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Record W2089952228 · doi:10.1159/000081629

Pharmacodynamic Equivalence of a Decapeptyl 3-Month SR Formulation with the 28-Day SR Formulation in Patients with Advanced Prostate Cancer

2004· article· en· W2089952228 on OpenAlexaff
Pierre Teillac, Christiaan F. Heyns, Amir V. Kaisary, Olivier Bouchot, Joëlle Blumberg

Bibliographic record

VenueHormone Research in Paediatrics · 2004
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsHotel Dieu Hospital
Fundersnot available
KeywordsMedicineProstate cancerPharmacodynamicsEquivalence (formal languages)UrologyOncologyCancerGynecologyInternal medicinePharmacokineticsMathematics

Abstract

fetched live from OpenAlex

AIMS: The objective of the study was to assess the pharmacodynamic equivalence of LHRH analogue triptorelin 3-month and 28-day SR formulations. METHODS: Patients with documented locally advanced or metastatic prostate cancer were randomized to receive one injection of the 3-month formulation (n = 63) or three injections at 28-day intervals of the 28-day formulation (n = 68). Group-chemical castration rates defined as the percentage of patients reaching a testosterone plasma level </=0.5 ng/ml were compared at D84 (i.e., 3 x 28 days). Testosterone, LH and triptorelin plasma profiles, and change from baseline in plasma PSA were assessed over 3 months (from baseline to D91). RESULTS: Chemical castration rates were 98 and 96% in the 3-month and 28-day formulation groups, respectively, with confidence interval (two-sided 94.2% CI) of [-8.1%; 9.6%]. Median times to reach chemical castration were 18.8 and 18.5 days (p = 0.86, log rank), respectively. Ratios for mean peak plasma levels and AUC(91) of the two formulations for both testosterone and LH fell within the [0.80; 1.25] equivalence interval. Mean PSA decreases from baseline at D91 were 91.0 and 91.7%, respectively (p = 0.73). CONCLUSION: Treatments with the two triptorelin formulations over 3 months are pharmacologically equivalent.

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)0.001
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 score0.055
Threshold uncertainty score0.528

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.028
GPT teacher head0.354
Teacher spread0.326 · 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

Citations24
Published2004
Admission routes1
Has abstractyes

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