Date: 2016-04-25
Type of information: Publication of results in a medical journal
phase:
Announcement: publication of results in European Urology.
Company: MDxHealth (Belgium)
Product: SelectMDx™ for Prostate Cancer
Action
mechanism: biomarker/diagnostic test. The novel biomarkers that make up SelectMDx were discovered by Prof. Dr. Jack Schalken, original developer of the PCA3 assay, and his team at the Department of Urology at Radboud University Medical Center in the Netherlands. The SelectMDx test was designed to address an unmet need in the stratification of patients at risk for potentially lethal high-grade prostate cancer compared to those with low-grade cancer. In clinical studies, SelectMDx has been shown to outperform PCA3, improving the information available to urologists seeking to further reduce unnecessary invasive biopsy procedures.
Disease: prostate cancer
Therapeutic area: Cancer - Oncology
Country:
Trial details:
Latest
news: * On April 25, 2016, MDxHealth announced that data validating the clinical performance of the SelectMDx™ for Prostate Cancer test have been published in European Urology. The study, conducted across six institutions in The Netherlands, was designed to identify methods to improve the detection of clinically significant or aggressive prostate cancer at an early, more treatable stage. Researchers believe that both over-diagnosis and overtreatment of indolent, non-lethal prostate cancer could be reduced if specific biomarkers, which accurately identify men with aggressive tumors, could be used to guide the decision to conduct a biopsy. * On March 14, 2016, MDxHealth announced that positive results of a prospective, multicenter validation study of SelectMDx™ for Prostate Cancer were presented at the 2016 Annual European Association of Urology (EAU) Congress, March 11-15 in Munich, Germany. The major challenge in prostate cancer (PCa) diagnostics is to improve the early detection of aggressive and potentially lethal prostate cancer. Ideally, prostate cancer-specific biomarkers could be assessed non-invasively, for example in urine. The aim of this study was to develop and validate a model that combines such biomarkers with traditional risk factors into a risk score that expresses an individual patient's risk of harboring high-grade prostate cancer.
Urine samples from two prospective, multicenter studies (n=905) were collected after digital rectal examination (DRE) to measure the mRNA expression levels of the SelectMDx genes, which were previously identified for their ability to specifically detect aggressive prostate cancer. These results were combined with standard clinical risk factors, i.e. DRE, PSA, PSA density, age and family and biopsy history to further improve patient stratification. An algorithm was developed in a training cohort, and successfully validated in an independent cohort. The SelectMDx risk score resulted in an improved identification of men at risk for harboring aggressive prostate cancer, significantly outperforming PSA and PCA3, with an area under the curve (AUC) of 0.90, and a negative predictive value (NPV) of 98% for clinically significant prostate cancer. In addition, SelectMDx resulted in the highest reduction of unnecessary biopsies in men with no or indolent prostate cancer.
Urine samples from two prospective, multicenter studies (cohort A: n=492 and cohort B: n=371) were collected after digital rectal examination (DRE) to measure the mRNA expression levels of the two genes included in the SelectMDx test. These results were combined with traditional clinical risk factors, i.e. DRE, PSA, PSA density, age and family history to further improve patient stratification. An algorithm was developed in cohort A, and successfully validated in the independent cohort B. The optimal model was generated to assess the likelihood of detecting high-grade disease upon biopsy for an individual patient. The SelectMDx urinary molecular biomarker-based risk score resulted in an improved detection of men harboring high-grade PCa, with a negative predictive value (NPV) for significant cancer of 98% and an area under the curve (AUC) of 0.88.
The poster presentation, entitled 'Multicenter validation study of a urine-based molecular biomarker algorithm to predict high-grade prostate cancer' (Abstract #383), was presented by Rianne Hendriks, MD at the 'Novel Biomarkers for Prostate Cancer Prediction' session (poster session 31) and was awarded a best poster presentation out of over 1100 submitted abstracts, by EAU's Scientific Congress Office.
