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Dehydroepiandrosterone in metastatic castration-resistant prostate cancer: Preliminary results from the SU2C-PCF West Coast Dream Team (WCDT).

2016· article· en· W2406217810 on OpenAlexaff
Won Bae Kim, Charles J. Ryan, Li Zhang, Jack Youngren, John H. Wilton, Joshi J. Alumkal, Tomasz M. Beer, Robert Baertsch, Joshua M. Stuart, Kim N., Martin Gleave, Matthew B. Rettig, Robert E. Reiter, Primo N. Lara, Christopher P. Evans, Eric J. Small

Bibliographic record

VenueJournal of Clinical Oncology · 2016
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsEnzalutamideMedicineProstate cancerDocetaxelAndrogen receptorInternal medicineOncologyUrologyAndrogen deprivation therapyDehydroepiandrosteroneCancerChemotherapyAndrogenHormone

Abstract

fetched live from OpenAlex

179 Background: Aberrant androgen receptor (AR) phenotypes (e.g. splice variants, amplification) are strongly correlated with abiraterone (Abi) and enzalutamide (Enz) resistance. Low serum dehydroepiandrosterone (DHEA) is also associated with poor outcomes to AR-targeted therapy. Here, we investigate the relationship between serum DHEA, AR phenotype, and treatment efficacy in the WCDT. Methods: Patients (pts) with progressive mCRPC enrolled to the WCDT from UCSF, OHSU, UCLA, UBC, and UCD were included in this analysis. Serum DHEA was analyzed via high-pressure liquid chromatography and tandem mass spectrometry. Limit of quantitation (LQ) of DHEA was 0.2ng/mL. Full-length AR (AR-FL) and AR-v7 expression, obtained via RNAseq of metastatic tumor biopsies, was expressed as total reads mapped to gene. PSA response (PSAr) was defined as ≥ 50% PSA decline. Results: 35 pts were included in this analysis: 15 had treatment-naïve mCRPC, and 20 had prior AR-targeted therapy (14 Abi, 6 Enz). All pts were docetaxel-naïve. 11 pts had DHEA < LQ; of these, 10 had received prior AR-targeted therapy. 12 pts received subsequent chemotherapy, and 23 received subsequent Abi/Enz (7 Abi, 16 Enz). In pts with DHEA < LQ, 4/5 (80%) chemotherapy-treated pts had PSAr, while 1/6 (17%) Abi/Enz-treated pts had PSAr. In pts with DHEA ≥ LQ, 2/7 (27%) chemotherapy-treated pts had PSAr, while 9/16 (56%) Abi/Enz-treated pts had PSAr. The relationship between DHEA and PSAr was significantly different between the treatment groups (p = 0.0285). DHEA was higher in patients with PSAr to Abi/Enz versus those without PSAr (median, 0.871 versus 0.275ng/mL, p = 0.006). In an analysis of 27 pts with RNAseq data, the AR-v7/AR-FL ratio was significantly higher in those with DHEA < LQ (median ratio 8.91, versus 3.38 in DHEA ≥ LQ, p = 0.032). Conclusions: In this exploratory analysis, there is a significant difference in the relationship between DHEA and PSAr in chemotherapy- versus Abi/Enz-treated patients. DHEA < LQ was also associated with a higher AR-v7/AR-FL ratio, a potential avenue for further exploration of tumor biology. These results support a larger study to evaluate DHEA as a potential biomarker in mCRPC. Clinical trial information: NCT02432001.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.016
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.137
GPT teacher head0.465
Teacher spread0.328 · 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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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