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Review

Maternal Serum Placental Growth Factor, Soluble Fms-Like Tyrosine Kinase-1, and Soluble Endoglin in Twin Gestations and the Risk of Preeclampsia—A Systematic Review

by
Katarzyna Kosinska-Kaczynska
1,
Magdalena Zgliczynska
1,2,*,
Szymon Kozlowski
3 and
Lukasz Wicherek
1
1
Second Department of Obstetrics and Gynecology, Center of Postgraduate Medical Education, 01-809 Warsaw, Poland
2
Chair and Department of Experimental and Clinical Physiology, Laboratory of the Centre for Preclinical Research, Medical University of Warsaw, 02-106 Warsaw, Poland
3
University Center for Woman and Newborn Health of the Medical University of Warsaw, 02-015 Warsaw, Poland
*
Author to whom correspondence should be addressed.
J. Clin. Med. 2020, 9(1), 183; https://doi.org/10.3390/jcm9010183
Submission received: 21 November 2019 / Revised: 16 December 2019 / Accepted: 7 January 2020 / Published: 9 January 2020
(This article belongs to the Section Obstetrics & Gynecology)

Abstract

:
Multiple gestation is one of the key risk factors for the occurrence of preeclampsia (PE). Soluble fms-like tyrosine kinase-1, placental growth factor, and soluble endoglin are molecules involved in the process of angiogenesis with a proven role in the pathogenesis of PE. The aim of the review was to summarize available data on maternal serum levels of the above-mentioned factors and their usefulness in predicting PE in twin pregnancies. Only original research articles written in English were considered eligible. Reviews, chapters, case studies, conference papers, experts’ opinions, editorials, and letters were excluded from the analysis. No publication date limitations were imposed. The systematic literature search using PubMed/MEDLINE, Scopus, Embase, and Cochrane Library databases identified 338 articles, 10 of which were included in the final qualitative analyses. The included studies showed significant differences in maternal serum levels of the discussed factors between women with twin pregnancies with PE and those who did not develop PE, and their promising performance in predicting PE, alone or in combination with other factors. The identification of the most effective algorithms, their prompt introduction to the clinical practice, and further assessment of the real-life performance should become a priority.

1. Introduction

According to the definitions of the American College of Obstetricians and Gynecologists and the International Society for the Study of Hypertension in Pregnancy, preeclampsia (PE) is defined as the new onset of hypertension after 20 weeks of gestation, accompanied with proteinuria or, in the absence of proteinuria, thrombocytopenia, renal insufficiency, impaired liver function, or pulmonary edema [1,2]. It affects about 5% of pregnancies worldwide with great regional diversity [3,4]. Together with eclampsia, it remains one of the leading causes of maternal mortality worldwide [4,5]. Although risk factors are well established, the majority of PE cases occur in otherwise healthy pregnant women. One of the independent risk factors is a multiple gestation, which was the subject of this review [2]. The occurrence of PE in multiple gestations is higher than in singleton gestations. Laine et al. recently published a large study on 16,174 twin pregnancies in which the risk of PE in twins was found to be three to four times higher in comparison with singletons, even after adjustment for other risk factors [6]. However, the relationship between PE and chorionicity remains unclear. The majority of available studies have indicated a higher incidence of PE in dichorionic (DC) [7,8,9], whereas others have described it in monochorionic (MC) twin gestations [10,11] or reported the lack of such an association [12,13,14].
Despite the immensity of research into the pathophysiology of PE, it remains unclear. Two main hypotheses explaining the pathogenesis of this condition are highlighted: exaggerated systemic inflammation and abnormal placentation [15,16]. During placentation, adequate vascular remodeling is a key process, allowing increased uterine blood flow, essential for the proper development of pregnancy. When the placentation process is disturbed, the placenta becomes ischemic, and the overlapping reperfusion additionally enhances the already existing damage through oxidative stress. This results in the massive secretion of various active molecules to the maternal circulation [17,18,19].
Placental growth factor (PlGF) is a protein from the vascular endothelial growth factor (VEGF) family, which promotes vessel formation. It is present in high concentrations within villous cytotrophoblastic tissue and the syncytiotrophoblast [20]. PlGF maternal serum levels increase throughout pregnancy, with a peak of around 30–32 weeks of gestation, followed by a decrease, probably due to placental maturation [20]. Serum soluble fms-like tyrosine kinase-1 (sFlt-1), also known as a soluble receptor for vascular endothelial factors (VEGF), is a protein that binds and decreases the concentrations of circulating VEGF and PlGF [21,22]. During a normal pregnancy, sFlt-1 concentration maintains a plateau of up to 32 weeks and then increases [23]. In women with PE, maternal serum levels of sFlt-1 are increased, whereas PlGF levels are decreased [24,25].
Both biomarkers are already successfully used in clinical practice. In the groundbreaking PROGNOSIS study published in 2016, sFlt-1:PlGF ratio of 38 or lower was proposed as short-term (within 1 week) prediction of the absence of PE in women with a singleton pregnancy in whom the syndrome is clinically suspected [26]. In a recent meta-analysis, the pooled ratio sensitivity in predicting PE was accounted for 0.80, and the pooled specificity for 0.92 [27].
Another factor playing a role in PE etiology is endoglin (Eng). It is a transmembrane glycoprotein, an accessory receptor for the transforming growth factor-beta (TGF-beta). Eng is highly expressed on the proliferating endothelial cells of the decidua and syncytiotrophoblast [28]. It affects the signaling pathways of TGF-beta and endothelial nitric oxide synthase and, therefore, exerts a significant influence on the angiogenic processes. Serum levels of the soluble form of Eng (sEng) are found to be higher in PE than in non-PE pregnant women [29]. Recently, Leanos-Miranda et al. found a positive correlation of sEng with blood pressure, proteinuria, and levels of creatinine, uric acid, aspartate aminotransferase, alanine aminotransferase, and lactate dehydrogenase, while an inverse correlation was demonstrated for gestational age, infant’s birth weight, and platelet counts in women with PE [30].
The aim of the review was to summarize currently available data on maternal serum levels of factors involved in the angiogenic process: PlGF, sFlt-1, and sEng and the risk of PE in twin pregnancies.

2. Methods

The article was written in accordance with the principles contained in preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement [31]. The systematic literature search for articles concerning PlGF, sFlt-1, and sEng in predicting PE in twin pregnancies was performed using four databases: PubMed/MEDLINE, Scopus, Embase, and Cochrane Central Register of Controlled Trials (CENTRAL). The last search was performed on October 23, 2019. We did not contact the authors of the papers to obtain additional information. The search strategy was suited to the specific database (details provided in Table 1).
Only original research articles written in English were considered eligible, whereas reviews, chapters, case reports or case series, conference papers and abstracts, experts’ opinions, editorials, and letters to the editor were excluded from the analysis. No publication date limitations were imposed. Titles, abstracts, and keywords of research works obtained via the search process, described above, were screened independently by all study authors. The next step, after rejecting papers that visibly did not meet the criteria, involved reviewing full-text publications by two authors. A customized data extraction sheet was used for the collection of the following information: type of study, population demographics, inclusion and exclusion criteria, methodology, diagnostic tools used, and results. The risk of bias was assessed using the Newcastle-Ottawa Quality Assessment Scale modified by authors for this work [32]. Additionally, other potential additional sources of bias, not included in the scale, have been described in the subsection “Risk of bias assessment” in the Results section. Any disagreements were resolved through consensus with all study authors.

3. Results

3.1. Characteristics of Retrieved Studies

The implemented systematic literature search identified 338 articles. After adjusting for duplicates with the use of EndNote X9 automatic duplicate search followed by manual verification, 220 studies remained, and 10 of which finally met the inclusion criteria. Details on the selection process are presented in a customized PRISMA flow chart in Supplementary Materials Figure S1. The basic characteristics of the studies included in the review are summarized in Table 2.

3.2. Serum Concentrations of sFlt-1, PlGF, sFlt1:PlGF Ratio, and sEng in PE and non-PE Twin Pregnancies

The general trends in serum concentrations of sFlt-1, PlGF, sFlt1:PlGF ratio, and sEng in PE and non-PE twin pregnancies reported in the selected studies are summarized in Table 3.

3.3. Accuracy of sFlt-1, PlGF, sFlt1:PlGF Ratio, and sEng in Predicting PE in Twin Gestations

Six out of ten selected studies attempted to determine the accuracy of the examined angiogenic factors in predicting PE in twin pregnancies. Detailed data on this subject are collected in Table 4.

3.4. Risk of Bias Assessment and Limitations

In the individual studies, the risk of bias was assessed using the Newcastle-Ottawa Quality Assessment Scale modified by authors for this work ([32]; See Supplementary Materials Table S1). Although most of the studies revealed low or medium bias risk, it is noteworthy that half of the studies in our review were secondary analyses. This, with a high probability, indicated a substantially higher bias risk than the original study. Another possible source of bias for this review could be the fact that two of the included studies defined the study group as “multiple gestation”, without specifying whether they were only twin pregnancies, and, in addition, the study by Boucoiran et al. covered also five triplets [33,38,40]. Nevertheless, the authors assumed that this should not be a source of a major bias for this review. Another factor potentially interfering with the collective interpretation of studies’ results was the variety of methods used. Firstly, the studies were conducted on populations, which differed in terms of factors that might presumably affect the initial risk of PE like race and ethnicity, maternal age, body mass index, or gestational age. Similarly, the diversity of assays, machines, as well as specimens used, might also be the source of potential bias.

4. Discussion and Synthesis of Results

4.1. Differences in Serum Concentrations of sFlt-1, PlGF, and sEng Between Singleton and Twin Pregnancies

The studied biomarkers are largely of placental origin. Hence, differences in their concentrations between singleton and twin gestations were hypothesized. Seven out of ten papers included in this systematic review reported such differences [33,37,38,41,44,46,47]. Two other studies did not include singleton pregnancies [35,45], and, in the third one, no such comparisons were made [40]. sFlt-1 maternal serum levels were reported to be statistically higher in women with twin pregnancies in comparison with singleton gestations [33,37,38,41,47]. Saleh et al. found a similar relationship only in a group unaffected by PE, while, in the PE group, no significant differences were observed [47]. PlGF concentrations were also higher in twins compared to singletons [33,37,38,41,44,46,47]. Dröge et al. and Saleh et al. reported PlGF levels to be higher in the group of preeclamptic women with a twin gestation in comparison with women with a singleton pregnancy [41,47], whereas Francisco et al. observed higher PlGF concentrations only in dichorionic twins [46]. Only two studies examined differences in sEng concentrations. One showed its higher level in twin pregnancies [33], and the other revealed no significant differences between singletons and twins [37].
Several other articles reporting differences in PlGF, sFlt-1, and sEng concentrations between singletons and twins have been published to date. Since they did not consider preeclamptic twin pregnancies, they were not included in the review. According to Maynard et al., the maternal sFlt-1 level was higher in multiple gestations compared to high-risk singletons, and PlGF was significantly higher in multiples before 31 weeks of gestation [49]. Furthermore, Bdolah et al. found higher sFlt-1 in twins but similar PlGF concentrations in twins and singletons [50]. Faupel-Badger et al. reported higher sFlt-1 and sEng. However, lower PlGF levels were noted in twin gestations [51].

4.2. Serum Concentrations of sFlt-1, PlGF, and sEng in Monochorionic and Dichorionic Twin Gestations

Regarding the studies included in the systematic review, only three investigated the correlation between chorionicity and angiogenic factor concentrations. In two, no significant differences in PlGF, sFlt-1, nor sEng levels between MC and DC twin gestations were found [37,44]. Francisco et al. reported higher PlGF in DC twin pregnancies that did not develop PE, in comparison to singleton pregnancies, while no such differences in MC twins [46]. Nevertheless, other reports of such a correlation are available in the literature. Faupel-Badger et al. found the concentrations of sFlt-1 and sEng to be higher in monochorionic than in dichorionic twin gestations after adjustment for gestational age [51]. Cowans and Spencer reported PlGF concentrations to be 41% higher in DC, but only 16% higher in MC compared to singleton pregnancies [52].

4.3. Differences in Serum Concentrations of sFlt-1, PlGF, and sEng between Non-Preeclamptic Twin Pregnancies and Those Who Developed PE

Five out of six studies, which investigated differences between sFlt-1 levels in PE and non-PE twin gestations, reported significantly higher maternal serum levels in those mothers who developed PE [33,35,37,38,41]. The above studies included women in all trimesters of pregnancy - the first [37], the second [33,38], and the third [35,41]. Interestingly, Sanchez et al. found statistical differences only in PE and non-PE twins conceived with assisted reproductive technologies, without significance in spontaneously conceived ones [37]. Conversely, Boucoiran et al. found significant differences only between 24 and 26 weeks of pregnancy, whereas they were absent between 12 and 18 weeks of gestation [38].
Nine out of ten studies included in the review investigated PlGF levels in PE and non-PE women. Seven papers reported lower PlGF concentrations in women with a twin gestation who developed PE compared to non-PE multiples [33,38,40,41,44,45,46]. Alike for sFlt-1, differences were shown for different gestational ages ranging from late first to the early third trimester. Two other studies did not report such differences [35,47]. Both of those studies concerned women in the third trimester of twin pregnancies with suspicion or symptoms of PE forming the control groups, which, to some extent, maybe the reason for obtaining different results.
Boucoiran et al. and Dröge et al. demonstrated that elevated sFlt-1:PlGF ratio increased the risk of PE in twins [38,41], and, additionally, Powers et al. and Metz et al. observed similar relationships for sFlt-1+sEng:PlGF ratio [33,40]. Also, in this case, Saleh et al. and Rana et al. did not observe any statistically significant associations [35,47].
One of the selected articles investigated sEng concentrations in women with twin pregnancies with and without PE [33]. sEng was significantly higher between 31 to 35 weeks of gestation in subjects who later developed preeclampsia.
Only Dröge et al. analyzed the relationship between biomarkers and the severity of PE [41]. Authors found significantly higher sFlt-1, lower PlGF plasma levels, and, consequently, higher sFlt-1/PlGF ratio compared to healthy controls in both mild and severe groups. Among the included articles, we did not find direct comparisons of biomarkers’ concentrations between early and late-onset PE in twin gestations.

4.4. The Usefulness of Selected Angiogenic Factors in the Prediction of PE in Twin Gestations

A practical aspect of differences in the concentration of biomarkers allowed the creation of algorithms for long- or short-term prediction of PE. Currently, PlGF, sFlt-1:PlGF ratio, and The Fetal Medicine Foundation calculators are widely used [26,53,54,55].
Six out of ten studies included in this review attempted to determine the usefulness of selected biomarkers in the prediction or the diagnosis of PE in twin pregnancies [35,38,41,44,45,46,47]. A vast majority of the algorithms proposed by authors were characterized by promising parameters.
Rana et al. built an algorithm based on the highest systolic blood pressure, proteinuria, gestational age, and sFlt-1:PlGF ratio for the prediction of PE-related adverse outcomes in twins within the next 2 weeks and received area under the receiver operating characteristic curve (AUC) of 0.85 for a 75% false-positive rate (FPR). The authors also noted that AUC was slightly higher (0.87) when only women <34 weeks of gestation were included in the analysis. Moreover, they proposed sFlt1:PlGF >75 as more suitable for the diagnosis of PE in this group, instead of sFlt1:PlGF >85 that had been validated as the optimal cut-off for singletons [36,56]. Dröge et al. suggested a cut-off point of ≥53 as the most optimal for twins; however, for both, women <34 and ≥34 gestational weeks [41]. Moreover, Saleh et al. recently published a paper, which evaluated the usefulness of sFlt-1:PlGF ratio of ≤38 in the prediction of the short-term absence of PE in late second and third-trimester twin pregnancies [47]. Five out of thirteen preeclamptic twin gestations had sFlt-1:PlGF ratio >38, and four out of eight non-preeclamptic twin gestations had sFlt-1:PlGF ratio ≤38. Thus, the authors concluded that such a ratio is not applicable for ruling out PE in twin pregnancies.
Boucoiran et al. showed that the prediction of PE development in current pregnancy was possible with high accuracy (AUC 0.81, 10% FPR) at the early stages of pregnancy, between 12 and 18 weeks, only with the use of PlGF serum levels [38]. Furthermore, complex algorithms were published, using various combinations of maternal factors (history, mean arterial pressure, uterine artery pulsatility index) and biochemical markers (PlGF, serum pregnancy-associated plasma protein-A, placental protein 13, free β-human chorionic gonadotropin, and α-fetoprotein) [44,45,46]. The authors of research, which was conducted in the largest group of patients from all papers included in our review, created an algorithm with the use of maternal risk factors, PlGF, uterine artery pulsatility index (UTPI), and mean arterial pressure (MAP) in the first trimester of pregnancy. In a mixed population (singletons and twins) with the risk cut-off of 1 in 75 for PE at <37 gestational weeks, the detection rate of PE at <32, <37, and <42 weeks in singletons was accounted for 91%, 77%, and 57% with screen-positive rate (SPR) of 13%. The analogous values for twins were 100%, 99%, and 97%, but with a high SPR of 75% [46]. Moreover, the AUC values for this algorithm were decreasing with the increasing gestational age at the delivery of the twin pregnancies complicated by PE, as shown in Table 4. Only one paper investigated the possible accuracy of sEng in predicting PE. The adjusted odds ratio (aOR) of developing PE for a twofold increase in sEng was accounted for 2.98 (95% confidence interval (CI) 1.44–6.36). As regards other biomarkers, the results were as follows: sFlt-1 aOR = 2.07 (95% CI 1.15–3.89), PlGF aOR = 0.50 (95% CI 0.30–0.83), and sFlt1+sEng/PlGF aOR = 2.18 (95% CI 1.46–3.32) [33].

5. Conclusions

This systematic review is the most recent summary of available knowledge about maternal serum levels of PlGF, sFlt-1, and sEng and the risk of PE in twin pregnancies. Most of the studies included in the review reported statistical differences in maternal serum levels of discussed biomarkers between singleton and twin gestations and between PE and non-PE ones. Several proposed algorithms for the prediction and diagnosis of PE seem promising. However, according to that current knowledge, determination of their usefulness in diagnosing or ruling out the PE in all twin pregnancies is not possible. Moreover, the reference ranges of analyzed biomarkers in uncomplicated twin pregnancies are also not available. Large prospective studies with repeatable measurements at different weeks of pregnancy, as well as comparisons of maternal characteristics, chorionicity, onset, and severity, are needed for improvement of the algorithms. Subsequently, their prompt introduction into the clinical practice and further assessment of the real-life performance could help improve the quality of care for women with twin pregnancies.

Supplementary Materials

The following are available online at https://www.mdpi.com/2077-0383/9/1/183/s1, Figure S1: PRISMA 2009 Flow Chart, Table S1: Risk of bias assessment.

Author Contributions

Conceptualization, K.K.-K., M.Z., S.K., L.W.; Methodology, K.K.-K., M.Z.; Investigation, K.K.-K., M.Z., S.K., L.W.; Resources, K.K.-K., M.Z., S.K., L.W.; Data curation, K.K.-K., M.Z., S.K., L.W.; Writing—original draft preparation, K.K.-K., M.Z., S.K., L.W.; Writing—review and editing, K.K.-K., L.W.; visualization, M.Z., S.K.; Supervision, K.K.-K., L.W.; Project administration, K.K.-K., M.Z., S.K., L.W.; Funding acquisition, K.K.-K., L.W. All authors have read and agreed to the published version of the manuscript.

Funding

This study was funded by The Center of Postgraduate Medical Education. Grant number: 501-99999-4-18.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Brown, M.A.; Magee, L.A.; Kenny, L.C.; Karumanchi, S.A.; McCarthy, F.P.; Saito, S.; Hall, D.R.; Warren, C.E.; Adoyi, G.; Ishaku, S.; et al. Hypertensive Disorders of Pregnancy: ISSHP Classification, Diagnosis, and Management Recommendations for International Practice. Hypertension 2018, 72, 24–43. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. ACOG Practice Bulletin No. 202: Gestational Hypertension and Preeclampsia. Obstet. Gynecol. 2019, 133, e1–e25. [CrossRef]
  3. Abalos, E.; Cuesta, C.; Grosso, A.L.; Chou, D.; Say, L. Global and Regional Estimates of Preeclampsia and Eclampsia: A Systematic Review. Eur. J. Obstet. Gynecol. Reprod. Biol. 2013, 170, 1–7. [Google Scholar] [CrossRef] [PubMed]
  4. Duley, L. The Global Impact of Pre-Eclampsia and Eclampsia. Semin. Perinatol. 2009, 33, 130–137. [Google Scholar] [CrossRef] [PubMed]
  5. Ghulmiyyah, L.; Sibai, B. Maternal Mortality from Preeclampsia/Eclampsia. Semin. Perinatol. 2012, 36, 56–59. [Google Scholar] [CrossRef]
  6. Laine, K.; Murzakanova, G.; Sole, K.B.; Pay, A.D.; Heradstveit, S.; Raisanen, S. Prevalence and Risk of Pre-Eclampsia and Gestational Hypertension in Twin Pregnancies: A Population-Based Register Study. BMJ Open 2019, 9, e029908. [Google Scholar] [CrossRef] [Green Version]
  7. Bartnik, P.; Kosinska-Kaczynska, K.; Kacperczyk, J.; Ananicz, W.; Sierocinska, A.; Wielgos, M.; Szymusik, I. Twin Chorionicity and the Risk of Hypertensive Disorders: Gestational Hypertension and Pre-eclampsia. Twin Res. Hum. Genet. 2016, 19, 377–382. [Google Scholar] [CrossRef] [Green Version]
  8. Sarno, L.; Maruotti, G.M.; Donadono, V.; Saccone, G.; Martinelli, P. Risk of Preeclampsia: Comparison between Dichorionic and Monochorionic Twin Pregnancies. J. Matern. Fetal. Neonatal. Med. 2014, 27, 1080–1081. [Google Scholar] [CrossRef] [Green Version]
  9. Sparks, T.N.; Cheng, Y.W.; Phan, N.; Caughey, A.B. Does Risk of Preeclampsia Differ by Twin Chorionicity? J. Matern. Fetal Neonatal Med. 2013, 26, 1273–1277. [Google Scholar] [CrossRef]
  10. Campbell, D.M.; Templeton, A. Maternal Complications of Twin Pregnancy. Int. J. Gynaecol. Obstet. 2004, 84, 71–73. [Google Scholar] [CrossRef]
  11. Campbell, D.M.; MacGillivray, I. Preeclampsia in Twin Pregnancies: Incidence and Outcome. Hypertens Pregnancy 1999, 18, 197–207. [Google Scholar] [CrossRef] [PubMed]
  12. Savvidou, M.D.; Karanastasi, E.; Skentou, C.; Geerts, L.; Nicolaides, K.H. Twin Chorionicity and Pre-Eclampsia. Ultrasound Obstet. Gynecol. 2001, 18, 228–231. [Google Scholar] [CrossRef] [PubMed]
  13. Leduc, L.; Takser, L.; Rinfret, D. Persistance of Adverse Obstetric and Neonatal Outcomes in Monochorionic Twins after Exclusion of Disorders Unique to Monochorionic Placentation. Am. J. Obstet. Gynecol. 2005, 193, 1670–1675. [Google Scholar] [CrossRef] [PubMed]
  14. Carter, E.B.; Bishop, K.C.; Goetzinger, K.R.; Tuuli, M.G.; Cahill, A.G. The Impact of Chorionicity on Maternal Pregnancy Outcomes. Am. J. Obstet. Gynecol. 2015, 213, 390.e391–390.e397. [Google Scholar] [CrossRef] [PubMed]
  15. Fisher, S.J. Why is Placentation Abnormal in Preeclampsia? Am. J. Obstet. Gynecol. 2015, 213, S115–S122. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  16. Harmon, A.C.; Cornelius, D.C.; Amaral, L.M.; Faulkner, J.L.; Cunningham, M.W., Jr.; Wallace, K.; LaMarca, B. The Role of Inflammation in the Pathology of Preeclampsia. Clin. Sci. (Lond) 2016, 130, 409–419. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  17. Brosens, I.; Pijnenborg, R.; Vercruysse, L.; Romero, R. The Great Obstetrical Syndromes are Associated with Disorders of Deep Placentation. Am. J. Obstet. Gynecol. 2011, 204, 193–201. [Google Scholar] [CrossRef] [Green Version]
  18. Burton, G.J.; Yung, H.W.; Cindrova-Davies, T.; Charnock-Jones, D.S. Placental Endoplasmic Reticulum Stress and Oxidative Stress in the Pathophysiology of Unexplained Intrauterine Growth Restriction and Early Onset Preeclampsia. Placenta 2009, 30 (Suppl. A), S43–S48. [Google Scholar] [CrossRef] [Green Version]
  19. Chaiworapongsa, T.; Chaemsaithong, P.; Yeo, L.; Romero, R. Pre-Eclampsia Part 1: Current Understanding of its Pathophysiology. Nat. Rev. Nephrol. 2014, 10, 466–480. [Google Scholar] [CrossRef] [Green Version]
  20. Williams, D.; Kenyon, A.; Adamson, D. Chapter Ten-Physiology. In Basic Science in Obstetrics and Gynaecology, 4th ed; Bennett, P., Williamson, C., Eds.; Churchill Livingstone: London, UK, 2010; pp. 173–230. [Google Scholar] [CrossRef]
  21. Romero, R.; Chaiworapongsa, T. Preeclampsia: A Link between Trophoblast Dysregulation and an Antiangiogenic State. J. Clin. Invest. 2013, 123, 2775–2777. [Google Scholar] [CrossRef] [Green Version]
  22. Phipps, E.A.; Thadhani, R.; Benzing, T.; Karumanchi, S.A. Pre-Eclampsia: Pathogenesis, Novel Diagnostics and Therapies. Nat. Rev. Nephrol. 2019, 15, 275–289. [Google Scholar] [CrossRef] [PubMed]
  23. Birdir, C.; Droste, L.; Fox, L.; Frank, M.; Fryze, J.; Enekwe, A.; Koninger, A.; Kimmig, R.; Schmidt, B.; Gellhaus, A. Predictive Value of sFlt-1, PlGF, sFlt-1/PlGF ratio and PAPP-A for Late-Onset Preeclampsia and IUGR between 32 and 37 Weeks of Pregnancy. Pregnancy Hypertens. 2018, 12, 124–128. [Google Scholar] [CrossRef] [PubMed]
  24. Maynard, S.E.; Min, J.Y.; Merchan, J.; Lim, K.H.; Li, J.; Mondal, S.; Libermann, T.A.; Morgan, J.P.; Sellke, F.W.; Stillman, I.E.; et al. Excess Placental Soluble Fms-Like Tyrosine Kinase 1 (sFlt1) May Contribute to Endothelial Dysfunction, Hypertension, and Proteinuria in Preeclampsia. J. Clin. Invest 2003, 111, 649–658. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  25. Levine, R.J.; Lam, C.; Qian, C.; Yu, K.F.; Maynard, S.E.; Sachs, B.P.; Sibai, B.M.; Epstein, F.H.; Romero, R.; Thadhani, R.; et al. Soluble Endoglin and Other Circulating Antiangiogenic Factors in Preeclampsia. N Engl. J. Med. 2006, 355, 992–1005. [Google Scholar] [CrossRef] [PubMed]
  26. Zeisler, H.; Llurba, E.; Chantraine, F.; Vatish, M.; Staff, A.C.; Sennstrom, M.; Olovsson, M.; Brennecke, S.P.; Stepan, H.; Allegranza, D.; et al. Predictive Value of the sFlt-1:PlGF Ratio in Women with Suspected Preeclampsia. N. Engl. J. Med. 2016, 374, 13–22. [Google Scholar] [CrossRef]
  27. Agrawal, S.; Cerdeira, A.S.; Redman, C.; Vatish, M. Meta-Analysis and Systematic Review to Assess the Role of Soluble FMS-Like Tyrosine Kinase-1 and Placenta Growth Factor Ratio in Prediction of Preeclampsia: The SaPPPhirE Study. Hypertension 2018, 71, 306–316. [Google Scholar] [CrossRef]
  28. Venkatesha, S.; Toporsian, M.; Lam, C.; Hanai, J.; Mammoto, T.; Kim, Y.M.; Bdolah, Y.; Lim, K.H.; Yuan, H.T.; Libermann, T.A.; et al. Soluble Endoglin Contributes to the Pathogenesis of Preeclampsia. Nat. Med. 2006, 12, 642–649. [Google Scholar] [CrossRef]
  29. Romero, R.; Nien, J.K.; Espinoza, J.; Todem, D.; Fu, W.; Chung, H.; Kusanovic, J.P.; Gotsch, F.; Erez, O.; Mazaki-Tovi, S.; et al. A Longitudinal Study of Angiogenic (Placental Growth Factor) and Anti-Angiogenic (Soluble Endoglin and Soluble Vascular Endothelial Growth Factor Receptor-1) Factors in Normal Pregnancy and Patients Destined to Develop Preeclampsia and Deliver a Small for Gestational Age Neonate. J. Matern. Fetal Neonatal Med. 2008, 21, 9–23. [Google Scholar] [CrossRef]
  30. Leanos-Miranda, A.; Navarro-Romero, C.S.; Sillas-Pardo, L.J.; Ramirez-Valenzuela, K.L.; Isordia-Salas, I.; Jimenez-Trejo, L.M. Soluble Endoglin As a Marker for Preeclampsia, Its Severity, and the Occurrence of Adverse Outcomes. Hypertension 2019, 74, 991–997. [Google Scholar] [CrossRef]
  31. Liberati, A.; Altman, D.G.; Tetzlaff, J.; Mulrow, C.; Gotzsche, P.C.; Ioannidis, J.P.; Clarke, M.; Devereaux, P.J.; Kleijnen, J.; Moher, D. The PRISMA Statement for Reporting Systematic Reviews and Meta-Analyses of Studies that Evaluate Health Care Interventions: Explanation and Elaboration. PLoS Med. 2009, 6, e1000100. [Google Scholar] [CrossRef]
  32. Wells, G.A.; Shea, B.; O′Connell, D.; Peterson, J.; Welch, V.; Losos, M.; Tugwell, P. The Newcastle-Ottawa Scale (NOS) for Assessing the Quality of Nonrandomised Studies in Meta-Analyses. Available online: http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp (accessed on 15 November 2019).
  33. Powers, R.W.; Jeyabalan, A.; Clifton, R.G.; Van Dorsten, P.; Hauth, J.C.; Klebanoff, M.A.; Lindheimer, M.D.; Sibai, B.; Landon, M.; Miodovnik, M. Soluble fms-Like Tyrosine Kinase 1 (sFlt1), Endoglin and Placental Growth Factor (PlGF) in Preeclampsia among High Risk Pregnancies. PLoS ONE 2010, 5, e13263. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  34. Caritis, S.; Sibai, B.; Hauth, J.; Lindheimer, M.D.; Klebanoff, M.; Thom, E.; VanDorsten, P.; Landon, M.; Paul, R.; Miodovnik, M.; et al. Low-Dose Aspirin to Prevent Preeclampsia in Women at High Risk. National Institute of Child Health and Human Development Network of Maternal-Fetal Medicine Units. N. Engl. J. Med. 1998, 338, 701–705. [Google Scholar] [CrossRef] [PubMed]
  35. Rana, S.; Hacker, M.R.; Modest, A.M.; Salahuddin, S.; Lim, K.H.; Verlohren, S.; Perschel, F.H.; Karumanchi, S.A. Circulating Angiogenic Factors and Risk of Adverse Maternal and Perinatal Outcomes in Twin Pregnancies with Suspected Preeclampsia. Hypertension 2012, 60, 451–458. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  36. Rana, S.; Powe, C.E.; Salahuddin, S.; Verlohren, S.; Perschel, F.H.; Levine, R.J.; Lim, K.H.; Wenger, J.B.; Thadhani, R.; Karumanchi, S.A. Angiogenic Factors and the Risk of Adverse Outcomes in Women with Suspected Preeclampsia. Circulation 2012, 125, 911–919. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  37. Sánchez, O.; Llurba, E.; Marsal, G.; Domínguez, C.; Aulesa, C.; Sánchez-Durán, M.A.; Goya, M.M.; Alijotas-Reig, J.; Carreras, E.; Cabero, L. First Trimester Serum Angiogenic/Anti-Angiogenic Status in Twin Pregnancies: Relationship with Assisted Reproduction Technology. Hum. Reprod. 2012, 27, 358–365. [Google Scholar] [CrossRef] [PubMed]
  38. Boucoiran, I.; Thissier-Levy, S.; Wu, Y.; Wei, S.Q.; Luo, Z.C.; Delvin, E.; Fraser, W.; Audibert, F. Risks for Preeclampsia and Small for Gestational Age: Predictive Values of Placental Growth Factor, Soluble Fms-Like Tyrosine Kinase-1, and Inhibin a in Singleton and Multiple-Gestation Pregnancies. Am. J. Perinatol. 2013, 30, 607–612. [Google Scholar] [CrossRef]
  39. Xu, H.; Perez-Cuevas, R.; Xiong, X.; Reyes, H.; Roy, C.; Julien, P.; Smith, G.; von Dadelszen, P.; Leduc, L.; Audibert, F.; et al. An International Trial of Antioxidants in the Prevention of Preeclampsia (INTAPP). Am. J. Obstet. Gynecol. 2010, 202, 239.e1–239.e10. [Google Scholar] [CrossRef]
  40. Metz, T.D.; Allshouse, A.A.; Euser, A.G.; Heyborne, K.D. Preeclampsia in High Risk Women is Characterized by Risk Group-Specific Abnormalities in Serum Biomarkers. Am. J. Obstet. Gynecol. 2014, 211, 512.e1–512.e6. [Google Scholar] [CrossRef] [Green Version]
  41. Dröge, L.; Herraiz, I.; Zeisler, H.; Schlembach, D.; Stepan, H.; Küssel, L.; Henrich, W.; Galindo, A.; Verlohren, S. Maternal Serum sFlt-1/PlGF Ratio in Twin Pregnancies with and without Pre-Eclampsia in Comparison with Singleton Pregnancies. Ultrasound Obstet. Gynecol. 2015, 45, 286–293. [Google Scholar] [CrossRef] [Green Version]
  42. Verlohren, S.; Herraiz, I.; Lapaire, O.; Schlembach, D.; Zeisler, H.; Calda, P.; Sabria, J.; Markfeld-Erol, F.; Galindo, A.; Schoofs, K.; et al. New Gestational Phase-Specific Cutoff Values for the Use of the Soluble Fms-Like Tyrosine Kinase-1/Placental Growth Factor Ratio as a Diagnostic Test for Preeclampsia. Hypertension 2014, 63, 346–352. [Google Scholar] [CrossRef]
  43. Verlohren, S.; Galindo, A.; Schlembach, D.; Zeisler, H.; Herraiz, I.; Moertl, M.G.; Pape, J.; Dudenhausen, J.W.; Denk, B.; Stepan, H. An Automated Method for the Determination of the sFlt-1/PIGF Ratio in the Assessment of Preeclampsia. Am. J. Obstet. Gynecol. 2010, 202, 161.e1–161.e11. [Google Scholar] [CrossRef] [PubMed]
  44. Svirsky, R.; Levinsohn-Tavor, O.; Feldman, N.; Klog, E.; Cuckle, H.; Maymon, R. First-and Second-Trimester Maternal Serum Markers of Pre-Eclampsia in Twin Pregnancy. Ultrasound Obstet. Gynecol. 2016, 47, 560–564. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  45. Maymon, R.; Trahtenherts, A.; Svirsky, R.; Melcer, Y.; Madar-Shapiro, L.; Klog, E.; Meiri, H.; Cuckle, H. Developing a New Algorithm for First and Second Trimester Preeclampsia Screening in Twin Pregnancies. Hypertens. Pregnancy 2017, 36, 108–115. [Google Scholar] [CrossRef] [PubMed]
  46. Francisco, C.; Wright, D.; Benkő, Z.; Syngelaki, A.; Nicolaides, K.H. Competing-Risks Model in Screening for Pre-Eclampsia in Twin Pregnancy according to Maternal Factors and Biomarkers at 11–13 Weeks’ Gestation. Ultrasound Obstet. Gynecol. 2017, 50, 589–595. [Google Scholar] [CrossRef]
  47. Saleh, L.; Tahitu, S.I.M.; Danser, A.H.J.; van den Meiracker, A.H.; Visser, W. The Predictive Value of the sFlt-1/PlGF Ratio on Short-Term Absence of Preeclampsia and Maternal and Fetal or Neonatal Complications in Twin Pregnancies. Pregnancy Hypertens. 2018, 14, 222–227. [Google Scholar] [CrossRef]
  48. Saleh, L.; Vergouwe, Y.; van den Meiracker, A.H.; Verdonk, K.; Russcher, H.; Bremer, H.A.; Versendaal, H.J.; Steegers, E.A.P.; Danser, A.H.J.; Visser, W. Angiogenic Markers Predict Pregnancy Complications and Prolongation in Preeclampsia: Continuous Versus Cutoff Values. Hypertension 2017, 70, 1025–1033. [Google Scholar] [CrossRef] [Green Version]
  49. Maynard, S.E.; Moore Simas, T.A.; Solitro, M.J.; Rajan, A.; Crawford, S.; Soderland, P.; Meyer, B.A. Circulating Angiogenic Factors in Singleton vs Multiple-Gestation Pregnancies. Am. J. Obstet. Gynecol. 2008, 198, 200.e1–200.e7. [Google Scholar] [CrossRef]
  50. Bdolah, Y.; Lam, C.; Rajakumar, A.; Shivalingappa, V.; Mutter, W.; Sachs, B.P.; Lim, K.H.; Bdolah-Abram, T.; Epstein, F.H.; Karumanchi, S.A. Twin Pregnancy and the Risk of Preeclampsia: Bigger Placenta or Relative Ischemia? Am. J. Obstet. Gynecol. 2008, 198, 428.e421–428.e426. [Google Scholar] [CrossRef]
  51. Faupel-Badger, J.M.; McElrath, T.F.; Lauria, M.; Houghton, L.C.; Lim, K.H.; Parry, S.; Cantonwine, D.; Lai, G.; Karumanchi, S.A.; Hoover, R.N.; et al. Maternal Circulating Angiogenic Factors in Twin and Singleton Pregnancies. Am. J. Obstet. Gynecol. 2015, 212, 636.e1–636.e8. [Google Scholar] [CrossRef] [Green Version]
  52. Cowans, N.J.; Spencer, K. First Trimester Maternal Serum Placental Growth Factor Levels in Twin Pregnancies. Prenat. Diagn. 2013, 33, 1260–1263. [Google Scholar] [CrossRef]
  53. The Fetal Medicine Foundation. Risk for preeclampsia 11+0 to 14+1 weeks. Available online: https://fetalmedicine.org/research/assess/preeclampsia/first-trimester (accessed on 15 November 2019).
  54. The Fetal Medicine Foundation. Risk for preeclampsia 19+0 to 24+6 weeks. Available online: https://fetalmedicine.org/research/assess/preeclampsia/second-trimester (accessed on 15 November 2019).
  55. The Fetal Medicine Foundation. Risk for preeclampsia 30+0 to 37+6 weeks. Available online: https://fetalmedicine.org/research/assess/preeclampsia/third-trimester (accessed on 15 November 2019).
  56. Herraiz, I.; Llurba, E.; Verlohren, S.; Galindo, A. Spanish Group for the Study of Angiogenic Markers in, P. Update on the Diagnosis and Prognosis of Preeclampsia with the Aid of the sFlt-1/ PlGF Ratio in Singleton Pregnancies. Fetal Diagn. Ther. 2018, 43, 81–89. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Table 1. Detailed search strategies used for databases.
Table 1. Detailed search strategies used for databases.
DatabaseNumber of StudiesSearch Strategy
Pubmed152(‘Placental Growth Factor’ [Mesh] OR ‘Placental Growth Factor*’ OR ‘PlGF’ OR ‘PIGF’ OR ‘PGF’ OR ‘P1GF’ OR ‘PGFL’ OR ‘PLGF’ OR ‘Vascular Endothelial Growth Factor Receptor-1’ [Mesh] OR ‘Receptors, Vascular Endothelial Growth Factor’[Mesh] OR ‘Flt1’ OR ‘sFlt-1’ OR ‘fms-like tyrosine kinase*’ OR ‘soluble fms-like tyrosine kinase*’ OR ‘soluble VEGF receptor*’ OR ‘VEGFR-1’ OR ‘VEGFR1’ OR ‘sVEGFR-1’ OR ‘sVEGFR1’ OR ‘VEGF *’ OR ‘vasculotropin’ OR ‘Endoglin’ [Mesh] OR ‘endoglin’ OR ‘eng’ OR ‘seng’) AND (‘Pregnancy, Multiple’ [Mesh] OR ‘Pregnancy, Twin’ [Mesh] OR ‘multiple pregnanc*’ OR ‘multiple gestation*’ OR ‘multifetal’ OR ‘twin*’) AND (‘Pre-Eclampsia’ [Mesh] OR ‘pre-eclamp*’ OR ‘preeclamp*’ OR ‘eclamp*’ OR ‘toxem*’)
Scopus63TITLE-ABS-KEY ((‘Placental Growth Factor*’ OR ‘plgf’ OR ‘pgf’ OR ‘p1gf’ OR ‘pgfl’ OR ‘plgf’ OR ‘vascular endothelial growth factor receptor*’ OR ‘flt1’ OR ‘sflt-1’ OR ‘fms-like tyrosine kinase*’ OR ‘soluble fms-like tyrosine kinase*’ OR ‘soluble VEGF receptor*’ OR ‘vegfr-1’ OR ‘vegfr1’ OR ‘svegfr-1’ OR ‘svegfr1’ OR ‘VEGF’ OR ‘vasculotropin’ OR ‘endoglin’ OR ‘eng’ OR ‘seng’) AND (‘multiple pregnanc*’ OR ‘multiple gestation*’ OR ‘multifetal’ OR ‘twin*’) AND (‘pre-eclamp*’ OR ‘preeclamp*’ OR ‘eclamp*’ OR ‘toxem*’))
Embase119(‘placental growth factor*’ OR ‘pgf’/exp OR ‘pgf’ OR ‘p1gf’ OR ‘pgfl’ OR ‘plgf’ OR ‘vascular endothelial growth factor receptor*’ OR ‘flt1’ OR ‘sflt 1’ OR ‘fms-like tyrosine kinase*’ OR ‘soluble fms-like tyrosine kinase*’ OR ‘soluble vegf receptor*’ OR ‘vegfr 1‘/exp OR ‘vegfr 1’ OR ‘vegfr1’ OR ‘svegfr 1’ OR ‘svegfr1’ OR ‘vegf’/exp OR ‘vegf’ OR ‘vasculotropin’/exp OR ‘vasculotropin’ OR ‘endoglin’/exp OR ‘endoglin’ OR ‘eng’/exp OR ‘eng’ OR ‘seng’) AND (‘multiple pregnanc*’ OR ‘multiple gestation*’ OR ‘multifetal’ OR ‘twin*’) AND (‘pre eclamp*’ OR ‘preeclamp*’ OR ‘eclamp*’ OR ‘toxem*’)
Cochrane Library4#1 ‘Placental Growth Factor’ [Mesh]
#2 ‘Placental Growth Factor*’ OR ‘PlGF’ OR ‘PGF’ OR ‘P1GF’ OR ‘PGFL’ OR ‘PLGF’
#3 ‘Vascular Endothelial Growth Factor Receptor-1’ [Mesh]
#4 ‘Receptors, Vascular Endothelial Growth Factor’ [Mesh]
#5 ‘Flt1’ OR ‘sFlt-1’ OR ‘fms-like tyrosine kinase*’ OR ‘soluble fms-like tyrosine kinase*’ OR ‘soluble VEGF receptor*’ OR ‘VEGFR-1’ OR ‘VEGFR1’ OR ‘sVEGFR-1’ OR ‘sVEGFR1’ OR ‘VEGF*’ OR ‘vasculotropin’
#6 ‘Endoglin’ [Mesh]
#7 ‘endoglin’ OR ‘eng’ OR ‘seng’
#8 ‘Pregnancy, Multiple’ [Mesh]
#9 ‘Pregnancy, Twins’ [Mesh]
#10 ‘multiple pregnanc*’ OR ‘multiple gestation*’ OR ‘multifetal’ OR ‘twin*’
#11 ‘Pre-Eclampsia’ [Mesh]
#12 ‘pre-eclamp*’ OR ‘preeclamp*’ OR ‘eclamp*’ OR ‘toxem*’
#13 (#1 OR #2 OR #3 #4 OR #5 OR #6 OR #7) AND (#8 OR #9 OR #10) AND (#11 OR #12)
Table 2. Basic characteristics of included studies.
Table 2. Basic characteristics of included studies.
StudyMain AimStudy DesignFinal Study Population of MG/TG Race or Ethnic Group of MG/TGAnalyzed Sample Collection Timing [in GW]Specimen;
Assay
Powers et al. 2010 [33]To investigate if differences in sFlt1, sEng, and PlGF in high-risk patients would identify women who later developed PE in a manner similar to low-risk women.Secondary analysis of samples obtained during a multicenter RCT of low-dose aspirin in the prevention of PE conducted between 1991 and 1995 [34].MG: 234 (not stated if all TG)Black: 49%
White: 39%
Hispanic: 12%
Non-PE: mean 21
PE: mean 20
Serum;
R&D Systems, Minneapolis, MN, USA
Rana et al. 2012 [35]To evaluate if sFlt-1 and PlGF levels correlate with PE-related adverse outcomes (HELLP, DIC, abruption, pulmonary edema, cerebral hemorrhage, maternal/ fetal/neonatal death, eclampsia, acute renal failure, SGA, indicated delivery) in TGs.Analysis of chosen cohort from another prospective cohort study evaluating the role of angiogenic factors in women with a suspicion of PE conducted between 2009 and 2011 [36].TG: 79Black: 4%
White: 86%
Asian: 9%
Other: 1%
All: median 34
Adverse outcome: median 35
Normal outcome: median 32
Plasma;
Elecsys, Roche Diagnostics, Penzberg, Germany
Sánchez et al. 2012 [37]To assess levels of sFlt1, sEng, and PlGF in maternal serum in the 1st trimester of TGs and establish if the mode of conception influences the angiogenic status.A prospective study on women with TGs or SGs who attended the first-trimester screening visit, conducted between 2008 and 2010.TG: 61LoDMean 12Serum;
R&D Systems Europe,
Abington, UK
Boucoiran
et al. 2013 [38]
To determine the accuracy of PlGF, sFlt-1, and inhibin A in SGs and MGs for predicting PE and SGA.A prospective multicenter cohort study nested in an RCT of antioxidant supplementation for the prevention of PE conducted between 2004 and 2006 [39].MG: 69 TG
+ 5 triplets
LoD; in the whole study group up to 90% CaucasianVisit 1: 12–18
Visit 2: 24–26
Plasma;
Inhibin-A, sFlt-1 - Beckman-Coulter, Chaska, MN, USA;
PlGF - DELFIA Xpress, PerkinElmer, Turku, Finland
Metz et al. 2014 [40]To determine if early pregnancy serum markers in high-risk women who develop PE vary depending on the risk factor.Secondary analysis of samples obtained during a multicenter RCT of low-dose aspirin for the prevention of PE conducted between 1991 and 1995 [34].MG: 315 (not stated if all TG)Black: 53%
White: 35%
Hispanic: 12%
Mean 21Serum;
LoD
Dröge et al. 2015 [41]To characterize serum levels of sFlt-1, PlGF, and sFlt-1:PlGF ratio in normal and PE MGs.The cohort derived from a European multicenter cohort study on the role of sFlt-1 and PlGF conducted between 2007 and 2010 [42,43].TG: 49Black: 4%
White: 90%
Other: 6%
Non-PE: mean 30
PE: mean 33
Serum;
Elecsys, Roche Diagnostics, Penzberg, Germany
Svirsky et al. 2016 [44]To evaluate the distribution of 1st and 2nd-trimester maternal serum markers (PlGF, PAPP-A, b-HCG, AFP) in TGs with and without PE.A prospective study on TG patients who attended a tertiary referral clinic for targeted scanning of TGs conducted between 2011 and 2013.TG: 133LoDSamples were collected in the 1st and 2nd trimesterSerum;
PlGF, PAPP-A - DELFIA Xpress, PerkinElmer, Turku, Finland; AFP, β-hCG – AutoDELFIA, PerkinElmer Inc., Turku, Finland; PP13 – Hylabs, Rehovot, Israel
Maymon et al. 2017 [45]To construct a new PE predicting algorithm for TGs.TG: 105 (92 DC, 13 MC)LoD
Francisco et al. 2017 [46]To develop a model for PE prediction in TGs at 11+0–13+6 GWs basing on maternal factors and markers.A prospective screening study in women with TGs attending the 1st routine hospital visit conducted between 2006 and 2015.TG: 1100 (885 DC, 215 MC)In the screening population (1200): Caucasian: 74%
Afro-Caribbean: 18%
South Asian: 4%
East Asian: 2%
Mixed: 3%
All: median 13
PE: median 13
Serum;
DELFIA Xpress, PerkinElmer, Waltham, MA, USA
Saleh et al. 2018 [47]To evaluate if a ratio of ≤38 could be used to predict the absence of PE and maternal and fetal or neonatal complications in TGs.Secondary analysis of a prospective multicenter cohort study that enrolled women with suspected or confirmed PE, conducted between 2013 and 2016 [48].TG: 21Black: 14%
White: 86%
Suspected PE: median 29
PE: median 30
Serum;
LoD
Abbreviations: CH—chronic hypertension; DC—dichorionic; DIC—disseminated intravascular coagulation; DM—diabetes mellitus; GW—gestation weeks; HELLP—hemolysis, elevated liver enzymes, low platelets syndrome; LoD—lack of data; MC—monochorionic; MG—multiple gestation; N/A—not applicable; PE—preeclampsia; PP—previous preeclampsia; RCT—randomized controlled trial; SG—single gestation; SGA—small for gestational age; TG—twin gestation; sFlt-1—soluble fms-like tyrosine kinase-1; sEng—soluble endoglin; PlGF—placental growth factor.
Table 3. Serum concentrations of sFlt-1, PlGF, sFlt1:PlGF ratio, and sEng in women in twin pregnancies who developed PE compared to women in twin pregnancies who did not develop PE.
Table 3. Serum concentrations of sFlt-1, PlGF, sFlt1:PlGF ratio, and sEng in women in twin pregnancies who developed PE compared to women in twin pregnancies who did not develop PE.
StudyAnalyzed Sample Collection Timing [in GW]sFlt-1PlGFsFlt1:PlGF ratiosEng
Power et al. 2010 [33]Non-PE MG: mean 21
PE MG: mean 20
↑ *
Rana et al. 2012 [35] **Adverse outcome TG: median 35
Normal outcome TG: median 32
==N/A
Sánchez et al. 2012 [37]TG: mean 12↑ ***N/AN/AN/A
Boucoiran et al. 2013 [38]Visit 1: 12–18
Visit 2: 24–26
↑ ****↑ ****N/A
Metz et al. 2014 [40]MG: mean 21N/A↑ *N/A
Dröge et al. 2015 [41]Non-PE TG: mean 30
PE TG: mean 33
N/A
Svirsky et al. 2016 [44]Samples were collected in the 1st and 2nd trimesterN/AN/AN/A
Maymon et al. 2017 [45]N/AN/AN/A
Francisco et al. 2017 [46]All TG: median 13
PE TG: median 13
N/AN/AN/A
Saleh et al. 2018 [47] **Suspected PE TG: median 29
PE TG: median 30
===N/A
Abbreviations: ↑—significantly higher; ↓—significantly lower; = - no significant differences; GW—gestational week; N/A—not applicable/not studied/not reported; PlGF—placental growth factor; sEng—soluble endoglin; sFlt-1—soluble fms-like tyrosine kinase-1; * sFlt-1 + sEng:PlGF; ** all women in the study had a suspicion or clinical symptoms of PE; *** PE and intrauterine growth restriction taken into account, difference significant only in twins conceived with assisted reproductive technologies; **** only at visit 2.
Table 4. Proposed algorithms for the detection of PE in twin pregnancies.
Table 4. Proposed algorithms for the detection of PE in twin pregnancies.
StudyAimFactors Taken into AccountSpecimen;
Assay
Parameters
Rana et al. 2012 [35]Prediction of PE-related adverse outcomes in the next 2 weeksHighest SBP, proteinuria, gestational age, sFlt-1:PlGF ratioPlasma;
Elecsys, Roche Diagnostics, Penzberg, Germany
AUC 0.85
10% FPR
Diagnosis of PEsFlt-1:PlGF ratio >75Sensitivity 77.8%
Specificity 86.4%
Boucoiran et al. 2013 [38]Prediction of PE
performed at 12–18 GWs
PlGFPlasma;
DELFIA Xpress, PerkinElmer, Turku, Finland
AUC 0.81
10% FPR
Dröge et al. 2015 [41]Diagnosis of PEsFlt-1:PlGF ratio ≥53Serum;
Elecsys, Roche Diagnostics, Penzberg, Germany
AUC 0.83
Sensitivity 94.4%
Specificity 74.2%
Svirsky et al. 2016 [44]Prediction of PE1st and 2nd trimester PlGF and PAPP-A with UTPI, MAPSerum;
PlGF, PAPP-A - DELFIA Xpress, PerkinElmer, Turku, Finland; AFP, β-hCG – AutoDELFIA, PerkinElmer, Turku, Finland; PP13 – Hylabs, Rehovot, Israel
65% DR
10% FPR
Maymon et al. 2017 [45]Prediction of PE
performed in the 1st and 2nd trimester
Maternal factors, PlGF, PAPP-A, PP13, UTPI, MAPAUC 0.91
75% DR
10% FPR
Francisco et al. 2017 [46]Prediction of PE
(delivery <32 GWs)
Maternal factors, PlGF, UTPI, MAP Serum;
DELFIA Xpress, PerkinElmer, Waltham, MA, USA
AUC 0.94
Prediction of PE
(delivery <37 GWs)
AUC 0.82
Prediction of PE
(delivery <42 GWs)
AUC 0.79
Abbreviations: AUC—area under the receiver operating characteristic curve; DR—detection rate; FPR—false-positive rate; GW—gestational week; MAP—mean arterial pressure; PAPP-A—pregnancy-associated protein A; PE—preeclampsia, PlGF—placental growth factor; PP13—placental protein 13; SBP—systolic blood pressure; sFlt-1—soluble fms-like tyrosine kinase-1; UTPI—uterine artery pulsatility index.

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Kosinska-Kaczynska, K.; Zgliczynska, M.; Kozlowski, S.; Wicherek, L. Maternal Serum Placental Growth Factor, Soluble Fms-Like Tyrosine Kinase-1, and Soluble Endoglin in Twin Gestations and the Risk of Preeclampsia—A Systematic Review. J. Clin. Med. 2020, 9, 183. https://doi.org/10.3390/jcm9010183

AMA Style

Kosinska-Kaczynska K, Zgliczynska M, Kozlowski S, Wicherek L. Maternal Serum Placental Growth Factor, Soluble Fms-Like Tyrosine Kinase-1, and Soluble Endoglin in Twin Gestations and the Risk of Preeclampsia—A Systematic Review. Journal of Clinical Medicine. 2020; 9(1):183. https://doi.org/10.3390/jcm9010183

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Kosinska-Kaczynska, Katarzyna, Magdalena Zgliczynska, Szymon Kozlowski, and Lukasz Wicherek. 2020. "Maternal Serum Placental Growth Factor, Soluble Fms-Like Tyrosine Kinase-1, and Soluble Endoglin in Twin Gestations and the Risk of Preeclampsia—A Systematic Review" Journal of Clinical Medicine 9, no. 1: 183. https://doi.org/10.3390/jcm9010183

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