BARD1 Life Sciences Limited announced positive results from its OC-400 Study that showed BARD1-Ovarian achieved high accuracy for detection of ovarian cancer with an average AUC (area under the curve) of 0.92 in the training sets, and an average AUC of 0.88, 82% sensitivity and 79% specificity in the test sets. BARD1 has successfully completed the retrospective, case-control, OC-400 Study to evaluate the accuracy of the multi-analyte BARD1-Ovarian test to detect ovarian cancer in 400 female bio-banked samples of ovarian cancer and aged-matched healthy controls. The objectives of the study were to optimise the BARD1 panel and algorithm used in BARD1-Ovarian for early detection of ovarian cancer and to evaluate the accuracy of the test using the POC (proof-of-concept) method on a panel of 20 peptides (analytes). Data analysis generated a model with an average AUC of 0.92, 90% sensitivity and 85% specificity in the training sets, and an average AUC of 0.88, 82% sensitivity and 79% specificity in the cross-validation test sets. The results of the OC-400 Study confirmed previous study findings that BARD1-Ovarian could accurately detect ovarian cancer with high sensitivity and specificity. Importantly, these results were achieved using less analytes reducing the complexity and cost of the BARD1-Ovarian test, which may offer improved performance over the CA125 blood test that is routinely used as a diagnostic aid for ovarian cancer. The study concluded that BARD1-Ovarian accurately discriminated ovarian cancer from healthy controls using the POC method and a 20-analyte panel, could detect all subtypes and stages of ovarian cancer, and confirmed the potential of the research-grade test to be further developed into a commercial test with expected high sensitivity and specificity for early detection of ovarian cancer. BARD1 intends to advance the development of BARD1-Ovarian for early detection of ovarian cancer including outsourcing further assay development to a contract development organisation to build a commercial test, complete technical validation, and undertake clinical validation studies to demonstrate its clinical performance and support future marketing and/or licensing of the test. BARD1-Ovarian is an ELISA-based blood test in development for early detection of ovarian cancer. The test measures multiple BARD1 autoantibodies in the blood and uses a proprietary diagnostic algorithm to combine these levels into a cancer score that identifies the presence or absence of ovarian cancer. Preliminary results from pilot studies indicate the high accuracy of BARD1-Ovarian for detection of ovarian cancer with up to 92% sensitivity and 84% specificity. BARD1-Ovarian could potentially be used as a screening test for early detection of ovarian cancer in high-risk asymptomatic individuals, for risk assessment of malignancy in women with pelvic masses, or to monitor ovarian cancer recurrence. The performance of a diagnostic test can be measured by 'AUC', 'sensitivity' and 'specificity'. AUC (area under the curve) is an overall score of accuracy generated by a ROC (receiver operating characteristic) curve, where a perfect test would have an AUC=1.0, an excellent test AUC=0.9-0.99, a good test AUC=0.8-0.89, and a useless test AUC=0.5. Sensitivity is the percent of patients with cancer correctly identified positive (true positive rate) and specificity refers to the percent of patients without cancer correctly identified negative (true negative result). A good diagnostic test must demonstrate acceptable sensitivity and false positives rates for its intended use. Cross-validation is a statistical method to evaluate the predictive performance of a model. In repeated random sub-sampling cross-validation, the samples are randomly split into 3/4 training sets to train the algorithm and 1/4 test sets to evaluate the algorithm, and the process repeated 200 times. The performance of the algorithm is then evaluated by computing the average AUC, sensitivity and specificity in the test sets.