■这项研究旨在开发和验证一种META算法,该算法结合了个体免疫介导的炎性疾病(IMID)特异性算法,以从索赔数据中确定事件生物药物使用者的确切IMID适应症意大利VALORE项目。
■所有接受至少一种TNF-α抑制剂的受试者,抗白细胞介素剂,从意大利Latium地区的索赔数据库中确定了批准用于IMID的选择性免疫抑制剂(观察期:2010-2020年)。从已发表的文献中找到了用于从索赔数据库中识别单个IMID的经过验证的编码算法,并将其组合成META算法。阳性预测值(PPV),灵敏度(Se),负预测值(NPV),特异性(Sp),以Latium地区的电子治疗计划(ETP)作为参考标准,对每个适应症的准确性(Acc)进行评估.最后,将单个生物药物使用适应症的频率与意大利其他三个地区的报告进行了比较(伦巴第,普利亚,和威尼托地区)。
■总共,确定了9755名具有单一IMID适应症的事件生物吸毒者。使用新开发的META算法,在总队列的95%(n=9255)中检测到使用指征.估计的Acc,Se,SP,PPV,和净现值,与参考标准相比如下:克罗恩病的0.96、0.86、0.97、0.82和0.98,溃疡性结肠炎为0.96、0.80、0.98、0.85和0.97,0.93,0.76,0.99,0.95和0.92类风湿性关节炎,0.97,0.75,0.99,0.85和0.98的脊椎关节炎,和0.91,0.92,0.91,0.88和0.94的银屑病关节炎/银屑病,分别。此外,在Latium和本研究纳入的其他三个意大利地区中,活性成分的使用指征频率没有实质性差异.
■新开发的META算法在意大利索赔数据中显示出较高的有效性估计,并且能够在最常见的IMID适应症中以良好的性能进行区分。
在索赔数据库中,缺乏有关使用适应症的信息是进行观察性研究的一个众所周知的局限性.进行这项研究是为了开发和验证META算法,该算法可准确识别使用生物药物治疗各种免疫介导的炎性疾病的确切适应症。使用Latium地区的索赔数据库,我们开发并验证了META算法。META算法结合了针对不同免疫介导的炎性疾病的疾病特异性算法(即,克罗恩病,溃疡性结肠炎,类风湿性关节炎,脊柱关节炎,牛皮癣,和银屑病关节炎),并根据参考标准(拉齐奥地区的电子治疗计划)进行了测试。META算法报告了较高的有效性估计,并且能够以良好的性能区分最频繁的IMID作为使用指示。应用这种META算法可以促进生物药物如TNF-α抑制剂的上市后监测,抗白细胞介素,和选择性免疫抑制剂在意大利的特定治疗领域。
UNASSIGNED: This research aimed to develop and validate a META-algorithm combining individual immune-mediated inflammatory disease (IMID)-specific algorithms to identify the exact IMID indications for incident biological drug users from claims data within the context of the Italian VALORE project.
UNASSIGNED: All subjects with at least one dispensing of TNF-alpha inhibitors, anti-interleukin agents, and selective immunosuppressants approved for IMIDs were identified from claims databases of Latium region in Italy (observation period: 2010-2020). Validated coding algorithms for identifying individual IMIDs from claims databases were found from published literature and combined into a META-algorithm. Positive predictive value (PPV), sensitivity (Se), negative predictive value (NPV), specificity (Sp), and accuracy (Acc) were estimated for each indication against the electronic therapeutic plans (ETPs) of the Latium region as the reference standard. Lastly, the frequency of the indication of use across individual biologic drugs was compared with that reported in three other Italian regions (Lombardy, Apulia, and the Veneto region).
UNASSIGNED: In total, 9755 incident biological drug users with a single IMID indication were identified. Using the newly developed META-algorithm, an indication of use was detected in 95% (n=9255) of the total cohort. The estimated Acc, Se, Sp, PPV, and NPV, against the reference standard were as follows: 0.96, 0.86, 0.97, 0.82, and 0.98 for Crohn\'s disease, 0.96, 0.80, 0.98, 0.85, and 0.97 for ulcerative colitis, 0.93, 0.76, 0.99, 0.95, and 0.92 for rheumatoid arthritis, 0.97, 0.75, 0.99, 0.85, and 0.98 for spondylarthritis, and 0.91, 0.92, 0.91, 0.88, and 0.94 for psoriatic arthritis/psoriasis, respectively. Additionally, no substantial difference was observed in the frequency of indication of use by active ingredient among Latium and the other three Italian regions included in the study.
UNASSIGNED: The newly developed META-algorithm demonstrated high validity estimates in the Italian claims data and was capable of discriminating with good performance among the most frequent IMID indications.
In the claims database, the lack of information on the indication of use represents a well-known limitation for the conduct of observational studies. This study was conducted to develop and validate a META-algorithm that accurately identifies the exact indication for the use of biological drugs in treating various immune-mediated inflammatory diseases. Using claims databases from the Latium region, we developed and validated a META-algorithm. The META-algorithm combines disease-specific algorithms for different immune-mediated inflammatory diseases (ie, Crohn’s disease, ulcerative colitis, rheumatoid arthritis, spondyloarthritis, psoriasis, and psoriatic arthritis) and was tested against a reference standard (electronic therapeutic plans of the Lazio region). The META-algorithm reported high validity estimates and was able to distinguish with a good performance among the most frequent IMIDs as indications for use. Applying this META-algorithm may facilitate post-marketing surveillance of biological drugs such as TNF-alpha inhibitors, anti-interleukin, and selective immunosuppressants in specific therapeutic areas in an Italian setting.