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Original Research |

A Multidimensional Index and Staging System for Idiopathic Pulmonary Fibrosis

Brett Ley, MD; Christopher J. Ryerson, MD, MAS; Eric Vittinghoff, PhD; Jay H. Ryu, MD; Sara Tomassetti, MD; Joyce S. Lee, MD, MAS; Venerino Poletti, MD; Matteo Buccioli, BS; Brett M. Elicker, MD; Kirk D. Jones, MD; Talmadge E. King, MD; and Harold R. Collard, MD
[+] Article and Author Information

From the University of California, San Francisco, San Francisco, California; Mayo Clinic, Rochester, Minnesota; and Morgagni-Pierantoni Hospital, Forli, Italy.

Acknowledgment: The authors acknowledge the providers and staff of the University of California, San Francisco, Interstitial Lung Disease Program and Consortium, Mayo Clinic, and Morgagni-Pierantoni Hospital for their assistance in recruiting patients for this study, and the patients with IPF who, through their generosity and efforts, allow us to conduct clinical research studies in an effort to improve the lives of patients with IPF.

Grant Support: By the University of California, San Francisco Clinical and Translational Science Institute Resident Research Award and the National Institutes of Health (HL086516).

Potential Conflicts of Interest: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M11-1362.

Reproducible Research Statement:Study protocol: Not available. Data set and statistical code: Available from Dr. Ley (e-mail, brett.ley@ucsf.edu).

Requests for Single Reprints: Brett Ley, MD, 505 Parnassus Avenue, Box 0111, San Francisco, CA, 94143; e-mail, brett.ley@ucsf.edu.

Current Author Addresses: Drs. Ley, Lee, and Collard: Department of Medicine, University of California, San Francisco, 505 Parnassus Avenue, Box 0111, San Francisco, CA 94143.

Dr. Ryerson: St. Paul's Hospital, 1081 Burrard Street, Ward 8B, Vancouver, British Columbia, Canada V6Z 1Y6.

Dr. Vittinghoff: Department of Epidemiology and Biostatistics, University of California, San Francisco, 185 Berry Street, Box 0560, San Francisco, CA 94143.

Dr. Ryu: Division of Pulmonary and Critical Care Medicine, Gonda 18 South, Mayo Clinic, 200 1st Street, Southwest, Rochester, MN 55905.

Drs. Tomassetti and Poletti and Mr. Buccioli: Department of Diseases of the Thorax, Pulmonology Unit, Morgagni-Pierantoni Hospital, via C. Forlanini 34, 47100 Forli, Italy.

Dr. Elicker: Department of Radiology, University of California, San Francisco, 505 Parnassus Avenue, Box 0628, San Francisco, CA 94143.

Dr. Jones: Department of Pathology, University of California, San Francisco, 505 Parnassus Avenue, Box 0628, San Francisco, CA 94143.

Dr. King: Department of Medicine, University of California, San Francisco, 505 Parnassus Avenue, Box 0120, San Francisco, CA 94143.

Author Contributions: Conception and design: B. Ley, J.H. Ryu, B.M. Elicker, T.E. King, H.R. Collard.

Analysis and interpretation of the data: B. Ley, C.J. Ryerson, E. Vittinghoff, J.H. Ryu, V. Poletti, M. Buccioli, B.M. Elicker, T.E. King, H.R. Collard.

Drafting of the article: B. Ley, C.J. Ryerson, E. Vittinghoff, J.H. Ryu, S. Tomassetti, V. Poletti, M. Buccioli, T.E. King, H.R. Collard.

Critical revision of the article for important intellectual content: B. Ley, C.J. Ryerson, E. Vittinghoff, J.H. Ryu, J.S. Lee, V. Poletti, B.M. Elicker, K.D. Jones, T.E. King, H.R. Collard.

Final approval of the article: B. Ley, C.J. Ryerson, E. Vittinghoff, J.H. Ryu, S. Tomassetti, J.S. Lee, V. Poletti, B.M. Elicker, K.D. Jones, T.E. King, H.R. Collard.

Provision of study materials or patients: J.H. Ryu, S. Tomassetti, H.R. Collard.

Statistical expertise: E. Vittinghoff, M. Buccioli, H.R. Collard.

Obtaining of funding: B. Ley, T.E. King, H.R. Collard.

Administrative, technical, or logistic support: B. Ley.

Collection and assembly of data: B. Ley, C.J. Ryerson, J.H. Ryu, S. Tomassetti, J.S. Lee, V. Poletti, M. Buccioli, B.M. Elicker, K.D. Jones, H.R. Collard.


Ann Intern Med. 2012;156(10):684-691. doi:10.7326/0003-4819-156-10-201205150-00004
Text Size: A A A

Background: Idiopathic pulmonary fibrosis (IPF) is a progressive fibrotic lung disease with an overall poor prognosis. A simple-to-use staging system for IPF may improve prognostication, help guide management, and facilitate research.

Objective: To develop a multidimensional prognostic staging system for IPF by using commonly measured clinical and physiologic variables.

Design: A clinical prediction model was developed and validated by using retrospective data from 3 large, geographically distinct cohorts.

Setting: Interstitial lung disease referral centers in California, Minnesota, and Italy.

Patients: 228 patients with IPF at the University of California, San Francisco (derivation cohort), and 330 patients at the Mayo Clinic and Morgagni-Pierantoni Hospital (validation cohort).

Measurements: The primary outcome was mortality, treating transplantation as a competing risk. Model discrimination was assessed by the c-index, and calibration was assessed by comparing predicted and observed cumulative mortality at 1, 2, and 3 years.

Results: Four variables were included in the final model: gender (G), age (A), and 2 lung physiology variables (P) (FVC and Dlco). A model using continuous predictors (GAP calculator) and a simple point-scoring system (GAP index) performed similarly in derivation (c-index of 70.8 and 69.3, respectively) and validation (c-index of 69.1 and 68.7, respectively). Three stages (stages I, II, and III) were identified based on the GAP index with 1-year mortality of 6%, 16%, and 39%, respectively. The GAP models performed similarly in pooled follow-up visits (c-index ≥71.9).

Limitation: Patients were drawn from academic centers and analyzed retrospectively.

Conclusion: The GAP models use commonly measured clinical and physiologic variables to predict mortality in patients with IPF.

Primary Funding Source: University of California, San Francisco Clinical and Translational Science Institute.

Figures

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Appendix Figure.

Calculating mortality risks by using the GAP calculator.

Note: Age is modeled by using a 3-knot restricted cubic spline function. For simplicity, we represent this by using 2 age variables (AGE1 and AGE2) in the figure, utilizing a value look-up table for AGE2. AGE1 and AGE2 = age variables after 3-knot restricted cubic spline (knots = −12.68, 0.32, and 10.32, after centering age on its mean (67.68 y); GAP = gender, age, and 2 lung physiology variables (FVC and Dlco).

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Figure 1.

Distribution and attributed mortality risk of predictors in the GAP calculator.

Histograms (bar plots) show the percentage of distribution of the predictor in the combined cohort. Curves (lines) show the mortality risk attributed to the predictor, whereas the other predictors are held constant at their sample means. The y-axis is scaled to represent both percentage of distribution for the histograms and percentage of mortality for the curves. Note: In the upper 4 panels, which represent age and FVC in men and women, the 1-y risk curve for patients who cannot do the Dlco test overlaps with the 2-y risk curve for patients who can perform the Dlco test, creating the appearance of a red-and-green dashed line. GAP = gender, age, and 2 lung physiology variables (FVC and Dlco).

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Figure 2.

The GAP index and staging system.

Points are assigned for each variable of the scoring system to obtain a total point score (range, 0–8). Patients should be scored in the “Cannot perform” category for Dlco if their symptoms or lung function prohibited performance of the Dlco maneuver. If Dlco is unavailable because it was not ordered or not completed because of nonrespiratory limitations, then the model cannot be applied. The total point score is used to classify patients as stage I (0–3 points), stage II (4–5 points), or stage III (6–8 points). Model-predicted 1-, 2-, and 3-y mortality is shown by stage. GAP = gender, age, and 2 lung physiology variables (FVC and Dlco).

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Figure 3.

Cumulative mortality in the combined cohort by stage for the GAP calculator and GAP index and staging system.

GAP = gender, age, and 2 lung physiology variables (FVC and Dlco).

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