Abstract

Background

Lung cancer survival rates remain low.  Therapeutic nihilism and under-treatment have been suggested.  In a large, population-based study, we investigated whether there are age-related or socioeconomic inequalities in treatment receipt and survival for lung cancer.

Method

Information was abstracted from the National Cancer Registry Ireland on 34,152 primary lung cancers (ICD10 C34) diagnosed 1994-2013. Joinpoint was used to assess time trends in treatment receipt for small cell (SCLC) and non-small cell (NSCLC) tumours separately. Logistic regression and Cox regression were performed to assess treatment receipt and survival, respectively, by socioeconomic status and age. Adjustment was made for significant confounders.

Results

Time trend analysis showed increasing rates of surgery, radiotherapy and chemotherapy for NSCLC over time. Rates of radiotherapy and chemotherapy for SCLC have increased, but rates of surgery remain low. Likelihood of receipt of surgery and chemotherapy, but not radiotherapy, was significantly lower in the most socioeconomically deprived NSCLC patients (surgery: most vs least deprived OR=0.82, 95%CI 0.73-0.93; chemotherapy: OR=0.80, 95%CI 0.71-0.90). No association between socioeconomic status and receipt of any cancer-directed treatment was identified for SCLC. Younger age was strongly associated with an increased likelihood of receipt of surgery, radiotherapy and chemotherapy for both NSCLC and SCLC. For NSCLC, but not SCLC, there was an increased risk of death for NSCLC patients in the most deprived areas (HR=1.09, 95%CI 1.03-1.15). Younger age was associated with a significantly reduced risk of death in both NSCLC and SCLC patients.

Conclusion

Our findings support the existence of age-related and socioeconomic inequalities in lung cancer treatment receipt and survival. These patterns persisted despite adjustment for clinical confounders, including stage and grade. The reasons for these inequalities remain unclear. Future studies should consider other clinical factors affecting treatment choices (e.g. comorbidities, performance status) and potential non-clinical influences (e.g. patient and clinical preferences).