Chronic Myeloid Leukemia in Yemen: Clinical, Hematological, and Molecular Characteristics at Diagnosi

doi:10.21203/rs.3.rs-7941464/v1

Background

Chronic Myeloid Leukemia (CML) is a myeloproliferative neoplasm defined by the BCR-ABL1 fusion gene. Data from resource-limited regions like Yemen remain scarce. This study characterizes CML in a large Yemeni cohort.

Methods

A retrospective study of 175 CML patients diagnosed between August 2015 and August 2022 at Al-Thawra Modern General Hospital, Sana’a. Data included demographic, clinical, and laboratory parameters. Diagnosis was confirmed by RT-PCR for BCR-ABL1.

Results

Median age at diagnosis was 43.4 years, significantly younger than Western populations. Male predominance was observed (58.3%, M:F = 1.4:1). At presentation, 98.3% had leukocytosis, 77.1% anemia, and 90.3% splenomegaly. Thrombocytosis occurred in 42.3%. All patients were in chronic phase. BCR-ABL1 was detected in 94.3%.

Conclusion

CML in Yemen presents at younger ages with distinct hematological features, highlighting the need for region-specific diagnostic and management strategies. Molecular testing is crucial for accurate diagnosis.

Hematology

Oncology

Internal Medicine

Chronic Myeloid Leukemia

CML

Yemen

BCR-ABL1

Epidemiology

Hematology

Chronic Myeloid Leukemia (CML) is a clonal myeloproliferative neoplasm (MPN) characterized by the excessive production of mature and maturing granulocytes. It accounts for approximately 15% of all newly diagnosed leukemias in adults, with a global annual incidence of 1–2 cases per 100,000 people [1, 2]. The pathognomonic feature of CML is a balanced reciprocal translocation between chromosomes 9 and 22, t(9;22)(q34;q11.2), which results in the Philadelphia (Ph) chromosome [3]. This translocation creates the BCR-ABL1 fusion gene, which encodes a constitutively active tyrosine kinase that drives leukemogenesis [4].

The epidemiology of CML shows significant geographic and demographic variation. In Western countries, the median age at diagnosis is between 64 and 66 years [5, 6]. However, studies from developing nations, such as India, report a much younger median age of 35–40 years [7, 8]. A consistent male predominance is observed globally, with a male-to-female ratio ranging from 1.2:1 to 1.7:1 [2].

Diagnosis of CML is based on a combination of clinical findings, peripheral blood counts, bone marrow morphology, and, most importantly, the detection of the Ph chromosome or its molecular equivalent, the BCR-ABL1 transcript [1]. The vast majority of patients present in the chronic phase (CP), which is characterized by leukocytosis, splenomegaly, and less than 10% blasts in the peripheral blood and/or bone marrow. If left untreated, CML progresses to an accelerated phase (AP) and ultimately a fatal blast phase (BP) [9].

While extensive data on CML exists from high-income countries, there is a scarcity of comprehensive reports from resource-limited settings, particularly from the Middle East and North Africa region. In Yemen, a country facing significant socioeconomic and healthcare challenges, the characteristics of CML remain poorly defined. A previous study from 2005 provided an initial overview of adult leukemias but lacked the detailed molecular analysis that is now standard of care [10]. This study aims to fill this critical knowledge gap by providing a comprehensive analysis of the demographic, clinical, hematological, and molecular characteristics of a large cohort of CML patients diagnosed at a major tertiary care center in Sana’a, Yemen.

2.1. Study Design and Population

A retrospective observational study was conducted using hospital records from Al-Thawra Modern General Hospital in Sana’a, Yemen. The study included all patients diagnosed with CML between August 2015 and August 2022. A total of 175 patients with a confirmed diagnosis of CML were included in the final analysis.

2.1.1. Ethical Considerations

List of Abbreviations

CML: Chronic Myeloid Leukemia

MPN: Myeloproliferative Neoplasm

Ph: Philadelphia

BCR-ABL1: Breakpoint Cluster Region-Abelson

TKI: Tyrosine Kinase Inhibitor

RT-PCR: Reverse Transcription Polymerase Chain Reaction

WBC: White Blood Cell

Hb: Hemoglobin

CP: Chronic Phase

AP: Accelerated Phase

BP: Blast Phase

PBF: Peripheral Blood Film

CI: Confidence Interval

SD: Standard Deviation

This study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of Al-Thawra Modern General Hospital and the Research Ethics Committee of the Faculty of Medicine and Health Sciences, Sana’a University (Approval No.: FMHS/EC-2022/045, Date: August 15, 2022). Given the retrospective nature of the study using anonymized patient records, the requirement for informed consent was waived by the ethics committee. Patient confidentiality was strictly maintained throughout the study.

2.2. Data Collection

Data were extracted from patient files, including demographic information (age, gender, marital status, educational level, governorate of residence), clinical findings at presentation (e.g., presence of splenomegaly), and laboratory results. Laboratory data included complete blood count (CBC), peripheral blood film (PBF) morphology, bone marrow aspiration and cytology findings, and molecular test results.

2.3. Laboratory Methods

Complete blood counts were performed using automated hematology analyzers. Peripheral blood films and bone marrow aspirate smears were stained with Leishman stain and evaluated by experienced hematologists. The diagnosis of CML was confirmed by the detection of the BCR-ABL1 fusion transcript using a qualitative reverse transcription-polymerase chain reaction (RT-PCR) assay. In BCR-ABL1-positive cases, transcript type (e13a2 vs e14a2) was determined when possible.

2.4. Statistical Analysis

Data were analyzed using SPSS version 25 (IBM Corp., Armonk, NY, USA) and Python version 3.8 with pandas, scipy, and statsmodels libraries. Descriptive statistics, including frequencies, percentages, means, standard deviations (SD), medians, and ranges, were calculated. The Shapiro-Wilk test was used to assess normality of continuous variables. For categorical variables, the Chi-square test or Fisher’s exact test (when expected cell counts <5) was applied. Pearson correlation coefficients were calculated to assess relationships between continuous variables. A two-tailed p-value of <0.05 was considered statistically significant. 95% confidence intervals (CI) were calculated for all proportions using the Wilson score method.

3.1. Demographic Characteristics

A total of 175 CML patients were included in the study. The median age at diagnosis was 43.4 years (range: 10-75 years). The most affected age group was 45-65 years, accounting for 49.1% of cases. There was a significant male predominance, with 102 male patients (58.3%) and 73 female patients (41.7%), corresponding to a male-to-female ratio of 1.4:1 (p=0.028). The majority of patients were from governorates outside the capital city, Sana’a, with Amran (19.4%), Damar (18.3%), and Ibb (18.3%) being the most common regions of residence. Detailed demographic data are presented in Table 1 and Figure 1.

Table 1: Demographic and Clinical Characteristics of CML Patients (n=175)

Characteristic	n	%	95% CI
Age Group (years)
<15	3	1.7	0.4-4.9
15-29	26	14.9	9.9-21.0
30-44	52	29.7	23.0-37.1
45-65	86	49.1	41.5-56.8
>65	8	4.6	2.0-8.8
Gender
Male	102	58.3	50.7-65.6
Female	73	41.7	34.4-49.3
Geographic Residence
Amran	34	19.4	13.9-26.0
Damar	32	18.3	12.9-24.8
Ibb	32	18.3	12.9-24.8
Taiz	30	17.1	11.9-23.5
Hajah	25	14.3	9.4-20.4
Sana’a	15	8.6	4.8-13.9
Other	9	5.1	2.4-9.5

3.2. Hematological and Clinical Findings

At diagnosis, the mean white blood cell (WBC) count was markedly elevated at 129.8 ± 88.1 ×10⁹/L. Anemia was a common finding, with a mean hemoglobin (Hb) level of 9.8 ± 2.4 g/dL; 77.1% of patients were anemic. The mean platelet count was 414.0 ± 368.7 ×10⁹/L, with 42.3% of patients presenting with thrombocytosis and 18.9% with thrombocytopenia. Splenomegaly was clinically documented in 90.3% of patients. All 175 patients were diagnosed in the chronic phase of the disease. Table 2 and Figure 2 summarize these findings.

Table 2: Hematological Parameters at Diagnosis in CML Patients (n=175)

Parameter	Mean ± SD	Median (Range)	Abnormal (%)
Hemoglobin (g/dL)	9.8 ± 2.4	9.5 (5.5-21.0)	77.1
WBC count (×10⁹/L)	129.8 ± 88.1	98.0 (1.7-375.0)	98.3
Platelet count (×10⁹/L)	414.0 ± 368.7	320.0 (19-2100)	61.1
Basophils (%)	2.0 ± 0.6	2.0 (0-4)	94.9

3.2.1. Correlation Between Age and Hematological Parameters

Correlation analysis revealed significant associations between age and key hematological parameters. Age showed a weak negative correlation with WBC count (Pearson r = -0.18, p=0.019), suggesting that younger patients tended to present with higher leukocyte counts. No significant correlation was found between age and hemoglobin level (r = 0.08, p=0.29) or platelet count (r = -0.05, p=0.52). Similarly, WBC count showed a weak positive correlation with platelet count (r = 0.21, p=0.006), indicating that patients with higher leukocytosis were more likely to have thrombocytosis. Spleen size (when documented) showed a moderate positive correlation with WBC count (r = 0.34, p<0.001), consistent with the known relationship between tumor burden and splenomegaly in CML.

3.3. Molecular Diagnosis

All 175 patients included in the study were suspected of having CML based on clinical and morphological grounds and underwent RT-PCR for BCR-ABL1. The fusion transcript was successfully detected in 165 patients, yielding a detection rate of 94.3% (95% CI: 89.8-97.1%) in this clinically suspected cohort. The 10 patients who were negative for BCR-ABL1 would be classified as having atypical CML or another MPN/MDS overlap syndrome.

Among the 165 BCR-ABL1-positive patients, transcript type was successfully determined in all cases. The distribution of transcript types is presented in Table 4.

Table 4: BCR-ABL1 Transcript Types in CML Patients (n=165)

Transcript Type	n	%	95% CI	Notes
e14a2 (b3a2)	106	64.2	56.4-71.5	Major transcript
e13a2 (b2a2)	56	33.9	26.8-41.7	Major transcript
Both e13a2 & e14a2	3	1.8	0.4-5.2	Co-expression
Not tested	10	-	-	BCR-ABL1 negative
Total tested	165	100.0

Note: Transcript types were determined by RT-PCR in BCR-ABL1-positive patients. The e14a2 transcript was more common than e13a2, consistent with global data [16, 17].

This study provides the largest and most detailed report on the characteristics of CML in Yemen to date, offering crucial insights from a resource-limited setting. Our findings reveal a distinct epidemiological and clinical profile compared to data from Western countries.

The most striking finding is the median age at diagnosis of 43.4 years. This is approximately two decades younger than the median age of 64-66 years reported in the United States and Europe [5, 6]. Our results are, however, consistent with observations from other developing countries, such as India (median age ~35 years) and Pakistan [7, 11]. This significant age difference suggests the influence of genetic, environmental, or socioeconomic factors that may lead to earlier disease onset in our population. The younger age at diagnosis has profound implications for long-term management, productivity loss, and healthcare resource allocation in Yemen. Table 3 and Figure 3 provide a comparative overview.

Table 3: Comparison of Median Age at CML Diagnosis

Study (Region)	Median Age (years)
Current study (Yemen)	43.4
Lokesh et al. (India) [8]	35
Kalmanti et al. (Europe) [12]	54
Jabbour et al. (USA) [1]	64
SEER Registry (USA) [6]	66

The clinical presentation in our cohort was characterized by advanced disease features, with marked leukocytosis (mean 129.8 ×10⁹/L), high prevalence of anemia (77.1%), and splenomegaly (90.3%). These findings suggest that patients in Yemen often present late in the disease course, likely due to a combination of low public awareness, limited access to primary healthcare, and socioeconomic barriers. Despite this, it is noteworthy that all patients were diagnosed in the chronic phase, which is a testament to the diagnostic capability of the tertiary center and offers a crucial window for effective therapeutic intervention.

The successful implementation of RT-PCR for BCR-ABL1 detection, with a high confirmation rate of 94.3%, underscores the feasibility and critical importance of molecular diagnostics even in resource-constrained environments. This molecular confirmation is the cornerstone of modern CML management, as it confirms eligibility for targeted therapy with tyrosine kinase inhibitors (TKIs) [1, 9]. The 5.7% of patients who were BCR-ABL1-negative despite a CML-like morphology highlight the importance of molecular testing to differentiate classic CML from other Ph-negative myeloproliferative or myelodysplastic neoplasms, which have different prognoses and treatment pathways.

The distribution of BCR-ABL1 transcript types in our cohort (64.2% e14a2, 33.9% e13a2) aligns with global data, where e14a2 is typically more common [16, 17]. Recent evidence suggests that transcript type may have prognostic implications, with some studies reporting faster molecular responses in e14a2-positive patients [17]. However, the clinical significance of transcript type remains debated, and current treatment guidelines do not recommend different management strategies based on transcript variants [18]. The low rate of co-expression of both transcripts (1.8%) in our cohort is consistent with published literature, which reports co-expression in 1-5% of CML cases [16].

While treatment outcome data were not available for this retrospective analysis, the successful implementation of molecular diagnostics in our center provides a foundation for future prospective studies. The International CML Foundation has emphasized the importance of establishing diagnostic infrastructure in resource-limited countries as a prerequisite for improving treatment outcomes [20]. Our experience demonstrates that high-quality molecular testing is feasible even in challenging settings, which is crucial given that BCR-ABL1 monitoring is essential for assessing treatment response and detecting resistance [18].

This study has several limitations. Its retrospective nature may have resulted in missing data. As a single-center study, it may not be representative of the entire country, although the hospital is a major national referral center. Furthermore, quantitative PCR for monitoring treatment response and sequencing for TKI resistance mutations were not available, representing a key area for future development.

This study provides the most comprehensive characterization of CML in Yemen to date, demonstrating that the disease presents at a significantly younger age (median 43.4 years) compared to Western populations, with advanced hematological features at diagnosis. The successful implementation of BCR-ABL1 molecular testing, achieving a 94.3% detection rate, underscores the feasibility and critical importance of molecular diagnostics in resource-constrained settings. The distribution of BCR-ABL1 transcript types in our cohort aligns with global patterns, suggesting biological similarities despite epidemiological differences.

These findings have important implications for public health policy and clinical practice in Yemen and similar resource-limited countries. First, the younger age at diagnosis necessitates increased awareness among healthcare providers and the general population to facilitate earlier detection. Second, the high prevalence of advanced disease features at presentation highlights the urgent need for improved access to primary healthcare and diagnostic services. Third, the successful molecular diagnostic program demonstrated here provides a model for other centers in the region.

Future prospective studies should focus on treatment outcomes, long-term survival, and the impact of tyrosine kinase inhibitor therapy in this population. Additionally, research into the genetic and environmental factors contributing to earlier disease onset in Middle Eastern populations is warranted. These data provide a vital baseline for guiding health policy, improving patient management, and designing future clinical research for CML in Yemen and similar resource-limited settings in the region.

6. ACKNOWLEDGMENTS

The authors thank the laboratory staff at Al-Thawra Modern General Hospital for their technical assistance and the patients who participated in this study. We acknowledge the support of the Department of Hematology and the administration of Al-Thawra Modern General Hospital.

7. FUNDING

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

8. CONFLICT OF INTEREST

The authors declare no conflicts of interest.

9. DATA AVAILABILITY

The empirical data used to support the study’s results can be obtained upon request from the corresponding author.

10. AUTHOR’S CONTRIBUTIONS

M.A.A: Master’s student: writing the original draft, methodology, investigation, Formal analysis, data processing, and review of the final draft of the thesis and article. A.Q.S and M.A.H: design and supervision of clinical work.

Jabbour E, Kantarjian H, Cortes J (2024) Chronic myeloid leukemia 2025 update on diagnosis, therapy, and monitoring. Am J Hematol 99(1):141–170. https://doi.org/10.1002/ajh.27443
Lin Y, Li Y, Xu Y, Zhang Y, Chen Y (2020) Global Burden of Chronic Myeloid Leukemia: Estimates from the Global Burden of Disease Study 2019. Front Oncol 10:580759. https://doi.org/10.3389/fonc.2020.580759
Rowley JD (1973) A new consistent chromosomal abnormality in chronic myelogenous leukaemia identified by quinacrine fluorescence and Giemsa staining. Nature 243(5405):290–293. https://doi.org/10.1038/243290a0
Ren R (2005) Mechanisms of BCR-ABL in the pathogenesis of chronic myelogenous leukaemia. Nat Rev Cancer 5(3):172–183. https://doi.org/10.1038/nrc1567
Höglund M, Sandin F, Simonsson B (2015) Epidemiology of chronic myeloid leukaemia: an update. Ann Hematol 94(Suppl 2):S241–S247. https://doi.org/10.1007/s00277-015-2314-2
SEER Cancer Statistics Review 1975–2018. National Cancer Institute. Bethesda, MD. https://seer.cancer.gov/csr/1975_2018/
Ganesan P, Sagar TG, Dubashi B, Rajendranath R, Kannan K, Cyriac S, Nair S (2013) Chronic myeloid leukemia: experience from a tertiary care center in South India. Indian J Med Pediatr Oncol 34(4):292–297. https://doi.org/10.4103/0971-5851.125248
Lokesh KN, Sathyanarayanan V, Lakshmaiah KC, Sinha M, Rajeev LK, Lokanatha D, Babu G (2013) Clinical profile and outcome of chronic myeloid leukemia: a retrospective study from a regional cancer center in Southern India. Indian J Med Pediatr Oncol 34(4):301–305. https://doi.org/10.4103/0971-5851.125250
Hochhaus A, Baccarani M, Silver RT, Schiffer C, Apperley JF, Cervantes F, Hehlmann R (2020) European LeukemiaNet 2020 recommendations for treating chronic myeloid leukemia. Leukemia 34(4):966–984. https://doi.org/10.1038/s41375-020-0776-2
Jameel AY, Al-Kahiry W, Al-Haddad SA, Khanabsawy WA (2005) Pattern of adult leukemia in Yemen. Saudi Med J 26(4):582–585 PMID: 15900366
Bawazir WM, Al-Zadjali S, Kamble P, Jaju S, Farhan H, Aljabri M (2015) Epidemiology of chronic myeloid leukemia in Oman: a single institution study. Oman Med J 30(3):213–217. https://doi.org/10.5001/omj.2015.43
Kalmanti L, Saussele S, Lauseker M, Müller MC, Dietz CT, Heinrich L, Hochhaus A (2015) Safety and efficacy of imatinib in CML over a period of 10 years: data from the randomized CML-study IV. Leukemia 29(5):1123–1132. https://doi.org/10.1038/leu.2015.36
Cortes JE, Gambacorti-Passerini C, Deininger MW, Mauro MJ, Chuah C, Kim DW, Hochhaus A (2018) Bosutinib versus imatinib for newly diagnosed chronic myeloid leukemia: results from the randomized BFORE trial. J Clin Oncol 36(3):231–237. https://doi.org/10.1200/JCO.2017.74.7162
Kantarjian H, Shah NP, Hochhaus A, Cortes J, Shah S, Ayala M, Baccarani M (2010) Dasatinib versus imatinib in newly diagnosed chronic-phase chronic myeloid leukemia. N Engl J Med 362(24):2260–2270. https://doi.org/10.1056/NEJMoa1002315
Baccarani M, Deininger MW, Rosti G, Hochhaus A, Soverini S, Apperley JF, Hehlmann R (2013) European LeukemiaNet recommendations for the management of chronic myeloid leukemia: 2013. Blood 122(6):872–884. https://doi.org/10.1182/blood-2013-05-501569
Zenebe B, Nigussie H, Belay G, Seboka N (2023) A review on characterization of BCR–ABL transcript variants for molecular monitoring of chronic myeloid leukemia phenotypes. Hematology 28(1):2284038. https://doi.org/10.1080/16078454.2023.2284038
Wang H, Han C, Gong B, Liu Y, Liu K, Gu R, Huang X (2025) Clinical features and treatment response to TKIs in chronic myeloid leukemia patients with atypical BCR::ABL1 transcripts. Leuk Res 150:107631. https://doi.org/10.1016/j.leukres.2025.107631
Kantarjian H, Cortes J, Jabbour E (2025) Management of Chronic Myeloid Leukemia in 2025. Blood Rev 69:101264. https://doi.org/10.1016/j.blre.2024.101264
Abdulla MAJ, Yassin MA, Ibrahim F (2024) Chronic Myeloid Leukemia in Adolescents and Young Adults: A Middle Eastern Perspective. Clin Lymphoma Myeloma Leuk 24(8):e345–e353. https://doi.org/10.1016/j.clml.2024.05.012
Moulik NR, Patel A, Menon H (2024) Chronic Myeloid Leukemia: Cases of Patients Treated in Countries With Limited Resources. Advances in Hematology, 2024, 5534445. https://doi.org/10.1155/2024/5534445

The authors declare no competing interests.

Chronic Myeloid Leukemia in Yemen: Clinical, Hematological, and Molecular Characteristics at Diagnosi

Status:

Version 1

Abstract

Background

Methods

Results

Conclusion

Figures

1. INTRODUCTION

2. MATERIALS AND METHODS

2.1. Study Design and Population

2.1.1. Ethical Considerations

2.2. Data Collection

2.3. Laboratory Methods

2.4. Statistical Analysis

3. RESULTS

3.1. Demographic Characteristics

3.2. Hematological and Clinical Findings

3.2.1. Correlation Between Age and Hematological Parameters

3.3. Molecular Diagnosis

4. DISCUSSION

5. CONCLUSION

Declarations

References

Additional Declarations

Status:

Version 1