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The test detects the presence of two biomarkers within a single cell associated with HPV infections that can progress to cervical cancer.
The expanded test can be used for genotype risk-based patient monitoring to prevent over-treatment, BD has said.
The researchers are developing an automated machine-learning approach to analyze the expression of protein markers associated with cervical cancer.
The peer-reviewed study assessed sensitivity rates of HPV testing alone, Pap testing alone, and cotesting with both HPV and Pap tests.
The test, which is used to screen for cervical cancer, was previously approved by the agency for use with the Cobas 4800 system.
The biomarker-based test determines women whose human papillomavirus infections are most likely to be associated with cervical pre-cancers.
The system showed good performance for cervical samples as well as orophyrengeal samples, and required no extraction step.
The assay, which received premarket approval last year, detects 14 high-risk HPV types and individually identifies and reports HPV genotypes 16, 18, and 45.
The new test uses the number of sequencing reads at specific early and late HPV transcripts as a biomarker for high-grade cytology.
The system has been evaluated by researchers studying cervical cancer prevention as well as other HPV-related cancers, with positive feedback so far.