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Record W4210316818 · doi:10.1016/j.prnil.2022.01.004

Up- and downgrading in single intermediate-risk positive biopsy core prostate cancer

2022· article· en· W4210316818 on OpenAlexaff
Benedikt Hoeh, Rocco Simone Flammia, Lukas Hohenhorst, Gabriele Sorce, Francesco Chierigo, Zhe Tian, Fred Saad, Michele Gallucci, Alberto Briganti, Carlo Terrone, Shahrokh F. Shariat, Markus Graefen, Derya Tilki, Luis A. Kluth, Philipp Mandel, Felix K.‐H. Chun, Pierre I. Karakiewicz

Bibliographic record

VenueProstate International · 2022
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMedicineBiopsyProstate cancerLogistic regressionProstate biopsyCore (optical fiber)CancerStage (stratigraphy)Core biopsyInternal medicineSurgeryUrologyBreast cancer

Abstract

fetched live from OpenAlex

Up- and/or downgrading rates in single intermediate-risk positive biopsy core are unknown. We identified single intermediate-risk (Gleason grade group (GGG) 2/GGG3) positive biopsy core prostate cancer patients (≤ cT2c and PSA ≤ 20 ng/mL) within the Surveillance, Epidemiology, and End Results (SEER) database (2010–2015). Subsequently, separate uni- and multivariable logistic regression models tested for independent predictors of up- and downgrading. Of 1,328 assessable patients with single core positive intermediate-risk prostate cancer at biopsy, 972 (73%) harbored GGG2 versus 356 (27%) harbored GGG3. Median PSA (5.5 vs 5.7; p = 0.3), median age (62 vs 63 years; p = 0.07) and cT1-stage (77 vs 75%; p = 0.3) did not differ between GGG2 and GGG3 patients. Of individuals with single GGG2 positive biopsy core, 191 (20%) showed downgrading to GGG1 versus 35 (4%) upgrading to GGG4 or GGG5 at RP. Of individuals with single GGG3 positive biopsy core, 36 (10%) showed downgrading to GGG1 versus 42 (12%) significant upgrading to GGG4 or GGG5 at RP. In multivariable logistic regression models, elevated PSA (10–20 ng/mL) was an independent predictor of upgrading to GGG4/GGG5 in single GGG3 positive biopsy core patients (OR:2.89; 95%-CI: 1.31–6.11; p = 0.007). In single GGG2 positive biopsy core patients, downgrading was four times more often recorded compared to upgrading. Conversely, in single GGG3 positive biopsy core patients, up- and downgrading rates were comparable and should be expected in one out of ten patients.

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 score0.048
Threshold uncertainty score0.689

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 head0.019
GPT teacher head0.292
Teacher spread0.274 · 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

Citations4
Published2022
Admission routes1
Has abstractyes

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