PD07-07 PERSONAL PSA SCREENING AND TREATMENT CHOICES FOR LOCALIZED PROSTATE CANCER AMONG EXPERT PHYSICIANS
Notice bibliographique
Résumé
You have accessJournal of UrologyProstate Cancer: Detection & Screening II1 Apr 2017PD07-07 PERSONAL PSA SCREENING AND TREATMENT CHOICES FOR LOCALIZED PROSTATE CANCER AMONG EXPERT PHYSICIANS Christopher Wallis, Douglas Cheung, Laurence Klotz, Venu Chalasani, Ricardo Leao, Juan Garisto, Gerard Morton, Robert Nam, Ian Tannock, and Raj Satkunasivam Christopher WallisChristopher Wallis More articles by this author , Douglas CheungDouglas Cheung More articles by this author , Laurence KlotzLaurence Klotz More articles by this author , Venu ChalasaniVenu Chalasani More articles by this author , Ricardo LeaoRicardo Leao More articles by this author , Juan GaristoJuan Garisto More articles by this author , Gerard MortonGerard Morton More articles by this author , Robert NamRobert Nam More articles by this author , Ian TannockIan Tannock More articles by this author , and Raj SatkunasivamRaj Satkunasivam More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2017.02.382AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Prostate-specific antigen (PSA) based prostate cancer (PCa) screening and treatment choice for localized PCa remain highly controversial. The physician surrogate method seeks to identify acceptable healthcare interventions by ascertaining the interventions physicians select for themselves. We surveyed urologists, radiation oncologists, and medical oncologists with respect to their personal practices and recommendations to immediate family members regarding PSA screening and the treatment of localized PCa. METHODS A hierarchical, contingent survey was developed by consensus among a team of urologists, radiation oncologists, and medical oncologists. After piloting, it was electronically circulated to eligible members of the Canadian Urological Association, Genitourinary Radiation Oncologists of Canada, Urologist, Medical Oncologist and Radiation Oncologist Members of the American Medical Association, Urological Society of Australia and New Zealand and Confederacion Americana de Urologia. We characterized physicians' choices regarding PSA screening and PCa treatment. Among urologists and radiation oncologists, we assessed for correlation between specialty and treatment selection. RESULTS Of 893 respondents, 869 provided consent and completed the survey. Their median age was 50 years (IQR 41-60 years) and most were male (n=807; 93%) and lived in Canada (n=413; 47%) or the United States (n=143; 16%). 719 (83%) were urologists, 89 (10%) radiation oncologists, 9 (1%) medical oncologists, 8 (1%) other specialties (e.g. internist) and 45 did not provide specialty information. Of 807 male respondents, 494 (61%) had personally undergone PSA screening and 662 (82%) planned to in the future. Of 62 female respondents, 43 (69%) had recommended PSA testing to immediate family members. In total, 784 of 869 respondents (90%) endorsed past or future screening for themselves or for relatives. 30 (4%) of men had been diagnosed with PCa personally and 16 (26%) of women had recommended PCa treatment to an immediate family member. After restricting to responses from urologists and radiation oncologists, there was a significant correlation between physician specialty and the treatment selected (Phi coefficient=0.61; p=0.001). CONCLUSIONS Physicians who routinely treat PCa are very likely to undertake PCa screening themselves or recommend it for their immediate family members. Among those diagnosed with prostate cancer, there is a significant correlation between specialty and treatment selection. © 2017FiguresReferencesRelatedDetails Volume 197Issue 4SApril 2017Page: e130 Advertisement Copyright & Permissions© 2017MetricsAuthor Information Christopher Wallis More articles by this author Douglas Cheung More articles by this author Laurence Klotz More articles by this author Venu Chalasani More articles by this author Ricardo Leao More articles by this author Juan Garisto More articles by this author Gerard Morton More articles by this author Robert Nam More articles by this author Ian Tannock More articles by this author Raj Satkunasivam 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 | 0,002 | 0,011 |
| 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 | 0,002 | 0,000 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,309 | 0,095 |
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 ».