Abstract 4212
Background
Among the inflammation-related biomarkers, high MLR values are associated to poorer outcomes in different cancers. We explored the prognostic role of MLR in a multicenter series of EOC patients (p).
Methods
We included all pathologically confirmed stage III/IV EOC p who had undergone radical treatment in Institut Català d’Oncologia (ICO) Badalona (from 2008 to 2017), ICO Girona (2013 - 2015) and ICO Hospitalet (2011-2014). MLR was calculated from the counts of monocytes and lymphocytes at diagnosis. Overall survival (OS) was assessed by Kaplan Meyer. The impact of MLR on OS was explored by COX regression. Variables included in these analyses were: histology (high grade serous carcinomas –HGSOC-, other), stage (III, IV), primary treatment (primary surgery –PS-, interval debulking surgery –IDS-), residual disease (R0 vs R1/R2), age at diagnosis and MLR (the last two assessed as continuous variables). Maximally selected rank statistics was used to identify an optimal MLR cut-off value that resulted in two groups with different OS, in the whole sample, in p who underwent PS, and in p who received IDS.
Results
128 p were included. Median age at diagnosis was 62 years; 82.9% were HGSOC; 65.8% were stage III; 52.3% had undergone PS, and 47.7% IDS; 73.4 % were R0. Stage III, R0, and low MLR values were associated to better OS (p = 0.047, <0.0007, and 0.043, respectively) in the multivariate Cox analyses (analysis done in 109 p, as 19 observations deleted due to missingness). Optimal MLR cut-off was 0.33: 44 p were low risk (MLR-lo), and 84 p were high risk (MLR-hi), with significant differences in OS between them (82.36 vs 41.8 months, p = 0.032). Among p who underwent PS (67p), optimal cut-off was 0.42: 46p MLR-lo, and 21p MLR-hi (OS: 87.17 vs 41.2 months, p = 0.012). Among p who underwent IDS, an optimal cut-off related to OS could not be identified.
Conclusions
High MLR values appear to be related to worse OS in EOC p, specifically among p who underwent PS, but not among p who received IDS. MLR could be used to identify high risk p, even undergoing PS, in whom alternative therapies may be explored.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
M. Cucurull Salamero: Speaker Bureau / Expert testimony, Travel / Accommodation / Expenses: Roche. M. Gil: Speaker Bureau / Expert testimony, Travel / Accommodation / Expenses: Roche Pharma; Speaker Bureau / Expert testimony: AstraZeneca; Speaker Bureau / Expert testimony, Travel / Accommodation / Expenses: PharmaMar. E. Felip Falgas: Speaker Bureau / Expert testimony, Travel / Accommodation / Expenses: AstraZeneca; Speaker Bureau / Expert testimony: MSD; Speaker Bureau / Expert testimony: Kyowa Kirin; Travel / Accommodation / Expenses: Pfizer; Travel / Accommodation / Expenses: Novartis; Travel / Accommodation / Expenses: Roche. C. Erasun Lecuona: Full / Part-time employment: Pierre Fabre. J.J. García Mosquera: Honoraria (self), Travel / Accommodation / Expenses: Merck; Travel / Accommodation / Expenses: Servier; Travel / Accommodation / Expenses: Roche; Travel / Accommodation / Expenses: Otsuka; Travel / Accommodation / Expenses: Mundipharma. S. Martinez Román: Advisory / Consultancy, Speaker Bureau / Expert testimony, Travel / Accommodation / Expenses: Roche Pharma. All other authors have declared no conflicts of interest.
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