BACKGROUND AND AIM: Remnant cholesterol (remnant-C) mediates the progression of major adverse cardiovascular events. It is unclear whether remnant-C, and particularly cumulative exposure to remnant-C, is associated with nonalcoholic fatty liver disease (NAFLD). This study aimed to explore whether remnant-C, not only baseline but cumulative exposure, can be used to independently evaluate the risk of NAFLD. METHODS: This study included 1 cohort totaling 21,958 subjects without NAFLD at baseline who underwent at least 2 repeated health checkups and 1 sub-cohort totaling 2,649 subjects restricted to those individuals with at least 4 examinations and no history of NAFLD until Exam 3. Cumulative remnant-C was calculated as a timeweighted model for each examination multiplied by the time between the 2 examinations divided the whole duration. Cox regression models were performed to estimate the association between baseline and cumulative exposure to remnant-C and incident NAFLD. RESULTS: After multivariable adjustment, compared with the quintile 1 of baseline remnant-C, individuals with higher quintiles demonstrated significantly higher risks for NAFLD (hazard ratio [HR] 1.48, 95%CI 1.31-1.67 for quintile 2; HR 2.07, 95%CI 1.85-2.33 for quintile 3; HR 2.55, 95%CI 2.27-2.88 for quintile 4). Similarly, high cumulative remnant-C quintiles were significantly associated with higher risks for NAFLD (HR 3.43, 95%CI 1.95-6.05 for quintile 2; HR 4.25, 95%CI 2.44-7.40 for quintile 3; HR 6.29, 95%CI 3.59-10.99 for quintile 4), compared with the quintile 1. CONCLUSION Elevated levels of baseline and cumulative remnant-C were independently associated with incident NAFLD. Monitoring immediate levels and longitudinal trends of remnant-C may need to be emphasized in adults as part of NAFLD prevention strategy.
Adult ; Humans ; Cohort Studies ; Non-alcoholic Fatty Liver Disease/etiology* ; Cholesterol ; Proportional Hazards Models ; Risk Factors

OBJECTIVE: To assess whether the use of Tanreqing (TRQ) Injection could show improvements in time to extubation, intensive care unit (ICU) mortality, ventilator-associated events (VAEs) and infection-related ventilator associated complication (IVAC) among patients receiving mechanical ventilation (MV). METHODS: A time-dependent cox-regression analysis was conducted using data from a well-established registry of healthcare-associated infections at ICUs in China. Patients receiving continuous MV for 3 days or more were included. A time-varying exposure definition was used for TRQ Injection, which were recorded on daily basis. The outcomes included time to extubation, ICU mortality, VAEs and IVAC. Time-dependent Cox models were used to compare the clinical outcomes between TRQ Injection and non-use, after controlling for the influence of comorbidities/conditions and other medications with both fixed and time-varying covariates. For the analyses of time to extubation and ICU mortality, Fine-Gray competing risk models were also used to measure competing risks and outcomes of interest. RESULTS: Overall, 7,685 patients were included for the analyses of MV duration, and 7,273 patients for the analysis of ICU mortality. Compared to non-use, patients with TRQ Injection had a lower risk of ICU mortality (Hazards ratios (HR) 0.761, 95% CI, 0.581-0.997), and was associated with a higher hazard for time to extubation (HR 1.105, 95% CI, 1.005-1.216), suggesting a beneficial effect on shortened time to extubation. No significant differences were observed between TRQ Injection and non-use regarding VAEs (HR 1.057, 95% CI, 0.912-1.225) and IVAC (HR 1.177, 95% CI, 0.929-1.491). The effect estimates were robust when using alternative statistic models, applying alternative inclusion and exclusion criteria, and handling missing data by alternative approaches. CONCLUSION Our findings suggested that the use of TRQ Injection might lower mortality and improve time to extubation among patients receiving MV, even after controlling for the factor that the use of TRQ changed over time.
Humans ; Respiration, Artificial/adverse effects* ; Intensive Care Units ; Proportional Hazards Models ; Registries ; Length of Stay

Objective: To explore the influencing factors of the adverse outcome of pulmonary tuberculosis (PTB) among adolescents in Hangzhou City between 2005 and 2020. Methods: A retrospective cohort study was used to collect the information of adolescent PTB patients with the onset of PTB occurring from January 1, 2005 to December 31 in 12 designated tuberculosis hospitals in Hangzhou, mainly including demographic, epidemiological, clinical manifestations, bacteriological characteristics and other data, through the China Management Information System for Infectious Disease Surveillance and Reporting and the follow-up survey. All patients were followed up and the end time was December 31, 2021. Multivariate Cox regression model was used to analyze the factors affecting the adverse outcome of these patients. Results: The mean age of 4 921 adolescent PTB patients was (18.9±3.6) years old, and the number of male and female patients were 3 074 and 1 847 respectively. The adverse outcome accounted for 14.7% (725) of all patients. Multivariate Cox regression model showed that eight risk factors, including management model from patients themselves or family members (HR=5.87, 95%CI: 4.55-7.64), molecular biology examination positive for PTB (HR=4.62, 95%CI: 2.98-7.19), the number of sputum smears-positive≥1 (HR=3.72, 95%CI: 2.87-4.83), non-standardized therapy regimens of PTB (HR=3.69, 95%CI: 2.95-4.64), history of retreated PTB (HR=2.22, 95%CI: 1.46-3.36), migrant adolescents (HR=1.89, 95%CI: 1.54-2.34), the number of chest X-ray scan (HR=1.83, 95%CI: 1.65-2.04), and severe PTB (HR=1.38, 95%CI: 1.02-2.05), were associated with the adverse outcome of adolescent PTB patients. Age (HR=0.94, 95%CI: 0.92-0.96), as the only protective factor, was associated with the adverse outcome of these patients. Conclusion: The management mode, molecular biological examination, chemotherapy program, history of tuberculosis, sputum smear examination, severity of tuberculosis, household residence, chest X-ray examination and age are associated with the adverse outcomes of adolescent PTB patients in Hangzhou.
Humans ; Male ; Adolescent ; Female ; Young Adult ; Adult ; Retrospective Studies ; Tuberculosis, Pulmonary/drug therapy* ; Risk Factors ; Proportional Hazards Models ; Sputum ; Mycobacterium tuberculosis

OBJECTIVE: To study the prognostic value of LPCAT1 in acute myeloid leukemia (AML). METHODS: TaqMan-based reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to detect relative expression of LPCAT1 in 214 newly diagnosed adult AML patients and 24 normal controls. Survival functions were estimated using the Kaplan-Meier method and were compared by the Log-rank test. A Cox proportional hazard regression model was used to identify prognostic factors. RESULTS: The expression level of LPCAT1 in adult AML was 34.37%(1.83%-392.63%), which was significantly lower than 92.81%(2.60%-325.84%) of normal controls (P<0.001). The prognostic significance of LPCAT1 was evaluated in 171 non-acute promyelocytic leukemia patients with complete clinical information and prognostic data. Survival analysis showed that the expression level of LPCAT1 had no significant effect on the prognosis of the whole cohort. However, in AML patients with FAB subtype M2 (AML-M2), the 2-year relapse-free survival (RFS) rate of patients with low LPCAT1 expression was 35.4%(95%CI: 0.107-0.601), which was significantly lower than 79.2%(95%CI: 0.627-0.957) of patients with high LPCAT1 expression (P=0.012). Multivariate analysis showed that low expression of LPCAT1 was an independent risk factor for RFS of AML-M2 patients (HR=0.355, 95%CI: 0.126-0.966, P=0.049). CONCLUSION In adult AML patients LPCAT1 shows low expression. Low LPCAT1 expression is an independent risk factor for RFS in M2-AML patients.
Humans ; Adult ; Prognosis ; Leukemia, Myeloid, Acute/metabolism* ; Survival Analysis ; Proportional Hazards Models ; Risk Factors ; 1-Acylglycerophosphocholine O-Acyltransferase

OBJECTIVE: To compare the predictive ability of two extended Cox models in nonlinear survival data analysis. METHODS: Through Monte Carlo simulation and empirical study and with the conventional Cox Proportional Hazards model and Random Survival Forests as the reference models, we compared restricted cubic spline Cox model (Cox_RCS) and DeepSurv neural network Cox model (Cox_DNN) for their prediction ability in nonlinear survival data analysis. Concordance index was used to evaluate the differentiation of the prediction results (a larger concordance index indicates a better prediction ability of the model). Integrated Brier Score was used to evaluate the calibration degree of the prediction (a smaller index indicates a better prediction ability). RESULTS: For data that met requirement of the proportion risk, the Cox_RCS model had the best prediction ability regardless of the sample size or deletion rate. For data that failed to meet the proportion risk, the prediction ability of Cox_DNN was optimal for a large sample size (≥500) with a low deletion (< 40%); the prediction ability of Cox_RCS was superior to those of other models in all other scenarios. For example data, the Cox_RCS model showed the best performance. CONCLUSION In analysis of nonlinear low maintenance data, Cox_RCS and Cox_DNN have their respective advantages and disadvantages in prediction. The conventional survival analysis methods are not inferior to machine learning or deep learning methods under certain conditions.
Proportional Hazards Models ; Survival Analysis ; Calibration ; Computer Simulation ; Data Analysis

Objective: To development the prognostic nomogram for malignant pleural mesothelioma (MPM). Methods: Two hundred and ten patients pathologically confirmed as MPM were enrolled in this retrospective study from 2007 to 2020 in the People's Hospital of Chuxiong Yi Autonomous Prefecture, the First and Third Affiliated Hospital of Kunming Medical University, and divided into training (n=112) and test (n=98) sets according to the admission time. The observation factors included demography, symptoms, history, clinical score and stage, blood cell and biochemistry, tumor markers, pathology and treatment. The Cox proportional risk model was used to analyze the prognostic factors of 112 patients in the training set. According to the results of multivariate Cox regression analysis, the prognostic prediction nomogram was established. C-Index and calibration curve were used to evaluate the model's discrimination and consistency in raining and test sets, respectively. Patients were stratified according to the median risk score of nomogram in the training set. Log rank test was performed to compare the survival differences between the high and low risk groups in the two sets. Results: The median overall survival (OS) of 210 MPM patients was 384 days (IQR=472 days), and the 6-month, 1-year, 2-year, and 3-year survival rates were 75.7%, 52.6%, 19.7%, and 13.0%, respectively. Cox multivariate regression analysis showed that residence (HR=2.127, 95% CI: 1.154-3.920), serum albumin (HR=1.583, 95% CI: 1.017-2.464), clinical stage (stage Ⅳ: HR=3.073, 95% CI: 1.366-6.910) and the chemotherapy (HR=0.476, 95% CI: 0.292-0.777) were independent prognostic factors for MPM patients. The C-index of the nomogram established based on the results of Cox multivariate regression analysis in the training and test sets were 0.662 and 0.613, respectively. Calibration curves for both the training and test sets showed moderate consistency between the predicted and actual survival probabilities of MPM patients at 6 months, 1 year, and 2 years. The low-risk group had better outcomes than the high-risk group in both training (P=0.001) and test (P=0.003) sets. Conclusion: The survival prediction nomogram established based on routine clinical indicators of MPM patients provides a reliable tool for prognostic prediction and risk stratification.
Humans ; Mesothelioma, Malignant ; Prognosis ; Nomograms ; Retrospective Studies ; Proportional Hazards Models

OBJECTIVE: To develop and validate a three-year risk prediction model for new-onset cardiovascular diseases (CVD) among female patients with breast cancer. METHODS: Based on the data from Inner Mongolia Regional Healthcare Information Platform, female breast cancer patients over 18 years old who had received anti-tumor treatments were included. The candidate predictors were selected by Lasso regression after being included according to the results of the multivariate Fine & Gray model. Cox proportional hazard model, Logistic regression model, Fine & Gray model, random forest model, and XGBoost model were trained on the training set, and the model performance was evaluated on the testing set. The discrimination was evaluated by the area under the curve (AUC) of the receiver operator characteristic curve (ROC), and the calibration was evaluated by the calibration curve. RESULTS: A total of 19 325 breast cancer patients were identified, with an average age of (52.76±10.44) years. The median follow-up was 1.18 [interquartile range (IQR): 2.71] years. In the study, 7 856 patients (40.65%) developed CVD within 3 years after the diagnosis of breast cancer. The final selected variables included age at diagnosis of breast cancer, gross domestic product (GDP) of residence, tumor stage, history of hypertension, ischemic heart disease, and cerebrovascular disease, type of surgery, type of chemotherapy and radiotherapy. In terms of model discrimination, when not considering survival time, the AUC of the XGBoost model was significantly higher than that of the random forest model [0.660 (95%CI: 0.644-0.675) vs. 0.608 (95%CI: 0.591-0.624), P < 0.001] and Logistic regression model [0.609 (95%CI: 0.593-0.625), P < 0.001]. The Logistic regression model and the XGBoost model showed better calibration. When considering survival time, Cox proportional hazard model and Fine & Gray model showed no significant difference for AUC [0.600 (95%CI: 0.584-0.616) vs. 0.615 (95%CI: 0.599-0.631), P=0.188], but Fine & Gray model showed better calibration. CONCLUSION It is feasible to develop a risk prediction model for new-onset CVD of breast cancer based on regional medical data in China. When not considering survival time, the XGBoost model and the Logistic regression model both showed better performance; Fine & Gray model showed better performance in consideration of survival time.
Humans ; Female ; Adult ; Middle Aged ; Adolescent ; Breast Neoplasms/epidemiology* ; Cardiovascular Diseases/etiology* ; Proportional Hazards Models ; Logistic Models ; China/epidemiology*

BACKGROUND: The effect of intra-operative chemotherapy (IOC) on the long-term survival of patients with colorectal cancer (CRC) remains unclear. In this study, we evaluated the independent effect of intra-operative infusion of 5-fluorouracil in combination with calcium folinate on the survival of CRC patients following radical resection. METHODS: 1820 patients were recruited, and 1263 received IOC and 557 did not. Clinical and demographic data were collected, including overall survival (OS), clinicopathological features, and treatment strategies. Risk factors for IOC-related deaths were identified using multivariate Cox proportional hazards models. A regression model was developed to analyze the independent effects of IOC. RESULTS: Proportional hazard regression analysis showed that IOC (hazard ratio [HR]=0.53, 95% confidence intervals [CI] [0.43, 0.65], P  < 0.001) was a protective factor for the survival of patients. The mean overall survival time in IOC group was 82.50 (95% CI [80.52, 84.49]) months, and 71.21 (95% CI [67.92, 74.50]) months in non-IOC group. The OS in IOC-treated patients were significantly higher than non-IOC-treated patients ( P  < 0.001, log-rank test). Further analysis revealed that IOC decreased the risk of death in patients with CRC in a non-adjusted model (HR=0.53, 95% CI [0.43, 0.65], P  < 0.001), model 2 (adjusted for age and gender, HR=0.52, 95% CI [0.43, 0.64], P  < 0.001), and model 3 (adjusted for all factors, 95% CI 0.71 [0.55, 0.90], P  = 0.006). The subgroup analysis showed that the HR for the effect of IOC on survival was lower in patients with stage II (HR = 0.46, 95% CI [0.31, 0.67]) or III disease (HR=0.59, 95% CI [0.45, 0.76]), regardless of pre-operative radiotherapy (HR=0.55, 95% CI [0.45, 0.68]) or pre-operative chemotherapy (HR=0.54, 95% CI [0.44, 0.66]). CONCLUSIONS: IOC is an independent factor that influences the survival of CRC patients. It improved the OS of patients with stages II and III CRC after radical surgery. TRIAL REGISTRATION chictr.org.cn, ChiCTR 2100043775.
Humans ; Fluorouracil/therapeutic use* ; Leucovorin/therapeutic use* ; Colorectal Neoplasms/pathology* ; Retrospective Studies ; Antineoplastic Combined Chemotherapy Protocols/therapeutic use* ; Proportional Hazards Models ; Prognosis

Objective: To evaluate the association between pre-and post-diagnosis body mass index (BMI) and risk of colorectal cancer (CRC) death. Methods: The cohort consisted of 3, 057 CRC patients from Shanghai who were diagnosed from Jan. 1, 2009 to Dec. 31, 2011 and aged from 20 to 74 years. The pre- and post-diagnosis BMI and clinical and lifestyle factors were collected at baseline. Death information was collected using record linkage with the Shanghai Cancer Registry and telephone confirmation during follow-up by the end of 2019. The Cox proportional regression model was used to estimate HR with 95% CI. Results: Analysis by multivariable Cox model showed no association between pre-diagnosis BMI and death risk in both male and female patients. Male patients with a post-diagnosis underweight BMI had an elevated risk of death compared to those in normal weight (HR=1.69, 95% CI: 1.21-2.37), especially in early stage cases. Overweight patients (HR=0.74, 95% CI: 0.61-0.89) and patients with obesity class Ⅰ (HR=0.63, 95% CI: 0.45-0.89)had better survival with decreased risks of death, especially in advanced stage cases. The decreased death risk in patients with obesity class Ⅱ was not significant (HR=0.57, 95% CI: 0.24-1.39). The P(trend) value for decreased risk of death with increased BMI in female patients was statistically significant (P<0.001), and the overweight and obesity class Ⅰ categories had better survival in advanced stage(HR(overweight)=0.62, 95% CI: 0.42-0.93; HR(obesity class Ⅰ)=0.39, 95% CI: 0.16-0.98). Both male and female patients with post-diagnosis BMI loss >2.0 kg/m(2) had an increased death risk when compared with those with stable BMI (change≤1.0 kg/m(2)) between pre- and post-diagnosis. BMI gain after diagnosis did not change death risk. Conclusions: Post-diagnosis BMI in the overweight or obesity class Ⅰ groups might be conducive to prolonging male CRC patients' survival, while underweight might result in poor prognosis. Keeping weight and avoiding excessive weight loss should be suggested for all CRC patients after diagnosis.
Female ; Humans ; Male ; Body Mass Index ; China/epidemiology* ; Colorectal Neoplasms/complications* ; Obesity/complications* ; Overweight/complications* ; Proportional Hazards Models ; Prospective Studies ; Risk Factors ; Thinness/complications* ; Young Adult ; Adult ; Middle Aged ; Aged

Objective: To evaluate the association between pre-and post-diagnosis body mass index (BMI) and risk of colorectal cancer (CRC) death. Methods: The cohort consisted of 3, 057 CRC patients from Shanghai who were diagnosed from Jan. 1, 2009 to Dec. 31, 2011 and aged from 20 to 74 years. The pre- and post-diagnosis BMI and clinical and lifestyle factors were collected at baseline. Death information was collected using record linkage with the Shanghai Cancer Registry and telephone confirmation during follow-up by the end of 2019. The Cox proportional regression model was used to estimate HR with 95% CI. Results: Analysis by multivariable Cox model showed no association between pre-diagnosis BMI and death risk in both male and female patients. Male patients with a post-diagnosis underweight BMI had an elevated risk of death compared to those in normal weight (HR=1.69, 95% CI: 1.21-2.37), especially in early stage cases. Overweight patients (HR=0.74, 95% CI: 0.61-0.89) and patients with obesity class Ⅰ (HR=0.63, 95% CI: 0.45-0.89)had better survival with decreased risks of death, especially in advanced stage cases. The decreased death risk in patients with obesity class Ⅱ was not significant (HR=0.57, 95% CI: 0.24-1.39). The P(trend) value for decreased risk of death with increased BMI in female patients was statistically significant (P<0.001), and the overweight and obesity class Ⅰ categories had better survival in advanced stage(HR(overweight)=0.62, 95% CI: 0.42-0.93; HR(obesity class Ⅰ)=0.39, 95% CI: 0.16-0.98). Both male and female patients with post-diagnosis BMI loss >2.0 kg/m(2) had an increased death risk when compared with those with stable BMI (change≤1.0 kg/m(2)) between pre- and post-diagnosis. BMI gain after diagnosis did not change death risk. Conclusions: Post-diagnosis BMI in the overweight or obesity class Ⅰ groups might be conducive to prolonging male CRC patients' survival, while underweight might result in poor prognosis. Keeping weight and avoiding excessive weight loss should be suggested for all CRC patients after diagnosis.
Female ; Humans ; Male ; Body Mass Index ; China/epidemiology* ; Colorectal Neoplasms/complications* ; Obesity/complications* ; Overweight/complications* ; Proportional Hazards Models ; Prospective Studies ; Risk Factors ; Thinness/complications* ; Young Adult ; Adult ; Middle Aged ; Aged