PT  - JOURNAL ARTICLE
AU  - Kaman Chung
AU  - Onno M Mets
AU  - Paul K Gerke
AU  - Colin Jacobs
AU  - Annemarie M den Harder
AU  - Ernst T Scholten
AU  - Mathias Prokop
AU  - Pim A de Jong
AU  - Bram van Ginneken
AU  - Cornelia M Schaefer-Prokop
TI  - Brock malignancy risk calculator for pulmonary nodules: validation outside a lung cancer screening population
AID  - 10.1136/thoraxjnl-2017-211372
DP  - 2018 Sep 01
TA  - Thorax
PG  - 857--863
VI  - 73
IP  - 9
4099  - http://thorax.bmj.com/content/73/9/857.short
4100  - http://thorax.bmj.com/content/73/9/857.full
SO  - Thorax2018 Sep 01; 73
AB  - 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.