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A hybrid model for combining case-control and cohort studies in systematic reviews of diagnostic tests.

ABSTRACT: Systematic reviews of diagnostic tests often involve a mixture of case-control and cohort studies. The standard methods for evaluating diagnostic accuracy only focus on sensitivity and specificity and ignore the information on disease prevalence contained in cohort studies. Consequently, such methods cannot provide estimates of measures related to disease prevalence, such as population averaged or overall positive and negative predictive values, which reflect the clinical utility of a diagnostic test. In this paper, we propose a hybrid approach that jointly models the disease prevalence along with the diagnostic test sensitivity and specificity in cohort studies, and the sensitivity and specificity in case-control studies. In order to overcome the potential computational difficulties in the standard full likelihood inference of the proposed hybrid model, we propose an alternative inference procedure based on the composite likelihood. Such composite likelihood based inference does not suffer computational problems and maintains high relative efficiency. In addition, it is more robust to model mis-specifications compared to the standard full likelihood inference. We apply our approach to a review of the performance of contemporary diagnostic imaging modalities for detecting metastases in patients with melanoma.

SUBMITTER: Chen Y

PROVIDER: S-EPMC4401477 | biostudies-literature | 2015 Apr

REPOSITORIES: biostudies-literature

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A hybrid model for combining case-control and cohort studies in systematic reviews of diagnostic tests.

Chen Yong Y Liu Yulun Y Ning Jing J Cormier Janice J Chu Haitao H

Journal of the Royal Statistical Society. Series C, Applied statistics 20150401 3

Systematic reviews of diagnostic tests often involve a mixture of case-control and cohort studies. The standard methods for evaluating diagnostic accuracy only focus on sensitivity and specificity and ignore the information on disease prevalence contained in cohort studies. Consequently, such methods cannot provide estimates of measures related to disease prevalence, such as population averaged or overall positive and negative predictive values, which reflect the clinical utility of a diagnostic ...[more]

PMID: 25897179

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Project description:BackgroundDecision-makers increasingly request rapid answers to clinical or public health questions. To save time, personnel, and financial resources, rapid reviews streamline the methodological steps of the systematic review process. We aimed to explore the validity of a rapid review approach that combines a substantially abbreviated literature search with a single-reviewer screening of abstracts and full texts using three case studies.MethodsWe used a convenience sample of three ongoing Cochrane reviews as reference standards. Two reviews addressed oncological topics and one addressed a public health topic. For each of the three topics, three reviewers screened the literature independently. Our primary outcome was the change in conclusions between the rapid reviews and the respective Cochrane reviews. In case the rapid approach missed studies, we recalculated the meta-analyses for the main outcomes and asked Cochrane review authors if the new body of evidence would change their original conclusion compared with the reference standards. Additionally, we assessed the sensitivity of the rapid review approach compared with the results of the original Cochrane reviews.ResultsFor the two oncological topics (case studies 1 and 2), the three rapid reviews each yielded the same conclusions as the Cochrane reviews. However, the authors would have had less certainty about their conclusion in case study 2. For case study 3, the public health topic, only one of the three rapid reviews led to the same conclusion as the Cochrane review. The other two rapid reviews provided insufficient information for the authors to draw conclusions. Using the rapid review approach, the sensitivity was 100% (3 of 3) for case study 1. For case study 2, the three rapid reviews identified 40% (4 of 10), 50% (5 of 10), and 60% (6 of 10) of the included studies, respectively; for case study 3, the respective numbers were 38% (8 of 21), 43% (9 of 21), and 48% (10 of 21).ConclusionsWithin the limitations of these case studies, a rapid review approach that combines abbreviated literature searches with single-reviewer screening may be feasible for focused clinical questions. For complex public health topics, sensitivity seems to be insufficient.

Project description:ImportanceSystematic reviews of medical imaging diagnostic test accuracy (DTA) studies are affected by between-study heterogeneity due to a range of factors. Failure to appropriately assess the extent and causes of heterogeneity compromises the interpretability of systematic review findings.ObjectiveTo assess how heterogeneity has been examined in medical imaging DTA studies.Evidence reviewThe PubMed database was searched for systematic reviews of medical imaging DTA studies that performed a meta-analysis. The search was limited to the 40 journals with highest impact factor in the radiology, nuclear medicine, and medical imaging category in the InCites Journal Citation Reports of 2021 to reach a sample size of 200 to 300 included studies. Descriptive analysis was performed to characterize the imaging modality, target condition, type of meta-analysis model used, strategies for evaluating heterogeneity, and sources of heterogeneity identified. Multivariable logistic regression was performed to assess whether any factors were associated with at least 1 source of heterogeneity being identified in the included meta-analyses. Methodological quality evaluation was not performed. Data analysis occurred from October to December 2022.FindingsA total of 242 meta-analyses involving a median (range) of 987 (119-441 510) patients across a diverse range of disease categories and imaging modalities were included. The extent of heterogeneity was adequately described (ie, whether it was absent, low, moderate, or high) in 220 studies (91%) and was most commonly assessed using the I2 statistic (185 studies [76%]) and forest plots (181 studies [75%]). Heterogeneity was rated as moderate to high in 191 studies (79%). Of all included meta-analyses, 122 (50%) performed subgroup analysis and 87 (36%) performed meta-regression. Of the 242 studies assessed, 189 (78%) included 10 or more primary studies. Of these 189 studies, 60 (32%) did not perform meta-regression or subgroup analysis. Reasons for being unable to investigate sources of heterogeneity included inadequate reporting of primary study characteristics and a low number of included primary studies. Use of meta-regression was associated with identification of at least 1 source of variability (odds ratio, 1.90; 95% CI, 1.11-3.23; P = .02).Conclusions and relevanceIn this systematic review of assessment of heterogeneity in medical imaging DTA meta-analyses, most meta-analyses were impacted by a moderate to high level of heterogeneity, presenting interpretive challenges. These findings suggest that, despite the development and availability of more rigorous statistical models, heterogeneity appeared to be incomplete, inconsistently evaluated, or methodologically questionable in many cases, which lessened the interpretability of the analyses performed; comprehensive heterogeneity assessment should be addressed at the author level by improving personal familiarity with appropriate statistical methodology for assessing heterogeneity and involving biostatisticians and epidemiologists in study design, as well as at the editorial level, by mandating adherence to methodologic standards in primary DTA studies and DTA meta-analyses.

Dataset Information

A hybrid model for combining case-control and cohort studies in systematic reviews of diagnostic tests.

Publications

A hybrid model for combining case-control and cohort studies in systematic reviews of diagnostic tests.

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