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The use of pretest probability increases the value of high-resolution CT in diagnosing usual interstitial pneumonia
  1. Robert Brownell1,
  2. Teng Moua2,
  3. Travis S Henry3,
  4. Brett M Elicker3,
  5. Darin White4,
  6. Eric Vittinghoff5,
  7. Kirk D Jones6,
  8. Anatoly Urisman6,
  9. Carlos Aravena7,
  10. Kerri A Johannson8,
  11. Jeffrey A Golden1,
  12. Talmadge E King Jr1,
  13. Paul J Wolters1,
  14. Harold R Collard1,
  15. Brett Ley1
  1. 1Department of Medicine, University of California San Francisco, San Francisco, California, USA
  2. 2Department of Medicine, Mayo Clinic, Rochester, Minnesota, USA
  3. 3Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
  4. 4Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
  5. 5Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, USA
  6. 6Department of Pathology, University of California San Francisco, San Francisco, California, USA
  7. 7Respiratory Diseases Department, Pontifical Catholic University, Santiago, Chile
  8. 8Department of Medicine, University of Calgary, Calgary, Canada
  1. Correspondence to Dr Brett Ley, Department of Medicine, University of California San Francisco, 505 Parnassus Ave, Box 0111, San Francisco, CA 94143, USA; Brett.Ley{at}UCSF.edu

Abstract

Background Recent studies have suggested that non-definitive patterns on high-resolution CT (HRCT) scan provide sufficient diagnostic specificity to forgo surgical lung biopsy in the diagnosis of idiopathic pulmonary fibrosis (IPF). The objective of this study was to determine test characteristics of non-definitive HRCT patterns for identifying histopathological usual interstitial pneumonia (UIP).

Methods Patients with biopsy-proven interstitial lung disease (ILD) and non-definitive HRCT scans were identified from two academic ILD centres. Test characteristics for HRCT patterns as predictors of UIP on surgical lung biopsy were derived and validated in independent cohorts.

Results In the derivation cohort, 64/385 (17%) had possible UIP pattern on HRCT; 321/385 (83%) had inconsistent with UIP pattern. 113/385 (29%) patients had histopathological UIP pattern in the derivation cohort. Possible UIP pattern had a specificity of 91.2% (95% CI 87.2% to 94.3%) and a positive predictive value (PPV) of 62.5% (95% CI 49.5% to 74.3%) for UIP pattern on surgical lung biopsy. The addition of age, sex and total traction bronchiectasis score improved the PPV. Inconsistent with UIP pattern demonstrated poor PPV (22.7%, 95% CI 18.3% to 27.7%). HRCT pattern specificity was nearly identical in the validation cohort (92.7%, 95% CI 82.4% to 98.0%). The substantially higher prevalence of UIP pattern in the validation cohort improved the PPV of HRCT patterns.

Conclusions A possible UIP pattern on HRCT has high specificity for UIP on surgical lung biopsy, but PPV is highly dependent on underlying prevalence. Adding clinical and radiographic features to possible UIP pattern on HRCT may provide sufficient probability of histopathological UIP across prevalence ranges to change clinical decision-making.

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Footnotes

  • Contributors RB, HRC and BL designed the study. RB, BL, TSH, BME, KDJ, AU, CA, KAJ, TM and DW collected data. RB, BL and EV performed the data analysis. All authors contributed to data interpretation. RB, BL and HRC wrote the original manuscript. All authors contributed to revisions of the manuscript, provided final approval of the version to be published and agree to be accountable for all aspects of the work.

  • Funding Research reported in this publication was supported by the National Center for Advancing Translational Sciences of the NIH under Award Number KL2TR001870 as well as NIH/NHLBI grants F32HL124895 and K24HL127131. The Nina Ireland Program for Lung Health supports the UCSF ILD clinical database.

  • Competing interests None declared.

  • Ethics approval IRB at UCSF and Mayo Clinic, Rochester.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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