卵巢癌：一种基于证据、易于使用的预测规则，以优化随访胸部CT的使用。

Ovarian Cancer: An Evidence-Based, Easy-to-Use Prediction Rule to Optimize the Use of Follow-up Chest CT.

作者信息

Shinagare Atul B, Suh Chong Hyun, Kim Kyung Won, Somarouthu Bhanusupriya, Van den Abbeele Annick D, Ramaiya Nikhil H

机构信息

Department of Radiology, Brigham and Women's Hospital/Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts.

Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea; Department of Radiology, Namwon Medical Center, Jeollabuk-Do, South Korea.

出版信息

J Am Coll Radiol. 2017 Apr;14(4):499-508. doi: 10.1016/j.jacr.2016.08.010. Epub 2016 Oct 6.

DOI:10.1016/j.jacr.2016.08.010

PMID:27720583

Abstract

PURPOSE

To create and validate an evidence-based prediction rule to optimize use of follow-up chest CT for ovarian cancer.

METHODS

In this Institutional Review Board-approved retrospective study performed at two academic medical centers, electronic medical records from January through December 2013 at center 1 (USA) and January 2012 through December 2013 at center 2 (South Korea) were searched to identify consecutive chest CTs performed within 5 years of initial cytoreductive surgery in patients with pathologically proven ovarian cancer. Three separate study cohorts were created: cohort 1, 316 CTs (in 150 patients) with high-grade serous ovarian cancer (HGSC) from center 1; cohort 2, 374 CTs (81 patients) with HGSC from center 2; and cohort 3, 87 CTs (56 patients) with non-HGSC histologies from center 1. A radiologist blinded to outcome of CT, using a prediction rule that utilized previously available information, categorized each CT into "high-risk" (stage 4 at presentation and/or preexisting abdominal disease [disease below diaphragmatic dome, visualized on abdominal CT]) or "low-risk" (neither of above). A blinded radiologist then reviewed chest CTs in random order to record thoracic metastases above the diaphragmatic dome, and outcome was compared with prediction rule risk category.

RESULTS

Among the three cohorts and in the total population, the prediction rule identified 94 of 316 (30%), 170 of 374 (45%), 53 of 87 (61%), and 317 of 777 (41%) CTs as "low-risk," respectively. The sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, and negative likelihood ratio were as follows: cohort 1: 95%, 35%, 24%, 97%, 1.46, 0.14; cohort 2: 88%, 53%, 29%, 95%, 1.87, 0.22; cohort 3: 88%, 66%, 21%, 98%, 2.59, 0.18; total population: 91%, 47%, 26%, 96%, 1.72, 0.19. False-negative rate in the three cohorts and in total population was 3 of 94 (3%), 8 of 170 (5%), 1 of 53 (2%), and 12 of 317 (4%); however, in each of these cases there was concurrent new abdominal disease.

CONCLUSIONS

The easy-to-use prediction rule helps avoid unnecessary chest CTs in patients with ovarian cancer with high sensitivity and negative predictive value, and with minimal risk of missing thoracoabdominal metastases.

摘要

目的

创建并验证一个基于证据的预测规则，以优化卵巢癌患者随访胸部CT的使用。

方法

在这项经机构审查委员会批准的回顾性研究中，对两个学术医疗中心的数据进行了分析。在美国中心1检索了2013年1月至12月的电子病历，在韩国中心2检索了2012年1月至2013年12月的电子病历，以识别经病理证实的卵巢癌患者在初次肿瘤细胞减灭术后5年内进行的连续胸部CT检查。创建了三个独立的研究队列：队列1，来自中心1的316例（150名患者）高级别浆液性卵巢癌（HGSC）的CT检查；队列2，来自中心2的374例（81名患者）HGSC的CT检查；队列3，来自中心1的87例（56名患者）非HGSC组织学类型的CT检查。一名对CT结果不知情的放射科医生，使用一个利用先前可用信息的预测规则，将每个CT分类为“高风险”（就诊时为4期和/或先前存在腹部疾病[腹部CT显示膈肌穹窿以下的疾病]）或“低风险”（以上情况均无）。然后一名不知情的放射科医生按随机顺序复查胸部CT，记录膈肌穹窿以上的胸部转移情况，并将结果与预测规则风险类别进行比较。

结果

在三个队列和总体人群中，预测规则分别将316例中的94例（30%）、374例中的170例（45%）、87例中的53例（61%）以及777例中的317例（41%）CT检查识别为“低风险”。敏感性、特异性、阳性预测值、阴性预测值、阳性似然比和阴性似然比分别如下：队列1：95%，35%，24%，97%，1.46，0.14；队列2：88%，53%，29%，95%，1.87，0.22；队列3：88%，66%，21%，98%，2.59，0.18；总体人群：91%，47%，26%，96%，1.72，0.19。三个队列和总体人群中的假阴性率分别为94例中的3例（3%）、170例中的8例（5%）、53例中的1例（2%）以及317例中的12例（4%）；然而，在这些病例中的每一例中都同时存在新的腹部疾病。