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Interpreting a rising prostate‐specific antigen after brachytherapy for prostate cancer

2012· review· en· W1555274153 on OpenAlexaff
Miren Gaztañaga, Juanita Crook

Bibliographic record

VenueInternational Journal of Urology · 2012
Typereview
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsBrachytherapyMedicineProstateProstate-specific antigenProstate cancerProstate brachytherapyUrologyAntigenRadiation therapyOncologyInternal medicineCancerImmunology

Abstract

fetched live from OpenAlex

The aim of the present study was to review the English language literature on the topic of prostate-specific antigen bounce after brachytherapy and present a summary of the current knowledge. Although ultimately prostate-specific antigen is a reliable measure of success after prostate brachytherapy, it can be very misleading in the first 3 years because of the frequency with which temporary benign rises in prostate-specific antigen occur. We have reviewed the English language literature on the topic of prostate-specific antigen bounce under the following headings: prostate neoplasms, brachytherapy, biochemical definition of prostate-specific antigen failure, "benign prostate-specific antigen bounce" and "prostate-specific antigen spike". We included brachytherapy delivered as either low dose rate or high dose rate, and either as monotherapy or as a boost combined with external beam radiotherapy. A benign self-limited rise in prostate-specific antigen after prostate brachytherapy is seen in an average of 35% of patients, but increases in frequency with younger age. In patients aged less than 55 years, it is observed in up to 68%. Other factors, such as sexual activity, dose, prostate volume and the use of high dose rate versus low dose rate have been implicated in affecting the frequency of the benign bounce. Benign increases in prostate-specific antigen are frequent after prostate brachytherapy. It is important to recognize and correctly diagnose this phenomenon in order to avoid unnecessary salvage treatment.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.044
GPT teacher head0.388
Teacher spread0.345 · 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 designOther design
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

Citations13
Published2012
Admission routes1
Has abstractyes

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