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Evaluation of a genomic classifier in primary tumor and lymph node metastases in pre- and post-radical prostatectomy tissue specimens from patients with lymph node positive prostate cancer.

2015· article· en· W2921618481 on OpenAlexaff
Hak J. Lee, Elana Godebu, Omer Raheem, Song Wang, Kasra Yousefi, Lucia L.C. Lam, Zaid Haddad, Mohammed Alshalalfa, Elai Davicioni, Ahmed Shabaik, Christopher J. Kane

Bibliographic record

VenueJournal of Clinical Oncology · 2015
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsGenome British Columbia
Fundersnot available
KeywordsMedicineProstatectomyProstate cancerConcordanceLymph nodeProstateBiopsyBiochemical recurrenceStage (stratigraphy)CancerLymphMetastasisInternal medicinePathologyOncologyUrology

Abstract

fetched live from OpenAlex

e16087 Background: Genomic Classifiers (GC) are in common use to predict outcomes for men with prostate cancer (PCA). The Decipher test is a validated genomic classifier (GC) that predicts early metastasis after radical prostatectomy (RP). We sought to evaluate whether the GC scores of pre-treatment diagnostic needle biopsy (Bx) and RP can actually predict the metastatic lesion in patients with lymph node positive (LN+) PCA. Methods: Twenty-five LN+ PCA pts who underwent RP and extended LN dissection from a single institution from 2001-2009 were identified and analyzed for genomic aberrations in Bx, prostate and LN samples. Tissue specimens for Bx, RP and LN were available for 13, 22 and 19 pts, respectively. GC results were calculated for a total of 62 patient specimens that passed quality control. Concordance of risk groups was performed using validated cut-points for low ( < 0.45), intermediate (0.45-0.6) and high ( > 0.6) GC score. PCA markers (ERG+, ETS+ or non-ETS/SPINK1+) were used to determine subtype and clonal relationship between Bx, RP and LN. Results: Pre-operatively, 91% of pts were NCCN high and very high-risk groups. Post-operatively, 77% of patients had Gleason ≥ 9 disease and 86% were pT3 or greater stage. Median GC in RP was 0.76 (IQR: 0.63 - 0.80) and 0.85 (IQR: 0.61-0.91) in LN. Median GC in Bx was 0.64 (IQR: 0.48-0.73) and the Bx with the highest Gleason grade and percent tumor cells had 86% concordance with both RP and LN GC risk. Forty-one percent were ERG+, 17% ETS+ and 39% non-ETS/SPINK1+ in prostate specimens. The clonal subtype in RP and LN tumors was the same in 83% of pts. Conclusions: In our cohort, most pts with LN metastases at RP were classified as high GC risk in Bx, RP and LN specimens. There was a high Bx to RP and LN genomic concordance of 86% in Bx specimens with highest Gleason grade and percent tumor cells. Predicting the presence of LN metastasis could be useful for accurate pre-treatment staging and optimization of radical, neo- and adjuvant therapy.

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)0.002
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.083
GPT teacher head0.434
Teacher spread0.351 · 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

Citations3
Published2015
Admission routes1
Has abstractyes

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