CAJ | 학술논문

目的预测海门市男性肝癌死亡趋势,并定量描述肝癌死亡率的年龄、时期和出生队列特征.方法应用男性肝癌1993-2006年的年龄标化死亡率(SMR)构建GM(1,1)模型,预测SMR至2012年.同时,以每4年为一间隔的肝癌死亡密度(MD)拟合年龄-时期-队列(age-period-cohort,APC)模型的梯度模型,并进行模型拟合优度评价和模型比较,筛选最优模型;根据APC全模型和最优模型的拟合结果评估年龄、时期和出生队列效应;利用最优模型预测MD至2012年.结果根据构建的GM(1,1)残差修正模型对SMR进行预测,结果显示,2007年SMR预测值为48.578/10万,相对误差为-1.267%;2008-2012年男性SMR轻微下降,最低值为45.578/10万(2012年).APC梯度模型拟合优度检验及模型比较结果显示,年龄-时期模型为最优模型(△G2=9.065,AIC=202.544).APC模型的曲率估计结果显示,曲率改变显著的年龄组为36.5～40.5岁(-0.368)和64.5～68.5岁(-0.489),队列作用的曲率改变主要发生在1956-1959年(C2 1949.5,1967.5=-0.492);年龄-时期模型的分层相对危险度估计结果显示,随年龄增加,年龄效应呈升高趋势,至64.5～68.5岁组后开始下降;时期越晚相对危险度越低.年龄-时期模型的预测结果显示2005-2012年肝癌死亡率呈下降趋势.结论年龄、时期和部分队列效应可以预测肝癌死亡率趋势;未来几年肝癌死亡率会略微下降,但仍处于较高发病状态.
목적 예측해문시남성간암사망추세,병정량묘술간암사망솔적년령、시기화출생대렬특정.방법 응용남성간암1993-2006년적년령표화사망솔(SMR)구건GM(1,1)모형,예측SMR지2012년.동시,이매4년위일간격적간암사망밀도(MD)의합년령-시기-대렬(age-period-cohort,APC)모형적제도모형,병진행모형의합우도평개화모형비교,사선최우모형;근거APC전모형화최우모형적의합결과평고년령、시기화출생대렬효응;이용최우모형예측MD지2012년.결과 근거구건적GM(1,1)잔차수정모형대SMR진행예측,결과현시,2007년SMR예측치위48.578/10만,상대오차위-1.267%;2008-2012년남성SMR경미하강,최저치위45.578/10만(2012년).APC제도모형의합우도검험급모형비교결과현시,년령-시기모형위최우모형(△G2=9.065,AIC=202.544).APC모형적곡솔고계결과현시,곡솔개변현저적년령조위36.5～40.5세(-0.368)화64.5～68.5세(-0.489),대렬작용적곡솔개변주요발생재1956-1959년(C2 1949.5,1967.5=-0.492);년령-시기모형적분층상대위험도고계결과현시,수년령증가,년령효응정승고추세,지64.5～68.5세조후개시하강;시기월만상대위험도월저.년령-시기모형적예측결과현시2005-2012년간암사망솔정하강추세.결론 년령、시기화부분대렬효응가이예측간암사망솔추세;미래궤년간암사망솔회략미하강,단잉처우교고발병상태.
Objective To predict the trend of hepatocellular carcinoma (HCC) mortality and investigate the features of its mortality including age, period, and birth cohort in males living in Haimen city of Jiangsu province, China. Methods Grey model (GM) was modeled using standardized mortality rate (SMR) of HCC from 1993 to 2006, and was applied to predicting SMR until 2012. Based on the mortality density (MD) for a four-year period, the goodness-of-fit of models and comparisons between models were evaluated so as to obtain the best one among these models including the effects of intercept, age-period-cohort (APC) , age-period (AP), age-cohort (AC),period-cohort(PC), and APC. Both APC full model and the best model were used to estimate effects of age, period, and cohort on HCC mortality. In addition, MD from 2005 to 2012 was predicted by the best model. Results Predictions based on GM (1,1 )showed that SMR was 48.578 per 100 000 population (relative error=-1.267% ) in 2007 year, which declined between 2008 and 2012. The lowest value was 45.578 per 100 000 people (in the 2012 year). The results of fitted models and comparisons between models showed that AP model was the best one (△G2=9.065,AIC=202.544). The curvatures of the effects of the three factors from APC model suggested that significances existed in changes of curvatures of 36.5-40.5 years old- (-0.368) and 64.5-68.5 years old-(-0.489) as well as in the change of 1956-1959 birth cohort (C21949.5. 1967.5=-0.492). The estimation of relative risks for AP model showed that the age effects were upward to 64.5-68.5 years old-, then downward; and that the period effects were found to be declined between 1993 and 2004. Predictions based on AP model suggested the decrease of HCC mortality. Conclusion The slightly decreasing trend of HCC mortality for males might be explained by age, period and a minor birth cohort effects in Haimen of China.