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恶性漏出性胸腔积液的预测模型。

Predictive models of malignant transudative pleural effusions.

作者信息

Ferreiro Lucía, Gude Francisco, Toubes María E, Lama Adriana, Suárez-Antelo Juan, San-José Esther, González-Barcala Francisco Javier, Golpe Antonio, Álvarez-Dobaño José M, Rábade Carlos, Rodríguez-Núñez Nuria, Díaz-Louzao Carla, Valdés Luis

机构信息

Department of Pulmonology, University Clinical Hospital of Santiago de Compostela, Santiago de Compostela, Spain;; Interdisciplinary Research Group in Pulmonology, Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain.

Department of Clinical Epidemiology, University Clinical Hospital of Santiago de Compostela, Santiago de Compostela, Spain;; Department of Epidemiology of Common Diseases, Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain.

出版信息

J Thorac Dis. 2017 Jan;9(1):106-116. doi: 10.21037/jtd.2017.01.12.

Abstract

BACKGROUND

There are no firm recommendations when cytology should be performed in pleural transudates, since some malignant pleural effusions (MPEs) behave biochemically as transudates. The objective was to assess when would be justified to perform cytology on pleural transudates.

METHODS

Consecutive patients with transudative pleural effusion (PE) were enrolled and divided in two groups: malignant and non-MPE. Logistic regression analysis was used to estimate the probability of malignancy. Two prognostic models were considered: (I) clinical-radiological variables; and (II) combination of clinical-radiological and analytical variables. Calibration and discrimination [receiver operating characteristics (ROC) curves and area under the curve (AUC)] were performed.

RESULTS

A total of 281 pleural transudates were included: 26 malignant and 255 non-malignant. The AUC obtained with Model 1 (left PE, radiological images compatible with malignancy, absence of dyspnea, and serosanguinous appearance of the fluid), and Model 2 (the variables of Model 1 plus CEA) were 0.973 and 0.995, respectively. Although no false negatives are found in Models 1 and 2 to probabilities of 11% and 14%, respectively, by applying bootstrapping techniques to not find false negatives in 95% of other possible samples would require lowering the cut-off points for the aforementioned probabilities to 3% (Model 1) and 4% (Model 2), respectively. The false positive results are 32 (Model 1) and 18 (Model 2), with no false negatives.

CONCLUSIONS

The applied models have a high discriminative ability to predict when a transudative PE may be of neoplastic origin, being superior to adding an analytical variable to the clinic-radiological variables.

摘要

背景

对于何时应对胸腔漏出液进行细胞学检查尚无明确建议,因为一些恶性胸腔积液(MPE)在生化表现上类似漏出液。目的是评估对胸腔漏出液进行细胞学检查的合理时机。

方法

纳入连续性胸腔漏出液患者并分为两组:恶性组和非MPE组。采用逻辑回归分析评估恶性肿瘤的概率。考虑了两种预后模型:(I)临床-放射学变量;(II)临床-放射学与分析变量的组合。进行了校准和鉴别分析[受试者操作特征(ROC)曲线及曲线下面积(AUC)]。

结果

共纳入281例胸腔漏出液:26例为恶性,255例为非恶性。模型1(左侧胸腔积液、放射学影像符合恶性、无呼吸困难及液体呈血性外观)和模型2(模型1的变量加上癌胚抗原)得到的AUC分别为0.973和0.995。尽管模型1和模型2在概率分别为11%和14%时未发现假阴性,但通过应用自抽样技术在95%的其他可能样本中不发现假阴性,则需要将上述概率的截断点分别降至3%(模型1)和4%(模型2)。假阳性结果分别为32例(模型1)和18例(模型2),无假阴性。

结论

所应用的模型在预测漏出性胸腔积液是否可能源于肿瘤方面具有较高的鉴别能力,优于在临床-放射学变量基础上增加一个分析变量。

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本文引用的文献

1
Recommendations of diagnosis and treatment of pleural effusion. Update.
Arch Bronconeumol. 2014 Jun;50(6):235-49. doi: 10.1016/j.arbres.2014.01.016. Epub 2014 Mar 31.
2
Developing a 'pleural team' to run a reactive pleural service.
Clin Med (Lond). 2013 Oct;13(5):452-6. doi: 10.7861/clinmedicine.13-5-452.
3
Combining clinical and analytical parameters improves prediction of malignant pleural effusion.
Lung. 2013 Dec;191(6):633-43. doi: 10.1007/s00408-013-9512-2. Epub 2013 Oct 2.
4
Unexpandable lung.
Arch Bronconeumol. 2013 Feb;49(2):63-9. doi: 10.1016/j.arbres.2012.05.007. Epub 2012 Jun 30.
5
Pleural effusions.
Med Clin North Am. 2011 Nov;95(6):1055-70. doi: 10.1016/j.mcna.2011.08.005. Epub 2011 Sep 25.
6
Diagnostic value of N-terminal pro-brain natriuretic peptide in pleural effusions of cardiac origin.
Arch Bronconeumol. 2011 May;47(5):246-51. doi: 10.1016/j.arbres.2011.02.004. Epub 2011 Apr 6.
8
Transudates in malignancy: still a role for pleural fluid.
Ann Acad Med Singap. 2008 Sep;37(9):760-3.
9
Diagnostic accuracy of tumour markers for malignant pleural effusion: a meta-analysis.
Thorax. 2008 Jan;63(1):35-41. doi: 10.1136/thx.2007.077958. Epub 2007 Jun 15.
10
Diagnostic and therapeutic approach to acute decompensated heart failure.
Am J Med. 2007 Feb;120(2):121-7. doi: 10.1016/j.amjmed.2006.05.066.

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