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Genomic Classifier for Guiding Treatment of Intermediate-Risk Prostate Cancers to Dose-Escalated Image Guided Radiation Therapy Without Hormone Therapy.
Berlin, Alejandro; Murgic, Jure; Hosni, Ali; Pintilie, Melania; Salcedo, Adriana; Fraser, Michael; Kamel-Reid, Suzanne; Zhang, Jingbin; Wang, Qiqi; Ch'ng, Carolyn; Deheshi, Samineh; Davicioni, Elai; van der Kwast, Theodorus; Boutros, Paul C; Bristow, Robert G; Chua, Melvin L K.
Afiliação
  • Berlin A; Princess Margaret Cancer Centre, University Health Network, Ontario, Canada; Department of Radiation Oncology, University of Toronto, Ontario, Canada; Techna Institute, University Health Network, Ontario, Canada. Electronic address: alejandroberlin@gmail.com.
  • Murgic J; Princess Margaret Cancer Centre, University Health Network, Ontario, Canada.
  • Hosni A; Princess Margaret Cancer Centre, University Health Network, Ontario, Canada.
  • Pintilie M; Princess Margaret Cancer Centre, University Health Network, Ontario, Canada.
  • Salcedo A; Informatics and Biocomputing Program, Ontario Institute for Cancer Research, Ontario, Canada; Department of Medical Biophysics, University of Toronto, Ontario, Canada.
  • Fraser M; Informatics and Biocomputing Program, Ontario Institute for Cancer Research, Ontario, Canada.
  • Kamel-Reid S; Laboratory Medicine Program, University Health Network, Ontario, Canada.
  • Zhang J; GenomeDx Biosciences Inc., Vancouver, British Columbia, Canada.
  • Wang Q; GenomeDx Biosciences Inc., Vancouver, British Columbia, Canada.
  • Ch'ng C; GenomeDx Biosciences Inc., Vancouver, British Columbia, Canada.
  • Deheshi S; GenomeDx Biosciences Inc., Vancouver, British Columbia, Canada.
  • Davicioni E; GenomeDx Biosciences Inc., Vancouver, British Columbia, Canada.
  • van der Kwast T; Laboratory Medicine Program, University Health Network, Ontario, Canada.
  • Boutros PC; Informatics and Biocomputing Program, Ontario Institute for Cancer Research, Ontario, Canada; Department of Medical Biophysics, University of Toronto, Ontario, Canada; Department of Pharmacology and Toxicology, University of Toronto, Ontario, Canada.
  • Bristow RG; Princess Margaret Cancer Centre, University Health Network, Ontario, Canada; Department of Radiation Oncology, University of Toronto, Ontario, Canada; Manchester Cancer Research Centre, Manchester, United Kingdom.
  • Chua MLK; Princess Margaret Cancer Centre, University Health Network, Ontario, Canada; Division of Radiation Oncology, National Cancer Centre Singapore, Singapore; Division of Medical Sciences, National Cancer Centre Singapore, Singapore; Oncology Academic Program, Duke-NUS Medical School, Singapore.
Int J Radiat Oncol Biol Phys ; 103(1): 84-91, 2019 01 01.
Article em En | MEDLINE | ID: mdl-30170099
ABSTRACT

PURPOSE:

The National Comprehensive Cancer Network (NCCN) has recently endorsed the stratification of intermediate-risk prostate cancer (IR-PCa) into favorable and unfavorable subgroups and recommend the addition of androgen deprivation therapy (ADT) to radiation therapy (RT) for unfavorable IR-PCa. Recently, more accurate prognostication was demonstrated by integrating a 22-feature genomic classifier (GC) to the NCCN stratification system. Here, we test the utility of the GC to better identify patients with IR-PCa who are sufficiently treated by RT alone. METHODS AND MATERIALS We identified a novel cohort comprising 121 patients with IR-PCa treated with dose-escalated image guided RT (78 Gy in 39 fractions) without ADT. GC scores were derived from tumors sampled in diagnostic biopsies. Multivariable analyses, including both NCCN subclassification and GC scores, were performed for biochemical failure (prostate-specific antigen nadir + 2 ng/mL) and metastasis occurrence.

RESULTS:

By NCCN subclassification, 33 (27.3%) and 87 (71.9%) of men were classified as having favorable and unfavorable IR-PCa, respectively (1 case unclassifiable). GC scores were high in 3 favorable IR-PCa and low in 60 unfavorable IR-PCa. Higher GC scores, but not NCCN risk subgroups, were associated with biochemical relapse (hazard ratio, 1.36; 95% confidence interval [CI], 1.09-1.71] per 10% increase; P = .007) and metastasis (hazard ratio, 2.05; 95% CI, 1.24-4.24; P = .004). GC predicted biochemical failure at 5 years (area under the curve, 0.78; 95% CI, 0.59-0.91), and the combinatorial NCCN + GC model significantly outperformed the NCCN alone model for predicting early-onset metastasis (area under the curve for 5-year metastasis of 0.89 vs 0.86 [GC alone] vs 0.54 [NCCN alone]).

CONCLUSIONS:

We demonstrated the accuracy of the GC for predicting disease recurrence in IR-PCa treated with dose-escalated image guided RT alone. Our findings highlight the need to evaluate this GC in a prospective clinical trial investigating the role of ADT-RT in clinicogenomic-defined IR-PCa subgroups.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias da Próstata / Radioterapia Guiada por Imagem Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Limite: Aged / Humans / Male Idioma: En Revista: Int J Radiat Oncol Biol Phys Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias da Próstata / Radioterapia Guiada por Imagem Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Limite: Aged / Humans / Male Idioma: En Revista: Int J Radiat Oncol Biol Phys Ano de publicação: 2019 Tipo de documento: Article