A trivariate meta-analysis of diagnostic studies accounting for prevalence and non-evaluable subjects: re-evaluation of the meta-analysis of coronary CT angiography studies.

TitleA trivariate meta-analysis of diagnostic studies accounting for prevalence and non-evaluable subjects: re-evaluation of the meta-analysis of coronary CT angiography studies.
Publication TypeJournal Article
Year of Publication2014
AuthorsMa, Xiaoye, Muhammad Fareed K. Suri, and Haitao Chu
JournalBMC Med Res Methodol
Volume14
Pagination128
Date Published2014 Dec 04
ISSN1471-2288
KeywordsCoronary Angiography, Data Interpretation, Statistical, Diagnostic Techniques, Cardiovascular, Humans, Prevalence, Tomography, X-Ray Computed
Abstract

BACKGROUND: A recent paper proposed an intent-to-diagnose approach to handle non-evaluable index test results and discussed several alternative approaches, with an application to the meta-analysis of coronary CT angiography diagnostic accuracy studies. However, no simulation studies have been conducted to test the performance of the methods.METHODS: We propose an extended trivariate generalized linear mixed model (TGLMM) to handle non-evaluable index test results. The performance of the intent-to-diagnose approach, the alternative approaches and the extended TGLMM approach is examined by extensive simulation studies. The meta-analysis of coronary CT angiography diagnostic accuracy studies is re-evaluated by the extended TGLMM.RESULTS: Simulation studies showed that the intent-to-diagnose approach under-estimate sensitivity and specificity. Under the missing at random (MAR) assumption, the TGLMM gives nearly unbiased estimates of test accuracy indices and disease prevalence. After applying the TGLMM approach to re-evaluate the coronary CT angiography meta-analysis, overall median sensitivity is 0.98 (0.967, 0.993), specificity is 0.875 (0.827, 0.923) and disease prevalence is 0.478 (0.379, 0.577).CONCLUSIONS: Under MAR assumption, the intent-to-diagnose approach under-estimate both sensitivity and specificity, while the extended TGLMM gives nearly unbiased estimates of sensitivity, specificity and prevalence. We recommend the extended TGLMM to handle non-evaluable index test subjects.

DOI10.1186/1471-2288-14-128
Alternate JournalBMC Med Res Methodol
Original PublicationA trivariate meta-analysis of diagnostic studies accounting for prevalence and non-evaluable subjects: re-evaluation of the meta-analysis of coronary CT angiography studies.
PubMed ID25475705
PubMed Central IDPMC4280699
Grant List1R01HL105626 / HL / NHLBI NIH HHS / United States
P30 CA077598 / CA / NCI NIH HHS / United States
R01 HL105626 / HL / NHLBI NIH HHS / United States
U54 MD008620 / MD / NIMHD NIH HHS / United States
U54-MD008620 / MD / NIMHD NIH HHS / United States
AI103012 / AI / NIAID NIH HHS / United States
R21 AI103012 / AI / NIAID NIH HHS / United States
P01CA142538 / CA / NCI NIH HHS / United States
P01 CA142538 / CA / NCI NIH HHS / United States
P30CA077598 / CA / NCI NIH HHS / United States