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The average 'cancer burden' is measured in the Atlas by two separate concepts. First, the risk of being diagnosed with cancer and second, the excess risk of dying from that cancer within five years of diagnosis.

CANCER DIAGNOSIS

The average 'cancer burden' is measured in the Atlas by two separate concepts. First, the risk of being diagnosed with cancer and second, the excess risk of dying from that cancer within five years of diagnosis.

'Cancer diagnosis' refers to the number of new cancers diagnosed among people living in a defined geographical area within a given time period. Reporting just the number of cancer diagnoses can be misleading, because some areas may have many residents while others have few. For this reason, cancer diagnoses are typically reported using rates. Cancer diagnosis rates are the number of new cancers diagnosed in an area, divided by the total number of people in that area.

Cancer is more common among older people. If one geographical area has an older population on average than another, comparing rates between these areas would not be a fair comparison. Age-standardisation allows for the different age structures of the populations to be considered, so that any differences between areas are differences that can't be explained by the different ages of the populations.

To compare the cancer diagnosis rate between areas, the cancer diagnosis rate for a specific area is compared to the Australian average. This measure is known as the Standardised Incidence Ratio or SIR for short (Incidence is another name for diagnosis). The SIR is a number that indicates whether the cancer diagnosis burden in one area is higher or lower than expected, given the population size and age structure of that area.

In the Australian Cancer Atlas, the SIRs are calculated using appropriate statistical models. An SIR greater than 1 (shown in orange/red) means that, overall, people living in that area have a greater risk of being diagnosed with cancer than the Australian average. Conversely, values below 1 (shown in blue) mean that, overall, people living in the area have a lower risk of being diagnosed with cancer than the Australian average. SIR values around 1 are shown in yellow, meaning they are very similar to the Australian average.

It is important to note that the SIR for a specific geographical area reflects the overall result for that area. All the results presented in the Australian Cancer Atlas are about the average cancer burden for all people living within an area. Since individual people are very different, with different characteristics, lifestyles and habits, this overall result does not apply to every person living in that area.

Australian cancer atlas reports 5 year (2012-2016) aggregated SIR for all cancers, breast, bowel, lung, melanoma and prostate cancers; and 10 year (2007-2016) aggregated SIR for brain, cervical, head and neck, kidney, leukaemia, liver, myeloma, non-Hodgkin lymphoma, oesophageal, ovarian, pancreatic, stomach, thyroid, uterine cancers and classic myeloproliferative neoplasms (classic MPN). The aggregated Australian cancer numbers (new cases per year, rate per 100k) are reported for the respective time period (2007-2017 or 2012-2016) for the above cancer types.

CONFIDENCE ('UNCERTAINTY') OF DIAGNOSIS ESTIMATES

A single number is not enough to understand the cancer diagnosis burden in an area as statistical estimates are not perfect. Each estimate has a degree of uncertainty, or imprecision, around it. If an estimate has a high level of uncertainty, then there is less confidence in what the true estimate is.

Areas with smaller populations are generally more likely to have more uncertainty around their estimates of cancer diagnosis, and therefore lower confidence.

In the main map of the Australian Cancer Atlas, the level of uncertainty is shown by the level of transparency in the map colours. The more uncertain the estimates are, the higher the transparency. This means that even if the SIR for an area is larger than one, if there is a high level of uncertainty, then the high transparency will mean it looks similar to the Australian average (that is, yellow). The transparency effect in the map can be turned on and off.

Information about the uncertainty around the SIR estimates can also be found in the V-plots and wave plots.

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