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Keywords:

  • PAPP-A;
  • fβ-hCG;
  • hypertensive disorders;
  • stillbirth;
  • placenta-related disorders;
  • miscarriage

Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

Objective

To determine the clinical relevance of maternal characteristics and first-trimester serum concentrations of pregnancy-associated plasma protein A (PAPP-A) and free beta human chorionic gonadotrophin (fβ-hCG) in predicting placenta-related complications, miscarriage and preterm delivery.

Design, Setting and Population

A historical cohort study of data of the National Institute for Public Health and the Environment of first-trimester screening tests performed between July 2002 and May 2006 was done. Data from 28 566 (64.1%) tests were eligible for analysis.

Methods

By logistic regression, predictive rules were made based on PAPP-A and fβ-hCG concentrations, maternal smoking, maternal weight and age, low birth weight, stillbirth and hypertensive disorders, miscarriage and preterm birth. Predictive values were analysed with the area under the curve (AUC) of receiver operating curves (ROC).

Results

Predictive for placenta-related complications were low PAPP-A, low fβ-hCG, smoking and weight (AUC 54%). For miscarriage low PAPP-A, low fβ-hCG and maternal age (MA) were predictive (AUC 78%) and for preterm delivery low PAPP-A, smoking, MA and maternal weight (AUC 55%).

Conclusion

Only the predictive model for miscarriage had a clinically relevant predictive value of 28%. Results together do not justify closer surveillance of chromosomally normal pregnancies with PAPP-A or fβ-hCG levels below the fifth percentile. Copyright © 2010 John Wiley & Sons, Ltd.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

First-trimester screening (including fetal nuchal translucency and maternal serum levels of pregnancy-associated plasma protein A (PAPP-A) and free beta human chorionic gonadotrophin (fβ-hCG)) is a widely applied screening method for Down syndrome (DS).

Previous studies have suggested that women with low maternal serum concentrations of PAPP-A in the first trimester with a low risk of DS are at higher risk to develop pregnancy complications or adverse outcomes, such as low birth weight (Ong et al., 2000; Smith et al., 2002; Yaron et al., 2002; Tul et al., 2003; Dugoff et al., 2004; Krantz et al., 2004; Spencer et al., 2005; Nese Kavak et al., 2006; Smith et al., 2006), preterm delivery (Smith et al., 2002; Dugoff et al., 2004; Krantz et al., 2004; Spencer et al., 2005; Smith et al., 2006), stillbirth (Smith et al., 2002; Dugoff et al., 2004; Smith et al., 2004; Smith et al., 2006), miscarriage (Ong et al., 2000; Yaron et al., 2002; Dugoff et al., 2004; Goetzl et al., 2004; Liu et al., 2004; Krantz et al., 2006; Nese Kavak et al., 2006) and pregnancy-induced hypertensive disorders (Ong et al., 2000; Yaron et al., 2002; Dugoff et al., 2004; Spencer et al., 2005; Nese Kavak et al., 2006; Poon et al., 2009). However, those associations were not found in other studies (Morssink et al., 1998; Ong et al., 2000; Yaron et al., 2002; Tul et al., 2003; Goetzl et al., 2004; Nese Kavak et al., 2006).

Whether there is a similar association between pregnancy complications and low concentrations of fβ-hCG is less clear. The only association described in more than one study was that between low concentrations of fβ-hCG and miscarriage (Morssink et al., 1998; Ong et al., 2000; Smith et al., 2002; Tul et al., 2003; Dugoff et al., 2004; Krantz et al., 2004; Smith et al., 2004).

Maternal characteristics such as smoking, maternal weight and advanced maternal age (MA) are also known to be related to adverse pregnancy outcome (Cnattingius et al., 1998; Andres et al., 2000; Baeten et al., 2001; Rosenberg et al., 2003; Chiolero et al., 2005; Cleary-Goldman et al., 2005; Kristensen et al., 2005). Smoking during pregnancy is associated with low birth weight, preterm delivery and stillbirth (Andres et al., 2000; Chiolero et al., 2005). Advanced MA is associated with miscarriage, preterm delivery and low birth weight (Cleary-Goldman et al., 2005). Women with excessive body weight are at risk for preterm delivery and stillbirth (Cnattingius et al., 1998; Baeten et al., 2001; Rosenberg et al., 2003; Kristensen et al., 2005). These associations are often statistically significant but are not necessarily clinically relevant.

In a large patient cohort (n = 28 566), we therefore studied the association between low first-trimester serum concentrations of PAPP-A and/or fβ-hCG and specific maternal characteristics (such as smoking status, age and weight) to construct a model to predict birth weight < 2500 g after 37 weeks of gestation, stillbirth and hypertensive disorders (categorised together as placenta-related complications), miscarriage and preterm delivery. Moreover, we judged the applicability of such a model, that is, whether low serum concentrations of PAPP-A and/or fβ-hCG and specific maternal characteristics should prompt the obstetricians to apply special care to women. Data of our study were compared to those of the literature.

METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

Subjects

For this study, data collected by the RIVM (The Dutch National institute for Public Health and the Environment) were used. Since June 2004, all pregnant women in the Netherlands are informed about screening for DS (Ross-van Dorp, 2004). Before June 2004, only women aged 36 and older were offered screening or an invasive diagnostic test. Screening tests for DS were performed only at the specific request of the pregnant woman. Health insurance basically only reimbursed screening for the group of women aged 36 years and older.

Blood samples originated from all parts of the Netherlands, except from the northern provinces (which had their own DS screening facilities). They were sent by mail to the laboratory of the RIVM and upon arrival immediately stored at 4 °C, until analysis. In general, samples were in transport for no longer than 2–3 days. For all requests, sample date, MA and gestational age (GA) at sampling, maternal weight and smoking status were recorded. The GA at the time of serum collection (between 8 and 14 weeks) was determined either by ultrasound measurement or first day of last menstrual period depending on the preference of the applying health professional (Koster et al., 2008).

Maternal serum concentrations of PAPP-A and fβ-hCG were measured using commercially available kits and the AutoDELFIA analyser (PerkinElmer, Turku, Finland).

Pregnant women were asked to report on a follow-up form: date of birth, birth weight, chromosomal or structural anomalies or other complications during pregnancy or birth. The data used in this study was from samples processed between July 2002 and April 2006.

Test characteristics

Screening for DS was accomplished by using MA, maternal serum concentrations of fβ-hCG and PAPP-A between 8 and 14 weeks of gestation and fetal nuchal translucency. These measurements were subsequently transformed to a risk using an algorithm incorporated in risk estimation software. Maternal serum levels of fβ-hCG and PAPP-A were expressed as multiples of the median (MoM) for GA, which were subsequently corrected for weight. Following the guidelines of the national screening programme, MoMs were not corrected for smoking (but smoking was a factor in the multiple regressions analysis, see below). Correction of MoMs for ethnic origin, again, was not recommended by the national guidelines, and therefore not performed. As the question on ethnicity was generally not answered unambiguously, and the percentage Caucasian pregnancies was generally about 95% and the percentage Afro-Caribbean pregnancies < 2%, ethnicity was not taken into account as a factor in the multiple regression analysis (see below).

Adverse pregnancy outcome

Data was searched to identify pregnancy complications. The following outcome measures were examined:

  • 1.
    Placenta-related complications including low birth weight, stillbirth and hypertensive disorders of pregnancy (the individual outcomes were combined to ‘placenta-related complications’ to gain more statistical power). Low birth weight was defined as a weight below 2500 g when the infant was born between 37 and 42 weeks. Stillbirth was defined as delivery of an intrauterine death at or after 16 weeks of gestation. Pregnancy-induced hypertension, preeclampsia and the Hemolyse Elevated Liver enzymes and Low Platelets syndrome (HELLP syndrome) were categorised as hypertensive disorders. The written reports that women gave on the follow-up form did not allow distinguishing between the latter three diseases.
  • 2.
    Miscarriage was defined as pregnancy loss before 16 completed weeks of gestation.
  • 3.
    Preterm delivery was defined as spontaneous delivery between 16 and 37 completed weeks of pregnancy.

Exclusion criteria

The following cases were excluded from final analysis: women with unknown follow-up, women who were pregnant with a fetus having a chromosomal anomaly, women with a multiple pregnancy or a vanishing twin, women who were pregnant through oocyte donation, women with blood samples taken before 8 weeks or after 13 weeks and 6 days of gestation and women with type 1 or 2 diabetes mellitus (DM).

Factors

On the basis of previous studies, a cut-off point below the fifth percentile was considered as abnormal for PAPP-A MoM (low PAPP-A) and fβ-hCG MoM (low fβ-hCG) (Smith et al., 2002; Cuckle et al., 2003; Dugoff et al., 2004; Krantz et al., 2004; Liu et al., 2004; Smith et al., 2004; Spencer et al., 2005; Smith et al., 2006).

The fifth percentile was calculated based on all available PAPP-A MoM and fβ-hCG MoM in the study group.

Predictive rules were established for each of the three outcomes and based on the following characteristics: low PAPP-A, low fβ-hCG, MA (by year), maternal weight (by kg) and maternal smoking status (smoker/non-smoker).

Statistical analyses

Appropriate descriptive statistics were used to test for normality. Logistic regression was used to make a predictive rule based on the characteristics mentioned above. Univariate logistic regression was performed to identify which characteristics had a statistically significant relation with the outcomes. Odds ratios (ORs) and 95% confidence intervals (CI) were calculated. Secondly, multivariate logistic regression was performed on the outcomes. Only the statistically significant characteristics of the univariate analyses were included in the model. The characteristics which were also statistically significant in the multivariate model were used to make a predictive rule. The predictive rule was based on the logistic regression model and written as

  • equation image

The R2 of the logistic regression model describes which percentage of the complications could be explained by the used characteristics.

The area under the curve (AUC) of the receiver operating curve (ROC) analysis, which indicates the predictive power of the predictive rules, was calculated. The AUC presents a measure of how well a predictive rule can distinguish between an affected and unaffected population.

When the AUC is 0.50, a predictive rule performs equal to chance. A p value < 0.05 was accepted as statistically significant for all analyses. Data were analysed with SPSS for Windows version 12.0.1.

Meta-analysis

To compare our results to those of others, a limited meta-analysis was performed on the 14 studies used as background information in the course of this study.

From all studies an OR and 95% CI was extracted.

The data from the different studies were analysed with Review Manager (RevMan) (Computer program. Version 5.0. Copenhagen: The Nordic Cochrane Centre, The Cochrane Collaboration, 2008).

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

During the study period, serum was collected from 44 588 women. After employing the exclusion criteria, a total of 28 566 (64.1%) cases were eligible for analysis (Figure 1).

thumbnail image

Figure 1. Flow chart indicating the number of requests eligible for the epidemiological analysis

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The epidemiological characteristics of these pregnancies are summarised in Table 1. Notably, median MA at screening was 35.1 years. (range 17–47). Mean maternal weight was 69.4 ± 12.4 kg. Mean GA at blood sampling was 11.4 ± 1.2 weeks. Mean GA at delivery was 39 ± 5.1 weeks (SD). Mean birth weight was 3480 ± 600 g.

Table 1. Characteristics of the study group (n = 28 566)
  1. MA, maternal age; GA, gestational age; PAPP-A, pregnancy-associated plasma protein A; MoM, multiples of the median; fβhCG, beta human chorionic gonadotrophin; SD, standard deviation.

  2. Maternal weight was unknown in 757 cases, gender was unknown in 435 cases and birth weight of 552 children was unknown.

MA at early serum screening (year) Median (range)35.1(17–47)
Maternal weight (kg) Mean ( ± SD)69.4( ± 12.4)
GA at early serum screening (weeks) Mean ( ± SD)11.4( ± 1.2)
GA at delivery (weeks) Mean ( ± SD)39( ± 5.1)
Smoking statusNon-smokerN (%)26 624(93.2%)
 SmokerN (%)1942(6.8%)
GenderMaleN (%)14 424(50.5%)
 FemaleN (%)13 707(48.0%)
Infant birth weight (g)AllMean ( ± SD)3480( ± 600)
 MaleMean ( ± SD)3538( ± 614)
 FemaleMean ( ± SD)3419( ± 578)
PAPP-A MoM corrected for weight Median (range)1.11(0.01–18.40)
fβ-hCG MoM corrected for weight Median (range)1.04(0.01–10.62)

The calculated fifth percentile for PAPP-A MoM corrected for weight was 0.39, defining a PAPP-A MoM < 0.39 as low and ≥ 0.39 as normal. The calculated fifth percentile for the fβ-hCG MoM corrected for weight was 0.40, defining a fβ-hCG MoM < 0.40 as low and ≥ 0.40 as normal.

Predictors for placenta-related complications

Predictive models were created for the different subcategories that formed the ‘placenta-related complications’ group, that is, (1) stillbirth, (2) low birth weight, (3) hypertensive disorders in women who delivered at a GA before 34 weeks and (4) hypertensive disorders in women who delivered after a GA before 37 weeks. Resulting AUC were 54.4%, 65%, 54.5% and 60.6%, respectively. Because of the small numbers of cases in the individual subgroups, it was decided to only present the results of the outcome measure ‘placenta-related complications’ that combines (1)–(4).

Data (n = 1074, 3.8%) of the univariate and multivariate analysis of the predictors for the placenta-related complications are summarised in Table 2a. Multivariate analysis showed that low serum PAPP-A, low fβ-hCG concentrations, smoking and high maternal weight predicted a higher risk for one of the placenta-related complications. To predict placenta-related complications with the statistically significant characteristics, the following predictive rule was formulated.

  • equation image
Table 2a. Predictors for one of the placenta-related complications (n = 1, 074; 3.8% of study population)
 Univariate analysesMultivariate analyses
PredictorOdds ratio95% CIOdds ratio95% CI
  • PAPP-A, pregnancy-associated plasma protein A; fβ-hCG, beta human chorionic gonadotrophin; CI, confidence interval; NS, not statistically significant.

  • a

    In univariate analyses not statistically significant.

Low PAPP-A (<P5)1.841.47–2.291.711.37–2.15
Low fβ-hCG (<P5)1.571.24–1.991.411.10–1.80
Smoking status1.541.26–1.881.451.19–1.79
Maternal age by yeara1.011.00–1.03NSNS
Maternal weight by kg1.011.00–1.011.011.00–1.01

The explained variance (R2) of this model was only 0.7%, so the characteristics used in the predictive model explained 0.7% of the placenta-related complications. The AUC was 56%, thus 6% more women at risk for one of the placenta-related complications can be correctly classified by the predictive model.

Predictors for miscarriage

Data (n = 150, 0.5%) of the univariate and multivariate analysis of the predictors for miscarriage are summarised in Table 2b. In multivariate analysis, again, low PAPP-A and low fβ-hCG serum concentrations and advanced MA predicted a higher risk for miscarriage. To predict miscarriage, with the statistically significant characteristics, the following predictive rule was formulated.

  • equation image
Table 2b. Predictors for miscarriage (n = 150; 0.5% of study population)
 Univariate analysesMultivariate analyses
PredictorOdds ratio95% CIOdds ratio95% CI
  • PAPP-A, pregnancy-associated plasma protein A; fβ-hCG, beta human chorionic gonadotrophin; CI, confidence interval; NS, statistically not significant.

  • a

    In univariate analyses not statistically significant.

Low PAPP-A (<P5)14.5310.44–20.2211.067.85–15.58
Low fβ-hCG (<P5)9.756.87–13.826.614.68–9.63
Smoking statusa1.410.81–2.46NSNS
Maternal age by year1.101.05–1.161.101.05–1.15
Maternal weight by kga1.010.99–1.02NSNS

The R2 of this model was 15.2%, so the characteristics used in the predictive model explained 15.2% of the miscarriages. The AUC was 78%, indicating that 28% more women at risk for miscarriage can be correctly classified by the predictive model.

Predictors for preterm delivery

Data (n = 1503, 5.3%) of the univariate and multivariate analysis of the predictors for preterm delivery are summarised in Table 2c.

Table 2c. Predictors for preterm delivery (n = 1, 503; 5.3% of study population)
 Univariate analysesMultivariate analyses
PredictorOdds ratio95% CIOdds ratio95% CI
  • PAPP-A, pregnancy-associated plasma protein A; fβ-hCG, beta human chorionic gonadotrophin; CI, confidence interval; NS, statistically not significant.

  • a

    In univariate analyses not statistically significant.

Low PAPP-A (<P5)2.371.98–2.832.301.91–2.77
Low fβ-hCG (<P5)a1.311.05–1.63NSNS
Smoking status1.281.06–1.551.221.01–1.48
Maternal age by year0.980.97–1.000.990.97–1.00
Maternal weight by kg0.990.99–1.000.990.99–1.00

In multivariate analysis, low PAPP-A serum concentrations, smoking, advanced MA and high maternal weight predicted a higher risk for preterm delivery. To predict preterm delivery with the statistically significant characteristics, the following predictive rule was formulated.

  • equation image

The R2 from this model was 1.0%, so the characteristics used in the predictive model explained 1.0% of preterm delivery. The AUC was 56%, so 6% more women at risk for preterm delivery can be correctly classified by the predictive model.

DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

This is the first study in which a predictive rule was developed to study the clinical relevance of PAPP-A and fβ-hCG levels to predict pregnancy complications. Our study was based on a very large cohort, surpassed by only one previous study (Dugoff et al., 2004). Because incidences of adverse pregnancy outcomes are low and since a large cohort was used OR can be interpreted as relative risks.

Previous studies have shown varying relationships between low PAPP-A and low fβ-hCG and pregnancy outcome. We performed a limited meta-analysis of these studies for comparative reasons. However, the study designs, definitions and outcome measures were too heterogeneous to make a statistically valid analysis. Nevertheless, for illustrative reasons, OR and 95% CI that were most relevant in relation to the results of our study are graphically depicted in Figure 2a–2e. Since none of the previous studies, nor the present one, showed a significant OR for low fβ-hCG and hypertensive disorders, this category is not presented as a forest plot.

thumbnail image

Figure 2a. Forest plot of the odds ratio (OR) of low pregnancy-associated plasma protein A (PAPP-A) for miscarriage. Presented are the OR of low PAPP-A multiples of the median (MoMs) in relation to miscarriage, as presented in the different studies. Please note that the definition of miscarriage varied: Yaron, 2002: fetal loss < 23 weeks of gestational age (GA), Dugoff, 2004: fetal loss < 24 weeks of GA, Goetzl, 2004: fetal loss < 20 weeks of GA, Krantz, 2006: fetal loss < 14 weeks of GA, present study: fetal loss < 16 weeks of GA. *Relative risk

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thumbnail image

Figure 2b. Forest plot of the odds ratio (OR) of low free beta human chorionic gonadotrophin (fβ-hCG) for miscarriage. Presented are the OR of fβ-hCG multiples of the median (MoMs) in relation to miscarriage, as presented in the different studies. Please note that the definition of miscarriage varies: Dugoff, 2004: fetal loss < 24 weeks of gestational age (GA), Goetzl, 2004: fetal loss < 20 weeks of GA, Krantz, 2006: fetal loss < 14 weeks of GA, present study: fetal loss < 16 weeks of GA

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thumbnail image

Figure 2c. Forest plot of the odds ratio (OR) of low pregnancy-associated plasma protein A (PAPP-A) for stillbirth. Presented are the OR of low PAPP-A multiples of the median (MoMs) in relation to stillbirth, as presented in the different studies. Please note that the definition of stillbirth varies. Definition of stillbirth: delivery of a dead baby > 24 weeks of gestational age (GA). Exceptions are Goetzl 2004: delivery > 20 weeks of GA and present study: delivery > 16 weeks of GA. *Hazard ratio. **Unadjusted OR

Download figure to PowerPoint

thumbnail image

Figure 2d. Forest plot of the odds ratio (OR) of low free beta human chorionic gonadotrophin (fβ-hCG) for stillbirth. Presented are the OR of low fβ-hCG MoMs in relation to stillbirth, as presented in the different studies. Please note that the definition of stillbirth varies. Definition of stillbirth: delivery of a dead baby > 24 weeks of gestational age (GA). Exceptions are Goetzl 2004: delivery > 20 weeks of GA and present study: delivery > 16 weeks of GA. *Unadjusted OR

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thumbnail image

Figure 2e. Forest plot of the odds ratio (OR) of low pregnancy-associated plasma protein A (PAPP-A) for hypersensitive disorders. Presented are the OR of PAPP-A multiples of the median (MoMs) in relation to hypertensive disorders, as presented in the different studies. *Cut-off point PAPP-A, GH, gestational hypertension; Preecl, preeclampsia; Del < 34 weeks, preeclampsia/HELLP, delivery < 34 weeks of GA; Del > 37 weeks, preeclampsia/HELLP, delivery > 37 weeks of GA

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Our study as well as that of the others only show weak to moderate predictive relations between low PAPP-A and low fβ-hCG first-trimester serum concentrations and various adverse pregnancy outcomes.

The poor relationships regarding placenta-related complications and preterm delivery imply that these are, unfortunately, clinically not relevant.

For miscarriage, the R2 and AUC of the model were moderate, but since miscarriage currently cannot be prevented by special care a predictive model will have no added value. So the results of this study give unsatisfactory evidence to justify special prenatal care for women with PAPP-A and/or fβ-hCG below the fifth percentile.

There are some limitations to our study. The pregnancy complications were gathered through self-reporting. Reporting of pregnancy complications was done with an open question and not by a specified multiple-choice question. Thus, there was no complete identification of all complications. Also, compared to other published studies, there may indeed have been some degree of underreporting. This study also suffered from a considerable loss to follow-up (34%). This is at least in part due to the fact that for a small part of the study population, the follow-up process had not yet been completed. However, when predictive models were made with data from the period during which the follow-up process was completed (data up to December 2004; follow-up percentage: 83.5%) R2 and AUC remained the same. So, in summary, some selection bias may be anticipated, but probably with limited consequences for the presented predictive models.

Finally, the GA applied to define miscarriage and preterm delivery in this study was 16 weeks. In other studies, various other definitions have been used, for example, a GA of 20, 23 or 24 weeks (Yaron et al., 2002; Dugoff et al., 2004; Goetzl et al., 2004; Liu et al., 2004). Since pregnancy loss rates do not differ greatly between 16 and 24 weeks, this will hamper the comparability of our results only to a limited extent.

In this study, only five predictors were used to construct a predictive model. Other predictors for pregnancy complications, such as parity, body mass index (Cnattingius et al., 1998; Baeten et al., 2001; Rosenberg et al., 2003; Kristensen et al., 2005), socioeconomic status (Longo et al., 1999) and race/ethnicity (Shiao et al., 2005) may prove to be valuable additional predictors. Moreover, new biochemical markers (e.g. ADAM 12, PP13: Romero et al., 2008; Spencer et al., 2008) may be helpful. New studies should take into account these parameters.

Acknowledgements

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

The authors thank Dr Joke Koelewijn for helpful advice.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES
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