NSCLCiPRECISENCT07559123
Imaging-based PRediction of Eligibility for ChemoImmunotherapy in reSEctable NSCLC, iPRECISE
An observational study of NSCLC and Neoadjuvant Chemoimmunotherapy, run by Samsung Medical Center at 1 site in South Korea.
Trial summary
This study is for adults with resectable non-small cell lung cancer who are scheduled to receive neoadjuvant chemoimmunotherapy before surgery. Neoadjuvant chemoimmunotherapy can help shrink lung cancer before surgery and may improve treatment outcomes. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- NSCLC, Neoadjuvant Chemoimmunotherapy, CT
- What is being tested?
- High-resolution deep learning-based CT reconstruction
- How many people
- 150 participants
- Where
- 1 siteSouth Korea
- Study dates
- 1 Feb 2026to Dec 2028
- 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: The study population will include adult patients with resectable non-small cell lung cancer of stage IIIA or lower who are scheduled to receive neoadjuvant chemoimmunotherapy before surgery at Samsung Medical Center. Participants will be enrolled prospectively after providing written informed consent. Treatment decisions, including the use of neoadjuvant chemoimmunotherapy and surgery, will be made according to standard clinical practice and will not be assigned by the investigators. Participants will undergo chest computed tomography before neoadjuvant chemoimmunotherapy and before surgery as part of the study protocol. Imaging, clinical, molecular, and pathologic data will be collected to evaluate computed tomography-based imaging biomarkers associated with treatment response, pathologic response, treatment-related pneumonitis, and clinical outcomes.
Who may be able to join
- Age: 18 years or older.
- Diagnosis: Histologically or cytologically confirmed non-small cell lung cancer (NSCLC).
- Staging: Resectable NSCLC of stage IIIA or lower.
- Treatment Plan: Planned to receive neoadjuvant chemoimmunotherapy before surgery according to standard clinical practice.
- Performance Status: Eastern Cooperative Oncology Group (ECOG) performance status of 0 or 1.
- Informed Consent: Able and willing to provide written informed consent after receiving a detailed explanation of the study.
Who cannot join
- No Measurable Lesion: Participants must have at least one measurable lesion (>= 10 mm on spiral/multidetector computed tomography).
- Prior Malignancy: History of another malignancy within 5 years before enrollment (excluding adequately treated basal cell skin carcinoma or cervical carcinoma in situ).
- Neurological/Psychiatric Conditions: History of clinically significant uncontrolled seizures, CNS disease, or psychiatric disorders that may interfere with study participation or consent.
- Contrast Allergy: History of severe allergic reaction to iodinated CT contrast media.
- Renal Impairment: Acute renal failure or moderate to severe renal impairment (CrCl < 45 mL/min/1.73 m² or serum creatinine > 1.5x upper limit of normal).
- Recent Surgery: Major surgery within 4 weeks of enrollment or incomplete recovery from major surgery.
- Pregnancy/Nursing: Currently pregnant or breastfeeding; women of childbearing potential without a negative baseline pregnancy test.
- Contraception: Men or women of childbearing potential unwilling to use appropriate contraception during the study.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
South Korea1 site, 1 recruiting
- Recruiting
Samsung Medical Center
Seoul
Ho Yun Lee, Prof., 82-02-3410-2502, hoyunlee96@gmail.com
About this study
This study is for adults with resectable non-small cell lung cancer who are scheduled to receive neoadjuvant chemoimmunotherapy before surgery.
Neoadjuvant chemoimmunotherapy can help shrink lung cancer before surgery and may improve treatment outcomes. However, not all patients benefit from this treatment in the same way, and it can sometimes cause side effects, such as immune-related pneumonitis. At present, it is still difficult to predict before or during treatment which patients will have a strong response.
Read more
The purpose of this study is to find imaging features on chest computed tomography scans that may help predict how well a patient's cancer responds to neoadjuvant chemoimmunotherapy. The study will compare computed tomography findings before treatment and before surgery with pathologic findings from surgery, including pathologic complete response and major pathologic response. The study will also evaluate whether computed tomography-based imaging features are associated with treatment-related side effects and long-term outcomes such as disease progression and survival.
This is an observational study. The investigators will not assign participants to a specific cancer treatment. Participants will receive neoadjuvant chemoimmunotherapy and surgery according to standard clinical practice. Chest computed tomography scans will be obtained before treatment and before surgery as part of the study protocol. These computed tomography images will also be reconstructed using a high-resolution deep learning-based computed tomography reconstruction technique to explore whether this approach can improve the development of imaging biomarkers.
The results of this study may help develop a noninvasive imaging-based model to identify patients who are more likely to benefit from neoadjuvant chemoimmunotherapy and to better guide treatment planning for resectable non-small cell lung cancer.
Read the detailed description
This is a prospective observational study designed to evaluate imaging biomarkers in patients with resectable non-small cell lung cancer who receive neoadjuvant chemoimmunotherapy before planned surgery.
Neoadjuvant chemoimmunotherapy has become an important treatment option for resectable non-small cell lung cancer. Although pathologic complete response and major pathologic response are associated with favorable outcomes, reliable noninvasive methods for predicting these responses remain limited. Imaging biomarkers derived from computed tomography may provide a quantitative and repeatable way to assess tumor burden, nodal disease, treatment response, and treatment-related lung toxicity over time.
In this study, participants will undergo chest computed tomography before starting neoadjuvant chemoimmunotherapy and again after completion of neoadjuvant treatment before surgery. If disease progression is clinically suspected before planned surgery, an additional computed tomography scan may be performed and used for response assessment. Computed tomography scans will be acquired using a standardized imaging protocol. In addition to conventional computed tomography reconstruction, high-resolution deep learning-based computed tomography reconstruction will be applied after image acquisition.
The study will evaluate imaging features of the primary tumor, lymph nodes, suspected extranodal extension, adjacent structure involvement, radiologic treatment response, and possible immune-related pneumonitis. Imaging findings will be compared with clinical data, molecular and immunohistochemical findings, and surgical pathology findings, including pathologic complete response, major pathologic response, final pathologic stage, extranodal extension, and spread through air spaces when available.
The study will also explore whether imaging biomarkers are associated with progression-free survival, overall survival, treatment-related pneumonitis, and whether high-resolution deep learning-based CT reconstruction improves imaging biomarker development compared with conventional reconstruction. The anticipated enrollment is 150 participants.
- Conditions
- NSCLC, Neoadjuvant Chemoimmunotherapy, CT
- Being tested
- High-resolution deep learning-based CT reconstruction
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
High-resolution deep learning-based CT reconstructionDiagnostic test
High-resolution deep learning-based computed tomography reconstruction will be applied after computed tomography image acquisition to generate additional reconstructed images. These images will be compared with conventional computed tomography reconstruction images to evaluate their usefulness for imaging biomarker development and assessment of extranodal extension.
What is being measured
The primary outcome is the main question the study is designed to answer.
Predictive performance of computed tomography-based imaging biomarkers for pathologic complete response
The predictive performance of imaging biomarkers derived from contrast-enhanced chest computed tomography scans obtained before and after neoadjuvant chemoimmunotherapy will be evaluated for pathologic complete response. Pathologic complete response will be assessed using surgical pathology findings after resection. Predictive performance will be measured using model discrimination, including the area under the receiver operating characteristic curve.
Measured: From baseline computed tomography before neoadjuvant chemoimmunotherapy to surgical pathology assessment after surgery, up to 6 months after enrollment.
Secondary outcomes (1)
Association between computed tomography-based imaging biomarkers and progression-free survival
The association between computed tomography-based imaging biomarkers and progression-free survival will be evaluated. Progression-free survival is defined as the time from initiation of neoadjuvant chemoimmunotherapy to disease progression, recurrence, or death, whichever occurs first.
Measured: From initiation of neoadjuvant chemoimmunotherapy through disease progression, recurrence, death, or last follow-up, up to study completion.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted30 Apr 2026
- Study start1 Feb 2026
- Primary completionDec 2028 (estimated)
- Study completionDec 2028 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (5)Papers the sponsor has linked to this study.
- Other trials for NSCLCStudies of the same condition, open and under way.
- More trials run by Samsung Medical CenterThe 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
- Cohort
- Time perspective
- Prospective
- Enrolment
- 150 participants (estimated)
- Target duration
- 3 Years
Sponsor and investigators
- Lead sponsor
- Samsung Medical Center
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Ho Yun Lee, Samsung Medical Center
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07559123
- Sponsor's protocol ID
- 2024-12-118
- Acronym
- iPRECISE
- Status last verified
- May 2026
- First submitted
- 23 Apr 2026
- Last updated
- 8 May 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Individual participant data will not be shared. This study includes clinical data, imaging-derived data, molecular and pathologic information, and follow-up outcome data from patients with resectable non-small cell lung cancer. Because of the potential risk of participant re-identification and the absence of a pre-specified external IPD sharing plan in the study protocol and informed consent process, individual participant-level data will not be made available to other researchers.
Publications
She Y, He B, Wang F, Zhong Y, Wang T, Liu Z, Yang M, Yu B, Deng J, Sun X, Wu C, Hou L, Zhu Y, Yang Y, Hu H, Dong D, Chen C, Tian J. Deep learning for predicting major pathological response to neoadjuvant chemoimmunotherapy in non-small cell lung cancer: A multicentre study. EBioMedicine. 2022 Dec;86:104364. doi: 10.1016/j.ebiom.2022.104364. Epub 2022 Nov 14.
PubMed 36395737Greffier J, Pastor M, Si-Mohamed S, Goutain-Majorel C, Peudon-Balas A, Bensalah MZ, Frandon J, Beregi JP, Dabli D. Comparison of two deep-learning image reconstruction algorithms on cardiac CT images: A phantom study. Diagn Interv Imaging. 2024 Mar;105(3):110-117. doi: 10.1016/j.diii.2023.10.004. Epub 2023 Nov 8.
PubMed 37949769Marinelli D, Nuccio A, Di Federico A, Ambrosi F, Bertoglio P, Faccioli E, Ferrara R, Ferro A, Giusti R, Guerrera F, Mammana M, Pittaro A, Sepulcri M, Viscardi G, Gallina FT. Improved Event-Free Survival After Complete or Major Pathologic Response in Patients With Resectable NSCLC Treated With Neoadjuvant Chemoimmunotherapy Regardless of Adjuvant Treatment: A Systematic Review and Individual Patient Data Meta-Analysis. J Thorac Oncol. 2025 Mar;20(3):285-295. doi: 10.1016/j.jtho.2024.09.1443. Epub 2024 Oct 9.
PubMed 39389220Sorin M, Prosty C, Ghaleb L, Nie K, Katergi K, Shahzad MH, Dube LR, Atallah A, Swaby A, Dankner M, Crump T, Walsh LA, Fiset PO, Sepesi B, Forde PM, Cascone T, Provencio M, Spicer JD. Neoadjuvant Chemoimmunotherapy for NSCLC: A Systematic Review and Meta-Analysis. JAMA Oncol. 2024 May 1;10(5):621-633. doi: 10.1001/jamaoncol.2024.0057.
PubMed 38512301Forde PM, Spicer J, Lu S, Provencio M, Mitsudomi T, Awad MM, Felip E, Broderick SR, Brahmer JR, Swanson SJ, Kerr K, Wang C, Ciuleanu TE, Saylors GB, Tanaka F, Ito H, Chen KN, Liberman M, Vokes EE, Taube JM, Dorange C, Cai J, Fiore J, Jarkowski A, Balli D, Sausen M, Pandya D, Calvet CY, Girard N; CheckMate 816 Investigators. Neoadjuvant Nivolumab plus Chemotherapy in Resectable Lung Cancer. N Engl J Med. 2022 May 26;386(21):1973-1985. doi: 10.1056/NEJMoa2202170. Epub 2022 Apr 11.
PubMed 35403841
Study at a glance
From the registry record, last updated by the sponsor on 8 May 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Imaging-based PRediction of Eligibility for ChemoImmunotherapy in reSEctable NSCLC, iPRECISE
- ClinicalTrials.gov ID
- NCT07559123
- Acronym / sponsor ID
- iPRECISE / 2024-12-118
- Conditions
- NSCLC, Neoadjuvant Chemoimmunotherapy, CT
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 150 participants (estimated)
- Lead sponsor
- Samsung Medical CenterUniversity, hospital or other
- Study start
- 1 Feb 2026 (actual)
- Primary completion
- Dec 2028 (estimated)
- Study completion
- Dec 2028 (estimated)
- First posted
- 30 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 is for adults with resectable non-small cell lung cancer who are scheduled to receive neoadjuvant chemoimmunotherapy before surgery.
Neoadjuvant chemoimmunotherapy can help shrink lung cancer before surgery and may improve treatment outcomes. However, not all patients benefit from this treatment in the same way, and it can sometimes cause side effects, such as immune-related pneumonitis. At present, it is still difficult to predict before or during treatment which patients will have a strong response.
The purpose of this study is to find imaging features on chest computed tomography scans that may help predict how well a patient's cancer responds to neoadjuvant chemoimmunotherapy. The study will compare computed tomography findings before treatment and before surgery with pathologic findings from surgery, including pathologic complete response and major pathologic response. The study will also evaluate whether computed tomography-based imaging features are associated with treatment-related side effects and long-term outcomes such as disease progression and survival.
This is an observational study. The investigators will not assign participants to a specific cancer treatment. Participants will receive neoadjuvant chemoimmunotherapy and surgery according to standard clinical practice. Chest computed tomography scans will be obtained before treatment and before surgery as part of the study protocol. These computed tomography images will also be reconstructed using a high-resolution deep learning-based computed tomography reconstruction technique to explore whether this approach can improve the development of imaging biomarkers.
The results of this study may help develop a noninvasive imaging-based model to identify patients who are more likely to benefit from neoadjuvant chemoimmunotherapy and to better guide treatment planning for resectable non-small cell lung cancer.
Detailed description
This is a prospective observational study designed to evaluate imaging biomarkers in patients with resectable non-small cell lung cancer who receive neoadjuvant chemoimmunotherapy before planned surgery.
Neoadjuvant chemoimmunotherapy has become an important treatment option for resectable non-small cell lung cancer. Although pathologic complete response and major pathologic response are associated with favorable outcomes, reliable noninvasive methods for predicting these responses remain limited. Imaging biomarkers derived from computed tomography may provide a quantitative and repeatable way to assess tumor burden, nodal disease, treatment response, and treatment-related lung toxicity over time.
In this study, participants will undergo chest computed tomography before starting neoadjuvant chemoimmunotherapy and again after completion of neoadjuvant treatment before surgery. If disease progression is clinically suspected before planned surgery, an additional computed tomography scan may be performed and used for response assessment. Computed tomography scans will be acquired using a standardized imaging protocol. In addition to conventional computed tomography reconstruction, high-resolution deep learning-based computed tomography reconstruction will be applied after image acquisition.
The study will evaluate imaging features of the primary tumor, lymph nodes, suspected extranodal extension, adjacent structure involvement, radiologic treatment response, and possible immune-related pneumonitis. Imaging findings will be compared with clinical data, molecular and immunohistochemical findings, and surgical pathology findings, including pathologic complete response, major pathologic response, final pathologic stage, extranodal extension, and spread through air spaces when available.
The study will also explore whether imaging biomarkers are associated with progression-free survival, overall survival, treatment-related pneumonitis, and whether high-resolution deep learning-based CT reconstruction improves imaging biomarker development compared with conventional reconstruction. The anticipated enrollment is 150 participants.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Target follow-up
- 3 Years
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- The study population will include adult patients with resectable non-small cell lung cancer of stage IIIA or lower who are scheduled to receive neoadjuvant chemoimmunotherapy before surgery at Samsung Medical Center. Participants will be enrolled prospectively after providing written informed consent. Treatment decisions, including the use of neoadjuvant chemoimmunotherapy and surgery, will be made according to standard clinical practice and will not be assigned by the investigators. Participants will undergo chest computed tomography before neoadjuvant chemoimmunotherapy and before surgery as part of the study protocol. Imaging, clinical, molecular, and pathologic data will be collected to evaluate computed tomography-based imaging biomarkers associated with treatment response, pathologic response, treatment-related pneumonitis, and clinical outcomes.
Key inclusion criteria (6 listed)
- Age: 18 years or older.
- Diagnosis: Histologically or cytologically confirmed non-small cell lung cancer (NSCLC).
- Staging: Resectable NSCLC of stage IIIA or lower.
- Treatment Plan: Planned to receive neoadjuvant chemoimmunotherapy before surgery according to standard clinical practice.
- Performance Status: Eastern Cooperative Oncology Group (ECOG) performance status of 0 or 1.
Key exclusion criteria (8 listed)
- No Measurable Lesion: Participants must have at least one measurable lesion (>= 10 mm on spiral/multidetector computed tomography).
- Prior Malignancy: History of another malignancy within 5 years before enrollment (excluding adequately treated basal cell skin carcinoma or cervical carcinoma in situ).
- Neurological/Psychiatric Conditions: History of clinically significant uncontrolled seizures, CNS disease, or psychiatric disorders that may interfere with study participation or consent.
- Contrast Allergy: History of severe allergic reaction to iodinated CT contrast media.
- Renal Impairment: Acute renal failure or moderate to severe renal impairment (CrCl < 45 mL/min/1.73 m² or serum creatinine > 1.5x upper limit of normal).
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 |
|---|---|---|
| High-resolution deep learning-based CT reconstructionHigh-resolution deep learning-based computed tomography reconstruction will be applied after computed tomography image acquisition to generate additional reconstructed images. These images will be compared with conventional computed tomography reconstruction images to evaluate their usefulness for imaging biomarker development and assessment of extranodal extension. | Diagnostic test | – |
Primary outcome
Predictive performance of computed tomography-based imaging biomarkers for pathologic complete response
Time frame: From baseline computed tomography before neoadjuvant chemoimmunotherapy to surgical pathology assessment after surgery, up to 6 months after enrollment.
The predictive performance of imaging biomarkers derived from contrast-enhanced chest computed tomography scans obtained before and after neoadjuvant chemoimmunotherapy will be evaluated for pathologic complete response. Pathologic complete response will be assessed using surgical pathology findings after resection. Predictive performance will be measured using model discrimination, including the area under the receiver operating characteristic curve.
1 secondary outcome
Association between computed tomography-based imaging biomarkers and progression-free survival
Time frame: From initiation of neoadjuvant chemoimmunotherapy through disease progression, recurrence, death, or last follow-up, up to study completion.
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 8 May 2026.
- Background: PubMed 36395737She Y, He B, Wang F, Zhong Y, Wang T, Liu Z, Yang M, Yu B, Deng J, Sun X, Wu C, Hou L, Zhu Y, Yang Y, Hu H, Dong D, Chen C, Tian J. Deep learning for predicting major pathological response to neoadjuvant chemoimmunotherapy in non-small cell lung cancer: A multicentre study. EBioMedicine. 2022 Dec;86:104364. doi: 10.1016/j.ebiom.2022.104364. Epub 2022 Nov 14.
- Background: PubMed 37949769Greffier J, Pastor M, Si-Mohamed S, Goutain-Majorel C, Peudon-Balas A, Bensalah MZ, Frandon J, Beregi JP, Dabli D. Comparison of two deep-learning image reconstruction algorithms on cardiac CT images: A phantom study. Diagn Interv Imaging. 2024 Mar;105(3):110-117. doi: 10.1016/j.diii.2023.10.004. Epub 2023 Nov 8.
- Background: PubMed 39389220Marinelli D, Nuccio A, Di Federico A, Ambrosi F, Bertoglio P, Faccioli E, Ferrara R, Ferro A, Giusti R, Guerrera F, Mammana M, Pittaro A, Sepulcri M, Viscardi G, Gallina FT. Improved Event-Free Survival After Complete or Major Pathologic Response in Patients With Resectable NSCLC Treated With Neoadjuvant Chemoimmunotherapy Regardless of Adjuvant Treatment: A Systematic Review and Individual Patient Data Meta-Analysis. J Thorac Oncol. 2025 Mar;20(3):285-295. doi: 10.1016/j.jtho.2024.09.1443. Epub 2024 Oct 9.
- Results publication: PubMed 38512301Sorin M, Prosty C, Ghaleb L, Nie K, Katergi K, Shahzad MH, Dube LR, Atallah A, Swaby A, Dankner M, Crump T, Walsh LA, Fiset PO, Sepesi B, Forde PM, Cascone T, Provencio M, Spicer JD. Neoadjuvant Chemoimmunotherapy for NSCLC: A Systematic Review and Meta-Analysis. JAMA Oncol. 2024 May 1;10(5):621-633. doi: 10.1001/jamaoncol.2024.0057.
- Results publication: PubMed 35403841Forde PM, Spicer J, Lu S, Provencio M, Mitsudomi T, Awad MM, Felip E, Broderick SR, Brahmer JR, Swanson SJ, Kerr K, Wang C, Ciuleanu TE, Saylors GB, Tanaka F, Ito H, Chen KN, Liberman M, Vokes EE, Taube JM, Dorange C, Cai J, Fiore J, Jarkowski A, Balli D, Sausen M, Pandya D, Calvet CY, Girard N; CheckMate 816 Investigators. Neoadjuvant Nivolumab plus Chemotherapy in Resectable Lung Cancer. N Engl J Med. 2022 May 26;386(21):1973-1985. doi: 10.1056/NEJMoa2202170. Epub 2022 Apr 11.
- Individual participant dataSharing planned: No. Individual participant data will not be shared. This study includes clinical data, imaging-derived data, molecular and pathologic information, and follow-up outcome data from patients with resectable non-small cell lung cancer. Because of the potential risk of participant re-identification and the absence of a pre-specified external IPD sharing plan in the study protocol and informed consent process, individual participant-level data will not be made available to other researchers.
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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 NSCLC and Neoadjuvant Chemoimmunotherapy, run by Samsung Medical Center at 1 site in South Korea.
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 6 inclusion and 8 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 8 May 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 South Korea. 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 Ho Yun Lee, Prof. (82-02-3410-2502, hoyunlee96@gmail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Predictive performance of computed tomography-based imaging biomarkers for pathologic complete response (time frame: From baseline computed tomography before neoadjuvant chemoimmunotherapy to surgical pathology assessment after surgery, up to 6 months after enrollment.). 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 NCT07559123, which also lists 5 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 8 May 2026.