Exposure to PM2.5 Metal Constituents and Liver Cancer Risk in REVEAL-HBV.

BACKGROUND: Ambient particulate matter is classified as a human Class 1 carcinogen, and recent studies found a positive relationship between fine particulate matter (PM2.5) and liver cancer. Nevertheless, little is known about which specific metal constituent contributes to the development of liver cancer. OBJECTIVE: To evaluate the association of long-term exposure to metal constituents in PM2.5 with the risk of liver cancer using a Taiwanese cohort study. METHODS: A total of 13,511 Taiwanese participants were recruited from the REVEAL-HBV in 1991-1992. Participants' long-term exposure to eight metal constituents (Ba, Cu, Mn, Sb, Zn, Pb, Ni, and Cd) in PM2.5 was based on ambient measurement in 2002-2006 followed by a land-use regression model for spatial interpolation. We ascertained newly developed liver cancer (ie, hepatocellular carcinoma [HCC]) through data linkage with the Taiwan Cancer Registry and national health death certification in 1991-2014. A Cox proportional hazards model was utilized to assess the association between exposure to PM2.5 metal component and HCC. RESULTS: We identified 322 newly developed HCC with a median follow-up of 23.1 years. Long-term exposure to PM2.5 Cu was positively associated with a risk of liver cancer. The adjusted hazard ratio (HR) was 1.13 (95% confidence interval [CI], 1.02-1.25; P = 0.023) with one unit increment on Cu normalized by PM2.5 mass concentration in the logarithmic scale. The PM2.5 Cu-HCC association remained statistically significant with adjustment for co-exposures to other metal constituents in PM2.5. CONCLUSION: Our findings suggest PM2.5 containing Cu may attribute to the association of PM2.5 exposure with liver cancer.

Model-based hypothesis tests for the causal mediation of semi-competing risks.

Analyzing the causal mediation of semi-competing risks has become important in medical research. Semi-competing risks refers to a scenario wherein an intermediate event may be censored by a primary event but not vice versa. Causal mediation analyses decompose the effect of an exposure on the primary outcome into an indirect (mediation) effect: an effect mediated through a mediator, and a direct effect: an effect not through the mediator. Here we proposed a model-based testing procedure to examine the indirect effect of the exposure on the primary event through the intermediate event. Under the counterfactual outcome framework, we defined a causal mediation effect using counting process. To assess statistical evidence for the mediation effect, we proposed two tests: an intersection-union test (IUT) and a weighted log-rank test (WLR). The test statistic was developed from a semi-parametric estimator of the mediation effect using a Cox proportional hazards model for the primary event and a series of logistic regression models for the intermediate event. We built a connection between the IUT and WLR. Asymptotic properties of the two tests were derived, and the IUT was determined to be a size [Formula: see text] test and statistically more powerful than the WLR. In numerical simulations, both the model-based IUT and WLR can properly adjust for confounding covariates, and the Type I error rates of the proposed methods are well protected, with the IUT being more powerful than the WLR. Our methods demonstrate the strongly significant effects of hepatitis B or C on the risk of liver cancer mediated through liver cirrhosis incidence in a prospective cohort study. The proposed method is also applicable to surrogate endpoint analyses in clinical trials.

Genome-wide multimediator analyses using the generalized Berk-Jones statistics with the composite test.

MOTIVATION: Mediation analysis is performed to evaluate the effects of a hypothetical causal mechanism that marks the progression from an exposure, through mediators, to an outcome. In the age of high-throughput technologies, it has become routine to assess numerous potential mechanisms at the genome or proteome scales. Alongside this, the necessity to address issues related to multiple testing has also arisen. In a sparse scenario where only a few genes or proteins are causally involved, conventional methods for assessing mediation effects lose statistical power because the composite null distribution behind this experiment cannot be attained. The power loss hence decreases the true mechanisms identified after multiple testing corrections. To fairly delineate a uniform distribution under the composite null, Huang (Genome-wide analyses of sparse mediation effects under composite null hypotheses. Ann Appl Stat 2019a;13:60-84; AoAS) proposed the composite test to provide adjusted P-values for single-mediator analyses. RESULTS: Our contribution is to extend the method to multimediator analyses, which are commonly encountered in genomic studies and also flexible to various biological interests. Using the generalized Berk-Jones statistics with the composite test, we proposed a multivariate approach that favors dense and diverse mediation effects, a decorrelation approach that favors sparse and consistent effects, and a hybrid approach that captures the edges of both approaches. Our analysis suite has been implemented as an R package MACtest. The utility is demonstrated by analyzing the lung adenocarcinoma datasets from The Cancer Genome Atlas and Clinical Proteomic Tumor Analysis Consortium. We further investigate the genes and networks whose expression may be regulated by smoking-induced epigenetic aberrations. AVAILABILITY AND IMPLEMENTATION: An R package MACtest is available on https://github.com/roqe/MACtest.

Unified semicompeting risks analysis of hepatitis natural history through mediation modeling.

Natural history of hepatitis B or C is comprised of multiple milestones such as liver cirrhosis and liver cancer. To fully characterize its natural course, semicompeting risks represent a common problem where liver cirrhosis and liver cancer are both of interest, but only the former may be censored by the latter. Copula, frailty and multistate models serve as well-established analytics for semicompeting risks. Here, we cast the semicompeting risks in a mediation framework, with liver cirrhosis as a mediator and liver cancer as an outcome. We define the indirect and direct effects as the effects of an exposure on the liver cancer incidence mediated and not mediated through liver cirrhosis, respectively. With the estimands derived as conditional probabilities, we derive respective expressions under the copula, frailty, and multistate models. Next, we propose estimators based on nonparametric maximum likelihood or U-statistics and establish their asymptotic results. Numerical studies demonstrate that the efficiency of copula models leads to potential bias due to model misspecification. Moreover, the robustness of frailty models is accompanied by a loss in efficiency, and multistate models balance the efficiency and robustness. We demonstrate the utility of the proposed methods by a hepatitis study, showing that hepatitis B and C lead to a higher incidence of liver cancer by increasing liver cirrhosis incidence. Thus, mediation modeling provides a unified framework that accommodates various semicompeting risks models.

Effectiveness of entecavir vs tenofovir disoproxil fumarate for functional cure of chronic hepatitis B in an international cohort.

INTRODUCTION: Both entecavir (ETV) and tenofovir disoproxil fumarate (TDF) are first-line therapies for chronic hepatitis B (CHB), but their comparative effectiveness with regards to hepatitis B surface antigen (HBsAg) seroclearance remains unclear. METHODS: This international multicenter cohort study enrolled 7697 treatment-naïve CHB patients (median age 50 years; male 66.75%) initiated on either ETV (n = 5430) or TDF (n = 2267) without baseline malignancy or immunosuppression from 23 centers across 10 countries or regions. Patients were observed for HBsAg seroclearance until death, loss to follow-up, or treatment discontinuation or switching. The incidences of HBsAg seroclearance were adjusted for competing mortality and compared between ETV and TDF cohorts with inverse probability of treatment weighting (IPTW) and also by multivariable regression analysis. RESULTS: The study population was followed up for a median duration of 56.1 months with 36,929 11 person-years of observation. HBsAg seroclearance occurred in 70 ETV-treated and 21 TDF-treated patients, yielding 8-year cumulative incidence of 1.69% (95% confidence interval [CI] 1.32-2.17) for ETV and 1.34% (95% CI 0.85-2.10%), for TDF (p = 0.58). In the IPTW analysis with the two study cohorts more balanced in background covariates, the age-adjusted hazard ratio (HR) of TDF versus ETV for HBsAg seroclearance was 0.91 (95% CI 0.50-1.64; p = 0.75). Furthermore, there was no significant difference between the two medications in the multivariable competing risk regression model (adjusted sub-distributional HR 0.92 for TDF vs. ETV; 95% CI 0.56-1.53; p = 0.76). CONCLUSIONS: ETV and TDF did not differ significantly in the incidence of HBsAg seroclearance, which rarely occurred with either regimen.

Assisted Reproductive Technology and Risk of Childhood Cancers.

Importance: The number of children born through the use of assisted reproductive technology (ART) has been increasing. These children may have higher risks for epigenetic alteration and adverse perinatal outcomes, which may be associated with childhood cancers. Objective: To determine the associations between different modes of conception and childhood cancers and potential mediation by preterm birth and low birth weight. Design, Setting, and Participants: This nationwide, population-based cohort study included registry data from 2 308 016 eligible parents-child triads in Taiwan from January 1, 2004, to December 31, 2017. A total of 1880 children with incident childhood cancer were identified. Data were analyzed between September 1, 2020, and June 30, 2022. Exposure: Mode of conception, defined as (1) natural conception, (2) subfertility and non-ART (ie, infertility diagnosis but no ART-facilitated conception), or (3) ART (ie, infertility diagnosis and ART-facilitated conception). Main Outcomes and Measures: Diagnosis of childhood cancer according to the International Classification of Childhood Cancers, Third Edition. Results: The mean (SD) paternal and maternal ages were 33.28 (5.07) and 30.83 (4.56) years, respectively. Of the 2 308 016 children, 52.06% were boys, 8.16% were born preterm, and 7.38% had low birth weight. During 14.9 million person-years of follow-up (median, 6 years [IQR, 3-10 years]), ART conception was associated with an increased risk of any type of childhood cancers compared with natural conception (hazard ratio, 1.58; 95% CI, 1.17-2.12) and subfertility with non-ART conception (hazard ratio, 1.42; 95% CI, 1.04-1.95). The increased cancer risk of children conceived with ART was mainly owing to leukemia and hepatic tumor. The increased cancer risk associated with ART conception was not mediated by preterm birth or low birth weight. Conclusions and Relevance: In this cohort study, children conceived via ART had a higher risk of childhood cancers than those conceived naturally and those born to parents with an infertility diagnosis did not use ART. The increased risk could not be explained by preterm birth or low birth weight.

Path-specific effects in the presence of a survival outcome and causally ordered multiple mediators with application to genomic data.

Causal multimediation analysis (i.e. the causal mediation analysis with multiple mediators) is critical for understanding the effectiveness of interventions, especially in medical research. Deriving the path-specific effects of exposure on the outcome through a set of mediators can provide detail about the causal mechanism of interest However, existing models are usually restricted to partial decomposition, which can only be used to evaluate the cumulative effect of several paths. In genetics studies, partial decomposition fails to reflect the real causal effects mediated by genes, especially in complex gene regulatory networks. Moreover, because of the lack of a generalized identification procedure, the current multimediation analysis cannot be applied to the estimation of path-specific effects for any number of mediators. In this study, we derive the interventional analogs of path-specific effect for complete decomposition to address the difficulty of nonidentifiability. On the basis of two survival models of the outcome, we derive the generalized analytic forms for interventional analogs of path-specific effects by assuming the normal distributions of mediators. We apply the new methodology to investigate the causal mechanism of signature genes in lung cancer based on the cell cycle pathway, and the results clarify the gene pathway in cancer.

Familial aggregation and shared genetic loading for major psychiatric disorders and type 2 diabetes.

AIMS/HYPOTHESIS: Psychiatric disorders, such as schizophrenia (SCZ), major depressive disorder (MDD) and bipolar disorder (BPD), are highly comorbid with type 2 diabetes. However, the mechanisms underlying such comorbidity are understudied. This study explored the familial aggregation of common psychiatric disorders and type 2 diabetes by testing family history association, and investigated the shared genetic loading between them by testing the polygenic risk score (PRS) association. METHODS: A total of 105,184 participants were recruited from the Taiwan Biobank, and genome-wide genotyping data were available for 95,238 participants. The Psychiatric Genomics Consortium-derived PRS for SCZ, MDD and BPD was calculated. Logistic regression was used to estimate the OR with CIs between a family history of SCZ/MDD/BPD and a family history of type 2 diabetes, and between the PRS and the risk of type 2 diabetes. RESULTS: A family history of type 2 diabetes was associated with a family history of SCZ (OR 1.23, 95% CI 1.08, 1.40), MDD (OR 1.19, 95% CI 1.13, 1.26) and BPD (OR 1.26, 95% CI 1.15, 1.39). Compared with paternal type 2 diabetes, maternal type 2 diabetes was associated with a higher risk of a family history of SCZ. SCZ PRS was negatively associated with type 2 diabetes in women (OR 0.92, 95% CI 0.88, 0.97), but not in men; the effect of SCZ PRS reduced after adjusting for BMI. MDD PRS was positively associated with type 2 diabetes (OR 1.04, 95% CI 1.00, 1.07); the effect of MDD PRS reduced after adjusting for BMI or smoking. BPD PRS was not associated with type 2 diabetes. CONCLUSIONS/INTERPRETATION: The comorbidity of type 2 diabetes with psychiatric disorders may be explained by shared familial factors. The shared polygenic loading between MDD and type 2 diabetes implies not only pleiotropy but also a shared genetic aetiology for the mechanism behind the comorbidity. The negative correlation between polygenic loading for SCZ and type 2 diabetes implies the role of environmental factors.

Hypothesis test for causal mediation of time-to-event mediator and outcome.

Hepatitis B has been a well-documented risk factor of liver cancer and mortality. To what extent hepatitis B affects mortality through increasing liver cancer incidence is of research interest and remains to be studied. We formulate the research question as a hypothesis testing problem of causal mediation where both the mediator and the outcome are time-to-event variables. The problem is closely related to semicompeting risks because time to the intermediate event may be censored by an occurrence of the outcome. We propose two hypothesis testing methods: a weighted log-rank test (WLR) and an intersection-union test (IUT). A test statistic of the WLR is constructed by adapting a nonparametric estimator of the mediation effect; however, the test may be conservative regarding its Type I Error rate. To address this, we further propose the IUT, the test statistic of which is constructed under the composite null hypothesis. Asymptotic properties of the two tests are studied, showing that the IUT is a size α test with better statistical power than the WLR. The theoretical properties are supported by extensive simulation studies under finite samples. Applying the proposed methods to the motivating hepatitis study, both WLR and IUT provided strong evidence that hepatitis B had a significant mediation effect on mortality via liver cancer incidence.

Inhibition of Viral Replication Reduces Transcriptionally Active Distinct Hepatitis B Virus Integrations With Implications on Host Gene Dysregulation.

BACKGROUND & AIMS: Hepatocellular carcinogenesis of hepatitis B virus (HBV) infection may arise from integration of viral DNA into the host genome. We aimed to gauge the effect of viral inhibition on transcriptionally active HBV-host integration events and explore the correlation of viral integrations with host gene dysregulation. METHODS: We leveraged data and biospecimens from an interventional trial, in which patients with HBV viremia above 2000 IU/mL and minimally raised serum liver enzyme were randomized to receive tenofovir disoproxil fumarate (TDF) or placebo for 3 years. Total RNA-sequencing was performed on paired liver biopsies taken before and after the 3-year intervention in 119 patients. Virus-host chimeric reads were captured to quantify the number of distinct viral integrations. Dysregulation of a host gene disrupted by viral integration was defined by aberrant expression >2 standard deviations away from samples without viral integration. RESULTS: The TDF (n = 64) and placebo groups (n = 55) were comparable at baseline. Expressed viral integrations were detected in all pre- and posttreatment samples. The number of distinct viral integrations significantly correlated with circulatory biomarkers indicative of viral activities including HBV DNA, RNA, and viral antigens (P < .0003 for all correlations). Moreover, TDF vs placebo achieved a significantly greater reduction in distinct viral integrations, with 3.28-fold and 1.81-fold decreases in the expressed integrations per million reads, respectively (analysis of covariance, P = .037). Besides, viral integrations significantly correlated with host gene dysregulation. CONCLUSION: Inhibition of viral replication reduces the number of transcriptionally active distinct HBV-host DNA integrations in patients with substantial viremia. Given the mutagenic potentials of viral integrations, such treatment effects should be considered in patient management.

NK cell receptor and ligand composition influences the clearance of SARS-CoV-2.

To explore how the immune system controls clearance of SARS-CoV-2, we used a single-cell, mass cytometry-based proteomics platform to profile the immune systems of 21 patients who had recovered from SARS-CoV-2 infection without need for admission to an intensive care unit or for mechanical ventilation. We focused on receptors involved in interactions between immune cells and virus-infected cells. We found that the diversity of receptor repertoires on natural killer (NK) cells was negatively correlated with the viral clearance rate. In addition, NK subsets expressing the receptor DNAM1 were increased in patients who more rapidly recovered from infection. Ex vivo functional studies revealed that NK subpopulations with high DNAM1 expression had cytolytic activities in response to target cell stimulation. We also found that SARS-CoV-2 infection induced the expression of CD155 and nectin-4, ligands of DNAM1 and its paired coinhibitory receptor TIGIT, which counterbalanced the cytolytic activities of NK cells. Collectively, our results link the cytolytic immune responses of NK cells to the clearance of SARS-CoV-2 and show that the DNAM1 pathway modulates host-pathogen interactions during SARS-CoV-2 infection.

Causal mediation of semicompeting risks.

The semi-competing risks problem arises when one is interested in the effect of an exposure or treatment on both intermediate (e.g., having cancer) and primary events (e.g., death) where the intermediate event may be censored by the primary event, but not vice versa. Here we propose a nonparametric approach casting the semi-competing risks problem in the framework of causal mediation modeling. We set up a mediation model with the intermediate and primary events, respectively as the mediator and the outcome, and define an indirect effect as the effect of the exposure on the primary event mediated by the intermediate event and a direct effect as that not mediated by the intermediate event. A nonparametric estimator with time-varying weights is proposed for direct and indirect effects where the counting process at time t of the primary event N2n1(t) and its compensator An1(t) are both defined conditional on the status of the intermediate event right before t, N1(t-)=n1 . We show that N2n1(t)-An1(t) is a zero-mean martingale. Based on this, we further establish theoretical properties for the proposed estimators. Simulation studies are presented to illustrate the finite sample performance of the proposed method. Its advantage in causal interpretation over existing methods is also demonstrated in a hepatitis study.

Application of Risk Scores for Hepatocellular Carcinoma in Patients with Chronic Hepatitis B: Current Status and Future Perspective.

Accurate risk prediction for hepatocellular carcinoma (HCC) among patients with chronic hepatitis B (CHB) may guide treatment strategies including initiation of antiviral therapy and also inform implementation of HCC surveillance. There have been 26 risk scores developed to predict HCC in CHB patients with (n = 14) or without (n = 12) receiving antiviral treatment; all of them invariably include age in the scoring formula. Virological biomarkers of replicative activities (i.e., hepatitis B virus DNA level or hepatitis B envelope antigen status) are frequently included in the scores derived from patients with untreated CHB, whereas measurements that gauge severity of liver fibrosis and/or reserve of hepatic function (i.e., cirrhosis diagnosis, liver stiffness measurement, platelet count, or albumin) are essential components in the scores developed from treated patients. External validation is a prerequisite for clinical application but not yet performed for all scores. For the future, higher predictive accuracy may be achieved with machine learning based on more comprehensive data.

G-Computation to Causal Mediation Analysis With Sequential Multiple Mediators-Investigating the Vulnerable Time Window of HBV Activity for the Mechanism of HCV Induced Hepatocellular Carcinoma.

Regression-based approaches are widely used in causal mediation analysis. The presence of multiple mediators, however, increases the complexity and difficulty of mediation analysis. In such cases, regression-based approaches cannot efficiently address estimation issues. Hence, a flexible approach to mediation analysis is needed. Therefore, we developed a method for using g-computation algorithm to conduct causal mediation analysis in the presence of multiple ordered mediators. Compared to regression-based approaches, the proposed simulation-based approach increases flexibility in the choice of models and increases the range of the outcome scale. The Taiwanese Cohort Study dataset was used to evaluate the efficacy of the proposed approach for investigating the mediating role of early and late HBV viral load in the effect of HCV infection on hepatocellular carcinoma (HCC) in HBV seropositive patients (n = 2,878; HCV carrier n = 123). Our results indicated that early HBV viral load had a negative mediating role in HCV-induced HCC. Additionally, early exposure to a low HBV viral load affected HCC through a lag effect on HCC incidence [OR = 0.873, 95% CI = (0.853, 0.893)], and the effect of early exposure to a low HBV viral load on HCC incidence was slightly larger than that of a persistently low viral load on HCC incidence [OR = 0.918, 95% CI = (0.896, 0.941)].

Epidemiology of Virus Infection and Human Cancer.

Seven viruses including the Epstein-Barr virus (EBV), hepatitis B virus (HBV), hepatitis C virus (HCV), Kaposi's sarcoma herpes virus (KSHV), human immunodeficiency virus, type-1 (HIV-1), human T cell lymphotrophic virus, type-1 (HTLV-1), and human papillomavirus (HPV) have been classified as Group 1 human carcinogens by the International Agency for Research on Cancer (IARC). The conclusions are based on the findings of epidemiological and mechanistic studies. EBV, HPV, HTLV-1, and KSHV are direct carcinogens; HBV and HCV are indirect carcinogens through chronic inflammation; and HIV-1 is an indirect carcinogen through immune suppression. Some viruses may cause more than one cancer, while some cancers may be caused by more than one virus. However, only a proportion of persons infected by these oncogenic viruses will develop specific cancers. A series of studies have been carried out to assess the viral, host, and environmental cofactors of EBV-associated nasopharyngeal carcinoma, HBV/HCV-associated hepatocellular carcinoma, and HPV-associated cervical carcinoma. Persistent infection, high viral load, and viral genotype are important risk predictors of these virus-caused cancers. Risk calculators incorporating host and viral risk predictors have been developed for the prediction of long-term risk of hepatocellular carcinoma, nasopharyngeal carcinoma and cervical cancer. These risk calculators are useful for the triage and clinical management of infected patients. Both clinical trials and national programs of immunization, antiviral therapy and screening have demonstrated a significant reduction in the incidence of cancers caused by HBV, HCV, and HPV. Future research on gene-gene and gene-environment interactions of oncogenic viruses and the human host using large-scale longitudinal studies with serial measurements of biosignatures are in urgent need.

Multi-kinase framework promotes proliferation and invasion of lung adenocarcinoma through activation of dynamin-related protein 1.

Recent studies revealed the role of dynamin-related protein 1 (DRP1), encoded by the DNM1L gene, in regulating the growth of cancer cells of various origins. However, the regulation, function, and clinical significance of DRP1 remain undetermined in lung adenocarcinoma. Our study shows that the expression and activation of DRP1 are significantly correlated with proliferation and disease extent, as well as an increased risk of postoperative recurrence in stage I to stage IIIA lung adenocarcinoma. Loss of DRP1 in lung adenocarcinoma cell lines leads to an altered mitochondrial morphology, fewer copies of mitochondrial DNA, decreased respiratory complexes, and impaired oxidative phosphorylation. Additionally, the proliferation and invasion are both suppressed in DRP1-depleted lung adenocarcinoma cell lines. Our data further revealed that DRP1 activation through serine 616 phosphorylation is regulated by ERK/AKT and CDK2 in lung adenocarcinoma cell lines. Collectively, we propose the multikinase framework in activating DRP1 in lung adenocarcinoma to promote the malignant properties. Biomarkers related to mitochondrial reprogramming, such as DRP1, can be used to evaluate the risk of postoperative recurrence in early-stage lung adenocarcinoma.

Six-way decomposition of causal effects: Unifying mediation and mechanistic interaction.

The sufficient component cause (SCC) model and counterfactual model are two common methods for causal inference, each with their own advantages: the SCC model allows the mechanistic interaction to be detailed, whereas the counterfactual model features a systemic framework for quantifying causal effects. Hence, integrating the SCC and counterfactual models may facilitate the conceptualization of causation. Based on the marginal SCC (mSCC) model, we propose a novel counterfactual mSCC framework that includes the steps of definition, identification, and estimation. We further propose a six-way effect decomposition for assessing mediation and the mechanistic interaction. The results demonstrate that when all variables are binary, the six-way decomposition is an extension of four-way decomposition and that without agonism, the six-way decomposition is reduced to four-way decomposition. To illustrate the utility of the proposed decomposition, we apply it to a Taiwanese cohort to examine the mechanism of hepatitis C virus (HCV)-induced hepatocellular carcinoma (HCC) with liver inflammation measured by alanine aminotransferase (ALT) as a mediator. Among the HCV-induced HCC cases, 62.27% are not explained by either mediation or interaction in relation to ALT; 9.32% are purely mediated by ALT; 16.53% are caused by the synergistic effect of HCV and ALT; and 9.31% are due to the mediated synergistic effect of HCV and ALT. In summary, we introduce an SCC model framework based on counterfactual theory and detail the required identification assumptions and estimation procedures; we also propose a six-way effect decomposition to unify mediation and mechanistic interaction analyses.

Cigarette smoking increases the risk of nasopharyngeal carcinoma through the elevated level of IgA antibody against Epstein-Barr virus capsid antigen: A mediation analysis.

BACKGROUND: The study aims are to evaluate the associations between nasopharyngeal carcinoma (NPC) risk and cigarette smoking and to explore the effects of cigarette smoking on Epstein-Barr virus (EBV) infection for NPC risk. METHODS: 1235 male NPC cases and 1262 hospital-based male controls matched to cases were recruited across six collaborative hospitals between 2010 and 2014. Using a standardized questionnaire, information on cigarette smoking and other potential risk factors for NPC was obtained. Blood was collected and used for anti-EBV VCA IgA and anti-EBV EA-EBNA1 IgA testing using standard methods. Unconditional logistic regression analysis was used to estimate odds ratio (OR) with 95% confidence interval (CI) for each risk factor after adjusting for confounders. RESULTS: 63.6% of cases and 44.0% of controls reported ever smoking cigarettes. After full adjustment, current smokers had a significant 1.60-fold (95% CI = 1.30-1.97) and former smokers a borderline significant 1.27-fold (95% CI = 1.00-1.60) increased NPC risk compared to never smokers. NPC risk increased with increasing duration, intensity, and pack-years of cigarette smoking but not with age at smoking initiation. Among controls, anti-EBV VCA IgA seropositivity rate was higher in current smokers than never smokers (14.0% vs 8.4%; OR = 1.82; 95% CI = 1.19-2.79). Mediation analyses showed that more than 90% of the cigarette smoking effect on NPC risk is mediated through anti-EBV VCA IgA. CONCLUSION: This study confirms the association between long-term cigarette smoking and NPC and demonstrates that current smoking is associated with seropositivity of anti-EBV VCA IgA antibodies.

Tenofovir Versus Entecavir for Hepatocellular Carcinoma Prevention in an International Consortium of Chronic Hepatitis B.

INTRODUCTION: It is unclear whether entecavir (ETV) and tenofovir disoproxil fumarate (TDF) differ in their effectiveness for preventing hepatocellular carcinoma (HCC) in patients with chronic hepatitis B (CHB). METHODS: This retrospective cohort study analyzed an international consortium that encompassed 19 centers from 6 countries or regions composed of previously untreated CHB patients then treated with either ETV or TDF monotherapy. Those who developed HCC before antiviral treatment or within 1 year of therapy were excluded. The association between antiviral regimen and HCC risk was evaluated using competing-risk survival regression. We also applied propensity score matching (PSM) to 1:1 balance the 2 treatment cohorts. A total of 5,537 patients were eligible (n = 4,837 received ETV and n = 700 received TDF) and observed for HCC occurrence until December 23, 2018. Before PSM, the TDF cohort was significantly younger and had generally less advanced diseases. RESULTS: In the unadjusted analysis, TDF was associated with a lower risk of HCC (subdistribution hazard ratio [SHR], 0.45; 95% confidence interval [CI], 0.26-0.79; P = 0.005). The multivariable analysis, however, found that the association between TDF and HCC no longer existed (SHR, 0.81; 95% CI, 0.42-1.56; P = 0.52) after adjustment for age, sex, country, albumin, platelet, α-fetoprotein, cirrhosis, and diabetes mellitus. Furthermore, the PSM analysis (n = 1,040) found no between-cohort differences in HCC incidences (P = 0.51) and no association between regimens (TDF or ETV) and HCC risk in the multivariable-adjusted analysis (adjusted SHR, 0.89; 95% CI, 0.41-1.92; P = 0.77). DISCUSSION: TDF and ETV did not significantly differ in the prevention of HCC in patients with CHB.