PD44-11 UNDERSTANDING THE PERFORMANCE OF ACTIVE SURVEILLANCE SELECTION CRITERIA IN REAL-WORLD PRACTICE
Notice bibliographique
Résumé
You have accessJournal of UrologyProstate Cancer: Detection and Screening IV1 Apr 2015PD44-11 UNDERSTANDING THE PERFORMANCE OF ACTIVE SURVEILLANCE SELECTION CRITERIA IN REAL-WORLD PRACTICE Scott Hawken, Paul Womble, Lindsey Herrel, Zaojun Ye, Susan Linsell, James Montie, and David Miller Scott HawkenScott Hawken More articles by this author , Paul WomblePaul Womble More articles by this author , Lindsey HerrelLindsey Herrel More articles by this author , Zaojun YeZaojun Ye More articles by this author , Susan LinsellSusan Linsell More articles by this author , James MontieJames Montie More articles by this author , and David MillerDavid Miller More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2015.02.2557AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Although there are many published guidelines for selecting patients for Active Surveillance (AS), little is known about how well these work in real-world practice. We used data from the Michigan Urological Surgery Improvement Collaborative (MUSIC) to evaluate the performance of several published guidelines for identifying patients actually undergoing initial AS in diverse community and academic practices. METHODS From March 2012 through October 2014, clinicopathologic and treatment data for 4,934 men with newly-diagnosed prostate cancer were entered into the MUSIC registry. For several accepted AS guidelines (Table), we calculated the proportion of all men meeting each set of selection criteria that actually entered AS (defined as the sensitivity of the guideline for real world practice patterns). Using the single guideline determined to be most sensitive for the entire cohort, we then compared demographics, tumor volume, and life expectancy (based on a published algorithm) for patients meeting this guideline who entered AS and those who received definitive therapy. RESULTS Overall, 871 men (20%) underwent initial AS. When applied to the entire patient cohort, published guidelines varied widely in their sensitivity for identifying patients initiating AS, ranging from 49% (Toronto) to 64% (Johns Hopkins, JH) (Table). At a practice-level, the sensitivity of the JH guideline (the most sensitive for the entire cohort) spanned from 29% to 84% across participating sites (p<0.001). Compared with men undergoing initial AS, patients meeting the JH criteria that received definitive therapy were more likely to have 2 (vs 1) positive cores on biopsy (p=0.003). The greatest percentage of a core positive for cancer was also higher in treated men (13% vs 11%, p=0.01). The proportion of patients with life expectancy greater than 10 years was similar for these two groups (p=0.4). CONCLUSIONS Published AS selection guidelines vary widely in their sensitivity for identifying men who initiate this treatment in real-world practice. Among patients meeting the most sensitive criteria, those who received definitive therapy had evidence of higher tumor volume, but not longer life expectancy, underscoring the influence of even small differences in cancer severity on treatment decisions. Active Surveillance selection criteria and performance Guideline Gleason Score PSA PSA Density T-Stage Positive Cores GPC* (%) Patients Meeting Selection Criteria (n) Sensitivity (95% CI) JH ≤ 6 – < 0.15 cT1c ≤ 2 ≤ 50 463 64 (59-68) NCCN: Very Low Risk ≤ 6 <10 < 0.15 cT1c ≤ 2 ≤ 50 445 63 (59-68) MSKCC ≤ 6 <10 – ≤ cT2a ≤ 3 < 50 948 56 (53-60) UCSF ≤ 6 ≤10 – ≤ cT2 ≤ 33% ≤ 50 1048 54 (51-57) NCCN: Low Risk ≤ 6 <10 – ≤ cT2a – – 1228 50 (47-52) Toronto ≤ 6 <10 – – – – 1282 49 (46-51) *GPC: Greatest Percentage Positive of a Biopsy Core © 2015 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 193Issue 4SApril 2015Page: e901 Advertisement Copyright & Permissions© 2015 by American Urological Association Education and Research, Inc.MetricsAuthor Information Scott Hawken More articles by this author Paul Womble More articles by this author Lindsey Herrel More articles by this author Zaojun Ye More articles by this author Susan Linsell More articles by this author James Montie More articles by this author David Miller 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 | 0,049 | 0,283 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,005 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».