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Updated: Mar 5, 2026

Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer
Published on: November 2, 2013
Genomic Classifier Augments the Role of Pathological Features in Identifying Optimal Candidates for Adjuvant
Deepansh Dalela1, María Santiago-Jiménez1, Kasra Yousefi1
1Deepansh Dalela, Mani Menon, and Firas Abdollah, Henry Ford Health System, Detroit, MI; María Santiago-Jiménez, Kasra Yousefi, and Elai Davicioni, GenomeDx Biosciences, Vancouver, British Columbia, Canada; R. Jeffrey Karnes, Mayo Clinic, Rochester, MN; Ashley E. Ross, Johns Hopkins Hospital, Baltimore, MD; Adam P. Dicker and Robert B. Den, Thomas Jefferson University, Philadelphia, PA; Stephen J. Freedland, Cedars-Sinai Medical Center, Los Angeles, CA; Edward M. Schaeffer, Northwestern University Feinberg School of Medicine, Chicago, IL; and Alberto Briganti, Vita Salute San Raffaele Hospital, Milan, Italy.
Abstract:
Purpose Despite documented oncologic benefit, use of postoperative adjuvant radiotherapy (aRT) in patients with prostate cancer is still limited in the United States. We aimed to develop and internally validate a risk-stratification tool incorporating the Decipher score, along with routinely available clinicopathologic features, to identify patients who would benefit the most from aRT. Patient and Methods Our cohort included 512 patients with prostate cancer treated with radical prostatectomy at one of four US academic centers between 1990 and 2010. All patients had ≥ pT3a disease, positive surgical margins, and/or pathologic lymph node invasion. Multivariable Cox regression analysis tested the relationship between available predictors (including Decipher score) and clinical recurrence (CR), which were then used to develop a novel risk-stratification tool. Our study adhered to the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis guidelines for development of prognostic models. Results Overall, 21.9% of patients received aRT. Median follow-up in censored patients was 8.3 years. The 10-year CR rate was 4.9% vs. 17.4% in patients treated with aRT versus initial observation ( P < .001). Pathologic T3b/T4 stage, Gleason score 8-10, lymph node invasion, and Decipher score > 0.6 were independent predictors of CR (all P < .01). The cumulative number of risk factors was 0, 1, 2, and 3 to 4 in 46.5%, 28.9%, 17.2%, and 7.4% of patients, respectively. aRT was associated with decreased CR rate in patients with two or more risk factors (10-year CR rate 10.1% in aRT v 42.1% in initial observation; P = .012), but not in those with fewer than two risk factors ( P = .18). Conclusion Using the new model to indicate aRT might reduce overtreatment, decrease unnecessary adverse effects, and reduce risk of CR in the subset of patients (approximately 25% of all patients with aggressive pathologic disease in our cohort) who benefit from this therapy.
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