Rowida Mohamed, Rahul G. Sangani, Khalid M. Kamal, Traci J. LeMaster, Toni Marie Rudisill, Virginia G. Scott, George A. Kelley, Sijin Wen
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Risk groups were defined based on the nomogram's probability tertiles. The performance of the nomogram-based model was evaluated using Harrell's concordance index (C-index) and the Hosmer–Lemeshow test.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>The study included 152 patients with IPF. The majority of the patients were elderly, male, and had a BMI above 24 kg/m<sup>2</sup>. The median survival duration was 7.6 years. The survival rates were 91% at 1 year, 78% at 3 years, and 68% at 5 years. LASSO regression selected carbon monoxide lung diffusion capacity percentage predicted (DLco%), BMI, pulmonary hypertension, pulmonary embolism, and sleep apnea as independent predictive variables. The nomogram demonstrated good discrimination (C-index = 0.71) and calibration.</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>Pulmonary comorbidities and BMI have significant prognostic value in IPF, emphasizing the necessity for consistent screening, assessment, and management of these factors in IPF care. Furthermore, the nomogram-based staging system showed promising performance in predicting OS and represents an actionable staging system that could potentially improve clinical management in IPF. Further validation of the nomogram is warranted to confirm its utility in clinical practice.</p>\n </section>\n </div>","PeriodicalId":100913,"journal":{"name":"Medicine Advances","volume":"2 4","pages":"336-348"},"PeriodicalIF":0.0000,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/med4.86","citationCount":"0","resultStr":"{\"title\":\"Development of a local nomogram-based scoring system for predicting overall survival in idiopathic pulmonary fibrosis: A rural appalachian experience\",\"authors\":\"Rowida Mohamed, Rahul G. Sangani, Khalid M. Kamal, Traci J. LeMaster, Toni Marie Rudisill, Virginia G. Scott, George A. 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引用次数: 0
摘要
准确的分期系统对于评估特发性肺纤维化(IPF)的严重程度和指导临床管理至关重要。本研究旨在评价肺部合并症和体重指数(BMI)在IPF中的预后价值,建立预测总生存期(OS)的nomogram,并建立基于nomogram的生存期预测模型。方法从西弗吉尼亚州医院系统的电子病历中对IPF患者进行鉴定。采用最小绝对收缩和选择算子(LASSO) Cox回归分析进行变量选择,并构建模态图。根据nomogram概率三分位数来定义风险组。采用Harrell’s concordance index (C-index)和Hosmer-Lemeshow检验对基于nomogram模型的性能进行评价。结果纳入IPF患者152例。大多数患者为老年男性,BMI大于24 kg/m2。中位生存期为7.6年。1年生存率91%,3年生存率78%,5年生存率68%。LASSO回归选择预测的一氧化碳肺弥散容量百分比(DLco%)、BMI、肺动脉高压、肺栓塞和睡眠呼吸暂停作为独立预测变量。nomogram具有良好的判别性(C-index = 0.71)和定标性。结论肺部合并症和BMI在IPF中具有重要的预后价值,强调在IPF护理中对这些因素进行一致的筛查、评估和管理的必要性。此外,基于形态图的分期系统在预测OS方面表现出良好的性能,代表了一种可操作的分期系统,可能会改善IPF的临床管理。为了确认其在临床实践中的效用,有必要进一步验证nomogram。
Development of a local nomogram-based scoring system for predicting overall survival in idiopathic pulmonary fibrosis: A rural appalachian experience
Background
Accurate staging systems are essential for assessing the severity of idiopathic pulmonary fibrosis (IPF) and guiding clinical management. This study aimed to evaluate the prognostic value of pulmonary comorbidities and body mass index (BMI) in IPF, develop a nomogram predicting overall survival (OS), and create a nomogram-based survival prediction model.
Methods
Patients with IPF were identified from electronic medical records of the West Virginia hospital system. Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis was used for variable selection, and a nomogram was constructed. Risk groups were defined based on the nomogram's probability tertiles. The performance of the nomogram-based model was evaluated using Harrell's concordance index (C-index) and the Hosmer–Lemeshow test.
Results
The study included 152 patients with IPF. The majority of the patients were elderly, male, and had a BMI above 24 kg/m2. The median survival duration was 7.6 years. The survival rates were 91% at 1 year, 78% at 3 years, and 68% at 5 years. LASSO regression selected carbon monoxide lung diffusion capacity percentage predicted (DLco%), BMI, pulmonary hypertension, pulmonary embolism, and sleep apnea as independent predictive variables. The nomogram demonstrated good discrimination (C-index = 0.71) and calibration.
Conclusions
Pulmonary comorbidities and BMI have significant prognostic value in IPF, emphasizing the necessity for consistent screening, assessment, and management of these factors in IPF care. Furthermore, the nomogram-based staging system showed promising performance in predicting OS and represents an actionable staging system that could potentially improve clinical management in IPF. Further validation of the nomogram is warranted to confirm its utility in clinical practice.