The ability of prostate‐specific antigen (PSA) density to predict an upgrade in Gleason score between initial prostate biopsy and prostatectomy diminishes with increasing tumour grade due to reduced PSA secretion per unit tumour volume
Notice bibliographique
Résumé
UNLABELLED: Study Type - Diagnostic (exploratory cohort) Level of Evidence 2b What's known on the subject? and What does the study add? Due to sampling error, the Gleason score of clinically localized prostate cancer is frequently underestimated at the time of initial biopsy. Given that this may lead to inappropriate surveillance of patients with high-risk disease, there is considerable interest in identifying predictors of significant undergrading. Recently PSAD has been proposed to be an accurate predictor of subsequent upgrading in patients diagnosed with Gleason 6 disease on biopsy. We examined the predictive characteristics of PSAD in patients with low- and intermediate-risk disease on biopsy subsequently treated with radical prostatectomy. We found that although PSAD was a significant predictor of upgrade of biopsy Gleason 6 and 3 + 4 = 7 tumours, it failed to predict upgrading in patients with Gleason 7 tumours taken as a whole. When we explored reasons for this discrepancy, we found that the amount of PSA produced per unit tumour volume decreased with increasing Gleason score, thereby diminishing the predictive value of PSAD. OBJECTIVES: To analyse the performance of PSA density (PSAD) as a predictor of Gleason score upgrade in a large cohort stratified by Gleason score. We and others have shown that an upgrade in Gleason score between initial prostate biopsy and final radical prostatectomy (RP) pathology is a significant risk factor for recurrence after local therapy. PATIENTS AND METHODS: Patients undergoing RP with matching biopsy information were identified from two prospective databases. Patients were analysed according to the concordance between biopsy and final pathology Gleason score in three paired groups: 6/>6, 3 + 4/>3 + 4, 7/>7. Receiver-operating characteristic (ROC) curves were generated stratified by Gleason score, and the area under the curve (AUC) calculated. Logistic regression models were fitted to identify significant predictors of tumour upgrade. RESULTS: From 1516 patients, 435 (29%) had an upgrade in Gleason score. ROC analysis showed a decline in AUC with increasing biopsy Gleason score, from 0.64 for biopsy Gleason score 6, to 0.57 for Gleason score 7. In logistic regression models containing pretreatment variables, e.g. clinical stage and number of positive cores, for Gleason score 6 and 3 + 4, PSAD was the strongest predictor of subsequent tumour upgrade (odds ratio [OR] 1.46, 95% confidence interval [95% CI] 1.18-1.83, P= 0.001 and OR 1.37, 95% CI 1.14-1.67, P= 0.002, respectively). Surprisingly, in tumours upgraded from Gleason score 7 to >7, PSAD was not predictive even on univariable analysis, whereas clinical stage and number of positive cores were significant independent predictors. To explore the relationship between serum PSA and Gleason score, tumour volume was calculated in 669 patients. There was a strong association between Gleason score and tumour volume, with the median volume of Gleason score 7 and Gleason score >7 tumours being approximately twice and four-times that of Gleason score 6 tumours, respectively (P < 0.001). In contrast, the median serum PSA level per millilitre tumour volume decreased significantly with increasing grade, from 5.4 ng/mL for Gleason score 6 to 2.1 ng/mL for >7 (P < 0.001). CONCLUSIONS: There is a strong correlation between Gleason score and tumour volume in well/intermediate differentiated tumours, and as they produce relatively high amounts of PSA per unit volume of cancer, high PSAD is the strongest single predictor of tumour undergrading. However, as higher grade tumours produce less PSA per unit volume, PSAD loses its predictive ability, and other clinical markers of tumour volume such as palpable disease and numbers of positive cores become more predictive.
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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 | 0,000 |
| 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 | 0,001 |
| 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 ».