Summarising and validating test accuracy results across multiple studies for use in clinical practice

Statistics in Medicine

Volumn 34, Issue 13, 2015, Pages 2081-2103

  Riley, Richard D ^a   Ahmed, Ikhlaaq ^b   Debray, Thomas P A ^c   Willis, Brian H ^b   Noordzij, J Pieter ^d   Higgins, Julian P T ^e   Deeks, Jonathan J ^b  

^a KEELE UNIVERSITY   (United Kingdom)

^b UNIVERSITY OF BIRMINGHAM   (United Kingdom)

^c UNIVERSITY MEDICAL CENTER UTRECHT   (Netherlands)

^d BOSTON UNIVERSITY SCHOOL OF MEDICINE   (United States)

^e UNIVERSITY OF BRISTOL   (United Kingdom)

Author keywords

Calibration; Diagnostic; Discrimination; Meta analysis; Prognostic; Test accuracy

Indexed keywords

PARATHYROID HORMONE;

ARTICLE; CALIBRATION; CLINICAL PRACTICE; CONCEPTUAL FRAMEWORK; DIAGNOSTIC ACCURACY; DIAGNOSTIC TEST; FEVER; HUMAN; HYPOCALCEMIA; INFRARED EAR THERMOMETRY; PREDICTIVE VALUE; PROBABILITY; SENSITIVITY AND SPECIFICITY; THERMOMETRY; VALIDATION STUDY; BAYES THEOREM; CLASSIFICATION; COHORT ANALYSIS; EVALUATION STUDY; META ANALYSIS (TOPIC); METHODOLOGY; PROGNOSIS; REPRODUCIBILITY; STANDARD; STANDARDS; THERMOMETER;

BAYES THEOREM; CALIBRATION; COHORT STUDIES; EVALUATION STUDIES AS TOPIC; FEVER; HUMANS; HYPOCALCEMIA; META-ANALYSIS AS TOPIC; PREDICTIVE VALUE OF TESTS; PROBABILITY; PROGNOSIS; REFERENCE STANDARDS; REPRODUCIBILITY OF RESULTS; RESEARCH DESIGN; SENSITIVITY AND SPECIFICITY; THERMOMETERS;

EID: 84928762608     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.6471     Document Type: Article

References (42)

1. Deeks JJ. Systematic reviews in health care: systematic reviews of evaluations of diagnostic and screening tests. BMJ 2001; 323:157-162.
2. Reitsma JB, Glas AS, Rutjes AW, Scholten RJ, Bossuyt PM, Zwinderman AH. Bivariate analysis of sensitivity and specificity produces informative summary measures in diagnostic reviews. Journal of Clinical Epidemiology 2005; 58:982-990.
3. Harbord RM, Deeks JJ, Egger M, Whiting P, Sterne JA. A unification of models for meta-analysis of diagnostic accuracy studies. Biostatistics 2007; 8:239-251.
4. Chu H, Cole SR. Bivariate meta-analysis of sensitivity and specificity with sparse data: a generalized linear mixed model approach. Journal of Clinical Epidemiology 2006;591331-1332. author reply 1332-1333.
5. Leeflang MM, Deeks JJ, Rutjes AW, Reitsma JB, Bossuyt PM. Bivariate meta-analysis of predictive values of diagnostic tests can be an alternative to bivariate meta-analysis of sensitivity and specificity. Journal of Clinical Epidemiology 2012; 65:1088-1097.
6. Harbord RM, Whiting P, Sterne JA, Egger M, Deeks JJ, Shang A, Bachmann LM. An empirical comparison of methods for meta-analysis of diagnostic accuracy showed hierarchical models are necessary. Journal of Clinical Epidemiology 2008; 61:1095-1103.
7. Noordzij JP, Lee SL, Bernet VJ, Payne RJ, Cohen SM, McLeod IK, Hier MP, Black MJ, PD Kerr, Richards ML, Lo CY, Raffaelli M, Bellantone R, Lombardi CP, Cohen JI, Dietrich MS. Early prediction of hypocalcemia after thyroidectomy using parathyroid hormone: an analysis of pooled individual patient data from nine observational studies. Journal of the American College of Surgeons 2007; 205:748-754.
8. Higgins JP, Thompson SG, Spiegelhalter DJ. A re-evaluation of random-effects meta-analysis. Journal of the Royal Statistical Society, Series A 2009; 172:137-159.
9. Riley RD, Higgins JP, Deeks JJ. Interpretation of random effects meta-analyses. BMJ 2011; :d549.
10. Willis BH, Hyde CJ. Estimating a test's accuracy using tailored meta-analysis - how setting-specific data may aid study selection. Journal of Clinical Epidemiology 2014; 67:538-546.
11. Craig JV, Lancaster GA, Taylor S, Williamson PR, Smyth RL. Infrared ear thermometry compared with rectal thermometry in children: a systematic review. Lancet 2002; 360:603-609.
12. Dodd SR, Lancaster GA, Craig JV, Smyth RL, Williamson PR. In a systematic review, infrared ear thermometry for fever diagnosis in children finds poor sensitivity. Journal of Clinical Epidemiology 2006; 59:354-357.
13. Hamza TH, van Houwelingen HC, Stijnen T. The binomial distribution of meta-analysis was preferred to model within-study variability. Journal of Clinical Epidemiology 2008; 61:41-51.
14. Zeger SL, Liang KY, Albert PS. Models for longitudinal data: a generalized estimating equation approach. Biometrics 1988; 44:1049-1060.
15. Pinheiro JC, Bates DM. Approximations to the log-likelihood function in the nonlinear mixed-effects model. Journal of Computational and Graphical Statistics 1995; 4:12-35.
16. Statistical Software . Release 13.0. Stata Corporation. College Station, TX, 2013.
17. Lunn DJ, Thomas A, Best N, Spiegelhalter D. WinBUGS - a Bayesian modelling framework: concepts, structure, and extensibility. Statistics and Computing 2000; 10:325-337.
18. Lambert PC, Sutton AJ, Burton PR, Abrams KR, Jones DR. How vague is vague? A simulation study of the impact of the use of vague prior distributions in MCMC. Statistics in Medicine 2005; 24:2401-2428.
19. Browne WJ, Draper D. Implementation and performance issues in the Bayesian and likelihood fitting of multilevel models. Computational Statistics 2000; 15:391-420.
20. Zwinderman AH, Bossuyt PM. We should not pool diagnostic likelihood ratios in systematic reviews. Statistics in Medicine 2008; 27:687-697.
21. Wei Y, Higgins JP. Bayesian multivariate meta-analysis with multiple outcomes. Statistics in Medicine 2013; 32:2911-2934.
22. Bujkiewicz S, Thompson JR, Sutton AJ, Cooper NJ, Harrison MJ, Symmons DP, Abrams KR. Multivariate meta-analysis of mixed outcomes: a Bayesian approach. Statistics in Medicine 2013; 32:3926-3943.
23. Harrell FE. Regression Modeling Strategies, with Applications to Linear models, Logistic Regression, and Survival Analysis. Springer: New York, 2001.
24. van Klaveren D, Steyerberg EW, Perel P, Vergouwe Y. Assessing discriminative ability of risk models in clustered data. BMC Med Res Methodol 2014; 14:5.
25. DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials 1986; 7:177-188.
26. Steyerberg EW. Clinical Prediction Models: A Practical Approach to Development, Validation, and Updating, Springer: New York, 2009.
27. Royston P, Parmar MKB, Sylvester R. Construction and validation of a prognostic model across several studies, with an application in superficial bladder cancer. Statistics in Medicine 2004; 23:907-926.
28. Debray TP, Moons KG, Ahmed I, Koffijberg H, Riley RD. A framework for developing, implementing, and evaluating clinical prediction models in an individual participant data meta-analysis. Statistics in Medicine 2013; 32:3158-3158.
29. Hemingway H, Croft P, Perel P, Hayden JA, Abrams K, Timmis A, Briggs A, Udumyan R, KG Moons, Steyerberg EW, Roberts I, Schroter S, Altman DG, Riley RD. Prognosis research strategy (PROGRESS) 1: a framework for researching clinical outcomes. BMJ 2013; 346:e5595.
30. Chu H, Nie L, Cole SR, Poole C. Meta-analysis of diagnostic accuracy studies accounting for disease prevalence: alternative parameterizations and model selection. Statistics in Medicine 2009; 28:2384-2399.
31. Steyerberg EW, Moons KG, van der Windt DA, Hayden JA, Perel P, Schroter S, Riley RD, H Hemingway, Altman DG. Prognosis research strategy (PROGRESS) 3: prognostic model research. PLoS Med 2013; 10:e1001381.
32. Bleeker SE, Moll HA, Steyerberg EW, Donders ART, Derksen-Lubsen G, Grobbee DE, KGM Moons . External validation is necessary in, prediction research: a clinical example. Journal of Clinical Epidemiology 2003; 56:826-832.
33. Selvin S 2008. Survival Analysis for Epidemiologic and Medical Research: A Practical Guide, Cambridge University Press: New York.
34. Pennells L, Kaptoge S, White IR, Thompson SG, Wood AM. Assessing risk prediction models using individual participant data from multiple studies. American Journal of Epidemiology 2014; 179:621-632.
35. Snell KIE, Hua H, Debray TP, Ensor J, Look MP, Moons KG, Riley RD. Multivariate meta-analysis of individual participant data helps externally validate the performance and implementation of a prediction model. Journal of Clinical Epidemiology (2015). (submitted).
36. Ferrante di Ruffano L, Hyde CJ, McCaffery KJ, Bossuyt PM, Deeks JJ. Assessing the value of diagnostic tests: a framework for designing and evaluating trials. BMJ 2012; 344:e686.
37. Schmid CH, Stark PC, Berlin JA, Landais P, Lau J. Meta-regression detected associations between heterogeneous treatment effects and study-level, but not patient-level, factors. Journal of Clinical Epidemiology 2004; 57:683-697.
38. Berlin JA, Santanna J, Schmid CH, Szczech LA, Feldman HI. Individual patient- versus group-level data meta-regressions for the investigation of treatment effect modifiers: ecological bias rears its ugly head. Statistics in Medicine 2002; 21:371-387.
39. Whiting PF, Rutjes AW, Westwood ME, Mallett S, Deeks JJ, Reitsma JB, Leeflang MM, Sterne JA, Bossuyt PM. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Annals of Internal Medicine 2011; 155:529-536.
40. Willis BH, Hyde CJ. What is the test's accuracy in my practice population? Tailored meta-analysis provides a plausible estimate. Journal of Clinical Epidemiology 2014. DOI: 10.1016/j.jclinepi.2014.10.002.
41. Takwoingi Y, Leeflang MM, Deeks JJ. Empirical evidence of the importance of comparative studies of diagnostic test accuracy. Annals of Internal Medicine 2013; 158:544-554.
42. Lee KJ, Thompson SG. Flexible parametric models for random-effects distributions. Statistics in Medicine 2008; 27:418-434.