Background: An assessment method that can accurately assess the severity and prognosis of pulmonary fibrosis, including idiopathic pulmonary fibrosis (IPF), is currently lacking. This study aimed to develop a new multiparameter-based method, which can be easily used to accurately assess pulmonary fibrosis severity. Method: 1. Development of a HRCT combined pulmonary function & physiological parameter (CTPF) assessment method: Parameters that can be easily collected in clinical practice and have been proven by literature to have a good prognostic value were used to develop the new assessment method. The method included two parts. 1) CT-based fibrosis staging: a four-section honeycomb lung method. Four representative lung CT sections were selected (the aortic arch section, the tracheal bifurcation section, the section of basal (dorsal) segment of the tracheal bifurcation at the inferior lobes, and the section below the right lung apex) and evenly divided into 100 small areas. The percentage of honeycomb lesion area in the entire lung was determined semi-quantitatively and used to determine fibrosis stage (I-V) (CT-based fibrosis stage). 2) Five representative lung function and physiological parameters including FVC%pred, DLco%pred, SpO2%, age, and gender were used to assess IPF severity grade (PF-based severity grade). The 5 parameters were scored, and the total scores were used to determine PF-based severity grade, which included score 0-3 for mild (a), score 4-6 for moderate (b), and score 7-10 for severe (c). The two parts were combined to determine a CTPF stage. For example, CTPF stage II a represents fibrosis stage II and severity grade a (mild). 2. Validation of the new method: The CTPF method was used to assess 192 patients with IPF, who were diagnosed in Shanghai Pulmonary Hospital and had complete medical records. Two radiologists used the CT-based fibrosis staging method to evaluate patients' HRCT and determined the fibrosis stage. Pulmonologist determined the PF-based severity grade and combined both assessments to determine the final CTPF stage. 3. Statistical analyses: Intra-group correlation coefficient was calculated to estimate the consistency between the CT scores from the two radiologists. Spearman correlation coefficient was calculated to evaluate the correlation between CT scores and lung function parameters: FVC%pred, DLco%pred, SpO2%, and composite physiologic index (CPI). Death was the study endpoint. Lung transplantation was considered a competitive risk. The competitive risk Fine-Gray model was used to analyze the relationship between CT-based stage/PF-based grade and prognosis (accumulative death). CT-based stage, PF-based grade, and gender, age, and physiologic (GAP) stage were used as predictors to establish Fine-Gray regression prediction models. Nomogram was prepared to illustrate the prediction models. The predictive effectiveness of the models on predicting death risk was verified by cross-validation method. Results: 1. The intra-group correlation coefficient of the CT scores of the two radiologists was 0.95, P<0.05. 2. The CT scores negatively correlated with FVC%pred/DLco%pred/SpO2% and positively with CPI index. 3. The CTPF comprehensive model, which combined CT stage and PF grade, predicted that the AUC index of one-, two-, and three-year death risk was 78.6 (95% CI: 58.6-93.0), 77.8 (95% CI: 58.8- 83.4), and 73.4 (95% CI: 57.5- 85.1), respectively. 4.The CTPF model showed higher predictive accuracy than the GAP model. Conclusion: We combined CT-based staging and PF-based grading methods to develop a new comprehensive CTPF assessment method. The new method is simple, can be adopted easily in clinical practice, and can more accurately assess IPF severity and predict death risk than existing assessment methods. Funding Statement: This study was funded by grants from the National Science Foundation of China (Grant No: 81730002, 81670055, 81670056, 91442103, 81500052, and 81570057), Ministry of Science and Technology of the People’s Republic of China (2016YFC1100200 and 2016YFC1100204) and Shanghai Family Planning Commission Health Industry Clinical Research Project (20184Y0084). Declaration of Interests: The authors confirm that there are no conflicts of interest. Ethics Approval Statement: The study was approved by the Institutional Ethics Committee of Shanghai Pulmonary Hospital (No. K17-006).
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May 31, 2020
Nazish Masud + 9
Open Access
