Development and validation of a prediction model for the indication of inhaled corticosteroid (ICS) in patients with chronic obstructive pulmonary disease (COPD)

Chronic obstructive pulmonary disease (COPD) is the third leading cause of death worldwide. COPD is well known as a clinical syndrome characterized by chronic respiratory symptoms, structural pulmonary abnormalities, lung function impairment, or any combination of these. Inhaled drugs, including long-acting bronchodilators and steroids, are mainly used for COPD pharmacotherapy. Among them, the role of inhaled corticosteroid (ICS) for COPD patients are less known than bronchodilators. Pneumonia, which can be detrimental for COPD patients, is the well-known side effect for ICS. Therefore, when prescribing ICS to COPD patients, its positive effects and side effects must be fully considered. In this study, we intend to create a model that predicts COPD patients who can expect a positive effect when using ICS. Through this study, we expect to improve the quality of life and provide better therapeutic effects for patients requiring ICS in COPD patients.慢性阻塞性肺疾病（Chronic obstructive pulmonary disease, COPD）是全球第三大致死病因。COPD作为一类临床综合征，以慢性呼吸道症状、肺部结构异常、肺功能受损，或上述任意组合为典型特征。吸入性药物（含长效支气管扩张剂与糖皮质激素）是COPD药物治疗的主要手段。其中，吸入性糖皮质激素（inhaled corticosteroid, ICS）在COPD患者中的应用价值，相较于支气管扩张剂仍未得到充分明确。而肺炎作为ICS已知的不良反应，对COPD患者而言可能造成严重危害。因此，为COPD患者开具ICS处方时，需全面权衡其治疗收益与不良反应风险。本研究旨在构建一款预测模型，用于识别可从ICS治疗中获益的COPD患者。通过本研究，我们期望提升COPD患者中需接受ICS治疗人群的生活质量，并优化其临床治疗效果。

搜集汇总

背景与挑战

背景概述

该数据集聚焦于慢性阻塞性肺疾病（COPD）患者吸入皮质类固醇（ICS）适应症的预测模型开发与验证，旨在通过风险评分系统识别可能从ICS治疗中获益的患者，以优化临床决策。研究基于IMPACT和TRIBUTE两项临床试验数据，采用Cox回归分析进行模型构建，并评估其预测准确性和校准性，最终目标是为COPD患者提供更个体化的治疗建议，改善生活质量。