中国实验诊断学
中國實驗診斷學
중국실험진단학
Chinese Journal of Laboratory Diagnosis
2015年
11期
1837-1840
,共4页
任红岩%金明月%黄禹%陈正贤
任紅巖%金明月%黃禹%陳正賢
임홍암%금명월%황우%진정현
气道内超声%周围型肺癌%简易模型
氣道內超聲%週圍型肺癌%簡易模型
기도내초성%주위형폐암%간역모형
endobronchial ultrasonography%peripheral lung cancer%prediction model
目的:由患者肺外周病变的气道内超声图像及临床特征建立恶性概率估算模型,并探讨该模型临床诊断价值。方法收集我院2010年9月1日-2015年1月30日共150例肺外周病变患者入选本研究,其中135例获得明确的病理诊断结果,采集其气道内超声图像,分析、记录超声图像内部结构特征。结果经二分类多因素 logistic 回归分析,最终2个临床因素及5个超声特征纳入恶性概率估算模型, P = l/[l +e-(-2.986+1.993吸烟史+2.293CEA +1.552边界+l.616异质-2.011支气管充气影+1.748无回声)];绘制 ROC 曲线,计算曲线下面积(AUC)为0.926(95%CI:0.883-0.969),以 P ≥0.62为诊断界值,得出此方程的灵敏度为69/77=89.6%,特异度为42/58=72.4%,准确率为82.2%。结论①气道内超声对肺外周病变具有较高的良恶性诊断价值,是一种有效的影像学检查方法。②建立肺外周病变恶性概率估算模型,超声图像与临床特征相结合,更能提高对周围型肺癌诊断的准确率。
目的:由患者肺外週病變的氣道內超聲圖像及臨床特徵建立噁性概率估算模型,併探討該模型臨床診斷價值。方法收集我院2010年9月1日-2015年1月30日共150例肺外週病變患者入選本研究,其中135例穫得明確的病理診斷結果,採集其氣道內超聲圖像,分析、記錄超聲圖像內部結構特徵。結果經二分類多因素 logistic 迴歸分析,最終2箇臨床因素及5箇超聲特徵納入噁性概率估算模型, P = l/[l +e-(-2.986+1.993吸煙史+2.293CEA +1.552邊界+l.616異質-2.011支氣管充氣影+1.748無迴聲)];繪製 ROC 麯線,計算麯線下麵積(AUC)為0.926(95%CI:0.883-0.969),以 P ≥0.62為診斷界值,得齣此方程的靈敏度為69/77=89.6%,特異度為42/58=72.4%,準確率為82.2%。結論①氣道內超聲對肺外週病變具有較高的良噁性診斷價值,是一種有效的影像學檢查方法。②建立肺外週病變噁性概率估算模型,超聲圖像與臨床特徵相結閤,更能提高對週圍型肺癌診斷的準確率。
목적:유환자폐외주병변적기도내초성도상급림상특정건립악성개솔고산모형,병탐토해모형림상진단개치。방법수집아원2010년9월1일-2015년1월30일공150례폐외주병변환자입선본연구,기중135례획득명학적병리진단결과,채집기기도내초성도상,분석、기록초성도상내부결구특정。결과경이분류다인소 logistic 회귀분석,최종2개림상인소급5개초성특정납입악성개솔고산모형, P = l/[l +e-(-2.986+1.993흡연사+2.293CEA +1.552변계+l.616이질-2.011지기관충기영+1.748무회성)];회제 ROC 곡선,계산곡선하면적(AUC)위0.926(95%CI:0.883-0.969),이 P ≥0.62위진단계치,득출차방정적령민도위69/77=89.6%,특이도위42/58=72.4%,준학솔위82.2%。결론①기도내초성대폐외주병변구유교고적량악성진단개치,시일충유효적영상학검사방법。②건립폐외주병변악성개솔고산모형,초성도상여림상특정상결합,경능제고대주위형폐암진단적준학솔。
Objective To use the endobronchial ultrasonographic features of peripheral lung cancer with clinical data and establish a model to estimate the probability of malignancy in peripheral pulmonary lesions(PPLs),and evaluate its clinical diagnostic value.Methods Between September lst 2010 and May 30th 2015,endobronchial ultrasonography (EBUS)were performed in 150 patients with peripheral pulmonary lesions.At last,the EBUS images of the 135 cases were en-rolled,who had a definite pathological diagnosis.Analyse and record the characters of endobronchial images.Results According to the result of binary multivariable logistic regression analysis,we concluded two clinical data and five distinct EBUS image patterns which contribute to predicting the presence of malignancy.The equation of malignancy probability for any patient was:P = l/[l + e-(-2.9861.993smorking +2.293CEA +1.552 borderline +l.616 heterogeneity-2.011 air bronchogram +1.748 anechoic area)];the area under the ROC curve (AUC)was 0.926(95% CI:0.883-0.969),with P≥0.62 for the diagnosis of community values,it is concluded that the sensi-tivity of this equation was 69/77=89.6% and specificity was 42/58=72.4%,the accuracy rate was 82.2%.Conclusion ①Endobronchial ultrasonography in diagnosis of benign and malignant pulmonary peripheral lesions have a high value,and is an effective method of imaging.②Combining image results with the clinical data to establish binary logistic models to predict the malignant probability could raise the accuracy.