EFFECTIVENESS AND COST-EFFECTIVENESS OF DOUBLE READING IN DIGITAL MAMMOGRAPHY SCREENING: A SYSTEMATIC REVIEW AND META-ANALYSIS
DOI:
https://doi.org/10.53555/nnmhs.v9i5.1656Keywords:
Digital Mammography, Double Reading, Systematic Review, Meta Analysis, Single ReadingAbstract
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.
References
. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021 May;71(3):209–49.
. Gondhowiardjo S, Christina N, Ngakan ;, Ganapati PD, Hawariy S, Radityamurti F, et al. Five-Year Cancer Epidemiology at the National Referral Hospital: Hospital-Based Cancer Registry Data in Indonesia. JCO Global Oncol. 2021;7:190–203.
. Takahashi R, Toh U, Iwakuma N, Mishima M, Fujii T, Takenaka M, et al. Treatment outcome in patients with stage III breast cancer treated with neoadjuvant chemotherapy. Exp Ther Med. 2013 Nov;6(5):1089–95.
. Deanasa RS, Umar M, Fitri AD. Overall Survival for Stage III Breast Cancer Patients at DR. Mohammad Hoesin General Hospital Palembang and the Influencing Factors. Indonesian Journal of Cancer. 2022 Dec 28;16(4):231.
. Prusty RK, Begum S, Patil A, Naik DD, Pimple S, Mishra G. Knowledge of symptoms and risk factors of breast cancer among women: A community based study in a low socio-economic area of Mumbai, India. BMC Womens Health. 2020 May 18;20(1).
. Guo F, Kuo Y fang, Shih YCT, Giordano SH, Berenson AB. Trends in breast cancer mortality by stage at diagnosis among young women in the United States. Cancer. 2018 Sep 1;124(17):3500–9.
. Taheri M, Tavakol M, Akbari ME, Almasi-Hashiani A, Abbasi M. Relationship of Socio Economic Status, Income, and Education with the Survival Rate of Breast Cancer: A Meta-Analysis. Iran J Public Health. 2019;48(8):1428–38.
. Solikhah S, Perwitasari DA, Rejeki DSS. Geographic Characteristics of Various Cancers in Yogyakarta Province, Indonesia: A Spatial Analysis at the Community Level. Asian Pacific Journal of Cancer Prevention. 2022;23(4):1231–8.
. Icanervilia A V., van der Schans J, Cao Q, de Carvalho AC, Cordova-Pozo K, At Thobari J, et al. Economic evaluations of mammography to screen for breast cancer in low- and middle-income countries: A systematic review. J Glob Health. 2022 Jul 16;12:04048.
. Schünemann HJ, Lerda D, Quinn C, Follmann M, Alonso-Coello P, Rossi PG, et al. Breast cancer screening and diagnosis: A synopsis of the european breast guidelines. Ann Intern Med. 2020 Jan 7;172(1):46–56.
. Zeeshan M, Salam B, Khalid QSB, Alam S, Sayani R. Diagnostic Accuracy of Digital Mammography in the Detection of Breast Cancer. Cureus. 2018 Apr 8;
. Sankatsing VDV, Juraniec K, Grimm SE, Joore MA, Pijnappel RM, de Koning HJ, et al. Cost-effectiveness of digital breast tomosynthesis in population-based breast cancer screening: A probabilistic sensitivity analysis. Radiology. 2020 Oct 1;297(1):40–8.
. Brennan PC, Ganesan A, Eckstein MP, Ekpo EU, Tapia K, Mello-Thoms C, et al. Benefits of Independent Double Reading in Digital Mammography: A Theoretical Evaluation of All Possible Pairing Methodologies. Acad Radiol. 2019 Jun 1;26(6):717–23.
. Gossner J. Digital mammography in young women: Is a single view sufficient? Journal of Clinical and Diagnostic Research. 2016 Mar 1;10(3):10–2.
. Sato M, Kawai M, Nishino Y. Cost-effectiveness analysis for breast cancer screening?: double reading versus single + CAD reading. Breast Cancer. 2014;21:532–41.
. Posso M, Puig T, Carles M, Rué M, Canelo-Aybar C, Bonfill X. Effectiveness and cost-effectiveness of double reading in digital mammography screening: A systematic review and meta-analysis. Eur J Radiol. 2017;96:40–9.
. Posso MC, Puig T, Quintana MJ, Solà-Roca J, Bonfill X. Double versus single reading of mammograms in a breast cancer screening programme: a cost-consequence analysis. Eur Radiol. 2016;26(9):3262–71.
. Posso M, Carles M, Rué M, Puig T, Bonfill X. Cost-effectiveness of double reading versus single reading of mammograms in a breast cancer screening programme. PLoS One. 2016;11(7).
. Taylor P, Potts H, Wilkinson L, Given-Wilson R. Impact of CAD with full field digital mammography on workflow and cost. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2010. p. 1–8.
. Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. Vol. 372, The BMJ. BMJ Publishing Group; 2021.
. Whiting PF, Rutjes AWS, Westwood ME, Mallett S, Deeks JJ, Reitsma JB, et al. QUADAS-2: A Revised Tool for the Quality Assessment of Diagnostic Accuracy Studies. Ann Intern Med. 2011;155(8):1–10.
. Husereau D, Drummond M, Augustovski F, De Bekker-Grob E, Briggs AH, Carswell C, et al. Consolidated Health Economic Evaluation Reporting Standards 2022 (CHEERS 2022) statement: Updated reporting guidance for health economic evaluations. Vol. 376, The BMJ. BMJ Publishing Group; 2022.
. Houssami N, Macaskill P, Bernardi D, Caumo F, Pellegrini M, Brunelli S, et al. Breast screening using 2D-mammography or integrating digital breast tomosynthesis ( 3D-mammography ) for single-reading or double-reading – Evidence to guide future screening strategies. Eur J Cancer. 2014;50(May 2012):1799–807.
. Weigel S. Digital mammography screening?: sensitivity of the programme dependent on breast density. Eur Radiol. 2016;27:2744–51.
. Houssami N, Bernardi D, Pellegrini M, Valentini M, Fantò C, Ostillio L, et al. Breast cancer detection using single-reading of breast tomosynthesis (3D-mammography) compared to double-reading of 2D-mammography: Evidence from a population-based trial. Cancer Epidemiol. 2017;47:94–9.
. Martín SR, Povedano JLR, García MC, Romero ALS, Garriguet MP, Benito MÁ. Prospective study aiming to compare 2D mammography and tomosynthesis + synthesized mammography in terms of cancer detection and recall. From double reading of 2D mammography to single reading of tomosynthesis. Eur Radiol. 2018;28(6):2484–91.
. van den Biggelaar FJHM, Kessels AGH, van Engelshoven JMA, Flobbe K. Strategies for digital mammography interpretation in a clinical patient population. Int J Cancer. 2009 Dec;125(12):2923–9.
. Coolen AMP, Voogd AC, Strobbe LJ, Louwman MWJ, Tjan-Heijnen VCG, Duijm LEM. Impact of the second reader on screening outcome at blinded double reading of digital screening mammograms. Br J Cancer. 2018 Aug 14;119(4):503–7.
. Henriksen EL, Carlsen JF, Vejborg IMM, Nielsen MB, Lauridsen CA. The efficacy of using computer-aided detection (CAD) for detection of breast cancer in mammography screening: a systematic review. Vol. 60, Acta Radiologica. SAGE Publications Inc.; 2019. p. 13–8.
. Lehman CD, Wellman RD, Buist DSM, Kerlikowske K, Tosteson ANA, Miglioretti DL. Diagnostic accuracy of digital screening mammography with and without computer-aided detection. JAMA Intern Med. 2015 Nov 1;175(11):1828–37.
. Azavedo E, Zackrisson S, Mejàre I, Heibert Arnlind M. Is single reading with computer-aided detection (CAD) as good as double reading in mammography screening? A systematic review. BMC Med Imaging. 2012 Jul 24;12.
. Kohli A, Jha S. Why CAD Failed in Mammography. Vol. 15, Journal of the American College of Radiology. Elsevier B.V.; 2018. p. 535–7.
. Dahlblom V, Andersson I, Lång K, Tingberg A, Zackrisson S, Dustler M. Artificial intelligence detection of missed cancers at digital mammography that were detected at digital breast tomosynthesis. Radiol Artif Intell. 2021 Nov 1;3(6).
. Al-antari MA, Al-masni MA, Kim TS. Deep Learning Computer-Aided Diagnosis for Breast Lesion in Digital Mammogram. In: Lee G, Fujita H, editors. Deep Learning in Medical Image Analysis: Challenges and Applications. Cham: Springer; 2018. p. 59–71.
. Taylor-Phillips S, Stinton C. Double reading in breast cancer screening: considerations for policy-making. Br J Radiol. 2020 Feb;93(1106):20190610.
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