At a glance
ClinicalIndex Comparison RecordN/ACompleted· 1,267 enrolled
Drug / intervention
esophagectomyprocedure
Likely dose
Not stated in record
Structured eligibility isn't available for this trial yet — see the full criteria in the Eligibility tab below.
Standardized by ClinicalIndex from the ClinicalTrials.gov record · verify against the source.
Machine Learning to Predict Lymph Node Metastasis in T1 Esophageal Squamous Cell Carcinoma: A Multicenter Study
In Brief
A clinical study evaluating esophagectomy for Lymph Node Metastasis. Completed, enrolled 1,267 participants across 1 site.
Detailed Summary
Existing models do poorly when it comes to quantifying the risk of Lymph node metastases (LNM). This study generated elastic net regression (ELR), random forest (RF), extreme gradient boosting (XGB), and a combined (ensemble) model of these for LNM in patients with T1 esophageal squamous cell carcinoma.
Study Details
Study Typeinterventional
Allocation--
Masking--
Primary Purpose--
ConditionsLymph Node Metastasis
CountriesChina
Collaborators--
Timeline
N/ACompletedFinished
20102011201220132014201520162017201820192020202120222023202420252026
Enrollment StartJan 2010
Primary CompletionDec 2019
Study CompletionJul 2023
First PostedFeb 2024
TodayJul 2026
First PostedFeb 13, 2024
Enrollment StartJan 15, 2010
Primary CompletionDec 15, 2019
Study CompletionJul 15, 2023
TodayJul 2, 2026
Enrollment to primary: 9.9 yearsPosted 2.4 years ago
Interventions
esophagectomyprocedure
Resection of esophageal tumor and lymph node dissection