Platelet-to-lymphocyte ratio associated with the clinicopathological features and prognostic value of breast cancer: A meta-analysis

Gong, Zhixun; Xin, Ruomei; Li, Long; Lv, Liping; Wu, Xinni

doi:10.1177/03936155221118098

Cited by 16 publications

(10 citation statements)

References 60 publications

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“…For example, high NLR and PLR were associated with shorter overall survival and disease-free survival, while low LMR was associated with improved prognosis [12,14]. Besides, the elevated PLR was related to the risk of lymph node metastasis and distant metastasis [13]. In addition, PLR was an independent factor for predicting pCR after NAC for BC, and patients with low PLR achieved higher pCR rates [15][16][17].…”

Section: Introductionmentioning

confidence: 95%

“…Previous studies have shown that PLR can be used as a predictor and prognostic factor of treatment response to NAC for BC. Low PLR was associated with prolonged overall survival and diseasefree survival [12], while high PLR was associated with increased risk of lymph node and distant metastasis in BC patients [13]. PLR can also predict the pathological response of BC patients after NAC.…”

Section: Table 1 (Continued)mentioning

confidence: 99%

“…Previous studies have shown that the host immune system plays an important role in the occurrence, development and metastasis of tumor [9,10]. Peripheral blood inflammatory indexes, including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte (PLR), lymphocyte-to-monocyte ratio (LMR) and systemic immune inflammation index (SII), were significantly correlated with the prognosis of BC patients [11][12][13]. For example, high NLR and PLR were associated with shorter overall survival and disease-free survival, while low LMR was associated with improved prognosis [12,14].…”

Section: Introductionmentioning

confidence: 99%

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A nomogram based on platelet-to-lymphocyte ratio for predicting pathological complete response of breast cancer after neoadjuvant chemotherapy

Wei

et al. 2023

BMC Cancer

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Objective To investigate the role of platelet-to-lymphocyte ratio (PLR) in complete pathological response (pCR) of breast cancer (BC) patients after neoadjuvant chemotherapy (NAC), as well as to establish and validate a nomogram for predicting pCR. Methods BC patients diagnosed and treated in the First Affiliated Hospital of Xi’an Jiaotong University from January 2019 to June 2022 were included. The correlation between pCR and clinicopathological characteristics was analyzed by Chi-square test. Logistic regression analysis was performed to evaluate the factors that might affect pCR. Based on the results of regression analysis, a nomogram for predicting pCR was established and validated. Results A total of 112 BC patients were included in this study. 50.89% of the patients acquired pCR after NAC. Chi-square test showed that PLR was significantly correlated with pCR (X2 = 18.878, P < 0.001). And the PLR before NAC in pCR group was lower than that in Non-pCR group (t = 3.290, P = 0.001). Logistic regression analysis suggested that white blood cell (WBC) [odds ratio (OR): 0.19, 95% confidence interval (CI): 0.04–0.85, P = 0.030)], platelet (PLT) (OR: 0.19, 95%CI: 0.04–0.85, P = 0.030), PLR (OR: 0.18, 95%CI: 0.04–0.90, P = 0.036) and tumor grade (OR: 9.24, 95%CI: 1.89–45.07, P = 0.006) were independent predictors of pCR after NAC. A nomogram prediction model based on WBC, PLR, PLR and tumor grade showed a good predictive ability. Conclusion PLR, PLT, WBC and tumor grade were independent predictors of pCR in BC patients after NAC. The nomogram based on the above positive factors showed a good predictive ability.

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Section: Introductionmentioning

confidence: 95%

Section: Table 1 (Continued)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A nomogram based on platelet-to-lymphocyte ratio for predicting pathological complete response of breast cancer after neoadjuvant chemotherapy

Wei

et al. 2023

BMC Cancer

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“…33 In a meta-analysis of 7484 patients with BC, elevated platelet-lymphocyte ratios were associated with a poor BC prognosis and a high risk of distant metastasis. 34 In this study, several blood parameters were associated with TLSs, including LYMPH%, MONO %, BASO%, and PLT.…”

Section: Discussionmentioning

confidence: 61%

Analysis of the Correlation and Prognostic Significance of Tertiary Lymphoid Structures in Breast Cancer: A Radiomics‐Clinical Integration Approach

et al. 2023

Magnetic Resonance Imaging

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BackgroundTertiary lymphoid structures (TLSs) are potential prognostic indicators. Radiomics may help reduce unnecessary invasive operations.PurposeTo analyze the association between TLSs and prognosis, and to establish a nomogram model to evaluate the expression of TLSs in breast cancer (BC) patients.Study TypeRetrospective.PopulationTwo hundred forty‐two patients with localized primary BC (confirmed by surgery) were divided into BC + TLS group (N = 122) and BC − TLS group (N = 120).Field Strength/Sequence3.0T; Caipirinha‐Dixon‐TWIST‐volume interpolated breath‐hold sequence for dynamic contrast‐enhanced (DCE) MRI and inversion‐recovery turbo spin echo sequence for T2‐weighted imaging (T2WI).AssessmentThree models for differentiating BC + TLS and BC − TLS were developed: 1) a clinical model, 2) a radiomics signature model, and 3) a combined clinical and radiomics (nomogram) model. The overall survival (OS), distant metastasis‐free survival (DMFS), and disease‐free survival (DFS) were compared to evaluate the prognostic value of TLSs.Statistical TestsLASSO algorithm and ANOVA were used to select highly correlated features. Clinical relevant variables were identified by multivariable logistic regression. Model performance was evaluated by the area under the receiver operating characteristic (ROC) curve (AUC), and through decision curve analysis (DCA). The Kaplan–Meier method was used to calculate the survival rate.ResultsThe radiomics signature model (training: AUC 0.766; test: AUC 0.749) and the nomogram model (training: AUC 0.820; test: AUC 0.749) showed better validation performance than the clinical model. DCA showed that the nomogram model had a higher net benefit than the other models. The median follow‐up time was 52 months. While there was no significant difference in 3‐year OS (P = 0.22) between BC + TLS and BC − TLS patients, there were significant differences in 3‐year DFS and 3‐year DMFS between the two groups.Data ConclusionThe nomogram model performs well in distinguishing the presence or absence of TLS. BC + TLS patients had higher long‐term disease control rates and better prognoses than those without TLS.Evidence Level2Technical EfficacyStage 2

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“…Many studies have found that systemic inflammatory responses affect the occurrence and development of malignant tumors by regulating the biological microenvironment[ 29 - 33 ]. Based on this concept, several simple and stable inflammatory markers have been shown to be associated with prognosis in malignancy, including platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index, neutrophil-to-lymphocyte ratio (NLR), prognostic nutritional index and Glasgow Prognostic Score[ 34 - 38 ]. Recently, a novel inflammatory marker, the C-reactive protein (CRP) to albumin ratio (CAR), has been reported as an independent prognostic factor in various malignancies.…”

Section: Introductionmentioning

confidence: 99%

C-reactive protein to albumin ratio predict responses to programmed cell death-1 inhibitors in hepatocellular carcinoma patients

Li,

Chen,

et al. 2024

World J Gastrointest Oncol

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BACKGROUND Over the years, programmed cell death-1 (PD-1) inhibitors have been routinely used for hepatocellular carcinoma (HCC) treatment and yielded improved survival outcomes. Nonetheless, significant heterogeneity surrounds the outcomes of most studies. Therefore, it is critical to search for biomarkers that predict the efficacy of PD-1 inhibitors in patients with HCC. AIM To investigate the role of the C-reactive protein to albumin ratio (CAR) in evaluating the efficacy of PD-1 inhibitors for HCC. METHODS The clinical data of 160 patients with HCC treated with PD-1 inhibitors from January 2018 to November 2022 at the First Affiliated Hospital of Guangxi Medical University were retrospectively analyzed. RESULTS The optimal cut-off value for CAR based on progression-free survival (PFS) was determined to be 1.20 using x-tile software. Cox proportional risk model was used to determine the factors affecting prognosis. Eastern Cooperative Oncology Group performance status [hazard ratio (HR) = 1.754, 95% confidence interval (95%CI) = 1.045-2.944, P = 0.033], CAR (HR = 2.118, 95%CI = 1.057-4.243, P = 0.034) and tumor number (HR = 2.932, 95%CI = 1.246-6.897, P = 0.014) were independent prognostic factors for overall survival. CAR (HR = 2.730, 95%CI = 1.502-4.961, P = 0.001), tumor number (HR = 1.584, 95%CI = 1.003-2.500, P = 0.048) and neutrophil to lymphocyte ratio (HR = 1.120, 95%CI = 1.022-1.228, P = 0.015) were independent prognostic factors for PFS. Two nomograms were constructed based on independent prognostic factors. The C-index index and calibration plots confirmed that the nomogram is a reliable risk prediction tool. The ROC curve and decision curve analysis confirmed that the nomogram has a good predictive effect as well as a net clinical benefit. CONCLUSION Overall, we reveal that the CAR is a potential predictor of short- and long-term prognosis in patients with HCC treated with PD-1 inhibitors. If further verified, CAR-based nomogram may increase the number of markers that predict individualized prognosis.

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Platelet-to-lymphocyte ratio associated with the clinicopathological features and prognostic value of breast cancer: A meta-analysis

Cited by 16 publications

References 60 publications

A nomogram based on platelet-to-lymphocyte ratio for predicting pathological complete response of breast cancer after neoadjuvant chemotherapy

A nomogram based on platelet-to-lymphocyte ratio for predicting pathological complete response of breast cancer after neoadjuvant chemotherapy

Analysis of the Correlation and Prognostic Significance of Tertiary Lymphoid Structures in Breast Cancer: A Radiomics‐Clinical Integration Approach

C-reactive protein to albumin ratio predict responses to programmed cell death-1 inhibitors in hepatocellular carcinoma patients

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