Related Experiment Videos
Second-trimester biochemical screening.
M I Evans1, J E O'Brien, E Dvorin
1Department of Obstetrics and Gynecology and Fetal Therapy Program, MCP Hahnemann University School of Medicine, Philadelphia, Pennsylvania, USA.
Clinics in Perinatology
|August 14, 2001
Summary
Biochemical screening shows multiple markers, like beta-hCG, improve detection over AFP alone. Current methods plateau, necessitating new approaches for enhanced screening sensitivity and reduced false positives.
Area of Science:
- Biochemistry
- Medical Diagnostics
- Screening Methodologies
Background:
- Biochemical screening has advanced, with multiple markers like beta-hCG demonstrating superiority over single markers such as AFP.
- Controversy persists regarding optimal mathematical algorithms and marker combinations (e.g., beta-hCG, uE3) for screening.
- Current screening methodologies appear to have reached a plateau in detection frequencies, typically between 65% and 70%.
Purpose of the Study:
- To review the progress and limitations of current biochemical screening methods.
- To highlight the need for novel approaches to improve screening sensitivity.
- To explore the integration of biochemical and biophysical parameters for advanced abnormality detection.
Main Methods:
- Analysis of existing data on biochemical screening markers.
- Discussion of mathematical algorithms used in screening.
- Exploration of combined biochemical and biophysical parameter approaches.
Main Results:
- Multiple markers, particularly beta-hCG, offer advantages over single markers like AFP.
- Detection rates for current methods are limited, reaching a plateau around 65-70%.
- Combining biochemical and biophysical parameters is proposed as a next-generation approach.
Conclusions:
- Substantial improvement in screening sensitivity requires innovative approaches beyond current methodologies.
- The combination of biochemical and biophysical parameters represents a promising strategy for enhancing abnormality detection.
- Future research should focus on integrating diverse parameters to minimize false positives and maximize detection rates.