Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.

Mice ; Animals ; Tandem Mass Spectrometry ; Alpha-Amanitin ; Chromatography, Liquid ; Metabolomics ; Chromatography, High Pressure Liquid/methods*

Objective:To explore the difference of lymphocyte subsets in peripheral blood(PB)between aplastic anemia(AA)and hypoplastic myelodysplastic syndrome(hypo-MDS)patients,meanwhile to compare the clinical parameters obtained from PB and bone marrow(BM).Methods:The lymphocyte subsets in hypo-MDS(n=25)and AA(n=33)patients were investigated by flow cytometry.Meanwhile,the differences in PB cell counts,biochemical indicators,BM cell counts and abnormal chromosomes between the two groups were analyzed.Results:The percentage of CD8+T cells in A A group was significantly higher than that in hypo-MDS group(P=0.001),while the percentage of CD4+T cells and the CD4+/CD8+ratio in AA group were obviously lower than those in hypo-MDS group(P=0.015 and0.001,respectively).Furthermore,the proportion of CD4+andCD8+activated T(TA)cells,and memory Tregs in AA group was distinctly lower than those in hypo-MDS group(P=0.043,0.015 and 0.024,respectively).Nevertheless,the percentage of CD8+naive T(TN)cells in AA patients was remarkably higher(P=0.044).And hypo-MDS patients had declined lymphocyte counts(P=0.025),increased levels of total bilirubin(TBil),lactate dehydrogenase(LDH),vitamin B12 and proportion of BM blasts than AA patients(P=0.019,0.023,0.027 and 0.045,respectively).Conclusion:In this study it was confirmed that the percentages of CD4+and CD8+TA cells,memory Tregs and CD8+TN cells were significantly different between AA and hypo-MDS patients,which provide an essential basis for the identification of these two diseases.

OBJECTIVE: To explore the potential mechanism of resistance to axitinib in clear cell renal cell carcinoma (ccRCC), with a view to expanding the understanding of axitinib resistance, facilitating the design of more specific treatment options, and improving the treatment effectiveness and survival prognosis of patients. METHODS: By exploring the half maximum inhibitory concentration (IC₅₀) of axitinib on ccRCC cell lines 786-O and Caki-1, cell lines resistant to axitinib were constructed by repeatedly stimulated with axitinib at this concentration for 30 cycles in vitro. Cell lines that were not treated by axitinib were sensitive cell lines. The phenotypic differences of cell proliferation and apoptosis levels between drug resistant and sensitive lines were tested. Genes that might be involved in the drug resistance process were screened from the differentially expressed genes that were co-upregulated in the two drug resistant lines by transcriptome sequencing. The expression level of the target gene in the drug resistant lines was verified by real-time quantitative polymerase chain reaction (RT-qPCR) and Western blot (WB). The expression differences of the target gene in ccRCC tumor tissues and adjacent tissues were analyzed in the Gene Expression Profiling Interactive Analysis (GEPIA) public database, and the impact of the target gene on the prognosis of ccRCC patients was analyzed in the Kaplan-Meier Plotter (K-M Plotter) database. After knocking down the target gene in the drug resistant lines using RNA interference by lentivirus vector, the phenotypic differences of the cell lines were tested again. WB was used to detect the levels of apoptosis-related proteins in the different treated cell lines to find molecular pathways that might lead to drug resistance. RESULTS: Cell lines 786-O-R and Caki-1-R resistant to axitinib were successfully constructed in vitro, and their IC₅₀ were significantly higher than those of the sensitive cell lines (10.99 μmol/L, P < 0.01; 11.96 μmol/L, P < 0.01, respectively). Cell counting kit-8 (CCK-8) assay, colony formation, and 5-ethynyl-2 '-deoxyuridine (EdU) assay showed that compared with the sensitive lines, the proliferative ability of the resistant lines decreased, but apoptosis staining showed a significant decrease in the level of cell apoptosis of the resistant lines (P < 0.01). Although resistant to axitinib, the resistant lines had no obvious new replicated cells in the environment of 20 μmol/L axitinib. Nuclear protein 1 (NUPR1) gene was screened by transcriptome sequencing, and its RNA (P < 0.0001) and protein expression levels significantly increased in the resistant lines. Database analysis showed that NUPR1 was significantly overexpressed in ccRCC tumor tissue (P < 0.05); the ccRCC patients with higher expression ofNUPR1had a worse survival prognosis (P < 0.001). Apoptosis staining results showed that knockdown ofNUPR1inhibited the anti-apoptotic ability of the resistant lines to axitinib (786-O, P < 0.01; Caki-1, P < 0.05). WB results showed that knocking downNUPR1decreased the protein level of B-cell lymphoma-2 (BCL2), increased the protein level of BCL2-associated X protein (BAX), decreased the protein level of pro-caspase3, and increased the level of cleaved-caspase3 in the resistant lines after being treated with axitinib. CONCLUSION ccRCC cell lines reduce apoptosis through theNUPR1 -BAX/ BCL2 -caspase3 pathway, which is involved in the process of resistance to axitinib.
Humans ; Carcinoma, Renal Cell/metabolism* ; Axitinib/pharmacology* ; Kidney Neoplasms/metabolism* ; bcl-2-Associated X Protein ; Nuclear Proteins ; Cell Line, Tumor ; Apoptosis ; Cell Proliferation

OBJECTIVES: To investigate the risk factors for neonatal asphyxia in Hubei Enshi Tujia and Miao Autonomous Prefecture and establish a nomogram model for predicting the risk of neonatal asphyxia. METHODS: A retrospective study was conducted with 613 cases of neonatal asphyxia treated in 20 cooperative hospitals in Enshi Tujia and Miao Autonomous Prefecture from January to December 2019 as the asphyxia group, and 988 randomly selected non-asphyxia neonates born and admitted to the neonatology department of these hospitals during the same period as the control group. Univariate and multivariate analyses were used to identify risk factors for neonatal asphyxia. R software (4.2.2) was used to establish a nomogram model. Receiver operator characteristic curve, calibration curve, and decision curve analysis were used to assess the discrimination, calibration, and clinical usefulness of the model for predicting the risk of neonatal asphyxia, respectively. RESULTS: Multivariate logistic regression analysis showed that minority (Tujia), male sex, premature birth, congenital malformations, abnormal fetal position, intrauterine distress, maternal occupation as a farmer, education level below high school, fewer than 9 prenatal check-ups, threatened abortion, abnormal umbilical cord, abnormal amniotic fluid, placenta previa, abruptio placentae, emergency caesarean section, and assisted delivery were independent risk factors for neonatal asphyxia (P<0.05). The area under the curve of the model for predicting the risk of neonatal asphyxia based on these risk factors was 0.748 (95%CI: 0.723-0.772). The calibration curve indicated high accuracy of the model for predicting the risk of neonatal asphyxia. The decision curve analysis showed that the model could provide a higher net benefit for neonates at risk of asphyxia. CONCLUSIONS The risk factors for neonatal asphyxia in Hubei Enshi Tujia and Miao Autonomous Prefecture are multifactorial, and the nomogram model based on these factors has good value in predicting the risk of neonatal asphyxia, which can help clinicians identify neonates at high risk of asphyxia early, and reduce the incidence of neonatal asphyxia.
Infant, Newborn ; Humans ; Male ; Pregnancy ; Female ; Nomograms ; Retrospective Studies ; Cesarean Section ; Risk Factors ; Asphyxia Neonatorum/etiology*

Objective: To investigate the distribution of blood pressure and analyze the associated factors of blood pressure of the elderly with type 2 diabetes in Jiangsu Province. Methods: The elderly over 60 years old participants with type 2 diabetes in the communities of Huai'an City and Changshu City, Jiangsu Province were selected in this study. They were divided into two groups: taking antihypertensive drugs and not taking antihypertensive drugs. The demographic characteristics, such as age and sex, and relevant factors were collected by questionnaire. The systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured by physical examination. The percentile of SBP and DBP in each age group of men and women were described. The kernel density estimation curve was used to show the blood pressure distribution. The trend of blood pressure with age was fitted by locally weighted regression. The logistic regression model was used to analyze relevant factors of blood pressure. Results: A total of 12 949 participants were included in this study, including 7 775 patients in the antihypertensive drug group and 5 174 patients in the group without antihypertensive drugs. The SBP of participants was concentrated at 140-160 mmHg, and their DBP was concentrated at 75-85 mmHg. There were significant differences in the distribution of blood pressure among the subgroups of body mass index (BMI) and rural areas whether taking antihypertensive drugs and not. For participants aged under 80 years old, the SBP showed an increasing trend with age and the DBP showed a decreasing trend with age. Age, BMI ≥24 kg/m², fasting blood glucose ≥7.0 mmol/L, living in rural areas and no smoking were influencing factors of the elevated SBP; BMI ≥24 kg/m², male, living in rural areas, no smoking, drinking alcohol and not receiving drug hypoglycemic treatment were influencing factors of the elevated DBP. Conclusion: The SBP of older diabetic adults in Jiangsu Province is at a high level, and the distribution of blood pressure is significantly different between men and women in taking antihypertensive drugs group. The SBP presents a rising trend and the DBP is decreasing at the age of 60-80 years. The blood pressure level of this population are mainly affected by age, BMI, urban and rural areas, smoking.
Adult ; Aged ; Humans ; Male ; Female ; Middle Aged ; Aged, 80 and over ; Blood Pressure/physiology* ; Diabetes Mellitus, Type 2/epidemiology* ; Antihypertensive Agents/therapeutic use* ; Smoking ; Body Mass Index ; Hypertension/epidemiology*

Objective: To investigate the association between long-term fasting blood glucose (FPG) variability and all-cause mortality in patients with type 2 diabetes. Methods: A total of 7 174 type 2 diabetic patients included in National Basic Public Health Service Program in Changshu of Jiangsu Province were recruited as participants. Long-term glucose variability was assessed using standard deviation (SD), coefficient of variation (CV), average real variability (ARV), and variability independent of the mean (VIM) across FPG measurements at the more than three visits. Death information were mainly obtained from the death registry system in Jiangsu. Then Cox proportional hazards regression models were used to estimate the associations of four variability indicators and all-cause mortality's hazard ratios (HRs) and their 95%CIs. Results: Among 55 058.50 person-years of the follow-up, the mean follow-up time was 7.67 years, and 898 deaths occurred during the follow-up period. After adjustment, compared with T₁ group, the Cox regression model showed that HRs of T₃ group in SD, CV, ARV and VIM were 1.24 (95%CI: 1.03-1.49), 1.20 (95%CI: 1.01-1.43), 1.28 (95%CI: 1.07-1.55) and 1.20 (95%CI:1.01-1.41), respectively. HRs of per 1 SD higher SD, CV, ARV and VIM were 1.13 (95%CI: 1.06-1.21), 1.08 (95%CI: 1.01-1.15), 1.05 (95%CI: 1.00-1.12) and 1.09 (95%CI: 1.02-1.16) for all-cause mortality, respectively. In the stratified analysis, age, gender, hypoglycemic agent and insulin uses had no effect on the above associations (all P for interaction >0.05). Conclusion: Long-term FPG glycemic variability was positively associated with the risk of all-cause mortality in type 2 diabetes patients.

Purpose: This study aimed to identify prognostic factors for patients with distant lymph node-involved gastric cancer (GC) using a machine learning algorithm, a method that offers considerable advantages and new prospects for high-dimensional biomedical data exploration. Materials and Methods: This study employed 79 features of clinical pathology, laboratory tests, and therapeutic details from 289 GC patients whose distant lymphadenopathy was presented as the first episode of recurrence or metastasis. Outcomes were measured as anycause death events and survival months after distant lymph node metastasis. A prediction model was built based on possible outcome predictors using a random survival forest algorithm and confirmed by 5×5 nested cross-validation. The effects of single variables were interpreted using partial dependence plots. A contour plot was used to visually represent survival prediction based on 2 predictive features. Results: The median survival time of patients with GC with distant nodal metastasis was 9.2 months. The optimal model incorporated the prealbumin level and the prothrombin time (PT), and yielded a prediction error of 0.353. The inclusion of other variables resulted in poorer model performance. Patients with higher serum prealbumin levels or shorter PTs had a significantly better prognosis. The predicted one-year survival rate was stratified and illustrated as a contour plot based on the combined effect the prealbumin level and the PT. Conclusions Machine learning is useful for identifying the important determinants of cancer survival using high-dimensional datasets. The prealbumin level and the PT on distant lymph node metastasis are the 2 most crucial factors in predicting the subsequent survival time of advanced GC.Trial Registration: ChiCTR Identifier: ChiCTR1800019978

Objective: To investigate the relationship between socioeconomic status (SES) and all-cause mortality in patients with type 2 diabetes. Methods: A total of 17 553 patients with type 2 diabetes were recruited under the National Basic Public Health Service Project in Changshu county, Qingjiangpu district, and Huai'an district in Huai'an city of Jiangsu province as participants. Latent class analysis was applied to classify the individuals based on five socioeconomic indicators. Then, Cox proportional hazards regression models were used to estimate the associations of different levels of SES with all-cause mortality, and stratified analysis was performed according to age and area. Results: Among 100 529.08 person-years of the fo1low-up, the median follow-up time was 5.7 years, and 1 829 deaths occurred during the follow-up period. According to the relevant results of the latent class model, the model of the "three classes" was the best. The related population was then divided into low SES (8 256 people, 47.0%), medium SES (4 427 people, 25.2%), and high SES groups (4 870 people, 27.8%). Compared to patients with high SES, the multivariate-adjusted hazard ratio (95%CI) of all-cause mortality associated with low SES for males and females were 1.84 (1.53-2.21) and 1.41 (1.51-1.72), respectively. Stratified analysis showed that the hazard ration (95%CI) of all-cause mortality associated with low SES for males and females were 1.99 (1.12-2.95) and 2.01 (1.20-3.23), respectively, in people younger than 60 years old, and were 1.90 (1.57-2.31) and 1.40 (1.13-1.73) in people over 60 years old. The HR values (95%CI) for all-cause mortality associated with low SES for the male and females were 1.54 (1.17-2.04) and 1.27 (1.02-1.59) in the urban population with 2.11 (1.55-2.85) and 2.64 (1.17-3.35) in rural population, respectively. Conclusions: Lower SES increased the risk of all-cause mortality in type 2 diabetic patients, which is more significant in younger and rural populations.
United States ; Female ; Humans ; Male ; Middle Aged ; Latent Class Analysis ; Diabetes Mellitus, Type 2 ; Prospective Studies ; Social Class ; Income

Objective: To evaluate the efficacy of the Hodgkin lymphoma (HL)-2013 regimen in the treatment of children with HL, and to investigate the prognostic factors of childhood HL. Methods: Clinical data of 145 children (aged ≤18 years) with newly diagnosed HL, treated with HL-2013 regimen in 8 tertiary referral centers for childhood cancer from August 2011 to April 2021 were analyzed retrospectively. All the diagnosis were confirmed by histopathological morphology and immunohistochemical examination. The clinical characteristics and treatment outcomes were summarized, and the patients were divided into different groups according to clinical characteristics. Kaplan-Meier method was used for survival analysis, and the comparison of survival rates between groups was performed with Log-rank test. Results: Of the 145 cases, there were 115 males and 30 females, the age at diagnosis was 7.9 (5.8, 10.6) years. Cervical lymph node enlargement (114 cases, 78.6%) was the common symptom of the disease, and 57 patients (39.3%) were accompanied by large masses. The most common pathological classification was mixed cell type (93 cases, 64.1%). According to the Ann Arbor staging system, there were 9 cases of stage Ⅰ, 62 cases of stage Ⅱ, 45 cases of stage Ⅲ, 29 cases of stage Ⅳ. According to the risk stratification: there were 14 cases of low-risk group, 76 cases of medium-risk group and 55 cases of high-risk group. Of all patients, 68 cases (46.9%) achieved an early complete remission (CR) after 2 courses of chemotherapy, and the CR rate was 93.8% (136/145) after first-line treatment. Disease recurrence or progression occurred in 22 cases (15.2%). Of all patients, 125 cases survived, 6 cases died and 14 cases were lost to follow-up. Among the survived cases, 123 cases were continuously at CR state,and the follow-up time was 55 (40, 76) months. The 5-year overall survival (OS) and event free survival (EFS) rates were (95.3±1.9)% and (84.2±3.0)% for the entire group, respectively. 5-year OS and EFS rates for patients with stage Ⅲ-Ⅳ were both lower than those for patients with stage Ⅰ-Ⅱ (χ²=6.28 and 7.58, both P<0.05), the 5-year OS and EFS rates for patients in high-risk group were both lower than those for patients in low-risk and medium-risk group (χ²=10.93, 7.79, both P<0.05). The 5-year OS rates for the patient with early CR and without early CR were 100.0% and (90.9±3.6)% (χ²=5.77, P=0.016). EFS rates for the patient with early CR (68 cases) and without early CR (77 cases) were (93.8±3.0)% and (75.8±5.0)% (χ²=8.78, P=0.003). Conclusions: HL-2013 regimen is significantly effective in the treatment of pediatric HL. However, the patients in high-risk group and those without early CR are prone to disease recurrence or progression. Stage Ⅲ-Ⅳ and without early CR were associated with worse prognosis.
Child ; Female ; Male ; Humans ; Hodgkin Disease ; Retrospective Studies ; Neoplasm Recurrence, Local ; China ; Antineoplastic Combined Chemotherapy Protocols ; Prognosis ; Disease-Free Survival