Colorectal Liver Metastasis (CRLM)NCT07027605
Multi-Reader Multi-Case Trial Evaluating Computer-Aided Tool for Prognostic Prediction of Colorectal Liver Metastases
An observational study of Colorectal Liver Metastasis (CRLM), run by Cancer Institute and Hospital, Chinese Academy of Medical Sciences at 1 site in China.
Trial summary
This study evaluates the impact of a novel computer-aided prognostic prediction tool for colorectal liver metastases (CRLM) on clinician performance. Colorectal cancer is a leading cause of cancer-related mortality worldwide, with 20-30% of patients presenting synchronous liver metastases, which are associated with… Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Colorectal Liver Metastasis (CRLM)
- How many people
- 166 participants
- Where
- 1 siteChina
- Study dates
- 1 Jan 2025to 25 Sep 2025
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
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 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: This reader study involves 12 physicians (4 junior, 4 mid-level, 4 senior) from the Surgical Oncology Department of the Digestive Tract. All readers will receive standardized training on accessing patient data through the medical record system and completing the questionnaire. The study includes 166 colorectal liver metastases (CRLM) patients who underwent simultaneous colorectal and liver resection. Inclusion criteria: age ≥18 years, histologically confirmed colorectal adenocarcinoma liver metastases, and simultaneous resection. Exclusion criteria: presence of other malignancies, lack of follow-up data, or postoperative follow-up less than 5 years without death occurrence.
Who may be able to join
- ≥ 18 years old
- confirmation of histologically diagnosed liver metastases of colorectal adenocarcinoma
- receiving colorectal resection with simultaneous liver resection.
Who cannot join
- presence of other malignancies
- absence of follow-up data
- patients who were followed up postoperatively for less than 5 years and had no occurrences of death.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
China1 site, 1 recruiting
- Recruiting
No. 17, South Panjiayuan, Chaoyang District, Beijing, Cancer Hospital, Chinese Academy of Medical Sciences, China
Beijing, Beijing Municipality, 100021
HONG ZHAO, MD, 01087788224, zhaohong@cicams.ac.cn
About this study
Official title: A Multi-Reader Multi-Case Controlled Clinical Trial to Evaluate the Performance Improvement From Computer-aided Tool for the Prognostic Prediction of Colorectal Liver Metastases
This study evaluates the impact of a novel computer-aided prognostic prediction tool for colorectal liver metastases (CRLM) on clinician performance. Colorectal cancer is a leading cause of cancer-related mortality worldwide, with 20-30% of patients presenting synchronous liver metastases, which are associated with poor prognosis and high postoperative recurrence rates. Simultaneous resection of primary tumor and liver metastases is a preferred treatment for selected patients but outcomes vary significantly. The latest web-based tool uses Random Forest models integrating demographic, clinical, laboratory, and genetic data to predict postoperative recurrence and mortality specifically for CRLM patients undergoing simultaneous resection. This multiple-reader, multiple-case (MRMC) study will assess 12 physicians who will predict 1-, 3-, and 5-year recurrence and mortality risks in 166 retrospective cases, with and without the tool's aid, separated by a washout period. The primary focus is to determine whether the tool improves prediction accuracy for 3-year postoperative mortality, measured by AUC-ROC. Secondary and exploratory endpoints include other time points, sensitivity, specificity, inter-rater reliability, decision-making confidence, and evaluation time. By enabling individualized risk assessment, this tool aims to support optimized clinical decision-making and tailored treatment strategies for CRLM patients undergoing simultaneous resection.
Read the detailed description
This study aims to evaluate the impact of a novel computer-aided prognostic prediction tool on clinician performance in managing patients with colorectal liver metastases (CRLM). Colorectal cancer remains one of the leading causes of cancer-related mortality worldwide, with approximately 20-30% of patients presenting synchronous liver metastases at diagnosis. These metastases are associated with poor prognosis and a high rate of postoperative recurrence.
For selected patients, simultaneous resection of the primary colorectal tumor and liver metastases is the preferred treatment approach, though clinical outcomes vary widely. To address this variability, the latest web-based prediction tool employs Random Forest machine learning models that integrate comprehensive demographic, clinical, laboratory, and genetic data. This tool is specifically designed to predict postoperative recurrence and mortality for CRLM patients undergoing simultaneous resection, enabling individualized risk assessment.
In this multiple-reader, multiple-case (MRMC) study, 12 physicians will independently evaluate 166 retrospective patient cases. Each physician will estimate the risk of disease recurrence and mortality at 1-, 3-, and 5-year time points, both with and without access to the prediction tool. These two assessment phases will be separated by a washout period to minimize bias.
The primary objective is to determine whether use of the tool improves the accuracy of predicting 3-year postoperative mortality, quantified by the area under the receiver operating characteristic curve (AUC-ROC). Secondary and exploratory endpoints include prediction accuracy at other time points, sensitivity, specificity, inter-rater reliability, clinician confidence in decision-making, and time required for evaluation.
By providing specific, data-driven risk estimates, this computer-aided prognostic tool aims to enhance clinical decision-making and support personalized treatment planning for CRLM patients undergoing simultaneous resection, ultimately striving to improve patient outcomes.
- Conditions
- Colorectal Liver Metastasis (CRLM)
- Keywords
- Multi-Reader Multi-Case Controlled Clinical Trial, Prognostic Prediction, Colorectal Liver Metastases
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 |
|---|---|---|
| Reader Group A: Interprets Dataset A in unaided scenario and Dataset B in aided scenario | A reader study with 12 readers (4 Junior Physician, 4 mid-level Physician and 4 Senior Physician) from the Department of Surgical Oncology of the Digestive Tract will be conducted. The readers are equally and randomly split between Group A and Group B. The study will target 166 CRLM patient cases receiving simultaneous resection.Patient cases will be equally and randomly split between Dataset A and Dataset B. | |
| Reader Group B: Interprets Dataset A in aided scenario and Dataset B in unaided scenario | A reader study with 12 readers (4 Junior Physician, 4 mid-level Physician and 4 Senior Physician) from the Department of Surgical Oncology of the Digestive Tract will be conducted. The readers are equally and randomly split between Group A and Group B. The study will target 166 CRLM patient cases receiving simultaneous resection.Patient cases will be equally and randomly split between Dataset A and Dataset B. |
What is being measured
The primary outcome is the main question the study is designed to answer.
AUCs: Area Under the Receiver Operating Characteristic Curve (AUC-ROC)
The comparative accuracy of model aided versus unaided risk prediction of post-operative 3-year mortality assessed by readers. Under model aided condition, prediction model will estimate the overall survival (OS) rate at Year 3 for each individual patient. OS was defined as the time from the date of simultaneous resection to death due to any cause. Patients without death were censored at their last known alive date. The mortality data were retrospectively collected and the event status were known. Patients were followed up to approximately 120 months after simultaneous resection.
Measured: Up to approximately 120 months
Secondary outcomes (4)
AUCs: Area Under the Receiver Operating Characteristic Curve (AUC-ROC)
The comparative accuracy of model aided versus unaided risk prediction of post-operative 1-year recurrence, 3-year recurrence, 5-year recurrence, 1-year mortality, and 5-year mortality made by readers.
PFS was defined as the time from the date of simultaneous colorectal and liver resection to first documented disease progression or death due to any cause, whichever occurs first. Patients without PFS event were censored at their last assessment follow-up.
OS was defined as the time from the date of simultaneous resection to death due to any cause. Patients without death were censored at their last known alive date.
Patients were followed up to approximately 120 months after simultaneous resection.
Measured: Up to approximately 120 months
Sensitivity: the ratio of true positives to total (actual) positives.
To evaluate aided versus unaided with respect to (improved) sensitivity for prediction of post-operative 1-year, 3-year, and 5-year recurrence and mortality made by readers.
Measured: Up to approximately 120 months
Specificity: the ratio of true negatives to total (actual) negatives.
To evaluate aided versus unaided with respect to (improved) specificity for prediction of post-operative 1-year, 3-year, and 5-year recurrence and mortality made by readers.
Measured: Up to approximately 120 months
Inter-rater reliability: the consistency of ratings made by readers on the cases
To evaluate aided versus unaided with respect to (improved) inter-rater reliability for rating on the likelihood of post-operative 1-year, 3-year, and 5-year recurrence and mortality made by readers.
Measured: Up to approximately 120 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted18 Jun 2025
- Study start1 Jan 2025
- Primary completion20 Sep 2025 (estimated)
- Study completion25 Sep 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (7)Papers the sponsor has linked to this study.
- Other trials for Colorectal Liver Metastasis (CRLM)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
- Prospective
- Enrolment
- 166 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Cancer Institute and Hospital, Chinese Academy of Medical Sciences
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Hong Zhao, MD, Principal investigator, Cancer Hospital Chinese Academy of Medical Science
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07027605
- Sponsor's protocol ID
- NCC-017834
- Status last verified
- Jan 2025
- First submitted
- 11 Jun 2025
- Last updated
- 19 Aug 2025
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Imai K, Allard MA, Castro Benitez C, Vibert E, Sa Cunha A, Cherqui D, Castaing D, Bismuth H, Baba H, Adam R. Nomogram for prediction of prognosis in patients with initially unresectable colorectal liver metastases. Br J Surg. 2016 Apr;103(5):590-9. doi: 10.1002/bjs.10073. Epub 2016 Jan 18.
PubMed 26780341Chen Q, Deng Y, Li Y, Chen J, Zhang R, Yang L, Guo R, Xing B, Ding P, Cai J, Zhao H. Association of preoperative aspartate aminotransferase to platelet ratio index with outcomes and tumour microenvironment among colorectal cancer with liver metastases. Cancer Lett. 2024 Apr 28;588:216778. doi: 10.1016/j.canlet.2024.216778. Epub 2024 Mar 6.
PubMed 38458593Wu Y, Mao A, Wang H, Fang G, Zhou J, He X, Cai S, Wang L. Association of Simultaneous vs Delayed Resection of Liver Metastasis With Complications and Survival Among Adults With Colorectal Cancer. JAMA Netw Open. 2022 Sep 1;5(9):e2231956. doi: 10.1001/jamanetworkopen.2022.31956.
PubMed 36121654Kataoka K, Takahashi K, Takeuchi J, Ito K, Beppu N, Ceelen W, Kanemitsu Y, Ajioka Y, Endo I, Hasegawa K, Takahashi K, Ikeda M. Correlation between recurrence-free survival and overall survival after upfront surgery for resected colorectal liver metastases. Br J Surg. 2023 Jun 12;110(7):864-869. doi: 10.1093/bjs/znad127.
PubMed 37196147Machairas N, Di Martino M, Primavesi F, Underwood P, de Santibanes M, Ntanasis-Stathopoulos I, Urban I, Tsilimigras DI, Siriwardena AK, Frampton AE, Pawlik TM. Simultaneous resection for colorectal cancer with synchronous liver metastases: current state-of-the-art. J Gastrointest Surg. 2024 Apr;28(4):577-586. doi: 10.1016/j.gassur.2024.01.034. Epub 2024 Feb 9.
PubMed 38583912Bray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, Jemal A. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2024 May-Jun;74(3):229-263. doi: 10.3322/caac.21834. Epub 2024 Apr 4.
PubMed 38572751Chen Q, Chen J, Deng Y, Bi X, Zhao J, Zhou J, Huang Z, Cai J, Xing B, Li Y, Li K, Zhao H. Personalized prediction of postoperative complication and survival among Colorectal Liver Metastases Patients Receiving Simultaneous Resection using machine learning approaches: A multi-center study. Cancer Lett. 2024 Jul 1;593:216967. doi: 10.1016/j.canlet.2024.216967. Epub 2024 May 18.
PubMed 38768679
Study at a glance
From the registry record, last updated by the sponsor on 19 Aug 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Multi-Reader Multi-Case Controlled Clinical Trial to Evaluate the Performance Improvement From Computer-aided Tool for the Prognostic Prediction of Colorectal Liver Metastases
- ClinicalTrials.gov ID
- NCT07027605
- Acronym / sponsor ID
- NCC-017834
- Conditions
- Colorectal Liver Metastasis (CRLM)
- Keywords
- Multi-Reader Multi-Case Controlled Clinical Trial, Prognostic Prediction, Colorectal Liver Metastases
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 166 participants (estimated)
- Lead sponsor
- Cancer Institute and Hospital, Chinese Academy of Medical SciencesUniversity, hospital or other
- Study start
- 1 Jan 2025 (actual)
- Primary completion
- 20 Sep 2025 (estimated)
- Study completion
- 25 Sep 2025 (estimated)
- First posted
- 18 Jun 2025 (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.
This study evaluates the impact of a novel computer-aided prognostic prediction tool for colorectal liver metastases (CRLM) on clinician performance. Colorectal cancer is a leading cause of cancer-related mortality worldwide, with 20-30% of patients presenting synchronous liver metastases, which are associated with poor prognosis and high postoperative recurrence rates. Simultaneous resection of primary tumor and liver metastases is a preferred treatment for selected patients but outcomes vary significantly. The latest web-based tool uses Random Forest models integrating demographic, clinical, laboratory, and genetic data to predict postoperative recurrence and mortality specifically for CRLM patients undergoing simultaneous resection. This multiple-reader, multiple-case (MRMC) study will assess 12 physicians who will predict 1-, 3-, and 5-year recurrence and mortality risks in 166 retrospective cases, with and without the tool's aid, separated by a washout period. The primary focus is to determine whether the tool improves prediction accuracy for 3-year postoperative mortality, measured by AUC-ROC. Secondary and exploratory endpoints include other time points, sensitivity, specificity, inter-rater reliability, decision-making confidence, and evaluation time. By enabling individualized risk assessment, this tool aims to support optimized clinical decision-making and tailored treatment strategies for CRLM patients undergoing simultaneous resection.
Detailed description
This study aims to evaluate the impact of a novel computer-aided prognostic prediction tool on clinician performance in managing patients with colorectal liver metastases (CRLM). Colorectal cancer remains one of the leading causes of cancer-related mortality worldwide, with approximately 20-30% of patients presenting synchronous liver metastases at diagnosis. These metastases are associated with poor prognosis and a high rate of postoperative recurrence.
For selected patients, simultaneous resection of the primary colorectal tumor and liver metastases is the preferred treatment approach, though clinical outcomes vary widely. To address this variability, the latest web-based prediction tool employs Random Forest machine learning models that integrate comprehensive demographic, clinical, laboratory, and genetic data. This tool is specifically designed to predict postoperative recurrence and mortality for CRLM patients undergoing simultaneous resection, enabling individualized risk assessment.
In this multiple-reader, multiple-case (MRMC) study, 12 physicians will independently evaluate 166 retrospective patient cases. Each physician will estimate the risk of disease recurrence and mortality at 1-, 3-, and 5-year time points, both with and without access to the prediction tool. These two assessment phases will be separated by a washout period to minimize bias.
The primary objective is to determine whether use of the tool improves the accuracy of predicting 3-year postoperative mortality, quantified by the area under the receiver operating characteristic curve (AUC-ROC). Secondary and exploratory endpoints include prediction accuracy at other time points, sensitivity, specificity, inter-rater reliability, clinician confidence in decision-making, and time required for evaluation.
By providing specific, data-driven risk estimates, this computer-aided prognostic tool aims to enhance clinical decision-making and support personalized treatment planning for CRLM patients undergoing simultaneous resection, ultimately striving to improve patient outcomes.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Reader Group A: Interprets Dataset A in unaided scenario and Dataset B in aided scenario | – | –A reader study with 12 readers (4 Junior Physician, 4 mid-level Physician and 4 Senior Physician) from the Department of Surgical Oncology of the Digestive Tract will be conducted. The readers are equally and randomly split between Group A and Group B. The study will target 166 CRLM patient cases receiving simultaneous resection.Patient cases will be equally and randomly split between Dataset A and Dataset B. |
| Reader Group B: Interprets Dataset A in aided scenario and Dataset B in unaided scenario | – | –A reader study with 12 readers (4 Junior Physician, 4 mid-level Physician and 4 Senior Physician) from the Department of Surgical Oncology of the Digestive Tract will be conducted. The readers are equally and randomly split between Group A and Group B. The study will target 166 CRLM patient cases receiving simultaneous resection.Patient cases will be equally and randomly split between Dataset A and Dataset B. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- This reader study involves 12 physicians (4 junior, 4 mid-level, 4 senior) from the Surgical Oncology Department of the Digestive Tract. All readers will receive standardized training on accessing patient data through the medical record system and completing the questionnaire. The study includes 166 colorectal liver metastases (CRLM) patients who underwent simultaneous colorectal and liver resection. Inclusion criteria: age ≥18 years, histologically confirmed colorectal adenocarcinoma liver metastases, and simultaneous resection. Exclusion criteria: presence of other malignancies, lack of follow-up data, or postoperative follow-up less than 5 years without death occurrence.
Key inclusion criteria (3 listed)
- ≥ 18 years old
- confirmation of histologically diagnosed liver metastases of colorectal adenocarcinoma
- receiving colorectal resection with simultaneous liver resection.
Key exclusion criteria (3 listed)
- presence of other malignancies
- absence of follow-up data
- patients who were followed up postoperatively for less than 5 years and had no occurrences of death.
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
AUCs: Area Under the Receiver Operating Characteristic Curve (AUC-ROC)
Time frame: Up to approximately 120 months
The comparative accuracy of model aided versus unaided risk prediction of post-operative 3-year mortality assessed by readers. Under model aided condition, prediction model will estimate the overall survival (OS) rate at Year 3 for each individual patient. OS was defined as the time from the date of simultaneous resection to death due to any cause. Patients without death were censored at their last known alive date. The mortality data were retrospectively collected and the event status were known. Patients were followed up to approximately 120 months after simultaneous resection.
4 secondary outcomes
AUCs: Area Under the Receiver Operating Characteristic Curve (AUC-ROC)
Time frame: Up to approximately 120 months
Sensitivity: the ratio of true positives to total (actual) positives.
Time frame: Up to approximately 120 months
Specificity: the ratio of true negatives to total (actual) negatives.
Time frame: Up to approximately 120 months
Inter-rater reliability: the consistency of ratings made by readers on the cases
Time frame: Up to approximately 120 months
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 19 Aug 2025.
- Results publication: PubMed 26780341Imai K, Allard MA, Castro Benitez C, Vibert E, Sa Cunha A, Cherqui D, Castaing D, Bismuth H, Baba H, Adam R. Nomogram for prediction of prognosis in patients with initially unresectable colorectal liver metastases. Br J Surg. 2016 Apr;103(5):590-9. doi: 10.1002/bjs.10073. Epub 2016 Jan 18.
- Results publication: PubMed 38458593Chen Q, Deng Y, Li Y, Chen J, Zhang R, Yang L, Guo R, Xing B, Ding P, Cai J, Zhao H. Association of preoperative aspartate aminotransferase to platelet ratio index with outcomes and tumour microenvironment among colorectal cancer with liver metastases. Cancer Lett. 2024 Apr 28;588:216778. doi: 10.1016/j.canlet.2024.216778. Epub 2024 Mar 6.
- Results publication: PubMed 36121654Wu Y, Mao A, Wang H, Fang G, Zhou J, He X, Cai S, Wang L. Association of Simultaneous vs Delayed Resection of Liver Metastasis With Complications and Survival Among Adults With Colorectal Cancer. JAMA Netw Open. 2022 Sep 1;5(9):e2231956. doi: 10.1001/jamanetworkopen.2022.31956.
- Results publication: PubMed 37196147Kataoka K, Takahashi K, Takeuchi J, Ito K, Beppu N, Ceelen W, Kanemitsu Y, Ajioka Y, Endo I, Hasegawa K, Takahashi K, Ikeda M. Correlation between recurrence-free survival and overall survival after upfront surgery for resected colorectal liver metastases. Br J Surg. 2023 Jun 12;110(7):864-869. doi: 10.1093/bjs/znad127.
- Results publication: PubMed 38583912Machairas N, Di Martino M, Primavesi F, Underwood P, de Santibanes M, Ntanasis-Stathopoulos I, Urban I, Tsilimigras DI, Siriwardena AK, Frampton AE, Pawlik TM. Simultaneous resection for colorectal cancer with synchronous liver metastases: current state-of-the-art. J Gastrointest Surg. 2024 Apr;28(4):577-586. doi: 10.1016/j.gassur.2024.01.034. Epub 2024 Feb 9.
- Results publication: PubMed 38572751Bray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, Jemal A. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2024 May-Jun;74(3):229-263. doi: 10.3322/caac.21834. Epub 2024 Apr 4.
- Results publication: PubMed 38768679Chen Q, Chen J, Deng Y, Bi X, Zhao J, Zhou J, Huang Z, Cai J, Xing B, Li Y, Li K, Zhao H. Personalized prediction of postoperative complication and survival among Colorectal Liver Metastases Patients Receiving Simultaneous Resection using machine learning approaches: A multi-center study. Cancer Lett. 2024 Jul 1;593:216967. doi: 10.1016/j.canlet.2024.216967. Epub 2024 May 18.
- Individual participant dataSharing planned: No
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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.
Hong Zhao, MD principal investigator
Cancer Hospital Chinese Academy of Medical Science
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 Colorectal Liver Metastasis (CRLM), run by Cancer Institute and Hospital, Chinese Academy of Medical Sciences 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 3 inclusion and 3 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: looking for participants now, as of the sponsor's last update on 19 Aug 2025. 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?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact HONG ZHAO, MD (+8613381106850, zhaohong@cicams.ac.cn), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
AUCs: Area Under the Receiver Operating Characteristic Curve (AUC-ROC) (time frame: Up to approximately 120 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT07027605, which also lists 7 linked publications.
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 19 Aug 2025.