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  • Univariate and stepwise multivariate Cox regression analyses

    2019-08-26

    Univariate and stepwise multivariate Cox-regression analyses for variables influencing PFS and OS are depicted in Table 4. Multivariate analyses revealed a significant effect on PFS (hazard ratio (HR) for progression/death) for leading STM response (p < 0.001), RECIST response (p = 0.003) and PD-L1 status (p = 0.003). Analogously for OS (HR for death), STM response (p < 0.001), presence of cerebral metastases (p = 0.036) and therapy line≥3 (p = 0.001) prove significant.
    Discussion There is a clinical need for additional biomarkers of disease activity and prediction of prognosis next to imaging in ICI treated advanced NSCLC patients. On the one hand, radiological responses may be delayed and phenomena like pseudo-progression upon ICI therapy do exist [1,22]. Also, selected patients may benefit from ICI treatment beyond progression [23]. On the other hand, timely determination of progressive disease is essential, as no time should be lost to ineffective therapies, being neither beneficial nor cost-effective in most patients. In that context, our observation that patients with leading STM more than doubled (19%) have distinctly inferior PFS and OS resembles recent observations on hyper-progressive disease upon PD-1/PD-L1 inhibitor therapy as reported by Ferrara et al. in approximately 14% of patients [24]. Recently published data by Dal Bello et al. show, that CEA and CYFRA 21-1 change in parallel with radiological tumor response in nivolumab treated NSCLC patients, while NSE did not provide similar results. A decrease in CEA and CYFRA 21-1 of ≥20% was associated with radiologically assessed disease control rate, PFS and OS [9,10]. The similarity of the published results support the findings presented in this Cucurbitacin I paper. Our reported cohort contains a slightly higher number of patients, also treated with other PD-1/PD-L1 inhibitors, e.g. pembrolizumab and atezolizumab. Also, we used CA19-9 as an additional STM and proposed the model of a leading STM out of an initially assessed STM panel. We believe, that STM elevated at the time of diagnosis are more likely to be associated with tumor activity, while values within or near the normal range may often be unspecific. NSE primates is being analyzed in our routine STM panel upon primary lung cancer diagnosis with special regard to neuroendocrine tumors, where data suggests a higher value than for NSCLC [25]. Like also suggested by Dal Bello et al. [10], we do not regard NSE as an adequate tumor marker for the monitoring of NSCLC under ICI therapy. In our presented dataset, only one patient had NSE as a leading STM (with concomitantly elevated CYFRA 21-1). Our study has several limitations, mainly its retrospective design and its limited patient number. Nevertheless, the distinct differences between the subgroups identified by STM dynamics strongly suggest a significant prognostic impact of these biomarkers. A general limitation of STM measurement is that none of the tested markers is specific to a certain cancer entity. Also, various chronic or acute conditions apart from malignancies may influence STM concentrations [26,27]. Another limitation may be, that although a panel of four STM was initially assessed, the leading STM was not elevated in a considerable fraction of patients (n = 8; 9.5%). Whether the predictive value of the leading STM differed in those cases cannot be comprehensively assessed due to the low absolute number of cases. Obviously, STM change can only be measured retrospectively after a patient has already been treated with ICI therapy, while biomarkers like PD-L1 status or TMB allow an a priori prognosis. Previously published data [7,8], and our presented ROC analyses show that baseline STM may provide some prognostic information. A limitation of the reported ROC analysis however is, that it only accounts for progression/death or death, respectively, not considering the time to the event.