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Original article
Brock malignancy risk calculator for pulmonary nodules: validation outside a lung cancer screening population
  1. Kaman Chung1,
  2. Onno M Mets2,
  3. Paul K Gerke1,
  4. Colin Jacobs1,
  5. Annemarie M den Harder2,
  6. Ernst T Scholten1,
  7. Mathias Prokop1,
  8. Pim A de Jong2,
  9. Bram van Ginneken1,
  10. Cornelia M Schaefer-Prokop1,3
  1. 1Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands
  2. 2Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
  3. 3Department of Radiology, Meander Medical Center, Amersfoort, The Netherlands
  1. Correspondence to Dr Kaman Chung, Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, 6525 GA, The Netherlands; kaman.chung10{at}gmail.com

Abstract

Objective To assess the performance of the Brock malignancy risk model for pulmonary nodules detected in routine clinical setting.

Methods In two academic centres in the Netherlands, we established a list of patients aged ≥40 years who received a chest CT scan between 2004 and 2012, resulting in 16 850 and 23 454 eligible subjects. Subsequent diagnosis of lung cancer until the end of 2014 was established through linking with the National Cancer Registry. A nested case–control study was performed (ratio 1:3). Two observers used semiautomated software to annotate the nodules. The Brock model was separately validated on each data set using ROC analysis and compared with a solely size-based model.

Results After the annotation process the final analysis included 177 malignant and 695 benign nodules for centre A, and 264 malignant and 710 benign nodules for centre B. The full Brock model resulted in areas under the curve (AUCs) of 0.90 and 0.91, while the size-only model yielded significantly lower AUCs of 0.88 and 0.87, respectively (p<0.001). At 10% malignancy risk, the threshold suggested by the British Thoracic Society, sensitivity of the full model was 75% and 81%, specificity was 85% and 84%, positive predictive values were 14% and 10% at negative predictive value (NPV) of 99%. The optimal threshold was 6% for centre A and 8% for centre B, with NPVs >99%.

Discussion The Brock model shows high predictive discrimination of potentially malignant and benign nodules when validated in an unselected, heterogeneous clinical population. The high NPV may be used to decrease the number of nodule follow-up examinations.

  • lung cancer

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Footnotes

  • Contributors Conception or design of the work: KC, OMM, BvG, MP, PAdJ, CMS-P. Data collection: KC, OMM, PKG, CJ, ETS. Data analysis and interpretation: KC, OMM, AMdH. Drafting the article: KC, OMM, CMS-P. Critical revision of the article: KC, OMM, PKG, CJ, AMdH, ETS, MP, PAdJ, BvG, CMS-P. Final approval of the version to be published: KC, OMM, PKG, CJ, AMdH, ETS, MP, PAdJ, BvG, CMS-P.

  • Funding This research is funded by a grant from the Dutch Cancer Society (project no KUN 2013−6110).

  • Competing interests None declared.

  • Patient consent Not required.

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

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