Gastric CancerNCT05617469
DLCS for Predicting Neoadjuvant Chemotherapy Response
An observational study of Gastric Cancer and CT Images, run by Zhejiang Cancer Hospital at 1 site in China.
Trial summary
The early noninvasive screening of patients suitable for neoadjuvant chemotherapy (NCT) is essential for personalized treatment in locally advanced gastric cancer (LAGC). The aim of this study was to develop and visualized a radio-clinical biomarker from pretreatment oversampled CT images to predict the response and… Read more about this study
- Who is it for?
- Ages 18 to 80 years
- Conditions the study is for
- Gastric Cancer, CT Images, Deep Learning
- What is being tested?
- develop and visualized a radio-clinical signatures from pretreatment oversampled CT images
- How many people
- 1,100 participants
- Where
- 1 siteChina
- Study dates
- 1 Jul 2022to 31 Jul 2023
- 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 18 to 80 years
- All sexes
- Adult, Older adult
Study population: patients with histologically confirmed GC/esophagogastric junction cancer (EGJC) who received NCT prior to surgical resection
Who may be able to join
- 1) patients with GC/EGJC confirmed by pathological examination; 2) patients who underwent D2 lymphadenectomy; 3) patients who received at least two cycles of preoperative chemotherapy; 4) patients with negative resection margins; and 5) patients with complete CT image data and clinical data.
Who cannot join
- 1) patients unable to undergo D2 radical gastrectomy after neoadjuvant therapy; and 2) patients with incomplete CT images and clinical data.
Trial locations and contacts
1 site in 1 country.
China1 site, 1 recruiting
- Recruiting
Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital)
Hangzhou, Zhejiang, 310022
Xiangdong Cheng, MD, +0086-0571-88128041, Chengxd516@126.com
About this study
Official title: Deep Learning Radio-clinical Signatures for Predicting Neoadjuvant Chemotherapy Response and Prognosis From Pretreatment CT Images of LAGC Patients
The early noninvasive screening of patients suitable for neoadjuvant chemotherapy (NCT) is essential for personalized treatment in locally advanced gastric cancer (LAGC). The aim of this study was to develop and visualized a radio-clinical biomarker from pretreatment oversampled CT images to predict the response and prognosis to NCT in LAGC patients.
- Conditions
- Gastric Cancer, CT Images, Deep Learning, Neoadjuvant Chemotherapy, Tumor Regression Grade
- Being tested
- develop and visualized a radio-clinical signatures from pretreatment oversampled CT images
- Medical subject headings
- Stomach Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
develop and visualized a radio-clinical signatures from pretreatment oversampled CT imagesOther
develop and visualized a radio-clinical signatures from pretreatment oversampled CT images to predict the neoadjuvant chemotherapy response and prognosis
What is being measured
The primary outcome is the main question the study is designed to answer.
Tumor regression grade
Tumor regression grade
Measured: 3 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted15 Nov 2022
- Study start1 Jul 2022
- Primary completion30 Jan 2023 (estimated)
- Study completion31 Jul 2023 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Gastric CancerStudies 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
- Other
- Time perspective
- Retrospective
- Enrolment
- 1,100 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Zhejiang Cancer Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Xiangdong Cheng, Zhejiang Cancer Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05617469
- Sponsor's protocol ID
- AICT-01
- Status last verified
- Nov 2022
- First submitted
- 8 Nov 2022
- Last updated
- 15 Nov 2022
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Due to the privacy of patients, the data related to patients cannot be available for public access but can be obtained from the corresponding author on reasonable request approved by the institutional review board of all enrolled centers.
Study at a glance
From the registry record, last updated by the sponsor on 15 Nov 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Deep Learning Radio-clinical Signatures for Predicting Neoadjuvant Chemotherapy Response and Prognosis From Pretreatment CT Images of LAGC Patients
- ClinicalTrials.gov ID
- NCT05617469
- Acronym / sponsor ID
- AICT-01
- Conditions
- Gastric Cancer, CT Images, Deep Learning, Neoadjuvant Chemotherapy, Tumor Regression Grade
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 1,100 participants (estimated)
- Lead sponsor
- Zhejiang Cancer HospitalUniversity, hospital or other
- Study start
- 1 Jul 2022 (actual)
- Primary completion
- 30 Jan 2023 (estimated)
- Study completion
- 31 Jul 2023 (estimated)
- First posted
- 15 Nov 2022 (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.
The early noninvasive screening of patients suitable for neoadjuvant chemotherapy (NCT) is essential for personalized treatment in locally advanced gastric cancer (LAGC). The aim of this study was to develop and visualized a radio-clinical biomarker from pretreatment oversampled CT images to predict the response and prognosis to NCT in LAGC patients.
Study design
- Observational model
- Other
- Time perspective
- Retrospective
Who may qualify
- Ages
- 18 to 80 years
- Sex
- All
- Age groups
- Adult, Older adult
- Study population
- patients with histologically confirmed GC/esophagogastric junction cancer (EGJC) who received NCT prior to surgical resection
Key inclusion criteria (1 listed)
- 1) patients with GC/EGJC confirmed by pathological examination; 2) patients who underwent D2 lymphadenectomy; 3) patients who received at least two cycles of preoperative chemotherapy; 4) patients with negative resection margins; and 5) patients with complete CT image data and clinical data.
Key exclusion criteria (1 listed)
- 1) patients unable to undergo D2 radical gastrectomy after neoadjuvant therapy; and 2) patients with incomplete CT images and clinical data.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| develop and visualized a radio-clinical signatures from pretreatment oversampled CT imagesdevelop and visualized a radio-clinical signatures from pretreatment oversampled CT images to predict the neoadjuvant chemotherapy response and prognosis | Other | – |
Primary outcome
Tumor regression grade
Time frame: 3 months
Tumor regression grade
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 15 Nov 2022.
- Individual participant dataSharing planned: No. Due to the privacy of patients, the data related to patients cannot be available for public access but can be obtained from the corresponding author on reasonable request approved by the institutional review board of all enrolled centers.
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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.
Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital)
Hangzhou, China
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 Cancer and CT Images, run by Zhejiang Cancer Hospital 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 1 inclusion and 1 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: status not confirmed, as of the sponsor's last update on 15 Nov 2022. 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?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Each site lists its own contact: choose the nearest one under Trial locations. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Tumor regression grade (time frame: 3 months). 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 15 Nov 2022.