Prognostic Value of Systemic Inflammatory Biomarkers in Patients with Metastatic Renal Cell Carcinoma

The use of platelets as a clinical tool in oncology: opportunities and challenges

Platelets are small circulating anucleated cells mainly involved in thrombosis and hemostasis processes. Moreover, platelets play an active role in tumorigenesis and cancer progression, stimulating angiogenesis and vascular remodelling, and protecting circulating cancer cells from shear forces and immune surveillance. Several reports indicate that platelet number in the blood circulation of cancer patients is associated with prognosis and response to treatment. However, the mechanisms of platelets "education" by cancer cells and the crosstalk between platelets and tumor are still unclear, and the role of "tumor educated platelets" (TEPs) is achieving growing interest in cancer research. TEPs are a biological source of cancer-derived biomarkers, especially RNAs that are protected by platelets membrane from circulating RNases, and could serve as a non-invasive tool for tumor detection, molecular profiling and evolution during therapy in clinical practice. Moreover, short platelet lifespan offers the possibility to get a snapshot assessment of cancer molecular profile, providing a real-time tool. We review and discuss the potential and the clinical utility, in terms of cancer diagnosis and monitoring, of platelet count together with other morphological parameters and of the more recent and innovative TEP profiling.

The potential of high-order features of routine blood test in predicting the prognosis of non-small cell lung cancer

BACKGROUND

Numerous studies have demonstrated that the high-order features (HOFs) of blood test data can be used to predict the prognosis of patients with different types of cancer. Although the majority of blood HOFs can be divided into inflammatory or nutritional markers, there are still numerous that have not been classified correctly, with the same feature being named differently. It is an urgent need to reclassify the blood HOFs and comprehensively assess their potential for cancer prognosis.

METHODS

Initially, a review of existing literature was conducted to identify the high-order features (HOFs) and classify them based on their calculation method. Subsequently, a cohort of patients diagnosed with non-small cell lung cancer (NSCLC) was established, and their clinical information prior to treatment was collected, including low-order features (LOFs) obtained from routine blood tests. The HOFs were then computed and their associations with clinical features were examined. Using the LOF and HOF data sets, a deep learning algorithm called DeepSurv was utilized to predict the prognostic risk values. The effectiveness of each data set's prediction was evaluated using the decision curve analysis (DCA). Finally, a prognostic model in the form of a nomogram was developed, and its accuracy was assessed using the calibration curve.

RESULTS

From 1210 documents, over 160 blood HOFs were obtained, arranged into 110, and divided into three distinct categories: 76 proportional features, 6 composition features, and 28 scoring features. Correlation analysis did not reveal a strong association between blood features and clinical features; however, the risk value predicted by the DeepSurv LOF- and HOF-models is significantly linked to the stage. Results from DCA showed that the HOF model was superior to the LOF model in terms of prediction, and that the risk value predicted by the blood data model could be employed as a complementary factor to enhance the prognosis of patients. A nomograph was created with a C-index value of 0.74, which is capable of providing a reasonably accurate prediction of 1-year and 3-year overall survival for patients.

CONCLUSIONS

This research initially explored the categorization and nomenclature of blood HOF, and proved its potential in lung cancer prognosis.

Prognostic model for overall survival that includes the combination of platelet count and neutrophil-lymphocyte ratio within the first six weeks of sunitinib treatment for metastatic renal cell carcinoma

BACKGROUND

The association between the combination of platelet count and neutrophil-lymphocyte ratio (COP-NLR) at the time of adverse events during sunitinib treatment and prognosis is unclear, and prognostic models combining the prognostic factors of sunitinib have not been well studied. Thus, we developed a prognostic model that includes the COP-NLR to predict the prognosis of patients with metastatic renal cell carcinoma (mRCC) treated with sunitinib.

METHODS

We performed a retrospective cohort study of 102 patients treated with sunitinib for mRCC between 2008 and 2020 in three hospitals associated with Showa University, Japan. The primary outcome was overall survival (OS). The collected data included baseline patient characteristics, adverse events, laboratory values, and COP-NLR scores within the first 6 weeks of sunitinib treatment. Prognostic factors of OS were analyzed using the Cox proportional hazards model. The integer score was derived from the beta-coefficient (β) of these factors and was divided into three groups. The survival curves were visualized using the Kaplan-Meier method and estimated using a log-rank test.

RESULTS

The median OS was 32.3 months. Multivariable analysis showed that the number of metastatic sites, Memorial Sloan Kettering Cancer Center risk group, number of metastases, non-hypertension, modified Glasgow Prognostic Score, and 6-week COP-NLR were significantly associated with OS. A higher 6-week COP-NLR was significantly associated with a shorter OS (p < 0.001). The β values of the five factors for OS were scored (non-hypertension, mGPS, and 6-week COP-NLR = 1 point; number of metastatic sites = 2 points; MSKCC risk group = 3 points) and patients divided into three groups (≤ 1, 2-3, and ≥ 4). The low-risk (≤ 1) group had significantly longer OS than the high-risk (≥ 4) group (median OS: 99.0 vs. 6.2 months, p < 0.001).

CONCLUSIONS

This study showed that the COP-NLR within the first 6 weeks of sunitinib treatment had a greater impact on OS than the COP-NLR at the start of sunitinib treatment. The developed prognostic model for OS, including the 6-week COP-NLR, will be useful in decision-making to continue sunitinib in the early treatment stage of patients with mRCC.

Preoperative red blood cell distribution width as an independent prognostic factor in metastatic renal cell carcinoma

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Patients with higher red blood cell distribution width (RDW) levels had worse OS and PFS.

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Preoperative RDW was independently associated with PFS and OS in patients with metastatic renal cell carcinoma (mRCC).

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Preoperative RDW can be utilized as a novel prognostic biomarker for patients with mRCC.

Objective

This study aimed to explore the prognostic value of preoperative red blood cell distribution width (RDW) in patients with metastatic renal cell carcinoma (mRCC).

Methods

Clinicopathological data of 230 patients with mRCC treated at the First Affiliated Hospital of Chongqing Medical University and the Chinese PLA General Hospital from January 2008 to December 2018 were retrospectively analyzed. Patients were stratified according to the optimal cut-off value of RDW calculated using X-tile software. The prognostic value of RDW was analyzed using the Kaplan-Meier curve with log-rank test and univariate and multivariate Cox proportional hazards models.

Results

A total of 230 patients were included. The optimal cut-off value of RDW obtained using X-tile software was 13.1%. The median Progression-free survival (PFS) and Overall survival (OS) of all populations were 12.06 months (IQR: 4.73–36.9) and 32.20 months (IQR: 13.73–69.46), respectively. Kaplan–Meier curves showed that patients with high RDW had worse PFS and OS than those with low RDW (median PFS of 9.7 months vs. 17.9 months, P = 0.002, and median OS of 27.8 months vs. 45.1 months, P = 0.012, respectively). Multivariate analysis showed that RDW was an independent risk factor for PFS (HR: 1.505; 95% CI: 1.111–2.037; P = 0.008) and OS (HR: 1.626; 95% CI: 1.164–2.272; P = 0.004) in mRCC after cytoreductive nephrectomy.

Conclusion

Preoperative RDW was independently associated with PFS and OS in patients with mRCC and may be a potential predictor of survival outcomes in mRCC.

A meta-analysis of the platelet-lymphocyte ratio: A notable prognostic factor in renal cell carcinoma

BACKGROUND

The platelet-lymphocyte ratio (PLR) has been assessed in some studies on renal cell carcinoma (RCC), but the results have been inconsistent. This meta-analysis aims to review and report the latest data regarding the prognostic role of the PLR in RCC patients.

METHOD

Articles were searched in the PubMed, EMBASE, and Cochrane Library electronic databases. Studies were filtered according to a selection strategy, and data corresponding to the index of interest were extracted. A fixed-effects model or random-effects model was selected based on heterogeneity. The sensitivity analysis was carried out by eliminating the studies one by one. Finally, funnel plots and Egger's test were used to assess publication bias, and the trim and fill method was used to assess the impact of bias on the results.

RESULTS

In total, 15,193 patients with RCC from 44 studies were included in this meta-analysis. The pooled analysis indicated that the higher the PLR was, the poorer the prognosis for RCC patients in terms of overall survival (hazard ratio (HR) = 1.01 (95% confidence interval (CI) 1.00, 1.02), P = 0.010), cancer-special survival (CSS) (HR = 1.21 (95% CI 1.00, 1.46), P = 0.05), progression-free survival (HR = 1.44 (95% CI 1.28, 1.62), P < 0.00001), recurrence-free survival (HR = 1.73 (95% CI 1.11, 2.71), P = 0.02), disease-free survival (HR = 1.63 (95% CI 0.91, 2.94), P = 0.01) and metastasis-free survival (HR = 1.223 (95% CI 0.712, 2.099), P = 0.466). In the subgroup analysis of high PLR, targeted treatment, TKI use, nivolumab use, surgical treatment, clear cell RCC, metastasis, Asian race, and high PLR were related to poor prognosis.

CONCLUSION

This study showed that a high PLR was associated with the poor prognosis of RCC patients, but more studies are needed to confirm the value of the PLR.

Association of Neutrophil-to-Lymphocyte Ratio with Efficacy of First-Line Avelumab plus Axitinib vs. Sunitinib in Patients with Advanced Renal Cell Carcinoma Enrolled in the Phase 3 JAVELIN Renal 101 Trial

PURPOSE

To evaluate the association between neutrophil-to-lymphocyte ratio (NLR) and efficacy of avelumab plus axitinib or sunitinib.

EXPERIMENTAL DESIGN

Adult patients with untreated advanced renal cell carcinoma (RCC) with a clear-cell component, ≥1 measurable lesions, Eastern Cooperative Oncology Group performance status of 0 or 1, fresh or archival tumor specimen, and adequate renal, cardiac, and hepatic function were included. Retrospective analyses of the association between baseline NLR and progression-free survival (PFS) and overall survival (OS) in the avelumab plus axitinib or sunitinib arms were performed using the first interim analysis of the phase 3 JAVELIN Renal 101 trial (NCT02684006). Multivariate Cox regression analyses of PFS and OS were conducted. Translational data were assessed to elucidate the underlying biology associated with differences in NLR.

RESULTS

Patients with below-median NLR had longer observed PFS with avelumab plus axitinib [stratified HR, 0.85; 95% confidence interval (CI), 0.634-1.153] or sunitinib (HR, 0.56; 95% CI, 0.415-0.745). In the avelumab plus axitinib or sunitinib arms, respectively, median PFS was 13.8 and 11.2 months in patients with below-median NLR, and 13.3 and 5.6 months in patients with median-or-higher NLR. Below-median NLR was also associated with longer observed OS in the avelumab plus axitinib (HR, 0.51; 95% CI, 0.300-0.871) and sunitinib arms (HR, 0.30; 95% CI, 0.174-0.511). Tumor analyses showed an association between NLR and key biological characteristics, suggesting a role of NLR in underlying mechanisms influencing clinical outcome.

CONCLUSIONS

Current data support NLR as a prognostic biomarker in patients with advanced RCC receiving avelumab plus axitinib or sunitinib.

C-reactive protein and neutrophil-lymphocyte ratio are prognostic in metastatic clear-cell renal cell carcinoma patients treated with nivolumab

OBJECTIVE

To evaluate the impact of markers of systemic inflammation such as C-reactive protein (CRP) and neutrophil-lymphocyte ratio (NLR) on outcomes of metastatic clear-cell renal cell carcinoma (m-ccRCC) patients treated with nivolumab.

PATIENTS AND METHODS

We retrospectively evaluated m-ccRCC patients treated with nivolumab and collected known prognostic factors and survival data. We used Kaplan-Meier survival analysis and cox proportional hazards regression analysis to study prognostic factors for overall survival (OS) and progression-free survival (PFS) since start of nivolumab. Harrell's C-index was used to evaluate the models.

RESULTS

We included 113 patients. Median OS and PFS after initiation of nivolumab was 15 (interquartile range 7-28) and 4 months (interquartile range 3-11), respectively. Elevated baseline CRP was associated with worse OS (HR per 25 mg/l 1.35, 95% CI 1.16-1.52, P < 0.001) and PFS (HR per 25 mg/l 1.19, 95% CI 1.08-1.35, P = 0.001), independent from the international metastatic renal cell carcinoma database consortium (IMDC) prognostic criteria, increasing the model's C-index from 0.72 to 0.77 for OS and 0.59 to 0.62 for PFS. Elevated NLR was associated with worse OS (HR 1.10, 95% CI 1.04-1.17, P = 0.002) and PFS (HR 1.06, 95% CI 1.01-1.11, P = 0.03) independent from the other IMDC prognostic criteria. The model's C-index decreased from 0.72 to 0.70 for OS and increased from 0.59 to 0.60 for PFS.

CONCLUSIONS

Elevated baseline CRP and NLR predict worse OS and PFS on nivolumab in m-ccRCC patients. Including baseline CRP in the IMDC prognostic model improves its discriminatory power to predict OS and PFS since start of nivolumab.