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Record W4322617782 · doi:10.1002/pros.24501

Mass spectrometry redefines optimal testosterone thresholds in prostate cancer patients undergoing androgen deprivation therapy

2023· article· en· W4322617782 on OpenAlexafffund
Jérémie Beck, Mélanie Rouleau, Francis Lemire, Bertrand Neveu, Michel Déry, Benoît Thériault, Gabriel Dubois, Dominique Guérette, Frédéric Pouliot

Bibliographic record

VenueThe Prostate · 2023
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsUniversité LavalCentre hospitalier universitaire de Québec
FundersFonds de Recherche du Québec - SantéSanofi GenzymeCentre Hospitalier Universitaire de QuébecUniversité Laval
KeywordsTestosterone (patch)Prostate cancerMedicineAndrogen deprivation therapyCastrationHazard ratioInternal medicineUrologyAndrogenProportional hazards modelProstateEndocrinologyConfidence intervalCancerOncologyHormone

Abstract

fetched live from OpenAlex

BACKGROUND: Androgen deprivation therapy (ADT) is the standard of care for prostate cancer treatment. Studies suggest that patients with testosterone levels below 0.7 nM have a longer time to castration resistance. Using the most accurate testosterone measurement method, namely mass spectrometry (MS), we sought to determine if a lower testosterone level under ADT could be associated with longer time to castration resistance. METHODS: This retrospective study included 138 prostate cancer patients undergoing noncurative continuous ADT for which we had access to testosterone measurements assessed by MS. For 108 samples, paired immunoassays (IA) testosterone measurement was available. Primary outcome was time to castration-resistant prostate cancer (CRPC). The Contal and O'Quigley method was used to determine the optimal testosterone castration cut-off point considering the outcome and time-to-event variables. Relationship between testosterone levels assessed either by IA or MS and time to CRPC was evaluated using Cox regression. RESULTS: Mean testosterone level was 0.370 nM by IA and 0.275 nM as assessed by MS. The optimal testosterone cut-off point identified to predict time to CRPC was of 0.705 nM for IA and of 0.270 nM for MS. While no significant difference for time to CRPC was found between patients showing IA testosterone level ≥0.705 nM versus <0.705 nM (hazard ratio [HR]: 1.579; 95% confidence interval [CI]: 0.908-2.745), patients with MS testosterone ≥0.270 nM had an increased risk of progression to CRPC compared to MS testosterone <0.270 nM in univariate (HR: 1.717; 95% CI: 1.160-2.541) and multivariate analysis (HR: 1.662; 95% CI: 1.043-2.648). CONCLUSIONS: The higher sensitivity of MS testosterone measurement methods allows the identification of a lower castration threshold and leads to early identification of patients more likely to progress to CRPC. These patients would likely benefit from treatment intensification by androgen receptor axis-targeted therapies to delay disease progression.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.570

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.035
GPT teacher head0.315
Teacher spread0.280 · 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 teacher head, 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

Citations2
Published2023
Admission routes2
Has abstractyes

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