Forecasting annual incidence and mortality rate for prostate cancer in Australia until 2022 using autoregressive integrated moving average (ARIMA) models
Objectives 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 t...
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| Format: | Article |
| Language: | English |
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BMJ Publishing Group
2019-08-01
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| Series: | BMJ Open |
| Online Access: | https://bmjopen.bmj.com/content/9/8/e031331.full |
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| author | Sue M Evans Arul Earnest Fanny Sampurno Jeremy Millar |
| author_facet | Sue M Evans Arul Earnest Fanny Sampurno Jeremy Millar |
| author_sort | Sue M Evans |
| collection | DOAJ |
| description | Objectives 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.Design 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.Results 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).Conclusion 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. |
| format | Article |
| id | doaj-art-86ce243b5c1141a995e853ea518f9ccc |
| institution | DOAJ |
| issn | 2044-6055 |
| language | English |
| publishDate | 2019-08-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | BMJ Open |
| spelling | doaj-art-86ce243b5c1141a995e853ea518f9ccc2025-08-20T02:48:09ZengBMJ Publishing GroupBMJ Open2044-60552019-08-019810.1136/bmjopen-2019-031331Forecasting annual incidence and mortality rate for prostate cancer in Australia until 2022 using autoregressive integrated moving average (ARIMA) modelsSue M Evans0Arul Earnest1Fanny Sampurno2Jeremy Millar31 Monash University Faculty of Medicine, Nursing and Health Sciences, Melbourne, Victoria, AustraliaSchool of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia1 Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia8 Radiation Oncology, Alfred Health, Melbourne, Victoria, AustraliaObjectives 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.Design 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.Results 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).Conclusion 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.https://bmjopen.bmj.com/content/9/8/e031331.full |
| spellingShingle | Sue M Evans Arul Earnest Fanny Sampurno Jeremy Millar Forecasting annual incidence and mortality rate for prostate cancer in Australia until 2022 using autoregressive integrated moving average (ARIMA) models BMJ Open |
| title | Forecasting annual incidence and mortality rate for prostate cancer in Australia until 2022 using autoregressive integrated moving average (ARIMA) models |
| title_full | Forecasting annual incidence and mortality rate for prostate cancer in Australia until 2022 using autoregressive integrated moving average (ARIMA) models |
| title_fullStr | Forecasting annual incidence and mortality rate for prostate cancer in Australia until 2022 using autoregressive integrated moving average (ARIMA) models |
| title_full_unstemmed | Forecasting annual incidence and mortality rate for prostate cancer in Australia until 2022 using autoregressive integrated moving average (ARIMA) models |
| title_short | Forecasting annual incidence and mortality rate for prostate cancer in Australia until 2022 using autoregressive integrated moving average (ARIMA) models |
| title_sort | forecasting annual incidence and mortality rate for prostate cancer in australia until 2022 using autoregressive integrated moving average arima models |
| url | https://bmjopen.bmj.com/content/9/8/e031331.full |
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