Abstract
Background:
Cancer is a leading cause of death globally. Given the elevated risk of cancer with age and an ageing population, it is important to understand the changing burden of cancer in older populations. The ASPirin in Reducing Events in the Elderly (ASPREE) study randomised healthy older individuals to 100 mg aspirin or placebo, with clinical outcomes and disability-free survival endpoints. Detailed baseline data provides a rare opportunity to explore cancer burden in a uniquely healthy older population.
Methods:
At study enrolment (2010–2014), self-reported personal cancer history, cancer type and cancer risk factor data were sought from 19,114 participants (Australia, n = 16,703; U.S., n = 2411). Eligible participants were healthy, free of major diseases and expected to survive 5 years.
Results:
Nearly 20% of enrolling ASPREE participants reported a prior cancer diagnosis; 18% of women and 22% of men, with women diagnosed younger (16% vs 6% of diagnoses < 50 years). Cancer prevalence increased with age. Prevalence of prostate and breast cancer history were higher in U.S. participants; melanoma and colorectal cancer were higher in Australian participants. Cancer history prevalence was not associated with contemporary common risk factors nor previous aspirin use, but was associated with poor health ratings in men. Blood and breast cancer history were more common with past aspirin use.
Conclusions:
Personal cancer history in healthy older ASPREE participants was as expected for the most common cancer types in the respective populations, but was not necessarily aligned with known risk factors. We attribute this to survivor bias, likely driven by entry criteria.
Trial Registration:
International Standard Randomised Controlled Trial Number Register (ISRCTN83772183) and clinicaltrials.gov (NCT01038583).
Keywords: Cancer prevalence, Cancer epidemiology, Cancer risk factors, Aspirin, Selection criteria, Survivor bias
1. Introduction
Cancer is the second leading cause of death worldwide, and the global burden is expected to reach around 26 million new cases and 17 million deaths per year by 2030 [15,16,46]. Risk factors associated with cancer incidence and mortality include smoking, obesity and poor diet [16]. Additionally, the risk of cancer increases with age beyond 50 years [7,18,23]. Understanding the burden of disease in older populations is essential to inform age-appropriate prevention, treatment strategies and public policy. Given an ageing population, characterising the cancer experience of relatively healthy older individuals, may provide useful insights into successful cancer prevention and treatment at earlier ages.
Whilst some behavioural changes have led to decreases in cancer incidence of a few cancer types (e.g. sunscreen use with melanoma and reduced smoking prevalence with lung cancer), this is not the case across many others, including colorectal, breast and prostate cancers [28,30,48]. Currently, there are no population-wide effective chemo-prevention strategies for cancer. Since chronic inflammation plays a significant role in the pathogenesis of cancer [13,14,20,44], anti-inflammatory drugs, including aspirin, may have a role in cancer prevention. Recent meta-analyses examined the cancer outcomes of participants enrolled in cardiovascular disease prevention trials, in predominantly middle aged people [39–41]. Results indicated that taking regular low-dose aspirin (75–100 mg) for at least 4–5 years could reduce cancer incidence, risk of metastatic spread, and cancer mortality, over the subsequent 10+ years. However, because these are all post-hoc analyses of outcomes that were not pre-specified and the trials included only small numbers of older people (70+ years), there remain important questions about the use of aspirin in preventing cancer, particularly in older persons.
ASPirin in Reducing Events in the Elderly (ASPREE) was a multi-centre, randomised, double-blinded, placebo-controlled trial of low-dose (100 mg) aspirin in 19,114 community dwelling adults, in Australia and the U.S. [3]. ASPREE found no difference between aspirin and placebo for the primary outcome of disability- and dementia-free survival, thereby providing no net benefit to participants [32]. The ASPREE cohort provides a unique opportunity to explore the burden of cancer and the utility of aspirin for cancer prevention, in the healthy elderly. This paper describes the baseline characteristics and cancer risk profile of ASPREE participants, in those with and without a self-reported cancer history at enrolment, and compares them with the general Australian and U.S. populations. We also aim to determine whether there are associations between current cancer risk factors and past cancer history.
2. Materials and methods
The ASPREE trial enrolled Australian and U.S. men and women who were ≥ 70 years (or ≥ 65 years for U.S. African-Americans and Hispanics) with approval from multiple ethics committees [2]. The recruitment methods, and general baseline characteristics are described elsewhere [3,31]. Briefly, from March 2010 to December 2014, 19,114 participants (16,703 Australian and 2411 U.S. participants), after giving informed consent, were randomly assigned to daily 100 mg enteric-coated aspirin or matched placebo. Recruitment was primarily community based, in Australia, through general practice, and in the U.S., through academic health centres.
ASPREE participants were 56% female and 9% minorities, 11% had diabetes, 74% had hypertension, 4% were current smokers, 41% were former smokers, 77% were current drinkers (≥1 drink per week), 65% had hypercholesterolaemia, 2% were underweight (< 20 kg/m2), 30% were obese (≥30 kg/m2), and 11% reported previous regular aspirin use (but agreed to cease upon study enrolment) [31].
A previous history of cancer was not an ASPREE exclusion criterion, however, participants were required to be in good health, free of major diseases and expected to survive 5 years of follow-up (as confirmed with the participant’s primary care provider). Given these criteria, participants with recent diagnoses of any metastatic disease or poor prognosis malignancy, e.g. pancreatic cancer or glioblastoma, were excluded, even if they had been treated with curative intent and were currently disease free.
Initial baseline cancer data collection (pre June 2013) included self-reported personal (a specific question on colorectal cancer, and ‘other’ cancer as free text) and family cancer history, excluding non-melanoma skin cancer. A cancer history prior to ASPREE was not cross referenced with medical records nor confirmed with treating physicians. Where an incident cancer was reported during the ASPREE trial period, available data on any previous cancer history was reviewed. Upon funding from the National Cancer Institute in June 2013, data collection was expanded to include details about personal and family cancer history and personal cancer screening, including detailed cancer type (17 types) and the age at diagnosis (either < 50 or 50+ years). Previously collected free text, wherever possible, was converted to match the expanded data collection. The table in Appendix A Supplemental Data Digital Content 1 lists the changes between the two phases of cancer history data collection.
Of the 19,114 participants in ASPREE, 19,030 participants (99.6%) are included in this analysis, with the exclusion of 57 participants due to a response of ‘Unsure’ to the personal cancer history question, 22 participants for failure to provide any cancer history response, and 5 participants for failure to provide a response to cancer subtype. Odds ratios (OR) were estimated to describe associations between cancer history and known cancer risk factors (using logistic regression adjusted for age and country), and for cancer type prevalence with past regular aspirin use (logistic regression adjusted for age, sex and country).
3. Results
Personal cancer history prevalence in ASPREE participants at enrolment is shown by sex, age at diagnosis and demographics in Table 1. Of 19,030 participants, 19% (3655) reported a personal cancer history, and of these, 1870 were female (51%) and 1785 were male (49%), with 89% of diagnoses occurring after the age of 50 years. The prevalence of a prior cancer diagnosis increased with age at enrolment (18% for 65–74 yrs. vs 21% for 75–84 yrs. vs 26% for 85+ yrs). Whilst a greater proportion of males (22%) reported a past cancer history than females (18%), proportionately more females than males were diagnosed before 50 years (16% vs 6% of diagnoses). More white/Caucasians (20%) reported a personal cancer history compared to other racial categories combined (13%). More Australians (20%) reported a past cancer history at baseline than U.S. participants (17%), although this may be confounded by the inclusion of younger U.S. minorities.
Table 1.
Self-reported personal cancer history by sex, age at diagnosis, age at baseline of the ASPREE trial, and demographics.
| Female (n = 10,741) | Male (n = 8289) | |||||
|---|---|---|---|---|---|---|
| No Cancer | Cancer, by age at diagnosis | No Cancer | Cancer, by age at diagnosis | |||
| < 50 Years | 50+ Years | < 50 Years | 50+ Years | |||
| Total (% sex) | 8871 (82%) | 295 (3%) | 1575 (15%) | 6504 (79%) | 105 (1%) | 1680 (20%) |
| Age (years) | ||||||
| 65–74 | 5092 (83%) | 197 (3%) | 822 (14%) | 4014 (80%) | 68 (1%) | 921 (18%) |
| 75–84 | 3442 (82%) | 87 (2%) | 666 (16%) | 2282 (76%) | 35 (1%) | 676 (23%) |
| 85+ | 337 (78%) | 11(3%) | 87 (20%) | 208 (71%) | 2 (1%) | 83 (28%) |
| Race | ||||||
| White | 7990 (82%) | 270 (3%) | 1476 (15%) | 5948 (78%) | 99 (1%) | 1595 (21%) |
| African American | 508 (87%) | 16 (3%) | 63 (11%) | 252 (83%) | 3 (1%) | 48 (16%) |
| Hispanic | 252 (88%) | 7 (3%) | 26 (9%) | 179 (89%) | 2 (1%) | 21 (10%) |
| Asian | 69 (90%) | 1 (1%) | 7 (9%) | 76 (87%) | 1 (1%) | 10 (12%) |
| Other | 52 (93%) | 1 (2%) | 3 (5%) | 49 (89%) | 0 (0%) | 6 (11%) |
| Country | ||||||
| Australia | 7530 (82%) | 251 (3%) | 1366 (15%) | 5862 (78%) | 94 (1%) | 1531 (20%) |
| U.S. | 1341 (84%) | 44 (3%) | 209 (13%) | 642 (80%) | 11 (1%) | 149 (19%) |
The relationships between cancer history and known cancer risk factors, co-morbidities, and general health/well-being are presented in Table 2. Smoking history did not change the prevalence of cancer history for either sex. The median smoking pack years was 16 for those with a cancer history and 15 for those without (data not shown). There were only small numbers of baseline lung cancers reported (n = 45; < 1% of all baseline cancers), consistent with the exclusion criterion of an absence of an illness likely to cause death within 5 years. Of these 45 lung cancer cases, 80% (n = 36) also had a smoking history (current or former). Overall, there was no association between smoking history and prior cancer diagnosis (all cancer types) in either sex (OR = 1.08, 95% CI 0.97–1.20, p = 0.15 for females; OR = 1.03, 95% CI 0.92–1.14, p = 0.62 for males).
Table 2.
Cancer history of ASPREE participants by sex, risk factors, comorbidities and general health.
| Female | Male | |||||||
|---|---|---|---|---|---|---|---|---|
| No Cancer history (% of females) | Cancer history (% of females) | Odds ratiod, adjusted for age and country (95% CI) | p value | No Cancer history (% of males) | Cancer history (% of males) | Odds ratiod, adjusted for age and country (95% CI) | p value | |
| Total | 8871 (83%) | 1870 (17%) | 6504 (79%) | 1785 (21%) | ||||
| Smoking history (% of row) | ||||||||
| No smoking history | 5778 (83%) | 1192 (17%) | 2809 (79%) | 760 (21%) | ||||
| Smoking history | 3093 (82%) | 678 (18%) | 1.08 (0.97, 1.20) | 0.15 | 3695 (78%) | 1025 (22%) | 1.03 (0.92, 1.14) | 0.62 |
| Alcohol use (% of row) | ||||||||
| No alcohol use | 2119 (84%) | 409 (16%) | 631 (80%) | 157 (20%) | ||||
| Any alcohol use | 6752 (82%) | 1461 (18%) | 1.12 (1.00, 1.27) | 0.06 | 5873 (78%) | 1628 (22%) | 1.14 (0.95, 1.38) | 0.15 |
| BMI (% of row)a | ||||||||
| Low-mid BMIc | 2518 (82%) | 558 (19%) | 1417 (79%) | 366 (21%) | ||||
| High BMIc | 6311 (83%) | 1306 (17%) | 0.95 (0.85, 1.06) | 0.37 | 5067 (78%) | 1410 (22%) | 1.12 (0.98, 1.27) | 0.10 |
| Diabetes (% of row)a | ||||||||
| Non-diabetes | 8044 (83%) | 1697 (17%) | 5676 (78%) | 1570 (22%) | ||||
| Diabetes | 827 (83%) | 173 (17%) | 1.01 (0.85, 1.20) | 0.94 | 828 (79%) | 215 (21%) | 0.94 (0.80, 1.10) | 0.45 |
| Physical function; mean (SD) | ||||||||
| Grip strength (dominant hand, kg) | 20.7 (5.9) | 20.3 (5.8) | 0.95 (0.86, 1.06) | 0.34 | 35.0 (8.4) | 34.7 (8.5) | 1.1 (0.86, 1.40) | 0.46 |
| Gait speed (Time to walk 3 m, sec) | 3.3 (1.0) | 3.3 (1.1) | 1.01 (0.91, 1.13) | 0.85 | 3.0 (0.8) | 3.0 (0.8) | 0.99 (0.87, 1.12) | 0.86 |
| Quality of lifee | ||||||||
| Health rating of fair/poor (% of row; % of column) | 411 (82%; 4.6%) | 90 (18%; 4.8%) | 1.04 (0.82, 1.32) | 0.73 | 247 (70%; 3.8%) | 106 (30%; 5.9%) | 1.59 (1.26, 2.01) | < 0.001 |
| SF-12 MCS; median (IQR) | 57.1 (51.6–60.3) | 56.9 (51.2–60.1) | 1.09 (0.99, 1.20) | 0.09 | 57.3 (53.2–60.3) | 57.3 (52.9–60.5) | 0.98 (0.88, 1.09) | 0.67 |
| SF-12 PCS; median (IQR) | 49.4 (42.0–55.1) | 48.7 (41.3–54.5) | 1.09 (0.99, 1.21) | 0.08 | 51.8 (45.1–56.1) | 51.3 (44.0–55.1) | 1.07 (0.96, 1.19) | 0.23 |
| CES-D; median (IQR) | 3 (1–5) | 3 (1–5) | 1.06 (0.96, 1.17) | 0.29 | 2 (0–4) | 2 (0–4) | 1.06 (0.95, 1.17) | 0.32 |
| Medication use (n and % of row and column) | ||||||||
| Past aspirin useb | 970 (83%; 11%) | 203 (18%; 11%) | 1.03 (0.87, 1.22) | 0.73 | 710 (78%; 11%) | 201 (22%; 11%) | 1.04 (0.87, 1.24) | 0.66 |
| No past aspirin useb | 7901 (83%; 89%) | 1667 (17%; 89%) | 5792 (79%; 89%) | 1584 (21%; 89%) | ||||
| Current statin use | 2997 (82%; 34%) | 636 (18%; 34%) | 1.01 (0.91, 1.13) | 0.81 | 1832 (79%; 28%) | 493 (21%; 28%) | 0.99 (0.88, 1.11) | 0.84 |
| No statin use | 5874 (83%; 66%) | 1234 (17%; 66%) | 4672 (78%; 72%) | 1292 (22%; 72%) | ||||
| 5+ medications | 2759 (82%; 31%) | 609 (18%; 33%) | 1.06 (0.95, 1.18) | 0.29 | 1299 (77%; 20%) | 390 (23%; 22%) | 1.11 (0.97, 1.26) | 0.13 |
| 0–4 medications | 6112 (83%; 69%) | 1261 (17%; 67%) | 5205 (79%; 80%) | 1395 (21%; 78%) | ||||
Abbreviations: SF-12: Short-Form 12 questionnaire; MCS: Mental Component Score of the SF-12; PCS: Physical Component Score of the SF-12; CES D − 10: Centre for Epidemiologic Studies – Short Depression Scale Depression – s10 question form; IQR: Inter-Quartile range.
77 participants are missing their BMI value due to either no weight or no height measurement.
2 male participants did not provide a response for past aspirin use.
Low-mid BMI is defined as < 25 kg/m2 (underweight and normal categories) and high BMI as ≥25 kg/m2 (overweight and obese categories).
Odds ratio, adjusted for age and country, for association between past cancer and risk factor or comorbidity with the reference group being the absence of the factor/comorbidity. In the case of continuous factors the association is between past cancer and a dichotomy of the factor into above and below the median (or mean, whichever is specified).
Quality of Life assessed through a number of measures: via the Short-Form 12 questionnaire [26], with a self reported health rating of fair/poor, and via a derived Physical Component Score (PCS) and a Mental Component Score (MCS), as described in McNeil et al. [31] and Stocks et al. [45]; and the CES D-10: Centre for Epidemiologic Studies – Short Depression Scale Depression – s10 question form [38].
For both sexes who reported current alcohol use (any amount and any frequency), 2% more participants had a history of cancer compared with those reporting no alcohol use. Of the females with current alcohol use (n = 8213), 18% (n = 1461) reported a history of cancer whilst the proportion with a past cancer history was 16% without alcohol use; and for males, the proportions were 22% vs 20%, respectively. There was no association between current alcohol intake and history of cancer for either sex (for females, OR = 1.12, 95% CI 1.00–1.27, p = 0.06; and for males, OR = 1.14, 95% CI 0.95–1.38, p = 0.15).
Fewer ASPREE females had high BMI compared to males (71% vs 79%). No association was observed between high BMI and past cancer history in either sex (OR = 0.95, 95% CI 0.85–1.06, p = 0.37 for females; OR = 1.12, 95% CI 0.98–1.27, p = 0.10 for males). The proportion of ASPREE participants with diabetes (11%) reporting a cancer history within each sex was the same as for those without a cancer history. No association was observed between diabetes and past cancer history (OR = 1.01, 95% CI 0.85–1.20, p = 0.94 for females; OR = 0.94, 95% CI 0.80–1.10, p = 0.45 for males).
Physical function (as defined by mean grip strength and gait time to walk 3 m) and quality of life were examined relative to past cancer history (Table 2). There was no association between a past cancer history and physical function for either sex. However, males with a cancer history were more likely to report fair/poor health than males without a cancer history (OR = 1.59, 95% CI 1.26–2.01, p < 0.001). Fair/poor health ratings were similar in frequency in females with or without a past cancer history (around 5%).
The physical and mental component scores (PCS and MCS, respectively) of health related quality of life are linked to an individual’s health status, with higher scores indicating better physical and mental health [38,45]. No association was observed for any of these quality of life measures or depressive symptoms, as measured for the CES-D 10 survey, and past cancer history (Table 2).
There was no difference in past aspirin use or current statin use between those reporting the presence or absence of a personal cancer history. The proportion of males with a prior diagnosis of cancer was numerically higher in those reporting 5 or more medications compared with those on fewer than 5 (23% vs 21%), but no association was observed between those with a past cancer history and number of medications for either sex (OR = 1.06, 95% CI 0.95–1.18, p = 0.29, for females; OR = 1.11, 95% CI 0.97–1.26, p = 0.13 for males).
The prevalence of cancer types by sex and country is shown in Fig. 1. Within the 3655 ASPREE participants with a past cancer history, 4013 prior cancer events were reported at baseline (multiple types in some participants). Overall, the four most common cancer types were prostate (n = 925), breast (n = 835), melanoma (n = 684) and colorectal (n = 472) cancers. A cancer history was more prevalent in the male population of both countries, relative to the females (21% and 20% of Australian and U.S. males versus 18% and 16% of Australian and U.S. females, respectively).
Figure 1. Cancer type by gender and country (% of country total).
Cancer type ‘other’ includes all other cancer types that are not specified within the list presented and includes gall bladder/bile duct, thyroid, brain, kidney, liver, lung, pancreatic, stomach/oesophagus.
Cancer type differed slightly by country (Fig. 1). Compared to their U.S. counterparts, Australian participants had a higher prevalence of colorectal cancer history (2.5% vs 1.1% for females; 2.8% vs 1.4% for males), and melanoma cancer history (females, 3.7% vs 1.1%; males, 4.3% vs 1.1%). The proportion of African-Americans with a colorectal cancer history did not differ from the proportion of all U.S. races combined with a colorectal cancer history (results not shown). U.S. females had a higher prevalence of breast cancer history compared to Australian females (9.6% vs 7.4%) and U.S. males had a higher prevalence of prostate cancer history compared to Australian males (13.7% vs 10.9%).
Table 3 describes the association between previous aspirin use and cancer by type, using an OR adjusted for age, sex and country. There was no association between a past cancer history (i.e. any cancer history) and previous aspirin use (OR = 1.04, 95% CI 0.92–1.17, p = 0.53), but haematological and breast cancer histories were more common with past aspirin use (OR = 1.69, 95% CI 1.02–2.81, p = 0.04 for haematological cancer; OR = 1.34, 95% CI 1.08–1.66, p = 0.008 for breast cancer). A past history of melanoma and colorectal cancer appeared less common with past aspirin use; however there was no significant association when adjusted for age, sex and country. Prior diagnosis of ‘other’ cancers (i.e. those not specified in Table 3; includes gall bladder/bile duct, thyroid, brain, kidney, liver, lung, pancreatic, stomach/oesophagus) was less common with past aspirin use (OR = 0.71, 95% CI 0.52–0.97, p = 0.03).
Table 3.
Association between previous aspirin use and prevalence of cancer subtype expressed as odds ratio for past cancer between previous regular aspirin use and not.
| Cancer type | Previous aspirin use | Adjusted Odds Ratioc (95%CI) | p-value | ||
|---|---|---|---|---|---|
| No | Yes | ||||
| (n = 16,944)a | (n = 2084)a | ||||
| Any cancer history | n | 3251 | 404 | 1.04 | 0.53 |
| % previous aspirin use | 19% | 19% | (0.92–1.17) | ||
| Bladder | n | 126 | 16 | 1.02 | 0.95 |
| % any cancer history | 4% | 4% | (0.59–1.77) | ||
| Blood (haematological), including Myeloma | n | 107 | 20 | 1.69 | 0.04 |
| % any cancer history | 3% | 5% | (1.02–2.81) | ||
| Breast | n | 713 | 122 | 1.34 | 0.008 |
| % any cancer history | 22% | 30% | (1.08–1.66) | ||
| Cervicalc (only females) | n | 68 | 10 | 1.2 | 0.61 |
| % any cancer history | 4% | 5% | (0.59–2.44) | ||
| Colon/Rectum | n | 430 | 42 | 0.93 | 0.67 |
| % any cancer history | 13% | 10% | (0.67–1.30) | ||
| Melanoma | n | 626 | 58 | 0.99 | 0.94 |
| % any cancer history | 19% | 14% | (0.75–1.31) | ||
| Ovarian/Endometriumc (only females) | n | 121 | 15 | 0.90 | 0.72 |
| % any cancer history | 7% | 7% | (0.51–1.59) | ||
| Prostatec (only males) | n | 818 | 107 | 0.96 | 0.70 |
| % any cancer history | 52% | 53% | (0.76–1.20) | ||
| All other cancersb | n | 532 | 49 | 0.71 | 0.03 |
| % any cancer history | 16% | 12% | (0.52–0.97) | ||
2 participants who did not provide details of past aspirin use were excluded from this table.
‘All other cancers’ includes gall bladder/bile duct, thyroid, brain, kidney, liver, lung, pancreatic, stomach/oesophagus and other.
Odds ratio presented for past cancer history between previous regular aspirin use and not, adjusted for age, sex and country, except for those cancers expressed relative to a single sex, as indicated (cervical, ovarian/endometrium, prostate).
4. Discussion
The ASPREE population exhibited a healthy survivor bias due to the study entry criteria, and this was observed in total mortality and cancer mortality after median 4.7 years follow-up [31,33]; 19% of ASPREE participants reported a previous cancer history, a slightly higher proportion in males than females, and the majority of these diagnoses were after the age of 50 years (89%). As expected [7,18,23], the prevalence of a past cancer history increased with age at enrolment (18% for 65–74 yrs. vs 21% for 75–84 yrs. vs 26% for 85+ yrs). More Caucasians/whites (20%) reported a personal cancer history than any other race (13% for all other races combined) and more Australians had a previous history of cancer than U.S. participants (20% vs 18%), consistent with the older average age of the Australian cohort [31]. Prostate and breast cancers were the first and second most prevalent cancers in the ASPREE population, respectively, in line with their high global ranking (fourth and first, respectively) [15,16]. The low frequencies in ASPREE participants at study enrolment of lung and pancreatic cancer histories, both of which have high mortality [15], are consistent with the exclusion criterion of a 5 year life-limiting illness and contribute to the survivor bias of ASPREE participants. The high proportion of participants with a melanoma history is compatible with the bulk of recruitment being in Australia, which has near the highest global incidence of melanoma [8,24,27] but a very high cure rate due to most having low risk disease [19,52]. Consistent with the general Australian [8] and U.S. [1] populations, more ASPREE males than females reported a past history of melanoma.
African-Americans reportedly have the highest incidence and mortality from colorectal cancer of any other race within the general U.S. population [4,50]. Whilst a smaller proportion of ASPREE African-American participants had a past cancer history (14%) compared to the U.S. races combined (19%), no difference was observed for colorectal cancer history between these two groups (results not shown).
Multiple risk factors contribute to an individual’s likelihood of developing cancer, with one third of cancer deaths estimated to be due to 5 leading behavioural and dietary risk factors: tobacco use, alcohol use, high BMI, low fruit and vegetable intake, and lack of physical activity [15,16]. The ASPREE population is a select group with possibly a lower genetic predisposition to lethal cancers and/or behaviours (lifelong or modifications over time) which minimise cancer risk. For example, only 4% of ASPREE participants were current smokers at enrolment compared to the general older Australian (7%) [6,9] and U.S. (9%) [22,47] populations.
Alcohol consumption is thought to contribute to 2.8% of all Australian adult cancers [37,51] and specifically increases the risk of oral cavity, pharynx, larynx, oesophagus, liver, colorectal and female breast cancers, with the level of risk linked to the level of consumption [37,42]. Of these cancer types, alcohol consumption had the greatest impact on colorectal and breast cancers in women [37]. The rates of alcohol use in ASPREE (~83%) were similar to that of the general populations of both countries (~83%) [36,55]. Within the ASPREE population, there was no association observed between a personal cancer history and current alcohol use in either sex (OR = 1.14, 95% CI 0.95–1.38, p = 0.15 for males; OR = 1.12, 95% CI 1.00–1.27, p = 0.06 for females), although it is possible that heavy alcohol consumers would have been excluded due to their development of significant co-morbidities (e.g. chronic liver disease), and the survivor bias of the study’s selection criteria.
Overweight or obese individuals have a higher risk for many cancer types compared with individuals in the normal BMI range (18.5 to < 25 kg/m2), including breast (in postmenopausal women), colorectal, endometrial, pancreatic, oesophageal, kidney, gallbladder and liver cancers [11,54]. Obesity may also increase the risk of cancer mortality, such as from prostate cancer [29]. In the ASPREE population, the prevalence of high BMI (~74%) was similar to that reported for the general Australian (72%) [5] and U.S. (71%) [35] populations, but was not associated with a personal history of cancer at enrolment (OR = 0.95, 95% CI 0.85–1.06, p = 0.37 for females; OR = 1.12, 95% CI 0.98–1.27, p = 0.10 for males). Additionally, there were no observed differences in the age of onset of a cancer diagnosis between any of the BMI categories (results not shown).
The results of recent meta-analyses, indicate that some cancers develop more commonly in those with diabetes (predominantly type 2) [57], and some epidemiological studies suggest diabetes may also significantly increase mortality in patients with a cancer diagnosis [53]. Rates of diabetes in ASPREE participants (11%) were lower than those reported for older individuals in each country: 19% for Australia [10] and 22% for the U.S. [12]. Within the ASPREE population, regardless of sex, diabetes was not associated with a reported cancer history, nor with the age of cancer diagnosis (Table 2).
Observational epidemiologic studies consistently suggest that higher levels of physical activity are associated with a lower risk of many cancers, especially colon cancer, postmenopausal breast cancer and endometrial cancer [25,54], and may improve survival from some cancers, including breast [17,21] and colorectal cancers [34]. There was no difference in reporting of cancer history by measures of physical function (hand grip or gait speed) at enrolment, nor any of the quality of life measures except for a significant association between males reporting a fair/poor quality of life and a past cancer history.
Studies are now showing that the molecular makeup of cancer changes with age [43,49], and these changes impact the response to therapies and treatment strategies. Differences in the DNA methylation state of genes [56], along with differences in the types of mutations found within genes [43,49] may play a role in contributing to changing cancer risk profiles from young to middle to older aged people.
A limitation of this analysis is that we have analysed risk factors present at the time of study enrolment, not at the time of cancer diagnosis. We do not know what risk factors were present at the time of diagnosis, nor whether the diagnosis itself induced behavioural changes, particularly smoking and diet. Additionally, as already acknowledged, the study selection criteria ensured our data manifests a survivor bias. Nevertheless, we cannot exclude the possibility that differences in cancer genetics with age may also have contributed to our lack of observed association between cancer history and recognised cancer risk factors, and may lead to risk factor profiles differing with age.
5. Conclusion
Nearly 1 in 5 ASPREE participants reported a personal cancer history at enrolment, with similar prevalence for females (18%) and males (21%), but with females more likely to be diagnosed at a younger age. There were minor differences in cancer type by country. Compared to the general populations of both countries, ASPREE participants had similar prevalence of alcohol use and high BMI, but lower rates of tobacco use and diabetes prevalence. In our surviving older population, no common risk factors present at enrolment, including high BMI, alcohol use, a smoking history or diabetes, were associated with past cancer history. Cancer history was associated with a poor current health rating in males. Modest associations between previous aspirin use and haematological, breast and ‘other’ cancers, were observed. Overall, these data are consistent with the ASPREE cohort exhibiting a healthy survivor bias, driven by the study entry criteria. There is also evidence of differences in the molecular make-up of cancer, and hence cancer risk profile, between elderly and middle aged people. These matters will need to be considered when interpreting the relevance of any ASPREE cancer outcome data to the wider population of older individuals.
Supplementary Material
Acknowledgments
Bayer AG provided aspirin and matching placebo. The authors acknowledge the dedicated and skilled staff in Australia and the U.S. for the conduct of the trial. The authors also are most grateful to the ASPREE participants, who so willingly volunteered for this study, and the general practitioners and medical clinics who support the participants in the ASPREE study. Finally, the authors would like to thank Dr Kathlyn Ronaldson for her valuable assistance in proof-reading and editing the manuscript in preparation for submission.
Declaration of Competing Interest
The ASPREE trial was supported by a National Institute on Aging grant (U01AG029824) with supplemental funding from the National Cancer Institute at the National Institutes of Health (R01 CA137178), by grants (334047 and 1127060) from the National Health and Medical Research Council of Australia, and by Monash University and the Victorian Cancer Agency. These sponsors did not contribute to study design, data collection, analysis, data interpretation, manuscript writing or the decision to submit this article for publication, however, representatives of the NIA sit on the International Executive Committee in an advisory role. Mark Nelson received travel and financial support to attend an advisory board meeting sponsored by Bayer AG, which provided study medication for the ASPREE trial. Anne Murray and John McNeil received travel and consulting fees to present published results from the ASPREE study at a Bayer AG sponsored conference. All other authors declare that there has been no financial or personal interest that has affected their objectivity.
Footnotes
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://doi.org/10.1016/j.cct.2020.106095.
References
- [1].American Cancer Society, Facts & Figures 2018. Atlanta, Ga, Internet https://www.cancer.org/content/dam/cancer-org/research/cancer-facts-and-statistics/annual-cancer-facts-and-figures/2018/cancer-facts-and-figures-2018.pdf, (2018) (19 December 2019). [Google Scholar]
- [2].ASPREE Protocol Version 9, November. Internet https://aspree.org/usa/wp-content/uploads/sites/3/2014/04/ASPREE-Protocol-Version-9_-Nov2014_FINAL.pdf, (2014) , Accessed date: 19 December 2019.
- [3].ASPREE Study Group, Study design of ASPirin in Reducing Events in the Elderly (ASPREE): a randomised controlled trial, Contemp. Clin. Trials 36 (2) (2013) 555–564, 10.1016/j.cct.2013.09.014. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [4].Augustus GJ, Ellis NA, Colorectal cancer disparity in African Americans: risk factors and carcinogenic mechanisms, Am. J. Pathol 188 (2) (2018) 291–303, 10.1016/j.ajpath.2017.07.023. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [5].Australian Bureau of Statistics (ABS), General Social Survey: summary results, Australia, 2014, ABS cat. no. 4159.0, ABS, Canberra, 2015Internet https://www.abs.gov.au/ausstats/abs@.nsf/mf/4159.0 (18 December 2019).
- [6].Australian Bureau of Statistics (ABS), National Health Survey: First Results, 2014–15. ABS cat. no. 4364.0, ABS, Canberra, 2015 Internet https://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/4364.0.55.0012014-15?OpenDocument (18 December 2019).
- [7].Australian Institute of Health and Welfare, Cancer in Australia: an Overview 2014. Cancer Series no. 90. CAN 88. AIHW, Canberra, 2014 ISSN 1039-3307. ISBN 978-1-74249-677-1. Internet https://www.aihw.gov.au/getmedia/79c940b1-2438-45c8-99e2-a4b593253ccd/18114.pdf.aspx?inline=true (18 December 2019).
- [8].Australian Institute of Health and Welfare, Cancer in Australia 2017. Cancer Series no. 101. Cat. no. CAN 100, AIHW, Canberra, 2017 ISSN: 1039-3307; ISBN: 978-1-76054-075-3. Internet https://www.aihw.gov.au/getmedia/3da1f3c2-30f0-4475-8aed-1f19f8e16d48/20066-cancer-2017.pdf.aspx?inline=true (18 December 2019).
- [9].Australian Institute of Health and Welfare, Older Australians at a Glance. AGE 87, AIHW, Canberra, 2017 Internet https://www.aihw.gov.au/reports/older-people/older-australia-at-a-glance/contents/summary (18 December 2019).
- [10].Australian Institute of Health and Welfare, 2014b-2015 Data, Internet https://www.aihw.gov.au/reports/diabetes/diabetes/data, (2018) (19 December 2019).
- [11].Calle EE, Rodriguez C, Walker-Thurmond K, Thun MJ, Overweight, obesity, and mortality from cancer in a prospectively studied cohort of U.S. adults, N. Engl. J. Med 348 (17) (2003) 1625–1638, 10.1056/NEJMoa021423. [DOI] [PubMed] [Google Scholar]
- [12].Centers for Disease Control and Prevention, National Diabetes Statistics Report, 2017. Atlanta, GA: Centers for Disease Control and Prevention, U.S. Dept of Health and Human Services, Internet https://www.cdc.gov/features/diabetes-statistic-report/index.html, (2017) (18 December 2019). [Google Scholar]
- [13].Chen R, Alvero AB, Silasi DA, Mor G, Inflammation, cancer and chemoresistance: taking advantage of the toll-like receptor signaling pathway, Am. J. Reprod. Immunol 57 (2) (2007) 93–107, 10.1111/j.1600-0897.2006.00441.x. [DOI] [PubMed] [Google Scholar]
- [14].Coussens LM, Werb Z, Inflammation and cancer, Nature 420 (6917) (2002) 860–867, 10.1038/nature01322. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [15].Fitzmaurice C, Allen C, Barber RM, Barregard L, Bhutta ZA, Brenner H, et al. , Global, regional, and national cancer incidence, mortality, years of life lost, years lived with disability, and disability-adjusted life-years for 32 cancer groups, 1990 to 2015: a systematic analysis for the global burden of disease study, JAMA Oncol. 3 (4) (2017) 524–548. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [16].Fitzmaurice C, Dicker D, Pain A, Hamavid H, Moradi-Lakeh M, MacIntyre MF, et al. , The global burden of cancer 2013, JAMA Oncol. 1 (4) (2015) 505–527. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [17].Friedenreich CM, Orenstein MR, Physical activity and cancer prevention: etiologic evidence and biological mechanisms, J. Nutr 132 (11) (2002) 3456S–3464S, 10.1093/jn/132.11.3456S. [DOI] [PubMed] [Google Scholar]
- [18].GBD, Mortality and Causes of Death Collaborators. (2016). Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980–2015: a systematic analysis for the Global Burden of Disease Study 2015, Lancet 388 (10053) (2015) 1459–1544, 10.1016/S0140-6736(16)31012-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [19].Grossmann KF, Margolin K, Long-term survival as a treatment benchmark in melanoma: latest results and clinical implications, Ther. Adv. Med. Oncol 7 (3) (2015) 181–191, 10.1177/1758834015572284. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [20].Hanahan D, Weinberg RA, Hallmarks of cancer: the next generation, Cell 144 (5) (2011) 646–674, 10.1016/j.cell.2011.02.013. [DOI] [PubMed] [Google Scholar]
- [21].Holmes MD, Chen WY, Feskanich D, Kroenke CH, Colditz GA, Physical activity and survival after breast cancer diagnosis, J. Am. Med. Assoc 293 (20) (2005) 2479–2486, 10.1001/jama.293.20.2479. [DOI] [PubMed] [Google Scholar]
- [22].Jamal A, Phillips E, Gentzke AS, Homa DM, Babb SD, King BA, et al. , Current cigarette smoking among adults - United States, 2016, MMWR Morb. Mortal. Wkly Rep 67 (2) (2018) 53–59, 10.15585/mmwr.mm6702a1externalicon. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [23].Jemal A, Center MM, DeSantis C, Ward EM, Global patterns of cancer incidence and mortality rates and trends, Cancer Epidemiol. Biomark. Prev 19 (8) (2010) 1893–1907. [DOI] [PubMed] [Google Scholar]
- [24].Karimkhani C, Green AC, Nijsten T, Weinstock MA, Dellavalle RP, Naghavi M, Fitzmaurice C, The global burden of melanoma: results from the global burden of disease study 2015, Br. J. Dermatol 177 (1) (2017) 134–140, 10.1111/bjd.15510. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [25].Lee IM, Physical activity and cancer prevention—data from epidemiologic studies, Med. Sci. Sports Exerc 35 (11) (2003) 1823–1827, 10.1249/01.MSS.0000093620.27893.23. [DOI] [PubMed] [Google Scholar]
- [26].Lim LL, Fisher JD, Use of the 12-item short form (SF-12) health survey in an Australian heart and stroke population, Qual. Life Res 8 (1999) 1–8. [DOI] [PubMed] [Google Scholar]
- [27].Liu-Smith F, Farhat AM, Arce A, Ziogas A, Taylor T, Wang Z, et al. , Sex differences in the association of cutaneous melanoma incidence rates and geographic ultraviolet light exposure, J. Am. Acad. Dermatol 76 (3) (2017) 499–505, 10.1016/j.jaad.2016.08.027. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [28].Lubin JH, Purdue M, Kelsey K, Zhang ZF, Winn D, Wei Q, et al. , Total exposure and exposure rate effects for alcohol and smoking and risk of head and neck cancer: a pooled analysis of case-control studies, Am. J. Epidemiol 170 (8) (2009) 937–947, 10.1093/aje/kwp222. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [29].Ma J, Li H, Giovannucci E, Mucci L, Qiu W, Nguyen PL, et al. , Prediagnostic body-mass index, plasma C-peptide concentration, and prostate cancer-specific mortality in men with prostate cancer: a long-term survival analysis, Lancet Oncol. 9 (11) (2008) 1039–1047, 10.1016/S1470-2045(08)70235-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [30].Marron M, Boffetta P, Zhang ZF, Zaridze D, Wunsch-Filho V, Winn DM, et al. , Cessation of alcohol drinking, tobacco smoking and the reversal of head and neck cancer risk, Int. J. Epidemiol 39 (1) (2010) 182–196, 10.1093/ije/dyp291. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [31].McNeil JJ, Woods RL, Nelson MR, Murray AM, Reid CM, Kirpach B, et al. , Baseline characteristics of participants in the ASPREE (ASPirin in Reducing Events in the Elderly) study, J. Gerontol. A-Biol. Sci. Med. Sci 72 (11) (2017) 1586–1593, 10.1093/gerona/gly278. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [32].McNeil JJ, Woods RL, Nelson MR, Reid CM, Kirpach B, Wolfe R, et al. , Effect of aspirin on disability-free survival in the healthy elderly, N. Engl. J. Med 379 (16) (2018) 1499–1508, 10.1056/NEJMoa1800722. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [33].McNeil JJ, Nelson MR, Woods RL, Lockery JE, Wolfe R, Reid CM, et al. , Effect of aspirin on all-cause mortality in the healthy elderly, N. Engl. J. Med 379 (2018) 1519–1528. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [34].Meyerhardt JA, Giovannucci EL, Holmes MD, Chan AT, Chan JA, Colditz GA, et al. , Physical activity and survival after colorectal cancer diagnosis, J. Clin. Oncol 24 (22) (2006) 3527–3534, 10.1200/JCO.2006.06.0855. [DOI] [PubMed] [Google Scholar]
- [35].National Center for Health Statistics, Health, United States, 2016: With Chartbook on Long-Term Trends in Health, Internet, 2017. https://www.cdc.gov/nchs/data/hus/hus16.pdf. [PubMed]
- [36].National Health and Medical Research Council, Australian Guidelines – To Reduce Health Risks from Drinking Alcohol, Internet https://www.nhmrc.gov.au/about-us/publications/australian-guidelines-reduce-health-risks-drinking-alcohol, (2009) (18 December 2019).
- [37].Pandeya N, Wilson LF, Webb PM, Neale RE, Bain CJ, Whiteman DC, Cancers in Australia in 2010 attributable to the consumption of alcohol, Aust. N. Z. J. Public Health 39 (5) (2015) 408–413, 10.1111/1753-6405.12456. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [38].Radloff LS, The CES-D scale: a self report depression scale for research in the general population, Appl. Psychol. Meas 1 (1977) 385–401, 10.1177/014662167700100306. [DOI] [Google Scholar]
- [39].Rothwell PM, Fowkes FG, Belch JF, Ogawa H, Warlow CP, Meade TW, Effect of daily aspirin on long-term risk of death due to cancer: analysis of individual patient data from randomised trials, Lancet 377 (9759) (2011) 31–41, 10.1016/S0140-6736(10)62110-1. [DOI] [PubMed] [Google Scholar]
- [40].Rothwell PM, Wilson M, Elwin CE, Norrving B, Algra A, Warlow CP, et al. , Long-term effect of aspirin on colorectal cancer incidence and mortality: 20-year follow-up of five randomised trials, Lancet 376 (9754) (2010) 1741–1750, 10.1016/S0140-6736(10)61543-7. [DOI] [PubMed] [Google Scholar]
- [41].Rothwell PM, Wilson M, Price JF, Belch JF, Meade TW, Mehta Z, Effect of daily aspirin on risk of cancer metastasis: a study of incident cancers during randomised controlled trials, Lancet 379 (9826) (2012) 1591–1601, 10.1016/S0140-6736(12)60209-8. [DOI] [PubMed] [Google Scholar]
- [42].Secretan B, Straif K, Baan R, Grosse Y, El Ghissassi F, Bouvard V, et al. , A review of human carcinogens—part E: tobacco, areca nut, alcohol, coal smoke, and salted fish, Lancet Oncol. 10 (11) (2009) 1033–1034. [DOI] [PubMed] [Google Scholar]
- [43].Serebriiskii IG, Connelly C, Frampton G, Newberg J, Cooke M, Miller V, et al. , Comprehensive characterization of RAS mutations in colon and rectal cancers in old and young patients, Nat. Comm 10 (2019) 3722. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [44].Shacter E, Weitzman SA, Chronic inflammation and cancer, Oncology (Williston Park) 16 (2) (2002) 217–226. [PubMed] [Google Scholar]
- [45].Stocks NP, González-Chica DA, Woods RL, Lockery JE, Wolfe RSJ, Murray AM, The ASPREE Investigator Group, et al. , Quality of life for 19,114 participants in the ASPREE (ASPirin in reducing events in the elderly) study and their association with sociodemographic and modifiable lifestyle risk factors, Qual. Life Res 28 (2019) 935–946. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [46].Thun MJ, DeLancey JO, Center MM, Jemal A, Ward EM, The global burden of cancer: priorities for prevention, Carcinogenesis 31 (1) (2010) 100–110. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [47].US Department of Health and Human Services, The Health Consequences of Smoking—50 Years of Progress: A Report of the Surgeon General. Atlanta: Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health, Internet, 2014. https://www.cdc.gov/tobacco/data_statistics/sgr/50th-anniversary/index.htm. [Google Scholar]
- [48].Wakai K, Seki N, Tamakoshi A, Kondo T, Nishino Y, Ito Y, et al. , Decrease in risk of lung cancer death in males after smoking cessation by age at quitting: findings from the JACC study, Jpn. J. Cancer Res 92 (8) (2001) 821–828, 10.1111/j.1349-7006.2001.tb01167.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [49].Wang M-X, Ren J-T, Tang L-Y, Ren Z-F, Molecular features in young vs elderly breast cancer patients and the impacts on survival disparities by age at diagnosis, Cancer Med. 7 (2018) 3269–3277. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [50].Williams R, White P, Nieto J, Vieira D, Francois F, Hamilton F, Colorectal cancer in African Americans: an update, Clin. Transl. Gastroenterol 7 (7) (2016), 10.1038/ctg.2016.36e185. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [51].Winstanley MH, Pratt IS, Chapman K, Griffin HJ, Croager EJ, Olver IN, et al. , Alcohol and cancer: a position statement from Cancer council Australia, Med. J. Aust 194 (9) (2011) 479–482, 10.5694/j.1326-5377.2011.tb03067.x. [DOI] [PubMed] [Google Scholar]
- [52].Wolchok JD, Chiarion-Sileni V, Gonzalez R, Rutkowski P, Grob JJ, Cowey CL, et al. , Overall survival with combined Nivolumab and Ipilimumab in advanced melanoma, N. Engl. J. Med 377 (14) (2017) 1345–1356, 10.1056/NEJMoa1709684. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [53].Wolpin BM, Meyerhardt JA, Chan AT, Ng K, Chan JA, Wu K, et al. , Insulin, the insulin-like growth factor axis, and mortality in patients with nonmetastatic colorectal cancer, J. Clin. Oncol 27 (2) (2009) 176–185, 10.1200/JCO.2008.17.9945. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [54].World Cancer Research Fund American Institute for Cancer Research, Diet, Nutrition, Physical Activity, and Cancer: a Global Perspective, Internet https://www.wcrf.org/dietandcancer, (2018) (18 December 2019).
- [55].World Health Organization, Global Status Report on Alcohol and Health, WHO Press, Geneva, 2011 ISBN 978 92 4 156415 1.: Internet https://www.who.int/substance_abuse/publications/alcohol_2011/en/ (18 December 2019). [Google Scholar]
- [56].Xu Z, Taylor JA, Genome-wide age-related DNA methylation changes in blood and other tissues relate to histone modification, expression and cancer, Carcinogenesis 35 (2013) 356–364. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [57].Zhou XH, Qiao Q, Zethelius B, Pyorala K, Soderberg S, Pajak A, et al. , Diabetes, prediabetes and cancer mortality, Diabetologia 53 (9) (2010) 1867–1876, 10.1007/s00125-010-1796-7. [DOI] [PubMed] [Google Scholar]
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