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Record W2318305838 · doi:10.1177/201010581202100203

Pathological Outcome in Men with Prostate Cancer Suitable for Active Surveillance after Radical Prostatectomy

2012· article· en· W2318305838 on OpenAlexaboutno aff
Grace Tan, Henry Sun Sien Ho, Hong Huang, Christopher Wai Sam Cheng, Weber Kam On Lau

Bibliographic record

VenueProceedings of Singapore Healthcare · 2012
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineProstatectomyProstate cancerStage (stratigraphy)PathologicalWatchful waitingCancerUnivariate analysisProstateInternal medicineOncologyGynecologyMultivariate analysis

Abstract

fetched live from OpenAlex

Background: Active surveillance (AS) as a treatment option for low risk prostate cancer is gaining recognition. We evaluate the validity of the AS protocol in our patient population, by defining the risk of undergrading and understaging in their pathology. We also aim to determine more accurate inclusion criteria, in order to improve the prediction of early low risk prostate cancer. Materials and Methods: Data was taken from our institutional prostate cancer registry for all men who underwent radical prostatectomy (RP) between Jan 2000 and June 2009. We determined if any of the patients would have met the University of Toronto's (UoT) AS inclusion criteria and examined their post-operative pathology. The primary end-point was pathological upgrading and upstaging. The individual inclusion factors i.e. preoperative PSA, were tested for statistical significance and better cutoffs. Univariate, multivariate and ROC curves were used in the statistical analysis. Results: 216 RPs were performed between January 2000 and June 2009. We identified 79 men who fulfilled the UoT AS criteria. 35% of patients had a Gleason score upgrade from biopsy to surgery, and 21.5% of patients had an upstage to T3 disease. Overall, 34 (43%) patients had an unfavourable change in the grade and/or stage of their prostate cancer. Conclusions: There is a significant risk of undergrading and understaging with the current criteria used for AS. There is a need to identify more discriminative AS criteria before it can be offered as an option to patients with clinically early 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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.798

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.033
GPT teacher head0.332
Teacher spread0.300 · 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 designObservational
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

Citations2
Published2012
Admission routes1
Has abstractyes

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