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通过结合临床、放射学和胸水分析参数预测恶性及准恶性胸腔积液

Predicting Malignant and Paramalignant Pleural Effusions by Combining Clinical, Radiological and Pleural Fluid Analytical Parameters.

作者信息

Herrera Lara Susana, Fernández-Fabrellas Estrella, Juan Samper Gustavo, Marco Buades Josefa, Andreu Lapiedra Rafael, Pinilla Moreno Amparo, Morales Suárez-Varela María

机构信息

Pulmonology Department, Dr Peset University Hospital, Avenue Gaspar Aguilar, 90, 46017, Valencia, Spain.

Pulmonology Department, General University Consorci Hospital, Valencia, Spain.

出版信息

Lung. 2017 Oct;195(5):653-660. doi: 10.1007/s00408-017-0032-3. Epub 2017 Jun 27.

Abstract

BACKGROUND

The usefulness of clinical, radiological and pleural fluid analytical parameters for diagnosing malignant and paramalignant pleural effusion is not clearly stated. Hence this study aimed to identify possible predictor variables of diagnosing malignancy in pleural effusion of unknown aetiology.

METHODS

Clinical, radiological and pleural fluid analytical parameters were obtained from consecutive patients who had suffered pleural effusion of unknown aetiology. They were classified into three groups according to their final diagnosis: malignant, paramalignant and benign pleural effusion. The CHAID (Chi-square automatic interaction detector) methodology was used to estimate the implication of the clinical, radiological and analytical variables in daily practice through decision trees.

RESULTS

Of 71 patients, malignant (n = 31), paramalignant (n = 15) and benign (n = 25), smoking habit, dyspnoea, weight loss, radiological characteristics (mass, node, adenopathies and pleural thickening) and pleural fluid analytical parameters (pH and glucose) distinguished malignant and paramalignant pleural effusions (all with a p < 0.05). Decision tree 1 classified 77.8% of malignant and paramalignant pleural effusions in step 2. Decision tree 2 classified 83.3% of malignant pleural effusions in step 2, 73.3% of paramalignant pleural effusions and 91.7% of benign ones.

CONCLUSIONS

The data herein suggest that the identified predictor values applied to tree diagrams, which required no extraordinary measures, have a higher rate of correct identification of malignant, paramalignant and benign effusions when compared to techniques available today and proved most useful for usual clinical practice. Future studies are still needed to further improve the classification of patients.

摘要

背景

临床、放射学及胸腔积液分析参数在诊断恶性和准恶性胸腔积液方面的效用尚无明确阐述。因此,本研究旨在确定在病因不明的胸腔积液中诊断恶性肿瘤的可能预测变量。

方法

从连续的病因不明胸腔积液患者中获取临床、放射学及胸腔积液分析参数。根据最终诊断将他们分为三组:恶性、准恶性和良性胸腔积液。采用CHAID(卡方自动交互检测器)方法,通过决策树评估临床、放射学及分析变量在日常实践中的影响。

结果

71例患者中,恶性(n = 31)、准恶性(n = 15)和良性(n = 25),吸烟习惯、呼吸困难、体重减轻、放射学特征(肿块、结节、淋巴结病和胸膜增厚)以及胸腔积液分析参数(pH值和葡萄糖)可区分恶性和准恶性胸腔积液(均p < 0.05)。决策树1在第2步对77.8%的恶性和准恶性胸腔积液进行了分类。决策树2在第2步对83.3%的恶性胸腔积液、73.3%的准恶性胸腔积液和91.7%的良性胸腔积液进行了分类。

结论

本文数据表明,应用于树形图的已确定预测值无需特殊措施,与当今现有技术相比,对恶性、准恶性和良性胸腔积液的正确识别率更高,且被证明对日常临床实践最为有用。仍需进一步研究以进一步完善患者分类。

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