ONLINE ANALYSIS > PREDICTIONS

These options allow computation of short and long term predictions of cancer mortality. Predictions are uncertain, and the results should always be interpreted with caution.The Section of Cancer Surveillance (CSU) at IARC does not accept any responsibility or liability in regard of the reliance on, and/or use of the results.
1. The countries available for analysis are those having mortality data available for at least 10 consecutive years.
2. The cancer dictionary is restricted to the cancer sites that are almost comparable overtime in term of ICD codes.
3. The forecast populations were extracted from the UN database.

Short term predictions (up to five years)

The short term predictions are computed using a program developed by M. Colombet, J. Ferlay and G. Byrnes at the IARC, based on T. Dyba and T. Hakulinen methods (see REFERENCES option).
For a selected combination of country, cancer, sex and a 'latest year' of observation, the age-period models require at least six consecutive years of data with at least 50 deaths (all ages) recorded per year. The results are presented by age groups and for all ages combined, together with their corresponding prediction interval. The change in the number of predicted cancer deaths to the latest year of observation is divided into one part due to change in risk of dying from cancer, and another one due to changes in the population size and age distribution. Graphical representations of the results are provided.

Long term predictions (more than five years)

Long term predictions are computed using the NORDPRED package developed by Harald Fekjær and Bjørn Møller at the Cancer Registry of Norway. For a selected combination of country, cancer, sex and a 'latest year' of observation, the model requires at least fifteen years of consecutive data (in order to build at least three 5-year periods), with at least 100 deaths (all ages) recorded per 5-year period. It can predict  up to five 5-year periods. The results are presented by age groups and for all ages combined. For each predicted period, the change in the number of predicted cancer deaths to the latest period of observation is divided into one part due to change in risk of dying from cancer, and another one due to changes in the population size and age distribution. Graphical representations of the results are provided.


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