Clinical trial NCT02851329: Therapeutic Resistance Prediction of Tyrosine Kinase Inhibitors
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
Study type: OBSERVATIONAL
Overall status: UNKNOWN
Conditions: Non-small Cell Lung Cancer
Keywords: stage IV EGFR-mutant
EGFR TKIs
progression-free survival
prognosis
computed tomography
Lead sponsor: Chinese Academy of Sciences
Sponsor class: OTHER_GOV
Collaborators: name: Guangdong Academy of Medical Sciences
name: West China Hospital
name: Shanghai Pulmonary Hospital, Shanghai, China
First posted: 2016-08-01
Enrollment: 500
Sex: ALL
Minimum age (years): 20
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: COHORT
Time perspective: RETROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
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.

Brief 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.

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.

Eligibility criteria: Inclusion Criteria:

* 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.

Exclusion Criteria:

* Based on the criteria above, patients who underwent resection for local advanced or metastatic disease were withdrawn from the study.

Primary outcomes:
measure: progression-free survival
timeFrame: 3 years
Secondary outcomes:
Other outcomes:
Locations:
city: Beijing
country: China
facility: Key Laboratory of Molecular Imaging, Chinese Academy of Sciences
state: Beijing
Study officials:
affiliation: CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences
name: Jiangdian Song, Ph.D.
role: PRINCIPAL_INVESTIGATOR
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