Interpretable Machine Learning Models for Prognosis in Gastric Cancer Patients

Completed

• Conditions: Stomach Neoplasms; Machine Learning; Gastrectomy

• Registration Number: NCT06548464
• Lead Sponsor: Chang-Ming Huang, Prof.

Brief Summary

This multicenter, retrospective cohort study aimed to develop and validate an explainable prediction model for prognosis after gastrectomy in patients with gastric cancer.

Detailed Description

This multicenter, retrospective cohort study aimed to develop and validate an explainable prediction model for prognosis after gastrectomy in patients with gastric cancer. The study included patients who underwent radical gastrectomy for primary gastric or gastroesophageal junction cancer across multiple institutions in China.

The primary objective was to create a machine learning-based model to predict postoperative outcomes following gastrectomy, using readily available clinical and pathological parameters. The main outcome of interest was early recurrence within 2 years after surgery, which significantly impacts overall prognosis.

The study employed various machine learning algorithms to develop prediction models, which were then compared and validated. Model performance was assessed through measures such as area under the receiver operating characteristic curve (AUC), calibration, and Brier score. The SHapley Additive exPlanations (SHAP) method was used to interpret the model and rank feature importance.

This research aims to provide clinicians with a tool for identifying patients at higher risk of poor postoperative outcomes who may benefit from more intensive post-operative monitoring and early intervention strategies, potentially improving prognosis for gastric cancer patients.

Basic Information
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Recruitment & Eligibility
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Study & Design
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Trial Locations

Study Timeline

• Study Start: 2024-06-01
• Status Verified: 2024-08
• Primary Completion: 2024-08-01
• Study Completion: 2024-08-06
• Study First Submitted: 2024-08-06
• Study First Submitted QC: 2024-08-09
• Last Update Submitted: 2024-08-09
• Study First Posted: 2024-08-12
• Last Update Posted: 2024-08-12

Recruitment & Eligibility

• Status: COMPLETED
• Sex: All
• Target Recruitment: 18000

Inclusion Criteria

• Patients diagnosed with primary gastric or gastroesophageal junction cancer
• Underwent radical gastrectomy
• Complete clinical and pathological data available

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Exclusion Criteria

• Presence of distant metastases before surgery
• Non-adenocarcinoma histology
• Incomplete follow-up data

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Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Survival	Up to 5 years after surgery	Assessment of overall survival outcomes in gastric cancer patients after gastrectomy.

Secondary Outcome Measures

Name	Time	Method
5-Year Survival Rate	5 years after surgery	Percentage of patients alive 5 years after gastrectomy.
Neoadjuvant Treatment Efficacy	From initiation of neoadjuvant therapy to surgery (typically 2-3 months)	Assessment of tumor response to neoadjuvant therapy before gastrectomy.
Early Recurrence	Within 2 years after surgery	Incidence of cancer recurrence within 2 years after gastrectomy.
Late Recurrence	From 2 years up to 5 years after surgery	Incidence of cancer recurrence occurring more than 2 years after gastrectomy.
Postoperative Complications	Within 30 days after surgery	Incidence and severity of complications following gastrectomy.

Trial Locations

Locations (1)

Chang-ming Huang; 🇨🇳 Fuzhou, Fujian, China