IJE Advance Access originally published online on July 31, 2006
International Journal of Epidemiology 2006 35(5):1169-1177; doi:10.1093/ije/dyl154
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Maternal and biochemical predictors of spontaneous preterm birth among nulliparous women: a systematic analysis in relation to the degree of prematurity
1 Department of Obstetrics and Gynaecology, Cambridge University, Cambridge, CB2 2QQ, UK
2 Medical Research Council Biostatistics Unit, Institute of Public Health, Robinson Way, Cambridge CB2 2SR, UK
3 Department of Public Health, Greater Glasgow NHS Board, Glasgow, G3 8YU, UK
4 Institute of Medical Genetics, Yorkhill NHS Trust, Glasgow, G3 8SJ, UK
5 Information and Statistics Division, Common Services Agency, Edinburgh, EH5 3SE, UK
* Corresponding author. Professor of Obstetrics and Gynaecology, Cambridge University, Rosie Maternity Hospital, Cambridge, CB2 2SW, UK. E-mail: gcss2{at}cam.ac.uk
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Background Nulliparous women are at increased risk of spontaneous preterm birth. Other maternal and biochemical risk factors have also been described. However, it is unclear whether these associations are strong enough to offer clinically useful prediction. It is also unclear whether the predictive power of these factors varies in relation to the degree of prematurity.
Methods The risk of spontaneous preterm birth associated with maternal characteristics and second trimester serum screening data was analysed in a dataset of 84 391 first births in Scotland between 1992 and 2001 using Cox and logistic regression. Variation in the relative risk of preterm birth over the period 24–36 weeks was assessed using a test of the proportional hazards assumption.
Results The risk of spontaneous preterm birth was positively associated with maternal serum levels of alpha-fetoprotein, socioeconomic deprivation, number of previous therapeutic abortions, smoking, and being unmarried and was negatively associated with height and body mass index. The risk of preterm birth at 24–28 weeks, but not later gestations, was increased in association with maternal levels of human chorionic gonadotrophin >95th percentile, maternal age <20, and two or more previous miscarriages. The area under the receiver operating characterise curve (95% CI) for models based on these factors was 0.67 (0.63–0.71) for 24–28 weeks, 0.65 (0.62–0.68) for 29–32 weeks, and 0.62 (0.61–0.63) for 33–36 weeks.
Conclusions Time to event analytic methods can identify factors that are differentially associated with spontaneous preterm birth according to the degree of prematurity. However, models based on maternal and biochemical data perform poorly as a screening test for any degree of spontaneous preterm birth.
Keywords alpha-Fetoproteins, chorionic gonadotrophin, labour, premature, proportional hazards models, risk
Accepted 15 June 2006
Preterm birth is a major source of morbidity and mortality in the neonatal period and in infancy and later childhood.1–4 One of the major clinical risk factors for spontaneous preterm birth is a previous pregnancy that ended in this event. Self evidently, this information is not available for woman having a first birth, making risk assessment in this substantial proportion of the population problematic. A number of other factors have, however, been shown to be associated with the risk of spontaneous preterm birth, and these have been reviewed elsewhere.5,6 However, it remains unclear whether the combined information available from such characteristics provides useful predictive information.
A further complication in assessing risk factors for spontaneous preterm birth is the degree of prematurity. Whereas birth between 33 and 36 weeks gestation carries a relatively favourable short-term and long-term prognosis, extreme preterm birth is associated with high absolute risks of death and severe disability.1,4 The profoundly different consequences of extreme, moderate, and mild prematurity mean that interventions to reduce the risk of these events should be targeted at the clinically important extreme cases. However, many analyses of factors associated with the risk of preterm birth fail to distinguish between different degrees of prematurity. Moreover, we are unaware of any widely utilized approach to determine objectively whether the relative risk associated with a given factor significantly varies across the range of gestational age.
We have previously proposed that time to event analytic methods, specifically Cox proportional hazards regression, might be employed in assessing the factors associated with the spontaneous onset of labour.7 Tests have been developed using residuals estimated from the Cox model, which allow a formal test of the assumption that the relative risk of an event associated with a given factor is the same across a period of time.8 This analytic approach could also be used to determine whether the strength of association between the risk of spontaneous preterm birth and maternal or obstetric factors varies in relation to the degree of prematurity. We are unaware of any study that has previously performed such an analysis.
In the present study, we analysed data from over 80 000 women having first pregnancies in the West of Scotland and sought to determine (i) which maternal and biochemical factors are associated with the relative risk of spontaneous preterm birth over the period 24–36 weeks gestation, (ii) whether the relative risks associated with these factors significantly varied over the period 24–36 weeks, and (iii) whether these factors could yield clinically useful prediction of risk.
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Data sources and patient selection
The Scottish Morbidity Record collects information on clinical and demographic characteristics and outcomes for all women discharged from Scottish maternity hospitals. The register is subjected to regular quality assurance checks and has been >99% complete since the late 1970s.9 The Scottish Stillbirth and Infant Death Enquiry is a national register, which routinely classifies all perinatal deaths in Scotland.10 All women attending for prenatal care in the West of Scotland are offered biochemical screening, using maternal serum levels of alpha-fetoprotein (AFP) and human chorionic gonadotrophin (hCG), to assess their risk of having a fetus affected by Down syndrome and/or structural fetal abnormality.11 The laboratory information management system for the West of Scotland prenatal screening programme in the Institute of Medical Genetics in Glasgow contains a database of the maternal information and biochemical screening results, and electronic storage of these data in their current form was commenced in September 1991. A probability-based matching approach12 was employed using maternal identifiers to link the Scottish Morbidity Record, the Scottish Stillbirth and Infant Death Enquiry, and the prenatal screening database in the Institute of Medical Genetics. We excluded multiparous patients, multiple births, stillbirths, and births outside the range 24–43 weeks gestation. Ethical approval for the linkage was obtained from the Privacy Advisory Committee of the Information and Statistics Division of the National Health Service, Scotland.
The maternal age, parity, previous miscarriages and therapeutic abortions, postcode of residence, and all outcome data were obtained solely from the Scottish Morbidity Record. Maternal weight was obtained solely from the biochemical database. Maternal height and smoking were obtained from the Scottish Morbidity Record except in cases where they were missing from the Scottish Morbidity Record and the biochemical database was employed. The smoking status (current, past, never) was determined from information at the time of the first prenatal visit. The maternal age was defined as the age of the mother at the time of delivery. The body mass index was calculated from the weight in kilograms recorded at the time of sampling for serum screening assay divided by the height in metres squared. Socioeconomic status was estimated based on the postcode of residence, using Carstairs socioeconomic deprivation categories13 (based on 1991 Census data on car ownership, unemployment, overcrowding, and social class within postcode sectors of residence containing, on average, 
1600 residents).
Definitions
Previous miscarriage was defined as previous delivery of a conceptus showing no signs of life before 24 weeks gestation, excluding therapeutic abortions. Previous therapeutic abortion was defined as previous therapeutic termination of pregnancy by any means prior to 24 weeks gestation. Spontaneous birth was defined as all births that were vaginal or had a documented duration of labour but were not recorded as having had labour induced. Elective births were taken to be all other births. The gestational age at birth was defined as the completed weeks of gestation on the basis of the estimated date of delivery in each woman's clinical record; standard national criteria exist for the estimation of date of delivery using menstrual and ultrasound data.14 The gestational age has been confirmed by ultrasound scan in the first half of pregnancy in >95% of pregnancies in the UK from the early 1990s.15 Maternal serum levels of AFP and hCG were quantified as multiples of the median for week of gestation, corrected for maternal weight.16
Statistical analysis
Continuous variables were summarized by the median and inter-quartile range. Univariate comparisons were performed using the Kruskal–Wallis test, the chi-squared test, and the chi-squared test for trend, as appropriate. The P-values for all hypothesis tests were two-sided, and we set statistical significance at P < 0.05. All the variables were treated as categorical. Biochemical data were categorized into quintiles with the highest quintile split into a decile and vigesimals. We preformed univariate and multivariate Cox regression using gestational age as the time scale, spontaneous labour as the event, elective preterm deliveries as censored at the gestation of birth, and all term deliveries censored at the start of the 37th week. The proportional hazards assumption was tested using the method of Grambsch and Therneau.8 This was used to determine whether the relative risk of spontaneous preterm birth associated with a given factor varied across the range 24–36 weeks gestation. Preterm delivery was then divided into extreme (24–28 weeks), moderate (29–32 weeks), and mild (33–36 weeks), thus, dividing the span of gestation into approximate thirds. Logistic regression analysis was used to estimate adjusted odds ratios associated with the different degrees of prematurity using spontaneous preterm birth within the given range as the event, excluding elective preterm births within the gestational age range, and using spontaneous preterm birth within the age range and all births at later gestations as the denominator. Factors which had been shown in the proportional hazards model to vary significantly with gestation, were allowed to vary in the three preterm gestational age groups, whereas the rest of the predictors remained fixed. The predicted probability of each outcome was obtained from the logistic model. The screening performance of the model was assessed using the predicted probability to estimate the area under the receiver operating characteristic (ROC) curve. Further, the positive predictive value, sensitivity, specificity, and positive and negative likelihood ratios were estimated using different thresholds of predicted risk as screen positive (predicted probability in the top 1, 5, 10, or 20%). All statistical analyses were performed using the Stata software package (Stata Corporation, TX, USA), version 8.2.
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There were 216 563 records of singleton births with a recorded value of maternal serum AFP and hCG, which could be linked to the Scottish Morbidity Record, and 97 264 (44.9%) of these were first births. Among this group we excluded 69 (0.1%) deliveries that were outside the range of 24–43 gestational weeks and 518 (0.5%) antepartum stillbirths. Of the remaining 96 677 records, 12 286 (12.7%) had missing data on one or more variable [47 (0.1%) maternal age, 1290 (1.3%) height, 6907 (7.1%) body mass index, 171 (0.2%) deprivation category, 5691 (5.9%) smoking status, and 5 (0.01%) previous miscarriages] leaving a study group of 84 391 births.
When categorized by gestational age at birth, there were significant differences in the proportion of spontaneous births, maternal height, deprivation category, smoking status, previous miscarriages, previous therapeutic abortions, marital status, and second trimester levels of AFP and hCG (Table 1). The risk of spontaneous preterm birth over the range 24–36 weeks was then assessed using a multivariate Cox model (Table 2). There were linear trends between the risk of spontaneous preterm birth and second trimester maternal serum levels of AFP and hCG. The risk of spontaneous preterm birth also varied according to maternal age, marital status, and smoking status; decreased linearly with height and body mass index; and, increased linearly with maternal deprivation category, number of previous miscarriages, and number of previous therapeutic abortions. The relative risk of preterm birth varied across the range 24–36 weeks in association with high levels of hCG (P = 0.008), maternal age <20 (P = 0.0001), and the number of previous miscarriages (P = 0.006).
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The nature of variation across the range of gestational ages was then assessed using logistic regression for each of the categories of spontaneous preterm birth (Table 3). Separate odds ratios were estimated within each of the windows of gestational age for each of the variables where the relative risk had been shown to vary over the range 24–36 weeks. For the other variables where Cox modelling had shown the relative risk was constant, a single odds ratio was estimated across the range 24–36 weeks. Using this approach, high levels of hCG and age <20 were associated with extreme preterm birth but not moderate or mild preterm birth. The number of previous miscarriages was associated with all categories of preterm birth, but the association was strongest for extreme prematurity and weakest for mild prematurity.
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The screening performance of the multivariate logistic regression models were then assessed for the different degrees of prematurity assuming classification of the top 1, 5, 10, or 20% of predicted risk as having screened positive (Table 4). The positive likelihood ratios were highest for extreme prematurity (5.5 for women in the top 1% of predicted risk). However, owing to the fact that mild prematurity was much more common, the positive predictive value was greatest for the model of mild prematurity. In no case did any positive predictive value exceed 10%. Finally, the predictive ability of the models was assessed using the area under the ROC curve. Values were highest for extreme preterm birth and lowest for mild preterm birth. Adding AFP and hCG to the maternal characteristics resulted in an increase in the area under the ROC of 0.04 at all gestations (Table 5).
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In the present study, we demonstrated in a large population of primigravid women that the risk of spontaneous preterm birth was significantly associated with marital status, smoking status, height, body mass index, socioeconomic deprivation category, previous miscarriages and therapeutic abortions, and with maternal serum levels of AFP in the second trimester. We also demonstrated significant variation in the relative risk of spontaneous birth across the range 24–36 weeks gestation associated with maternal age <20, elevated levels of hCG, and with number of previous miscarriages. Each of these factors was strongly associated with extreme preterm birth but not associated, or only weakly associated, with moderate or mild spontaneous preterm birth.
The results of the current study expand considerably on previous studies. In relation to elevated hCG, a number of studies had shown increased rates of preterm delivery,17–21 but others had shown no association22 or only a very weak association.23 However, these analyses did not distinguish between spontaneous and elective preterm birth. A study, which did make this distinction, demonstrated that elevated hCG was associated with elective preterm birth, but there was no significant association with spontaneous preterm birth.24 However, no attempt was made to analyse this outcome in relation to the degree of severity of preterm delivery. In relation to maternal age <20, we had previously analysed routinely data from Scotland and shown no association between this characteristic and the risk of preterm birth at either 24–32 weeks or 33–36 weeks.25 However, we also pooled spontaneous and elective preterm birth. With regard to prior miscarriages, a previous Swedish study had indicated a history of prior losses was more strongly associated with extreme preterm delivery.26 However, there was no direct statistical test of whether the apparent variation in relation to the degree of prematurity was more than would be expected by chance. Finally, a previous analysis of spontaneous preterm birth in relation to the number of previous therapeutic abortions suggested that the association was stronger for extreme preterm delivery.27 However, there was considerable overlap in the confidence intervals for odds ratios for the different degrees of prematurity and, again, that study lacked a specific test that the apparent variation between the groups was statistically significant. We confirm that the number of prior therapeutic abortions is associated with the risk of spontaneous preterm birth but show that the association is similar for different degrees of prematurity.
Many previous studies have analysed risk factors according to different degrees of prematurity. Variation in the strength of associations is critical since the consequences of preterm delivery vary profoundly in relation to the degree of prematurity. However, this is the first study, to our knowledge, to use Cox modelling and a test of the proportional hazards assumption to address whether the relative risk of spontaneous preterm birth associated with a given factor varies in relation to the degree of prematurity. Other approaches to this question are possible. First, categories of prematurity can be created and separate logistic regression models can be estimated, as we described in Table 3. Moreover, by stacking the datasets for the different outcomes and use of interaction terms, it can be determined whether odds ratios significantly vary among the categories. However, this requires deliberate selection of categories. In contrast, using the Cox method, gestational age is treated continuously. This will increase the power to detect variation in the relative risk and removes the possibility of data-derived or investigator-derived categorization. We propose that this method may be useful in systematically determining whether an association varies in relation to the degree of prematurity. Such an approach is usefully combined with categorization, which then allows a simpler assessment of the pattern of variation in relation to the degree of prematurity. A further strength of the present study is its size. Deliveries prior to 28 weeks account for 60% of all neonatal deaths of preterm infants.10 However, extreme preterm birth is rare. In our study, the risk of spontaneous preterm birth between 24 and 28 weeks was 1 in 500. It follows, therefore, that very large-scale studies are required to address the factors associated with this outcome. In practice, many studies of preterm birth are insufficiently powerful to assess the risk of extreme preterm birth and, in effect, use moderate and mild preterm birth as proxies of this outcome. This approach is only valid if the relative risk of spontaneous preterm birth does not vary in relation to known risk factors over the range 24–36 weeks. In the present study we show that this is not the case.
Clinical prediction of the risk of spontaneous preterm birth among women with no previous births is an area of profound clinical interest. Recent studies have indicated that use of progesterone analogues may reduce the risk of spontaneous preterm birth among women deemed to be at high risk of this event.28 The majority of women recruited to these trials are selected as high risk on the basis of previous preterm deliveries, as this is the maternal characteristic most strongly associated with the risk of spontaneous preterm birth.5 This method of selection is clearly effective, as the rate of preterm birth in the control group in one major trial exceeded 50%.29 Given the devastating consequences to the infant of extreme preterm birth and the possibility of an effective intervention, predictive tools to identify women at high risk of extreme preterm delivery in their first pregnancy are urgently required. However, characterization of the parameters used in the present study indicate that, in our population, the model employed performed poorly as a screening tool with positive predictive values of <10%. This suggests that maternal characteristics and second trimester maternal serum screening, although statistically associated with the risk of preterm birth, are insufficiently informative to be used to identify women at clinically significant risk of preterm birth. This may reflect the fact that spontaneous preterm birth has multiple aetiologies. If population-based screening and intervention to prevent preterm birth in nulliparous women is to be attempted, other specific methods will be required, such as cervical ultrasound or fetal fibronectin assay from vaginal swabs.30
In summary, we show that the risk of spontaneous preterm delivery among nulliparous women with no previous births is associated with a number of maternal characteristics and with second trimester maternal serum levels of placentally derived proteins. High levels of hCG, maternal age <20 and two or more previous miscarriages were more strongly associated with extreme preterm delivery than moderate or mild preterm delivery. However, models using maternal characteristics and second trimester serum screening results did not have the predictive ability for any degree of spontaneous preterm birth, which would allow useful population-based screening.
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Supported by a project grant from the Foundation for the Study of Infant Deaths (UK).
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