An Evaluation of a Web-Based Decision Aid for Treatment Planning of Small Kidney Tumors: Pilot Randomized Controlled Trial
Notice bibliographique
Résumé
BACKGROUND: Surgery is the most common treatment for localized small kidney masses (SKMs) up to 4 cm, despite a lack of evidence for improved overall survival. Nonsurgical management options are gaining recognition, as evidence supports the indolence of most SKMs. Decision aids (DAs) have been shown to improve patient comprehension of the trade-offs of treatment options and overall decision quality, and may improve consideration of all major options according to individual health priorities and preferences. OBJECTIVE: This pilot randomized controlled trial (RCT) primarily aims to evaluate the impact of a new web-based DA on treatment decisions for patients with SKM; that is, selection of surgical versus nonsurgical treatment options. Secondary objectives include an assessment of decision-making outcomes: decisional conflict, decision satisfaction, and an understanding of individual preferences for treatment that incorporate the trade-offs associated with surgical versus nonsurgical interventions. METHODS: Three phases comprise the construction and evaluation of a new web-based DA on SKM treatment. In phase 1, this DA was developed in print format through a multidisciplinary design committee incorporating patient focus groups. Phase 2 was an observational study on patient knowledge and decision-making measures after randomization to receive the printed DA or institutional educational materials, which identified further educational needs applied to a web-based DA. Phase 3 will preliminarily evaluate the web-based DA: in a pilot RCT, 50 adults diagnosed with SKMs will receive the web-based DA or an existing web-based institutional website at urology clinics at a large academic medical center. The web-based DA applies risk communication and information about diagnosis and treatment options, elicits preferences regarding treatment options, and provides a set of options to consider with their doctor based on a decision-analytic model of benefits/harm analysis that accounts for comorbidity, age group, and tumor features. Questionnaires and treatment decision data will be gathered before and after viewing the educational material. RESULTS: This phase will consist of a pilot RCT from August 2022 to January 2023 to establish feasibility and preliminarily evaluate decision outcomes. Previous study phases from 2018 to 2020 supported the feasibility of providing the printed DA in urology clinics before clinical consultation and demonstrated increased patient knowledge about the diagnosis and treatment options and greater likelihood of favoring nonsurgical treatment just before consultation. This study was funded by the National Cancer Institute. Recruitment will begin in August 2022. CONCLUSIONS: A web-based DA has been designed to address educational needs for patients making treatment decisions for SKM, accounting for comorbidities and treatment-related benefits and risks. Outcomes from the pilot trial will evaluate the potential of a web-based DA in personalizing treatment decisions and in helping patients weigh attributes of surgical versus nonsurgical treatment options for their SKMs. TRIAL REGISTRATION: ClinicalTrials.gov NCT05387863; https://clinicaltrials.gov/ct2/show/NCT05387863. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/41451.
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 | 0,014 | 0,024 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,004 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,003 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,013 | 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 ».