MétaCan
Menu
← Back to cohort

PD53-07 CLINICAL SIGNIFICANCE OF THE SIAα2,3GAL-GLYCOSYLATED PROSTATE-SPECIFIC ANTIGEN ASSAY FOR PROSTATE CANCER DETECTION

2020· article· en· W4240799807 on OpenAlexaboutno aff
Tohru Yoneyama, Yuki Tobisawa, Tomokazu Ishikawa, Shingo Hatakeyama, Kazuyuki Mori, Mihoko Sutoh Yoneyama, Teppei Okubo, Koji Mitsuzuka, Wilhelmina Duivenvoorden, Jehonathan H. Pinthus, Yasuhiro Hashimoto, Akihiro Ito, Takuya Koie, M. DATE, Robert A. Gardiner, Chikara Οhyama

Bibliographic record

VenueThe Journal of Urology · 2020
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineProstate cancerUrologyProstate-specific antigenReceiver operating characteristicArea under the curveProstateCohortInternal medicineArea under curveGastroenterologyCancerOncologyPharmacokinetics

Abstract

fetched live from OpenAlex

INTRODUCTION AND OBJECTIVE: To reduce unnecessary prostate biopsies (Pbx), better discrimination is needed. To identify significant prostate cancer (sigPC) we determined the performance of Siaα2,3Gal-glycosylated prostate-specific antigen (S2,3PSA) and S2,3PSA normalized by prostate volume (S2,3PSAD). METHODS: We retrospectively measured S2,3PSA, total PSA (tPSA), and free PSA/tPSA (F/T PSA) values in 349 men who underwent a Pbx in three academic urology clinics in Japan and Canada (Pbx cohort). The assays were evaluated using the area under receiver operating characteristics curve (AUC) and decision curve analyses (DCA) to discriminate overall PC and sigPC. RESULTS: In the Pbx cohort, S2,3PSAD (AUC 0.795) provided significantly better clinical performance for discriminating overall PC compared with S2,3PSA (AUC 0.780, p <0.0001), PSAD (AUC 0.684, p <0.0001), tPSA (AUC 0.552, p <0.0001) and F/T PSA (AUC 0.689, p <0.0001). DCA analysis showed that using a risk threshold of 30%, adding S2,3PSA and S2,3PSAD to the base model (age, DRE status, tPSA, and F/T PSA) permitted avoidance of even more biopsies without missing PC (8.0% and 7.6% resp. vs. -0.3% (base model)). In addition, S2,3PSAD (AUC 0.827) provided significantly better clinical performance for discriminating sigPC compared with S2,3PSA (AUC 0.778, p <0.0001), PSAD (AUC 0.787, p <0.0001), tPSA (AUC 0.642,p <0.0001) and F/T PSA (AUC 0.686, p <0.0001). DCA analysis showed that using a risk threshold of 30%, adding S2,3PSA and S2,3PSAD to the base model permitted avoidance of even more biopsies without missing sigPC (14.0% and 13.2% resp. vs. 2.3% (base model)). CONCLUSIONS: The diagnostic performance of S2,3PSA is significantly better than the PSA, FT/ PSA & PSAD test in identifying patients with overall PC and sigPC. Addition of S2,3PSA test to conventional diagnostic model significantly improve avoidable biopsy effect in identifying patients with PC.Source of Funding: none

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.067
GPT teacher head0.363
Teacher spread0.296 · 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 source (direct Gemma or distilled Codex), 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
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of Urology→Same topicProstate Cancer Treatment and Research→French-language works237,207→