Pediatric acute lymphoblastic leukemia (ALL) is highly curable. Advances in the treatment of ALL embody one of the most successful examples of the progress of the field of pediatric oncology (1). An increased understanding of the biological underpinnings of ALL, the development of risk-stratified treatment, including response-based intensity, and the optimization of supportive care have led to a remarkable increase in cure rates (2, 3). In high-income countries (HICs), survival rates for pediatric ALL have surpassed 90%, and much of the current research focuses on decreasing short- and long-term treatment-related morbidity (4). Nonetheless, the majority of the children diagnosed with ALL live in low- and middle-income countries (LMICs) and do not have access to the optimal care that permits these high cure rates (5). Thus, the success of curing pediatric ALL depends on improving access to quality care for children in LMICs.

Recent studies show that the survival of pediatric patients with ALL varies considerably, with appreciably worse outcomes in LMICs (6). Data from CONCORD-3, an analysis of cancer-related survival from population-based cancer registries, showed survival rates between 50% and 70% for many countries in Latin America, Africa, and Asia (7). A recent simulation-based study estimated the survival of ALL at 61% in Latin America and the Caribbean (6). Mexico is an upper-middle-income country with approximately 2,300 new cases of pediatric ALL each year (8). The estimated 5-year overall survival for ALL in Mexico is approximately 60% (9–11). Adverse outcomes have been associated with late presentation, delayed diagnosis, malnutrition (12), infection-related deaths (13), and abandonment (14). In Mexico, between 2004 and 2019, Seguro Popular provided health coverage to the population without social security or private insurance, including financing care for children and adolescents with ALL. Since 2020, the Mexican health system has been in constant redesign. New health governance and financing strategies are being proposed, but their adoption, implementation, spread, and permanence remain to be determined.

In 2016, eight centers from eight different states in Mexico and St. Jude Children’s Research Hospital (St. Jude) in Memphis, United States, joined to create, and in 2017 launch, “Mexico in Alliance with St. Jude (MAS)”, a collaborative group dedicated to increasing the survival and quality of care of children and adolescents with cancer in Mexico. Within the workstream to identify gaps in access and quality care for children with care, a retrospective study was developed to ascertain deficiencies and strengths of care for pediatric ALL. This multi-institutional study sought to characterize the outcomes of children with ALL diagnosed at institutions in Mexico, correlating the findings with clinical and biological factors and elements related to access to quality care. Preliminary results have been used to co-design and co-produce prospective interdisciplinary projects over the years, including an evidence-based, consensus-derived, adapted treatment guideline, which now serves as the standard of care at many MAS member institutions.

A total of 2,116 eligible patients were identified with a median age of 6.3 years (IQR, 7.5). Patient characteristics are presented in Table 1 . Most patients had B-cell ALL (1,889, 89.3%) and no central nervous system (CNS) involvement (1,810, 85.5%). Only 160 (7.6%) of patients presented with T-cell phenotype, and only 61 (2.9%) of the patients were reported to have trisomy 21 (Down syndrome). The diagnostic lumbar puncture was traumatic in 127 patients (6.0%). Data on CNS status, immunophenotype, and karyotype were not available in 130 (6.1%), 39 (1.8%), and 745 (35.2%) patients, respectively.

This detailed review of a large cohort of patients diagnosed and treated in Mexico has allowed for the evaluation of multiple elements of pediatric ALL care and outcomes. Our study analyzed data from 2,116 patients across 16 centers and suggests outcomes are lower than desirable, with a high frequency of treatment-related toxicity and relapse, and inconsistent access to diagnostic tests, both at diagnosis to characterize ALL samples and for disease monitoring through MRD.

Consistent with prior institutional and population-based cancer registry reports from Mexico (7, 9–11), our study describes lower OS and EFS for pediatric ALL than reported in HICs. Furthermore, regional variability can also be seen in our study, similar to published reports (9). Compared to reports from collaborative studies from North America and Europe, the outcomes from our report are close to 20% to 30% lower. High rates of death in induction, abandonment, death in remission, and relapse are the main contributing factors to these poor outcomes. Nonetheless, factors associated with outcomes from high-resource settings such as age, WBC count at diagnosis, ploidy, presence of translocation, and response to therapy (MRD) continue to portend prognostic significance.

We report an abandonment rate of 6%, like prior reports from Mexico (10, 18, 19) During the time that this cohort was treated, government-funded healthcare existed for children and adolescents with ALL. Despite coverage, treatment abandonment is a complex phenomenon, and it has been associated with social, economic, and treatment-related factors (20, 21). Social inequalities and social determinants of health continue to impact cancer outcomes even when direct costs for cancer care are covered (22). This study did not collect data on social determinants of health for the cohort; hence, additional analyses would be necessary to further describe factors that increase the risk of treatment abandonment in Mexico.

Induction has the highest risk of infectious complications due to prolonged immunosuppression from disease and the intensity of induction chemotherapy (23, 24). In our study, close to 10% mortality was seen during induction, with most deaths from infectious processes. This rate is markedly above reports not only of the clinical trials of cooperative groups in high-resource settings where <2% is usually reported (2, 25, 26) but also in pediatric oncology units in Central America (27, 28). The risk of death in induction was not associated with treatment intensity (anthracycline dose), suggesting that earlier diagnosis of ALL and improved management of infectious complications may be the most valuable intervention. Importantly, the MAS centers are participating in a project to implement a pediatric early warning system (PEWS) (29) and timely antibiotic administration in febrile patients (30) as mechanisms to improve treatment-related mortality. Additional interventions such as prophylactic antibiotics during induction (31) could be considered as strategies to decrease infectious mortality early in treatment. Interventions that mitigate unplanned toxicities could also impact the financial aspects of pediatric cancer care (32).

Contrary to most pediatric ALL studies, our study reports that most patients were classified as high-risk, including 70% at the beginning of induction. The NCI standard-risk criteria are effective risk stratification criteria (33), especially when access to molecular tests is inconsistent. Based on these two variables, we describe how close to 50% of patients were inappropriately assigned risk groups. Although other variables are used for risk assignment, such as steroid response and DNA index, this is unlikely to explain the large disparity. Ultimately, these data suggest that a large proportion of patients were over-treated, increasing the risk of treatment-related mortality and long-term morbidity. This is especially worrisome, as it is known that close to 40% of patients can be cured with minimally intensive therapy (34, 35). Standardized approach to risk stratification would optimize the intensity of therapy based on the risk of relapse.

In our report, the frequency of CNS-2 status was 3.2%. This is lower than recently published studies from North America, where St. Jude’s Total XVI had 33% (24) and COG’s standard-risk trial, AALL0331, had 8% (25). On further investigation, some centers included in the study did not have the capacity to perform cytospin to evaluate for leukemic blasts, hence likely under-reporting CNS-2 status. Given these elements and the previously mentioned discordance in risk stratification, the association of CNS status and outcomes in this cohort was likely confounded due to these factors.

Over the past decades, the molecular characterization of ALL has transformed the field of pediatric leukemia care (36). Access to advanced diagnostic tests to characterize ALL samples are essential to provide risk-adapted therapy, seeking to maximize cure rates and minimize therapy-associated toxicities. Our data suggested limited access to advanced diagnostics like FISH and PCR. Furthermore, uninterpretable tests were also reported, highlighting the need to improve the quality of testing also. Strategies to achieve increased access to quality diagnostics could be the identification of centralized, regional testing centers with adequate validation processes.

Response to treatment and MRD has been the most important prognostic factor for pediatric ALL (37–40). The role of MRD in risk stratification has already been used in LMICs for close to two decades, confirming its relevance in resource-limited settings even when simplified flow cytometry-based assays are utilized (41, 42). In our study, 55% of patients had MRD performed during different points of therapy. Importantly, in univariate and multivariable analyses, negative MRD was associated with EFS. Furthermore, patients whose MRD was performed, regardless of results, had better survival, suggesting that access to comprehensive testing can influence outcomes. Based on these data, consistent access to timely and high-quality MRD would optimize therapy for patients with ALL. Increasing access to MRD could be achieved by identifying regional centers to process samples for treatment response.

Pediatric ALL is a heterogeneous disease, with recurrent genetic alterations conferring treatment prognosis. Some studies have described a lower frequency of favorable translocations, like ETV6-RUNX1, in Hispanic populations within the United States (43). The frequency of ETV6-RUNX1 in our cohort is consistent with Hispanic patients in the United States, which is lower than other populations. Of the patients with ALL and BCR-ABL fusions, the 5-year OS was 45.6%, consistent with the outcomes seen before the use of ABL-class tyrosine kinase inhibitors (44). In our study, of the 74 patients identified with BCR-ABL1 fusions, only 24 received targeted therapy, likely hindering the possibility of early remission. It is important to note that an important fraction of the cohort does not have alterations frequently seen in pediatric ALL. It is unclear if this is related to a true variation or inherently a marker of inadequate access to comprehensive, validated molecular testing. Ultimately, the size of the cohort with complete molecular characterizations is insufficient to comprehensively describe variations of genetic alterations in ALL for the Mexican population.

Our study has limitations. As a retrospective study, the availability of all details of care was absent for some patients, especially as we sought to extract granular features of diagnostic evaluations and therapy. Nonetheless, given the size of the cohort and explicit mention of when data elements were absent, relevant conclusions can still be reached. Furthermore, as patients were treated with different protocols, the impact of specific treatment phases and chemotherapy strategies cannot be concluded from this study.

In Mexico, cancer is the leading cause of death in children aged 5–14 (45, 46); hence, investment in the care of children with ALL and pediatric cancer is imperative. The results from this study highlight areas that are relevant for interventions to improve quality care for children with ALL not only in Mexico but also in other LMICs. Based on these data, the MAS group has developed an evidence-based consensus-derived treatment guideline for ALL currently being used in more than 10 pediatric cancer units in Mexico. Furthermore, these data informed a peer-reviewed grant-funded prospective project to improve access to a consensus-derived diagnostic panel and support comprehensive risk stratification. Some of the outputs of these interventions are included in other manuscripts of this Frontiers in Oncology Research Topic. With these data-driven approaches, improved outcomes are anticipated.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The studies involving humans were approved by St. Jude Children’s Research Hospital and each participating site. The studies were conducted in accordance with the local legislation and institutional requirements. Written informed consent for participation was not required from the participants or the participants’ legal guardians/next of kin. Exemption is due to retrospective nature of study.

DM: Formal Analysis, Supervision, Visualization, Writing – original draft, Writing – review & editing. OG-R: Investigation, Supervision, Writing – review & editing. ME: Investigation, Supervision, Writing – review & editing. AC: Data curation, Project administration, Writing – review & editing. LF: Project administration, Writing – review & editing. GJ: Formal Analysis, Writing – review & editing. YC: Formal Analysis, Writing – review & editing. CV: Supervision, Writing – review & editing. AI: Investigation, Writing – review & editing. RB: Investigation, Writing – review & editing. MR: Data curation, Investigation, Writing – review & editing. EA: Investigation, Writing – review & editing. JE: Investigation, Writing – review & editing. NL: Investigation, Writing – review & editing. JC: Investigation, Writing – review & editing. FR: Investigation, Writing – review & editing. AA: Investigation, Writing – review & editing. ET: Investigation, Writing – review & editing. CPZ: Investigation, Writing – review & editing. NN: Investigation, Writing – review & editing. SP: Investigation, Writing – review & editing. DC: Investigation, Writing – review & editing. PC: Data curation, Writing – review & editing. KS: Data curation, Writing – review & editing. PM: Data curation, Writing – review & editing. CPA: Data curation, Writing – review & editing. GT: Data curation, Writing – review & editing. MG: Data curation, Writing – review & editing. JÁ: Data curation, Writing – review & editing. JB: Data curation, Writing – review & editing. HR: Data curation, Writing – review & editing. AS: Data curation, Writing – review & editing. AP: Data curation, Writing – review & editing. DA: Data curation, Writing – review & editing. LM: Data curation, Writing – review & editing. LB: Data curation, Writing – review & editing. IG: Data curation, Writing – review & editing. MJ: Data curation, Writing – review & editing. NE: Data curation, Writing – review & editing. EC: Data curation, Supervision, Writing – review & editing. KG: Supervision, Writing – review & editing. MD: Formal Analysis, Writing – review & editing. PF: Conceptualization, Investigation, Methodology, Project administration, Resources, Writing – review & editing.