A METHOD FOR THE ESTIMATION OF CHRONIC DISEASE MORBIDITY AND TRENDS FROM MORTALITY DATA
A METHOD FOR THE ESTIMATION OF CHRONIC DISEASE MORBIDITY AND TRENDS FROM MORTALITY DATA
复制标题
DOI：
10.1002/sim.4780080207
复制
发表时间：
1989-02-01
影响因子：
2
通讯作者：
GOLINI, A
中科院分区：
文献类型：
--
作者：
VERDECCHIA, A;CAPOCACCIA, R;GOLINI, A
慢性退行性疾病扩散的措施，如发病率和患病率，是流行病学家和其他人在人类科学的许多领域工作的基本需要。从队列的角度来看，慢性退行性疾病的发病率和生存概率的死亡概率方程。采用最大似然法估计作为时间相关协变量函数的发生率。当死亡率的时间序列数据可用时，该模型可以用来描述和分析发病率的水平和动态。肺癌和乳腺癌的试验应用是为意大利的瓦雷塞省提供的，那里的发病率数据可从伦巴第癌症登记处获得。
Measures of chronic degenerative disease diffusion, such as incidence and prevalence rates, are a basic need for epidemiologists and others working in many fields of human sciences. Equations relating death probabilities to incidence and survival probabilities for chronic degenerative diseases are derived from a cohort point of view. A maximum likelihood approach is adopted for the estimation of incidence as a function of time related covariates. When time series of mortality data are available, the model can be used to describe and analyze levels and dynamics of morbidity. A trial application to lung and breast cancer is given for the province of Varese, Italy, where incidence data are available from the Lombardy Cancer Register.