Derivation and Validation of a Diagnostic Prediction Tool for Interstitial Lung Disease

doi:10.1016/j.chest.2020.02.044

Chest

Volume 158, Issue 2, August 2020, Pages 620-629

Preliminary data for this study were presented in abstract form at the International Colloquium on Lung and Airway Fibrosis, October 13-17, 2018, Pacific Grove, CA, and the 2019 American Thoracic Society International Conference, May 17-22, 2019, Dallas, TX.

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Background

Interstitial lung disease (ILD) results in high morbidity and health-care utilization. Diagnostic delays remain common and often occur in nonpulmonology settings. Screening for ILD in these settings has the potential to reduce diagnostic delays and improve patient outcomes.

Research Question

This study sought to determine whether a pulmonary function test (PFT)-derived diagnostic prediction tool (ILD-Screen) could accurately identify incident ILD cases in patients undergoing PFT in nonpulmonology settings.

Study Design and Methods

Clinical and physiologic PFT variables predictive of ILD were identified by using iterative multivariable logistic regression models. ILD status was determined by using a multi-reader approach. An ILD-Screen score was generated by using final regression model coefficients, with a score ≥ 8 considered positive. ILD-Screen test performance was validated in an independent external cohort and applied prospectively to PFTs over 1 year to identify incident ILD cases at our institution.

Results

Variables comprising the ILD-Screen were age, height, total lung capacity, FEV₁, diffusion capacity, and PFT indication. The ILD-Screen showed consistent test performance across cohorts, with a sensitivity of 0.79 and a specificity of 0.83 when applied prospectively. A positive ILD-Screen strongly predicted ILD (OR, 18.6; 95% CI, 9.4-36.9) and outperformed common ILD clinical features, including cough, dyspnea, lung crackles, and restrictive lung physiology. Prospective ILD-Screen application resulted in a higher proportion of patients undergoing chest CT imaging compared with a historical control cohort (74% vs 56%, respectively; P = .003), with a significantly shorter median time to chest CT imaging (5.6 vs 21.1 months; P < .001).

Interpretation

The ILD-Screen showed good test performance in predicting ILD across diverse geographic settings and when applied prospectively. Systematic ILD-Screen application has the potential to reduce diagnostic delays and facilitate earlier intervention in patients with ILD.

Section snippets

Patients and Methods

This investigation was performed at the University of California at Davis and the Centre Hospitalier de l’Université de Montréal (CHUM). It was approved by the institutional review board at each center, which provided waivers of consent (UC-Davis protocol #928979 and CHUM protocol #2019-7786).

ILD-Screen Derivation

Of 1,271 patients undergoing paired PFT and chest CT imaging over the derivation period, 212 (16.7%) had evidence of ILD. Interobserver agreement for ILD presence on chest CT imaging was good (κ = 0.79). Compared vs those without ILD, case subjects were older, with a higher predominance of male subjects and lower TLC, FVC, and Dlco (Table 1). ILD was observed in a higher number of patients referred for a pulmonary indication compared with a nonpulmonary indication.

Variables selected for the

Discussion

In the current investigation, we developed the ILD-Screen, a diagnostic prediction tool for ILD derived from variables collected on PFTs. Prospective application of the ILD-Screen identified a large number of incident ILD cases, including all cases with pulmonary fibrosis and nearly all patients with IPF, CTD-ILD, and U-ILD. The ILD-Screen showed consistent test performance across two geographically diverse North American cohorts and when applied prospectively, thus suggesting good

Conclusions

The current study showed that the ILD-Screen is a more reliable predictor of ILD than hallmark clinical and physiologic features of ILD among patients undergoing PFT for diverse indications and across various care settings. This tool represents a promising modality to begin identifying at-risk patients who should be referred for HRCT imaging, as such an intervention has the potential to reduce diagnostic delays, facilitate earlier intervention, and improve patient outcomes.

Acknowledgments

Author contributions: J. M. O. had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. J. V. P., S. A., A.-C. M.-P., D. P., J. G., N. B., A. K., E. L., E. F., C. M., and S. C. were responsible for clinical/physiologic data acquisition. A. K., J. C., M. K., and J. M. O. were responsible for chest CT data acquisition. J. V. P., J. M., M. K., and J. M. O. designed the study. J. M. O. analyzed the data. J. V. P.,

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Nevertheless, dyspnoea and chronic cough justify seeking medical advice—particularly lung auscultation—irrespective of age and smoking history. In addition, a 2020 study of patients referred for pulmonary function testing by primary care providers found that cough had more than 80% sensitivity for ILD, but with poor specificity, whereas dyspnoea was neither sensitive nor specific.19 By contrast, there could also be a group of patients who have minimal symptom burden, most commonly patients in whom exercise capacity is already limited by extrapulmonary causes, such as musculoskeletal limitations in patients with connective tissue disease-associated ILD.
Many patients with interstitial lung disease (ILD) develop pulmonary fibrosis, which can lead to reduced quality of life and early mortality. Patients with fibrotic ILD often have considerable diagnostic delay, and are exposed to unnecessary and costly diagnostic procedures, and ineffective and potentially harmful treatments. Non-specific and insidious presenting symptoms, along with scarce knowledge of fibrotic ILD among primary care physicians and non-ILD experts, are some of the main causes of diagnostic delay. Here, we outline and discuss the challenges facing both patients and physicians in making an early diagnosis of fibrotic ILD, and explore strategies to facilitate early identification of patients with fibrotic ILD, both in the general population and among individuals at highest risk of developing the disease. Finally, we discuss controversies and key uncertainties in screening programmes for fibrotic ILD. Timely identification and accurate diagnosis of patients with fibrotic ILD poses several substantial clinical challenges, but could potentially improve outcomes through early initiation of appropriate management.
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: FUNDING/SUPPORT: This study was funded by the National Heart, Lung, and Blood Institute [K23HL138190].

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Chest

Diffuse Lung Disease: Original ResearchDerivation and Validation of a Diagnostic Prediction Tool for Interstitial Lung Disease

Background

Research Question

Study Design and Methods

Results

Interpretation

Section snippets

Patients and Methods

ILD-Screen Derivation

Discussion

Conclusions

Acknowledgments

Chest

Chest

Respir Med

Chest

Respir Med

Chest

All-cause healthcare costs and mortality in patients with systemic sclerosis with lung involvement

J Rheumatol

Health care utilization and costs of idiopathic pulmonary fibrosis in U.S. Medicare beneficiaries aged 65 years and older

Ann Am Thorac Soc

Idiopathic pulmonary fibrosis: physiologic tests, quantitative CT indexes, and CT visual scores as predictors of mortality

Radiology

Mycophenolate mofetil improves lung function in connective tissue disease-associated interstitial lung disease

J Rheumatol

Idiopathic pulmonary fibrosis

N Engl J Med

Nintedanib for systemic sclerosis-associated interstitial lung disease

N Engl J Med

Barriers to timely diagnosis of interstitial lung disease in the real world: the INTENSITY survey

BMC Pulmon Med

Risk factors for diagnostic delay in idiopathic pulmonary fibrosis

Respir Res

Diagnostic test interpretation and referral delay in patients with interstitial lung disease

Respir Res

Diffuse Lung Disease: Original Research
Derivation and Validation of a Diagnostic Prediction Tool for Interstitial Lung Disease