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

Missing values and inconclusive results in diagnostic studies - A scoping review of methods

Most diagnostic studies exclude missing values and inconclusive results from the analysis or apply simple methods resulting in biased accuracy estimates. This may be due to the lack of availability or awareness of appropriate methods. This scoping review aimed to provide an overview of strategies to handle missing values and inconclusive results in the reference standard or index test in diagnostic accuracy studies. Conducting a systematic literature search in MEDLINE, Cochrane Library, and Web of Science, we could identify many articles proposing methods for addressing missing values in the reference standard. There are also several articles describing methods regarding missing values or inconclusive results in the index test. The latter encompass imputation, frequentist and Bayesian likelihood, model-based, and latent class methods. While methods for missing values in the reference standard are regularly applied in practice, this is not true for methods addressing missing values and inconclusive results in the index test. Our comprehensive overview and description of available methods may raise further awareness of these methods and will enhance their application. Future research is needed to compare the performance of these methods under different conditions to give valid and robust recommendations for their usage in various diagnostic accuracy research scenarios.

An extended trivariate vine copula mixed model for meta-analysis of diagnostic studies in the presence of non-evaluable outcomes

A recent paper proposed an extended trivariate generalized linear mixed model (TGLMM) for synthesis of diagnostic test accuracy studies in the presence of non-evaluable index test results. Inspired by the aforementioned model we propose an extended trivariate vine copula mixed model that includes the TGLMM as special case, but can also operate on the original scale of sensitivity, specificity, and disease prevalence. The performance of the proposed vine copula mixed model is examined by extensive simulation studies in comparison with the TGLMM. Simulation studies showed that the TGLMM leads to biased meta-analytic estimates of sensitivity, specificity, and prevalence when the univariate random effects are misspecified. The vine copula mixed model gives nearly unbiased estimates of test accuracy indices and disease prevalence. Our general methodology is illustrated by meta-analysing coronary CT angiography studies.

Reporting and handling of equivocal imaging findings in diagnostic studies of bone metastasis in prostate cancer

BACKGROUND

Equivocal scanning results occur. It remains unclear how these results are presented and their management influence diagnostic characteristics.

PURPOSE

To investigate the reporting and handling of equivocal imaging findings in diagnostic studies of bone metastases, and to assess the impact on diagnostic performance of the methods used to analyze equivocal findings. The conceptual issue was reified based on two actual observations.

MATERIAL AND METHODS

A recent meta-analysis of bone metastases in prostate cancer was conducted and data were obtained from a large clinical trial with a true reference of bone metastasis, where diagnostic characteristics were calculated with equivocal scans handled by: removal; considered malignant; considered benign; and intention-to-diagnose.

RESULTS

The meta-analysis included 18 trials where the median proportion of reported equivocal results was 27%. Eleven (61%) studies reported an equivocal option for the index test, 42% reported equivocal results and described how these were analyzed. The clinical trial included 583 prostate cancer patients with 20% equivocal results. The different methods of managing equivocal findings resulted in highly variable outcomes: sensitivity = 85%-100%; specificity = 78%-99%; and positive and negative predictive values = 44%-94% and 97%-100%, respectively. The diagnostic performances obtained using the four methods were differentially susceptible to the proportion of equivocal imaging findings and the prevalence of bone metastases.

CONCLUSION

Reporting of equivocal results was inadequate in bone imaging trials. The handling of equivocal findings strongly influenced diagnostic accuracy.

A multinomial quadrivariate D-vine copula mixed model for meta-analysis of diagnostic studies in the presence of non-evaluable subjects

Diagnostic test accuracy studies observe the result of a gold standard procedure that defines the presence or absence of a disease and the result of a diagnostic test. They typically report the number of true positives, false positives, true negatives and false negatives. However, diagnostic test outcomes can also be either non-evaluable positives or non-evaluable negatives. We propose a novel model for the meta-analysis of diagnostic studies in the presence of non-evaluable outcomes, which assumes independent multinomial distributions for the true and non-evaluable positives, and, the true and non-evaluable negatives, conditional on the latent sensitivity, specificity, probability of non-evaluable positives and probability of non-evaluable negatives in each study. For the random effects distribution of the latent proportions, we employ a drawable vine copula that can successively model the dependence in the joint tails. Our methodology is demonstrated with an extensive simulation study and applied to data from diagnostic accuracy studies of coronary computed tomography angiography for the detection of coronary artery disease. The comparison of our method with the existing approaches yields findings in the real data application that change the current conclusions.

The Clinical Relevance of Methods for Handling Inconclusive Medical Test Results: Quantification of Uncertainty in Medical Decision-Making and Screening

BACKGROUND

although the existence of inconclusive medical test results or bio-markers is widely recognized, there are indications that this inherent diagnostic uncertainty is sometimes ignored. This paper discusses three methods for defining and determining inconclusive medical test results, which use different definitions and differ in clinical relevance.

METHODS

the TG-ROC (two graphs receiver operating characteristics) method is the easiest to use, while the grey zone method and the uncertain interval method require more extensive calculations.

RESULTS

this paper discusses the technical details of the methods, as well as advantages and disadvantages for their clinical use. TG-ROC and the grey zone method can help in the acquisition of high rates of diagnostic certainty, but can exclude large groups. The uncertain interval method can prevent decisions that are the most uncertain, invalid and unreliable, while excluding smaller groups.

CONCLUSIONS

the identification of uncertain test scores is relevant, because these scores indicate the need to obtain better information or to await further developments. The methods presented help to determine inconclusive test scores and can help to reduce erroneous decisions. However, further research and development is desirable.