The goal of this study is to find out whether a system that uses trained detection dogs and artificial intelligence (AI) can identify breast cancer from a person's breath. Women who are scheduled to have routine breast cancer screening, such as a mammogram, ultrasound, or a biopsy for a possible cancer, will be invited to take part. Participants will be asked to breathe into a surgical mask to collect a breath sample. The mask will be sent to a special laboratory, where trained dogs and an AI-based system will check the sample for signs of breast cancer. The results from the dogs and AI will be compared to the actual results from the medical screening or biopsy to see how accurate the system is at detecting breast cancer.
Study Type
OBSERVATIONAL
Enrollment
1,204
Breath sample collection using a sample collection kit
Hackensack Meridian Health
Totowa, New Jersey, United States
RECRUITINGRambam Health Care Campus
Haifa, Israel
RECRUITINGSheba Medical Center
Ramat Gan, Israel
RECRUITINGAssuta Medical Centers
Tel Aviv, Israel
RECRUITINGTel Aviv Sourasky Medical Center
Tel Aviv, Israel
RECRUITINGTest Performance Evaluation
The test performance will be determined by analysis of the sensitivity and the specificity of the primary endpoint sample set, where sensitivity is the number of participants with a true positive result divided by the number of participants with a positive clinical diagnosis (positive biopsy), and specificity is the number of participants with a true negative result divided by the number of participants with a negative clinical diagnosis.
Time frame: 24 months
Test Performance Evaluation in different subgroups
Sensitivity and specificity of the SpotitEarly test will be measured and compared in each of the subgroups: * Age: under 40, 40-49, 50-64, 65 and older. * Race: White, Black/African American, Asian. * Ethnicity: hispanic vs. non hispanic * Germline pathogenic variant carriers associated with high risk for breast cancer versus non carriers. * Smoking status: smokers versus nonsmokers. * Women with type-2 diabetes versus not diagnosed with type-2 diabetes Sensitivity is the number of participants with a true positive result divided by the number of participants with a positive clinical diagnosis (positive biopsy). Specificity is the number of participants with a true negative result divided by the number of participants with a negative clinical diagnosis.
Time frame: 24 months
Test Performance in early-stage cancer
To evaluate the performance (sensitivity and specificity) of the SpotitEarly test in detecting early-stage breast cancer (stages 0-2). Sensitivity is the number of participants with a true positive result divided by the number of participants with a positive clinical diagnosis (positive biopsy). Specificity is the number of participants with a true negative result divided by the number of participants with a negative clinical diagnosis.
Time frame: 24 months
Test Performance in the clinic vs. at patients' home
To evaluate the performance (sensitivity and specificity, as described in 3.4) of the SpotitEarly test over samples provided by participants at their home. Sensitivity is the number of participants with a true positive result divided by the number of participants with a positive clinical diagnosis (positive biopsy). Specificity is the number of participants with a true negative result divided by the number of participants with a negative clinical diagnosis.
Time frame: 24 months
Effect of psychological impacts on performance in the enriched arm
To assess whether the performance (sensitivity and specificity) of the SpotitEarly test is affected by the subject's psychological impacts (anxiety is assumed for all arm 2 subjects who are undergoing a biopsy). Sensitivity is the number of participants with a true positive result divided by the number of participants with a positive clinical diagnosis (positive biopsy). Specificity is the number of participants with a true negative result divided by the number of participants with a negative clinical diagnosis.
Time frame: 12 months
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