Country of birth and non-small cell lung cancer incidence, treatment, and outcomes in New South Wales, Australia: a population-based linkage study

Abstract

Objective To compare treatment within 12 months of diagnosis, and survival by country of birth for people diagnosed with invasive non-small cell lung cancer (NSCLC) in New South Wales (NSW), Australia. Design, patients, and setting A population-based cohort study of NSW residents diagnosed with NSCLC in 2003–2016 using de-identified linked data from the NSW Cancer Registry, NSW Admitted Patient Data collection, Emergency Departments, Medicare Benefits and Pharmaceutical Benefits Scheme, and National Death Index. Main outcome measures Odds of receiving any treatment, surgery, systemic therapy, or radiotherapy respectively, in the 12 months following diagnosis were calculated using multivariable logistic regression. The hazard of death (all-cause) at one- and five-years following diagnosis was calculated using multivariable proportional hazards regression. Results 27,114 People were recorded with NSCLC in the 14-year study period. Higher percentages of older males from European countries applied in the earlier years, with a shift to younger people from South East Asia, New Zealand, and the Middle East. Adjusted analyses indicated that, compared with the Australian born, people from European countries were more likely to receive treatment, and, specifically surgery. Also, people from Asian countries were more likely to receive systemic therapy but less likely to receive radiotherapy. Survival at one- and five-years following diagnosis was higher for people born in countries other than Australia, New Zealand the United Kingdom and Germany. Conclusions Variations exist in treatment and survival by country of birth in NSW. This may be affected by differences in factors not recorded in the NSW Registry, including use of general health services, family histories, underlying health conditions, other intrinsic factors, and cultural, social, and behavioural influences.

Demographic, health, and prognostic characteristics of Australians with liver cancer: a cohort study of linked data in New South Wales for informing cancer control

“…In step 1, cross-tabulations, and odds ratios with 95% confidence intervals derived from multiple logistic regressions, were used to compare characteristics of cohort members according to whether they were subsequently diagnosed with liver cancer. Also, within cohort members diagnosed with liver cancer, similar comparisons were made by degree of spread (i.e., distant/unknown degree of spread compared with localized/regional) [ 18 , 19 ]. This was undertaken for each socio-demographic and health status variable.…”

“…In step 2, multivariable analyses were undertaken, starting with all covariates, then purposefully removing the least-contributing covariates (using Wald statistic p-values of > 0.2 as a guide), and refitting the model with remaining covariates until deriving a main effects model where each retained covariate substantially contributed [ 18 , 19 ]. Potential for co-linearity among predictor variables was tested using variance inflation factors to ensure it was within accepted limits.…”