Relationships Among Serological Indicators and In Vitro High-Throughput Drug Sensitivity Screening Results in Patients with Hepatocellular Carcinoma.

AIM: The purpose of this study was to analyze the relationship between serum indicators and high-throughput drug screening (HDS) results, aiming to achieve specific therapy for hepatocellular carcinoma (HCC). METHODS: This study recruited patients with HCC who underwent surgical resection at the Hepatobiliary Surgery Center of the First Affiliated Hospital of Chongqing Medical University from December 2019 to December 2021. HCC tissues were obtained from patients during surgery and subjected to in vitro cell culture, and then HDS testing was performed on the cultured tissue samples. We used Spearman's correlation analysis to examine the relationships between drug sensitivity results for anti-hepatocellular carcinoma drugs, other antitumor drugs, and serological indicators, the Neutrophil Lymphocyte Ratio (NLR), Platelet Lymphocyte Ratio (PLR), Systemic Immune Inflammatory Index (SII), Systemic Inflammatory Response Index (SIRI), Prognostic Nutritional Index (PNI), and Lymphocyte Monocyte Ratio (LMR). A significant correlation was considered when P<0.05 and |r|>0.40. Furthermore, linear regression analysis was conducted to elucidate the relationship between serological indicators and drug susceptibility, with significant results indicated by P<0.05 and R²≥0.50. RESULTS: In this study, 82 patients with HCC who had undergone hepatectomy and completed in vitro cell culture and HDS testing were evaluated. Using Spearman's correlation with a significance threshold of P<0.05 and |r|>0.40, we identified significant associations between serological indicators and specific drug regimens: NLR correlated with 5-Fluorouracil, 5- Fluorouracil+Calcium folinate (FOLFOX4), and Capecitabine + Cisplatin (XP); PLR with FOLFOX4; SII with XP, FOLFOX4, Doxorubicin + Oxaliplatin (ADM+L-OHP); and SIRI with XP and FOLFOX4. No correlations were found between PNI or LMR and any drug inhibition rates. A comprehensive evaluation using linear regression analysis-which included variables such as sex, age, hepatitis B virus and liver cirrhosis status, size and number of lesions, alphafetoprotein, total bilirubin, albumin, alanine aminotransferase, aspartate aminotransferase, and prothrombin time, alongside NLR, PLR, SII, and SIRI was conducted in relation to drug regimens. This analysis revealed that NLR, SII, and SIRI are significant predictors of FOLFOX4 inhibition rate, while NLR predicts the inhibition rate of XP effectively. However, no significant links were established between molecular targeted drugs, other antitumor drugs, and serological indicators. CONCLUSIONS: NLR, SII, and SIRI were correlated with FOLFOX4, and the higher the values of NLR, SII, and SIRI, the higher the in vitro inhibition of FOLFOX. Also, NLR was correlated with XP, and the higher the value of NLR, the higher the in vitro inhibition of XP.

Serology-Based Model for Personalized Epithelial Ovarian Cancer Risk Evaluation.

This study aimed to establish a prognosis-prediction model based on serological indicators in patients with epithelial ovarian cancer (EOC). Patients initially diagnosed as ovarian cancer and surgically treated in Fudan University Shanghai Cancer Center from 2014 to 2018 were consecutively enrolled. Serological indicators preoperatively were collected. A risk model score (RMS) was constructed based on the levels of serological indicators determined by receiver operating characteristic curves. We correlated this RMS with EOC patients' overall survival (OS). Finally, 635 patients were identified. Pearson's χ2 results showed that RMS was significantly related to clinical parameters. Kaplan−Meier analysis demonstrated that an RMS less than 3 correlated with a longer OS (p < 0.0001). Specifically, significant differences were perceived in the survival curves of different subgroups. Multivariate Cox analysis revealed that age (p = 0.015), FIGO stage (p = 0.006), ascites (p = 0.015) and RMS (p = 0.005) were independent risk factors for OS. Moreover, RMS combined with age, FIGO and ascites could better evaluate for patients' prognosis in DCA analyses. Our novel RMS-guided classification preoperatively identified the prognostic subgroups of patients with EOC and showed higher accuracy than the conventional method, meaning that it could be a useful and economical tool for tailored monitoring and/or therapy.

Construction of diagnostic prediction model for Wilson's disease.

Background: Wilson's disease, also known as hepatolenticular degeneration, is a rare human autosomal recessive inherited disorder of copper metabolism. The clinical manifestations are diverse, and the diagnosis and treatment are often delayed. The purpose of this study is to establish a new predictive diagnostic model of Wilson's disease and evaluate its predictive efficacy by multivariate regression analysis of small trauma, good accuracy, low cost, and quantifiable serological indicators, in order to identify Wilson's disease early, improve the diagnosis rate, and clarify the treatment plan. Methods: A retrospective analysis was performed on 127 patients with Wilson's disease admitted to the First People's Hospital of Yunnan Province from January 2003 to May 2022 as the experimental group and 73 patients with normal serological indicators who were not diagnosed with Wilson's disease. SPSS version 26.0 software was used for single factor screening and a multivariate binary logistic regression analysis to screen out independent factors. R version 4.1.0 software was used to establish an intuitive nomogram prediction model for the independent influencing factors included. The accuracy of the nomogram prediction model was evaluated and quantified by calculating the concordance index (C-index) and drawing the calibration curve. At the same time, the area under the curve (AUC) of the nomogram prediction model and the receiver operating characteristic (ROC) curve of the Leipzig score was calculated to compare the predictive ability of the nomogram model and the current Leipzig score for Wilson's disease. Results: Alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (AKP), albumin (ALB), uric acid (UA), serum calcium (Ca), serum phosphorus (P), and hemoglobin (HGB) are closely related to the occurrence of Wilson's disease (p < 0.1). The prediction model of Wilson's disease contains seven independent predictors: ALT, AST, AKP, ALB, UA, Ca, and P. The AUC value of the prediction model was 0.971, and the C-index value was 0.972. The calibration curve was well fitted with the ideal curve. The nomogram prediction model had a good predictive effect on the occurrence of Wilson's disease; the ROC curve of Leipzig score was drawn, and the AUC value was calculated. The AUC of the Leipzig score was 0.969, indicating that the prediction model and the scoring system had predictive value, and the nomogram prediction model had a better predictive effect on the research objects of the center. Conclusion: ALT, AST, AKP, ALB, UA, Ca, and P are independent predictors of Wilson's disease, and can be used as early predictors. Based on the nomogram prediction model, the optimal threshold was determined to be 0.698, which was an important reference index for judging Wilson's disease. Compared with the Leipzig score, the nomogram prediction model has a relatively high sensitivity and specificity and has a good clinical application value.

Risk Factors and Their Diagnostic Values for Ocular Metastases in Gastric Adenocarcinoma.

OBJECTIVE: Gastric adenocarcinoma originates from the glands in the superficial layer or mucosa of the stomach. It is prone to metastases, of which ocular metastasis (OM) is rare, but once it occurs the disease is considered more serious. The aim of this study was to investigate the risk factors for OM in gastric adenocarcinoma. METHODS: Patients with gastric adenocarcinoma were recruited to this study between June 2003 and July 2019. Demographic data and serological indicators (SI) were compared between patients with and without OM, and binary logistic regression was used to explore whether the relevant SI may be risk factors for OM of gastric adenocarcinoma. Receiver operating characteristic (ROC) curves were used to analyze different SIs for OM in gastric cancer patients. RESULTS: Chi-square tests showed significant between-groups difference in gender composition (P < 0.05), but not in age or histological grade (P > 0.05). t-test results showed that low-density lipoprotein (LDL) and carbohydrate antigen-724 (CA724) were significantly higher in patients with than without OM (P < 0.05). Binary logistic regression analysis showed that LDL was an independent risk factor for OM (P < 0.001). ROC curve analysis showed that the areas under the curves (AUC) for LDL and CA724 were 0.903 and 0.913 respectively, with higher AUC for combined LDL and CA724 (0.934; P < 0.001). CONCLUSION: LDL and CA724 have value as predictors for OM in patients with gastric adenocarcinoma, with higher predictive value when these factors are combined.

Artificial Neural Network Model for Liver Cirrhosis Diagnosis in Patients with Hepatitis B Virus-Related Hepatocellular Carcinoma.

BACKGROUND: Testing for the presence of liver cirrhosis (LC) is one of the most critical diagnostic and prognostic assessments for patients with hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC). More non-invasive tools are needed to diagnose LC but the predictive abilities of current models are still inconclusive. This study aimed to develop and validate a novel and non-invasive artificial neural network (ANN) model for diagnosing LC in patients with HBV-related HCC using routine laboratory serological indicators. METHODS: A total of 1152 HBV-related HCC patients who underwent hepatectomy were included and randomly divided into the training set (n = 864, 75%) and validation set (n = 288, 25%). The ANN model was constructed from the training set using multivariate Logistic regression analysis and then verified in the validation set. RESULTS: The morbidity of LC in the training and validation sets was 41.2% and 46.8%, respectively. Multivariate analysis showed that age, platelet count, prothrombin time and total bilirubin were independent risk factors for LC (P < 0.05). The area under the ROC curve (AUC) analyses revealed that the ANN model had higher predictive accuracy than the Logistic model (ANN: 0.757 vs Logistic: 0.721; P < 0.001), and other scoring systems (ANN: 0.757 vs CP: 0.532, MELD: 0.594, ALBI: 0.575, APRI: 0.621, FIB-4: 0.644, AAR: 0.491, and GPR: 0.604; P < 0.05 for all) in diagnosing LC. Similar results were obtained in the validation set. CONCLUSION: The ANN model has better diagnostic capabilities than other commonly used models and scoring systems in assessing LC risk in patients with HBV-related HCC.

Nested case-control study of multiple serological indexes and Brighton pediatric early warming score in predicting death of children with sepsis.

BACKGROUND: Currently, it is difficult to predict the complications of children at the early stage of sepsis. Brighton pediatric early warning score (PEWS) is a disease risk assessment system that is simple and easy to operate, which has good sensitivity and specificity in disease recognition among children. Because detection indicators vary widely in children, a single indicator is difficult to assess the post-treatment status of children with sepsis. AIM: To investigate the relationship between serological markers, Brighton PEWS, and death in children with sepsis after treatment. METHODS: A total of 205 children diagnosed with sepsis at our hospital were enrolled. The baseline data, serum scores, and PEWS scores were recorded. In the nested case-control study, children who died during the study period were included in an observation group. According to the matching principle, the children who were not dead in the same cohort were included in a control group. The influencing factors of death in children with sepsis after treatment and the value of each evaluation index in predicting the prognosis of children were analyzed. RESULTS: A total of 96 children were enrolled in the study, including 48 each in the observation group and the control group. Multivariate logistic regression analysis indicated that antibacterial treatments within 1 h (P = 0.017), shock (P = 0.044), multiple organ dysfunction syndrome (MODS) (P = 0.027), serum procalcitonin (PCT) (P = 0.047), serum albumin (ALB) (P = 0.024), and PEWS (P = 0.012) were independent risk factors for the death of children with sepsis. The area under the curve of the combination of ALB, PCT, and PEWS to predict the death in children with sepsis was the highest (0.908). CONCLUSION: Antibacterial treatments within 1 h, shock, MODS, PCT, ALB, and PEWS are independent risk factors for the death of children with sepsis. The predictive accuracy of the combination of PCT, ALB, and PEWS for the prognosis of children with sepsis is the best.

A Behavioral and Serological Survey on HIV Prevalence Among Prisoners in Benin.

Cases of HIV are common in Benin, with infection rates varying according to socioeconomic and cultural factors, and by region. Certain segments of the population, such as prison inmates, sex worker clients and truck drivers are at high risk for HIV/AIDS. The aim of this study is to identify which behavioral and serological indicators contribute to the spread of HIV among prisoners. A total of 496 inmates from prisons located in all major cities in Benin were surveyed. Data was collected through interview sessions carried out using a questionnaire and through blood samples. The results show that most inmates are Beninese (83.5%), and the average age is 33 years (range: 14-80 years). No prisoner reported using a condom the last time they engaged in sexual intercourse. Blood exposure was found in 14.6% of inmates and HIV was detected in 1.4% of cases. Our analysis indicates that the length of detention and gender are factors that influence HIV status. However, age, education, nationality and HIV awareness had no significant effect on HIV prevalence among inmates. The results highlight the need to raise awareness in prisons about HIV. This can be achieved by strengthening communication strategies and by organizing HIV and sexually transmitted diseases information sessions for both prison officers and inmates.