Australian Institute of Health and Welfare (2022) Cancer data in Australia, AIHW, Australian Government, accessed 29 March 2023.
Australian Institute of Health and Welfare. (2022). Cancer data in Australia. Retrieved from https://www.aihw.gov.au/reports/cancer/cancer-data-in-australia
Cancer data in Australia. Australian Institute of Health and Welfare, 04 October 2022, https://www.aihw.gov.au/reports/cancer/cancer-data-in-australia
Australian Institute of Health and Welfare. Cancer data in Australia [Internet]. Canberra: Australian Institute of Health and Welfare, 2022 [cited 2023 Mar. 29]. Available from: https://www.aihw.gov.au/reports/cancer/cancer-data-in-australia
Australian Institute of Health and Welfare (AIHW) 2022, Cancer data in Australia, viewed 29 March 2023, https://www.aihw.gov.au/reports/cancer/cancer-data-in-australia
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The 2020 release of Cancer data in Australia (CDiA) contains a greater range of risk data than previous AIHW releases. This cancer data commentary provides guidance on using the new risk data and summarises key changes.
Changes to CDiA include the following:
‘Cancer risk’ is generally used to describe the risk of being diagnosed with, or the risk of dying from, cancer.
CDiA includes a ‘risk adjusted for competing mortality’ (AdjCom) method and a ‘risk unadjusted for competing mortality’ (RUCM) method. A more technical overview of the methods is available in the methods section of CDiA.
Risk unadjusted for competing mortality only considers the likelihood of being diagnosed with, or dying from, cancer. ‘Competing mortality’ considers the probability of a certain event occurring for a person (e.g. diagnosis of cancer, death from cancer) while taking into account the fact that the person might die before the event happens. The additional factor of competing mortality results in an estimate that better reflects the ‘real world’ risk but it also produces more complex comparisons. In particular, to what extent are changes in risk over time, or differences between the risk for two populations, influenced by competing mortality and to what extent are they driven by cancer risk?
The different methods have their own respective strengths and limitations. Therefore, one method may be better suited to inform a particular investigation than the other. Guidance on using the methods is provided in more detail in the following sections.
AdjCom measures risk by taking into account the mortality that occurs due to other causes whereas RUCM does not. The following hypothetical situation helps highlight the practical differences.
Table 1 provides the risk of diagnosis using RUCM and AdjCom for conditions X and Y in 1982 and 2015 and calculates the risk for each condition.
Condition
RUCM 1982
RUCM 2015
AdjCom 1982
AdjCom 2015
Condition X
2.4690% (1 in 41)
2.4635% (1 in 41)
2.4889% (1 in 40)
Condition Y
0.4822% (1 in 207)
1.0636% (1 in 94)
Observations:
Please note that RUCM minus AdjCom does not somehow isolate the effect of competing mortality. In fact, AdjCom can be higher than RUCM, as is the case for condition X in 2015 in the example above. To view RUCM and AdjCom formulas, please go to Cancer data in Australia methods section.
The selection of which risk method to use depends on the purpose of the investigation. The most complete understanding of risk is accomplished when using the two methods together.
By factoring in competing mortality, AdjCom provides a better estimate of ‘real world’ cancer risk (that is, a better approximation of the likelihood of being diagnosed with, or dying from, cancer in Australia). However, when viewing changes over time or between populations, the question when using AdjCom is “are the observed differences or changes due to competing mortality or due to the risk purely attributable to cancer?".
On the other hand, in not factoring in competing mortality, RUCM is less representative of the ‘real world’ risk, particularly at older ages. However, its strength is that comparisons and time series are solely attributable to cancer risk (i.e. not affected by differences in competing mortality).
Because the methods have opposing strengths and limitations, use of the two methods together can help provide a more complete understanding of risk. In general, when writing about cancer risk, AIHW cite AdjCom but also use RUCM to understand cancer-specific trends that are isolated from competing mortality.
RUCM and AdjCom measure risk differently and are not directly comparable. However, the information from the respective time series can be used in a complementary manner to provide greater insights into changes over time; the following discussion of changes in lung cancer risk over time helps illustrate this by using AdjCom to estimate the ‘real world’ risk and RUCM to isolate cancer risk.
Between 1982 and 2020, the risk of persons being diagnosed with lung cancer by the age of 90 is estimated to have increased from 1 in 23 to 1 in 18. The increase in risk of being diagnosed with lung cancer by the age of 90 is mostly due to a greater proportion of people surviving to the ages where lung cancer is more commonly diagnosed but increasing lung cancer rates have contributed to some degree (Figure 1).
Source: AIHW ACD 2016
The above interpretation of lung cancer risk is undertaken by using AdjCom to provide the ‘real world’ estimate but RUCM to interpret cancer specific risk change over time. Given RUCM focusses only on cancer risk and the RUCM time series is considerably flatter than AdjCom, the sharper increase in AdjCom is likely predominantly due to changes in competing mortality over time.
When using RUCM to assist in the interpretation of AdjCom time series, note that RUCM less AdjCom does not equal competing mortality.
AdjCom comparisons between different populations are accurate but can be open to misinterpretation. Where readers are not aware of the competing mortality concept, it is likely that comparisons will be interpreted as only being due to cancer rates. Where readers are aware of the concept, the question often arises as to whether differences are due to competing mortality or cancer rates.
The potential for misinterpretation, and how to address the issue by using the methods together, is demonstrated in the following consideration of the question ‘Are males more likely to be diagnosed with pancreatic cancer?’.
AdjCom analysis: The risk of males being diagnosed with pancreatic cancer by the age of 90 between 1982 and 2020 is generally quite similar to females (Figure 2). RUCM analysis: Between 1982 and 2020, males consistently have a greater risk of being diagnosed with pancreatic cancer by the age of 90 (Figure 2). AdjCom used in conjunction with RUCM analysis: Between 1982 and 2020, the risk of males being diagnosed with pancreatic cancer is quite similar to females. More precisely though, males have a greater risk of being diagnosed with pancreatic cancer but females are more likely to live to the ages where pancreatic cancer more commonly occurs (Figure 2).
When comparing Australian cancer risk data internationally, care should be taken to ensure the comparisons use the same method.
The International Agency for Research on Cancer presents international risk comparisons; these comparisons are unadjusted for competing mortality and the comparisons measure risk of being diagnosed with (based on cases), and risk of death from, specific cancers. The RUCM data AIHW produces is the most comparable method, noting that it measures the risk of being diagnosed for people, not cases (Appendix B provides information on the generally negligible difference between measuring risk of people being diagnosed with cancer and the risk of cancer cases being diagnosed).
Over time, life expectancy is increasing. Cancer is more common in older ages and more people are surviving to older ages. Cancer specific risk may be increasing or decreasing depending on the cancer but the greater number of people reaching older ages, the greater the upwards pressure on the population’s cancer risk.
AdjCom comparisons between populations are influenced by cancer rates and competing mortality. RUCM can be used to identify which population has higher rates of cancer. In regards to competing mortality differences, the population with lower life expectancy should have less upwards pressure on risk to some extent because the population is less likely to live to the ages where cancer more commonly occurs.
In many circumstances, risk will be used as supportive information or used a simple measure to inform a general audience. In such circumstances, it may be both undesirable and impractical to distinguish between competing mortality impacts and cancer specific impacts. If appropriate, consideration could be given to reporting on risk by age 75 in preference to older ages. Risk by age 75 is less impacted by competing mortality than older ages; this results in:
Lifetime risk is not the risk for an average lifetime. Lifetime risk may be considered as risk by the age of the oldest person in the population for each year; this will be risk by age over 100 for the cancer data time series. Given most people are not expected to live to beyond 100, lifetime risk may not be the most appropriate indicator where the purpose is to provide the general population with a simple and relevant indication of cancer risk.
For both AdjCom and RUCM, risk is reported in 5-year increments from risk by age 5 to risk by age 90. Lifetime risk is also provided for AdjCom.
The provision of additional risk data by age allows interpretation of cancer risk, and cancer risk trends, for more stages of life.
The time series for All cancers combined incidence risk are not available because the RUCM and AdjCom methods cannot do so with suitable accuracy; the following paragraphs discuss this in more detail.
What should AdjCom and RUCM measure?
The AdjCom and RUCM methods should ideally calculate incidence risk only including people who have not been diagnosed with cancer before; the population who have previously been diagnosed with cancer realised their cancer incidence risk in the year they were first diagnosed with cancer.
What do AdjCom and RUCM measure?
The AdjCom and RUCM methods used calculate incidence risk based on the number of people diagnosed in the year, irrespective of whether individuals have been diagnosed with cancer in previous years.
Why can’t cancer incidence risk be calculated using only those diagnosed with cancer for the first time?
Over 100 years of cancer incidence data would be required to identify all people diagnosed with cancer for the first time so the data required to calculate the exact risk of diagnosis are not yet available, i.e. based only on those diagnosed with cancer for the first time.
A ‘best estimate’ of cancer incidence risk using the ‘first time diagnosed’ concept is provided in Attachment A. The ‘best estimate’ is provided for 2015 and uses 34 years of cancer data to identify and account for the population who have previously been diagnosed with cancer.
Are the AdjCom and RUCM incidence risk measures reliable?
Comparisons between AdjCom and the ‘best estimate’ of cancer incidence risk are provided in Attachment A. Where the two values are suitably close, AdjCom and RUCM risk are considered acceptable proxies that are accurate enough to approximate cancer incidence risk.
For most cancers, the proxy and the best estimate are usually quite close. However, for the group ‘all cancers combined’, the proxy measure of risk is around 10 percentage points higher than the best estimate. The all cancers combined incidence risk using the proxy is over-stated to the extent that it is not considered suitable.
Is the all cancers combined mortality risk time series available?
All cancers combined mortality risk is available. The complexities surrounding cancer incidence risk do not apply to cancer mortality risk. This is because death occurs only once, so the issue of multiple diagnoses and recognising the first occurrence does not apply to mortality risk.
What information is available to inform all cancers combined risk?
The ‘best estimate’ of all cancers combined incidence risk as presented in Attachment A can be used as the most recent estimate of risk. The ‘best estimate’ is only produced for the most recent year for which all states and territories have provided data. A time-series is not available due to comparability issues across time. For example, 2015 will have over 30 years of data from which to identify if a person has been diagnosed with cancer before, whereas the first year of data, 1982, would have no earlier years to identify if a person has been diagnosed with cancer before.
Prior to the 2020 release of cancer risk data, AIHW measured risk of diagnosis using the RUCM method. However, the previous method measured this risk using ‘cases diagnosed in the year’ while the replacement method of RUCM measures this risk using ‘people diagnosed in the year’. The change to measuring risk of people being diagnosed is closer to the recommended measure of measuring risk of people who were diagnosed for the first time. Attachment B quantifies the impact of changing measurement from cases to people for 2015.
Note that the RUCM method of measuring the risk of death from cancer has not changed from previous publications.
Comparison of risk adjusted for competing mortality estimates based on:
* the first time ever only factors if a person has been diagnosed previously and since 1982; data on earlier years is not available
Acute lymphoblastic leukaemia (ALL)
0.1492
670
0.1414
707
Acute myeloid leukaemia (AML)
0.4826
207
0.3842
260
All blood cancers combined
6.9784
14
7.0902
5.5780
18
5.6781
All cancers combined
50.7679
2
60.4152
43.2378
50.5515
Anal cancer
0.2056
486
0.1824
548
Bladder cancer
1.5179
66
1.5204
1.0836
92
1.0846
Bone cancer
0.1051
951
0.0966
1,036
Brain cancer
0.7492
133
0.6738
148
Breast cancer
13.9630
7
13.9794
12.5910
8
12.6060
Cancer of other and ill-defined digestive organs
0.1537
650
0.0792
1,262
Cancer of other soft tissue
0.3402
294
0.2881
347
Cancer of small intestine
0.2561
391
0.2175
460
Cancer of the gallbladder and extrahepatic bile ducts
0.5128
195
0.3793
264
Cancer of the salivary glands
0.1552
644
0.1218
821
Cancer of unknown primary site
1.4443
69
1.4450
0.8589
116
0.8596
Cervical cancer
0.5805
172
0.5818
0.5545
180
0.5557
Chronic lymphocytic leukaemia (CLL)
0.8249
121
0.6783
147
Chronic myeloid leukaemia (CML)
0.1368
731
0.1127
887
Colon cancer
5.3789
19
5.3863
4.2091
24
4.2132
Colorectal cancer
7.5169
13
7.6324
6.0378
17
6.1236
16
Eye cancer
0.1575
635
0.1348
742
Gynaecological cancers
4.7001
21
4.7502
4.1486
4.1853
Head and neck cancer (excluding lip)
1.5594
64
1.6196
62
1.3639
73
1.4184
71
Head and neck cancer (with lip)
1.9785
51
2.0507
49
1.7096
58
1.7737
56
Hodgkin lymphoma
0.2423
413
0.2244
446
Hypopharyngeal cancer
0.0827
1,209
0.0739
1,354
Immunoproliferative cancers
0.1363
734
0.1086
921
Kaposi sarcoma
0.0239
4,188
0.0191
5,232
Kidney cancer
1.5171
1.3577
74
Laryngeal cancer
0.2821
355
0.2521
397
Leukaemia
1.8992
53
1.9088
52
1.5405
65
1.5492
Lip cancer
0.4311
232
0.3553
281
Liver cancer
0.9608
104
0.9611
0.8270
0.8273
Lung cancer
5.8633
5.9000
4.8731
4.9077
20
Lymphoma
2.6273
38
2.6425
2.2005
45
2.2156
Melanoma of the skin
6.1037
6.1086
5.1930
5.1978
Mesothelioma
0.4134
242
0.3074
325
Mouth cancer
0.2841
352
0.2295
436
Multiple myeloma
0.9315
107
0.7660
131
Myelodysplastic syndromes
0.8336
120
0.5236
191
Nasal cavity, middle ear and sinuses cancer
0.0979
1,021
0.0771
1,297
Nasopharyngeal cancer
0.0498
2,010
0.0488
2,050
Neuroendocrine tumours
1.7932
1.8010
1.5412
1.5473
Non-Hodgkin lymphoma
2.3953
42
2.4010
1.9864
50
1.9921
Non-melanoma skin cancer (rare types)
0.5461
183
0.5511
181
0.3592
278
0.3635
275
Oesophageal cancer
0.7208
139
0.7215
0.5733
174
0.5740
Oropharyngeal cancer
0.2661
376
0.2560
Ovarian cancer
1.2121
83
1.0084
99
Pancreatic cancer
1.7829
1.3386
75
Penile cancer
0.1017
983
0.0852
1,174
Peritoneal cancer
0.0968
1,033
0.0971
1,030
0.0835
1,197
0.0839
1,192
Prostate cancer
17.4717
6
17.4732
15.6084
15.6099
Rectal cancer
2.3007
43
2.3017
1.9581
1.9591
Soft tissue sarcoma
0.6944
144
0.6970
143
0.5882
170
0.5908
169
Stomach cancer
1.0694
94
1.0702
93
0.8354
0.8362
Testicular cancer
0.5093
196
0.5078
197
Thyroid cancer
1.0519
95
1.0548
1.0204
98
1.0232
Tongue cancer
0.3795
0.3428
292
Uterine cancer
2.3069
2.3089
2.0998
48
2.1018
Vaginal cancer
1,263
0.0582
1,717
Vulvar cancer
0.3492
286
0.2657
Notes:
Source: AIHW 2016 Australian Cancer Database
Comparison of risk unadjusted for competing mortality estimates based on:
0.1292
774
0.1532
653
0.2468
405
0.4831
3.7598
27
3.7512
6.9097
6.8820
15
31.6111
3
31.1792
47.0215
46.3565
0.1469
681
0.2176
459
0.5817
1.4279
70
1,210
0.1097
912
0.5438
184
0.7925
126
10.2107
10
10.2101
13.2263
13.2258
0.0403
2,478
0.1055
948
0.2182
458
0.3463
289
0.1591
628
0.1587
630
0.2652
377
0.2648
378
0.2208
453
0.2205
454
0.4935
203
0.4932
0.0867
1,154
0.1496
669
0.4514
222
1.1344
88
0.4890
204
0.4878
205
0.6040
166
0.6027
0.4671
214
0.8525
117
0.0940
1,064
0.1325
755
2.5473
39
2.5391
5.2992
5.2846
3.9495
25
3.9167
26
7.5604
7.4842
0.1040
961
0.1641
609
3.2728
31
3.2380
4.7229
4.6777
1.1712
85
1.1657
86
1.6840
59
1.6770
60
1.4484
1.4429
2.1027
2.0957
0.1972
507
0.2500
400
0.0569
1,759
0.0897
1,115
0.0733
1,365
0.1360
735
0.0144
6,942
0.0238
4,202
1.0910
1.0903
1.6202
1.6195
0.1932
518
0.1928
519
0.3112
321
0.3101
323
1.0659
1.0643
1.9144
1.9106
0.2805
357
0.4259
235
0.6056
165
1.0117
3.1713
32
3.1580
6.1065
6.0845
1.5740
1.5726
2.7017
37
2.7003
3.9255
6.0996
0.1625
616
0.4081
245
0.1775
564
0.1771
565
0.2814
0.2811
356
0.5055
198
0.9699
103
0.2225
449
0.7120
140
0.0616
1,624
0.0916
1,092
0.0436
2,294
0.0555
1,802
1.1545
87
1.1515
1.8807
1.8759
1.3796
72
1.3791
2.4579
41
2.4574
0.1886
530
0.1883
531
0.4796
209
0.4792
0.3762
266
0.3754
0.7307
137
0.7298
0.2392
418
0.2914
343
0.7546
0.7529
1.1633
1.1616
0.8343
0.8338
1.7042
1.7037
0.0574
1,742
0.1154
867
0.0592
1,690
0.1038
963
12.0198
18.2445
5
1.4389
1.4370
2.3877
2.3858
0.4343
230
0.7162
0.7154
0.5361
187
0.5351
1.0632
1.0622
0.5165
194
0.5249
0.9721
0.9603
1.1448
1.1322
0.2999
333
0.3998
250
1.6707
1.6701
2.3797
2.3771
0.0429
2,328
0.0674
1,483
0.1747
572
0.3159
317
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