Hospital Universitario La Paz, Paseo de la Castellana, 261, 28046 Madrid, Spain.
Rheumatology (Oxford). 2010 Mar;49(3):458-66. doi: 10.1093/rheumatology/kep380. Epub 2009 Dec 23.
To develop a model to predict RA outcome based on biochemical variables and single nucleotide polymorphisms (SNPs).
We collected baseline data from RA patients. SNP genotyping was performed using an oligonucleotide microarray. Remission and severe disability were investigated as outcomes of the study. Logistic regression models and receiver operating characteristic (ROC) curves were used to determine sensitivity (S), specificity (Sp) and likelihood ratio (LR).
Six hundred and thirty-two patients (375 in the study and 257 in the validation) were included. Twenty-two out of 152, and 19 out of 208 patients had an HAQ > 2. The model obtained to predict disability included levels of the anti-cyclic citrullinated peptide (anti-CCP) antibodies, ESR and SNP rs2070874 in the IL-4 gene. Homozygous and heterozygous carriers of the IL-4 33T allele had a decreased risk of severe disability. The discriminative power had an area under the curve (AUC) of 0.792 (95% CI 0.694, 0.889), with S 41%, Sp 95% and LR +7.6. Twenty-one out of 268 and 17 out of 211 patients were in remission in the study and validation cohorts, respectively. The model included absence of anti-CCP antibodies and the SNP rs2476601 on the PTPN22 gene. Homozygous and heterozygous carriers of the PTPN22 1858T allele had a decreased probability of remission. The discriminative power had an AUC of 0.842 (95% CI 0.756, 0.928), with S 76%, Sp 86% and LR + 5.4. Predictive ability was confirmed on the validation cohort.
We have developed two models based on laboratory variables that are associated with relevant outcomes for RA patients at disease onset.
基于生化变量和单核苷酸多态性（SNP）开发预测 RA 结局的模型。
我们收集 RA 患者的基线数据。采用寡核苷酸微阵列进行 SNP 基因分型。将缓解和严重残疾作为研究结果进行研究。使用逻辑回归模型和受试者工作特征（ROC）曲线确定敏感性（S）、特异性（Sp）和似然比（LR）。
共纳入 632 例患者（研究组 375 例，验证组 257 例）。22 例（152 例中的 22 例）和 19 例（208 例中的 19 例）患者的 HAQ>2。预测残疾的模型包括抗环瓜氨酸肽（抗-CCP）抗体水平、ESR 和 IL-4 基因中的 SNP rs2070874。IL-4 33T 等位基因的纯合子和杂合子携带者发生严重残疾的风险降低。鉴别力的曲线下面积（AUC）为 0.792（95%CI 0.694，0.889），S 为 41%，Sp 为 95%，LR+为 7.6。研究和验证队列中分别有 21 例（268 例中的 21 例）和 17 例（211 例中的 17 例）患者缓解。该模型包括无抗-CCP 抗体和 PTPN22 基因上的 SNP rs2476601。PTPN22 1858T 等位基因的纯合子和杂合子携带者缓解的可能性降低。鉴别力的 AUC 为 0.842（95%CI 0.756，0.928），S 为 76%，Sp 为 86%，LR+为 5.4。验证队列证实了预测能力。
我们基于与疾病发病时 RA 患者相关结局相关的实验室变量开发了两个模型。
