NeoplasmsPanCanBloodNCT07554157
Development of a Pan-Cancer Screening Model Based on Blood Biomarkers
An observational study of Neoplasms, run by Zhejiang Cancer Hospital at 1 site in China.
Trial summary
This study aims to develop a pan-cancer screening model using routine blood biomarkers (including complete blood count, biochemical tests, coagulation panel, and tumor markers). The study is retrospective, collecting data from approximately 10,000,000 cancer patients diagnosed at multiple centers in China between… Read more about this study
- Who is it for?
- Ages 18 to 80 yearsHealthy volunteers can take part
- Conditions the study is for
- Neoplasms
- How many people
- 10,000,000 participants
- Where
- 1 siteChina
- Study dates
- 22 Oct 2025to 31 Dec 2030
- 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 to 80 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: The study population consists of two groups: (1) patients with pathologically confirmed cancer (including gastric, colorectal, liver, lung, ovarian, and other solid tumors) and (2) non-cancer controls (individuals undergoing routine health checkups without cancer or other major organic diseases). All participants are aged 18-80 years. Data are retrospectively collected from medical records across multiple centers in China.
Who may be able to join
- Pathologically confirmed cancer patients (for case group) OR individuals without cancer (for control group)
- Age between 18 and 80 years
- Complete clinical data and blood test results (complete blood count, biochemistry, coagulation panel, tumor markers) available
- No history of other organic diseases (excluding cancer)
Who cannot join
- Presence of organic diseases other than cancer (e.g., severe heart, liver, kidney disease)
- Hematologic disorders or immunodeficiency diseases (e.g., AIDS)
- Incomplete data or missing timeline records
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Establishment of a Pan-Cancer Screening Model Based on Blood Biomarkers
This study aims to develop a pan-cancer screening model using routine blood biomarkers (including complete blood count, biochemical tests, coagulation panel, and tumor markers). The study is retrospective, collecting data from approximately 10,000,000 cancer patients diagnosed at multiple centers in China between January 2006 and September 2025. All patients have confirmed pathological diagnosis and complete blood test records. A Mixture of Experts (MoE) machine learning model will be built to predict the presence of various cancers (e.g., gastric, colorectal, liver, lung, ovarian cancer). The goal is to establish a low-cost, non-invasive screening tool suitable for large-scale population screening.
Read the detailed description
Background: Cancer is a leading cause of death worldwide. Early detection improves survival, but current screening methods (e.g., endoscopy, imaging) are invasive, costly, or not widely accessible. Blood-based biomarkers offer a non-invasive, repeatable, and cost-effective alternative.
Objective: Primary: To establish a pan-cancer screening model based on blood biomarkers. Secondary: To combine multiple blood markers for identifying high-risk populations. Exploratory: To develop a cost-effective, scalable screening technology.
Study Design: This is a multicenter, retrospective study. Data will be collected from 15 participating hospitals in China, including Zhejiang Cancer Hospital, Tongling People's Hospital, Pingyang People's Hospital, Fenghua People's Hospital, Shaoxing Central Hospital, Bingqi General Hospital, the Second Affiliated Hospital of Jiaxing University, Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Yunnan Cancer Hospital, Xianju People's Hospital, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, No.9 Hospital Ningbo, Norinco General Hospital, Quzhou Kecheng People's Hospital.
Participants: Approximately 10,000,000 patients aged 18-80 years with pathologically confirmed cancer (including respiratory, digestive, urogenital, nervous, endocrine, and soft tissue malignancies). Exclusion criteria: presence of non-cancer organic diseases, hematologic disorders, immunodeficiency (e.g., AIDS), or incomplete data.
Data collection: Blood biomarkers including complete blood count, biochemical tests (liver/kidney function, glucose, lipids), coagulation (PT, APTT, TT, fibrinogen), and tumor markers (e.g., CEA, CA19-9, AFP, CA125, etc.) along with clinical data (age, sex, height, weight, diagnosis) will be extracted from medical records.
Statistical analysis: A Mixture of Experts (MoE) architecture with deep residual networks, attention-based gating, and feature interaction (FM + deep neural networks) will be used. Multi-task learning, Focal Loss for class imbalance, and adaptive sample weighting will be applied. Model performance will be evaluated for sensitivity, specificity, and AUC.
Ethics: Approved by the Ethics Committee of Zhejiang Cancer Hospital (IRB-2025-1319[IIT]). Because this is a retrospective study using de-identified data, the committee approved a waiver of informed consent for patients without prior general consent, in accordance with Chinese regulations and the Declaration of Helsinki. Data will be encrypted and stored securely for 15 years after study completion.
Dissemination: Results will be published in peer-reviewed journals and presented at conferences.
- Conditions
- Neoplasms
- Being tested
- No intervention
- Keywords
- pan-cancer, blood biomarkers, machine learning, early detection
- Medical subject headings
- Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
No interventionOther
This is an observational, retrospective study with no assigned interventions. Data are collected from existing medical records, including routine blood biomarkers (complete blood count, biochemistry, coagulation panel, tumor markers). No experimental drugs, devices, or procedures are administered. Only de-identified historical data are used for model development.
| Study group | Role | What they receive |
|---|---|---|
| All Participants | All enrolled individuals (cancer patients and non-cancer controls) with retrospective blood biomarker data. Receives: Other: No intervention |
What is being measured
The primary outcome is the main question the study is designed to answer.
Area under the ROC curve (AUC)
AUC of the MoE model for discriminating cancer from non-cancer controls.
Measured: At study completion, approximately December 2030
Sensitivity of the model
True positive rate of the pan-cancer screening model.
Measured: At study completion, approximately December 2030
Specificity of the model
True negative rate of the pan-cancer screening model.
Measured: At study completion, approximately December 2030
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted28 Apr 2026
- Study start22 Oct 2025
- Primary completion31 Jul 2027 (estimated)
- Study completion31 Dec 2030 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for NeoplasmsStudies of the same condition, open and under way.
- More trials run by Zhejiang Cancer HospitalThe sponsor's other registered studies.
- 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
- Case-control
- Time perspective
- Retrospective
- Enrolment
- 10,000,000 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
- Investigators
- Xiangdong Cheng, MD, PhD, Principal investigator, Zhejiang Cancer Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07554157
- Sponsor's protocol ID
- IRB-2025-1319[IIT]
- Acronym
- PanCanBlood
- Status last verified
- Apr 2026
- First submitted
- 14 Apr 2026
- Last updated
- 28 Apr 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Data sharing is not permitted due to ethical and privacy restrictions.
Study at a glance
From the registry record, last updated by the sponsor on 28 Apr 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Establishment of a Pan-Cancer Screening Model Based on Blood Biomarkers
- ClinicalTrials.gov ID
- NCT07554157
- Acronym / sponsor ID
- PanCanBlood / IRB-2025-1319[IIT]
- Conditions
- Neoplasms
- Keywords
- pan-cancer, blood biomarkers, machine learning, early detection
- Study type
- Observational
- Recruitment status
- Active, not recruiting
- Enrolment
- 10,000,000 participants (estimated)
- Lead sponsor
- Zhejiang Cancer HospitalUniversity, hospital or other
- Study start
- 22 Oct 2025 (actual)
- Primary completion
- 31 Jul 2027 (estimated)
- Study completion
- 31 Dec 2030 (estimated)
- First posted
- 28 Apr 2026 (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 aims to develop a pan-cancer screening model using routine blood biomarkers (including complete blood count, biochemical tests, coagulation panel, and tumor markers). The study is retrospective, collecting data from approximately 10,000,000 cancer patients diagnosed at multiple centers in China between January 2006 and September 2025. All patients have confirmed pathological diagnosis and complete blood test records. A Mixture of Experts (MoE) machine learning model will be built to predict the presence of various cancers (e.g., gastric, colorectal, liver, lung, ovarian cancer). The goal is to establish a low-cost, non-invasive screening tool suitable for large-scale population screening.
Detailed description
Background: Cancer is a leading cause of death worldwide. Early detection improves survival, but current screening methods (e.g., endoscopy, imaging) are invasive, costly, or not widely accessible. Blood-based biomarkers offer a non-invasive, repeatable, and cost-effective alternative.
Objective: Primary: To establish a pan-cancer screening model based on blood biomarkers. Secondary: To combine multiple blood markers for identifying high-risk populations. Exploratory: To develop a cost-effective, scalable screening technology.
Study Design: This is a multicenter, retrospective study. Data will be collected from 15 participating hospitals in China, including Zhejiang Cancer Hospital, Tongling People's Hospital, Pingyang People's Hospital, Fenghua People's Hospital, Shaoxing Central Hospital, Bingqi General Hospital, the Second Affiliated Hospital of Jiaxing University, Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Yunnan Cancer Hospital, Xianju People's Hospital, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, No.9 Hospital Ningbo, Norinco General Hospital, Quzhou Kecheng People's Hospital.
Participants: Approximately 10,000,000 patients aged 18-80 years with pathologically confirmed cancer (including respiratory, digestive, urogenital, nervous, endocrine, and soft tissue malignancies). Exclusion criteria: presence of non-cancer organic diseases, hematologic disorders, immunodeficiency (e.g., AIDS), or incomplete data.
Data collection: Blood biomarkers including complete blood count, biochemical tests (liver/kidney function, glucose, lipids), coagulation (PT, APTT, TT, fibrinogen), and tumor markers (e.g., CEA, CA19-9, AFP, CA125, etc.) along with clinical data (age, sex, height, weight, diagnosis) will be extracted from medical records.
Statistical analysis: A Mixture of Experts (MoE) architecture with deep residual networks, attention-based gating, and feature interaction (FM + deep neural networks) will be used. Multi-task learning, Focal Loss for class imbalance, and adaptive sample weighting will be applied. Model performance will be evaluated for sensitivity, specificity, and AUC.
Ethics: Approved by the Ethics Committee of Zhejiang Cancer Hospital (IRB-2025-1319[IIT]). Because this is a retrospective study using de-identified data, the committee approved a waiver of informed consent for patients without prior general consent, in accordance with Chinese regulations and the Declaration of Helsinki. Data will be encrypted and stored securely for 15 years after study completion.
Dissemination: Results will be published in peer-reviewed journals and presented at conferences.
Study design
- Observational model
- Case-control
- Time perspective
- Retrospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| All Participants | – | Other: No interventionAll enrolled individuals (cancer patients and non-cancer controls) with retrospective blood biomarker data. |
Who may qualify
- Ages
- 18 to 80 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- The study population consists of two groups: (1) patients with pathologically confirmed cancer (including gastric, colorectal, liver, lung, ovarian, and other solid tumors) and (2) non-cancer controls (individuals undergoing routine health checkups without cancer or other major organic diseases). All participants are aged 18-80 years. Data are retrospectively collected from medical records across multiple centers in China.
Key inclusion criteria (4 listed)
- Pathologically confirmed cancer patients (for case group) OR individuals without cancer (for control group)
- Age between 18 and 80 years
- Complete clinical data and blood test results (complete blood count, biochemistry, coagulation panel, tumor markers) available
- No history of other organic diseases (excluding cancer)
Key exclusion criteria (3 listed)
- Presence of organic diseases other than cancer (e.g., severe heart, liver, kidney disease)
- Hematologic disorders or immunodeficiency diseases (e.g., AIDS)
- Incomplete data or missing timeline records
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 |
|---|---|---|
| No interventionThis is an observational, retrospective study with no assigned interventions. Data are collected from existing medical records, including routine blood biomarkers (complete blood count, biochemistry, coagulation panel, tumor markers). No experimental drugs, devices, or procedures are administered. Only de-identified historical data are used for model development. | Other | All Participants |
Primary outcome
Area under the ROC curve (AUC)
Time frame: At study completion, approximately December 2030
AUC of the MoE model for discriminating cancer from non-cancer controls.
Sensitivity of the model
Time frame: At study completion, approximately December 2030
True positive rate of the pan-cancer screening model.
Specificity of the model
Time frame: At study completion, approximately December 2030
True negative rate of the pan-cancer screening model.
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 28 Apr 2026.
- Individual participant dataSharing planned: No. Data sharing is not permitted due to ethical and privacy restrictions.
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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.
Xiangdong Cheng, MD, PhD principal investigator
Zhejiang Cancer Hospital
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 Neoplasms, 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 4 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: under way, not looking for participants, as of the sponsor's last update on 28 Apr 2026. 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?
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?
Area under the ROC curve (AUC) (time frame: At study completion, approximately December 2030). The study lists 3 primary outcomes in all. 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 28 Apr 2026.