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QUADAS-3: A Revised Tool for the Quality Assessment of Diagnostic Test Accuracy Studies
Open accessAbstract
Assessing risk of bias and applicability is critical in diagnostic test accuracy reviews to ensure valid, relevant findings that can inform decision making and policy. This article introduces QUADAS-3, an updated version of the widely used QUADAS-2 tool that was developed in response to the latest evidence, feedback from users of QUADAS-2, and comprehensive piloting. The QUADAS-3 tool comprises 6 phases: 1) define the systematic review synthesis question, 2) define the ideal test accuracy trial for each synthesis question, 3) draw a flow diagram, 4) identify estimates of accuracy for assessment, 5) assess risk of bias and applicability, and 6) make an overall judgment. Risk of bias is assessed across 4 domains: Participants, Index Test, Target Condition, and Analysis. The first 3 domains are also assessed in terms of concerns regarding applicability to the synthesis question. Signaling questions are included to help judge risk of bias. The QUADAS-3 tool incorporates several changes compared with the previous version (QUADAS-2) which will ideally improve its validity, usability, and usefulness. Key changes from QUADAS-2 include introduction of the concept of an ideal test accuracy trial, assessment at the estimate level rather than the study level, replacement of the "Flow and Timing" domain with a new "Analysis" domain, introduction of sections on the rationale for judgments, and formal introduction of overall judgment of risk of bias and concerns regarding applicability. Some changes to domains and signaling questions have also been made.
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RoB 2: a revised tool for assessing risk of bias in randomised trials
Sterne, J. A. C., Savović, J., Page, M. J., Elbers, R. G., Blencowe, N. S., Boutron, I., Cates, C. J., Cheng, H.-Y., Corbett, M. S., Eldridge, S. M., et al. (2019) · BMJ · doi:10.1136/bmj.l4898 · Cited by 34,787
Self-citationROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions
Sterne, J. A., Hernán, M. A., Reeves, B. C., Savović, J., Berkman, N. D., Viswanathan, M., Henry, D., Altman, D. G., Ansari, M. T., Boutron, I., et al. (2016) · BMJ · doi:10.1136/bmj.i4919 · Cited by 20,329
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Whiting, P. F., Rutjes, A. W. S., Westwood, M. E., Mallett, S., Deeks, J. J., Reitsma, J. B., Leeflang, M. M. G., Sterne, J. A. C., Bossuyt, P. M. M., & the QUADAS-2 Group* (2011) · Annals of Internal Medicine · doi:10.7326/0003-4819-155-8-201110180-00009 · Cited by 14,199
Self-citationWhiting, P., Rutjes, A. W., Reitsma, J. B., Bossuyt, P. M., & Kleijnen, J. (2003) · BMC Medical Research Methodology · doi:10.1186/1471-2288-3-25 · Cited by 3,592
Self-citationQUADAS-C: A Tool for Assessing Risk of Bias in Comparative Diagnostic Accuracy Studies
Yang, B., Mallett, S., Takwoingi, Y., Davenport, C. F., Hyde, C., Whiting, P. F., Deeks, J. J., Leeflang, M., & the QUADAS-C Group† (2021) · Annals of Internal Medicine · doi:10.7326/m21-2234 · Cited by 341
Self-citationA systematic review classifies sources of bias and variation in diagnostic test accuracy studies
Whiting, P. F., Rutjes, A. W. S., Westwood, M. E., & Mallett, S. (2013) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2013.05.014 · Cited by 283
Self-citationAssessing risk of bias and applicability
Reitsma, J. B., Rutjes, A. W., Whiting, P. F., Yang, B., Leeflang, M., Bossuyt, P. M., & Deeks, J. J. (2023) · Wiley eBooks · doi:10.1002/9781119756194.ch8 · Cited by 50
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Gasem, M. H., Smits, H. L., Goris, M. G. A., & Dolmans, W. M. V. (2002) · Journal of Medical Microbiology · doi:10.1099/0022-1317-51-2-173 · Cited by 44
di Ruffano, L. F., Harris, I. M., Zhelev, Z., Davenport, C. F., Mallett, S., Peters, J., Takwoingi, Y., Deeks, J. J., & Hyde, C. (2023) · International Journal of Technology Assessment in Health Care · doi:10.1017/s0266462323000065 · Cited by 32
Self-citationDavenport, C. F., Rutjes, A. W., Mallett, S., Tomlinson, E., Yang, B., Holmes, J., Westwood, M. E., Takwoingi, Y., Reitsma, J. B., Hyde, C., et al. (2026) · Annals of Internal Medicine · doi:10.7326/annals-25-04943 · Cited by 9
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Tomlinson, E., Yang, B., Davenport, C. F., Rutjes, A. W., Mallett, S., & Whiting, P. F. (2025) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2025.111983 · Cited by 6
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Davenport, C. F., Rutjes, A. W., Mallett, S., Tomlinson, E., Yang, B., Holmes, J., Westwood, M. E., Takwoingi, Y., Reitsma, J. B., Hyde, C., et al. (2026) · Annals of Internal Medicine · doi:10.7326/annals-25-04943 · Cited by 9
Self-citationWu, C., Bartak, A., & Sharma, R. (2026) · Frontiers in Oncology · doi:10.3389/fonc.2026.1870768 · Cited by 2
Generative AI and Large Language Models in Rehabilitation: A Scoping Review
Cha, S. (2026) · Life · doi:10.3390/life16081310 · Cited by 2
Jedliński, M., Jedliński, A., Rostkowski, G., Janiszewska‐Olszowska, J., & Mazur, M. (2026) · Journal of Clinical Medicine · doi:10.3390/jcm15093373 · Cited by 1
Nigam, J. S., Rath, A., Bharti, J. N., & Pradeep, I. (2026) · Diagnostic Cytopathology · doi:10.1002/dc.70152 · Cited by 1
PECORARO, V., per il Gruppo di Studio SIBioC Medicina di Laboratorio Basata sulle Evidenze e, H. T. A., Vassalle, C., PISANI, K., Fasano, T., & Fasano, T. (2026) · Biochimica Clinica · doi:10.23736/s0393-0564.26.00205-0 · Cited by 1
Banala, M., Ezuddin, S., Foley, M., & Kuker, R. A. (2026) · Frontiers in Nuclear Medicine · doi:10.3389/fnume.2026.1935247 · Cited by 1
Gil, A. M. C., Galdames, I. S., Vázquez, L. P., Velázquez, M. S., & Menendez, J. J. (2026) · Diagnostics · doi:10.3390/diagnostics16182995 · Cited by 1
Khanzadeh, H., AziziGermi, S., Mokhlesi, A., Gheisari, R., Çakmak, G., Molinero‐Mourelle, P., Roccuzzo, A., & Mosaddad, S. A. (2026) · Journal of Prosthodontics · doi:10.1111/jopr.70245 · Cited by 1
Schouten, J. C., Huygen, F. J. P. M., & Tiemensma, J. (2026) · Journal of Clinical Medicine · doi:10.3390/jcm15103740 · Cited by 1
Hung, H.-Y., Su, P.-A., Lai, P.-C., & Huang, Y.-T. (2026) · Diagnostics · doi:10.3390/diagnostics16071110
Anghel, R., Moga, V.-L., Folea, A.-R., Zgura, A. F., Serbanescu, L. G., Toma, R.-V., Marinescu, Ș., Şerban, A.-I., & Bîlteanu, L. (2026) · Frontiers in Oncology · doi:10.3389/fonc.2026.1744385
Nguyen, T. T., Tran, T. H., Shahait, M., Tran, Q. S., Duong, N. X., Nguyen, D., Dobbs, R. W., Huu, H. P., Ngo, X. T., Khanmammadova, N., et al. (2026) · Research Square · doi:10.21203/rs.3.rs-10059315/v1
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Grover, P., Kaur, G., Jain, R., Singh, K., & Singh, B. (2026) · Advances in Molecular Imaging · doi:10.4236/ami.2026.152002
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Vandeputte, F.-J., Sergooris, A., Roose, S., Timmermans, A. A. A., & Corten, K. (2026) · Journal of Clinical Medicine · doi:10.3390/jcm15155912
Wang, Y.-C., Chen, Y., & Yang, C. (2026) · Research Square · doi:10.21203/rs.3.rs-10350569/v1
Cordeiro, G. D. O., Martins, C. D. C., Vieira, T. D. O., Ramos, M. D. S. X., & Vieira, G. O. (2026) · Aracê. · doi:10.56238/arev8n8-030
Cuandra, K. N., Karyana, D. N. N., Saputri, A. Y. F., Putra, H. H., Besari, A. R., Karera, A. D., Gusvania, A. A., Syahroni, M. A., Soekiono, C. J., Mahyoniariasih, N. K., et al. (2026) · European Journal of Pediatrics · doi:10.1007/s00431-026-07324-4
Nigam, J. S., Rath, A., Bharti, J. N., & Pradeep, I. (2026) · Diagnostic Cytopathology · doi:10.1002/dc.70199
Wang, T., Hong, J., Liu, H.-R., Wu, K.-T., Fu, H.-N., Lee, Y., Liao, P.-H., Huang, G.-H., Chen, I., Yin, W., et al. (2026) · European Journal of Radiology · doi:10.1016/j.ejrad.2026.113189
Arnautu, E. M., Pleșea, E. L., Zlatian, O. M., Camen, G. C., Mititelu, R. R., Osman, A., Țieranu, M.-L., Golli, A. L., & Ghenea, A. E. (2026) · Microorganisms · doi:10.3390/microorganisms14091908
Lockwood, P., & Barrett, E. (2026) · BMJ Open · doi:10.1136/bmjopen-2026-118511
Kaltsas, A., Markou, E., Zachariou, A., Dimitriadis, F., & Sofikitis, N. (2026) · Genes · doi:10.3390/genes17091074
Mopti, A. N. M. A., Alqahtani, A. M., & Alshehri, A. H. D. (2026) · Diagnostics · doi:10.3390/diagnostics16182900
Ahmed, A. U., Kausar, Z., & Niazi, M. (2026) · Cureus · doi:10.7759/cureus.118520
Neri, G., Mazza, G., Ielapi, J., Russo, A., Serapide, F., Mastrangelo, H., Mesiti, A., Caroleo, Z., Fresilli, S., Bruni, A., et al. (2026) · Journal of Fungi · doi:10.3390/jof12090681
King, D. A., Hume, P. A., Clark, T. N., Pearce, A. J., & Hecimovich, M. D. (2026) · Research Square · doi:10.21203/rs.3.rs-10782032/v1
Methods for Development of AAGL Clinical Practice Guidelines
Xu, X. J., Garcia-Filion, P., Hackett, L. A., Siegel, A., & Kho, R. M. (2026) · Journal of Minimally Invasive Gynecology · doi:10.1016/j.jmig.2026.09.003
Zhang, M., Tang, B., Dai, H., Huang, W., Bai, W., He, J., & Chen, Q. (2026) · European Radiology Experimental · doi:10.1186/s41747-026-00803-1
Foundation models and taxonomy inference for metagenomics: A practical review
Schoier, A. F., de Castro, Í. M. S., & Dorn, M. (2026) · Computational Biology and Chemistry · doi:10.1016/j.compbiolchem.2026.109409
Murray, C., Temperley, H. C., Doyle, R. S., Khair, A. M., Jagiello, M., John, A., & O’Callaghan, P. (2026) · Echocardiography · doi:10.1111/echo.70630
Zhou, H., Liu, L., Fu, B., Cao, B., Ma, J., Yang, K., Bao, Y., Yang, F., & Lian, X. (2026) · Journal of Medical Internet Research · doi:10.2196/105068
Artificial Intelligence in Emergency Medical Call-Taking and Dispatch Operations: A Scoping Review
Lee, D. H., Kim, M. J., & Chang, H. (2026) · Healthcare · doi:10.3390/healthcare14193176
Martins, C. C., Bhosale, A. S., Urquhart, O., Verdugo‐Paiva, F., Lee, G. H., O’Brien, K. K., Rojas-Gómez, A. M., Glick, M., Lingen, M. W., Chaturvedi, A. K., et al. (2026) · The Journal of the American Dental Association · doi:10.1016/j.adaj.2026.08.007
Das, S. (2026) · arXiv (Cornell University) · doi:10.48550/arxiv.2609.35240
Bisiaux, T., da Costa, J. M., Martins, R. C., & Barroso, T. (2026) · The Veterinary Journal · doi:10.1016/j.tvjl.2026.106914
Lunger, F., Burillo, L., Meza, N., Franco, J. V. A., Rivero, T. M., & Kaderli, R. M. (2026) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd016398
Sahloul, S., Englebert, L., Aryanpour, S., & Boukpessi, T. (2026) · Journal of Endodontics · doi:10.1016/j.joen.2026.09.014
Terzi, O. E., Demirdöğen, E., Öztürk, N. A. A., Güçlü, Ö. A., & Ursavaş, A. (2026) · Medicine · doi:10.1097/md.0000000000050981
Bendifallah, S., Chapron, C., Petraglia, F., & D’Hooghe, T. (2026) · European Journal of Obstetrics & Gynecology and Reproductive Biology · doi:10.1016/j.ejogrb.2026.115487
Hu, X., Wang, L., Shi, J., Fernández-Bussy, S., & Liu, D. (2026) · Respiration · doi:10.1159/res/aepag020
Aggarwal, R. V., Sharma, A., Murphy, H., Bhuvanesan, N., & Li, N. (2026) · Journal of the Society for Cardiovascular Angiography & Interventions · doi:10.1016/j.jscai.2026.105744
Bucolo, G. M., Gaeta, M., Blandino, A., Vinci, S. L., Cau, R., Booz, C., Vogl, T. J., Koch, V., Gruenewald, L. D., Yel, İ., et al. (2026) · Journal of Clinical Medicine · doi:10.3390/jcm15207870
Șușu, O.-I., Botoncea, M., Serac, G., Beleaua, M. A., Sipos, T.-C., Tăurean, O. A., Molnár, D., Șipoș, R.-S., & Pap, Z. (2026) · Medicina · doi:10.3390/medicina62101974
Kachmar, V., Mikhlin, R., Danko, T., & Shmal, A. (2026) · Cureus · doi:10.7759/cureus.117978
Yassen, K. A., Görlinger, K., Alzimami, L. Z., Alswilem, N. S., Almutairi, A. A., Alsagheer, M., Alwayel, H., Alkhalaf, A. M. A., Aljamaan, N. H., Alqurqush, N., et al. (2026) · Journal of Clinical Medicine · doi:10.3390/jcm15208048
Tuuk, A. L. Z., & Legrans, H. R. P. (2026) · The International Journal of Medical Science and Health Research · doi:10.70070/386qqf40
van Daalen, L. E., Schueler, B. L. F., Collinson, P. O., & Backus, B. E. (2026) · European Journal of Emergency Medicine · doi:10.1097/mej.0000000000001381
Lersten, A. K., & Dolan, C. B. (2026) · Frontiers in Public Health · doi:10.3389/fpubh.2026.1885854
Evidence-Based Anthropometric Evaluation Methods for Obesity: A Systematic Review
Bagwan, H. A., Shinde, S., Ambali, M. P., Shinde, R. V., Vani, A., & Joshi, A. G. (2026) · Cureus · doi:10.7759/cureus.118331
Li, Y., Wu, F., Liu, W., He, X., & Chen, C. (2026) · Epigenomics · doi:10.1080/17501911.2026.2751832
Ricci, E., Magrini, E., Vincenti, M., Berardino, M., Bianchi, F., Nardi, N., & Prestipino, M. (2026) · Journal of Pediatric Surgery · doi:10.1016/j.jpedsurg.2026.163544
Chen, J., Zhou, Q., Zhang, Y., 陈建良, Zheng, X., & Ye, F. (2026) · Frontiers in Medicine · doi:10.3389/fmed.2026.1936572
Kamandi, N., Mohammadzadeh, S., Mirzai, M., Ghasemi, M., Elyassirad, D., Agah, S. A. A., & Firouznia, K. (2026) · Journal of Imaging Informatics in Medicine · doi:10.1007/s10278-026-02419-8
Luo, H., Huang, X., Yu, Q., Li, Q., & Zha, H. (2026) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2026.1986098
Lockwood, P., & Barrett, E. (2026) · BMJ Open · doi:10.1136/bmjopen-2026-124306
Medvediev, M. V., Nuriieva, J., Medvedieva, N., Pampukha, P., & Tinelli, A. (2026) · Therapeutic Advances in Reproductive Health · doi:10.1177/26334941261502486
Du, Y., Teoh, Y. J., & Abir, I. A. (2026) · Physics and Chemistry of the Earth Parts A/B/C · doi:10.1016/j.pce.2026.104961
Mazoba, T. K., Mbuyamba, G. M., Yanda, S. T., Zakayi, P. K., Katalay, P. K., & Molua, A. A. (2026) · Neuroscience Informatics · doi:10.1016/j.neuri.2026.100305
Qiu, Q., Qiu, Q., & Zhang, J. (2026) · Research Square · doi:10.21203/rs.3.rs-10974067/v1
Metadata
- Authors
- Whiting, P. F., Tomlinson, E., Rutjes, A. W. S., Davenport, C. F., Yang, B., Westwood, M. E., Takwoingi, Y., Reitsma, J. B., Hyde, C., Bossuyt, P. M. M., Deeks, J. J., Leeflang, M. M. G., & Mallett, S.
- Affiliations
- University of Bristol (GB)
- Saint Camillus International University of Health and Medical Sciences (IT)
- National Institute for Health and Care Research (GB)
- Amsterdam University Medical Centers (NL)
- Utrecht University (NL)
- University of Exeter (GB)
- UCL Centre for Medical Imaging, University College London, London, United Kingdom (S.M.).
- ORCID
- Venue
- Annals of Internal Medicine
- Publisher
- American College of Physicians
- Published
- 2026-04
- Volume
- 179
- Issue
- 4
- Pages
- 548-555
- ISSN
- 0003-4819 (ISSN-L)
- 1539-3704
- OpenAlex
- W7129060162
- Semantic Scholar
- ceb4a6d2e452212b5ca8298a82ed8df14aa60dcc
- Cited by
- 60
- References
- 11
- Citations by year
- 2026: 60
- FWCI
- 144.80
- Type
- journal article
- Language
- en
- Open access
- Locations
- Annals of Internal Medicine (publishedVersion)
- PubMed (publishedVersion)
- University of Birmingham Research Portal (University of Birmingham) (publishedVersion)
- Explore Bristol Research (publishedVersion, cc-by)
- Bristol Research (University of Bristol) (publishedVersion, cc-by)
- Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Clinical practice guidelines implementation
- Keywords
- QUADAS-2, diagnostic accuracy, risk of bias, applicability, quality assessment tools, flowcharts, meta-analysis of diagnostic accuracy
- MeSH terms
- Systematic Reviews as Topic, Diagnostic Tests, Routine, Humans, Bias
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