Lung CancerNCT06262386
Combined Relapse Prediction Model for Resectable Non-Small Cell Patients - a Prospective Clinical Feasibility Trial
A study testing Cisplatin based chemottherapy in people with Lung Cancer and Relapse/Recurrence, run by Chang Gung Memorial Hospital at 1 site in Taiwan.
Trial summary
For patients with lung cancer who have undergone tumor resection, early relapse significantly impacts survival. However, there are currently no reliable screening or imaging tools available to identify patients at risk of early relapse. Read more about this study
- Who is it for?
- Ages 20 to 90 years
- Conditions the study is for
- Lung Cancer, Relapse/Recurrence
- What is being tested?
- Cisplatin based chemottherapy
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 358 participants
- Where
- 1 siteTaiwan
- Study dates
- 1 Aug 2023to 31 Jul 2028
- Phase
- Interventional
- 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 20 to 90 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Patients who presented with resectable disease ( Clinical stage 1a to 3a)
- Patients who received tumor resection
Who cannot join
- Pathologic stage greater than stage 3b or 4
- Pathologic stage less than stage 1a1
- Could not complete treatment course
- Could not receive blood sampling for CTC (circulating tumor cell) or regular surveillance
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Taiwan1 site, 1 recruiting
- Recruiting
Ching-Yang Wu
Taoyuan City, 333
Ching-Yang Wu, +886975368204, wu.chingyang@gmail.com
Jason CH Hsieh, +886975366137, wisdom5000@gmail.com
About this study
Official title: Utilizing Perioperative Variation Trends of Circulating Tumor Cells and Tumor Pathological Characteristics as a Combined Relapse Prediction Model for Resectable Non-Small Cell Patients - a Prospective Clinical Feasibility Trial
For patients with lung cancer who have undergone tumor resection, early relapse significantly impacts survival. However, there are currently no reliable screening or imaging tools available to identify patients at risk of early relapse. To address this clinical challenge, many studies have focused on understanding the clinicopathologic characteristics associated with an increased risk of early relapse. Despite these efforts, we can identify patients at risk but cannot pinpoint which individuals will actually experience early relapse. Studies on adjuvant therapy have shown improved survival in cases of more advanced disease but have not demonstrated a reduction in early relapse rates.
In our preliminary analysis of previous study data, we observed that patients with a smaller reduction in circulating tumor cells (CTCs) within the first three days after surgery, followed by an increase on the third-day post-operation, are more likely to experience early relapse during regular monitoring. This pattern may be indicative of minimal residual disease. By combining trends in circulating tumor cell variations with pathologic characteristics, we aim to select patients for adjuvant therapy who are at high risk of developing early relapse.
The objective of our study is to employ screening based on circulating tumor cell dynamics and pathologic features to identify patients likely to experience early relapse and to assess the effectiveness of adjuvant therapy in these cases.
Read the detailed description
For patients with resectable lung cancer, anatomic resection alongside mediastinal lymph node dissection is pivotal in removing all tumor tissue visible on imaging from the patient's body. Despite these efforts, early relapse remains a significant issue. Literature review shows that the early relapse rate varies between 8 to 10%, potentially due to undetectable occult metastasis by imaging modalities, suggesting the presence of minimal residual disease or tumor cells evading the primary site. Limitations in imaging, such as the slice thickness in computed tomography (CT) scans, which range from 0.375 to 0.5 centimeters, can render tumors smaller than the slice thickness invisible. Similarly, tumors smaller than 0.5 cm may not accumulate sufficient F18-Deoxyglucose to be detectable in positron emission tomography (PET) scans. Additionally, tumor cells may migrate to extrapulmonary sites via lymphatic drainage or circulation.
Survival studies have predominantly focused on the pathologic TNM stage, which aggregates different disease presentations with similar survival outcomes. However, the heterogeneity inherent in pathology may help in identifying patients prone to relapse. From a tumor biology perspective, tumor cells may detach from surrounding tissues, becoming more invasive and entering the bloodstream. Circulating tumor cells (CTCs) have been recognized early in cancer stages and are correlated with treatment response, tumor genetic alterations, and survival. Research has combined CT tumor size and CTCs in a malignancy prediction model for suspicious pulmonary lesions, highlighting that CTCs can rebound in patients experiencing early relapse, indicating occult metastases or minimal residual disease.
Systemic adjuvant therapy is considered the best approach to minimize disease relapse in resectable lung cancer patients. Although many studies have sought to identify patients at risk of relapse to improve survival, the presence of intrapulmonary (N1) or mediastinal (N2) lymph node invasion significantly affects survival in non-small cell lung cancer patients. Even tumors smaller than 1 cm carry a risk of lymph node metastases, with respective risks for cT1a, cT1b, and cT1c tumors reported as 3.8%, 16.3%, and 19.6%. Therefore, patients with tumors larger than 1 cm are recommended adjuvant therapy due to the high risk of lymph node involvement. Adjuvant chemotherapy is advised for patients with stages 1b to 3a, showing a 5.4% survival benefit by the fifth postoperative year, although this benefit diminishes in subsequent years. This could be due to adjuvant therapy being administered based on the pathologic stage rather than the likelihood of relapse. Tumor heterogeneity might also influence the response to different therapeutic regimens. Molecular profiling of tumors has identified mutations predicting responses to targeted therapies and elucidated drug resistance mechanisms, offering more precise treatments and improving survival. Targeted and immune therapies have shown improved survival in specific tumor subgroups.
This study aims to utilize trends in CTC variations as a screening tool to identify patients at risk of relapse and prescribe adjuvant therapy to evaluate the therapeutic efficacy and survival impact of CTCs.
- Conditions
- Lung Cancer, Relapse/Recurrence
- Being tested
- Cisplatin based chemottherapy
- Keywords
- Circulating tumor cell, resectable non-small cell lung cancer, Early relapse
- Medical subject headings
- Lung Neoplasms, Recurrence, Neoplastic Cells, Circulating
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Cisplatin based chemottherapyDrug
adjuvant therapy for high risk patient
| Study group | Role | What they receive |
|---|---|---|
| Patient at risk for disease relapse after surgery | Experimental | 1. we utilized a relapse prediction model that combined perioperative variation trends of circulating tumor cells and pathologic characteristics that were collated with relapse
1. circulating tumor cell variation trend: difference between the CTC count on post-operation day 3 and day 1; difference between the CTC count on post-operation day 3 and post-operation
2. pathologic staging 0-1a/ 1b-4
2. patient with high relapse for relapse
* Adjuvant was recommended as NCCN guidelines recommended Receives: Drug: Cisplatin based chemottherapy |
What is being measured
The primary outcome is the main question the study is designed to answer.
Accuracy of proposed relapse prediction model
- Utilized the enrolled patients to testify proposed relapse prediction model
- Calculated Positive prediction rate, Negative prediction rate, accuracy
- Goal: high positive prediction rate, lower negative prediction rate, high accuracy
Measured: follow up in 3 month-interval
early relapse rate
- adjuvant therapy based on proposed relapse prediction model
- calculate the early relapse rate (relapse within 3 years)
- utilized historical cohort as historical control (cohort that utilized to establish proposed relapse prediction model
- adjuvant therapy based on TNM stage
- calculate the early relapse rate (relapse within 3 years)
- follow up Chest CT/ CTC in 3-month interval
Measured: follow up in 3 month-interval
Secondary outcomes (1)
Overall surveival
Goal: difference of overall survival among patients with relapse risk
- treatment based on proposed relapse prediction model
- calculate the overall survival
- utilized historical cohort as historical control ( cohort that utilized to establish proposed relapse prediction model
- treatment based on TNM stage
- calculate the overall survival rate
Measured: follow up in 3 month-interval
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted16 Feb 2024
- Study start1 Aug 2023
- Primary completion31 Jul 2028 (estimated)
- Study completion31 Jul 2028 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (35)Papers the sponsor has linked to this study.
- Other trials for 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
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Other
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 358 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Chang Gung Memorial Hospital
- Sponsor type
- University, hospital or other
- Collaborators
- National Science and Technology Council
- Responsible party
- Sponsor
- Investigators
- Ching-Yang Wu, Principal investigator, Chang Gung Memorial Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06262386
- Sponsor's protocol ID
- 202202172B0
- Status last verified
- Aug 2023
- First submitted
- 22 Sep 2023
- Last updated
- 16 Feb 2024
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
Publications
Wu CY, Fu JY, Wu CF, Liu YH, Hsieh MJ, Wu YC, Yang CT, Tsai YH. Pathologic Stage of Nonsmall Cell Lung Cancer Patients Presenting as Resectable Cases After Neoadjuvant Therapy Did Not Predict the Prognosis. Medicine (Baltimore). 2015 Oct;94(40):1. doi: 10.1097/MD.0000000000001700.
PubMed 26448022Boedeker KL, Cooper VN, McNitt-Gray MF. Application of the noise power spectrum in modern diagnostic MDCT: part I. Measurement of noise power spectra and noise equivalent quanta. Phys Med Biol. 2007 Jul 21;52(14):4027-46. doi: 10.1088/0031-9155/52/14/002. Epub 2007 Jun 8.
PubMed 17664593Sun F, Xi J, Zhan C, Yang X, Wang L, Shi Y, Jiang W, Wang Q. Ground glass opacities: Imaging, pathology, and gene mutations. J Thorac Cardiovasc Surg. 2018 Aug;156(2):808-813. doi: 10.1016/j.jtcvs.2018.02.110. Epub 2018 Apr 13.
PubMed 29753514Funama Y, Awai K, Liu D, Oda S, Yanaga Y, Nakaura T, Kawanaka K, Shimamura M, Yamashita Y. Detection of nodules showing ground-glass opacity in the lungs at low-dose multidetector computed tomography: phantom and clinical study. J Comput Assist Tomogr. 2009 Jan-Feb;33(1):49-53. doi: 10.1097/RCT.0b013e31815e6291.
PubMed 19188784Dahlbom M, Hoffman EJ, Hoh CK, Schiepers C, Rosenqvist G, Hawkins RA, Phelps ME. Whole-body positron emission tomography: Part I. Methods and performance characteristics. J Nucl Med. 1992 Jun;33(6):1191-9.
PubMed 1597738Nolop KB, Rhodes CG, Brudin LH, Beaney RP, Krausz T, Jones T, Hughes JM. Glucose utilization in vivo by human pulmonary neoplasms. Cancer. 1987 Dec 1;60(11):2682-9. doi: 10.1002/1097-0142(19871201)60:113.0.co;2-h.
PubMed 3499969Brown RS, Leung JY, Kison PV, Zasadny KR, Flint A, Wahl RL. Glucose transporters and FDG uptake in untreated primary human non-small cell lung cancer. J Nucl Med. 1999 Apr;40(4):556-65.
PubMed 10210213Pieterman RM, van Putten JW, Meuzelaar JJ, Mooyaart EL, Vaalburg W, Koeter GH, Fidler V, Pruim J, Groen HJ. Preoperative staging of non-small-cell lung cancer with positron-emission tomography. N Engl J Med. 2000 Jul 27;343(4):254-61. doi: 10.1056/NEJM200007273430404.
PubMed 10911007Gupta GP, Massague J. Cancer metastasis: building a framework. Cell. 2006 Nov 17;127(4):679-95. doi: 10.1016/j.cell.2006.11.001.
PubMed 17110329Fidler IJ. The pathogenesis of cancer metastasis: the 'seed and soil' hypothesis revisited. Nat Rev Cancer. 2003 Jun;3(6):453-8. doi: 10.1038/nrc1098.
PubMed 12778135Carbone DP, Salmon JS, Billheimer D, Chen H, Sandler A, Roder H, Roder J, Tsypin M, Herbst RS, Tsao AS, Tran HT, Dang TP. VeriStrat classifier for survival and time to progression in non-small cell lung cancer (NSCLC) patients treated with erlotinib and bevacizumab. Lung Cancer. 2010 Sep;69(3):337-40. doi: 10.1016/j.lungcan.2009.11.019. Epub 2009 Dec 29.
PubMed 20036440Maheswaran S, Sequist LV, Nagrath S, Ulkus L, Brannigan B, Collura CV, Inserra E, Diederichs S, Iafrate AJ, Bell DW, Digumarthy S, Muzikansky A, Irimia D, Settleman J, Tompkins RG, Lynch TJ, Toner M, Haber DA. Detection of mutations in EGFR in circulating lung-cancer cells. N Engl J Med. 2008 Jul 24;359(4):366-77. doi: 10.1056/NEJMoa0800668. Epub 2008 Jul 2.
PubMed 18596266O'Flaherty JD, Gray S, Richard D, Fennell D, O'Leary JJ, Blackhall FH, O'Byrne KJ. Circulating tumour cells, their role in metastasis and their clinical utility in lung cancer. Lung Cancer. 2012 Apr;76(1):19-25. doi: 10.1016/j.lungcan.2011.10.018. Epub 2011 Dec 29.
PubMed 22209049Nieva J, Wendel M, Luttgen MS, Marrinucci D, Bazhenova L, Kolatkar A, Santala R, Whittenberger B, Burke J, Torrey M, Bethel K, Kuhn P. High-definition imaging of circulating tumor cells and associated cellular events in non-small cell lung cancer patients: a longitudinal analysis. Phys Biol. 2012 Feb;9(1):016004. doi: 10.1088/1478-3975/9/1/016004. Epub 2012 Feb 3.
PubMed 22306961Wu CY, Lee CL, Wu CF, Fu JY, Yang CT, Wen CT, Liu YH, Liu HP, Hsieh JC. Circulating Tumor Cells as a Tool of Minimal Residual Disease Can Predict Lung Cancer Recurrence: A longitudinal, Prospective Trial. Diagnostics (Basel). 2020 Mar 6;10(3):144. doi: 10.3390/diagnostics10030144.
PubMed 32155787
Study at a glance
From the registry record, last updated by the sponsor on 16 Feb 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Utilizing Perioperative Variation Trends of Circulating Tumor Cells and Tumor Pathological Characteristics as a Combined Relapse Prediction Model for Resectable Non-Small Cell Patients - a Prospective Clinical Feasibility Trial
- ClinicalTrials.gov ID
- NCT06262386
- Acronym / sponsor ID
- 202202172B0
- Conditions
- Lung Cancer, Relapse/Recurrence
- Keywords
- Circulating tumor cell, resectable non-small cell lung cancer, Early relapse
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 358 participants (estimated)
- Lead sponsor
- Chang Gung Memorial HospitalUniversity, hospital or other
- Collaborators
- National Science and Technology Council
- Study start
- 1 Aug 2023 (actual)
- Primary completion
- 31 Jul 2028 (estimated)
- Study completion
- 31 Jul 2028 (estimated)
- First posted
- 16 Feb 2024 (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.
For patients with lung cancer who have undergone tumor resection, early relapse significantly impacts survival. However, there are currently no reliable screening or imaging tools available to identify patients at risk of early relapse. To address this clinical challenge, many studies have focused on understanding the clinicopathologic characteristics associated with an increased risk of early relapse. Despite these efforts, we can identify patients at risk but cannot pinpoint which individuals will actually experience early relapse. Studies on adjuvant therapy have shown improved survival in cases of more advanced disease but have not demonstrated a reduction in early relapse rates.
In our preliminary analysis of previous study data, we observed that patients with a smaller reduction in circulating tumor cells (CTCs) within the first three days after surgery, followed by an increase on the third-day post-operation, are more likely to experience early relapse during regular monitoring. This pattern may be indicative of minimal residual disease. By combining trends in circulating tumor cell variations with pathologic characteristics, we aim to select patients for adjuvant therapy who are at high risk of developing early relapse.
The objective of our study is to employ screening based on circulating tumor cell dynamics and pathologic features to identify patients likely to experience early relapse and to assess the effectiveness of adjuvant therapy in these cases.
Detailed description
For patients with resectable lung cancer, anatomic resection alongside mediastinal lymph node dissection is pivotal in removing all tumor tissue visible on imaging from the patient's body. Despite these efforts, early relapse remains a significant issue. Literature review shows that the early relapse rate varies between 8 to 10%, potentially due to undetectable occult metastasis by imaging modalities, suggesting the presence of minimal residual disease or tumor cells evading the primary site. Limitations in imaging, such as the slice thickness in computed tomography (CT) scans, which range from 0.375 to 0.5 centimeters, can render tumors smaller than the slice thickness invisible. Similarly, tumors smaller than 0.5 cm may not accumulate sufficient F18-Deoxyglucose to be detectable in positron emission tomography (PET) scans. Additionally, tumor cells may migrate to extrapulmonary sites via lymphatic drainage or circulation.
Survival studies have predominantly focused on the pathologic TNM stage, which aggregates different disease presentations with similar survival outcomes. However, the heterogeneity inherent in pathology may help in identifying patients prone to relapse. From a tumor biology perspective, tumor cells may detach from surrounding tissues, becoming more invasive and entering the bloodstream. Circulating tumor cells (CTCs) have been recognized early in cancer stages and are correlated with treatment response, tumor genetic alterations, and survival. Research has combined CT tumor size and CTCs in a malignancy prediction model for suspicious pulmonary lesions, highlighting that CTCs can rebound in patients experiencing early relapse, indicating occult metastases or minimal residual disease.
Systemic adjuvant therapy is considered the best approach to minimize disease relapse in resectable lung cancer patients. Although many studies have sought to identify patients at risk of relapse to improve survival, the presence of intrapulmonary (N1) or mediastinal (N2) lymph node invasion significantly affects survival in non-small cell lung cancer patients. Even tumors smaller than 1 cm carry a risk of lymph node metastases, with respective risks for cT1a, cT1b, and cT1c tumors reported as 3.8%, 16.3%, and 19.6%. Therefore, patients with tumors larger than 1 cm are recommended adjuvant therapy due to the high risk of lymph node involvement. Adjuvant chemotherapy is advised for patients with stages 1b to 3a, showing a 5.4% survival benefit by the fifth postoperative year, although this benefit diminishes in subsequent years. This could be due to adjuvant therapy being administered based on the pathologic stage rather than the likelihood of relapse. Tumor heterogeneity might also influence the response to different therapeutic regimens. Molecular profiling of tumors has identified mutations predicting responses to targeted therapies and elucidated drug resistance mechanisms, offering more precise treatments and improving survival. Targeted and immune therapies have shown improved survival in specific tumor subgroups.
This study aims to utilize trends in CTC variations as a screening tool to identify patients at risk of relapse and prescribe adjuvant therapy to evaluate the therapeutic efficacy and survival impact of CTCs.
Study design
- Primary purpose
- Other
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Patient at risk for disease relapse after surgery | Experimental | Drug: Cisplatin based chemottherapy1. we utilized a relapse prediction model that combined perioperative variation trends of circulating tumor cells and pathologic characteristics that were collated with relapse 1. circulating tumor cell variation trend: difference between the CTC count on post-operation day 3 and day 1; difference between the CTC count on post-operation day 3 and post-operation 2. pathologic staging 0-1a/ 1b-4 2. patient with high relapse for relapse * Adjuvant was recommended as NCCN guidelines recommended |
Who may qualify
- Ages
- 20 to 90 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (2 listed)
- Patients who presented with resectable disease ( Clinical stage 1a to 3a)
- Patients who received tumor resection
Key exclusion criteria (4 listed)
- Pathologic stage greater than stage 3b or 4
- Pathologic stage less than stage 1a1
- Could not complete treatment course
- Could not receive blood sampling for CTC (circulating tumor cell) or regular surveillance
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 |
|---|---|---|
| Cisplatin based chemottherapyadjuvant therapy for high risk patient | Drug | Patient at risk for disease relapse after surgery |
Primary outcome
Accuracy of proposed relapse prediction model
Time frame: follow up in 3 month-interval
1. Utilized the enrolled patients to testify proposed relapse prediction model 2. Calculated Positive prediction rate, Negative prediction rate, accuracy 3. Goal: high positive prediction rate, lower negative prediction rate, high accuracy
early relapse rate
Time frame: follow up in 3 month-interval
1. adjuvant therapy based on proposed relapse prediction model * calculate the early relapse rate (relapse within 3 years) 2. utilized historical cohort as historical control (cohort that utilized to establish proposed relapse prediction model * adjuvant therapy based on TNM stage * calculate the early relapse rate (relapse within 3 years) * follow up Chest CT/ CTC in 3-month interval
1 secondary outcome
Overall surveival
Time frame: follow up in 3 month-interval
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 16 Feb 2024.
- Results publication: PubMed 26448022Wu CY, Fu JY, Wu CF, Liu YH, Hsieh MJ, Wu YC, Yang CT, Tsai YH. Pathologic Stage of Nonsmall Cell Lung Cancer Patients Presenting as Resectable Cases After Neoadjuvant Therapy Did Not Predict the Prognosis. Medicine (Baltimore). 2015 Oct;94(40):1. doi: 10.1097/MD.0000000000001700.
- Results publication: PubMed 17664593Boedeker KL, Cooper VN, McNitt-Gray MF. Application of the noise power spectrum in modern diagnostic MDCT: part I. Measurement of noise power spectra and noise equivalent quanta. Phys Med Biol. 2007 Jul 21;52(14):4027-46. doi: 10.1088/0031-9155/52/14/002. Epub 2007 Jun 8.
- Results publication: PubMed 29753514Sun F, Xi J, Zhan C, Yang X, Wang L, Shi Y, Jiang W, Wang Q. Ground glass opacities: Imaging, pathology, and gene mutations. J Thorac Cardiovasc Surg. 2018 Aug;156(2):808-813. doi: 10.1016/j.jtcvs.2018.02.110. Epub 2018 Apr 13.
- Results publication: PubMed 19188784Funama Y, Awai K, Liu D, Oda S, Yanaga Y, Nakaura T, Kawanaka K, Shimamura M, Yamashita Y. Detection of nodules showing ground-glass opacity in the lungs at low-dose multidetector computed tomography: phantom and clinical study. J Comput Assist Tomogr. 2009 Jan-Feb;33(1):49-53. doi: 10.1097/RCT.0b013e31815e6291.
- Results publication: PubMed 1597738Dahlbom M, Hoffman EJ, Hoh CK, Schiepers C, Rosenqvist G, Hawkins RA, Phelps ME. Whole-body positron emission tomography: Part I. Methods and performance characteristics. J Nucl Med. 1992 Jun;33(6):1191-9.
- Results publication: PubMed 3499969Nolop KB, Rhodes CG, Brudin LH, Beaney RP, Krausz T, Jones T, Hughes JM. Glucose utilization in vivo by human pulmonary neoplasms. Cancer. 1987 Dec 1;60(11):2682-9. doi: 10.1002/1097-0142(19871201)60:113.0.co;2-h.
- Results publication: PubMed 10210213Brown RS, Leung JY, Kison PV, Zasadny KR, Flint A, Wahl RL. Glucose transporters and FDG uptake in untreated primary human non-small cell lung cancer. J Nucl Med. 1999 Apr;40(4):556-65.
- Results publication: PubMed 10911007Pieterman RM, van Putten JW, Meuzelaar JJ, Mooyaart EL, Vaalburg W, Koeter GH, Fidler V, Pruim J, Groen HJ. Preoperative staging of non-small-cell lung cancer with positron-emission tomography. N Engl J Med. 2000 Jul 27;343(4):254-61. doi: 10.1056/NEJM200007273430404.
- Results publication: PubMed 17110329Gupta GP, Massague J. Cancer metastasis: building a framework. Cell. 2006 Nov 17;127(4):679-95. doi: 10.1016/j.cell.2006.11.001.
- Results publication: PubMed 12778135Fidler IJ. The pathogenesis of cancer metastasis: the 'seed and soil' hypothesis revisited. Nat Rev Cancer. 2003 Jun;3(6):453-8. doi: 10.1038/nrc1098.
- Results publication: PubMed 20036440Carbone DP, Salmon JS, Billheimer D, Chen H, Sandler A, Roder H, Roder J, Tsypin M, Herbst RS, Tsao AS, Tran HT, Dang TP. VeriStrat classifier for survival and time to progression in non-small cell lung cancer (NSCLC) patients treated with erlotinib and bevacizumab. Lung Cancer. 2010 Sep;69(3):337-40. doi: 10.1016/j.lungcan.2009.11.019. Epub 2009 Dec 29.
- Results publication: PubMed 18596266Maheswaran S, Sequist LV, Nagrath S, Ulkus L, Brannigan B, Collura CV, Inserra E, Diederichs S, Iafrate AJ, Bell DW, Digumarthy S, Muzikansky A, Irimia D, Settleman J, Tompkins RG, Lynch TJ, Toner M, Haber DA. Detection of mutations in EGFR in circulating lung-cancer cells. N Engl J Med. 2008 Jul 24;359(4):366-77. doi: 10.1056/NEJMoa0800668. Epub 2008 Jul 2.
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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.
Ching-Yang Wu principal investigator
Chang Gung Memorial Hospital
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Cisplatin based chemottherapy in people with Lung Cancer and Relapse/Recurrence, run by Chang Gung Memorial Hospital at 1 site in Taiwan.
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 2 inclusion and 4 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 16 Feb 2024. 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 Taiwan. 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 Ching-Yang Wu (+886975368204, wu.chingyang@gmail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Accuracy of proposed relapse prediction model (time frame: follow up in 3 month-interval). The study lists 2 primary outcomes in all. 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 NCT06262386, which also lists 35 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 16 Feb 2024.