Improving Detection of Early Lung Cancer in a Diverse Population (IDEAL) Study
- Conditions
- Lung CancerPulmonary Nodule
- Interventions
- Diagnostic Test: Chest CT Scan
- Registration Number
- NCT06628102
- Lead Sponsor
- British Columbia Cancer Agency
- Brief Summary
The goal of this trial is to (a) identify people at high risk of lung cancer who would benefit from LDCT screening but are currently ineligible based on current lung cancer screening criteria (b) provide the framework to manage patients with Incidental Pulmonary Nodules (IPNs) with appropriate follow-up based on accurate interpretation of the Chest CT scan that is already available and (c) develop a simple, point-of-care, minimally invasive test, focusing on the breath and circulating blood proteins, to detect lung cancer, and develop a method to differentiate between cancerous and non-cancerous nodules using a single. Participants will be asked to answer a questionnaire regarding their age, race/ethnicity, smoking history, and residential history if they have ever been told they have chronic obstructive pulmonary disease (COPD), high blood pressure, education level, medications and height and weight. Participants will then be asked to give a breath sample via the breath collection device. All this information will be collected before the breath collection. After that, participants will give 1-2 tablespoons of blood. CT scans with IPN(s) will be reviewed and run through a computer detection software to identify nodules, followed up as per current clinical guidelines.
- Detailed Description
Lung cancer continues to be the leading cause of cancer death in Canada and worldwide. Low-dose computed tomography (LDCT) screening has been shown to be a cost-effective measure to save lives in people who have smoked heavily based on several large randomized control trials. The evidence led to the implementation of LDCT lung cancer screening in Canada for people who have smoked heavily in the past or are still smoking. However, over 50% of patients who develop lung cancer today would not meet current screening eligibility criteria. A strategy to identify individuals who are not currently eligible for screening but are at high risk for lung cancer is urgently needed. Meanwhile, recent studies have shown that patients with incidental pulmonary nodules (IPNs), often do not meet LDCT screening criteria. These patients despite having a higher risk of lung cancer, the majority are never followed up in the clinical setting. This represents an important opportunity to address the emerging challenge for lung cancer early detection while addressing the missing link between IPNs and lung cancer.
Objective.
Our proposed study will have two important goals: (a) identify people at high risk of lung cancer who would benefit from LDCT screening but are currently ineligible; (b) provide the framework to manage patients with Incidental Pulmonary Nodules with appropriate follow-up based on accurate interpretation of the chest CT scan that is already available.
Specific Aims
(i) Develop the framework to assess the lung cancer risk of IPN patients; (ii) Develop and validate an exhaled breath test to identify high-risk individuals who do not meet current eligibility criteria for LDCT screening; (iii) Prospectively validate a panel of circulating blood proteins to personalize the management of incidental pulmonary nodules; (iv) Improve the accuracy and consistency of reading chest CT scans with incidental pulmonary nodules to improve lung cancer early detection; (v) Evaluate the health-economic benefits of a multi-modal approach to the management of incidental pulmonary nodules
Methods. In total, there will be 3600 participants recruited between both arms of the study.
As IPN patients represent a high-risk, screening ineligible and usually under-served population, we will establish a multi-provincial IPN cohort based on 3600 patients with IPNs from 3 provinces: British Columbia, Ontario and Quebec. For the Breathomics, we will conduct a comprehensive investigation of volatile organic compounds using state-of-the-art technology, and high-resolution accurate mass gas chromatography spectrometry. The breath signatures will be validated using pre-diagnostic breath samples in the IPN cohort and test the clinical utility with a point-of-care mobile device. We will validate the circulating protein panel prospectively and assess the absolute risk of lung cancer in the IPN cohort to establish the risk thresholds for clinical application. In parallel, we will develop a deep learning algorithm based on LDCT images to improve the classification of IPN. A health economic analysis will be performed on the clinical utility of these tools.
Significance:
The IPN population provides an untapped learning opportunity for us to improve lung cancer early detection. Identification of individuals who are not currently eligible for screening but are at high risk of lung cancer allows us to utilize artificial intelligence and other biomarkers to predict lung cancer from an already available single chest CT that is already available.
Recruitment & Eligibility
- Status
- RECRUITING
- Sex
- All
- Target Recruitment
- 3600
Age 50-80
- Able to consent
- Chest CT positive for nodule equal to or greater than 6mm
- No additional other cancer- (outside of lung cancer for group 1)
- Must be able to abstain from smoking tobacco for 24 hours prior to the breath test.
- Too sick to provide a breath sample
- you have smoked in the last 24 hours
- You are pregnant
- You have been diagnosed with a respiratory infection in the last 3 months
- Unwilling to consent to the study
Study & Design
- Study Type
- INTERVENTIONAL
- Study Design
- SINGLE_GROUP
- Arm && Interventions
Group Intervention Description Incidental Pulmonary Nodule Arm Chest CT Scan Nodule Follow up as per Fleischner Guidelines
- Primary Outcome Measures
Name Time Method Develop the framework to assess the lung cancer risk of Incidental Pulmonary Nodule patients 4 years Aim 1: Develop the framework within the Canadian context to promote the diagnosis of early-stage lung cancert hat can work synergistically with organized lung cancer screening programs to improve outcome of patients with lung cancer, using IPN population as a learning example.
1. Establish the cohorts of individuals with incidental pulmonary nodules (IPN) across 3 provinces in Canada, focused on those who do not fit current LDCT screening criteria, with a total of 3600 IPN patients with incidental pulmonary nodules at least 6mm in diameter
2. Estimate the lung cancer incidence among those with IPNs in Canada
- Secondary Outcome Measures
Name Time Method Develop and validate an exhaled breath test to identify high-risk individuals who do not meet current eligibility criteria for LDCT screening 4 years Aim 2: Develop and validate an exhaled breath test to identify high risk individuals who do not meet current eligibility criteria for LDCT screening
1. Identify the VOC signature that distinguishes early lung cancer versus non-lung cancer patients with 1:1:1 ratio of lung cancer cases, IPN patients without lung cancer, and healthy controls with frequency matching with 200 individuals in each group.
2. Prospectively validate VOC signature on IPN cohorts at 3 Canadian provinces: British Columbia, Ontario and QuebecProspectively validate a panel of circulating proteins to personalize the management of incidental pulmonary nodules 4 years Aim 3: Prospectively validate the INTEGRAL panel of blood-based biomarkers to personalize the management of incidental pulmonary nodules based on their lung cancer risk and nodule malignancy probability
1. Assay the informative circulating protein markers in the IPN cohorts
2. Estimate the absolute risk threshold based on the integrated model for IPN patients that as equivalence to heavy smokers in LDCT screening programs, and estimate nodule malignancy probability that would warrant clinical follow-up with optimized benefit-harm ratio.Improve the accuracy and consistency of reading chest CT scans with incidental pulmonary nodules to improve lung cancer early detection; 4 years Aim 4 Improve the accuracy and consistency of reading chest CT scans with incidental pulmonary nodules
1. Train a deep learning model based on multi-angled 2-dimensional and 3-dimensional approaches using 4 existing LDCT screening programs, including the National Lung Screening Study (NLST), the Early Detection of Lung Cancer - a Pan-Canadian Study (PanCan), and the International Early Lung Cancer Action Program (IELCAP)-Toronto site, and the International Lung Screening Trial (ILST), with a total of 23,200 screening participants with LDCT images available
2. Validate the deep learning model in the IPN cohort to improve the diagnostic accuracy of IPN nodulesEvaluate the health-economic benefits of a multi-modal approach to the management of incidental pulmonary nodule 4 years Aim 5: Evaluate the health economic benefits of a multi-modal approach to management of incidental pulmonary nodules
1. Measure resource use and costs relevant for decision-makers implementing the new interventions for the early detection of lung cancer
2. Estimate the effectiveness and cost-effectiveness of: the novel breath test, the INTEGRAL blood panel, the AI model for quantitative imaging analysis, compared to standard care for IPN patients
Trial Locations
- Locations (1)
BC Cancer Research, part of the Provincial Health Authority
🇨🇦Vancouver, British Columbia, Canada