乳腺癌前哨淋巴結(jié)術(shù)中分子診斷及其對(duì)非前哨淋巴結(jié)轉(zhuǎn)移的預(yù)測(cè)研究
發(fā)布時(shí)間：2018-08-25 11:06
【摘要】：目的:本研究旨在評(píng)估乳腺癌前哨淋巴結(jié)(Sentinel Lymph Node,SLN)術(shù)中分子診斷技術(shù)一步核酸擴(kuò)增法(One-Step Nucleic Acid Amplification,OSNA)的診斷價(jià)值,并根據(jù)OSNA檢測(cè)結(jié)果分析其對(duì)非前哨淋巴結(jié)(Non-Sentinel Lymph Node,NSLN)轉(zhuǎn)移的預(yù)測(cè)能力,進(jìn)一步建立乳腺癌術(shù)中快速預(yù)測(cè)NSLN轉(zhuǎn)移的預(yù)測(cè)模型,以期有效指導(dǎo)乳腺癌后續(xù)治療。方法:本研究包括2010年OSNA臨床試驗(yàn)入組的552例患者及此次試驗(yàn)本中心前瞻性入組的348例患者,共計(jì)入組患者900例,有效病例為870例。術(shù)中根據(jù)SLN的質(zhì)量及短軸長(zhǎng)度進(jìn)行切分。若SLN質(zhì)量100 mg,則不進(jìn)行切分,僅術(shù)后行逐層切片病理檢測(cè);若SLN質(zhì)量為100~1200 mg,則垂直于短軸進(jìn)行切分。短軸長(zhǎng)度≤4mm時(shí),則切分為a和b兩個(gè)組織塊,a組織塊術(shù)中行OSNA檢測(cè),b組織塊行病理檢測(cè);短軸長(zhǎng)度4 mm時(shí),則切分為a,b,c,d四個(gè)組織塊,a、c組織塊術(shù)中行OSNA檢測(cè),b、d組織塊行病理檢測(cè)。其中a,b,c,d組織塊均行術(shù)中印片細(xì)胞學(xué)(Touch Imprint Cytology,TIC)檢測(cè)。一方面,OSNA檢測(cè)結(jié)果同術(shù)后逐層連續(xù)切片病理作比較,另一方面根據(jù)OSNA結(jié)果建立NSLN轉(zhuǎn)移風(fēng)險(xiǎn)的術(shù)中快速預(yù)測(cè)模型。結(jié)果:1、OSNA檢測(cè)的診斷價(jià)值(1)以病例數(shù)為統(tǒng)計(jì)對(duì)象分析,以術(shù)后病理為金標(biāo)準(zhǔn),OSNA與FS、TIC比較以病例數(shù)為統(tǒng)計(jì)對(duì)象分析,OSNA的敏感性、準(zhǔn)確性、特異性、陽性預(yù)測(cè)值、陰性預(yù)測(cè)值分別為88.7%、89.0%、89.1%、72.3%、96.1%。FS的敏感性、準(zhǔn)確性、特異性、陽性預(yù)測(cè)值、陰性預(yù)測(cè)值分別為77.9%、94.0%、100.0%、100.0%、92.3%。TIC的敏感性、準(zhǔn)確性、特異性、陽性預(yù)測(cè)值、陰性預(yù)測(cè)值分別為83.0%、93.5%、96.8%、89.3%、94.7%。OSNA的敏感性顯著優(yōu)于FS(88.7%vs.77.9%,P=0.0095),與TIC相比并無統(tǒng)計(jì)學(xué)差異(88.7%vs.83.0%,P=0.1254)。(2)以淋巴結(jié)數(shù)為統(tǒng)計(jì)對(duì)象分析,以術(shù)后病理為金標(biāo)準(zhǔn),OSNA與FS、TIC比較以淋巴結(jié)數(shù)為統(tǒng)計(jì)對(duì)象分析,OSNA的敏感性、準(zhǔn)確性、特異性、陽性預(yù)測(cè)值、陰性預(yù)測(cè)值分別為85.4%、91.4%、92.6%、68.4%、97.1%。FS的敏感性、準(zhǔn)確性、特異性、陽性預(yù)測(cè)值、陰性預(yù)測(cè)值分別為68.6%,94.3%,100.0%,100.0%,93.5%。TIC的敏感性、準(zhǔn)確性、特異性、陽性預(yù)測(cè)值、陰性預(yù)測(cè)值分別為81.0%,94.4%,96.9%,83.2%,96.5%。OSNA的敏感性顯著優(yōu)于FS(85.4%vs.68.6%,P=0.0021),與TIC相比并無統(tǒng)計(jì)學(xué)差異(85.4%vs.81.0%,P=0.82)。(3)OSNA與FS、TIC對(duì)于宏轉(zhuǎn)移及微轉(zhuǎn)移的敏感性比較對(duì)于術(shù)后伴有宏轉(zhuǎn)移灶的SLN,OSNA檢出的敏感性是93.1%,FS檢出的敏感性是88.5%,TIC檢出的敏感性是92.2%,OSNA的敏感性與FS及TIC相似(P=0.1907,P=0.8543),并無統(tǒng)計(jì)學(xué)差異。對(duì)于術(shù)后伴有微轉(zhuǎn)移灶的SLN,OSNA檢出的敏感性是65.3%,FS檢出的敏感性是40.4%,TIC檢出的敏感性是44.0%,OSNA的敏感性均顯著優(yōu)于FS及TIC(P=0.0121,P=0.0139)。2、NSLN轉(zhuǎn)移風(fēng)險(xiǎn)的術(shù)中快速預(yù)測(cè)模型(1)建立基于分子診斷預(yù)測(cè)NSLN轉(zhuǎn)移的列線圖模型對(duì)建模組103例患者行單因素分析發(fā)現(xiàn),原發(fā)腫瘤大小(P=0.001)、脈管浸潤(rùn)(P=0.007)、SLN總腫瘤負(fù)荷(Total Tumor Load,TTL)(P=0.000)、最大轉(zhuǎn)移灶大小(P=0.000)、SLN陽性數(shù)(P=0.000)、SLN陰性數(shù)(P=0.000)、SLN陽性數(shù)/SLN總數(shù)(P=0.000)均與NSLN轉(zhuǎn)移相關(guān)。Logistic多因素回歸分析后發(fā)現(xiàn)TTL(P=0.002)、原發(fā)腫瘤大小(P=0.013)、SLN陽性數(shù)(P=0.000)、SLN陰性數(shù)(P=0.001)是NSLN轉(zhuǎn)移的獨(dú)立相關(guān)因素,利用TTL、原發(fā)腫瘤大小、SLN陽性數(shù)及SLN陰性數(shù)建立預(yù)測(cè)乳腺癌NSLN轉(zhuǎn)移的列線圖模型。建模組患者NSLN轉(zhuǎn)移預(yù)測(cè)值的受試者工作特征曲線(Receiver Operating Characteristic Curve,ROC)下面積(AUC)為0.814。(2)本模型的預(yù)測(cè)性驗(yàn)證研究本研究利用驗(yàn)證組61例患者對(duì)建立的預(yù)測(cè)模型進(jìn)行了驗(yàn)證,得出AUC為0.842。(3)影像學(xué)評(píng)估的腫瘤大小與原發(fā)腫瘤大小對(duì)模型預(yù)測(cè)性差異的比較本研究利用驗(yàn)證組患者影像學(xué)(超聲、鉬靶、乳腺磁共振)評(píng)估的腫瘤大小數(shù)據(jù)替代術(shù)后病理評(píng)估的原發(fā)腫瘤大小數(shù)據(jù),對(duì)模型進(jìn)行了驗(yàn)證,得出AUC為0.838,與前述驗(yàn)證性ROC曲線下面積相比并無統(tǒng)計(jì)學(xué)差異,P=0.7406。(4)本模型對(duì)腋窩淋巴結(jié)分期pN1及≥pN2患者的預(yù)測(cè)性研究本模型區(qū)分患者pN1及≥pN2腋窩淋巴結(jié)分期的預(yù)測(cè)風(fēng)險(xiǎn)臨界值為45.4%,AUC為0.861,P0.0001。另外,為探究術(shù)中利用影像學(xué)腫瘤大小快速預(yù)測(cè)腋窩淋巴結(jié)分期情況,利用本模型得出驗(yàn)證組患者中pN1及≥p N2的預(yù)測(cè)風(fēng)險(xiǎn)臨界值為33.5%,AUC為0.839,P0.0001。(5)本模型與其他預(yù)測(cè)模型的驗(yàn)證性比較利用入組患者分別對(duì)美國(guó)安德森癌癥中心(MD Anderson,MDA)的模型及法國(guó)Tenon醫(yī)院的模型進(jìn)行了驗(yàn)證,得出AUC分別為0.745及0.623。另外,本模型對(duì)西班牙Isabel等建立的模型進(jìn)行了驗(yàn)證,得出AUC為0.834。通過對(duì)比分析,本模型與MDA及Tenon模型相比有統(tǒng)計(jì)學(xué)差異,與Isabel等人的模型相比并無統(tǒng)計(jì)學(xué)差異。結(jié)論:OSNA檢測(cè)作為一種客觀的標(biāo)準(zhǔn)化技術(shù),可以術(shù)中快速、準(zhǔn)確的對(duì)SLN做出診斷,且操作簡(jiǎn)單,大大降低了病理醫(yī)師的主觀性和工作負(fù)擔(dān),可作為SLN術(shù)中診斷乃至術(shù)后診斷的首選,適合在中國(guó)推廣�；贠SNA術(shù)中分子診斷結(jié)果建立的術(shù)中快速預(yù)測(cè)NSLN轉(zhuǎn)移的模型明顯優(yōu)于其他預(yù)測(cè)模型,對(duì)后續(xù)腋窩的處理、放療靶區(qū)勾畫及全身治療具有更好的指導(dǎo)價(jià)值。
[Abstract]:Objective: To evaluate the diagnostic value of one-step Nucleic Acid Amplification (OSNA), a molecular diagnostic technique for sentinel lymph node (SLN) metastasis in breast cancer, and to analyze its predictive ability for non-Sentinel Lymph Node (NSLN) metastasis according to the results of OSNA detection. Methods: This study included 552 patients enrolled in the 2010 OSNA clinical trial and 348 prospective patients enrolled in the center of this trial. A total of 900 patients were enrolled in the study and 870 effective patients were enrolled in the study. If the length of SLN is less than 4 mm, it is divided into a and B tissue blocks. When the length of the short axis is less than 4 mm, OSNA detection is performed in a tissue block, and pathological examination is performed in B tissue block. When the length of the short axis is 4 mm, it is divided into a, B and B tissue blocks. The intraoperative Touch Imprint Cytology (TIC) was performed in all the tissues of a, b, C and D. On the one hand, the results of OSNA were compared with the pathology of successive slices after operation, on the other hand, the risk of NSLN metastasis was established according to the results of OSNA. Results: 1. The diagnostic value of OSNA (1) was analyzed by case number and pathology after operation as golden standard. The sensitivity, accuracy, specificity, positive predictive value and negative predictive value of OSNA were 88.7%, 89.0%, 89.1%, 72.3%, 96.1% respectively. Specificity, positive predictive value, negative predictive value were 77.9%, 94.0%, 100.0%, 100.0%, and 92.3%, respectively. Sensitivity, accuracy, specificity, positive predictive value and negative predictive value of TIC were 83.0%, 93.5%, 96.8%, 89.3%, 94.7% respectively. OSNA was significantly more sensitive than FS (88.7% vs. 77.9%, P = 0.0095), and had no statistical difference compared with TIC (88.7% vs. 83.0%, P = 0.1254). (2) The sensitivity, accuracy, specificity, positive predictive value and negative predictive value of OSNA were 85.4%, 91.4%, 92.6%, 68.4%, 97.1% respectively. The sensitivity, accuracy, specificity, positive predictive value and negative predictive value of FS were 85.4%, 91.4%, 92.6%, 68.4% and 97.1% respectively. The sensitivity, accuracy, specificity, positive predictive value and negative predictive value of TIC were 81.0%, 94.4%, 96.9%, 83.2% and 96.5%, respectively. OSNA was significantly superior to FS (85.4% vs. 68.6%, P = 0.0021), and had no statistical difference compared with TIC (85.4% vs. 81.0%, P = 0.82). (3) OSNA and FS, TIC were more sensitive to macrometastasis and microrotation. The sensitivity of OSNA was 93.1%, FS 88.5%, TIC 92.2%, OSNA was similar to FS and TIC (P = 0.1907, P = 0.8543), and there was no significant difference between them. Sensitivity was 40.4%. Sensitivity of TIC was 44.0%. OSNA was significantly superior to FS and TIC (P = 0.0121, P = 0.0139). Intraoperative rapid prediction model of NSLN metastasis risk (1) Establishment of a molecular diagnosis-based contour map model for predicting NSLN metastasis in 103 patients in the modeling group by univariate analysis found that primary tumor size (P = 0.001), vascular vessels. Infiltration (P = 0.007), total Tumor Load (TTL) (P = 0.000), maximum metastasis size (P = 0.000), SLN positive (P = 0.000), SLN negative (P = 0.000), and SLN positive / SLN total (P = 0.000) were all associated with NSLN metastasis. Negative number (P = 0.001) was an independent risk factor for NSLN metastasis. TTL, primary tumor size, SLN positive number and SLN negative number were used to establish a contour map model for predicting NSLN metastasis in breast cancer. Predictive validation of the model This study used 61 patients in the validation group to validate the predictive model. AUC was 0.842. (3) Comparison of predictive differences between the size of the tumor and the size of the primary tumor in the imaging evaluation. This study used validation group imaging (ultrasound, mammography, MRI) to assess tumor size. The AUC of the model was 0.838, which was not significantly different from the area under the validated ROC curve (P = 0.7406). (4) The model predicted axillary lymph node staging in patients with pN1 and < pN2. The model distinguished between pN1 and < pN2 axillary lymph nodes. The predictive risk threshold for staging was 45.4%, AUC was 0.861, P 0.0001. In addition, the predictive risk threshold for pN1 and < P N2 was 33.5%, AUC was 0.839, P 0.0001. (5) The validity of this model with other predictive models was verified. Compared with the model of Anderson Cancer Center (MDA) in USA and Tenon Hospital in France, the AUC was 0.745 and 0.623 respectively. In addition, the model was validated by Isabel in Spain and the AUC was 0.834. Conclusion: OSNA, as an objective standardized technique, can diagnose SLN quickly and accurately during operation, and the operation is simple, which greatly reduces the subjectivity and workload of pathologists, and can be used as the first diagnosis of SLN during operation and even after operation. The model based on OSNA intraoperative molecular diagnosis is superior to other predictive models in predicting NSLN metastasis. It has better guiding value for the follow-up axillary treatment, radiotherapy target delineation and systemic treatment.
【學(xué)位授予單位】：濟(jì)南大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：R737.9
本文編號(hào)：2202691
[Abstract]:Objective: To evaluate the diagnostic value of one-step Nucleic Acid Amplification (OSNA), a molecular diagnostic technique for sentinel lymph node (SLN) metastasis in breast cancer, and to analyze its predictive ability for non-Sentinel Lymph Node (NSLN) metastasis according to the results of OSNA detection. Methods: This study included 552 patients enrolled in the 2010 OSNA clinical trial and 348 prospective patients enrolled in the center of this trial. A total of 900 patients were enrolled in the study and 870 effective patients were enrolled in the study. If the length of SLN is less than 4 mm, it is divided into a and B tissue blocks. When the length of the short axis is less than 4 mm, OSNA detection is performed in a tissue block, and pathological examination is performed in B tissue block. When the length of the short axis is 4 mm, it is divided into a, B and B tissue blocks. The intraoperative Touch Imprint Cytology (TIC) was performed in all the tissues of a, b, C and D. On the one hand, the results of OSNA were compared with the pathology of successive slices after operation, on the other hand, the risk of NSLN metastasis was established according to the results of OSNA. Results: 1. The diagnostic value of OSNA (1) was analyzed by case number and pathology after operation as golden standard. The sensitivity, accuracy, specificity, positive predictive value and negative predictive value of OSNA were 88.7%, 89.0%, 89.1%, 72.3%, 96.1% respectively. Specificity, positive predictive value, negative predictive value were 77.9%, 94.0%, 100.0%, 100.0%, and 92.3%, respectively. Sensitivity, accuracy, specificity, positive predictive value and negative predictive value of TIC were 83.0%, 93.5%, 96.8%, 89.3%, 94.7% respectively. OSNA was significantly more sensitive than FS (88.7% vs. 77.9%, P = 0.0095), and had no statistical difference compared with TIC (88.7% vs. 83.0%, P = 0.1254). (2) The sensitivity, accuracy, specificity, positive predictive value and negative predictive value of OSNA were 85.4%, 91.4%, 92.6%, 68.4%, 97.1% respectively. The sensitivity, accuracy, specificity, positive predictive value and negative predictive value of FS were 85.4%, 91.4%, 92.6%, 68.4% and 97.1% respectively. The sensitivity, accuracy, specificity, positive predictive value and negative predictive value of TIC were 81.0%, 94.4%, 96.9%, 83.2% and 96.5%, respectively. OSNA was significantly superior to FS (85.4% vs. 68.6%, P = 0.0021), and had no statistical difference compared with TIC (85.4% vs. 81.0%, P = 0.82). (3) OSNA and FS, TIC were more sensitive to macrometastasis and microrotation. The sensitivity of OSNA was 93.1%, FS 88.5%, TIC 92.2%, OSNA was similar to FS and TIC (P = 0.1907, P = 0.8543), and there was no significant difference between them. Sensitivity was 40.4%. Sensitivity of TIC was 44.0%. OSNA was significantly superior to FS and TIC (P = 0.0121, P = 0.0139). Intraoperative rapid prediction model of NSLN metastasis risk (1) Establishment of a molecular diagnosis-based contour map model for predicting NSLN metastasis in 103 patients in the modeling group by univariate analysis found that primary tumor size (P = 0.001), vascular vessels. Infiltration (P = 0.007), total Tumor Load (TTL) (P = 0.000), maximum metastasis size (P = 0.000), SLN positive (P = 0.000), SLN negative (P = 0.000), and SLN positive / SLN total (P = 0.000) were all associated with NSLN metastasis. Negative number (P = 0.001) was an independent risk factor for NSLN metastasis. TTL, primary tumor size, SLN positive number and SLN negative number were used to establish a contour map model for predicting NSLN metastasis in breast cancer. Predictive validation of the model This study used 61 patients in the validation group to validate the predictive model. AUC was 0.842. (3) Comparison of predictive differences between the size of the tumor and the size of the primary tumor in the imaging evaluation. This study used validation group imaging (ultrasound, mammography, MRI) to assess tumor size. The AUC of the model was 0.838, which was not significantly different from the area under the validated ROC curve (P = 0.7406). (4) The model predicted axillary lymph node staging in patients with pN1 and < pN2. The model distinguished between pN1 and < pN2 axillary lymph nodes. The predictive risk threshold for staging was 45.4%, AUC was 0.861, P 0.0001. In addition, the predictive risk threshold for pN1 and < P N2 was 33.5%, AUC was 0.839, P 0.0001. (5) The validity of this model with other predictive models was verified. Compared with the model of Anderson Cancer Center (MDA) in USA and Tenon Hospital in France, the AUC was 0.745 and 0.623 respectively. In addition, the model was validated by Isabel in Spain and the AUC was 0.834. Conclusion: OSNA, as an objective standardized technique, can diagnose SLN quickly and accurately during operation, and the operation is simple, which greatly reduces the subjectivity and workload of pathologists, and can be used as the first diagnosis of SLN during operation and even after operation. The model based on OSNA intraoperative molecular diagnosis is superior to other predictive models in predicting NSLN metastasis. It has better guiding value for the follow-up axillary treatment, radiotherapy target delineation and systemic treatment.
【學(xué)位授予單位】：濟(jì)南大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：R737.9
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