PCGF2 Acts as an Oncogenic Driver in Colon Cancer through the Upregulation of CENPE.

BACKGROUND: Colon cancer (CC) is a highly prevalent malignancy that contributes significantly to global morbidity and mortality. The polycomb group ring finger 2 (PCGF2) has been identified as a relevant factor influencing the outcomes of CC. At the same time, the centromere-associated protein E (CENPE) is implicated in promoting carcinogenesis and adversely affecting the survival of tumor patients. The primary objective of this study was to elucidate the precise impact of PCGF2 on CC and unravel the underlying mechanisms associated with CENPE. METHODS: Human normal colon epithelial cells and CC cells were utilized to investigate the differential expression of PCGF2 and CENPE. CC cell line LOVO was exploited and transfected for PCGF2 regulation. Subsequently, cell viability and proliferation were assessed using the cell counting kit 8 (CCK-8) and colony forming assay. Cell viability and proliferation were assessed using the terminal deoxynucleotidyl transferase (TdT) dUTP nick-end labeling (TUNEL) assay, while cell migration and invasion capabilities were determined using the transwell assay, and mRNA levels of cell cycle-related genes were measured for evaluating cell cycle activation. In addition, mice were used for in vivo experiments to investigate the progression of CC cells with different levels of PCGF2. Moreover, GSK-923295 was used to inhibit CENPE, followed by the evaluation of cell progression. RESULTS: PCGF2 and CENPE were upregulated in CC cell lines (p < 0.001), and upregulation/downregulation of PCGF2 led to the upregulation and downregulation of CENPE (p < 0.001). The upregulation/downregulation of PCGF2 led to an increase/decrease in viability, proliferation, migration, and invasion while suppressing/enhancing apoptosis in LOVO cells (p < 0.001), promoting cell progression. The tumor progression of LOVO cells with PCGF2 knockdown was slower (p < 0.001). The PCGF2-promoting LOVO cell progression was disrupted when CENPE was inhibited, presented by the reversely decreased viability, proliferation, migration, invasion, and cell cycle activation, and increased apoptosis (p < 0.001). CONCLUSION: PCGF2 promotes CC cell progression by upregulating CENPE, providing PCGF2 inhibition and CENPE inhibition as potential therapeutic targets for treating CC.

The association between vaping and subsequent initiation of cigarette smoking in young Australians from age 12 to 17 years: a retrospective cohort analysis using cross-sectional recall data from 5114 adolescents.

OBJECTIVE: The objective of this study was to estimate the association between vaping and subsequent initiation of smoking among Australian adolescents and explore the impact of design and analytical methods in previous studies. METHODS: We conducted a retrospective cohort analysis of cross-sectional data from 5114 Australian adolescents aged 14-17 recalling information on smoking and vaping initiation from age 12 to 17. The outcome was smoking initiation, analysed with negative-binomial regression to estimate incidence rate ratios (IRRs) for vape status (ever-vaped vs never-vaped) as a time-varying exposure. We also re-analysed using the methods of previous studies not accounting for the time-varying nature of e-cigarette exposure. RESULTS: Participants (n=5114) were retrospectively followed for 20478 person-years. After adjusting for socio-demographic variables and proxy measures of common liabilities for vaping and smoking, the rate of smoking initiation for those who ever-vaped was nearly 5 times that of those who never-vaped (IRR=4.9; 95% confidence interval: [3.9, 6.0], p<0.001), with IRRs considerably higher at younger ages. Not accounting for the time-varying nature of e-cigarette exposure in re-analysis attenuated the estimated IRR by 44%. CONCLUSIONS: Controlled analyses indicate that vaping markedly increases the risk of subsequent smoking initiation among Australian adolescents from age 12 to 17, with those aged 12, 13, and 14 bearing an alarmingly disproportionate burden of the elevated risk. Additionally, the relative risk of future smoking due to vaping may have been underestimated in other studies due to methodological differences. IMPLICATIONS FOR PUBLIC HEALTH: Our findings highlight the need for public health interventions and strict e-cigarette access laws.

Multiple myeloma survival in New South Wales, Australia, by treatment era to 2020.

OBJECTIVE: Australia has relatively high multiple myeloma (MM) incidence and mortality rates. Advancements in MM treatment over recent decades have driven improvements in MM survival in high-income countries; however, reporting in Australia is limited. We investigated temporal trends in population-wide MM survival across 3 periods of treatment advancements in New South Wales (NSW), Australia. METHODS: Individuals with an MM diagnosis in the NSW Cancer Registry between 1985 and 2015 with vital follow-up to 2020, were categorized into 3 previously defined treatment eras according to their diagnosis date (1985-1995, chemotherapy only; 1996-2007, autologous stem cell transplantation; and 2008-2015, novel agents including proteasome inhibitors and immunomodulatory drugs). Both relative survival and cause-specific survival according to Fine and Gray's competing risks cumulative incidence function were calculated by treatment era and age at diagnosis. RESULTS: Overall, 11,591 individuals were included in the study, with a median age of 70 years at diagnosis. Five-year relative survival improved over the 36-year (1985-2020) study period (31.0% in 1985-1995; 41.9% in 1996-2007; and 56.1% in 2008-2015). For individuals diagnosed before 70 years of age, the 5-year relative survival nearly doubled, from 36.5% in 1985-1995 to 68.5% in 2008-2015. Improvements for those > 70 years of age were less pronounced between 1985-1995 and 1996-2007; however, significant improvements were observed for those diagnosed in 2008-2015. Similar overall and age-specific patterns were observed for cause-specific survival. After adjustment for gender and age at diagnosis, treatment era was strongly associated with both relative and cause-specific survival (P < 0.0001). CONCLUSIONS: Survival of individuals with MM is improving in Australia with treatment advances. However, older age groups continue to experience poor survival outcomes with only modest improvements over time. Given the increasing prevalence of MM in Australia, the effects of MM treatment on quality of life, particularly in older age, warrant further attention.

Multiple myeloma incidence, mortality, and prevalence estimates and projections, Australia, 1982-2043: a statistical modelling study.

OBJECTIVES: To examine changes in multiple myeloma incidence and mortality rates during 1982-2018, and to estimate its incidence, mortality, and prevalence for 2019-2043. STUDY DESIGN: Population-based statistical modelling study; analysis of and projections based on Australian Institute of Health and Welfare multiple myeloma incidence, mortality, and survival data. SETTING: Australia, 1982-2018 (historical data) and projections to 2043. MAIN OUTCOME MEASURES: Changes in multiple myeloma incidence and mortality rates, 1982-2018, determined by joinpoint regression analysis (age-standardised to 2021 Australian population); projection of rates to 2043 based on age-period-cohort models; estimated 5- and 30-year prevalence of multiple myeloma (modified counting method). RESULTS: The incidence of multiple myeloma increased during 1982-2018 (eg, annual percentage change [APC], 2006-2018, 1.9%; 95% confidence interval [CI], 1.7-2.2%), but the mortality rate declined during 1990-2018 (APC, -0.4%; 95% CI, -0.5% to -0.2%). The age-standardised incidence rate was projected to increase by 14.9% during 2018-2043, from 8.7 in 2018 to 10.0 (95% CI, 9.4-10.7) new cases per 100 000 population in 2043; the mortality rate was projected to decline by 27.5%, from 4.0 to 2.9 (95% CI, 2.6-3.3) deaths per 100 000 population. The annual number of people newly diagnosed with multiple myeloma was estimated to increase by 89.2%, from 2120 in 2018 to 4012 in 2043; the number of deaths from multiple myeloma was projected to increase by 31.7%, from 979 to 1289. The number of people living with multiple myeloma up to 30 years after initial diagnosis was projected to increase by 163%, from 10 288 in 2018 to 27 093 in 2043, including 13 019 people (48.1%) diagnosed during the preceding five years. CONCLUSION: Although the decline in the mortality rate was projected to continue, the projected increases in the incidence and prevalence of multiple myeloma in Australia over the next 25 years indicate that investment in prevention and early detection research, and planning for prolonged treatment and care, are needed.

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.

Trends and projections of cause-specific premature mortality in Australia to 2044: a statistical modelling study.

Background: Long-term projections of premature mortality (defined as deaths age <75 years) help to inform decisions about public health priorities. This study aimed to project premature mortality rates in Australia to 2044, and to estimate numbers of deaths and potential years of life lost (PYLL) due to premature mortality overall and for 59 causes. Methods: We examined the past trends in premature mortality rates using Australian mortality data by sex, 5-year age group and 5-year calendar period up to 2019. Cigarette smoking exposure data (1945-2019) were included to project lung cancer mortality. Age-period-cohort or generalised linear models were developed and validated for each cause to project premature mortality rates to 2044. Findings: Over the 25-year period from 1990-1994 to 2015-2019, there was a 44.4% decrease in the overall age-standardised premature mortality rate. This decline is expected to continue, from 162.4 deaths/100,000 population in 2015-2019 to 141.7/100,000 in 2040-2044 (12.7% decrease). Despite declining rates, total numbers of premature deaths are projected to increase by 22.8%, rising from 272,815 deaths in 2015-2019 to 334,894 deaths in 2040-2044. This is expected to result in 1.58 million premature deaths over the 25-year period 2020-2044, accounting for 24.5 million PYLL. Of the high-level cause categories, cancer is projected to remain the most common cause of premature death in Australia by 2044, followed by cardiovascular disease, external causes (including injury, poisoning, and suicide), and respiratory diseases. Interpretation: Despite continuously declining overall premature mortality rates, the total number of premature deaths in Australia is projected to remain substantial, and cancer will continue to be the leading cause. These projections can inform the targeting of public health efforts and can serve as benchmarks against which to measure the impact of future interventions. They emphasise the ongoing importance of accelerating the prevention, early detection, and treatment of key health conditions. Funding: No funding was provided for this study.

Benefits and harms of prostate specific antigen testing according to Australian guidelines.

Guidelines for prostate specific antigen (PSA) testing in Australia recommend that men at average risk of prostate cancer who have been informed of the benefits and harms, and who decide to undergo regular testing, should be offered testing every 2 years from 50 to 69 years. This study aimed to estimate the benefits and harms of regular testing in this context. We constructed Policy1-Prostate, a discrete event microsimulation platform of the natural history of prostate cancer and prostate cancer survival, and PSA testing patterns and subsequent management in Australia. The model was calibrated to pre-PSA (before 1985) prostate cancer incidence and mortality and validated against incidence and mortality trends from 1985 to 2011 and international trials. The model predictions were concordant with trials and Australian observed incidence and mortality data from 1985 to 2011. Out of 1000 men who choose to test according to the guidelines, 36 [21-41] men will die from prostate cancer and 126 [119-133] men will be diagnosed with prostate cancer, compared with 50 [47-54] and 94 [90-98] men who do not test, respectively. During the 20 years of active PSA testing, 32.3% [25.6%-38.8%] of all PSA-test detected cancers are overdiagnosed cases that is, 30 [21-42] out of 94 [83-107] PSA-test detected cancers. Australian men choosing to test with PSA every two years from 50 to 69 will reduce their risk of ever dying from prostate cancer and incur a risk of overdiagnosis: for every man who avoids dying from prostate cancer, two will be overdiagnosed with prostate cancer between 50 and 69 years of age. Australian men, with health professionals, can use these results to inform decision-making about PSA testing.

Problems Paying Medical Bills Among Adults With Diagnosed HIV in the United States.

ABSTRACT: Problems paying medical bills may affect HIV outcomes among people with HIV (PWH), thus limiting progress toward achieving national HIV prevention goals. We analyzed nationally representative data from CDC's Medical Monitoring Project collected during 6/2018-5/2020. Among 8,108 PWH, we reported weighted percentages of characteristics and examined associations between problems paying medical bills and clinical outcomes using prevalence ratios with predicted marginal means, adjusting for potential confounding. Nineteen percent of PWH reported problems paying medical bills. Problems paying medical bills were more prevalent among persons who experienced homelessness (26.9% vs. 18.3%). People with problems paying medical bills were more likely to have adverse HIV outcomes and were more likely to have ≥1 emergency room visit (prevalence ratio [PR]: 1.59; 95% CI [1.51-1.68]) or hospitalization (PR: 1.72; 95% CI [1.55-1.91]) in the past year. Identifying PWH experiencing financial barriers and expanding access to safety net programs could improve access to care and outcomes.

Exploring HONO formation and its role in driving secondary pollutants formation during winter in the North China Plain.

Daytime HONO photolysis is an important source of atmospheric hydroxyl radicals (OH). Knowledge of HONO formation chemistry under typical haze conditions, however, is still limited. In the Multiphase chemistry experiment in Fogs and Aerosols in the North China Plain in 2018, we investigated the wintertime HONO formation and its atmospheric implications at a rural site Gucheng. Three different episodes based on atmospheric aerosol loading levels were classified: clean periods (CPs), moderately polluted periods (MPPs) and severely polluted periods (SPPs). Correlation analysis revealed that HONO formation via heterogeneous conversion of NO2 was more efficient on aerosol surfaces than on ground, highlighting the important role of aerosols in promoting HONO formation. Daytime HONO budget analysis indicated a large missing source (with an average production rate of 0.66 ± 0.26, 0.97 ± 0.47 and 1.45 ± 0.55 ppbV/hr for CPs, MPPs and SPPs, respectively), which strongly correlated with photo-enhanced reactions (NO2 heterogeneous reaction and particulate nitrate photolysis). Average OH formation derived from HONO photolysis reached up to (0.92 ± 0.71), (1.75 ± 1.26) and (1.82 ± 1.47) ppbV/hr in CPs, MPPs and SPPs respectively, much higher than that from O3 photolysis (i.e., (0.004 ± 0.004), (0.006 ± 0.007) and (0.0035 ± 0.0034) ppbV/hr). Such high OH production rates could markedly regulate the atmospheric oxidation capacity and hence promote the formation of secondary aerosols and pollutants.

Breast Cancer Risk Assessment Tools for Stratifying Women into Risk Groups: A Systematic Review.

BACKGROUND: The benefits and harms of breast screening may be better balanced through a risk-stratified approach. We conducted a systematic review assessing the accuracy of questionnaire-based risk assessment tools for this purpose. METHODS: Population: asymptomatic women aged ≥40 years; Intervention: questionnaire-based risk assessment tool (incorporating breast density and polygenic risk where available); Comparison: different tool applied to the same population; Primary outcome: breast cancer incidence; Scope: external validation studies identified from databases including Medline and Embase (period 1 January 2008-20 July 2021). We assessed calibration (goodness-of-fit) between expected and observed cancers and compared observed cancer rates by risk group. Risk of bias was assessed with PROBAST. RESULTS: Of 5124 records, 13 were included examining 11 tools across 15 cohorts. The Gail tool was most represented (n = 11), followed by Tyrer-Cuzick (n = 5), BRCAPRO and iCARE-Lit (n = 3). No tool was consistently well-calibrated across multiple studies and breast density or polygenic risk scores did not improve calibration. Most tools identified a risk group with higher rates of observed cancers, but few tools identified lower-risk groups across different settings. All tools demonstrated a high risk of bias. CONCLUSION: Some risk tools can identify groups of women at higher or lower breast cancer risk, but this is highly dependent on the setting and population.

Stigma, Discrimination, and Mental Health Outcomes Among Transgender Women With Diagnosed HIV Infection in the United States, 2015-2018.

OBJECTIVE: Transgender women with diagnosed HIV experience social and structural factors that could negatively affect their overall health and HIV-related health outcomes. We describe estimates from the Centers for Disease Control and Prevention Medical Monitoring Project (MMP) of sociodemographic characteristics, HIV stigma, discrimination, and mental health outcomes among transgender women with diagnosed HIV. METHODS: We analyzed pooled data of all transgender women with diagnosed HIV (N = 217) from the 2015 through 2018 MMP cycles. We reported unweighted frequencies, weighted percentages, and 95% CIs for all characteristics. We post-stratified data to known population totals by age, race and ethnicity, and sex at birth from the National HIV Surveillance System. RESULTS: Approximately 46% of transgender women with diagnosed HIV identified as Black or African American, 67% lived at or below the federal poverty level, 18% had experienced homelessness in the past year, 26% experienced mild to severe symptoms of depression, 30% experienced mild to severe anxiety symptoms, 32% reported physical violence by an intimate partner, and 30% reported forced sex during their lifetime. Despite 80% being very satisfied with their current HIV care, 94% experienced current HIV stigma and 20% experienced health care-related discrimination since being diagnosed with HIV. Among transgender women with diagnosed HIV who experienced discrimination, 46% and 51% experienced health care discrimination attributed to their gender and sexual orientation or sexual practices, respectively. CONCLUSIONS: Our findings underscore a need to address unmet ancillary services, such as housing, intimate partner violence, and mental health needs, and the need for strategies to reduce experiences with HIV stigma and discrimination in care for transgender women with diagnosed HIV in the United States.

Sociodemographic and Clinical Characteristics Associated With Recent Incarceration Among People With HIV, United States, 2015-2017.

OBJECTIVES: We examined sociodemographic, clinical, and behavioral factors associated with previous incarceration among people with diagnosed HIV to inform HIV care efforts for this population. METHODS: We used 2015-2017 data from a cross-sectional, nationally representative sample of US adults with diagnosed HIV (N = 11 739). We computed weighted percentages and 95% CIs to compare the characteristics of people with HIV incarcerated in the past 12 months (ie, recently) with people with HIV not recently incarcerated. We used adjusted prevalence ratios (aPRs) with predicted marginal means to examine associations between selected factors and incarceration status. RESULTS: Adults with HIV who were recently incarcerated, when compared with those who were not, were more likely to be aged 18-29 years (prevalence ratio [PR] = 2.51), non-Hispanic Black (PR = 1.39), less educated (

Sociodemographic, behavioral, and clinical characteristics associated with perceived discrimination in healthcare settings among Black persons with diagnosed HIV in the United States.

Research that explores the intra-racial socio-demographic and clinical characteristics associated with perceived discrimination in healthcare settings in the US is lacking. We examined the prevalence of self-reported discrimination in HIV care settings during the past 12 months among Black persons from a nationally representative sample of US adults with diagnosed HIV collected 6/2018-5/2019. We assessed the prevalence of self-reported discrimination in HIV care settings during the past 12 months, perceived reasons for discrimination, and factors associated with discrimination among Black persons with diagnosed HIV (n = 1,631). Overall, 22% reported experiencing discrimination in a healthcare setting; discrimination was most often attributed to HIV status. Those reporting discrimination were younger, MSM, and living at or below the federal poverty level. They also experienced homelessness, incarceration and illicit substance use in the past 12 months, and anxiety and depression symptoms in the past 2 weeks. They were less likely to use ART or report 100% ART dose adherence in the past 30 days. No associations were found with viral suppression. Systems are needed to monitor, evaluate reports of, and address discrimination in healthcare settings. Incorporating anti-discrimination policies and continuing education opportunities for providers and staff may reduce experiences of discrimination among persons with HIV.

Projections of smoking-related cancer mortality in Australia to 2044.

BACKGROUND: While many high-income countries including Australia have successfully implemented a range of tobacco control policies, smoking remains the leading preventable cause of cancer death in Australia. We have projected Australian mortality rates for cancer types, which have been shown to have an established relationship with cigarette smoking and estimated numbers of cancer deaths attributable to smoking to 2044. METHODS: Cancer types were grouped according to the proportion of cases currently caused by smoking: 8%-30% and >30%. For each group, an age-period- cohort model or generalised linear model with cigarette smoking exposure as a covariate was selected based on the model fit statistics and validation using observed data. The smoking-attributable fraction (SAF) was calculated for each smoking-related cancer using Australian smoking prevalence data and published relative risks. RESULTS: Despite the decreasing mortality rates projected for the period 2015-2019 to 2040-2044 for both men and women, the overall number of smoking-related cancer deaths is estimated to increase by 28.7% for men and 35.8% for women: from 138 707 (77 839 men and 60 868 women) in 2015-2019 to 182 819 (100 153 men and 82 666 women) in 2040-2044. Over the period 2020-2044, there will be 254 583 cancer deaths (173 943 men and 80 640 women) directly attributable to smoking, with lung, larynx, oesophagus and oral (comprising lip, oral cavity and pharynx) cancers having the largest SAFs. INTERPRETATION: Cigarette smoking will cause over 250 000 cancer deaths in Australia from 2020 to 2044. Continued efforts in tobacco control remain a public health priority, even in countries where smoking prevalence has substantially declined.

Cancer incidence and mortality in Australia from 2020 to 2044 and an exploratory analysis of the potential effect of treatment delays during the COVID-19 pandemic: a statistical modelling study.

BACKGROUND: Long-term projections of cancer incidence and mortality estimate the future burden of cancer in a population, and can be of great use in informing the planning of health services and the management of resources. We aimed to estimate incidence and mortality rates and numbers of new cases and deaths up until 2044 for all cancers combined and for 21 individual cancer types in Australia. We also illustrate the potential effect of treatment delays due to the COVID-19 pandemic on future colorectal cancer mortality rates. METHODS: In this statistical modelling study, cancer incidence and mortality rates in Australia from 2020 to 2044 were projected based on data up to 2017 and 2019, respectively. Cigarette smoking exposure (1945-2019), participation rates in the breast cancer screening programme (1996-2019), and prostate-specific antigen testing rates (1994-2020) were included where relevant. The baseline projection model using an age-period-cohort model or generalised linear model for each cancer type was selected based on model fit statistics and validation with pre-COVID-19 observed data. To assess the impact of treatment delays during the COVID-19 pandemic on colorectal cancer mortality, we obtained data on incidence, survival, prevalence, and cancer treatment for colorectal cancer from different authorities. The relative risks of death due to system-caused treatment delays were derived from a published systematic review. Numbers of excess colorectal cancer deaths were estimated using the relative risk of death per week of treatment delay and different durations of delay under a number of hypothetical scenarios. FINDINGS: Projections indicate that in the absence of the COVID-19 pandemic effects, the age-standardised incidence rate for all cancers combined for males would decline over 2020-44, and for females the incidence rate would be relatively stable in Australia. The mortality rates for all cancers combined for both males and females are expected to continuously decline during 2020-44. The total number of new cases are projected to increase by 47·4% (95% uncertainty interval [UI] 35·2-61·3) for males, from 380 306 in 2015-19 to 560 744 (95% UI 514 244-613 356) in 2040-44, and by 54·4% (95% UI 40·2-70·5) for females, from 313 263 in 2015-19 to 483 527 (95% UI 439 069-534 090) in 2040-44. The number of cancer deaths are projected to increase by 36·4% (95% UI 15·3-63·9) for males, from 132 440 in 2015-19 to 180 663 (95% UI 152 719-217 126) in 2040-44, and by 36·6% (95% UI 15·8-64·1) for females, from 102 103 in 2015-19 to 139 482 (95% UI 118 186-167 527) in 2040-44, due to population ageing and growth. The example COVID-19 pandemic scenario of a 6-month health-care system disruption with 16-week treatment delays for colorectal cancer patients could result in 460 (95% UI 338-595) additional deaths and 437 (95% UI 314-570) deaths occurring earlier than expected in 2020-44. INTERPRETATION: These projections can inform health service planning for cancer care and treatment in Australia. Despite the continuous decline in cancer mortality rates, and the decline or plateau in incidence rates, our projections suggest an overall 51% increase in the number of new cancer cases and a 36% increase in the number of cancer deaths over the 25-year projection period. This means that continued efforts to increase screening uptake and to control risk factors, including smoking exposure, obesity, physical inactivity, alcohol use, and infections, must remain public health priorities. FUNDING: Partly funded by Cancer Council Australia.

Raking of data from a large Australian cohort study improves generalisability of estimates of prevalence of health and behaviour characteristics and cancer incidence.

BACKGROUND: Health surveys are commonly somewhat non-representative of their target population, potentially limiting the generalisability of prevalence estimates for health/behaviour characteristics and disease to the population. To reduce bias, weighting methods have been developed, though few studies have validated weighted survey estimates against generally accepted high-quality independent population benchmark estimates. METHODS: We applied post-stratification and raking methods to the Australian 45 and Up Study using Census data and compared the resulting prevalence of characteristics to accepted population benchmark estimates and separately, the incidence rates of lung, colorectal, breast and prostate cancer to whole-of-population estimates using Standardised Incidence Ratios (SIRs). RESULTS: The differences between 45 and Up Study and population benchmark estimates narrowed following sufficiently-informed raking, e.g. 13.6% unweighted prevalence of self-reported fair/poor overall health, compared to 17.0% after raking and 17.9% from a population benchmark estimate. Raking also improved generalisability of cancer incidence estimates. For example, unweighted 45 and Up Study versus whole-of-population SIRs were 0.700 (95%CI:0.574-0.848) for male lung cancer and 1.098 (95%CI:1.002-1.204) for prostate cancer, while estimated SIRs after sufficiently-informed raking were 0.828 (95%CI:0.684-0.998) and 1.019 (95%CI:0.926-1.121), respectively. CONCLUSION: Raking may be a useful tool for improving the generalisability of exposure prevalence and disease incidence from surveys to the population.

Changes in prostate cancer incidence, mortality and survival in relation to prostate specific antigen testing in New South Wales, Australia.

BACKGROUND: To examine changes in prostate cancer incidence and mortality rates, and 5-year relative survival, in relation to changes in the rate of prostate specific antigen (PSA) screening tests and the use of radical prostatectomy (RP) in the Australian population. METHODS: Prostate cancer stage-specific incidence rates, 5-year relative survival and mortality rates were estimated using New South Wales Cancer Registry data. PSA screening test rates and RP/Incidence ratios were estimated from Medicare Benefits Schedule claims data. We used multiple imputation to impute stage for cases with "unknown" stage at diagnosis. Annual percentage changes (APC) in rates were estimated using Joinpoint regression. RESULTS: Trends in the age-standardized incidence rates for localized disease largely mirrored the trends in PSA screening test rates, with a substantial 'spike' in the rates occurring in 1994, followed by a second 'spike' in 2008, and then a significant decrease from 2008 to 2015 (APC -6.7, 95% CI -8.2, -5.1). Increasing trends in incidence rates were observed for regional stage from the early 2000s, while decreasing or stable trends were observed for distant stage since 1993. The overall RP/Incidence ratio increased from 1998 to 2003 (APC 9.6, 95% CI 3.8, 15.6), then remained relatively stable to 2015. The overall 5-year relative survival for prostate cancer increased from 58.4% (95% CI: 55.0-61.7%) in 1981-1985 to 91.3% (95% CI: 90.5-92.1%) in 2011-2015. Prostate cancer mortality rates decreased from 1990 onwards (1990-2006: APC -1.7, 95% CI -2.1, -1.2; 2006-2017: APC -3.8, 95% CI -4.4, -3.1). CONCLUSIONS: Overall, there was a decrease in the incidence rate of localized prostate cancer after 2008, an increase in survival over time and a decrease in the mortality rate since the 1990s. This seems to indicate that the more conservative use of PSA screening tests in clinical practice since 2008 has not had a negative impact on population-wide prostate cancer outcomes.

Trends in colon and rectal cancer mortality in Australia from 1972 to 2015 and associated projections to 2040.

Previously published sub-site Australian projections for colon and rectal cancers to 2035 using the World Health Organization's mortality database sourced from the Australian Bureau of Statistics (ABS) predicted mortality rate decreases for colon cancer and increases for rectal cancer. There are complexities related to the interpretation of ABS's Australian colon and rectal cancer mortality rates, which could lead to possible inaccuracies in mortality rates for these sub-sites. The largest Australian population-wide registry, New South Wales Cancer Registry (NSWCR), compares routinely-reported causes of death with the recorded medical history from multiple data sources. Therefore, this study used the NSWCR data to project mortality rates for colon and rectal cancers separately to 2040 in Australia. The mortality rates for colon cancer are projected to continuously decline over the period 2015-2040, from 7.0 to 4.7 per 100,000 males, and from 5.3 to 3.2 per 100,000 females. Similar decreasing trends in mortality rates for rectal cancer were projected over the period 2015-2040, from 4.9 to 3.7 per 100,000 males, and from 2.6 to 2.3 per 100,000 females. These projections provide benchmark estimates for the colorectal cancer burden in Australia against which the effectiveness of cancer control interventions can be measured.

How Well Have Projected Lung Cancer Rates Predicted the Actual Observed Rates?

BACKGROUND: While many past studies have constructed projections of future lung cancer rates, little is known about their consistency with the corresponding observed data for the time period covered by the projections. The aim of this study was to assess the agreement between previously published lung cancer incidence and/or mortality rate projections and observed rates. METHODS: Published studies were included in the current study if they projected future lung cancer rates for at least 10 years beyond the period for which rates were used to obtain the projections, and if more recent observed rates for comparison covered a minimum of 10 years from the beginning of the projection period. Projected lung cancer incidence and/or mortality rates from these included studies were extracted from the publications. Observed rates were obtained from cancer registries or the World Health Organization's Mortality Database. Agreement between projected and observed rates was assessed and the relative difference (RD) for each projected rate was calculated as the percentage difference between the projected and observed rates. RESULTS: A total of 59 projections reported in 14 studies were included. Nine studies provided projections for 20 years or more. RDs were higher for those projections in which the lung cancer rates peaked during the projection period, and RDs increased substantially with the length of the projection period. When lung cancer rates peaked during the projection period, methods incorporating smoking data were generally more successful at predicting the trend reversal than those which did not incorporate smoking data. Mean RDs for 15-year projections comparing methods with or without smoking data were 12.7% versus 48.0% for males and 8.2% versus 42.3% for females. CONCLUSIONS: The agreement between projected and observed lung cancer rates is dependent on the trends in the observed rates and characteristics of the population, particularly trends in smoking.