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Prognostic impact of PSA nadir (n) ≥0.1 ng/mL within 6 months (m) after completion of radiotherapy (RT) for localized prostate cancer (PCa): An individual patient-data (IPD) analysis of randomized trials from the ICECAP collaborative.

2023· article· en· W4379282877 on OpenAlexaff
Praful Ravi, Lucia Kwak, John Armstrong, V. Beckendorf, Joseph L. Chin, Anthony V. D’Amico, David P. Dearnaley, James W. Denham, Savino M. Di Stasi, Silke Gillessen, Himanshu Lukka, Nicolas Mottet Auselo, P. Pommier, Wendy Seiferheld, Matthew R. Sydes, Bertrand Tombal, A. Zapatero, Meredith M. Regan, Wanling Xie, Christopher J. Sweeney

Bibliographic record

VenueJournal of Clinical Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsJuravinski Cancer CentreMcMaster UniversityLondon Health Sciences Centre
Fundersnot available
KeywordsMedicineAndrogen deprivation therapyProstate cancerProportional hazards modelInternal medicineRandomizationOncologyRadiation therapyStage (stratigraphy)Surrogate endpointRandomized controlled trialClinical endpointHazard ratioUrologySurvival analysisCancerConfidence interval

Abstract

fetched live from OpenAlex

5002 Background: RT + androgen deprivation therapy (ADT) is a standard of care in treatment of intermediate- and high-risk localized PCa. Identification of early surrogate measures for long-term outcome measures such as PCa-specific survival (PCSS), metastasis-free survival (MFS) and overall survival (OS) could expedite development of new systemic therapies added to RT/ADT while potentially identifying patients (pts) for therapy (de)escalation. Methods: IPD from the RT+/-ADT trials in the ICECAP repository with evaluable PSA follow-up were eligible for inclusion. Pts were grouped based on their trial-allocated treatment: RT alone, RT+stADT (short-term ADT: 3-6m), RT+ltADT (long-term ADT: 18-36m). PSAn was defined as the lowest PSA recorded within 6m after RT completion. A 12m landmark analysis for PCSS, MFS and OS was performed to account for guarantee-time bias. Multivariable Cox proportional hazards regression was used to estimate associations of PSAn < or ≥0.1ng/mL with MFS and OS, and a multivariable Fine and Gray distribution used for PCSS to account for competing risk of non-PCa deaths. Models were adjusted for age, ECOG performance status, clinical T stage, Gleason score and PSA at randomization. Results: 10,415 pts from 16 RCTs were included: 2629 (25%) allocated to RT, 6033 (58%) to RT+stADT, and 1753 (17%) to RT+ltADT. Median follow-up was 10.1years (yrs). 2339 (98%), 4756 (84%) and 1258 (77%) of patients allocated to RT, RT+stADT and RT+ltADT respectively achieved a PSAn ≥0.1ng/mL within 6m after RT completion. After adjustment, PSAn ≥0.1ng/mL was associated with poorer PCSS, MFS and OS in pts allocated to RT+stADT (PCSS hazard ratio [HR] = 1.97 [95% CI 1.52-2.92], MFS HR = 1.27 [1.12-1.44], OS HR = 1.26 [1.11-1.44]) and RT+ltADT (PCSS HR = 1.97 [1.11-3.49], MFS HR = 1.58 [1.27-1.96], OS HR = 1.59 [1.27-1.99]). A weaker association was noted in pts allocated to RT (PCSS HR = 1.82 [0.51-6.49], MFS HR = 2.23 [1.20-4.14], OS HR = 1.72 [0.97-3.05]). Table shows 5-yr MFS, 10-yr PCSS and 10-yr OS based on PSAn within 6m after RT completion. Conclusions: PSAn ≥0.1ng/mL within 6 mths after RT completion was strongly prognostic for PCSS, MFS and OS in pts receiving RT+ADT for localized PCa in this IPD analysis of > 10,000 patients. This could be used as an early signal-seeking endpoint in trials evaluating novel systemic therapies with RT + ADT and to help identify pts for therapy (de)escalation trials. [Table: see text]

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)0.026
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.998
Threshold uncertainty score0.136

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.031
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.007
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.266
GPT teacher head0.554
Teacher spread0.288 · 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.

Study designMeta-analysis
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

Citations3
Published2023
Admission routes1
Has abstractyes

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