EFFECTIVENESS AND COST-EFFECTIVENESS OF DOUBLE READING IN DIGITAL MAMMOGRAPHY SCREENING: A SYSTEMATIC REVIEW AND META-ANALYSIS - Tjiayadi, Jonathan Billy Christian; Theresia, Deborah Josephine (Journal of Advanced Research in Medical and Health Science (ISSN 2208-2425), 2023)
Background: Female breast cancer has become the global leading cause of cancer-related mortality. Although digital mammography has been proposed as an effective and cost-efficient screening method, its real performance and cost-benefit value has been debated by several studies especially concerning the available reading methods. Double reading of digital mammography has been said to increase reading sensitivity but often found some challenges in terms of cost and false positive rate. This systematic review and meta-analysis aim to evaluate the effectiveness and cost-effectiveness of double reading for digital mammography screening. Methods: This review included comparative studies and cost-effectiveness studies from databases such as Pubmed and Cochrane up to April 2023. We excluded non-English studies, cost-effectiveness studies with lacking adequate statistics, single-armed trials, study protocols, earlier meta-analyses, review articles, and studies that merely evaluated double reading of two different methodologies. Study quality was assessed using the QUADAS-2 tool and CHEERS 2022 checklist. Meta-analysis was conducted to evaluate cancer detection and false positive rate of double reading. Ten studies were included in this review, three of which were obtained from a reference article. Mammograms in this review were obtained from a total of 260,501 women. Double reading had a slightly but significant chance of finding a breast cancer (OR = 1.137; p-value = 0.004). False-positive rate in double reading was also prominent (ER = 0.041; p value = 0.000). Single reading with CAD was still proven to be a more cost-effective method. Discussion: Studies in this review was generally had low risk of bias and applicability concern. High cost of double reading may be attributed to the high number of false positive result. Integration of CAD with AI or deep learning may enhance the performance of digital mammography single reading.  Conclusion:  with consensus and arbitration, double reading strategy present itself as a screening method for breast cancer, however single reading with CAD has proven more superior as a more-cost effective method.