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P. Tini



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    Poster Display Session (ID 63)

    • Event: ELCC 2017
    • Type: Poster Display Session
    • Track:
    • Presentations: 1
    • Moderators:
    • Coordinates: 5/07/2017, 12:30 - 13:00, Hall 1
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      75P - Predictive value of CT texture analysis in lung cancer patients undergoing nivolumab (ID 231)

      12:30 - 13:00  |  Author(s): P. Tini

      • Abstract

      Background:
      Nivolumab is a human mAb to PD-1 with significant antitumor activity in a number of solid malignancies including NSCLC, kidney cancer and melanoma. At the present, no predictive factor has been identified for this drug, thus its administration is mostly empirical, at price of frequent adverse events and high costs. In this context, we evaluated whether baseline CT texture analysis (TA) could be used to identify advanced NSCLC patients who will benefit by Nivolumab treatment, by taking in consideration that the therapeutic effects PD-1 blockade depends by its ability of reactivating a pre-existing immuneresponse, whose activity is strictly related to the presence of necrosis, hypoxia, and inflammation in the tumor sites, which can be evaluated by imaging assessments.

      Methods:
      A retrospective analysis was performed on a sample of seventeen NSCLC patients who received salvage therapy with Nivolumab 3 mg/kg every 15 days between October 2015 and January 2017 with a median follow up of twelve months. The gross primary tumor volume before treatment (baseline) was contoured on pre and post contrast CT sequences. TA parameters were extrapolated by using LifeX Software ©, tested for reliability and then correlated with patients’ outcome, in particular with early failure defined as a confirmed disease progression or death within 6 months (7 patients), by means of univariate and multivariate analysis.

      Results:
      We found a significant correlation among TA parameters and patients’ outcome at univariate analysis. In fact, early vs longer responders showed differences in term of volume in voxel (p:0.049), entropy (p:0.046), compacity (p:0.033), GLCM-contrast (p: 0.018), GLCM-dissimilarity (p:0.017), LRHGE (p:0.019), coarseness (p:0.036), contrast (0.020), ZP (p:0.025), pre contrast: GLCM-contrast (p:0.031), GLCM-dissimilarity (p:0.035), contrast (p:0.038), SZE (p:0.029), ZP (p:0.040). Multivariate analysis (Logistic regression) confirmed a significant correlation between early failure and post contrast GLCM dissimilarity (p:0.011, OR: 3.30, AUC: 0.800; 95% CI 0.578-1.00).

      Conclusions:
      Our results, if confirmed on a larger series, suggest that TA may predict early failure, and therefore may help the selection of patients who may benefit by Nivolumab treatment.

      Clinical trial identification:


      Legal entity responsible for the study:
      Azienda Ospedaliera Universitaria Senese

      Funding:
      Azienda Ospedaliera Universitaria Senese

      Disclosure:
      All authors have declared no conflicts of interest.