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NCT Number: NCT06663852

ML Decision Model for G-NEC Adjuvant Therapy

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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Key information

Conditions

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

Sex eligibility

All sexes

Study type

Observational

Primary location

Fujian Medical University

Fuzhou, Fujian, 350001, China

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • (1) patients who underwent radical surgery without any neoadjuvant therapy;
  • (2) pathology confirmed NEC or mixed adenoneuroendocrine carcinoma (MANEC).

Exclusion criteria

  • (1) history of other malignant neoplasms;
  • (2) treatment with endoscopic submucosal dissection or endoscopic mucosal resection or thoracotomy;
  • (3) incomplete clinical data (including pathological, adjuvant chemotherapy, and follow-up information);
  • (4) receipt of alternative adjuvant treatment regimens;
  • (5) death within 30 days postoperatively.

Treatment and study plan

Primary outcomes

  1. Disease-Free Survival (DFS)

    Time frame: From date of surgery up to 5 years

    Disease-free survival is defined as the time from the date of surgery to disease recurrence, death from any cause, or last follow-up, whichever occurs first. The machine learning model's performance in predicting DFS and recommending optimal adjuvant therapy will be evaluated.

Sponsors and collaborators

Lead sponsor

Chang-Ming Huang, Prof.

Other

Registry information

Official study title

Machine Learning-Based Decision Model for Optimal Adjuvant Therapy in Primary Gastric Neuroendocrine Carcinoma: a National Real-World Evidence Study

Acronym: G-NEC

Important dates

Study start
2024
Primary completion
2024
Study completion
2024
First posted
Oct 29, 2024
Registry last updated
Nov 27, 2024

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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