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Record W2037565714 · doi:10.5114/jcb.2014.45759

High-dose-rate brachytherapy boost for prostate cancer: rationale and technique

2014· review· en· W2037565714 on OpenAlexaff
Gerard Morton

Bibliographic record

VenueJournal of Contemporary Brachytherapy · 2014
Typereview
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineBrachytherapyProstate cancerDose fractionationExternal beam radiotherapyRadiation therapyProstateRadiation treatment planningNuclear medicineDose rateRadiologyOncologyCancerInternal medicineMedical physics

Abstract

fetched live from OpenAlex

High-dose-rate brachytherapy (HDR) is a method of conformal dose escalation to the prostate. It can be used as a local boost in combination with external beam radiotherapy, with a high degree of efficacy and low rate of long term toxicity. Data consistently reports relapse free survival rates of greater than 90% for intermediate risk patients and greater than 80% for high risk. Results are superior to those achieved with external beam radiotherapy alone. A wide range of dose and fractionation is reported, however, we have found that a single 15 Gy HDR combined with hypofractionated radiotherapy to a dose of 37.5 Gy in 15 fractions is well tolerated and is associated with a long term relapse-free survival of over 90%. Either CT-based or trans-rectal ultrasound-based planning may be used. The latter enables treatment delivery without having to move the patient with risk of catheter displacement. We have found it to be an efficient and quick method of treatment, allowing catheter insertion, planning, and treatment delivery to be completed in less than 90 minutes. High-dose-rate boost should be considered the treatment of choice for many men with high and intermediate risk 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 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 score0.970
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.000
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 head0.049
GPT teacher head0.355
Teacher spread0.305 · 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

Citations61
Published2014
Admission routes1
Has abstractyes

Explore more

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