Prognostic roles of neutrophil to lymphocyte ratio and platelet to lymphocyte ratio in ovarian cancer: a meta-analysis of retrospective studies

Zhao, Zhe; Zhao, Xiaomin; Lu, Jingjing; Xue, Jing; Liu, Peishu; Mao, Hongluan

doi:10.1007/s00404-018-4678-8

Cited by 84 publications

(85 citation statements)

References 43 publications

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“…In a previous study, readily available biomarkers in clinical settings including indicators of the systemic inflammatory response and pretherapeutic coagulation-related factors were shown to be of prognostic relevance in patients with EOC (24). A recent meta-analysis of data from 13 studies (n ¼ 3,467) showed that both high neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio are associated with unfavorable prognosis of patients with EOC (25). In addition, elevated levels of pretreatment plasma D-dimer, Fbg, and PLT were found useful in predicting disease progression and survival outcomes of patients with EOC (26)(27)(28).…”

Section: Discussionmentioning

confidence: 99%

Application of Artificial Intelligence for Preoperative Diagnostic and Prognostic Prediction in Epithelial Ovarian Cancer Based on Blood Biomarkers

Kawakami

Tabata

Yanaihara

et al. 2019

Clinical Cancer Research

150

103

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Purpose: We aimed to develop an ovarian cancer-specific predictive framework for clinical stage, histotype, residual tumor burden, and prognosis using machine learning methods based on multiple biomarkers.Experimental Design: Overall, 334 patients with epithelial ovarian cancer (EOC) and 101 patients with benign ovarian tumors were randomly assigned to "training" and "test" cohorts. Seven supervised machine learning classifiers, including Gradient Boosting Machine (GBM), Support Vector Machine, Random Forest (RF), Conditional RF (CRF), Na€ ve Bayes, Neural Network, and Elastic Net, were used to derive diagnostic and prognostic information from 32 parameters commonly available from pretreatment peripheral blood tests and age.Results: Machine learning techniques were superior to conventional regression-based analyses in predicting multiple clinical parameters pertaining to EOC. Ensemble meth-ods combining weak decision trees, such as GBM, RF, and CRF, showed the best performance in EOC prediction. The values for the highest accuracy and area under the ROC curve (AUC) for segregating EOC from benign ovarian tumors with RF were 92.4% and 0.968, respectively. The highest accuracy and AUC for predicting clinical stages with RF were 69.0% and 0.760, respectively. High-grade serous and mucinous histotypes of EOC could be preoperatively predicted with RF. An ordinal RF classifier could distinguish complete resection from others. Unsupervised clustering analysis identified subgroups among early-stage EOC patients with significantly worse survival.Conclusions: Machine learning systems can provide critical diagnostic and prognostic prediction for patients with EOC before initial intervention, and the use of predictive algorithms may facilitate personalized treatment options through pretreatment stratification of patients.NOTE: There were too few early-stage EOC patients with residual tumor. A definition for the significance of bold is P value of < 0.05.

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Section: Discussionmentioning

confidence: 99%

Application of Artificial Intelligence for Preoperative Diagnostic and Prognostic Prediction in Epithelial Ovarian Cancer Based on Blood Biomarkers

Kawakami

Tabata

Yanaihara

et al. 2019

Clinical Cancer Research

150

103

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“…PLR is reported to be associated with breast, pancreatic, and colorectal cancers [ 4 , 5 ]. In obstetrics and gynecology, NLR and PLR has been reported to be correlated with ovarian cancer [ 10 , 11 ] Another study suggested that NLR is associated with hormonal status in polycystic ovarian syndrome [ 12 ]. Recent study reported that NLR could identify PTB in women with spontaneous, late preterm labor [ 13 ].…”

Section: Discussionmentioning

confidence: 99%

Prognostic Significance of Neutrophil-to-Lymphocyte Ratio for Repeat Cerclage in Women with Prolapsed Membranes

Song

Lee

Son

2018

BioMed Research International

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Objective Cerclage is a surgical option for preventing preterm birth (PTB). Repeat cerclage (RC) could prevent impending PTB in women with prolapsed membrane who already had primary cerclage. PTB is associated with a state of inflammation. It has been widely known that neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) reflect systemic inflammation. We aimed to investigate whether NLR and PLR could be used as reliable markers in predicting pregnancy outcome following RC. Methods The study group consisted of 26 patients, who underwent RC resulting from prolapsed membrane after primary cerclage. NLR and PLR at the time of primary cerclage and RC were calculated. ROC curve analysis and multivariate analysis were performed for determining predictive factors. The study group was divided into two groups according to NLR 4.7 at RC: High NLR group was defined as NLR > 4.7, and low NLR group was defined as NLR ≤ 4.7. We compared pregnancy outcomes, such as delivery at gestational age, and rate of delivery < 28 weeks between two groups. Results The average gestational age at primary cerclage was 15.7 weeks, and the mean gestational age at RC was 21.0 weeks. NLR at RC was significantly elevated when compared with NLR at primary cerclage (NLR, 4.0 vs. 8.9, p=0.001), but there was no significant difference in terms of PLR (p=0.07). ROC curve showed that there was a significant prediction power of NLR at RC for delivery < 28 weeks (AUC, 0.91; p<0.01). Using NLR cut-off of 4.7, 8 had NLR ≤ 4.7 (low NLR group), whereas 18 had NLR > 4.7 (high NLR group). High NLR group showed worse pregnancy outcome compared to low NLR group: there were significant differences in gestational age at delivery, and neonatal survival rate between two groups (31.5 weeks vs. 25.9 weeks, p=0.02; 100% (8/8) vs. 55.6% (10/18), p=0.03, respectively). Survival analysis demonstrated a lower incidence of delivery < 28 weeks of gestation in low NLR group compared with high NLR group (p<0.01, log-rank test). Conclusion NLR might be used as a reliable factor for predicting pregnancy outcome following RC.

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“…A high pretreatment NLR is an adverse prognostic indicator for both the early and advanced stages of several malignancies [10,16] . Emerging evidence showed that SIR markers, such as NLR, PLR, and MLR, were associated with the prognosis of ovarian cancer patients [17,18] . To date, few reliable preoperative biomarkers that predict resistance or prognosis in OCCC have been identi ed.…”

Section: Discussionmentioning

confidence: 99%

Serum D-dimer, Albumin and Systemic Inflammatory Response Markers in Ovarian Clear Cell Carcinoma and Their Prognostic Implications

Chen

Zhong

Shan

et al. 2020

Preprint

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Background: This study attempts to evaluate whether preoperative systemic inflammatory response (SIR) markers or other hematological variables, such as albumin, D-dimer, and carbohydrate antigen 125, play roles in predicting chemotherapy response and survival outcome in patients with ovarian clear cell carcinoma (OCCC).Methods: Preoperative leukocyte differential counts, as well as platelet, serum albumin, plasma D-dimer and CA-125 levels, were measured in patients with FIGO IC-IV ovarian clear cell cancer. The correlations of these hematological biomarkers with clinicopathological features, chemotherapy response, and survival outcomes were further analyzed. Survival time was estimated using the Kaplan-Meier model, whereas Cox regression was conducted for multivariate analysis.Results: Among the 84 patients, 28.6% were classified as platinum resistant, and 69.0% were platinum sensitive. Preoperative CA125, albumin, and D-dimer levels; neutrophil to lymphocyte ratios (NLR); and monocyte to lymphocyte ratios were significantly correlated with FIGO stage, residual tumor, and platinum response. Platelet to lymphocyte ratio was not related to platinum response (P=0.060). The median follow-up time was 28 months (range, 1 to 128 months). Preoperative CA125, albumin, and D-dimer levels were significant prognostic factors for overall survival (OS) and progression-free survival (PFS). In the univariate analysis, only NLR exhibited prognostic significance for PFS (P = 0.007). Multivariate analysis indicated that D-dimer > 3.27 (P = 0.001 for OS; P = 0.040 for PFS) and albumin <39.6 (P = 0.005 for OS and P = 0.041 for PFS) retained significance.Conclusions: Preoperative NLR has some predictive value for platinum resistance in patients with IC-IV stage OCCC but has little predictive effect on prognosis. Elevated D-dimer and reduced albumin might be potential biomarkers for worse response to first-line platinum-based chemotherapy and poor clinical outcomes.

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Prognostic roles of neutrophil to lymphocyte ratio and platelet to lymphocyte ratio in ovarian cancer: a meta-analysis of retrospective studies

Abstract: In conclusion, we found that both NLR and PLR had an unfavorable impact on PFS and OS of patients with ovarian cancer. Our meta-analysis supported that NLR/PLR could be effective prognostic predictors of ovarian cancer.

Cited by 84 publications

References 43 publications

Application of Artificial Intelligence for Preoperative Diagnostic and Prognostic Prediction in Epithelial Ovarian Cancer Based on Blood Biomarkers

Application of Artificial Intelligence for Preoperative Diagnostic and Prognostic Prediction in Epithelial Ovarian Cancer Based on Blood Biomarkers

Prognostic Significance of Neutrophil-to-Lymphocyte Ratio for Repeat Cerclage in Women with Prolapsed Membranes

Serum D-dimer, Albumin and Systemic Inflammatory Response Markers in Ovarian Clear Cell Carcinoma and Their Prognostic Implications

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