Statistical methods for multivariate meta-analysis of diagnostic tests: An overview and tutorial

Statistical Methods in Medical Research

Volumn 25, Issue 4, 2016, Pages 1596-1619

  Ma, Xiaoye ^a   Nie, Lei ^b   Cole, Stephen R ^c   Chu, Haitao ^a   Lawson, Andrew B ^d   Lee, Duncan ^d   MacNab, Ying ^d  

^a UNIVERSITY OF MINNESOTA   (United States)

^b CENTER FOR DRUG EVALUATION AND RESEARCH   (United States)

^c University of North Carolina at Chapel Hill   (United States)

^d NONE

Author keywords

diagnostic test; generalized linear mixed models; gold standard; Meta analysis

Indexed keywords

BINOMIAL DISTRIBUTION; CALCULATION; DIAGNOSTIC TEST ACCURACY STUDY; GOLD STANDARD; HUMAN; META ANALYSIS; PREVALENCE; RECEIVER OPERATING CHARACTERISTIC; STATISTICAL ANALYSIS; STATISTICAL MODEL; DIAGNOSTIC TEST; META ANALYSIS (TOPIC); MULTIVARIATE ANALYSIS; SENSITIVITY AND SPECIFICITY;

DIAGNOSTIC TESTS, ROUTINE; HUMANS; LINEAR MODELS; META-ANALYSIS AS TOPIC; MULTIVARIATE ANALYSIS; ROC CURVE; SENSITIVITY AND SPECIFICITY;

EID: 84983766468     PISSN: 09622802     EISSN: 14770334     Source Type: Journal    
DOI: 10.1177/0962280213492588     Document Type: Conference Paper

References (42)

1. Zhou XH, Obuchowski NA, McClish DK,. Statistical methods in diagnostic medicine, New York, NY: Wiley, 2002.
2. Pepe MS,. The statistical evaluation of medical tests for classification and prediction, Oxford: Oxford University Press, 2003.
3. Rutter CA, Gatsonis CA,. A hierarchical regression approach to meta-analysis of diagnostic test accuracy evaluations. Stat Med 2001; 20: 2865-2884.
4. Song F, Khan KS, Dinnes J, et al. Asymmetric funnel plots and publication bias in meta-analyses of diagnostic accuracy. Int J Epidemiol 2002; 31: 88-95.
5. van Houwelingen HC,. Advanced methods in meta-analysis: multivariate approach and meta-regression. Stat Med 2002; 21: 589-624.
6. Harbord RM, Deeks JJ, Egger M, et al. A unification of models for meta-analysis of diagnostic accuracy studies. Biostatistics 2007; 8: 239-251.
7. Macaskill P,. Empirical Bayes estimates generated in a hierarchical summary ROC analysis agreed closely with those of a full Bayesian analysis. J Clin Epidemiol 2004; 57: 925-932.
8. Mallett S, Deeks JJ, Halligan S, et al. Systematic reviews of diagnostic tests in cancer: review of methods and reporting. BMJ 2006; 333: 413-413.
9. Zwinderman AH, Bossuyt PM,. We should not pool diagnostic likelihood ratios in systematic reviews. Stat Med 2008; 27: 687-697.
10. Arends LR, Hamza TH, van Houwelingen JC, et al. Bivariate random effects meta-analysis of ROC curves. Med Decis Making 2008; 28: 621-638.
11. Reitsma JB,. Bivariate analysis of sensitivity and specificity produces informative summary measures in diagnostic reviews. J Clin Epidemiol 2005; 58: 982-990.
12. Chu H, Cole SR,. Bivariate meta-analysis of sensitivity and specificity with sparse data: a generalized linear mixed model approach. J Clin Epidemiol 2006; 59: 1331-1332.
13. Chu H, Guo H,. Letter to the editor: a unification of models for meta-analysis of diagnostic accuracy studies. Biostatistics 2009; 10: 201-203.
14. Riley R, Abrams K, Sutton A, et al. Bivariate random-effects meta-analysis and the estimation of between-study correlation. BMC Med Res Methodol 2007; 7: 3-3.
15. Riley RD, Abrams KR, Lambert PC, et al. An evaluation of bivariate random-effects meta-analysis for the joint synthesis of two correlated outcomes. Stat Med 2007; 26: 78-97.
16. Hamza TH, van Houwelingen HC, Stijnen T,. The binomial distribution of meta-analysis was preferred to model within-study variability. J Clin Epidemiol 2008; 61: 41-51.
17. Chu H, Nie L, Cole SR, et al. Meta-analysis of diagnostic accuracy studies accounting for disease prevalence: alternative parameterizations and model selection. StatMed 2009; 28: 2384-2399.
18. Walter SD, Irwig L, Glasziou PP,. Meta-analysis of diagnostic tests with imperfect reference standards. J Clin Epidemiol 1999; 52: 943-951.
19. Chu H, Chen SN, Louis TA,. Random effects models in a meta-analysis of the accuracy of two diagnostic tests without a gold standard. J Am Stat Assoc 2009; 104: 512-523.
20. Sadatsafavi M, Shahidi N, Marra F, et al. A statistical method was used for the meta-analysis of tests for latent TB in the absence of a gold standard, combining random-effect and latent-class methods to estimate test accuracy. J Clin Epidemiol 2010; 63: 257-269.
21. Dendukuri N, Schiller I, Joseph L, et al. Bayesian meta-analysis of the accuracy of a test for tuberculous pleuritis in the absence of a gold standard reference. Biometrics 2012; 68: 1285-1293.
22. Moses LE, Shapiro D, Littenberg B,. Combining independent studies of a diagnostic-test into a summary roc curve-data-analytic approaches and some additional considerations. Stat Med 1993; 12: 1293-1316.
23. Walter SD,. Properties of the summary receiver operating characteristic (SROC) curve for diagnostic test data. Stat Med 2002; 21: 1237-1256.
24. Walter SD,. The partial area under the summary ROC curve. Stat Med 2005; 24: 2025-2040.
25. Sutton AJ, Cooper NJ, Goodacre S, et al. Integration of meta-analysis and economic decision modeling for evaluating diagnostic tests. Med Decis Making 2008; 28: 650-667.
26. Irwig L, Tosteson ANA, Gatsonis C, et al. Guidelines for meta-analyses evaluating diagnostic tests. Ann Internal Med 1994; 120: 667-676.
27. Deeks JJ,. Systematic reviews in health care: systematic reviews of evaluations of diagnostic and screening tests. Br Med J 2001; 323: 157-162.
28. Sweeting MJ, Sutton AJ, Lambert PC,. What to add to nothing? Use and avoidance of continuity corrections in meta-analysis of sparse data. Stat Med 2004; 23: 1351-1375.
29. Starmer CF, Grizzle JE, Sen PK,. Some reasons for not using the Yates continuity corrections in meta-analysis of sparse data. J Am Stat Assoc 1974; 69: 376-378.
30. Tosteson AN, Begg CB,. A general regression methodology for ROC curve estimation. Med Decis Making 1988; 8: 204-215.
31. Chu H, Guo H, Zhou Y,. Bivariate Random effects meta-analysis of diagnostic studies using generalized linear mixed models. Med Decis Making 2010; 30: 499-508.
32. Ransohoff DF, Feinstein AR,. Problems of spectrum and bias in evaluating the efficacy of diagnostic tests. N Engl J Med 1978; 299: 926-930.
33. Brenner H, Gefeller O,. Variation of sensitivity, specificity, likelihood ratios and predictive values with disease prevalence. Stat Med 1997; 16: 981-991.
34. Li J and Fine JP. Assessing the dependence of sensitivity and specificity on prevalence in meta-analysis. Biostatistics 2011; 12 (4): 710-722.
35. Shin KM,. Partial-thickness rotator cuff tears. Korean J Pain 2011; 24: 69-73.
36. Singisetti K,. Shoulder ultrasonography versus arthroscopy for the detection of rotator cuff tears: analysis of errors. J Orthop Surg (Hong Kong) 2011; 19 (1): 76-79.
37. Smith TO, Back T, Tomas AP, Hing CB,. Diagnostic accuracy of ultrasound for rotator cuff tears in adults: a systematic review and meta-analysis. Clin Radiol 2011; 66 (11): 1036-1048.
38. Fahey MT, Irwig L, Macaskill P,. Meta-analysis of Pap test accuracy. Am J Epidemiol 1995; 141: 680-689.
39. Takwoingi Y and Deeks JJ. METADAS: an SAS macro for meta-analysis of diagnostic accuracy studies. 2011.
40. Hamza TH, van Houwelingen HC, Stijnen T,. The binomial distribution of meta-analysis was preferred to model within-study variability. J Clin Epidemiol 2008; 61: 41-51.
41. Riley RD, Thompson JR, Abrams KR,. An alternative model for bivariate random-effects meta-analysis when the within-study correlations are unknown. Biostatistics (Oxford, England) 2008; 9: 172-186.
42. de Groot JA, Dendukuri N, Janssen KJ, et al. Adjusting for partial verification or workup bias in meta-analyses of diagnostic accuracy studies. Am J Epidemiol 2012; 175: 847-853.