Department of Obstetrics and Reproductive Medicine, Tenon Hospital, Paris.
Clinical Research Group Paris 6: Endometriosis Expert Center, Sorbonne University, Sorbonne, France.
NEJM Evid. 2023 Jul;2(7):EVIDoa2200282. doi: 10.1056/EVIDoa2200282. Epub 2023 Jun 9.
The discovery of a saliva-based micro–ribonucleic acid (miRNA) signature for endometriosis in 2022 opened up new perspectives for early and noninvasive diagnosis of the disease. The 109-miRNA saliva signature is the product of miRNA biomarkers and artificial intelligence (AI) modeling. We designed a multicenter study to provide external validation of its diagnostic accuracy. We present here an interim analysis. METHODS: The first 200 patients included in the multicenter prospective ENDOmiRNA Saliva Test study (NCT05244668) were included for interim analysis. The study population comprised women from 18 to 43 years of age with a formal diagnosis of endometriosis or with suspected endometriosis. Epidemiologic, clinical, and saliva sequencing data were collected between November 2021 and March 2022. Genomewide miRNA expression profiling by small RNA sequencing using next-generation sequencing (NGS) was performed, and a random forest algorithm was used to assess the diagnostic accuracy. RESULTS: In this interim analysis of the external validation cohort, with a population prevalence of 79.5%, the 109-miRNA saliva diagnostic signature for endometriosis had a sensitivity of 96.2% (95% confidence interval [CI], 93.7 to 97.3%), specificity of 95.1% (95% CI, 85.2 to 99.1%), positive predictive value of 95.1% (95% CI, 85.2 to 99.1%), negative predictive value of 86.7% (95% CI, 77.6 to 90.3%), positive likelihood ratio of 19.7 (95% CI, 6.3 to 108.8), negative likelihood ratio of 0.04 (95% CI, 0.03 to 0.07), and area under the receiver operating characteristic curve of 0.96 (95% CI, 0.92 to 0.98). CONCLUSIONS: The use of NGS and AI in the sequencing and analysis of miRNA provided a saliva-based miRNA signature for endometriosis. Our interim analysis of a prospective multicenter external validation study provides support for its ongoing investigation as a diagnostic tool. (Funded by Ziwig and the Conseil Régional d’Ile de France [Grant EX024087]; ClinicalTrials.gov number, NCT05244668.)
2022 年，一种基于唾液的微小 RNA（miRNA）标志物的发现为子宫内膜异位症的早期和非侵入性诊断开辟了新的前景。109-miRNA 唾液标志物是 miRNA 生物标志物和人工智能（AI）建模的产物。我们设计了一项多中心研究，以提供其诊断准确性的外部验证。我们在此介绍一项中期分析。方法：这项多中心前瞻性 ENDOmiRNA 唾液检测研究（NCT05244668）纳入的首批 200 例患者纳入中期分析。研究人群包括年龄在 18 至 43 岁之间、经正式诊断为子宫内膜异位症或疑似子宫内膜异位症的女性。2021 年 11 月至 2022 年 3 月期间收集了流行病学、临床和唾液测序数据。采用下一代测序（NGS）进行小 RNA 测序的全基因组 miRNA 表达谱分析，并采用随机森林算法评估诊断准确性。结果：在这项外部验证队列的中期分析中，人群患病率为 79.5%，用于诊断子宫内膜异位症的 109-miRNA 唾液诊断标志物的敏感性为 96.2%（95%置信区间 [CI]，93.7%至 97.3%），特异性为 95.1%（95% CI，85.2%至 99.1%），阳性预测值为 95.1%（95% CI，85.2%至 99.1%），阴性预测值为 86.7%（95% CI，77.6%至 90.3%），阳性似然比为 19.7（95% CI，6.3 至 108.8），阴性似然比为 0.04（95% CI，0.03 至 0.07），受试者工作特征曲线下面积为 0.96（95% CI，0.92 至 0.98）。结论：NGS 和 AI 在 miRNA 测序和分析中的应用为子宫内膜异位症提供了一种基于唾液的 miRNA 标志物。我们对这项前瞻性多中心外部验证研究的中期分析为将其作为一种诊断工具进行进一步研究提供了支持。（由 Ziwig 和法兰西岛大区理事会资助[赠款 EX024087]；临床试验编号，NCT05244668）。
