The Effect of Pre-Biopsy Prostate MRI on the Congruency and Upgrading of Gleason Grade Groups Between Prostate Biopsy and Radical Prostatectomy
Notice bibliographique
Résumé
Introduction: Prostate biopsy results form the mainstay of patient care. However, there is often significant discordance between the biopsied histology and the ‘true’ histology shown on a radical prostatectomy (RP). Discordance in pathology can lead to the mismanagement of patients, potentially missing clinically significant cancer and delaying treatment. There have been many advancements to improve the concordance of pathology and more accurately counsel patients; most notably, the induction of pre-biopsy mpMRIs has become a gold standard to aid in triaging and identifying clinically significant cancers, and also to facilitate ‘targeted’ biopsies. Although there have been multiple reviews on MRI-targeted biopsies, upgrading remains an ongoing phenomenon. Aim: To assess the rates of prostate cancer upgrading and the clinical implication of upgrading on NCCN stratification. Methods: We conducted a retrospective audit of 2994 men with non-metastatic prostate cancer diagnosed between 2010 and 2019 who progressed to a radical prostatectomy within 1 year of diagnosis without alternative cancer treatment from the multi-institutional South Australia Prostate Cancer Clinical Outcomes Collaborative registry. The study compared the histological grading between the biopsies and radical prostatectomies of men with prostate cancer and the varying rates of upgrading and downgrading for patients with and without a pre-biopsy MRI. Data were also obtain on suspected confounding variables; age, PSA, time to RP, T-stage at diagnosis and RP, number of cores, number of positive cores, prostate size, tumour volume and procedure type. The results were assessed through cross tabulation and uni- and multi-variate logistic regression while adjusting for confounders. Results: Upgrading occurred in (926) 30.9% of patients and downgrading in (458) 15.3% of patients. In total, 71% (410/579) of grade group 1 and 24.9% (289/1159) of grade group 2 were upgraded following a radical prostatectomy. By contrast, 33.4% (373/1118) of patients without prebiopsy MRI were upgraded at RP compared to 29.5% (553/1876) of the patients who received a pre-biopsy MRI. When analysed on a uni-variate level, the inclusion of a pre-biopsy MRI demonstrated a statically significant decrease in upgrading of the patient’s pathology and NCCN risk stratification (p = 0.026, OR 0.83, CI 0.71–0.98) (p = 0.049, OR 0.82, CI 0.64–1.01). However, when adjusted for confounders, the use of an MRI did not maintain a statistically significance. Conclusions: When considering the multiple variables associated with tumour upgrading, a pre-biopsy MRI did not show a statistically significant impact. However, upgrading of Gleason Grade Group following a prostatectomy is an ongoing phenomenon which can carry significant treatment implications and should remain a consideration with patients and clinicians when making decisions around treatment pathways. More research is still required to understand and improve biopsy grading to prevent further upgrading from affecting treatment choices.
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 | 0,004 | 0,024 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 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 ».