TissueCypher is cost-saving after 5 years and improves patient outcomes due to improving the effectiveness of surveillance and treatment.

Prospective analysis reporting long-term outcomes for patients tested with DecisionDx-Melanoma (follow-up to study first published as Hsueh, 2017).

Independent, prospective study with over 3.5 years of follow-up, showing results consistent with previous validation studies with GEP class score as statistically associated with MSS, DMFS and RFS.

Histological review of community-based LGD showed a high inter-observer variability with a signification number of cases classified as non-informative.

To develop and validate a gene expression profile (GEP) test for predicting risk for metastasis in localized, high-risk cSCC with the goal of improving risk-directed patient management.

The risk prediction assay provided significant risk stratification in BE patients with LGD and identified progressors that the experts downstaged to NDBE.

Although most patients with cutaneous melanoma (CM) will have a negative sentinel lymph node biopsy (SLNB), up to 20%-30% of these patients will recur. The 31-gene expression profile (31-GEP) test has been prospectively validated to identify patients at low (Class 1A), intermediate (Class 1B/2A), and high (Class 2B) risk of SLN positivity and recurrence.

Prospective multicenter study showed that integration of 31-GEP and T stage can gain clinically useful prognostic information from data obtained noninvasively.

DecisionDx-Melanoma data significantly stratified MSS in stage I, II, and III patients. This test has also demonstrated high specificity and NPV for melanoma-specific mortality (MSM)

Clinical validation study of the 23-GEP in lesions with clinical outcomes and follow-up data

The individualized risk prediction test has the potential to improve the efficiency of endoscopic surveillance in BE and to enable early intervention as needed.

TissueCypher better predicts progression in BE than clinicopathologic variables, and can improve on histology as a method to risk stratify patients with BE