Impact of implementing the first edition of the Paris system for reporting: A systematic review and meta-analysis.

Urine cytology is a noninvasive, widely used diagnostic tool for screening and surveillance of genitourinary tract neoplasms. However, the absence of unified terminology and clear objective morphological criteria limits the clinical benefit of urine cytology. The Paris System for Reporting Urine Cytology (TPS) was developed with the goal of standardizing reporting and improving urine cytology performance in detecting high-grade malignancy (HGM). We aimed to evaluate potential effects of TPS on improving urine cytology diagnostic performance and clinical utility by conducting a systematic review and meta-analysis. We searched six electronic databases to identify cross-sectional and cohort studies written in English assessing the accuracy of urine cytology in detecting genitourinary tract malignancies of patients under surveillance or with clinical suspicion of malignancy from January 2004 to December 2022. We extracted relevant data from eligible studies to calculate relative distribution of cytology diagnostic categories; ratio of atypical to HGM cytology diagnosis; and risk of HGM (ROHGM) and HGM likelihood ratio (HGM-LR) associated with cytology diagnostic categories. We used a generalized linear mixed model with logit transformation to combine proportions and multilevel mixed-effect logistic regression to pool diagnostic accuracy measurements. We performed meta-regression to evaluate any significant difference between TPS and non-TPS cohorts. We included 64 studies for 99,796 combined total cytology samples, across 31 TPS and 49 non-TPS cohorts. Pooled relative distribution [95% confidence interval (CI)] of negative for high-grade urothelial carcinoma (NHGUC)/negative for malignancy (NM); atypical urothelial cells (AUC); suspicious for high-grade urothelial carcinoma (SHGUC)/suspicious for malignancy (SM); low-grade urothelial neoplasm (LGUN); and HGM categories among satisfactory cytology cases were 83.8% (80.3%-86.9%), 8.0% (6.0%-10.6%), 2.2% (1.4%-3.3%), 0.01% (0.0%-0.1%), and 4.2% (3.2%-5.5%) in TPS versus 80.8% (76.8-2.7%), 11.3% (8.6%-14.7%), 1.8% (1.2%-2.7%), 0.01% (0.0%-0.1%), and 3.3% (2.5%-4.3%) in non-TPS cohorts. Adopting TPS classification resulted in a significant increase in the frequency of NHGUC and a reduction in AUC cytology diagnoses, respectively. The AUC/HGM ratio in TPS cohort was 2.0, which showed a statistically significant difference from the atypical/HGM ratio of 4.1 in non-TPS cohort (p-value: 0.01). Moreover, the summary rate (95% CI) of LGUN called AUC on cytology significantly decreased to 20.8% (14.9%-28.3%) in the TPS compared with 34.1% (26.4%-42.8%) in non-TPS cohorts. The pooled ROHGM (95% CI) was 20.4% (6.2%-50.0%) in nondiagnostic (NDX), 15.5% (9.6%-24.2%) in NHGUC, 40.2% (30.9%-50.2%) in AUC, 80.8% (72.9%-86.8%) in SHGUC, 15.1% (5.7%-34.3%) in LGUN, and 91.4% (87.3%-94.3%) in HGM categories in TPS studies. NHGUC, AUC, SHGUC, and HGM categories were associated with HGM-LR (95% CI) of 0.2 (0.1-0.3), 0.9 (0.6-1.3), 6.9 (2.4-19.9), and 16.8 (8.3-33.8). Our results suggest that TPS 1.0 has reduced the relative frequency of AUC diagnosis, AUC/HGM ratio, and the frequency of LGUNs diagnosed as AUC on cytology. Adopting this classification has improved the clinical utility of SHGUC and HGM cytology diagnoses in ruling in high-grade lesions. However, an NHGUC diagnosis does not reliably rule out the presence of a high-grade lesion.

Targeted next-generation sequencing to diagnose drug-resistant tuberculosis: a systematic review and meta-analysis.

BACKGROUND: Targeted next-generation sequencing (NGS) can rapidly and simultaneously detect mutations associated with resistance to tuberculosis drugs across multiple gene targets. The use of targeted NGS to diagnose drug-resistant tuberculosis, as described in publicly available data, has not been comprehensively reviewed. We aimed to identify targeted NGS assays that diagnose drug-resistant tuberculosis, determine how widely this technology has been used, and assess the diagnostic accuracy of these assays. METHODS: In this systematic review and meta-analysis, we searched MEDLINE, Embase, Cochrane Library, Web of Science Core Collection, Global Index Medicus, Google Scholar, ClinicalTrials.gov, and the WHO International Clinical Trials Registry Platform for published and unpublished reports on targeted NGS for drug-resistant tuberculosis from Jan 1, 2005, to Oct 14, 2022, with updates to our search in Embase and Google Scholar until Feb 13, 2024. Studies eligible for the systematic review described targeted NGS approaches to predict drug resistance in Mycobacterium tuberculosis infections using primary samples, reference strain collections, or cultured isolates from individuals with presumed or confirmed tuberculosis. Our search had no limitations on study type or language, although only reports in English, German, and French were screened for eligibility. For the meta-analysis, we included test accuracy studies that used any reference standard, and we assessed risk of bias using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. The primary outcomes for the meta-analysis were sensitivity and specificity of targeted NGS to diagnose drug-resistant tuberculosis compared to phenotypic and genotypic drug susceptibility testing. We used a Bayesian bivariate model to generate summary receiver operating characteristic plots and diagnostic accuracy measures, overall and stratified by drug and sample type. This study is registered with PROSPERO, CRD42022368707. FINDINGS: We identified and screened 2920 reports, of which 124 were eligible for our systematic review, including 37 review articles and 87 reports of studies collecting samples for targeted NGS. Sequencing was mainly done in the USA (14 [16%] of 87), western Europe (ten [11%]), India (ten [11%]), and China (nine [10%]). We included 24 test accuracy studies in the meta-analysis, in which 23 different tuberculosis drugs or drug groups were assessed, covering first-line drugs, injectable drugs, and fluoroquinolones and predominantly comparing targeted NGS with phenotypic drug susceptibility testing. The combined sensitivity of targeted NGS across all drugs was 94·1% (95% credible interval [CrI] 90·9-96·3) and specificity was 98·1% (97·0-98·9). Sensitivity for individual drugs ranged from 76·5% (52·5-92·3) for capreomycin to 99·1% (98·3-99·7) for rifampicin; specificity ranged from 93·1% (88·0-96·3) for ethambutol to 99·4% (98·3-99·8) for amikacin. Diagnostic accuracy was similar for primary clinical samples and culture isolates overall and for rifampicin, isoniazid, ethambutol, streptomycin, and fluoroquinolones, and similar after excluding studies at high risk of bias (overall sensitivity 95·2% [95% CrI 91·7-97·1] and specificity 98·6% [97·4-99·3]). INTERPRETATION: Targeted NGS is highly sensitive and specific for detecting drug resistance across panels of tuberculosis drugs and can be performed directly on clinical samples. There is a paucity of data on performance for some currently recommended drugs. The barriers preventing the use of targeted NGS to diagnose drug-resistant tuberculosis in high-burden countries need to be addressed. FUNDING: National Institutes of Allergy and Infectious Diseases and Swiss National Science Foundation.