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 causespecific 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.

Impact of cancer diagnosis on life expectancy by area-level socioeconomic groups in New South Wales, Australia: a population-based study

Objective: Improvement in cancer survival over recent decades has not been accompanied by a narrowing of socioeconomic disparities. This study aimed to quantify the loss of life expectancy(LOLE) resulting from a cancer diagnosis and examine disparities in LOLE based on area-level socioeconomic status(SES).Methods: Data were collected for all people between 50 and 89 years of age who were diagnosed with cancer, registered in the NSW Cancer Registry between 2001 and 2019, and underwent mortality follow-up evaluations until December 2020. Flexible parametric survival models were fitted to estimate the LOLE by gender and area-level SES for 12 common cancers.Results: Of 422,680 people with cancer, 24% and 18% lived in the most and least disadvantaged areas, respectively. Patients from the most disadvantaged areas had a significantly greater average LOLE than patients from the least disadvantaged areas for cancers with high survival rates, including prostate [2.9 years(95% CI: 2.5±3.2 years) vs. 1.6 years(95% CI: 1.3±1.9 years)] and breast cancer [1.6 years(95% CI: 1.4±1.8 years) vs. 1.2 years(95% CI: 1.0±1.4 years)]. The highest average LOLE occurred in males residing in the most disadvantaged areas with pancreatic [16.5 years(95% CI: 16.1±16.8 years) vs. 16.2 years(95% CI: 15.7±16.7 years)] and liver cancer [15.5 years(95% CI: 15.0±16.0 years) vs. 14.7 years(95% CI: 14.0±15.5 years)]. Females residing in the least disadvantaged areas with thyroid cancer [0.9 years(95% CI: 0.4±1.4 years) vs. 0.6 years(95% CI: 0.2±1.0 years)] or melanoma [0.9 years(95% CI: 0.8±1.1 years) vs. 0.7 years(95% CI: 0.5±0.8 years)] had the lowest average LOLE.Conclusions: Patients from the most disadvantaged areas had the highest LOLE with SES-based differences greatest for patients diagnosed with cancer at an early stage or cancers with higher survival rates, suggesting the need to prioritise early detection and reduce treatment-related barriers and survivorship challenges to improve life expectancy.

Lung cancer risk in never-smokers:An overview of environmental and genetic factors

Lung cancer is the leading cause of cancer-related mortality globally,accounting for 1.8 million deaths in 2020.While the vast majority are caused by tobacco smoking,15%-25%of all lung cancer cases occur in lifelong neversmokers.The International Agency for Research on Cancer(IARC)has classified multiple agents with sufficient evidence for lung carcinogenesis in humans,which include tobacco smoking,as well as several environmental exposures such as radon,second-hand tobacco smoke,outdoor air pollution,household combustion of coal and several occupational hazards.However,the IARC evaluation had not been stratified based on smoking status,and notably lung cancer in never-smokers(LCINS)has different epidemiological,clinicopathologic and molecular characteristics from lung cancer in ever-smokers.Among several risk factors proposed for the development of LCINS,environmental factors have the most available evidence for their association with LCINS and their roles cannot be overemphasized.Additionally,while initial genetic studies largely focused on lung cancer as a whole,recent studies have also identified genetic risk factors for LCINS.This article presents an overview of several environmental factors associated with LCINS,and some of the emerging evidence for genetic factors associated with LCINS.An increased understanding of the risk factors associated with LCINS not only helps to evaluate a never-smoker’s personal risk for lung cancer,but also has important public health implications for the prevention and early detection of the disease.Conclusive evidence on causal associations could inform longer-term policy reform in a range of areas including occupational health and safety,urban design,energy use and particle emissions,and the importance of considering the impacts of second-hand smoke in tobacco control policy.