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NAOYUKI Okabe



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    EP1.01 - Advanced NSCLC (ID 150)

    • Event: WCLC 2019
    • Type: E-Poster Viewing in the Exhibit Hall
    • Track: Advanced NSCLC
    • Presentations: 1
    • Now Available
    • Moderators:
    • Coordinates: 9/08/2019, 08:00 - 18:00, Exhibit Hall
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      EP1.01-61 - iSEND Model as a Predictor of Efficacy in Immune Checkpoint Inhibitors for Non-Small Cell Lung Cancer: Fukushima Cohort (Now Available) (ID 1689)

      08:00 - 18:00  |  Presenting Author(s): NAOYUKI Okabe

      • Abstract
      • Slides

      Background

      The expression of PD-L1 in tumor tissue and the number of gene mutations (TMB) in tumor tissue have been investigated as predictors of the efficacy of PD-1/PD-L1 inhibitors in non-small cell lung cancer. However. In actual clinical practice, it is difficult to perform these tests in all cases.

      Therefore, we are searching for an effect prediction marker that can be done easily and inexpensively. Wungki Park et al. constructed the iSEND model as a therapeutic effect predictor and showed its usefulness. We examined the usefulness of iSEND model for non-small cell lung cancer patients who received PD-1 / PD-L1 inhibitor at our institution.

      Method

      We retrospectively examined the usefulness of the iSEND model in 56 patients with non-small cell lung cancer who were treated with PD-1/PD-L1 inhibitor in our department after the second treatment. The iSEND model uses patient background and blood tests. Calculated and scored using gender, ECOG performance status, NLR before treatment and after treatment (Neutrophi-to-Lymphocyte Ratios), and divided into three group. For each group, we statistically compared the clinical course such as overall survival and recurrence-free survival.

      Result

      In the analysis by Wungki Park et al. , The iSEND Poor group has a median overall survival of 4.0 months and 15.9 months, respectively, compared with the iSEND Good group (p = 0.0002), and the median recurrence free period is 1.6 months and 2.6 months, respectively. Months (p = 0.0045), and each showed a significant difference. In our study, no statistically significant difference was found, but a trend similar to the analysis of Wungki Park et al.

      Conclusion

      In this study, it is suggested that the iSEND model may be useful as a predictor of the effect of PD-1/PD-L1 inhibitor.

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