Non-small Cell Lung CancerNCT02851329
Therapeutic Resistance Prediction of Tyrosine Kinase Inhibitors
An observational study of Non-small Cell Lung Cancer, run by Chinese Academy of Sciences at 1 site in China.
Trial summary
The investigators propose a non-invasive prognostic tool for TKIs resistance in patients with stage IV EGFR-mutant non-small cell lung cancer (NSCLC) by computed tomography phenotypic features, which can be conveniently translated to facilitate the pre-therapy individualized management of EGFR TKIs in this disease. Read more about this study
- Who is it for?
- Ages 20 years and olderHealthy volunteers can take part
- Conditions the study is for
- Non-small Cell Lung Cancer
- How many people
- 500 participants
- Where
- 1 siteChina
- Study dates
- Feb 2015to Jul 2017
- Phase
- Observational
- Are there results?
- None posted in the registry
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 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: Currently, a cohort of 300 patients has already been collected from the collaborating hospitals. Next, the 3 hospitals will collect at least 200 patients within 1 years.
Who may be able to join
- Eligible patients were diagnosed with NSCLC, and stage IV according to the TNM system classification of the American Joint Committee on Cancer.
- Presence of activating EGFR mutations.
- Age 20 years or older, and no history of systemic anticancer therapy for advanced disease.
- Patients who underwent first-line or second-line EGFR TKIs were eligible for inclusion.
- All patients had to be capable of undergoing contrast-enhanced CT, and pretreatment CT was strictly controlled in two weeks before the EGFR TKIs starts.
Who cannot join
- Based on the criteria above, patients who underwent resection for local advanced or metastatic disease were withdrawn from the study.
Trial locations and contacts
1 site in 1 country.
China1 site
Key Laboratory of Molecular Imaging, Chinese Academy of Sciences
Beijing, Beijing Municipality, 100190
About this study
Official title: Association of Computed Tomography Phenotypic Signature With Progression-free Survival in Stage IV EGFR-mutant Non-small Cell Lung Cancer Undergoing Tyrosine Kinase Inhibitors
The investigators propose a non-invasive prognostic tool for TKIs resistance in patients with stage IV EGFR-mutant non-small cell lung cancer (NSCLC) by computed tomography phenotypic features, which can be conveniently translated to facilitate the pre-therapy individualized management of EGFR TKIs in this disease.
Read the detailed description
The investigators develop a multi-CT-phenotypic-feature-based classifier to predict TKI benefit and therapeutic resistance for stage IV EGFR-mutant non-small cell lung cancer (NSCLC). The investigators also compared its prognostic and predictive efficacy with single features and clinicopathological risk factors. An individualized nomogram integrated the classifier and three clinicopathological risk factors was built for clinical use. The prognostic accuracy of the proposed model was evaluated in two independent validation sets.
Nearly 500 patients will be enrolled in this clinical trial. Eligible patients were diagnosed with NSCLC, and stage IV according to the TNM system classification of the American Joint Committee on Cancer, presence of activating EGFR mutations, age 20 years or older, and no history of systemic anticancer therapy for advanced disease. Patients who underwent first-line or second-line EGFR TKIs were eligible for inclusion. All patients had to be capable of undergoing contrast-enhanced CT, and pretreatment CT was strictly controlled in two weeks before the EGFR TKIs starts. Patients who underwent resection for local advanced or metastatic disease were withdrawn from the study.
Therapeutic resistance was measured by PFS, as the time from the initiation of EGFR TKIs therapy to the date of confirmed disease progression or death. PFS was censored at the date of death from other causes, or the date of the last follow-up visit for progression-free patients.
The investigators will use extracted 1000 phenotypic features on the region of interest manually segmented by radiologists. The Lasso Cox regression model and Nomogram will be used to build a prognosis model for the therapeutic resistance prediction of EGFR TKIs for stage IV EGFR-mutant NSCLC. The Harrell's concordance index(C-index) of the proposed nomogram will be used to quantify the discrimination performance.
- Conditions
- Non-small Cell Lung Cancer
- Keywords
- stage IV EGFR-mutant, EGFR TKIs, progression-free survival, prognosis, computed tomography
- Medical subject headings
- Carcinoma, Non-Small-Cell Lung
What is being measured
The primary outcome is the main question the study is designed to answer.
progression-free survival
Measured: 3 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted1 Aug 2016 (estimated)
- Study startFeb 2015
- Primary completionMar 2017 (estimated)
- Study completionJul 2017 (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 Non-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
- Retrospective
- Enrolment
- 500 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Chinese Academy of Sciences
- Sponsor type
- Other government
- Collaborators
- Guangdong Academy of Medical Sciences, West China Hospital, Shanghai Pulmonary Hospital, Shanghai, China
- Responsible party
- Principal investigator, Chongwei Chi, Ph.D, Chinese Academy of Sciences
- Investigators
- Jiangdian Song, Ph.D., Principal investigator, CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT02851329
- Sponsor's protocol ID
- 20160728TRPN
- Status last verified
- Jan 2017
- First submitted
- 28 Jul 2016
- Last updated
- 19 Jan 2017
- Results posted
- No
- Data monitoring committee
- No
- Individual data sharing
- Undecided
Publications
Crystal AS, Shaw AT, Sequist LV, Friboulet L, Niederst MJ, Lockerman EL, Frias RL, Gainor JF, Amzallag A, Greninger P, Lee D, Kalsy A, Gomez-Caraballo M, Elamine L, Howe E, Hur W, Lifshits E, Robinson HE, Katayama R, Faber AC, Awad MM, Ramaswamy S, Mino-Kenudson M, Iafrate AJ, Benes CH, Engelman JA. Patient-derived models of acquired resistance can identify effective drug combinations for cancer. Science. 2014 Dec 19;346(6216):1480-6. doi: 10.1126/science.1254721. Epub 2014 Nov 13.
PubMed 25394791Seto T, Kato T, Nishio M, Goto K, Atagi S, Hosomi Y, Yamamoto N, Hida T, Maemondo M, Nakagawa K, Nagase S, Okamoto I, Yamanaka T, Tajima K, Harada R, Fukuoka M, Yamamoto N. Erlotinib alone or with bevacizumab as first-line therapy in patients with advanced non-squamous non-small-cell lung cancer harbouring EGFR mutations (JO25567): an open-label, randomised, multicentre, phase 2 study. Lancet Oncol. 2014 Oct;15(11):1236-44. doi: 10.1016/S1470-2045(14)70381-X. Epub 2014 Aug 27.
PubMed 25175099Lambin P, van Stiphout RG, Starmans MH, Rios-Velazquez E, Nalbantov G, Aerts HJ, Roelofs E, van Elmpt W, Boutros PC, Granone P, Valentini V, Begg AC, De Ruysscher D, Dekker A. Predicting outcomes in radiation oncology--multifactorial decision support systems. Nat Rev Clin Oncol. 2013 Jan;10(1):27-40. doi: 10.1038/nrclinonc.2012.196. Epub 2012 Nov 20.
PubMed 23165123Balachandran VP, Gonen M, Smith JJ, DeMatteo RP. Nomograms in oncology: more than meets the eye. Lancet Oncol. 2015 Apr;16(4):e173-80. doi: 10.1016/S1470-2045(14)71116-7.
PubMed 25846097Miller VA, Hirsh V, Cadranel J, Chen YM, Park K, Kim SW, Zhou C, Su WC, Wang M, Sun Y, Heo DS, Crino L, Tan EH, Chao TY, Shahidi M, Cong XJ, Lorence RM, Yang JC. Afatinib versus placebo for patients with advanced, metastatic non-small-cell lung cancer after failure of erlotinib, gefitinib, or both, and one or two lines of chemotherapy (LUX-Lung 1): a phase 2b/3 randomised trial. Lancet Oncol. 2012 May;13(5):528-38. doi: 10.1016/S1470-2045(12)70087-6. Epub 2012 Mar 26.
PubMed 22452896
Study at a glance
From the registry record, last updated by the sponsor on 19 Jan 2017. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Association of Computed Tomography Phenotypic Signature With Progression-free Survival in Stage IV EGFR-mutant Non-small Cell Lung Cancer Undergoing Tyrosine Kinase Inhibitors
- ClinicalTrials.gov ID
- NCT02851329
- Acronym / sponsor ID
- 20160728TRPN
- Conditions
- Non-small Cell Lung Cancer
- Keywords
- stage IV EGFR-mutant, EGFR TKIs, progression-free survival, prognosis, computed tomography
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 500 participants (estimated)
- Lead sponsor
- Chinese Academy of SciencesOther government
- Collaborators
- Guangdong Academy of Medical Sciences, West China Hospital, Shanghai Pulmonary Hospital, Shanghai, China
- Study start
- Feb 2015
- Primary completion
- Mar 2017 (estimated)
- Study completion
- Jul 2017 (estimated)
- First posted
- 1 Aug 2016 (estimated)
- 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.
The investigators propose a non-invasive prognostic tool for TKIs resistance in patients with stage IV EGFR-mutant non-small cell lung cancer (NSCLC) by computed tomography phenotypic features, which can be conveniently translated to facilitate the pre-therapy individualized management of EGFR TKIs in this disease.
Detailed description
The investigators develop a multi-CT-phenotypic-feature-based classifier to predict TKI benefit and therapeutic resistance for stage IV EGFR-mutant non-small cell lung cancer (NSCLC). The investigators also compared its prognostic and predictive efficacy with single features and clinicopathological risk factors. An individualized nomogram integrated the classifier and three clinicopathological risk factors was built for clinical use. The prognostic accuracy of the proposed model was evaluated in two independent validation sets.
Nearly 500 patients will be enrolled in this clinical trial. Eligible patients were diagnosed with NSCLC, and stage IV according to the TNM system classification of the American Joint Committee on Cancer, presence of activating EGFR mutations, age 20 years or older, and no history of systemic anticancer therapy for advanced disease. Patients who underwent first-line or second-line EGFR TKIs were eligible for inclusion. All patients had to be capable of undergoing contrast-enhanced CT, and pretreatment CT was strictly controlled in two weeks before the EGFR TKIs starts. Patients who underwent resection for local advanced or metastatic disease were withdrawn from the study.
Therapeutic resistance was measured by PFS, as the time from the initiation of EGFR TKIs therapy to the date of confirmed disease progression or death. PFS was censored at the date of death from other causes, or the date of the last follow-up visit for progression-free patients.
The investigators will use extracted 1000 phenotypic features on the region of interest manually segmented by radiologists. The Lasso Cox regression model and Nomogram will be used to build a prognosis model for the therapeutic resistance prediction of EGFR TKIs for stage IV EGFR-mutant NSCLC. The Harrell's concordance index(C-index) of the proposed nomogram will be used to quantify the discrimination performance.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
Who may qualify
- Ages
- 20 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- Currently, a cohort of 300 patients has already been collected from the collaborating hospitals. Next, the 3 hospitals will collect at least 200 patients within 1 years.
Key inclusion criteria (5 listed)
- Eligible patients were diagnosed with NSCLC, and stage IV according to the TNM system classification of the American Joint Committee on Cancer.
- Presence of activating EGFR mutations.
- Age 20 years or older, and no history of systemic anticancer therapy for advanced disease.
- Patients who underwent first-line or second-line EGFR TKIs were eligible for inclusion.
- All patients had to be capable of undergoing contrast-enhanced CT, and pretreatment CT was strictly controlled in two weeks before the EGFR TKIs starts.
Key exclusion criteria (1 listed)
- Based on the criteria above, patients who underwent resection for local advanced or metastatic disease were withdrawn from the study.
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
progression-free survival
Time frame: 3 years
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 19 Jan 2017.
- Background: PubMed 25394791Crystal AS, Shaw AT, Sequist LV, Friboulet L, Niederst MJ, Lockerman EL, Frias RL, Gainor JF, Amzallag A, Greninger P, Lee D, Kalsy A, Gomez-Caraballo M, Elamine L, Howe E, Hur W, Lifshits E, Robinson HE, Katayama R, Faber AC, Awad MM, Ramaswamy S, Mino-Kenudson M, Iafrate AJ, Benes CH, Engelman JA. Patient-derived models of acquired resistance can identify effective drug combinations for cancer. Science. 2014 Dec 19;346(6216):1480-6. doi: 10.1126/science.1254721. Epub 2014 Nov 13.
- Background: PubMed 25175099Seto T, Kato T, Nishio M, Goto K, Atagi S, Hosomi Y, Yamamoto N, Hida T, Maemondo M, Nakagawa K, Nagase S, Okamoto I, Yamanaka T, Tajima K, Harada R, Fukuoka M, Yamamoto N. Erlotinib alone or with bevacizumab as first-line therapy in patients with advanced non-squamous non-small-cell lung cancer harbouring EGFR mutations (JO25567): an open-label, randomised, multicentre, phase 2 study. Lancet Oncol. 2014 Oct;15(11):1236-44. doi: 10.1016/S1470-2045(14)70381-X. Epub 2014 Aug 27.
- Background: PubMed 23165123Lambin P, van Stiphout RG, Starmans MH, Rios-Velazquez E, Nalbantov G, Aerts HJ, Roelofs E, van Elmpt W, Boutros PC, Granone P, Valentini V, Begg AC, De Ruysscher D, Dekker A. Predicting outcomes in radiation oncology--multifactorial decision support systems. Nat Rev Clin Oncol. 2013 Jan;10(1):27-40. doi: 10.1038/nrclinonc.2012.196. Epub 2012 Nov 20.
- Background: PubMed 25846097Balachandran VP, Gonen M, Smith JJ, DeMatteo RP. Nomograms in oncology: more than meets the eye. Lancet Oncol. 2015 Apr;16(4):e173-80. doi: 10.1016/S1470-2045(14)71116-7.
- Background: PubMed 22452896Miller VA, Hirsh V, Cadranel J, Chen YM, Park K, Kim SW, Zhou C, Su WC, Wang M, Sun Y, Heo DS, Crino L, Tan EH, Chao TY, Shahidi M, Cong XJ, Lorence RM, Yang JC. Afatinib versus placebo for patients with advanced, metastatic non-small-cell lung cancer after failure of erlotinib, gefitinib, or both, and one or two lines of chemotherapy (LUX-Lung 1): a phase 2b/3 randomised trial. Lancet Oncol. 2012 May;13(5):528-38. doi: 10.1016/S1470-2045(12)70087-6. Epub 2012 Mar 26.
- Individual participant dataSharing planned: Undecided
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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.
Jiangdian Song, Ph.D. principal investigator
CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences
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 Non-small Cell Lung Cancer, run by Chinese Academy of 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 5 inclusion and 1 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: status not confirmed, as of the sponsor's last update on 19 Jan 2017. 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?
Results are not available in the source record.
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?
progression-free survival (time frame: 3 years). 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 NCT02851329, 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 19 Jan 2017.