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Chronic inflammation is negatively associated with prostate cancer and high-grade prostatic intraepithelial neoplasia on needle biopsy

2007· article· en· W1587093626 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Clinical Practice · 2007
Typearticle
Languageen
FieldMedicine
TopicInflammatory Biomarkers in Disease Prognosis
Canadian institutionsHôpital du Sacré-Cœur de MontréalUniversité de Montréal
Fundersnot available
KeywordsMedicineHigh-grade prostatic intraepithelial neoplasiaIntraepithelial neoplasiaProstate cancerProstateInflammationBiopsyRectal examinationUrologyCancerProstatitisProstate-specific antigenPathologyInternal medicineGastroenterology

Abstract

fetched live from OpenAlex

Tissue inflammation has been linked to cancer in several disease models. We tested the association between chronic inflammation and prostate cancer (PCa), as well as high-grade prostatic intraepithelial neoplasia (HGPIN), in prostatic needle biopsy specimens. Tissues from 4526 men, who underwent systematic ultrasound-guided sextant needle biopsies of the prostate, were classified in the following order as PCa, or HGPIN, or chronic inflammation or benign. PCa was diagnosed in 1633 (36.1%), HGPIN in 535 (11.8%) and chronic inflammation in 347 (7.7%). Chronic inflammation conferred a protective effect from PCa: odds ratio (OR) = 0.20, 95% confidence interval (CI) = 0.15-0.28. Chronic inflammation was also inversely associated with HGPIN: OR = 0.11, 95% CI = 0.05-0.22. The ORs remained virtually unchanged after adjustment for age, serum prostate-specific antigen (PSA), digital rectal examination (DRE) and gland volume. Chronic inflammation is more frequent in the presence of benign histology than it is in the presence of PCa or HGPIN.

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.

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)0.003
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.601
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.029
GPT teacher head0.397
Teacher spread0.368 · 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