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ML Decision Model for G-NEC Adjuvant Therapy

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clinicaltrials.gov/study/NCT06663852
Is a
‌
Clinical study
0

Clinical Study attributes

NCT Number
NCT066638520
Health Conditions in Trial
Machine learning
Machine learning
0
Trial Recruitment Size
1,5050
Clinical Trial Start Date
January 1, 2024
0
Primary Completion Date
June 1, 2024
0
Study Completion Date
June 30, 2024
0
Clinical Trial Study Type
Observational0
Observational Clinical Trial Type
Cohort0
Observational Study Perspective
Retrospective0
Participating Facility
Fujian Medical University
Fujian Medical University
0
Official Name
Machine Learning-Based Decision Model for Optimal Adjuvant Therapy in Primary Gastric Neuroendocrine Carcinoma: a National Real-World Evidence Study0
Last Updated
October 29, 2024
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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.

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