Diagnostic Test Accuracy Review of Cytology for Squamous Intraepithelial Lesion and Squamous Cell Carcinoma of Uterine Cervix

BACKGROUND: Even though cervico-vaginal smears have been used as a primary screening test for cervical carcinoma, the diagnostic accuracy has been controversial. The present study aimed to evaluate the diagnostic accuracy of cytology for squamous intraepithelial lesion (SIL) and squamous cell carcinoma (SqCC) of the uterine cervix through a diagnostic test accuracy (DTA) review. METHODS: A DTA review was performed using 38 eligible studies that showed concordance between cytology and histology. In the DTA review, sensitivity, specificity, diagnostic odds ratio (OR), and the area under the curve (AUC) on the summary receiver operating characteristic (SROC) curve were calculated. RESULTS: In the comparison between abnormal cytology and histology, the pooled sensitivity and specificity were 93.9% (95% confidence interval [CI], 93.7%–94.1%) and 77.6% (95% CI, 77.4–77.8%), respectively. The diagnostic OR and AUC on the SROC curve were 8.90 (95% CI, 5.57–14.23) and 0.8148, respectively. High-grade squamous intraepithelial lesion (HSIL) cytology had a higher sensitivity (97.6%; 95% CI, 94.7%–97.8%) for predicting HSIL or worse histology. In the comparison between SqCC identified on cytology and on histological analysis, the pooled sensitivity and specificity, diagnostic OR, and AUC were 92.7% (95% CI, 87.3%–96.3%), 87.5% (95% CI, 87.2%–87.8%), 865.81 (95% CI, 68.61–10,925.12), and 0.9855, respectively. Geographic locations with well-organized screening programs had higher sensitivity than areas with insufficient screening programs. CONCLUSION: These results indicate that cytology had a higher sensitivity and specificity for detecting SIL and SqCC of the uterine cervix during primary screening.

Diagnostic test accuracy: application and practice using R software / 한국역학회지

The objective of this paper is to describe general approaches of diagnostic test accuracy (DTA) that are available for the quantitative synthesis of data using R software. We conduct a DTA that summarizes statistics for univariate analysis and bivariate analysis. The package commands of R software were “metaprop” and “metabin” for sensitivity, specificity, and diagnostic odds ratio; forest for forest plot; reitsma of “mada” for a summarized receiver-operating characteristic (ROC) curve; and “metareg” for meta-regression analysis. The estimated total effect sizes, test for heterogeneity and moderator effect, and a summarized ROC curve are reported using R software. In particular, we focus on how to calculate the effect sizes of target studies in DTA. This study focuses on the practical methods of DTA rather than theoretical concepts for researchers whose fields of study were non-statistics related. By performing this study, we hope that many researchers will use R software to determine the DTA more easily, and that there will be greater interest in related research.

Diagnostic test accuracy: application and practice using R software / 한국역학회지

The objective of this paper is to describe general approaches of diagnostic test accuracy (DTA) that are available for the quantitative synthesis of data using R software. We conduct a DTA that summarizes statistics for univariate analysis and bivariate analysis. The package commands of R software were “metaprop” and “metabin” for sensitivity, specificity, and diagnostic odds ratio; forest for forest plot; reitsma of “mada” for a summarized receiver-operating characteristic (ROC) curve; and “metareg” for meta-regression analysis. The estimated total effect sizes, test for heterogeneity and moderator effect, and a summarized ROC curve are reported using R software. In particular, we focus on how to calculate the effect sizes of target studies in DTA. This study focuses on the practical methods of DTA rather than theoretical concepts for researchers whose fields of study were non-statistics related. By performing this study, we hope that many researchers will use R software to determine the DTA more easily, and that there will be greater interest in related research.

Clinicopathological Significance and Diagnostic Accuracy of c-MET Expression by Immunohistochemistry in Gastric Cancer: A Meta-Analysis

PURPOSE: The aim of the present study was to elucidate the clinicopathological significance and diagnostic accuracy of immunohistochemistry (IHC) for determining the mesenchymal epidermal transition (c-MET) expression in patients with gastric cancer (GC). MATERIALS AND METHODS: The present meta-analysis investigated the correlation between c-MET expression as determined by IHC and the clinicopathological parameters in 8,395 GC patients from 37 studies that satisfied the eligibility criteria. In addition, a concordance analysis was performed between c-MET expression as determined by IHC and c-MET amplification, and the diagnostic test accuracy was reviewed. RESULTS: The estimated rate of c-MET overexpression was 0.403 (95% confidence interval [CI], 0.327~0.484) and it was significantly correlated with male patients, poor differentiation, lymph node metastasis, higher TNM stage, and human epidermal growth factor receptor 2 (HER2) positivity in IHC analysis. There was a significant correlation between c-MET expression and worse overall survival rate (hazard ratio, 1.588; 95% CI, 1.266~1.992). The concordance rates between c-MET expression and c-MET amplification were 0.967 (95% CI, 0.916~0.987) and 0.270 (95% CI, 0.173~0.395) for cases with non-overexpressed and overexpressed c-MET, respectively. In the diagnostic test accuracy review, the pooled sensitivity and specificity were 0.56 (95% CI, 0.50~0.63) and 0.79 (95% CI, 0.77~0.81), respectively. CONCLUSIONS: The c-MET overexpression as determined by IHC was significantly correlated with aggressive tumor behavior and positive IHC status for HER2 in patients with GC. In addition, the c-MET expression status could be useful in the screening of c-MET amplification in patients with GC.

Systematic Review and Meta-Analysis of Studies Evaluating Diagnostic Test Accuracy: A Practical Review for Clinical Researchers-Part I. General Guidance and Tips

In the field of diagnostic test accuracy (DTA), the use of systematic review and meta-analyses is steadily increasing. By means of objective evaluation of all available primary studies, these two processes generate an evidence-based systematic summary regarding a specific research topic. The methodology for systematic review and meta-analysis in DTA studies differs from that in therapeutic/interventional studies, and its content is still evolving. Here we review the overall process from a practical standpoint, which may serve as a reference for those who implement these methods.

Systematic Review and Meta-Analysis of Studies Evaluating Diagnostic Test Accuracy: A Practical Review for Clinical Researchers-Part II. Statistical Methods of Meta-Analysis

Meta-analysis of diagnostic test accuracy studies differs from the usual meta-analysis of therapeutic/interventional studies in that, it is required to simultaneously analyze a pair of two outcome measures such as sensitivity and specificity, instead of a single outcome. Since sensitivity and specificity are generally inversely correlated and could be affected by a threshold effect, more sophisticated statistical methods are required for the meta-analysis of diagnostic test accuracy. Hierarchical models including the bivariate model and the hierarchical summary receiver operating characteristic model are increasingly being accepted as standard methods for meta-analysis of diagnostic test accuracy studies. We provide a conceptual review of statistical methods currently used and recommended for meta-analysis of diagnostic test accuracy studies. This article could serve as a methodological reference for those who perform systematic review and meta-analysis of diagnostic test accuracy studies.

Clinical Trials and Accuracy of Diagnostic Tests

Most clinicians understand clinical trials as the evaluation process for new medicine before their use. However, clinical trials can also be applied to laboratory diagnostic tests (LDTs) to verify diagnostic accuracy and efficacy before their clinical laboratory implementation for patients. The clinical trial of LDT has two distinctive characteristics that are different from the case of pharmaceuticals and thus worth special consideration. One of them is the level of evidence. The well-designed randomized controlled trials (RCTs) are known to provide the best evidence to prove the clinical efficacy of any pharmaceutical products. However, RCTs lose practicality when applied to LDTs due to various issues including ethical complications. For this reason, comparative study format is considered more feasible approach for LDTs. In addition pharmaceuticals and LDTs are different in that the user's intervention is not required for the former but critical to the latter. Moreover, in the case of pharmaceuticals, end-products are produced by manufacturers before being used by clinicians. However, in LDTs, once reagents and instruments are provided by manufacturers, they are first utilized by clinical laboratories to produce test results in order for clinicians to use them later. In other words, when it comes to LDTs, clinical laboratories play the role of manufacturers, providing reliable test results with improved quality assurance. Considering the distinctive characteristics of LDTs, we would like to offer detailed suggestions to successfully perform clinical trials in LDTs, which include analytical performance measures, clinical test performance measures, diagnostic test accuracy measures, clinical effectiveness measures, and post-implementation surveillance.