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Record W4407484999 · doi:10.1016/j.annonc.2025.01.017

Predicting dose response to prostate cancer radiotherapy: validation of a radiation signature in the randomized phase III NRG/RTOG 0126 and SAKK 09/10 trials

2025· article· en· W4407484999 on OpenAlexaff
A. Dal Pra, Pirus Ghadjar, Hyunnam Ryu, J.A. Proudfoot, Stefanie Hayoz, J.M. Michalski, D.E. Spratt, Yang Liu, Corinne Schär, Alejandro Berlín, Daniel R. Zwahlen, J Simko, Tobias Hölscher, Jason A. Efstathiou, Bülent Polat, H.M. Sandler, Guido Hildebrandt, Matthew Parliament, Arndt-Christian Mueller, Ian S. Dayes, L. Plasswilm, Rohann Correa, John M. Robertson, Theodore Karrison, E. Davicioni, Walter A. Hall, F.Y. Feng, Alan Pollack, G.N. Thalmann, Paul L. Nguyen, D.M. Aebersold, P.T. Tran, Shuang G. Zhao

Bibliographic record

VenueAnnals of Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsLondon Health Sciences CentreJuravinski Cancer CentreUniversity of AlbertaUniversity Health NetworkHamilton Health SciencesPrincess Margaret Cancer Centre
FundersNational Cancer InstituteProstate Cancer FoundationNational Institutes of HealthNRG OncologySchweizerische Arbeitsgemeinschaft für Klinische KrebsforschungU.S. Department of Defense
KeywordsMedicineProstatectomyProstate cancerRadiation therapyInternal medicineOncologyRandomized controlled trialAndrogen suppressionProstateCancer

Abstract

fetched live from OpenAlex

BACKGROUND: The SAKK 09/10 trial randomized biochemically recurrent prostate cancer patients to salvage radiation 64 Gy versus 70 Gy, and the NRG/RTOG 0126 randomized intermediate-risk prostate cancer patients to definitive radiation 70.2 Gy versus 79.2 Gy. We investigated a previously developed Post-Operative Radiation Therapy Outcomes Score (PORTOS) to identify preferential benefit from radiation dose escalation (DE). MATERIALS AND METHODS: PORTOS was evaluated in patients enrolled in SAKK 09/10 and NRG/RTOG 0126 with available tissue that passed quality control (n = 226, 215). PORTOS was evaluated in the published post-operative groups in SAKK 09/10 and in tertiles in NRG/RTOG 0126 as cut-offs had not been established for biopsy samples and definitive radiation patients. Clinical and molecular correlates in a real-world dataset of 42 407 prostatectomy and 31 107 biopsy samples were also analyzed. RESULTS: In SAKK 09/10, the biomarker-treatment interaction was statistically significant between PORTOS (lower versus higher) and treatment arm for clinical progression-free survival. Only patients in the higher PORTOS group benefited from DE. In NRG/RTOG 0126, in patients with a lower tertile PORTOS, there was no difference in Phoenix biochemical failure (BF). However, for patients in the average and higher tertile PORTOS range, there was a significant benefit for DE for Phoenix BF. An interaction test indicated a significant difference in benefit for DE between higher and lower PORTOS groups. PORTOS was not strongly associated with clinicopathological variables in either trial or the large real-world dataset. In the latter, PORTOS was modestly associated with hypoxia signatures and strongly associated with immune signatures and subtypes. CONCLUSION: In the SAKK 09/10 and RTOG 0126 randomized controlled trials, we demonstrated that PORTOS can potentially identify a subset of patients who benefit from DE, a subgroup that cannot be identified using clinicopathological or prognostic variables. These results suggest that PORTOS could be used clinically as a predictor of radiation response.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.021
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.058
GPT teacher head0.446
Teacher spread0.388 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations15
Published2025
Admission routes1
Has abstractyes

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