Decipher may help avoid over-treatment by reclassifying those men originally identified as high-risk who are unlikely to develop metastatic disease.

Following a radical prostatectomy, up to half of men will present with pathology or clinical features that put them at high risk of recurrence1. Though considered high risk, 90% will not develop metastases or die of prostate cancer2.

This means that – if treated – these patients may receive no benefit at all. Worse, they may be subject to unnecessary complications caused by post-surgery treatment for prostate cancer.

Decipher may help avoid over-treatment by reclassifying those men originally identified as high-risk who are unlikely to develop metastatic disease.

In clinical studies of high-risk men after surgery, Decipher reclassified 60% of men to lower risk categories3. 98.5% of patients reclassified to low risk by Decipher did not develop metastasis within 5 years of radical prostatectomy.

Across multiple clinical utility studies, 39% of physicians changed patient treatment planning after reviewing Decipher results4,5, resulting in a 50% reduction in radiation therapy planning in those identified as low risk by Decipher.

References
  1. Swanson, G.P. & J.W. Basler, Prognostic factors for failure after prostatectomy. J Cancer, 2011. 2: p. 1-19.
  2. Thompson, I.M., Jr., et al., Adjuvant radiotherapy for pathologically advanced prostate cancer: a randomized clinical trial. JAMA, 2006. 296(19): p. 2329-35.
  3. Karnes, R.J., et al. Validation of a Genomic Classifier that Predicts Metastasis Following Radical Prostatectomy in an At Risk Patient Population. J Urol. 2013 Dec;190(6):2047-53.
  4. Badani, K., et al. Impact of a genomic classifier of metastatic risk on postoperative treatment recommendations for prostate cancer patients: a report from the DECIDE study group. Oncotarget 4(4): 600-609 (2013)
  5. Badani, K., et al. Effect of a 22-marker genomic classifier assay on adjuvant radiation therapy recommendations in patients with high-risk prostate cancer. BJUI (in review)