Integrated Multimodal Diagnostic Validation in Hematological Disorders: First Prospective Study from a Conflict-Affected, Resource-Limited Setting in Yemen

Integrated Multimodal Diagnostic Validation in Hematological Disorders: First Prospective Study from a Conflict-Affected, Resource-Limited Setting in Yemen | 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 Integrated Multimodal Diagnostic Validation in Hematological Disorders: First Prospective Study from a Conflict-Affected, Resource-Limited Setting in Yemen Mohammed A Alqadhi, Ahmed K Salem, Mohammed A Hajar This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8168085/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 and objectives: Hematological disorders pose significant diagnostic challenges, particularly in conflict-affected, resource-limited regions like Yemen, leading to delays, misdiagnoses, and suboptimal patient care. This study aimed to prospectively validate an integrated multimodal diagnostic approach for hematological disorders in Yemen, assessing its diagnostic accuracy, clinical utility, prognostic value, and cost-effectiveness compared to conventional morphology-based diagnosis. Methods A prospective study enrolled 420 patients with suspected hematological disorders. A comprehensive algorithm, integrating peripheral blood film morphology, flow cytometry, molecular genetics, bone marrow trephine biopsy with immunohistochemistry, and targeted ancillary tests, was employed. The final integrated diagnosis, established by a multidisciplinary team, served as the gold standard. Diagnostic accuracy, agreement, malignancy prediction, survival analysis, and cost-effectiveness were assessed. Results The cohort showed a diverse spectrum, predominantly malignancies. PBF achieved 87.5% overall accuracy but had low sensitivity (41.5%) for lymphoma infiltration, highlighting its limitations. The integrated approach achieved 96.8% combined diagnostic accuracy. Flow cytometry was crucial for acute leukemias, chronic lymphocytic leukemia, and lymphomas. Molecular testing confirmed BCR-ABL1 in 94% of CML and JAK2 V617F in 89% of BCR-ABL1-negative myeloproliferative neoplasms. Bone marrow trephine biopsy combined with IHC provided 100% definitive diagnosis for lymphoma. Prognostic factors included age > 40 years, hemoglobin 50,000/µL, platelet 60 years, high WBC (> 100,000/µL), low hemoglobin ( 50%, and delayed diagnosis. The complete integrated panel ( $ 245/patient) demonstrated superior diagnostic accuracy and improved Quality-Adjusted Life Years, showing a favorable economic profile. Conclusion This pioneering study in a conflict-affected, resource-limited setting establishes that an integrated multimodal diagnostic approach substantially improves diagnosis of hematological disorders, overcoming morphology-based limitations. These findings emphasize the critical need for implementing comprehensive diagnostic capabilities to optimize patient outcomes and inform public health strategies. Hematology Molecular Genetics Internal Medicine hematological disorders multimodal diagnostics resource-limited settings yemen cost-effectiveness Introduction Accurate, timely diagnosis of hematological disorders is critical for effective patient management. While traditional morphological assessment is foundational, modern hematology increasingly relies on advanced diagnostics like flow cytometry, molecular genetics, and immunohistochemistry for precise classification [1]. However, in resource-limited settings, particularly those affected by conflict, access to advanced diagnostic modalities is severely constrained [2]. This often leads to diagnostic delays, misdiagnoses, and suboptimal patient outcomes. Yemen, experiencing protracted conflict, exemplifies these challenges; its healthcare infrastructure, supply chains, and skilled personnel are severely impacted, hindering advanced diagnostic services [3–5]. Reports from Yemen highlight the lack of flow cytometry, cytogenetic, and molecular analysis, often forcing expensive outsourcing of samples [6]. This situation creates significant barriers to quality healthcare, underscoring the urgent need for validated, sustainable diagnostic solutions. This study presents the first prospective validation of an integrated multimodal diagnostic algorithm for hematological disorders in this specific context. Our aim was to comprehensively evaluate the diagnostic accuracy, clinical utility, prognostic implications, and cost-effectiveness of combining PBF morphology with flow cytometry, molecular genetics, bone marrow trephine biopsy with immunohistochemistry, and targeted ancillary tests in Yemen. This research seeks to improve diagnostic standards and enhance patient care by establishing a robust diagnostic framework adapted to challenging conditions. The peripheral blood film remains an indispensable, inexpensive, and powerful initial diagnostic tool in hematology, often sufficient for initial diagnosis and guiding further investigations [7,8]. In resource-limited settings, PBF is frequently the primary method [9]. However, PBF has significant limitations. While acceptably accurate for conditions like Chronic Myeloid Leukemia and Chronic Lymphocytic Leukemia, it struggles with conditions requiring precise immunophenotypic or architectural assessment, such as lymphomas. Its interpretation is labor-intensive and susceptible to inter-observer variation, making it insufficient as a standalone comprehensive diagnostic tool [10]. Modern hematology relies on advanced techniques. Flow cytometry immunophenotyping is critical for lineage assignment and identifying aberrant cell populations, especially in acute leukemias and lymphomas, offering superior sensitivity and rapid turnaround [11]. The WHO classification integrates immunophenotyping and molecular features with morphology [1]. Molecular genetic analysis further refines diagnosis by detecting specific genetic aberrations relevant to various malignancies, including leukemias and myeloproliferative neoplasms, guiding targeted therapeutic strategies [12]. Immunohistochemistry on bone marrow trephine biopsies is crucial for definitive diagnosis and subtyping of infiltrating diseases, particularly lymphomas, when morphological findings are ambiguous [13,14]. Implementing these advanced tools in resource-limited settings faces formidable barriers, yet their utility in enhancing diagnostic accuracy for conditions like acute lymphoblastic leukemia is widely recognized [11,15]. Conflict-affected regions like Yemen face profound challenges in healthcare delivery and diagnostic capacity due to damaged infrastructure, fragmented supply chains, and a shortage of skilled personnel. The absence of facilities for flow cytometry, cytogenetic, and molecular analysis forces patients to bear the cost of sending samples abroad. The lack of robust cancer registries also impedes public health planning [16]. These issues highlight an urgent need for resilient diagnostic solutions within fragile health systems [4,17]. Prognostic factors are crucial for risk stratification and optimal treatment planning. Studies consistently identify age, blood counts, and disease subtype as key indicators influencing survival [18]. Understanding these factors in resource-limited contexts is vital, as delayed diagnosis significantly impacts survival. While advanced diagnostic tests have higher initial costs, their cost-effectiveness, in terms of improved accuracy and superior health outcomes, must be rigorously evaluated. Such investments can be highly cost-effective by reducing misdiagnosis, optimizing treatment, and improving Quality-Adjusted Life Years [19,20]. Methodology Study design and patient cohort This was a prospective study conducted on 420 consecutive patients referred with suspected hematological disorders between August 2024 and May 2025 at Al-Thawra Modern General Hospital in Sana'a, Yemen. Ethical approval was obtained from, and informed consent was secured from all participants or their legal guardians. Inclusion criteria comprised all patients presenting with clinical and/or preliminary laboratory findings suggestive of a hematological disorder requiring comprehensive evaluation. Exclusion criteria included patients unwilling or unable to provide consent, or those with incomplete diagnostic workups. Integrated diagnostic algorithm Each patient underwent a systematic, integrated diagnostic evaluation comprising: Peripheral blood film morphology: Initial assessment by experienced hematopathologists for cellular morphology, differential counts, and presence of abnormal cells. Bone marrow aspiration and trephine biopsy: Performed when indicated, followed by morphological examination of aspirate smears and histological assessment of trephine biopsies. Immunohistochemistry: Applied to bone marrow trephine biopsies using a panel of specific antibodies for precise lineage determination and subtyping of malignancies. Flow cytometry immunophenotyping: Performed on peripheral blood or bone marrow aspirates using a standardized panel of monoclonal antibodies for immunophenotypic characterization of suspected leukemias and lymphomas. Molecular genetic analysis: Targeted testing for specific mutations relevant to diagnosed or suspected conditions, such as BCR-ABL1 for Chronic Myeloid Leukemia and JAK2 V617F for Myeloproliferative Neoplasms. Targeted ancillary laboratory tests: Including, but not limited to, serum ferritin [21], vitamin B12, folate, protein electrophoresis, and beta-2 microglobulin, as clinically indicated for specific diagnoses like anemia subtyping [22] or monoclonal gammopathies [23]. These tests were selected based on initial clinical suspicion and peripheral blood film findings to further subtype anemias or evaluate for monoclonal gammopathies. The final diagnosis for each patient was established through a consensus review by a multidisciplinary team of hematologists and pathologists, integrating all available morphological, immunophenotypic, molecular, and clinical data, adhering to the latest WHO classification criteria. This integrated diagnosis served as the gold standard for evaluating the performance of individual and combined diagnostic modalities. Data collection and statistical analysis Demographic data, clinical presentations, laboratory parameters, and diagnostic findings were meticulously collected. Statistical analyses were performed using SPSS version 28.0 Diagnostic accuracy: Sensitivity, specificity, positive predictive value, negative predictive value, and overall accuracy were calculated for PBF, comparing its results against the final integrated diagnosis. Agreement analysis: Cohen's kappa coefficient was used to assess the level of agreement between PBF diagnosis and the final integrated diagnosis for various conditions. Prognostic factor identification: Multivariate logistic regression was employed to identify independent predictors of malignancy. A Cox proportional hazards model was utilized to determine factors independently associated with patient survival. Cost-effectiveness analysis: A comparative analysis was conducted to evaluate the cost per patient and cost per correct diagnosis for different diagnostic strategies. Quality-Adjusted Life Years were estimated, and the Incremental Cost-Effectiveness Ratio was calculated to assess the value for money of the integrated approach. Results Demographic and clinical characteristics of the study cohort A total of 420 patients were enrolled. The cohort displayed a slight male predominance and a wide age range, with 40.0% of patients aged 21-40 years. Details are provided in Table 1. Table 1: Demographic characteristics of study participants Characteristic Category Number (n) Percentage (%) 95% CI Gender Male 229 54.5 49.6-59.4 Female 191 45.5 40.6-50.4 Age Groups 0-20 years 85 20.2 16.5-24.3 21-40 years 168 40.0 35.2-44.9 41-60 years 126 30.0 25.6-34.7 61-80 years 35 8.3 5.9-11.4 >80 years 6 1.4 0.5-3.1 Age Statistics Mean ± SD 32.5 ± 18.7 years Median (IQR) 28 (18-45) years Total 420 100.0 Spectrum of hematological disorders The integrated multimodal approach confirmed a diverse spectrum of hematological conditions. Malignant disorders predominated, led by Chronic Myeloid and Lymphocytic Leukemias. Acute Myeloid and Lymphoblastic Leukemias were also common, alongside lymphoma infiltration (25 patients). Benign disorders included Erythroid Hyperplasia, Aplastic Anemia, Myelofibrosis, Myelodysplastic Syndrome, and Multiple Myeloma as shown in Table 2. Table 2: Distribution of hematological disorders Diagnosis Number (n) Percentage (%) 95% CI Classification Erythroid Hyperplasia 120 28.6 24.3-33.2 Benign Chronic Myeloid Leukemia (CML) 100 23.8 19.8-28.2 Malignant Chronic Lymphocytic Leukemia (CLL) 65 15.5 12.2-19.3 Malignant Acute Myeloid Leukemia (AML) 48 11.4 8.6-14.8 Malignant Acute Lymphoblastic Leukemia (ALL) 35 8.3 5.9-11.4 Malignant Lymphoma Infiltration 25 6.0 3.9-8.7 Malignant Aplastic Anemia 15 3.6 2.0-5.8 Benign Myelofibrosis 4 1.0 0.3-2.5 Malignant Myelodysplastic Syndrome 3 0.7 0.1-2.1 Malignant Multiple Myeloma 3 0.7 0.1-2.1 Malignant Leishmaniasis 2 0.5 0.1-1.7 Benign Total 420 100.0 Baseline diagnostic performance of peripheral blood film PBF's low sensitivity for lymphoma suggests over half of cases could be missed, leading to delays/misdiagnoses. High specificity generally indicates correct PBF-indicated diagnoses. High NPVs for CML/CLL denote reliability, but lymphoma's lower NPV risks false negatives from PBF alone. Cohen's kappa showed excellent overall agreement (0.82), with near-perfect for CML, excellent for CLL/Erythroid Hyperplasia, but only moderate for lymphoma, reinforcing PBF limitations, Details are provided in Table 3 and Table 4. Table 3: Diagnostic accuracy parameters of peripheral blood film Condition Sensitivity (%) 95% CI Specificity (%) 95% CI PPV (%) NPV (%) Accuracy (%) CML 94.0 87.4-97.8 98.1 96.1-99.2 96.9 96.3 96.8 CLL 92.3 82.1-97.4 96.6 94.2-98.2 92.3 96.6 95.2 AML 83.3 69.8-92.5 86.2 82.4-89.4 76.9 90.4 85.2 ALL 80.0 63.1-91.6 84.4 80.4-87.8 68.6 90.8 82.8 Lymphoma 41.5 22.5-62.5 97.2 95.1-98.6 68.0 91.5 76.8 Erythroid Hyperplasia 90.8 84.3-95.2 94.3 91.2-96.6 89.3 95.2 92.5 Aplastic Anemia 86.7 59.5-98.3 90.1 86.9-92.7 65.0 97.3 89.5 Overall 84.2 80.1-87.8 96.8 94.2-98.5 91.3 94.7 87.5 Table 4: Agreement between peripheral blood film and final integrated diagnosis Condition Kappa Coefficient 95% CI Agreement Level p-value CML 0.94 0.89-0.99 Near-perfect <0.001 CLL 0.89 0.83-0.95 Excellent <0.001 Erythroid Hyperplasia 0.85 0.79-0.91 Excellent <0.001 Aplastic Anemia 0.75 0.62-0.88 Good <0.001 AML 0.70 0.61-0.79 Good <0.001 ALL 0.67 0.56-0.78 Good <0.001 Lymphoma 0.58 0.42-0.74 Moderate <0.001 Overall 0.82 0.77-0.87 Excellent <0.001 Incremental diagnostic value of the integrated multimodal approach Advanced ancillary tests significantly improved diagnostic value. Flow cytometry immunophenotyping Flow cytometry definitively diagnosed and classified 173 cases, including all 48 AML and 35 ALL by confirming lineage and providing immunophenotypic data for WHO sub classification. It confirmed clonality in all 65 CLL cases and was critical for initial characterization of 25 lymphoma cases, guiding subsequent IHC. Molecular genetic validation Molecular testing confirmed specific genetic aberrations. BCR-ABL1 fusion transcript was detected in 94% of CML cases. For BCR-ABL1-negative MPNs, JAK2 V617F was identified in 89% of cases (100% for Polycythemia Vera). The overall diagnostic yield of the molecular panel was 91.8%, as shown in Table 5 and Table 6. Table 5: BCR-ABL1 testing results in CML patients BCR-ABL1 Status Number (n) Percentage (%) 95% CI Test Performance Positive 94 94.0 87.4-97.8 Sensitivity: 94.0% Negative 6 6.0 2.2-12.6 Specificity: 100% Total CML Cases 100 100.0 Accuracy: 96.7% Non-CML Controls 320 - PPV: 100% False Positives 0 0.0 0.0-1.1 NPV: 89.3% Table 6: JAK2 V617F mutation analysis in myeloproliferative neoplasms MPN Subtype JAK2 Positive n(%) JAK2 Negative n(%) Total Mutation Rate (%) 95% CI p-value Primary Myelofibrosis 8 (89) 1 (11) 9 89.0 51.8-99.7 <0.001 Polycythemia Vera 5 (100) 0 (0) 5 100.0 47.8-100.0 <0.001 Essential Thrombocythemia 3 (75) 1 (25) 4 75.0 19.4-99.4 0.125 Total MPN Cases 16 (89) 2 (11) 18 89.0 65.3-98.6 <0.001 Bone marrow trephine biopsy and immunohistochemistry For the 25 lymphoma cases, where PBF sensitivity was low, trephine biopsy and IHC achieved a 100% definitive diagnosis and sub classification, crucial for targeted treatment. Laboratory parameters and hematological indices Baseline laboratory parameters showed significant abnormalities, including mean hemoglobin 8.4 ± 3.2 g/dL, elevated mean WBC 45.6 ± 67.8 × 10³/μL, and thrombocytopenia. Blast cells were detected in 43.6% of patients' peripheral blood, Details are provided in Table 7. Table 7: Baseline laboratory parameters of study cohort Parameter Normal Range Mean ± SD Median (IQR) Abnormal Cases n(%) 95% CI Hemoglobin (g/dL) 12-16 8.4 ± 3.2 7.8 (5.9-10.5) 356 (84.8) 81.2-87.9 WBC Count (×10³/μL) 4-11 45.6 ± 67.8 18.2 (6.8-52.4) 298 (71.0) 66.4-75.2 Platelet Count (×10³/μL) 150-450 156.7 ± 189.3 89.5 (34.2-198.7) 267 (63.6) 58.8-68.1 Blast Percentage (%) <5 23.8 ± 31.4 8.0 (2.0-35.0) 183 (43.6) 38.8-48.4 M:E Ratio 2:1-4:1 3.8 ± 4.2 2.1 (1.2-4.8) 198 (47.1) 42.3-52.0 Prognostic factors and survival analysis Multivariate logistic regression identified age >40 years, hemoglobin 50,000/μL, platelet 60 years, high WBC >100,000/μL, low hemoglobin 50%, and delayed diagnosis >30 days were independent predictors of poor survival, Details are provided in Table 8 and Table 9. Table 8: Multivariate logistic regression for malignancy prediction Predictor Variable β Coefficient SE Odds Ratio 95% CI Wald χ² p-value Age >40 years 0.851 0.245 2.34 1.45-3.78 12.05 <0.001 Male Gender 0.207 0.234 1.23 0.78-1.94 0.78 0.374 Hemoglobin <8 g/dL 1.138 0.257 3.12 1.89-5.15 19.67 50,000/μL 1.541 0.354 4.67 2.34-9.32 18.95 <0.001 Platelet <50,000/μL 1.062 0.284 2.89 1.67-5.01 13.98 <0.001 Splenomegaly Present 1.023 0.295 2.78 1.56-4.95 12.01 0.001 Lymphadenopathy 0.678 0.312 1.97 1.07-3.63 4.72 0.030 Table 9: Cox proportional hazards model for survival analysis Variable Hazard Ratio 95% CI SE Wald χ² p-value Age >60 years 2.45 1.34-4.48 0.309 8.67 0.003 High WBC (>100,000/μL) 3.21 1.78-5.79 0.302 15.23 <0.001 Low Hemoglobin (50% 4.12 2.23-7.61 0.314 21.34 30 days) 1.89 1.12-3.19 0.267 5.67 0.017 AML vs Other Diagnoses 2.34 1.28-4.28 0.305 7.89 0.005 Cost-effectiveness of diagnostic strategies Morphology-only diagnosis was least expensive but had limited accuracy. The complete integrated panel ($245 per patient) achieved the highest diagnostic accuracy. The Incremental Cost-Effectiveness Ratio indicated significant gains in diagnostic accuracy and Quality-Adjusted Life Years for the additional investment, demonstrating a favorable economic profile, Details are provided in Table 10. Table 10: Cost-effectiveness analysis of diagnostic strategies Diagnostic Strategy Cost per Patient (USD) Diagnostic Accuracy (%) Cost per Correct Diagnosis ICER QALYs Gained Morphology Only 45 72.3 62.2 Reference Reference Morphology + Flow Cytometry 125 84.7 147.5 285.7 0.15 Morphology + Molecular 180 89.2 201.8 423.1 0.22 Complete Panel 245 96.8 253.1 512.8 0.31 Discussion This pioneering prospective study in conflict-affected, resource-limited Yemen provides compelling evidence for the superior diagnostic accuracy and clinical utility of an integrated multimodal approach to hematological disorders. Our findings underscore that while conventional PBF is a valuable initial screening tool, its limitations, particularly for complex malignancies, necessitate advanced diagnostics for definitive classification. The observed 87.5% overall PBF accuracy aligns with its foundational role. However, PBF's reduced sensitivity for lymphoma infiltration and moderate agreement with the integrated diagnosis highlights that morphology alone is often insufficient for diseases requiring immunophenotypic or genetic features. PBF also has limitations in characterizing various anemias or precisely subtyping myelodysplastic syndromes, where cytogenetic or molecular studies are crucial [24,25]. The incremental diagnostic value of integrating flow cytometry, molecular genetics, and bone marrow trephine biopsy with immunohistochemistry was profound. Flow cytometry was instrumental for accurate immunophenotypic characterization and lineage assignment of acute leukemias and lymphomas [11]. Molecular genetic testing provided critical confirmation of specific genetic aberrations (e.g., BCR-ABL1 in CML, JAK2 V617F in MPNs), essential for guiding targeted therapies and prognostication [12]. For lymphoma, where PBF proved inadequate, trephine biopsy and IHC achieved 100% definitive diagnosis and subclassification [13,14]. These results underscore the necessity of establishing modern diagnostic laboratories and training personnel in resource-constrained environments. Our identification of significant prognostic factors, including age, specific hematological parameters, and clinical signs, offers critical insights into Yemen's disease landscape. Delayed diagnosis was an independent predictor of poor survival, as longer diagnostic intervals allow disease progression and narrow treatment windows [26–29]. These prognostic factors resonate with findings from studies in the Middle East and Africa [18]. Our findings contribute to the scarce literature on hematological disorders in Yemen. An older study by Al-Ghazaly et al. in Sana'a reported different prevalences of AML, ALL, CML, and CLL compared to our study, possibly reflecting shifting epidemiology or diagnostic capabilities [30]. More recently, Al-Nuzaili et al. in Sana'a described hematological malignancy prevalence [31]. A previous study by Saeed N. et al. in south-west Yemen reported various acute and chronic leukemias, MPN, MDS, multiple myeloma, and lymphoma [31]. Our study shows notably lower prevalence of AML and ALL, and higher CML and CLL compared to these reports. A study in Hadhramout highlighted chronic MPN followed by AML [32]. Our specific MPN prevalence rates and JAK2 V617F mutation rates are detailed in Table 6. These comparisons underscore regional variability and the dynamic nature of hematological disease patterns within Yemen. Our identification of Leishmaniasis (0.5%) is consistent with other studies [33]. The overall lack of comprehensive epidemiological reports across Yemen, as noted by Al-Nuzaili et al. [31] and Al-Ghazaly et al. [30], underscores our study's critical importance in providing contemporary data. Anemia challenges [34] and transfusion-transmitted infections [35] also remain public health problems. Furthermore, the cost-effectiveness analysis strongly justifies investing in an integrated multimodal diagnostic approach. While the complete panel has a higher initial cost, its substantial increase in diagnostic accuracy and resulting gains in Quality-Adjusted Life Years demonstrate a favorable economic profile. This is consistent with studies from other resource-limited environments, showing advanced diagnostics can be highly cost-effective by improving patient outcomes and reducing long-term healthcare burdens. This evidence supports strategic investment in comprehensive diagnostic capabilities. The unique contribution of this study lies in its prospective validation of these integrated diagnostics within a conflict-affected, resource-limited setting like Yemen. Challenges from ongoing conflict amplify the importance of developing resilient and effective diagnostic systems. Our results demonstrate that despite formidable obstacles, high diagnostic accuracy is achievable, offering a blueprint for other regions [11]. To ensure long-term sustainability, strategies must include continuous investment in local personnel training, resilient supply chains, and innovative approaches like tele-consultation models [36–38]. Strengths and limitations: Significant strengths include the prospective design and comprehensive evaluation of a large patient cohort, with a multidisciplinary team establishing the gold standard. A limitation is the single-center nature, potentially affecting generalizability. Future research should include multi-center studies and implementation science research. Conclusion This first prospective study from a conflict-affected, resource-limited setting in Yemen conclusively demonstrates that an integrated multimodal diagnostic approach significantly improves the accuracy and comprehensiveness of diagnosing hematological disorders. While PBF remains a valuable initial screening tool, its utility is considerably enhanced by sequential integration of flow cytometry, molecular genetic analysis, bone marrow trephine biopsy, and immunohistochemistry. These advanced techniques are indispensable for definitive classification, accurate prognostication, and guiding targeted therapies, leading to better patient outcomes. The study also provides strong evidence for the cost-effectiveness of this integrated approach, justifying the investment required to establish and sustain such capabilities in challenging environments. These findings provide a compelling economic argument for international and national health bodies to prioritize strategic investments in comprehensive diagnostic capabilities within fragile health systems. Our findings offer a validated framework and underscore the critical need for strengthening comprehensive hematological diagnostic services in Yemen and other similarly constrained regions globally, ultimately contributing to improved healthcare standards and patient survival. Declarations Additional information Data availability The data supporting the findings of this study are not openly available due to sensitivity reasons. However, they are available from the author upon reasonable request. All patient data were anonymized and stored securely using digital storage protocols to ensure the protection of patient confidentiality, particularly given the vulnerable population studied. Author contributions Concept and design: Mohammed A. Al-Qadhi, Ahmed K. Salem, Mohammed A. Hajar Acquisition, analysis, or interpretation of data: Mohammed A. Al-Qadhi, Ahmed K. Salem, Mohammed A. Hajar Drafting of the manuscript: Mohammed A. Al-Qadhi, Ahmed K. Salem, Mohammed A. Hajar Critical review of the manuscript for important intellectual content: Mohammed A. Al-Qadhi, Ahmed K. Salem, Mohammed A. Hajar Supervision: Mohammed A. Al-Qadhi, Ahmed K. Salem, Mohammed A. Hajar Disclosures Human subjects Informed consent for treatment and open access publication was obtained or waived by all participants in this study. The Institutional Review Board of Al-Thawra Modern General Hospital in Sana'a approved this study. Written informed consent was obtained from all adult participants and parents/guardian's of pediatric patients. All procedures were conducted in accordance with the ethical principles of the Declaration of Helsinki and local ethical guidelines. Animal subjects All authors have confirmed that this study did not involve animal subjects or tissue. Conflicts of interest In compliance with the International Committee of Medical Journal Editors uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work. References Pavithra P, Laxminarayana SLK, Manohar C, Belurkar S, Kairanna NV. Transition from morphologic diagnosis to immunophenotypic diagnosis of acute leukemia—experience of establishing a new flow cytometry laboratory. Journal of Hematopathology [Internet]. 2019 [cited 2025 Nov];12:191. 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Baishideng Publishing Group; 2009 [cited 2025 Oct]. p. 4627. Available from: https://doi.org/10.3748/wjg.15.4627 Abduh MS. An overview of multiple myeloma: A monoclonal plasma cell malignancy’s diagnosis, management, and treatment modalities. Saudi Journal of Biological Sciences [Internet]. 2023 [cited 2025 Oct];31:103920. Available from: https://doi.org/10.1016/j.sjbs.2023.103920 Beckman A, Ng V, Jaye DL, Gaddh M, Thomas S, Yohe S, et al. Clinician-ordered peripheral blood smears have low reimbursement and variable clinical value: a three-institution study, with suggestions for operational efficiency. Diagnostic Pathology [Internet]. 2020 [cited 2025 Aug];15. Available from: https://doi.org/10.1186/s13000-020-01033-8 Tria F, Ang D, Fan G. Myelodysplastic Syndrome: Diagnosis and Screening [Internet]. Diagnostics. Multidisciplinary Digital Publishing Institute; 2022 [cited 2025 Nov]. p. 1581. Available from: https://doi.org/10.3390/diagnostics12071581 Dapkevičiūtė A, Šapoka V, Martynova E, Pečeliūnas V. Time from Symptom Onset to Diagnosis and Treatment among Haematological Malignancies: Influencing Factors and Associated Negative Outcomes. Medicina [Internet]. 2019 [cited 2025 Aug];55:238. Available from: https://doi.org/10.3390/medicina55060238 Black G, Boswell L, Harris J, Whitaker KL. What causes delays in diagnosing blood cancers? A rapid review of the evidence [Internet]. Primary Health Care Research & Development. Cambridge University Press; 2023 [cited 2025 Oct]. Available from: https://doi.org/10.1017/s1463423623000129 Howell D, Smith A, Jack A, Patmore R, Macleod U, Mironska E, et al. Time-to-diagnosis and symptoms of myeloma, lymphomas and leukaemias: a report from the Haematological Malignancy Research Network. BMC Blood Disorders [Internet]. 2013 [cited 2025 Sep];13. Available from: https://doi.org/10.1186/2052-1839-13-9 López‐García YK, Valdez-Carrizales M, Nuñez-Zuno JA, Apodaca E, Rangel‐Patiño J, Demichelis‐Gómez R. Are delays in diagnosis and treatment of acute leukemia in a middle-income country associated with poor outcomes? A retrospective cohort study. Hematology Transfusion and Cell Therapy [Internet]. 2023 [cited 2025 Nov];46:366. Available from: https://doi.org/10.1016/j.htct.2023.05.010 Al-Ghazaly J, AL-SELWI AH, Abdullah M, AL-JAHAFI AK, Al-Dubai W, Al-Hashdi A. Pattern of haematological diseases diagnosed by bone marrow examination in Yemen: a developing country experience. Clinical & Laboratory Haematology [Internet]. 2006 [cited 2025 Nov];28:376. Available from: https://doi.org/10.1111/j.1365-2257.2006.00823.x Al-Nuzaili MA, Al-Khamesy KSA, Yahia OM. Acute myeloid leukemia among patients at the National Oncology Center in Sana ’ a, Yemen: prevalence, subtypes, and hematological features. Research Square (Research Square) [Internet]. 2022 [cited 2025 Aug]; Available from: https://doi.org/10.21203/rs.3.rs-2299384/v1 AM D, AA B, AA B, AA A-Z. Correlation Hematological Malignancies in the Hadhramout Sector Pattern and Distribution. Journal of Blood Disorders and Medicine [Internet]. 2023 [cited 2025 Nov];5. Available from: https://doi.org/10.16966/2471-5026.129 Al-Ghazaly J, Al-Dubai W, Abdullah M, Al-Gharasi L. HEMATOLOGICAL CHARACTERISTICS OF YEMENI ADULTS AND CHILDREN WITH VISCERAL LEISHMANIASIS. COULD EOSINOPENIA BE A SUSPICION INDEX? Mediterranean Journal of Hematology and Infectious Diseases [Internet]. 2017 [cited 2025 Nov];9:2017056. Available from: https://doi.org/10.4084/mjhid.2017.056 Al-Jermmy ASM, Idris SM, Coulibaly-Zerbo F, Nasreddine L, Al‐Jawaldeh A. Prevalence and Correlates of Anemia among Adolescents Living in Hodeida, Yemen. Children [Internet]. 2022 [cited 2025 Nov];9:977. Available from: https://doi.org/10.3390/children9070977 Alharazi T, Al-Zubiery T, Alcantara JC, Qanash H, Bazaid AS, Altayar MA, et al. Prevalence of Transfusion-Transmitted Infections (HCV, HIV, Syphilis and Malaria) in Blood Donors: A Large-Scale Cross-Sectional Study. Pathogens [Internet]. 2022 [cited 2025 Nov];11:726. Available from: https://doi.org/10.3390/pathogens11070726 Allen A, Allen S, Olivieri NF. Improving Laboratory and Clinical Hematology Services in Resource Limited Settings [Internet]. Hematology/Oncology Clinics of North America. Elsevier BV; 2016 [cited 2025 Nov]. p. 497. Available from: https://doi.org/10.1016/j.hoc.2015.11.012 Luethi U, Risch L, Korte W, Bader M, Huber AR. Telehematology: critical determinants for successful implementation. Blood [Internet]. 2003 [cited 2025 Jul];103:486. Available from: https://doi.org/10.1182/blood-2003-05-1615 Shah A, O’Dwyer L, Badawy SM. Telemedicine in Malignant and Nonmalignant Hematology: Systematic Review of Pediatric and Adult Studies [Internet]. JMIR mhealth and uhealth. JMIR Publications; 2021 [cited 2025 Aug]. Available from: https://doi.org/10.2196/29619 Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8168085","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":548380815,"identity":"8dd74be6-0ab2-4217-a774-96d2774b4dc8","order_by":0,"name":"Mohammed A 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08:19:55","extension":"html","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":144331,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8168085/v1/d0712e467655e260a4f4b7c1.html"},{"id":96912983,"identity":"315f68a3-a507-4355-ba99-d9084c9ce3fc","added_by":"auto","created_at":"2025-11-27 13:48:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1905986,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8168085/v1/a6c78416-bd21-4f1d-ad1b-af6e9f5eddc6.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eIntegrated Multimodal Diagnostic Validation in Hematological Disorders: First Prospective Study from a Conflict-Affected, Resource-Limited Setting in Yemen\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAccurate, timely diagnosis of hematological disorders is critical for effective patient management. While traditional morphological assessment is foundational, modern hematology increasingly relies on advanced diagnostics like flow cytometry, molecular genetics, and immunohistochemistry for precise classification [1].\u003c/p\u003e\n\u003cp\u003eHowever, in resource-limited settings, particularly those affected by conflict, access to advanced diagnostic modalities is severely constrained [2]. This often leads to diagnostic delays, misdiagnoses, and suboptimal patient outcomes. Yemen, experiencing protracted conflict, exemplifies these challenges; its healthcare infrastructure, supply chains, and skilled personnel are severely impacted, hindering advanced diagnostic services [3\u0026ndash;5]. Reports from Yemen highlight the lack of flow cytometry, cytogenetic, and molecular analysis, often forcing expensive outsourcing of samples [6]. This situation creates significant barriers to quality healthcare, underscoring the urgent need for validated, sustainable diagnostic solutions.\u003c/p\u003e\n\u003cp\u003eThis study presents the first prospective validation of an integrated multimodal diagnostic algorithm for hematological disorders in this specific context. Our aim was to comprehensively evaluate the diagnostic accuracy, clinical utility, prognostic implications, and cost-effectiveness of combining PBF morphology with flow cytometry, molecular genetics, bone marrow trephine biopsy with immunohistochemistry, and targeted ancillary tests in Yemen. This research seeks to improve diagnostic standards and enhance patient care by establishing a robust diagnostic framework adapted to challenging conditions.\u003c/p\u003e\n\u003cp\u003eThe peripheral blood film remains an indispensable, inexpensive, and powerful initial diagnostic tool in hematology, often sufficient for initial diagnosis and guiding further investigations [7,8]. In resource-limited settings, PBF is frequently the primary method [9]. However, PBF has significant limitations. While acceptably accurate for conditions like Chronic Myeloid Leukemia and Chronic Lymphocytic Leukemia, it struggles with conditions requiring precise immunophenotypic or architectural assessment, such as lymphomas. Its interpretation is labor-intensive and susceptible to inter-observer variation, making it insufficient as a standalone comprehensive diagnostic tool [10].\u003c/p\u003e\n\u003cp\u003eModern hematology relies on advanced techniques. Flow cytometry immunophenotyping is critical for lineage assignment and identifying aberrant cell populations, especially in acute leukemias and lymphomas, offering superior sensitivity and rapid turnaround [11]. The WHO classification integrates immunophenotyping and molecular features with morphology [1]. Molecular genetic analysis further refines diagnosis by detecting specific genetic aberrations relevant to various malignancies, including leukemias and myeloproliferative neoplasms, guiding targeted therapeutic strategies [12]. Immunohistochemistry on bone marrow trephine biopsies is crucial for definitive diagnosis and subtyping of infiltrating diseases, particularly lymphomas, when morphological findings are ambiguous [13,14]. Implementing these advanced tools in resource-limited settings faces formidable barriers, yet their utility in enhancing diagnostic accuracy for conditions like acute lymphoblastic leukemia is widely recognized [11,15].\u003c/p\u003e\n\u003cp\u003eConflict-affected regions like Yemen face profound challenges in healthcare delivery and diagnostic capacity due to damaged infrastructure, fragmented supply chains, and a shortage of skilled personnel. The absence of facilities for flow cytometry, cytogenetic, and molecular analysis forces patients to bear the cost of sending samples abroad. The lack of robust cancer registries also impedes public health planning [16]. These issues highlight an urgent need for resilient diagnostic solutions within fragile health systems [4,17].\u003c/p\u003e\n\u003cp\u003ePrognostic factors are crucial for risk stratification and optimal treatment planning. Studies consistently identify age, blood counts, and disease subtype as key indicators influencing survival [18]. Understanding these factors in resource-limited contexts is vital, as delayed diagnosis significantly impacts survival. While advanced diagnostic tests have higher initial costs, their cost-effectiveness, in terms of improved accuracy and superior health outcomes, must be rigorously evaluated. Such investments can be highly cost-effective by reducing misdiagnosis, optimizing treatment, and improving Quality-Adjusted Life Years [19,20].\u003c/p\u003e"},{"header":"Methodology","content":"\u003ch3\u003eStudy design and patient cohort\u003c/h3\u003e\n\u003cp\u003eThis was a prospective study conducted on 420 consecutive patients referred with suspected hematological disorders between August 2024 and May 2025 at Al-Thawra Modern General Hospital in Sana\u0026apos;a, Yemen. Ethical approval was obtained from, and informed consent was secured from all participants or their legal guardians. Inclusion criteria comprised all patients presenting with clinical and/or preliminary laboratory findings suggestive of a hematological disorder requiring comprehensive evaluation. Exclusion criteria included patients unwilling or unable to provide consent, or those with incomplete diagnostic workups.\u003c/p\u003e\n\u003ch3\u003eIntegrated diagnostic algorithm\u003c/h3\u003e\n\u003cp\u003eEach patient underwent a systematic, integrated diagnostic evaluation comprising:\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003e\u003cstrong\u003ePeripheral blood film morphology:\u003c/strong\u003e Initial assessment by experienced hematopathologists for cellular morphology, differential counts, and presence of abnormal cells.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eBone marrow aspiration and trephine biopsy:\u003c/strong\u003e Performed when indicated, followed by morphological examination of aspirate smears and histological assessment of trephine biopsies.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eImmunohistochemistry:\u003c/strong\u003e Applied to bone marrow trephine biopsies using a panel of specific antibodies for precise lineage determination and subtyping of malignancies.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eFlow cytometry immunophenotyping:\u003c/strong\u003e Performed on peripheral blood or bone marrow aspirates using a standardized panel of monoclonal antibodies for immunophenotypic characterization of suspected leukemias and lymphomas.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eMolecular genetic analysis:\u003c/strong\u003e Targeted testing for specific mutations relevant to diagnosed or suspected conditions, such as BCR-ABL1 for Chronic Myeloid Leukemia and JAK2 V617F for Myeloproliferative Neoplasms.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eTargeted ancillary laboratory tests:\u003c/strong\u003e Including, but not limited to, serum ferritin [21], vitamin B12, folate, protein electrophoresis, and beta-2 microglobulin, as clinically indicated for specific diagnoses like anemia subtyping [22] or monoclonal gammopathies [23]. These tests were selected based on initial clinical suspicion and peripheral blood film findings to further subtype anemias or evaluate for monoclonal gammopathies.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eThe final diagnosis for each patient was established through a consensus review by a multidisciplinary team of hematologists and pathologists, integrating all available morphological, immunophenotypic, molecular, and clinical data, adhering to the latest WHO classification criteria. This integrated diagnosis served as the gold standard for evaluating the performance of individual and combined diagnostic modalities.\u003c/p\u003e\n\u003ch3\u003eData collection and statistical analysis\u003c/h3\u003e\n\u003cp\u003eDemographic data, clinical presentations, laboratory parameters, and diagnostic findings were meticulously collected. Statistical analyses were performed using SPSS version 28.0\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003eDiagnostic accuracy:\u003c/strong\u003e Sensitivity, specificity, positive predictive value, negative predictive value, and overall accuracy were calculated for PBF, comparing its results against the final integrated diagnosis.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eAgreement analysis:\u003c/strong\u003e Cohen\u0026apos;s kappa coefficient was used to assess the level of agreement between PBF diagnosis and the final integrated diagnosis for various conditions.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003ePrognostic factor identification:\u003c/strong\u003e Multivariate logistic regression was employed to identify independent predictors of malignancy. A Cox proportional hazards model was utilized to determine factors independently associated with patient survival.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eCost-effectiveness analysis:\u003c/strong\u003e A comparative analysis was conducted to evaluate the cost per patient and cost per correct diagnosis for different diagnostic strategies. Quality-Adjusted Life Years were estimated, and the Incremental Cost-Effectiveness Ratio was calculated to assess the value for money of the integrated approach.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Results","content":"\u003ch3\u003eDemographic and clinical characteristics of the study cohort\u003c/h3\u003e\n\u003cp\u003eA total of 420 patients were enrolled. The cohort displayed a slight male predominance and a wide age range, with 40.0% of patients aged 21-40 years. Details are provided in Table 1.\u003c/p\u003e\n\u003cp\u003eTable 1: Demographic characteristics of study participants\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber (n)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercentage (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e229\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e54.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e49.6-59.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e191\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e45.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e40.6-50.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge Groups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e0-20 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e20.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e16.5-24.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e21-40 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e40.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e35.2-44.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e41-60 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e30.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e25.6-34.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e61-80 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e8.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e5.9-11.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026gt;80 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e0.5-3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge Statistics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e32.5 \u0026plusmn; 18.7 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e28 (18-45) years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e420\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e100.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch3\u003eSpectrum of hematological disorders\u003c/h3\u003e\n\u003cp\u003eThe integrated multimodal approach confirmed a diverse spectrum of hematological conditions. Malignant disorders predominated, led by Chronic Myeloid and Lymphocytic Leukemias. Acute Myeloid and Lymphoblastic Leukemias were also common, alongside lymphoma infiltration (25 patients). Benign disorders included Erythroid Hyperplasia, Aplastic Anemia, Myelofibrosis, Myelodysplastic Syndrome, and Multiple Myeloma as shown in Table 2.\u003c/p\u003e\n\u003cp\u003eTable 2: Distribution of hematological disorders\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eDiagnosis\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eNumber (n)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003ePercentage (%)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003e95% CI\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eClassification\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eErythroid Hyperplasia\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e120\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e28.6\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e24.3-33.2\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eBenign\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eChronic Myeloid Leukemia (CML)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e100\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e23.8\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e19.8-28.2\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eMalignant\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eChronic Lymphocytic Leukemia (CLL)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e65\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e15.5\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e12.2-19.3\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eMalignant\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eAcute Myeloid Leukemia (AML)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e48\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e11.4\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e8.6-14.8\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eMalignant\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eAcute Lymphoblastic Leukemia (ALL)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e35\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e8.3\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e5.9-11.4\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eMalignant\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eLymphoma Infiltration\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e25\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e6.0\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e3.9-8.7\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eMalignant\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eAplastic Anemia\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e15\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e3.6\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e2.0-5.8\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eBenign\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eMyelofibrosis\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e4\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e1.0\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.3-2.5\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eMalignant\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eMyelodysplastic Syndrome\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e3\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.7\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.1-2.1\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eMalignant\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eMultiple Myeloma\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e3\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.7\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.1-2.1\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eMalignant\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eLeishmaniasis\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e2\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.5\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.1-1.7\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eBenign\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eTotal\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e420\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e100.0\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch3\u003eBaseline diagnostic performance of peripheral blood film\u003c/h3\u003e\n\u003cp\u003ePBF\u0026apos;s low sensitivity for lymphoma suggests over half of cases could be missed, leading to delays/misdiagnoses. High specificity generally indicates correct PBF-indicated diagnoses. High NPVs for CML/CLL denote reliability, but lymphoma\u0026apos;s lower NPV risks false negatives from PBF alone. Cohen\u0026apos;s kappa showed excellent overall agreement (0.82), with near-perfect for CML, excellent for CLL/Erythroid Hyperplasia, but only moderate for lymphoma, reinforcing PBF limitations, Details are provided in Table 3 and Table 4.\u003c/p\u003e\n\u003cp\u003eTable 3: Diagnostic accuracy parameters of peripheral blood film\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eCondition\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eSensitivity (%)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003e95% CI\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eSpecificity (%)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003e95% CI\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003ePPV (%)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eNPV (%)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eAccuracy (%)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eCML\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e94.0\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e87.4-97.8\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e98.1\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e96.1-99.2\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e96.9\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e96.3\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e96.8\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eCLL\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e92.3\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e82.1-97.4\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e96.6\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e94.2-98.2\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e92.3\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e96.6\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e95.2\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eAML\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e83.3\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e69.8-92.5\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e86.2\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e82.4-89.4\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e76.9\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e90.4\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e85.2\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eALL\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e80.0\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e63.1-91.6\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e84.4\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e80.4-87.8\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e68.6\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e90.8\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e82.8\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eLymphoma\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e41.5\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e22.5-62.5\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e97.2\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e95.1-98.6\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e68.0\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e91.5\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e76.8\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eErythroid Hyperplasia\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e90.8\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e84.3-95.2\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e94.3\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e91.2-96.6\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e89.3\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e95.2\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e92.5\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eAplastic Anemia\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e86.7\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e59.5-98.3\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e90.1\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e86.9-92.7\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e65.0\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e97.3\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e89.5\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eOverall\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e84.2\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e80.1-87.8\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e96.8\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e94.2-98.5\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e91.3\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e94.7\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e87.5\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 4: Agreement between peripheral blood film and final integrated diagnosis\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eCondition\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eKappa Coefficient\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003e95% CI\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eAgreement Level\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003ep-value\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eCML\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.94\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.89-0.99\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eNear-perfect\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026lt;0.001\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eCLL\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.89\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.83-0.95\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eExcellent\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026lt;0.001\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eErythroid Hyperplasia\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.85\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.79-0.91\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eExcellent\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026lt;0.001\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eAplastic Anemia\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.75\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.62-0.88\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eGood\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026lt;0.001\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eAML\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.70\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.61-0.79\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eGood\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026lt;0.001\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eALL\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.67\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.56-0.78\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eGood\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026lt;0.001\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eLymphoma\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.58\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.42-0.74\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eModerate\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026lt;0.001\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eOverall\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.82\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.77-0.87\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eExcellent\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026lt;0.001\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch3\u003eIncremental diagnostic value of the integrated multimodal approach\u003c/h3\u003e\n\u003cp\u003eAdvanced ancillary tests significantly improved diagnostic value.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFlow cytometry immunophenotyping\u003c/strong\u003e\u003cbr\u003eFlow cytometry definitively diagnosed and classified 173 cases, including all 48 AML and 35 ALL by confirming lineage and providing immunophenotypic data for WHO sub classification. It confirmed clonality in all 65 CLL cases and was critical for initial characterization of 25 lymphoma cases, guiding subsequent IHC.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMolecular genetic validation\u003c/strong\u003e\u003cbr\u003eMolecular testing confirmed specific genetic aberrations. BCR-ABL1 fusion transcript was detected in 94% of CML cases. For BCR-ABL1-negative MPNs, JAK2 V617F was identified in 89% of cases (100% for Polycythemia Vera). The overall diagnostic yield of the molecular panel was 91.8%, as shown in Table 5 and Table 6.\u003c/p\u003e\n\u003cp\u003eTable 5: BCR-ABL1 testing results in CML patients\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eBCR-ABL1 Status\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eNumber (n)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003ePercentage (%)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003e95% CI\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eTest Performance\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003ePositive\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e94\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e94.0\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e87.4-97.8\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eSensitivity: 94.0%\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eNegative\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e6\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e6.0\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e2.2-12.6\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eSpecificity: 100%\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eTotal CML Cases\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e100\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e100.0\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eAccuracy: 96.7%\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eNon-CML Controls\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e320\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e-\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003ePPV: 100%\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eFalse Positives\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.0\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.0-1.1\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eNPV: 89.3%\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 6: JAK2 V617F mutation analysis in myeloproliferative neoplasms\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eMPN Subtype\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eJAK2 Positive n(%)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eJAK2 Negative n(%)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eTotal\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eMutation Rate (%)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003e95% CI\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003ep-value\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003ePrimary Myelofibrosis\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e8 (89)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e1 (11)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e9\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e89.0\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e51.8-99.7\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026lt;0.001\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003ePolycythemia Vera\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e5 (100)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0 (0)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e5\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e100.0\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e47.8-100.0\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026lt;0.001\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eEssential Thrombocythemia\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e3 (75)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e1 (25)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e4\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e75.0\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e19.4-99.4\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.125\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eTotal MPN Cases\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e16 (89)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e2 (11)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e18\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e89.0\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e65.3-98.6\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026lt;0.001\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eBone marrow trephine biopsy and immunohistochemistry\u003c/strong\u003e\u003cbr\u003eFor the 25 lymphoma cases, where PBF sensitivity was low, trephine biopsy and IHC achieved a 100% definitive diagnosis and sub classification, crucial for targeted treatment.\u003c/p\u003e\n\u003ch3\u003eLaboratory parameters and hematological indices\u003c/h3\u003e\n\u003cp\u003eBaseline laboratory parameters showed significant abnormalities, including mean hemoglobin 8.4 \u0026plusmn; 3.2 g/dL, elevated mean WBC 45.6 \u0026plusmn; 67.8 \u0026times; 10\u0026sup3;/\u0026mu;L, and thrombocytopenia. Blast cells were detected in 43.6% of patients\u0026apos; peripheral blood, Details are provided in Table 7.\u003c/p\u003e\n\u003ch3\u003eTable 7: Baseline laboratory parameters of study cohort\u003c/h3\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eParameter\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eNormal Range\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eMean \u0026plusmn; SD\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eMedian (IQR)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eAbnormal Cases n(%)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003e95% CI\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eHemoglobin (g/dL)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e12-16\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e8.4 \u0026plusmn; 3.2\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e7.8 (5.9-10.5)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e356 (84.8)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e81.2-87.9\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eWBC Count (\u0026times;10\u0026sup3;/\u0026mu;L)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e4-11\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e45.6 \u0026plusmn; 67.8\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e18.2 (6.8-52.4)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e298 (71.0)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e66.4-75.2\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003ePlatelet Count (\u0026times;10\u0026sup3;/\u0026mu;L)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e150-450\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e156.7 \u0026plusmn; 189.3\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e89.5 (34.2-198.7)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e267 (63.6)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e58.8-68.1\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eBlast Percentage (%)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026lt;5\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e23.8 \u0026plusmn; 31.4\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e8.0 (2.0-35.0)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e183 (43.6)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e38.8-48.4\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eM:E Ratio\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e2:1-4:1\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e3.8 \u0026plusmn; 4.2\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e2.1 (1.2-4.8)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e198 (47.1)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e42.3-52.0\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch3\u003ePrognostic factors and survival analysis\u003c/h3\u003e\n\u003cp\u003eMultivariate logistic regression identified age \u0026gt;40 years, hemoglobin \u0026lt;8 g/dL, WBC \u0026gt;50,000/\u0026mu;L, platelet \u0026lt;50,000/\u0026mu;L, splenomegaly, and lymphadenopathy as significant independent malignancy predictors. A Cox proportional hazards model revealed that age \u0026gt;60 years, high WBC \u0026gt;100,000/\u0026mu;L, low hemoglobin \u0026lt;6 g/dL, blast percentage \u0026gt;50%, and delayed diagnosis \u0026gt;30 days were independent predictors of poor survival, Details are provided in Table 8 and Table 9.\u003c/p\u003e\n\u003cp\u003eTable 8: Multivariate logistic regression for malignancy prediction\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003ePredictor Variable\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003e\u0026beta; Coefficient\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eSE\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eOdds Ratio\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003e95% CI\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eWald \u0026chi;\u0026sup2;\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003ep-value\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eAge \u0026gt;40 years\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.851\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.245\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e2.34\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e1.45-3.78\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e12.05\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026lt;0.001\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eMale Gender\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.207\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.234\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e1.23\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.78-1.94\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.78\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.374\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eHemoglobin \u0026lt;8 g/dL\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e1.138\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.257\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e3.12\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e1.89-5.15\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e19.67\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026lt;0.001\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eWBC \u0026gt;50,000/\u0026mu;L\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e1.541\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.354\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e4.67\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e2.34-9.32\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e18.95\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026lt;0.001\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003ePlatelet \u0026lt;50,000/\u0026mu;L\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e1.062\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.284\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e2.89\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e1.67-5.01\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e13.98\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026lt;0.001\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eSplenomegaly Present\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e1.023\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.295\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e2.78\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e1.56-4.95\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e12.01\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.001\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eLymphadenopathy\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.678\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.312\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e1.97\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e1.07-3.63\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e4.72\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.030\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 9: Cox proportional hazards model for survival analysis\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eVariable\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eHazard Ratio\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003e95% CI\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eSE\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eWald \u0026chi;\u0026sup2;\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003ep-value\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eAge \u0026gt;60 years\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e2.45\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e1.34-4.48\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.309\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e8.67\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.003\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eHigh WBC (\u0026gt;100,000/\u0026mu;L)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e3.21\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e1.78-5.79\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.302\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e15.23\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026lt;0.001\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eLow Hemoglobin (\u0026lt;6 g/dL)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e2.67\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e1.45-4.91\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.312\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e9.45\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.002\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eBlast Percentage \u0026gt;50%\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e4.12\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e2.23-7.61\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.314\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e21.34\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026lt;0.001\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eDelayed Diagnosis (\u0026gt;30 days)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e1.89\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e1.12-3.19\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.267\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e5.67\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.017\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eAML vs Other Diagnoses\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e2.34\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e1.28-4.28\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.305\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e7.89\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.005\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch3\u003eCost-effectiveness of diagnostic strategies\u003c/h3\u003e\n\u003cp\u003eMorphology-only diagnosis was least expensive but had limited accuracy. The complete integrated panel ($245 per patient) achieved the highest diagnostic accuracy. The Incremental Cost-Effectiveness Ratio indicated significant gains in diagnostic accuracy and Quality-Adjusted Life Years for the additional investment, demonstrating a favorable economic profile, Details are provided in Table 10.\u003c/p\u003e\n\u003cp\u003eTable 10: Cost-effectiveness analysis of diagnostic strategies\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eDiagnostic Strategy\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eCost per Patient (USD)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eDiagnostic Accuracy (%)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eCost per Correct Diagnosis\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eICER\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eQALYs Gained\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eMorphology Only\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e45\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e72.3\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e62.2\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eReference\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eReference\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eMorphology + Flow Cytometry\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e125\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e84.7\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e147.5\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e285.7\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.15\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eMorphology + Molecular\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e180\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e89.2\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e201.8\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e423.1\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.22\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eComplete Panel\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e245\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e96.8\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e253.1\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e512.8\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.31\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis pioneering prospective study in conflict-affected, resource-limited Yemen provides compelling evidence for the superior diagnostic accuracy and clinical utility of an integrated multimodal approach to hematological disorders. Our findings underscore that while conventional PBF is a valuable initial screening tool, its limitations, particularly for complex malignancies, necessitate advanced diagnostics for definitive classification.\u003c/p\u003e\n\u003cp\u003eThe observed 87.5% overall PBF accuracy aligns with its foundational role. However, PBF\u0026apos;s reduced sensitivity for lymphoma infiltration and moderate agreement with the integrated diagnosis highlights that morphology alone is often insufficient for diseases requiring immunophenotypic or genetic features. PBF also has limitations in characterizing various anemias or precisely subtyping myelodysplastic syndromes, where cytogenetic or molecular studies are crucial [24,25].\u003c/p\u003e\n\u003cp\u003eThe incremental diagnostic value of integrating flow cytometry, molecular genetics, and bone marrow trephine biopsy with immunohistochemistry was profound. Flow cytometry was instrumental for accurate immunophenotypic characterization and lineage assignment of acute leukemias and lymphomas [11]. Molecular genetic testing provided critical confirmation of specific genetic aberrations (e.g., BCR-ABL1 in CML, JAK2 V617F in MPNs), essential for guiding targeted therapies and prognostication [12]. For lymphoma, where PBF proved inadequate, trephine biopsy and IHC achieved 100% definitive diagnosis and subclassification [13,14]. These results underscore the necessity of establishing modern diagnostic laboratories and training personnel in resource-constrained environments.\u003c/p\u003e\n\u003cp\u003eOur identification of significant prognostic factors, including age, specific hematological parameters, and clinical signs, offers critical insights into Yemen\u0026apos;s disease landscape. Delayed diagnosis was an independent predictor of poor survival, as longer diagnostic intervals allow disease progression and narrow treatment windows [26\u0026ndash;29]. These prognostic factors resonate with findings from studies in the Middle East and Africa [18].\u003cbr\u003eOur findings contribute to the scarce literature on hematological disorders in Yemen. An older study by Al-Ghazaly et al. in Sana\u0026apos;a reported different prevalences of AML, ALL, CML, and CLL compared to our study, possibly reflecting shifting epidemiology or diagnostic capabilities [30]. More recently, Al-Nuzaili et al. in Sana\u0026apos;a described hematological malignancy prevalence [31]. A previous study by Saeed N. et al. in south-west Yemen reported various acute and chronic leukemias, MPN, MDS, multiple myeloma, and lymphoma [31]. Our study shows notably lower prevalence of AML and ALL, and higher CML and CLL compared to these reports. A study in Hadhramout highlighted chronic MPN followed by AML [32]. Our specific MPN prevalence rates and JAK2 V617F mutation rates are detailed in Table 6. These comparisons underscore regional variability and the dynamic nature of hematological disease patterns within Yemen. Our identification of Leishmaniasis (0.5%) is consistent with other studies [33]. The overall lack of comprehensive epidemiological reports across Yemen, as noted by Al-Nuzaili et al. [31] and Al-Ghazaly et al. [30], underscores our study\u0026apos;s critical importance in providing contemporary data. Anemia challenges [34] and transfusion-transmitted infections [35] also remain public health problems.\u003c/p\u003e\n\u003cp\u003eFurthermore, the cost-effectiveness analysis strongly justifies investing in an integrated multimodal diagnostic approach. While the complete panel has a higher initial cost, its substantial increase in diagnostic accuracy and resulting gains in Quality-Adjusted Life Years demonstrate a favorable economic profile. This is consistent with studies from other resource-limited environments, showing advanced diagnostics can be highly cost-effective by improving patient outcomes and reducing long-term healthcare burdens. This evidence supports strategic investment in comprehensive diagnostic capabilities.\u003c/p\u003e\n\u003cp\u003eThe unique contribution of this study lies in its prospective validation of these integrated diagnostics within a conflict-affected, resource-limited setting like Yemen. Challenges from ongoing conflict amplify the importance of developing resilient and effective diagnostic systems. Our results demonstrate that despite formidable obstacles, high diagnostic accuracy is achievable, offering a blueprint for other regions [11]. To ensure long-term sustainability, strategies must include continuous investment in local personnel training, resilient supply chains, and innovative approaches like tele-consultation models [36\u0026ndash;38].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStrengths and limitations:\u003c/strong\u003e Significant strengths include the prospective design and comprehensive evaluation of a large patient cohort, with a multidisciplinary team establishing the gold standard. A limitation is the single-center nature, potentially affecting generalizability. Future research should include multi-center studies and implementation science research.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis first prospective study from a conflict-affected, resource-limited setting in Yemen conclusively demonstrates that an integrated multimodal diagnostic approach significantly improves the accuracy and comprehensiveness of diagnosing hematological disorders. While PBF remains a valuable initial screening tool, its utility is considerably enhanced by sequential integration of flow cytometry, molecular genetic analysis, bone marrow trephine biopsy, and immunohistochemistry. These advanced techniques are indispensable for definitive classification, accurate prognostication, and guiding targeted therapies, leading to better patient outcomes. The study also provides strong evidence for the cost-effectiveness of this integrated approach, justifying the investment required to establish and sustain such capabilities in challenging environments. These findings provide a compelling economic argument for international and national health bodies to prioritize strategic investments in comprehensive diagnostic capabilities within fragile health systems. Our findings offer a validated framework and underscore the critical need for strengthening comprehensive hematological diagnostic services in Yemen and other similarly constrained regions globally, ultimately contributing to improved healthcare standards and patient survival.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAdditional information\u003c/h2\u003e\n\u003ch3\u003eData availability\u003c/h3\u003e\n\u003cp\u003eThe data supporting the findings of this study are not openly available due to sensitivity reasons. However, they are available from the author upon reasonable request. All patient data were anonymized and stored securely using digital storage protocols to ensure the protection of patient confidentiality, particularly given the vulnerable population studied.\u003c/p\u003e\n\u003ch2\u003eAuthor contributions\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003eConcept and design:\u003c/strong\u003e Mohammed A. Al-Qadhi, Ahmed K. Salem, Mohammed A. Hajar\u003cbr\u003e\u003cstrong\u003eAcquisition, analysis, or interpretation of data:\u003c/strong\u003e Mohammed A. Al-Qadhi, Ahmed K. Salem, Mohammed A. Hajar\u003cbr\u003e\u003cstrong\u003eDrafting of the manuscript:\u003c/strong\u003e Mohammed A. Al-Qadhi, Ahmed K. Salem, Mohammed A. Hajar\u003cbr\u003e\u003cstrong\u003eCritical review of the manuscript for important intellectual content:\u003c/strong\u003e Mohammed A. Al-Qadhi, Ahmed K. Salem, Mohammed A. Hajar\u003cbr\u003e\u003cstrong\u003eSupervision:\u003c/strong\u003e Mohammed A. Al-Qadhi, Ahmed K. Salem, Mohammed A. Hajar\u003c/p\u003e\n\u003ch2\u003eDisclosures\u003c/h2\u003e\n\u003ch3\u003eHuman subjects\u003c/h3\u003e\n\u003cp\u003eInformed consent for treatment and open access publication was obtained or waived by all participants in this study. The Institutional Review Board of Al-Thawra Modern General Hospital in Sana\u0026apos;a approved this study. Written informed consent was obtained from all adult participants and parents/guardian\u0026apos;s of pediatric patients. All procedures were conducted in accordance with the ethical principles of the Declaration of Helsinki and local ethical guidelines.\u003c/p\u003e\n\u003ch3\u003eAnimal subjects\u003c/h3\u003e\n\u003cp\u003eAll authors have confirmed that this study did not involve animal subjects or tissue.\u003c/p\u003e\n\u003ch3\u003eConflicts of interest\u003c/h3\u003e\n\u003cp\u003eIn compliance with the International Committee of Medical Journal Editors uniform disclosure form, all authors declare the following:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003ePayment/services info:\u003c/strong\u003e All authors have declared that no financial support was received from any organization for the submitted work.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eFinancial relationships:\u003c/strong\u003e All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eOther relationships:\u003c/strong\u003e All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003ePavithra P, Laxminarayana SLK, Manohar C, Belurkar S, Kairanna NV. 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Time-to-diagnosis and symptoms of myeloma, lymphomas and leukaemias: a report from the Haematological Malignancy Research Network. BMC Blood Disorders [Internet]. 2013 [cited 2025 Sep];13. Available from: https://doi.org/10.1186/2052-1839-13-9 \u003c/li\u003e\n\u003cli\u003eL\u0026oacute;pez‐Garc\u0026iacute;a YK, Valdez-Carrizales M, Nu\u0026ntilde;ez-Zuno JA, Apodaca E, Rangel‐Pati\u0026ntilde;o J, Demichelis‐G\u0026oacute;mez R. Are delays in diagnosis and treatment of acute leukemia in a middle-income country associated with poor outcomes? A retrospective cohort study. Hematology Transfusion and Cell Therapy [Internet]. 2023 [cited 2025 Nov];46:366. Available from: https://doi.org/10.1016/j.htct.2023.05.010 \u003c/li\u003e\n\u003cli\u003eAl-Ghazaly J, AL-SELWI AH, Abdullah M, AL-JAHAFI AK, Al-Dubai W, Al-Hashdi A. Pattern of haematological diseases diagnosed by bone marrow examination in Yemen: a developing country experience. Clinical \u0026amp; Laboratory Haematology [Internet]. 2006 [cited 2025 Nov];28:376. Available from: https://doi.org/10.1111/j.1365-2257.2006.00823.x \u003c/li\u003e\n\u003cli\u003eAl-Nuzaili MA, Al-Khamesy KSA, Yahia OM. Acute myeloid leukemia among patients at the National Oncology Center in Sana \u0026rsquo; a, Yemen: prevalence, subtypes, and hematological features. Research Square (Research Square) [Internet]. 2022 [cited 2025 Aug]; Available from: https://doi.org/10.21203/rs.3.rs-2299384/v1 \u003c/li\u003e\n\u003cli\u003eAM D, AA B, AA B, AA A-Z. Correlation Hematological Malignancies in the Hadhramout Sector Pattern and Distribution. Journal of Blood Disorders and Medicine [Internet]. 2023 [cited 2025 Nov];5. Available from: https://doi.org/10.16966/2471-5026.129 \u003c/li\u003e\n\u003cli\u003eAl-Ghazaly J, Al-Dubai W, Abdullah M, Al-Gharasi L. HEMATOLOGICAL CHARACTERISTICS OF YEMENI ADULTS AND CHILDREN WITH VISCERAL LEISHMANIASIS. COULD EOSINOPENIA BE A SUSPICION INDEX? 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Available from: https://doi.org/10.2196/29619 \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Faculty of Medicine and Health Sciences, Sana'a University, Sana'a, Yemen","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"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":"hematological disorders, multimodal diagnostics, resource-limited settings, yemen, cost-effectiveness","lastPublishedDoi":"10.21203/rs.3.rs-8168085/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8168085/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground and objectives:\u003c/h2\u003e\u003cp\u003eHematological disorders pose significant diagnostic challenges, particularly in conflict-affected, resource-limited regions like Yemen, leading to delays, misdiagnoses, and suboptimal patient care. This study aimed to prospectively validate an integrated multimodal diagnostic approach for hematological disorders in Yemen, assessing its diagnostic accuracy, clinical utility, prognostic value, and cost-effectiveness compared to conventional morphology-based diagnosis.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eA prospective study enrolled 420 patients with suspected hematological disorders. A comprehensive algorithm, integrating peripheral blood film morphology, flow cytometry, molecular genetics, bone marrow trephine biopsy with immunohistochemistry, and targeted ancillary tests, was employed. The final integrated diagnosis, established by a multidisciplinary team, served as the gold standard. Diagnostic accuracy, agreement, malignancy prediction, survival analysis, and cost-effectiveness were assessed.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThe cohort showed a diverse spectrum, predominantly malignancies. PBF achieved 87.5% overall accuracy but had low sensitivity (41.5%) for lymphoma infiltration, highlighting its limitations. The integrated approach achieved 96.8% combined diagnostic accuracy. Flow cytometry was crucial for acute leukemias, chronic lymphocytic leukemia, and lymphomas. Molecular testing confirmed BCR-ABL1 in 94% of CML and JAK2 V617F in 89% of BCR-ABL1-negative myeloproliferative neoplasms. Bone marrow trephine biopsy combined with IHC provided 100% definitive diagnosis for lymphoma. Prognostic factors included age\u0026thinsp;\u0026gt;\u0026thinsp;40 years, hemoglobin\u0026thinsp;\u0026lt;\u0026thinsp;8 g/dL, WBC\u0026thinsp;\u0026gt;\u0026thinsp;50,000/\u0026micro;L, platelet\u0026thinsp;\u0026lt;\u0026thinsp;50,000/\u0026micro;L, splenomegaly, and lymphadenopathy. Poor survival was predicted by age\u0026thinsp;\u0026gt;\u0026thinsp;60 years, high WBC (\u0026gt;\u0026thinsp;100,000/\u0026micro;L), low hemoglobin (\u0026lt;\u0026thinsp;6 g/dL), blast percentage\u0026thinsp;\u0026gt;\u0026thinsp;50%, and delayed diagnosis. The complete integrated panel (\u003cspan\u003e$\u003c/span\u003e245/patient) demonstrated superior diagnostic accuracy and improved Quality-Adjusted Life Years, showing a favorable economic profile.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eThis pioneering study in a conflict-affected, resource-limited setting establishes that an integrated multimodal diagnostic approach substantially improves diagnosis of hematological disorders, overcoming morphology-based limitations. These findings emphasize the critical need for implementing comprehensive diagnostic capabilities to optimize patient outcomes and inform public health strategies.\u003c/p\u003e","manuscriptTitle":"Integrated Multimodal Diagnostic Validation in Hematological Disorders: First Prospective Study from a Conflict-Affected, Resource-Limited Setting in Yemen","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-25 08:19:50","doi":"10.21203/rs.3.rs-8168085/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":"November 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":58351846,"name":"Hematology"},{"id":58351847,"name":"Molecular Genetics"},{"id":58351848,"name":"Internal Medicine"}],"tags":[],"updatedAt":"2025-11-25T08:19:50+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-25 08:19:50","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8168085","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8168085","identity":"rs-8168085","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}