- Home
- Medical news & Guidelines
- Anesthesiology
- Cardiology and CTVS
- Critical Care
- Dentistry
- Dermatology
- Diabetes and Endocrinology
- ENT
- Gastroenterology
- Medicine
- Nephrology
- Neurology
- Obstretics-Gynaecology
- Oncology
- Ophthalmology
- Orthopaedics
- Pediatrics-Neonatology
- Psychiatry
- Pulmonology
- Radiology
- Surgery
- Urology
- Laboratory Medicine
- Diet
- Nursing
- Paramedical
- Physiotherapy
- Health news
- Fact Check
- Bone Health Fact Check
- Brain Health Fact Check
- Cancer Related Fact Check
- Child Care Fact Check
- Dental and oral health fact check
- Diabetes and metabolic health fact check
- Diet and Nutrition Fact Check
- Eye and ENT Care Fact Check
- Fitness fact check
- Gut health fact check
- Heart health fact check
- Kidney health fact check
- Medical education fact check
- Men's health fact check
- Respiratory fact check
- Skin and hair care fact check
- Vaccine and Immunization fact check
- Women's health fact check
- AYUSH
- State News
- Andaman and Nicobar Islands
- Andhra Pradesh
- Arunachal Pradesh
- Assam
- Bihar
- Chandigarh
- Chattisgarh
- Dadra and Nagar Haveli
- Daman and Diu
- Delhi
- Goa
- Gujarat
- Haryana
- Himachal Pradesh
- Jammu & Kashmir
- Jharkhand
- Karnataka
- Kerala
- Ladakh
- Lakshadweep
- Madhya Pradesh
- Maharashtra
- Manipur
- Meghalaya
- Mizoram
- Nagaland
- Odisha
- Puducherry
- Punjab
- Rajasthan
- Sikkim
- Tamil Nadu
- Telangana
- Tripura
- Uttar Pradesh
- Uttrakhand
- West Bengal
- Medical Education
- Industry
PTerm Classifier promising tool for Accurately Predicting Preterm Birth: Study Finds

China: In a significant advancement for prenatal care, researchers have developed a blood-based classifier called PTerm that can accurately predict the risk of preterm birth using genome-wide patterns in cell-free DNA (cfDNA). This innovative tool, which leverages existing non-invasive prenatal testing (NIPT) data, offers a highly accurate and cost-effective method for early detection of at-risk pregnancies.
The findings were published online in PLOS Medicine on April 15, 2025.
Preterm birth (PTB)—delivery before 37 weeks of gestation—remains a global challenge, affecting around 11% of pregnancies and contributing significantly to neonatal complications and maternal health risks. PTerm harnesses cfDNA, which circulates in the maternal bloodstream and reflects genetic material from the placenta and other maternal tissues. Because these DNA fragments dynamically respond to biological and pathological changes during pregnancy, they serve as a valuable biomarker for anticipating complications such as PTB.
To establish the model, Zhiwei Guo, Southern Medical University, Guangzhou, China, and colleagues conducted a comprehensive, multi-center study involving 2,590 pregnant women—518 with spontaneous preterm births and 2,072 with full-term deliveries—recruited from three independent hospitals. Whole-genome sequencing of plasma cfDNA was performed, focusing on promoter regions that regulate gene expression. Advanced machine learning techniques, including support vector machines and feature selection algorithms, were used to build the predictive model.
Key Findings:
- PTerm, the Promoter profiling classifier for preterm prediction, achieved the highest accuracy among all tested models with an AUC of 0.878 based on leave-one-out cross-validation.
- The classifier maintained strong predictive performance across three independent validation cohorts, with a consistent AUC of 0.849, highlighting its reliability across varied populations.
- A major benefit of PTerm is its compatibility with current non-invasive prenatal testing (NIPT) workflows, requiring no changes in procedure or additional cost.
- Its integration into routine prenatal screening could help identify high-risk pregnancies early, enabling timely and targeted medical interventions.
The researchers emphasized that incorporating tools like PTerm into clinical practice could enhance early risk assessment and help lower the global burden of preterm births. They hope future studies will further validate its clinical utility and encourage widespread adoption of cfDNA-based risk prediction models in obstetric care.
"PTerm showed strong predictive accuracy for identifying preterm birth risk. Moreover, it can be applied directly to existing non-invasive prenatal testing data without altering current procedures or incurring additional costs, making it a practical and scalable option for early screening in clinical settings," the authors concluded.
Reference:
Guo Z, Wang K, Huang X, Li K, Ouyang G, Yang X, et al. (2025) Genome-wide nucleosome footprints of plasma cfDNA predict preterm birth: A case-control study. PLoS Med 22(4): e1004571. https://doi.org/10.1371/journal.pmed.1004571
Dr Kamal Kant Kohli-MBBS, DTCD- a chest specialist with more than 30 years of practice and a flair for writing clinical articles, Dr Kamal Kant Kohli joined Medical Dialogues as a Chief Editor of Medical News. Besides writing articles, as an editor, he proofreads and verifies all the medical content published on Medical Dialogues including those coming from journals, studies,medical conferences,guidelines etc. Email: drkohli@medicaldialogues.in. Contact no. 011-43720751