Mortality trends of liver diseases from 1981 to 2016 and the projection to 2035 in Taiwan: An age-period-cohort analysis

Machine Learning Models for Predicting Mortality in Patients with Cirrhosis and Acute Upper Gastrointestinal Bleeding at an Emergency Department: A Retrospective Cohort Study

BACKGROUND

Cirrhosis is a major global cause of mortality, and upper gastrointestinal (GI) bleeding significantly increases the mortality risk in these patients. Although scoring systems such as the Child-Pugh score and the Model for End-stage Liver Disease evaluate the severity of cirrhosis, none of these systems specifically target the risk of mortality in patients with upper GI bleeding. In this study, we constructed machine learning (ML) models for predicting mortality in patients with cirrhosis and upper GI bleeding, particularly in emergency settings, to achieve early intervention and improve outcomes.

METHODS

In this retrospective study, we analyzed the electronic health records of adult patients with cirrhosis who presented at an emergency department (ED) with GI bleeding between 2001 and 2019. Data were divided into training and testing sets at a ratio of 90:10. The ability of three ML models-a linear regression model, an XGBoost (XGB) model, and a three-layer neural network model-to predict mortality in the patients was evaluated.

RESULTS

A total of 16,025 patients with cirrhosis and 32,826 ED visits for upper GI bleeding were included in the study. The in-hospital and ED mortality rates were 11.2% and 2.2%, respectively. The XGB model exhibited the highest performance in predicting both in-hospital and ED mortality (area under the receiver operating characteristic curve: 0.866 and 0.861, respectively). International normalized ratio, renal function, red blood cell distribution width, age, and white blood cell count were the strongest predictors in all the ML models. The median ED length of stay for the ED mortality group was 17.54 h (7.16-40.01 h).

CONCLUSIONS

ML models can be used to predict mortality in patients with cirrhosis and upper GI bleeding. Of the three models, the XGB model exhibits the highest performance. Further research is required to determine the actual efficacy of our ML models in clinical settings.

Projected Time for the Elimination of Cervical Cancer Under Various Intervention Scenarios: Age-Period-Cohort Macrosimulation Study

BACKGROUND

The World Health Organization aims for the global elimination of cervical cancer, necessitating modeling studies to forecast long-term outcomes.

OBJECTIVE

This paper introduces a macrosimulation framework using age-period-cohort modeling and population attributable fractions to predict the timeline for eliminating cervical cancer in Taiwan.

METHODS

Data for cervical cancer cases from 1997 to 2016 were obtained from the Taiwan Cancer Registry. Future incidence rates under the current approach and various intervention strategies, such as scaled-up screening (cytology based or human papillomavirus [HPV] based) and HPV vaccination, were projected.

RESULTS

Our projections indicate that Taiwan could eliminate cervical cancer by 2050 with either 70% compliance in cytology-based or HPV-based screening or 90% HPV vaccination coverage. The years projected for elimination are 2047 and 2035 for cytology-based and HPV-based screening, respectively; 2050 for vaccination alone; and 2038 and 2033 for combined screening and vaccination approaches.

CONCLUSIONS

The age-period-cohort macrosimulation framework offers a valuable policy analysis tool for cervical cancer control. Our findings can inform strategies in other high-incidence countries, serving as a benchmark for global efforts to eliminate the disease.

Synthesized Age-Period-Cohort Prediction Method: Application to Lung Cancer Mortality in Taiwan

Age-period-cohort analysis involves 3 temporal factors: age (the length of time from birth to diagnosis), period (the calendar time of diagnosis), and cohort (the calendar time of birth). The application of age-period-cohort analysis in disease forecasting can help researchers and health authorities anticipate future disease burden. In this study, a synthesized age-period-cohort prediction method was proposed based on 4 assumptions: 1) no single model can dominate as the most accurate prediction model in all forecasting scenarios; 2) historical trends will not continue indefinitely; 3) a model with the most accurate forecast for the training data will also be appropriate for forecasting future data; and 4) a model dominated by the stochastic temporal change will be the best-selected model with the robust forecasting. An ensemble of age-period-cohort prediction models was constructed, and Monte Carlo cross-validation was performed to evaluate forecasting accuracy of these models. Data on lung cancer mortality from 1996 to 2015 in Taiwan were used and projected to the year 2035 to illustrate the method. The actual lung cancer mortality rates from 2016 to 2020 were then used to verify the forecasting accuracy.

Dehydrocrenatidine Induces Liver Cancer Cell Apoptosis by Suppressing JNK-Mediated Signaling

Liver cancer is a leading cause of death worldwide. Despite advancement in therapeutic interventions, liver cancer is associated with poor prognosis because of highly lethal characteristics and high recurrence rate. In the present study, the anticancer potential of a plant-based alkaloid namely dehydrocrenatidine has been evaluated in human liver cancer cells. The study findings revealed that dehydrocrenatidine reduced cancer cell viability by arresting cell cycle at G2/M phase and activating mitochondria-mediated and death receptor-mediated apoptotic pathways. Specifically, dehydrocrenatidine significantly increased the expression of extrinsic pathway components (FAS, DR5, FADD, and TRADD) as well as intrinsic pathway components (Bax and Bim L/S) in liver cancer cells. In addition, dehydrocrenatidine significantly increased the cleavage and activation of PARP and caspases 3, 8, and 9. The analysis of upstream signaling pathways revealed that dehydrocrenatidine induced caspase-mediated apoptosis by suppressing the phosphorylation of JNK1/2. Taken together, the study identifies dehydrocrenatidine as a potent anticancer agent that can be use clinically to inhibit the proliferation of human liver cancer cells.

Nonsteroidal Anti-Inflammatory Drugs Reduce Second Cancer Risk in Patients With Breast Cancer: A Nationwide Population-Based Propensity Score-Matched Cohort Study in Taiwan

Nonsteroidal anti-inflammatory drugs (NSAIDs) reduce mortality in patients with cancer, especially breast cancer, but their influence on second cancer risk is uncertain. This study aimed to examine whether NSAID use is associated with second cancer risk in patients with breast cancer. This population-based propensity score-matched cohort study using Taiwan’s National Health Insurance Research Database enrolled patients with newly diagnosed breast cancer (n = 7356) with and without (n = 1839) NSAID therapy from 2000 to 2009. They were followed up until the diagnosis of second cancer, death, or end of 2011. Cox proportional hazard models were used to estimate adjusted hazard ratios (aHR). The NSAID cohort had a lower incidence rate of second cancer than the non-NSAID cohort (5.57 vs. 9.19 per 1,000 person-years), with an aHR of 0.63 (95% confidence interval (CI) 0.46–0.87). When compared with the non-NSAID cohort, the second cancer incidence was lower in patients taking non-cyclooxygenase 2 inhibitors (aHR 0.67, 95% CI 0.47–0.94) and in those receiving multiple NSAIDs during follow-up (aHR 0.55, 95% CI 0.37–0.84). A dose–response relationship existed in NSAID cumulative days. The findings demonstrate that NSAID use reduces second cancer risk in a dose-dependent manner in patients with primary breast cancer.

Efficacy and Safety of Lenvatinib in Hepatocellular Carcinoma Patients with Liver Transplantation: A Case-Control Study

Simple Summary

Growing evidence has reported the role of sorafenib in hepatocellular carcinoma (HCC) patients with liver transplantation (LT). However, the clinical impact of lenvatinib in this population is limited. Our study enrolled 10 HCC patients who received lenvatinib after LT in our institute. Partial response was 20% and disease control rate was 70%. The median progression-free survival and overall survival were 3.7 and 16.4 months, respectively. Adverse events (AEs) were predominantly grade 1–2 in severity, and the majority of patients tolerated. Additionally, 25 HCC patients without LT who underwent lenvatinib treatment were identified as the control group; there was no significant difference in survival or AEs between these two groups. The significance of our study is that it is the first to investigate the efficacy and safety of lenvatinib among HCC patients with LT. It provides more information to physicians about the role of lenvatinib in this special population in clinical practice.

Abstract

Tumor recurrence is the most common cause of death in hepatocellular carcinoma (HCC) patients who received liver transplantation (LT). Recently, lenvatinib was approved for the systemic treatment of unresectable HCC patients; however, the role of lenvatinib in HCC patients after LT remains unclear. There were 56 patients with recurrent HCC after LT from 2008 to 2018 in our institute, and 10 patients who received lenvatinib were identified. Additionally, to understand the difference in the clinical impact of lenvatinib in the LT and non-LT settings, 25 HCC patients without LT who underwent lenvatinib treatment were identified from our HCC database and regarded as the control group. In the LT group, partial response was 20% and stable disease was 50%, resulting in a disease control rate of 70%; the median progression-free survival (PFS), time to treatment failure (TTF) and overall survival (OS) were 3.7, 3.6 and 16.4 months, respectively. Adverse events (AEs) were predominantly grade 1–2 in severity, and the majority of patients tolerated the side effects. There was no significant difference in PFS/OS, and we observed a similar pattern of AEs between these two groups. Our study confirms the comparable efficacy and safety of lenvatinib in HCC patients with LT and non-LT in clinical practice.

A Survivorship-Period-Cohort Model for Cancer Survival: Application to Liver Cancer in Taiwan, 1997-2016

Monitoring survival in cancer is a common concern for patients, physicians, and public health researchers. The traditional cohort approach for monitoring cancer prognosis has a timeliness problem. In this paper, we propose a survivorship-period-cohort (SPC) model for examining the effects of survivorship, period, and year-of-diagnosis cohort on cancer prognosis and for predicting future trends in cancer survival. We used the developed SPC model to evaluate the relative survival (RS) of patients with liver cancer in Taiwan (diagnosed from 1997 to 2016) and to predict future trends in RS by imputing incomplete follow-up data for recently diagnosed patient cohorts. We used cross-validation to select the extrapolation method and bootstrapping to estimate the 95% confidence interval for RS. We found that 5-year cumulative RS increased for both men and women with liver cancer diagnosed after 2003. For patients diagnosed before 2010, the 5-year cumulative RS rate for men was lower than that for women; thereafter, the rates were better for men than for women. The SPC model can help elucidate the effects of survivorship, period, and year-of-diagnosis cohort effects on cancer prognosis. Moreover, the SPC model can be used to monitor cancer prognosis in real time and predict future trends; thus, we recommend its use.

Ensemble forecasting of a continuously decreasing trend in bladder cancer incidence in Taiwan

Bladder cancer is one of the most common malignancies involving the urinary system of about 1.65 million cases worldwide. To attain the 25 by 25 goal set by the World Health Organization (25% reduction in non-communicable diseases between 2015 and 2025), developing strategies to reduce cancer burdens is essential. The data of the study comprised the age-specific bladder cancer cases and total population numbers from age 25 to 85 and above from 1997 to 2016 in Taiwan. An ensemble age-period-cohort model was used to estimate bladder cancer incidence trends and forecast the trends to 2025. For men, the projected age-standardized incidence rates per 100,000 people in 2020 and 2025 are 13.0 and 10.4, respectively, with a 16.1% and 32.9% decrease projected from 2016 to 2020 and 2025, respectively. For women, the projected age-standardized incidence rates per 100,000 people in 2020 and 2025 are 4.7 and 3.7, respectively, with a 16.1% and 33.9% decrease projected from 2016 to 2020 and 2025, respectively. The age-specific bladder cancer incidence rates demonstrated a consistently downward trend after 2003 for all ages and both sexes. This study projects that the incidence rates of bladder cancer in Taiwan will continue to decrease, and more than a 25% reduction can be achieved from 2016 to 2025.

Long-Term Trend of Liver Cancer Mortality in Serbia, 1991-2015: An Age-Period-Cohort and Joinpoint Regression Analysis

Background and Objectives: Trends of liver cancer mortality vary widely around the world. The purpose of this study was to assess the trend of liver cancer mortality in Serbia. Material and Methods: Descriptive epidemiological study design was used in this research. The age-standardized rates (ASRs, per 100,000) were calculated using the direct method, according to the World standard population. Temporal trends were assessed using the average annual percent change (AAPC) with 95% confidence interval (95% CI), according to joinpoint regression. An age-period-cohort analysis was used to evaluate the underlying factors for liver cancer mortality trends. Results: In Serbia from 1991 to 2015, over 11,000 men and nearly 8000 women died from liver cancer. The trend in liver cancer mortality significantly decreased both in men (AAPC = -1.3%; 95% CI = -1.7 to -0.9) and women (AAPC = -1.5%; 95% CI = -1.9 to -1.1). For liver cancer mortality, statistically significant cohort and period effects were observed in both genders. Conclusions: The downward trends in liver cancer mortality in Serbia are recorded during the past decades.

Comorbidities and Outcome of Alcoholic and Non-Alcoholic Liver Cirrhosis in Taiwan: A Population-Based Study

The prognosis of different etiologies of liver cirrhosis (LC) is not well understood. Previous studies performed on alcoholic LC-dominated cohorts have demonstrated a few conflicting results. We aimed to compare the outcome and the effect of comorbidities on survival between alcoholic and non-alcoholic LC in a viral hepatitis-dominated LC cohort. We identified newly diagnosed alcoholic and non-alcoholic LC patients, aged ≥40 years old, between 2006 and 2011, by using the Longitudinal Health Insurance Database. The hazard ratios (HRs) were calculated using the Cox proportional hazards model and the Kaplan–Meier method. A total of 472 alcoholic LC and 4313 non-alcoholic LC patients were identified in our study cohort. We found that alcoholic LC patients were predominantly male (94.7% of alcoholic LC and 62.6% of non-alcoholic LC patients were male) and younger (78.8% of alcoholic LC and 37.4% of non-alcoholic LC patients were less than 60 years old) compared with non-alcoholic LC patients. Non-alcoholic LC patients had a higher rate of concomitant comorbidities than alcoholic LC patients (79.6% vs. 68.6%, p < 0.001). LC patients with chronic kidney disease demonstrated the highest adjusted HRs of 2.762 in alcoholic LC and 1.751 in non-alcoholic LC (all p < 0.001). In contrast, LC patients with hypertension and hyperlipidemia had a decreased risk of mortality. The six-year survival rates showed no difference between both study groups (p = 0.312). In conclusion, alcoholic LC patients were younger and had lower rates of concomitant comorbidities compared with non-alcoholic LC patients. However, all-cause mortality was not different between alcoholic and non-alcoholic LC patients.

The association between vitamin D-related gene polymorphisms and hepatitis B virus-related liver cirrhosis

OBJECTIVES

To investigate the relationship between vitamin D-related gene single nucleotide polymorphisms (SNPs) and hepatitis B-related liver cirrhosis.

METHODS

This study included patients with chronic hepatitis B who were admitted to the Liver Research Center of the First Affiliated Hospital of Fujian Medical University from July 2012 to August 2016. SNPs rs1544410 and rs2228570 in the vitamin D receptor gene and rs2282679 in the vitamin D-binding protein gene were detected using the imLDR™ multiple SNP typing kit. Genotype and allele frequencies were compared between groups using the chi-square test or Fisher’s exact test.

RESULTS

A total of 226 patients with hepatitis B virus (HBV) infection were enrolled, including 116 with HBV-related cirrhosis and 110 patients without. The distributions of vitamin D-related gene SNPs in both groups were in accordance with the Hardy–Weinberg equilibrium. There was no significant difference in the frequency or allelic distributions of rs1544410, rs2228570, and rs2282679 between the two groups. Additionally, the SNPs were not associated with the severity of cirrhosis.

CONCLUSION

No significant connection was identified between vitamin D-related SNPs and HBV-related liver cirrhosis.