DESCRIPTION OF THE PANEL
PAULA’s Test measures a panel of four biomarkers including a group of three tumor antigens and one tumor autoantibody. Each tumor antigen in our test, both individually and as a panel, has been extensively studied by numerous investigators. Dozens of peer reviewed scientific publications support the validity of these antigens as biomarkers for early lung cancer. The novelty of our test includes proprietary scoring algorithms and methodology as well as the combination of testing at least one autoantibody with tumor antigens.
WHY A COMBINATION OF ANTIGENS AND AUTOANTIBODIES?
Analysis of a multiplex biomarker panel increases the test sensitivity and specificity thereby reducing false positives and negatives. Tumors produce antigens, and the body mounts an immune response to those antigens at the earliest stages. Our algorithm combines the values for each of the biomarkers to give a score that indicates the probability that a patient has lung cancer.
TYPES AND SUBTYPES OF LUNG CANCER DETECTED
PAULA’s Test is used to detect non-small cell lung cancer which includes adenocarcinoma, squamous cell carcinoma, and large cell carcinoma.
PAULS’S TEST SENSITIVITY & SPECIFICITY
20/20 GeneSystems has recently published a peer reviewed PAPER describing the development of PAULA’S test
PAULA’S Test SENSITIVITY: 74%
The sensitivity of PAULA’s Test is 74% when the specificity is set at 80%. For examples if there is a group of 1,000 high-risk patients, about 2% (20) will have lung cancer. Of that group, 15 of the 20 cancers will test positive using PAULA’s Test. A specificity of 80% means that 200 patients without lung cancer will also test positive.
Specificity is defined as the number of patients who test negative in the absence of disease divided by the total number of patients who do not have disease. The specificity of PAULAs Test is 80% when the sensitivity is 74%. For examples if there is a group of 1000 high-risk patients, about 98% or 980 will not have lung cancer. Of that group, about 780 will test negative for PAULA’s Test and about 5 of the patients with lung cancer will also test negative. The test results are generated from an algorithm that combines results from all four biomarkers. The score is then assigned as high or Low risk. Patients are then directed to LDCT based on their risk score and their initial clinical history.
POSITIVE PREDICTIVE VALUE (PPV)
The positive predictive value, defined as TP/(TP+FP), is 8.3%, i.e. out of 100 positive results, 8.3% have lung cancer.
NEGATIVE PREDICTIVE VALUE (NPV)
The negative predictive value, defined as TN/(TN+FN), is 99.3%, i.e. if a patient has a lower risk score there is a 99.3% chance that this patient does NOT have lung cancer.