IJCM_129A: Is intelligent Breast Exam (iBE) a sensitive and specific test compared with mammography in the early detection of breast cancer and patient triage in adults? A Diagnostic review and Meta-analysis

Abstract

Background: Breast cancer represents the most common cause of cancer death among women globally. Early cancer detection in low-income countries is difficult because of the relatively expensive mammographic screening. Intelligent Breast Exam [iBE] is a portable device that is available at low cost and provides electronic documentation for additional diagnostic workup. Objectives: This study aims to investigate the diagnostic accuracy of i breast device in the early detection of breast cancer and patient triage in adults. Secondary objectives: 1) To review the usability of i Breast device as a triage test for breast pathologies in primary care setting. 2) To review the feasibility, ease and cost-effectiveness of i Breast device Methodology: A systematic literature search of the MEDLINE, Embase and Cochrane Library databases will be performed to identify the studies reporting the accuracy of i breast device for the detection of breast cancer from January 2010 to December 2023. The search strategy will be carried out by using key words and MeSH (Medical Subject Headings) terms. The reference test will be mammogram. The search will be in accordance with the PRISMA-DTA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses of Diagnostic Test Accuracy studies) guidelines. Two reviewer authors will independently screen the results. The full-text articles will be reviewed when studies meet the inclusion criteria or in any uncertainty. Non-consensus will be resolved by a third reviewer. The quality of the studies will be examined using the QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies) tool. The review will be registered with PROSPERO (Prospective Register of Systematic Reviews). The estimates of sensitivity, specificity and area under the curve will be attempted using the bivariate model for the diagnostic meta-analysis.