Rheumatology Department, University Hospital Centre Rouen, Rouen, Normandie, France
Rheumatology Department, University Hospital Centre Rouen, Rouen, Normandie, France.
RMD Open. 2024 Sep 28;10(3):e004472. doi: 10.1136/rmdopen-2024-004472.
In rheumatoid arthritis (RA), the identification of prognostic factors (PF) capable of predicting disease outcome, response to treatment or success of dose reduction is an important issue, as these factors are intended to serve as a basis for decision-making. The task is complex from the outset, as the definition of disease prognosis or therapeutic prognosis is not uniquevocal. The heterogeneity of the definitions used partly explains the failure to identify PF that can be applied at an individual level. But other factors also contribute. First, the scope of the disease studied is too broad, including nosologically different entities. Second, potential PF are only measured at a single point of time, whereas changes over a period of time should be taken into account to a greater extent, not forgetting the potential impact of the treatment received during this period. Beyond these limiting factors, one of the main obstacles to the identification of PF is probably the fact that the phase of the disease is not sufficiently taken into account. Predicting the disease outcome when it is well established is a more complex challenge than when it is just beginning, as many factors are likely to interfere. The same applies to therapeutic PF, which should be determined according to disease duration. Difficulties also arise from the approaches used, which are often restricted to a single field of interest whereas they should be much more integrative and call on new large-scale data analysis tools with a view to precision medicine.In RA, prognosis can be defined at two levels: disease outcome, including joint damage and risk of extra-articular manifestations and/or complications, and treatment outcome, including response to therapy, risk of adverse effects and drug-free remission.
在类风湿关节炎 (RA) 中，确定能够预测疾病结局、治疗反应或减少剂量成功的预后因素 (PF) 是一个重要问题，因为这些因素旨在为决策提供依据。从一开始，这项任务就很复杂，因为疾病预后或治疗预后的定义并不唯一。所使用的定义的异质性部分解释了未能确定可在个体层面应用的 PF 的原因。但其他因素也有贡献。首先，所研究疾病的范围过于广泛，包括不同分类学实体。其次，潜在的 PF 仅在单个时间点测量，而应该在更大程度上考虑一段时间内的变化，不要忘记在此期间接受的治疗的潜在影响。除了这些限制因素外，识别 PF 的主要障碍之一可能是疾病阶段没有得到充分考虑。与疾病刚开始时相比，在疾病已经确立时预测疾病结局是一个更复杂的挑战，因为许多因素可能会产生干扰。这同样适用于治疗性 PF，其应根据疾病持续时间确定。从所使用的方法来看，也存在困难，这些方法通常仅限于单一的兴趣领域，而应该更加综合，并采用新的大规模数据分析工具，以实现精准医学。在 RA 中，可以在两个层面定义预后：疾病结局，包括关节损伤和关节外表现和/或并发症的风险，以及治疗结局，包括对治疗的反应、不良反应风险和无药物缓解。
