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U. Ahmad



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    MA 17 - Locally Advanced NSCLC (ID 671)

    • Event: WCLC 2017
    • Type: Mini Oral
    • Track: Locally Advanced NSCLC
    • Presentations: 1
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      MA 17.11 - Prediction of Response to Trimodality Therapy Using CT-Derived Radiomic Features in Stage III Non-Small Cell Lung Cancer (NSCLC) (ID 10336)

      15:45 - 17:30  |  Author(s): U. Ahmad

      • Abstract
      • Presentation
      • Slides

      Background:
      There are no clinically validated biomarkers to identify patients with locally advanced NSCLC who benefit from trimodality therapy (TMT) (i.e. neoadjuvant chemoradiation (NAT) followed by surgery). In this study, we evaluate radiomic (i.e. computer extracted imaging) features of tumor phenotype as potential predictors of pathological response.

      Method:
      123 patients with stage III NSCLC who received TMT were selected for this study. Of these, 33 patients including those with distant metastasis at presentation and those without baseline pre-NAT CT scans were excluded. Lung tumors were retrospectively contoured on 3D SLICER software by an expert reader. A total of 1542 radiomic features (textural and shape) were extracted from intra and peritumoral region using the MATLAB® 2016a platform (Mathworks, Natick, MA). A random forest (RF) machine classifier was trained with the most predictive features identified on the training set (n=45) and then validated on an independent test set (n=45). The primary endpoint of our study was pathological response defined as the percentage of the residual viable tumor.

      Result:
      90 patients with NSCLC were included for analysis with a median age of 64 years (38−88), and 54.4 % men. Tumor histology was predominantly adenocarcinoma (71.1%), stage IIIA (94.4%), with positive N2 nodes (91.1%). Pathological response was achieved in 36 (40%) patients; labeled responders (R) and the rest 54 (60%) were labeled non-responders (NR). No statistically significant difference was found in clinical characteristics. We identified five radiomic features (intratumoral and peritumoral textural patterns) predictive of pathological response (Area under Receiver Operating Characteristic (ROC) Curve = 0.7806, RF classifier). Figure 1



      Conclusion:
      Texture features extracted from within and around the lung tumor on CT images were predictive of pathological response to NAT. Additional validation of these quantitative image-based biomarkers is warranted for accurate early identification of responders who could be potentially spared surgery.

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    P1.05 - Early Stage NSCLC (ID 691)

    • Event: WCLC 2017
    • Type: Poster Session with Presenters Present
    • Track: Early Stage NSCLC
    • Presentations: 1
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      P1.05-022d - Lung Cancer in the Innocent Isn't so Innocent (ID 9516)

      09:30 - 16:00  |  Author(s): U. Ahmad

      • Abstract

      Background:
      Do never-smokers who develop non–small-cell lung cancer catch a break as innocent bystanders? This study seeks to understand differences in presentation and outcome after resection of lung cancer in never-smokers vs. smokers.

      Method:
      From 2006 to 2013, 652 patients underwent lung resection for clinical stage I-III (p I-II or yp I-II) non–small-cell lung cancer (NSCLC)—584 smokers (90%) and 68 never-smokers. Propensity matching yielded comparable pairs of smokers and never-smokers to assess cancer recurrence, overall survival, and recurrence-free survival.

      Result:
      Never-smokers presented with somewhat more advanced disease than smokers (59% pT2 vs. 48%, 34% pN1 or pN2 vs. 27%), were more likely to have had preoperative chemotherapy or radiotherapy (26% vs. 17%), and more often were female (66% vs. 45%) and of Asian descent (10% vs. 0.34%). Among matched patients (including for cancer stage), 5-year freedom from cancer recurrence was 57% vs. 49% (Figure) in never-smokers vs. smokers. However, not surprisingly, non-cancer death was lower in never-smokers than smokers (6.3% vs. 16% at 5 years; Figure). Thus, when this competing risk of death without recurrence is accounted for, the proportion of never-smokers experiencing recurrence was 40% vs. 37% for smokers, and recurrence-free survival was 54% vs. 46%.Figure 1



      Conclusion:
      Because disease presentation and response to therapy are unexpectedly and surprisingly similar in never-smokers and smokers, the effect of lung cancer on survival is magnified in never-smokers by fewer non–cancer-related deaths. Moreover, since never-smokers present with fewer comorbidities and singular disease, they are optimal candidates for the most aggressive therapies and tightest long-term surveillance.