Nomograms confirm serum IL-6 and CRP as predictors of immune checkpoint inhibitor efficacy in unresectable hepatocellular carcinoma

BackgroundImmunotherapy based on immune checkpoint inhibitors (ICIs) has become the first-line treatment for unresectable hepatocellular carcinoma (uHCC). However, only a small portion of patients are responsive to ICIs. It is important to identify the patients who are likely to benefit from ICIs in clinical practice. We aimed to examine the significance of serum IL-6 and CRP levels in predicting the effectiveness of ICIs for uHCC.MethodsWe retrospectively recruited 222 uHCC patients who received ICIs treatment (training cohort: 124 patients, validation cohort: 98 patients). In the training cohort, patients are categorized into the response group (R) and no-response group (NR). The levels of serum IL-6 and CRP were compared between the two groups. Internal validation was performed in the validation cohort. Survival analysis was carried out using the Kaplan-Meier method and Cox proportional hazard regression model. The nomograms were developed and assessed using the consistency index (C-index) and calibration curve.ResultsSerum levels of IL-6 and CRP were significantly lower in the R group than in the NR group (9.94 vs. 36.85 pg/ml, p< 0.001; 9.90 vs. 24.50 mg/L, p< 0.001, respectively). An ROC curve was employed to identify the optimal cut-off values for IL-6 and CRP in both groups, resulting in values of 19.82 pg/ml and 15.50 mg/L, respectively. Multivariate Cox regression analysis revealed that MVI (HR 1.751, 95%CI 1.059-2.894, p=0.029; HR 1.530, 95%CI 0.955-2.451, p=0.077), elevated IL-6 (HR 1.624, 95%CI 1.016-2.596, p=0.043; HR 2.146, 95%CI 1.361-3.383, p =0.001) and high CRP (HR 1.709, 95%CI 1.041-2.807, p=0.034; HR 1.846, 95%CI 1.128-3.022, p = 0.015) were independent risk factors for PFS and OS, even after various confounders adjustments. Nomograms are well-structured and validated prognostic maps constructed from three variables, as MVI, IL6 and CRP.ConclusionLow levels of IL-6 and CRP have a positive correlation with efficacy for uHCC patients receiving ICIs

Hierarchical Resource Allocation Framework for Hyper-Dense Small Cell Networks

This paper considers joint power control and subchannel allocation for co-tier interference mitigation in extremely dense small cell networks, which is formulated as a combinatorial optimization problem. Since it is intractable to obtain the globally optimum assignment policy for existing techniques due to the huge computation and communication overheads in ultra-dense scenario, in this paper, we propose a hierarchical resource allocation framework to achieve a desirable solution. Speci cally, the solution is obtained by dividing the original optimization problem into four stages in partially distributed manner. First, we propose a divide-and-conquer strategy by invoking clustering technique to decompose the dense network into smaller disjoint clusters. Then, within each cluster, one of the small cell access points is elected as a cluster head to carry out intra-cluster subchannel allocation with a low-complexity algorithm. To tackle the issue of inter-cluster interference, we further develop a distributed learning-base coordination mechanism. Moreover, a local power adjustment scheme is also presented to improve the system performance. Numerical results verify the ef ciency of the proposed hierarchical scheme, and demonstrate that our solution outperforms the state-of-the-art methods, especially for hyper-dense networks