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Record W2157550245 · doi:10.5539/cco.v1n1p118

Cabazitaxel for Metastatic Castrate-Resistant Prostate Cancer: A Case Presentation

2012· article· en· W2157550245 on OpenAlexvenueno aff
Simon B. Zeichner, Michael Cusnir, Michael L. Francavilla

Bibliographic record

VenueCancer and Clinical Oncology · 2012
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsnot available
Fundersnot available
KeywordsCabazitaxelProstate cancerDocetaxelMedicineTaxaneOncologyInternal medicineCancerProstateMitoxantroneUrologyChemotherapyAndrogen deprivation therapyBreast cancer

Abstract

fetched live from OpenAlex

Introduction: Although cabazitaxel was proven efficacious by a large Phase III trial and was approved for second-line treatment of metastatic castrate-resistant prostate cancer, case reports describing its efficacy and safety are lacking in the literature. More data is needed describing castrate-resistant prostate cancer cases that progress with 1st line therapy. Case Presentation: A 78-year old Hispanic male presented to the clinic in July 2011 with a 3-month history of worsening left knee pain, generalized fatigue, and a 5.4 kilogram weight loss. His past medical history was significant for metastatic prostate cancer and his laboratory results were notable for an alkaline phosphatase of 221U/L, a prostate specific antigen of 837.7ng/ml, and a creatinine of 1.94. Discussion: Metastatic prostate cancer results from the combination of lymphatic, blood, or contiguous local spread. Cabazitaxel is a novel semi-synthetic tubulin binding taxane that uses a precursor molecule extracted from yew tree needles. In the phase III TROPIC study, CRPC patients previously taking docetaxel had a significant increase in overall survival with cabazitaxel compared with mitoxantrone (15.1 vs. 12.7 months, p<0.001). Conclusion: Cabazitaxel appears to be safe chemotherapeutic agent and has moved to the forefront in our armamentarium for the treatment in castrate-resistant prostate cancer.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.727
Threshold uncertainty score0.473

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.195
GPT teacher head0.539
Teacher spread0.343 · 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 designOther design
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

Citations0
Published2012
Admission routes1
Has abstractyes

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