DGH - Dissertações de mestrado
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- Multiple criteria decision analysis for biomarker prioritization: developing a socio-technical approach to assist researchers and clinicians in biomarker selection for validation and translation into clinical applicationsPublication . Ribeiro Norte, Beatriz; Correia de Oliveira, Mónica Duarte; Penque, DeborahAlthough thousands of biomarkers have already been discovered, not many have been applied into clinical practice, due to the high time and monetary resources necessary for their identification and validation. Due to its complexity and heterogeneity, and consequent lack of specific biomarkers, Chronic Obstructive Pulmonary Disease (COPD) is ideal to apply the model developed in this thesis. With the purpose of evaluating and selecting the most promising COPD prognostic biomarkers among those found in literature, a multiple-criteria decision analysis (MCDA) model was developed, with focus on the structuring phase. To meet this goal, a socio-technical approach based on the MACBETH method was followed, including an assessment of areas of concern in the biomarker field, the definition of criteria for biomarker selection and respective descriptors of performance and reference levels (using literature, interviews and a Web-Delphi), testing for preference dependence and the design of the resultant value tree. Results show that experts believe that the clinical relevance, clinical added value, quality of studies and test reliability are relevant dimensions, while the costs of development, the patient comfort, the easiness to measure and analyse a biomarker and the easiness to interpret the results are secondary, as one must be available to give up certain benefits if the biomarker significantly improves the patients’ health/well-being. Although ten evaluation dimensions were considered relevant by experts, some dependencies were found, namely between the evaluation dimensions clinical relevance and clinical added value, leading to the grouping and reformulation of the dependent dimensions, resulting in independent evaluation criteria. Overall, and despite some difficulties, the approach applied in this thesis worked well, resulting in a good structure for the MCDA model, with seven well defined and relevant evaluation criteria for the prioritization of COPD prognostic biomarkers. In the future, it would be interesting to complete the model, including the building, testing and validation phases of the model.