A predictive model using platelets and neutrophil-to-lymphocyte ratio for the number of lymph node metastases in papillary thyroid carcinoma: a retrospective analysis
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View abstract on PubMed
Summary
This summary is machine-generated.Predicting lymph node metastases in papillary thyroid cancer is now more accurate. A new model uses age, tumor size, platelet count, and neutrophil-to-lymphocyte ratio to identify high-risk patients before surgery.
Area Of Science
- Oncology
- Surgical Oncology
- Biomarkers
Background
- Large number lymph node metastases (LNLNMs) in papillary thyroid carcinoma (PTC) increase recurrence risk.
- Preoperative prediction of LNLNMs in PTC is challenging for clinicians.
- Identifying high-risk patients is crucial for personalized treatment strategies.
Purpose Of The Study
- To develop and validate a predictive model for LNLNMs in PTC.
- Integrate blood inflammatory markers and clinical features for risk assessment.
- Enhance preoperative risk stratification for PTC patients.
Main Methods
- Retrospective cohort study of 731 PTC patients.
- Logistic regression analysis to identify independent risk factors for LNLNM.
- Model development and validation using ROC curves, HL test, and DCA.
Main Results
- Age, tumor diameter, platelet (Plt) count, and neutrophil-to-lymphocyte ratio (NLR) were independent risk factors for LNLNM.
- The predictive model achieved an AUC of 0.827 in the model group and 0.824 in the validation group.
- The model demonstrated good calibration and diagnostic value.
Conclusions
- Age, tumor diameter, Plt count, and NLR are significant risk factors for LNLNM in PTC.
- The developed predictive model effectively identifies patients at high risk for LNLNM.
- This model aids surgeons in preoperative risk assessment and personalized treatment planning.
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