https://orcid.org/0009-0001-1621-034X
Figures
Abstract
Background
Acute lymphoblastic leukemia (ALL) is a common childhood cancer characterized by the uncontrolled proliferation of immature white blood cells. While advancements in treatment have significantly improved outcomes in developed countries, significant challenges remain in resource-limited settings, such as Ethiopia. This study aimed to assess the clinical profiles and treatment outcomes of ALL patients at the University of Gondar Comprehensive Specialized Hospital (UoGCSH) and Tikur Anbessa Specialized Hospital (TASH) in Ethiopia.
A prospective longitudinal study was conducted among 179 ALL patients receiving treatment at the outpatient department and pediatric oncology centers of the UoGCSH and TASH between December 25, 2022, and August 30, 2024. Sociodemographic and clinical data were collected using a structured questionnaire. The data were entered and analyzed using SPSS version 25. Descriptive statistics were employed to summarize patient characteristics, while overall survival was evaluated using Kaplan-Meier analysis. Additionally, both univariate and multivariate Cox proportional hazards regression analyses were performed, with statistical significance set at a P-value of < 0.05.
Results
Among the 179 patients, 81 (45.3%) died during the course of treatment. Of these, 33 (18%) died before initiating induction therapy, while 48 (27.4%) died primarily due to treatment abandonment during various phases of therapy. The event-free survival rate was 75 (41.9%). Mortality rates were significantly higher in patients with certain variables identified through Cox regression analysis, including age, sepsis, and relapse, which nearly doubled the risk of death. Elevated LDH levels, malaria infection, and T-cell ALL were associated with approximately six-fold, three-fold, and seven-fold increases in the risk of death, respectively. Only 22 out of 179 patients (12.29%) achieved remission. Among these patients, hematotoxicities observed during the maintenance phase included anemia in 19/22 (86.4%), grade 3–4 neutropenia in 12/22 (52.2%), and thrombocytopenia in 17/22 (77.3%).
Conclusion
A high mortality rate was observed among children with ALL, with significant risk factors including relapse, age over 10 years, elevated LDH levels, sepsis, low platelet counts, T-cell ALL, malaria infection, and induction failure. To improve survival rates, it is essential to address these factors by optimizing treatment regimens and minimizing delays in diagnosis and care delivery.
Citation: Kassa E, Ayalew M, Birhan M, Gelaw A, Gidey AM, Zeleke TA, et al. (2025) Clinical profile and treatment outcomes of acute lymphoblastic leukemia among children attending at the University of Gondar comprehensive specialized hospital and Tikur Anbessa Specialized Hospital in Ethiopia. PLoS One 20(6): e0322747. https://doi.org/10.1371/journal.pone.0322747
Editor: Tebelay Dilnessa, Debre Markos University, ETHIOPIA
Received: November 9, 2024; Accepted: March 28, 2025; Published: June 5, 2025
Copyright: © 2025 Kassa et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All data generated and analyzed in this study are available within the paper.
Funding: The author(s) received no specific funding for this work.
Competing interests: All authors listed have made sufficient contributions to be included as authors, and all qualified authors are listed in the author list in order of their contributions. To the best of our knowledge, there are no conflicts of interest to declare, and these declarations are included in the manuscript. All authors have approved the manuscript, and we believe it aligns with the aims and scope of the journal. Finally, all of the authors have agreed with this submission.
Abbreviation:: ALL, Acute lymphoblastic leukemia; TPMT, Thiopurine mythyltransferase; ADR, Adverse drug reaction; EFDA, Ethiopian Food and Drug Administration; HCPs, Healthcare professionals; KAP, Knowledge, Attitude, and Practice; UoGCSH, University of Gondar Comprehensive Specialized Hospital; AAU, Addis Ababa University; AL, Acute Leukemia; AML, Acute Myeloid Leukemia; BM, Bone Marrow; CNS, Central Nervous System; EFS, Event free survival; FAB, French-American-British; Hgb, Hemoglobin; LDH, Lactate Dehydrogenase; SNNPR, Southern Nations Nationalities and Peoples Region; TASH, Tikur Anbessa Specialized Hospital; WHO, World Health Organization
Introduction
Leukemia is the most common malignancy in children, accounting for approximately 30% of all cancers diagnosed in children under 15 years of age in developed countries [1]. Globally, acute lymphoblastic leukemia (ALL) represents the most prevalent pediatric cancer, characterized as a malignancy of B or T lymphocytes involving the uncontrolled proliferation of abnormal, immature lymphocytes. Worldwide, nearly 400,000 new cases of childhood cancer (age range, 0–19 years) are reported annually, with low- and middle-income countries (LMICs) accounting for a significant proportion (90%) of these cases [2]. However, for much of the past three decades, leukemia’s were considered rare hematological cancers, with only sporadic cases reported, particularly in regions like Africa, where data were scarce and the condition was often thought to be nonexistent [3]. In Ethiopia, the annual incidence of childhood cancers is estimated to be between 3,707 and 6,000 cases, with leukemia being the most prevalent, accounting for 29% of these cases. Acute leukemia constitutes 89% of all childhood leukemia cases in Ethiopia, with ALL representing 91% and acute myeloid leukemia (AML) accounting for the remaining 9% [4,5].
In high-income countries (HICs), survival rates have drastically improved from 30% to 90% over the past 50 years. A recent report by the children’s oncology group stated that the overall survival rate for children with standard-risk B-cell ALL is approximately 96% [1,6–9]. However, 30–40% of these patients relapse during the maintenance phase. The relapse rate in developed countries has been 11% in recent years. In contrast, survival rates in LMICs, remain poor, often around 35%. Mortality rates for most pediatric cancers are close to 100% in developing countries, including Ethiopia [10]. Treatment abandonment is a major reason for treatment failure and low survival rates in LMICs [11], and this issue is directly correlated with the country’s income level [12]. The stark disparity in pediatric cancer survival rates between HICs and LMICs is largely attributable to differences in healthcare systems. Inadequate government health spending in LMICs often results in inefficient healthcare delivery, contributing to several factors that undermine survival rates. These factors include delayed diagnosis, insufficient numbers of physicians and nurses, limited supportive care infrastructure, restricted access to effective treatments, high treatment-related mortality rates, increased relapse rates, and elevated rates of treatment abandonment [13].
The treatment regimen for childhood ALL typically involves the induction of remission through chemotherapy at the time of diagnosis, followed by consolidation therapy, delayed intensification, and maintenance therapy [14]. Over the years, treatment protocols for ALL have improved significantly evolving from aminopterin, which achieved only a temporary remission in 1948 [15], to the chemotherapy regimens used today. These regimens have been refined through the consolidative clinical experiences of the Italian Association of Pediatric Hematology (AIEOP) and Berlin-Frankfurt-Münster Study Group (BFM) study groups. As a result of these improved protocols, the current treatment for ALL now achieves a 5-year survival rate of 92% [16]. Thiopurines, such as 6-mercaptopurine (6-MP), are critical components of the current ALL treatment. However, their use is associated with significant toxicity, particularly myelosuppression, due to interindividual variability in thiopurine S-methyltransferase (TPMT) enzyme activity [17–19].
Baseline data on diseases are essential for understanding disease patterns, treatment outcomes, and informing effective public health policies. By studying ALL, researchers can identify trends, develop optimal treatment strategies, and advocate for improved resource allocation and public awareness. Consequently, this study aims to address a critical gap by providing a detailed analysis of the clinical characteristics, treatment outcomes, and factors influencing survival in pediatric ALL patients treated at two major referral hospitals in Ethiopia. By identifying key barriers to optimal care and predictors of poor outcomes, this research seeks to inform targeted interventions and policy changes to improve survival rates and the quality of care for children with ALL in resource-limited settings. Furthermore, the findings will contribute to the broader understanding of ALL management in Ethiopia and other LMICs, supporting global efforts to reduce disparities in childhood cancer outcomes.
2. Materials and methods
2.1. Study area and setting
The study was conducted at the UoGCSH and TASH, in Ethiopia. The University of Gondar Hospital is a referral hospital located 727 km from the capital, Addis Ababa, in the northwestern part of the country. The hospital has a dedicated pediatric hematology-oncology unit with 35 beds, as well as a separate adult oncology unit. Currently, it serves approximately seven million people, providing both outpatient and inpatient services. As a referral center, it offers various medical services to the surrounding areas and neighboring regions, including adult and pediatric hematology-oncology care. The pediatric hematology-oncology center at UoGCSH is the only one in the region, with essential imaging and pathology services available. Tikur Anbessa Specialized Hospital, located in Addis Ababa, serves as a teaching hospital for the country’s leading medical and health Sciences University. It is the first and largest hospital in Ethiopia to offer hematology-oncology services. Together, both hospitals serve more than 10 million people within their catchment areas [10,20–22].
2.2. Study design and period
An institution-based prospective longitudinal study design was used to evaluate the clinical profile and treatment outcomes of children with ALL at the UoGCSH and TASH from December 25, 2022, to August 30, 2024.
2.3. Source and study population
The source population included all children who visited the pediatrics OPD, as well as those admitted to the pediatric oncology unit during the study period at the UoGCSH and TASH. All children below the age of 18 years who were diagnosed with ALL were the study population.
2.4. Eligibility
2.4.1. Inclusion criteria.
All patients below the age of 18 who presented for care, were diagnosed with ALL and were admitted to UoGCSH and TASH from December 25, 2022, to August 30, 2024. All patients had a confirmed pathologic diagnosis of ALL based on biopsy samples.
2.4.2. Exclusion criteria.
Patients suspected of having ALL based on clinically findings and FNAC results, but without a confirmed diagnosis from biopsy pathology, were excluded. Additionally, patients without a confirmed diagnosis of ALL or those who did not provide consent were also excluded from the study.
2.5. Operational definition
- Treatment outcome: The result obtained after the use of a drug. Which may include cure, death, or complication.
- Neutropenic fever: A temperature ≥ 100.4F (38.3°C) for at least an hour, accompanied by an absolute neutrophilic count (ANC) of less than 1500cells/µL.
- Complete Remission: Defined as the eradication of all detectable leukemia cells (less than 5 percent blasts) from the bone marrow and blood, along with the restoration of normal hematopoiesis (>25 percent cellularity and normal peripheral blood counts).
- Relapse: The reappearance of leukemia cells in the bone marrow or peripheral blood after the attainment of complete remission [23].
- CNS Involvement: ≥ 5 cells/mm3 of CSF analysis [24].
2.6. Risk stratification and treatment protocols
The treatment regimen for ALL was determined based on patient stratification into standard risk (SR) and high-risk (HR) categories. The SR ALL is defined as patients aged 1 to less than 10 years with a white blood cell count below 50,000/µL, no CNS blast cell infiltration at presentation, and confirmed bone marrow remission. The SR ALL patients received treatment in three phases: induction, consolidation, and maintenance [25]. The HR patients, in this group underwent additional treatment phases, such as re-induction or intensification, before entering the maintenance phase. A four-drug regimen consisting of prednisolone, vincristine, L-asparaginase, and doxorubicin was administered for most patients, including HR patients with central nervous system (CNS) involvement. For patients with CNS involvement, hydrocortisone and intrathecal cytarabine were added to the treatment regimen. In SR patients, however, doxorubicin was omitted from the treatment regimen. The specific timelines for each phase of treatment may differ depending on individual risk factors and the treatment protocols employed. Initially, a clinical and hematological assessment is performed, followed by induction therapy for pediatric ALL, which generally lasts between 4–8 weeks with the goal of achieving remission. This is succeeded by a consolidation phase that lasts approximately 6 months, aimed at eradicating any remaining leukemia cells.
2.7. Data collection tools and laboratory analysis
A structured questionnaire was used to collect demographic information, while a review of medical records was conducted to gather data on diagnosis, treatment protocols, therapeutic response, and follow-up information. A 4 ml venous blood sample was obtained from each patient for complete blood count (CBC), and morphology assessment. The CBC was performed using Sysmex XS-500i and XT-1800 analyzers (Sysmex Corporation, Kobe, Japan). Wright’s stain was performed for peripheral morphology assessment. Subsequently, peripheral morphology and bone marrow aspiration examinations were performed by an experienced pathologist. Following the conclusion of the six-month maintenance phase, clinical and hematological evaluations were conducted. Consequently, patients were monitored for a minimum duration of 13 months (1 year and 1 month).
2.8. Quality assurance mechanisms
Data on the sociodemographic characteristics of children and their caregivers, along with related factors, were collected through face-to-face interviews using a structured questionnaire adapted from various sources. Three BSc nurses conducted data collection under the close supervision of two pediatric hematology-oncology fellows at both study sites. Data collectors and supervisors received two days of training on study objectives, data collection tools, techniques, and ethical considerations. Interviewers manually recorded responses to both closed and open-ended questions. Supervisors assessed daily data consistency and completeness.
To ensure data quality, the questionnaire was adapted from previous studies [26,27] and reviewed by oncology experts. It was subsequently translated from English to Amharic by language experts. Rigorous quality control measures were implemented for laboratory procedures, including regular maintenance and cleaning of equipment to ensure accurate and reliable results. Additionally, data quality was validated using statistical parameters to assess the reliability and validity of the collected data.
2.9. Statistical analysis
Data were entered into Epi-Info version 7 and analyzed using SPSS version 25. Descriptive statistics, including frequencies, means with ± standard deviations, and medians with interquartile ranges, were used to summarize sociodemographic, clinical, and laboratory characteristics. Survival analysis was performed using the Kaplan-Meier method, and the log-rank test was used to compare survival rates. Univariate and multivariate Cox proportional hazard regression models were fitted to identify factors associated with survival in ALL. Statistical significance was determined at the p < 0.05 level with a 95% confidence interval.
2.10. Ethical considerations
Ethical clearance was obtained from the University of Gondar Institutional Ethical Review Board (Rfe. VP/RTT/05/246/2022), and a supportive letter was provided by TASH, Health Science College, Addis Ababa University. Every effort was made to protect participants’ well-being and dignity. Voluntary participation was emphasized, and participants had the right to withdraw from the study at any time. Informed consent was obtained from caregivers, and assent was obtained from children as appropriate. All research procedures adhered to the Declaration of Helsinki.
3. Results
3.1. Socio-demographic and clinical characteristics of study participants
A total of 179 children with ALL were enrolled in the study. Of these, 115 (64.2%) were male. The age of the participants ranged from 1 to17 year, with a mean age of 8.06 ± 4.05 years. The majority of participants, 122(68.2%) were aged 1–10 years, followed by those aged 10–17 years. More than half the participants, 95 (53.1%) were rural residents, and 135 (75.5%) of the caregivers were unemployed. Most caregivers reported a monthly income below 1,000 ETB. The regional distribution of the study participants was as follows: 105 (58.66%) of the patients were from Amhara, 35 (19.55%) from Oromiya, 16 (8.94%) from the Southern Nations, Nationalities, and Peoples Region (SNNP), 15 (8.38%) from Addis Ababa, 5 (2.79%) from Somalia and 3 (1.68%) from Tigray (Table 1).
3.2. Initial clinical presentation of children diagnosed with ALL
The most common presenting symptom was bone pain observed in 154 (86.0%) of the patients. Neutropenic fever was the second most common symptoms, affecting 146 (81.6%) patients; however, osteonecrosis was not found in these study participants. Persistent infection was observed in 134 (74.9%) of the patients. Loss of appetite was noted in 153 (85.5) patients and behavioral alteration was observed in 128 (71.5%) patients. Petechiae (skin rash) occurred in 108 (60.3%) patients. Anemia was present in 144 (80.4%) patients, and abdominal swelling was noted in 84 (46.9%). The most common laboratory finding was severe anemia, affecting 22.9% of the patients (hemoglobin < 7 g/dl). Regarding physical signs, pallor was the most common, observed in 145 (81.0%) of the patients. Lymphadenopathy (LAP) was detected in 26 (14.5%), and subcutaneous nodules were found in 10 (5.6%) of the patients. Additionally, 7 (3.9%) patients exhibited raddish discoloration of the urine, and 5 (2.8%) had eye involvement. Regarding the ALL status of the children, 92 (51.4%) were diagnosed with SR ALL, and 87 (48.6%) with HR ALL. Of these, 146 (81.6%) were alive, while 33 (18.4%) had passed away before treatment initiation during the study period at the two study settings (Table 2).
3.3. Changes in hematologic parameters across treatment phases
Initial white blood cell (WBC) counts ranged from 1.10 x 103 counts/mm³ to 465 x 103 counts/mm³, hemoglobin (Hgb) levels ranged from 1.60 g/dl to 31.70 g/dl, and platelet counts ranged from 2.0 counts/mm3 to 700,000 counts/mm3. The initial median white blood cell count, hemoglobin level, and platelet count at presentation were 42,000 counts/mm³ (IQR: 72,200 counts/mm³), 8.9 g/dl (IQR: 3.50 g/dl), and 97 (IQR: 170/mm³), respectively. Overall, the hematological profile at the end of consolidation indicates persistent cytopenias, particularly leukopenia, anemia, and thrombocytopenia. During the third phase, significant hematological challenges were faced by children with ALL undergoing mercaptopurine maintenance therapy. The high prevalence of low white blood cell counts (15/22, 68.2%), low hemoglobin levels (7–10 g/dl) (12/22, 54.5%), and platelet counts < 20k (6/22, 27.3%) were notable (Table 3).
At the end of the induction phase, the median white blood cell (WBC) count was 12,000/mm³, indicating an improvement compared to the initial hematological profiles. The majority of patients, 85(70.8%), gained weight during induction therapy. A small percentage of patients, 9 (7.5%), experienced treatment failure during induction therapy, while 18 (10.1%) of ALL patients relapsed at different phases of treatment (Table 4).
3.4. Chemotherapy-related side effects during the first six months of maintenance therapy
Among the adverse effects and complications associated with treatment, hepatotoxicity, characterized by elevated liver transaminases, was observed in 9 (40.9%) of patients, predominantly during the maintenance phase. The most frequently reported side effects were fever and flu-like symptoms, which occurred in 18 (81.8%) patients. Nausea and vomiting were reported in 17 (77.3%) patients, itching or skin rash in 15 (68.2%) patients, and loss of appetite in 11 patients (50%), making them the most common side effects consecutively. Furthermore, mucositis was reported in 7 patients (31.8%), neutropenic fever affected 18 patients (81.8%). A significant proportion of patients experienced hematological side effects such as neutropenia 12(52.2%), leukopenia 15(68.2%), thrombocytopenia 17(77.3%), and anemia 19(86.4%). These are common consequences of chemotherapy. These side effects are common outcomes of chemotherapy and can considerably affect the quality of life for patients as well as their adherence to treatment. Most of the study participants who completed their treatment were male (13/22, 59.1%) and urban residents (16/22, 72.7%) (Table 5).
3.5. Treatment Outcomes and Abandonment Rates in ALL Patients Across Induction, Consolidation, and Maintenance Phases
The rates of treatment abandonment during the induction, consolidation, and maintenance phases were 26 (14.53%), 13 (7.3%), and 10 (5.6%), respectively. Additionally, 75 (41.9%) of the study participants achieved event-free survival. Across all treatment phases, 22 (12.29%) of patients completed their treatment (Fig 1). Treatment abandonment was significantly higher among children from rural backgrounds (p < 0.001), those with lower socioeconomic status (p < 0.001), and those with low hemoglobin levels (p = 0.000) or severe wasting (p = 0.001).
3.6. Kaplan-Meier analysis of overall survival in ALL patients
Kaplan-Meier survival curves were generated to assess the impact of key prognostic factors on overall survival in patients with ALL. It was hypothesized that patients presenting with elevated WBC counts would exhibit a steeper decline in the survival curve during the initial period, reflecting an increased risk of early mortality. This is consistent with the established association between high initial WBC counts and a more aggressive disease phenotype. Similarly, patients with concomitant malaria infection were expected to demonstrate a significantly steeper decline in survival compared to malaria-negative patients, suggesting a poorer prognosis. Furthermore, CNS involvement at diagnosis was also anticipated to correlate with a steeper survival curve, indicative of a diminished survival probability.
Kaplan-Meier hazard curves demonstrated a significantly elevated cumulative risk of mortality in patients with high initial WBC counts, malaria infection, and CNS involvement, compared to those with low initial WBC counts, absence of malaria, and no CNS involvement (P < 0.05) (Fig 2).
3.7. Predictor of for mortality during the treatment phase
Cox proportional hazards regression analysis was performed to identify predictors of mortality during the treatment phase of ALL. The univariate analysis revealed that an initial leukocyte count of ≥50x103/µL (p > 0.05), sex (p > 0.05), and CNS involvement (p < 0.058) did not show statistical significance. In contrast, factors such as platelet count (p < 0.002), age (p < 0.011), relapsed ALL patients (p < 0.001), sepsis (p < 0.047), LDH levels (p < 0.008), malaria infection (p < 0.043), and area of residence (p < 0.050) were significantly associated with mortality. The multivariate analysis identified several statistically significant variables: the absence of bone marrow remission after the induction phase (relapsed) increased the risk nearly twofold; age over 10 years increased the risk by 2.2 times; elevated LDH levels raised the risk by 2.7 times; sepsis increased the risk by 2.4 times; low platelet counts nearly doubled the risk; and T-cell ALL, malaria, and induction failure were associated with approximately sevenfold, fourfold, and fourfold higher risks of death, respectively (Table 6).
Discussion
The significant improvement in survival rates for childhood ALL represents a major milestone in cancer treatment. In the 1960s, only 15% of children diagnosed with ALL survived for five years post-diagnosis. Today, over 80% of these children achieve five years, with a remarkable 93.5% considered cured [28]. Recent advancements have enabled nearly all children with standard-risk ALL (100%) to achieve a cure [29,30]. However, treatment outcomes for ALL in sub-Saharan Africa remain suboptimal, facing substantial challenges [31]. To our knowledge, this is the first prospective longitudinal study to describes the clinical profile and treatment outcomes for ALL among pediatric patients in Ethiopia and more broadly, across sub-Saharan Africa.
The most common initial clinical feature among patients with ALL was anemia, observed in 144 patients (80.4%). These findings are consistent with a study conducted in Kenya, where anemia was present in 147 patients (86.0%). In our study, fever was noted in 81.6% of patients, whereas in Rwanda, it was observed in 76% of patients [6]. Other common clinical features include lymphadenopathy in 26 patients (14.5%) and abdominal swelling in 84 (46.9%) patients, with subcutaneous nodule found in 10 (5.6%). Similarly, in Kenya, lymphadenopathy was reported in 83 (48.5%) patients, and abdominal swelling in 82 (48.0%) patients [32]. In Syria, lymphadenopathy was observed in 82.9% of patients [30].
In our study, the most common French-American-British (FAB) ALL subtype was L2 (48.0%), followed by L1 (38%), L3 (7.8%) and non-categorized cases (6.1%). This is consistent with findings from Kenya, where L1 was present in 16 patients (10.13%), L2 in 129 patients (81.65%), and non-categorized in 13 patients (8.23%) [32]. In contrast, a study from Indonesia reported that 77.5% of cases were FAB L1, 20.8% were FAB L2, and 1.7% were FAB L3 [33]. Similarly, a study from the United Kingdom found that 13% case were L2, 0.7% were L3, and 86% were L1[34]. A study conducted in Syria found L1 in 77.4%, L2 in 20.4%, and L3 in 21% [30], while a Brazilian study found L1 in 83% and L2 in 17% [35]. Our findings for L1 are comparable to those observed in Tehran, where L1 was found in 57.6% of cases, and L2 + L3 accounted for 42.4% (P > 0.05). Another study reported that L1 was present in 85–89% of cases, with L2 at 14.1% and L3 at 0.8% [36].
The results of this study indicated that 81 (45.3%) of children with ALL died during various phases of treatment. This mortality rate is higher than the 20% reported in Kosobo [18] and lower than the 71% observed in Rwanda [2]. Among these deaths, 33 (18.4%) occurred prior to induction, 14.5% during induction, and 5.6% after chemotherapy, while 9 patients (7.5%) experienced relapse. Notably, there was a 41.90% event-free survival (EFS) rate, with only 22 patients (12.3%) completing the entire treatment regimen. Our findings are lower than those of a study conducted in Cambodia, which reported a mortality rate of 34.9% [37]. A similar study in Kenya found death, relapse, and abandonment rates of 30%, 26%, and 24%, respectively, with an EFS rate of 20%. Among all recorded deaths, 80% occurred in patients who had relapsed, while only 20% were in remission [35]. Furthermore, Research from Egypt indicated relapse rates of 12% to 20% and a mortality rate of 23% [23,36]. In other study, relapse was observed in 27% of patients who had achieved remission, contributing to elevated mortality rates and a low overall survival (OS) rate at five years. Most patients who relapsed did so shortly after achieving remission [23]. Refusal and abandonment of treatment are leading causes of treatment failure [38,39].
Different studies have shown varying patient outcomes across countries. In Nicaragua, 7% of patients died during induction, and 9% abandoned treatment, with 5-year and ten-year EFS rates of 38.1% and 36.6% respectively, and OS rates of 48.0% and 39.6% [37]. In Brazil, treatment mortality varied widely from 32% to 63%, while Indonesia reported a high death rate of 60.5%. In contrast, a Central American study showed much better results: only 3.0% of patients died during induction, with just 2.7% abandoning treatment and only 1.1% developing resistant ALL. Additionally, 93.2% achieved complete remission, with deaths and treatment abandonment during the first complete remission period at only 2.7% and 7.0%, respectively [40].
Global variability in 6-mercaptopurine 6-MP-induced toxicity can be attributed to factors such as patient characteristics, follow-up periods, genetic variations, and differences in dosing and adjustment protocols [40]. This study observed a higher incidence of grade 4 neutropenia (52.2%) which is consistent with similar studies from China (47%) [41] and Thailand (47%) [42]. Swedish and Korean studies reported even higher rates [43,44]. Additionally, this study identified increased rates of 6-MP interruption and neutropenic fever compared to earlier reports [1], although some studies documented higher treatment interruptions [5]. The most common side effects reported were fever or flu-like symptoms (81.8%), itching or skin rash (68.2%), decreased appetite (50%), and behavior changes (63.6%). However, a study from Indonesia found behavior changes to be the most frequent side effect, followed by increased appetite and infections. The higher incidence of fever or flu-like symptoms in this study may be related to hematotoxicity [1]. Neutropenia was the primary cause of death-related treatment complications, often exacerbated by infections that led to life-threatening conditions requiring further treatment. This may have contributed to delays in therapy during the induction phase [45].
In our study, the leading cause of mortality was identified as treatment abandonment, often attributed to financial constraints, inadequate healthcare facilities, and misconceptions among healthcare providers. These factors contribute to delays in seeking medical attention and increase the risk of severe infections. Various studies have indicated that the predominant reasons for abandonment include financial limitations (34.5% in one study and 59.4% in another), [57], misconceptions regarding the curability of conditions (20% in one study and 22.9% in another), [57], poor overall health status of the child (15%), lack of improvement in condition (13%), and refusal to donate blood (3%). A significant number of fatalities were directly associated with infections [23].
Malaria infection complicates the treatment of ALL, increasing the risk of severe infections. Conversely, patients who tested negative for malaria were more likely to exhibit a favorable survival trajectory due to the absence of malaria-related complications. Central nervous system (CNS) involvement at baseline was notably prevalent in this study and was associated with adverse outcomes. This finding aligns with observations from high-income countries, where CNS involvement is recognized as a negative prognostic indicator in pediatric ALL [46]. The incidence of CNS disease at presentation in our study was significantly higher than that reported in high-income countries, where it typically occurs in less than 10% of cases [47]. This discrepancy may be attributed to chance, delayed disease presentation, or differences in biological factors; however, further studies are needed to investigate this issue in greater detail.
A high initial leukocyte count is a critical factor in therapy risk stratification and is associated with a worse prognosis. High-risk HR patients experience lower overall survival (OS) and EFS due to both the poorer prognosis associated with their condition and the more intensive therapy required for treatment [46]. In our study, 63 patients (48.6%) were classified as HR, while 51.4% were classified as SR. This is comparable to the HR rate of 51.4% reported in Addis Ababa (51.4%) and other SR classifications [5], in Cambodia, 57% were classified as HR and 43% as SR [37], while in Rwanda, 14.29% were SR, 21.43% were HR, 4.76% were very HR, and 59.52% were unclassifiable [6]. The highest mortality rates were observed in the HR and very high-risk groups (p < 0.001), consistent with other studies [48].
Factors contributing to the longer duration of the induction phase included infections. Inadequate clearance of leukemic cells during induction may increase the risk of induction failure and lead to a higher likelihood of relapse and severe complications [49]. However, our study shows that 10% of patients experienced relapse, which is Comparable to the study conducted in Kosobo and in Egypt, where the relapse rate was 11% [16], and 27% [23] respectively. Our study found a 7.5% induction failure rate and a 10.1% relapse rate, likely due to the reliance on morphological examination at the end of the induction phase. This method remains crucial for assessing ALL therapy in many developing countries with limited minimal residual disease (MRD) facilities. A prolonged induction phase can negatively impact prognosis and treatment outcomes, increasing the risk of complications [50]. Similar findings were reported in a study conducted in India [51], as well as in studies conducted in other countries [45,52].
In a multivariate analysis, several significant factors were identified as contributing to mortality and poor prognosis, including age, rural residency, T-cell ALL, sepsis, elevated LDH levels, relapsed ALL patients, low platelet counts, malaria infection and induction failure (all p < 0.05). These findings are consistent with numerous studies conducted in various countries, which have reported similar associations between these factors and adverse outcomes in ALL patients [45,49,52,53].
Future prospective cohort studies should investigate factors that may influence the survival of patients with ALL in LMICs. Key factors to assess include socioeconomic status, healthcare providers’ perceptions, inadequate medical facilities, parental education, family attitudes toward the disease, and the distance between patients’ homes, healthcare facilities, and pediatric oncology centers. Understanding these variables is critical for developing targeted interventions to improve treatment outcomes and survival rates in these regions.
Conclusion
This study observed a high mortality rate among children with ALL, despite advancements in treatment. Key risk factors for death included the absence of bone marrow remission after the induction phase; age over 10 years, elevated LDH levels, and sepsis. Additionally, low platelet counts, T-cell ALL, and malaria infection were significantly associated with increased mortality risk. To improve survival rates, it is essential to address these risk factors through targeted interventions. Furthermore, optimizing treatment regimens, minimizing delays in diagnosis and treatment initiation, and providing personalized care based on individual genetic and clinical profiles are critical steps toward enhancing outcomes for ALL patients.
Acknowledgments
The authors would like to thank the University of Gondar Comprehensive Specialized Hospital for their kind cooperation in facilitating this study. We are also grateful to the data collectors and study participants for their valuable contributions.
References
- 1. Rosdian DS, Louisa M, Gatot D, Setiabudy R. Hematotoxicity in Acute Lymphoblastic Leukemia children who received 6-mercaptopurine during maintenance therapy in Indonesia. J Int Dental Med Res. 2019;12(3):1154–61.
- 2. Ward ZJ, Yeh JM, Bhakta N, Frazier AL, Atun R. Estimating the total incidence of global childhood cancer: a simulation-based analysis. Lancet Oncol. 2019;20(4):483–93. pmid:30824204
- 3.
Agwata BN. A ten year retrospective study on therapeutic management and clinical outcomes of acute lymphoblastic leukemia among children at Kenyatta National Hospital, Kenya. 2012.
- 4. Ali AM, Adam H, Hailu D, Engidawork E, Howe R, Abula T, et al. Genetic variants of genes involved in thiopurine metabolism pathway are associated with 6-mercaptopurine toxicity in pediatric acute lymphoblastic leukemia patients from Ethiopia. Front Pharmacol. 2023;14:1159307. pmid:37251339
- 5. Ali AM, Adam H, Hailu D, Coenen MJH, Howe R, Abula T. Incidence and determinants of hematotoxicity in acute lymphoblastic leukemia children who received 6-mercaptopurine based maintenance therapy in Addis Ababa, Ethiopia. PLoS One. 2023;18(6):e0286544. pmid:37267380
- 6. Rubagumya F, Xu MJ, May L, Driscoll C, Uwizeye FR, Shyirambere C, et al. Outcomes of low-intensity treatment of Acute Lymphoblastic Leukemia at Butaro cancer center of excellence in Rwanda. J Glob Oncol. 2017;4:1–11. pmid:30241148
- 7. Rudin S, Marable M, Huang RS. The promise of pharmacogenomics in reducing toxicity during Acute Lymphoblastic Leukemia maintenance treatment. Genomics Proteomics Bioinform. 2017;15(2):82–93. pmid:28391009
- 8.
Puckett Y, Chan O. Acute Lymphocytic Leukemia. StatPearls [Internet]. StatPearls Publishing; 2021.
- 9. Lejman M, Kuśmierczuk K, Bednarz K, Ostapińska K, Zawitkowska J. Targeted therapy in the treatment of pediatric Acute Lymphoblastic Leukemia-therapy and toxicity mechanisms. Int J Mol Sci. 2021;22(18):9827. pmid:34575992
- 10. Yifru S, Muluye D. Childhood cancer in Gondar university hospital, Northwest Ethiopia. BMC Research Notes. 2015;8:1–5.
- 11. Mirutse MK, Tolla MT, Memirie ST, Palm MT, Hailu D, Abdi KA, et al. The magnitude and perceived reasons for childhood cancer treatment abandonment in Ethiopia: from health care providers’ perspective. BMC Health Serv Res. 2022;22(1):1014. pmid:35941600
- 12. Kersten E, Scanlan P, Dubois SG, Matthay KK. Current treatment and outcome for childhood acute leukemia in Tanzania. Pediatr Blood Cancer. 2013;60(12):2047–53. pmid:24039163
- 13. Cai J, Yu J, Zhu X, Hu S, Zhu Y, Jiang H, 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):522–9. pmid:30705079
- 14.
Pui CH, Evans WE, editors. A 50-year journey to cure childhood acute lymphoblastic leukemia. In: Seminars in hematology. Elsevier; 2013.
- 15. Farber S, Diamond LK, Mercer RD, Sylvester Jr RF, Wolff JA. Temporary remissions in acute leukemia in children produced by folic acid antagonist, 4-aminopteroyl-glutamic acid (aminopterin). N Engl J Med. 1948;238(23):787–93. pmid:18860765
- 16. Pasha F, Urbančič D, Maxhuni R, Krasniqi S, Grajçevci Uka V, Mlinarič-Raščan I. Prevalence and treatment outcomes of childhood acute lymphoblastic leukemia in Kosovo. Cancers (Basel). 2024;16(11):1988. pmid:38893109
- 17. Sousa P, Estevinho MM, Dias CC, Ministro P, Kopylov U, Danese S, et al. Thiopurines’ metabolites and drug toxicity: a meta-analysis. J Clin Med. 2020;9(7):2216. pmid:32668748
- 18. Ataseven E, Kosova B, Aktan Ç, Kurugöl Z, Kantar M. Thiopurine-S-methyltransferase gene polymorphism and drug-related toxicity in children treated for acute leukemia and non-hodgkin’s lymphoma. J Pediatric Res. 2022;9(1):60.
- 19.
Azad M, Kaviani S, Soleymani M, Nourouzinia M, Hajfathali A. Common polymorphism’s analysis of thiopurine S-methyltransferase (TPMT) in Iranian population. 2009.
- 20. Dagnew SB, Tadesse TY, Zeleke MM, Yiblet TG, Addis GT, Mekonnen GB. Drug–drug interactions among hospitalized elderly in patients at medical wards of Northwest Ethiopia’s comprehensive specialized hospitals: a multicenter observational study. SAGE Open Med. 2022;10.
- 21. Enawgaw B, Aynalem M, Melku M, Asrie F, Abebe M, Yalew A, et al. Hematological malignancies in the Northwest Ethiopia. PLoS One. 2021;16(12):e0260639. pmid:34852010
- 22. Balta B, Gebreyohannis T, Tachbele E. Survival and predictors of mortality among acute leukemia patients on follow‐up in Tikur Anbessa specialized hospital, Addis Ababa, Ethiopia: a 5‐year retrospective cohort study. Cancer Reports. 2023;2023:e1890.
- 23. Abdelmabood S, Fouda AE, Boujettif F, Mansour A. Treatment outcomes of children with acute lymphoblastic leukemia in a middle-income developing country: high mortalities, early relapses, and poor survival. J Pediatr (Rio J). 2020;96(1):108–16. pmid:30240631
- 24. Hailu A, Mekasha A, Hailu D, Fentie AM, Korones DN, Gidey AM. Impact of delay prior to treatment in Ethiopian children with acute lymphoblastic leukemia. Pediatr Health Med Therapeutics. 2023:147–57.
- 25. Smith M, Arthur D, Camitta B, Carroll AJ, Crist W, Gaynon P, et al. Uniform approach to risk classification and treatment assignment for children with acute lymphoblastic leukemia. J Clin Oncol. 1996;14(1):18–24. pmid:8558195
- 26. Omoti CE, Nwannadi AI, Obieche JC, Olu-Eddo AN. The epidemiological features of lymphoid malignancies in Benin City, Nigeria: a 15 years study. Pan Afr Med J. 2012;11:10. pmid:22368753
- 27. Kamath GR, Tremblay D, Coltoff A, Caro J, Lancman G, Bhalla S, et al. Comparing the epidemiology, clinical characteristics and prognostic factors of acute myeloid leukemia with and without acute promyelocytic leukemia. Carcinogenesis. 2019;40(5):651–60. pmid:30715157
- 28. Carroll WL. Race and outcome in childhood acute lymphoblastic leukemia. JAMA. 2003;290(15):2061–3. pmid:14559962
- 29. Hayashi H, Makimoto A, Yuza Y. Treatment of pediatric acute lymphoblastic leukemia: a historical perspective. Cancers (Basel). 2024;16(4):723. pmid:38398113
- 30. Kakaje A, Alhalabi MM, Ghareeb A, Karam B, Mansour B, Zahra B, et al. Rates and trends of childhood acute lymphoblastic leukaemia: an epidemiology study. Sci Rep. 2020;10(1):6756. pmid:32317670
- 31. Chagaluka G, Carey P, Banda K, Schwab C, Chilton L, Schwalbe E, et al. Treating childhood acute lymphoblastic leukemia in Malawi. Haematologica. 2013;98(1):e1-3. pmid:22899578
- 32.
Agwata BN. A ten year retrospective study on therapeutic management and clinical outcomes of acute lymphoblastic leukemia among children at Kenyatta National Hospital, Kenya January 2001-December 2010. Kenya: University of Nairobi; 2012.
- 33. Arifin Z, Nasution F, Sutjipto A. Acute lymphoblastic leukemia in the department of child health, school of medicine, University of North Sumatera/Dr. Pirngadi Hospital Medan (1980-1988). Paediatrica Indonesiana. 1991;31(7-8):185–90.
- 34. Lilleyman J, Hann I, Stevens R, Eden O, Richards S. French American British (FAB) morphological classification of childhood lymphoblastic leukaemia and its clinical importance. J Clin Pathol. 1986;39(9):998–1002.
- 35. Sousa DWLd, Ferreira FVdA, Félix FHC, Lopes MVdO. Acute lymphoblastic leukemia in children and adolescents: prognostic factors and analysis of survival. Revista Brasileira de Hematologia e Hemoterapia. 2015;37:223–9.
- 36. Miller DR, Leikin S, Albo V, Sather H, Hammond D. Prognostic importance of morphology (FAB classification) in childhood acute lymphoblastic leukaemia (ALL). Br J Haematol. 1981;48(2):199–206. pmid:6940623
- 37. Küpfer L, Meng B, Laurent D, Zimmermann M, Niggli F, Bourquin J-P, et al. Treatment of children with acute lymphoblastic leukemia in Cambodia. Pediatr Blood Cancer. 2021;68(10):e29184. pmid:34319655
- 38.
Alam AA, Kumar AK. Prevalence, predictors, causes of treatment refusal and abandonment in children with acute lymphoblastic leukaemia over 18 years in North India. Treatment phase affecting factors: a step towards better focussed counselling. 2018.
- 39. Hazarika M, Mishra R, Saikia BJ, Bhuyan C, Nyuthe CW, Sarma A, et al. Causes of treatment abandonment of pediatric cancer patients – experience in a regional cancer centre in North East India. Asian Pac J Cancer Prev. 2019;20(4):1133–7. pmid:31030486
- 40.
Vu HPT. Predictors of treatment toxicity and prognosis in pediatric acute lymphoblastic leukemia in Belgian and Vietnamese populations. UCL-Université Catholique de Louvain; 2015.
- 41. Fan POL, Leung K-T, Chan KYY, Leung AWK, Lam GKS, Chow TTW, et al. ABCC4, ITPA, NUDT15, TPMT and their interaction as genetic predictors of 6-mercaptopurine intolerance in chinese patients with acute lymphoblastic leukemia. Pediatr Hematol Oncol. 2022;39(3):254–66. pmid:34665987
- 42. Puangpetch A, Tiyasirichokchai R, Pakakasama S, Wiwattanakul S, Anurathapan U, Hongeng S, et al. NUDT15 genetic variants are related to thiopurine-induced neutropenia in Thai children with acute lymphoblastic leukemia. Pharmacogenomics. 2020;21(6):403–10. pmid:32308129
- 43. Wahlund M, Nilsson A, Kahlin AZ, Broliden K, Myrberg IH, Appell ML, et al. The Role of TPMT, ITPA, and NUDT15 variants during mercaptopurine treatment of Swedish pediatric patients with acute lymphoblastic leukemia. J Pediatr. 2020;216:150-157.e1. pmid:31635813
- 44. Lee JM, Shim YJ, Kim D-H, Jung N, Ha J-S. The Effect of NUDT15, TPMT, APEX1, and ITPA genetic variations on mercaptopurine treatment of pediatric acute lymphoblastic leukemia. Children (Basel). 2021;8(3):224. pmid:33804051
- 45. Ramadhan MH, Sari NM, Peryoga SU, Susanah S. Survival and treatment outcomes of childhood acute lymphoblastic leukemia in a low-middle income country: a single-center experience in West Java, Indonesia. J Blood Med. 2024:77–85.
- 46. Park KM, Yang EJ, Lee JM, Hah JO, Park SK, Park ES, et al. Treatment outcome in pediatric acute lymphoblastic leukemia with hyperleukocytosis in the Yeungnam region of Korea: a multicenter retrospective study. J Pediatr Hematol Oncol. 2020;42(4):275–80. pmid:32134842
- 47. Stary J, Zimmermann M, Campbell M, Castillo L, Dibar E, Donska S, et al. Intensive chemotherapy for childhood acute lymphoblastic leukemia: results of the randomized intercontinental trial ALL IC-BFM 2002. J Clin Oncol. 2014;32(3):174–84. pmid:24344215
- 48. Björk-Eriksson T, Boström M, Bryngelsson L, Lähteenmäki PM, Jarfelt M, Kalm M. Mortality among pediatric patients with acute lymphoblastic leukemia in Sweden from 1988 to 2017. JAMA Network Open. 2022;5(11):e2243857-e.
- 49. Schrappe M, Hunger SP, Pui C-H, Saha V, Gaynon PS, Baruchel A, et al. Outcomes after induction failure in childhood acute lymphoblastic leukemia. N Engl J Med. 2012;366(15):1371–81. pmid:22494120
- 50. Kato M, Manabe A. Treatment and biology of pediatric acute lymphoblastic leukemia. Pediatr Int. 2018;60(1):4–12. pmid:29143423
- 51. Jaime-Pérez JC, Pinzón-Uresti MA, Jiménez-Castillo RA, Colunga-Pedraza JE, González-Llano Ó, Gómez-Almaguer D. Relapse of childhood acute lymphoblastic leukemia and outcomes at a reference center in Latin America: organomegaly at diagnosis is a significant clinical predictor. Hematology. 2018;23(1):1–9. pmid:28580844
- 52. Alam A, Kumar A. Prevalence, predictors, causes of treatment refusal and abandonment in children with acute lymphoblastic leukaemia over 18 years in North India. Treatment phase affecting factors: a step towards better focussed counselling. Cancer Epidemiol. 2018;57:53–9. pmid:30316108
- 53. Widjajanto PH, Sumadiono S, Cloos J, Purwanto I, Sutaryo S, Veerman AJ. Randomized double blind trial of ciprofloxacin prophylaxis during induction treatment in childhood acute lymphoblastic leukemia in the WK-ALL protocol in Indonesia. J Blood Med. 2013;4:1–9. pmid:23403504