Individual and area level factors associated with the breast cancer diagnostic-treatment interval in Queensland, Australia.

BACKGROUND: Delays to breast cancer treatment can lead to more aggressive and extensive treatments, increased expenses, increased psychological distress, and poorer survival. We explored the individual and area level factors associated with the interval between diagnosis and first treatment in a population-based cohort in Queensland, Australia. METHODS: Data from 3216 Queensland women aged 20 to 79, diagnosed with invasive breast cancer (ICD-O-3 C50) between March 2010 and June 2013 were analysed. Diagnostic dates were sourced from the Queensland Cancer Registry and treatment dates were collected via self-report. Diagnostics-treatment intervals were modelled using flexible parametric survival methods. RESULTS: The median interval between breast cancer diagnosis and first treatment was 15 days, with an interquartile range of 9-26 days. Longer diagnostic-treatment intervals were associated with a lack of private health coverage, lower pre-diagnostic income, first treatments other than breast conserving surgery, and residence outside a major city. The model explained a modest 13.7% of the variance in the diagnostic-treatment interval [Formula: see text]. Sauerbrei's D was 0.82, demonstrating low to moderate discrimination performance. CONCLUSION: Whilst this study identified several individual- and area-level factors associated with the time between breast cancer diagnosis and first treatment, much of the variation remained unexplained. Increased socioeconomic disadvantage appears to predict longer diagnostic-treatment intervals. Though some of the differences are small, many of the same factors have also been linked to screening and diagnostic delay. Given the potential for accumulation of delay at multiple stages along the diagnostic and treatment pathway, identifying and applying effective strategies address barriers to timely health care faced by socioeconomically disadvantaged women remains a priority.

Geographical and spatial disparities in the incidence and survival of rare cancers in Australia.

Rare cancers collectively account for around a quarter of cancer diagnoses and deaths. However, epidemiological studies are sparse. We describe spatial and geographical patterns in incidence and survival of rare cancers across Australia using a population-based cancer registry cohort of rare cancer cases diagnosed among Australians aged at least 15 years, 2007 to 2016. Rare cancers were defined using site- and histology-based categories from the European RARECARE study, as individual cancer types having crude annual incidence rates of less than 6/100 000. Incidence and survival patterns were modelled with generalised linear and Bayesian spatial Leroux models. Spatial heterogeneity was tested using the maximised excess events test. Rare cancers (n = 268 070) collectively comprised 22% of all invasive cancer diagnoses and accounted for 27% of all cancer-related deaths in Australia, 2007 to 2016 with an overall 5-year relative survival of around 53%. Males and those living in more remote or more disadvantaged areas had higher incidence but lower survival. There was substantial evidence for spatial variation in both incidence and survival for rare cancers between small geographical areas across Australia, with similar patterns so that those areas with higher incidence tended to have lower survival. Rare cancers are a substantial health burden in Australia. Our study has highlighted the need to better understand the higher burden of these cancers in rural and disadvantaged regions where the logistical challenges in their diagnosis, treatment and support are magnified.

Cancer statistics in China, 2015.

With increasing incidence and mortality, cancer is the leading cause of death in China and is a major public health problem. Because of China's massive population (1.37 billion), previous national incidence and mortality estimates have been limited to small samples of the population using data from the 1990s or based on a specific year. With high-quality data from an additional number of population-based registries now available through the National Central Cancer Registry of China, the authors analyzed data from 72 local, population-based cancer registries (2009-2011), representing 6.5% of the population, to estimate the number of new cases and cancer deaths for 2015. Data from 22 registries were used for trend analyses (2000-2011). The results indicated that an estimated 4292,000 new cancer cases and 2814,000 cancer deaths would occur in China in 2015, with lung cancer being the most common incident cancer and the leading cause of cancer death. Stomach, esophageal, and liver cancers were also commonly diagnosed and were identified as leading causes of cancer death. Residents of rural areas had significantly higher age-standardized (Segi population) incidence and mortality rates for all cancers combined than urban residents (213.6 per 100,000 vs 191.5 per 100,000 for incidence; 149.0 per 100,000 vs 109.5 per 100,000 for mortality, respectively). For all cancers combined, the incidence rates were stable during 2000 through 2011 for males (+0.2% per year; P = .1), whereas they increased significantly (+2.2% per year; P < .05) among females. In contrast, the mortality rates since 2006 have decreased significantly for both males (-1.4% per year; P < .05) and females (-1.1% per year; P < .05). Many of the estimated cancer cases and deaths can be prevented through reducing the prevalence of risk factors, while increasing the effectiveness of clinical care delivery, particularly for those living in rural areas and in disadvantaged populations.

Long-term childhood cancer survival in Australia using period estimation.

Estimates of childhood cancer survival are usually reported at 5 years after diagnosis only. Using cases prevalent between 2014 and 2018 from the population-based Australian Childhood Cancer Registry, we used the period method to calculate relative survival up to 20 years post diagnosis by cancer type. Twenty-year relative survival for all childhood cancers combined (n = 14,353) was 83.8% (95% confidence interval [CI] = 82.6%-85.0%). Survival decreased only slightly after 10 years for most childhood cancers, except for some types of brain and liver tumours. These contemporary estimates of long-term survival provide valuable information to assist childhood cancer patients and their families in planning for the future.

Childhood cancer survival and avoided deaths in Australia, 1983-2016.

BACKGROUND: Large improvements in childhood cancer survival have been reported over recent decades. Data from cancer registries have the advantage of providing a 'whole of population' approach to gauge the success of cancer control efforts. OBJECTIVES: The aim of this study was to investigate recent survival estimates for children diagnosed with cancer Australia and to examine the extent of changes in survival over the last 35 years. For the first time, we also estimated the number of deaths among Australian children that were potentially avoided due to improvements in survival. METHODS: A retrospective, population-based cohort study design was used. Case information was extracted from the Australian Childhood Cancer Registry for 1983-2016, with follow-up to 31 December 2017. Eligible children were aged 0-14 with a basis of diagnosis other than autopsy or death certificate only. Five-year relative survival was calculated using the semi-complete cohort method for three diagnosis periods (1983-1994, 1995-2006 and 2007-2016), and changes in survival over time were assessed via flexible parametric models. Avoided deaths within 5 years for those diagnosed between 1995 and 2016 were estimated under the assumption that survival rates remained the same as for 1983-1994. RESULTS: Overall 5-year survival within the study cohort (n = 20,871) increased from 72.8% between 1983 and1994 to 86.1% between 2007 and 2016, equating to an adjusted excess mortality hazard ratio of 1.82 (95% confidence interval 1.67, 1.97). Most cancers showed improvements in survival; other gliomas, hepatoblastoma and osteosarcoma were exceptions. Among children diagnosed between 1995 and 2016, 38.7% of expected deaths within 5 years of diagnosis (n = 1537 of 3970) were avoided due to temporal improvements in survival. CONCLUSIONS: Survival for childhood cancer has continued to improve over recent years, thanks mainly to ongoing progress in treatment development combined with improved supportive care. Providing innovative measures of survival, such as avoided deaths, may assist with understanding outcome data produced by cancer registries.

Temporal changes in childhood cancer incidence and survival by stage at diagnosis in Australia, 2000-2017.

BACKGROUND: The Toronto Paediatric Cancer Stage Guidelines are a compendium of staging systems developed to facilitate collection of consistent and comparable data on stage at diagnosis for childhood cancers by cancer registries. MATERIAL AND METHODS: This retrospective, observational cohort study investigated changes in stage-specific incidence and survival for children diagnosed between 2000-2008 compared to 2009-2017 using the population-based Australian Childhood Cancer Registry. Information on mortality for each patient was available to 31st December 2020. Shifts in incidence by stage were evaluated using chi-square tests, and differences in stage-specific five-year observed survival for all causes of death over time were assessed using flexible parametric models. RESULTS: Stage was assigned according to the Toronto Guidelines for 96% (n = 7944) of the total study cohort (n = 8292). Changes in the distribution of incidence by stage between the two diagnosis periods were observed for retinoblastoma, with stage 0 increasing from 26% to 37% of cases (p = 0.02), and hepatoblastoma, with metastatic disease increasing from 22% to 39% of cases (p = 0.04). There were large gains in stage-specific survival over time for stage IV rhabdomyosarcoma (five-year adjusted mortality hazard ratio for 2009-2017 compared to 2000-2008 of 0.38, 95% CI 0.19-0.77; p = 0.01), stage M3 for medulloblastoma (HR = 0.41, 95% CI 0.21-0.79; p = 0.01) and metastatic neuroblastoma excluding stage MS (HR = 0.61, 95% CI 0.44-0.84; p < 0.01). CONCLUSION: These results indicate that improvements in childhood cancer survival in Australia are most likely due to refined management rather than changes in stage at diagnosis, particularly for metastatic solid tumours. Wide international uptake of the Toronto Guidelines will allow comprehensive evaluation of differences in survival between countries.

Treatment intervals and survival for women diagnosed with early breast cancer in Queensland: the Breast Cancer Outcomes Study, a population-based cohort study.

OBJECTIVES: To assess associations between breast cancer-specific survival and timeliness of treatment, based on 2020 Australian guidelines for the treatment of early breast cancer. DESIGN: Population-based cohort study; analysis of linked Queensland Cancer Register, patient medical record, and National Death Index data, supplemented by telephone interviews. SETTING, PARTICIPANTS: Women aged 20-79 years diagnosed with invasive breast cancer during 1 March 2010 - 30 June 2013, followed to 31 December 2020. MAIN OUTCOME MEASURES: Breast cancer-specific survival for women who received or did not receive treatment within the recommended timeframe, overall and for six treatment intervals; optimal cut-points for each treatment interval; characteristics of women for whom treatment was not provided within the recommended timeframe. RESULTS: Of 5426 eligible women, 4762 could be invited for interviews; complete data were available for 3044 women (56% of eligible women, 65% of invited women). Incomplete compliance with guideline interval recommendations was identified for 1375 women (45%); their risk of death from breast cancer during the follow-up period was greater than for those for whom guideline compliance was complete (adjusted hazard ratio [aHR], 1.43; 95% confidence interval [CI], 1.04-1.96). Risk of death was greater for women for whom the diagnosis to surgery interval exceeded 29 days (aHR, 1.76; 95% CI, 1.19-2.59), the surgery to chemotherapy interval exceeded 36 days (aHR, 1.63; 95% CI, 1.13-2.36), or the chemotherapy to radiotherapy interval exceeded 31 days (aHR, 1.83; 95% CI, 1.19-2.80). Treatment intervals longer than recommended were more frequent for women for whom breast cancer was detected by public facility screening (adjusted odds ratio [aOR], 1.58; 95% CI, 1.22-2.04) or by symptoms (aOR, 1.39; 95% CI, 1.09-1.79) than when cancer had been detected in private facilities, and for women without private health insurance (aOR, 1.96; 95% CI, 1.66-2.32) or living outside major cities (aOR, 1.38; 95% CI, 1.18-1.62). CONCLUSIONS: Breast cancer-specific survival was poorer for women for whom the diagnosis to surgery, surgery to chemotherapy, or chemotherapy to radiotherapy intervals exceeded guideline-recommended limits. Our findings support 2020 Australian guideline recommendations regarding timely care.

A prognostic survival model for women diagnosed with invasive breast cancer in Queensland, Australia.

PURPOSE: Prognostic models can help inform patients on the future course of their cancer and assist the decision making of clinicians and patients in respect to management and treatment of the cancer. In contrast to previous studies considering survival following treatment, this study aimed to develop a prognostic model to quantify breast cancer-specific survival at the time of diagnosis. METHODS: A large (n = 3323), population-based prospective cohort of women were diagnosed with invasive breast cancer in Queensland, Australia between 2010 and 2013, and followed up to December 2018. Data were collected through a validated semi-structured telephone interview and a self-administered questionnaire, along with data linkage to the Queensland Cancer Register and additional extraction from medical records. Flexible parametric survival models, with multiple imputation to deal with missing data, were used. RESULTS: Key factors identified as being predictive of poorer survival included more advanced stage at diagnosis, higher tumour grade, "triple negative" breast cancers, and being symptom-detected rather than screen detected. The Harrell's C-statistic for the final predictive model was 0.84 (95% CI 0.82, 0.87), while the area under the ROC curve for 5-year mortality was 0.87. The final model explained about 36% of the variation in survival, with stage at diagnosis alone explaining 26% of the variation. CONCLUSIONS: In addition to confirming the prognostic importance of stage, grade and clinical subtype, these results highlighted the independent survival benefit of breast cancers diagnosed through screening, although lead and length time bias should be considered. Understanding what additional factors contribute to the substantial unexplained variation in survival outcomes remains an important objective.

Supportive care needs and psychosocial outcomes of rural versus urban women with breast cancer.

OBJECTIVE: To identify whether supportive care needs vary according to remoteness and area-level socio-economic status and to identify the combinations of socio-demographic, area-level and health factors that are associated with poorer quality of life, psychological distress and severity of unmet supportive care needs. METHODS: Cross sectional data was collected from women with a breast cancer diagnosis (n = 2635) in Queensland, Australia, through a telephone survey including socio-demographic, health, psychosocial and supportive care needs measures. Hierarchical regression and cluster analyses were applied to assess the predictors of unmet need and psychosocial outcomes and to identify socio-demographic and health status profiles of women, comparing their level of unmet needs and psychosocial outcomes. RESULTS: Women living in outer regional areas reported the highest severity of unmet need in the patient care domain. Greater unmet need for health systems and information and patient care was also evident for those in moderately and most disadvantaged areas. Three clusters were identified reflecting (1) older women with poorer health and lower education (19%); (2) younger educated women with better health and private insurance (61%); and (3) physically active women with localised cancer who had completed treatment (20%). Poorer outcomes were evident in the first two of these clusters. CONCLUSIONS: This better understanding of the combinations of characteristics associated with poorer psychosocial outcomes and higher unmet need can be used to identify women with higher supportive care needs early and to target interventions.

Changes in cancer incidence and survival among Aboriginal and Torres Strait Islander children in Australia, 1997-2016.

BACKGROUND: This study reports cancer incidence and survival among Aboriginal and Torres Strait Islander children and other Australian children, and assesses changes over time. PROCEDURE: Data were from the population-based Australian Childhood Cancer Registry. The study comprised children aged under 15 diagnosed between 1997 and 2016 and with mortality follow-up until 31 December 2017. Incidence trends were analysed using JoinPoint regression. Five-year cancer-specific survival was calculated using the semi-complete approach with survival comparisons made using multivariable flexible parametric models. RESULTS: Aboriginal and Torres Strait Islander children accounted for 506 of 13,299 eligible cases (3.8%). Incidence rates for Aboriginal and Torres Strait Islander children across the study period increased by 2.3% annually (95% confidence interval [CI]: +0.6% to +4.0%) and for other Australian children increased by 0.6% annually (95% CI: +0.3% to +0.9%; p = .05). Nonetheless, cancer incidence was consistently lower for Aboriginal and Torres Strait Islander children, with an incidence rate ratio of 0.73 (95% CI: 0.62-0.85; p < .01) between 2012 and 2016. Survival for Aboriginal and Torres Strait Islander children with solid tumours was 70.6% (95% CI: 62.5%-77.3%) and for other Australian children was 83.5% (95% CI: 82.3%-84.7%; p < .01), with indications of this difference diminishing in recent years. CONCLUSIONS: Improvements in identification, particularly in urban areas, most likely accounts for the greater increase in cancer incidence rates among Aboriginal and Torres Strait Islander children. Examination of data on stage at diagnosis and treatment may provide important insights into survival for children with solid tumours.

Risk of extracolonic second primary cancers following a primary colorectal cancer: a systematic review and meta-analysis.

PURPOSE: The purpose of the study is to assess the global risk of extracolonic secondary primary cancers (SPCs) in patients with colorectal cancer (CRC). METHODS: Studies of SPC in patients with CRC were included if they reported the standardised incidence ratio (SIR) for extracolonic SPCs in patients with CRC compared with the general population. Pooled summary estimates were calculated using a random-effects model. RESULTS: A total of 7,716,750 patients with CRC from 13 retrospective cohort studies that reported extracolonic SPC incidence were included. The overall risk of several SPCs was significantly higher in patients with CRC compared with the general population, including cancers of the urinary bladder (pooled SIR 1.19, 95% confidence interval (CI) 1.06-1.33; p = 0.003), female genital tract (1.88, 1.07-3.31; p = 0.03), kidney (1.50, 1.19-1.89; p = 0.0007), thorax (lung, bronchus and mediastinum) (1.16, 1.01-1.32; p = 0.03), small intestine (4.26, 2.58-7.01; p < 0.0001), stomach (1.22, 1.07-1.39; p = 0.003), and thyroid (1.40, 1.28-1.53; p < 0.0001), as well as melanoma (1.28, 1.01-1.62; p = 0.04). There was also a decreased risk of developing cancer of the gall bladder (0.75, 0.60-0.94; p = 0.01). CONCLUSION: Patients with CRC had a significantly increased risk of extracolonic SPCs compared with the general population. These findings highlight the need to develop research strategies for the management of second primary cancer in patients with CRC.

Tobacco smoking and risk of thyroid cancer according to BRAFV600E mutational subtypes.

OBJECTIVE: Smoking has been associated with a reduced risk of thyroid cancer, but whether the association varies between higher- and lower-risk cancers remains unclear. We aimed to assess the association between smoking and risk of thyroid cancer overall as well as by tumour BRAF mutational status as a marker of potentially higher-risk cancer. DESIGN AND PATIENTS: We recruited 1013 people diagnosed with thyroid cancer and 1057 population controls frequency-matched on age and sex. METHODS: Multivariable logistic regression was used to assess the association overall and in analyses stratified by tumour characteristics. We used sensitivity analysis to assess the potential for selection bias. RESULTS: We found little evidence of an association with current smoking (odds ratio [OR] = 0.93; 95% confidence interval [CI]: 0.69-1.26; current vs. never smoking), but a higher number of pack-years of smoking was associated with a lower risk of thyroid cancer (OR = 0.75; 95% CI: 0.57-0.99; ≥20 pack-years vs. never). However, after correcting for potential selection bias, we observed a statistically significant inverse association between current smoking and risk of thyroid cancer (bias-corrected OR = 0.65; 95% CI: 0.51-0.83). Those with BRAF-positive cancers were less likely to be current smokers than those with BRAF-negative cancers (prevalence ratio: 0.79; 95% CI: 0.62-0.99). CONCLUSION: We found smoking was inversely related to thyroid cancer risk and, in particular, current smoking was associated with a reduced risk of potentially more aggressive BRAF-positive than the likely more indolent BRAF-negative papillary thyroid cancers.

Long-term deaths from melanoma according to tumor thickness at diagnosis.

There is little long-term follow-up information about how the number of melanoma deaths and case fatality vary over time according to the measured thickness of melanoma at diagnosis. This population-based longitudinal cohort study examines patterns and trends in case fatality among 44,531 people in Queensland (Australia) diagnosed with a single invasive melanoma (International Classification of Diseases for Oncology, third revision [ICD-O-3], C44, Morphology 872-879) between 1987 and 2011, including 11,883 diagnosed between 1987 and 1996, with up to 20 years follow-up (to December 2016). The 20-year case fatality increased by thickness, with the percentage of melanoma deaths within 20 years of diagnosis being up to 4.8% for melanomas with measured thickness <0.80 mm, 10.6% for tumors 0.8 to <1.0 mm and generally more than 30% for melanomas measuring 3 mm and more. For melanomas <1.0 mm, most deaths occurred between 5 and 20 years after diagnosis, whereas for thicker melanomas the reverse was true with most deaths occurring within the first 5 years. Five-year case fatality decreased over successive calendar time periods for melanomas <1.0 mm, but not for melanomas ≥1.0 mm. These findings demonstrate that the time course for fatal melanomas varies markedly according to tumor thickness at diagnosis. Improved understanding of the patient factors and characteristics of melanomas, in addition to tumor thickness, which increase the likelihood of progression, is needed to guide clinical diagnosis, communication with patients and ongoing surveillance pathways of patients with potentially fatal lesions.

Factors associated with being diagnosed with high severity of breast cancer: a population-based study in Queensland, Australia.

PURPOSE: This study explores factors that are associated with the severity of breast cancer (BC) at diagnosis. METHODS: Interviews were conducted among women (n = 3326) aged 20-79 diagnosed with BC between 2011 and 2013 in Queensland, Australia. High-severity cancers were defined as either Stage II-IV, Grade 3, or having negative hormone receptors at diagnosis. Logistic regression models were used to estimate odds ratios (ORs) of high severity BC for variables relating to screening, lifestyle, reproductive habits, family history, socioeconomic status, and area disadvantage. RESULTS: Symptom-detected women had greater odds (OR 3.38, 2.86-4.00) of being diagnosed with high-severity cancer than screen-detected women. Women who did not have regular mammograms had greater odds (OR 1.78, 1.40-2.28) of being diagnosed with high-severity cancer than those who had mammograms biennially. This trend was significant in both screen-detected and symptom-detected women. Screen-detected women who were non-smokers (OR 1.77, 1.16-2.71), postmenopausal (OR 2.01, 1.42-2.84), or employed (OR 1.46, 1.15-1.85) had greater odds of being diagnosed with high-severity cancer than those who were current smokers, premenopausal, or unemployed. Symptom-detected women being overweight (OR 1.67, 1.31-2.14), postmenopausal (OR 2.01, 1.43-2.82), had hormone replacement therapy (HRT) < 2 years (OR 1.60, 1.02-2.51) had greater odds of being diagnosed with high-severity cancer than those of healthy weight, premenopausal, had HRT > 10 years. CONCLUSION: Screen-detected women and women who had mammograms biennially had lower odds of being diagnosed with high-severity breast cancer, which highlighted the benefit of regular breast cancer screening. Women in subgroups who are more likely to have more severe cancers should be particularly encouraged to participate in regular mammography screening.

Global trends in incidence rates of childhood liver cancers: A systematic review and meta-analysis.

BACKGROUND: Childhood liver cancers are relatively rare, hence inferences on incidence trends over time are limited by lack of precision in most studies. OBJECTIVE: To conduct a systematic review and meta-analysis of published contemporary trends on childhood liver cancer incidence rates worldwide. DATA SOURCES: PubMed, EMBASE, CINAHL, Web of Science. STUDY SELECTION AND DATA EXTRACTION: English-language peer-reviewed articles published from 1 January 2008 to 1 December 2019 that presented quantitative estimates of incidence trends for childhood liver cancer and diagnostic subgroups. Review was conducted per PRISMA guidelines. Two authors independently extracted data and critically assessed studies. SYNTHESIS: Random effects meta-analysis models were used to estimate pooled incidence trends by diagnostic subgroups. Heterogeneity was measured using the Q and I2 statistics and publication bias evaluated using Egger's test. RESULTS: Eighteen studies were included, all based on population-based cancer registries. Trends were reported on average for 18 years. Overall pooled estimates of the annual percentage change (APC) were 1.4 (95% confidence interval [CI] 0.5, 2.3) for childhood liver cancers, 2.8 (95% CI 1.8, 3.8) for hepatoblastoma and -3.0 (95% CI -11.0, 4.9) for hepatocellular carcinoma. Sub-group analysis by region indicated increasing trends for childhood liver cancers in North America/Europe/Australia (APC 1.7, 95% CI 0.7, 2.8) whereas corresponding trends were stable in Asia (APC 1.4, 95%CI -0.3, 2.7). Publication bias was not detected for any of these analyses. The I2 statistic indicated that the heterogeneity among included studies was low for combined liver cancers, moderate for hepatoblastoma and high for hepatocellular carcinoma. CONCLUSIONS: Incidence is increasing for childhood liver cancers and the most commonly diagnosed subgroup hepatoblastoma. Lack of knowledge of the etiology of childhood liver cancers limited the ability to understand the reasons for observed incidence trends. This review highlighted the need for ongoing monitoring of incidence trends and etiological studies.

Second primary cancers in people who had cancer as children: an Australian Childhood Cancer Registry population-based study.

OBJECTIVE: To investigate the incidence of second primary cancers in people diagnosed with cancer during childhood. DESIGN, SETTING: Retrospective, population-based study; analysis of Australian Childhood Cancer Registry data. PARTICIPANTS: People alive at least two months after being diagnosed before the age of 15 years with a primary cancer, 1983-2013, followed until 31 December 2015 (2-33 years' follow-up). MAIN OUTCOME MEASURES: Risks of second primary cancer compared with the general population, expressed as standardised incidence ratios (SIRs). RESULTS: Among 18 230 people diagnosed with cancer during childhood, 388 (2%) were later diagnosed with second primary cancers; the estimated 30-year cumulative incidence of second cancers was 4.4% (95% CI, 3.8-5.0%). The risk of a new primary cancer was five times as high as for the general population (SIR, 5.13; 95% CI, 4.65-5.67). Relative risk of a second primary cancer was greatest for people who had childhood rhabdomyosarcoma (SIR, 19.9; 95% CI, 14.4-27.6). Relative risk was particularly high for children who had undergone both chemotherapy and radiotherapy (SIR, 9.80; 95% CI, 8.35-11.5). Relative risk peaked during the 5 years following the first diagnosis (2 to less than 5 years: SIR, 10.3; 95% CI, 8.20-13.0), but was still significant at 20-33 years (SIR, 2.58; 95% CI, 2.02-3.30). The most frequent second primary cancers were thyroid carcinomas (65 of 388, 17%) and acute myeloid leukaemias (57, 15%). CONCLUSIONS: Survivors of childhood cancer remain at increased risk of a second primary cancer well into adulthood. As the late effects of cancer treatment probably contribute to this risk, treatments need to be refined and their toxicity reduced, without reducing their benefit for survival.

The incidence of childhood cancer in Australia, 1983-2015, and projections to 2035.

OBJECTIVES: To describe changes in childhood cancer incidence in Australia, 1983-2015, and to estimate projected incidence to 2035. DESIGN, SETTING: Population-based study; analysis of Australian Childhood Cancer Registry data for the 20 547 children under 15 years of age diagnosed with cancer in Australia between 1983 and 2015. MAIN OUTCOME MEASURES: Incidence rate changes during 1983-2015 were assessed by joinpoint regression, with rates age-standardised to the 2001 Australian standard population. Incidence projections to 2035 were estimated by age-period-cohort modelling. RESULTS: The overall age-standardised incidence rate of childhood cancer increased by 34% between 1983 and 2015, increasing by 1.2% (95% CI, +0.5% to +1.9%) per annum between 2005 and 2015. During 2011-2015, the mean annual number of children diagnosed with cancer in Australia was 770, an incidence rate of 174 cases (95% CI, 169-180 cases) per million children per year. The incidence of hepatoblastoma (annual percentage change [APC], +2.3%; 95% CI, +0.8% to +3.8%), Burkitt lymphoma (APC, +1.6%; 95% CI, +0.4% to +2.8%), osteosarcoma (APC, +1.1%; 95%, +0.0% to +2.3%), intracranial and intraspinal embryonal tumours (APC, +0.9%; 95% CI, +0.4% to +1.5%), and lymphoid leukaemia (APC, +0.5%; 95% CI, +0.2% to +0.8%) increased significantly across the period 1983-2015. The incidence rate of childhood melanoma fell sharply between 1996 and 2015 (APC, -7.7%; 95% CI, -10% to -4.8%). The overall annual cancer incidence rate is conservatively projected to rise to about 186 cases (95% CI, 175-197 cases) per million children by 2035 (1060 cases per year). CONCLUSIONS: The incidence rates of several childhood cancer types steadily increased during 1983-2015. Although the reasons for these rises are largely unknown, our findings provide a foundation for health service planning for meeting the needs of children who will be diagnosed with cancer until 2035.

Multivariate Bayesian meta-analysis: joint modelling of multiple cancer types using summary statistics.

BACKGROUND: Cancer atlases often provide estimates of cancer incidence, mortality or survival across small areas of a region or country. A recent example of a cancer atlas is the Australian cancer atlas (ACA), that provides interactive maps to visualise spatially smoothed estimates of cancer incidence and survival for 20 different cancer types over 2148 small areas across Australia. METHODS: The present study proposes a multivariate Bayesian meta-analysis model, which can model multiple cancers jointly using summary measures without requiring access to the unit record data. This new approach is illustrated by modelling the publicly available spatially smoothed standardised incidence ratios for multiple cancers in the ACA divided into three groups: common, rare/less common and smoking-related. The multivariate Bayesian meta-analysis models are fitted to each group in order to explore any possible association between the cancers in three remoteness regions: major cities, regional and remote areas across Australia. The correlation between the pairs of cancers included in each multivariate model for a group was examined by computing the posterior correlation matrix for each cancer group in each region. The posterior correlation matrices in different remoteness regions were compared using Jennrich's test of equality of correlation matrices (Jennrich in J Am Stat Assoc. 1970;65(330):904-12. https://doi.org/10.1080/01621459.1970.10481133 ). RESULTS: Substantive correlation was observed among some cancer types. There was evidence that the magnitude of this correlation varied according to remoteness of a region. For example, there has been significant negative correlation between prostate and lung cancer in major cities, but zero correlation found in regional and remote areas for the same pair of cancer types. High risk areas for specific combinations of cancer types were identified and visualised from the proposed model. CONCLUSIONS: Publicly available spatially smoothed disease estimates can be used to explore additional research questions by modelling multiple cancer types jointly. These proposed multivariate meta-analysis models could be useful when unit record data are unavailable because of privacy and confidentiality requirements.

Pancreaticoduodenectomy in a low-resection volume region: a population-level study examining the impact of hospital-volume on surgical quality and longer-term survival.

BACKGROUND: An association between higher hospital-volume and better "quality of surgery" and long-term survival has not been reported following pancreatic cancer surgery in low resection-volume regions such as in Australia. Using a population-level study, we compare "quality of surgery" and two-year survival following pancreaticoduodenectomy between Australian hospitals grouped by resection-volume. METHODS: Data on all patients undergoing pancreaticoduodenectomy for adenocarcinoma in the Australian state of Queensland, between 2001 and 2015, were obtained from the Queensland Oncology Repository. Hospitals were grouped into high (≥6 resections annually) and low (<6) volume centres. Following adjustment for case-mix, "quality-of-treatment" indicators were compared between hospital groups using multivariate logistic regression and Poisson regression analysis; and two-year cancer-specific and overall survival were compared using multivariate Cox proportional hazard models. RESULTS: Compared with high-volume centres, low-volume centres had worse two-year cancer-specific survival (Adjusted HR = 1.31; 95% CI:1.03-1.68), higher 30-day mortality (Adjusted IRR = 3.81; 95% CI: 1.36-10.62) and fewer patients received "high-quality surgery" (Adjusted OR = 0.55; 95% CI: 0.33-0.90). Differences in 30-day mortality, or "quality-of-treatment" indicators did not entirely explain the observed survival difference between hospital-volume groups. CONCLUSION: In an Australian environment, a "high" hospital-volume was significantly associated with better quality surgery and two-year survival following pancreaticoduodenectomy.

The impact of changing the prevalence of overweight/obesity and physical inactivity in Australia: An estimate of the proportion of potentially avoidable cancers 2013-2037.

Globally, 39% of the world's adult population is overweight or obese and 23% is insufficiently active. These percentages are even larger in high-income countries with 58% overweight/obese and 33% insufficiently active. Fourteen cancer types have been declared by the World Cancer Research Fund to be causally associated with being overweight or obese: oesophageal adenocarcinoma, stomach cardia, colon, rectum, liver, gallbladder, pancreas, breast, endometrium, ovary, advanced/fatal prostate, kidney, thyroid and multiple myeloma. Colon, postmenopausal breast and endometrial cancers have also been judged causally associated with physical inactivity. We aimed to quantify the proportion of cancer cases that would be potentially avoidable in Australia if the prevalence of overweight/obesity and physical inactivity in the population could be reduced. We used the simulation modelling software PREVENT 3.01 to calculate the proportion of avoidable cancers over a 25-year period under different theoretical intervention scenarios that change the prevalence of overweight/obesity and physical inactivity in the population. Between 2013 and 2037, 10-13% of overweight/obesity-related cancers in men and 7-11% in women could be avoided if overweight and obesity were eliminated in the Australian population. If everyone in the population met the Australian physical activity guidelines for cancer prevention (i.e. engaged in at least 300 min of moderate-intensity physical activity per week), an estimated 2-3% of physical inactivity-related cancers could be prevented in men (colon cancer) and 1-2% in women (colon, breast and endometrial cancers). This would translate to the prevention of up to 190,500 overweight/obesity-related cancers and 19,200 inactivity-related cancers over 25 years.