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Record W2809344555 · doi:10.1016/j.ehpc.2018.05.005

IgG4 prostatitis associated with prostatic adenocarcinoma: A case report and literature review

2018· article· en· W2809344555 on OpenAlexaff
Shaun Medlicott, A. F. Oryschak, Kiril Trpkov

Bibliographic record

VenueHuman Pathology Case Reports · 2018
Typearticle
Languageen
FieldMedicine
TopicIgG4-Related and Inflammatory Diseases
Canadian institutionsUniversity of CalgaryCalgary Laboratory Services
Fundersnot available
KeywordsProstatitisMedicineProstateAdenocarcinomaProstatectomyBiopsyUrologyProstate-specific antigenPathologyInternal medicineCancer

Abstract

fetched live from OpenAlex

A 66-year-old male patient had a prostate biopsy for an elevated serum prostate specific antigen which revealed prostatic adenocarcinoma, Gleason score 3 + 4 = 7 (Grade group 2) with marked background chronic inflammation. A radical prostatectomy showed prostatic adenocarcinoma accompanied by IgG4 prostatitis, which had not been appreciated in the biopsy. The patient had chronic asthma and 4 years prior to the biopsy he had been diagnosed with IgG4-related orbital disease. This history was however unknown during the initial interpretation of the prostate biopsy and prostatectomy. No autoimmune pancreatobiliary involvement was documented at any point, either initially or during the follow-up. IgG4-related prostatitis and prostatic adenocarcinoma have been previously reported to occur simultaneously only in 2 cases. We provide additional evidence that prostatic adenocarcinoma and IgG4-related disease may be found synchronously in the prostate. Therefore, it is important to consider the possibility of an unrecognized IgG4 prostatitis, whenever a heavy lymphoplasmacytic inflammation is found in the prostate, particularly in the absence of a marked granulomatous reaction. To our knowledge, IgG4 prostatitis and prostatic adenocarcinoma accompanied by orbital IgG4-related disease, but without a pancreatobiliary involvement, have not been previously documented.

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)0.001
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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.012
GPT teacher head0.278
Teacher spread0.266 · 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 designCase report
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
Published2018
Admission routes1
Has abstractyes

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