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A Proposed Diagnostic Algorithm for Helicobacter pylori Infection in Cameroon: A Comparison of Five Diagnostic
Stanley Ngemeshe Ngimgoh1, Kobada Maaga Marina2, Justine Laure Nguieguia Konang3
1Department of Biochemistry, University of Dschang, Dschang, CMR.
Abstract:
Introduction Helicobacter pylori (H. pylori) infection remains an important cause of gastrointestinal disease worldwide. Both direct (polymerase chain reaction (PCR), histology, and rapid urease test (RUT)) and indirect (stool antigen test (SAT) and serology) diagnostic methods have been developed, yet each technique has its own limitations and merits. In Cameroon, there is no consensus guideline for H. pylori diagnosis, and diagnostic practices vary widely across healthcare settings. Consequently, establishing an accurate, context-appropriate diagnostic algorithm is imperative to facilitate effective management in our milieu. The present study aimed to compare the diagnostic methods for H. pylori currently used in Cameroon so as to propose a context-appropriate diagnostic algorithm for this infection. Materials and methods This cross-sectional, prospective, hospital-based study enrolled 82 dyspeptic adult patients presenting with gastroduodenal symptoms. Gastric samples were tested for H. pylori using five diagnostic techniques: PCR, SAT, histology, serology, and RUT. PCR was designated as the reference test for comparative analysis. Diagnostic performance of all tests was evaluated by calculating sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy, and discriminatory power between tests was evaluated using the area under the curve (AUC) with corresponding receiver operating characteristic (ROC) curves. Statistical analyses were performed using RStudio version 4.4.1 (RStudio, Inc., Boston, MA, USA). Results H. pylori infection detection rates were as follows: PCR, 79.26%; SAT, 62.2%; histology, 45.1%; serology, 76.8%; and RUT, 73.2%. Using PCR as the reference standard, the performance characteristics of sensitivity, specificity, PPV, and NPV of histology, RUT, SAT, and serology were 52.31%, 82.35%, 91.89%, and 31.11%; 76.92%, 41.18%, 83.33%, and 31.81%; 67.69%, 58.82%, 86.27%, and 32.26%; and 81.54%, 41.18%, 84.13%, and 36.84%, respectively. The accuracy of histology, RUT, SAT, and serology was 58.54%, 57.32%, 65.85%, and 73.17%, respectively. Discriminatory ability was significantly higher for histology (AUC: 0.673) compared to RUT (AUC: 0.405) (p < 0.001). SAT showed comparable discriminatory ability (AUC: 0.633) to serology (AUC: 0.614) (p > 0.05). Conclusion Histology is the most accurate invasive test, while SAT is the most accurate non-invasive test for H. pylori diagnosis in our setting. Despite serology's high sensitivity and low specificity, its predominant use in Cameroon necessitates a pragmatic diagnostic approach. We propose the following algorithm: serology as the first-line assessment, followed by SAT or histology for confirmation in seropositive patients before treatment initiation. This algorithm balances diagnostic accuracy with resource availability and current practice patterns in Cameroon. Larger validation studies are needed to confirm this approach.
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