Gastric Neuroendocrine Carcinoma (G-NEC)G-NECNCT06663852
ML Decision Model for G-NEC Adjuvant Therapy
An observational study of Gastric Neuroendocrine Carcinoma (G-NEC) and Postoperative Adjuvant Therapy for G-NEC, run by Chang-Ming Huang, Prof. at 1 site in China.
Trial 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. Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Gastric Neuroendocrine Carcinoma (G-NEC), Postoperative Adjuvant Therapy for G-NEC, Survival Outcomes
- How many people
- 1,505 participants
- Where
- 1 siteChina
- Study dates
- 1 Jan 2024to 30 Jun 2024
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
Study population: This study includes adult patients diagnosed with gastric neuroendocrine carcinoma (G-NEC) or mixed adenoneuroendocrine carcinoma (MANEC) who underwent radical surgery at 38 tertiary hospitals in China between January 2006 and December 2020. The study population consists of patients who received either no adjuvant chemotherapy, etoposide and platinum derivatives-based chemotherapy, or fluorouracil-based chemotherapy following surgery.
Who may be able to join
- (1) patients who underwent radical surgery without any neoadjuvant therapy;
- (2) pathology confirmed NEC or mixed adenoneuroendocrine carcinoma (MANEC).
Who cannot join
- (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.
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Machine Learning-Based Decision Model for Optimal Adjuvant Therapy in Primary Gastric Neuroendocrine Carcinoma: a National Real-World Evidence Study
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
- Keywords
- Gastric Neuroendocrine Carcinoma (G-NEC), Adjuvant Chemotherapy, Machine Learning, Decision Support Model, Random Survival Forest
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Gastric Neuroendocrine Carcinoma (G-NEC) Patients | This study focuses on patients diagnosed with gastric neuroendocrine carcinoma (G-NEC) who have undergone radical surgery. The cohort includes adult patients (≥18 years) treated at 38 tertiary hospitals in China between January 2006 and December 2020. Patients are divided into three groups based on their postoperative adjuvant treatment: no adjuvant chemotherapy, etoposide and platinum derivatives-based chemotherapy, and fluorouracil-based chemotherapy. The study aims to develop and validate a machine learning-based decision support model to optimize individualized adjuvant therapy strategies for G-NEC patients, with the primary outcome being disease-free survival (DFS). |
What is being measured
The primary outcome is the main question the study is designed to answer.
Disease-Free Survival (DFS)
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.
Measured: From date of surgery up to 5 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted29 Oct 2024
- Study start1 Jan 2024
- Primary completion1 Jun 2024
- Study completion30 Jun 2024
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Gastric Neuroendocrine Carcinoma (G-NEC)Studies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 1,505 participants (actual)
Sponsor and investigators
- Lead sponsor
- Chang-Ming Huang, Prof.
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor-investigator, Chang-Ming Huang, Prof., Fujian Medical University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06663852
- Sponsor's protocol ID
- 2024GNEC
- Acronym
- G-NEC
- Status last verified
- Oct 2024
- First submitted
- 26 Oct 2024
- Last updated
- 27 Nov 2024
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided: Patient Privacy: As this study involves sensitive medical information, we must ensure that any data sharing plan complies with all relevant privacy laws and regulations. Ethical Considerations: We are consulting with our ethics committee to determine the most appropriate approach to data sharing that respects patient consent and maintains the integrity of the research. Data Standardization: Given the multi-center nature of this study, we are working on standardizing our data collection and storage processes across all 38 participating hospitals to ensure consistency and quality of any potentially shared data. Collaborative Potential: We recognize the value of data sharing in advancing gastric neuroendocrine carcinoma research and are exploring potential collaborations with other research groups. Resource Allocation: We are assessing the resources required to prepare the data for sharing, including de-identification processes and creation of data dictionaries.
Study at a glance
From the registry record, last updated by the sponsor on 27 Nov 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Machine Learning-Based Decision Model for Optimal Adjuvant Therapy in Primary Gastric Neuroendocrine Carcinoma: a National Real-World Evidence Study
- ClinicalTrials.gov ID
- NCT06663852
- Acronym / sponsor ID
- G-NEC / 2024GNEC
- Conditions
- Gastric Neuroendocrine Carcinoma (G-NEC), Postoperative Adjuvant Therapy for G-NEC, Survival Outcomes, Machine Learning
- Keywords
- Gastric Neuroendocrine Carcinoma (G-NEC), Adjuvant Chemotherapy, Machine Learning, Decision Support Model, Random Survival Forest
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 1,505 participants (actual)
- Lead sponsor
- Chang-Ming Huang, Prof.University, hospital or other
- Study start
- 1 Jan 2024 (actual)
- Primary completion
- 1 Jun 2024 (actual)
- Study completion
- 30 Jun 2024 (actual)
- First posted
- 29 Oct 2024 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Gastric Neuroendocrine Carcinoma (G-NEC) Patients | – | –This study focuses on patients diagnosed with gastric neuroendocrine carcinoma (G-NEC) who have undergone radical surgery. The cohort includes adult patients (≥18 years) treated at 38 tertiary hospitals in China between January 2006 and December 2020. Patients are divided into three groups based on their postoperative adjuvant treatment: no adjuvant chemotherapy, etoposide and platinum derivatives-based chemotherapy, and fluorouracil-based chemotherapy. The study aims to develop and validate a machine learning-based decision support model to optimize individualized adjuvant therapy strategies for G-NEC patients, with the primary outcome being disease-free survival (DFS). |
Who may qualify
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
- Study population
- This study includes adult patients diagnosed with gastric neuroendocrine carcinoma (G-NEC) or mixed adenoneuroendocrine carcinoma (MANEC) who underwent radical surgery at 38 tertiary hospitals in China between January 2006 and December 2020. The study population consists of patients who received either no adjuvant chemotherapy, etoposide and platinum derivatives-based chemotherapy, or fluorouracil-based chemotherapy following surgery.
Key inclusion criteria (2 listed)
- (1) patients who underwent radical surgery without any neoadjuvant therapy;
- (2) pathology confirmed NEC or mixed adenoneuroendocrine carcinoma (MANEC).
Key exclusion criteria (5 listed)
- (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.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
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.
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 27 Nov 2024.
- Individual participant dataSharing planned: Undecided. Patient Privacy: As this study involves sensitive medical information, we must ensure that any data sharing plan complies with all relevant privacy laws and regulations. Ethical Considerations: We are consulting with our ethics committee to determine the most appropriate approach to data sharing that respects patient consent and maintains the integrity of the research. Data Standardization: Given the multi-center nature of this study, we are working on standardizing our data collection and storage processes across all 38 participating hospitals to ensure consistency and quality of any potentially shared data. Collaborative Potential: We recognize the value of data sharing in advancing gastric neuroendocrine carcinoma research and are exploring potential collaborations with other research groups. Resource Allocation: We are assessing the resources required to prepare the data for sharing, including de-identification processes and creation of data dictionaries.
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Gastric Neuroendocrine Carcinoma (G-NEC) and Postoperative Adjuvant Therapy for G-NEC, run by Chang-Ming Huang, Prof. at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 5 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 27 Nov 2024. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Disease-Free Survival (DFS) (time frame: From date of surgery up to 5 years). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 27 Nov 2024.