Baseline neutrophil-lymphocyte ratio and platelet-lymphocyte ratio appear predictive of immune treatment related toxicity in hepatocellular carcinoma

BACKGROUND A well-recognized class effect of immune checkpoint inhibitors(ICI)is immune-related adverse events(IrAEs)ranging from low grade toxicities to life-threatening end organ damage requiring permanent discontinuation of ICI.Deaths are reported in<5%of patients treated with ICI.There are,however,no reliable markers to predict the onset and severity of IrAEs.We tested the association between neutrophil-lymphocyte ratio(NLR)and platelet-lymphocyte ratio(PLR)at baseline with development of clinically significant IrAEs(grade≥2)in hepatocellular carcinoma(HCC)patients treated with ICI.AIM To test the association between NLR and PLR at baseline with development of clinically significant IrAEs(grade≥2)in HCC patients treated with ICI.METHODS Data was extracted from an international database from a consortium of 11 tertiary-care referral centers.NLR=absolute neutrophil count/absolute lymphocyte count(ALC)and PLR=platelet count/ALC.Cutoff of 5 was used for NLR and 300 for PLR based on literature.We also tested the association between RESULTS Data was collected from 361 patients treated between 2016-2020 across the United States(67%),Asia(14%)and Europe(19%).Most patients received Nivolumab(n=255,71%).One hundred sixty-seven(46%)patients developed at least one IrAE,highest grade 1 in 80(48%),grade≥2 in 87(52%)patients.In a univariable regression model PLR>300 was significantly associated with a lower incidence of grade≥2 IrAEs(OR=0.40;P=0.044).Similarly,a trend was observed between NLR>5 and lower incidence of grade≥2 IrAEs(OR=0.58;P=0.097).Multivariate analyses confirmed PLR>300 as an independent predictive marker of grade≥2 IrAEs(OR=0.26;P=0.011),in addition to treatment with programmed cell death ligand 1(PD-1)/cytotoxic T lymphocyte-associated protein-4(OR=2.57;P=0.037)and PD-1/tyrosine kinase inhibitor(OR=3.39;P=0.01)combinations.Antibiotic use was not associated with IrAE incidence(OR=1.02;P=0.954).Patients treated with steroids had a>2-fold higher incidence of grade≥2 IrAEs(OR=2.74;P<0.001),although 74%were prescribed steroids for the treatment of IrAEs.CONCLUSION Given that high baseline NLR and PLR are associated with a decreased incidence of IrAEs,lower baseline NLR and PLR may be predictive biomarkers for the appearance of IrAEs in HCC treated with ICI.This finding is in keeping with several studies in solid tumors that have shown that baseline NLR and PLR appear predictive of IrAEs.

Differentially private data publication with multi‐level data utility

Conventional private data publication mechanisms aim to retain as much data utility as possible while ensuring sufficient privacy protection on sensitive data.Such data publication schemes implicitly assume that all data analysts and users have the same data access privilege levels.However,it is not applicable for the scenario that data users often have different levels of access to the same data,or different requirements of data utility.The multi-level privacy requirements for different authorization levels pose new challenges for private data publication.Traditional PPDP mechanisms only publish one perturbed and private data copy satisfying some privacy guarantee to provide relatively accurate analysis results.To find a good tradeoffbetween privacy preservation level and data utility itself is a hard problem,let alone achieving multi-level data utility on this basis.In this paper,we address this challenge in proposing a novel framework of data publication with compressive sensing supporting multi-level utility-privacy tradeoffs,which provides differential privacy.Specifically,we resort to compressive sensing(CS)method to project a n-dimensional vector representation of users’data to a lower m-dimensional space,and then add deliberately designed noise to satisfy differential privacy.Then,we selectively obfuscate the measurement vector under compressive sensing by adding linearly encoded noise,and provide different data reconstruction algorithms for users with different authorization levels.Extensive experimental results demonstrate that ML-DPCS yields multi-level of data utility for specific users at different authorization levels.