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Exploring sources of heterogeneity in systematic reviews of diagnostic tests
Abstract
It is indispensable for any meta‐analysis that potential sources of heterogeneity are examined, before one considers pooling the results of primary studies into summary estimates with enhanced precision. In reviews of studies on the diagnostic accuracy of tests, variability beyond chance can be attributed to between‐study differences in the selected cutpoint for positivity, in patient selection and clinical setting, in the type of test used, in the type of reference standard, or any combination of these factors. In addition, heterogeneity in study results can also be caused by flaws in study design. This paper critically examines some of the potential reasons for heterogeneity and the methods to explore them. Empirical support for the existence of different sources of variation is reviewed. Incorporation of sources of variability explicitly into systematic reviews on diagnostic accuracy is demonstrated with data from a recent review. Application of regression techniques in meta‐analysis of diagnostic tests can provide relevant additional information. Results of such analyses will help understand problems with the transferability of diagnostic tests and to point out flaws in primary studies. As such, they can guide the design of future studies. Copyright © 2002 John Wiley & Sons, Ltd.
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Cites
Quantifying heterogeneity in a meta‐analysis
Higgins, J. P. T., & Thompson, S. G. (2002) · Statistics in Medicine · doi:10.1002/sim.1186 · Cited by 36,763
Meta-analysis of Observational Studies in Epidemiology<SUBTITLE>A Proposal for Reporting</SUBTITLE>
Stroup, D. F. (2000) · JAMA · doi:10.1001/jama.283.15.2008 · Cited by 20,623
The combination of estimates from different experiments
Cochran, W. G. (1954) · Biometrics · doi:10.2307/3001666 · Cited by 5,380
Empirical evidence of design-related bias in studies of diagnostic tests.
Lijmer, J. G. (1999) · JAMA · doi:10.1001/jama.282.11.1061 · Cited by 1,861
Self-citationSystematic Review: Why sources of heterogeneity in meta-analysis should be investigated
Thompson, S. G. (1994) · BMJ · doi:10.1136/bmj.309.6965.1351 · Cited by 1,017 · cited 2×
“Heterogeneity in study results may also be caused by clinical di erences, so called clinical heterogeneity [1].”
BackgroundEvaluation of old and new tests of heterogeneity in epidemiologic meta-analysis
Takkouche, B., Cadarso-Suarez, C., & Spiegelman, D. (1999) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a009981 · Cited by 380
Moons, K. G. M., van Es, G.-A., Deckers, J. W., Habbema, J. D. F., & Grobbee, D. E. (1997) · Epidemiology · doi:10.1097/00001648-199701000-00002 · Cited by 189
Cited by
Reitsma, J. B., Glas, A. S., Rutjes, A. W. S., Scholten, R. J. P. M., Bossuyt, P. M., & Zwinderman, A. H. (2005) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2005.02.022 · Cited by 3,369
“Again, the effect of these differences in design and conduct will be estimated in the sROC approach as changes on the diagnostic odds ratio scale [8,29].”
MethodSelf-citationManea, L., Gilbody, S., & McMillan, D. (2012) · Canadian Medical Association Journal · doi:10.1503/cmaj.110829 · Cited by 1,966
Systematic Reviews of Diagnostic Test Accuracy
Leeflang, M. M. G., Deeks, J. J., Gatsonis, C., & Bossuyt, P. M. M. (2008) · Annals of Internal Medicine · doi:10.7326/0003-4819-149-12-200812160-00008 · Cited by 1,124
Self-citationManea, L., Gilbody, S., & McMillan, D. (2015) · General Hospital Psychiatry · doi:10.1016/j.genhosppsych.2014.09.009 · Cited by 795
Sperber, A. D., Dumitrascu, D., Fukudo, S., Gerson, C., Ghoshal, U. C., Gwee, K. A., Hungin, A. P. S., Kang, J.-Y., Minhu, C., Schmulson, M., et al. (2017) · Gut · doi:10.1136/gutjnl-2015-311240 · Cited by 554
-D-Glucan Assay for the Diagnosis of Invasive Fungal Infections: A Meta-analysis
Karageorgopoulos, D. E., Vouloumanou, E. K., Ntziora, F., Michalopoulos, A., Rafailidis, P. I., & Falagas, M. E. (2011) · Clinical Infectious Diseases · doi:10.1093/cid/ciq206 · Cited by 538
metandi: Meta-analysis of diagnostic accuracy using hierarchical logistic regression
Harbord, R. M., & Whiting, P. (2009) · The Stata Journal: Promoting communications on statistics and Stata · doi:10.1177/1536867x0900900203 · Cited by 453
Gao, H., McDonnell, A., Harrison, D. A., Moore, T., Adam, S., Daly, K., Esmonde, L., Goldhill, D. R., Parry, G. J., Rashidian, A., et al. (2007) · Intensive Care Medicine · doi:10.1007/s00134-007-0532-3 · Cited by 466
Malin, G. L., Morris, R. K., & Khan, K. S. (2010) · BMJ · doi:10.1136/bmj.c1471 · Cited by 461
Association Between Sarcopenia and Cognitive Impairment: A Systematic Review and Meta-Analysis
Chang, K.-V., Hsu, T.-H., Wu, W.-T., Huang, K.-C., & Han, D.-S. (2016) · Journal of the American Medical Directors Association · doi:10.1016/j.jamda.2016.09.013 · Cited by 448
Pai, M., Flores, L. L., Pai, N., Hubbard, A., Riley, L. W., & Colford, J. M. (2003) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(03)00772-2 · Cited by 384
Moriarty, A. S., Gilbody, S., McMillan, D., & Manea, L. (2015) · General Hospital Psychiatry · doi:10.1016/j.genhosppsych.2015.06.012 · Cited by 372
A Meta-analysis of Clinical Screening Tests for Obstructive Sleep Apnea
Ramachandran, S. K., & Josephs, L. A. (2009) · Anesthesiology · doi:10.1097/aln.0b013e31819c47b6 · Cited by 297
Yavchitz, A., Ravaud, P., Altman, D. G., Moher, D., Hrobjartsson, A., Lasserson, T., & Boutron, I. (2016) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2016.01.020 · Cited by 224
Accuracy of Diagnostic Tests for Cushing’s Syndrome: A Systematic Review and Metaanalyses
Elamin, M. B., Murad, M. H., Mullan, R., Erickson, D., Harris, K., Nadeem, S., Ennis, R., Erwin, P. J., & Montori, V. M. (2008) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2008-0139 · Cited by 222
Sample sizes of studies on diagnostic accuracy: literature survey.
Bachmann, L. M., Puhan, M. A., Riet, G. T., & Bossuyt, P. M. (2006) · BMJ · doi:10.1136/bmj.38793.637789.2f · Cited by 184
Self-citationHeng, S. C., Morrissey, O., Chen, S. C.-A., Thursky, K., Manser, R. L., Nation, R. L., Kong, D. C.-M., & Slavin, M. (2015) · Critical Reviews in Microbiology · doi:10.3109/1040841x.2013.804033 · Cited by 133
Value of composite reference standards in diagnostic research
Naaktgeboren, C. A., Bertens, L. C. M., Smeden, M. V., Groot, J. A. H. D., Moons, K. G. M., & Reitsma, J. B. (2013) · BMJ · doi:10.1136/bmj.f5605 · Cited by 105
Athanasopoulou, E., & Fox, J. R. E. (2014) · Infant Mental Health Journal · doi:10.1002/imhj.21444 · Cited by 100
PCR Using Blood for Diagnosis of Invasive Pneumococcal Disease: Systematic Review and Meta-Analysis
Avni, T., Mansur, N., Leibovici, L., & Paul, M. (2010) · Journal of Clinical Microbiology · doi:10.1128/jcm.01636-09 · Cited by 72
de Sousa, M. R., Morillo, C. A., Rabelo, F. T., Filho, A. M. N., & Ribeiro, A. L. P. (2008) · European Journal of Heart Failure · doi:10.1016/j.ejheart.2008.07.002 · Cited by 72
Xpert MTB/RIF test for detection of pulmonary tuberculosis and rifampicin resistance
Sohn, H., Pai, M., Dendukuri, N., Kloda, L. A., Boehme, C. C., & Steingart, K. R. (2012) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd009593 · Cited by 20
Covariate‐adjusted measures of discrimination for survival data
White, I. R., Rapsomaniki, E., & for the Emerging Risk Factors Collaboration (2015) · Biometrical Journal · doi:10.1002/bimj.201400061 · Cited by 13
Meta-analysis and structured literature review in radiology1
Doria, A. S. (2005) · Academic Radiology · doi:10.1016/j.acra.2005.01.007 · Cited by 9
Metadata
- Authors
- Lijmer, J. G., Bossuyt, P. M. M., & Heisterkamp, S. H.
- Venue
- Statistics in Medicine
- Publisher
- Wiley
- Published
- 2002-05-21
- Volume
- 21
- Issue
- 11
- Pages
- 1525-1537
- ISSN
- 0277-6715 (ISSN-L)
- 1097-0258
- OpenAlex
- W2100280977
- Cited by
- 446
- References
- 7
- FWCI
- 4.46
- Type
- journal article
- Language
- en
- Open access
- closed
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