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Record W1484814684 · doi:10.1002/cncr.23827

Currently used criteria for active surveillance in men with low‐risk prostate cancer

2008· article· en· W1484814684 on OpenAlexaff
Nazareno Suardi, Umberto Capitanio, Felix K.‐H. Chun, Markus Graefen, Paul Perrotte, Thorsten Schlomm, Alexander Haese, Hartwig Huland, Andreas Erbersdobler, Francesco Montorsi, Pierre I. Karakiewicz

Bibliographic record

VenueCancer · 2008
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsFonds de Recherche du Québec - SantéUniversité de Montréal
Fundersnot available
KeywordsMedicineProstate cancerWatchful waitingGynecologyCancerOncologyMedical physicsInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Active surveillance (AS) represents a treatment option for select patients with low-risk, organ-confined prostate cancer (PCa). In this report, the authors addressed the rates of misclassification associated with the use of 5 different clinical criteria for AS. Misclassification was defined as the presence of either nonorgan-confined disease or high-grade PCa. METHODS: Between 1992 and 2007, 4885 patients underwent radical prostatectomy (RP) at 1 of 2 European academic centers, and the patients were identified who fulfilled the criteria for AS according to 5 different investigational groups (Hardie et al, Roemeling et al, Choo et al, Klotz, and D'Amico and Coleman). Statistics targeted the rates of misclassification for each of the 5 definitions. RESULTS: Four thousand three hundred eight patients, 4047 patients, 3993 patients, 2455 patients, and 2345 patients fulfilled the AS criteria of Hardie et al, Roemeling et al, Choo et al, Klotz, and D'Amico and Coleman, respectively. Extracapsular extension was reported in 13.5% to 26% of patients, and seminal vesicle invasion was reported in 2.9% to 8.2% of patients. When PCa with Gleason scores from 8 to 10 at RP was considered high grade, the misclassification rates were 27%, 25%, 25%, 15%, and 14% for the 5 studies, respectively. Conversely, when PCa with Gleason scores from 7 to 10 was considered high grade, the misclassification rates increased to 56%, 55%, 45%, 42%, and 39%, respectively. CONCLUSIONS: The currently available AS criteria are limited by a high rate of misclassification. The use of more selective AS criteria may reduce the rate of misclassification but also may reduce significantly the percentage of patients who may be considered for AS.

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 score0.029
Threshold uncertainty score0.690

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.028
GPT teacher head0.334
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.

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

Citations105
Published2008
Admission routes1
Has abstractyes

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