Earnest Arul, Evans Sue M, Sampurno Fanny, Millar Jeremy
Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
BMJ Open. 2019 Aug 19;9(8):e031331. doi: 10.1136/bmjopen-2019-031331.
Prostate cancer is the second most common cause of cancer-related death in males after lung cancer, imposing a significant burden on the healthcare system in Australia. We propose the use of autoregressive integrated moving average (ARIMA) models in conjunction with population forecasts to provide for robust annual projections of prostate cancer.
Data on the incidence and mortality from prostate cancer was obtained from the Australian Institute of Health and Welfare. We formulated several ARIMA models with different autocorrelation terms and chose one which provided for an accurate fit of the data based on the mean absolute percentage error (MAPE). We also assessed the model for external validity. A similar process was used to model age-standardised incidence and mortality rate for prostate cancer in Australia during the same time period.
The annual number of prostate cancer cases diagnosed in Australia increased from 3606 in 1982 to 20 065 in 2012. There were two peaks observed around 1994 and 2009. Among the various models evaluated, we found that the model with an autoregressive term of 1 (coefficient=0.45, p=0.028) as well as differencing the series provided the best fit, with a MAPE of 5.2%. External validation showed a good MAPE of 5.8% as well. We project prostate cancer incident cases in 2022 to rise to 25 283 cases (95% CI: 23 233 to 27 333).
Our study has accurately characterised the trend of prostate cancer incidence and mortality in Australia, and this information will prove useful for resource planning and manpower allocation.
前列腺癌是男性癌症相关死亡的第二大常见原因,仅次于肺癌,给澳大利亚的医疗保健系统带来了沉重负担。我们建议使用自回归积分移动平均(ARIMA)模型并结合人口预测,以对前列腺癌进行可靠的年度预测。
前列腺癌发病率和死亡率的数据来自澳大利亚卫生与福利研究所。我们构建了几个具有不同自相关项的ARIMA模型,并根据平均绝对百分比误差(MAPE)选择了一个能准确拟合数据的模型。我们还评估了该模型的外部有效性。在同一时期,采用类似的过程对澳大利亚前列腺癌的年龄标准化发病率和死亡率进行建模。
澳大利亚每年诊断出的前列腺癌病例数从1982年的3606例增加到2012年的20065例。在1994年和2009年左右观察到两个峰值。在评估的各种模型中,我们发现自回归项为1(系数 = 0.45,p = 0.028)且对序列进行差分的模型拟合效果最佳,MAPE为5.2%。外部验证显示MAPE也很好,为5.8%。我们预测2022年前列腺癌发病病例将增至25283例(95%CI:23233至27333)。
我们的研究准确地描述了澳大利亚前列腺癌发病率和死亡率的趋势,这些信息将有助于资源规划和人力分配。