开发和验证 META 算法，从索赔数据库中识别获准用于治疗免疫相关炎症性疾病的生物药物的使用指征：VALORE 项目的启示
IF 3.4
2区 医学
Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
引用次数: 0
摘要
目的：本研究旨在开发和验证一种 META 算法，该算法结合了针对个别免疫介导炎症性疾病（IMID）的算法，可从意大利 VALORE 项目的理赔数据中识别出生物药使用者的确切 IMID 适应症：从意大利拉齐姆大区的理赔数据库（观察期：2010-2020 年）中确定了所有至少配发过一次 TNF-α 抑制剂、抗白细胞介素制剂和经批准用于 IMID 的选择性免疫抑制剂的受试者。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，并将其合并为 META 算法。以拉齐奥地区的电子治疗计划（ETPs）为参考标准，对每个适应症的阳性预测值（PPV）、灵敏度（Se）、阴性预测值（NPV）、特异性（Sp）和准确性（Acc）进行了估算。最后，将各生物药的使用适应症频率与意大利其他三个大区（伦巴第大区、阿普利亚大区和威尼托大区）报告的频率进行了比较：结果：总共发现了 9755 名具有单一 IMID 适应症的生物药使用者。使用新开发的 META 算法，在全部人群中，95%（n=9255）的人检测到了使用指征。与参考标准相比，估计的Acc、Se、Sp、PPV和NPV如下：克罗恩病为 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，类风湿性关节炎为 0.93、0.76、0.99、0.95 和 0.92。类风湿性关节炎分别为 0.93、0.76、0.99、0.95 和 0.92，脊柱关节炎分别为 0.97、0.75、0.99、0.85 和 0.98，银屑病关节炎/银屑病分别为 0.91、0.92、0.91、0.88 和 0.94。此外，拉齐奥大区和研究中的其他三个意大利大区在按有效成分划分的使用适应症频率方面没有发现实质性差异：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值，并能以良好的性能区分最常见的 IMID 适应症。本研究旨在开发并验证一种 META 算法，该算法能准确识别治疗各种免疫介导炎症性疾病的生物药物的确切适应症。利用拉齐奥地区的报销数据库，我们开发并验证了一种 META 算法。META 算法结合了针对不同免疫介导的炎症性疾病（即克罗恩病、溃疡性结肠炎、类风湿性关节炎、脊柱关节炎、银屑病和银屑病关节炎）的特定疾病算法，并与参考标准（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值，并能以良好的性能区分作为使用适应症的最常见IMID。在意大利环境下，应用该 META 算法可促进对 TNF-α 抑制剂、抗白细胞介素和选择性免疫抑制剂等生物药物在特定治疗领域的上市后监测。 关键词：免疫介导的炎症性疾病；生物药物；验证；索赔数据；META 算法；使用适应症本文章由计算机程序翻译，如有差异，请以英文原文为准。
Development and Validation of a META-Algorithm to Identify the Indications of Use of Biological Drugs Approved for the Treatment of Immune-Mediated Inflammatory Diseases from Claims Databases: Insights from the VALORE Project
Purpose: 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.
Methods and Patients: 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).
Results: 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.
Conclusion: 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.
Plain Language Summary: 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.
Keywords: immune-mediated inflammatory diseases, biological drugs, validation, claims data, META-algorithm, indication for use
Methods and Patients: 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).
Results: 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.
Conclusion: 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.
Plain Language Summary: 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.
Keywords: immune-mediated inflammatory diseases, biological drugs, validation, claims data, META-algorithm, indication for use
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来源期刊
Clinical Epidemiology
Medicine-Epidemiology
CiteScore
6.30
自引率
5.10%
发文量
169
审稿时长
16 weeks
期刊介绍：
Clinical Epidemiology is an international, peer reviewed, open access journal. Clinical Epidemiology focuses on the application of epidemiological principles and questions relating to patients and clinical care in terms of prevention, diagnosis, prognosis, and treatment.
Clinical Epidemiology welcomes papers covering these topics in form of original research and systematic reviews.
Clinical Epidemiology has a special interest in international electronic medical patient records and other routine health care data, especially as applied to safety of medical interventions, clinical utility of diagnostic procedures, understanding short- and long-term clinical course of diseases, clinical epidemiological and biostatistical methods, and systematic reviews.
When considering submission of a paper utilizing publicly-available data, authors should ensure that such studies add significantly to the body of knowledge and that they use appropriate validated methods for identifying health outcomes.
The journal has launched special series describing existing data sources for clinical epidemiology, international health care systems and validation studies of algorithms based on databases and registries.
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