MP79-11 IMPACT OF KI67 LABELING INDEX ON PROGRESSION AND DEATH OF PROSTATE CANCER POST-PROSTATECTOMY: COMPARISON OF VISUAL AND AUTOMATED SCORING
Notice bibliographique
Résumé
You have accessJournal of UrologyProstate Cancer: Markers II1 Apr 2014MP79-11 IMPACT OF KI67 LABELING INDEX ON PROGRESSION AND DEATH OF PROSTATE CANCER POST-PROSTATECTOMY: COMPARISON OF VISUAL AND AUTOMATED SCORING Ta Ben-Zvi, Patrice Desmeules, Hélène Hovington, Caroline Léger, André Caron, Louis Lacombe, Yves Fradet, Bernard Têtu, and Vincent Fradet Ta Ben-ZviTa Ben-Zvi More articles by this author , Patrice DesmeulesPatrice Desmeules More articles by this author , Hélène HovingtonHélène Hovington More articles by this author , Caroline LégerCaroline Léger More articles by this author , André CaronAndré Caron More articles by this author , Louis LacombeLouis Lacombe More articles by this author , Yves FradetYves Fradet More articles by this author , Bernard TêtuBernard Têtu More articles by this author , and Vincent FradetVincent Fradet More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2014.02.2514AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Even after radical prostatectomy (RP), prostate cancer (PCa) demonstrates high variability in its aggressiveness, currently imperfectly predictable. Better prognostic markers are needed. The tumor proliferative index has shown interesting associations in PCa. Its application has limitations: low expression level, lack of uniformity and consistency in quantification. The purpose of this study was to evaluate whether the tumor proliferation index, as assessed with Ki67 by virtual microscopy and digital image analysis (DIA), could predict the occurrence of progression and death in men with PCa after radical prostatectomy (RP). METHODS A tissue microarray series of PCa (251 men; RP 1998-2006) at CHU-L’Hôtel-Dieu de Québec was immunostained for Ki67 (Mib-1, DAKO) and digitized. Ki67 positive nuclei in malignant cells (%) were assessed manually on virtual slides. For DIA, tissue segmentation and staining quantification algorithms using CalopixTM (Tribvn, distributed by AGFA Healthcare) were developed, and Histoscore (H-score) was calculated. Patients underwent complete follow-up (bi-annual PSA and clinical follow-up). Adjusted hazard ratios (HR) of progression (biochemical recurrence (BR); PSA ≥0.2ng/ml), death of disease (DOD), and 95% confidence intervals (CI) were estimated via Cox proportional hazard regression model. RESULTS Kaplan-Meier analyses showed that high Ki67 labeling index (≥4.2%) was associated with increased risk of BR and DOD (logrank p<0.0131; p<0.0101), when assessed manually. H-score (≥7%) utilizing DIA results demonstrated increased risk for BR and DOD (logrank p<0.0085; p<0.0004). In multivariate Cox regression models, correcting for age, PSA and grade, a high proliferation index was significantly associated with BR and DOD. Meanwhile, both univariate and multivariate Cox regression models have shown that Ki-67 is not associated with the risk of death from other causes. CONCLUSIONS In this cohort, high Ki67 index is an independent prognostic factor for BR and DOD. Ki67 quantification by DIA reproduced all significant associations observed with manual scoring. These findings support the use of automated DIA tools for objective and reproducible biomarker quantification and subsequent integration in future clinical algorithms. Multivariate cox proportional hazards regression analysis to predict biochemical recurrence and disease-specific mortality in prostate cancer, using Ki67 proliferative index Biochemical recurrence P-value Biochemical recurrence P-value Hazard ratio (95% CI) Hazard ratio (95% CI) Visual scoring < 4.2% 1.0 1.0 > 4.2% 1.8 (1.1-2.9) 0.02 5,6 (1,5-20,9) 0.01 Digital image analysis H-Score < 7% 1.0 1.0 H-Score > 7% 1.7 (1.1-2.7) 0.03 9.0 (2,1-38,4) 0.003 © 2014FiguresReferencesRelatedDetails Volume 191Issue 4SApril 2014Page: e933-e934 Advertisement Copyright & Permissions© 2014Metrics Author Information Ta Ben-Zvi More articles by this author Patrice Desmeules More articles by this author Hélène Hovington More articles by this author Caroline Léger More articles by this author André Caron More articles by this author Louis Lacombe More articles by this author Yves Fradet More articles by this author Bernard Têtu More articles by this author Vincent Fradet More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
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 source (Gemma direct ou Codex distillé), 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 ».