https://www.selleckchem.com/pr....oducts/bgb-15025.htm
432; 95% CI -0.954, 0.078) reduced the risk. The final model explained 60% of variance and bias was low (- 0.006 to 0.002). Different modelling approaches are needed to predict rather than explain patient reported outcomes. We developed a parsimonious and pragmatic PRM. External validation is required prior to translation to digital tool and evaluation of clinical implementation. The routine use of PROs and data driven PRM in practice provides a new opportunity to target supportive care and specialist interventions for cancer patients
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