Current practices in prostate pathology reporting: results from a survey of genitourinary and general pathologists
Notice bibliographique
Résumé
AIMS: Standardizing pathology reporting protocols through peer consensus review is critical for the best quality of care metrics. Reporting heterogeneity due to discrepancies among professional societies and practice patterns may lead to heterogeneous management and treatment approaches. This issue prompted a multi-institutional survey of pathologists to address potential similarities or differences in trends and practice patterns in prostate pathology reporting worldwide. METHODS AND RESULTS: A REDCap survey was distributed among 175 pathologists worldwide, recruited through invitations and social media. The response rate among invited pathologists was 83%. The practice locations were as follows: North America (USA, Canada, and Mexico, 62%), Europe (17%), Australia/New Zealand (3%), Central/South America (2%), Asia (13%), and Africa (2%). Most pathologists practiced for <5 years (28%). A genitourinary (GU) pathology fellowship was completed by 37%, 58% practiced in a subspecialized setting, and 43% in academia. Reporting includes (63%) or subtracts (37%) intervening benign tissue. Both Gleason score and Grade Groups (GG)s were reported by 96% of responders, whereas 94% report percent pattern 4 (%4). Aggregate grading and volume estimation in undesignated cores with different grades in the same jar are reported by 73% and 54% for systematic biopsies, and 83% and 62% for targeted biopsies, respectively. Cribriform morphology was reported by 81%. For presumed intraductal carcinoma (IDC), 89% use basal cell markers when isolated (iIDC), 82% with GG1 cancer, and 37% with ≥GG2. iIDC or IDC associated with GG1 or with ≥GG2 was not graded by 90%, 78%, and 70%, respectively. In radical prostatectomies, 90% report %4, but only 53% report it if the overall grade is ≥7. A tumour with Gleason 3 + 3 = 6 and <5% pattern 4 was graded as GG2 by 64%. A <5% cutoff for defining tertiary pattern was used by 74%, and 80% report >5% pattern 4 or 5 as a secondary pattern. Grading was assigned based on the dominant nodule by 59%. Finally, reporting practices were significantly associated with demographic characteristics. CONCLUSIONS: Although most issues are agreed upon, significant discordance is identified among societies and pathologists in different practice settings. We hope this survey will serve as the basis for future studies and new collaborative approaches to more standardized reporting practices.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».