A Lymph Node Metastasis Predictor (LN-MASTER) in Rectal Cancer
An Easy-to-use Artificial Intelligence Preoperative Lymph Node Metastasis Predictor (LN-MASTER) in Rectal Cancer Based on a Privacy-preserving Computing Platform: Multicenter Retrospective Cohort Study
1 other identifier
observational
6,578
0 countries
N/A
Brief Summary
In this study, we aim to develop and validate an easy-to-use machine learning prediction model to preoperatively identify the lymph node metastasis status for rectal cancer patients by using these clinical data from three hospitals.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Jan 2010
Longer than P75 for all trials
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
Study Start
First participant enrolled
January 1, 2010
CompletedPrimary Completion
Last participant's last visit for primary outcome
December 31, 2015
CompletedStudy Completion
Last participant's last visit for all outcomes
December 31, 2015
CompletedFirst Submitted
Initial submission to the registry
August 5, 2022
CompletedFirst Posted
Study publicly available on registry
August 9, 2022
CompletedAugust 9, 2022
August 1, 2022
6 years
August 5, 2022
August 6, 2022
Conditions
Outcome Measures
Primary Outcomes (1)
diagnosis of lymph node metastasis
The lymph node metastasis (LNM) status was determined based on the pathological diagnosis of the surgical specimens.
through study completion, an average of 1 month
Study Arms (3)
development set;
RC patients from the Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical College
external validation sets 1
RC patients from Changhai Hospital, Naval Medical University
external validation sets 2
RC patients from the Second Affiliated Hospital of Harbin Medical University
Interventions
Eligibility Criteria
rectal cancer patients with/without lymph node metastasis
You may qualify if:
- American Joint Committee on Cancer (AJCC) stages I -III rectal cancer
- underwent radical surgery
You may not qualify if:
- other malignancies
- received treatment with endoscopic submucosal dissection (ESD)
- metastatic lesions
- did not undergo lymph node dissection
- had unavailable assessed lymph node status
- received neoadjuvant therapy
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- Peking Union Medical Collegelead
- The Second Affiliated Hospital of Harbin Medical Universitycollaborator
- Changhai Hospitalcollaborator
Related Publications (1)
Guan X, Yu G, Zhang W, Wen R, Wei R, Jiao S, Zhao Q, Lou Z, Hao L, Liu E, Gao X, Wang G, Zhang W, Wang X. An easy-to-use artificial intelligence preoperative lymph node metastasis predictor (LN-MASTER) in rectal cancer based on a privacy-preserving computing platform: multicenter retrospective cohort study. Int J Surg. 2023 Mar 1;109(3):255-265. doi: 10.1097/JS9.0000000000000067.
PMID: 36927812DERIVED
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Design
- Study Type
- observational
- Observational Model
- COHORT
- Time Perspective
- RETROSPECTIVE
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Chief of Colorectal Cancer Surgery
Study Record Dates
First Submitted
August 5, 2022
First Posted
August 9, 2022
Study Start
January 1, 2010
Primary Completion
December 31, 2015
Study Completion
December 31, 2015
Last Updated
August 9, 2022
Record last verified: 2022-08