Prostatic malakoplakia: clinicopathological assessment of a multi‐institutional series of 49 patients
Bibliographic record
Abstract
Prostatic malakoplakia (MP) is rare, with only case reports and small series (< five patients) available in the literature. In this study we analysed an international multi-institutional series of 49 patients with prostatic MP to more clearly define its clinicopathological features. The median age was 67 years and the median serum prostate-specific antigen (PSA) was 7.5 ng/ml. MP was clinically manifest in most cases (28 of 45 patients with data available, 62%). Of 43 patients with detailed clinical history available, 21 (49%) had concurrent or metachronous malignancies (including prostate cancer). Diabetes or insulin resistance was present in 11 patients (26%). Additionally, three patients had a history of solid organ transplantation and one had HIV. Of note, six of 34 patients (18%) without concurrent prostate cancer had an abnormal digital rectal examination and/or lesions on magnetic resonance imaging (MRI) with prostate imaging reporting and data system (PIRADS) scores 4-5. The initial diagnosis was made on core biopsies (25 of 49, 51%), transurethal resection specimens (12 of 49, 24%), radical prostatectomies (10 of 49, 20%), Holmium-laser enucleation (one of 49, 2%) and cystoprostatectomy (one of 49, 2%). Tissue involvement was more commonly diffuse or multifocal (40 of 49, 82%). Von Kossa and periodic acid-Schiff stains were positive in 35 of 38 (92%) and 26 of 27 lesions (96%), respectively. Of note, two cases were received in consultation by the authors with a preliminary diagnosis of mesenchymal tumour/tumour of the specialised prostatic stroma. The present study suggests that prostatic MP is often associated with clinical findings that may mimic those of prostate cancer in a subset of patients. Moreover, MP may be found incidentally in patients with concurrent prostate cancer.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".