MP19-03 COMPARISON OF FACT-G SCORES WITH CANCER AND GENERAL POPULATION NORMS IN CANADIAN PATIENTS UNDERGOING RADICAL CYSTECTOMY
Notice bibliographique
Résumé
You have accessJournal of UrologyHealth Services Research: Practice Patterns, Quality of Life and Shared Decision Making II (MP19)1 Sep 2021MP19-03 COMPARISON OF FACT-G SCORES WITH CANCER AND GENERAL POPULATION NORMS IN CANADIAN PATIENTS UNDERGOING RADICAL CYSTECTOMY Julie Trudel, Ryan McLarty, and Conrad Maciejewski Julie TrudelJulie Trudel More articles by this author , Ryan McLartyRyan McLarty More articles by this author , and Conrad MaciejewskiConrad Maciejewski More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002004.03AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: The Functional Assessment of Cancer Therapy-General (FACT-G) is often used as a generic measure in Health-Related Quality of Life (HRQOL) assessment among cancer patients. Its reference values relating to the general population and patients with different diseases are useful for the interpretation of HRQOL scores and allow a better understanding of the patients needs and HRQOL. No study to date has yet compared FACT-G normative data scores to those of Canadian patients undergoing radical cystectomy (RC) for bladder cancer. The objective of this study was to compare our patients pre-cystectomy FACT-G scores with US cancer and general population norms. METHODS: Patients were recruited from the Diana Wood Cancer Survivorship Clinic at The Ottawa Hospital between January 2019 and August 2020. HRQOL was evaluated by the FACT-G and raw scores were obtained for each FACT-G subscale, higher scores indicating better HRQOL. Effect sizes (ES-Hedge's g statistics), confidence intervals and minimal clinical significant differences (MCIDs) were used to compare pre FACT-G subscale scores with normative data. As suggested by current literature, a change of at least 5% to 10% within the instrument range was used as an estimate calculation of the MCID. RESULTS: 55 patients completed the FACT-G questionnaire before RC. The mean age was 67 years (SD: 10 years), 71% were male, 80% were in a married/common law partnership and 84% lived with someone. Overall, ES between pre-surgery FACT-G subscale scores and US cancer norms were small (ES≤0.2) and the MCIDs were less than 5% of change in the FACT-G measurement scale except for the dimension “Physical Well-Being” (ES=0.3, reported MCID value of 1.77, 6% of change). ES calculated between FACT-G scores and those from the US general population showed small effect sizes (ES≤0.2) for all FACT-G subscales except for the dimensions “Emotional Well-Being” (Medium ES=-0.56, reported MCID value of 2.7, 11% of change) and “Social Well-Being” (Medium ES=0.37, reported MCID value of 2.5, 9% of change). CONCLUSIONS: In our survivorship clinic, patients undergoing RC reported broadly similar FACT-G scores to US cancer population norms, with a notable exception of increased perceived “Physical Well-Being”. When comparing our data to US population norms, we once again showed similar scores on FACT-G subscales with the exception of decreased “Emotional Well-Being” and higher “Social Well-Being”. These results emphasize unique aspects of the bladder cancer survivorship experience, and highlight the value of patient reported assessment of HRQOL in RC patients. Source of Funding: The Diana Wood Bladder Cancer Survivorship Program © 2021 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 206Issue Supplement 3September 2021Page: e328-e328 Advertisement Copyright & Permissions© 2021 by American Urological Association Education and Research, Inc.MetricsAuthor Information Julie Trudel More articles by this author Ryan McLarty More articles by this author Conrad Maciejewski More articles by this author Expand All Advertisement Loading ...
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 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».