Purpose: Higher neutrophil-lymphocyte ratio (NLRs) indicate a pro-inflammatory state and are associated with poor survival. Conversely, higher albumin-globulin ratio (AGRs) may be associated with improved prognosis. We aimed to investigate the association between NLR and AGR and prognosis and survival in patients with breast cancer. Methods: This retrospective study included all patients with stage I–III breast cancer between 2011 and 2017 in Singapore General Hospital and National Cancer Center Singapore.Multivariate logistic regression analysis of NLR, AGR, age, stage, grade, and subtype was performed. Survival data between groups were compared using Cox regression analysis and log-rank tests. Results: A total of 1,188 patients were included, of whom 323 received neoadjuvant chemotherapy (NACT) and 865 underwent upfront surgery. In patients who underwent NACT, a higher AGR was significantly associated with a higher pCR rate (cut-off > 1.28; odds ratio [OR], 2.03; 95% confidence interval [CI], 1.13–3.74; p = 0.020), better DFS (cut off > 1.55; hazard ratio [HR], 0.37; 95% CI, 0.16–0.85; p = 0.019), and better CSS (cut off > 1.46; HR, 0.39; 95% CI, 0.17–0.92; p = 0.031). Higher NLR was significantly associated with worse DFS (cut off > 4.09; HR, 1.77; 95% CI, 1.07–2.91; p = 0.026) and worse CSS (cut off > 4.09; HR, 1.98; 95% CI, 1.11–3.53; p = 0.021). In patients who underwent upfront surgery, higher AGR correlated with significantly better OS (cut off > 1.17; HR, 0.54; 95% CI, 0.36–0.82; p = 0.004) and higher NLR correlated with worse OS (cut off > 2.38; HR, 1.63; 95% CI, 1.09–2.44; p = 0.018). Conclusion NLR and AGR are useful in predicting the response to NACT as well as prognosis of patients with breast cancer. Further studies are needed to explore their value in clinical decision making.

Background/Aims: Chronic hepatitis B (CHB) and fatty liver (FL) often co-exist, but natural history data of this dual condition (CHB-FL) are sparse. Via a systematic review, conventional meta-analysis (MA) and individual patient-level data MA (IPDMA), we compared liver-related outcomes and mortality between CHB-FL and CHB-no FL patients. Methods: We searched 4 databases from inception to December 2021 and pooled study-level estimates using a random- effects model for conventional MA. For IPDMA, we evaluated outcomes after balancing the two study groups with inverse probability treatment weighting (IPTW) on age, sex, cirrhosis, diabetes, ALT, HBeAg, HBV DNA, and antiviral treatment. Results: We screened 2,157 articles and included 19 eligible studies (17,955 patients: 11,908 CHB-no FL; 6,047 CHB-FL) in conventional MA, which found severe heterogeneity (I2=88–95%) and no significant differences in HCC, cirrhosis, mortality, or HBsAg seroclearance incidence (P=0.27–0.93). IPDMA included 13,262 patients: 8,625 CHB-no FL and 4,637 CHB-FL patients who differed in several characteristics. The IPTW cohort included 6,955 CHB-no FL and 3,346 CHB-FL well-matched patients. CHB-FL patients (vs. CHB-no FL) had significantly lower HCC, cirrhosis, mortality and higher HBsAg seroclearance incidence (all p≤0.002), with consistent results in subgroups. CHB-FL diagnosed by liver biopsy had a higher 10-year cumulative HCC incidence than CHB-FL diagnosed with non-invasive methods (63.6% vs. 4.3%, p<0.0001). Conclusions IPDMA data with well-matched CHB patient groups showed that FL (vs. no FL) was associated with significantly lower HCC, cirrhosis, and mortality risk and higher HBsAg seroclearance probability.

Humans ; Neoplasms, Second Primary/epidemiology* ; Neoplasms/epidemiology* ; Risk Factors ; Prognosis

Inflammation is the key driver of liver fibrosis progression in non-alcoholic fatty liver disease (NAFLD). Unfortunately, it is often challenging to assess inflammation in NAFLD due to its dynamic nature and poor correlation with liver biochemical markers. Liver histology keeps its role as the standard tool, yet it is well-known for substantial sampling, intraobserver, and interobserver variability. Serum proinflammatory cytokines and apoptotic markers, namely cytokeratin-18, are well-studied with reasonable accuracy, whereas serum metabolomics and lipidomics have been adopted in some commercially available diagnostic models. Ultrasound and computed tomography imaging techniques are attractive due to their wide availability; yet their accuracies may not be comparable with magnetic resonance imaging-based tools. Machine learning and deep learning models, be they supervised or unsupervised learning, are promising tools to identify various subtypes of NAFLD, including those with dominating liver inflammation, contributing to sustainable care pathways for NAFLD.