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Androgen Deprivation for Prostate Cancer: When and How, the Good and the Bad

2013· review· en· W4242383671 on OpenAlexaff
Kim N., Paul L. Nguyen, Celestia S. Higano

Bibliographic record

VenueAmerican Society of Clinical Oncology Educational Book · 2013
Typereview
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsAndrogen deprivation therapyMedicineProstate cancerProstatectomyRadiation therapyOncologyInternal medicineRandomized controlled trialDiseaseAdverse effectCancer

Abstract

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Androgen deprivation therapy (ADT) is the mainstay systemic treatment of prostate cancer because of the androgen dependence of the disease. Although ADT has long been used to manage prostate cancer, its use continues to evolve as data from clinical trials mature and long-term effects are recognized. For patients with localized disease and high-risk features, short and long courses of ADT as neoadjuvant/adjuvant therapy have been shown to improve survival when used with radiation therapy, but this has not been demonstrated with radical prostatectomy. The role of ADT with salvage radiotherapy after radical prostatectomy continues to be defined. Lifelong ADT in patients with node-positive disease after surgery or with radiation is also associated with increased survival. Increasingly though, the adverse effects of ADT that go beyond those on libido and hot flashes are being acknowledged. The metabolic effects on lipids, glycemic control, and bone loss from ADT can lead to an increased risk of cardiovascular events and osteoporosis, which needs to be considered when deciding to initiate and treat patients with ADT. Large, randomized trials comparing intermittent to continuous ADT have now been reported. Although the hope for improved cancer outcomes with intermittent therapy has not come to realization, an interrupted approach to therapy may help mitigate some of the negative effects of ADT in selected patients by allowing for off-treatment intervals.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.929
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.004
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 head0.144
GPT teacher head0.507
Teacher spread0.362 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations6
Published2013
Admission routes1
Has abstractyes

Explore more

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