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Journal of Cancer
Article . 2020 . Peer-reviewed
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Journal of Cancer
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PubMed Central
Article . 2020
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Combined Preoperative LMR and CA125 for Prognostic Assessment of Ovarian Cancer

Authors: Tang, Ying; Hu, Hui-quan; Tang, Fang-xiang; Lin, Dan; Shen, Rui; Deng, Li; Tang, Ya-lan; +5 Authors

Combined Preoperative LMR and CA125 for Prognostic Assessment of Ovarian Cancer

Abstract

Objectives: To investigate the role of inflammation-related factors, lymphocyte-to-monocyte ratio (LMR) alone and combined detection with cancer antigen 125 (CA125), in the prognostic assessment of ovarian cancer (OC). Methods: A retrospective clinicopathologic review was performed. The receiver-operating characteristic (ROC) curves of LMR, CA125, and COLC predicting mortality in OC patients were constructed. Besides, Kaplan-Meier and Cox logistic regression models were used to plot the survival curves and determine the independent prognostic factors. Results: A total of 214 OC patients were identified in this cohort. The mean duration of follow-up was 64 months (minimum 8 months, maximum 116 months). In this cohort, 135 cases died (63.1%), and the median progression-free survival (PFS) and overall survival (OS) were 20 and 39.5 months, respectively. Results of the multivariate Cox regression model showed that LMR≤3.8 (HR = 0.494, 95% CI: 0.329-0.742, P = 0.001) and CA125>34 U/ml (HR = 1.641, 95% CI: 1.057-2.550, P = 0.027) were significantly associated with poor PFS; and LMR≤3.8 (HR = 0.459, 95% CI: 0.306-0.688, P = 34 U/ml (HR = 1.946, 95% CI: 1.256-3.015, P = 0.003) were significantly associated with OS. Furthermore, the area under the curve of COLC was higher (0.713) than that of LMR (0.709) or CA125 (0.583), the specificity of COLC was higher (75.9%) than that of LMR (62%) or CA125 (40.5%) in predicting mortality in OC patients. Conclusions: LMR alone and combined with CA125 might be used as predictive markers in OC. Furthermore, as a prognostic factor, COLC might have a higher specificity to predict the outcome.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
22
Top 10%
Top 10%
Top 10%
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gold
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Cancer Research