Australian Childhood
Cancer Statistics Online

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Australian Childhood Cancer Statistics Online is an interactive platform that provides the latest statistics on childhood cancer incidence, mortality and survival for the most common cancers among children under the age of 15 in Australia. Key cancer statistics are available by sex and age group, along with trends in these statistics over time. Australian Childhood Cancer Statistics Online serves as a platform to raise awareness of childhood cancer among government bodies and the broader community. It provides accurate, up-to-date statistics about the burden of childhood cancer in the community, which can be used to support advocacy efforts and inform policy decisions. These statistics also have the potential to motivate and prioritize further research into the causes, prevention, and treatment of this rare but critical disease.

Data for the Australian Childhood Cancer Statistics Online are sourced from the Australian Childhood Cancer Registry (ACCR), funded and managed by Cancer Council Queensland. See Data Sources and Methodology below for further details.

Navigating Australian Childhood Cancer Statistics Online

Users can navigate Australian Childhood Cancer Statistics Online using the drop-down menu for cancer type within each of the incidence, mortality and survival pages. The statistics used to produce the graphs can be viewed by right-clicking anywhere in the graph and then selecting “Show as a table”.

Referencing the website

You are welcome and encouraged to use the information contained in this website, provided the source is appropriately acknowledged. A suggested citation is:

Australian Childhood Cancer Registry, Cancer Council Queensland. Australian Childhood Cancer Statistics Online (1983-2021). CCQ: Brisbane, Australia; October 2024.

Data sources and methodology

Data sources
Australian Bureau of Statistics (ABS)
The following information was obtained from the ABS:

  • Australian Standard Population (2001) – used in the calculation of age-standardised rates.(1) 
  • Estimated resident population – used as the denominator for calculating rates.(2) 
  • Population mortality data – used in relative survival calculations.(3) 

Australian Childhood Cancer Registry (ACCR)
The Australian Childhood Cancer Registry (ACCR) is a complete register of all childhood cancer cases (defined here as children between the ages of 0–14 years) diagnosed in Australia since 1983, excluding keratinocyte (non-melanoma) skin cancers. Managed by Cancer Council Queensland, it serves as a national resource supporting childhood cancer research and surveillance. The ACCR operates in collaboration with the Australasian Association of Cancer Registries, all Australian State and Territory population cancer registries, the Australian Institute of Health and Welfare, and paediatric oncology treating hospitals, and is one of the longest-running and most comprehensive databanks of childhood cancer in the world.

With appropriate ethical and legislative approvals, every State and Territory Cancer Registry provides information to the ACCR each year on all incident childhood cancer cases. Under these ethics agreements, state-specific data cannot be published without permission and unit record data cannot be supplied to researchers other than investigators named in the ethics applications.

Patients’ medical charts are also reviewed to collect additional clinical information during on-site visits by the ACCR Data Manager to each of the major children’s hospitals throughout Australia. Mortality status is determined by matching cases in the ACCR against the National Death Index, which contains records of all deaths that have occurred in Australia since 1980.

The ACCR includes information on cancer stage (a measure of how far the cancer has spread at the time of diagnosis). Information on childhood cancer incidence and survival by stage at diagnosis is published separately by Cancer Australia as part of the National Cancer Control Indicators.

Classification of childhood cancers
The tissue of origin of childhood cancers is the best predictor of tumour behaviour and prognosis, and they are classified accordingly. This differs from adult cancers, which are generally classified based on the body site where the cancer occurs. The International Classification of Childhood Cancers, 3rd edition (ICCC-3) 4 is the accepted international standard. All malignant neoplasms are included except for keratinocyte (non-melanoma) skin cancers, which are not registered in Australia and hence are not included in the data contained within the ACCR. In accordance with the ICCC-3, diagnostic groups III (tumours of the central nervous system) and X (germ cell tumours) also include intracranial and intraspinal tumours of benign or uncertain behaviour.

Stage at diagnosis
The collection of internationally consistent information on childhood cancer stage by population-based cancer registries is essential for epidemiologic analysis, international benchmarking and meaningful comparisons of childhood cancer incidence and outcomes. The Australian Childhood Cancer Registry has had a leading role in the development and testing of rules for the collection of childhood cancer stage by cancer registries.

This work was supported through a national initiative by Cancer Australia as part of an approach to improve national cancer data on stage, treatment and recurrence. Information on the distribution of cancer stage and survival by stage at diagnosis for childhood cancers has been published online by Cancer Australia as part of the National Cancer Control Indicators (available at the links below).

Distribution of childhood cancer stage – https://ncci.canceraustralia.gov.au/diagnosis/stage-diagnosis/distribution-childhood-cancer-stage

Five-year observed survival by stage at diagnosis for childhood cancers – https://ncci.canceraustralia.gov.au/outcomes/survival-stage-diagnosis-childhood-cancers/five-year-relative-survival-stage-diagnosis

Methods
Age-standardised rates
Age-standardised rates adjust for variation in age structures in different populations (either different geographical areas or the same population across time). All incidence and mortality trends shown here were calculated using directly standardised rates. The method involves applying age-specific rates in five-year age groups from the population of interest (i.e. children with cancer in Australia) to a standard population, which on this website is the Australian Standard Population 2001.

Annual percentage change (APC)
This is the annual increase or decrease in the incidence or mortality trends over the specified period. Negative APC values describe a decreasing trend and positive APC values describe an increasing trend. A trend is taken to be statistically significant if the 95% confidence interval does not include zero.

APC values were calculated from a statistical method called joinpoint analysis, using software developed by the Statistical Research and Applications Branch of the National Cancer Institute. The joinpoint method evaluates changing trends (both the direction and the magnitude of the trend) over successive segments of time. A joinpoint is the data point (year) at which the trend changes significantly.

The analysis begins with the assumption of constant change over time (i.e. no joinpoint). Up to two joinpoints were tested in each model, depending on the number of years of data available and the stability of the yearly estimates. A minimum of 5 years was specified between joinpoints or between a joinpoint and either end of the data series. The selected trend line was the one with the fewest joinpoints which provided the best fit to the observed data, based on Monte Carlo permutation tests. (5)

Australian Standard Population (2001)
The population currently used for direct age-standardisation within Australia is the 2001 Australian Standard Population, which is based on the age distribution of the estimated resident population as at 30 June 2001. The data is available from the Australian Bureau of Statistics. (1)

Confidence intervals
All estimates are calculated with some degree of uncertainty. This uncertainty is typically reported in terms of a confidence interval, which specifies a range of values in which the true data point is expected to occur with a given level of certainty. For example, a 5-year survival rate may be estimated as 85.0% with a 95% confidence interval of 82.5% – 88.1%. This means that there is a 95% probability that the true survival rate will be somewhere between 82.5% and 88.1%.

Incidence
Incidence measures the number of new cases of cancer diagnosed within a specified population during a given time period (usually one year). Incidence is also commonly expressed as a rate (e.g. per 100,000 population). Since the risk of most cancers varies with age, it is common practice to age-standardise incidence rates to account for variation in the age structures of different populations or changes over time (see Age-standardised rates).

Mortality
Mortality measures the number of deaths caused by cancer within a specified population during a given time period (usually one year). Similar to incidence, mortality can also be expressed as a rate (per 100,000 population), and these rates are often age-standardised to account for variation in the age structures of different populations or changes over time (see Age-standardised rates).

Survival
Survival measures the percentage of people with cancer who remain alive for a given period of time (typically 5 years). Relative survival is the most commonly presented measure of cancer survival when using data from population-based cancer registries.6 It compares the observed survival of children with cancer against the expected survival of children from the general population, taking into account age, sex and year of diagnosis. The method does not require knowledge of the specific cause of death, only knowledge of whether the patient has died.

Relative survival estimates can be calculated using either the period or cohort methods. The cohort approach was used for the relative survival estimates shown here. Although the period method is recognised as providing more up-to-date survival estimates,7 the cohort method was used in the calculations presented here as it was considered more appropriate within the context of children’s cancers to enable the monitoring of changes in treatment over time.

A suite of Stata programs developed by Paul Dickman from the Karolinska Institutet in Sweden were used to generate the relative survival estimates. These programs use a life table (or actuarial) method for calculating observed survival. This approach involves dividing the total period of observation into a series of discrete time intervals. Survival probabilities are then calculated for each of these intervals, and multiplied together to get the estimate for observed survival. Expected survival (based on total Queensland mortality data obtained from the Australian Bureau of Statistics) was calculated based on the Ederer II method.8 Three-year averages for expected survival were used to minimise the effects of year to year variation. Relative survival was then obtained from the ratio of observed survival to expected survival. Survival time was censored for patients who were still alive at 31st December 2021.

References
1. Australian Bureau of Statistics. Population by age and sex – 2001 census edition. ABS Cat No 32010. Canberra: ABS; 2003.
2. Australian Bureau of Statistics. National, State and Territory Population Canberra: ABS; 2023. Available from: https://www.abs.gov.au/statistics/people/population/national-state-and-territory-population/latest-release, accessed 31 May 2023.
3. Australian Bureau of Statistics. Deaths, Australia. Canberra: ABS; 2022. Available from: https://www.abs.gov.au/statistics/people/population/deaths-australia/latest-release#data-downloads, accessed 31 May 2023.
4. Steliarova-Foucher E, Stiller C, Lacour B, Kaatsch P. International Classification of Childhood Cancer, third edition. Cancer 2005; 103: 1457-1467. Kim H, Fay M, Feuer E, Midthune D.
5. Permutation tests for joinpoint regression with applications to cancer rates. Statistics in Medicine 2000; 19: 335-351.
6. Dickman PW, Sloggett A, Hills M, Hakulinen T. Regression models for relative survival. Stat Med 2004; 23: 51-64.
7. Brenner H, Gefeller O, Hakulinen T. Period analysis for ‘up-to-date’ cancer survival data: theory, empirical evaluation, computation realisation and applications. Eur J Cancer 2004; 40: 326-335.
8. Ederer F, Axtell LM, Cutler SJ. The relative survival rate: a statistical methodology. NCI Monogr 1961; 6: 101-121.

Get in touch

If you require any further assistance regarding Australian Childhood Cancer Statistics Online, please contact us at statistics@cancerqld.org.au.