scholarly journals Placental growth factor for the prognosis of women with preeclampsia (fullPIERS model extension): context matters

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
U. Vivian Ukah ◽  
◽  
Beth A. Payne ◽  
Jennifer A. Hutcheon ◽  
Lucy C. Chappell ◽  
...  
Keyword(s):  
Growth Factor ◽  
Characteristic Curve ◽  
External Validation ◽  
Expectant Management ◽  
Placental Growth Factor ◽  
Maternal Outcomes ◽  
Study Cohort ◽  
Extended Model ◽  
Incremental Value ◽  
Discriminatory Performance

Abstract Background The fullPIERS risk prediction model was developed to identify which women admitted with confirmed diagnosis of preeclampsia are at highest risk of developing serious maternal complications. The model discriminates well between women who develop (vs. those who do not) adverse maternal outcomes. It has been externally validated in several populations. We assessed whether placental growth factor (PlGF), a biomarker associated with preeclampsia risk, adds incremental value to the fullPIERS model. Methods Using a cohort of women admitted into tertiary hospitals in well-resourced settings (the USA and Canada), between May 2010 to February 2012, we evaluated the incremental value of PlGF added to fullPIERS for prediction of adverse maternal outcomes within 48 h after admission with confirmed preeclampsia. The discriminatory performance of PlGF and the fullPIERS model were assessed in this cohort using the area under the receiver’s operating characteristic curve (AUROC) while the extended model (fullPIERS +PlGF) was assessed based on net reclassification index (NRI) and integrated discrimination improvement (IDI) performances. Results In a cohort of 541 women delivered shortly (< 1 week) after presentation, 8.1% experienced an adverse maternal outcome within 48 h of admission. Prediction of adverse maternal outcomes was not improved by addition of PlGF to fullPIERS (NRI: -8.7, IDI − 0.06). Discriminatory performance (AUROC) was 0.67 [95%CI: 0.59–0.75] for fullPIERS only and 0.67 [95%CI: 0.58–0.76]) for fullPIERS extended with PlGF, a performance worse than previously documented in fullPIERS external validation studies (AUROC > 0.75). Conclusions While fullPIERS model performance may have been affected by differences in healthcare context between this study cohort and the model development and validation cohorts, future studies are required to confirm whether PlGF adds incremental benefit to the fullPIERS model for prediction of adverse maternal outcomes in preeclampsia in settings where expectant management is practiced.

scholarly journals Placental Growth Factor for the Prognosis of Women with Preeclampsia (fullPIERS model extension): Context matters

2020 ◽  
Author(s):  
U. Vivian Ukah ◽  
Beth A Payne ◽  
Jennifer Hutcheon ◽  
Lucy Chappell ◽  
Paul Seed ◽  
...  
Keyword(s):  
Growth Factor ◽  
Characteristic Curve ◽  
External Validation ◽  
Expectant Management ◽  
Placental Growth Factor ◽  
Maternal Outcomes ◽  
Study Cohort ◽  
Extended Model ◽  
Incremental Value ◽  
Discriminatory Performance

Abstract Background: The fullPIERS risk prediction model was developed to identify which women admitted with confirmed diagnosis of preeclampsia are at highest risk of developing serious maternal complications. The model discriminates well between women who develop (vs. those who do not) adverse maternal outcomes. It has been externally validated in several populations. We assessed whether placental growth factor (PlGF), a biomarker associated with preeclampsia risk, adds incremental value to the fullPIERS model. Methods: Using a cohort of women admitted into tertiary hospitals in well-resourced settings (the USA and Canada), between May 2010 to February 2012, we evaluated the incremental value of PlGF added to fullPIERS for prediction of adverse maternal outcomes within 48 hours after admission with confirmed preeclampsia. The discriminatory performance of PlGF and the fullPIERS model were assessed in this cohort using the area under the receiver`s operating characteristic curve (AUROC) while the extended model (fullPIERS +PlGF) was assessed based on net reclassification index (NRI) and integrated discrimination improvement (IDI) performances. Results: In a cohort of 541 women delivered shortly (<1 week) after presentation, 8.1% experienced an adverse maternal outcome within 48hrs of admission. Prediction of adverse maternal outcomes was not improved by addition of PlGF to fullPIERS (NRI: -8.7, IDI -0.06). Discriminatory performance (AUROC) was 0.67 [95%CI: 0.59-0.75] for fullPIERS only and 0.67 [95%CI: 0.58-0.76]) for fullPIERS extended with PlGF, a performance worse than previously documented in fullPIERS external validation studies (AUROC > 0.75). Conclusions: While fullPIERS model performance may have been affected by differences in healthcare context between this study cohort and the model development and validation cohorts, future studies are required to confirm whether PlGF adds incremental benefit to the fullPIERS model for prediction of adverse maternal outcomes in preeclampsia in settings where expectant management is practiced.

scholarly journals Placental Growth Factor for the Prognosis of Women with Preeclampsia (fullPIERS model extension): Context matters

2020 ◽  
Author(s):  
U. Vivian Ukah ◽  
Beth A Payne ◽  
Jennifer Hutcheon ◽  
Lucy Chappell ◽  
Paul Seed ◽  
...  
Keyword(s):  
Growth Factor ◽  
Characteristic Curve ◽  
External Validation ◽  
Expectant Management ◽  
Placental Growth Factor ◽  
Maternal Outcomes ◽  
Study Cohort ◽  
Extended Model ◽  
Incremental Value ◽  
Discriminatory Performance

Abstract Background The fullPIERS risk prediction model was developed to identify which women admitted with confirmed diagnosis of preeclampsia are at highest risk of developing serious maternal complications. The model discriminates well between women who develop (vs. those who do not) adverse maternal outcomes. It has been externally validated in several populations. We assessed whether placental growth factor (PlGF), a biomarker associated with preeclampsia risk, adds incremental value to the fullPIERS model. Methods Using a cohort of women admitted into tertiary hospitals in well-resourced settings (the USA and Canada), between May 2010 to February 2012, we evaluated the incremental value of PlGF added to fullPIERS for prediction of adverse maternal outcomes within 48 hours after admission with confirmed preeclampsia. The discriminatory performance of PlGF and the fullPIERS model were assessed in this cohort using the area under the receiver`s operating characteristic curve (AUROC) while the extended model (fullPIERS + PlGF) was assessed based on net reclassification index (NRI) and integrated discrimination improvement (IDI) performances. Results In a cohort of 541 women delivered shortly (< 1 week) after presentation, 8.1% experienced an adverse maternal outcome within 48hrs of admission. Prediction of adverse maternal outcomes was not improved by addition of PlGF to fullPIERS (NRI: -8.7, IDI − 0.06). Discriminatory performance (AUROC) was 0.67 [95%CI: 0.59–0.75] for fullPIERS only and 0.67 [95%CI: 0.58–0.76]) for fullPIERS extended with PlGF, a performance worse than previously documented in fullPIERS external validation studies (AUROC > 0.75). Conclusions While fullPIERS model performance may have been affected by differences in healthcare context between this study cohort and the model development and validation cohorts, future studies are required to confirm whether PlGF adds incremental benefit to the fullPIERS model for prediction of adverse maternal outcomes in preeclampsia in settings where expectant management is practiced.

scholarly journals Placental Growth Factor and the Risk of Adverse Neonatal and Maternal Outcomes

2020 ◽  
Vol 135 (3) ◽  
pp. 665-673 ◽  
Author(s):  
Jacqueline G. Parchem ◽  
Clifton O. Brock ◽  
Han-Yang Chen ◽  
Raghu Kalluri ◽  
John R. Barton ◽  
...  
Keyword(s):  
Growth Factor ◽  
Placental Growth Factor ◽  
Maternal Outcomes

The role of placental growth factor in regulating fetal brain vascular development

2014 ◽  
Author(s):  
Matthew T Ratsep ◽  
Bruno Zavan ◽  
Nicki Peterson ◽  
Leandra Tolusso ◽  
Vanessa Kay ◽  
...  
Keyword(s):  
Growth Factor ◽  
Vascular Development ◽  
Fetal Brain ◽  
Placental Growth Factor

Early predictors of placental dysfunction

2016 ◽  
pp. 25-28
Author(s):  
J.M. Melnik ◽  
◽  
A.A. Shlyahtina ◽  
Keyword(s):  
Vascular Endothelial Growth Factor ◽  
Growth Factor ◽  
Pregnant Women ◽  
Umbilical Artery ◽  
Placental Growth Factor ◽  
Vascular Endothelial ◽  
Endothelin 1 ◽  
Placental Dysfunction ◽  
Early Predictors ◽  
Endothelial Growth Factor

The article presents the predictors of placental dysfunction on the early stage of pregnancy. The objective: the search for prognostic markers and criteria for the occurrence of placental insufficiency in the early stages of the gestational process to optimize the pregnancy and labor with improved perinatal outcomes. Patients and methods. To solve this goal in the period from 2013 to 2015 were conducted a comprehensive survey of 334 pregnant women, which depending on the peculiarities of pregnancy and childbirth were divided into groups. The control group consisted of 236 pregnant women with uncomplicated gestational period, no morphological signs of placental dysfunction. The study group included 98 patients with a complicated pregnancy who had revealed violations of the fetal-placental relations, which was confirmed by morphological examination of the placenta in the postpartum period. Results. It was found that pregnant women with placental insufficiency in the first trimester of pregnancy have higher levels of interleukin-1B (IL-1v) and interleukin-3 (IL-3) in comparison with physiological pregnancy, as well as there is a direct significant correlation between IL-1v and pulsative index (PI) in the spiral (r=0.84) and uterine artery (r=0.77), and the inverse correlation between the level of IL-3 and PI in the terminal branches of the umbilical artery (r=-0.69). Verified an inverse relationship between the concentration of endothelin-1, the level of vascular endothelial growth factor (r=-0.87) and placental growth factor (r=-0.73), and also a direct link between the content of endothelin-1 and PI in spiral arteries (r=0.89), uterine artery (r=0.83) and the terminal branches of the umbilical artery (r=0.79). Conclusion. Thus, it is proven that early predictors of placental dysfunction can be considered the concentration of endothelin-1, vascular endothelial growth factor, placental growth factor, interleukin-1, interleukin-3, and the indices of pulsative index. Key words: placental dysfunction, predictors, endothelin-1, vascular endothelial growth factor, placental growth factor, interleukin, pulsative index.

scholarly journals A radiomics-based model for predicting prognosis of locally advanced gastric cancer in the preoperative setting

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jaeseung Shin ◽  
Joon Seok Lim ◽  
Yong-Min Huh ◽  
Jie-Hyun Kim ◽  
Woo Jin Hyung ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Advanced Gastric Cancer ◽  
Cox Regression ◽  
Characteristic Curve ◽  
External Validation ◽  
Locally Advanced ◽  
Clinical Model ◽  
Locally Advanced Gastric Cancer ◽  
Contrast Enhanced Ct ◽  
Preoperative Ct

AbstractThis study aims to evaluate the performance of a radiomic signature-based model for predicting recurrence-free survival (RFS) of locally advanced gastric cancer (LAGC) using preoperative contrast-enhanced CT. This retrospective study included a training cohort (349 patients) and an external validation cohort (61 patients) who underwent curative resection for LAGC in 2010 without neoadjuvant therapies. Available preoperative clinical factors, including conventional CT staging and endoscopic data, and 438 radiomic features from the preoperative CT were obtained. To predict RFS, a radiomic model was developed using penalized Cox regression with the least absolute shrinkage and selection operator with ten-fold cross-validation. Internal and external validations were performed using a bootstrapping method. With the final 410 patients (58.2 ± 13.0 years-old; 268 female), the radiomic model consisted of seven selected features. In both of the internal and the external validation, the integrated area under the receiver operating characteristic curve values of both the radiomic model (0.714, P < 0.001 [internal validation]; 0.652, P = 0.010 [external validation]) and the merged model (0.719, P < 0.001; 0.651, P = 0.014) were significantly higher than those of the clinical model (0.616; 0.594). The radiomics-based model on preoperative CT images may improve RFS prediction and high-risk stratification in the preoperative setting of LAGC.

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