Machine learning-based prediction of lymph node metastases for individualized surgical decision-making in older patients with gastric cancer: A retrospective simulation study compliant with TRIPOD+AI

Machine learning-based prediction of lymph node metastases for individualized surgical decision-making in older patients with gastric cancer: A retrospective simulation study compliant with TRIPOD+AI - ML-based LNM prediction in GC

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

JPRN

Registry ID

JPRN-UMIN000061679

Enrollment

1405

Registered

2026-05-25

Start date

2026-05-18

Completion date

Unknown

Last updated

2026-06-29

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Gastric cancer

Interventions

None listed

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: patients aged 70 years and above who underwent gastrectomies with lymph node dissections for gastric cancer between April 1995 and March 2025.

Exclusion criteria

Exclusion criteria: (i) neoadjuvant chemotherapy (ii) distant metastases (M1)

Design outcomes

Primary

Measure	Time frame
the area under the receiver operating characteristic curve (ROC-AUC) and area under the precision-recall curve (PR-AUC) of the model	—

Countries

Japan

Contacts

Public ContactGoshi Fujimoto

Kameda Medical Center Gastroenterological Surgery

g_chimera_7@yahoo.co.jp0470922211

Outcome results