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Record W1576917821 · doi:10.1159/000139874

Radiotherapy as Primary Treatment Modality

2008· review· en· W1576917821 on OpenAlexaff
Michael Sia, Tara Rosewall, Padraig Warde

Bibliographic record

VenueFrontiers of radiation therapy and oncology · 2008
Typereview
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsMedicineRadiation therapyProstate cancerOncologyHormonal therapyRegimenAdjuvantProstate-specific antigenInternal medicineStage (stratigraphy)DiseaseHormone therapyCancer

Abstract

fetched live from OpenAlex

The proper management of prostate cancer is dependent on appropriate risk categorization, based on pretreatment prostate-specific antigen (PSA), clinical stage and Gleason score (GS). The use of radiotherapy in low-risk (T1-T2a, PSA < 10 ng/ml and GS <or= 6) and intermediate-risk (T1/T2, PSA < 20 ng/ml and GS <or= 7) disease is well established, with comparable results to surgery in the era of modern radiation therapy. However, cancer-related outcomes in some radiotherapy patients might still be improved with the use of adjuvant hormonal therapy. There is presently no clear evidence to support its use in low-risk patients and benefits in intermediate-risk patients need to be elucidated in the era of dose-escalated radiation therapy. Hypofractionated radiotherapy using biologically equivalent doses also has the potential to improve the therapeutic index, given the low alpha / beta ratio of prostate cancer, and to reduce overall treatment time, but the most advantageous regimen needs to be determined. In patients with high-risk disease (T3-T4, PSA > 20 ng/ml or GS >or=6 8), radiation with hormones has become the standard treatment. The issues that remain focus on determining the optimal duration of hormones, assessing the use of locoregional dose escalation and determining the possible benefit from adjuvant chemotherapy.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.987
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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 head0.043
GPT teacher head0.350
Teacher spread0.307 · 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
Published2008
Admission routes1
Has abstractyes

Explore more

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