ArticlePharmacoEconomics - open2024
Artificial-Intelligence Cloud-Based Platform to Support Shared Decision-Making in the Locoregional Treatment of Breast Cancer: Protocol for a Multidimensional Evaluation Embedded in the CINDERELLA Clinical Trial.
Article in PharmacoEconomics - open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05196269 (Comparing Decision on Match of Expectations and Aesthetics Using a Conventional Versus a Cloud-based Healthcare Platform Approach in Breast Cancer Patients Proposed for Locoregional Treatment), which is not on this map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Comparing Decision on Match of Expectations and Aesthetics Using a Conventional Versus a Cloud-based Healthcare Platform Approach in Breast Cancer Patients Proposed for Locoregional Treatment: A Prospective Randomized Trial
Who cites it
1 citing paper in PubMed.
- Evidence on Patient Decision Aids and Shared Decision-Making Across Breast Centers in Europe: A Cross-Sectional Survey Study.Cancer control : journal of the Moffitt Cancer CenterArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
backgroundShared decision-making (SDM) plays a crucial role in breast cancer care by empowering patients and reducing decision regret. Patient decision aids (PtDAs) are valuable tools for facilitating SDM, now available in digital and artificial intelligence (AI)-powered formats to offer increasingly personalized contents. The ongoing CINDERELLA clinical trial (ClinicalTrials.gov: NCT05196269) evaluates an innovative AI cloud-based approach using a web platform and a mobile application (CINDERELLA APProach) versus the conventional approach to support SDM in breast cancer patients undergoing locoregional treatment. This protocol outlines a trial-based multidimensional evaluation, encompassing economic, financial, implementability, and environmental considerations associated with the CINDERELLA APProach.
methodsA within-trial cost-consequence and cost-utility analysis from a societal perspective will be performed using patient-level data on outcomes and resource use. The latter will be valued in monetary terms using country-specific unit costs or patient valuations. A budget impact analysis will be performed over 1 and 5 years from the budget holder perspectives. The CINDERELLA APProach implementability will be assessed through an evaluation of its usability, acceptability, organizational impact, and overall feasibility. The environmental impact will be quantitatively assessed across several dimensions, such as quantity, appropriateness, and emissions, supplemented by qualitative insights. Overall, data for the evaluation will be gathered from patient questionnaires, interviews with patients and managers, focus groups with healthcare professionals, and app electronic data. DISCUSSION: A thorough understanding of the broad consequences of the CINDERELLA APProach may foster its successful translation into real-world settings, hopefully benefiting breast cancer patients and clinical practice.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.