Out-of-pocket health care expenses for people with and without cancer, New South Wales, 2020: a cross-sectional study.

OBJECTIVES: To investigate self-reported out-of-pocket health care expenses, both overall and by cost type, for a large population-based sample of Australians, by cancer status and socio-demographic and medical characteristics. STUDY DESIGN: Cross-sectional study. SETTING, PARTICIPANTS: New South Wales residents participating in the 45 and Up Study (recruited aged 45 years or older during 2005-2009) who completed the 2020 follow-up questionnaire; survey responses linked with New South Wales Cancer Registry data. MAIN OUTCOME MEASURES: Proportions of respondents who reported that out-of-pocket health care expenses during the preceding twelve months exceeded $1000 or $10 000; adjusted odds ratios (aORs) for associations with socio-demographic and medical characteristics. RESULTS: Of the 267 357 recruited 45 and Up Study participants, 45 061 completed the 2020 survey (response rate, 53%); 42.7% (95% confidence interval [CI], 42.2-43.1%) reported that overall out-of-pocket health care expenses during the previous year exceeded $1000, including 55.4% (52.1-58.7%) of participants diagnosed in the preceding two years and 44.9% (43.7-46.1%) of participants diagnosed with cancer more than two years ago. After adjustment for socio-demographic factors, out-of-pocket expenses greater than $1000 were more likely to be reported by participants with cancer than by those without cancer (diagnosis in past two years: aOR, 2.06 [95% CI, 1.77-2.40]; diagnosis more than two years ago: aOR, 1.22 [95% CI, 1.15-1.29]). The odds of out-of-pocket expenses exceeding $1000 increased with area-based socio-economic advantage and household income, and were higher for people with private health insurance (v people with Medicare coverage only: aOR, 1.64; 95% CI, 1.53-1.75). Out-of-pocket expenses exceeding $10 000 were also more likely for participants diagnosed with cancer during the past two years (v no cancer: aOR, 3.30; 95% CI, 2.56-4.26). CONCLUSIONS: People diagnosed with cancer during the past two years were much more likely than people without cancer to report twelve-month out-of-pocket health care expenses that exceeded $1000. Out-of-pocket expenses for people with cancer can exacerbate financial strain at a time of vulnerability, and affect health care equity because some people cannot pay for all available treatments.

Impact of weighting on the association between sociodemographic characteristics, health behaviours and cancer, cardiovascular and all-cause mortality in the Australian 45 and Up Study.

BACKGROUND: Weighting can improve study estimate representativeness. We examined the impact of weighting on associations between participants' characteristics and cancer, cardiovascular and all-cause mortality in the Australian 45 and Up Study cohort. METHODS: Raking weighted cohort data to the 2006 Australian population for seven sociodemographic characteristics. Deaths were ascertained via linkage to routinely collected data. Cox's proportional hazards regression quantified associations between 11 sociodemographic and health characteristics and cancer, cardiovascular and all-cause mortality. The ratios of hazard ratios (RHRs) compared unweighted and weighted estimates. RESULTS: Among 195,052 included participants (median follow-up 11.4 years), there were 7200 cancer, 5912 cardiovascular and 21,840 all-cause deaths. Overall, 102/111 (91.9%) weighted HRs did not differ significantly from unweighted HRs (100%, 86.5% and 89.2% of 37 HRs for cancer, cardiovascular and all-cause mortality, respectively). Significant differences included a somewhat stronger association between single/widowed/divorced (versus married/de-facto) and cardiovascular mortality (unweighted HR=1.25 (95%CI:1.18-1.32), weighted HR=1.33 (95%CI:1.24-1.42), RHR=1.06 (95%CI:1.02-1.11)); and between no school certificate/qualification (versus university degree) and all-cause mortality (unweighted HR=1.21 (95%CI:1.15-1.27), weighted HR=1.28 (95%CI:1.19-1.38), RHR=1.06 (95%CI:1.03-1.10)). CONCLUSION: Our results support the generalisability of most estimates of associations in the 45 and Up Study, particularly in relation to cancer mortality. Slight distortion of a few associations with cardiovascular or all-cause mortality were observed.

Accelerometer vs. other activity measures in heart failure with preserved ejection fraction: the VITALITY-HFpEF trial.

AIMS: The relationship between accelerometry data and changes in Kansas City Cardiomyopathy Questionnaire-Physical Limitation Score (KCCQ-PLS) or 6 min walk test (6MWT) is not well understood. METHODS AND RESULTS: VITALITY-HFpEF accelerometry substudy (n = 69) data were assessed at baseline and 24 weeks. Ordinal logistic regression models were used to assess the association between accelerometry activity and deterioration, improved, or unchanged KCCQ-PLS (≥8.33 and ≤ -4.17 points) and 6MWT (≥32 vs. ≤ -32 m). KCCQ-PLS score deteriorated in 16 patients, improved in 34, and was unchanged in 19. 6MWT deteriorated in 8 patients, improved in 21, and was unchanged in 19. Mean accelerometer wear was 21.4 (±2.1) h/day. Changes in hours active from baseline to 24 weeks were not significantly different among patients who exhibited deterioration, improvement, or no change in KCCQ-PLS [odds ratio (OR) 0.91, 95% confidence interval (CI) 0.71-1.18; P = 0.48] or 6MWT (OR 1.21, 95% CI 0.91-1.60; P = 0.18). Similar lack of association was observed for other accelerometry metrics and change in KCCQ and 6MWT. These findings were unaffected when KCCQ and 6MWT were examined as continuous variables. CONCLUSIONS: Accelerometer-based activity measures did not correlate with subjective or objective standard measures of health status and functional capacity in heart failure with preserved ejection fraction. Further investigation of their relationships to clinical outcomes is required.

Challenges and solutions to cancer-related financial toxicity according to Australian health professionals: qualitative results from a national survey.

PURPOSE: To qualitatively explore Australian healthcare professionals' perspectives on how to improve the care and management of cancer-related financial toxicity, including relevant practices, services, and unmet needs. METHODS: We invited healthcare professionals (HCP) who currently provide care to people with cancer within their role to complete an online survey, which was distributed via the networks of Australian clinical oncology professional associations/organisations. The survey was developed by the Clinical Oncology Society of Australia's Financial Toxicity Working Group and contained 12 open-ended items which we analysed using descriptive content analysis and NVivo software. RESULTS: HCPs (n = 277) believed that identifying and addressing financial concerns within routine cancer care was important and most believed this to be the responsibility of all HCP involved in the patient's care. However, financial toxicity was viewed as a "blind spot" within a medical model of healthcare, with a lack of services, resources, and training identified as barriers to care. Social workers reported assessment and advocacy were part of their role, but many reported lacking formal training and understanding of financial complexities/laws. HCPs reported positive attitudes towards transparent discussions of costs and actioning cost-reduction strategies within their control, but feelings of helplessness when they perceived no solution was available. CONCLUSION: Identifying financial needs and providing transparent information about cancer-related costs was viewed as a cross-disciplinary responsibility, however, a lack of training and services limited the provision of support. Increased cancer-specific financial counselling and advocacy, via dedicated roles or developing HCPs' skills, is urgently needed within the healthcare system.

Development and Validation of txSim: A Model of Advanced Lung Cancer Treatment in Australia.

BACKGROUND AND OBJECTIVE: Since 2016, new therapies have transformed the standard of care for lung cancer, creating a need for up-to-date evidence for health economic modelling. We developed a discrete event simulation of advanced lung cancer treatment to provide estimates of survival outcomes and healthcare costs in the Australian setting that can be updated as new therapies are introduced. METHODS: Treatment for advanced lung cancer was modelled under a clinician-specified treatment algorithm for Australia in 2022. Prevalence of lung cancer subpopulations was extracted from cBioPortal and the Sax Institute's 45 and Up Study, a large prospective cohort linked to cancer registrations. All costs were from the health system perspective for the year 2020. Pharmaceutical and molecular diagnostic costs were obtained from public reimbursement fees, while other healthcare costs were obtained from health system costs in the 45 and Up Study. Treatment efficacy was obtained from clinical trials and observational study data. Costs and survival were modelled over a 10-year horizon. Uncertainty intervals were generated with probabilistic sensitivity analyses. Overall survival predictions were validated against real-world studies. RESULTS: Under the 2022 treatment algorithm, estimated mean survival and costs for advanced lung cancer 10 years post-diagnosis were 16.4 months (95% uncertainty interval [UI]: 14.7-18.1) and AU$116,069 (95% UI: $107,378-$124,933). Survival and costs were higher assuming optimal treatment utilisation rates (20.5 months, 95% UI: 19.1-22.5; $154,299, 95% UI: $146,499-$161,591). The model performed well in validation, with good agreement between predicted and observed survival in real-world studies. CONCLUSIONS: Survival improvements for advanced lung cancer have been accompanied by growing treatment costs. The estimates reported here can be used for budget planning and economic evaluations of interventions across the spectrum of cancer control.

Health services costs for ovarian cancer in Australia: Estimates from the 45 and Up Study.

INTRODUCTION: There have been significant advancements in risk identification and treatment for ovarian cancer over the last decade. However, their impact on health services costs is unclear. This study estimated the direct health system costs (government perspective) for women diagnosed with ovarian cancer in Australia during 2006-2013, as a benchmark prior to opportunities for precision-medicine approaches to treatment, and for health care planning. METHODS: Using cancer registry data, we identified 176 incident ovarian cancers (including fallopian tube and primary peritoneal cancer) in the Australian 45 and Up Study cohort. Each case was matched with four cancer-free controls on sex, age, geography, and smoking history. Costs were derived from linked health records on hospitalisations, subsidised prescription medicines and medical services to 2016. Excess costs for cancer cases were estimated for different phases of care relative to cancer diagnosis. Overall costs for prevalent ovarian cancers in Australia in 2013 were estimated based on 5-year prevalence statistics. RESULTS: At diagnosis, 10% of women had localised disease, 15% regional spread and 70% distant metastasis (5% unknown). The mean excess cost per ovarian cancer case was $40,556 in the initial treatment phase (≤12 months post-diagnosis), $9,514 per annum in the continuing care phase and $49,208 in the terminal phase (up to 12 months before death). Hospital admissions accounted for the greatest proportion of costs during all phases (66%, 52% and 68% respectively). Excess costs were higher for patients diagnosed with distant metastatic disease, particularly during the continuing care phase ($13,814 versus $4,884 for localised/regional disease). The estimated overall direct health services cost of ovarian cancer in 2013 was AUD$99million (4,700 women nationally). CONCLUSION: The excess health system costs of ovarian cancer are substantial. Continued investment in ovarian cancer research, particularly prevention, early detection and more effective personalised treatments is necessary to reduce the burden of disease.

Colon and rectal cancer treatment patterns and their associations with clinical, sociodemographic and lifestyle characteristics: analysis of the Australian 45 and Up Study cohort.

BACKGROUND: Colorectal cancer is the third most diagnosed cancer globally and the second leading cause of cancer death. We examined colon and rectal cancer treatment patterns in Australia. METHODS: From cancer registry records, we identified 1,236 and 542 people with incident colon and rectal cancer, respectively, diagnosed during 2006-2013 in the 45 and Up Study cohort (267,357 participants). Cancer treatment and deaths were determined via linkage to routinely collected data, including hospital and medical services records. For colon cancer, we examined treatment categories of "surgery only", "surgery plus chemotherapy", "other treatment" (i.e. other combinations of surgery/chemotherapy/radiotherapy), "no record of cancer-related treatment, died"; and, for rectal cancer, "surgery only", "surgery plus chemotherapy and/or radiotherapy", "other treatment", and "no record of cancer-related treatment, died". We analysed survival, time to first treatment, and characteristics associated with treatment receipt using competing risks regression. RESULTS: 86.4% and 86.5% of people with colon and rectal cancer, respectively, had a record of receiving any treatment ≤2 years post-diagnosis. Of those treated, 93.2% and 90.8% started treatment ≤2 months post-diagnosis, respectively. Characteristics significantly associated with treatment receipt were similar for colon and rectal cancer, with strongest associations for spread of disease and age at diagnosis (p<0.003). For colon cancer, the rate of "no record of cancer-related treatment, died" was higher for people with distant spread of disease (versus localised, subdistribution hazard ratio (SHR)=13.6, 95% confidence interval (CI):5.5-33.9), age ≥75 years (versus age 45-74, SHR=3.6, 95%CI:1.8-7.1), and visiting an emergency department ≤1 month pre-diagnosis (SHR=2.9, 95%CI:1.6-5.2). For rectal cancer, the rate of "surgery plus chemotherapy and/or radiotherapy" was higher for people with regional spread of disease (versus localised, SHR=5.2, 95%CI:3.6-7.7) and lower for people with poorer physical functioning (SHR=0.5, 95%CI:0.3-0.8) or no private health insurance (SHR=0.7, 95%CI:0.5-0.9). CONCLUSION: Before the COVID-19 pandemic, most people with colon or rectal cancer received treatment ≤2 months post-diagnosis, however, treatment patterns varied by spread of disease and age. This work can be used to inform future healthcare requirements, to estimate the impact of cancer control interventions to improve prevention and early diagnosis, and serve as a benchmark to assess treatment delays/disruptions during the pandemic. Future work should examine associations with clinical factors (e.g. performance status at diagnosis) and interdependencies between characteristics such as age, comorbidities, and emergency department visits.

Opinions and strategies of Australian health professionals on tackling cancer-related financial toxicity: A nationwide survey.

AIM: To understand the opinions and current practices of health professionals on the topic of addressing cancer-related financial toxicity among patients. METHODS: A cross-sectional online survey was distributed through Australian clinical oncology professional organizations/networks. The multidisciplinary Clinical Oncology Society of Australia Financial Toxicity Working Group developed 25 questions relating to the frequency and comfort levels of patient-clinician discussions, opinions about their role, strategies used, and barriers to providing solutions for patients. Descriptive statistics were used and subgroup analyses were undertaken by occupational groups. RESULTS: Two hundred and seventy-seven health professionals completed the survey. The majority were female (n = 213, 77%), worked in public facilities (200, 72%), and treated patients with varied cancer types across all of Australia. Most participants agreed that it was appropriate in their clinical role to discuss financial concerns and 231 (88%) believed that these discussions were an important part of high-quality care. However, 73 (28%) stated that they did not have the appropriate information on support services or resources to facilitate such conversations, differing by occupation group; 7 (11%) social workers, 34 (44%) medical specialists, 18 (25%) nurses, and 14 (27%) of other occupations. Hindrances to discussing financial concerns were insufficient resources or support systems to refer to, followed by lack of time in a typical consultation. CONCLUSION: Health professionals in cancer care commonly address the financial concerns of their patients but attitudes differed across occupations about their role, and frustrations were raised about available solutions. Resources supporting financial-related discussions for all health professionals are urgently needed to advance action in this field.

Pathways to diagnosis of endometrial and ovarian cancer in the 45 and Up Study cohort.

PURPOSE: To determine pathways to endometrial or ovarian cancer diagnosis by comparing health service utilization between cancer cases and matched cancer-free controls, using linked health records. METHODS: From cancer registry records, we identified 238 incident endometrial and 167 ovarian cancer cases diagnosed during 2006-2013 in the Australian 45 and Up Study cohort (142,973 female participants). Each case was matched to four cancer-free controls on birthdate, sex, place of residence, smoking status, and body mass index. The use of relevant health services during the 13-18-, 7-12-, 0-6-, and 0-1-months pre-diagnosis for cases and the corresponding dates for their matched controls was determined through linkage with subsidized medical services and hospital records. RESULTS: Healthcare utilization diverged between women with cancer and controls in the 0-6-months, particularly 0-1 months, pre-diagnosis. In the 0-1 months, 74.8% of endometrial and 50.3% of ovarian cases visited a gynecologist/gynecological oncologist, 11.3% and 59.3% had a CA125 test, 5.5% and 48.5% an abdominal pelvic CT scan, and 34.5% and 30.5% a transvaginal pelvic ultrasound, respectively (versus ≤ 1% of matched controls). Moreover, 25.1% of ovarian cancer cases visited an emergency department in the 0-1-months pre-diagnosis (versus 1.3% of matched controls), and GP visits were significantly more common for cases than controls in this period. CONCLUSION: Most women with endometrial or ovarian cancer accessed recommended specialists and tests in the 0-1-months pre-diagnosis, but a high proportion of women with ovarian cancer visited an emergency department. This reinforces the importance of timely specialist referral.

Capacity of the 45 and Up Study to mobilise evidence-based improvements in cancer control: lung cancer case study.

OBJECTIVE: Over the 15 years since the 45 and Up Study (the Study) was established, researchers have harnessed its capacity for enabling rigorous, comprehensive investigation of cancer causes, care, and outcomes. For the first time in Australia, the entire cancer-control continuum could be investigated by linking questionnaire data with cancer registry notifications, hospital records, outpatient medical services and prescription medications at scale. Here, we use lung cancer as a case study to demonstrate the Study's potential to improve cancer control. METHOD: Narrative description. RESULTS: Between 2006-2013, approximately 1200 participants in the Study cohort who had no prior history of cancer were diagnosed with lung cancer, allowing the generation of novel, policy- and practice-relevant evidence for tobacco control, screening, and systems of care. The Study produced evidence on the continuing impact of smoking, including that 'light smoking' (1-5 cigarettes/day) is associated with nine times the risk of lung cancer compared to never-smoking; and that 54% of lung cancers could be avoided long-term if all Australians who smoked were to quit. The Study was used to validate a lung cancer screening risk prediction tool, correctly identifying 70% of the participants with a history of smoking who developed lung cancer within a 6-year period as 'high-risk'. Potential inequities in lung cancer care were identified using the Study cohort, including suboptimal levels of radiotherapy utilisation, below benchmark levels of systemic therapy for patients with metastatic disease, and high numbers of emergency department presentations prior to diagnosis. Participants with lung cancer reported poorer quality of life than those with almost any other cancer type, and about 50% reported severe physical functioning limitations. The Study also provided the infrastructure for the first comprehensive report on lung cancer health system costs. LESSONS LEARNT: As a statewide, population-based cohort, the Study provides reliable estimates of cancer risk, health services utilisation, and person-centred outcomes that can inform policy and practice decision making; and has provided the backbone for localising policy-relevant insights from international experience. We have found that the direct involvement of clinicians and policy makers in research design, and engagement with community networks, can yield tractable, policy-relevant, and ultimately impactful scientific insights.

Accurate categorisation of menopausal status for research studies: a step-by-step guide and detailed algorithm considering age, self-reported menopause and factors potentially masking the occurrence of menopause.

OBJECTIVE: Menopausal status impacts risk for many health outcomes. However, factors including hysterectomy without oophorectomy and Menopausal Hormone Therapy (MHT) can mask menopause, affecting reliability of self-reported menopausal status in surveys. We describe a step-by-step algorithm for classifying menopausal status using: directly self-reported menopausal status; MHT use; hysterectomy; oophorectomy; intervention timing; and attained age. We illustrate this approach using the Australian 45 and Up Study cohort (142,973 women aged ≥ 45 years). RESULTS: We derived a detailed seven-category menopausal status, able to be further consolidated into four categories ("pre-menopause"/"peri-menopause"/"post-menopause"/"unknown") accounting for participants' ages. 48.3% of women had potentially menopause-masking interventions. Overall, 93,107 (65.1%), 9076 (6.4%), 17,930 (12.5%) and 22,860 (16.0%) women had a directly self-reported "post-menopause", "peri-menopause", "pre-menopause" and "not sure"/missing status, respectively. 61,464 women with directly self-reported "post-menopause" status were assigned a "natural menopause" detailed derived status (menopause without MHT use/hysterectomy/oophorectomy). By accounting for participants' ages, 105,817 (74.0%) women were assigned a "post-menopause" consolidated derived status, including 15,009 of 22,860 women with "not sure"/missing directly self-reported status. Conversely, 3178 of women with directly self-reported "post-menopause" status were assigned "unknown" consolidated derived status. This algorithm is likely to improve the accuracy and reliability of studies examining outcomes impacted by menopausal status.

The economics of skin cancer prevention with implications for Australia and New Zealand: where are we now?

The incidence of skin cancer, including melanoma, continues to climb in white populations around the world, imposing a large and growing burden on health systems and individuals. Harmful exposure to ultraviolet (UV) radiation, mostly solar UV, is the most avoidable cause of skin cancer risk and mortality. Many economic evaluations attest to the favourable benefits for governments and citizens from skin cancer prevention programs. This overview presents the current 'state of play' of the economics of skin cancer prevention. More research is required to document contemporary costs of managing skin cancer in Australia and New Zealand to accurately assess the true savings from primary prevention. New directions are proposed for ways that economics could contribute to the investment case for prevention. The majority of skin cancers are avoidable and curable, yet cost the Australian health economy A$1.7 billion each year. Therefore primary prevention of skin cancers must remain high on the public health agenda.

Lung cancer treatment patterns and factors relating to systemic therapy use in Australia.

AIM: Systemic therapies for lung cancer are rapidly evolving. This study aimed to describe lung cancer treatment patterns in New South Wales, Australia, prior to the introduction of immunotherapy and latest-generation targeted therapies. METHODS: Systemic therapy utilization and treatment-related factors were examined for participants in the New South Wales 45 and Up Study with incident lung cancer ascertained by record linkage to the New South Wales Cancer Registry (2006-2013). Systemic therapy receipt to June 2016 was determined using medical and pharmaceutical claims data from Services Australia, and in-patient hospital records. Factors related to treatment were identified using competing risks regressions. RESULTS: A total of 1,116 lung cancer cases were identified with a mean age at diagnosis of 72 years and median survival of 10.6 months. Systemic therapy was received by 45% of cases. Among 400 cases with metastatic non-small cell lung cancer, 51% and 28% received first- and second-line systemic therapy, respectively. Among 112 diagnosed with small-cell lung cancer, 79% and 29% received first- and second-line systemic therapy. The incidence of systemic therapy was lower for participants with indicators of poor performance status, lower educational attainment, and those who lived in areas of socioeconomic disadvantage; and was higher for participants with small-cell lung cancer histology or higher body mass index. CONCLUSION: This population-based Australian study identified patterns of systemic therapy use for lung cancer, particularly small-cell lung cancer. Despite a universal healthcare system, the analysis revealed socioeconomic disparities in health service utilization and relatively low utilization of systemic therapy overall.

Socioeconomic disparities in colorectal cancer survival: contributions of prognostic factors in a large Australian cohort.

PURPOSE: We quantified the contributions of prognostic factors to socioeconomic disparities in colorectal cancer survival in a large Australian cohort. METHODS: The sample comprised 45 and Up Study participants (recruited 2006-2009) who were subsequently diagnosed with colorectal cancer. Both individual (education attained) and neighbourhood socioeconomic measures were used. Questionnaire responses were linked with cancer registrations (to December 2013), records for hospital inpatient stays, emergency department presentations, death information (to December 2015), and Medicare and Pharmaceutical Benefits claims for subsidised procedures and medicines. Proportions of socioeconomic survival differences explained by prognostic factors were quantified using multiple Cox proportional hazards regression. RESULTS: 1720 eligible participants were diagnosed with colorectal cancer after recruitment: 1174 colon and 546 rectal cancers. Significant colon cancer survival differences were only observed for neighbourhood socioeconomic measure (p = 0.033): HR = 1.55; 95% CI 1.09-2.19 for lowest versus highest quartile, and disease-related factors explained 95% of this difference. For rectal cancer, patient- and disease-related factors were the main drivers of neighbourhood survival differences (28-36%), while these factors and treatment-related factors explained 24-41% of individual socioeconomic differences. However, differences remained significant for rectal cancer after adjusting for all these factors. CONCLUSION: In this large contemporary Australian cohort, we identified several drivers of socioeconomic disparities in colorectal cancer survival. Understanding of the role these contributors play remains incomplete, but these findings suggest that improving access to optimal care may significantly reduce these survival disparities.

Health system costs and days in hospital for colorectal cancer patients in New South Wales, Australia.

INTRODUCTION: Colorectal cancer (CRC) care costs the Australian healthcare system more than any other cancer. We estimated costs and days in hospital for CRC cases, stratified by site (colon/rectal cancer) and disease stage, to inform detailed analyses of CRC-related healthcare. METHODS: Incident CRC patients were identified using the Australian 45 and Up Study cohort linked with cancer registry records. We analysed linked hospital admission records, emergency department records, and reimbursement records for government-subsidised medical services and prescription medicines. Cases' health system costs (2020 Australian dollars) and hospital days were compared with those for cancer-free controls (matched by age, sex, geography, smoking) to estimate excess resources by phase of care, analysed by sociodemographic, health, and disease characteristics. RESULTS: 1200 colon and 546 rectal cancer cases were diagnosed 2006-2013, and followed up to June 2016. Eighty-nine percent of cases had surgery, chemotherapy or radiotherapy, and excess costs were predominantly for hospitalisations. Initial phase (12 months post-diagnosis) mean excess health system costs were $50,434 for colon and $60,877 for rectal cancer cases, with means of 16 and 18.5 excess hospital days, respectively. The annual continuing mean excess costs were $6,779 (colon) and $8,336 (rectal), with a mean of 2 excess hospital days each. Resources utilised (costs and days) in these phases increased with more advanced disease, comorbidities, and younger age. Mean excess costs in the year before death were $74,952 (colon) and $67,733 (rectal), with means of 34 and 30 excess hospital days, respectively-resources utilised were similar across all characteristics, apart from lower costs for cases aged ≥75 at diagnosis. CONCLUSIONS: Health system costs and hospital utilisation for CRC care are greater for people with more advanced disease. These findings provide a benchmark, and will help inform future cost-effectiveness analyses of potential approaches to CRC screening and treatment.

Cancer incidence and cancer death in relation to tobacco smoking in a population-based Australian cohort study.

Tobacco smoke is a known carcinogen, but the magnitude of smoking-related cancer risk depends on country-specific, generational smoking patterns. We quantified cancer risk in relation to smoking in a population-based cohort, the 45 and Up Study (2006-2009) in New South Wales, Australia. Cox proportional hazards regressions estimated adjusted hazard ratios (HR) by self-reported smoking history at baseline (2006-2009) for incident, primary cancers via linkage to cancer registry data to 2013 and cancer death data to 2015. Among 229 028 participants aged ≥45 years, 18 475 cancers and 5382 cancer deaths occurred. Current-smokers had increased risks of all cancers combined (HR = 1.42, 95% confidence interval [CI], 1.34-1.51), cancers of the lung (HR = 17.66, 95%CI, 14.65-21.29), larynx (HR = 11.29, 95%CI, 5.49-23.20), head-and-neck (HR = 2.53, 95%CI, 1.87-3.41), oesophagus (HR = 3.84, 95%CI, 2.33-6.35), liver (HR = 4.07, 95%CI, 2.55-6.51), bladder (HR = 3.08, 95%CI, 2.00-4.73), pancreas (HR = 2.68, 95%CI, 1.93-3.71), colorectum (HR = 1.31, 95%CI, 1.09-1.57) and unknown primary site (HR = 3.26, 95%CI, 2.19-4.84) versus never-smokers. Hazards increased with increasing smoking intensity; compared to never-smokers, lung cancer HR = 9.22 (95%CI, 5.14-16.55) for 1-5 cigarettes/day and 38.61 (95%CI, 25.65-58.13) for >35 cigarettes/day. Lung cancer risk was lower with quitting at any age but remained higher than never-smokers for quitters aged >25y. By age 80y, an estimated 48.3% of current-smokers (41.1% never-smokers) will develop cancer, and 14% will develop lung cancer, including 7.7% currently smoking 1-5 cigarettes/day and 26.4% for >35 cigarettes/day (1.0% never-smokers). Cancer risk for Australian smokers is significant, even for 'light' smokers. These contemporary estimates underpin the need for continued investment in strategies to prevent smoking uptake and facilitate cessation, which remain key to reducing cancer morbidity and mortality worldwide.

Patterns of care for men with prostate cancer: the 45 and Up Study.

OBJECTIVES: To describe patterns of care in New South Wales for men with prostate cancer, and to ascertain factors associated with receiving different types of treatment. DESIGN: Individual patient data record linkage study. SETTING, PARTICIPANTS: 4003 New South Wales men aged 45 years or more enrolled in the population-based 45 and Up Study in whom prostate cancer was first diagnosed during 2006-2013. MAIN OUTCOME MEASURES: Prostate cancer treatment type received; factors statistically associated with treatment received; proportions of patients who consulted radiation oncologists prior to treatment. RESULTS: In total, 1619 of 4003 patients underwent radical prostatectomy (40%), 893 external beam radiotherapy (EBRT) (22%), 183 brachytherapy (5%), 87 chemotherapy (2%), 373 androgen deprivation therapy alone (9%), and 848 no active treatment (21%). 205 of 1628 patients who had radical prostatectomies (13%) had radiation oncology consultations prior to surgery. Radical prostatectomy was more likely for patients aged 45-59 years, with regional stage disease, living 100 km or more from the nearest radiotherapy centre, having partners, or having private health insurance, while lower physical functioning, obesity, and living in areas of greater socio-economic disadvantage reduced the likelihood. EBRT was more likely for patients aged 70-79 years, with non-localised or unknown stage disease, living less than 100 km from the nearest radiotherapy centre, or not having private health insurance, while the likelihood was lower for patients aged 45-59 years or more than 80 years and for those who had several comorbid conditions. CONCLUSIONS: Men with prostate cancer were twice as likely to have radical prostatectomy as to receive EBRT, and fewer than one in seven had consulted radiation oncologists prior to prostatectomy. The treatment received was influenced by several socio-demographic factors. Given the treatment-specific side effects and costs, policies that affect access to different treatments for prostate cancer should be reviewed.

Large-scale systematic analysis of exposure to multiple cancer risk factors and the associations between exposure patterns and cancer incidence.

Exposures to cancer risk factors such as smoking and alcohol are not mutually independent. We aimed to identify risk factor exposure patterns and their associations with sociodemographic characteristics and cancer incidence. We considered 120,771 female and, separately, 100,891 male participants of the Australian prospective cohort 45 and Up Study. Factor analysis grouped 36 self-reported variables into 8 combined factors each for females (largely representing 'smoking', 'alcohol', 'vigorous exercise', 'age at childbirth', 'Menopausal Hormone Therapy', 'parity and breastfeeding', 'standing/sitting', 'fruit and vegetables') and males (largely representing 'smoking', 'alcohol', 'vigorous exercise', 'urology and health', 'moderate exercise', 'standing/sitting', 'fruit and vegetables', 'meat and BMI'). Associations with cancer incidence were investigated using multivariable logistic regression (4-8 years follow-up: 6193 females, 8749 males diagnosed with cancer). After multiple-testing correction, we identified 10 associations between combined factors and cancer incidence for females and 6 for males, of which 14 represent well-known relationships (e.g. bowel cancer: females 'smoking' factor Odds Ratio (OR) 1.16 (95% Confidence Interval (CI) 1.08-1.25), males 'smoking' factor OR 1.15 (95% CI 1.07-1.23)), providing evidence for the validity of this approach. The catalogue of associations between exposure patterns, sociodemographic characteristics, and cancer incidence can help inform design of future studies and targeted prevention programmes.

Health services costs for lung cancer care in Australia: Estimates from the 45 and Up Study.

BACKGROUND: Of all cancer types, healthcare for lung cancer is the third most costly in Australia, but there is little detailed information about these costs. Our aim was to provide detailed population-based estimates of health system costs for lung cancer care, as a benchmark prior to wider availability of targeted therapies/immunotherapy and to inform cost-effectiveness analyses of lung cancer screening and other interventions in Australia. METHODS: Health system costs were estimated for incident lung cancers in the Australian 45 and Up Study cohort, diagnosed between recruitment (2006-2009) and 2013. Costs to June 2016 included services reimbursed via the Medicare Benefits Schedule, medicines reimbursed via the Pharmaceutical Benefits Scheme, inpatient hospitalisations, and emergency department presentations. Costs for cases and matched, cancer-free controls were compared to derive excess costs of care. Costs were disaggregated by patient and tumour characteristics. Data for more recent cases identified in hospital records provided preliminary information on targeted therapy/immunotherapy. RESULTS: 994 eligible cases were diagnosed with lung cancer 2006-2013; 51% and 74% died within one and three years respectively. Excess costs from one-year pre-diagnosis to three years post-diagnosis averaged ~$51,900 per case. Observed costs were higher for cases diagnosed at age 45-59 ($67,700) or 60-69 ($63,500), and lower for cases aged ≥80 ($29,500) and those with unspecified histology ($31,700) or unknown stage ($36,500). Factors associated with lower costs generally related to shorter survival: older age (p<0.0001), smoking (p<0.0001) and unknown stage (p = 0.002). There was no evidence of differences by year of diagnosis or sex (both p>0.50). For 465 cases diagnosed 2014-2015, 29% had subsidised molecular testing for targeted therapy/immunotherapy and 4% had subsidised targeted therapies. CONCLUSIONS: Lung cancer healthcare costs are strongly associated with survival-related factors. Costs appeared stable over the period 2006-2013. This study provides a framework for evaluating the health/economic impact of introducing lung cancer screening and other interventions in Australia.