Abstract
Genomic classifier to augment the role of pathological features in identifying optimal candidates for adjuvant radiation therapy in patients with prostate cancer: Development and internal validation of a multivariable prognostic model
Journal of clinical oncology, Vol.35(6_suppl), pp.142-142
02/20/2017
DOI: 10.1200/JCO.2017.35.6_suppl.142
Abstract
Abstract only 142 Background: Despite documented oncological benefit, postoperative adjuvant radiotherapy (aRT) utilization in prostate cancer (PCa) patients is still limited in the US. 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. Methods: Our cohort included a total of 512 PCa patients treated with RP at one of four US academic centers between 1990-2010. All patients had ≥ pT3a disease, positive margins, and/or pathologic lymph node invasion (LNI). Multivariable Cox regression analysis (MVA) 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 TRIPOD guidelines for development of prognostic models. Results: Overall, 21.9% 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 vs. initial observation (p < 0.001). Pathological T3b/T4 stage, Gleason score 8-10, LNI and Decipher score > 0.6 were independent predictors of CR (all p < 0.01) Cumulative number of risk factors was 0, 1, 2, and 3-4 in respectively 46.5, 28.9, 17.2, and 7.4% of patients. Adjuvant RT was associated with decreased CR rate in patients with ≥ 2 risk factors (10-year CR rate 10.1% in aRT vs. 42.1% in initial observation, p = 0.008), but not in those with < 2 risk factors (p = 0.23). Conclusions: Utilizing the novel model to indicate aRT might reduce overtreatment, decrease unnecessary side effects, and reduce risk of CR in the subset of patients (~25% of all patients with aggressive pathological disease) who really benefit from this therapy.
Details
- Title: Subtitle
- Genomic classifier to augment the role of pathological features in identifying optimal candidates for adjuvant radiation therapy in patients with prostate cancer: Development and internal validation of a multivariable prognostic model
- Creators
- Firas Abdollah - Vattikuti Urology Institute, Detroit, MIDeepansh Dalela - Henry Ford HospitalMaria Santiago-Jimenez - Genome British ColumbiaKasra Yousefi - Genome British ColumbiaJeffrey Karnes - Mayo Clinic in ArizonaAshley Ross - Johns Hopkins UniversityRobert B. Den - Thomas Jefferson UniversityStephen J. Freedland - Cedars-Sinai Medical CenterEdward M. Schaeffer - Johns Hopkins MedicineAdam Dicker - Sidney Kimmel Cancer CenterAlberto Briganti - MylanElai Davicioni - Genome British ColumbiaMani Menon - Henry Ford Hospital
- Resource Type
- Abstract
- Publication Details
- Journal of clinical oncology, Vol.35(6_suppl), pp.142-142
- DOI
- 10.1200/JCO.2017.35.6_suppl.142
- ISSN
- 0732-183X
- eISSN
- 1527-7755
- Publisher
- LIPPINCOTT WILLIAMS & WILKINS
- Language
- English
- Date published
- 02/20/2017
- Academic Unit
- Urology
- Record Identifier
- 9984958309002771
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