Prevalence and Patterns of EGFR Mutations in Non-Small Cell Lung Cancer in the Middle East and North Africa: A Systematic Review

Prevalence and Patterns of EGFR Mutations in Non-Small Cell Lung Cancer in the Middle East and North Africa: A Systematic Review | 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 Prevalence and Patterns of EGFR Mutations in Non-Small Cell Lung Cancer in the Middle East and North Africa: A Systematic Review Youssra Boustany, Abdelilah Laraqui, Hicham El Rhaffouli, Tahar Bajjou, and 15 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1051050/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 To summarize current evidence and estimate the prevalence of epidermal growth factor receptor ( EGFR ) mutation frequency and its association with ethnicity and clinic-pathological features in non-small cell lung cancer (NSCLC) patients in the Middle East (ME) and North Africa (NA), a systematic literature review was undertaken. We conducted a literature search of original articles published in six databases (PubMed, Science Direct, Web of Science, Embase, Scopus, and Google scholar) from the time of inception until April 2021. Search terms included “lung cancer”, “NSCLC”, “ EGFR mutation”, “Middle East”, “North Africa”, and specific country names belonging to the considered region. The included studies had to meet the following criteria: the study must relate to the role of the EGFR gene in NSCLC, analyze mutations in exon 18, 19, 20, and 21 or select exons of the EGFR gene, and provide sufficient information on the clinic-pathological characteristics of the included NSCLC patients. A total of 24 eligible studies were included [(66.6%) in the ME and (34.4%) in NA]. Overall, 6544 patients with NSCLC were analyzed for EGFR mutations [(55.1%) in the ME and (44.8%) in NA]. The overall prevalence of EGFR mutations was 17.9%. In the ME, the reported frequency was 17.3%, whereas in NA, the prevalence of EGFR mutations was 18.5%. The most frequently encountered mutations were the exon 19 deletions (45.2%) and exon 21 substitutions (30.9%). Exon 20 alterations were detected in 11.2%, of which, the T790M resistance mutation was the most prevalent (45.5%). Exon 18 mutations were reported in 3.8%. In the ME, 50.5% of NSCLC patients were positive for exon 19 deletions versus 48.3% in NA. Exon 21 mutations were slightly more commonly detected in the ME (36.3%) than NA (31.3%). There was 1.2% of patients that had concurrent EGFR mutations. Overall, EGFR mutations prevalence was higher in females, non-smokers, and patients with adenocarcinoma. Our systematic literature review concurs that EGFR mutation prevalence among MENA populations is slightly higher than that seen in NSCLC patients of Caucasian ethnicity but is lower than that identified in Asian NSCLC patients. The distribution of these mutations varies significantly throughout the MENA region. Cancer Biology Oncology Non-small cell lung cancer EGFR mutations MENA Introduction Lung cancer occurred in approximately 2.2 million patients, representing 22.7% of the global cancer burden. In 2020, 1.8 million patients died of lung cancer [ 1 ]. It is the leading cause of cancer morbidity and mortality in men, whereas in women, it is the third most common cancer, behind breast and colorectal cancers, and the second leading cause of female cancer death. Incidence and mortality rates are roughly 2 times higher in men than in women, and the male-to-female ratio varies widely across regions, ranging from 1.2 in Northern America to 5.6 in Northern Africa [ 1 ]. The incidence and mortality estimates for lung cancer are 3 to 4 times higher in countries with a high Human Development Index (HDI) than in countries with a low HDI; this pattern may well change as the tobacco epidemic evolves given that 80% of smokers aged ≥15 years resided in low-income and middle-income countries in 2016 [ 2 ]. Worldwide, the lung cancer mortality rate is foreseen to increase up to 3 million by 2035. The figures are set to double for both genders (men: from 1.1 million in 2012 to 2.1 million by 2035; and women: from 0.5 million in 2012 to 0.9 million by 2035) and the existing gender gap is expected to persist. Most prominent increases are expected in Africa and the Eastern Mediterranean region [ 3 ]. The Middle East (ME) and North Africa (NA) countries have witnessed a steady increase in the incidence rates of lung cancer [ 4 ]. In 2018, an estimated new 79887 lung cancer cases were registered in the MENA region versus 470000 new diagnoses in Europe. The age-standardized incidence rate of lung cancer in the MENA region is less than international rates, with figures varying from lowest in Yemen (4.2 per 100,000) to highest in Lebanon (23 per 100,000) [ 5 ]. Lung cancer incidence rates increases are more eminent among older age groups in the MENA area [ 6 ]. Despite recent breakthroughs in lung cancer management, the 5-year relative survival rate in the region doesn’t surpass 8%. This is largely due to late diagnoses. In the MENA countries, the highest mortality rates were reported in Morocco and Tunisia, whereas the lowest were in Yemen and Egypt [ 5 ]. Lung carcinomas are categorized by the size and appearance of the malignant cells and are divided into two broad categories of small cell lung cancers (SCLC) and non-small cell lung cancers (NSCLC). SCLC comprises about 10%-15% of all lung cancers. NSCLC is the most common type of lung cancer and accounts for 80-90% of all lung tumors. SCLC, commonly centrally located in the major airway, tends to grow and spread faster than NSCLC. It is estimated that 70% of SCLC patients present with locally advanced or distant metastatic disease at the time of diagnosis [ 7 ]. NSCLC is a highly heterogeneous disease and is mainly divided into three major histological subtypes: adenocarcinoma, squamous cell carcinoma, and large cell carcinoma; it harbors various genetic alterations within each subtype. The identification of mutations in certain histological subtypes has led to molecular sub-classification of NSCLC and also opened therapeutic opportunities for personalized medicine based on targeted drugs [ 8 , 9 ]. Several mutations in NSCLC are considered actionable with available or promising targeted therapies. Some of the most common mutations for NSCLC occur in epidermal growth factor receptor ( EGFR ) and favor cell survival, proliferation and migration, and metastasis development by increasing the activity of EGFR tyrosine kinase [ 10 ]. EGFR tyrosine kinase inhibitors (TKIs) are established effective therapies in patients who have mutations in exons 18, 19, 20, and 21 of EGFR , leading to longer progression-free survival intervals with fewer or at least different side-effects than chemotherapy [ 11 , 12 ]. Previous studies have established marked variations in EGFR mutation rates depending on different geographic locations and race/ethnicity backgrounds. It occurs at the rate of 10-15% in North Americans and Europeans, 15–20% in African-Americans, 20-30% in various East Asian series (Chinese, Koreans, Japanese), and 20–25% in patients from the Indian subcontinent [ 13 – 17 ]. In ME and African populations, the EGFR mutation frequency is higher than that shown in white populations but still lower than the frequency reported in Asian populations [ 18 ]. In the MENA, the frequency of EGFR mutations is considered among the lowest. To summarize current evidence and estimate the prevalence of EGFR mutations and its association with geographic region/country and clinic-pathological features of EGFR mutation-positive NSCLC patients in the Middle East (ME) and North Africa (NA), A systematic literature review was undertaken in Bahrain, Egypt, Iran, Iraq, Jordan, Kingdom of Saudi Arabia, Kuwait, Lebanon, Oman, Palestine, Qatar, Syria, Turkey, United Arab Emirates, Yemen, Algeria, Egypt, Morocco, and Tunisia. Methods We conducted a systematic review of literature published on EGFR mutation prevalence and its association with geographic region/country and clinic-pathological features in NSCLC patients in MENA region. We carried out a literature search of original articles published in six databases (PubMed, Science Direct, Web of science, Embase, Scopus, and Google scholar) from the time of inception until April 2021. Included articles have been published in English in indexed and peer-reviewed journals. Search terms included lung cancer, or lung tumor, or lung adenocarcinoma, or NSCLC, or EGFR , or EGFR mutation, or EGFR oncogene mutations, or EGFR oncogenic driver mutation, or EGFR activating mutation, or EGFR prevalence, or EGFR rate, or EGFR incidence or EGFR frequency. An additional literature search was also conducted using Middle East, Middle Eastern, North Africa, North African and specific country names belonging to the considered region and any other variant names for any of the MENA countries (ex: Maghreb, Levant, Gulf, Arab). We manually checked reference lists of the included studies and relevant review articles to identify additional studies. We also searched relevant abstracts reported in the most important multi-disciplinary societies of medical oncology such as the American Society of Clinical Oncology (ASCO) meetings to identify unpublished studies. Original articles were identified from Jordan [ 19 ], Iran [ 20 , 21 ], Turkey [ 22 – 26 ], Bahrain [ 27 ], Iraq [ 29 , 30 ], Lebanon [ 31 – 33 ], Morocco [ 35 – 37 ], Tunisia [ 38 – 40 ], Egypt [ 41 ], and Algeria [ 42 ]. A multicenter prospective study from Levant (Lebanone, Syria, Palestine, Jordan, Iraq, and Egypt) [ 34 ] and a multisite retrospective study from Gulf region (Saudi Arabia, the United Arab Emirates and Qatar) were also identified and will part of our analysis [ 28 ]. The included studies had to meet the following criteria: the study must relate to the role of the EGFR gene in NSCLC, analyze mutations in exon 18, 19, 20, and 21 or select exons of the EGFR gene, and provide sufficient information on the clinico-pathological characteristics of the included NSCLC patients. A total of 24 studies met the inclusion criteria. In most studies, materials were formalin-fixed paraffin-embedded (FFPE) tissues and included small biopsies such as trans-bronchial biopsy or tru-cut biopsy and also resection materials. DNA extraction was applied on tissue samples using kits that extracted DNA from paraffin blocks. Mutations in exon 18 (codon 719), exon 19 deletions, exon 20 (codons 768 and 790), and exon 21 (codons 858 and 861) were assessed in 79.1% (19/24) of the studies. A wide variety of detection methods were used to identify recognized mutations of the EGFR kinase domain, from exon 18 to 21. Direct sequencing was broadly used, as it was used in the most of the studies [ 19 – 21 , 23 , 24 , 26 , 33 , 34 , 36 , 37 , 40 ]. RT-PCR-based assays, namely scorpions-amplification refractory mutation system (ARMS/Scorpion) methodology, was also widely used [ 27 , 29 , 31 – 33 , 37 , 40 ]. EGFR mutation analysis was carried out with quantitative PCR analysis in the study from Gulf region [ 41 ]. The INFINITI system using BioFilmChip-based microarray assay was used in one study from Turkey [ 22 ]. Details of the study methods and population characteristics are summarized in Table 1 . Table 1 Characteristics of the included studies. Country/Region Author [reference] Year of publication cases Age (years) Male/female n (%) Smokers/non smokers n (%) ADK/NADK n (%) Detection gene Site (exon) Test type Jordan Obeidatet al. [ 19 ] 2016 166 59 ± 12.6 116 (70)/50 (30) 129 (77)/37 (23) 166 (100)/0 (0) 18, 19, 20, and 21 PCR/Sequencing Iran Mohammad et al. [ 20 ] 2019 50 58.4 ± 13 30 (60)/20 (40) 31 (42)/29 (58) 50 (100)/0 (0) 18, 19, 20, and 21 PCR/Sequencing Basi et al. [ 21 ] 2018 103 67 51(49.5)/52 (50.5) 37 (36)/66 (64) 103 (100)/0 (0) 18, 19, 20, and 21 PCR/Sequencing Turkey Calibasi et al. [ 22 ] 2020 409 60 299 (73.1)/110 (26.9) 246 (60.1)/163 (35.9) 409 (100)/0 (0) 18, 19, 20, and 21 INFINITI method Bircan et al. [ 23 ] 2014 25 65.3 21(84)/4 (16) 17 (73.9)/6 (26.1) 14 (56)/11 (44) 19 and 21 Sequencing Unal et al. [ 24 ] 2013 48 63.2 41 (85.4)/7 (14.6) 43 (89.6)/5 (10.4) 32 (66)/16 (34) 18, 19, 20, and 21 Sequencing Tezel et al. [ 25 ] 2017 959 60 700 (73)/259 (27) (10) 1/25 (2.6) 698 (72.8)/261(27.2) 18, 19, 20, and 21 RT-PCR Ozcelik et al. [ 26 ] 2019 703 63.3±12.5 545 (77.6)/158 (22.3) 546 (83.5)/154 (16.5) 613 (87)/90 (13) - PCR/Sequencing Bahrain Mubarak et al. [ 27 ] 2020 65 68 - - 61 (93.8)/4 (6.2) 18, 19, 20, and 21 Scorpion-ARMS technology Gulf Region Jazieh et al. [ 28 ] 2015 230 61 162 (70.4)/68 (29.5) 96 (41.7)/134 (58.2) 191 (83.4)/ 39 (16.6) 18, 19, 20, and 21 PCR Iraq Hassani et al. [ 29 ] 2014 27 - 14 (51.8)/13 (48.1) - - 18, 19, 20, and 21 Scorpion-ARMS technology Ramadhan et al. [ 30 ] 2021 138 60.1± 12.4 79 (57.2)/59 (42.8) - - 18, 19, 20, and 21 RT-PCR / PCR Lebanon Naderia et al. [ 31 ] 2015 201 65.2± 10.4 123 (61.2)/78 (38.8) 157 (78.1)/44 (21.9) 182 (90.5)/19 (9.5) 18, 19, 20, and 21 Scorpion-ARMS technology Kattan et al. [ 32 ] 2015 170 65.2 102 (59.8)/68 (40.2) 131 (76.8)/39 (23.9) 157 (92.1)/13 (7.9) 18, 19, 20, and 21 Scorpion-ARMS technology Fakhruddin et al. [ 33 ] 2014 106 62.1± 10.4 72 (67.9)/34 (32.1) 59 (55.7)/18 (17) 106 (100)/0 (0) 18, 19, 20, and 21 Scorpion-ARMS technology Levant Erea Tfayli et al. [ 34 ] 2017 210 63.4±10.8 139 (66.2)/71 (33.8) 152 (72.4)/49 (23.3) 210 (100)/0 (0) 18, 19, 20, and 21 PCR Morocco Errihani et al. [ 35 ] 2013 137 59 91 (66)/46 (44) 79 (58)/58 (42) 137 (100)/0 (0) 18, 19, 20, and 21 Sequencing Sow et al. [ 36 ] 2020 334 62 242 (72.5)/92 (27.5) 178 (53)/135 (40) 314 (94)/20 (6) 18, 19, 20, and 21 PCR/Sequencing Kaanane et al. [ 37 ] 2019 239 61.4 ± 8.9 169 (70,7)/70 (29.3) 139 (58.2)/100 (41.8) 218 (91.2)/21 (8.8) 18, 19, 20, and 21 ARMS technology and the Idylla™ system Tunisia Dhieb et al. [ 38 ] 2019 73 73 61 (83.5)/12 (16.4) 45 (76.2)/14 (23.7) 73 (100)/0 (0) - IHC Mraihi et al. [ 39 ] 2018 50 59.9 48 (96)/2 (4) 47 (94)/3 (6) 50 (100)/0 (0) 19 and 21 Sequencing and IHC Toumi et al. [ 40 ] 2018 26 58 23 (91.4)/3 (8.6) 12 (80)/3 (20) 26 (100)/0 (0) 18, 19, 20, and 21 ARMS technology Egypt Ibrahim et al. [ 41 ] 2019 2017 - - - - 18, 19, 20, and 21 PCR Algeria Lahmadi et al. [ 42 ] 2021 58 59 53 (91.4)/5 (8.6) 23 (39.6)/17 (29.3) 27 (46.5)/31 (53.5) Exon 19 Exon 21 Sequencing Results We identified 24 eligible studies: 16 (66.6%) in the ME [ 19 – 34 ] and 8 (34.4%) in NA [ 35 – 42 ]. Overall, EGFR mutations were analyzed in 6544 patients with NSCLC [3610 (55.2%) in the ME and 2934 (44.8%) in NA]. The median age is 61.7±3,8 years old, with a range of 22 [ 25 ] to 89 [ 22 ] years old. Male patients were predominant in all of the considered studies, accounting for 71.3% (3182/4462). Two studies, one from Bahrain [ 27 ] and another from Egypt [ 41 ] did not include information about male/female proportions. There were more smokers than nonsmokers, as 66.4% (2177/3276) self-reported a history of smoking; they were either former or current smokers. Four of the considered studies did not report data regarding patient smoking history [ 27 , 29 , 30 , 41 ]. The histological subtype was defined in only 20 of the included studies [ 19 – 28 , 31 – 39 , 42 ]. Specimens were obtained from FFPE blocks in 19 studies [ 19 – 25 , 30 , 31 , 33 – 42 ]. Five of the considered studies failed to report the type of specimens used [ 26 – 29 , 32 ]. Baseline characteristics of enrolled studies are summarized in Table 1 . Overall, EGFR exons 18 through 21 mutations were assessed in 19 out of the 24 considered studies in 86,1% (5635/6544) NSCLC patients: Jordan (1 study, 166 patients) [ 19 ], Iran (2 studies, 153 patients) [ 20 , 21 ],Turkey (3 studies, 1416 patients) [ 22 , 24 , 25 ], Bahrain (1 study, 65 patients) [ 27 ], the Gulf Region (1 study, 230 patients) [ 28 ], Iraq (2 study, 165 patients) [ 29 , 30 ], Lebanon (3 studies, 477 patients) [ 31 – 33 ], the Levant area (1 study, 210 patients) [ 34 ], Morocco (3 studies, 710 patients) [ 35 – 37 ], Tunisia (1 study, 26 patients) [ 40 ], and Egypt (1 study, 2017 patients) [ 41 ]. Studies from Turkey (1 study, 25 patients) [ 23 ], Tunisia (1 study, 50 patients) [ 39 ], and Algeria (1 study, 58 patients) [ 42 ] identified mutations in exons 19 and 21 in 25, 50 and 58 patients, respectively. One study from Tunisia (73 patients) and another from Turkey (703 patients) did not mention specific exons genotyped [ 38 , 26 ] (Table 1 ). In total, the prevalence of EGFR mutations among NSCLC patients in the MENA region was 17.9% (1171/6544). In the ME, the reported frequency was 17.3% (626/3610) and varied throughout the geographic region/country. In the Levant and Gulf regions, EGFR mutations were found in 15.6% (32/205) [ 34 ] and in 28.7% (66/230) [ 28 ], respectively. EGFR mutations were least common in Lebanon, accounting for 11.7% (56/477) [ 31 – 33 ]. In Turkey, the EGFR mutation rate ranged between 13% and 44% [ 22 – 26 ]. In NA, EGFR mutations were found in 18.5% (545/2934) of NSCLC patient. Tunisia highlights a wide range of EGFR mutations rates, ranging from 5.5% (4/73) to 44% (22/50) [ 38 – 40 ]. In Morocco, EGFR mutation prevalences ranged from 15.9–26.8% [ 35 – 37 ] and one study has shown a frequency of 21.9%, similar to that seen among Caucasian populations [ 36 ]. Details of EGFR mutation prevalences in the MENA region are summarized in Table 2 . Table 2 Correlation between clinicopathological features of included patients and the EGFR mutational status. Country/Region Author [reference] Frequency of EGFR mutation n (%) Male EGFR+/female EGFR+ n (%) EGFR+ADK/EGFR+NADK n (%) EGFR+ smokers/EGFR+ nonsmokers n (%) Jordan Obeidat et al. [ 19 ] 24 (14.7) 13 (11.2)/11 (22) 24 (100)/0 (0) 9 (37.5)/15 (62.5) Iran Mohammad et al. [ 20 ] 14 (28) 8 (26.7)/6 (30) 14 (100)/0 (0) 3 (9.6)/11 (37.9) Basi et al. [ 21 ] 25 (24.3) 14 (27.4)/11 (21.1) 25 (100)/0 (0) 8 (12.1)/17 (46) Turkey Calibasi et al. [ 22 ] 68 (16.6) 42 (14)/26 (23.6) 68 (100)/0 (0) 32 (13)/36 (22) Bircan et al. [ 23 ] 11 (44) 10 (47.6)/1 (25) 5 (35.7) /6 (54.5) 7 (41.1)/4 (66.6) Unal et al. [ 24 ] 18 (37.5) 13 (31.7)/5 (71.4) 13 (40.6)/5 (31.3) 13 (30,2)/5 (100) Tezel et al. [ 25 ] 160 (16.7) 64 (9.1)/96 (37.1) 142 (20.3)/18 (6.8) 2 (20)/10 (40) Ozcelik et al. [ 26 ] 92 (13) - - - Bahrain Mubarak et al. [ 27 ] 14 (21.5) - 14 (22.9)/0 (0) - Gulf Region Jazieh et al. [ 28 ] 66 (28.7) 79.1 (129)/93.5(63) 62 (32.4)/4 (10.2) - Iraq Hassani et al. [ 29 ] 8 (29.6) 4 (28.5)/4 (30.7) - - Ramadhan et al. [ 30 ] 38 (27.5) 22 (27.8)/16 (27.1) - - Lebanon Naderia et al. [ 31 ] 25 (12.4) 8 (6.5)/16 (20.5) 25 (13.7)/0 (0) 8 (5)/16 (36.3) Kattan et al. [ 32 ] 22 (12.7) 8 (7.8)/14 (20.5) - 8 (6.1)/14 (35.8) Fakhruddin et al. [ 33 ] 9 (8.8) 2 (2.7)/7 (20.5) 9 (8.4)/0 (0) 1 (1.6)/5 (27.7) Levant Erea Tfayli et al. [ 34 ] 32 (15.6) 12 (9.6)/20 (40.8) 32 (15.2)/0 (0) 14 (10.4)/16 (50) Morocco Errihani et al. [ 35 ] 29 (26.8) 7 (7.6)/22 (47.8) 29 (21.1)/0 (0) 5 (6.3)/24 (41.3) Sow et al. [ 36 ] 73 (21.9) 35 (14.5)/38 (41.3) - 23 (13)/47 (35) Kaanane et al. [ 37 ] 38 (15.9) 21 (12.4)/17 (24.2) 38 (17.4)/0 (0) 16 (11.5)/22 (22) Tunisia Dhieb et al. [ 38 ] 4 (5.5) 3 (4,9)/1 (8.3) 4 (5.4)/0 (0) 3 (6.6)/1 (7.1) Mraihi et al. [ 39 ] 22 (44) - - - Toumi et al. [ 40 ] 3 (11.5) 3 (13)/0 (0) 3 (13)/0 (0) 3 (25)/0 (0) Egypt Ibrahim et al. [ 41 ] 353 (17.5) - - - Algeria Lahmadi et al. [ 42 ] 23 (39.6) 22 (41.5)/1 (20) 9 (39.1)/6 (35.3) 14 (51.8)/9 (29) Overall, the most frequently encountered EGFR mutations were the exon 19 deletions (45.2%, 523/1157) and exon 21 substitutions (30.9%, 358/1157) of all detected mutations. Exon 20 alterations were detected in (11.2%, 112/998) including the T790 M mutation (45.5%, 51/112), which is the primary cause of acquired resistance to first-generation TKI. Exon 18 mutations were reported in 3.8% (38/998) of the EGFR -mutated patients (Table 3 ). In the ME, we report that 50.5% (270/534) of NSCLC patients were positive for exon 19 deletions versus 48.3% (253/523) in NA. Exon 19 deletion were most commonly detected in the Levant region (78.1%, 25/32) and in Morocco (67.8%, 95/140), in ME and NA, respectively. Exon 21 L858R mutation was slightly less commonly detected in ME (64.4%, 125/194) compared with NA (68.2%, 112/164). Algeria from NA and Jordan from ME had a noticeably higher exon 21 mutation detection rate at (91.3%, 21/23) and (50%, 12/24), respectively. Exon 20 and exon 18 mutations were the least commonly identified EGFR alterations in ME and NA. Exon 20 mutations were most common in Egypt (16.7%, 59/2017) and Turkey (13.4%, 33/246) in NA and the ME, respectively. Exon 18 mutations were most prevalent in Jordan (37.5%, 9/24) and Morocco (6.4%, 9/140) from ME and NA, respectively. Table 3 Distribution of EGFR Mutations among included Patients by mutation types. Country/Region Author [reference] exon 18 n (%) exon 19 n (%) exon 20 n (%) exon 21 n (%) Jordan Obeidat et al. [ 19 ] 2 (8.3) 9 (37.5) 1 (4.2) 12 (50) Iran Mohammad et al. [ 20 ] - 10 (71.4) 3 (21.4) 1 (7.2) Basi et al. [ 21 ] - 10 (40) - 15 (60) Turkey Calibasi et al. [ 22 ] 5 (1.2) 26 (38.2) 15 (22) 30 (44.1) Bircan et al. [ 23 ] - 8 (72.7) - 5 (45.4) Unal et al. [ 24 ] - 7 (38.9) 9 (50) 2 (11.1) Tezel et al. [ 25 ] 9 (5.6) 78 (48.8) 9 (5.6) 61 (38.1) Ozcelik et al. [ 26 ] - - - - Bahrain Mubarak et al. [ 27 ] 1 (7) 4 (29) 1 (7) 3 (22) Gulf Region Jazieh et al. [ 28 ] 4 (6) 36 (54.5) 1 (0.01) 26 (39.4) Iraq Hassani et al. [ 29 ] 5 (35.7) 0 (0) 1 (5.5) 2 (8.5) Ramadhan et al. [ 30 ] - 26 (65.8) 2 (5.3) 10 (26.3) Lebanon Naderia et al. [ 31 ] 1 (4) 12 (48) 2 (8) 10 (40) Kattan et al. [ 32 ] 1 (4.2) 11 (50) 1 (4.2) 9 (41.6) Fakhruddin et al. [ 33 ] - 8 (88.9) - 1 (11.1) Levant Erea Tfayli et al. [ 34 ] - 25 (78.1) - 7 (21.9) Morocco Errihani et al. [ 35 ] 2 (7) 20 (69) 1 (3) 6 (21) Sow et al. [ 36 ] 5 (6.8) 48 (65.8) 3 (4,1) 17 (23.3) Kaanane et al. [ 37 ] 2 (5.2) 27 (71) 3 (7.8) 6 (15.7) Tunisia Dhieb et al. [ 38 ] - 4 (5.5) - - Mraihi et al. [ 39 ] - - - - Toumi et al. [ 40 ] 1 (33.3) 1 (33.3) 1 (33.3) - Egypt Ibrahim et al. [ 41 ] 0 (0) 151 (42.8) 59 (16.7) 114(32.2) Algeria Lahmadi et al. [ 42 ] - 2 (8.7) - 21 (91.3) Concurrent mutations were found in 1.2% (14/1171) of the included patients. A total of 12 Turkish patients had multiple exon mutations [ 22 , 23 , 25 ]. A single Turkish study reported that 8 patients harbored concurrent mutations: 1 patient had mutations in exon 18 and exon 19, 3 patients had mutations in exon 18 and exon 21, 1 patient had mutations in exon 19 and exon 21, and 3 patients had mutations in exon 20 and exon 21 [ 22 ]. Another study reported that 2 Turkish unrelated patients harbored double EGFR exon 19 and 21 mutations, each [ 23 ]. In two Turkish cases, exon 19 deletions and exon 20 T790M point mutation were detected together in a single patient, and exon 21 L858R mutation and exon 18 G718X point mutation were found together in another patient [ 25 ]. A single Jordanian patient carried four concurrent mutations: A735T, D770_N771 insY, G719A, L861Q, and L858P [ 19 ]. One EGFR -positive Lebanese patient harbored one double mutation; an exon 19 deletion and an exon 20 T790M substitution [ 31 ]. Patients’ clinicopathological characteristics (gender, smoking history, and histology) had considerable influence on EGFR mutation prevalences. A total of 20 studies highlighted the correlation between gender and the EGFR mutational status. Overall, EGFR mutation prevalence was higher in females [females versus males: 33.4% (375/1121) versus 17% (440/2588)], particularly in a study from Turkey where 71.4% of EGFR -mutated patients were female versus 31.7% of male EGFR -mutated patients. Patient data regarding smoking history was patchy, as it lacked from 4 studies [ 27 , 29 , 30 , 41 ]. The association between patients smoking history and the EGFR mutational status was underlined in 17 studies [ 19 – 25 , 31 – 38 , 40 , 42 ]. The prevalence of EGFR mutations was higher in non-smokers [non-smokers versus current smokers: 31.1% (252/808) versus 11,1% (169/1479)]. Histology was reported in all of the considered studies. NSCLC patients with adenocarcinoma were far more likely to carry EGFR mutations [adenocarcinoma versus non-adenocarcinoma: 19% (516/2703) versus 9.7% (39/402)] in overall cases from studies that reported patients’ histological features (Table 2 ). Discussion The identification of EGFR mutations in tumors of NSCLC patients has led to personalized molecular therapies and to a paradigm shift for patients with lung cancer candidates for targeted therapy. Furthermore, it has been established that EFGR mutations are key diagnostic biomarkers in NSCLC, therefore NSCLC patients genotyping for these alterations should be a standard of care right along standard clinical examination, pathology and imaging studies [ 43 ]. Practice guidelines outlined by the National Comprehensive Cancer Network (NCCN) and the European Society for Medical Oncology (ESMO) now include EGFR genotyping to guide therapy selection [ 44 , 45 ]. Worldwide, 32.4% of NSCLCs involve EGFR mutations [ 46 ]. Previous studies have established marked variations in EGFR rates depending on different geographic regions and race/ethnicity backgrounds. The frequency of mutations was greater for EGFR mutation-positive NSCLC patients of East Asian ethnicity than those of other ethnicities (30% versus 8%) [ 47 ]. A slightly lower incidence of EGFR mutations (12%) has been identified among the Oceanic ethnicities and other insular Mediterranean patients with NSCLC [ 48 , 49 ]. A prevalence of 21.2% of EGFR mutations has been observed in the ME and African NSCLC patients [ 18 ]. Different frequencies of EGFR mutations have been found in Russia (18%), South Africa (23%), Australia (23.8%), and Latin America (26%) [ 50 – 53 ]. In our systematic review, an overall prevalence of 17.8% was identified in patients with EGFR mutation-positive NSCLC across the MENA region. The reported prevalence was slightly higher than those observed among Western populations but still lower than frequencies reported in Latino and Asian populations. In the Levant countries, a region flanked by the ME and Europe, and the Gulf region (also known as Arabian Gulf), the reported EGFR mutation frequency was 15.6% [ 34 ] and 28.7 [ 28 ], respectively. The lowest mutation frequencies were seen in Lebanon (8.8 to 12,7%) [ 31 – 33 ]. Among the Turkish population, an EGFR mutation frequency of 42.6% in NSCLC patients was identified in western Turkey [ 25 ], when Tezel et al ., showed that the mutations rate in Turkish patients with EGFR mutation-positive NSCLC was 16.7% [ 25 ]. Regional distribution of genetic mutations of lung cancer in Turkey, as reported in the (REDIGMA) study, including 25 centers, showed that mutation tests were found to be positive in 18.9% of these patients. The mutations were 69.9% EGFR , 26.3% ALK , 1.6% ROS and 2.2% PDL [ 26 ]. Our systematic review also highlights a wide range in EGFR mutation frequencies in NA populations. The overall EGFR mutation rate of NSCLC patients varied from 15.9% [ 37 ] to 26.8% [ 35 ] in Morocco. Additionally, one Moroccan study showed similar EGFR incidence rates (21%) as in patients of Caucasian descent [ 36 ]. An overall rate of 39.6% was found in EGFR mutation-positive NSCLC patients in Algeria [ 42 ]. In Tunisia, while first reports account for an EGFR mutation frequency as low as 5.5% [ 38 ], other reports show discrepant data of 11.5% and 44% [ 40 , 39 ]. The mechanism behind the differences of EGFR mutation rates across geographic regions and the race/ethnicity is still unclear. A persistent finding in the literature is the substantial variation in EGFR mutation prevalence across different geographic areas and among various race/ethnicity backgrounds [ 54 ]. Although such mutations are over-represented in more than 40% of EGFR mutation-positive NSCLC in Japan and China, they are detected in roughly 15% of EGFR mutation-positive NSCLC patients in France and Italy [ 48 ]. It has been demonstrated that ethnic genetic variation may explain these differences [ 55 , 56 ]. In the ME, the frequency of EGFR mutations was reported to range between 16.6% and 44% in the Turkish population [ 22 – 26 ]. This disproportion is a result of the genetic heterogeneity and the ethnic diversity that characterize Turkey, a country endowed with a distinguished geographic location that is between Europe and Asia and near the ME. In NA, the EGFR mutation frequency in Tunisians range from 5.5% and 44% [ 38 – 40 ]. This disparity in frequencies is mainly attributable to the ethnicities that have succeeded in Tunisia, contributing to this country’s ethnic diversity and therefore genetic heterogeneity [ 57 ]. Some studies showed that difference in EGFR mutations frequencies might be caused by exposing to indoor and/or outdoor air pollution [ 58 ]. The unique EGFR mutation spectrum in southwestern China might be related to the exposure of air pollution from local smoky coal and can reflect a specific environmental exposure [ 59 ].In Europe, a positive association between various indicators of indoor air pollution and lung cancer risk has also been reported [ 60 ]. Indoor air pollution coal burning in poorly ventilated houses, burning of wood and other solid fuels, as well as fumes from high-temperature cooking using unrefined vegetable oils such as rapeseed oil [ 61 ]. Cooking oil fumes from vegetable oils are mutagenic [ 62 , 63 ]. The International Agency for Research on Cancer classifies outdoor air pollution as an established lung carcinogen in humans [ 64 ]. In 2017, the global proportion of lung cancer deaths attributable to outdoor ambient PM2.5 5 air pollution was 14%, ranging from 4.7% in the United States to 20.5% in China [ 65 ]. PM2.5 is generally described as fine particles and is emitted by vehicles, coal-burning in power plants, industrial activity, waste burning, and other human activities. Several studies have reported a higher incidence of EGFR mutations among women in comparison to men, with figures up to 69.7%. In effect, up to 42% of females versus only 14% of males with NSCLC are expected to harbor an EGFR TK domain mutation [ 46 , 47 , 66 ]. In our review, EGFR mutation prevalence was higher in females (females versus males: 33.4% versus 17%).This is similar to data from Europe, Spain and other Asian studies which concluded that EGFR mutations were more common in women [ 67 – 69 ]. A systematic review covering 151 worldwide studies published in 2014 observed that the EGFR mutation-positive proportions were 60% and 37% in women and in men, respectively [ 48 ]. Previous studies showed that women can be more exposed to domestic radon which poses a risk for lung cancer at exposure levels approaching those for underground miners [ 70 ]. Others studies reported that domestic radon is associated with a low excess risk for lung cancer [ 71 , 72 ]. Generally, women tend to be non-smokers or light smokers compared to men, but their domestic lifestyle may expose them to certain indoor mutagen. If the occurrence of EGFR mutations is associated with potential indoor mutagens, women would have a higher mutation rate than men [ 73 ]. Furthermore, female endocrine factors such as progesterone receptor and aromatase expression could also play a role in the prevalence of the EGFR mutations [ 74 ]. Further studies are needed to investigate the role of hormones in EGFR mutation-positive NSCLC. In our review article, the prevalence of EGFR mutations was more than two folds higher in non-smokers than current smokers (31.1% versus 11.1%). In European or American studies, EGFR mutations rate in non-smokers ranged from 10–30% [ 75 ]. EGFR mutations are the most common driver gene found in never-smoker adenocarcinoma from East Asia, constituting 60-78% of this subgroup [ 76 – 78 ]. While some studies found that non-smokers were associated with a significantly higher EGFR mutations prevalence [ 79 ]. Others have reported an association between EGFR mutations and the amount and duration of cigarette smoking, with a higher incidence of mutations than that seen in never smokers [ 80 ]. Furthermore, clinical studies have suggested that the pathogenesis, clinical manifestation, and prognosis of non-smokers and smokers are different in lung cancer tumors [ 81 – 83 ]. Genetic differences have been also found in the tumors of non-smokers versus smokers [ 84 , 85 ]. The proportion of non-smokers with NSCLC is increasing. Multiple environmental factors are implicated in lung carcinogenesis including exposure to secondhand tobacco smoke, pre-existing lung diseases, and family history of cancer. Exposure to industrial substances such as toxin (ex: arsenic, nickel, chromium, tar, soot), some organic chemicals (ex: radon, asbestos), radiation exposure, air pollution, tuberculosis and environmental tobacco smoke in non-smokers also increases the risk of developing lung cancer. More thorough investigations are needed to pinpoint causal mutagens and determine the amplitude of their potential mutagenic capability. Deletions in exon 19 and the single amino acid substitution L858R in exon 21 account for approximately 85%-90% of all EGFR mutations in NSCLC, they are the most common and can predict response to EGFR TKIs and confer sensitivity to EGFR TKIs [ 86 ]. Exon 18 and 20 insertion mutations are less common and represent the remaining 10% of EGFR mutants in NSCLC. The exon 20 T790M point mutation, and most EGFR exon 20 mutations, are predictive of treatment resistance to first- and second-generation EGFR TKI therapies [ 44 , 87 ]. In our article review, the average frequency of the exon 19 and substitutions in exon 21 were 45.2% and 30.9%, respectively, among all EGFR mutations. Together, these two mutations account for up to 76.1% of identified EGFR mutations. Our findings also identified potential EGFR TKI-resistant mutations in 11.2% (112/998) among which, the T790M substitution was the most prevalent resistance mutation to first-generation TKI (45.5%, 51/112). The low frequency of exon 19 del and the point mutation L858R at exon 21 (73.4%) among the MENA population is likely the result of the heterogeneity in screening and targeted methods, potentially engendering inaccuracies in the incidence rates of otherwise common EGFR mutations. Direct sequencing was the most commonly used methodology in MENA studies (45.9%, 11/24). However, Direct sequencing has some critical limitations among which the low mutation detection sensitivity; below a certain threshold of mutant DNA, mutations could not be detected. The sensitivity of this technique is under par in representative clinical tumor samples and can yield accurate results only at higher concentrations of mutant DNA [ 88 ]. Soussa et al . showed that approximately 3% of NSCLC patients have rare mutations not identified by real-time PCR approaches [ 89 ]. The molecular characterization of peripheral blood may provide a strategy for the non-invasive serial monitoring of tumor genotypes during treatment, particularly for the EGFR T790M mutation [ 90 ]. The frequency of T790M mutation depends on the types of assays for this mutation [ 91 ]. Oxnard et al . found that 31% of NSCLC patients who are negative for T790M on central tumor genotyping have detectable T790M in plasma and recommend that tissue biopsy T790M genotyping would be substituted by liquid biopsy [ 92 ]. Other plasma assays have similarly identified unexpected false-positives for T790M in the absence of false-positives for other mutations [ 93 ]. T790M mutational analysis in liquid biopsies is currently incorporated in recent guidelines for the management of acquired TKI resistance [ 94 ]. Recent studies have confirmed that EGFR mutations from plasma can predict the clinical response to targeted therapy [ 95 , 96 ]. In the MENA region, the T790M mutation, using liquid biopsy, has been conducted only in NSCLC patients from Lebanon [ 97 ]. In addition, Next Generation Sequencing (NGS) has the ability to detect the whole exome or genome and is not restricted to specific target sequences. NGS can simultaneously analyze multiple variations, including uncommon alterations. Uncommon EGFR mutations make up a highly heterogeneous subgroup of NSCLCs that account for approximately 10%-18% of EGFR -mutated patients, and NGS testing can broaden the spectrum of alterations within the uncommon group in NSCLC patients [ 98 ]. However, Non-invasive plasma-based detection of EGFR mutations using digital PCR is still the most suitable method in clinical EGFR testing, thanks to its higher sensitivity, easier-to-understand results, low turn-around time and low cost to predicting the efficiency of EGFR -TKI [ 96 ]. This report revealed that the molecular epidemiology of EGFR mutations is heavily influenced by ethnicity and geography; EGFR mutations were found to be more frequent in patients in the MENA region than in patients of caucasian ancestry, in contrast, the rates reported among Asian populations were quite higher. Although results from this study were consistent with findings in previous reports, they should be considered cautiously due to some limitations. Firstly, a considerable portion of the considered studies have low statistical power as 8 of them included less than 100 patients. This could misrepresent the true prevalence of EGFR mutations in the region. Also, data about the stage of the tumors lacked from the majority of the included studies. Therefore, the correlation of tumor-stage and EGFR mutational status remains undefined in the region. Furthermore, the majority of the analyzed cases of the studies had adenocarcinomas, consequently, the reported influence of this particular histological subtype on EGFR mutational status could be inaccurate. Despite these limitations, a major strength of this review is the inclusion of available studies from a wide range of countries in the region. These estimates can serve as a reference for future research or policy making. Since EGFR mutation rates vary depend depending on, inter alia, ethnicity, NSCLC patients genotyping should be a standard of care in the MENA region in order to have more accurate and realistic data on EGFR mutation frequencies. Declarations Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Availability of data and materials: The data that support the findings of this study are available from original articles that have been included in this study. Data are available from the authors upon reasonable request from the corresponding author. Competing Interest: The authors declare no competing interest. Funding : This research received no external funding. Authors’ Contributions : YB, AL, and HElR have conceived the study, exploited data, coordinated and drafted the paper. TB, BElM, HElA, and HC participated in the designed. HS, HE , IAR and, TM generated data and involved in data analyses. YS, BB, KE, IL-A, MI, RT, AA, and MO have read and agreed to the published version of the manuscript. All authors have read and agreed to the published version of the manuscript. Acknowledgements: All authors thank HAMZAOUI Said for the English language revision. References Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. 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Association between plasma genotyping and outcomes of treatment with osimertinib (AZD9291) in advanced non–small-cell lung cancer. Journal of Clinical Oncology. 2016;34:28. Sacher AG, Paweletz C, Dahlberg SE, Alden RS, O’Connell A, Feeney N, et al. Prospective validation of rapid plasma genotyping for the detection of EGFR and KRAS mutations in advanced lung cancer. JAMA oncology. 2016;2:8. Shin DH, Shim HS, Kim TJ, Park HS, La Choi Y, Kim WS, et al. Provisional guideline recommendation for EGFR gene mutation testing in liquid samples of lung cancer patients: a proposal by the Korean Cardiopulmonary Pathology Study Group. Journal of pathology and translational medicine. 2019;53:3. Seki Y, Fujiwara Y, Kohno T, Yoshida K, Goto Y, Horinouchi H, et al. Circulating cell-free plasma tumour DNA shows a higher incidence of EGFR mutations in patients with extrathoracic disease progression. ESMO open. 2018;3:2. Song X, Gong J, Zhang X, Feng X, Huang H, Gao M, et al. Plasma-based early screening and monitoring of EGFR mutations in NSCLC patients by a 3-color digital PCR assay. British Journal of Cancer. 2020;123:9. Assi H, Tfayli A, Assaf N, Abou Daya S, Bidikian AH, Kawsarani D, et al. Prevalence of T790M mutation among TKI-therapy resistant Lebanese lung cancer patients based on liquid biopsy analysis: A first report from a major tertiary care center. Molecular biology reports. 2019;46:4. O’Kane GM, Bradbury PA, Feld R, Leighl NB, Liu G, Pisters KM, et al. Uncommon EGFR mutations in advanced non-small cell lung cancer. Lung Cancer. 2017;109. Additional Declarations No competing interests reported. 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. 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Militaire et d'Instruction Mohammed V, Université Mohammed V de Rabat","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hicham","middleName":"","lastName":"Souhi","suffix":""},{"id":71853089,"identity":"43d66f96-04fa-4e84-a5af-a1fb6aa935d6","order_by":10,"name":"Hanane El Ouazzani","email":"","orcid":"","institution":"Hôpital Militaire et d'Instruction Mohammed V, Université Mohammed V de Rabat","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hanane","middleName":"El","lastName":"Ouazzani","suffix":""},{"id":71853090,"identity":"bab397eb-7f8e-4195-948c-d4aafe367422","order_by":11,"name":"Ismail Abderrahmani Rhorfi","email":"","orcid":"","institution":"Hôpital Militaire et d'Instruction Mohammed V, Université Mohammed V de Rabat","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ismail","middleName":"Abderrahmani","lastName":"Rhorfi","suffix":""},{"id":71853091,"identity":"c8989395-a325-4e21-90f8-af7c166bec02","order_by":12,"name":"Ahmed Abid","email":"","orcid":"","institution":"Hôpital Militaire et d'Instruction Mohammed V, Université Mohammed V de Rabat","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ahmed","middleName":"","lastName":"Abid","suffix":""},{"id":71853092,"identity":"309adfc9-1023-40e0-abcf-4977c3a84f5a","order_by":13,"name":"Tarik Mahfoud","email":"","orcid":"","institution":"Hôpital Militaire d’Instruction Mohammed V, Université Mohammed V de Rabat","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Tarik","middleName":"","lastName":"Mahfoud","suffix":""},{"id":71853093,"identity":"575e6720-496b-49c4-a44d-d2d333ea7a26","order_by":14,"name":"Rachid Tanz","email":"","orcid":"","institution":"Hôpital Militaire d’Instruction Mohammed V, Université Mohammed V de Rabat","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Rachid","middleName":"","lastName":"Tanz","suffix":""},{"id":71853094,"identity":"b8c4afe3-cc0b-493c-baf2-849cfa778e22","order_by":15,"name":"Mohammed Ichou","email":"","orcid":"","institution":"Hôpital Militaire d’Instruction Mohammed V, Université Mohammed V de Rabat","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Mohammed","middleName":"","lastName":"Ichou","suffix":""},{"id":71853095,"identity":"6dfb35be-a604-4f73-a5c6-ccd13d3ebe98","order_by":16,"name":"Khaled Ennibi","email":"","orcid":"","institution":"Hôpital Militaire d’Instruction Mohammed V, Université Mohammed V de Rabat","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Khaled","middleName":"","lastName":"Ennibi","suffix":""},{"id":71853096,"identity":"4c7741f0-ad00-41da-98a8-b08cf50f4003","order_by":17,"name":"Bouchra Belkadi","email":"","orcid":"","institution":"Université Mohammed V de Rabat","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Bouchra","middleName":"","lastName":"Belkadi","suffix":""},{"id":71853097,"identity":"af542e66-787a-4dc3-a57d-45e464433755","order_by":18,"name":"Yassine Sekhsokh","email":"","orcid":"","institution":"Hôpital Militaire d’Instruction Mohammed V, Université Mohammed V de Rabat","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yassine","middleName":"","lastName":"Sekhsokh","suffix":""}],"badges":[],"createdAt":"2021-11-04 17:59:04","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1051050/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1051050/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":18525024,"identity":"93a5e88d-03d2-496f-bfc6-70e83cf5d17a","added_by":"auto","created_at":"2022-02-23 15:29:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":424836,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1051050/v1/9245473c-263a-46e1-8188-d577b9854ee2.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003ePrevalence and Patterns of EGFR Mutations in Non-Small Cell Lung Cancer in the Middle East and North Africa: A Systematic Review\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eLung cancer occurred in approximately 2.2 million patients, representing 22.7% of the global cancer burden. In 2020, 1.8 million patients died of lung cancer [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. It is the leading cause of cancer morbidity and mortality in men, whereas in women, it is the third most common cancer, behind breast and colorectal cancers, and the second leading cause of female cancer death. Incidence and mortality rates are roughly 2 times higher in men than in women, and the male-to-female ratio varies widely across regions, ranging from 1.2 in Northern America to 5.6 in Northern Africa [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The incidence and mortality estimates for lung cancer are 3 to 4 times higher in countries with a high Human Development Index (HDI) than in countries with a low HDI; this pattern may well change as the tobacco epidemic evolves given that 80% of smokers aged \u0026ge;15 years resided in low-income and middle-income countries in 2016 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Worldwide, the lung cancer mortality rate is foreseen to increase up to 3 million by 2035. The figures are set to double for both genders (men: from 1.1 million in 2012 to 2.1 million by 2035; and women: from 0.5 million in 2012 to 0.9 million by 2035) and the existing gender gap is expected to persist. Most prominent increases are expected in Africa and the Eastern Mediterranean region [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe Middle East (ME) and North Africa (NA) countries have witnessed a steady increase in the incidence rates of lung cancer [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In 2018, an estimated new 79887 lung cancer cases were registered in the MENA region versus 470000 new diagnoses in Europe. The age-standardized incidence rate of lung cancer in the MENA region is less than international rates, with figures varying from lowest in Yemen (4.2 per 100,000) to highest in Lebanon (23 per 100,000) [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Lung cancer incidence rates increases are more eminent among older age groups in the MENA area [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Despite recent breakthroughs in lung cancer management, the 5-year relative survival rate in the region doesn\u0026rsquo;t surpass 8%. This is largely due to late diagnoses. In the MENA countries, the highest mortality rates were reported in Morocco and Tunisia, whereas the lowest were in Yemen and Egypt [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eLung carcinomas are categorized by the size and appearance of the malignant cells and are divided into two broad categories of small cell lung cancers (SCLC) and non-small cell lung cancers (NSCLC). SCLC comprises about 10%-15% of all lung cancers. NSCLC is the most common type of lung cancer and accounts for 80-90% of all lung tumors. SCLC, commonly centrally located in the major airway, tends to grow and spread faster than NSCLC. It is estimated that 70% of SCLC patients present with locally advanced or distant metastatic disease at the time of diagnosis [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. NSCLC is a highly heterogeneous disease and is mainly divided into three major histological subtypes: adenocarcinoma, squamous cell carcinoma, and large cell carcinoma; it harbors various genetic alterations within each subtype. The identification of mutations in certain histological subtypes has led to molecular sub-classification of NSCLC and also opened therapeutic opportunities for personalized medicine based on targeted drugs [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Several mutations in NSCLC are considered actionable with available or promising targeted therapies. Some of the most common mutations for NSCLC occur in epidermal growth factor receptor (\u003cem\u003eEGFR\u003c/em\u003e) and favor cell survival, proliferation and migration, and metastasis development by increasing the activity of \u003cem\u003eEGFR\u003c/em\u003e tyrosine kinase [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. \u003cem\u003eEGFR\u003c/em\u003e tyrosine kinase inhibitors (TKIs) are established effective therapies in patients who have mutations in exons 18, 19, 20, and 21 of \u003cem\u003eEGFR\u003c/em\u003e, leading to longer progression-free survival intervals with fewer or at least different side-effects than chemotherapy [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePrevious studies have established marked variations in \u003cem\u003eEGFR\u003c/em\u003e mutation rates depending on different geographic locations and race/ethnicity backgrounds. It occurs at the rate of 10-15% in North Americans and Europeans, 15\u0026ndash;20% in African-Americans, 20-30% in various East Asian series (Chinese, Koreans, Japanese), and 20\u0026ndash;25% in patients from the Indian subcontinent [\u003cspan additionalcitationids=\"CR14 CR15 CR16\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. In ME and African populations, the \u003cem\u003eEGFR\u003c/em\u003e mutation frequency is higher than that shown in white populations but still lower than the frequency reported in Asian populations [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. In the MENA, the frequency of \u003cem\u003eEGFR\u003c/em\u003e mutations is considered among the lowest. To summarize current evidence and estimate the prevalence of \u003cem\u003eEGFR\u003c/em\u003e mutations and its association with geographic region/country and clinic-pathological features of \u003cem\u003eEGFR\u003c/em\u003e mutation-positive NSCLC patients in the Middle East (ME) and North Africa (NA), A systematic literature review was undertaken in Bahrain, Egypt, Iran, Iraq, Jordan, Kingdom of Saudi Arabia, Kuwait, Lebanon, Oman, Palestine, Qatar, Syria, Turkey, United Arab Emirates, Yemen, Algeria, Egypt, Morocco, and Tunisia.\u003c/p\u003e \u003c/div\u003e"},{"header":"Methods","content":"\u003cp\u003eWe conducted a systematic review of literature published on \u003cem\u003eEGFR\u003c/em\u003e mutation prevalence and its association with geographic region/country and clinic-pathological features in NSCLC patients in MENA region. We carried out a literature search of original articles published in six databases (PubMed, Science Direct, Web of science, Embase, Scopus, and Google scholar) from the time of inception until April 2021. Included articles have been published in English in indexed and peer-reviewed journals. Search terms included lung cancer, or lung tumor, or lung adenocarcinoma, or NSCLC, or \u003cem\u003eEGFR\u003c/em\u003e, or \u003cem\u003eEGFR\u003c/em\u003e mutation, or \u003cem\u003eEGFR\u003c/em\u003e oncogene mutations, or \u003cem\u003eEGFR\u003c/em\u003e oncogenic driver mutation, or \u003cem\u003eEGFR\u003c/em\u003e activating mutation, or \u003cem\u003eEGFR\u003c/em\u003e prevalence, or \u003cem\u003eEGFR\u003c/em\u003e rate, or \u003cem\u003eEGFR\u003c/em\u003e incidence or \u003cem\u003eEGFR\u003c/em\u003e frequency. An additional literature search was also conducted using Middle East, Middle Eastern, North Africa, North African and specific country names belonging to the considered region and any other variant names for any of the MENA countries (ex: Maghreb, Levant, Gulf, Arab). We manually checked reference lists of the included studies and relevant review articles to identify additional studies. We also searched relevant abstracts reported in the most important multi-disciplinary societies of medical oncology such as the American Society of Clinical Oncology (ASCO) meetings to identify unpublished studies.\u003c/p\u003e \u003cp\u003eOriginal articles were identified from Jordan [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], Iran [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], Turkey [\u003cspan additionalcitationids=\"CR23 CR24 CR25\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], Bahrain [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], Iraq [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], Lebanon [\u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], Morocco [\u003cspan additionalcitationids=\"CR36\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], Tunisia [\u003cspan additionalcitationids=\"CR39\" citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], Egypt [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], and Algeria [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. A multicenter prospective study from Levant (Lebanone, Syria, Palestine, Jordan, Iraq, and Egypt) [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] and a multisite retrospective study from Gulf region (Saudi Arabia, the United Arab Emirates and Qatar) were also identified and will part of our analysis [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The included studies had to meet the following criteria: the study must relate to the role of the \u003cem\u003eEGFR\u003c/em\u003e gene in NSCLC, analyze mutations in exon 18, 19, 20, and 21 or select exons of the \u003cem\u003eEGFR\u003c/em\u003e gene, and provide sufficient information on the clinico-pathological characteristics of the included NSCLC patients.\u003c/p\u003e \u003cp\u003eA total of 24 studies met the inclusion criteria. In most studies, materials were formalin-fixed paraffin-embedded (FFPE) tissues and included small biopsies such as trans-bronchial biopsy or tru-cut biopsy and also resection materials. DNA extraction was applied on tissue samples using kits that extracted DNA from paraffin blocks. Mutations in exon 18 (codon 719), exon 19 deletions, exon 20 (codons 768 and 790), and exon 21 (codons 858 and 861) were assessed in 79.1% (19/24) of the studies. A wide variety of detection methods were used to identify recognized mutations of the \u003cem\u003eEGFR\u003c/em\u003e kinase domain, from exon 18 to 21. Direct sequencing was broadly used, as it was used in the most of the studies [\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. RT-PCR-based assays, namely scorpions-amplification refractory mutation system (ARMS/Scorpion) methodology, was also widely used [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. \u003cem\u003eEGFR\u003c/em\u003e mutation analysis was carried out with quantitative PCR analysis in the study from Gulf region [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. The INFINITI system using BioFilmChip-based microarray assay was used in one study from Turkey [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Details of the study methods and population characteristics are summarized in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of the included studies.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCountry/Region\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAuthor [reference]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003cp\u003eof publication\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ecases\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMale/female\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSmokers/non smokers\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eADK/NADK\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eDetection gene\u003c/p\u003e \u003cp\u003eSite (exon)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eTest type\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJordan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eObeidatet al. [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59 \u0026plusmn; 12.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e116 (70)/50 (30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e129 (77)/37 (23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e166 (100)/0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18, 19, 20, and 21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePCR/Sequencing\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMohammad et al. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58.4 \u0026plusmn; 13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30 (60)/20 (40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e31 (42)/29 (58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e50 (100)/0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18, 19, 20, and 21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePCR/Sequencing\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBasi et al. [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e51(49.5)/52 (50.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e37 (36)/66 (64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e103 (100)/0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18, 19, 20, and 21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePCR/Sequencing\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eTurkey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCalibasi et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e409\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e299 (73.1)/110 (26.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e246 (60.1)/163 (35.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e409 (100)/0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18, 19, 20, and 21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eINFINITI method\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBircan et al. [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e65.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21(84)/4 (16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17 (73.9)/6 (26.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e14 (56)/11 (44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e19 and 21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eSequencing\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnal et al. [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e63.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e41 (85.4)/7 (14.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e43 (89.6)/5 (10.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e32 (66)/16 (34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18, 19, 20, and 21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eSequencing\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTezel et al. [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e959\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e700 (73)/259 (27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(10) 1/25 (2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e698 (72.8)/261(27.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18, 19, 20, and 21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eRT-PCR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOzcelik et al. [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e703\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e63.3\u0026plusmn;12.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e545 (77.6)/158 (22.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e546 (83.5)/154 (16.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e613 (87)/90 (13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePCR/Sequencing\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBahrain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMubarak et al. [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e61 (93.8)/4 (6.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18, 19, 20, and 21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eScorpion-ARMS technology\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGulf Region\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJazieh et al. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e162 (70.4)/68 (29.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e96 (41.7)/134 (58.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e191 (83.4)/ 39 (16.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18, 19, 20, and 21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePCR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIraq\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHassani et al. [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14 (51.8)/13 (48.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18, 19, 20, and 21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eScorpion-ARMS technology\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRamadhan et al. [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e60.1\u0026plusmn; 12.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e79 (57.2)/59 (42.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18, 19, 20, and 21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eRT-PCR / PCR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eLebanon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNaderia et al. [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e65.2\u0026plusmn; 10.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e123 (61.2)/78 (38.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e157 (78.1)/44 (21.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e182 (90.5)/19 (9.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18, 19, 20, and 21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eScorpion-ARMS technology\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKattan et al. [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e65.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e102 (59.8)/68 (40.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e131 (76.8)/39 (23.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e157 (92.1)/13 (7.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18, 19, 20, and 21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eScorpion-ARMS technology\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFakhruddin et al. [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e62.1\u0026plusmn;\u003c/p\u003e \u003cp\u003e10.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e72 (67.9)/34 (32.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e59 (55.7)/18 (17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e106 (100)/0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18, 19, 20, and 21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eScorpion-ARMS technology\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLevant Erea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTfayli et al. [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e210\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e63.4\u0026plusmn;10.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e139 (66.2)/71 (33.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e152 (72.4)/49 (23.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e210 (100)/0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18, 19, 20, and 21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePCR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eMorocco\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eErrihani et al. [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e91 (66)/46 (44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e79 (58)/58 (42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e137 (100)/0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18, 19, 20, and 21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eSequencing\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSow et al. [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e334\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e242 (72.5)/92 (27.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e178 (53)/135 (40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e314 (94)/20 (6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18, 19, 20, and 21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePCR/Sequencing\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKaanane et al. [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e239\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e61.4 \u0026plusmn; 8.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e169 (70,7)/70 (29.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e139 (58.2)/100 (41.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e218 (91.2)/21 (8.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18, 19, 20, and 21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eARMS technology and the Idylla\u0026trade; system\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eTunisia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDhieb et al. [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e61 (83.5)/12 (16.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e45 (76.2)/14 (23.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e73 (100)/0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eIHC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMraihi et al. [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e48 (96)/2 (4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e47 (94)/3 (6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e50 (100)/0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e19 and 21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eSequencing and IHC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eToumi et al. [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23 (91.4)/3 (8.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12 (80)/3 (20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e26 (100)/0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18, 19, 20, and 21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eARMS technology\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEgypt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIbrahim et al. [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18, 19, 20, and 21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePCR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlgeria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLahmadi et al. [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e53 (91.4)/5 (8.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23 (39.6)/17 (29.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e27 (46.5)/31 (53.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eExon 19\u003c/p\u003e \u003cp\u003eExon 21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eSequencing\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eWe identified 24 eligible studies: 16 (66.6%) in the ME [\u003cspan additionalcitationids=\"CR20 CR21 CR22 CR23 CR24 CR25 CR26 CR27 CR28 CR29 CR30 CR31 CR32 CR33\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] and 8 (34.4%) in NA [\u003cspan additionalcitationids=\"CR36 CR37 CR38 CR39 CR40 CR41\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Overall, \u003cem\u003eEGFR\u003c/em\u003e mutations were analyzed in 6544 patients with NSCLC [3610 (55.2%) in the ME and 2934 (44.8%) in NA]. The median age is 61.7\u0026plusmn;3,8 years old, with a range of 22 [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] to 89 [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] years old. Male patients were predominant in all of the considered studies, accounting for 71.3% (3182/4462). Two studies, one from Bahrain [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] and another from Egypt [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] did not include information about male/female proportions. There were more smokers than nonsmokers, as 66.4% (2177/3276) self-reported a history of smoking; they were either former or current smokers. Four of the considered studies did not report data regarding patient smoking history [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. The histological subtype was defined in only 20 of the included studies [\u003cspan additionalcitationids=\"CR20 CR21 CR22 CR23 CR24 CR25 CR26 CR27\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan additionalcitationids=\"CR32 CR33 CR34 CR35 CR36 CR37 CR38\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Specimens were obtained from FFPE blocks in 19 studies [\u003cspan additionalcitationids=\"CR20 CR21 CR22 CR23 CR24\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan additionalcitationids=\"CR34 CR35 CR36 CR37 CR38 CR39 CR40 CR41\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Five of the considered studies failed to report the type of specimens used [\u003cspan additionalcitationids=\"CR27 CR28\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Baseline characteristics of enrolled studies are summarized in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eOverall, \u003cem\u003eEGFR\u003c/em\u003e exons 18 through 21 mutations were assessed in 19 out of the 24 considered studies in 86,1% (5635/6544) NSCLC patients: Jordan (1 study, 166 patients) [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], Iran (2 studies, 153 patients) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e],Turkey (3 studies, 1416 patients) [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], Bahrain (1 study, 65 patients) [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], the Gulf Region (1 study, 230 patients) [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], Iraq (2 study, 165 patients) [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], Lebanon (3 studies, 477 patients) [\u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], the Levant area (1 study, 210 patients) [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], Morocco (3 studies, 710 patients) [\u003cspan additionalcitationids=\"CR36\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], Tunisia (1 study, 26 patients) [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], and Egypt (1 study, 2017 patients) [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Studies from Turkey (1 study, 25 patients) [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], Tunisia (1 study, 50 patients) [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], and Algeria (1 study, 58 patients) [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e] identified mutations in exons 19 and 21 in 25, 50 and 58 patients, respectively. One study from Tunisia (73 patients) and another from Turkey (703 patients) did not mention specific exons genotyped [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] (Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn total, the prevalence of \u003cem\u003eEGFR\u003c/em\u003e mutations among NSCLC patients in the MENA region was 17.9% (1171/6544). In the ME, the reported frequency was 17.3% (626/3610) and varied throughout the geographic region/country. In the Levant and Gulf regions, \u003cem\u003eEGFR\u003c/em\u003e mutations were found in 15.6% (32/205) [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] and in 28.7% (66/230) [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], respectively. \u003cem\u003eEGFR\u003c/em\u003e mutations were least common in Lebanon, accounting for 11.7% (56/477) [\u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. In Turkey, the \u003cem\u003eEGFR\u003c/em\u003e mutation rate ranged between 13% and 44% [\u003cspan additionalcitationids=\"CR23 CR24 CR25\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In NA, \u003cem\u003eEGFR\u003c/em\u003e mutations were found in 18.5% (545/2934) of NSCLC patient. Tunisia highlights a wide range of \u003cem\u003eEGFR\u003c/em\u003e mutations rates, ranging from 5.5% (4/73) to 44% (22/50) [\u003cspan additionalcitationids=\"CR39\" citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. In Morocco, \u003cem\u003eEGFR\u003c/em\u003e mutation prevalences ranged from 15.9\u0026ndash;26.8% [\u003cspan additionalcitationids=\"CR36\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] and one study has shown a frequency of 21.9%, similar to that seen among Caucasian populations [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Details of \u003cem\u003eEGFR\u003c/em\u003e mutation prevalences in the MENA region are summarized in Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation between clinicopathological features of included patients and the EGFR mutational status.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCountry/Region\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAuthor [reference]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequency of\u003c/p\u003e \u003cp\u003eEGFR mutation\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMale EGFR+/female EGFR+\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEGFR+ADK/EGFR+NADK\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEGFR+ smokers/EGFR+ nonsmokers\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJordan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eObeidat et al. [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (14.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (11.2)/11 (22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24 (100)/0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9 (37.5)/15 (62.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMohammad et al. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (26.7)/6 (30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14 (100)/0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3 (9.6)/11 (37.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBasi et al. [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (24.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14 (27.4)/11 (21.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25 (100)/0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8 (12.1)/17 (46)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eTurkey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCalibasi et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68 (16.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42 (14)/26 (23.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e68 (100)/0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e32 (13)/36 (22)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBircan et al. [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (47.6)/1 (25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5 (35.7) /6 (54.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7 (41.1)/4 (66.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnal et al. [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (37.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (31.7)/5 (71.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13 (40.6)/5 (31.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13 (30,2)/5 (100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTezel et al. [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e160 (16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64 (9.1)/96 (37.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e142 (20.3)/18 (6.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2 (20)/10 (40)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOzcelik et al. [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92 (13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBahrain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMubarak et al. [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (21.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14 (22.9)/0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGulf Region\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJazieh et al. 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[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (29.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (28.5)/4 (30.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRamadhan et al. 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[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (12.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (7.8)/14 (20.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8 (6.1)/14 (35.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFakhruddin et al. [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (8.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (2.7)/7 (20.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9 (8.4)/0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (1.6)/5 (27.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLevant Erea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTfayli et al. [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (15.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (9.6)/20 (40.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32 (15.2)/0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14 (10.4)/16 (50)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eMorocco\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eErrihani et al. [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (26.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (7.6)/22 (47.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29 (21.1)/0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5 (6.3)/24 (41.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSow et al. [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73 (21.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35 (14.5)/38 (41.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23 (13)/47 (35)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKaanane et al. [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38 (15.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21 (12.4)/17 (24.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38 (17.4)/0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16 (11.5)/22 (22)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eTunisia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDhieb et al. [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (5.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (4,9)/1 (8.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4 (5.4)/0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3 (6.6)/1 (7.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMraihi et al. [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eToumi et al. [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (11.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (13)/0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 (13)/0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3 (25)/0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEgypt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIbrahim et al. [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e353 (17.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlgeria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLahmadi et al. [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (39.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22 (41.5)/1 (20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9 (39.1)/6 (35.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14 (51.8)/9 (29)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eOverall, the most frequently encountered \u003cem\u003eEGFR\u003c/em\u003e mutations were the exon 19 deletions (45.2%, 523/1157) and exon 21 substitutions (30.9%, 358/1157) of all detected mutations. Exon 20 alterations were detected in (11.2%, 112/998) including the T790 M mutation (45.5%, 51/112), which is the primary cause of acquired resistance to first-generation TKI. Exon 18 mutations were reported in 3.8% (38/998) of the \u003cem\u003eEGFR\u003c/em\u003e-mutated patients (Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In the ME, we report that 50.5% (270/534) of NSCLC patients were positive for exon 19 deletions versus 48.3% (253/523) in NA. Exon 19 deletion were most commonly detected in the Levant region (78.1%, 25/32) and in Morocco (67.8%, 95/140), in ME and NA, respectively. Exon 21 L858R mutation was slightly less commonly detected in ME (64.4%, 125/194) compared with NA (68.2%, 112/164). Algeria from NA and Jordan from ME had a noticeably higher exon 21 mutation detection rate at (91.3%, 21/23) and (50%, 12/24), respectively. Exon 20 and exon 18 mutations were the least commonly identified \u003cem\u003eEGFR\u003c/em\u003e alterations in ME and NA. Exon 20 mutations were most common in Egypt (16.7%, 59/2017) and Turkey (13.4%, 33/246) in NA and the ME, respectively. Exon 18 mutations were most prevalent in Jordan (37.5%, 9/24) and Morocco (6.4%, 9/140) from ME and NA, respectively.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of EGFR Mutations among included Patients by mutation types.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCountry/Region\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAuthor [reference]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eexon 18\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eexon 19\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eexon 20\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eexon 21\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJordan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eObeidat et al. [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (8.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (37.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (4.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12 (50)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMohammad et al. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (71.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 (21.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (7.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBasi et al. [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15 (60)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eTurkey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCalibasi et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26 (38.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15 (22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30 (44.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBircan et al. [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (72.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5 (45.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnal et al. [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (38.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9 (50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2 (11.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTezel et al. [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78 (48.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9 (5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e61 (38.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOzcelik et al. [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBahrain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMubarak et al. [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3 (22)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGulf Region\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJazieh et al. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36 (54.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26 (39.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIraq\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHassani et al. [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (35.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (5.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2 (8.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRamadhan et al. [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26 (65.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (5.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10 (26.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eLebanon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNaderia et al. [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10 (40)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKattan et al. [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (4.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (4.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9 (41.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFakhruddin et al. [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (88.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (11.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLevant Erea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTfayli et al. [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25 (78.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7 (21.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eMorocco\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eErrihani et al. [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20 (69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6 (21)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSow et al. [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (6.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48 (65.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 (4,1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17 (23.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKaanane et al. [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (5.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27 (71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 (7.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6 (15.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eTunisia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDhieb et al. [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (5.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMraihi et al. [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eToumi et al. [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEgypt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIbrahim et al. [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e151 (42.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59 (16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e114(32.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlgeria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLahmadi et al. [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (8.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21 (91.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eConcurrent mutations were found in 1.2% (14/1171) of the included patients. A total of 12 Turkish patients had multiple exon mutations [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. A single Turkish study reported that 8 patients harbored concurrent mutations: 1 patient had mutations in exon 18 and exon 19, 3 patients had mutations in exon 18 and exon 21, 1 patient had mutations in exon 19 and exon 21, and 3 patients had mutations in exon 20 and exon 21 [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Another study reported that 2 Turkish unrelated patients harbored double EGFR exon 19 and 21 mutations, each [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. In two Turkish cases, exon 19 deletions and exon 20 T790M point mutation were detected together in a single patient, and exon 21 L858R mutation and exon 18 G718X point mutation were found together in another patient [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. A single Jordanian patient carried four concurrent mutations: A735T, D770_N771 insY, G719A, L861Q, and L858P [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. One \u003cem\u003eEGFR\u003c/em\u003e-positive Lebanese patient harbored one double mutation; an exon 19 deletion and an exon 20 T790M substitution [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePatients\u0026rsquo; clinicopathological characteristics (gender, smoking history, and histology) had considerable influence on \u003cem\u003eEGFR\u003c/em\u003e mutation prevalences. A total of 20 studies highlighted the correlation between gender and the \u003cem\u003eEGFR\u003c/em\u003e mutational status. Overall, \u003cem\u003eEGFR\u003c/em\u003e mutation prevalence was higher in females [females versus males: 33.4% (375/1121) versus 17% (440/2588)], particularly in a study from Turkey where 71.4% of \u003cem\u003eEGFR\u003c/em\u003e-mutated patients were female versus 31.7% of male \u003cem\u003eEGFR\u003c/em\u003e-mutated patients. Patient data regarding smoking history was patchy, as it lacked from 4 studies [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. The association between patients smoking history and the \u003cem\u003eEGFR\u003c/em\u003e mutational status was underlined in 17 studies [\u003cspan additionalcitationids=\"CR20 CR21 CR22 CR23 CR24\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan additionalcitationids=\"CR32 CR33 CR34 CR35 CR36 CR37\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. The prevalence of \u003cem\u003eEGFR\u003c/em\u003e mutations was higher in non-smokers [non-smokers versus current smokers: 31.1% (252/808) versus 11,1% (169/1479)]. Histology was reported in all of the considered studies. NSCLC patients with adenocarcinoma were far more likely to carry \u003cem\u003eEGFR\u003c/em\u003e mutations [adenocarcinoma versus non-adenocarcinoma: 19% (516/2703) versus 9.7% (39/402)] in overall cases from studies that reported patients\u0026rsquo; histological features (Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe identification of \u003cem\u003eEGFR\u003c/em\u003e mutations in tumors of NSCLC patients has led to personalized molecular therapies and to a paradigm shift for patients with lung cancer candidates for targeted therapy. Furthermore, it has been established that \u003cem\u003eEFGR\u003c/em\u003e mutations are key diagnostic biomarkers in NSCLC, therefore NSCLC patients genotyping for these alterations should be a standard of care right along standard clinical examination, pathology and imaging studies [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Practice guidelines outlined by the National Comprehensive Cancer Network (NCCN) and the European Society for Medical Oncology (ESMO) now include \u003cem\u003eEGFR\u003c/em\u003e genotyping to guide therapy selection [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWorldwide, 32.4% of NSCLCs involve \u003cem\u003eEGFR\u003c/em\u003e mutations [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Previous studies have established marked variations in \u003cem\u003eEGFR\u003c/em\u003e rates depending on different geographic regions and race/ethnicity backgrounds. The frequency of mutations was greater for \u003cem\u003eEGFR\u003c/em\u003e mutation-positive NSCLC patients of East Asian ethnicity than those of other ethnicities (30% versus 8%) [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. A slightly lower incidence of \u003cem\u003eEGFR\u003c/em\u003e mutations (12%) has been identified among the Oceanic ethnicities and other insular Mediterranean patients with NSCLC [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. A prevalence of 21.2% of \u003cem\u003eEGFR\u003c/em\u003e mutations has been observed in the ME and African NSCLC patients [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Different frequencies of \u003cem\u003eEGFR\u003c/em\u003e mutations have been found in Russia (18%), South Africa (23%), Australia (23.8%), and Latin America (26%) [\u003cspan additionalcitationids=\"CR51 CR52\" citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. In our systematic review, an overall prevalence of 17.8% was identified in patients with \u003cem\u003eEGFR\u003c/em\u003e mutation-positive NSCLC across the MENA region. The reported prevalence was slightly higher than those observed among Western populations but still lower than frequencies reported in Latino and Asian populations. In the Levant countries, a region flanked by the ME and Europe, and the Gulf region (also known as Arabian Gulf), the reported \u003cem\u003eEGFR\u003c/em\u003e mutation frequency was 15.6% [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] and 28.7 [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], respectively. The lowest mutation frequencies were seen in Lebanon (8.8 to 12,7%) [\u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Among the Turkish population, an \u003cem\u003eEGFR\u003c/em\u003e mutation frequency of 42.6% in NSCLC patients was identified in western Turkey [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], when Tezel et \u003cem\u003eal\u003c/em\u003e., showed that the mutations rate in Turkish patients with \u003cem\u003eEGFR\u003c/em\u003e mutation-positive NSCLC was 16.7% [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Regional distribution of genetic mutations of lung cancer in Turkey, as reported in the (REDIGMA) study, including 25 centers, showed that mutation tests were found to be positive in 18.9% of these patients. The mutations were 69.9% \u003cem\u003eEGFR\u003c/em\u003e, 26.3% \u003cem\u003eALK\u003c/em\u003e, 1.6%\u003cem\u003eROS\u003c/em\u003e and 2.2% \u003cem\u003ePDL\u003c/em\u003e [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Our systematic review also highlights a wide range in \u003cem\u003eEGFR\u003c/em\u003e mutation frequencies in NA populations. The overall \u003cem\u003eEGFR\u003c/em\u003e mutation rate of NSCLC patients varied from 15.9% [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] to 26.8% [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] in Morocco. Additionally, one Moroccan study showed similar \u003cem\u003eEGFR\u003c/em\u003e incidence rates (21%) as in patients of Caucasian descent [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. An overall rate of 39.6% was found in \u003cem\u003eEGFR\u003c/em\u003e mutation-positive NSCLC patients in Algeria [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. In Tunisia, while first reports account for an \u003cem\u003eEGFR\u003c/em\u003e mutation frequency as low as 5.5% [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], other reports show discrepant data of 11.5% and 44% [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe mechanism behind the differences of \u003cem\u003eEGFR\u003c/em\u003e mutation rates across geographic regions and the race/ethnicity is still unclear. A persistent finding in the literature is the substantial variation in \u003cem\u003eEGFR\u003c/em\u003e mutation prevalence across different geographic areas and among various race/ethnicity backgrounds [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Although such mutations are over-represented in more than 40% of \u003cem\u003eEGFR\u003c/em\u003e mutation-positive NSCLC in Japan and China, they are detected in roughly 15% of \u003cem\u003eEGFR\u003c/em\u003e mutation-positive NSCLC patients in France and Italy [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. It has been demonstrated that ethnic genetic variation may explain these differences [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. In the ME, the frequency of \u003cem\u003eEGFR\u003c/em\u003e mutations was reported to range between 16.6% and 44% in the Turkish population [\u003cspan additionalcitationids=\"CR23 CR24 CR25\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. This disproportion is a result of the genetic heterogeneity and the ethnic diversity that characterize Turkey, a country endowed with a distinguished geographic location that is between Europe and Asia and near the ME. In NA, the \u003cem\u003eEGFR\u003c/em\u003e mutation frequency in Tunisians range from 5.5% and 44% [\u003cspan additionalcitationids=\"CR39\" citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. This disparity in frequencies is mainly attributable to the ethnicities that have succeeded in Tunisia, contributing to this country\u0026rsquo;s ethnic diversity and therefore genetic heterogeneity [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSome studies showed that difference in \u003cem\u003eEGFR\u003c/em\u003e mutations frequencies might be caused by exposing to indoor and/or outdoor air pollution [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. The unique \u003cem\u003eEGFR\u003c/em\u003e mutation spectrum in southwestern China might be related to the exposure of air pollution from local smoky coal and can reflect a specific environmental exposure [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e].In Europe, a positive association between various indicators of indoor air pollution and lung cancer risk has also been reported [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. Indoor air pollution coal burning in poorly ventilated houses, burning of wood and other solid fuels, as well as fumes from high-temperature cooking using unrefined vegetable oils such as rapeseed oil [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. Cooking oil fumes from vegetable oils are mutagenic [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. The International Agency for Research on Cancer classifies outdoor air pollution as an established lung carcinogen in humans [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. In 2017, the global proportion of lung cancer deaths attributable to outdoor ambient PM2.5\u003csub\u003e5\u003c/sub\u003e air pollution was 14%, ranging from 4.7% in the United States to 20.5% in China [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. PM2.5 is generally described as fine particles and is emitted by vehicles, coal-burning in power plants, industrial activity, waste burning, and other human activities.\u003c/p\u003e \u003cp\u003eSeveral studies have reported a higher incidence of \u003cem\u003eEGFR\u003c/em\u003e mutations among women in comparison to men, with figures up to 69.7%. In effect, up to 42% of females versus only 14% of males with NSCLC are expected to harbor an \u003cem\u003eEGFR\u003c/em\u003e TK domain mutation [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. In our review, \u003cem\u003eEGFR\u003c/em\u003e mutation prevalence was higher in females (females versus males: 33.4% versus 17%).This is similar to data from Europe, Spain and other Asian studies which concluded that \u003cem\u003eEGFR\u003c/em\u003e mutations were more common in women [\u003cspan additionalcitationids=\"CR68\" citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. A systematic review covering 151 worldwide studies published in 2014 observed that the \u003cem\u003eEGFR\u003c/em\u003e mutation-positive proportions were 60% and 37% in women and in men, respectively [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Previous studies showed that women can be more exposed to domestic radon which poses a risk for lung cancer at exposure levels approaching those for underground miners [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e]. Others studies reported that domestic radon is associated with a low excess risk for lung cancer [\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. Generally, women tend to be non-smokers or light smokers compared to men, but their domestic lifestyle may expose them to certain indoor mutagen. If the occurrence of \u003cem\u003eEGFR\u003c/em\u003e mutations is associated with potential indoor mutagens, women would have a higher mutation rate than men [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e]. Furthermore, female endocrine factors such as progesterone receptor and aromatase expression could also play a role in the prevalence of the \u003cem\u003eEGFR\u003c/em\u003e mutations [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e]. Further studies are needed to investigate the role of hormones in \u003cem\u003eEGFR\u003c/em\u003e mutation-positive NSCLC.\u003c/p\u003e \u003cp\u003eIn our review article, the prevalence of \u003cem\u003eEGFR\u003c/em\u003e mutations was more than two folds higher in non-smokers than current smokers (31.1% versus 11.1%). In European or American studies, \u003cem\u003eEGFR\u003c/em\u003e mutations rate in non-smokers ranged from 10\u0026ndash;30% [\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e]. \u003cem\u003eEGFR\u003c/em\u003e mutations are the most common driver gene found in never-smoker adenocarcinoma from East Asia, constituting 60-78% of this subgroup [\u003cspan additionalcitationids=\"CR77\" citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e]. While some studies found that non-smokers were associated with a significantly higher \u003cem\u003eEGFR\u003c/em\u003e mutations prevalence [\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e]. Others have reported an association between \u003cem\u003eEGFR\u003c/em\u003e mutations and the amount and duration of cigarette smoking, with a higher incidence of mutations than that seen in never smokers [\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e]. Furthermore, clinical studies have suggested that the pathogenesis, clinical manifestation, and prognosis of non-smokers and smokers are different in lung cancer tumors [\u003cspan additionalcitationids=\"CR82\" citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e]. Genetic differences have been also found in the tumors of non-smokers versus smokers [\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e, \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e]. The proportion of non-smokers with NSCLC is increasing. Multiple environmental factors are implicated in lung carcinogenesis including exposure to secondhand tobacco smoke, pre-existing lung diseases, and family history of cancer. Exposure to industrial substances such as toxin (ex: arsenic, nickel, chromium, tar, soot), some organic chemicals (ex: radon, asbestos), radiation exposure, air pollution, tuberculosis and environmental tobacco smoke in non-smokers also increases the risk of developing lung cancer. More thorough investigations are needed to pinpoint causal mutagens and determine the amplitude of their potential mutagenic capability.\u003c/p\u003e \u003cp\u003eDeletions in exon 19 and the single amino acid substitution L858R in exon 21 account for approximately 85%-90% of all \u003cem\u003eEGFR\u003c/em\u003e mutations in NSCLC, they are the most common and can predict response to \u003cem\u003eEGFR\u003c/em\u003e TKIs and confer sensitivity to \u003cem\u003eEGFR\u003c/em\u003e TKIs [\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e]. Exon 18 and 20 insertion mutations are less common and represent the remaining 10% of \u003cem\u003eEGFR\u003c/em\u003e mutants in NSCLC. The exon 20 T790M point mutation, and most \u003cem\u003eEGFR\u003c/em\u003e exon 20 mutations, are predictive of treatment resistance to first- and second-generation \u003cem\u003eEGFR\u003c/em\u003e TKI therapies [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e]. In our article review, the average frequency of the exon 19 and substitutions in exon 21 were 45.2% and 30.9%, respectively, among all \u003cem\u003eEGFR\u003c/em\u003e mutations. Together, these two mutations account for up to 76.1% of identified \u003cem\u003eEGFR\u003c/em\u003e mutations. Our findings also identified potential \u003cem\u003eEGFR\u003c/em\u003e TKI-resistant mutations in 11.2% (112/998) among which, the T790M substitution was the most prevalent resistance mutation to first-generation TKI (45.5%, 51/112). The low frequency of exon 19 del and the point mutation L858R at exon 21 (73.4%) among the MENA population is likely the result of the heterogeneity in screening and targeted methods, potentially engendering inaccuracies in the incidence rates of otherwise common \u003cem\u003eEGFR\u003c/em\u003e mutations. Direct sequencing was the most commonly used methodology in MENA studies (45.9%, 11/24). However, Direct sequencing has some critical limitations among which the low mutation detection sensitivity; below a certain threshold of mutant DNA, mutations could not be detected. The sensitivity of this technique is under par in representative clinical tumor samples and can yield accurate results only at higher concentrations of mutant DNA [\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e]. Soussa et \u003cem\u003eal\u003c/em\u003e. showed that approximately 3% of NSCLC patients have rare mutations not identified by real-time PCR approaches [\u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e]. The molecular characterization of peripheral blood may provide a strategy for the non-invasive serial monitoring of tumor genotypes during treatment, particularly for the \u003cem\u003eEGFR\u003c/em\u003e T790M mutation [\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e]. The frequency of T790M mutation depends on the types of assays for this mutation [\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e]. Oxnard et \u003cem\u003eal\u003c/em\u003e. found that 31% of NSCLC patients who are negative for T790M on central tumor genotyping have detectable T790M in plasma and recommend that tissue biopsy T790M genotyping would be substituted by liquid biopsy [\u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e]. Other plasma assays have similarly identified unexpected false-positives for T790M in the absence of false-positives for other mutations [\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e]. T790M mutational analysis in liquid biopsies is currently incorporated in recent guidelines for the management of acquired TKI resistance [\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e]. Recent studies have confirmed that \u003cem\u003eEGFR\u003c/em\u003e mutations from plasma can predict the clinical response to targeted therapy [\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e, \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e]. In the MENA region, the T790M mutation, using liquid biopsy, has been conducted only in NSCLC patients from Lebanon [\u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e]. In addition, Next Generation Sequencing (NGS) has the ability to detect the whole exome or genome and is not restricted to specific target sequences. NGS can simultaneously analyze multiple variations, including uncommon alterations. Uncommon \u003cem\u003eEGFR\u003c/em\u003e mutations make up a highly heterogeneous subgroup of NSCLCs that account for approximately 10%-18% of \u003cem\u003eEGFR\u003c/em\u003e-mutated patients, and NGS testing can broaden the spectrum of alterations within the uncommon group in NSCLC patients [\u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e]. However, Non-invasive plasma-based detection of \u003cem\u003eEGFR\u003c/em\u003e mutations using digital PCR is still the most suitable method in clinical \u003cem\u003eEGFR\u003c/em\u003e testing, thanks to its higher sensitivity, easier-to-understand results, low turn-around time and low cost to predicting the efficiency of \u003cem\u003eEGFR\u003c/em\u003e-TKI [\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis report revealed that the molecular epidemiology of EGFR mutations is heavily influenced by ethnicity and geography; EGFR mutations were found to be more frequent in patients in the MENA region than in patients of caucasian ancestry, in contrast, the rates reported among Asian populations were quite higher. Although results from this study were consistent with findings in previous reports, they should be considered cautiously due to some limitations. Firstly, a considerable portion of the considered studies have low statistical power as 8 of them included less than 100 patients. This could misrepresent the true prevalence of EGFR mutations in the region. Also, data about the stage of the tumors lacked from the majority of the included studies. Therefore, the correlation of tumor-stage and EGFR mutational status remains undefined in the region. Furthermore, the majority of the analyzed cases of the studies had adenocarcinomas, consequently, the reported influence of this particular histological subtype on EGFR mutational status could be inaccurate. Despite these limitations, a major strength of this review is the inclusion of available studies from a wide range of countries in the region. These estimates can serve as a reference for future research or policy making. Since EGFR mutation rates vary depend depending on, inter alia, ethnicity, NSCLC patients genotyping should be a standard of care in the MENA region in order to have more accurate and realistic data on EGFR mutation frequencies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eNot applicable.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u003c/strong\u003e The data that support the findings of this study are available from original articles that have been included in this study. Data are available from the authors upon reasonable request from the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interest:\u0026nbsp;\u003c/strong\u003eThe authors declare no competing interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e: This research received no external funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; Contributions\u003c/strong\u003e: YB, AL, and HElR have conceived the study, exploited data, coordinated and drafted the paper. TB, BElM, HElA, and HC participated in the designed. HS,\u0026nbsp;\u003ca href=\"https://pubmed.ncbi.nlm.nih.gov/?term=Elouazzani+H\u0026cauthor_id=32550974\"\u003eHE\u003c/a\u003e,\u0026nbsp;\u003ca href=\"https://pubmed.ncbi.nlm.nih.gov/?term=Rhorfi+IA\u0026cauthor_id=28292085\"\u003eIAR\u003c/a\u003e and, TM generated data and involved in data analyses. YS, BB, KE, IL-A, MI, RT, AA, and MO have read and agreed to the published version of the manuscript. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eAll authors thank HAMZAOUI Said for the English language revision.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003e\u003cspan\u003eSung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: a cancer journal for clinicians. 2021;71:3.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eFouad H, Commar A, Hamadeh R, El-Awa F, Shen Z, Fraser C. Estimated and projected prevalence of tobacco smoking in males, Eastern Mediterranean Region, 2000-2025. 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Lung Cancer. 2017;109.\u003c/span\u003e\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","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":"Non-small cell lung cancer, EGFR mutations, MENA","lastPublishedDoi":"10.21203/rs.3.rs-1051050/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1051050/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTo summarize current evidence and estimate the prevalence of epidermal growth factor receptor (\u003cem\u003eEGFR\u003c/em\u003e) mutation frequency and its association with ethnicity and clinic-pathological features in non-small cell lung cancer (NSCLC) patients in the Middle East (ME) and North Africa (NA), a systematic literature review was undertaken. We conducted a literature search of original articles published in six databases (PubMed, Science Direct, Web of Science, Embase, Scopus, and Google scholar) from the time of inception until April 2021. Search terms included \u0026ldquo;lung cancer\u0026rdquo;, \u0026ldquo;NSCLC\u0026rdquo;, \u0026ldquo;\u003cem\u003eEGFR\u003c/em\u003e mutation\u0026rdquo;, \u0026ldquo;Middle East\u0026rdquo;, \u0026ldquo;North Africa\u0026rdquo;, and specific country names belonging to the considered region. The included studies had to meet the following criteria: the study must relate to the role of the \u003cem\u003eEGFR\u003c/em\u003e gene in NSCLC, analyze mutations in exon 18, 19, 20, and 21 or select exons of the \u003cem\u003eEGFR\u003c/em\u003e gene, and provide sufficient information on the clinic-pathological characteristics of the included NSCLC patients. A total of 24 eligible studies were included [(66.6%) in the ME and (34.4%) in NA]. Overall, 6544 patients with NSCLC were analyzed for \u003cem\u003eEGFR\u003c/em\u003e mutations [(55.1%) in the ME and (44.8%) in NA]. The overall prevalence of \u003cem\u003eEGFR\u003c/em\u003e mutations was 17.9%. In the ME, the reported frequency was 17.3%, whereas in NA, the prevalence of \u003cem\u003eEGFR\u003c/em\u003e mutations was 18.5%. The most frequently encountered mutations were the exon 19 deletions (45.2%) and exon 21 substitutions (30.9%). Exon 20 alterations were detected in 11.2%, of which, the T790M resistance mutation was the most prevalent (45.5%). Exon 18 mutations were reported in 3.8%. In the ME, 50.5% of NSCLC patients were positive for exon 19 deletions versus 48.3% in NA. Exon 21 mutations were slightly more commonly detected in the ME (36.3%) than NA (31.3%). There was 1.2% of patients that had concurrent \u003cem\u003eEGFR\u003c/em\u003e mutations. Overall, \u003cem\u003eEGFR\u003c/em\u003e mutations prevalence was higher in females, non-smokers, and patients with adenocarcinoma. Our systematic literature review concurs that \u003cem\u003eEGFR\u003c/em\u003e mutation prevalence among MENA populations is slightly higher than that seen in NSCLC patients of Caucasian ethnicity but is lower than that identified in Asian NSCLC patients. The distribution of these mutations varies significantly throughout the MENA region.\u003c/p\u003e","manuscriptTitle":"Prevalence and Patterns of EGFR Mutations in Non-Small Cell Lung Cancer in the Middle East and North Africa: A Systematic Review","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-12-29 15:08:48","doi":"10.21203/rs.3.rs-1051050/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":"ac2373c9-773b-4e6c-88b8-7b62e5b4e09d","owner":[],"postedDate":"December 29th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":9343480,"name":"Cancer Biology"},{"id":9343481,"name":"Oncology"}],"tags":[],"updatedAt":"2022-02-23T15:29:09+00:00","versionOfRecord":[],"versionCreatedAt":"2021-12-29 15:08:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1051050","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1051050","identity":"rs-1051050","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}