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  • br Table br Univariate analyses


    Table 3
    Univariate analyses.
    PFS1, months
    OS2, months
    Median 95% CI3 p value Median 95% CI p value
    Variables Subgroups
    1 Progression Free Survival.
    2 Overall Survival.
    3 Confidence Interval.
    4 Performance Status.
    5 Immune Checkpoint Inhibitor.
    6 Immunotherapy.
    7 Not Reached.
    8 Antibiotic.
    9 Early Immunotherapy Period.
    10 Antibiotic-Immunotherapy Exposure Ratio.
    11 Whole Immunotherapy Period.
    process is limited in time, in particular, if IO is carried on meanwhile, it is likely that the effects of Heparin sodium on intestinal flora and, conse-quently, on anti-tumor immune response, is negligible. On the contrary, if a patient receives multiple or prolonged antibiotic cycles, the re-peated hits on gut microbiota may interfere with bacterial reconstitu-tion, leading to a deeper impact on systemic immunity. The significant relation between AIER and outcome, irrespective of the effects of PS and IO line, and in absence of a clear role for the simple antibiotic use at the beginning of IO, supports the potential role of AIER as a new in-dependent determinant.
    As regards to the lack of association between antibiotic use in the 
    EIOP and outcome, our results differ from most recent research data showing a significant negative impact of early antibiotics use on PFS. We can be made only hypotheses to explain this discrepancy, maybe due to the population characteristics and to the small sample size. In any case, a numerical trend towards superior PFS and OS in patients not receiving antibiotics was identified, in line with literature data. Nonetheless, it has to be underlined that also a previous retrospective work on 74 NSCLC cases treated with nivolumab did not find differ-ences in RR and PFS according to antibiotic use in the 3 months before the beginning of the ICI treatment [41]. This underlines the lack of definitive evidence in the field of microbiota and IO, in particular for
    Fig. 1. Kaplan-Meier curves for PFS and OS according to antibiotic use in the EIOP.
    PFS = Progression Free Survival.
    Atb = Antibiotics.
    EIOP = Early Immunotherapy Period.
    OS = Overall Survival.
    Fig. 2. Kaplan-Meier curves for PFS and OS according to AIER during the WIOP.
    PFS = Progression Free Survival.
    AIER = Antibiotic/Immunotherapy Exposure Ratio.
    OS = Overall Survival.
    Table 4
    Multivariate analyses.
    PFS1, months OS2, months
    1 Progression Free Survival.
    2 Overall Survival.
    3 Hazard Ratio.
    4 Confidence Interval.
    5 Immunotherapy.
    6 Antibiotic.
    7 Performance Status.
    NSCLC, and the consequent need of further research.
    This study has some limitations. First, it is a retrospective analysis of a single Institution population, with a small number of patients. This might limit the possibility of generalizing its results. Second, as this is a retrospective work on an unselected population, we did not perform either biologic analyses on stool samples, or translational correlations on animal models. This prevents from identifying a biologic rationale and confirmation for our observations. Indeed, in absence of a trans-lational correlative, the possibility that patients receiving repeated courses of antibiotics have a worse prognosis because of frequent in-fections and not for the use of antibiotics itself, cannot be excluded. In the end, AIER is a merely empiric variable, based on a theoretical ra-tionale, which will require additional studies to prove its scientific basis. Moreover, the cutoff chosen for stratification derives from the analysis of the population itself, being defined as the median value of the observed cases. This cutoff may be different when analyzing other case series, and the results may change consequently.
    Despite these limitations, the present work presents some inter-esting points. For the first time it proposes the AIER as a new variable that may condition the impact of antibiotic use on the efficacy of IO. Although the selection of a specific cut-off may be questionable, we conducted our analysis in the attempt of testing the potential applica-tions of this new variable. Indeed, a definite cut-off is essential for any tool aiming to be useful in clinical practice, whereas continuous