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

Predictive value of pretreatment circulating inflammatory response markers in the neoadjuvant treatment of breast cancer: meta-analysis

BACKGROUND

Systemic inflammatory response markers have been found to have a prognostic role in several cancers, but their value in predicting the response to neoadjuvant chemotherapy in breast cancer is uncertain. A systematic review and meta-analysis of the literature was carried out to investigate this.

METHODS

A systematic search of electronic databases was conducted to identify studies that explored the predictive value of circulating systemic inflammatory response markers in patients with breast cancer before commencing neoadjuvant therapy. A meta-analysis was undertaken for each inflammatory marker where three or more studies reported pCR rates in relation to the inflammatory marker. Outcome data are reported as ORs and 95% confidence intervals.

RESULTS

A total of 49 studies were included, of which 42 were suitable for meta-analysis. A lower pretreatment neutrophil-to-lymphocyte ratio was associated with an increased pCR rate (pooled OR 1.66 (95% c.i. 1.32 to 2.09); P < 0.001). A lower white cell count (OR 1.96 (95% c.i. 1.29 to 2.97); P = 0.002) and a lower monocyte count (OR 3.20 (95% c.i. 1.71 to 5.97); P < 0.001) were also associated with a pCR. A higher lymphocyte count was associated with an increased pCR rate (OR 0.44 (95% c.i. 0.30 to 0.64); P < 0.001).

CONCLUSION

The present study found the pretreatment neutrophil-to-lymphocyte ratio, white cell count, lymphocyte count, and monocyte count of value in the prediction of a pCR in the neoadjuvant treatment of breast cancer. Further research is required to determine their value in specific breast cancer subtypes and to establish optimal cut-off values, before their adoption in clinical practice.

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

BACKGROUND

Tertiary lymphoid structures (TLSs) are potential prognostic indicators. Radiomics may help reduce unnecessary invasive operations.

PURPOSE

To 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 TYPE

Retrospective.

POPULATION

Two 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/SEQUENCE

3.0T; 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).

ASSESSMENT

Three 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 TESTS

LASSO 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.

RESULTS

The 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 CONCLUSION

The 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 LEVEL

2 TECHNICAL EFFICACY: Stage 2.

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

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.

Validation of Inflammatory Prognostic Biomarkers in Pleural Mesothelioma

Evoked from asbestos-induced inflammation, pleural mesothelioma represents a fatal diagnosis. Therapy ranges from nihilism to aggressive multimodality regimens. However, it is still unclear who ultimately benefits from which treatment. We aimed to re-challenge inflammatory-related biomarkers' prognostic value in times of modern immune-oncology and lung-sparing surgery. The biomarkers (leukocytes, hemoglobin, platelets, neutrophils, lymphocytes, monocytes, neutrophil-lymphocyte ratio (NLR), lymphocyte-monocyte ratio (LMR), platelet-lymphocyte ratio (PLR), C-reactive protein (CRP)) and clinical characteristics (age, sex, histology, therapy) of 98 PM patients were correlated to overall survival (OS). The median OS was 19.4 months. Significant OS advantages (Log-Rank) were observed in multimodal treatment vs. others (26.1 vs. 7.2 months, p < 0.001), surgery (pleurectomy/decortication) vs. no surgery (25.5 vs. 3.8 months, p < 0.001), a high hemoglobin level (cut-off 12 g/dL, 15 vs. 24.2 months, p = 0.021), a low platelet count (cut-off 280 G/L, 26.1 vs. 11.7 months, p < 0.001), and a low PLR (cut-off 194.5, 25.5 vs. 12.3 months, p = 0.023). Histology (epithelioid vs. non-epithelioid, p = 0.002), surgery (p = 0.004), CRP (cut-off 1 mg/dL, p = 0.039), and platelets (p = 0.025) were identified as independent prognostic variables for this cohort in multivariate analysis (Cox regression, covariates: age, sex, histology, stage, CRP, platelets). Our data verified the previously shown prognostic role of systemic inflammatory parameters in patients treated with lung-sparing surgery within multimodality therapy.

Tumor educated platelet: the novel BioSource for cancer detection

Platelets, involved in the whole process of tumorigenesis and development, constantly absorb and enrich tumor-specific substances in the circulation during their life span, thus called "Tumor Educated Platelets" (TEPs). The alterations of platelet mRNA profiles have been identified as tumor markers due to the regulatory mechanism of post-transcriptional splicing. Small nuclear RNAs (SnRNAs), the important spliceosome components in platelets, dominate platelet RNA splicing and regulate the splicing intensity of pre-mRNA. Endogenous variation at the snRNA levels leads to widespread differences in alternative splicing, thereby driving the development and progression of neoplastic diseases. This review systematically expounds the bidirectional tumor-platelets interactions, especially the tumor induced alternative splicing in TEP, and further explores whether molecules related to alternative splicing such as snRNAs can serve as novel biomarkers for cancer diagnostics.

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

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.