Life Expectancy of Insured People With and Without Hepatitis C Virus Infection, 2007-2017

Mortality Evaluation and Life Expectancy Prediction of Patients with Hepatocellular Carcinoma with Data Mining

BACKGROUND

The complexity of systemic variables and comorbidities makes it difficult to determine the best treatment for patients with hepatocellular carcinoma (HCC). It is impossible to perform a multidimensional evaluation of every patient, but the development of guidelines based on analyses of said complexities would be the next best option. Whereas conventional statistics are often inadequate for developing multivariate predictive models, data mining has proven more capable. Patients, methods and findings: Clinical profiles and treatment responses of 537 patients diagnosed with Barcelona Clinic Liver Cancer stages B and C from 2009 to 2019 were retrospectively analyzed using 4 decision tree algorithms. A combination of 19 treatments, 7 biomarkers, and 4 states of hepatitis was tested to determine which combinations would result in survival times greater than a year in duration. Just 2 of the algorithms produced complete models through single trees, which made them only the ones suitable for clinical judgement. A combination of alpha fetoprotein ≤210.5 mcg/L, glutamic oxaloacetic transaminase ≤1.13 µkat/L, and total bilirubin ≤ 0.0283 mmol/L was shown to be a good predictor of survival >1 year, and the most effective treatments for such patients were radio-frequency ablation (RFA) and transarterial chemoembolization (TACE) with radiation therapy (RT). In patients without this combination, the best treatments were RFA, TACE with RT and targeted drug therapy, and TACE with targeted drug therapy and immunotherapy. The main limitation of this study was its small sample. With a small sample size, we may have developed a less reliable model system, failing to produce any clinically important results or outcomes.

CONCLUSION

Data mining can produce models to help clinicians predict survival time at the time of initial HCC diagnosis and then choose the most suitable treatment.

Cancer in People with and without Hepatitis C Virus Infection: Comparison of Risk Before and After Introduction of Direct-Acting Antivirals

BACKGROUND

Chronic hepatitis C virus (HCV) infection is a leading cause of liver cancer. The association of HCV infection with extrahepatic cancers, and the impact of direct-acting antiviral (DAA) treatment on these cancers, is less well known.

METHODS

We conducted a cohort study in a healthcare delivery system. Using electronic health record data from 2007 to 2017, we determined cancer incidence, overall and by type, in people with HCV infection and by DAA treatment status. All analyses included comparisons with a reference population of people without HCV infection. Covariate-adjusted Poisson models were used to estimate incidence rate ratios.

RESULTS

2,451 people with HCV and 173,548 people without HCV were diagnosed with at least one type of cancer. Compared with people without HCV, those with HCV were at higher risk for liver cancer [adjusted incidence rate ratio (aIRR) = 31.4, 95% confidence interval (CI) = 28.9-34.0], hematologic cancer (aIRR = 1.3, 95% CI = 1.1-1.5), lung cancer (aIRR = 1.3, 95% CI = 1.2-1.5), pancreatic cancer (aIRR = 2.0, 95% CI = 1.6-2.5), oral/oropharynx cancer (aIRR = 1.4, 95% CI = 1.1-1.8), and anal cancer (aIRR = 1.6, 95% CI = 1.1-2.4). Compared with people without HCV, the aIRR for liver cancer was 31.9 (95% CI = 27.9-36.4) among DAA-untreated and 21.2 (95% CI = 16.8-26.6) among DAA-treated, and the aIRR for hematologic cancer was 1.5 (95% CI = 1.1-2.0) among DAA-untreated and 0.6 (95% CI = 0.3-1.2) among DAA-treated.

CONCLUSIONS

People with HCV infection were at increased risk of liver cancer, hematologic cancer, and some other extrahepatic cancers. DAA treatment was associated with reduced risk of liver cancers and hematologic cancers.

IMPACT

DAA treatment is important for reducing cancer incidence among people with HCV infection.

Adverse outcomes after surgeries in patients with liver cirrhosis among Korean population: A population-based study

Background

Patients with liver cirrhosis have an increased risk of in-hospital mortality or postoperative complication after surgery. However, large-scale studies on the prognosis of these patients after surgery are lacking. The aim of the study was to investigate the adverse outcomes of patients with liver cirrhosis after surgery over five years.

Methods and findings

We used the Health Insurance Review and Assessment Service-National Inpatient Samples (HIRA-NIS) between 2012 and 2016. In-hospital mortality and hospital stay were analyzed using the data. Mortality rates according to the surgical department were also analyzed. Of the 1,662,887 patients who underwent surgery, 16,174 (1.0%) patients had cirrhosis. The in-hospital mortality (8.0% vs. 1.0%) and postoperative complications such as respiratory (6.0% vs. 5.3%) or infections (2.8% vs. 2.4%) was significantly higher in patients with cirrhosis than in those without cirrhosis. In addition, the total hospitalization period and use of the intensive care unit were significantly higher in patients with liver cirrhosis. In propensity score matching analysis, liver cirrhosis increased the risk of adverse outcome significantly [adjusted OR (aOR) 1.67, 95% CI 1.56–1.79, P<0.001], especially in-hospital mortality. In liver cirrhosis group, presence of decompensation or varices showed significantly increased postoperative complication or mortality. Adverse outcomes in patients with cirrhosis was the highest in patients who underwent otorhinolaryngology surgery (aOR 1.86), followed by neurosurgery (aOR 1.72), thoracic and cardiovascular surgery (aOR 1.56), and plastic surgery (aOR 1.36).

Conclusion

The adverse outcomes of patients with cirrhosis is significantly high after surgery, despite advances in cirrhosis treatment.

Application of a hemophilia mortality framework to the Emicizumab Global Safety Database

BACKGROUND

As the first non-factor replacement therapy for persons with congenital hemophilia A (PwcHA), emicizumab's safety profile is of particular interest to the community.

OBJECTIVES

We applied an algorithm for categorization of fatal events contemporaneous to emicizumab using reporter-assessed causality documented in the Roche Emicizumab Global Safety Database.

PATIENTS/METHODS

All fatalities in PwcHA reported to the database (from clinical trials, pre-market access, and spontaneous post-marketing reports) were categorized into: associated with hemophilia A-hemorrhagic, thrombotic, human immunodeficiency virus (HIV)/hepatitis C virus (HCV), hepatic (non-HCV); associated with general population-trauma/suicide, non-HA-associated conditions; or, unspecified. Reported cause of death was not reassessed.

RESULTS

As of cut-off May 15, 2020, 31 fatalities in PwcHA taking emicizumab were reported. Median age at death was 58 years; 51% had factor VIII inhibitors. Fifteen fatalities were considered associated with HA; overall, the most frequent category was hemorrhage (11/31). Of these, six had a history of life-threatening bleeds, and four had a history of intracranial hemorrhage. The remaining HA-associated fatalities were related to HIV/HCV (3/31) and other hepatic causes (1/31). No cases were categorized as thrombotic. Of 10 cases considered not associated with HA, two were categorized as cardiovascular (non-thrombotic), five as infection/sepsis, and one each of trauma/suicide, pulmonary, and malignancy. Six cases were unspecified.

CONCLUSIONS

No unique risk of death was associated with emicizumab prophylaxis in PwcHA. The data reveal that mortality in PwcHA receiving emicizumab was primarily associated with hemorrhage or non-HA-associated conditions, and was not reported by treaters to be related to emicizumab treatment.

Establishment of a framework for assessing mortality in persons with congenital hemophilia A and its application to an adverse event reporting database

BACKGROUND

Despite recent therapeutic advances, life expectancy in persons with congenital hemophilia A (PwcHA) remains below that of the non-HA population. As new therapies are introduced, a uniform approach to the assessment of mortality is required for comprehensive evaluation of risk-benefit profiles, timely identification of emerging safety signals, and comparisons between treatments.

OBJECTIVES

Develop and test a framework for consistent reporting and analysis of mortality across past, current, and future therapies.

PATIENTS/METHODS

We identified known causes of mortality in PwcHA through literature review, analysis of the US Food and Drug Administration Adverse Event Reporting System (FAERS) database, and expert insights. Leading causes of death in general populations are those recognized by the Centers for Disease Control and Prevention and the World Health Organization. We developed an algorithm for assessing fatalities in PwcHA and used this to categorize FAERS data as a proof of concept.

RESULTS

PwcHA share mortality causes with the non-HA population including cardiovascular disease, malignancy, infections, pulmonary disease, dementias, and trauma/suicide. Causes associated with HA include hemorrhage, thrombosis, human immunodeficiency virus, hepatitis C virus, and liver dysfunction. We propose an algorithm employing these classes to categorize fatalities and use it to classify FAERS fatality data between 01/01/2000 and 03/31/2020; the most common causes were hemorrhage (22.2%) and thrombosis (10.4%).

CONCLUSIONS

A conceptual framework for examining mortality in PwcHA receiving any hemophilia therapy is proposed to analyze and interpret fatalities, enabling consistent and objective assessment. Application of the framework using FAERS data suggests a generally consistent pattern of reported mortality across HA treatments, supporting the utility of this unified approach.