Journal of clinical epidemiology
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Diagnostic and prognostic prediction models often perform poorly when externally validated. We investigate how differences in the measurement of predictors across settings affect the discriminative power and transportability of a prediction model. ⋯ When a prediction model is applied to a different setting to the one in which it was developed, its discriminative ability can decrease or even increase if the magnitude or structure of the errors in predictor measurements differ between the two settings. This provides an important starting point for researchers to better understand how differences in measurement methods can affect the performance of a prediction model when externally validating or implementing it in practice.
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Multicenter Study
Evidence to Decision framework provides a structured "roadmap" for making GRADE guidelines recommendations.
It is unclear how guidelines panelists discuss and consider factors (criteria) that are formally and not formally included in the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. To describe the use of decision criteria, we explored how panelists adhered to GRADE criteria and sought to identify any emerging non-GRADE criteria when the panelists used the Evidence to Decision (EtD) framework as part of GRADE application. ⋯ The GRADE EtD framework provides structure to guidelines panel meetings, and ensures that the panelists consider all established formal GRADE criteria as they decide on the recommendation text, strength, and direction (for or against an intervention). This is the first study assessing the use of GRADE's EtD framework during real-time guidelines development using panel discussions. Given the widespread use of GRADE, this study provides important information for practice recommendations generated when guidelines panels explicitly follow, in a transparent and systematic manner, the structured GRADE EtD framework. By recognizing the extent to which panels discuss and consider GRADE and other (non-GRADE) criteria for producing guideline recommendations, we are one step closer to understanding the decision-making process in panels that use a structured framework such as the GRADE EtD framework.
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Despite their essential role in collecting and organizing published medical literature, indexed search engines are unable to cover all relevant knowledge. Hence, current literature recommends the inclusion of clinical trial registries in systematic reviews (SRs). This study aims to provide an automated approach to extend a search on PubMed to the ClinicalTrials.gov database, relying on text mining and machine learning techniques. ⋯ The proposed machine learning instrument has the potential to help researchers identify relevant studies in the SR process by reducing workload, without losing sensitivity and at a small price in terms of specificity.
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To synthesize the measurement properties of six health-related quality of life instruments (Short Form 36 [SF-36], Short Form 12 [SF-12], EuroQol 5D-3L [EQ-5D-3L], EuroQol 5D-5L [EQ-5D-5L], Nottingham Health Profile (NHP), and Patient-Reported Outcome Measurement Information System Global Health [PROMIS-GH-10]) in patients with low back pain (LBP). ⋯ Documentation of the measurement properties of health-related quality of life instruments in LBP is incomplete. Future clinimetric studies should prioritize content validity.
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To explore the impact of applying the Grading of Recommendations and Assessment, Development, and Evaluation (GRADE) approach to assess the certainty of the evidence in a published network meta-analysis (NMA) of antidepressant therapies. ⋯ In this example, application of GRADE highlighted varying evidence certainty, led to more conservative conclusions, and potentially avoided unwarranted strong inferences based on low certainty evidence.