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ML Decision Model for G-NEC Adjuvant Therapy

NCT06663852 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 1505

Last updated 2024-11-27

No results posted yet for this study

Summary

Gastric neuroendocrine carcinoma (G-NEC) is a rare and aggressive tumor originating from neuroendocrine cells in the stomach lining. It is characterized by a high propensity for recurrence and a generally poor prognosis. Due to its rarity, there is limited data and no established consensus on the optimal postoperative adjuvant therapy, making treatment decisions challenging for healthcare providers.

This study is a retrospective analysis focusing on evaluating survival rates, identifying prognostic factors, and formulating treatment recommendations for patients with G-NEC. By analyzing real-world clinical data, we aim to better understand the factors that influence patient outcomes and to develop evidence-based strategies for improving survival. Our goal is to provide clinicians with valuable insights and tools to make more informed treatment decisions, ultimately enhancing the quality of care and outcomes for patients with this challenging disease.

Conditions

  • Gastric Neuroendocrine Carcinoma (G-NEC)
  • Postoperative Adjuvant Therapy for G-NEC
  • Survival Outcomes
  • Machine Learning

Sponsors & Collaborators

  • Chang-Ming Huang, Prof.

    lead OTHER

Eligibility

Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2024-01-01
Primary Completion
2024-06-01
Completion
2024-06-30

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06663852 on ClinicalTrials.gov