pregnancy to their general practitioner before other healthcare professionals, and most will visit primary care as a component of their antenatal or postnatal care. (Redshaw et al., 2006) The CPRD, in collaboration with the London School of Hygiene and Tropical Medicine (LSHT), created a Pregnancy Register algorithm; utilizing >4000 medical codes and datatypes, it extracts discrete pregnancy episodes and their outcome. Currently, the CPRD/LSHTM are publishing validation work to establish the algorithm's ability to detect pregnancies and birth outcomes. As a data-quality exercise, we compared the live-birth rate of the Pregnancy Register with that in published national statistics and assessed whether this varied by age-group and period (eTable 2). (Office for National Statistics, 2016) A significant proportion of pregnancy outcomes (16% overall, 21% in this study) are unknown. As a sensitivity analysis, we included births where the pregnancy was ‘unknown’ in our definition of live-births. Also, 11% of pregnancy outcomes (10% in this study) were considered “probable termination of pregnancy” and classed as “abortions”, however the main analyses were restricted to live-births. The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008. This study is based in part on data from the Clinical Practice Research Datalink (CPRD) obtained under licence from the UK Medicines and Healthcare products Regulatory Agency. The data is provided by patients and collected by the NHS as part of their care and support. The study was approved by the Independent Scientific Advisory Committee for CPRD research (protocol number: 17_187)
2. Methods 2.1. Data source Data for this retrospective cohort study comes from the UK Clinical Practice Research Datalink (CPRD) GOLD primary care database. The dataset (Jan 2018) used for this analysis contained data on over 15.3 million primary care patients. CPRD GOLD includes individual-linked data on clinical consultations, treatments, referrals and tests, in addition to patient demographics and practice data since 1987. (Herrett et al., 2015) General practitioners’ record of diagnoses, symptoms and other information during a consultation are codified using Read codes. (Chisholm, 1990) 2.2. Study population The cohort for this analysis was selected from 3624,708 women registered at a CPRD GOLD-participating practice and aged 15 to 44 during the study window: 1st January 1990 to 31st December 2017. Women were considered eligible for inclusion if registered for at least two years at a general practice (GP) from the date it provided up-tostandard (UTS) data (a CPRD measure of data quality), in order to have an adequate observation window to ascertain exposure. They became ineligible at the earliest date of age 45; death; date the GP stopped collecting data; or they transferred out of a participating GP. For analysis of live-births, we included the further criterion that women must have at least 44 weeks of data prior to the date they transferred out from the participating practice or from the date the practice stopped contributing data to the CPRD. This additional criterion helped to ensure that data were available on the outcome of pregnancies. This
2.5. Analysis For each analysis year (1992–2017), eligible women were classified as exposed if they had a SMI diagnosis in the two years prior to the analysis year and unexposed if there was no diagnosis of SMI in their record. Subtypes of non-affective and affective psychotic disorders were identified. There were 3522 instances where women had diagnostic codes relating to both affective and non-affective psychotic disorders and these were classified using the latest recorded code. Instances where there were codes relating to both at the same date (n = 145) were coded as having non-affective psychosis. For each analysis year, women identified as having a recent history of psychotic disorder were matched (without replacement) to up to four unexposed women (no 142
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(rate = 48.9) and 8911 pregnancies among women without SMI (rate = 80.9). Relative to women without SMI, women with SMI had 32% fewer pregnancies (RR 0.68, 95% confidence interval (CI) 0.64–0.73) and the rate ratio changed significantly over time (p < 0.001). The pregnancy rate ratio decreased from 0.64 (95%CI 0.48–0.86) in 1992–1994 to 0.52 (95%CI 0.44–0.61) in 2004–2006 and increased to a peak at 1.00 (95%CI 0.8–1.22) in 2016–2017. The overall pregnancy rate ratio of women with affective psychotic disorders was 0.75 (95%CI 0.69–0.81) and this also changed significantly over time (p < 0.001): it decreased from 0.84 (95%CI 0.56–1.25) in 1992–1994 to 0.56 (95%CI 0.45–0.69) in 2004–2006 and increased to 1.00 (95%CI 0.83–1.20) in 2016–2017. In contrast, the pregnancy rate ratio of women with non-affective psychotic disorders was 0.61 (95%CI 0.56–0.67) and remained stable over time (p = 0.64) at 0.56 (95%CI 0.38–0.83) in 1992–1994, 0.54 (0.43–0.68) in 2004–2006 and 0.79 (0.58–1.09) in 2016–2017. The live-birth rate of women with serious mental illness (Table 2) The live-birth rate for women with SMI increased from 24.3 per 1000 person years during the period 1992–1994 to 33.5 from 2016–2017. There were 549 live-births among women with a recent SMI diagnosis (rate = 23.8) and 4547 live-births among women without a history of SMI (rate = 47.6) in the live-birth outcome cohort over the study period. Relative to women without SMI, women with SMI had fewer live-births (RR 0.50, 95%CI 0.45–0.55), and despite the apparent increasing birth rate among women with SMI this association did not significantly change over time (p = 0.24). Similarly, women with nonaffective psychotic disorders and women with affective psychotic disorders had fewer births relative to women without SMI (RR 0.44, 95% CI 0.39–0.51 and RR 0.55, 95%CI 0.49–0.62 respectively) and these associations did not change over time (p = 0.36). Other pregnancy outcomes (eTable 3) There were 10,640 pregnancies during the study period among women in the pregnancy outcome cohort. Fewer pregnancies resulted in a live-birth outcome for women with SMI than women without SMI (46.9% vs 57.9%). However, more pregnancies resulted in a termination (15.1% vs 9.9%) or an unknown pregnancy outcome (25.2% vs 20.9%) for women with SMI than women without SMI. The effect of antipsychotic use on the pregnancy rate of women with serious mental illness (Table 3) The rate of antipsychotic use was stable and there was a clear switch to second-generation antipsychotic prescribing from the year 2000 for women with SMI (Fig. 1). Women with SMI had 41.2 pregnancies whilst exposed and 82.1 pregnancies per 1000 person years when unexposed to any antipsychotic medication. After adjustment for type of SMI, year of birth and general practice,
record of SMI) who shared the same year of birth and general practice. Therefore, women with SMI might be observed in multiple years. The number of pregnancies and live-births were counted within each analysis year and divided by the follow-up time, within each exposure category. These counts were modelled using a negative binomial model and an off-set term of follow-up time was included in the model to account for differential follow-up time for each year. The resulting parameter is interpreted as a rate ratio. This was estimated using a Generalised Estimating Equation model with an exchangeable correlation structure to account for multiple years of follow-up for each subject. The GEE model is used to account for the longitudinal structure of the data, and the fact that women may be followed up over multiple calendar years. These models are suitable when the quantity of interest is in the population average change in the dependent variable, rather than the within subject change, when there is a unit change in the independent variable. 2.6. Sub-cohort analysis To determine whether the rate of pregnancy was higher on second or first-generation antipsychotics the sub-cohort of women with SMI aged 15 to 40 years (n = 11,028) were followed-up for up to 5-years following their first diagnosis and their pregnancy rate on and off first and second-generation antipsychotics was calculated. The rate ratio comparing the pregnancy rate on second with first-generation antipsychotic use, or both, was estimated using Poisson regression models, controlling for age at diagnosis and the square of age at diagnosis. Women who used contraception or had a history of infertility may not conceive for other reasons than exposure to antipsychotics, therefore as a sensitivity analysis these women were excluded. Post-hoc, we examined the proximity of the effect by restricting the analysis. The pregnancy rate whilst on a first or second generation antipsychotic was compared with the rate during the first six months after discontinuation. 3. Results A total of 12,524 women with SMI were identified in the cohort and matched by age and practice to 50,074 women with no history of serious mental illness (eFigure1). The median age of women was 34 [28–39] years for women exposed and unexposed to SMI. The pregnancy rate of women with serious mental illness (Table 1) The pregnancy rate of women with SMI was 48.7 (pregnancies per 1000-person years) in 1992–1994, this rate dipped to its lowest in 2004–2006 (40.3) and increased to its highest in 2016–2017 (74.0). Overall, there were 1449 pregnancies among women with SMI
Table 1 The effect of serious mental illness on pregnancies in the pregnancy cohort from 1992 to 2017. Variable
Any Within year 92–94 95–97 98–00 01–03 04–06 07–09 10–12 13–15 16–17
Any
Non-affective psychosis
Affective psychosis
None
N (rate)
RR [95% CI]
p-value
N (rate)
RR
p-value
N (rate)
RR [95% CI]
p-value
N (rate)
1449 (54.7)
0.68 [0.64, 0.73]
<0.001
624 (48.9)
0.61 [0.56, 0.67]
<0.001
825 (60.0)
0.75 [0.69, 0.81]
<0.001
8911 (80.9)
54 (48.7) 74 (50.8) 117 (50.3) 154 (45.2) 177 (40.3) 208 (50.5) 269 (68.9) 266 (65.9) 130 (74.0)
0.64 0.72 0.73 0.60 0.52 0.61 0.77 0.74 1.00
<0.001*
27 40 64 86 86 98 94 86 43
0.56 0.65 0.72 0.63 0.54 0.68 0.68 0.61 0.79
0.649
27 (61.4) 34 (60.3) 53 (54.5) 68 (45.2) 91 (40.5) 110 (48.1) 175 (75.6) 180 (75.5) 87 (84.5)
0.84 0.88 0.81 0.62 0.56 0.60 0.87 0.88 1.15
<0.001
364 (79.9) 457 (74.9) 680 (70.8) 1090 (77.4) 1446 (79.3) 1427 (83.9) 1452 (88.6) 1461 (87.0) 534 (72.5)
[0.48, [0.56, [0.60, [0.50, [0.44, [0.52, [0.67, [0.64, [0.81,
0.86] 0.92] 0.90] 0.71] 0.61] 0.71] 0.88] 0.85] 1.22]
(40.4) (44.9) (47.3) (45.3) (40.1) (53.4) (59.2) (52.0) (59.1)
[0.38, [0.47, [0.56, [0.51, [0.43, [0.55, [0.55, [0.49, [0.58,
0.83] 0.90] 0.94] 0.79] 0.68] 0.84] 0.85] 0.76] 1.09]
[0.56, [0.62, [0.60, [0.49, [0.45, [0.49, [0.74, [0.74, [0.91,
1.25] 1.25] 1.08] 0.80] 0.69] 0.73] 1.03] 1.03] 1.46]
Rate = number of pregnancies per 1000 person years; RR = Rate Ratio comparing effect on pregnancies of having a serious mental illness compared to unexposed controls, matched on observation year, year of birth and clinical practice. ⁎ P-value for effect modification by year. 143
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Table 2 Effect of serious mental illness on live-births in outcome cohort from 1992 to 2017. Variable
Any Within year 92–94 95–97 98–00 01–03 04–06 07–09 10–12 13–15 16–17
Any
Non-affective psychosis
Affective psychosis
None
N (rate)
RR [95% CI]
p-value
N (rate)
RR
p-value
N (rate)
RR [95% CI]
p-value
N (rate)
549 (23.8)
0.50 [0.45, 0.55]
<0.001
239 (21.4)
0.44 [0.39, 0.51]
<0.001
310 (26.0)
0.55 [0.49, 0.62]
<0.001
4547 (47.6)
25 29 52 76 86 73 83 97 28
0.50 0.42 0.50 0.54 0.46 0.41 0.47 0.60 0.73
0.24
11 (17.5) 15 (18.1) 27 (21.5) 45 (25.8) 38 (19.3) 30 (18.0) 26 (18.2) 40 (30.9) 7 (21.0)
0.38 0.38 0.48 0.61 0.45 0.40 0.38 0.64 0.46
0.356
14 14 25 31 48 43 57 57 21
0.79 [0.45, 1.37] 0.57 [033, 098] 0..61 [0.41, 0.93] 0.52 [0.36, 0.75] 0.53 [0.40, 0.72] 0.46 [0.34, 0.63] 0.58 [0.44, 0.76] 0.62 [0.47, 0.82] 0.96 [0.61, 1.53]
0.358
204 286 425 582 763 740 727 662 158
(24.3) (21.3) (23.9) (24.1) (21.1) (19.4) (23.7) (30.5) (33.5)
[0.33, [0.29, [0.37, [0.42, [0.37, [0.32, [0.37, [0.48, [0.48,
0.77] 0.62] 0.68] 0.69] 0.58] 0.52] 0.59] 0.75] 1.10]
[0.21, [0.23, [0.32, [0.45, [0.32, [0.28, [0.26, [0.46, [0.22,
0.70] 0.64] 0.71] 0.83] 0.63] 0.59] 0.57] 0.89] 0.98]
(34.8) (26.4) (27.3) (21.9) (22.8) (20.6) (27.6) (30.2) (41.7)
(48.5) (505) (47.2) (44.9) (45.6) (47.6) (50.0) (49.8) (45.0)
Rate = number of live-births per 1000 person years; RR = Rate Ratio comparing effect on live-births of having psychotic disorder compared to unexposed controls, matched on observation year, year of birth and clinical practice.
disadvantaged. (Power et al., 2013) Apart from the Canadian study, previous analyses are over ten years old and the UK study was undertaken before the widespread use of second-generation antipsychotics had occurred. We did not replicate the small increase over time in the relative live-birth rate of women with schizophrenia and schizoaffective disorder observed by Vigod et al. Their finding reflected a decrease in the live-birth rate in women without schizophrenia (from 43 to 37 per 1000 women (1996–2009)), whilst the live-birth rate among women with schizophrenia increased, modestly (12.8 to 15.3 per 1000 women), hence the relative fertility of women increased over time. In this analysis, the live-birth rate decreased and increased over time. We tested the interaction between time and SMI and its relationship with livebirth rate, rather than comparing rates at the beginning and end of the study. Therefore the different findings might reflect differences in the underlying population demographics and the statistical approach. We note that the raw live-birth rate amongst women with SMI appear to be increasing and replication of this analysis post-2017 is required to establish if there is a fertility trend. In this recent cohort from UK primary care, which covers the period of widespread introduction of second-generation antipsychotics, the live-birth rate did not change over time with the pregnancy rate; and more women with SMI suffered a pregnancy loss compared to women without SMI. Prior research has demonstrated that women with SMI are more likely to have pregnancy complications, (Zhong et al., 2018) including poor fetal growth of infants, which may reflect poorer maternal fetal environment. They are also more likely to have an elective abortion, (Simoila et al., 2018) suffer miscarriage, a neonatal death or stillbirth. (King-Hele et al., 2009) Further research is needed to understand whether women with SMI are increasingly electing to have terminations, experiencing more spontaneous miscarriages or increases in both types of loss, to explain these findings. Circumstances which predispose women to develop SMI (Ehrensaft et al., 2006; Taylor et al., 2015) may also affect women's physical health and, thereby, increase risk of pregnancy loss. (Hill et al., 2016) Despite the comparable antipsychotic use of women with affective
the pregnancy rate ratio during antipsychotic-free periods was 1.74 (95%CI 1.42–2.13), almost double the rate of that during times of antipsychotic use. The type of medication did not alter the rate ratio; women were equally unlikely to become pregnant when exposed to second as first-generation antipsychotics (RR 0.95, 95%CI 0.76–1.18). Excluding women who used contraception or had a history of infertility did not affect the results. The pregnancy rate almost doubled in the first six months after discontinuation of a first or second-generation antipsychotic (Fig. 2). 4. Discussion This study details the fertility trends of women with SMI in the UK from 1992–2017. Compared to women without SMI, women with SMI had fewer pregnancies (RR 0.68, 95%CI 0.64–0.73) and even fewer (half as many) live-births (RR 0.50, 95%CI 0.45–0.55). Contrary to our first hypothesis, the relative live-birth rate of women with SMI did not significantly increase over the study time period. However, the relative pregnancy rate for women with SMI changed in a non-linear fashion from 0.64 (95%CI 0.48–0.73) for the years 1992–1994 to 1.00 (95%CI 0.81–1.22) for the years 2016–2017, although this change was confined to women with affective psychosis. Overall, women with SMI experienced more pregnancy loss than women without SMI. As far as we are aware, this is the first study to examine the association between antipsychotic medication and the pregnancy rate of women with serious mental illness in the UK. The pregnancy rate of women with SMI doubled when unexposed to antipsychotics (RR 1.74, 95%CI 1.42–2.13); there was no change in the pregnancy rate when on second compared to first-generation antipsychotics (RR 0.95, 95%CI 0.76–1.18). Our findings replicate, update and extend findings in the UK, (Howard et al., 2002) Canada, (Vigod et al., 2012) Denmark (Laursen and Munk-Olsen, 2010) and Finland (Haukka et al., 2003) that women with SMI are less fertile than women without SMI; and that women with non-affective psychotic disorders are particularly
Table 3 Pregnancy rate on second with first-generation antipsychotics for the sub-cohort of 11,028 women with serious mental illness. Exposure
Person years
Number of pregnancies
Rate (per 1000 person years)
Rate Ratio*
No antipsychotic 1st Gen 2nd Gen Both
23,049 2657 9728 444
1754 100 395 15
76.1 37.6 40.6 33.7
1.74 [1.42, 2.13] REF 0.95 [0.76, 1.18] 0..83 [0.49, 1.44]
Note that there were two models fitted, one for any antipsychotic and another with 1st or 2nd generation antipsychotics. Adjusted for type of serious mental illness, year of birth, general practice and year of observation. ⁎ Controlled for age at start and time in study. 144
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Fig. 1. The proportion of women with SMI using first and second-generation antipsychotics from1992 to2017.
4.1. Strengths and limitations
and non-affective psychotic disorders only the pregnancy rate of women with affective psychoses changed between 1992 and 2017. When this analysis is restricted (1992–2014) the trend remains significant, which provide limited support these trends endure. Further research is required to quantify fertility post-2017 and test if type of SMI does mediate fertility trends. For example difficulties forming intimate relationships are a feature of non-affective but may be less so in affective psychotic disorders; this may be one of the possible mediating mechanisms. Women with SMI appear to be as unlikely to become pregnant when using first- or second-generation antipsychotic and discontinuation of any antipsychotic associated with an increased pregnancy rate. One explanation is confounding by illness severity, where women who are well are more likely to become pregnant and discontinue antipsychotics. Alternatively, the direct (Dossenbach et al., 2006) and indirect side effects associated with second-generation antipsychotics (Nulman, 2014) may negate any potential fertility benefit associated with second- antipsychotics compare to first-generation antipsychotics. We acknowledge that an increasing pregnancy rate for women with SMI may indicate, simultaneously, parity of reproductive health and disparity of reproductive choice for women with SMI. Currently, there is guidance to discuss family planning with patients when prescribing, switching or discontinuing mood stabilisers (National Institute for Health and Care Excellence (NICE) 2016) but not antipsychotics. (NICE 2014) Given that the association between discontinuation of any antipsychotic and a doubling of the pregnancy rate is evident within six months of discontinuation, current guidance should be amended to discuss family planning and prioritize the maternal health of all women with SMI, (Taylor et al., 2015) which may include support to dis/continue antipsychotic therapy. (Petersen et al., 2014)
To our knowledge, this is the first study to examine the fertility trends of women in the UK with affective and non-affective psychotic disorders over a 25 year period and to link it explicitly with change in antipsychotic exposure. Our rationale for choosing a retrospective cohort study was threefold: 1. large sample sizes are needed to generate the power necessary to investigate the relative rare exposure of SMI in women. Prospectively collected cohort studies will need to be very large and costly to investigate this population; 2. Longitudinally collected data on medications is needed to investigate time on and off second generation antipsychotics. The primary care registry used for this study has excellent data capture for medications and, unlike prospective studies, does not rely on self-report 3. There is considerably less loss to follow-up from retrospective cohort studies, limiting bias from missing data. However, the CPRD contains data collected for medical, rather than research purposes and has a number of limitations. First, the live-birth rate among women in the CPRD was lower than the national rate (eTable 2), partly because the Pregnancy Register cannot identify the outcome of approximately twenty percent of pregnancies. Recently, Minassian et al. validated the Pregnancy Register by cross referencing pregnancy and pregnancy outcomes in the register with Hospital records. They found the Pregnancy Register detects 91% of live-birth deliveries recorded in hospital, but is less accurate with respect to pregnancy losses (77%) (Minassian et al., 2019). Despite the high accuracy with respect to live-birth detection, more pregnancy outcomes were unknown for women with SMI and this may have biased our analyses and led to an underestimate of the live-birth rate. However, including unknown outcomes as live-births did not change our
145
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Fig. 2. The pregnancy rate (per 1000 person-years) of women with serious mental illness when on first or second-generation antipsychotic compared to the first six months after discontinuation.
findings. Secondly, the CPRD GOLD database may not detect all cases of SMI meaning some matched controls may have SMI thus underestimating the live-birth inequality of women with SMI. Thirdly, we cannot account for pregnancies once a women has transferred out of a general practice. The slightly shorter follow-up for women with SMI may mean the number of pregnancies and live-births are underestimated. We addressed potential confounding by matching women on maternal age, observation year and their general practice, which served as a marker for socioeconomic status. Unfortunately, the level of missing ethnicity data, particularly in the earlier period of study precluded its inclusion. Similarly, we couldn't adjust for maternal smoking, substance use or BMI or the presence of a romantic partner. (Herrett et al., 2015) However, these factors may be part of the causal pathway that link maternal mental illness to live-birth and pregnancy rates and, therefore, we would argue should not necessarily be adjusted for. (Vanderweele, 2009) Despite considerable changes in the care and therapies available to people with SMI, compared to other women, the live-birth rate of women in the UK with SMI has not significantly increased over the past 25 years. Specifically, there appears to be no fertility increase associated with the widespread change to second-generation antipsychotic use. The pregnancy rate of women with SMI is increasing and, in the future, may mean more children will be born to women with SMI (Abel et al., 2019). Resources need to be channelled to maternity and family planning services in order that these women can be identified and supported to plan their pregnancy and during their pregnancy. Traditionally, women with SMI do not engage with pregnancy planning or antenatal care as well as healthy women, (Abel and Rees, 2010) and
this needs to be taken into account in tailoring care for this vulnerable group. 5. Data availability The data was made available by the Clinical Practice Research Datalink (CPRD) obtained under licence from the UK Medicines and Healthcare products Regulatory Agency. Data is available to researchers who are approved by the Independent Scientific Advisory Committee https://www.cprd.com/Data-access. 6. Funding Funded by the European Research Council (ref: GA682741) and the National Institute for Health Research (ref: 111905). 7. Funding statement The study sponsor and funder had no role in the study design, nor the collection, analysis or interpretation of data. CRediT authorship contribution statement Holly Hope: Conceptualization, Data curation, Formal analysis, Visualization, Writing - original draft, Writing - review & editing. Rosa Parisi: Conceptualization, Writing - review & editing. Darren M Ashcroft: Conceptualization, Writing - review & editing. Rachael Williams: Conceptualization, Writing - review & editing. Sonia Coton: 146
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Conceptualization, Writing - review & editing. Kyriaki Kosidou: Writing - review & editing. Matthias Pierce: Conceptualization, Data curation, Formal analysis, Writing - review & editing. Kathryn M Abel: Conceptualization, Funding acquisition, Writing - original draft, Writing - review & editing.
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Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgements The authors would like to note the contribution of Wilhelmine Meeraus (CPRD), Caroline Minassian & Sara Thomas, London School of Hygiene & Tropical Medicine (LSHTM) to the development of the Pregnancy Register algorithm. Supplementary materials Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.jad.2020.03.037. References Howard, L.M., Kumar, C., Leese, M., Thornicroft, G, 2002. The general fertility rate in women with psychotic disorders. Am. J. Psychiatry 159, 991–997. Laursen, T.M., Munk-Olsen, T., 2010a. Reproductive patterns in psychotic patients. Schizophr. Res. 121, 234–240. Power, R.A., Kyaga, S., Uher, R., MacCabe, J.H., Långström, N., Landen, M., et al., 2013. Fecundity of patients with schizophrenia, autism, bipolar disorder, depression, anorexia nervosa, or substance abuse vs their unaffected siblings. JAMA Psychiatry 70, 22–30. Abel, K., Rees, S., 2010. Reproductive and sexual health of women service users: what's the fuss. Adv. Psychiatr. Treat. 16, 279–280. Goff, D.C., Sullivan, L.M., McEvoy, J.P., Meyer, J.M., Nasrallah, H.A., Daumit, G.L., et al., 2005. A comparison of ten-year cardiac risk estimates in schizophrenia patients from the CATIE study and matched controls. Schizophr. Res. 80, 45–53. De Hert, M., Correll, C.U., Bobes, J., Cetkovich-Bakmas, M., Cohen, D., Asai, I., et al., 2011. Physical illness in patients with severe mental disorders. I. Prevalence, impact of medications and disparities in health care. World Psychiatry 10, 52–77. Naylor H., Edward G., Beccy P., Nigel A., Edwards C. Service transformation lessons from mental health., 2014(https://www.kingsfund.org.uk/sites/default/files/field/field_ publication_file/service-transformation-lessons-mental-health-4-feb-2014.pdf). Kaye, J.A., Bradbury, B.D., Jick, H, 2003. Changes in antipsychotic drug prescribing by general practitioners in the United Kingdom from 1991 to 2000: a population-based observational study. Br. J. Clin. Pharmacol. 56, 569–575. Jones I., Chandra P.S., Dazzan P., Howard L.M. Perinatal mental health 2 bipolar disorder, aff ective psychosis, and schizophrenia in pregnancy and the post-partum period., 201410.1016/S0140-6736(14)61278-2. Bargiota, S.I., Bonotis, K.S., Messinis, I.E., Angelopoulos, N.V., 2013. The effects of antipsychotics on prolactin levels and women's menstruation. Schizophr. Res. Treat. 2013, 502697. Vigod, S.N., Seeman M, V., Ray, J.G., Anderson, G.M., Dennis, C.L., Grigoriadis, S., et al., 2012. Temporal trends in general and age-specific fertility rates among women with
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Journal of Affective Disorders journal homepage: www.elsevier.com/locate/jad
Research paper
Fertility trends of women with serious mental illness in the United Kingdom 1992–2017: A primary care cohort study using the clinical practice research datalink
T
Holly Hopea, , Rosa Parisib,c, Darren M Ashcroftc, Rachael Williamsd, Sonia Cotond, Kyriaki Kosidoue,f, Matthias Piercea,1, Kathryn M Abela,g,1 ⁎
a
Centre for Women’s Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, UK Division of Informatics, Imaging and Data Science, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, UK Centre for Pharmacoepidemiology and Drug Safety, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, UK d Clinical Practice Research Datalink, Medicines and Healthcare products Regulatory Agency, UK e Center for Epidemiology and Community Medicine, Region Stockholm, Sweden f Department of Global Public Health, Karolinska Institute, Stockholm, Sweden g Greater Manchester Mental Health NHS Foundation Trust, UK b c
ARTICLE INFO
ABSTRACT
Keywords: Fertility Women Schizophrenia Bipolar disorder Psychotic disorders Antipsychotics
Background: Changes in care may mean women with serious mental illness (SMI) are more fertile. We investigated 1) the live-birth and pregnancy rate of women with and without SMI over time, 2) the likelihood of pregnancy when using second or first-generation antipsychotics. Method: Retrospective cohort study of women (15–45 years) registered in Clinical Practice Research Datalink (CPRD) general practices between 1992 and 2017. Each analysis year, women with SMI (affective and nonaffective psychotic disorder) were matched with up to four women with no record of SMI on age, calendar year and general practice. Pregnancy and live-birth rates and the rate ratio (RR) comparing women with and without SMI were estimated. The stability of the RR between years was tested. For women with SMI, the pregnancy rates when on or off first or second-generation antipsychotics were calculated and compared using Poisson regression models. Results: In total, 12,524 women with SMI were matched to 50,074 women without SMI, median age 34 [IQR 28–39] years. Between 1992 and 2017 women with SMI had 50% fewer live-births than women without SMI (RR 0..50, 95%CI 0.45–0.55). The pregnancy rate ratio increased from 0.64 (95%CI 0.48–0.86) (1992–1994) to 1.00 (95%CI 0.81–1.22) (2016–2017), (p < 0.0001), but this change was only seen in women with affective disorders. Women are most likely to become pregnant after discontinuing either a second-generation or firstgeneration antipsychotic (RR 1.74, 95%CI 1.42–2.13). Conclusions: Women with SMI are increasingly experiencing pregnancy but not live-birth, which suggests the reproductive health needs of these women are unmet.
1. Introduction Women with serious mental illness (SMI), namely affective and nonaffective psychotic disorders, are less likely to get pregnant and have children than women without SMI, (Howard et al., 2002) and women with common mental illnesses, (Laursen and Munk-Olsen, 2010; Power et al., 2013) and, thus, have considerably lower fertility. This
information potentially highlights an important physical health inequality for women with serious mental illness (SMI) (Abel and Rees, 2010) and one which receives relatively little public health attention compared to cardiovascular, (Goff et al., 2005) or metabolic health (De Hert et al., 2011). In the last two decades, better treatment and community-based care may provide women with SMI more opportunities to develop relationships and start a family. (Naylor et al.,
Corresponding author: Centre for Women's Mental Health, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Room 3.320 Jean McFarlane Building, Oxford Road, Manchester, UK. E-mail address: [email protected] (H. Hope). 1 Shared senior authorship ⁎
https://doi.org/10.1016/j.jad.2020.03.037 Received 13 September 2019; Received in revised form 20 December 2019; Accepted 19 March 2020 Available online 20 March 2020 0165-0327/ © 2020 Elsevier B.V. All rights reserved.
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2014) In addition, since the mid 1990′s, second-generation antipsychotics are increasingly prescribed as first line agents in the treatment of SMI. (Kaye et al., 2003) These drugs were heralded as less likely to induce physical side effects, including hyperprolactinaemia and disruption of fertility. (Jones et al., 2014; Bargiota et al., 2013) However, only one prior study has examined if fertility has changed over time. (Vigod et al., 2012) Vigod et al. 2012 assessed 2473 live-births of women with schizophrenia from 1996 to 2009 in Canada and observed an increase in the relative fertility rate compared to women without schizophrenia from a rate-ratio of 0.30 (95% CI 0.25–0.35) in 1996 to 0.41 (95% CI 0.36–0.47) in 2009. However, to our knowledge, no prior analysis has compared the fertility of women with and without affective and non-affective psychotic disorders and if this has changed over the years where women were switched from first- to second-generation antipsychotics. In addition, our analytical approach will investigate the relative fertility of women with SMI for all years, rather than comparing rates of live births in the entry and end year of study. Nor has the link between first and second antipsychotic exposure and pregnancy in women with SMI been explicitly examined. Women with SMI and their offspring are a vulnerable group (King-Hele et al., 2009; MunkOlsen and Agerbo, 2015) therefore it is a public health imperative to investigate the fertility trends of women with SMI in order to properly resource the required services. Our study uses a large UK cohort identified in a primary care database to investigate trends in both pregnancy and live-births in women with SMI from 1992–2017. Our intention is first to investigate trends in the pregnancy and live-birth rate for women with serious mental illness (affective and non-affective psychoses) using women without SMI as a reference group. Second, and for the first time, we shall quantify the association between first and second-generation antipsychotic exposure and female fertility. We, therefore, test the following hypotheses: 1) Women with SMI relative to women without SMI experience increasing pregnancy and fertility (live-birth) rates from 1992–2017; and 2) second-generation compared to first-generation antipsychotic use associates with an increased likelihood of pregnancy for women with SMI.
resulted in 2680,149 and 2361,107 women available for the analysis of pregnancy and pregnancy outcome respectively (eFigure 1). The proportion of the cohort in each year of the study period diagnosed with SMI was 0.20% in 1992 and 0.23% in 2017 (eTable 1). 2.3. Exposure definitions Serious mental illness included a record of a diagnosis of a nonaffective psychotic disorder (e.g. schizophrenia, schizotypal, delusional, psychosis NOS) or affective psychotic disorder (e.g. bipolar, manic, schizoaffective disorders, or depression with psychosis). Read codes were identified by HH and validated by two psychiatrists (ES and KMA). All prescriptions for antipsychotics were identified by HH and verified by KMA and DMA. A previously developed algorithm cleaned the prescription data, calculated the duration and end date and handled incongruous prescription data. (Pye et al., 2018) The algorithm is further detailed in supplementary material (eFigure 2). Prescriptions were classed as first or second-generation antipsychotics according to the British National Formulary. 2.4. Identifying pregnancies and live-births In the UK, an estimated 83% of women report their pregnancy to their general practitioner before other healthcare professionals, and most will visit primary care as a component of their antenatal or postnatal care. (Redshaw et al., 2006) The CPRD, in collaboration with the London School of Hygiene and Tropical Medicine (LSHT), created a Pregnancy Register algorithm; utilizing >4000 medical codes and datatypes, it extracts discrete pregnancy episodes and their outcome. Currently, the CPRD/LSHTM are publishing validation work to establish the algorithm's ability to detect pregnancies and birth outcomes. As a data-quality exercise, we compared the live-birth rate of the Pregnancy Register with that in published national statistics and assessed whether this varied by age-group and period (eTable 2). (Office for National Statistics, 2016) A significant proportion of pregnancy outcomes (16% overall, 21% in this study) are unknown. As a sensitivity analysis, we included births where the pregnancy was ‘unknown’ in our definition of live-births. Also, 11% of pregnancy outcomes (10% in this study) were considered “probable termination of pregnancy” and classed as “abortions”, however the main analyses were restricted to live-births. The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008. This study is based in part on data from the Clinical Practice Research Datalink (CPRD) obtained under licence from the UK Medicines and Healthcare products Regulatory Agency. The data is provided by patients and collected by the NHS as part of their care and support. The study was approved by the Independent Scientific Advisory Committee for CPRD research (protocol number: 17_187)
2. Methods 2.1. Data source Data for this retrospective cohort study comes from the UK Clinical Practice Research Datalink (CPRD) GOLD primary care database. The dataset (Jan 2018) used for this analysis contained data on over 15.3 million primary care patients. CPRD GOLD includes individual-linked data on clinical consultations, treatments, referrals and tests, in addition to patient demographics and practice data since 1987. (Herrett et al., 2015) General practitioners’ record of diagnoses, symptoms and other information during a consultation are codified using Read codes. (Chisholm, 1990) 2.2. Study population The cohort for this analysis was selected from 3624,708 women registered at a CPRD GOLD-participating practice and aged 15 to 44 during the study window: 1st January 1990 to 31st December 2017. Women were considered eligible for inclusion if registered for at least two years at a general practice (GP) from the date it provided up-tostandard (UTS) data (a CPRD measure of data quality), in order to have an adequate observation window to ascertain exposure. They became ineligible at the earliest date of age 45; death; date the GP stopped collecting data; or they transferred out of a participating GP. For analysis of live-births, we included the further criterion that women must have at least 44 weeks of data prior to the date they transferred out from the participating practice or from the date the practice stopped contributing data to the CPRD. This additional criterion helped to ensure that data were available on the outcome of pregnancies. This
2.5. Analysis For each analysis year (1992–2017), eligible women were classified as exposed if they had a SMI diagnosis in the two years prior to the analysis year and unexposed if there was no diagnosis of SMI in their record. Subtypes of non-affective and affective psychotic disorders were identified. There were 3522 instances where women had diagnostic codes relating to both affective and non-affective psychotic disorders and these were classified using the latest recorded code. Instances where there were codes relating to both at the same date (n = 145) were coded as having non-affective psychosis. For each analysis year, women identified as having a recent history of psychotic disorder were matched (without replacement) to up to four unexposed women (no 142
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(rate = 48.9) and 8911 pregnancies among women without SMI (rate = 80.9). Relative to women without SMI, women with SMI had 32% fewer pregnancies (RR 0.68, 95% confidence interval (CI) 0.64–0.73) and the rate ratio changed significantly over time (p < 0.001). The pregnancy rate ratio decreased from 0.64 (95%CI 0.48–0.86) in 1992–1994 to 0.52 (95%CI 0.44–0.61) in 2004–2006 and increased to a peak at 1.00 (95%CI 0.8–1.22) in 2016–2017. The overall pregnancy rate ratio of women with affective psychotic disorders was 0.75 (95%CI 0.69–0.81) and this also changed significantly over time (p < 0.001): it decreased from 0.84 (95%CI 0.56–1.25) in 1992–1994 to 0.56 (95%CI 0.45–0.69) in 2004–2006 and increased to 1.00 (95%CI 0.83–1.20) in 2016–2017. In contrast, the pregnancy rate ratio of women with non-affective psychotic disorders was 0.61 (95%CI 0.56–0.67) and remained stable over time (p = 0.64) at 0.56 (95%CI 0.38–0.83) in 1992–1994, 0.54 (0.43–0.68) in 2004–2006 and 0.79 (0.58–1.09) in 2016–2017. The live-birth rate of women with serious mental illness (Table 2) The live-birth rate for women with SMI increased from 24.3 per 1000 person years during the period 1992–1994 to 33.5 from 2016–2017. There were 549 live-births among women with a recent SMI diagnosis (rate = 23.8) and 4547 live-births among women without a history of SMI (rate = 47.6) in the live-birth outcome cohort over the study period. Relative to women without SMI, women with SMI had fewer live-births (RR 0.50, 95%CI 0.45–0.55), and despite the apparent increasing birth rate among women with SMI this association did not significantly change over time (p = 0.24). Similarly, women with nonaffective psychotic disorders and women with affective psychotic disorders had fewer births relative to women without SMI (RR 0.44, 95% CI 0.39–0.51 and RR 0.55, 95%CI 0.49–0.62 respectively) and these associations did not change over time (p = 0.36). Other pregnancy outcomes (eTable 3) There were 10,640 pregnancies during the study period among women in the pregnancy outcome cohort. Fewer pregnancies resulted in a live-birth outcome for women with SMI than women without SMI (46.9% vs 57.9%). However, more pregnancies resulted in a termination (15.1% vs 9.9%) or an unknown pregnancy outcome (25.2% vs 20.9%) for women with SMI than women without SMI. The effect of antipsychotic use on the pregnancy rate of women with serious mental illness (Table 3) The rate of antipsychotic use was stable and there was a clear switch to second-generation antipsychotic prescribing from the year 2000 for women with SMI (Fig. 1). Women with SMI had 41.2 pregnancies whilst exposed and 82.1 pregnancies per 1000 person years when unexposed to any antipsychotic medication. After adjustment for type of SMI, year of birth and general practice,
record of SMI) who shared the same year of birth and general practice. Therefore, women with SMI might be observed in multiple years. The number of pregnancies and live-births were counted within each analysis year and divided by the follow-up time, within each exposure category. These counts were modelled using a negative binomial model and an off-set term of follow-up time was included in the model to account for differential follow-up time for each year. The resulting parameter is interpreted as a rate ratio. This was estimated using a Generalised Estimating Equation model with an exchangeable correlation structure to account for multiple years of follow-up for each subject. The GEE model is used to account for the longitudinal structure of the data, and the fact that women may be followed up over multiple calendar years. These models are suitable when the quantity of interest is in the population average change in the dependent variable, rather than the within subject change, when there is a unit change in the independent variable. 2.6. Sub-cohort analysis To determine whether the rate of pregnancy was higher on second or first-generation antipsychotics the sub-cohort of women with SMI aged 15 to 40 years (n = 11,028) were followed-up for up to 5-years following their first diagnosis and their pregnancy rate on and off first and second-generation antipsychotics was calculated. The rate ratio comparing the pregnancy rate on second with first-generation antipsychotic use, or both, was estimated using Poisson regression models, controlling for age at diagnosis and the square of age at diagnosis. Women who used contraception or had a history of infertility may not conceive for other reasons than exposure to antipsychotics, therefore as a sensitivity analysis these women were excluded. Post-hoc, we examined the proximity of the effect by restricting the analysis. The pregnancy rate whilst on a first or second generation antipsychotic was compared with the rate during the first six months after discontinuation. 3. Results A total of 12,524 women with SMI were identified in the cohort and matched by age and practice to 50,074 women with no history of serious mental illness (eFigure1). The median age of women was 34 [28–39] years for women exposed and unexposed to SMI. The pregnancy rate of women with serious mental illness (Table 1) The pregnancy rate of women with SMI was 48.7 (pregnancies per 1000-person years) in 1992–1994, this rate dipped to its lowest in 2004–2006 (40.3) and increased to its highest in 2016–2017 (74.0). Overall, there were 1449 pregnancies among women with SMI
Table 1 The effect of serious mental illness on pregnancies in the pregnancy cohort from 1992 to 2017. Variable
Any Within year 92–94 95–97 98–00 01–03 04–06 07–09 10–12 13–15 16–17
Any
Non-affective psychosis
Affective psychosis
None
N (rate)
RR [95% CI]
p-value
N (rate)
RR
p-value
N (rate)
RR [95% CI]
p-value
N (rate)
1449 (54.7)
0.68 [0.64, 0.73]
<0.001
624 (48.9)
0.61 [0.56, 0.67]
<0.001
825 (60.0)
0.75 [0.69, 0.81]
<0.001
8911 (80.9)
54 (48.7) 74 (50.8) 117 (50.3) 154 (45.2) 177 (40.3) 208 (50.5) 269 (68.9) 266 (65.9) 130 (74.0)
0.64 0.72 0.73 0.60 0.52 0.61 0.77 0.74 1.00
<0.001*
27 40 64 86 86 98 94 86 43
0.56 0.65 0.72 0.63 0.54 0.68 0.68 0.61 0.79
0.649
27 (61.4) 34 (60.3) 53 (54.5) 68 (45.2) 91 (40.5) 110 (48.1) 175 (75.6) 180 (75.5) 87 (84.5)
0.84 0.88 0.81 0.62 0.56 0.60 0.87 0.88 1.15
<0.001
364 (79.9) 457 (74.9) 680 (70.8) 1090 (77.4) 1446 (79.3) 1427 (83.9) 1452 (88.6) 1461 (87.0) 534 (72.5)
[0.48, [0.56, [0.60, [0.50, [0.44, [0.52, [0.67, [0.64, [0.81,
0.86] 0.92] 0.90] 0.71] 0.61] 0.71] 0.88] 0.85] 1.22]
(40.4) (44.9) (47.3) (45.3) (40.1) (53.4) (59.2) (52.0) (59.1)
[0.38, [0.47, [0.56, [0.51, [0.43, [0.55, [0.55, [0.49, [0.58,
0.83] 0.90] 0.94] 0.79] 0.68] 0.84] 0.85] 0.76] 1.09]
[0.56, [0.62, [0.60, [0.49, [0.45, [0.49, [0.74, [0.74, [0.91,
1.25] 1.25] 1.08] 0.80] 0.69] 0.73] 1.03] 1.03] 1.46]
Rate = number of pregnancies per 1000 person years; RR = Rate Ratio comparing effect on pregnancies of having a serious mental illness compared to unexposed controls, matched on observation year, year of birth and clinical practice. ⁎ P-value for effect modification by year. 143
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Table 2 Effect of serious mental illness on live-births in outcome cohort from 1992 to 2017. Variable
Any Within year 92–94 95–97 98–00 01–03 04–06 07–09 10–12 13–15 16–17
Any
Non-affective psychosis
Affective psychosis
None
N (rate)
RR [95% CI]
p-value
N (rate)
RR
p-value
N (rate)
RR [95% CI]
p-value
N (rate)
549 (23.8)
0.50 [0.45, 0.55]
<0.001
239 (21.4)
0.44 [0.39, 0.51]
<0.001
310 (26.0)
0.55 [0.49, 0.62]
<0.001
4547 (47.6)
25 29 52 76 86 73 83 97 28
0.50 0.42 0.50 0.54 0.46 0.41 0.47 0.60 0.73
0.24
11 (17.5) 15 (18.1) 27 (21.5) 45 (25.8) 38 (19.3) 30 (18.0) 26 (18.2) 40 (30.9) 7 (21.0)
0.38 0.38 0.48 0.61 0.45 0.40 0.38 0.64 0.46
0.356
14 14 25 31 48 43 57 57 21
0.79 [0.45, 1.37] 0.57 [033, 098] 0..61 [0.41, 0.93] 0.52 [0.36, 0.75] 0.53 [0.40, 0.72] 0.46 [0.34, 0.63] 0.58 [0.44, 0.76] 0.62 [0.47, 0.82] 0.96 [0.61, 1.53]
0.358
204 286 425 582 763 740 727 662 158
(24.3) (21.3) (23.9) (24.1) (21.1) (19.4) (23.7) (30.5) (33.5)
[0.33, [0.29, [0.37, [0.42, [0.37, [0.32, [0.37, [0.48, [0.48,
0.77] 0.62] 0.68] 0.69] 0.58] 0.52] 0.59] 0.75] 1.10]
[0.21, [0.23, [0.32, [0.45, [0.32, [0.28, [0.26, [0.46, [0.22,
0.70] 0.64] 0.71] 0.83] 0.63] 0.59] 0.57] 0.89] 0.98]
(34.8) (26.4) (27.3) (21.9) (22.8) (20.6) (27.6) (30.2) (41.7)
(48.5) (505) (47.2) (44.9) (45.6) (47.6) (50.0) (49.8) (45.0)
Rate = number of live-births per 1000 person years; RR = Rate Ratio comparing effect on live-births of having psychotic disorder compared to unexposed controls, matched on observation year, year of birth and clinical practice.
disadvantaged. (Power et al., 2013) Apart from the Canadian study, previous analyses are over ten years old and the UK study was undertaken before the widespread use of second-generation antipsychotics had occurred. We did not replicate the small increase over time in the relative live-birth rate of women with schizophrenia and schizoaffective disorder observed by Vigod et al. Their finding reflected a decrease in the live-birth rate in women without schizophrenia (from 43 to 37 per 1000 women (1996–2009)), whilst the live-birth rate among women with schizophrenia increased, modestly (12.8 to 15.3 per 1000 women), hence the relative fertility of women increased over time. In this analysis, the live-birth rate decreased and increased over time. We tested the interaction between time and SMI and its relationship with livebirth rate, rather than comparing rates at the beginning and end of the study. Therefore the different findings might reflect differences in the underlying population demographics and the statistical approach. We note that the raw live-birth rate amongst women with SMI appear to be increasing and replication of this analysis post-2017 is required to establish if there is a fertility trend. In this recent cohort from UK primary care, which covers the period of widespread introduction of second-generation antipsychotics, the live-birth rate did not change over time with the pregnancy rate; and more women with SMI suffered a pregnancy loss compared to women without SMI. Prior research has demonstrated that women with SMI are more likely to have pregnancy complications, (Zhong et al., 2018) including poor fetal growth of infants, which may reflect poorer maternal fetal environment. They are also more likely to have an elective abortion, (Simoila et al., 2018) suffer miscarriage, a neonatal death or stillbirth. (King-Hele et al., 2009) Further research is needed to understand whether women with SMI are increasingly electing to have terminations, experiencing more spontaneous miscarriages or increases in both types of loss, to explain these findings. Circumstances which predispose women to develop SMI (Ehrensaft et al., 2006; Taylor et al., 2015) may also affect women's physical health and, thereby, increase risk of pregnancy loss. (Hill et al., 2016) Despite the comparable antipsychotic use of women with affective
the pregnancy rate ratio during antipsychotic-free periods was 1.74 (95%CI 1.42–2.13), almost double the rate of that during times of antipsychotic use. The type of medication did not alter the rate ratio; women were equally unlikely to become pregnant when exposed to second as first-generation antipsychotics (RR 0.95, 95%CI 0.76–1.18). Excluding women who used contraception or had a history of infertility did not affect the results. The pregnancy rate almost doubled in the first six months after discontinuation of a first or second-generation antipsychotic (Fig. 2). 4. Discussion This study details the fertility trends of women with SMI in the UK from 1992–2017. Compared to women without SMI, women with SMI had fewer pregnancies (RR 0.68, 95%CI 0.64–0.73) and even fewer (half as many) live-births (RR 0.50, 95%CI 0.45–0.55). Contrary to our first hypothesis, the relative live-birth rate of women with SMI did not significantly increase over the study time period. However, the relative pregnancy rate for women with SMI changed in a non-linear fashion from 0.64 (95%CI 0.48–0.73) for the years 1992–1994 to 1.00 (95%CI 0.81–1.22) for the years 2016–2017, although this change was confined to women with affective psychosis. Overall, women with SMI experienced more pregnancy loss than women without SMI. As far as we are aware, this is the first study to examine the association between antipsychotic medication and the pregnancy rate of women with serious mental illness in the UK. The pregnancy rate of women with SMI doubled when unexposed to antipsychotics (RR 1.74, 95%CI 1.42–2.13); there was no change in the pregnancy rate when on second compared to first-generation antipsychotics (RR 0.95, 95%CI 0.76–1.18). Our findings replicate, update and extend findings in the UK, (Howard et al., 2002) Canada, (Vigod et al., 2012) Denmark (Laursen and Munk-Olsen, 2010) and Finland (Haukka et al., 2003) that women with SMI are less fertile than women without SMI; and that women with non-affective psychotic disorders are particularly
Table 3 Pregnancy rate on second with first-generation antipsychotics for the sub-cohort of 11,028 women with serious mental illness. Exposure
Person years
Number of pregnancies
Rate (per 1000 person years)
Rate Ratio*
No antipsychotic 1st Gen 2nd Gen Both
23,049 2657 9728 444
1754 100 395 15
76.1 37.6 40.6 33.7
1.74 [1.42, 2.13] REF 0.95 [0.76, 1.18] 0..83 [0.49, 1.44]
Note that there were two models fitted, one for any antipsychotic and another with 1st or 2nd generation antipsychotics. Adjusted for type of serious mental illness, year of birth, general practice and year of observation. ⁎ Controlled for age at start and time in study. 144
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Fig. 1. The proportion of women with SMI using first and second-generation antipsychotics from1992 to2017.
4.1. Strengths and limitations
and non-affective psychotic disorders only the pregnancy rate of women with affective psychoses changed between 1992 and 2017. When this analysis is restricted (1992–2014) the trend remains significant, which provide limited support these trends endure. Further research is required to quantify fertility post-2017 and test if type of SMI does mediate fertility trends. For example difficulties forming intimate relationships are a feature of non-affective but may be less so in affective psychotic disorders; this may be one of the possible mediating mechanisms. Women with SMI appear to be as unlikely to become pregnant when using first- or second-generation antipsychotic and discontinuation of any antipsychotic associated with an increased pregnancy rate. One explanation is confounding by illness severity, where women who are well are more likely to become pregnant and discontinue antipsychotics. Alternatively, the direct (Dossenbach et al., 2006) and indirect side effects associated with second-generation antipsychotics (Nulman, 2014) may negate any potential fertility benefit associated with second- antipsychotics compare to first-generation antipsychotics. We acknowledge that an increasing pregnancy rate for women with SMI may indicate, simultaneously, parity of reproductive health and disparity of reproductive choice for women with SMI. Currently, there is guidance to discuss family planning with patients when prescribing, switching or discontinuing mood stabilisers (National Institute for Health and Care Excellence (NICE) 2016) but not antipsychotics. (NICE 2014) Given that the association between discontinuation of any antipsychotic and a doubling of the pregnancy rate is evident within six months of discontinuation, current guidance should be amended to discuss family planning and prioritize the maternal health of all women with SMI, (Taylor et al., 2015) which may include support to dis/continue antipsychotic therapy. (Petersen et al., 2014)
To our knowledge, this is the first study to examine the fertility trends of women in the UK with affective and non-affective psychotic disorders over a 25 year period and to link it explicitly with change in antipsychotic exposure. Our rationale for choosing a retrospective cohort study was threefold: 1. large sample sizes are needed to generate the power necessary to investigate the relative rare exposure of SMI in women. Prospectively collected cohort studies will need to be very large and costly to investigate this population; 2. Longitudinally collected data on medications is needed to investigate time on and off second generation antipsychotics. The primary care registry used for this study has excellent data capture for medications and, unlike prospective studies, does not rely on self-report 3. There is considerably less loss to follow-up from retrospective cohort studies, limiting bias from missing data. However, the CPRD contains data collected for medical, rather than research purposes and has a number of limitations. First, the live-birth rate among women in the CPRD was lower than the national rate (eTable 2), partly because the Pregnancy Register cannot identify the outcome of approximately twenty percent of pregnancies. Recently, Minassian et al. validated the Pregnancy Register by cross referencing pregnancy and pregnancy outcomes in the register with Hospital records. They found the Pregnancy Register detects 91% of live-birth deliveries recorded in hospital, but is less accurate with respect to pregnancy losses (77%) (Minassian et al., 2019). Despite the high accuracy with respect to live-birth detection, more pregnancy outcomes were unknown for women with SMI and this may have biased our analyses and led to an underestimate of the live-birth rate. However, including unknown outcomes as live-births did not change our
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Fig. 2. The pregnancy rate (per 1000 person-years) of women with serious mental illness when on first or second-generation antipsychotic compared to the first six months after discontinuation.
findings. Secondly, the CPRD GOLD database may not detect all cases of SMI meaning some matched controls may have SMI thus underestimating the live-birth inequality of women with SMI. Thirdly, we cannot account for pregnancies once a women has transferred out of a general practice. The slightly shorter follow-up for women with SMI may mean the number of pregnancies and live-births are underestimated. We addressed potential confounding by matching women on maternal age, observation year and their general practice, which served as a marker for socioeconomic status. Unfortunately, the level of missing ethnicity data, particularly in the earlier period of study precluded its inclusion. Similarly, we couldn't adjust for maternal smoking, substance use or BMI or the presence of a romantic partner. (Herrett et al., 2015) However, these factors may be part of the causal pathway that link maternal mental illness to live-birth and pregnancy rates and, therefore, we would argue should not necessarily be adjusted for. (Vanderweele, 2009) Despite considerable changes in the care and therapies available to people with SMI, compared to other women, the live-birth rate of women in the UK with SMI has not significantly increased over the past 25 years. Specifically, there appears to be no fertility increase associated with the widespread change to second-generation antipsychotic use. The pregnancy rate of women with SMI is increasing and, in the future, may mean more children will be born to women with SMI (Abel et al., 2019). Resources need to be channelled to maternity and family planning services in order that these women can be identified and supported to plan their pregnancy and during their pregnancy. Traditionally, women with SMI do not engage with pregnancy planning or antenatal care as well as healthy women, (Abel and Rees, 2010) and
this needs to be taken into account in tailoring care for this vulnerable group. 5. Data availability The data was made available by the Clinical Practice Research Datalink (CPRD) obtained under licence from the UK Medicines and Healthcare products Regulatory Agency. Data is available to researchers who are approved by the Independent Scientific Advisory Committee https://www.cprd.com/Data-access. 6. Funding Funded by the European Research Council (ref: GA682741) and the National Institute for Health Research (ref: 111905). 7. Funding statement The study sponsor and funder had no role in the study design, nor the collection, analysis or interpretation of data. CRediT authorship contribution statement Holly Hope: Conceptualization, Data curation, Formal analysis, Visualization, Writing - original draft, Writing - review & editing. Rosa Parisi: Conceptualization, Writing - review & editing. Darren M Ashcroft: Conceptualization, Writing - review & editing. Rachael Williams: Conceptualization, Writing - review & editing. Sonia Coton: 146
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Conceptualization, Writing - review & editing. Kyriaki Kosidou: Writing - review & editing. Matthias Pierce: Conceptualization, Data curation, Formal analysis, Writing - review & editing. Kathryn M Abel: Conceptualization, Funding acquisition, Writing - original draft, Writing - review & editing.
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