Decipher score as a predictor of response to treatment intensification in the NRG Oncology-RTOG 0534 (SPPORT) phase III randomized post-prostatectomy salvage radiotherapy trial.
399 Background: The three-arm randomized SPPORT trial (n=1792) examined the effect of treatment intensification on the outcome of men treated with salvage radiotherapy (RT) for a detectable PSA. The arms were prostate bed RT (PBRT) alone (Arm I), PBRT + short term androgen deprivation therapy (STADT; Arm 2), and PBRT + STADT + pelvic lymph node RT (PLNRT; Arm 3). With treatment intensification in Arms 2 and 3, there were significant incremental gains in the primary freedom from progression (FFP) endpoint, but not metastasis free survival (MFS) with about 8 yr median follow-up; although metastatic events were reduced with intensification. Decipher score (DS) is strongly prognostic for metastasis and was hypothesized to be independently significant of clinical-pathologic covariates in predicting the need for treatment intensification. The main objective was to determine if gene expression estimates of metastatic risk using Decipher score result in significant interactions with treatment, especially for PLNRT. Methods: Prospectively collected prostatectomy tissuewas available for RNA extraction and generation of DS (Veracyte, San Diego, CA) in 916 patients. The protocol FFP endpoint included biochemical (nadir+2 ng/mL) failure, clinical failure, or death from any cause. MFS included distant metastasis or death from any cause. Multivariable (MVA) Cox models adjusted for Gleason score, margin status, pT-stage, pre-RT PSA, age, and race. Results: DS (median 0.61; IQR: 0.45-0.79) were obtained for 709 patients (median follow-up 7.9 yr), with 215 in Arm 1, 247 in Arm 2, and 247 in Arm 3. The arms were balanced for key covariates. There were 226 FFP and 136 MFS events. On MVA, DS (per 0.1 unit) was prognostic for FFP (HR 1.10, 95% CI 1.03-1.17, p=0.007) and borderline for MFS (HR 1.08, 95% CI 0.99 - 1.18, p=0.08). There was no significant DS-related benefit to adding STADT to PBRT. Adding PLNRT + STADT to PBRT resulted in a greater benefit in patients with high (>0.60, HR 0.36, 95% CI 0.25-0.54, p<0.001) vs. lower (≤0.60, HR 0.76, 95% CI 0.46-1.26, p=0.29) DSs, with an absolute benefit of 27% vs. 11% in high vs. lower DS, along with a significant treatment interaction on MVA (p-int = 0.04). Relative MFS benefit from adding PLNRT + STADT to PBRT ± STADT was greater in patients with high (HR 0.60, 95% CI 0.37-0.97, p=0.04) vs. lower (HR 1.14, 95% CI 0.66-1.98, p=0.63) DS, with a 10-year absolute benefit of 6% vs. 0%, and a borderline significant treatment interaction on MVA (p-int = 0.06). Conclusions: The unique SPPORT trial intensification design facilitated the discovery that high metastatic risk, as assessed by DS, may be abrogated at least in part by PLNRT, suggesting that lymph node micrometastases are a sole site of metastasis in some patients. Decipher score is a meaningful predictor of gains from PLNRT. Clinical trial information: NCT00567580 .
Authors
- Nader Khaouam
- Elai Davicioni (ORCID: https://orcid.org/0000-0001-9136-099X)
- Felix Yi-Chung Feng (ORCID: https://orcid.org/0000-0002-0963-7687)
- Marie Duclos (ORCID: https://orcid.org/0000-0003-3324-2375)
- George Rodrigues (ORCID: https://orcid.org/0000-0002-7174-4280)
- Theodore Karrison (ORCID: https://orcid.org/0009-0009-8641-5111)
- Jeff M. Michalski (ORCID: https://orcid.org/0000-0003-0563-3766)
- Angela Y. Jia (ORCID: https://orcid.org/0000-0002-0812-2614)
- J. Proudfoot (ORCID: https://orcid.org/0000-0003-1032-9945)
- André‐Guy Martin (ORCID: https://orcid.org/0000-0003-4214-9148)
- Phuoc T. Tran (ORCID: https://orcid.org/0000-0002-0147-0376)
- Himanshu Lukka
- Alan Pollack
- Jeff Simko
- R. Jeffrey Lee
- Alan Dal Pra (ORCID: https://orcid.org/0000-0002-1648-6557)
- Kevin S. Roof (ORCID: https://orcid.org/0000-0002-0705-7806)
- Samantha A. Seaward (ORCID: https://orcid.org/0000-0003-4459-4923)
- Steve Angyalfi
- Marla Johnson
Institutions
- University of Maryland, Baltimore (US)
- University Health Network (CA)
- Kaiser Permanente (US)
- Johns Hopkins University (US)
- University of Miami (US)
- University of California, San Francisco (US)
- Washington University in St. Louis (US)
- Johns Hopkins Medicine (US)
- McGill University Health Centre (CA)
- Princess Margaret Cancer Centre (CA)
- Intermountain Medical Center (US)
- Centre hospitalier universitaire de Québec (CA)
- University of Miami Health System (US)
- Veracyte (United States) (US)
- Southeast Radiation Oncology Group (US)
- NRG Oncology (US)
- McMaster University (CA)
Publication Details
- Journal
- Journal of Clinical Oncology
- Published
- 2025-02-10
- DOI
- https://doi.org/10.1200/jco.2025.43.5_suppl.399
- Citations
- 3
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 4.08
Funders
- National Institutes of Health