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Socioeconomic challenges in diagnosis, and treatment of patients with ALL

Nov 7, 2022
Learning objective: After reading this article, learners will be able to recall the key socioeconomic challenges in the management of ALL.

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With recent treatment advancements, survival rates in pediatric patients with acute lymphoblastic leukemia (ALL) exceed 90% in high-middle income countries (HMICs); however, disparities by socioeconomic status (SES), which relate to income, wealth, social status, occupation, education, and the environment where one resides, exist for both developed and developing countries.1,2 Also, pathways for the impact of SES on outcome likely differ between the two given the diverse landscape, 3 with survival rates in lower middle-income countries (LMIC)’s lagging behind HMIC’s.4

For adult patients with ALL, survival rates remain inferior compared to pediatrics, with social inequalities also apparent, thus also elucidating the possible interplay of socioeconomics in this context.5

In this review article, we discuss how differences across socioeconomic groups influence diagnosis, treatment, and survival disparities in ALL for both adults and children in different resource settings and describe the pathways involved.  

Diagnosis and prognosis

In a United States-based surveillance, epidemiology, and end results database (SEER) study from 2000 to 2016 which included 23,829 patients of all ages,6 SES’ impact on ALL incidence as it relates to ethnicity/race was evaluated. Across all age groups, SES was negatively associated with the age-adjusted incidence rate of ALL among non-latino (NL) white, NL Black, and positively associated for ALL incidence amongst Latinos/Hispanic populations. Both correlations were statistically significant (p < 0.01). In a converse SEER study from 2000 to 2010,7 the opposite trend was found in patients (N = 8,383) aged <19 years, with a negative association between SES and ALL among Latinos, and a positive association for NL White, Black, American Indian/Alaska native, and Asian/Pacific islander populations.

A report published in Blood 8 investigated the link between SES and disease characteristic outcomes in children and young adults at diagnosis (N = 4,726). It revealed that a lower SES was associated with poorer prognostic features of childhood ALL, including the presence of MLL rearrangement, a cytogenic feature, and central nervous system involvement, common amongst non-Hispanic White males. Conversely, a higher SES was associated with favorable features such as the presence of trisomy of Chromosome 4 and 10, and the ETV6-RUNX1 translocation amongst Hispanic males.


Treatment abandonment, treatment-related mortality, and maintenance therapy

In India, a LMIC, the impact of SES, parental educational status, and distance of residence from treating center on treatment outcomes in children with ALL (N = 308) were reported.9 For treatment abandonment, there were no significant differences (p = 0.34) across the upper, middle, and lower social classes, with two (2.4%), five (7.4%), and nine (5.8%) cases, respectively. However, there were no cases of abandoned therapy in the 20% of patients whose mother had a college degree (p < 0.05).

For treatment-related mortality, there were no correlations between SES and induction mortality but for the deaths relating to maintenance therapy, it was slightly higher for patients from lower social groups. There was one death (1.2%) in the upper class, six (8.8%) in the middle class, and 12 (7.7%) in the lower classes. Neutropenic deaths were also lower in patients whose mother graduated from college.9

A significantly higher proportion of underweight patients were in the lower socioeconomic groups, children with parents from a low education background, and those in rural areas; however, treatment abandonment and induction-related mortality did not differ by nutritional status. By SES, percentages of those underweight were:9

  • 12.9%, 22.1% and 44.5% (p < 0.001) in the upper, middle, and lower SES groups, respectively
  • 2.7%, 34.7% and 46.4% (p < 0.001) by parental educational strata for graduates, high school passed, and not high school passed, respectively
  • 3.2%, 24.8% and 49.6% (p < 0.001) by graduate, high school passed, and not high school passed maternal education stratum, respectively
  • 37.9 and 18.2% (p < 0.001) for rural areas versus and urban areas, respectively

A univariate analysis of treatment abandonment in a 2019 Chinese study,10 showed that it was significantly associated (p < 0.0001) with children who reside in a lower economic region at diagnosis. Abandonment rates in the multivariate analysis were 1.9%, 2.1%, and 6.1% (p = 0.0008) for high-income, middle-income, and low-income regions, respectively. In the conducted open-end interview with the patients’ parents, it was revealed that economic difficulties were the most common reason in 42/83 cases (50.6%) for treatment abandonment across all three income statuses, 47.6% of which corresponded to the lowest per capita disposable income and 23.8% to the Yunnan province, one of the poorest regions in China.

The socioeconomic variables of parental education, income, and parents’ affiliation to work have also been suggested to affect childhood outcomes during maintenance therapy in a HMIC setting, a national cohort Danish study (N = 173) by Pedersen et al.11 Two variables, physician’s compliance to treatment protocol (the dose levels of oral methotrexate (MTX) and oral 6-mercaptopurin (6MP) and the dose adjustments in those with a white blood cell (WBC) count of 3.0 × 109/L) and family adherence to treatment (differences in the metabolite levels of MTX and 6MP), were examined for their role as underlying mechanisms in the effect of SES on ALL maintenance therapy. There was no association of family adherence for SES and prescribed doses of MTX and 6MP.   

Conversely, the median prescribed doses of MTX (mMTX) and 6MP (m6MP) by the treating physician were significantly lower for children from families with a shorter educational background or with parents not affiliated with the workforce. The statistical significance for short vs medium vs higher education mMTX and parents unemployed vs mixed vs at work for both mMTX and m6MP was p < 0.01, with short vs medium vs higher education for m6MP also showing significance at p = 0.0311; this indicates both factors as a possible determining factor in SES and ALL outcomes.

The informative analysis in 96 patients with a WBC above 3.0 × 109/L showed a similar pattern of lower doses based on the same education (short vs medium vs higher) and workforce strata (parents unemployed vs mixed vs at work); however, only the parents affiliation to work variable yielded statistical significance (mMTX, p = 0.02; m6MP, p = 0.03) in the median dose levels.11

Utilization of chemotherapy and HSCT

A SEER study between 2006 and 2016 which included all age groups,12 showed that family income and educational status were determining factors in the receipt of chemotherapy. There was a significantly lower probability for receipt of chemotherapy among patients with a lower percentage of high school education, whereas those with a higher family income had a higher probability of receiving chemotherapy. Statistical significance was seen in the $50,000 to $75,000 group (odds ratio [OR], 1.24; 95% confidence interval [CI], 1.01–1.53; p = 0.04) and the >20% less than high school degree group (OR, 0.75; 95% CI, 0.60–0.92, p = 0.007).

Another retrospective study based in California and in patients aged >15 years (N = 3,221)13 also found that a lower neighborhood SES corresponded to a lower utilization of both chemotherapy and HSCT for adult patients with ALL. When lower SES levels were compared to the highest SES quintiles, the relative risk in patients with ALL for undergoing chemotherapy and HSCT was significantly reduced (p < 0.001) with at 0.95 (95% CI, 0.90–0.99) and 0.63 (95% CI, 0.47–0.84), respectively. The distance to the transplant center showed no effect in this regard.13

Survival outcomes

The Indian study mentioned above,9 also reported on SES and survival outcomes directly. The 5-year overall survival (OS) and event-free survival (EFS) rates were lower in children from lower socioeconomic groups, with EFS rates of 69.5%, 52.8%, and 54.3% and OS rates of 80.4%, 70%, and 73.7% in the higher, middle, and lower socioeconomic groups, respectively. There was no difference in the survival outcomes for rural and urban residences. A systematic review across 36 eligible studies on the impact of SES in children with cancer, including ALL,3 reported an association between low SES and inferior survival outcomes for several studies in both the LMIC and HMIC setting.

An English study in adult patients aged >18 years with ALL (N = 2,921)14 showed that those living in intermediate and most deprived areas had a poorer survival rate when compared to those living in the least deprived areas. The mortality hazard ratios for intermediate vs least deprived areas and most deprived vs least deprived areas were 21% and 16% higher, respectively. The predicted 5-year survival rates for least, intermediate, and most deprived areas were 36%, 30%, and 31%, respectively.

A study focused on distance to treatment centers and survival in children and young adults showed that a distance >50 miles may contribute to lower survival rates.15 Distances lower than 50 miles were associated with improved survival when compared to distances >50 miles. Comparison results for each were: ≤10 miles vs > 50 miles (hazard ratio [HR], 0.91; p = 0.04), >10 to ≤20 miles vs >50 miles (HR, 0.86; p = 0.004), and >20 to ≤50 miles vs >50 miles (HR, 0.87; p = 0.005).


In conclusion, the above studies highlight the significant impact of socioeconomic variables, including neighborhood SES, income, parental education, distance from treatment center, and occupation on disease outcomes in ALL. There is limited research on the socioeconomic challenges in adult populations across the cancer continuum and its underlying mechanisms, as well as diagnosis in both HMIC and LMIC settings and various age groups, thus there is a need for more conclusive research to better guide disease management.

Although poorly understood, possible pathways through which social inequalities can cause inferior outcomes in childhood ALL include treatment abandonment/refusal, malnutrition, avoidable relapse in LMIC’s, and communication barriers with healthcare professionals identified in HMIC’s, thus intervention strategies should focus on addressing these survival disparities to achieve a better outcome across the cancer continuum, all age groups, and countries.

  1. Abrahao R, Lichtensztajn D Y, Ribeiro R C, et al. Racial/ethnic and socioeconomic disparities in survival among children with acute lymphoblastic leukemia in California, 1988-2011: A population-based observational study. Pediatr Blood Cancer. 2015;62(10):1819-1825. DOI: 1002/pbc.25544
  2. Petridou E T, Sergentanis T N, Perlepe C, et al. Socioeconomic disparities in survival from childhood leukemia in the United States and globally: a meta-analysis. Oncol. 2015;26(3):589-597. DOI: 10.1093/annonc/mdu572
  3. Gupta S, Wilejto M, Pole J D, et al. Low socioeconomic status is associated with worse survival in children with cancer: a systematic review. PLoS One. 2014; 9(2):e89482. DOI: 1371/journal.pone.0089482
  4. Erdmann F, Feychting M, Mogensen H, et al. Social inequalities along the childhood cancer continuum: an overview of evidence and a conceptual framework to identify underlying mechanisms and pathways. Front Public Health 2019;7:84. DOI: 3389/fpubh.2019.00084
  5. Xu K, Feng Q, Wiemels J L, et al. Disparities in acute lymphoblastic leukemia risk and survival across the lifespan in the United States of America. J Transl Genet Genom. 2021;5:218-239. DOI: 20517/jtgg.2021.20
  6. Feng Q, Smith A J, Vergara-Lluri M, et al. Trends in acute lymphoblastic leukemia incidence in the united states by race/ethnicity from 2000 to 2016. Am J Epidemiol. 2021;190(4):519-527. DOI: 1093/aje/kwaa215
  7. Wang L, Gomez S L, and Yasui Y. Racial and ethnic differences in socioeconomic position and risk of childhood acute lymphoblastic leukemia. Am J Epidemiol. 2017;185(12):1263-1271. DOI: 1093/aje/kww164
  8. Ghosh T, Richardson M, Spector L, et al. Socioeconomic status is associated with prognostic factors in childhood acute lymphoblastic leukemia - implications for outcomes: A report from the children's oncology group. 2019;1(134)3808.
  9. Totadri S, Trehan A, Kaur A, et al. Effect of socio-economic status & proximity of patient residence to hospital on survival in childhood acute lymphoblastic leukaemia. Indian J Med Res. 2019;149(1):26-33. DOI: 4103/ijmr.IJMR_579_17
  10. Cai J, Yu J, Zu X, et al. Treatment abandonment in childhood acute lymphoblastic leukaemia in China: a retrospective cohort study of the chinese children's cancer group. Arch Dis Child. 2019;104(6):522-529. DOI: 1136/archdischild-2018-316181
  11. Pedersen L H, Ostergaard A; Bank V, et al. Socioeconomic position and maintenance therapy in children with acute lymphoblastic leukemia: a national cohort study. Pediatr Blood Cancer. 2022;69(7):e29508. DOI: 1002/pbc.29508
  12. Joshi U, Adhikari A, Bhetuwal U, et al. Effect of age and socioeconomic factors in the utilization of chemotherapy in acute lymphoblastic leukemia (ALL): A SEER database study of 16,196 patients. Clin Lymphoma Myeloma Leuk. 2022;22(10):e907-914. DOI: 1016/j.clml.2022.06.006
  13. Jabo B, Morgan JW, Martinez ME, et al. Sociodemographic disparities in chemotherapy and hematopoietic cell transplantation utilization among adult acute lymphoblastic and acute myeloid leukemia patients. PLoS One. 2017;12(4):e0174760. DOI: 1371/journal.pone.0174760
  14. Maheswaran R and Morley N. Incidence, socioeconomic deprivation, volume-outcome and survival in adult patients with acute lymphoblastic leukaemia in England. BMC Cancer. 2018;18(1):25. DOI: 1186/s12885-017-3975-0
  15. Rotz S, Wei W, Thomas SM, et al. Distance to treatment center is associated with survival in children and young adults with acute lymphoblastic leukemia. Cancer. 2020.126(24):5319-5327. DOI: 1002/cncr.33175

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