Predictive Cancer ModelNCT04511481
Deep Learning Magnetic Resonance Imaging Radiomic Predict Platinum-sensitive in Patients With Epithelial Ovarian Cancer
An observational study of Predictive Cancer Model, run by Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University at 1 site in China.
Trial summary
Platinum-sensitive is an important basis for the treatment of recurrent epithelial ovarian cancer (EOC) without effective methods to predict.We aimed to develop and validate the EOC deep learning system to predict the platinum-sensitive of EOC patients through analysis of enhanced magnetic resonance imaging (MRI)… Read more about this study
- Who is it for?
- Ages 22 to 99 years, women only
- Conditions the study is for
- Predictive Cancer Model
- What is being tested?
- Radiomic Algorithm
- How many people
- 93 participants
- Where
- 1 siteChina
- Study dates
- 15 Apr 2020to 1 Jan 2021
- 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 22 to 99 years
- Women only
- No healthy volunteers
- Adult, Older adult
Study population: Patients received platinum-based chemotherapy (>= 4 cycles) and debulking surgery from Sun Yat-sen Memorial Hospital in China from January 2011 to January 2020
Who may be able to join
- (1)Patients with epithelial ovarian cancer (2 )Patients received platinum-based chemotherapy (>= 4 cycles) and debulking surgery
Who cannot join
- Patients with epithelial ovarian cancer received less than 4 cycles platinum-based chemotherapy or no debulking surgery
Trial locations and contacts
1 site in 1 country.
China1 site, 1 recruiting
- Recruiting
Sun Yat-Sen Memorial Hospital of Sun Yat-sen University
Guangzhou, Guangdong, 510120
Herui Yao, PhD, +8613500018020, yaoherui@mail.sysu.edu.cn
Yunfang Yu, MD, +8613660238987, yuyf9@mail.sysu.edu.cn
About this study
Platinum-sensitive is an important basis for the treatment of recurrent epithelial ovarian cancer (EOC) without effective methods to predict.We aimed to develop and validate the EOC deep learning system to predict the platinum-sensitive of EOC patients through analysis of enhanced magnetic resonance imaging (MRI) images before initial treatment.Ninety-three EOC patients received platinum-based chemotherapy (>= 4 cycles) and debulking surgery from Sun Yat-sen Memorial Hospitalin China from January 2011 to January 2020 were enrolled. This deep-learning EOC signature achieved a high predictive power for platinum-sensitive, and the signature based on MRI whole volume is better than that on primary tumor area only.
- Conditions
- Predictive Cancer Model
- Being tested
- Radiomic Algorithm
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Radiomic AlgorithmOther
Different radiomic and machine learning strategies for radiomic features extraction, sorting features and model constriction
| Study group | Role | What they receive |
|---|---|---|
| platinum-resistant group | Not described Receives: Other: Radiomic Algorithm | |
| platinum-sensitive group | Not described Receives: Other: Radiomic Algorithm |
What is being measured
The primary outcome is the main question the study is designed to answer.
Platinum sensitivity
Platinum sensitivity
Measured: 9 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted13 Aug 2020
- Study start15 Apr 2020
- Primary completion3 Aug 2020 (estimated)
- Study completion1 Jan 2021 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Predictive Cancer ModelStudies 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
- 93 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Herui Yao, Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04511481
- Sponsor's protocol ID
- SYSEC-KY-KS-2020-072
- Status last verified
- Aug 2020
- First submitted
- 11 Aug 2020
- Last updated
- 13 Aug 2020
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: The datasets used or analysed during the current study are available from the corresponding author on reasonable request.
Study at a glance
From the registry record, last updated by the sponsor on 13 Aug 2020. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Deep Learning Magnetic Resonance Imaging Radiomic Predict Platinum-sensitive in Patients With Epithelial Ovarian Cancer
- ClinicalTrials.gov ID
- NCT04511481
- Acronym / sponsor ID
- SYSEC-KY-KS-2020-072
- Conditions
- Predictive Cancer Model
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 93 participants (estimated)
- Lead sponsor
- Sun Yat-Sen Memorial Hospital of Sun Yat-Sen UniversityUniversity, hospital or other
- Study start
- 15 Apr 2020 (actual)
- Primary completion
- 3 Aug 2020 (estimated)
- Study completion
- 1 Jan 2021 (estimated)
- First posted
- 13 Aug 2020 (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.
Platinum-sensitive is an important basis for the treatment of recurrent epithelial ovarian cancer (EOC) without effective methods to predict.We aimed to develop and validate the EOC deep learning system to predict the platinum-sensitive of EOC patients through analysis of enhanced magnetic resonance imaging (MRI) images before initial treatment.Ninety-three EOC patients received platinum-based chemotherapy (>= 4 cycles) and debulking surgery from Sun Yat-sen Memorial Hospitalin China from January 2011 to January 2020 were enrolled. This deep-learning EOC signature achieved a high predictive power for platinum-sensitive, and the signature based on MRI whole volume is better than that on primary tumor area only.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| platinum-resistant group | – | Other: Radiomic Algorithm |
| platinum-sensitive group | – | Other: Radiomic Algorithm |
Who may qualify
- Ages
- 22 to 99 years
- Sex
- Female only
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Patients received platinum-based chemotherapy (>= 4 cycles) and debulking surgery from Sun Yat-sen Memorial Hospital in China from January 2011 to January 2020
Key inclusion criteria (1 listed)
- (1)Patients with epithelial ovarian cancer (2 )Patients received platinum-based chemotherapy (>= 4 cycles) and debulking surgery
Key exclusion criteria (1 listed)
- Patients with epithelial ovarian cancer received less than 4 cycles platinum-based chemotherapy or no debulking surgery
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 |
|---|---|---|
| Radiomic AlgorithmDifferent radiomic and machine learning strategies for radiomic features extraction, sorting features and model constriction | Other | platinum-resistant group, platinum-sensitive group |
Primary outcome
Platinum sensitivity
Time frame: 9 years
Platinum sensitivity
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 13 Aug 2020.
- Individual participant dataSharing planned: No. The datasets used or analysed during the current study are available from the corresponding author on reasonable request.
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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.
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 Predictive Cancer Model, run by Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University 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 13 Aug 2020. 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?
Contact Ruilin Lei, phD (+8618898325866, leiruilin1988@163.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Platinum sensitivity (time frame: 9 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 13 Aug 2020.