Impact of Socioeconomic Factors on Survival for Adolescent and Young Adult (AYA) Patients (Pts) with Acute Myeloid Leukemia
Authors: Laganson Andrea , Klein Victoria , Nicolet Deedra , Teli Aadarsh , Mrózek Krzysztof , Wareti Jacob , Walker Michael C , Manring Christopher , Fisher James L , Paskett Electra D , Ghias Elizabeth , Plascak Jesse J , Mims Alice , Eisfeld Ann-Kathrin , Buss Jill 
Published: December 2024

Background: Long-term survival for AYA pts [aged 18-39 years (y)] diagnosed with AML remains poor, with only ~50% of pts surviving longer than 5 years despite advances in treatment. AML prognosis is driven mainly by the presence of cytogenetic abnormalities and recurrent gene mutations. However, additional factors reflective of individual lived experience, including socioeconomic contributors and geographic challenges, have also been found to affect survival in population-based studies. These population-based studies use data on large pt cohorts to develop meaningful conclusions, but they lack details on pt-related factors. Understanding the role these contributors play in a rigorously molecularly and socioeconomically characterized cohort, could prove beneficial in identifying potential trends associated with decreased overall survival.

Rationale and Methods: A total of 127 AYA pts (median age 31y, range 18-39y) diagnosed with AML at a major Comprehensive Cancer Center (CCC) from 2012-2020 was analyzed. Most pts had cytogenetic data as well as comprehensive clinical and molecular information available. Comprehensive geocoding to yield Yost estimates was performed using factor analysis of all variables by year, each centile rank-transformed prior to analysis, resulting in a single factor (analyses were limited to U.S. states). Yost indices were centile ranked nationally. Home-to-clinic travel time via motorized vehicle was estimated using previous and publicly available methods from Weiss et al. [Nat Med. 2020;26(12):1835-1838] using coordinates of the Ohio State University James Cancer Hospital.

Results: In our cohort, 50% of pts were female, and 78%, 10%, 4% self-identified as Non-Hispanic (NH)-White, NH-Black and Hispanic, respectively. The median time to diagnosis was 2 days, the median social deprivation score (national Yost rank) was 52.5, and 26% of pts had a travel time &gt;75 minutes to their treatment center. Univariable analysis using Cox proportional hazards regression models showed that the socioeconomic factors demonstrating the most significant impacts on pt survival included employment status and travel time to a treatment center, with significant reductions in both overall survival (OS) and event-free survival (EFS) found for pts who were unemployed (OS, p&lt;0.001; EFS, p=0.004) and who had a travel time of &gt;75 minutes to a treatment center (OS, p=0.008; EFS, p=0.005). In addition, the presence of a complex karyotype also associated with reduced OS (p=0.02) and EFS (p=0.009). Multivariable Cox regression analysis for OS showed that reduced OS for pts with a travel time of &gt;75 minutes (HR: 3.65, Cl: 1.53-8.69, p=0.003) was independent of the presence of a complex karyotype. Reduced EFS for pts who had a travel time of &gt;75 minutes from a treatment center (HR: 3.16, Cl: 1.46-6.83, p=0.004) also proved to be independent of the presence of a complex karyotype. Furthermore, self-reported non-White race also independently associated with reduced EFS (HR: 3.33, Cl: 1.38-8.06, p=0.008).

Conclusion: In addition to molecularly-based risk to define pt prognosis, our data provide support for the crucial contribution of neighborhood factors, especially treatment center distance, that independently affect pt survival. These potentially modifiable factors, that contrast with unmodifiable disease biology, may provide an important opportunity to improve survival with interventions that can overcome these survival modulators.