Prognostic role of C-reactive protein to albumin ratio in cancer patients treated with immune checkpoint inhibitors: a meta-analysis

Combining dynamics of serum inflammatory and nutritional indicators as novel biomarkers in immune checkpoint inhibitor treatment of non-small-cell lung cancer with bone metastases

OBJECTIVES

We aimed to investigate the association of the dynamics of serum inflammatory and nutritional indicators with immune checkpoint inhibitor (ICI) response in non-small-cell lung cancer (NSCLC) with bone metastases, and to develop a novel predictive scoring system based on these indicators.

METHODS

Patients with NSCLC having bone metastases treated with ICIs were categorized as: the development cohort (January 2016 to March 2021, n = 60) and the validation cohort (April 2021 to June 2023, n = 40). Serum indicators of inflammation and nutrition such as C-reactive protein (CRP), neutrophil-to-lymphocyte ratio (NLR), albumin, prognostic nutritional index (PNI) were investigated before and six weeks after ICI initiation. The correlations of these dynamics with bone metastasis response rate (BoMRR) and overall survival (OS) were analyzed. A scoring system consisting of independent predictors was developed (IMMUNO-SCORE) and correlations with clinical outcomes were validated using the validation cohort.

RESULTS

In the development cohort, multivariable analysis showed that NLR and PNI dynamics and CRP, NLR, and PNI dynamics were independent predictors of BoMRR and OS, respectively. The IMMUNO-SCORE consisting of NLR and PNI dynamics, which were the common predictors of the clinical outcomes, was significantly correlated with BoMRR (p < 0.01) and OS (p < 0.001) in cross-validation. The area under the curve of the score (0.786) was higher than individual NLR and PNI dynamics (0.72 and 0.684).

CONCLUSION

Dynamics in NLR and PNI were demonstrated as biomarkers of treatment response and prognosis in ICI treatment of NSCLC with bone metastases, and the score combining these biomarkers was significantly correlated with clinical outcomes.

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.

Clinical role of pretreatment albumin-to-alkaline phosphatase ratio in lung cancer: a meta-analysis

The association between pretreatment albumin-to-alkaline phosphatase ratio (AAPR) and clinicopathological parameters and prognosis in lung cancer is unclear. The study aimed to identify the clinical role of pretreatment AAPR among lung cancer patients. Several databases were searched for relevant studies. The primary outcome and secondary outcome were long-term survival including the overall survival (OS) and progression-free survival (PFS) and clinicopathological characteristics, respectively. The hazard ratios (HRs) and relative risks (RRs) with 95% confidence intervals (CIs) were combined. A total of 11 publications involving 10,589 participants were included in this meta-analysis. The pooled results manifested that a lower pretreatment AAPR predicted poorer OS (HR = 0.65, 95% CI 0.59-0.71, P < 0.001) and PFS (HR = 0.68, 95% CI 0.59-0.78, P < 0.001). Furthermore, subgroup analysis for the OS and PFS based on the pathological type and treatment showed similar results and pretreatment AAPR was significantly associated with worse prognosis. Besides, pretreatment AAPR was significantly associated with male (RR = 1.08, 95% CI 1.03-1.13, P < 0.001), poor differentiation (RR = 1.33, 95% CI 1.03-1.73, P = 0.029), advanced T stage (RR = 1.25, 95% CI 1.03-1.52, P = 0.026), N stage (RR = 1.34, 95% CI 1.15-1.55, P < 0.001) and TNM stage (RR = 1.14, 95% CI 1.06-1.223, P < 0.001). Therefore, pretreatment AAPR is significantly related to prognosis and tumor stage in lung cancer and patients with a lower pretreatment AAPR are more likely to experience poor survival and advanced tumor stage.