美国风湿病学会（ACR）年会发表的一项新研究表明，新发类风湿关节炎（RA）患者在治疗后的先进3年期间，可于不同的时间点出现疾病状态之间的转换；年前6个月至关重要，可观察到疾病状态的迅速转换。
在RA纵向研究中，通常根据在固定时间间隔内检查相关疾病指标，评估疾病进展。此次，研究者尝试利用多态模型：（1）对治疗前3年内的患者疾病状况进行描述性分析，患者疾病状况根据DAS-28疾病指数定义；（2）确定各疾病状态持续的时间；并且（3）估算疾病状态相互转变的概率。
患者选自于一项正在进行的前瞻性RA研究；纳入患者伴有活动性疾病（≥1个肿胀或触痛关节）并且至少进行过2次随访就诊。在各次就诊时采集DAS-28评分，并根据ACR标准和患者的DAS-28评分，将其分入缓解至高疾病活动性4组中的一组。构建多态（4态）Markov模型，以时间作为连续变量，通过随时间推移的疾病状态对患者病程进行描述，以观察真实中随时变化的疾病病程。利用Markov模型的多重分段转换参数确定患者在不同时间阶段是否伴有不同转换。
586例患者共就诊3014例次；在3年随访时间窗内就诊呈任意分布。在基线时，约50%的患者为高疾病活动性，但患者应答迅速，改变此种健康状态平均花费0.17年，95%CI（0.19，0.23）。基线时约8%的患者为DAS-28缓解；该患者比例迅速上升，在0.5和1年时分别约有25%和40%的患者出现缓解。一旦患者实现缓解，转换至其他疾病状态之前的平均持续时间为0.81年，95%CI（0.67，0.97）。在启动治疗1.5年之后，处于各疾病状态的患者保持相对稳定，提示健康状况之间无净转换。分段模型提示，患者在6个月时具有疾病状态的差异性转换，然后则可在任意其他时间点出现。起始时处于较高疾病状态的患者实现次缓解的时间较长约1.1年，中等和低疾病状态的患者则分别为0.9和0.8年。
以下为这一研究的主要结论：
在治疗后先进3年期间，个体患者在不同的时间点出现疾病状态之间的转换；年前6个月至关重要，可观察到疾病状态的迅速转换。
在前6个月中，高疾病活动性患者迅速减少，与之平行的是可观察到实现缓解的患者比例升高。
我们的分析提示，在患者获得疾病稳定但无净转换前的第1年关键治疗是应实现的。治疗年的主要变化可能为达标治疗策略所致。
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研究摘要原文：
ABSTRACT NUMBER: 130
Disease Activity Patterns in Incident Onset Rheumatoid Arthritis Patients in the First 3-Years of Follow up
Background/Purpose: Disease progression in longitudinal
studies of rheumatoid arthritis (RA) is usually assessed by examining a measure
of disease over time fixed time intervals. We sought to use a multi-state
model: (1)
to provide a descriptive analysis of patients’ disease states defined by the DAS-28
disease index throughout the first three years of treatment; (2) to determine
the time spent in each disease state; and (3) to estimate the probabilities of
changing between disease states.
Methods: Patients were selected from an
ongoing prospective study of RA if they had active disease
(>= 1 swollen or tender joint) and at least 2 follow-up visits to their rheumatologist.
The DAS-28 score was collected at each visit and assigned to one of four
category scores, from remission to high disease activity, using the ACR
criteria. A multi-state (4-state) Markov model was fitted to describe patient progression
through disease states over time to account for the irregular time intervals in
our data considering time as a continuous variable allowing us to examine real-world disease course over time. Multiple piecewise transition parameters
for the Markov model were fit to determine if patients have differential
transitions at different time periods.
Results: There were 3014 visits in 586
patients with visits distributed arbitrarily over the 3-year follow-up window.
At baseline, about 50% of patients were in high disease activity, but patients
respond rapidly, moving out of this health state spending on average 0.17
years, 95% CI (0.19, 0.23) there. At baseline about 8% of patients were in
DAS-28 remission, which rose rapidly at 0.5 years 25% probability and 1 year
with about 40% of patients in remission. Once a patient achieved remission, the
mean duration before moving to another disease state was 0.81 years, 95% CI (0.67,
0.97). By 1.5 years after initiation of treatment, patients in each disease state
remained relatively constant indicating no net movement between health states.
The piecewise model indicated that patients at 6-months had a differential movements
through disease states then at any other time point. Patients starting in the
highest disease state took the longest about 1.1 years to reach their first
remission compared to 0.9 and 0.8 years for the moderate and low groups.
Conclusion: Individual patients transition
between disease states in the first 3 years of treatment at differential times; the first 6-months are critical with the first year seeing rapid movement between states. Within the first 6-months, dramatic reductions are realized in patients with high disease activity in parallel with an observed increase in the proportion of patients achieving remission. Our analysis indicates the critical first year of treatment before a steady disease state with no net movement will be reached.
Major changes in the first year of treatment could be a result of treat-to target strategy.
