Esophageal Cancer Staging in Malawi: The Feasibility of Chest Radiography and Abdominal Ultrasound for Initial Evaluation

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Williams, Gift Mulima, Bongani Kaimila, Katherine Drew Marapese, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6994944/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 27 Nov, 2025 Read the published version in BMC Gastroenterology → Version 1 posted 10 You are reading this latest preprint version Abstract Background Esophageal cancer (EC) is the third leading cause of cancer-related morbidity and mortality in Malawi. Given limited imaging capacity and high costs, staging is not routinely performed. One proposed staging algorithm is to first evaluate for metastatic disease using low-cost chest radiography (CXR) and abdominal ultrasound (US) followed by confirmatory computerized tomography (CT) of the chest and abdomen if no metastases identified on initial screening. The feasibility of this approach is unknown for EC in sub–Saharan Africa and was studied in the context of a larger prospective observational cohort study of EC in Malawi. Methods From 2021 to 2022, EC patients at Kamuzu Central Hospital in Lilongwe, Malawi enrolled in the Treatment Outcomes of Esophageal Cancer in Malawi (TOEC-M) study were recruited. Participants were scheduled for a CXR, US, and CT scan as part of this sub-study. Participant characteristics, completion rates, imaging findings, and barriers to completion were documented. For participants undergoing all three imaging studies, sensitivity and specificity were calculated. Results Of 150 patients in TOEC-M, 67 (44.7%) enrolled in this sub-study. Mean age was 55.4 years and 50.8% were males. The majority had mid-esophageal (38 [56.7%]) squamous cell carcinomas (54 [80.6%]). CXR was completed in 54 (80.6%) study participants, US in 43 (64.2%), CT chest in 29 (43.3%), and CT abdomen in 24 (35.8%). Sixteen (23.9%) completed all studies and 4 (6.0%) did not undergo any imaging. Of the 63 patients that were imaged, metastatic disease was identified in 18 (28.6%) by any modality. Positive findings were identified on 3 (5.6%) CXRs, 4 (9.3%) US, and 18 (62.1%) CTs, most frequently liver masses followed by lung nodules and adenopathy. Barriers to imaging completion included participant functional status and scanner availability. Conclusions As access to EC treatment modalities expands, feasible and accurate staging will become increasingly important to guide clinical management. Our results suggest that CXR and US may serve as useful initial tools for assessing metastatic disease. In patients not medically fit for oncologic treatment, positive findings on CXR and US may allow CT to be deferred. Barriers to implementation of a pragmatic stepwise staging algorithm identified in this study can inform future research and care for patients with EC in similar resource-limited settings. Esophageal cancer staging low- and middle-income countries Figures Figure 1 Background Esophageal cancer (EC) is a leading cause of global cancer-related morbidity and mortality. EC is currently the eighth most commonly diagnosed and the sixth most common cause of cancer death worldwide [ 1 ]. The incidence of EC varies widely across geographic regions with an estimated 80% of cases and deaths occurring in low- and middle-income countries (LMIC) [ 2 ]. Eastern Africa, where esophageal squamous cell carcinoma (ESCC) is the predominant histology, has been identified as one of several distinct regions with a high burden of EC incidence and mortality [ 3 , 4 ]. Malawi, a country of 21.1 million population, has the third highest EC mortality rate worldwide at 19.5 male patients per 100,000 [ 1 ]. Despite this geographic preponderance, there remains a critical knowledge gap regarding the optimal method of diagnosis, staging, and treatment of EC in this region. In this setting, more than 90% of patients present with advanced disease and there is limited access to treatment with curative intent [ 5 ]. In Malawi, treatment options are currently palliative, consisting of endoscopic stent placement and chemotherapy. However, as treatment options expand in Malawi and other resource-limited settings, accurate staging will become increasingly important for appropriate triage, optimal resource use, and to guide evidence-based care. Additionally, the presenting stage of esophageal cancer in Malawi has not previously been described. In recognition of these gaps, there has been a global call to action for the study of EC in eastern and southern Africa by the African Esophageal Cancer Consortium (AfrECC) [ 6 ]. AfrECC was founded to advance research, training, and collaborative efforts focused on esophageal cancer control in eastern and southern Africa [ 6 , 7 ]. UNC Project-Malawi was a founding institutional member of the consortium. Aligned with this agenda, this study aims to evaluate disease stage among patients with esophageal cancer presenting to a national cancer referral hospital in Malawi, and the diagnostic performance of low-cost diagnostic imaging for staging during initial work up. The study also aims to evaluate barriers to completing staging workup and the feasibility of obtaining chest radiograph (CXR), abdominal ultrasound (US), and computed tomography (CT) scans. These insights will help address key knowledge and implementation gaps to support evidence-based clinical practice and inform healthy policy. ESCC is staged using the tumor-node-metastasis (TNM) classification system [ 8 ]. Leading guidelines from high-income countries, including those issued by the National Comprehensive Cancer Network (NCCN) and the Society of Thoracic Surgeons [ 9 ], recommend initial staging of esophageal cancer using contrast-enhanced CT of the chest and abdomen; pelvic CT as clinically indicated; FDG-PET/CT if no known metastatic disease; and endoscopic ultrasound (EUS) [ 9 ]. The NCCN Harmonized Guidelines™ for Sub-Saharan Africa for Esophageal and Esophagogastric Junction Cancers, endorsed by the Government of Malawi, recommend a resource-adapted approach for staging that includes CT of the chest and abdomen, with pelvic CT as clinically indicated. This recommendation is categorized within the guidelines as a “generally available standard of care.” However, in Malawi and many other resource-limited settings, access to CT scans is often limited by cost, availability, and infrastructure constraints—and access to advanced modalities such as PET/CT and EUS is virtually nonexistent. Given the challenges associated with cancer staging in LMICs, an alternative classification system has been proposed for = resource-limited settings by the Union for International Cancer Control. The Essential TNM system utilizes the same classification components of the standard TNM system but instead begins with assessment of distant metastasis before further diagnostic assessments [ 10 ]. This sequence represents a more pragmatic approach in resource-limiting settings, where identifying metastatic disease upfront can obviate the need for further testing. While not previously tailored to esophageal cancer, these principles informed the development of our proposed staging algorithm (Fig. 1). We hypothesize that CXR and abdominal US with confirmatory CT of the chest and abdomen can be utilized as a low-cost, pragmatic approach for initial assessment for metastatic disease in ESCC in Malawi. A staging algorithm has the potential to guide clinical decision making and optimize resource utilization. We hypothesize that a sequential staging approach using CXR and US, with CT of the chest/abdomen only if initial evaluates are negative can be utilized as a low cost, pragmatic approach Methods Study Design and Setting This study was performed as part of a larger prospective observational cohort study Treatment Outcomes of Esophageal Cancer in Malawi (TOEC-M) (NCT05177393). The parent study was retrospectively registered with the ClinicalTrials.gov database on December 15, 2021. Patients with either a pathologically or endoscopically confirmed diagnosis of EC were prospectively enrolled from Kamuzu Central Hospital (KCH), an 800-bed tertiary care hospital in Lilongwe, Malawi that serves 8 districts in the central region of Malawi with a catchment area of approximately 6 million people. Study Participants and Data Collection Methods of recruitment, ascertainment, and informed consent are previously described elsewhere [ 7 ]. Inclusion criteria were patients over 18 years of age with either a pathologically confirmed or presumptive diagnosis of EC based on barium swallow or endoscopy and clinical stability to independently present to a radiology facility. Patients that were pregnant, had another known cancer diagnosis, or were already receiving EC treatment were excluded. Informed consent was taken for both the parent study and the sub-study. Costs of imaging studies were covered by the study. Baseline socio-demographic and clinical information was collected upon enrollment, including length of symptoms, endoscopic findings, and histology if available. Each participant was scheduled for CXR, abdominal US, and CT of the chest and abdomen to evaluate for evidence of metastatic disease. During the course of the study, the CT facilities at KCH were intermittently not available, leading to an effort to provide transportation to private facilities using available funds. Imaging studies were interpreted by trained radiologists at KCH with support from the University of North Carolina. Positive findings were defined as the presence of pulmonary nodules, pleural effusions, hepatic masses, or ascites. The aim of our study was to determine to examine sensitivity and specificity of CXR/US to set the stage for testing and evaluation of a pragmatic algorithm. The long term goal of this study was to inform our understanding of the feasibility and limitations of sequential, algorithm staging approaches for EC. Statistical Analysis Descriptive statistics were used to describe the baseline characteristics of our patient population, compliance rates with each imaging study, and imaging study results. Differences in characteristics between eligible participants that did and did not enroll into the sub-study were compared using Pearson’s Chi-squared test. Sensitivity and specificity of CXR and US for detecting distant metastasis were calculated by generating a 2x2 table. CT scan was considered the ‘gold standard’ as PET/CT is unavailable in this setting. Barriers to completion of imaging studies were identified during weekly meetings with the research team. Results Of 150 total eligible patients in TOEC-M, 67 (44.7%) enrolled in the staging sub-study. Mean age was 55.4 years and 50.8% were males. Participants were largely never smokers (70.2%) and had no history of alcohol abuse (70.2%). Only 6 (9.0%) patients were insured. There were no significant differences between characteristics of patients enrolled and not enrolled into the sub-study (Table 1 ). Table 1 Demographics of TOEC-M eligible patients by enrollment in the imaging sub-study Enrolled (N = 67) Not Enrolled (N = 83) Total (N = 150) p Age (years), mean (SD) 55.4 (12.6) 54.8 (3.6) 55.1 (13.1) 0.79 Male, n (%) 34 (50.8) 46 (55.4) 80 (53.3) 0.57 HIV positive, n (%) 7 (10.5) 12 (14.5) 19 (12.7) 0.13 Smoking history, n (%) 0.92 Current 4 (6.0) 6 (7.2) 10 (6.7) Former 16 (23.9) 18 (21.7) 34 (22.7) Never 47 (70.2) 59. (71.1) 106 (70.7) Alcohol history, n (%) 0.78 Current 3 (4.5) 6 (7.3) 9 (6.0) Former 17 (25.4) 19 (23.2) 36 (24.2) Never 47 (70.2) 57 (69.5) 104 (69.8) Highest level of education, n (%) 0.69 None 35 (52.2) 44 (53.0) 79 (52.7) Primary 21 (31.3) 20 (24.1) 41 (27.3) Secondary 9 (13.4) 16 (19.3) 25 (16.7) Technical college or University 2 (3.0) 3 (3.6) 5 (3.3) Income (kwacha/USD) per year, median (IQR) 1350000/777 (500000/288- 2000000/1152) 1250000/720 (600000/345- 2500000/1439) 1350000/777 (500000/288- 2000000/1132) 0.75 Insured, n (%) 6 (9.0) 4 (4.9) 10 (6.8) 0.35 The majority of participants had mid-esophageal tumors (38 [56.7%]). Endoscopic biopsies were obtained in 60 (89.6%) patients, of which squamous cell carcinoma was the most prevalent histology (54 [90%]). The median duration of symptoms was 5 months (IQR 3–6) (Table 2 ). CXR was completed in n = 54 (80.6%), right upper quadrant US in n = 43 (64.2%), CT chest in n = 29 (43.3%), and CT abdomen in n = 24 (35.8%). All studies were completed in 16 (23.9%) and only 4 (6.0%) did not undergo any imaging (Table 3 ). Table 2 Tumor characteristics of TOEC-M eligible patients by enrollment in the imaging sub-study Enrolled (N = 67) Not Enrolled (N = 83) Total (N = 150) p Tumor location, n (%) 0.17 Upper 8 (11.9) 19 (22.9) 27 (18.0) Middle 38 (56.7) 34 (41.0) 72 (48.0) Distal 8 (11.9) 9 (10.8) 17 (11.3) Missing 13 (19.4) 21 (25.3) 34 (22.7) Tumor length (cm), median (IQR) 7 (5–8) 6 (5–7) 6 (5–8) 0.31 Mode of diagnosis, n (%) 0.17 Biopsy 60 (89.6) 66 (79.5) 126 (84.0) Endoscopy without biopsy 7 (10.5) 14 (16.9) 21 (14.0) Endoscopy with non-confirmatory biopsy 0 (0) 3 (3.6) 3 (2.0) Biopsy results, n (%) 0.28 Squamous cell carcinoma 54 (80.6) 56 (67.5) 110 (73.3) Adenocarcinoma 0 (0) 1 (1.2) 1 (0.7) Other malignancy 1 (1.5) 3 (3.6) 4 (2.7) Dysplasia 1 (1.5) 3 (3.6) 4 (2.7) Benign 2 (3.0) 4 (4.8) 6 (4.0) Non-diagnostic 2 (3.0) 0 (0) 2 (1.3) Duration of symptoms (months), median (IQR) 5 (3–6) 4 (3–6) 4 (3–6) 0.25 Table 3 Imaging completion rates (N = 67) Completed, n (%) None 4 (6.0) Chest x-ray 54 (80.6) Abdominal ultrasound 43 (64.2) CT chest 29 (43.3) CT abdomen 24 (35.8) Chest X-ray, Abdominal US, and CT chest and abdomen 16 (23.9) Of the 63 patients that were imaged, metastatic disease was identified in 18 (28.6%) by any modality. Positive findings consistent with metastasis were identified on 3 (5.6%) CXRs, 4 (9.3%) US, and 18 (62.1%) CTs. The most frequent sites of metastasis were liver followed by lung and distant lymph nodes (Table 4 ). None of the participants with positive findings on CXR and/or US underwent confirmatory CT precluding our ability to calculate false positive rate. Table 4 Imaging Findings* CXR (n = 54) US (n = 43) CT (n = 29) Metastatic disease, n (%) 3 (5.6) 4 (9.3) 18 (62.1) Liver - 4 (9.3) 5 (17.2) Lungs 2 (3.7) - 3 (10.3) Adenopathy 0 (0) 0 (0) 3 (10.3) Bones 0 (0) - 2 (6.9) Other 0 (0) 0 (0) 5 (17.2) Missing 1 (1.9) 0 (0) 0 (0) *More than one imaging test may have been completed in each participant Barriers to imaging completion included symptom burden and facility availability including malfunctioning scanners and distance to private facilities. Notably, in the group of 16 patients that underwent all 4 imaging modalities (Table 5 ), CXR and/or US did not detect any metastases, including among the 7 patients who were found to have metastasis on CT, leading to sensitivity of 0% in this small sample. CT chest/abdomen also did not show metastases in n = 9, leading to a specificity of 100% of CXR/US and a negative predictive value of 56.3%. Table 5 Rates of imaging detection of metastatic disease (n = 16) in patients undergoing all 4 imaging modalities CT positive CT negative CXR or US positive 0 0 CXR and US negative 7 9 Discussion We conducted a prospective observational cohort study examining the feasibility of using low-cost imaging modalities to stage the EC population in Malawi, a setting where staging of EC is not routinely performed. Of our potential participant pool of 150 patients, 67 (44.7%) patients were eligible and enrolled to receive imaging for staging. We found that the majority of patients had mid-esophageal squamous cell carcinomas and that 18 (28.6%) had evidence of metastatic disease. CXR and abdominal US were feasible to obtain and interpret as a low-cost solution for initial evaluation for metastases in resource-limited environments. As the sample size was limited, and we were unable to calculate the sensitivity of these imaging studies alone, they did show excellent specificity and may be used to defer CT scan if positive. Previous studies in high-income countries have shown the sensitivity of abdominal US and CXR in detecting metastatic disease in EC patients to be 65% and 68%, respectively [ 11 ]. Given a presumably higher prevalence of advanced disease in our East African population, the sensitivity of these studies is expected to be higher. While not yet validated, CXR and US have been previously used in resource-limited settings to evaluate the presence of metastatic disease. For example, Tenwek hospital in Kenya used CXR and abdominal US to exclude metastatic disease prior to esophagectomy [ 12 ]. As access to curative treatment options expands across this region, an algorithm for pre-treatment evaluation may be useful to guide resource allocation and clinical management, particularly when cost of cross-sectional imaging studies remains prohibitive to most patients. Our study did have several limitations largely related to our small sample size and limited completion rates. We faced several obstacles to imaging completion due to availability of radiology facilities, transportation, and the frailty of our population. Coordination with radiology was also a key barrier to completion given the limited availability of equipment. While it was our hope that all three studies could be performed on the same day to enhance completion rates, there was often discontinuity in this workflow leading to long patient wait times and difficulty rescheduling. Symptom burden (as patients were very ill due to obstructing esophageal tumors) often impeded patients from withstanding multi-day tests. Conclusions In Malawi and similar resource-limited settings, CXR and abdominal US are feasible, low-cost modalities as an initial evaluation for metastatic disease in EC patients. However, given barriers to completion of multiple imaging studies, focusing on obtaining or lowering costs of CT scans should be prioritized, particularly in patients medically fit for further treatment, e.g. chemotherapy or radiotherapy. For patients with borderline fitness for treatment, CXR and US can be used for initial staging as positive studies could potentially defer need for CT scan. In those too unwell for treatment, imaging could be deferred altogether. Future work on cost-effectiveness and applicability outside of a hospital-based population will be required prior to implementation. Abbreviations EC Esophageal cancer ESCC Esophageal squamous cell carcinoma CT Computed tomography CXR Chest radiography KCH Kamuzu Central Hospital LMIC Low- and middle-income countries PET Positron emission tomography TNM Tumor-node-metastasis TOEC-M Treatment Outcomes of Esophageal Cancer in Malawi US Ultrasound Declarations Ethics approval and consent to participate The Institutional Review Boards of University of North Carolina and the National Health Sciences Research Committee of Malawi approved the study protocols. Informed consent was obtained from all subjects. Consent for publication Not Applicable. Availability of data and materials The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Funding UJMT Fogarty Global Health Fellowship Program (NIH Fogarty International Center Grant #D43TW009340). Competing interests The authors declare no conflict of interest. Authors’ contributions GM, BK, KM, AS, AE, NN, CK, GB, KM, JG, AC, and GNM collected and analyzed data. BW, KD, and GNM were major contributors in writing the manuscript. All authors approved the final manuscript. References Morgan E, Soerjomataram I, Rumgay H, Coleman HG, Thrift AP, Vignat J, et al. The Global Landscape of Esophageal Squamous Cell Carcinoma and Esophageal Adenocarcinoma Incidence and Mortality in 2020 and Projections to 2040: New Estimates From GLOBOCAN 2020. Gastroenterology. 2022;163(3):649–e6582. Malekzadeh R, Abnet CC, Dawsey SM. Oesophageal cancer: A tale of two malignancies. In: Wild CP, Weiderpass E, Stewart BW, editors. World Cancer Report: Cancer Research for Cancer Prevention. Lyon, France: International Agency for Research on Cancer; 2020. Abnet CC, Arnold M, Wei W-Q. Epidemiology of Esophageal Squamous Cell Carcinoma. Gastroenterology. 2018;154(2):360–73. Cheng ML, Zhang L, Borok M, Chokunonga E, Dzamamala C, Korir A, et al. 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Varghese TK Jr, Hofstetter WL, Rizk NP, Low DE, Darling GE, Watson TJ, et al. The Society of Thoracic Surgeons Guidelines on the Diagnosis and Staging of Patients with Esophageal Cancer. Ann Thorac Surg. 2013;96(1):346–56. Piñeros M, Parkin DM, Ward K, Chokunonga E, Ervik M, Farrugia H, et al. Essential TNM: a registry tool to reduce gaps in cancer staging information. Lancet Oncol. 2019;20(2):e103–11. Van Vliet EP, Steyerberg EW, Eijkemans MJ, Kuipers EJ, Siersema PD. Detection of distant metastases in patients with oesophageal or gastric cardia cancer: a diagnostic decision analysis. Br J Cancer. 2007;97(7):868–76. Mwachiro M, Mitchell E, Topazian HM, White R. Esophagectomy in Patients with Human Immunodeficiency Virus and Acquired Immune Deficiency Syndrome: A Viable Option. Semin Thorac Cardiovasc Surg. 2018;30(1):116–21. Additional Declarations No competing interests reported. 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Salima","email":"","orcid":"","institution":"Kamuzu Central Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ande","middleName":"W.","lastName":"Salima","suffix":""},{"id":493162621,"identity":"17bfee4f-c9fc-4603-b465-7449d4e93a3f","order_by":5,"name":"Austin Evans","email":"","orcid":"","institution":"University of North Carolina","correspondingAuthor":false,"prefix":"","firstName":"Austin","middleName":"","lastName":"Evans","suffix":""},{"id":493162622,"identity":"9a925c6d-c7b3-4758-8e24-1fe852ea786d","order_by":6,"name":"Natasha Ngwira","email":"","orcid":"","institution":"Kamuzu Central Hospital","correspondingAuthor":false,"prefix":"","firstName":"Natasha","middleName":"","lastName":"Ngwira","suffix":""},{"id":493162623,"identity":"1fb56a9c-0a6c-43b4-bb58-5c4919677782","order_by":7,"name":"Chifundo Kajombo","email":"","orcid":"","institution":"Kamuzu Central Hospital","correspondingAuthor":false,"prefix":"","firstName":"Chifundo","middleName":"","lastName":"Kajombo","suffix":""},{"id":493162624,"identity":"1cce8518-1384-4075-a0f5-73566602c267","order_by":8,"name":"Jared Gallaher","email":"","orcid":"","institution":"University of North Carolina","correspondingAuthor":false,"prefix":"","firstName":"Jared","middleName":"","lastName":"Gallaher","suffix":""},{"id":493162625,"identity":"aec141ac-db82-4a8a-ae36-2875e7a662a7","order_by":9,"name":"Anthony Charles","email":"","orcid":"","institution":"University of Vermont","correspondingAuthor":false,"prefix":"","firstName":"Anthony","middleName":"","lastName":"Charles","suffix":""},{"id":493162626,"identity":"bb654a05-f76f-4d2c-a586-97032207c79f","order_by":10,"name":"Katrina McGinty","email":"","orcid":"","institution":"Novant Health","correspondingAuthor":false,"prefix":"","firstName":"Katrina","middleName":"","lastName":"McGinty","suffix":""},{"id":493162627,"identity":"b2ed87a1-3339-445d-9ab4-3d85d5e4e202","order_by":11,"name":"Geoffrey Buckle","email":"","orcid":"","institution":"University of California San Francisco (UCSF)","correspondingAuthor":false,"prefix":"","firstName":"Geoffrey","middleName":"","lastName":"Buckle","suffix":""},{"id":493162628,"identity":"6f904c1e-cb75-4002-abde-8098b2dffabd","order_by":12,"name":"Gita N. Mody","email":"","orcid":"","institution":"University of North Carolina","correspondingAuthor":false,"prefix":"","firstName":"Gita","middleName":"N.","lastName":"Mody","suffix":""}],"badges":[],"createdAt":"2025-06-28 02:08:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6994944/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6994944/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12876-025-04378-w","type":"published","date":"2025-11-27T15:58:21+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":88306589,"identity":"835a09c4-beb5-4cdb-8799-73ef7d34d20a","added_by":"auto","created_at":"2025-08-05 06:06:29","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":232466,"visible":true,"origin":"","legend":"\u003cp\u003eProposed algorithm for staging esophageal cancer patients in Malawi.\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6994944/v1/d8b0b28afc1a905048a758a1.jpg"},{"id":97178586,"identity":"6aca7b37-1359-4a03-8588-50d9ae921ca6","added_by":"auto","created_at":"2025-12-01 16:11:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":965985,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6994944/v1/fd0b1759-3649-4e6a-a819-931ee5961ad0.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Esophageal Cancer Staging in Malawi: The Feasibility of Chest Radiography and Abdominal Ultrasound for Initial Evaluation","fulltext":[{"header":"Background","content":"\u003cp\u003eEsophageal cancer (EC) is a leading cause of global cancer-related morbidity and mortality. EC is currently the eighth most commonly diagnosed and the sixth most common cause of cancer death worldwide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The incidence of EC varies widely across geographic regions with an estimated 80% of cases and deaths occurring in low- and middle-income countries (LMIC) [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Eastern Africa, where esophageal squamous cell carcinoma (ESCC) is the predominant histology, has been identified as one of several distinct regions with a high burden of EC incidence and mortality [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Malawi, a country of 21.1\u0026nbsp;million population, has the third highest EC mortality rate worldwide at 19.5 male patients per 100,000 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDespite this geographic preponderance, there remains a critical knowledge gap regarding the optimal method of diagnosis, staging, and treatment of EC in this region. In this setting, more than 90% of patients present with advanced disease and there is limited access to treatment with curative intent [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In Malawi, treatment options are currently palliative, consisting of endoscopic stent placement and chemotherapy. However, as treatment options expand in Malawi and other resource-limited settings, accurate staging will become increasingly important for appropriate triage, optimal resource use, and to guide evidence-based care. Additionally, the presenting stage of esophageal cancer in Malawi has not previously been described.\u003c/p\u003e\u003cp\u003eIn recognition of these gaps, there has been a global call to action for the study of EC in eastern and southern Africa by the African Esophageal Cancer Consortium (AfrECC) [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. AfrECC was founded to advance research, training, and collaborative efforts focused on esophageal cancer control in eastern and southern Africa [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. UNC Project-Malawi was a founding institutional member of the consortium. Aligned with this agenda, this study aims to evaluate disease stage among patients with esophageal cancer presenting to a national cancer referral hospital in Malawi, and the diagnostic performance of low-cost diagnostic imaging for staging during initial work up. The study also aims to evaluate barriers to completing staging workup and the feasibility of obtaining chest radiograph (CXR), abdominal ultrasound (US), and computed tomography (CT) scans. These insights will help address key knowledge and implementation gaps to support evidence-based clinical practice and inform healthy policy.\u003c/p\u003e\u003cp\u003eESCC is staged using the tumor-node-metastasis (TNM) classification system [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Leading guidelines from high-income countries, including those issued by the National Comprehensive Cancer Network (NCCN) and the Society of Thoracic Surgeons [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], recommend initial staging of esophageal cancer using contrast-enhanced CT of the chest and abdomen; pelvic CT as clinically indicated; FDG-PET/CT if no known metastatic disease; and endoscopic ultrasound (EUS) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The NCCN Harmonized Guidelines\u0026trade; for Sub-Saharan Africa for Esophageal and Esophagogastric Junction Cancers, endorsed by the Government of Malawi, recommend a resource-adapted approach for staging that includes CT of the chest and abdomen, with pelvic CT as clinically indicated. This recommendation is categorized within the guidelines as a \u0026ldquo;generally available standard of care.\u0026rdquo; However, in Malawi and many other resource-limited settings, access to CT scans is often limited by cost, availability, and infrastructure constraints\u0026mdash;and access to advanced modalities such as PET/CT and EUS is virtually nonexistent.\u003c/p\u003e\u003cp\u003eGiven the challenges associated with cancer staging in LMICs, an alternative classification system has been proposed for =\u0026thinsp;resource-limited settings by the Union for International Cancer Control. The Essential TNM system utilizes the same classification components of the standard TNM system but instead begins with assessment of distant metastasis before further diagnostic assessments [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. This sequence represents a more pragmatic approach in resource-limiting settings, where identifying metastatic disease upfront can obviate the need for further testing. While not previously tailored to esophageal cancer, these principles informed the development of our proposed staging algorithm (Fig.\u0026nbsp;1). We hypothesize that CXR and abdominal US with confirmatory CT of the chest and abdomen can be utilized as a low-cost, pragmatic approach for initial assessment for metastatic disease in ESCC in Malawi. A staging algorithm has the potential to guide clinical decision making and optimize resource utilization. We hypothesize that a sequential staging approach using CXR and US, with CT of the chest/abdomen only if initial evaluates are negative can be utilized as a low cost, pragmatic approach\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cb\u003eStudy Design and Setting\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis study was performed as part of a larger prospective observational cohort study Treatment Outcomes of Esophageal Cancer in Malawi (TOEC-M) (NCT05177393). The parent study was retrospectively registered with the ClinicalTrials.gov database on December 15, 2021. Patients with either a pathologically or endoscopically confirmed diagnosis of EC were prospectively enrolled from Kamuzu Central Hospital (KCH), an 800-bed tertiary care hospital in Lilongwe, Malawi that serves 8 districts in the central region of Malawi with a catchment area of approximately 6\u0026nbsp;million people.\u003c/p\u003e\u003cp\u003e\u003cb\u003eStudy Participants and Data Collection\u003c/b\u003e\u003c/p\u003e\u003cp\u003eMethods of recruitment, ascertainment, and informed consent are previously described elsewhere [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Inclusion criteria were patients over 18 years of age with either a pathologically confirmed or presumptive diagnosis of EC based on barium swallow or endoscopy and clinical stability to independently present to a radiology facility. Patients that were pregnant, had another known cancer diagnosis, or were already receiving EC treatment were excluded. Informed consent was taken for both the parent study and the sub-study. Costs of imaging studies were covered by the study.\u003c/p\u003e\u003cp\u003eBaseline socio-demographic and clinical information was collected upon enrollment, including length of symptoms, endoscopic findings, and histology if available. Each participant was scheduled for CXR, abdominal US, and CT of the chest and abdomen to evaluate for evidence of metastatic disease. During the course of the study, the CT facilities at KCH were intermittently not available, leading to an effort to provide transportation to private facilities using available funds.\u003c/p\u003e\u003cp\u003eImaging studies were interpreted by trained radiologists at KCH with support from the University of North Carolina. Positive findings were defined as the presence of pulmonary nodules, pleural effusions, hepatic masses, or ascites. The aim of our study was to determine to examine sensitivity and specificity of CXR/US to set the stage for testing and evaluation of a pragmatic algorithm. The long term goal of this study was to inform our understanding of the feasibility and limitations of sequential, algorithm staging approaches for EC.\u003c/p\u003e\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003e Descriptive statistics were used to describe the baseline characteristics of our patient population, compliance rates with each imaging study, and imaging study results. Differences in characteristics between eligible participants that did and did not enroll into the sub-study were compared using Pearson\u0026rsquo;s Chi-squared test. Sensitivity and specificity of CXR and US for detecting distant metastasis were calculated by generating a 2x2 table. CT scan was considered the \u0026lsquo;gold standard\u0026rsquo; as PET/CT is unavailable in this setting. Barriers to completion of imaging studies were identified during weekly meetings with the research team.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eOf 150 total eligible patients in TOEC-M, 67 (44.7%) enrolled in the staging sub-study. Mean age was 55.4 years and 50.8% were males. Participants were largely never smokers (70.2%) and had no history of alcohol abuse (70.2%). Only 6 (9.0%) patients were insured. There were no significant differences between characteristics of patients enrolled and not enrolled into the sub-study (Table\u0026nbsp;\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\u003eDemographics of TOEC-M eligible patients by enrollment in the imaging sub-study\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEnrolled\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;67)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNot Enrolled\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;83)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;150)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (years), mean (SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e55.4 (12.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e54.8 (3.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e55.1 (13.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.79\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e34 (50.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e46 (55.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e80 (53.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.57\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHIV positive, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (10.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12 (14.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19 (12.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.13\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoking history, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.92\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCurrent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4 (6.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6 (7.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10 (6.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFormer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16 (23.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18 (21.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e34 (22.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNever\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47 (70.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e59. (71.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e106 (70.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAlcohol history, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.78\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCurrent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (4.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6 (7.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9 (6.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFormer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17 (25.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19 (23.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36 (24.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNever\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47 (70.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e57 (69.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e104 (69.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHighest level of education, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.69\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e35 (52.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e44 (53.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e79 (52.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrimary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21 (31.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20 (24.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e41 (27.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSecondary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9 (13.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16 (19.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e25 (16.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTechnical college or University\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (3.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (3.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5 (3.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIncome (kwacha/USD) per year, median (IQR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1350000/777 (500000/288- 2000000/1152)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1250000/720 (600000/345- 2500000/1439)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1350000/777 (500000/288- 2000000/1132)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.75\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInsured, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6 (9.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (4.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10 (6.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.35\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\u003eThe majority of participants had mid-esophageal tumors (38 [56.7%]). Endoscopic biopsies were obtained in 60 (89.6%) patients, of which squamous cell carcinoma was the most prevalent histology (54 [90%]). The median duration of symptoms was 5 months (IQR 3\u0026ndash;6) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). CXR was completed in n\u0026thinsp;=\u0026thinsp;54 (80.6%), right upper quadrant US in n\u0026thinsp;=\u0026thinsp;43 (64.2%), CT chest in n\u0026thinsp;=\u0026thinsp;29 (43.3%), and CT abdomen in n\u0026thinsp;=\u0026thinsp;24 (35.8%). All studies were completed in 16 (23.9%) and only 4 (6.0%) did not undergo any imaging (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\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\u003eTumor characteristics of TOEC-M eligible patients by enrollment in the imaging sub-study\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEnrolled\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;67)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNot Enrolled\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;83)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;150)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTumor location, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.17\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUpper\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8 (11.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19 (22.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27 (18.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMiddle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e38 (56.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34 (41.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e72 (48.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDistal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8 (11.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9 (10.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e17 (11.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMissing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13 (19.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21 (25.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e34 (22.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTumor length (cm), median (IQR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (5\u0026ndash;8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6 (5\u0026ndash;7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 (5\u0026ndash;8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.31\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMode of diagnosis, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.17\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBiopsy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60 (89.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e66 (79.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e126 (84.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEndoscopy without biopsy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (10.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14 (16.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e21 (14.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEndoscopy with non-confirmatory biopsy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (3.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (2.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBiopsy results, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.28\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSquamous cell carcinoma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e54 (80.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e56 (67.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e110 (73.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdenocarcinoma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (1.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (0.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther malignancy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (1.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (3.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (2.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDysplasia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (1.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (3.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (2.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBenign\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (3.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (4.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 (4.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNon-diagnostic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (3.0)\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\u003e2 (1.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDuration of symptoms (months), median (IQR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5 (3\u0026ndash;6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (3\u0026ndash;6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (3\u0026ndash;6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.25\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\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\u003eImaging completion rates (N\u0026thinsp;=\u0026thinsp;67)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCompleted, n (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4 (6.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChest x-ray\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e54 (80.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAbdominal ultrasound\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e43 (64.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCT chest\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e29 (43.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCT abdomen\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e24 (35.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChest X-ray, Abdominal US, and CT chest and abdomen\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e16 (23.9)\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\u003eOf the 63 patients that were imaged, metastatic disease was identified in 18 (28.6%) by any modality. Positive findings consistent with metastasis were identified on 3 (5.6%) CXRs, 4 (9.3%) US, and 18 (62.1%) CTs. The most frequent sites of metastasis were liver followed by lung and distant lymph nodes (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). None of the participants with positive findings on CXR and/or US underwent confirmatory CT precluding our ability to calculate false positive rate.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eImaging Findings*\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCXR\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;54)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUS\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;43)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCT\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;29)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMetastatic disease, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (5.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (9.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18 (62.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLiver\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (9.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5 (17.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLungs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (3.7)\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\u003e3 (10.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdenopathy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0)\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\u003e3 (10.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBones\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0)\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 (6.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0)\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\u003e5 (17.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMissing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (1.9)\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\u003e0 (0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cb\u003e*More than one imaging test may have been completed in each participant\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eBarriers to imaging completion included symptom burden and facility availability including malfunctioning scanners and distance to private facilities. Notably, in the group of 16 patients that underwent all 4 imaging modalities (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), CXR and/or US did not detect any metastases, including among the 7 patients who were found to have metastasis on CT, leading to sensitivity of 0% in this small sample. CT chest/abdomen also did not show metastases in n\u0026thinsp;=\u0026thinsp;9, leading to a specificity of 100% of CXR/US and a negative predictive value of 56.3%.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eRates of imaging detection of metastatic disease (n\u0026thinsp;=\u0026thinsp;16) in patients undergoing all 4 imaging modalities\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCT positive\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCT negative\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCXR or US positive\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e0\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCXR and US negative\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e7\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e9\u003c/b\u003e\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":"Discussion","content":"\u003cp\u003eWe conducted a prospective observational cohort study examining the feasibility of using low-cost imaging modalities to stage the EC population in Malawi, a setting where staging of EC is not routinely performed. Of our potential participant pool of 150 patients, 67 (44.7%) patients were eligible and enrolled to receive imaging for staging. We found that the majority of patients had mid-esophageal squamous cell carcinomas and that 18 (28.6%) had evidence of metastatic disease. CXR and abdominal US were feasible to obtain and interpret as a low-cost solution for initial evaluation for metastases in resource-limited environments. As the sample size was limited, and we were unable to calculate the sensitivity of these imaging studies alone, they did show excellent specificity and may be used to defer CT scan if positive.\u003c/p\u003e\u003cp\u003ePrevious studies in high-income countries have shown the sensitivity of abdominal US and CXR in detecting metastatic disease in EC patients to be 65% and 68%, respectively [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Given a presumably higher prevalence of advanced disease in our East African population, the sensitivity of these studies is expected to be higher. While not yet validated, CXR and US have been previously used in resource-limited settings to evaluate the presence of metastatic disease. For example, Tenwek hospital in Kenya used CXR and abdominal US to exclude metastatic disease prior to esophagectomy [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. As access to curative treatment options expands across this region, an algorithm for pre-treatment evaluation may be useful to guide resource allocation and clinical management, particularly when cost of cross-sectional imaging studies remains prohibitive to most patients.\u003c/p\u003e\u003cp\u003eOur study did have several limitations largely related to our small sample size and limited completion rates. We faced several obstacles to imaging completion due to availability of radiology facilities, transportation, and the frailty of our population. Coordination with radiology was also a key barrier to completion given the limited availability of equipment. While it was our hope that all three studies could be performed on the same day to enhance completion rates, there was often discontinuity in this workflow leading to long patient wait times and difficulty rescheduling. Symptom burden (as patients were very ill due to obstructing esophageal tumors) often impeded patients from withstanding multi-day tests.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn Malawi and similar resource-limited settings, CXR and abdominal US are feasible, low-cost modalities as an initial evaluation for metastatic disease in EC patients. However, given barriers to completion of multiple imaging studies, focusing on obtaining or lowering costs of CT scans should be prioritized, particularly in patients medically fit for further treatment, e.g. chemotherapy or radiotherapy. For patients with borderline fitness for treatment, CXR and US can be used for initial staging as positive studies could potentially defer need for CT scan. In those too unwell for treatment, imaging could be deferred altogether. Future work on cost-effectiveness and applicability outside of a hospital-based population will be required prior to implementation.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eEC \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Esophageal cancer\u003c/p\u003e\n\u003cp\u003eESCC \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Esophageal squamous cell carcinoma\u003c/p\u003e\n\u003cp\u003eCT \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Computed tomography\u003c/p\u003e\n\u003cp\u003eCXR \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Chest radiography\u003c/p\u003e\n\u003cp\u003eKCH \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Kamuzu Central Hospital\u003c/p\u003e\n\u003cp\u003eLMIC \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Low- and middle-income countries\u003c/p\u003e\n\u003cp\u003ePET \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Positron emission tomography\u003c/p\u003e\n\u003cp\u003eTNM \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Tumor-node-metastasis\u003c/p\u003e\n\u003cp\u003eTOEC-M \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Treatment Outcomes of Esophageal Cancer in Malawi\u003c/p\u003e\n\u003cp\u003eUS \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Ultrasound\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Institutional Review Boards of University of North Carolina and the National Health Sciences Research Committee of Malawi approved the study protocols. Informed consent was obtained from all subjects.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUJMT Fogarty Global Health Fellowship Program (NIH Fogarty International Center Grant #D43TW009340).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGM, BK, KM, AS, AE, NN, CK, GB, KM, JG, AC, and GNM collected and analyzed data. BW, KD, and GNM were major contributors in writing the manuscript. All authors approved the final manuscript.\u003cbr\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMorgan E, Soerjomataram I, Rumgay H, Coleman HG, Thrift AP, Vignat J, et al. The Global Landscape of Esophageal Squamous Cell Carcinoma and Esophageal Adenocarcinoma Incidence and Mortality in 2020 and Projections to 2040: New Estimates From GLOBOCAN 2020. Gastroenterology. 2022;163(3):649\u0026ndash;e6582.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMalekzadeh R, Abnet CC, Dawsey SM. Oesophageal cancer: A tale of two malignancies. In: Wild CP, Weiderpass E, Stewart BW, editors. World Cancer Report: Cancer Research for Cancer Prevention. Lyon, France: International Agency for Research on Cancer; 2020.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAbnet CC, Arnold M, Wei W-Q. Epidemiology of Esophageal Squamous Cell Carcinoma. Gastroenterology. 2018;154(2):360\u0026ndash;73.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCheng ML, Zhang L, Borok M, Chokunonga E, Dzamamala C, Korir A, et al. The incidence of esophageal cancer in Eastern Africa: identification of a new geographic hot spot? Cancer Epidemiol. 2015;39(2):143\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBuckle GC, Mahapatra R, Mwachiro M, Akoko L, Mmbaga EJ, White RE, et al. Optimal management of esophageal cancer in Africa: A systemic review of treatment strategies. Int J Cancer. 2021;148(5):1115\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVan Loon K, Mwachiro MM, Abnet CC, Akoko L, Assefa M, Burgert SL, et al. The African Esophageal Cancer Consortium: A Call to Action. J Glob Oncol. 2018;4:1\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBuckle GC, Mrema A, Mwachiro M, Ringo Y, Selekwa M, Mulima G, et al. of the African Esophageal Cancer Consortium (AfrECC). Treatment outcomes of esophageal cancer in Eastern Africa: protocol of a multi-center, prospective, observational, open cohort study. BMC Cancer. 2022;22(1):82.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRice TW, Kelsen DP, Blackstone EH, et al. Esophagus and esophagogastric junction. In: Amin MB, Edge SB, Greene FL, et al. editors. AJCC Cancer Staging Manual. 8th ed. New York, NY: Springer; 2017. pp. 185\u0026ndash;202.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVarghese TK Jr, Hofstetter WL, Rizk NP, Low DE, Darling GE, Watson TJ, et al. The Society of Thoracic Surgeons Guidelines on the Diagnosis and Staging of Patients with Esophageal Cancer. Ann Thorac Surg. 2013;96(1):346\u0026ndash;56.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePi\u0026ntilde;eros M, Parkin DM, Ward K, Chokunonga E, Ervik M, Farrugia H, et al. Essential TNM: a registry tool to reduce gaps in cancer staging information. Lancet Oncol. 2019;20(2):e103\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVan Vliet EP, Steyerberg EW, Eijkemans MJ, Kuipers EJ, Siersema PD. Detection of distant metastases in patients with oesophageal or gastric cardia cancer: a diagnostic decision analysis. Br J Cancer. 2007;97(7):868\u0026ndash;76.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMwachiro M, Mitchell E, Topazian HM, White R. Esophagectomy in Patients with Human Immunodeficiency Virus and Acquired Immune Deficiency Syndrome: A Viable Option. Semin Thorac Cardiovasc Surg. 2018;30(1):116\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-gastroenterology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmge","sideBox":"Learn more about [BMC Gastroenterology](http://bmcgastroenterol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmge/default.aspx","title":"BMC Gastroenterology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Esophageal cancer, staging, low- and middle-income countries","lastPublishedDoi":"10.21203/rs.3.rs-6994944/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6994944/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eEsophageal cancer (EC) is the third leading cause of cancer-related morbidity and mortality in Malawi. Given limited imaging capacity and high costs, staging is not routinely performed. One proposed staging algorithm is to first evaluate for metastatic disease using low-cost chest radiography (CXR) and abdominal ultrasound (US) followed by confirmatory computerized tomography (CT) of the chest and abdomen if no metastases identified on initial screening. The feasibility of this approach is unknown for EC in sub\u0026ndash;Saharan Africa and was studied in the context of a larger prospective observational cohort study of EC in Malawi.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eFrom 2021 to 2022, EC patients at Kamuzu Central Hospital in Lilongwe, Malawi enrolled in the Treatment Outcomes of Esophageal Cancer in Malawi (TOEC-M) study were recruited. Participants were scheduled for a CXR, US, and CT scan as part of this sub-study. Participant characteristics, completion rates, imaging findings, and barriers to completion were documented. For participants undergoing all three imaging studies, sensitivity and specificity were calculated.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eOf 150 patients in TOEC-M, 67 (44.7%) enrolled in this sub-study. Mean age was 55.4 years and 50.8% were males. The majority had mid-esophageal (38 [56.7%]) squamous cell carcinomas (54 [80.6%]). CXR was completed in 54 (80.6%) study participants, US in 43 (64.2%), CT chest in 29 (43.3%), and CT abdomen in 24 (35.8%). Sixteen (23.9%) completed all studies and 4 (6.0%) did not undergo any imaging. Of the 63 patients that were imaged, metastatic disease was identified in 18 (28.6%) by any modality. Positive findings were identified on 3 (5.6%) CXRs, 4 (9.3%) US, and 18 (62.1%) CTs, most frequently liver masses followed by lung nodules and adenopathy. Barriers to imaging completion included participant functional status and scanner availability.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eAs access to EC treatment modalities expands, feasible and accurate staging will become increasingly important to guide clinical management. Our results suggest that CXR and US may serve as useful initial tools for assessing metastatic disease. In patients not medically fit for oncologic treatment, positive findings on CXR and US may allow CT to be deferred. Barriers to implementation of a pragmatic stepwise staging algorithm identified in this study can inform future research and care for patients with EC in similar resource-limited settings.\u003c/p\u003e","manuscriptTitle":"Esophageal Cancer Staging in Malawi: The Feasibility of Chest Radiography and Abdominal Ultrasound for Initial Evaluation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-05 06:06:24","doi":"10.21203/rs.3.rs-6994944/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-18T08:51:30+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-14T20:18:06+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-06T13:42:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"95549013240804760202783876244343371534","date":"2025-08-04T11:39:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"116231139493656139496555882164458748181","date":"2025-07-30T11:59:27+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-30T06:25:46+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-07-10T06:43:49+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-09T10:21:06+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-09T10:19:44+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Gastroenterology","date":"2025-06-28T01:58:35+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-gastroenterology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmge","sideBox":"Learn more about [BMC Gastroenterology](http://bmcgastroenterol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmge/default.aspx","title":"BMC Gastroenterology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fbcaddc0-b6ac-4934-9a4f-0d7a5c582250","owner":[],"postedDate":"August 5th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-01T16:03:52+00:00","versionOfRecord":{"articleIdentity":"rs-6994944","link":"https://doi.org/10.1186/s12876-025-04378-w","journal":{"identity":"bmc-gastroenterology","isVorOnly":false,"title":"BMC Gastroenterology"},"publishedOn":"2025-11-27 15:58:21","publishedOnDateReadable":"November 27th, 2025"},"versionCreatedAt":"2025-08-05 06:06:24","video":"","vorDoi":"10.1186/s12876-025-04378-w","vorDoiUrl":"https://doi.org/10.1186/s12876-025-04378-w","workflowStages":[]},"version":"v1","identity":"rs-6994944","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6994944","identity":"rs-6994944","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}