ArticleFrontiers in oncology2023
A LASSO-based model to predict central lymph node metastasis in preoperative patients with cN0 papillary thyroid cancer.
Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07357571 (Multicenter Retrospective Study of Dual-mode Contrast-enhanced Ultrasound Predictive Model for Lymph Node Metastasis Burden in T1N0M0 Papillary Thyroid Carcinoma), which is not on this map. Cited by 13 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Multicenter Retrospective Study of Dual-mode Contrast-enhanced Ultrasound Predictive Model for Lymph Node Metastasis Burden in T1N0M0 Papillary Thyroid Carcinoma
Who cites it
13 citing papers in PubMed, 16 citations in OpenAlex.
- AI Trustworthiness in the Perioperative Period for Patients with Serious Illness: Scoping Narrative Review.JMIR perioperative medicine · 2026Article
- Nomogram for postoperative pathological stratification of ≥0.2 cm clinically significant lymph node metastasis burden in pN1 papillary thyroid carcinoma: development and validation using L2 ridge penalized logistic regression.Frontiers in endocrinology · 2026Article
- Association between ultrasound radiomics features and central lymph node metastasis in patients with papillary thyroid carcinoma.American journal of cancer research · 2026Article
- Integration of Bioinformatics and Machine Learning Strategies Identifies Ferroptosis and Immune Infiltration Signatures in Peri-Implantitis.International journal of molecular sciences · 2025Article
- Article
- A lasso-based model to predict lateral lymph node metastasis in unifocal papillary thyroid carcinoma with central lymph node metastasis.Endocrine · 2025Article
- Construction and validation of a predictive model for lymph node metastasis in patients with papillary thyroid carcinoma.Frontiers in endocrinology · 2025Article
- Article
- Explainable machine learning model for predicting paratracheal lymph node metastasis in cN0 papillary thyroid cancer.Scientific reports · 2024Article
- Article
- Ultrasound radiomics signature for predicting central lymph node metastasis in clinically node-negative papillary thyroid microcarcinoma.Thyroid research · 2024Article
- Role of prophylactic central neck lymph node dissection for papillary thyroid carcinoma in the era of de-escalation.World journal of clinical oncology · 2023Review
- Risk factors for central lymph node metastasis in patients with papillary thyroid carcinoma: a retrospective study.Frontiers in endocrinology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Central lymph node metastasis (CLNM) is common in papillary thyroid carcinoma (PTC). Prophylactic central lymph node dissection (PCLND) in clinically negative central compartment lymph node (cN0) PTC patients is still controversial. How to predict CLNM before the operation is very important for surgical decision making. Methods: In this article, we retrospectively enrolled 243 cN0 PTC patients and gathered data including clinical characteristics, ultrasound (US) characteristics, pathological results of fine-needle aspiration (FNA), thyroid function, eight gene mutations, and immunoenzymatic results. Least absolute shrinkage and selection operator (LASSO) analysis was used for data dimensionality reduction and feature analysis. Results: According to the results, the important predictors of CLNM were identified. Multivariable logistic regression analysis was used to establish a new nomogram prediction model. The receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) curve were used to evaluate the performance of the new prediction model. Discussion: The new nomogram prediction model was a reasonable and reliable model for predicting CLNM in cN0 PTC patients, but further validation is warranted.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.