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

Chronic Myeloid Leukemia in Yemen: Clinical, Hematological, and Molecular Characteristics at Diagnosi | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Chronic Myeloid Leukemia in Yemen: Clinical, Hematological, and Molecular Characteristics at Diagnosi Mohammed Abdullah Al-Qadhi, Ahmed Qaid Salem, Mohammed Ahmed Hajar This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7941464/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract 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 Figures Figure 1 Figure 2 Figure 3 1. INTRODUCTION 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. MATERIALS AND METHODS 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. RESULTS 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) 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]. 4. DISCUSSION 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. 5. CONCLUSION 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. Declarations 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. 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07:50:10","extension":"png","order_by":21,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":84095,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7941464/v1/01ff2e9407ec651ea645639d.png"},{"id":94632243,"identity":"e4052e9c-68e3-4e2a-a9f3-ca963e6d8a44","added_by":"auto","created_at":"2025-10-29 06:28:37","extension":"xml","order_by":22,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":78223,"visible":true,"origin":"","legend":"","description":"","filename":"rs79414640structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7941464/v1/d1d3b946e1b478396c0cefe0.xml"},{"id":94632244,"identity":"c7b4116f-a2ce-40f5-a93f-37d8d634a07d","added_by":"auto","created_at":"2025-10-29 06:28:37","extension":"html","order_by":23,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":91220,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7941464/v1/87e0fe5bb28e7db337e2a6f0.html"},{"id":94632231,"identity":"ffd874d6-575d-4f3f-af9c-32ba206119ec","added_by":"auto","created_at":"2025-10-29 06:28:37","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":186661,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Age distribution showing a peak in the 45-65 year age group. (B) Gender distribution showing a male predominance (M:F ratio 1.4:1).\u003c/p\u003e","description":"","filename":"figure1agegenderdistribution1.png","url":"https://assets-eu.researchsquare.com/files/rs-7941464/v1/89a6eb044977335e89c75bff.png"},{"id":94632233,"identity":"4897eaa5-d64a-4600-898e-5c98fdfdd06a","added_by":"auto","created_at":"2025-10-29 06:28:37","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":372200,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of key hematological parameters. (A) WBC count, (B) Hemoglobin status, (C) Platelet count, and (D) Key peripheral blood film findings.\u003c/p\u003e","description":"","filename":"figure2hematologicalparameters1.png","url":"https://assets-eu.researchsquare.com/files/rs-7941464/v1/33311795ce061d39fb3429a8.png"},{"id":94640942,"identity":"6ee2e350-ee71-4b21-b655-0741305000b9","added_by":"auto","created_at":"2025-10-29 07:50:24","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":162892,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of median age at CML diagnosis in the current Yemeni cohort versus international data, highlighting the significantly younger age of onset in Yemen.\u003c/p\u003e","description":"","filename":"figure3geographicdistribution.png","url":"https://assets-eu.researchsquare.com/files/rs-7941464/v1/8984185f18ad5ccc42ecf50e.png"},{"id":94641145,"identity":"4794fe22-f347-44e7-b910-fcc49e59ed4a","added_by":"auto","created_at":"2025-10-29 07:51:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1356178,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7941464/v1/5b490002-43de-4e41-b6cd-bfce87c33eba.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eChronic Myeloid Leukemia in Yemen: Clinical, Hematological, and Molecular Characteristics at Diagnosi\u003c/p\u003e","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003eChronic 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\u0026ndash;2 cases per 100,000 people [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. 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 [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. This translocation creates the BCR-ABL1 fusion gene, which encodes a constitutively active tyrosine kinase that drives leukemogenesis [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe epidemiology of CML shows significant geographic and demographic variation. In Western countries, the median age at diagnosis is between 64 and 66 years [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. However, studies from developing nations, such as India, report a much younger median age of 35\u0026ndash;40 years [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. A consistent male predominance is observed globally, with a male-to-female ratio ranging from 1.2:1 to 1.7:1 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDiagnosis 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 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. 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) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eWhile 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 [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. 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\u0026rsquo;a, Yemen.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"2. MATERIALS AND METHODS","content":"\u003ch3\u003e2.1. Study Design and Population\u003c/h3\u003e\n\u003cp\u003eA 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.\u003c/p\u003e\n\u003ch4\u003e2.1.1. Ethical Considerations\u003c/h4\u003e\n\u003cp\u003e\u003cstrong\u003eList of Abbreviations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCML: Chronic Myeloid Leukemia\u003c/p\u003e\n\u003cp\u003eMPN: Myeloproliferative Neoplasm\u003c/p\u003e\n\u003cp\u003ePh: Philadelphia\u003c/p\u003e\n\u003cp\u003eBCR-ABL1: Breakpoint Cluster Region-Abelson\u003c/p\u003e\n\u003cp\u003eTKI: Tyrosine Kinase Inhibitor\u003c/p\u003e\n\u003cp\u003eRT-PCR: Reverse Transcription Polymerase Chain Reaction\u003c/p\u003e\n\u003cp\u003eWBC: White Blood Cell\u003c/p\u003e\n\u003cp\u003eHb: Hemoglobin\u003c/p\u003e\n\u003cp\u003eCP: Chronic Phase\u003c/p\u003e\n\u003cp\u003eAP: Accelerated Phase\u003c/p\u003e\n\u003cp\u003eBP: Blast Phase\u003c/p\u003e\n\u003cp\u003ePBF: Peripheral Blood Film\u003c/p\u003e\n\u003cp\u003eCI: Confidence Interval\u003c/p\u003e\n\u003cp\u003eSD: Standard Deviation\u003c/p\u003e\n\u003cp\u003eThis 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.\u003c/p\u003e\n\u003ch3\u003e2.2. Data Collection\u003c/h3\u003e\n\u003cp\u003eData 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.\u003c/p\u003e\n\u003ch3\u003e2.3. Laboratory Methods\u003c/h3\u003e\n\u003cp\u003eComplete 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.\u003c/p\u003e\n\u003ch3\u003e2.4. Statistical Analysis\u003c/h3\u003e\n\u003cp\u003eData 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 \u0026lt;5) was applied. Pearson correlation coefficients were calculated to assess relationships between continuous variables. A two-tailed p-value of \u0026lt;0.05 was considered statistically significant. 95% confidence intervals (CI) were calculated for all proportions using the Wilson score method.\u003c/p\u003e"},{"header":"3. RESULTS","content":"\u003ch3\u003e3.1. Demographic Characteristics\u003c/h3\u003e\n\u003cp\u003eA 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\u0026rsquo;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.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1: Demographic and Clinical Characteristics of CML Patients (n=175)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"0%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge Group (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.4-4.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15-29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9.9-21.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30-44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e29.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e23.0-37.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e45-65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e49.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e41.5-56.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026gt;65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.0-8.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e58.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e50.7-65.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e41.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34.4-49.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGeographic Residence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAmran\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e19.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13.9-26.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDamar\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e18.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12.9-24.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIbb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e18.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12.9-24.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTaiz\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e17.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11.9-23.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHajah\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9.4-20.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSana\u0026rsquo;a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.8-13.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.4-9.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch3\u003e3.2. Hematological and Clinical Findings\u003c/h3\u003e\n\u003cp\u003eAt diagnosis, the mean white blood cell (WBC) count was markedly elevated at 129.8 \u0026plusmn; 88.1 \u0026times;10⁹/L. Anemia was a common finding, with a mean hemoglobin (Hb) level of 9.8 \u0026plusmn; 2.4 g/dL; 77.1% of patients were anemic. The mean platelet count was 414.0 \u0026plusmn; 368.7 \u0026times;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.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2: Hematological Parameters at Diagnosis in CML Patients (n=175)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"0%\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eParameter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eMedian (Range)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAbnormal (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHemoglobin (g/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9.8 \u0026plusmn; 2.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9.5 (5.5-21.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e77.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eWBC count (\u0026times;10⁹/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e129.8 \u0026plusmn; 88.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e98.0 (1.7-375.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e98.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePlatelet count (\u0026times;10⁹/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e414.0 \u0026plusmn; 368.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e320.0 (19-2100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e61.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eBasophils (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.0 \u0026plusmn; 0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.0 (0-4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e94.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch4\u003e3.2.1. Correlation Between Age and Hematological Parameters\u003c/h4\u003e\n\u003cp\u003eCorrelation 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\u0026lt;0.001), consistent with the known relationship between tumor burden and splenomegaly in CML.\u003c/p\u003e\n\u003ch3\u003e3.3. Molecular Diagnosis\u003c/h3\u003e\n\u003cp\u003eAll 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.\u003c/p\u003e\n\u003cp\u003eAmong the 165 BCR-ABL1-positive patients, transcript type was successfully determined in all cases. The distribution of transcript types is presented in Table 4.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4: BCR-ABL1 Transcript Types in CML Patients (n=165)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"0%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eTranscript Type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eNotes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ee14a2 (b3a2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e64.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e56.4-71.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMajor transcript\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ee13a2 (b2a2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e33.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e26.8-41.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMajor transcript\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eBoth e13a2 \u0026amp; e14a2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.4-5.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCo-expression\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNot tested\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eBCR-ABL1 negative\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal tested\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e165\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e100.0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eNote: 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].\u003c/em\u003e\u003c/p\u003e"},{"header":"4. DISCUSSION","content":"\u003cp\u003eThis 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.\u003c/p\u003e\n\u003cp\u003eThe 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.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3: Comparison of Median Age at CML Diagnosis\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"0%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eStudy (Region)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eMedian Age (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCurrent study (Yemen)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e43.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLokesh et al.\u0026nbsp;(India) [8]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eKalmanti et al.\u0026nbsp;(Europe) [12]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eJabbour et al.\u0026nbsp;(USA) [1]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSEER Registry (USA) [6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe clinical presentation in our cohort was characterized by advanced disease features, with marked leukocytosis (mean 129.8 \u0026times;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.\u003c/p\u003e\n\u003cp\u003eThe 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.\u003c/p\u003e\n\u003cp\u003eThe 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].\u003c/p\u003e\n\u003cp\u003eWhile 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].\u003c/p\u003e\n\u003cp\u003eThis 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.\u003c/p\u003e"},{"header":"5. CONCLUSION","content":"\u003cp\u003eThis 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.\u003c/p\u003e\n\u003cp\u003eThese 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.\u003c/p\u003e\n\u003cp\u003eFuture 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.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e6. ACKNOWLEDGMENTS\u003c/p\u003e\n\u003cp\u003eThe 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.\u003c/p\u003e\n\u003cp\u003e7. FUNDING\u003c/p\u003e\n\u003cp\u003eThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e8. CONFLICT OF INTEREST\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e9. DATA AVAILABILITY\u003c/p\u003e\n\u003cp\u003eThe empirical data used to support the study\u0026rsquo;s results can be obtained upon request from the corresponding author.\u003c/p\u003e\n\u003cp\u003e10. AUTHOR\u0026rsquo;S CONTRIBUTIONS\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eM.A.A:\u0026nbsp;\u003c/strong\u003eMaster\u0026rsquo;s student: writing the original draft, methodology, investigation, Formal analysis, data processing, and review of the final draft of the thesis and article.\u003cstrong\u003e\u0026nbsp;A.Q.S and M.A.H:\u0026nbsp;\u003c/strong\u003edesign and supervision of clinical work.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eJabbour E, Kantarjian H, Cortes J (2024) Chronic myeloid leukemia 2025 update on diagnosis, therapy, and monitoring. 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Clin Lymphoma Myeloma Leuk 24(8):e345\u0026ndash;e353. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.clml.2024.05.012\u003c/span\u003e\u003cspan address=\"10.1016/j.clml.2024.05.012\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMoulik NR, Patel A, Menon H (2024) Chronic Myeloid Leukemia: Cases of Patients Treated in Countries With Limited Resources. \u003cem\u003eAdvances in Hematology\u003c/em\u003e, 2024, 5534445. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1155/2024/5534445\u003c/span\u003e\u003cspan address=\"10.1155/2024/5534445\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Chronic Myeloid Leukemia, CML, Yemen, BCR-ABL1, Epidemiology, Hematology","lastPublishedDoi":"10.21203/rs.3.rs-7941464/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7941464/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eChronic 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.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eA retrospective study of 175 CML patients diagnosed between August 2015 and August 2022 at Al-Thawra Modern General Hospital, Sana\u0026rsquo;a. Data included demographic, clinical, and laboratory parameters. Diagnosis was confirmed by RT-PCR for BCR-ABL1.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eMedian age at diagnosis was 43.4 years, significantly younger than Western populations. Male predominance was observed (58.3%, M:F\u0026thinsp;=\u0026thinsp;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%.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eCML 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.\u003c/p\u003e","manuscriptTitle":"Chronic Myeloid Leukemia in Yemen: Clinical, Hematological, and Molecular Characteristics at Diagnosi","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-29 06:28:32","doi":"10.21203/rs.3.rs-7941464/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7b8853b4-d3fb-49b9-b0f3-a21a8c0d273f","owner":[],"postedDate":"October 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":56839975,"name":"Hematology"},{"id":56839976,"name":"Oncology"},{"id":56839977,"name":"Internal Medicine"}],"tags":[],"updatedAt":"2025-10-29T06:28:32+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-29 06:28:32","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7941464","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7941464","identity":"rs-7941464","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}