Regional disparities in the use of intensive chemotherapy for AML in the Netherlands: does it influence survival?

OBJECTIVE

Acute myeloid leukaemia (AML) prognosis is enhanced with intensive remission induction chemotherapy (ICT) in eligible patients. However, ICT eligibility perceptions may differ among healthcare professionals. This nationwide, population-based study aimed to explore regional variation in ICT application and its relation with overall survival (OS).

METHODS AND ANALYSIS

We compared nine Dutch regional networks using data from the Netherlands Cancer Registry. Regional variance was assessed for the entire population and age subgroups (ie, ≤60 years and >60 years) using multivariable mixed effects logistic and Cox proportional hazard regression analyses, expressed via median OR (MOR) and median HR (MHR).

RESULTS

Including all adult AML patients from 2014 to 2018 (N=4060 patients; 58% males; median age, 70 years), 1761 (43%) received ICT. ICT application varied from 36% to 57% (MOR 1.36 (95% CI 1.11 to 1.58)) across regions, with minor variations for patients aged ≤60 years (MOR 1.16 (95% CI 1.00 to 1.40)) and more extensive differences for those aged >60 years (MOR 1.43 (95% CI 1.16 to 1.63)). Median OS spanned 4.9-8.4 months across regions (MHR 1.11 (95% CI 1.00 to 1.15)), with pronounced differences in older patients (MHR 1.12 (95% CI 1.08 to 1.20)) but negligible differences in the younger group (MHR 1.02 (95% CI 1.00 to 1.14)). Survival differences for the total population and the older patients decreased to respectively, MHR 1.09 (95% CI 1.00 to 1.13) and 1.10 (95% CI 1.04 to 1.18), after additional adjustment for the probability of receiving ICT within a region, indicating approximately 10% unexplained differences.

CONCLUSION

Regional disparities in ICT application and survival exist, especially in older AML patients. However, ICT application differences partially explain survival disparities, indicating the need for more standardised ICT eligibility criteria and a better understanding of underlying causes of outcome disparities.