Small Cell Lung CancerNCT07026669
A Multi-omics Sequencing-based Model for Predicting Efficacy and Dynamic Monitoring of Treatment in Small Cell Lung Cancer
An observational study of Small Cell Lung Cancer, run by Cancer Institute and Hospital, Chinese Academy of Medical Sciences at 1 site in China.
Trial summary
Lung cancer is one of the malignant tumors with the highest incidence and mortality rates globally, with small cell lung cancer (SCLC) accounting for approximately 15%. SCLC is characterized by high malignancy, propensity for metastasis and drug resistance, and a 5-year survival rate below 7%. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Small Cell Lung Cancer
- How many people
- 40 participants
- Where
- 1 siteChina
- Study dates
- 1 Jan 2025to 1 Dec 2027
- How long will I take part?
- 3 Years
- 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: SCLC patients From Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College
Who may be able to join
- Patients meeting the following criteria may have samples collected:
- Voluntary signing of informed consent;
- Age ≥18 years;
- Expected survival time ≥3 months;
- Eastern Cooperative Oncology Group (ECOG) performance status score of 0 or 1;
- Treatment-naïve limited-stage or extensive-stage SCLC confirmed by histology or cytology;
- Agreement to provide blood samples and paraffin-embedded samples;
- Measurable target lesions for efficacy evaluation.
Who cannot join
- Patients with any of the following conditions will be excluded from sample collection:
- Archived tumor tissue or pre-treatment tumor biopsy or histological examination showing previous histological or cytological evidence of non-small cell or small cell/non-small cell mixed components;
- Investigator-determined unsuitability for peripheral blood collection due to complications or other conditions;
- Active, known, or suspected autoimmune disease (excluding vitiligo, type I diabetes, residual hypothyroidism caused by autoimmune thyroiditis requiring only hormone replacement therapy, or conditions not expected to recur without external stimulation);
- Active tuberculosis (TB) infection based on chest X-ray, sputum examination, and clinical examination. Patients with active pulmonary TB infection history within the previous year should be excluded even if treated. Patients with active pulmonary TB infection history more than one year ago should also be excluded unless previous anti-TB treatment can be proven adequately effective;
- Comorbidities requiring immunosuppressive drug treatment, or requiring systemic or local corticosteroid use at immunosuppressive doses;
Show all 12Show fewer
- Pregnancy or lactation;
- Positive human immunodeficiency virus antibody (HIVAb), active hepatitis B virus infection (HBsAg positive and HBV-DNA >10³ copies/ml), or hepatitis C virus infection (HCV antibody positive and HCV-RNA > lower limit of detection at study center);
- History of severe neurological or psychiatric disorders, including but not limited to: dementia, depression, seizures, bipolar disorder, etc.;
- Use of any anti-tumor drugs before blood sample collection;
- Previous history of other malignant tumors (excluding non-melanoma skin cancer and the following carcinoma in situ: bladder, gastric, colon, endometrial, cervical/dysplasia, melanoma, or breast cancer);
- Patients receiving live vaccines within 28 days before blood sample collection.
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
National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College
Beijing, Beijing Municipality, 100021
Zhijie Wang, MD, +8613466323860, jie_969@163.com
About this study
Official title: A Multi-omics Sequencing-based Model for Predicting Efficacy and Dynamic Monitoring of Treatment in Small Cell Lung Cancer: A Prospective, Non-interventional Study
Lung cancer is one of the malignant tumors with the highest incidence and mortality rates globally, with small cell lung cancer (SCLC) accounting for approximately 15%. SCLC is characterized by high malignancy, propensity for metastasis and drug resistance, and a 5-year survival rate below 7%. Despite partial progress in chemotherapy and immunotherapy, SCLC patients generally have extremely poor prognosis, and there is a lack of precise therapeutic efficacy prediction and dynamic monitoring approaches. Existing biomarkers (such as TP53/RB1 mutations) are inadequate for clinical needs due to high heterogeneity and insufficient dynamic characteristics. The rapid development of multi-omics technologies provides new opportunities for analyzing SCLC molecular features; however, previous studies have predominantly focused on single omics approaches with insufficient systematic integration, limiting clinical translation. This study aims to systematically integrate multiple omics technologies to construct predictive and dynamic monitoring models for SCLC therapeutic efficacy, providing new methods and evidence for SCLC clinical treatment and dynamic monitoring.
Read the detailed description
Study Objectives To comprehensively analyze the molecular characteristics of small cell lung cancer (SCLC) through multi-omics technologies based on peripheral blood and paraffin-embedded samples, and establish and validate multi-omics data-based models for therapeutic efficacy prediction and dynamic monitoring.
Primary Objectives
- To collect blood and paraffin-embedded samples from SCLC patients before treatment and analyze multi-omics sequencing characteristics of these patients.
- To establish and validate SCLC therapeutic efficacy prediction and dynamic monitoring models based on multi-omics detection, constructing SCLC scoring models and molecular subtypes.
Secondary Objectives To investigate the sensitivity and specificity of SCLC therapeutic efficacy prediction and dynamic monitoring models in patients with different stages of SCLC.
Exploratory Objectives To analyze potential biomarkers and therapeutic targets in SCLC based on multi-omics data, and conduct in-depth analysis of dynamic changes in peripheral blood multi-omics data during SCLC treatment efficacy processes.
Study Design This is a prospective, single-center study aimed at establishing SCLC therapeutic efficacy prediction and dynamic monitoring models based on multi-omics detection of peripheral blood and paraffin-embedded samples.
Sample Collection Time Points
- Collection of 20ml peripheral blood (EDTA tubes×2) and 20 unstained paraffin tissue sections before first-line first cycle treatment;
- Collection of 20ml peripheral blood (EDTA tubes×2) before third cycle treatment;
- Collection of 20ml peripheral blood (EDTA tubes×2) at disease progression. Sample Size and Omics Detection This study plans to enroll 40 SCLC patients, collecting unstained paraffin tissue sections before treatment and dynamically collecting peripheral blood specimens.
Patient Information Collection
The study requires collection of patients' demographic information before blood collection, imaging data related to disease diagnosis, hospital laboratory biochemical test results, tumor marker test results, pathological diagnosis results or other information providing diagnostic evidence, and underlying disease information. Specific information collected includes:
Information to be collected for all patients includes but is not limited to:
General demographic data: age, gender, race, etc.; Vital signs: blood pressure, pulse, heart rate, etc.; Previous major disease history and corresponding medication history; Tumor history and corresponding treatment history; Family genetic history; Smoking and drinking history; Multi-omics detection results.
- Conditions
- Small Cell Lung Cancer
- Medical subject headings
- Small Cell Lung Carcinoma
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 |
|---|---|---|
| Limited-stage/Extensive-stage small cell lung cancer | Small cell lung cancer with lymph node metastasis/distant metastasis |
What is being measured
The primary outcome is the main question the study is designed to answer.
SCLC scoring models and molecular subtypes
To establish and validate SCLC therapeutic efficacy prediction and dynamic monitoring models based on multi-omics detection, and construct SCLC scoring models and molecular subtypes.
Measured: From enrollment to the end of monitoring at 3 years or the occurrence of disease progression.
Secondary outcomes (2)
Sensitivity and specificity of SCLC therapeutic efficacy prediction and dynamic monitoring models
To investigate the sensitivity and specificity of SCLC therapeutic efficacy prediction and dynamic monitoring models in patients with different stages of SCLC.
Measured: From enrollment to the end of monitoring at 3 years or the occurrence of disease progression.
Dynamic changes in peripheral blood multi-omics data during SCLC treatment efficacy processes
To analyze potential biomarkers and therapeutic targets in SCLC based on multi-omics data, and conduct an in-depth analysis of dynamic changes in peripheral blood multi-omics data during SCLC treatment efficacy processes.
Measured: From enrollment to the end of monitoring at 3 years or the occurrence of disease progression.
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 completion1 Dec 2027 (estimated)
- Study completion1 Dec 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (12)Papers the sponsor has linked to this study.
- Other trials for Small Cell Lung 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
- Cohort
- Time perspective
- Prospective
- Enrolment
- 40 participants (estimated)
- Target duration
- 3 Years
Sponsor and investigators
- Lead sponsor
- Cancer Institute and Hospital, Chinese Academy of Medical Sciences
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Zhijie Wang, Cancer Institute and Hospital, Chinese Academy of Medical Sciences
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07026669
- Sponsor's protocol ID
- NCC5154
- Status last verified
- Jun 2025
- First submitted
- 10 Jun 2025
- Last updated
- 18 Jun 2025
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Rosner S, Levy B. Relapsed small-cell lung cancer: a disease of continued unmet need. Lancet Respir Med. 2023 Jan;11(1):6-8. doi: 10.1016/S2213-2600(22)00389-7. Epub 2022 Oct 14. No abstract available.
PubMed 36252600Wang Z, Liu C, Zheng S, Yao Y, Wang S, Wang X, Yin E, Zeng Q, Zhang C, Zhang G, Tang W, Zheng B, Xue L, Wang Z, Feng X, Wang Y, Ying J, Xue Q, Sun N, He J. Molecular subtypes of neuroendocrine carcinomas: A cross-tissue classification framework based on five transcriptional regulators. Cancer Cell. 2024 Jun 10;42(6):1106-1125.e8. doi: 10.1016/j.ccell.2024.05.002. Epub 2024 May 23.
PubMed 38788718Heeke S, Gay CM, Estecio MR, Tran H, Morris BB, Zhang B, Tang X, Raso MG, Rocha P, Lai S, Arriola E, Hofman P, Hofman V, Kopparapu P, Lovly CM, Concannon K, De Sousa LG, Lewis WE, Kondo K, Hu X, Tanimoto A, Vokes NI, Nilsson MB, Stewart A, Jansen M, Horvath I, Gaga M, Panagoulias V, Raviv Y, Frumkin D, Wasserstrom A, Shuali A, Schnabel CA, Xi Y, Diao L, Wang Q, Zhang J, Van Loo P, Wang J, Wistuba II, Byers LA, Heymach JV. Tumor- and circulating-free DNA methylation identifies clinically relevant small cell lung cancer subtypes. Cancer Cell. 2024 Feb 12;42(2):225-237.e5. doi: 10.1016/j.ccell.2024.01.001. Epub 2024 Jan 25.
PubMed 38278149Blackhall FH. Reframing recalcitrance for small-cell lung cancer. Ann Oncol. 2021 Jul;32(7):829-830. doi: 10.1016/j.annonc.2021.04.022. Epub 2021 May 3. No abstract available.
PubMed 33957222Dingemans AC, Fruh M, Ardizzoni A, Besse B, Faivre-Finn C, Hendriks LE, Lantuejoul S, Peters S, Reguart N, Rudin CM, De Ruysscher D, Van Schil PE, Vansteenkiste J, Reck M; ESMO Guidelines Committee. Electronic address: clinicalguidelines@esmo.org. Small-cell lung cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up☆. Ann Oncol. 2021 Jul;32(7):839-853. doi: 10.1016/j.annonc.2021.03.207. Epub 2021 Apr 20. No abstract available.
PubMed 33864941Chen H, Drapkin BJ, Minna JD. Proteomics: A new dimension to decode small cell lung cancer. Cell. 2024 Jan 4;187(1):14-16. doi: 10.1016/j.cell.2023.11.042.
PubMed 38181738Remon J, Aldea M, Besse B, Planchard D, Reck M, Giaccone G, Soria JC. Small cell lung cancer: a slightly less orphan disease after immunotherapy. Ann Oncol. 2021 Jun;32(6):698-709. doi: 10.1016/j.annonc.2021.02.025. Epub 2021 Mar 15.
PubMed 33737119Lu C, Wei XW, Wang Z, Zhou Z, Liu YT, Zheng D, He Y, Xie ZH, Li Y, Zhang Y, Zhang YC, Huang ZJ, Mei SQ, Liu JQ, Guan XH, Deng Y, Chen ZH, Tu HY, Xu CR, Chen HJ, Zhong WZ, Yang JJ, Zhang XC, Mok TSK, Wu YL, Zhou Q. Allelic Context of EGFR C797X-Mutant Lung Cancer Defines Four Subtypes With Heterogeneous Genomic Landscape and Distinct Clinical Outcomes. J Thorac Oncol. 2024 Apr;19(4):601-612. doi: 10.1016/j.jtho.2023.11.016. Epub 2023 Nov 20.
PubMed 37981218Claxton L, O'Connor J, Woolacott N, Wright K, Hodgson R. Ceritinib for Untreated Anaplastic Lymphoma Kinase-Positive Advanced Non-Small-Cell Lung Cancer: An Evidence Review Group Evaluation of a NICE Single Technology Appraisal. Pharmacoeconomics. 2019 May;37(5):645-654. doi: 10.1007/s40273-018-0720-8.
PubMed 30298279Cao W, Chen HD, Yu YW, Li N, Chen WQ. Changing profiles of cancer burden worldwide and in China: a secondary analysis of the global cancer statistics 2020. Chin Med J (Engl). 2021 Mar 17;134(7):783-791. doi: 10.1097/CM9.0000000000001474.
PubMed 33734139Gao S, Li N, Wang S, Zhang F, Wei W, Li N, Bi N, Wang Z, He J. Lung Cancer in People's Republic of China. J Thorac Oncol. 2020 Oct;15(10):1567-1576. doi: 10.1016/j.jtho.2020.04.028. No abstract available.
PubMed 32981600Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021 May;71(3):209-249. doi: 10.3322/caac.21660. Epub 2021 Feb 4.
PubMed 33538338
Study at a glance
From the registry record, last updated by the sponsor on 18 Jun 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Multi-omics Sequencing-based Model for Predicting Efficacy and Dynamic Monitoring of Treatment in Small Cell Lung Cancer: A Prospective, Non-interventional Study
- ClinicalTrials.gov ID
- NCT07026669
- Acronym / sponsor ID
- NCC5154
- Conditions
- Small Cell Lung Cancer
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 40 participants (estimated)
- Lead sponsor
- Cancer Institute and Hospital, Chinese Academy of Medical SciencesUniversity, hospital or other
- Study start
- 1 Jan 2025 (actual)
- Primary completion
- 1 Dec 2027 (estimated)
- Study completion
- 1 Dec 2027 (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.
Lung cancer is one of the malignant tumors with the highest incidence and mortality rates globally, with small cell lung cancer (SCLC) accounting for approximately 15%. SCLC is characterized by high malignancy, propensity for metastasis and drug resistance, and a 5-year survival rate below 7%. Despite partial progress in chemotherapy and immunotherapy, SCLC patients generally have extremely poor prognosis, and there is a lack of precise therapeutic efficacy prediction and dynamic monitoring approaches. Existing biomarkers (such as TP53/RB1 mutations) are inadequate for clinical needs due to high heterogeneity and insufficient dynamic characteristics. The rapid development of multi-omics technologies provides new opportunities for analyzing SCLC molecular features; however, previous studies have predominantly focused on single omics approaches with insufficient systematic integration, limiting clinical translation. This study aims to systematically integrate multiple omics technologies to construct predictive and dynamic monitoring models for SCLC therapeutic efficacy, providing new methods and evidence for SCLC clinical treatment and dynamic monitoring.
Detailed description
Study Objectives To comprehensively analyze the molecular characteristics of small cell lung cancer (SCLC) through multi-omics technologies based on peripheral blood and paraffin-embedded samples, and establish and validate multi-omics data-based models for therapeutic efficacy prediction and dynamic monitoring.
Primary Objectives
- To collect blood and paraffin-embedded samples from SCLC patients before treatment and analyze multi-omics sequencing characteristics of these patients.
- To establish and validate SCLC therapeutic efficacy prediction and dynamic monitoring models based on multi-omics detection, constructing SCLC scoring models and molecular subtypes.
Secondary Objectives To investigate the sensitivity and specificity of SCLC therapeutic efficacy prediction and dynamic monitoring models in patients with different stages of SCLC.
Exploratory Objectives To analyze potential biomarkers and therapeutic targets in SCLC based on multi-omics data, and conduct in-depth analysis of dynamic changes in peripheral blood multi-omics data during SCLC treatment efficacy processes.
Study Design This is a prospective, single-center study aimed at establishing SCLC therapeutic efficacy prediction and dynamic monitoring models based on multi-omics detection of peripheral blood and paraffin-embedded samples.
Sample Collection Time Points
- Collection of 20ml peripheral blood (EDTA tubes×2) and 20 unstained paraffin tissue sections before first-line first cycle treatment;
- Collection of 20ml peripheral blood (EDTA tubes×2) before third cycle treatment;
- Collection of 20ml peripheral blood (EDTA tubes×2) at disease progression. Sample Size and Omics Detection This study plans to enroll 40 SCLC patients, collecting unstained paraffin tissue sections before treatment and dynamically collecting peripheral blood specimens.
Patient Information Collection
The study requires collection of patients' demographic information before blood collection, imaging data related to disease diagnosis, hospital laboratory biochemical test results, tumor marker test results, pathological diagnosis results or other information providing diagnostic evidence, and underlying disease information. Specific information collected includes:
Information to be collected for all patients includes but is not limited to:
General demographic data: age, gender, race, etc.; Vital signs: blood pressure, pulse, heart rate, etc.; Previous major disease history and corresponding medication history; Tumor history and corresponding treatment history; Family genetic history; Smoking and drinking history; Multi-omics detection results.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Target follow-up
- 3 Years
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Limited-stage/Extensive-stage small cell lung cancer | – | –Small cell lung cancer with lymph node metastasis/distant metastasis |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- SCLC patients From Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College
Key inclusion criteria (8 listed)
- Patients meeting the following criteria may have samples collected:
Key exclusion criteria (12 listed)
- Patients with any of the following conditions will be excluded from sample collection:
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
SCLC scoring models and molecular subtypes
Time frame: From enrollment to the end of monitoring at 3 years or the occurrence of disease progression.
To establish and validate SCLC therapeutic efficacy prediction and dynamic monitoring models based on multi-omics detection, and construct SCLC scoring models and molecular subtypes.
2 secondary outcomes
Sensitivity and specificity of SCLC therapeutic efficacy prediction and dynamic monitoring models
Time frame: From enrollment to the end of monitoring at 3 years or the occurrence of disease progression.
Dynamic changes in peripheral blood multi-omics data during SCLC treatment efficacy processes
Time frame: From enrollment to the end of monitoring at 3 years or the occurrence of disease progression.
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 18 Jun 2025.
- Background: PubMed 36252600Rosner S, Levy B. Relapsed small-cell lung cancer: a disease of continued unmet need. Lancet Respir Med. 2023 Jan;11(1):6-8. doi: 10.1016/S2213-2600(22)00389-7. Epub 2022 Oct 14. No abstract available.
- Background: PubMed 38788718Wang Z, Liu C, Zheng S, Yao Y, Wang S, Wang X, Yin E, Zeng Q, Zhang C, Zhang G, Tang W, Zheng B, Xue L, Wang Z, Feng X, Wang Y, Ying J, Xue Q, Sun N, He J. Molecular subtypes of neuroendocrine carcinomas: A cross-tissue classification framework based on five transcriptional regulators. Cancer Cell. 2024 Jun 10;42(6):1106-1125.e8. doi: 10.1016/j.ccell.2024.05.002. Epub 2024 May 23.
- Background: PubMed 38278149Heeke S, Gay CM, Estecio MR, Tran H, Morris BB, Zhang B, Tang X, Raso MG, Rocha P, Lai S, Arriola E, Hofman P, Hofman V, Kopparapu P, Lovly CM, Concannon K, De Sousa LG, Lewis WE, Kondo K, Hu X, Tanimoto A, Vokes NI, Nilsson MB, Stewart A, Jansen M, Horvath I, Gaga M, Panagoulias V, Raviv Y, Frumkin D, Wasserstrom A, Shuali A, Schnabel CA, Xi Y, Diao L, Wang Q, Zhang J, Van Loo P, Wang J, Wistuba II, Byers LA, Heymach JV. Tumor- and circulating-free DNA methylation identifies clinically relevant small cell lung cancer subtypes. Cancer Cell. 2024 Feb 12;42(2):225-237.e5. doi: 10.1016/j.ccell.2024.01.001. Epub 2024 Jan 25.
- Background: PubMed 33957222Blackhall FH. Reframing recalcitrance for small-cell lung cancer. Ann Oncol. 2021 Jul;32(7):829-830. doi: 10.1016/j.annonc.2021.04.022. Epub 2021 May 3. No abstract available.
- Background: PubMed 33864941Dingemans AC, Fruh M, Ardizzoni A, Besse B, Faivre-Finn C, Hendriks LE, Lantuejoul S, Peters S, Reguart N, Rudin CM, De Ruysscher D, Van Schil PE, Vansteenkiste J, Reck M; ESMO Guidelines Committee. Electronic address: clinicalguidelines@esmo.org. Small-cell lung cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up☆. Ann Oncol. 2021 Jul;32(7):839-853. doi: 10.1016/j.annonc.2021.03.207. Epub 2021 Apr 20. No abstract available.
- Background: PubMed 38181738Chen H, Drapkin BJ, Minna JD. Proteomics: A new dimension to decode small cell lung cancer. Cell. 2024 Jan 4;187(1):14-16. doi: 10.1016/j.cell.2023.11.042.
- Background: PubMed 33737119Remon J, Aldea M, Besse B, Planchard D, Reck M, Giaccone G, Soria JC. Small cell lung cancer: a slightly less orphan disease after immunotherapy. Ann Oncol. 2021 Jun;32(6):698-709. doi: 10.1016/j.annonc.2021.02.025. Epub 2021 Mar 15.
- Background: PubMed 37981218Lu C, Wei XW, Wang Z, Zhou Z, Liu YT, Zheng D, He Y, Xie ZH, Li Y, Zhang Y, Zhang YC, Huang ZJ, Mei SQ, Liu JQ, Guan XH, Deng Y, Chen ZH, Tu HY, Xu CR, Chen HJ, Zhong WZ, Yang JJ, Zhang XC, Mok TSK, Wu YL, Zhou Q. Allelic Context of EGFR C797X-Mutant Lung Cancer Defines Four Subtypes With Heterogeneous Genomic Landscape and Distinct Clinical Outcomes. J Thorac Oncol. 2024 Apr;19(4):601-612. doi: 10.1016/j.jtho.2023.11.016. Epub 2023 Nov 20.
- Background: PubMed 30298279Claxton L, O'Connor J, Woolacott N, Wright K, Hodgson R. Ceritinib for Untreated Anaplastic Lymphoma Kinase-Positive Advanced Non-Small-Cell Lung Cancer: An Evidence Review Group Evaluation of a NICE Single Technology Appraisal. Pharmacoeconomics. 2019 May;37(5):645-654. doi: 10.1007/s40273-018-0720-8.
- Background: PubMed 33734139Cao W, Chen HD, Yu YW, Li N, Chen WQ. Changing profiles of cancer burden worldwide and in China: a secondary analysis of the global cancer statistics 2020. Chin Med J (Engl). 2021 Mar 17;134(7):783-791. doi: 10.1097/CM9.0000000000001474.
- Background: PubMed 32981600Gao S, Li N, Wang S, Zhang F, Wei W, Li N, Bi N, Wang Z, He J. Lung Cancer in People's Republic of China. J Thorac Oncol. 2020 Oct;15(10):1567-1576. doi: 10.1016/j.jtho.2020.04.028. No abstract available.
- Background: PubMed 33538338Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021 May;71(3):209-249. doi: 10.3322/caac.21660. Epub 2021 Feb 4.
- 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.
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 Small Cell Lung Cancer, 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 8 inclusion and 12 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 18 Jun 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 Zhijie Wang, MD (+8613466323860, jie_969@163.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
SCLC scoring models and molecular subtypes (time frame: From enrollment to the end of monitoring at 3 years or the occurrence of disease progression.). 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 NCT07026669, which also lists 12 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 18 Jun 2025; AzTrials last refreshed its copy on 27 Oct 2026.