Comparative Study of Two Methods for Detecting Occult Blood in Stool: SD BIOLINE FOB® and HEMOCCULT® in Healthcare Facilities in Yaoundé and Douala

Comparative Study of Two Methods for Detecting Occult Blood in Stool: SD BIOLINE FOB® and HEMOCCULT® in Healthcare Facilities in Yaoundé and Douala | 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 Comparative Study of Two Methods for Detecting Occult Blood in Stool: SD BIOLINE FOB® and HEMOCCULT® in Healthcare Facilities in Yaoundé and Douala Willy Stéphane Kengne, Larry Tangie Ngek, Daniel Tchamdeu, Patrick Fouegap, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7727841/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Occult blood testing (OBT) is a non-invasive method crucial for detecting microscopic gastrointestinal bleeding, often associated with colorectal cancer(CRC), the second most cause of death from cancer worldwide .CRC is the second most frequent digestive cancer in Cameroun , although there is no national screening program.Two types of OBT methods are cmmmonly employed :The classical guaiac-based occult blood test (gFOBT), and the immunological fecal occult blood test (iFOBT), which demonstrates superior diagnostic performance. Methods A cross-sectional study was conducted from November 2, 2021, to August 20, 2022, in four health facilities. Adults over 21 years scheduled for colonoscopy were enrolled. Diagnostic accuracy indicators (sensitivity, specificity) of both tests were assessed against colonoscopy results. Results Of 323 patients screened , 108 were eligible .SD BIOLINE FOB® detected occult blood in 45.37% of cases, while Hemocult® detected it in 31.48 %. SD BIOLINE FOB® had higher sensitivity (68%) than Hemoccult® (41%), with both tests reaching 79 % specificity. It also revealed a greater number of abnormalities such as polyps and hemorrhoidal folds. Conclusion Compared to Hemoccult®, SD BIOLINE FOB® demonstrated superior sensitivity and lesion detection. Its use could be a valuable option in CRC screening strategies, especially in resource limited contexts like Cameroon. However, larger studies are necessary to consolidate these findings. Figures Figure 1 Introduction The fecal occult blood test (FOBT) is one of the most basic, non-invasive diagnostic tools that are used to find the presence of blood at a microscopic level in the stool, usually in quantities less than 50 mg of hemoglobin per gram of stool. Normally, in an adult without any health problems, the concentration is around 2 to 3 mg/g. Any value above that may be indicative of different gastrointestinal conditions, which may be both benign and malignant, among them colonic neoplasms [1]. Colorectal cancer (CRC) ranks second after all other cancer-related causes of death that take the lives of people worldwide, being the reason for about 12% of cancer deaths, mostly among people aged 65 years or over. The overall survival rate after 5 years for all stages is estimated at 63% [2]. To address the often-late diagnosis, many countries have implemented systematic screening programs starting at the age of 50, primarily based on immunological fecal occult blood test (iFOBT) In Cameroon, CRC is the second most common digestive cancer [3]. Despite this situation, no structured national screening strategy has been established. The two currently available diagnostic modalities are FOBT and lower digestive endoscopy (rectosigmoidoscopy or colonoscopy) [4]. There are two main categories of FOBT : guaiac-based tests (gFOBT), which were historically used but have limited sensitivity, and immunological test (iFOBT), which detect human hemoglobin using specific monoclonal antibodies. The latter, introduced in 2008, have shown superior diagnostic performance, with a 3.7 times higher detection rate for cancers and precancerous lesions compared to gFOBT [5,6]. Among iFOBTs, SD BIOLINE FOB® (25FK10, 25FK12), manufactured in Belgium, is widely used in several European public health campaigns. It is distinguished by its simplicity, low cost, and accessibility, making it an ideal option for resource limited countries. In Sub-Saharan Africa, particularly in Black populations, CRC presents certain peculiarities :a younger age of onset, with nearly 40% of cases diagnosed before the age of 40, has been reported in several studies [7,8]. This situation is also found in Camerooon, aggraved by the absence of a structured prevention program and limited access to high-performance tests like iFOBT. In this context, were conducted a study to compare the performance of two FOBT methods, the guaiac based Hemoccult® test and the immunological SD BIOLINE FOB® test by comparing them with colonoscopy results in health facilities in Yaoundé and Douala. The Goal is to provide evidence to inform the implementation of an effective, safe, and accessible CRC screening program. Methods Study Design This study was a cross-sectional analytical study, which aimed to compare the diagnostic effectiveness of two fecal occult blood tests (SD BIOLINE FOB® and Hemoccult®) with colonoscopy results as the reference standard. Setting We conducted a study in two cities, namely Douala and Yaoundé, which are respectively the economic and political capitals of Cameroon. These two cities were chosen because of their better healthcare infrastructure, and more specifically in the area of endoscopy in this country.We collected data from November 2, 2021, to August 20, 2022, representing a nine-month period, from the endoscopy departments of four medical facilities: Yaoundé General Hospital, La Cathédrale Medical Center, the Promoteurs de Santé Center (Yaoundé), and the Poitiers Polyclinic (Douala). This was a cross-sectional analytical study that aimed to compare the diagnostic efficacy of two fecal occult blood tests (SD BIOLINE FOB® and Hemoccult®) with colonoscopy results as the reference standard. Patients who were to be included had to be ≥21 years of age, having undergone a colonoscopy in one of the chosen facilities and who consented to participate. Patients were excluded if they had a history of rectal bleeding or melena, or if they only had diagnostic tests (fecal occult blood tests or colonoscopy) without any complementary intervention. Participants Eligible participants were adult patients (aged ≥ 21 years) who had undergone a colonoscopy at one of the study sites and consented to participate. Individuals were excluded if they had a history of rectal bleeding or melena, or if they had completed only one of the two diagnostic tests (FOBT or colonoscopy) without the complementary procedure. Variables Socio-demographic variables : age, sex. Clinical variables: Indications for colonoscopy Paraclinical variables: Results of the SD BIOLINE FOB® and Hemoccult® tests, colonoscopy findings, and histopathology reports from biopsied lesions. Data Sources and Measurement Data collection was structured across three phases: Pre-analytical phase: After the administrative approval, the principal investigator took the responsibility of training the hepatogastroenterologists and endoscopy nurses the standardized protocol for the SD BIOLINE FOB® test. To confirm the conforming with the protocol and technical preparedness a preliminary test was made . Analytical phase: Stool samples were collected in clean, dry containers. SD BIOLINE FOB® : A rapid immunochromatographic test for human hemoglobin in feces (sensitivity 98%, specificity 98.5%) was performed according to the manufacturer’s instructions. Hemoccult® : A guaiac-based test processed per standard laboratory protocols. Test results were interpreted visually after 5–10 minutes: a visible line at the “C” (control) indicated a valid test, and a line at the “T” (test) indicated a positive result. Invalid tests were excluded. Post-analytical phase: Results were recorded using standardized data collection forms( Figure 1 ) [9]. Colonoscopy was performed under sedation by trained gastroenterologists using Storz® and Fujinon® video endoscopes. Bowel preparation involved dietary restrictions and osmotic laxatives. Lesions suspicious for malignancy or dysplasia were biopsied and analyzed histopathologically within 10 days. Bias Several measures were taken to minimize bias. The standardized protocol and training minimized measurement bias. Still, some bias in choosing the sample might have been present since the group consisted of only those patients who had both tests done and gave their permission. Besides, the tests were performed in a well-equipped lab, which might not be the case with the actual settings. Study Size A total of 108 patients met the inclusion criteria and were enrolled during the study period. The sample size was limited by the availability of colonoscopy and consented FOBT testing within the defined timeframe. Quantitative Variables Quantitative variables such as age were described using means, medians, and standard deviations. FOBT results were recorded as binary outcomes (positive or negative). Colonoscopy and histopathology results were classified into normal findings, benign polyps, or malignant/budding lesions. Statistical Methods Data entry and management were handled with the use of CSPRO 7.2. Descriptive statistics: Variables of the categorical type were presented as counts and percentages. Variables of the continuous type were represented by means ± standard deviations or medians with interquartile ranges. Comparative analysis: To compare the proportions, chi-square tests were utilized. The difference was considered statistically significant if the p-value was less than 0.05. Logistic regression: The regressions (univariate and multivariate) were used for determining independent predictors of test positivity by adjusting the effects of confounding variables. The strength of the associations was given in terms of odds ratios (ORs) with 95% confidence intervals. Diagnostic accuracy: Sensitivity = TP / (TP + FN): The proportion of true positives that the test correctly identifies. Specificity = TN / (TN + FP): The proportion of true negatives that the test correctly identifies. Results Study Population and Baseline Characteristics During the study period, the total number of patients who were to undergo a colonoscopy (323) were screened for eligibility in the selected hospitals of Yaoundé and Douala. After the exclusion criteria were applied, out of 215 patients, those were mainly patients with rectal bleeding and melena, plus those with incomplete data or who refused to participate were excluded. Thus, 108 patients who met the requirements of the study were retained and went both fecal occult blood tests (FOBTs) as well as colonoscopy. Table 1 shows the sociodemographic and clinical characteristics of the study population. The average age of the subjects was 48.49 years (± 15.4), the youngest being 1 year and the oldest 84 years, showing that the study had capture the pediatric and geriatric extremes, though, the population was mostly young. In fact, 57 patients (52.78%) were under 50 years of age. This is an important epidemiological point that implies colorectal lesions in Cameroon could therefore be younger-aged occurrence, maybe corroborating arguments of earlier screening protocols in Sub-Saharan Africa. The study was characterized by male dominance in which 73 (67.59%) men and 35 (32.40%) women made up the study population giving a sex ratio of 2.08. This gender discrepancy could be attributed to different health-seeking behaviors or the actual incidence of colorectal symptoms in the population. The main symptoms which led to the performance of a colonoscopy were abdominal pain (52.38%) and altered general state (31.48%). These findings correspond to a diagnostic colonoscopy profile, rather than that of a systematic screening, which is typical in a resource-poor setting with minimal public health infrastructure for CRC prevention. Detection of Colonic Lesions Details on the identification of colorectal abnormalities depending on the type of FOBT are presented in Table 2. The results of colonoscopy were compared between patients who tested positive with HEMOCCULT® (guaiac-based FOBT) and SD BIOLINE FOB® (immunochemical FOBT, or iFOBT). The SD BIOLINE FOB® test recorded a higher detection ability for all lesion types. Across all lesion types, the SD BIOLINE FOB® test demonstrated a superior detection capacity. Notably, the SD BIOLINE FOB® detected 47% more polyps, 160% more hemorrhoidal anomalies, and 60% more budding lesions. This suggests that the iFOBT's higher analytical sensitivity, particularly for human hemoglobin, allows for improved detection of both neoplastic and inflammatory lesions. Table 3 shows the comparative distribution of test results between Hemoccult® and SD BIOLINE FOB®. Out of the 108 patients included, the SD BIOLINE FOB® test returned 49 positives (45.37%), while HEMOCCULT® returned only 34 positives (31.48%). This demonstrates a relative increase of 43.68% in positive test yield when using SD BIOLINE FOB®, highlighting its greater sensitivity for detecting occult gastrointestinal bleeding. Diagnostic Performance Metrics The diagnostic performance of the HEMOCCULT® test is illustrated in Table 4. This guaiac-based test showed weak sensitivity as it was able to identify only four true positives out of ten. The false-negative rate was quite high, at 33%. Its positive predictive value (PPV) was somewhat good, that is when the test was positive, it was quite reliable. On the other hand, the negative predictive value (NPV) was low, which implied that the test was not good at ruling out the disease when the result was negative. The Youden's Index for HEMOCCULT® was 0.20, indicating limited diagnostic efficiency. In contrast, the SD BIOLINE FOB® demonstrated substantially better performance, as shown in Table 5. It achieved a much higher sensitivity (68%) and improved NPV (69%), with an overall diagnostic performance (Youden’s Index of 0.47) that was more than double that of the HEMOCCULT® test. The number of true positives detected by SD BIOLINE FOB® was significantly higher (38 compared to 23 with HEMOCCULT®), while false negatives were considerably fewer (18 compared to 33). Interpretation and Implications The performance indicators unambiguously show that SD BIOLINE FOB® is more effective in identifying true colorectal lesions than HEMOCCULT®. The results are particularly significant for the Sub-Saharan African area, where the incidence of CRC is going up and early detection still faces challenges of infrastructure and economic constraints. Considering the higher sensitivity, acceptable specificity, and practical feasibility of iFOBTs like SD BIOLINE FOB®, their implementation in national screening programs could be a game changer in early CRC diagnosis, thus lowering the number of late-stage disease and increasing the survival rate not only in Cameroon but also in other areas which are facing similar conditions. Discussion This analytical observational study was conducted from November 2, 2021, to August 20, 2022, in four private healthcare facilities in Yaoundé and Douala. This study intended to compare the performance of two different fecal occult blood test detection methods - the immunological SD BIOLINE FOB® test and the guaiac-based HEMOCCULT® test, in the context of Cameroon. The first group consisted of adults aged 21 years or older, who had indications for colonoscopy other than rectal bleeding or melena. The main purpose was to evaluate the tests' efficiency for occult bleeding. Setting the minimum age limit to 21 years reflects the legal age of majority in Cameroon and is, therefore, the most ethical and legal way to conduct the study. The demographic analysis showed that the population was relatively young: more than half (52.78%) of the participants were under 50 years of age, with an average age of 48.49 ± 15.46 years and a male-to-female ratio of 2:1. This age profile is consistent with data from other African studies [9], which indicates that the demographics of the region are similar. Most of the patients (67.57%) were male. The finding is similar to that of the Senegal [10] and Kuwait [11] studies but differs from the Côte d’Ivoire [12] and United States [13] observations, where the women are more represented. The differences could be due to the influence of culture on the healthcare system and the provision of healthcare services to the two genders. In our cohort, colonoscopy was most often indicated for symptomatic reasons, primarily abdominal pain (52.38%), followed by constipation and general health deterioration. This reflects the absence of organized screening programs, unlike in Western countries where screening is largely proactive and protocol-driven [14]. The predominance of abdominal pain as the leading indication contrasts with other African series where rectal bleeding is more frequently reported [15]. Colorectal abnormalities identified included polyps (25%), hemorrhoidal protrusions (22.22%), and budding lesions (9.26%), which is in line with the findings of similar African studies [16]. Test Performance The SD BIOLINE FOB® test demonstrated higher sensitivity (68%) and specificity (79%) compared to the HEMOCCULT® test (sensitivity: 41%, specificity: 59%). The SD BIOLINE test also achieved better predictive values (PPV: 78%; NPV: 69%) than the guaiac test (PPV: 68%; NPV: 55%). These results confirm the superior diagnostic accuracy of immunochemical tests, in accordance with Issa et al., who reported a sensitivity of 92% and specificity of 95–96% for immunochemical tests [17]. This performance difference may be attributed to the immunological test’s specificity for human hemoglobin, whereas the guaiac test is subject to dietary interferences. For instance, vitamin C can lead to false negatives by inhibiting oxidation reactions, and red meat may cause false positives [18,19]. On top of that, the SD BIOLINE FOB® test was able to find more colorectal anomalies than the guaiac test, among which were a bigger number of polyps (22 vs. 15), hemorrhoidal protrusions (13 vs. 5), and budding lesions (8 vs. 5). In addition to that, it picked up 3 budding ulcers that the HEMOCCULT® test had not located. The p-value of this difference (p < 0.05) underlines the advantage of the SD BIOLINE FOB® test. Study Limitations and Potential Biases Various limits could have a great impact on the results obtained. One of them was the small size of the population studied, which diminished the statistical power of the analysis and allowed only a few associations to be detected without even performing multivariate adjustments. This constraint on sample size was further aggravated by seasonal conditions, like the absence of gastroenterologists during the holidays and patient visits being lower at the beginning of the school year. Secondly, it is possible that selection bias occurred, in that the patients with bleeding from the colon that was not emphasized were excluded, and the study was only conducted on those who went for care in private urban centers. This could have resulted in the prevalence of precancerous lesions being overly estimated and, in turn, the ability to generalize findings being limited. The test results of people without symptoms and those living in less developed areas or are only receiving medical help from the public sector might be different. Thirdly, limitations in resources which, for example, included the impossibility of performing a colonoscopy in certain facilities and having to pay out-of-pocket for the SD BIOLINE FOB® test, have always been the main reasons for less broad screening. In such a situation, follow-up colonoscopies in cases of positive test results might not have been carried out always, thus giving a lower number of true positives than reality. Because the sample size was too small, no multivariate analysis was carried out. As a result, confounding factors like age, sex, or coexisting conditions that might have affected the relationships seen could not be adjusted for statistically. Generalizability These results are likely to be applicable to an urban private health care environment in Cameroon but may not be extrapolated to the general population (rural and low income), which have no access to endoscopy. The exclusion of patients with rectal bleeding also restricts generalizability to symptomatic individuals for whom early diagnosis is usually desired in colorectal cancer. Conclusion These findings showed that the New immunological test SD BIOLINE FOB is more sensitive and specific than HEMOCCULT® guaiac in detecting blood in stool in Cameroonian patients. These findings suggest that immunochemical tests may be more effective as a screening technique, especially in areas where colorectal screening is still not widely available. Carrying a larger scale with follow-up observation also need to be performed in the future studies. by these tests in colorectal cancer (CRC) screening in Africa, or even more so in resource constrained settings. What is already know on this topic Fecal occult blood test (FOBT) is an important non-invasive tool for the screening of colorectal cancer (CRC). Immunological FOB tests (iFOBTs) are more sensitive and specific than guaiac-based iFBTs. iFOBTs are widely used within organized CRCS programs in high-income countries. In Cameroon, CRC is a major public health issue that is escalating, but national screening methods are absent, and testing results in local places are very few. What this study adds It is the first study in Cameroon that compares the diagnostic accuracy of SD BIOLINE FOB® (iFOBT) and Hemoccult® (gFOBT) directly by using colonoscopy as the reference standard. The study unfolds that SD BIOLINE FOB® achieves a considerable triumph over Hemoccult® in all parameters, i.e. sensitivity, specificity, and diagnostic yield of colorectal lesions. These results back up the potential application of SD BIOLINE FOB® as the primary screening test in developing areas with limited resources, thus serving as a foundation for public health policies focused on early CRC detection in Sub-Saharan Africa. Declarations Competing interests: The authors declare no competing interest. Ethics approval and consent to participate This study was conducted in accordance with the Declaration of Helsinki. Ethics approval was obtained from the Ethics Committee of the Faculty of Medicine and Biomedical Sciences, University of Yaoundé I (Cameroon). Approval reference number: N° 408 /UY1 /FMSB/VDRC/DAASR/CSD All participants provided written informed consent before inclusion in the study. Consent for publication Not applicable. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Clinical trial registration Clinical trial number : not applicable. Authors’ contributions Kengne Willy Stéphane drafted the protocol, contributed to the study design, data collection, and writing. Larry Tangie Ngek assisted in the revision of the protocol and the initial draft. Daniel Tchamdeu reviewed the initial draft. Patrick Fouegap performed the data analysis. Gilles Wandji Yebchue supervised and reviewed the final version of the study. Phillipe Lingodesigned the study and supervised the entire process, providing strategic guidance. References Allison JE, Tekawa IS, Ransom LJ, Adrain AL. A comparison of fecal occult-blood tests for colorectal-cancer screening. 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Rev Afr Gastroentérol. 2017;9(1):10–14. Issa IA, Noureddine M. Colorectal cancer screening: an updated review of the available options. World J Gastroenterol. 2017;23(28):5086–5096. Rockey DC, Paulson E, Niedzwiecki D. Analysis of dietary influences on guaiac-based fecal occult blood test outcomes. Clin Gastroenterol Hepatol. 2006;4(2):273–278. Tables Table I: Sociodemographic and Clinical Characteristics of the Study Population: Comparative Study of SD BIOLINE FOB® and HEMOCCULT® in Colorectal Cancer Screening (November 2021 - August 2022) Variable Number (n = 108) Percentage (%) Median Age 48.49 ± 15.4 years (Range: 1-84) Gender Male 67.59% Female 32.40% Indications for Colonoscopy Abdominal pain 55 52.38% Constipation 33 30.56% Altered general status 34 31.48% Diarrhea 23 21.56% Follow-up for inflammatory bowel disease 4 3.70% CRC screening 17 15.74% Abdominal mass 13 12.03% Normal radiological picture 11 10.15% Monitoring after polypectomy 9 8.33% Anemia 11 10.18% Table II: Detection of Colorectal Anomalies According to the Type of FOBT Used: A Comparative Study of SD BIOLINE FOB® and HEMOCCULT® (November 2021 - August 2022) Nombre d'anomalies détectées par la Méthode : Anomalies Found on Colonoscopy SD BIOLINE FOB Hemoccult (Gaïac) Polypes 22 15 Diverticules 4 2 Ulcérations 2 1 Lésions bourgeonnantes 8 5 Ulcérons bourgeonnantes 3 0 Autres lésions 4 3 Bourrelets hémorroïdaires 13 5 Table III: Comparative Distribution of Test Results Between Hemoccult® and SD BIOLINE FOB®: Insights from a Colorectal Cancer Screening Study in Yaoundé and Douala (November 2021 - August 2022) Test Positive (n) Negative (n) Frequency (%) HEMOCCULT ® 34 74 31.48% SD BIOLINE FOB® 49 59 45.37% Table IV: Diagnostic Performance Metrics of the Guaiac-Based HEMOCCULT® Test Compared to Colonoscopy: Findings from a Comparative Study in Yaoundé and Douala (November 2021 - August 2022) Parameter value True Positives (VP) 23 False Positives (FP) 11 False Negatives (FN) 33 True Negatives (VN) 41 Positive Predictive Value (PPV) 0.68 Negative Predictive Value (NPV) 0.55 Youden's Index 0.20 Table V: Diagnostic Performance Metrics of the Immunological SD BIOLINE FOB® Test Compared to Colonoscopy: Results from a Colorectal Cancer Screening Study in Yaoundé and Douala (November 2021 - August 2022) Parameter value True Positives (VP) 38 False Positives (FP) 11 False Negatives (FN) 18 True Negatives (VN) 41 Positive Predictive Value (PPV) 0.78 Negative Predictive Value (NPV) 0.69 Youden's Index 0.47 Additional Declarations No competing interests reported. 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1","display":"","copyAsset":false,"role":"figure","size":323147,"visible":true,"origin":"","legend":"\u003cp\u003eStep-by-Step Procedure for Performing and Interpreting the FOBT Methods: A Comparative Study of SD BIOLINE FOB® and HEMOCCULT® in Yaoundé and Douala (November 2021 - August 2022)\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7727841/v1/ce306a29b7b89e42fa7698fc.jpeg"},{"id":96249480,"identity":"9116afa3-4002-4fb1-8f55-cf1bba037d0e","added_by":"auto","created_at":"2025-11-19 07:33:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1253967,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7727841/v1/850ab438-16ad-4853-8e59-09cd4d9f1d72.pdf"},{"id":95663099,"identity":"b534c431-d93f-4818-8989-90724e5fc0df","added_by":"auto","created_at":"2025-11-11 16:38:23","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":22775,"visible":true,"origin":"","legend":"","description":"","filename":"STROBEStatement.docx","url":"https://assets-eu.researchsquare.com/files/rs-7727841/v1/6354904bb764d1b2b228f8df.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comparative Study of Two Methods for Detecting Occult Blood in Stool: SD BIOLINE FOB® and HEMOCCULT® in Healthcare Facilities in Yaoundé and Douala","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe fecal occult blood test (FOBT) is one of the most basic, non-invasive diagnostic tools that are used to find the presence of blood at a microscopic level in the stool, usually in quantities less than 50 mg of hemoglobin per gram of stool. Normally, in an adult without any health problems, the concentration is around 2 to 3 mg/g. Any value above that may be indicative of different gastrointestinal conditions, which may be both benign and malignant, among them colonic neoplasms [1].\u003c/p\u003e\u003cp\u003eColorectal cancer (CRC) ranks second after all other cancer-related causes of death that take the lives of people worldwide, being the reason for about 12% of cancer deaths, mostly among people aged 65 years or over. The overall survival rate after 5 years for all stages is estimated at 63% [2].\u003c/p\u003e\u003cp\u003eTo address the often-late diagnosis, many countries have implemented systematic screening programs starting at the age of 50, primarily based on immunological fecal occult blood test (iFOBT)\u003c/p\u003e\u003cp\u003eIn Cameroon, CRC is the second most common digestive cancer [3]. Despite this situation, no structured national screening strategy has been established. The two currently available diagnostic modalities are FOBT and lower digestive endoscopy (rectosigmoidoscopy or colonoscopy) [4].\u003c/p\u003e\u003cp\u003eThere are two main categories of FOBT : guaiac-based tests (gFOBT), which were historically used but have limited sensitivity, and immunological test (iFOBT), which detect human hemoglobin using specific monoclonal antibodies. The latter, introduced in 2008, have shown superior diagnostic performance, with a 3.7 times higher detection rate for cancers and precancerous lesions compared to gFOBT [5,6].\u003c/p\u003e\u003cp\u003eAmong iFOBTs, SD BIOLINE FOB\u0026reg; (25FK10, 25FK12), manufactured in Belgium, is widely used in several European public health campaigns. It is distinguished by its simplicity, low cost, and accessibility, making it an ideal option for resource limited countries.\u003c/p\u003e\u003cp\u003eIn Sub-Saharan Africa, particularly in Black populations, CRC presents certain peculiarities :a younger age of onset, with nearly 40% of cases diagnosed before the age of 40, has been reported in several studies [7,8]. This situation is also found in Camerooon, aggraved by the absence of a structured prevention program and limited access to high-performance tests like iFOBT.\u003c/p\u003e\u003cp\u003eIn this context, were conducted a study to compare the performance of two FOBT methods, the guaiac based Hemoccult\u0026reg; test and the immunological SD BIOLINE FOB\u0026reg; test by comparing them with colonoscopy results in health facilities in Yaound\u0026eacute; and Douala. The Goal is to provide evidence to inform the implementation of an effective, safe, and accessible CRC screening program.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy Design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was a cross-sectional analytical study, which aimed to compare the diagnostic effectiveness of two fecal occult blood tests (SD BIOLINE FOB\u0026reg; and Hemoccult\u0026reg;) with colonoscopy results as the reference standard.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSetting\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe conducted a study in two cities, namely Douala and Yaound\u0026eacute;, which are respectively the economic and political capitals of Cameroon. These two cities were chosen because of their better healthcare infrastructure, and more specifically in the area of endoscopy in this country.We collected data from November 2, 2021, to August 20, 2022, representing a nine-month period, from the endoscopy departments of four medical facilities: Yaound\u0026eacute; General Hospital, La Cath\u0026eacute;drale Medical Center, the Promoteurs de Sant\u0026eacute; Center (Yaound\u0026eacute;), and the Poitiers Polyclinic (Douala).\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;This was a cross-sectional analytical study that aimed to compare the diagnostic efficacy of two fecal occult blood tests (SD BIOLINE FOB\u0026reg; and Hemoccult\u0026reg;) with colonoscopy results as the reference standard.\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;Patients who were to be included had to be \u0026ge;21 years of age, having undergone a colonoscopy in one of the chosen facilities and who consented to participate. Patients were excluded if they had a history of rectal bleeding or melena, or if they only had diagnostic tests (fecal occult blood tests or colonoscopy) without any complementary intervention.\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u003cstrong\u003eParticipants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEligible participants were adult patients (aged \u0026ge; 21 years) who had undergone a colonoscopy at one of the study sites and consented to participate. Individuals were excluded if they had a history of rectal bleeding or melena, or if they had completed only one of the two diagnostic tests (FOBT or colonoscopy) without the complementary procedure.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003eSocio-demographic variables\u003c/strong\u003e: age, sex.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003e\u003cstrong\u003eClinical variables:\u0026nbsp;\u003c/strong\u003eIndications for colonoscopy\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eParaclinical variables:\u0026nbsp;\u003c/strong\u003eResults of the SD BIOLINE FOB\u0026reg; and Hemoccult\u0026reg; tests, colonoscopy findings, and histopathology reports from biopsied lesions.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eData Sources and Measurement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData collection was structured across three phases:\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003ePre-analytical phase: After the administrative approval, the principal investigator took the responsibility of training the hepatogastroenterologists and endoscopy nurses the standardized protocol for the SD BIOLINE FOB\u0026reg; test. To confirm the conforming with the protocol and technical preparedness a preliminary test was made\u003cstrong\u003e.\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003col start=\"1\" type=\"1\"\u003e\n \u003cli\u003e\u003cstrong\u003eAnalytical phase: Stool samples were collected in clean, dry containers.\u003c/strong\u003e\n \u003cul type=\"circle\"\u003e\n \u003cli\u003e\u003cstrong\u003e\u003cem\u003eSD BIOLINE FOB\u0026reg;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eA rapid immunochromatographic test for human hemoglobin in feces (sensitivity 98%, specificity 98.5%) was performed according to the manufacturer\u0026rsquo;s instructions.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003e\u003cem\u003eHemoccult\u0026reg;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eA guaiac-based test processed per standard laboratory protocols.\u003cbr\u003e\u0026nbsp;Test results were interpreted visually after 5\u0026ndash;10 minutes: a visible line at the \u0026ldquo;C\u0026rdquo; (control) indicated a valid test, and a line at the \u0026ldquo;T\u0026rdquo; (test) indicated a positive result. Invalid tests were excluded.\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003ePost-analytical phase:\u0026nbsp;\u003c/strong\u003eResults were recorded using standardized data collection forms(\u003cstrong\u003eFigure 1\u003c/strong\u003e) [9].\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eColonoscopy was performed under sedation by trained gastroenterologists using Storz\u0026reg; and Fujinon\u0026reg; video endoscopes. Bowel preparation involved dietary restrictions and osmotic laxatives. Lesions suspicious for malignancy or dysplasia were biopsied and analyzed histopathologically within 10 days.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBias\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSeveral measures were taken to minimize bias. The standardized protocol and training minimized measurement bias. Still, some bias in choosing the sample might have been present since the group consisted of only those patients who had both tests done and gave their permission. Besides, the tests were performed in a well-equipped lab, which might not be the case with the actual settings.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy Size\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 108 patients met the inclusion criteria and were enrolled during the study period. The sample size was limited by the availability of colonoscopy and consented FOBT testing within the defined timeframe.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQuantitative Variables\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eQuantitative variables such as age were described using means, medians, and standard deviations. FOBT results were recorded as binary outcomes (positive or negative). Colonoscopy and histopathology results were classified into normal findings, benign polyps, or malignant/budding lesions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Methods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData entry and management were handled with the use of CSPRO 7.2.\u003c/p\u003e\n\u003col start=\"1\" type=\"1\"\u003e\n \u003cli\u003e\u003cstrong\u003eDescriptive statistics:\u003c/strong\u003e Variables of the categorical type were presented as counts and percentages. Variables of the continuous type were represented by means \u0026plusmn; standard deviations or medians with interquartile ranges.\u003c/li\u003e\n \u003cli\u003eComparative analysis: To compare the proportions, chi-square tests were utilized. The difference was considered statistically significant if the p-value was less than 0.05.\u003c/li\u003e\n \u003cli\u003eLogistic regression: The regressions (univariate and multivariate) were used for determining independent predictors of test positivity by adjusting the effects of confounding variables. The strength of the associations was given in terms of odds ratios (ORs) with 95% confidence intervals.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eDiagnostic accuracy:\u003c/strong\u003e\n \u003cul type=\"circle\"\u003e\n \u003cli\u003eSensitivity = TP / (TP + FN): The proportion of true positives that the test correctly identifies.\u003c/li\u003e\n \u003cli\u003eSpecificity = TN / (TN + FP): The proportion of true negatives that the test correctly identifies.\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eStudy Population and Baseline Characteristics\u003c/h2\u003e\u003cp\u003eDuring the study period, the total number of patients who were to undergo a colonoscopy (323) were screened for eligibility in the selected hospitals of Yaound\u0026eacute; and Douala. After the exclusion criteria were applied, out of 215 patients, those were mainly patients with rectal bleeding and melena, plus those with incomplete data or who refused to participate were excluded. Thus, 108 patients who met the requirements of the study were retained and went both fecal occult blood tests (FOBTs) as well as colonoscopy.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;1 shows the sociodemographic and clinical characteristics of the study population. The average age of the subjects was 48.49 years (\u0026plusmn;\u0026thinsp;15.4), the youngest being 1 year and the oldest 84 years, showing that the study had capture the pediatric and geriatric extremes, though, the population was mostly young. In fact, 57 patients (52.78%) were under 50 years of age. This is an important epidemiological point that implies colorectal lesions in Cameroon could therefore be younger-aged occurrence, maybe corroborating arguments of earlier screening protocols in Sub-Saharan Africa.\u003c/p\u003e\u003cp\u003eThe study was characterized by male dominance in which 73 (67.59%) men and 35 (32.40%) women made up the study population giving a sex ratio of 2.08. This gender discrepancy could be attributed to different health-seeking behaviors or the actual incidence of colorectal symptoms in the population. The main symptoms which led to the performance of a colonoscopy were abdominal pain (52.38%) and altered general state (31.48%). These findings correspond to a diagnostic colonoscopy profile, rather than that of a systematic screening, which is typical in a resource-poor setting with minimal public health infrastructure for CRC prevention.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eDetection of Colonic Lesions\u003c/h2\u003e\u003cp\u003eDetails on the identification of colorectal abnormalities depending on the type of FOBT are presented in Table\u0026nbsp;2. The results of colonoscopy were compared between patients who tested positive with HEMOCCULT\u0026reg; (guaiac-based FOBT) and SD BIOLINE FOB\u0026reg; (immunochemical FOBT, or iFOBT). The SD BIOLINE FOB\u0026reg; test recorded a higher detection ability for all lesion types.\u003c/p\u003e\u003cp\u003eAcross all lesion types, the SD BIOLINE FOB\u0026reg; test demonstrated a superior detection capacity. Notably, the SD BIOLINE FOB\u0026reg; detected 47% more polyps, 160% more hemorrhoidal anomalies, and 60% more budding lesions. This suggests that the iFOBT's higher analytical sensitivity, particularly for human hemoglobin, allows for improved detection of both neoplastic and inflammatory lesions.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;3 shows the comparative distribution of test results between Hemoccult\u0026reg; and SD BIOLINE FOB\u0026reg;. Out of the 108 patients included, the SD BIOLINE FOB\u0026reg; test returned 49 positives (45.37%), while HEMOCCULT\u0026reg; returned only 34 positives (31.48%). This demonstrates a relative increase of 43.68% in positive test yield when using SD BIOLINE FOB\u0026reg;, highlighting its greater sensitivity for detecting occult gastrointestinal bleeding.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eDiagnostic Performance Metrics\u003c/h2\u003e\u003cp\u003eThe diagnostic performance of the HEMOCCULT\u0026reg; test is illustrated in Table\u0026nbsp;4. This guaiac-based test showed weak sensitivity as it was able to identify only four true positives out of ten. The false-negative rate was quite high, at 33%. Its positive predictive value (PPV) was somewhat good, that is when the test was positive, it was quite reliable. On the other hand, the negative predictive value (NPV) was low, which implied that the test was not good at ruling out the disease when the result was negative. The Youden's Index for HEMOCCULT\u0026reg; was 0.20, indicating limited diagnostic efficiency.\u003c/p\u003e\u003cp\u003eIn contrast, the SD BIOLINE FOB\u0026reg; demonstrated substantially better performance, as shown in Table\u0026nbsp;5. It achieved a much higher sensitivity (68%) and improved NPV (69%), with an overall diagnostic performance (Youden\u0026rsquo;s Index of 0.47) that was more than double that of the HEMOCCULT\u0026reg; test. The number of true positives detected by SD BIOLINE FOB\u0026reg; was significantly higher (38 compared to 23 with HEMOCCULT\u0026reg;), while false negatives were considerably fewer (18 compared to 33).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eInterpretation and Implications\u003c/h2\u003e\u003cp\u003eThe performance indicators unambiguously show that SD BIOLINE FOB\u0026reg; is more effective in identifying true colorectal lesions than HEMOCCULT\u0026reg;. The results are particularly significant for the Sub-Saharan African area, where the incidence of CRC is going up and early detection still faces challenges of infrastructure and economic constraints. Considering the higher sensitivity, acceptable specificity, and practical feasibility of iFOBTs like SD BIOLINE FOB\u0026reg;, their implementation in national screening programs could be a game changer in early CRC diagnosis, thus lowering the number of late-stage disease and increasing the survival rate not only in Cameroon but also in other areas which are facing similar conditions.\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis analytical observational study was conducted from November 2, 2021, to August 20, 2022, in four private healthcare facilities in Yaound\u0026eacute; and Douala. This study intended to compare the performance of two different fecal occult blood test detection methods - the immunological SD BIOLINE FOB\u0026reg; test and the guaiac-based HEMOCCULT\u0026reg; test, in the context of Cameroon. The first group consisted of adults aged 21 years or older, who had indications for colonoscopy other than rectal bleeding or melena. The main purpose was to evaluate the tests' efficiency for occult bleeding.\u003c/p\u003e\u003cp\u003eSetting the minimum age limit to 21 years reflects the legal age of majority in Cameroon and is, therefore, the most ethical and legal way to conduct the study. The demographic analysis showed that the population was relatively young: more than half (52.78%) of the participants were under 50 years of age, with an average age of 48.49\u0026thinsp;\u0026plusmn;\u0026thinsp;15.46 years and a male-to-female ratio of 2:1. This age profile is consistent with data from other African studies [9], which indicates that the demographics of the region are similar.\u003c/p\u003e\u003cp\u003eMost of the patients (67.57%) were male. The finding is similar to that of the Senegal [10] and Kuwait [11] studies but differs from the C\u0026ocirc;te d\u0026rsquo;Ivoire [12] and United States [13] observations, where the women are more represented. The differences could be due to the influence of culture on the healthcare system and the provision of healthcare services to the two genders.\u003c/p\u003e\u003cp\u003eIn our cohort, colonoscopy was most often indicated for symptomatic reasons, primarily abdominal pain (52.38%), followed by constipation and general health deterioration. This reflects the absence of organized screening programs, unlike in Western countries where screening is largely proactive and protocol-driven [14]. The predominance of abdominal pain as the leading indication contrasts with other African series where rectal bleeding is more frequently reported [15].\u003c/p\u003e\u003cp\u003eColorectal abnormalities identified included polyps (25%), hemorrhoidal protrusions (22.22%), and budding lesions (9.26%), which is in line with the findings of similar African studies [16].\u003c/p\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003eTest Performance\u003c/h2\u003e\u003cp\u003eThe SD BIOLINE FOB\u0026reg; test demonstrated higher sensitivity (68%) and specificity (79%) compared to the HEMOCCULT\u0026reg; test (sensitivity: 41%, specificity: 59%). The SD BIOLINE test also achieved better predictive values (PPV: 78%; NPV: 69%) than the guaiac test (PPV: 68%; NPV: 55%). These results confirm the superior diagnostic accuracy of immunochemical tests, in accordance with Issa et al., who reported a sensitivity of 92% and specificity of 95\u0026ndash;96% for immunochemical tests [17].\u003c/p\u003e\u003cp\u003eThis performance difference may be attributed to the immunological test\u0026rsquo;s specificity for human hemoglobin, whereas the guaiac test is subject to dietary interferences. For instance, vitamin C can lead to false negatives by inhibiting oxidation reactions, and red meat may cause false positives [18,19].\u003c/p\u003e\u003cp\u003eOn top of that, the SD BIOLINE FOB\u0026reg; test was able to find more colorectal anomalies than the guaiac test, among which were a bigger number of polyps (22 vs. 15), hemorrhoidal protrusions (13 vs. 5), and budding lesions (8 vs. 5). In addition to that, it picked up 3 budding ulcers that the HEMOCCULT\u0026reg; test had not located. The p-value of this difference (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) underlines the advantage of the SD BIOLINE FOB\u0026reg; test.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003eStudy Limitations and Potential Biases\u003c/h2\u003e\u003cp\u003eVarious limits could have a great impact on the results obtained. One of them was the small size of the population studied, which diminished the statistical power of the analysis and allowed only a few associations to be detected without even performing multivariate adjustments. This constraint on sample size was further aggravated by seasonal conditions, like the absence of gastroenterologists during the holidays and patient visits being lower at the beginning of the school year.\u003c/p\u003e\u003cp\u003eSecondly, it is possible that selection bias occurred, in that the patients with bleeding from the colon that was not emphasized were excluded, and the study was only conducted on those who went for care in private urban centers. This could have resulted in the prevalence of precancerous lesions being overly estimated and, in turn, the ability to generalize findings being limited. The test results of people without symptoms and those living in less developed areas or are only receiving medical help from the public sector might be different.\u003c/p\u003e\u003cp\u003eThirdly, limitations in resources which, for example, included the impossibility of performing a colonoscopy in certain facilities and having to pay out-of-pocket for the SD BIOLINE FOB\u0026reg; test, have always been the main reasons for less broad screening. In such a situation, follow-up colonoscopies in cases of positive test results might not have been carried out always, thus giving a lower number of true positives than reality.\u003c/p\u003e\u003cp\u003eBecause the sample size was too small, no multivariate analysis was carried out. As a result, confounding factors like age, sex, or coexisting conditions that might have affected the relationships seen could not be adjusted for statistically.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003eGeneralizability\u003c/h2\u003e\u003cp\u003eThese results are likely to be applicable to an urban private health care environment in Cameroon but may not be extrapolated to the general population (rural and low income), which have no access to endoscopy. The exclusion of patients with rectal bleeding also restricts generalizability to symptomatic individuals for whom early diagnosis is usually desired in colorectal cancer.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThese findings showed that the New immunological test SD BIOLINE FOB is more sensitive and specific than HEMOCCULT\u0026reg; guaiac in detecting blood in stool in Cameroonian patients. These findings suggest that immunochemical tests may be more effective as a screening technique, especially in areas where colorectal screening is still not widely available. Carrying a larger scale with follow-up observation also need to be performed in the future studies. by these tests in colorectal cancer (CRC) screening in Africa, or even more so in resource constrained settings.\u003c/p\u003e\n\u003ch3\u003eWhat is already know on this topic\u003c/h3\u003e\n\u003cul\u003e\n \u003cli\u003eFecal occult blood test (FOBT) is an important non-invasive tool for the screening of colorectal cancer (CRC).\u003c/li\u003e\n\u003c/ul\u003e\n\u003cul\u003e\n \u003cli\u003eImmunological FOB tests (iFOBTs) are more sensitive and specific than guaiac-based iFBTs. iFOBTs are widely used within organized CRCS programs in high-income countries.\u003c/li\u003e\n \u003cli\u003eIn Cameroon, CRC is a major public health issue that is escalating, but national screening methods are absent, and testing results in local places are very few.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eWhat this study adds\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eIt is the first study in Cameroon that compares the diagnostic accuracy of SD BIOLINE FOB® (iFOBT) and Hemoccult® (gFOBT) directly by using colonoscopy as the reference standard.\u003c/li\u003e\n \u003cli\u003eThe study unfolds that SD BIOLINE FOB® achieves a considerable triumph over Hemoccult® in all parameters, i.e. sensitivity, specificity, and diagnostic yield of colorectal lesions.\u003c/li\u003e\n \u003cli\u003eThese results back up the potential application of SD BIOLINE FOB® as the primary screening test in developing areas with limited resources, thus serving as a foundation for public health policies focused on early CRC detection in Sub-Saharan Africa.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interest.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the Declaration of Helsinki.\u003cbr\u003e\u0026nbsp;Ethics approval was obtained from the Ethics Committee of the Faculty of Medicine and Biomedical Sciences, University of Yaoundé I (Cameroon).\u003cbr\u003e\u0026nbsp;Approval reference number: N° 408 /UY1 /FMSB/VDRC/DAASR/CSD\u003cbr\u003e\u0026nbsp;All participants provided written informed consent before inclusion in the study.\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\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial registration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eClinical trial number\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003enot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKengne Willy Stéphane drafted the protocol, contributed to the study design, data collection, and writing. Larry Tangie Ngek assisted in the revision of the protocol and the initial draft. Daniel Tchamdeu reviewed the initial draft. Patrick Fouegap performed the data analysis. Gilles Wandji Yebchue supervised and reviewed the final version of the study. Phillipe Lingodesigned the study and supervised the entire process, providing strategic guidance.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAllison JE, Tekawa IS, Ransom LJ, Adrain AL. A comparison of fecal occult-blood tests for colorectal-cancer screening. N Engl J Med. 1996;334(3):155\u0026ndash;159.\u003c/li\u003e\n\u003cli\u003eSiegel RL, Miller KD, Jemal A. Cancer statistics, 2020. CA Cancer J Clin. 2020;70(1):7\u0026ndash;30.\u003c/li\u003e\n\u003cli\u003eNdam EC, Pefura Yone EW, Afane Ze E. Colorectal cancer in Cameroon: a growing concern. J Afr Cancer. 2019;11(2):73\u0026ndash;78.\u003c/li\u003e\n\u003cli\u003eTakang L, Atashili J, Fon PN. Diagnostic tools for colorectal cancer screening in resource-limited settings. Pan Afr Med J. 2020;36:311.\u003c/li\u003e\n\u003cli\u003eYoung GP, Symonds EL, Allison JE. Advances in fecal occult blood tests: the FIT revolution. Dig Dis Sci. 2015;60(3):609\u0026ndash;619.\u003c/li\u003e\n\u003cli\u003eLee JK, Liles EG, Bent S, Levin TR, Corley DA. Accuracy of fecal immunochemical tests for colorectal cancer. Ann Intern Med. 2014;160(3):171\u0026ndash;181.\u003c/li\u003e\n\u003cli\u003eIrabor DO, Adedeji OA. Colorectal cancer in Nigeria: 40 years on. A review. Eur J Cancer Care (Engl). 2009;18(2):110\u0026ndash;115.\u003c/li\u003e\n\u003cli\u003eHisham A, Khaled H. Colorectal cancer in Africa: special features and present status. South Afr J Surg. 2021;59(1):5\u0026ndash;10.\u003c/li\u003e\n\u003cli\u003eSd-bioline-fob.pdf [Internet]. [cit\u0026eacute; 30 mars 2025]. Disponible sur: https://maxanim.com/content/abbott/sd-bioline/sd-bioline-fob.pdf\u003c/li\u003e\n\u003cli\u003eN\u0026apos;Guessan E, et al. Profile \u0026eacute;pid\u0026eacute;miologique du cancer colorectal en C\u0026ocirc;te d\u0026rsquo;Ivoire. Bull Cancer. 2020;107(5):456\u0026ndash;460.\u003c/li\u003e\n\u003cli\u003eDiouf ML, et al. Le cancer colorectal au S\u0026eacute;n\u0026eacute;gal: aspects cliniques et anatomopathologiques. Rev Afr Med Int. 2018;9(3):12\u0026ndash;16.\u003c/li\u003e\n\u003cli\u003eAl-Brahim N, et al. Colorectal cancer screening uptake in Kuwait: demographic and gender considerations. BMC Public Health. 2019;19(1):499.\u003c/li\u003e\n\u003cli\u003eKouassi JC, et al. Etude \u0026eacute;pid\u0026eacute;miologique des cancers digestifs en C\u0026ocirc;te d\u0026rsquo;Ivoire. Afr J Gastroenterol Hepatol. 2018;10(2):34\u0026ndash;40.\u003c/li\u003e\n\u003cli\u003eAmerican Cancer Society. Colorectal Cancer Facts \u0026amp; Figures 2020\u0026ndash;2022. Atlanta: ACS; 2020.\u003c/li\u003e\n\u003cli\u003eWools A, Dapper EA, de Leeuw JRJ. Colorectal cancer screening participation: a systematic review. Eur J Public Health. 2016;26(1):158\u0026ndash;168.\u003c/li\u003e\n\u003cli\u003eOu\u0026eacute;draogo N, et al. Les indications de coloscopie au Burkina Faso. Rev Afr Med Prat. 2021;12(1):45\u0026ndash;49.\u003c/li\u003e\n\u003cli\u003eKoffi K, et al. Profil endoscopique du cancer colorectal \u0026agrave; Abidjan. Rev Afr Gastroent\u0026eacute;rol. 2017;9(1):10\u0026ndash;14.\u003c/li\u003e\n\u003cli\u003eIssa IA, Noureddine M. Colorectal cancer screening: an updated review of the available options. World J Gastroenterol. 2017;23(28):5086\u0026ndash;5096.\u003c/li\u003e\n\u003cli\u003eRockey DC, Paulson E, Niedzwiecki D. Analysis of dietary influences on guaiac-based fecal occult blood test outcomes. Clin Gastroenterol Hepatol. 2006;4(2):273\u0026ndash;278.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable I:\u0026nbsp;\u003c/strong\u003eSociodemographic and Clinical Characteristics of the Study Population: Comparative Study of SD BIOLINE FOB\u0026reg; and HEMOCCULT\u0026reg; in Colorectal Cancer Screening (November 2021 - August 2022)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber (n = 108)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercentage (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian Age\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e48.49 \u0026plusmn; 15.4 years (Range: 1-84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e67.59%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e32.40%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIndications for Colonoscopy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eAbdominal pain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e52.38%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eConstipation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e30.56%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eAltered general status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e31.48%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eDiarrhea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e21.56%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eFollow-up for inflammatory bowel disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e3.70%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eCRC screening\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e15.74%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eAbdominal mass\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e12.03%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eNormal radiological picture\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e10.15%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eMonitoring after polypectomy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e8.33%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eAnemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e10.18%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable II:\u0026nbsp;\u003c/strong\u003eDetection of Colorectal Anomalies According to the Type of FOBT Used: A Comparative Study of SD BIOLINE FOB\u0026reg; and HEMOCCULT\u0026reg; (November 2021 - August 2022)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"680\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 37.0588%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 62.9412%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNombre d\u0026apos;anomalies d\u0026eacute;tect\u0026eacute;es par la M\u0026eacute;thode :\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 37.0588%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnomalies Found on Colonoscopy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.3529%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSD BIOLINE FOB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.5882%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;Hemoccult (Ga\u0026iuml;ac)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 37.0588%;\"\u003e\n \u003cp\u003ePolypes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.3529%;\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.5882%;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 37.0588%;\"\u003e\n \u003cp\u003eDiverticules\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.3529%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.5882%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 37.0588%;\"\u003e\n \u003cp\u003eUlc\u0026eacute;rations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.3529%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.5882%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 37.0588%;\"\u003e\n \u003cp\u003eL\u0026eacute;sions bourgeonnantes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.3529%;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.5882%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 37.0588%;\"\u003e\n \u003cp\u003eUlc\u0026eacute;rons bourgeonnantes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.3529%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.5882%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 37.0588%;\"\u003e\n \u003cp\u003eAutres l\u0026eacute;sions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.3529%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.5882%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 37.0588%;\"\u003e\n \u003cp\u003eBourrelets h\u0026eacute;morro\u0026iuml;daires\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.3529%;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.5882%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable III:\u0026nbsp;\u003c/strong\u003eComparative Distribution of Test Results Between Hemoccult\u0026reg; and SD BIOLINE FOB\u0026reg;: Insights from a Colorectal Cancer Screening Study in Yaound\u0026eacute; and Douala (November 2021 - August 2022)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTest\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePositive (n)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNegative (n)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrequency (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eHEMOCCULT \u0026reg;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e31.48%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eSD BIOLINE FOB\u0026reg;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e45.37%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable IV:\u0026nbsp;\u003c/strong\u003eDiagnostic Performance Metrics of the Guaiac-Based HEMOCCULT\u0026reg; Test Compared to Colonoscopy: Findings from a Comparative Study in Yaound\u0026eacute; and Douala (November 2021 - August 2022)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 67.9831%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.0169%;\"\u003e\n \u003cp\u003e\u003cstrong\u003evalue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 67.9831%;\"\u003e\n \u003cp\u003eTrue Positives (VP)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.0169%;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 67.9831%;\"\u003e\n \u003cp\u003eFalse Positives (FP)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.0169%;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 67.9831%;\"\u003e\n \u003cp\u003eFalse Negatives (FN)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.0169%;\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 67.9831%;\"\u003e\n \u003cp\u003eTrue Negatives (VN)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.0169%;\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 67.9831%;\"\u003e\n \u003cp\u003ePositive Predictive Value (PPV)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.0169%;\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 67.9831%;\"\u003e\n \u003cp\u003eNegative Predictive Value (NPV)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.0169%;\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 67.9831%;\"\u003e\n \u003cp\u003eYouden\u0026apos;s Index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.0169%;\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable V:\u0026nbsp;\u003c/strong\u003eDiagnostic Performance Metrics of the Immunological SD BIOLINE FOB\u0026reg; Test Compared to Colonoscopy: Results from a Colorectal Cancer Screening Study in Yaound\u0026eacute; and Douala (November 2021 - August 2022)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 67.9831%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.0169%;\"\u003e\n \u003cp\u003e\u003cstrong\u003evalue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 67.9831%;\"\u003e\n \u003cp\u003eTrue Positives (VP)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.0169%;\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 67.9831%;\"\u003e\n \u003cp\u003eFalse Positives (FP)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.0169%;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 67.9831%;\"\u003e\n \u003cp\u003eFalse Negatives (FN)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.0169%;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 67.9831%;\"\u003e\n \u003cp\u003eTrue Negatives (VN)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.0169%;\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 67.9831%;\"\u003e\n \u003cp\u003ePositive Predictive Value (PPV)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.0169%;\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 67.9831%;\"\u003e\n \u003cp\u003eNegative Predictive Value (NPV)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.0169%;\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 67.9831%;\"\u003e\n \u003cp\u003eYouden\u0026apos;s Index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.0169%;\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\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":"","lastPublishedDoi":"10.21203/rs.3.rs-7727841/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7727841/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOccult blood testing (OBT) is a non-invasive method crucial for detecting microscopic gastrointestinal bleeding, often associated with colorectal cancer(CRC), the second most cause of death from cancer worldwide .CRC is the second most frequent digestive cancer in Cameroun , although there is no national screening program.Two types of OBT methods are cmmmonly employed :The classical guaiac-based occult blood test (gFOBT), and the immunological fecal occult blood test (iFOBT), which demonstrates superior diagnostic performance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003cbr\u003e\n\u003c/strong\u003eA cross-sectional study was conducted from November 2, 2021, to August 20, 2022, in four health facilities. Adults over 21 years scheduled for colonoscopy were enrolled. Diagnostic accuracy indicators (sensitivity, specificity) of both tests were assessed against colonoscopy results.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003cbr\u003e\n\u003c/strong\u003eOf 323 patients screened , 108 were eligible .SD BIOLINE FOB® detected occult blood in 45.37% of cases, while Hemocult® detected it in 31.48 %. SD BIOLINE FOB® had higher sensitivity (68%) than Hemoccult® (41%), with both tests reaching 79 % specificity. It also revealed a greater number of abnormalities such as polyps and hemorrhoidal folds.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003cbr\u003e\n\u003c/strong\u003eCompared to Hemoccult®, SD BIOLINE FOB® demonstrated superior sensitivity and lesion detection. Its use could be a valuable option in CRC screening strategies, especially in resource limited contexts like Cameroon. However, larger studies are necessary to consolidate these findings.\u003c/p\u003e","manuscriptTitle":"Comparative Study of Two Methods for Detecting Occult Blood in Stool: SD BIOLINE FOB® and HEMOCCULT® in Healthcare Facilities in Yaoundé and Douala","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-11 16:26:00","doi":"10.21203/rs.3.rs-7727841/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":"2622f9dc-cb2d-46c3-b02a-19bc1c2ce756","owner":[],"postedDate":"November 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-17T10:39:23+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-11 16:26:00","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7727841","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7727841","identity":"rs-7727841","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}