Demographic trends and projections of morbidity and mortality from cancer

On 25 September 2025, the National Medical Research Center of Oncology named after N.N. Petrov of the Ministry of Health of the Russian Federation held a webinar on "Demographic trends and projections of morbidity and mortality from cancer".

After a welcome speech by Ekaterina Nazarova, a physician in the analytical department and assistant in the continuing professional education department at the N. N. Petrov National Medical Research Center of Oncology, the following speakers took the floor:

Sergey Timonin, research fellow at the Australian National University and leading research fellow at the Russian Research Institute of Health, the topic of the presentation was “Age standardization of mortality rates: the impact of the choice of standard population”
Egor Sergeev, expert at the N. N. Petrov National Medical Research Center of Oncology, specialist at the Russian Research Institute of Health, and research assistant at the International Laboratory for Population and Health, and Alexey Shchur, senior research fellow at the International Laboratory for Population and Health and chief specialist at the Russian Research Institute of Health, the topic of the presentation was “Approaches to assessing the contribution of causes of death to life expectancy level and dynamics”
Gleb Marychev, research assistant at the International Laboratory for Population and Health, the topic of the presentation was “Spatial and temporal comparability of cause-of-death mortality in Russia: a demographer's perspective.”

Age standardization of mortality rates

Sergey Timonin spoke about how to measure mortality, including from cancer, at the population level. In his report, he focused on the need to standardize mortality rates by age to obtain estimates of the mortality that are free of the influence of the age structure of the population. However, in direct standardization of mortality rates, it matters what standard population is used.

Currently, several supranational standards for age structure are widely used in international practice, such as the 1960 World Standard or the 2013 European Standard. For Russian practice, it is proposed to use the Russian national standard population of 2025, obtained by analyzing the age structure of the Russian population in 2002, 2010, and 2020(2021*), as well as forecasts up to 2035.

Although the use of a specific standard population in a particular study makes it possible to accurately compare mortality rates between different populations or to study their dynamics, the choice of standard itself affects not only the value of standardized coefficients, but also their dynamics. Thus, when comparing standardized mortality rates from cancer in Russia, calculated on the basis of different population standards, the lowest values are obtained for the 1960 World Standard due to the larger proportion of young people in it. The highest values of the standardized coefficient for cancer were obtained using the 2013 European Standard, followed by the proposed Russian standard. However, compared to the Russian standard, the rate of decline in mortality from cancer between 1965 and 2014 based on the European standard is lower. Thus, the use of the Russian national standard population for 2025 in analyzing the magnitude and dynamics of mortality from cancer allows, on the one hand, to obtain mortality estimates that are not as low as those based on the 1960 World Standard and, on the other hand, to obtain more positive mortality dynamics compared to the 2013 European Standard.

Causes of death and life expectancy

Egor Sergeev and Alexey Shchur discussed another widely used measure of mortality – life expectancy. Of particular interest is the relationship between specific causes of death and life expectancy at birth; the report demonstrated two main approaches to assessing the impact of mortality from a given cause of death on life expectancy.

The first approach—decomposition—allows us to explain how changes in the level (and age profile) of mortality from a specific cause or group of causes of death have affected life expectancy. For example, life expectancy at birth for men in Russia increased from 58.9 years in 2005 to 68.3 years in 2019, but the decline in mortality from cancer accounts for only 0.44 years of the total increase in life expectancy. Cardiovascular diseases account for the largest increase (3.8 years), followed by external causes of death (3.5 years). However, when comparing life expectancy between men and women in 2019, the role of cancer becomes more apparent. Thus, mortality from cancer accounts for 1.3 years of the 9.8-year difference in life expectancy, mainly due to the fact that mortality from cancer among women is significantly lower than among men aged 50–84. However, the contribution of the 30–44 age group is the opposite: at these ages, there is a high mortality rate among women from cancers specific to women (cervical cancer, breast cancer, etc.).

The second approach—the method of eliminating mortality from a single cause—allows us to answer the question of what life expectancy would be if mortality from a single cause were completely or partially eliminated. In this case, for life expectancy, cancer becomes a more significant cause of death than external causes, even among men, although cardiovascular diseases remain the absolute leader. Thus, if mortality from cancer among men were eliminated, the increase in life expectancy in 2019 would be 2.9 years; if mortality from external causes were eliminated, it would be 2.8 years; and if mortality from diseases of the circulatory system were eliminated, it would be 10.1 years.

Comparability of cause-specific mortality between Russian regions and over time

When analyzing cause-specific mortality, it is important to understand how the relevant statistics are compiled. Gleb Marychev discussed the differences in determining the initial cause of death between regions in Russia and how these differences change over time.

With the use of an indirect regression method, an assessment was made of the degree of interregional heterogeneity in practices for establishing (coding) the initial cause of death for 2000–2004, 2005–2009, 2010–2014, and 2015–2019 for each of the 67 selected causes of death that are most important from a clinical and healthcare organization perspective. Overall, the highest level of homogeneity in coding practices for the entire period 2000–2019 is demonstrated by the class of neoplasms for both men and women, and certain causes of death from this class are among the most homogeneously used between regions.

However, some causes of death from the class of neoplasms can still be considered significantly heterogeneous in their coding. For example, high interregional differences are demonstrated by mortality from breast and liver cancer and benign tumours in men, as well as from cancer of the larynx, oesophagus, liver and bladder in women. During the discussion of the report, an explanation was proposed for the high heterogeneity of mortality from liver cancer: this location is characterised by frequent metastasis, which complicates the determination of the initial cause of death.

More details about the research by Gleb Marychev and his co-authors can be found in the pages of Demographic Review.