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- Seers, Kate, et al.
(författare)
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FIRE (Facilitating Implementation of Research Evidence) : a study protocol
- 2012
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Ingår i: Implementation Science. - : BioMed Central (BMC). - 1748-5908. ; 7:25
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Research evidence underpins best practice, but is not always used in healthcare. The Promoting Action on Research Implementation in Health Services (PARIHS) framework suggests that the nature of evidence, the context in which it is used, and whether those trying to use evidence are helped (or facilitated) affect the use of evidence. Urinary incontinence has a major effect on quality of life of older people, has a high prevalence, and is a key priority within European health and social care policy. Improving continence care has the potential to improve the quality of life for older people and reduce the costs associated with providing incontinence aids. OBJECTIVES: This study aims to advance understanding about the contribution facilitation can make to implementing research findings into practice via: extending current knowledge of facilitation as a process for translating research evidence into practice; evaluating the feasibility, effectiveness, and cost-effectiveness of two different models of facilitation in promoting the uptake of research evidence on continence management; assessing the impact of contextual factors on the processes and outcomes of implementation; and implementing a pro-active knowledge transfer and dissemination strategy to diffuse study findings to a wide policy and practice community. SETTING AND SAMPLE: Four European countries, each with six long-term nursing care sites (total 24 sites) for people aged 60 years and over with documented urinary incontinence METHODS AND DESIGN: Pragmatic randomised controlled trial with three arms (standard dissemination and two different programmes of facilitation), with embedded process and economic evaluation. The primary outcome is compliance with the continence recommendations. Secondary outcomes include proportion of residents with incontinence, incidence of incontinence-related dermatitis, urinary tract infections, and quality of life. Outcomes are assessed at baseline, then at 6, 12, 18, and 24 months after the start of the facilitation interventions. Detailed contextual and process data are collected throughout, using interviews with staff, residents and next of kin, observations, assessment of context using the Alberta Context Tool, and documentary evidence. A realistic evaluation framework is used to develop explanatory theory about what works for whom in what circumstances. TRIAL REGISTRATION: Current Controlled Trials ISRCTN11598502.
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| 2. |
- Wang, Xinan, et al.
(författare)
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Impact of individual level uncertainty of lung cancer polygenic risk score (PRS) on risk stratification
- 2024
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Ingår i: Genome Medicine. - : BioMed Central (BMC). - 1756-994X .- 1756-994X. ; 16:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Although polygenic risk score (PRS) has emerged as a promising tool for predicting cancer risk from genome-wide association studies (GWAS), the individual-level accuracy of lung cancer PRS and the extent to which its impact on subsequent clinical applications remains largely unexplored.Methods: Lung cancer PRSs and confidence/credible interval (CI) were constructed using two statistical approaches for each individual: (1) the weighted sum of 16 GWAS-derived significant SNP loci and the CI through the bootstrapping method (PRS-16-CV) and (2) LDpred2 and the CI through posteriors sampling (PRS-Bayes), among 17,166 lung cancer cases and 12,894 controls with European ancestry from the International Lung Cancer Consortium. Individuals were classified into different genetic risk subgroups based on the relationship between their own PRS mean/PRS CI and the population level threshold.Results: Considerable variances in PRS point estimates at the individual level were observed for both methods, with an average standard deviation (s.d.) of 0.12 for PRS-16-CV and a much larger s.d. of 0.88 for PRS-Bayes. Using PRS-16-CV, only 25.0% of individuals with PRS point estimates in the lowest decile of PRS and 16.8% in the highest decile have their entire 95% CI fully contained in the lowest and highest decile, respectively, while PRS-Bayes was unable to find any eligible individuals. Only 19% of the individuals were concordantly identified as having high genetic risk (> 90th percentile) using the two PRS estimators. An increased relative risk of lung cancer comparing the highest PRS percentile to the lowest was observed when taking the CI into account (OR = 2.73, 95% CI: 2.12–3.50, P-value = 4.13 × 10−15) compared to using PRS-16-CV mean (OR = 2.23, 95% CI: 1.99–2.49, P-value = 5.70 × 10−46). Improved risk prediction performance with higher AUC was consistently observed in individuals identified by PRS-16-CV CI, and the best performance was achieved by incorporating age, gender, and detailed smoking pack-years (AUC: 0.73, 95% CI = 0.72–0.74). Conclusions: Lung cancer PRS estimates using different methods have modest correlations at the individual level, highlighting the importance of considering individual-level uncertainty when evaluating the practical utility of PRS.
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