More Than Skin Deep: Bringing Precision Medicine to Systemic Sclerosis.
More Than Skin Deep: Bringing Precision Medicine to Systemic Sclerosis.
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不仅仅是表面层面：为系统性硬化症带来精准医学。
DOI：
10.1002/art.41154
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
Shah,AmiA
中科院分区：
文献类型：
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作者：
Mecoli,ChristopherA;Shah,AmiA
从历史上看，系统性硬化症（SSc）患者根据其皮肤受累程度进行分类，分为弥漫性皮肤SSc (dcSSc)，以躯干和肢体近端皮肤受累为特征，或局限性皮肤SSc (lcSSc)，受累皮肤主要位于肘部和膝盖远端。基于皮肤类型的亚组基于文献，其中器官受累和死亡率的差异已被证明(1)。然而，这种二元分类系统并没有捕捉到已知存在于这两个亚组中的显著临床异质性。在现代，仅根据皮肤类型对给定SSc患者的临床轨迹、器官特异性并发症和药物反应进行风险分层是一种不完善的方法。在过去的几十年里，ssc特异性和相关自身抗体的价值越来越被认识到（2,3）。随着更多的临床-血清学关联被发现和验证，我们对SSc患者进行表型分析的能力得到了显著提高。这种意识的提高，加上自身抗体检测实验室能力的提高，使得世界上大多数SSc队列能够进行全面和详细的血清分型。然而，即使在给定的自身抗体亚型中，临床表现和病程往往存在异质性；Cottrell等人证明了血清学和皮肤亚型鉴定结合预测结果的力量，他们证明在给定的ssc特异性自身抗体组（例如抗scl -70）中，基于皮肤亚型存在不同的临床轨迹(4)。除了利用皮肤型和自身抗体来帮助SSc患者临床表型，第三个组成部分——时间——可能是最关键的。鉴于已知器官特异性并发症在SSc患者的整个生命周期中并不均匀发生，与时间相关的流行病学问题对于SSc队列的特征是不可或缺的(5)。这些问题包括最小化不朽的人时间（例如，研究中相关结果无法观察到的时间），考虑SSc疾病持续时间，以及评估事件相对于彼此的时间。Herrick等人开发了一种预测SSc皮肤病进展的模型，有力地证明了这一概念(6)。虽然基线改良罗德曼皮肤厚度评分（MRSS）单独是一个较差的预测指标，但该模型在加入疾病持续时间后得到改善，并在RNA聚合酶III（抗rnap）抗体状态下进一步改善(6)。同样，利用皮肤亚型、自身抗体状态和时间作为研究癌症-硬皮病关系的过滤器，也说明了这些工具在SSc患者恶性发展风险分层中的价值(7)。正是在这一背景下，Nihtyanova等人在本期《关节炎与风湿病学》上的研究支持了将皮肤类型、血清学和疾病持续时间纳入SSc亚群的观点(8)。他们的研究包括在伦敦大学学院观察的1300多名SSc患者，并根据皮肤疾病类型（有限或弥漫性）和自身抗体状态(抗着丝粒抗体[ACA]阳性，抗拓扑异构酶I[抗拓扑异构酶I]；抗Scl-70阳性，抗rnap阳性，抗u3 RNP阳性，抗pm /Scl阳性，抗核抗体[ANA]阳性，但可提取核抗原[ENA]抗体阴性，“其他”[包括…]
Historically, patients with systemic sclerosis (SSc) have been classified by the extent of their skin involvement, given a classification of either diffuse cutaneous SSc (dcSSc), characterized by skin involvement of the torso and proximal limbs, or limited cutaneous SSc (lcSSc), with involved skin predominantly distal to the elbows and knees. Subgrouping based on cutaneous type is grounded in the literature, in which differences in organ involvement and mortality have been demonstrated (1). However, this binary classification system does not capture the marked clinical heterogeneity known to exist within these 2 subgroups. Attempting to risk stratify a given SSc patient’s clinical trajectory, organspecific complications, and response to medications based solely on cutaneous type is an imperfect approach in the modern era. Over the past few decades, the value of SSc-specific and-associated autoantibodies has been increasingly realized (2, 3). As more clinical–serologic associations have been discovered and validated, our ability to phenotype SSc patients has dramatically improved. This increased awareness, in conjunction with improved laboratory capabilities in autoantibody testing, has allowed for the majority of SSc cohorts around the world to have comprehensive and detailed serotyping. However, even within a given autoantibody subtype, there is often heterogeneity in clinical presentation and course; the power of combining both serology and skin subtype identification to predict outcomes has been illustrated by Cottrell et al, who demonstrated that within a given SSc-specific autoantibody group (eg, anti–Scl-70), different clinical trajectories exist based on cutaneous subtype (4). In addition to utilizing cutaneous type and autoantibodies to help clinically phenotype SSc patients, a third component—time—is perhaps most critical of all. Epidemiologic issues related to time are integral to characterizing SSc cohorts, given the known fact that organ-specific complications do not occur evenly throughout the life of a patient with SSc (5). These issues include minimizing immortal person-time (eg, the time during which the relevant outcome under study could not have been observed), accounting for SSc disease duration, and assessing the timing of events relative to one another. This concept has been eloquently shown by Herrick et al in their development of a model to predict progression of skin disease in SSc (6). Whereas the baseline modified Rodnan skin thickness score (MRSS) alone was a poor predictor, the model improved upon the addition of disease duration, and further improved with the incorporation of RNA polymerase III (anti-RNAP) antibody status (6). Similarly, the power of utilizing cutaneous subtype, autoantibody status, and timing as filters through which to study the cancer–scleroderma relationship has illustrated the value of these tools in risk stratifying SSc patients for the development of malignancy (7). It is within this landscape that the work by Nihtyanova et al in this issue of Arthritis & Rheumatology bolsters the argument for incorporating cutaneous type, serology, and disease duration to subgroup SSc populations (8). Their study included more than 1,300 SSc patients seen at the University College London and stratified them into 1 of 14 subgroups defined a priori based on different combinations of cutaneous disease type (limited or diffuse) and autoantibody status (anticentromere antibody [ACA] positive, anti–topoisomerase I [anti–topo I; anti–Scl-70] positive, anti-RNAP positive, anti–U3 RNP positive, anti-PM/Scl positive, antinuclear antibody [ANA] positive but extractable nuclear antigen [ENA] antibody negative, and “other”[including …