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Silvia Genestroni



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    P2.04 - Immuno-oncology (ID 167)

    • Event: WCLC 2019
    • Type: Poster Viewing in the Exhibit Hall
    • Track: Immuno-oncology
    • Presentations: 1
    • Moderators:
    • Coordinates: 9/09/2019, 10:15 - 18:15, Exhibit Hall
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      P2.04-14 - NLR, dNLR and PLR as Possible Predictive Markers in Patients with NSCLC Treated with ICI (ID 1063)

      10:15 - 18:15  |  Author(s): Silvia Genestroni

      • Abstract
      • Slides

      Background

      Clinical evidence suggests a possible predictive role of Neutrophil-to-Lymphocyte ratio (NLR), derived Neutrophils/(leukocytes minus neutrophils) ratio (dNLR) and Platelet-to-Lymphocyte ratio (PLR) in different tumors, including non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICI).

      Method

      In this Italian multicenter retrospective trial NLR, dLNR, PRL fluctuations were analyzed in patients with stage IV NSCLC treated with ICI. Those rates were assessed at baseline, before the second, third and fifth cycles. In patients still on treatment, samples were collected also at 1 and at 2 years from ICI start. The primary objective was the relationship between baseline ratios and response to ICI, through the identification of different cut-offs estimated using ROC curves.

      Result

      Data of 402 patients receiving ICI (antiPD1 91%, antiPDL1 7% and antiPDL1 plus antiCTLA-4 2%) were analysed: 287 (71%) were males, median age was 65 (39-86 yrs-old), 84 patients (21%) were on first line treatment. The most common histology was adenocarcinoma (62%) and 95% of patients had an ECOG performance status of 0-1. One hundred and eleven (30%) patients were using steroids in permissive doses for ICI. Disease control rate (DCR) was observed in 228 patients (58%) with 95 (24%) reporting an immune objective response. Median progression free survival was 5,3 months and the median overall survival was 9,6 months, after a median follow-up of 9,6 months (range 4,0-13.0). Basal NLR, dNLR and PRL were predictive of response (p=0.0002, p=0.0003 and p=0.0304, respectively). Best response categories were dichotomized in Response (SD + PR + CR) versus no Response (PD). With this classification, the differences were more pronounced and statistically significant for basal NLR and dNLR (p=0,045 and p=0,004, respectively). The cut-off values for basal NLR and dNLR were defined (BLNLR=2,46; BLdNLR=1,61) to identify patients most at risk of “non Response” through the ROC curves. Confounding factors were assessed using logistic regression models (age, gender, smoking). During treatment, an increase in the values was observed at the time of progression, both for NLR (average variation: -1.57) and for dNLR (average variation + 0.32), even if the statistical significance is limited to NLR (p = 0.041).

      Conclusion

      NLR, dNLR and PLR are independent factors of response to ICI. Compared to the present literature data, this study highlights that NLR ratio may predict progressive disease earlier than radiological restaging.

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