Prognostic Utility of Systemic Immune-Inflammation Index After Resection of Extrahepatic Cholangiocarcinoma: Results from the U.S. Extrahepatic Biliary Malignancy Consortium

Association of inflammatory markers based on routine blood with prognosis in patients underwent percutaneous coronary intervention

Inflammation contributes to the pathophysiological processes of coronary artery disease. We evaluated the association between inflammatory biomarkers, neutrophil-to-lymphocyte ratio (NLR), red cell distribution width (RDW), systemic inflammatory index, platelet-lymphocyte ratio, and 1-year all-cause mortality in patients underwent percutaneous coronary intervention (PCI). In this retrospective cohort, we consecutively enrolled 4651 patients who underwent PCI. Baseline demographic details, clinical data, and laboratory parameters on admission were analyzed. The primary outcome was 1-year all-cause mortality after PCI. We performed Cox regression and restricted cubic spline analysis to assessed the association between the inflammatory biomarkers and the clinical outcome. The area under the curve from receiver operating characteristic analysis was determined for the ability to classify mortality outcomes. A total of 4651 patients were included. Of these, 198 (4.26%) died on follow-up. Univariate Cox regression showed that NLR (heart rate [HR]: 1.070, 95% confidence interval [CI]: 1.060-1.082, P < .001), RDW (HR: 1.441, 95% CI 1.368-1.518, P < .001), systemic inflammatory index (HR: 1.000, 95% CI 1.000-3.180, P < .001), platelet-lymphocyte ratio (HR: 3.812, 95% CI 1.901-3.364, P < .001) were significant predictors of 1-year all-cause mortality. After adjusting for other confounders in multivariate analysis, NLR (HR: 01.038, 95% CI 1.022-1.054, P < .001) and RDW (HR: 1.437, 95% CI 1.346-1.535, P < .001) remained significant predictors. Restricted cubic spline analysis showed the relationship between RDW, NLR, and 1-year all-cause mortality was linear after adjusting for the covariables (P for non-linearity < 0.001). The multivariable adjusted model led to improvement in the area under the curve to 0.83 (P < .05). Nomogram was created to predict the probability of 1 year mortality. Among the laboratory indices, RDW and NLR showed the best performance for mortality risk prediction. Multivariate predictive models significantly improved risk stratification.

Predicting risk of recurrence after resection of stage I intrahepatic cholangiocarcinoma

BACKGROUND

Early-stage intrahepatic cholangiocarcinoma (ICC) is often an indication of curative-intent resection. Although patients with early-stage ICC generally have a better prognosis than individuals with advanced ICC, the incidence and risk factors of recurrence after early-stage ICC remain unclear.

METHODS

A multi-institutional database was used to identify patients who underwent surgery between 2000 and 2018 for ICC with pathologically confirmed stage I disease. Cox regression analysis was used to identify clinicopathological factors associated with recurrence, and an online prediction model was developed and validated.

RESULTS

Of 430 patients diagnosed with stage I ICC, approximately one-half of patients (n = 221, 51.4%) experienced recurrence after curative-intent resection. Among patients with a recurrence, most (n = 188, 85.1%) experienced it within 12 months. On multivariable analysis, carcinoembryonic antigen (hazard ratio [HR], 1.011; 95% CI, 1.004-1.018), systemic immune-inflammation index (HR, 1.036; 95% CI, 1.019-1.056), no lymph nodes evaluated (HR, 1.851; 95% CI, 1.276-2.683), and tumor size (HR, 1.101; 95% CI, 1.053-1.151) were associated with greater hazards of recurrence. A predictive model that included these weighted risk factors demonstrated excellent prognostic discrimination in the test (12-month recurrence-free survival [RFS]: low risk, 80.1%; intermediate risk, 60.3%; high risk, 37.7%; P = .001) and validation (12-month RFS: low risk, 84.5%; intermediate risk, 63.5%; high risk, 47.1%; P = .036) datasets. The online predictive model was made available at https://ktsahara.shinyapps.io/stageI_icc/.

CONCLUSIONS

Patients with stage I ICC without vascular invasion or lymph node metastasis had a relatively high incidence of recurrence. An online tool can risk stratify patients relative to recurrence risk to identify individuals best suited for alternative treatment approaches.

Development and validation of a gene expression-based nomogram to predict the prognosis of patients with cholangiocarcinoma

AIM

To establish and validate a prognostic nomogram of cholangiocarcinoma (CCA) using independent clinicopathological and genetic mutation factors.

METHODS

213 patients with CCA (training cohort n = 151, validation cohort n = 62) diagnosed from 2012 to 2018 were included from multi-centers. Deep sequencing targeting 450 cancer genes was performed. Independent prognostic factors were selected by univariate and multivariate Cox analyses. The clinicopathological factors combined with (A)/without (B) the gene risk were used to establish nomograms for predicting overall survival (OS). The discriminative ability and calibration of the nomograms were assessed using C-index values, integrated discrimination improvement (IDI), decision curve analysis (DCA), and calibration plots.

RESULTS

The clinical baseline information and gene mutations in the training and validation cohorts were similar. SMAD4, BRCA2, KRAS, NF1, and TERT were found to be related with CCA prognosis. Patients were divided into low-, median-, and high-risk groups according to the gene mutation, the OS of which was 42.7 ± 2.7 ms (95% CI 37.5-48.0), 27.5 ± 2.1 ms (95% CI 23.3-31.7), and 19.8 ± 4.0 ms (95% CI 11.8-27.8) (p < 0.001), respectively. The systemic chemotherapy improved the OS in high and median risk groups, but not in the low-risk group. The C-indexes of the nomogram A and B were 0.779 (95% CI 0.693-0.865) and 0.725 (95% CI 0.619-0.831), p < 0.01, respectively. The IDI was 0.079. The DCA showed a good performance and the prognostic accuracy was validated in the external cohort.

CONCLUSION

Gene risk has the potential to guide treatment decision for patients at different risks. The nomogram combined with gene risk showed a better accuracy in predicting OS of CCA than not.

Application of systemic inflammation indices and lipid metabolism-related factors in coronary artery disease

OBJECTIVE

We aimed to investigate the relationship between coronary artery disease (CAD) and systemic inflammation indices and lipid metabolism-related factors and subsequently, discuss the clinical application of these factors in CAD.

METHODS

We enrolled 284 consecutive inpatients with suspected CAD and divided them into a CAD group and a non-CAD group according to coronary angiography results. Serum levels of angiopoietin-like protein 3 (ANGPTL3), angiopoietin-like protein 4 (ANGPTL4), fatty acid-binding protein 4 (FABP4), and tumor necrosis factor-α (TNF-α) levels were assessed using the ELISA and the systemic inflammation indices were calculated. Multivariate logistic regression was used to assess the risk factors of CAD. The receiver operating characteristic curve was used to determine the cutoff and diagnostic values.

RESULTS

The neutrophil-to-high density lipoprotein cholesterol ratio (5.04 vs. 3.47), neutrophil-to-lymphocyte ratio (3.25 vs. 2.45), monocyte-to-high density lipoprotein cholesterol ratio (MHR) (0.46 vs. 0.36), monocyte-to-lymphocyte ratio (0.31 vs. 0.26), systemic immune-inflammation index (SII) (696.00 vs. 544.82), serum TNF-α (398.15 ng/l vs. 350.65 ng/l), FABP4 (1644.00 ng/l vs. 1553.00 ng/l), ANGPTL3 (57.60 ng/ml vs. 52.85 ng/ml), and ANGPTL4 (37.35 ng/ml vs. 35.20 ng/ml) values showed a significant difference between the CAD and non-CAD groups ( P  < 0.05). After adjusting for confounding factors, the following values were obtained: ANGPTL3 > 67.53 ng/ml [odds ratio (OR) = 8.108, 95% confidence interval (CI) (1.022-65.620)]; ANGPTL4 > 29.95 ng/ml [OR = 5.599, 95% CI (1.809-17.334)]; MHR > 0.47 [OR = 4.872, 95% CI (1.715-13.835)]; SII > 589.12 [OR = 5.131, 95% CI (1.995-13.200)]. These factors were found to be independently associated with CAD ( P  < 0.05). Diabetes combined with MHR > 0.47, SII > 589.12, TNF-α >285.60 ng/l, ANGPTL3 > 67.53 ng/ml, and ANGPTL4 > 29.95 ng/l had the highest diagnostic value for CAD [area under the curve: 0.921, 95% CI, (0.881-0.960), Sensitivity: 88.9%, Specificity: 82.2%, P  < 0.001].

CONCLUSION

MHR > 0.47, SII > 589.12, TNF-α >285.60 ng/l, ANGPTL3 > 67.53 ng/ml, and ANGPTL4 > 29.95 ng/l were identified as independent CAD risk factors and have valuable clinical implications in the diagnosis and treatment of CAD.

The BIDIAP index: a clinical, analytical and ultrasonographic score for the diagnosis of acute appendicitis in children

BACKGROUND

Pediatric acute appendicitis (PAA) continues to be a diagnostic challenge today. The diagnostic performance of classical indices is only moderate, especially in pediatric population. This study aimed to define a clinical, radiological and analytical index for the diagnosis of PAA.

MATERIALS AND METHODS

This prospective study included 151 patients divided into two groups: (1) 53 patients with non-surgical abdominal pain (NSAP) and (2) 98 patients with a confirmed PAA. Sociodemographic and clinical characteristics were compared between groups using the Mann-Whitney U test and the Fisher exact test. To identify the predictors of PAA, we performed a multivariable logistic regression using a forward stepwise analysis and we assigned multiples of integer values to the selected variables. The diagnostic performance of the index was assessed by calculating the area under the receiver operating characteristic curve. Intra-cohort calibration was assessed with the Hosmer-Lemeshow test.

RESULTS

We developed the BIDIAP index (BIomarkers for the DIagnosis of Appendicitis in Pediatrics), which included three variables that independently predicted higher odds of PAA: appendiceal caliber (≥ 6.9 mm), systemic immune-inflammation index (≥ 890) and peritoneal irritation, which scored 4, 3 and 2 points, respectively. Mean (SD) score of the participants was 2.38 (2.06) in group 1 and 7.89 (1.50) in group 2. The area under the ROC was 0.97 (95% CI 0.95-0.99). The cut-off point was established at 4 points, resulting in a sensitivity of 98.98% and a specificity of 77.78%.

CONCLUSIONS

The BIDIAP index has an exceptional diagnostic performance in PAA. The importance of these results lies in its novelty and in the simplicity of the index. Although external validation will be necessary, initial results look promising.

An overview of extrahepatic cholangiocarcinoma: from here to where?

Extrahepatic cholangiocarcinoma (eCCA) contains perihilar cholangiocarcinoma and distal cholangiocarcinoma both of which can arise at any point of the biliary tree and originate from disparate anatomical sites. Generally, the incidence of eCCA is increasing globally. Though surgical resection is the principal treatment of choice for the early stages of eCCA, optimal survival remains restricted by the high risk of recurrence when most patients are present with unresectable disease or distant metastasis. Furthermore, both intra- and intertumoral heterogeneity make it laborious to determine molecularly targeted therapies. In this review, we mainly focused on current findings in the field of eCCA, mostly including epidemiology, genomic abnormalities, molecular pathogenesis, tumor microenvironment, and other details while a summary of the biological mechanisms driving eCCA may shed light on intricate tumorigenesis and feasible treatment strategies.

Systemic immune-inflammation index as a potential biomarker of cardiovascular diseases: A systematic review and meta-analysis

Background

Several studies have investigated the value of the systemic immune-inflammation index (SII) for predicting cardiovascular disease (CVD), but the results were inconsistent. Therefore, a meta-analysis and systematic review were conducted to assess the correlation between SII and risk of CVD.

Materials and methods

Two investigators systematically searched PubMed, Embase, Web of Science, Cochrane library, and CINAHL databases to identify all studies that examined the association between SII levels and CVD. The risk estimates of CVD for people with high SII compared to those with low SII levels and the weighted mean difference (WMD) between the CVD and control groups were pooled using fixed- or random-effects models based on the heterogeneity test. We used the Newcastle-Ottawa Scale to assess the risk of bias in eligible studies, and the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system was applied to rate the certainty of evidence.

Results

A total of 13 studies with 152,996 participants were included for analysis. The overall pooled results showed that higher SII was significantly associated with an increased risk of CVD (HR = 1.39, 95%CI: 1.20–1.61, P < 0.001). This increased risk could be observed in almost all CVD subtypes, including ischemic stroke (HR = 1.31, 95%CI: 1.06–1.63, P = 0.013), hemorrhagic stroke (HR = 1.22, 95%CI: 1.10–1.37, P < 0.001), myocardial infarction (HR = 1.11, 95%CI: 1.01–1.23, P = 0.027), and peripheral arterial disease (HR = 1.51, 95%CI: 1.18–1.93, P = 0.001). There were no significant but still similar trends in venous thrombosis (HR = 4.65, 95%CI: 0.66–32.71, P = 0.122), cerebral small vessel disease (HR = 1.09, 95%CI: 0.95–1.25, P = 0.233), and acute coronary syndrome (HR = 1.08, 95%CI: 0.96–1.22, P = 0.200). Furthermore, the pooled results showed that SII levels at the onset of CVD were significantly higher than that in the general population (WMD = 355.2, 95%CI: 234.8–475.6, P < 0.001), which was consistent across different CVD subtypes. The GRADE assessment suggested that the quality of current evidence from observational studies was low or very low.

Conclusion

This study indicated that SII may be a potential biomarker for CVD development and elevated SII is associated with an increased risk of CVD. However, the quality of evidence is generally low. Additional well-designed studies are necessary to determine the optimal cutoff value and to characterize the benefited population.