2020
DOI: 10.1093/ije/dyaa196
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Global trend of aetiology-based primary liver cancer incidence from 1990 to 2030: a modelling study

Abstract: Background Predictions of primary liver cancer (PLC) incidence rates and case numbers are critical to understand and plan for PLC disease burden. Methods Data on PLC incidence rates and case numbers from 1990 to 2017 were retrieved from the Global Burden of Disease database. The estimated average percentage change (EAPC) was calculated to quantify the trends of PLC age-standardized incidence rates (ASRs). Bayesian age-period-… Show more

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Cited by 62 publications
(54 citation statements)
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“…EAPC is a summative and widely used measure for rate trends over specified intervals, which was calculated according to a regression model fitted to the natural logarithm of the rate, namely ln (rate) = a + b × (calendar year) + e, and EAPC was defined as 100 × (exp (b) −1). Its 95% confidence interval (95% CI) was also obtained from the linear regression model (23). The rate was deemed to be increased if the EAPC estimation and the lower boundary of its 95% CI were both >0.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…EAPC is a summative and widely used measure for rate trends over specified intervals, which was calculated according to a regression model fitted to the natural logarithm of the rate, namely ln (rate) = a + b × (calendar year) + e, and EAPC was defined as 100 × (exp (b) −1). Its 95% confidence interval (95% CI) was also obtained from the linear regression model (23). The rate was deemed to be increased if the EAPC estimation and the lower boundary of its 95% CI were both >0.…”
Section: Discussionmentioning
confidence: 99%
“…Previously, several methods have been used to predict cancer incidence based on population data, including the age-periodcohort (APC) model, Nordpred model, Bayesian age-periodcohort (BAPC) model, Bayesian age-period-cohort modeling, and prediction (BAMP) model, and Poisson regression (23)(24)(25)(26). Comparative studies based on these methods have demonstrated that age-period-cohort approaches have better predictive performance than time series approaches, especially, the probabilistic forecasts obtained by the Bayesian APC model are well calibrated and not too wide (27,28).…”
Section: Discussionmentioning
confidence: 99%
“…Despite the availability of direct-acting antivirals, chronic hepatitis C virus (HCV) infection still represents a major cause of liver disease and cirrhosis, a condition at high risk for HCC development [2,3]. It has been calculated that 2.5% of patients affected by chronic HCV infection develop HCC [4], and the incidence rate of HCC is expected to further increase between 2018 and 2030 [5].…”
Section: Introductionmentioning
confidence: 99%
“…According to the etiology of liver disease, HBV was responsible for 46.5% of cases of liver cancer in 1990 and 42.4% in 2017, and it is estimated that it will be associated with 40.7% of cases in 2030. With regard to HCV, it was associated with 25.2% of cases of primary liver cancer in 1990 and 27.0% in 2017, and it is projected that it will be responsible for 26.8% of cases in 2030[ 13 ]. The aim of this article is to review the current impact of viral hepatitis on the development of liver cancer, the characteristics of viral hepatitis-related HCC and the challenges to reduce their burden (Figure 1 ).…”
Section: Introductionmentioning
confidence: 99%