Clinical prediction model to characterize pulmonary nodules -: Validation and added value of 18F-fluorodeoxyglucose positron emission tomography
Clinical prediction model to characterize pulmonary nodules -: Validation and added value of 18F-fluorodeoxyglucose positron emission tomography
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DOI：
10.1378/chest.128.4.2490
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发表时间：
2005-10-01
期刊：
影响因子：
9.6
通讯作者：
Hoekstra, OS
中科院分区：
文献类型：
--
作者：
Herder, GJ;van Tinteren, H;Hoekstra, OS
背景：f -18氟脱氧葡萄糖（FDG）正电子发射断层扫描（PET）扫描作为不确定肺结节检测前风险评估功能的附加价值尚不清楚。目的：根据Swensen及其同事的研究，获得预测模型的外部验证，并量化FDG-PET扫描的潜在附加价值，作为其与该预测模型相关的操作特征的函数，在放射学上不确定的肺结节患者群体中。设计、环境和患者：1997年8月至2001年3月，从VU大学医学中心PET中心的数据库中回顾性地确定了所有转诊进行FDG-PET扫描的不确定孤立性肺结节患者。结果：106例患者符合研究条件，61例（57%）患者证实有恶性结节。模型的拟合优度统计（根据Swensen）表明，观察到的恶性肿瘤比例与预测的比例没有差异（p = 0.46）。PET扫描结果使用4点强度量表读数进行分类，评估的受试者工作特征曲线下的面积为0.88（95%可信区间[CI]， 0.77至0.91）。使用4点强度量表读数分类的PET扫描结果与Swensen预测的曲线下面积（AUC）之间的估计差异为0.095 (95% CI, -0.003至0.193)，差异不显著（p = 0.058）。当将PET扫描结果与Swensen模型计算的预测概率相加时，AUC提高了13.6% （95% CI, 6 ~ 21; p = 0.0003）。结论：Swensen等临床预测模型具有外部效度。然而，特别是在其估计的较低范围内，该模型可能低估了恶性肿瘤的实际概率。结合视觉读取FDG-PET扫描和预测因素似乎产生最佳的准确性。
Background: The added value of F-18-fluorodeoxyglucose (FDG) positron emission tomography (PET) scanning as a function of pretest risk assessment in indeterminate pulmonary nodules is still unclear.Objective: To obtain an external validation of the prediction model according to Swensen and colleagues, and to quantify the potential added value of FDG-PET scanning as a function of its operating characteristics in relation to this prediction model, in a population of patients with radiologically indeterminate pulmonary nodules.Design, setting, and patients: Between August 1997 and March 2001, all patients with an indeterminate solitary pulmonary nodule who had been referred for FDG-PET scanning were retrospectively identified from the database of the PET center at the VU University Medical Center.Results: One hundred six patients were eligible for the study, and 61 patients (57%) proved to have malignant nodules. The goodness-of-fit statistic for the model (according to Swensen) indicated that the observed proportion of malignancies did not differ from the predicted proportion (p = 0.46). PET scan results, which were classified using the 4-point intensity scale reading, yielded an area under the evaluated receiver operating characteristic curve of 0.88 (95% confidence interval [CI], 0.77 to 0.91). The estimated difference of 0.095 (95% CI, -0.003 to 0.193) between the PET scan results classified using the 4-point intensity scale reading and the area under the curve (AUC) from the Swensen prediction was not significant (p = 0.058). The PET scan results, when added to the predicted probability calculated by the Swensen model, improves the AUC by 13.6% (95% CI, 6 to 21; p = 0.0003).Conclusion: The clinical prediction model of Swensen et al was proven to have external validity. However, especially in the lower range of its estimates, the model may underestimate the actual probability of malignancy. The combination of visually read FDG-PET scans and pretest factors appears to yield the best accuracy.