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P-133CLINICAL PREDICTOR OF PRE- OR MINIMALLY-INVASIVE PULMONARY ADENOCARCINOMA: A PROPOSAL FOR SUB-CLASSIFICATION OF CLINICAL T1a

Objectives The pathological classification of pulmonary adenocarcinoma will be changed according to the amount of invasion, which relates to the prognosis. As such, it is crucial to distinguish the group of patients with extremely good survival before surgery. Methods Among 412 surgical patients of...

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Published in:Interactive cardiovascular and thoracic surgery 2013-07, Vol.17 (suppl_1), p.S35-S36
Main Authors: Sawabata, Noriyoshi, Sakamoto, T., Kusumoto, H., Kimura, T., Kanzaki, R., Mojiri, T., Kawamura, T., Susaki, Y., Funaki, S., Nakagiri, T., Shintani, Y., Inoue, M., Minami, M., Okumura, M.
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container_issue suppl_1
container_start_page S35
container_title Interactive cardiovascular and thoracic surgery
container_volume 17
creator Sawabata, Noriyoshi
Sakamoto, T.
Kusumoto, H.
Kimura, T.
Kanzaki, R.
Mojiri, T.
Kawamura, T.
Susaki, Y.
Funaki, S.
Nakagiri, T.
Shintani, Y.
Inoue, M.
Minami, M.
Okumura, M.
description Objectives The pathological classification of pulmonary adenocarcinoma will be changed according to the amount of invasion, which relates to the prognosis. As such, it is crucial to distinguish the group of patients with extremely good survival before surgery. Methods Among 412 surgical patients of lung cancer from 2008 to 2011, 110 clinical stage I patients underwent segmentectomy or lobectomy and revealing all 4 parameters: 1) whole size of the tumour in computed tomography (WS); 2) size of solid component in computed tomography (SS); 3) SUVmax and 4) serum level of carcinoembrionic antigen (CEA), were assessed on the points of predictive power for pre or minimally-invasive adenocarcinoma and relapse free survival (RFS). Results With respect to prediction of pre or minimally-invasive adenocarcinoma, the area under the curve (AUC) of the receiver-operation curve (ROC) was over 0.7 in all 4 parameters and only SS was independent in multivariate logistic regression analysis. In Cox proportional hazard model analysis, SS and SUVmax were statistically significant and SS was exclusively independent in a multivariate analysis. The RFS was more distinguishable using SS than WS between T1a and T1b, and in sub-classification of T1a using a break point of 1.0 cm in SS (T1a-{alpha} and T1a-{beta}), the 2-year RFS rate was 100% in T1a-{alpha} (n = 21), 89.4% in T1a-{beta} (n = 27) and 68.3% in T1b (n = 26), respectively (P = 0.002 between T1a-{beta} and T1b). Conclusions SS could distinguish pre- or minimally-invasive adenocarcinoma from other types of lung cancer and may provide sub-classification of T1a. Disclosure All authors have declared no conflicts of interest.
doi_str_mv 10.1093/icvts/ivt288.133
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As such, it is crucial to distinguish the group of patients with extremely good survival before surgery. Methods Among 412 surgical patients of lung cancer from 2008 to 2011, 110 clinical stage I patients underwent segmentectomy or lobectomy and revealing all 4 parameters: 1) whole size of the tumour in computed tomography (WS); 2) size of solid component in computed tomography (SS); 3) SUVmax and 4) serum level of carcinoembrionic antigen (CEA), were assessed on the points of predictive power for pre or minimally-invasive adenocarcinoma and relapse free survival (RFS). Results With respect to prediction of pre or minimally-invasive adenocarcinoma, the area under the curve (AUC) of the receiver-operation curve (ROC) was over 0.7 in all 4 parameters and only SS was independent in multivariate logistic regression analysis. In Cox proportional hazard model analysis, SS and SUVmax were statistically significant and SS was exclusively independent in a multivariate analysis. The RFS was more distinguishable using SS than WS between T1a and T1b, and in sub-classification of T1a using a break point of 1.0 cm in SS (T1a-{alpha} and T1a-{beta}), the 2-year RFS rate was 100% in T1a-{alpha} (n = 21), 89.4% in T1a-{beta} (n = 27) and 68.3% in T1b (n = 26), respectively (P = 0.002 between T1a-{beta} and T1b). Conclusions SS could distinguish pre- or minimally-invasive adenocarcinoma from other types of lung cancer and may provide sub-classification of T1a. Disclosure All authors have declared no conflicts of interest.</description><identifier>ISSN: 1569-9293</identifier><identifier>EISSN: 1569-9285</identifier><identifier>DOI: 10.1093/icvts/ivt288.133</identifier><language>eng</language><publisher>Oxford University Press</publisher><ispartof>Interactive cardiovascular and thoracic surgery, 2013-07, Vol.17 (suppl_1), p.S35-S36</ispartof><rights>The Author 2013. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. 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As such, it is crucial to distinguish the group of patients with extremely good survival before surgery. Methods Among 412 surgical patients of lung cancer from 2008 to 2011, 110 clinical stage I patients underwent segmentectomy or lobectomy and revealing all 4 parameters: 1) whole size of the tumour in computed tomography (WS); 2) size of solid component in computed tomography (SS); 3) SUVmax and 4) serum level of carcinoembrionic antigen (CEA), were assessed on the points of predictive power for pre or minimally-invasive adenocarcinoma and relapse free survival (RFS). Results With respect to prediction of pre or minimally-invasive adenocarcinoma, the area under the curve (AUC) of the receiver-operation curve (ROC) was over 0.7 in all 4 parameters and only SS was independent in multivariate logistic regression analysis. In Cox proportional hazard model analysis, SS and SUVmax were statistically significant and SS was exclusively independent in a multivariate analysis. The RFS was more distinguishable using SS than WS between T1a and T1b, and in sub-classification of T1a using a break point of 1.0 cm in SS (T1a-{alpha} and T1a-{beta}), the 2-year RFS rate was 100% in T1a-{alpha} (n = 21), 89.4% in T1a-{beta} (n = 27) and 68.3% in T1b (n = 26), respectively (P = 0.002 between T1a-{beta} and T1b). Conclusions SS could distinguish pre- or minimally-invasive adenocarcinoma from other types of lung cancer and may provide sub-classification of T1a. 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The RFS was more distinguishable using SS than WS between T1a and T1b, and in sub-classification of T1a using a break point of 1.0 cm in SS (T1a-{alpha} and T1a-{beta}), the 2-year RFS rate was 100% in T1a-{alpha} (n = 21), 89.4% in T1a-{beta} (n = 27) and 68.3% in T1b (n = 26), respectively (P = 0.002 between T1a-{beta} and T1b). Conclusions SS could distinguish pre- or minimally-invasive adenocarcinoma from other types of lung cancer and may provide sub-classification of T1a. Disclosure All authors have declared no conflicts of interest.</abstract><pub>Oxford University Press</pub><doi>10.1093/icvts/ivt288.133</doi><oa>free_for_read</oa></addata></record>
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