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Evaluation of Concordance between Gleason Scores of Tansrectal Ultrasound Guided Biopsy and Radical Prostatectomy Samples in Prostate Cancer

2018· article· en· W2789908339 on OpenAlexvenueno aff
Mutlu Değer, Volkan İzol, Fatih Gökalp, Yıldırım Bayazıt, İbrahim Atilla Arıdoğan, Zühtü Tansuğ

Bibliographic record

VenueJournal of Analytical Oncology · 2018
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsProstatectomyMedicineProstate cancerConcordanceUrologyBiopsyUltrasoundProstateProstate biopsyCancerRadiologyInternal medicine

Abstract

fetched live from OpenAlex

Objective: In this study, we investigated the concordance between Gleason scores of transrectal ultrasound guided biopsy and radical prostatectomy specimens in patients diagnosed with prostate cancer via transrectal ultrasound guided biopsy and treated with radical prostatectomy in our clinic. Material and Method: 115 patients were included in our study treated with radical prostatectomy for organ-confined prostate cancer between the dates of November 2011 and December 2014. Data of these patients are reviewed retrospectively. Results: The average age of the patients was 61.8 ± 6.8 (43-76) years. The average body mass index of these patients were (BMI) 26.7 ± 3.34 (19.3 - 35.3) kg/m². Average PSA value was 6.6 ± 10.1 (1.4 - 80) ng/ml. Gleason scores of transrectal ultrasound guided biopsy and radical prostatectomy were observed concordant in 74 (64.3%) of 115 patients, while 41 (35.6%) were not concordant. Gleason score was decreased by 1 grade for 8.6% (10 patients) of patients, it was increased by 1 for 26.0% (30 patients) of patients and for 0.8% (1 patient) it was increased by 3. Discussion: These findings indicate indicate that Gleason scores of transrectal ultrasound guided biopsy and prostatectomy specimens may be discordant.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.031
Threshold uncertainty score0.402

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.072
GPT teacher head0.408
Teacher spread0.337 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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