Coronary Disease Clinical Trial
Official title:
Accuracy and Heterogeneity of Stress Imaging for Detecting Coronary Artery Disease: A Systematic Review and Meta-Analysis Using HSROC Methods in 23,051 Patients.
Background: Detection of coronary artery disease (CAD) is important due to its high prevalence and its medical and economic implications. Purpose: A systematic review of the diagnostic performance of stress echocardiography (Echo), SPECT, cardiac magnetic resonance (CMR), CT Perfusion (CTP) and PET versus invasive coronary angiography (ICA) or fractional flow reserve (FFR) using hierarchical summary ROC (HSROC) methods. Data Sources: MEDLINE, EMBASE and SCOPUS for literature published in English or Spanish from January 1970 to December 2015. Study Selection: For inclusion, studies had to meet the Cochrane guidelines, had to evaluate the sensitivity and specificity methods, and use ICA and/or FFR. Only those studies with STARD methodology ≥60% were included. Data Extraction: Ten investigators extracted patient and study characteristics and 4 resolved any disagreements.
Review question: What non-invasive cardiovascular imaging tests (SPECT, Stress Echo [SE],
Cardiovascular Magnetic Resonance [CMR], CT Perfusion [CTP] and PET myocardial perfusion)
have the best diagnostic accuracy to detect obstructive coronary artery disease using four
different cutoffs, two anatomic (invasive coronary angiography) and two functional (invasive
fractional flow reserve)? Which non-invasive cardiovascular imaging tests (SPECT, Stress
Echo, CMR, CTP and PET myocardial perfusion) have the least bias and heterogeneity in their
published data?
Searches: Search in MEDLINE, EMBASE and SCOPUS databases for the literature published in
English or Spanish from January 1970 to December 2015 of all prospective and retrospective
studies performed with Stress Echo, SPECT, PET, CMR and CTP in patients with suspicion or
known CAD compared against the reference standard of ICA (two cutoffs: lesions >50% and
>70%) and/or invasive FFR (two cutoffs: <0.80 and <0.75).
Condition being studied: Obstructive coronary artery disease. Non-invasive imaging
modalities (SPECT, Stress Echo, CMR, CTP and PET) to evaluate myocardial perfusion as
indicative of obstructive coronary artery disease.
Intervention: There was no intervention or exposure, since it was an evaluation of
diagnostic accuracy of worldwide current non-invasive cardiovascular imaging modalities
compared to the accepted standard of reference.
Comparator: No control group used.
Context: Studies in English and Spanish were included to avoid missing any relevant, high
quality contributions in different languages. Other languages different from English and
Spanish were not included due to language barriers and limitations regarding understanding
the full text document and to obtaining the necessary data, since those papers generally
only have the abstract in English. There were no restrictions in country of origin, type of
technique or equipment used, since we made performed a sub-analysis for those minor
variables not reported in all papers.
Data extraction: After study planning, we decided to decided to included all published
studies and decided not to include data that hadn't been formally published. Our search
strategy with three terms related to the research question considering: patient population,
intervention types of the different imaging modalities and the design type; we decided to
include two types of search terms, free words and standardized words such as those use in
Medical Subject Headings (MeSH) for PubMed and for EMBASE we used EMTREE terms; we also used
a combination of thematic terms selected by a controlled vocabulary, the Thesaurus, open
when necessary and with broad range of free text terms. As we described in detail as
follows, the data extraction was always with more than two researchers. The team was divided
into a searcher, a search advisor, and five junior and four senior reviewers. Four senior
reviewers gathered together to define the MeSH terms necessary for the literature search.
The searcher and the search advisor (one senior reviewer) worked together to build up the
corresponding search algorithms as follows: for prospective or retrospective clinical
trials, case series, abstracts and gray literature in English or Spanish for PubMed, for
EMBASE, and for Scopus; also for meta-analysis and systemic reviews for PubMed, for EMBASE
and for Scopus for the period comprised between January 1970 to December 2015. One senior
author (first author) was designed as "administrator", then all retrievals from the searcher
went directly and only to the administrator to avoid duplications or gaps in the review
process. First the administrator received a search with titles and abstracts, which s/he
distributed equally to the four senior reviewers (including the administrator) to make an
initial selection and to eliminate all titles and abstracts that did not meet the inclusion
or exclusion criteria, which was then gathered together by the administrator and sent back
to the searcher, whose used the list of selected documents (titles and abstracts) to send a
second package of searches to the administrator with all documents in full text version, who
again equally distributed these documents to all four senior reviewers, who then validated
the inclusion and exclusion criteria, which may have been missed in the abstract alone; the
resulting package was again returned to the administrator who equally distributed the
documents to all junior and senior reviewers to score each study according to the STARD
checklist for this type of project. We previously established a minimum of 60% of points in
the STARD checklist for a study to be approved and be included in the next stage of the
review. All scoring sheets were sent back to the administrator within the timeline period.
All disagreements were solved during our research meetings by a consensus of the senior
reviewers. The administrator then selected the studies to be included in the meta-analysis
based on the STARD score and distributed them equally to all junior and senior reviewers
(including the administrator) to extract data in a pre- designed data capture sheet. At the
deadline, the administrator gathered together all data capture sheets and then
re-distributed equally with the original papers to the four senior reviewers who did a
second review of each study to assure quality of the extracted data. All disagreements were
solved during extra research meetings of the senior reviewers by consensus. After the data
were accepted by the four senior reviewers, the administrator provided another senior
reviewer, acting as a "statistician" with all captured data to start the statistical
analysis. At the same time, all studies included in the meta-analysis were again distributed
by the administrator to two senior reviewers (the administrator and the statistician) who
did the data extraction for the sub-analysis, each senior reviewer took two imaging
modalities for review, and after completion those sub-analysis data were gather together by
the statistician to be included in the meta-analysis.
Risk of bias: In the selection process bias risk was managed by using a double check of the
selection criteria by senior reviewers, by scoring each study by STARD methodology using its
checklist and a rigid criteria of >60% to be considered for further analysis, any
disagreements between the junior and/ senior review authors over the risk of bias in
particular studies were solved by discussion during an extra research meeting of two senior
authors, with involvement of a third reviewer when necessary. The publication bias was
evaluated in graphic manner using Funnel plots and in mathematical form with Begg and Egger
tests. A value of p<0.05 was defined as significant.
Strategy for data synthesis: We performed Forrest plots for each test and HSROC curves with
the Moses-Littenberg method. We calculated AUC and Q* for each test. Total values of
sensitivity, specificity, DOR, LR+ and LR-, as well as 95% CI were calculated using the
bivariate model of Teitsma and the models of HSROC (hierarchical summary ROC) of Rutter and
Gatsonis. The differences between the tests were evaluated using meta-regression comparing
different models with the likelihood ratio test. The analysis of heterogeneity between
studies was evaluated in graphic form in the HSROC curves, and in mathematical manner with
meta-regression and the calculation of Higgins' I2; this last test, Higgins' I2, was not
reported within the results, since in diagnostic test accuracy studies, this I2 statistic
alone may not be informative as they do not consider threshold effect; in comparison to this
same statistical test when it is used for the analysis of heterogeneity between therapeutic
and or interventional studies, since a threshold effect can be considered. In our study the
publication bias was evaluated in graphic manner using Funnel plots and in mathematical form
with Begg and Egger tests. A value of p<0.05 was defined as significant.
Analysis of subgroups: To analyze statistical differences in diagnostic accuracy between
modalities, we based the analyses on mathematical combinations and used the term "certainty"
to refer to diagnostic accuracy that one imaging modality has over the other one; then we
performed the meta-regression analysis for comparison of "certainty" between two imaging
modalities at the same time. We used a graphic representation for the results. We did a
post-hoc analysis by sub-groups to all other variables, common to every technique and/or
specific for each imaging modality studied.
Dissemination plans: A paper will be submitted to a leading journal in this field. The
findings of the review produced solid evidence that can change current worldwide practice
for the benefit of patients, institutions and public health services by obtaining higher
accuracy in the diagnosis of significant coronary artery disease in terms of myocardial
ischemia, thus avoiding extra unnecessary tests, less harm to the patients and less
unnecessary expenses.
Current review status: Completed but not published.
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