PD08-02 THE BLADDER UTILITY SYMPTOM SCALE (UTILITY): A NOVEL TOOL TO MEASURE UTILITIES AND QUALITY OF LIFE IN BLADDER CANCER PATIENTS
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Résumé
You have accessJournal of UrologyHealth Services Research: Value of Care: Cost and Outcomes I (PD08)1 May 2024PD08-02 THE BLADDER UTILITY SYMPTOM SCALE (UTILITY): A NOVEL TOOL TO MEASURE UTILITIES AND QUALITY OF LIFE IN BLADDER CANCER PATIENTS Girish S. Kulkarni, Nathan Perlis, Douglas Cheung, Karen E. Bremner, Mia Papasideris, Katherine Lajkosz, Nicholas Power, Robert K. Nam, and George Tomlinson Girish S. KulkarniGirish S. Kulkarni , Nathan PerlisNathan Perlis , Douglas CheungDouglas Cheung , Karen E. BremnerKaren E. Bremner , Mia PapasiderisMia Papasideris , Katherine LajkoszKatherine Lajkosz , Nicholas PowerNicholas Power , Robert K. NamRobert K. Nam , and George TomlinsonGeorge Tomlinson View All Author Informationhttps://doi.org/10.1097/01.JU.0001008576.33217.96.02AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Bladder cancer (BCa) and its treatments have significant impacts on patient quality of life (QOL) and decision-making. To facilitate comparative effectiveness research, a BCa specific tool to measure both quality of life and utilities is required. We previously created and validated the Bladder Utility Symptom Scale (BUSS)-Psychometric (P), a 10-item multiple-choice questionnaire to measure QOL in all phases of BCa care. Our objective was to create two distinct algorithms to calculate utilities from BUSS-P responses. METHODS: We conducted in-person interviews with 200 BCa patients and 200 members of the general public. Purposeful sampling was used to ensure proportionate numbers of non-muscle invasive (NMIBC), muscle invasive (MIBC) and metastatic BCa patients. The general public sample was recruited proportionate to national age, sex, and income distributions. Each respondent provided time tradeoff (TTO) utilities for 12 randomly-generated health state scenarios based on the BUSS-P attributes. Bayesian generalized linear multilevel models were used to estimate the impact of each of the 10 BUSS-P attributes to utility which was bound by 0 and 1. Pearson correlation coefficients were calculated between observed and expected model values. Two algorithms to calculate utilities from BUSS-P responses were then generated – one derived from BCa patients and one from the general public. RESULTS: Of 400 participants, 322 completed the TTO exercises with adequate comprehension. Of the BCa patients, 70 were NMIBC, 53 MIBC and 32 metastatic. A total of 3,288 randomly generated, unique BUSS-P health state valuations were obtained. The final model had a weighted correlation coefficient between predicted and observed utilities of 0.733 and 0.734 in the community and patient groups, respectively. A final table of weights for each response level of each question was created for final utility calculation. In an exploratory analysis of patients' own BUSS-Ucresponses, discrimination of utilities across health states was observed with mean (SD) utilities in NMIBC, cystectomy and minimally symptomatic metastatic patients at 0.897 (0.099), 0.831 (0.109) and 0.825 (0.157), respectively. CONCLUSIONS: The BUSS-P is the first instrument that provides utilities for BCa derived from both BCa patients and the general public. Grounded in robust TTO methodology, utilities in all phases of BCa care can be measured for use in comparative effectiveness research, cost-effectiveness and decision modeling and policy work. Source of Funding: Canadian Institutes for Health Research and the Canadian Cancer Society © 2024 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 211Issue 5SMay 2024Page: e173 Advertisement Copyright & Permissions© 2024 by American Urological Association Education and Research, Inc.Metrics Author Information Girish S. Kulkarni More articles by this author Nathan Perlis More articles by this author Douglas Cheung More articles by this author Karen E. Bremner More articles by this author Mia Papasideris More articles by this author Katherine Lajkosz More articles by this author Nicholas Power More articles by this author Robert K. Nam More articles by this author George Tomlinson More articles by this author Expand All 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 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 | 0,011 | 0,002 |
| 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 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».