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由神经网络驱动的MIA3G多变量指标检测显著改善了卵巢癌的手术考量。

Ovarian Cancer surgical consideration is markedly improved by the neural network powered-MIA3G multivariate index assay.

作者信息

Roy Choudhury Manjusha, Pappas Todd C, Twiggs Leo B, Caoili Emma, Fritsche Herbert, Phan Ryan T

机构信息

Department of Research and Development, Aspira Women's Health, Austin, TX, United States.

Division of Clinical Operations and Medical Affairs, Aspira Women's Health, Austin, TX, United States.

出版信息

Front Med (Lausanne). 2024 May 2;11:1374836. doi: 10.3389/fmed.2024.1374836. eCollection 2024.

Abstract

BACKGROUND

Surgery remains the main treatment option for an adnexal mass suspicious of ovarian cancer. The malignancy rate is, however, only 10-15% in women undergoing surgery. This results in a high number of unnecessary surgeries. A surveillance-based approach is recommended to form the basis for surgical referrals. We have previously reported the clinical performance of MIA3G, a deep neural network-based algorithm, for assessing ovarian cancer risk. In this study, we show that MIA3G markedly improves the surgical selection for women presenting with adnexal masses.

METHODS

MIA3G employs seven serum biomarkers, patient age, and menopausal status. Serum samples were collected from 785 women (IQR: 39-55 years) across 12 centers that presented with adnexal masses. MIA3G risk scores were calculated for all subjects in this cohort. Physicians had no access to the MIA3G risk score when deciding upon a surgical referral. The performance of MIA3G for surgery referral was compared to clinical and surgical outcomes. MIA3G was also tested in an independent cohort comprising 29 women across 14 study sites, in which the physicians had access to and utilized MIA3G prior to surgical consideration.

RESULTS

When compared to the actual number of surgeries ( = 207), referrals based on the MIA3G score would have reduced surgeries by 62% ( = 79). The reduction was higher in premenopausal patients (77%) and in patients ≤55 years old (70%). In addition, a 431% improvement in malignancy prediction would have been observed if physicians had utilized MIA3G scores for surgery selection. The accuracy of MIA3G referral was 90.00% (CI 87.89-92.11), while only 9.18% accuracy was observed when the MIA3G score was not used. These results were corroborated in an independent multi-site study of 29 patients in which the physicians utilized MIA3G in surgical consideration. The surgery reduction was 87% in this cohort. Moreover, the accuracy and concordance of MIA3G in this independent cohort were each 96.55%.

CONCLUSION

These findings demonstrate that MIA3G markedly augments the physician's decisions for surgical intervention and improves malignancy prediction in women presenting with adnexal masses. MIA3G utilization as a clinical diagnostic tool might help reduce unnecessary surgeries.

摘要

背景

手术仍然是疑似卵巢癌附件包块的主要治疗选择。然而,接受手术的女性中恶性肿瘤发生率仅为10%-15%。这导致大量不必要的手术。建议采用基于监测的方法作为手术转诊的依据。我们之前报道了基于深度神经网络的算法MIA3G评估卵巢癌风险的临床性能。在本研究中,我们表明MIA3G显著改善了有附件包块女性的手术选择。

方法

MIA3G采用七种血清生物标志物、患者年龄和绝经状态。从12个中心的785名有附件包块的女性(四分位间距:39-55岁)中收集血清样本。计算该队列中所有受试者的MIA3G风险评分。医生在决定手术转诊时无法获取MIA3G风险评分。将MIA3G用于手术转诊的性能与临床和手术结果进行比较。MIA3G也在一个独立队列中进行了测试,该队列包括14个研究地点的29名女性,其中医生在手术考虑前可以获取并使用MIA3G。

结果

与实际手术数量(=207)相比,基于MIA3G评分的转诊可减少62%的手术(=79)。绝经前患者(77%)和年龄≤55岁的患者(70%)减少幅度更大。此外,如果医生在手术选择中使用MIA3G评分,恶性肿瘤预测将提高431%。MIA3G转诊的准确率为90.00%(95%置信区间87.89-92.11),而不使用MIA3G评分时准确率仅为9.18%。这些结果在一项对29名患者的独立多中心研究中得到证实,该研究中医生在手术考虑中使用了MIA3G。该队列中的手术减少率为87%。此外,该独立队列中MIA3G的准确率和一致性均为96.55%。

结论

这些发现表明MIA3G显著增强了医生对手术干预的决策,并改善了有附件包块女性的恶性肿瘤预测。将MIA3G用作临床诊断工具可能有助于减少不必要的手术。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee12/11097110/90b5ed9f3720/fmed-11-1374836-g001.jpg

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