Validation of Fetal Medicine Foundation competing-risks model for small-for-gestational-age neonate in early third trimester.

Ultrasound Obstet Gynecol

Third Department of Obstetrics and Gynecology, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece.

Published: April 2024

Objective: To evaluate the new 36-week Fetal Medicine Foundation (FMF) competing-risks model for the prediction of small-for-gestational age (SGA) at an earlier gestation of 30 + 0 to 34 + 0 weeks.

Methods: This was a retrospective multicenter cohort study of prospectively collected data on 3012 women with a singleton pregnancy undergoing ultrasound examination at 30 + 0 to 34 + 0 weeks' gestation as part of a universal screening program. We used the default FMF competing-risks model for prediction of SGA at 36 weeks' gestation combining maternal factors (age, obstetric and medical history, weight, height, smoking status, race, mode of conception), estimated fetal weight (EFW) and uterine artery pulsatility index (UtA-PI) to calculate risks for different cut-offs of birth-weight percentile and gestational age at delivery. We examined the accuracy of the model by means of discrimination and calibration.

Results: The prediction of SGA < 3 percentile improved with the addition of UtA-PI and with a shorter examination-to-delivery interval. For a 10% false-positive rate, maternal factors, EFW and UtA-PI predicted 88.0%, 74.4% and 72.8% of SGA < 3 percentile delivered at < 37, < 40 and < 42 weeks' gestation, respectively. The respective values for SGA < 10 percentile were 86.1%, 69.3% and 66.2%. In terms of population stratification, if the biomarkers used are EFW and UtA-PI and the aim is to detect 90% of SGA < 10 percentile, then 10.8% of the population should be scanned within 2 weeks after the initial assessment, an additional 7.2% (total screen-positive rate (SPR), 18.0%) should be scanned within 2-4 weeks after the initial assessment and an additional 11.7% (total SPR, 29.7%) should be examined within 4-6 weeks after the initial assessment. The new model was well calibrated.

Conclusions: The 36-week FMF competing-risks model for SGA is also applicable and accurate at 30 + 0 to 34 + 0 weeks and provides effective risk stratification, especially for cases leading to delivery < 37 weeks of gestation. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Download full-text PDF

Source
http://dx.doi.org/10.1002/uog.27498DOI Listing

Publication Analysis

Top Keywords

competing-risks model
12
fetal medicine
8
medicine foundation
8
fmf competing-risks
8
model prediction
8
prediction sga
8
validation fetal
4
foundation competing-risks
4
model
4
model small-for-gestational-age
4

Similar Publications

Objectives: Admission to ICU is associated with long-term consequences for the survivors. The study explores whether Danish ICU survivors remain employed after ICU discharge.

Design: A longitudinal register study of 16,284 Danish ICU survivors 25-67 years old 1:1 sex- and age-matched with general population references.

View Article and Find Full Text PDF

An imbalance in the serum sodium to chloride ratio (Na/Cl) was linked to higher mortality among heart failure patients. Nonetheless, the prognostic significance of Na/Cl in individuals undergoing peritoneal dialysis (PD) remains unexplored. This study seeks to explore the association between initial Na/Cl levels and mortality in PD patients.

View Article and Find Full Text PDF

Competing risks regression for clustered data with covariate-dependent censoring.

Commun Stat Theory Methods

March 2024

Division of Biostatistics, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, 53226, Wisconsin,USA.

Competing risks data in clinical trial or observational studies often suffer from cluster effects such as center effects and matched pairs design. The proportional subdistribution hazards (PSH) model is one of the most widely used methods for competing risks data analyses. However, the current literature on the PSH model for clustered competing risks data is limited to covariate-independent censoring and the unstratified model.

View Article and Find Full Text PDF

Adjusted curves for clustered survival and competing risks data.

Commun Stat Simul Comput

August 2023

Division of Biostatistics, Medical College of Wisconsin, Milwaukee, WI 53226, USA.

Observational studies with right-censored data often have clustered data due to matched pairs or a study center effect. In such data, there may be an imbalance in patient characteristics between treatment groups, where Kaplan-Meier curves or unadjusted cumulative incidence curves can be misleading and may not represent the average patient on a given treatment arm. Adjusted curves are desirable to appropriately display survival or cumulative incidence curves in this case.

View Article and Find Full Text PDF

Objectives: Survival outcomes of patients with metastatic urothelial carcinoma (mUC) are still suboptimal and strategies to enhance response to immune-oncology (IO) compounds are under scrutiny. In preclinical studies, it has been demonstrated that antihistamines may reverse macrophage immunosuppression, reactivate T cell cytotoxicity, and enhance the immunotherapy response. We aimed to evaluate the role of concomitant antihistamines administration on oncological outcomes among patients with mUC.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!