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BackgroundChronic lymphocytic leukemia (CLL) is a group of highly heterogeneous mature B cell malignancy with various disease courses and diagnoses. Super-enhancer(SE) is a novel concept drew in recent years which is a cluster of enhancers involved in cell differentiation and tumorigenesis ,and is one of the promising therapeutic targets for cancer therapy. Although there is a multitude of prognostic markers in CLL, insights into the role of super-enhancer(SE)-related risk indicators are still lacking.MethodsThe CLL-related super-enhancers in training database were processed by Lasso penalized Cox regression analysis to screen a nine-gene prognostic model. And the associations between all of the individual markers and OS of CLL were assessed by Cox regression analysis. Besides, in order to understand the connection between individual genes and selected disease characteristics, like IGHV mutation status, FISH abnormality, and ZAP70 expression level, we performed correlation analysis.ResultsA nine-gene prognostic model was screened, including TCF7, VEGFA, MNT, GMIP, SLAMF1, TNFRSF25, GRWD1, SLC6AC, and LAG3. A SE-related risk score was further constructed and the robust predictive performance with 5-year survival and time-to-treatment (TTT) area under the curve(AUC): 0.997 and 1.000 in the training database and 0.628 and 0.673 in the testing database, respectively. Besides, a high correlation was found between the risk score and known prognostic markers of CLL, including the mutational status of immunoglobulin variable region loci (IGHV), chromosomal abnormalities, and ZAP70 expression. Meantime, we noticed that the expression of TCF7, GMIP, SLAMF1, TNFRSF25, and LAG3 in CLL were different from healthy donors(PConclusionTherefore, the SE-associated nine-gene prognostic model developed here may be used to predict the prognosis and assist in the risk stratification of CLL patients in the future.

Background: It is not clear whether there is value inflammatory markers for prognosis judgment in the intensive care unit (ICU). We therefore conducted a multicenter, prospective, observational study to evaluate the prognostic role of inflammatory markers.Methods: The clinical and laboratory data of patients at admission, including C-reactive protein (CRP), were collected in four general ICUs from September 1, 2018, to August 1, 2019. Multivariate logistic regression was used to identify factors independently associated with nonsurvival. The area under the receiver operating characteristic curve (AUC-ROC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI) were used to evaluate the effect size of different factors in predicting mortality during ICU stay. 3 knots was used to assess whether alternative cut points for these biomarkers were more appropriate. Results: A total of 813 patients were recruited, among whom 121 patients (14.88%) died during the ICU stay. The AUC-ROC values of PCT and CRP for discriminating ICU mortality were 0.696 (95% confidence interval [CI], 0.650-0.743) and 0.684 (95% CI, 0.633-0.735), respectively. In the multivariable analysis, only APACHE II score (odds ratio, 1.166; 95% CI, 1.129-1.203; P=0.000) and CRP concentration > 62.8 mg/L (odds ratio, 2.145; 95% CI, 1.343-3.427; P=0.001), were significantly associated with an increased risk of ICU mortality. Moreover, the combination of APACHE II score and CRP > 62.8 mg/L significantly improved risk reclassification over the APACHE II score alone, with NRI (0.556) and IDI (0.013). Restricted cubic spline analysis confirmed that CRP concentration >62.8 mg/L was the optimal cut-off value for differentiating between surviving and nonsurviving patients.Conclusion: CRP markedly improved risk reclassification for prognosis prediction.

Background: Hemophagocytic lymphohistiocytosis (HLH) a hyperinflammation disease and have high early mortality. The neutrophil-lymphocyte ratio (NLR) plays a prognostic role in various inflammation conditions. However, the role of NLR in HLH remains unknown.Results: 92 patients were collected from Sep 2014 to Dec 2019, the median age was 50 years (16-88) and 54 patients (58.6%) were male. 39 patients (42.3%) died during a 30-day follow-up. In addition, NLR was higher in nonsurvivor than survivor (P=0.005), higher NLR was correlated with older age (P=0.020), worse survival status (P=0.006), lower HB level (P=0.008), longer PT level (P=0.010), higher creatinine level (0.027) and higher IL-6 level (P=0.008)and in multivariate analysis, NLR (HR=2.508, 95%CI: 1.275-4.934), was indicated as an independent prognostic factor for early death. Conclusions: NLR was correlated with early death in HLH, suggest NLR could be used as a reference indicator for the monitoring and management of HLH.

Background: Despite the essential functions of the intestinal microbiota in human physiology, little research has been reported on the gut microbiota alteration in intensive care patients. This investigation aimed to explore the dysbacteriosis of intestinal flora in critically ill patients, and evaluate the prognostic performance of this dysbiosis to predict in-hospital mortality. Methods: A prospective cohort of patients were consecutively recruited at Intensive Care Units (ICUs) in Guangdong Provincial People's Hospital from March 2017 through October 2017. Acute Physiology and Chronic Health Evaluation (APACHE) II score and Sequential Organ Failure Assessment (SOFA) score were assessed, and fecal samples were taken for examination within 24 hours of ICU admission. The taxonomic composition of intestinal microbiome was determined using 16S rDNA gene sequencing. Patients were divided into survival and death group based on the outcomes in hospital. The two groups were statistically compared using the independent samples t test and Metastats analysis. Genera of bacteria showing significantly different abundance between groups were assessed for predictors of in-hospital death. The prognostic value of bacterial abundance alone and in combination with APACHE II or SOFA score were evaluated using the area under the receiver operating characteristic curve (AUROC). Results: Among the 61 patients that were examined, a total of 12 patients (19.7%) died during hospital stay. Bifidobacterium differed significantly in abundance between survival and death group ( P =0.031). The AUROC of Bifidobacterium abundance identifying in-hospital death at a cut-off probability of 0.0041 was 0.718 (95% confidence interval [CI], 0.588-0.826). The panel of Bifidobacterium abundance plus SOFA (AUROC, 0.882; 95% CI, 0.774-0.950) outperformed SOFA (AUROC, 0.649; 95% CI, 0.516-0.767; P =0.012) and Bifidobacterium abundance alone ( P =0.007). The panel of Bifidobacterium abundance plus APACHE II (AUROC, 0.876; 95% CI, 0.766-0.946) outperformed APACHE II (AUROC, 0.724; 95% CI, 0.595-0.831; P =0.035) and Bifidobacterium abundance alone ( P =0.012). Conclusions: Dysbiosis of intestinal microbiota with variable degree of reduction in Bifidobacterium abundance exhibits promising performance in predicting in-hospital mortality, and provides incremental prognostic value to existing scoring systems in the adult intensive care unit (ICU) setting.

BackgroundElevated red blood cell distribution width (RDW) and decreased platelet count (PLT) can be clinically relevant to the prognosis in cancer patients. However, their prognostic values in patients with diffuse large B-cell lymphoma (DLBCL) need to be further explored.MethodsHealthy donors (n = 130) and patients with DLBCL (n = 349) were included and evaluated retrospectively in this study. The prognostic influence of clinical and pathological factors including RDW and PLT on overall survival (OS) and progression-free survival (PFS) were studied by Kaplan-Meier curves. To evaluate the independent prognostic relevance of RDW and PLT, univariate and multivariate Cox proportional hazards regression models were applied. The adjusted IPI model was established based on the results of multivariate analysis, and verified by Harrell’s C statistical analysis.ResultsKaplan-Meier curves indicated that an elevated RDW value and thrombocytopenia are poor factors for OS (P P = 0.006) and PFS (P = 0.003,P P = 0.003) and decreased PLT count (HR =1.749, 95%CI = 1.010–3.028,P = 0.046) were both independent prognostic factors. The c-index of IPI and NCCN-IPI were increased when RDW level and PLT were supplemented in our cohort.ConclusionsOur study shows that elevated RDW level and decreased PLT are independent poor prognostic factors in newly diagnosed DLBCL patients. Adding RDW and PLT to the IPI score may improve its predictive ability, and the adjusted IPI may be more powerful in predicting the survival of DLBCL patients in the rituximab era.