Abstract
Osteoarthritis (OA) is a debilitating disease that causes a giant socioeconomic burden. Until now, there is no drug to limit disease progression. There are important steps towards a drug for OA. First, we need to be able to predict in which patients the disease will progress and at what time using accurate prediction models. We may use this knowledge to better identify “early OA” patients and include patients who are expected to progress in clinical trials. Second, we need to select the right patient for the right treatment. This can be achieved by defining robust phenoor endotypes of OA and tailoring treatments towards specific pathomechanisms within pheno/endotypes. Third, we need a better understanding of pathologic mechanisms in OA to identify treatment targets. Fourth, we need to develop sensitive outcome markers for follow-up. In this thesis, small steps brought us closer to reaching these four goals.
Original language | English |
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Awarding Institution |
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Supervisors/Advisors |
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Award date | 27 Jan 2022 |
Place of Publication | Utrecht |
Publisher | |
Print ISBNs | 978-94-6419-428-9 |
DOIs | |
Publication status | Published - 27 Jan 2022 |
Keywords
- Osteoarthritis
- prediction
- computed tomography
- whole leg radiography
- knee
- hip
- calcifications
- OACT-score