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R. Vliegenthart



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    OA 15 - Diagnostic Radiology, Staging and Screening for Lung Cancer II (ID 684)

    • Event: WCLC 2017
    • Type: Oral
    • Track: Radiology/Staging/Screening
    • Presentations: 2
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      OA 15.06 - Management of Nonresolving New Solid Nodules after Initial Detection in Incidence Rounds of CT Lung Cancer Screening (ID 8922)

      14:30 - 16:15  |  Author(s): R. Vliegenthart

      • Abstract
      • Presentation
      • Slides

      Background:
      Low-dose computed tomography (LDCT) lung cancer screening is recommended by US guidelines for high-risk individuals. New solid nodules are regularly found in incidence screening rounds and have a higher lung cancer probability at smaller size than do baseline nodules, leading to the proposal of lower size cutoffs at initial new solid nodule detection. However, currently there is no evidence concerning the risk-stratification of new solid nodules at first LDCT screening after initial detection.

      Method:
      In the ongoing, multicenter, randomized controlled Dutch-Belgian Lung Cancer Screening (NELSON) Trial, 7,295 participants underwent the second and 6,922 participants the third screening round. We included participants with solid non-calcified nodules, that were registered by the NELSON radiologists as new or smaller than 15mm[3] (study detection limit) at previous screens and received a follow-up or regular LDCT screening after initial detection; thereby excluding high-risk nodules according to the NELSON management protocol (nodules ≥500mm[3]). Nodule volume was generated semiautomatically. For assessment of the predictive performance, the area under the receiver operating characteristics curve (AUC) of nodule volume, volume doubling time (VDT), and VDT combined with a predefined 200mm[3] volume cutoff were evaluated with eventual lung cancer diagnosis as outcome.

      Result:
      Overall, 680 participants with 1,020 low and intermediate risk new solid nodules were included. A total of 562 (55%) new solid nodules were resolving, leaving 356 (52%) participants with a nonresolving new solid nodule of whom 25 (7%) were eventually diagnosed with lung cancer in such a nodule. At first follow-up or regular LDCT screening after initial new solid nodule detection, VDT, volume, and VDT combined with the predefined ≥200mm[3] volume cutoff had a high discriminative performance for lung cancer (VDT, AUC: 0.91; volume, AUC: 0.88; VDT and ≥200mm[3] combination, AUC: 0.94). A cutoff combination of ≤590 days VDT or ≥200mm[3] at first LDCT after initial new solid nodule detection, classifying a nodule positive when at least one criterion was fulfilled, provided 100% (95% confidence interval [CI] 84-100%) sensitivity and 84% (95%CI 80-87%) specificity for discriminating lung cancer, with positively classified nodules having a lung cancer probability of 27% (95%CI 19-37%).

      Conclusion:
      More than half of new solid nodules identified in LDCT lung cancer screening are resolving nodules. At first follow-up, a cutoff combination of ≤590 days VDT or ≥200mm[3] volume can be used for risk stratification.

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      OA 15.07 - Value of Nodule Characteristics in Risk-Stratification of New Incident Nodules Detected in CT Lung Cancer Screening (ID 9067)

      14:30 - 16:15  |  Author(s): R. Vliegenthart

      • Abstract
      • Presentation
      • Slides

      Background:
      New solid nodules detected in low-dose computed tomography (LDCT) lung cancer screening have a higher lung cancer probability at a smaller size than baseline nodules and lower size cutoff values for risk stratification at initial detection have been proposed. So far, it is unknown whether nodule characteristics, such as morphology or location, could improve risk stratification by size in new solid nodules.

      Method:
      This study forms part of the ongoing, randomized controlled Dutch-Belgian Lung Cancer Screening (NELSON) trial. This analysis included solid non-calcified nodules detected during the three incidence screening rounds and registered by the NELSON radiologists as new or previously below detection limit (15mm[3]). Nodule volume was generated semiautomatically. The predictive performance of nodule characteristics (location, distribution [peripheral, nonperipheral], shape [round, polygonal, irregular], margin [smooth, lobulated, spiculated, irregular], visibility <15mm[3] in retrospect) combined with previously established volume cutoffs (<30mm[3], low risk; 30-<200mm[3], intermediate risk; ≥200mm[3] high risk) was evaluated by multivariable logistic regression analysis with eventual lung cancer diagnosis as outcome. Discrimination of lung cancer based on volume, the final parsimonious model, and the model stratified into three risk groups (low, intermediate, high) was assessed through the area under the receiver operating characteristics curve (AUC) and compared using DeLong's Method.

      Result:
      Overall, 1,280 new nodules were included with 73 (6%) being diagnosed as lung cancer eventually. Of the new nodules visible <15mm[3] in retrospect and now ≥30mm[3], 22% (6/27) were lung cancer. Discrimination based on volume cutoffs (AUC: 0.80, 95% confidence interval [CI] 0.75-0.84) and continuous volume (AUC: 0.82, 95%CI 0.77-0.87) was comparable (P=0.14). After adjustment for volume cutoffs, only location in the right upper lobe (odds ratio [OR] 2.0, 95%CI 1.2-3.4), nonperipheral distribution (OR 2.4, 95%CI 1.4-4.2), and visibility <15mm[3] in retrospect (OR 4.7, 95%CI 1.7-12.8) remained significant predictors. Discrimination based on the model (AUC: 0.85, 95%CI 0.81-0.89) was superior to the volume cutoffs alone (P=0.0002), but when stratified into three risk groups (AUC: 0.82, 95%CI 0.78-0.86) discrimination was comparable (P=0.2).

      Conclusion:
      At initial detection, nodule volume is the strongest predictor for lung cancer in new nodules. Nodule characteristics may further improve lung cancer prediction, but only have limited incremental discriminatory value additional to volume cutoffs in a three-category stratification approach.

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    P2.13 - Radiology/Staging/Screening (ID 714)

    • Event: WCLC 2017
    • Type: Poster Session with Presenters Present
    • Track: Radiology/Staging/Screening
    • Presentations: 1
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      P2.13-007 - Relationship of Nodule Count and Lung Cancer Probability in New Nodules Detected after Baseline in CT Lung Cancer Screening (ID 9065)

      09:30 - 16:00  |  Author(s): R. Vliegenthart

      • Abstract

      Background:
      In low-dose computed tomography (LDCT) lung cancer screening new nodules are frequently found after baseline. Currently, there is no evidence concerning the relationship between a participant’s number of nodules and the lung cancer probability of new nodules.

      Method:
      This study is part of the ongoing Dutch-Belgian Randomized Lung Cancer Screening (NELSON) Trial. Participants with solid and sub-solid nodules detected after baseline and registered as new by the NELSON radiologists were included. Three nodule counts were calculated: The participant’s total number of new nodules present at new nodule detection, the participant’s overall number of nodules detected before new nodule detection, and the participants overall number of calcified nodules detected until new nodule detection. The discriminative performance of the nodule counts for prediction of lung cancer was assessed through the area under the receiver operating characteristic curve (AUC). On participant level, a multivariable logistic regression analysis with eventual lung cancer diagnosis in a detected new nodule as outcome was performed, including the nodule count and participant’s largest new nodule size (categorized as <50mm[3], 50-<500mm[3], ≥500mm[3]). On nodule level, the equivalent analysis was performed, including the nodule count and nodule size while adjusting for clustering of data within participants using Huber-White robust estimators.

      Result:
      A total of 706 participants with 964 new nodules (median 1, range 1-12) were included. Eventually, 9% (65/706) of the participants had lung cancer in one of the new nodules. The lung cancer probability was 10% (56/552) for participants with 1 new nodule, 7% (7/100) with 2 new nodules, and 4% (2/54) with ≥3 new nodules (P=0.21). On nodule level, the number of new nodules provided moderate discrimination for lung cancer (AUC: 0.67, P<0.001) and remained a significant predictor after adjusting for nodule size (odds ratio [OR] 0.42, 95% confidence interval [CI] 0.26-0.68, per additional new nodule present). On participant level, the number of new nodules provided poor discrimination for eventual lung cancer diagnosis in a detected new nodule (AUC: 0.55, P=0.22), but was significantly associated with lung cancer when corrected for largest new nodule size (OR 0.61, 95%CI 0.39-0.98 per additional new nodule present). The participant’s overall number of nodules before new nodule detection and the number of calcified nodules were not associated with lung cancer.

      Conclusion:
      While an increased number of detected new nodules signifies a reduced lung cancer probability of each individual new nodule, the impact on the participant’s overall lung cancer probability in the new nodules is limited.