Majed Ramadan¹, Doaa Aboalola¹, Raghad Alzahrani², Shahad Alasiri², Hala Althomali², Khulood Alsiary³, Mohieeldin Elsayid², Rawiah Alsiary^1*

¹King Abdullah International Medical Research Center (KAIMRC), Jeddah, Saudi Arabia/King Saud bin Abdulaziz University for Health Sciences (KSAU-HS), Jeddah, Saudi Arabia.

²Faculty of Applied Medical Sciences, King Saud bin Abdulaziz University for Health Sciences (KSAU-HS), Jeddah, Saudi Arabia.

³Family Medicine Department, National Guard Health Affairs, Prince Mohammad ben Abdul-Aziz Hospital. King Saud bin Abdulaziz University for Health Sciences (KSAU-HS), Jeddah, Saudi Arabia.

*Corresponding Author: Rawiah Alsiary, King Abdullah International Medical Research Center (KAIMRC), Jeddah, Saudi Arabia/King Saud bin Abdulaziz University for Health Sciences (KSAU-HS), Jeddah, Saudi Arabia.

Abstract
Background: The frequency of leukemia has been steadily rising in the Kingdom of Saudi Arabia during the last several years. In everyday practice, the information on survival rate to the age and types of leukemia is insufficient.

Objective: Therefore, the goal of this study was to determine the mortality factors and evaluate the overall clinical and epidemiological features of patients who were diagnosed with leukemia at Princess Norah Oncology Center.

Materials and Methods: A Retrospective analysis was conducted on the clinical and demographic data for patients diagnosed with leukemia, ranging in age from one to 81 years old, from 2015 to 2021 at the Princess Norah Oncology Center, King Abdulaziz Medical City, Western Region.

Results: The hazard ratio (HR) is 8.11 times higher for Acute Myeloid Leukemia (AML) patients compared to Acute Lymphoblastic Leukemia (ALL) patients. Also, according to the Kaplan-Meier survival curves, AML patients had worse overall survival than patients with ALL and other types of leukemia (APL, CLL, CML, and JMML). Unexpectedly, our findings showed that patients with abnormal cytogenetic mutations had a better survival rate than those with normal cytogenetic mutations.

Conclusions: Our study examined and defined the most common patterns of leukemia within the Saudi population at Princess Norah Oncology Center. It also identified prediction factors for mortality among our population.

Keywords: Leukemia, acute lymphatic leukemia, acute myeloid leukemia, mortality, demographic variables, clinical variables, Kingdom of Saudi Arabia.

Introduction
A form of cancer known as leukemia develops from the maturing myeloid and lymphoid stem cells in the bone marrow known as Hematopoietic stem cells [1]. Leukemia has four main types: Acute Myeloid Leukemia (AML), Chronic Lymphocytic Leukemia (CLL), Acute Lymphoblastic Leukemia (ALL), and Chronic Myeloid Leukemia (CML) [1]. These major types can be subdivided further as follows. ALL is classified as B-cell ALL and T-cell ALL by (WHO), the World Health Organization, based on gene and chromosomal alterations in leukemia cells. Moreover, the French American-British (FAB) classification divides AML into seven subtypes based on the type of cell from which the leukemia starts and how mature the cells are. This was mainly determined by how the leukemia cells appeared under the microscope following standard staining. In addition, there are two types of CLL that resemble one another but differ in the quantity of the proteins ZAP-70 and CD38. Furthermore, there are other more uncommon types of leukemia, such as myelodysplastic syndromes, hairy cell leukemia, and myeloproliferative disorders. Another chronic leukemia that begins in myeloid cells is chronic myelomonocytic leukemia (CMML) [2-6].

Because of advancements in diagnostic and therapeutic techniques over the last several decades, the survival rate for the majority of leukemia types has risen. The majority of childhood leukemia are considered cured after five years of remission since they are unlikely to recur after that time [18]. Based on the (NCI) National Cancer Institute, the relative 5-year survival rate for all types of leukemia is approximately 65% [18]. Regarding prognosis, the most critical factors are white blood cell count (WBC), cytogenetic results, and age [19-23]. In addition, leukemia is associated with a number of risk factors, such as smoking, chemical exposure, prior chemotherapy exposure, radiation exposure, rare congenital abnormalities, specific blood problems, age, and gender [24].

Furthermore, there was insufficient evidence in Saudi Arabia about the effectiveness of categorizing demographic and clinical characteristics, their impact on survival and mortality rates, and the prognosis of leukemia based on different ages, sexes, and cytogenetic or molecular profiles. Consequently, more research is needed. Thus, the current study aims to investigate leukemia trends and define the most common patterns of leukemia within the Saudi population of various ages and genders in a single center, Princess Norah Oncology Center at Western Region, using medical records from the BEST Care system from 2015 to 2021.

Material and Methods
Study Settings, Design, and Population
This retrospective cohort study used the Ministry of National Guard Health Affairs' (MNG-HA) data. The MNG-HA, with a 751-bed capacity, is a healthcare organization funded by the government of the Kingdom of Saudi Arabia, and it is affiliated with the Ministry of National Guard. It provides various clinical, academic, and research programs, from public health and primary care to the fine tertiary care specialties and sub-specialties. The medical city consists of a large oncology center that serves individuals living in Saudi Arabia from all regions. The current study used cancer registry unit data between 1/1/2015 to 31/12/2021. The registry includes all cancer patients' data for individuals diagnosed and treated at King Abdulaziz Medical City (KAMC) in Jeddah City, Western Province. Data include demographic and visit characteristics (age, gender, marital status, date of death, and date of last contact) and clinical characteristics (date of diagnosis, tumor histology, level of differentiation, stages, and cancer grades).

Princess Norah Oncology Center follows the World Health Organization's (WHO) leukemia protocols for leukemia diagnosis and tumor classification [25]. Categories, types, and subtypes of leukemia are classified according to WHO guidelines to increase levels of specificity. For instance, the lymphoblasts should make up more than 20% to 25% of the cells in a peripheral blood smear or bone marrow biopsy/aspirate to diagnose ALL. The treatment options in the Oncology Center for leukemia are influenced by various factors, such as the patient's overall health, age, and type and stage of leukemia. Common leukemia treatments are Chemotherapy, Immunotherapy, Radiation, Targeted therapy, and Bone marrow transplant.

Identification of patients
Ethical approval was obtained from the Local Institutional Review Board of the Saudi National Guard Health Affairs, Jeddah (JED-20- 427780-97365). All methods were performed in accordance with the relevant guidelines and regulations of KAIMRC. Informed consent for general treatment was obtained at admission. The patient's medical information was strictly confidential. All patients' identifying variables were omitted before the analysis. Study participant selection included all individuals diagnosed with leukemia cancer, International Classification of Diseases (ICD) (ICD-10 C95–C96) between 2015-2021, who were residing in Saudi Arabia and registered in MNG-HA hospitals system with follow-up to December 31, 2021. Four (0.7 %) of the 329 eligible patients were excluded due to unknown admission status, contact dates, or survival status.

Patient and Tumor Characteristics
Demographics such as age, gender, age at diagnosis, body mass index (BMI), and region were collected from the electronic medical records. Clinical data were also collected, including mutation and laboratory variables such as (hemoglobin level, red blood count (RBC), total white blood count (WBC), and platelet count). Types and subtypes of leukemia, complex karyotype, and transplantation were also documented. Other variables were also collected, like comorbidity such as (cardiovascular disease, obesity or underweight, diabetes, pulmonary disease, hypertension, coronary disease, renal failure, hepatic failure, asthma, anxiety, depression, behavioral problems and sleep disorder in children), family history, COVID19 infection status during the patients' follow-up in 2019-2020, relapse, easy bleeding from nose and gum bleeding due to low platelets count, infection status, such as whether the patients had symptoms that could have been caused by a bacterial, viral, or fungal infection, swallow lymph node which is defined as enlargement of one or more lymph nodes due impairment in the immune system caused by inflammatory conditions.

The cellularity of the bone marrow was determined by estimating the ratio of hematopoietic cells to fat; 25-75% of hematopoietic cells is considered a normal range.

Outcome Variable
The primary outcome variable was death status. The follow-up period began on the date of leukemia diagnosis recorded in the registry and finished either on the date of death, the last contact, or the study end date (December 31, 2021), whichever came first. Completeness of follow-up was computed at each time interval using Clark's completeness index (CCI) and a simplified person-time (SPT) method [26,27]. The resulting CCI and SPT were 84.22% and 80.77% respectively.

Statistical Analysis
Demographics, mutation status, and clinical and laboratory characteristics were evaluated across right- and left-sided mCRC tumors using Chi-square and Fisher exact tests. Purposeful variable selection was used in the multivariate analyses for model building [28]. All variables with a P value of less than 0.3 were kept via backward elimination. The log-rank test for all-cause mortality was used to evaluate the differences between curves and estimate the survival rates using the Kaplan-Meier product-limit method. We further stratified the Kaplan-Meier survival curve by cytogenetic mutation to examine the difference in survival between those with and without cytogenetic mutation. We employed Cox proportional hazards regression models to calculate the variations in all-cause mortality across the various leukemia types. Firth's Correction for Monotone Likelihood was applied to account for the small sample size and eliminate any potential bias [29, 30]. Results were deemed statistically significant at P < 0.05; all statistical tests were two-sided. Version 9.4 of SAS statistical software was used for all the analyses.

Results
329 patients diagnosed with leukemia were included in the study. Acute lymphatic leukemia (ALL) accounts for the majority of leukemia patients (79.0%), followed by acute myeloid leukemia (AML) for 16.72%, and other types of leukemia account for 4.2% (APL, CLL, CML, and JMML). Patients' mean and median age for ALL, AML, and other types of leukemia were 11.8 (10%), 26.4 (17%), and 40 (52%), respectively. For patients diagnosed with ALL, 80.38% were youth (1 to 15 years old), 58.08% were male, 65.3% were underweight, 80.7% were diagnosed at age 1 to 12 years old, 70.8% lived in the North/Western region, 74.6% had comorbidity, 96.3% received treatment, and 61.9% had a family history of cancer. The same patterns were observed among AML and other types of leukemia (Table 1). In addition, 6.4% of all leukemia patients were positive for the COVID-19 virus (Table 1). ALL patients had a higher survival rate compared to AML, as one-fourth of AML patients died (25.4%) compared to (6.9%) of ALL patients (Table 1). However, other types of leukemia had the highest relapse rate (21.4%), followed by ALL (19.2%) (Table 1).

Table 2 presents the clinical characteristics of the different types of leukemia. AML patients experienced the most pronounced symptoms in which they had the highest prevalence of easy bleeding (38.1%), Infection status (89.0%), swallowing lymph nodes (58.1%), losing appetite and weight (45.4%), high bone marrow results (69.0%), high hemoglobin at diagnosis (1.8%), and high white blood cells count (45.4%) compared to ALL and other types of leukemia. In contrast, red blood cell count, platelets, and transplantation were the highest among ALL patients (2.6%, 2.3%, and 37.3%, respectively) (Table 2).

Moreover, APL, CLL, CML, and JMML patients had the highest rate of at least one genetic mutation (64.29%). While complex karyotype and abnormal cytogenetic mutation were the most common among ALL patients (15 % and 72.3 %, respectively) (Table 2). In terms of specific deleterious genetic mutations, AML patients had a higher rate of FLT3 and RUNX1 mutations (36.3% and 12.7%, respectively), while other types of leukemia had higher JAK2 mutations (7.6%) compared to ALL and AML patients. Finally, ALL patients had a higher rate of ETV6 mutations (11.5%) compared to AML and other types of leukemia. In addition, the multivariate analysis in Table 3 showed that older ages were 1.02 more likely to die (95% CI, 1.005, 1.04; P = 0.01) while HR for patients with AML was 8.11 higher compared to ALL patients (95% CI, 3.46, 18.96; P = 0.0001) (Table 3).

Table 1: Demographic characteristics of leukemia patients by leukemia type at an Oncology Center in the Western Region of Saudi Arabia (2015- 2021)

Table 2: Clinical characteristics of leukemia patients by leukemia type at an Oncology Center in the Western Region of Saudi Arabia (2015-2021)

Table 3: Hazard ratio of leukemia patients’ all-cause death at an Oncology Center in the Western Region of Saudi Arabia (2015-2021) (Multivariate analyses)

Survival curves using the Kaplan-Meier for different types of leukemia patients were evaluated. Patients with AML had a shorter median overall survival of 33 months (95 percent CI, 19-41 months) compared to 38 months (95 percent CI, 34-45 months) for patients with ALL and 46 months for other types of leukemia (95 percent CI, 18-65 months, P = 0.059) (Figure 1). The Kaplan-Meier survival analysis for patients with normal and abnormal cytogenetic surprisingly showed that patients with abnormal cytogenetic mutations had a longer median overall survival of 39 months (95 percent CI, 33-46 months), while patients with normal cytogenetic mutations had a median overall survival of 33 months (95 percent CI, 19-38 months, P = 0.0007) (Figure 2).

Figure 1:  Kaplan-Meier Survival Curves Comparing Survival for Patients with ALL, AML and other type of leukemia

Figure 2: Kaplan-Meier Survival Curves Comparing Survival for Patients with abnormal, and normal cytogenetic mutation.

Moreover, the slight sample size restriction might have caused an underestimation of the predictive outcome of leukemia types. Second, there was missing information in several variables coded as "Not mentioned." These data would have permitted further analysis and evaluation of the predictive value of essential factors in specific subgroups, particularly transplantation.

Conclusion
In an oncology center serving the Saudi population in the Western region, our study looked at and outlined the most prevalent leukemia pattern types. Additionally, it revealed mortality risk factors for our demographic. The results from this study warrant the further investigation of leukemia prognostic factors that affect patients' survival and long-term outcome.

Conflict of Interest: The authors declare that the research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments: We thank King Abdullah International Medical Center (KAIMRC) and King Saud bin Abdulaziz University for Health Sciences (KSAU-HS) for their financial support.

Data Availability Statement: The data supporting this study's findings are available from King Abdullah International Medical Research Center (KAIMRC). However, restrictions apply to the availability of these data, which were used under license for the current study and are not publicly available. Data are, however, available from the authors upon reasonable request and with permission of King Abdullah International Medical Research Center (KAIMRC).

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