Development of a local nomogram‐based scoring system for predicting overall survival in idiopathic pulmonary fibrosis: A rural appalachian experience

• Published in: Medicine advances (Online) 2024-12, Vol.2 (4), p.336-348
• Main Authors: Mohamed, Rowida, Sangani, Rahul G., Kamal, Khalid M., LeMaster, Traci J., Rudisill, Toni Marie, Scott, Virginia G., Kelley, George A., Wen, Sijin
• Format: Article
• Language: English
• Subjects: body mass index; hypertension; idiopathic pulmonary fibrosis; nomogram; staging system; survival
• ISSN: 2834-4391; 2834-4405
• DOI: 10.1002/med4.86

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. In our study, we developed a nomogram‐based risk‐staging system for idiopathic pulmonary fibrosis based on inpatient data from West Virginia University Medicine hospitals. We identified DLco%, body mass index (used as an indicator of malnutrition), pulmonary hypertension, pulmonary embolism, and sleep apnea as independent predictors of overall survival. Nomograms offer a reliable visualization of multivariable prognostic models.