The Prognostic Impact of Pericardial Fat Volumes in Resected Non-small Cell Lung Cancer
Background Pericardial fat (PF) has not been considered a prognostic biomarker for overall survival (OS) in lung cancer. This study was designed to elucidate the impact of PF on prognosis of resected non-small cell lung cancer patients. Methods We retrospectively reviewed a total of 349 patients who...
Ausführliche Beschreibung
Autor*in: |
Shinohara, Shuichi [verfasserIn] Otsuki, Ryo [verfasserIn] Kobayashi, Kenichi [verfasserIn] Matsuo, Masaki [verfasserIn] Harada, Ken [verfasserIn] Sugaya, Masakazu [verfasserIn] Nakagawa, Makoto [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2019 |
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Übergeordnetes Werk: |
Enthalten in: Annals of surgical oncology - Berlin [u.a.] : Springer, 1994, 27(2019), 2 vom: 12. Aug., Seite 481-489 |
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Übergeordnetes Werk: |
volume:27 ; year:2019 ; number:2 ; day:12 ; month:08 ; pages:481-489 |
Links: |
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DOI / URN: |
10.1245/s10434-019-07703-2 |
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Katalog-ID: |
SPR010009531 |
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245 | 1 | 4 | |a The Prognostic Impact of Pericardial Fat Volumes in Resected Non-small Cell Lung Cancer |
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520 | |a Background Pericardial fat (PF) has not been considered a prognostic biomarker for overall survival (OS) in lung cancer. This study was designed to elucidate the impact of PF on prognosis of resected non-small cell lung cancer patients. Methods We retrospectively reviewed a total of 349 patients who underwent lung resection and received high-resolution computed tomography in our institute. PF volume was calculated. PF extended vertically from the diaphragm to the bifurcation of the right main pulmonary artery. Propensity score matched analysis was used to compare OS between the high- and low-PF groups. Results PF volume increased according to body mass index (p < 0.001). Receiver operating characteristics (ROC) curve analysis for 3-year OS showed the possibility of better predictivity of PF than body-mass index (area under the curve, 0.66 vs. 0.61, p = 0.010). Cutoff level of PF volume was determined based on the ROC with 122 $ cm^{3} $. Five-year OS was poorer in the low-PF group (63.5% vs. 73.4%; p = 0.002). After propensity score matching, each group consisted of 89 cases. Five-year OS was poorer in the low-PF group (66.5% vs. 82.7%; p = 0.008). A Cox proportional hazards model showed low-PF volume was associated with poorer OS (hazard ratio, 2.14; p = 0.009). The number of respiratory-related deaths was higher in the low-PF group (10/89 vs. 2/89, p = 0.032). Conclusions Low-PF volume may be associated with poor OS with an increase in the number of respiratory-related deaths. Patients with low-PF volume require careful follow-up after surgery. | ||
700 | 1 | |a Otsuki, Ryo |e verfasserin |4 aut | |
700 | 1 | |a Kobayashi, Kenichi |e verfasserin |4 aut | |
700 | 1 | |a Matsuo, Masaki |e verfasserin |4 aut | |
700 | 1 | |a Harada, Ken |e verfasserin |4 aut | |
700 | 1 | |a Sugaya, Masakazu |e verfasserin |4 aut | |
700 | 1 | |a Nakagawa, Makoto |e verfasserin |4 aut | |
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10.1245/s10434-019-07703-2 doi (DE-627)SPR010009531 (SPR)s10434-019-07703-2-e DE-627 ger DE-627 rakwb eng 610 ASE 44.81 bkl 44.65 bkl Shinohara, Shuichi verfasserin aut The Prognostic Impact of Pericardial Fat Volumes in Resected Non-small Cell Lung Cancer 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background Pericardial fat (PF) has not been considered a prognostic biomarker for overall survival (OS) in lung cancer. This study was designed to elucidate the impact of PF on prognosis of resected non-small cell lung cancer patients. Methods We retrospectively reviewed a total of 349 patients who underwent lung resection and received high-resolution computed tomography in our institute. PF volume was calculated. PF extended vertically from the diaphragm to the bifurcation of the right main pulmonary artery. Propensity score matched analysis was used to compare OS between the high- and low-PF groups. Results PF volume increased according to body mass index (p < 0.001). Receiver operating characteristics (ROC) curve analysis for 3-year OS showed the possibility of better predictivity of PF than body-mass index (area under the curve, 0.66 vs. 0.61, p = 0.010). Cutoff level of PF volume was determined based on the ROC with 122 $ cm^{3} $. Five-year OS was poorer in the low-PF group (63.5% vs. 73.4%; p = 0.002). After propensity score matching, each group consisted of 89 cases. Five-year OS was poorer in the low-PF group (66.5% vs. 82.7%; p = 0.008). A Cox proportional hazards model showed low-PF volume was associated with poorer OS (hazard ratio, 2.14; p = 0.009). The number of respiratory-related deaths was higher in the low-PF group (10/89 vs. 2/89, p = 0.032). Conclusions Low-PF volume may be associated with poor OS with an increase in the number of respiratory-related deaths. Patients with low-PF volume require careful follow-up after surgery. Otsuki, Ryo verfasserin aut Kobayashi, Kenichi verfasserin aut Matsuo, Masaki verfasserin aut Harada, Ken verfasserin aut Sugaya, Masakazu verfasserin aut Nakagawa, Makoto verfasserin aut Enthalten in Annals of surgical oncology Berlin [u.a.] : Springer, 1994 27(2019), 2 vom: 12. Aug., Seite 481-489 (DE-627)343969947 (DE-600)2074021-9 1534-4681 nnns volume:27 year:2019 number:2 day:12 month:08 pages:481-489 https://dx.doi.org/10.1245/s10434-019-07703-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.81 ASE 44.65 ASE AR 27 2019 2 12 08 481-489 |
spelling |
10.1245/s10434-019-07703-2 doi (DE-627)SPR010009531 (SPR)s10434-019-07703-2-e DE-627 ger DE-627 rakwb eng 610 ASE 44.81 bkl 44.65 bkl Shinohara, Shuichi verfasserin aut The Prognostic Impact of Pericardial Fat Volumes in Resected Non-small Cell Lung Cancer 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background Pericardial fat (PF) has not been considered a prognostic biomarker for overall survival (OS) in lung cancer. This study was designed to elucidate the impact of PF on prognosis of resected non-small cell lung cancer patients. Methods We retrospectively reviewed a total of 349 patients who underwent lung resection and received high-resolution computed tomography in our institute. PF volume was calculated. PF extended vertically from the diaphragm to the bifurcation of the right main pulmonary artery. Propensity score matched analysis was used to compare OS between the high- and low-PF groups. Results PF volume increased according to body mass index (p < 0.001). Receiver operating characteristics (ROC) curve analysis for 3-year OS showed the possibility of better predictivity of PF than body-mass index (area under the curve, 0.66 vs. 0.61, p = 0.010). Cutoff level of PF volume was determined based on the ROC with 122 $ cm^{3} $. Five-year OS was poorer in the low-PF group (63.5% vs. 73.4%; p = 0.002). After propensity score matching, each group consisted of 89 cases. Five-year OS was poorer in the low-PF group (66.5% vs. 82.7%; p = 0.008). A Cox proportional hazards model showed low-PF volume was associated with poorer OS (hazard ratio, 2.14; p = 0.009). The number of respiratory-related deaths was higher in the low-PF group (10/89 vs. 2/89, p = 0.032). Conclusions Low-PF volume may be associated with poor OS with an increase in the number of respiratory-related deaths. Patients with low-PF volume require careful follow-up after surgery. Otsuki, Ryo verfasserin aut Kobayashi, Kenichi verfasserin aut Matsuo, Masaki verfasserin aut Harada, Ken verfasserin aut Sugaya, Masakazu verfasserin aut Nakagawa, Makoto verfasserin aut Enthalten in Annals of surgical oncology Berlin [u.a.] : Springer, 1994 27(2019), 2 vom: 12. Aug., Seite 481-489 (DE-627)343969947 (DE-600)2074021-9 1534-4681 nnns volume:27 year:2019 number:2 day:12 month:08 pages:481-489 https://dx.doi.org/10.1245/s10434-019-07703-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.81 ASE 44.65 ASE AR 27 2019 2 12 08 481-489 |
allfields_unstemmed |
10.1245/s10434-019-07703-2 doi (DE-627)SPR010009531 (SPR)s10434-019-07703-2-e DE-627 ger DE-627 rakwb eng 610 ASE 44.81 bkl 44.65 bkl Shinohara, Shuichi verfasserin aut The Prognostic Impact of Pericardial Fat Volumes in Resected Non-small Cell Lung Cancer 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background Pericardial fat (PF) has not been considered a prognostic biomarker for overall survival (OS) in lung cancer. This study was designed to elucidate the impact of PF on prognosis of resected non-small cell lung cancer patients. Methods We retrospectively reviewed a total of 349 patients who underwent lung resection and received high-resolution computed tomography in our institute. PF volume was calculated. PF extended vertically from the diaphragm to the bifurcation of the right main pulmonary artery. Propensity score matched analysis was used to compare OS between the high- and low-PF groups. Results PF volume increased according to body mass index (p < 0.001). Receiver operating characteristics (ROC) curve analysis for 3-year OS showed the possibility of better predictivity of PF than body-mass index (area under the curve, 0.66 vs. 0.61, p = 0.010). Cutoff level of PF volume was determined based on the ROC with 122 $ cm^{3} $. Five-year OS was poorer in the low-PF group (63.5% vs. 73.4%; p = 0.002). After propensity score matching, each group consisted of 89 cases. Five-year OS was poorer in the low-PF group (66.5% vs. 82.7%; p = 0.008). A Cox proportional hazards model showed low-PF volume was associated with poorer OS (hazard ratio, 2.14; p = 0.009). The number of respiratory-related deaths was higher in the low-PF group (10/89 vs. 2/89, p = 0.032). Conclusions Low-PF volume may be associated with poor OS with an increase in the number of respiratory-related deaths. Patients with low-PF volume require careful follow-up after surgery. Otsuki, Ryo verfasserin aut Kobayashi, Kenichi verfasserin aut Matsuo, Masaki verfasserin aut Harada, Ken verfasserin aut Sugaya, Masakazu verfasserin aut Nakagawa, Makoto verfasserin aut Enthalten in Annals of surgical oncology Berlin [u.a.] : Springer, 1994 27(2019), 2 vom: 12. Aug., Seite 481-489 (DE-627)343969947 (DE-600)2074021-9 1534-4681 nnns volume:27 year:2019 number:2 day:12 month:08 pages:481-489 https://dx.doi.org/10.1245/s10434-019-07703-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.81 ASE 44.65 ASE AR 27 2019 2 12 08 481-489 |
allfieldsGer |
10.1245/s10434-019-07703-2 doi (DE-627)SPR010009531 (SPR)s10434-019-07703-2-e DE-627 ger DE-627 rakwb eng 610 ASE 44.81 bkl 44.65 bkl Shinohara, Shuichi verfasserin aut The Prognostic Impact of Pericardial Fat Volumes in Resected Non-small Cell Lung Cancer 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background Pericardial fat (PF) has not been considered a prognostic biomarker for overall survival (OS) in lung cancer. This study was designed to elucidate the impact of PF on prognosis of resected non-small cell lung cancer patients. Methods We retrospectively reviewed a total of 349 patients who underwent lung resection and received high-resolution computed tomography in our institute. PF volume was calculated. PF extended vertically from the diaphragm to the bifurcation of the right main pulmonary artery. Propensity score matched analysis was used to compare OS between the high- and low-PF groups. Results PF volume increased according to body mass index (p < 0.001). Receiver operating characteristics (ROC) curve analysis for 3-year OS showed the possibility of better predictivity of PF than body-mass index (area under the curve, 0.66 vs. 0.61, p = 0.010). Cutoff level of PF volume was determined based on the ROC with 122 $ cm^{3} $. Five-year OS was poorer in the low-PF group (63.5% vs. 73.4%; p = 0.002). After propensity score matching, each group consisted of 89 cases. Five-year OS was poorer in the low-PF group (66.5% vs. 82.7%; p = 0.008). A Cox proportional hazards model showed low-PF volume was associated with poorer OS (hazard ratio, 2.14; p = 0.009). The number of respiratory-related deaths was higher in the low-PF group (10/89 vs. 2/89, p = 0.032). Conclusions Low-PF volume may be associated with poor OS with an increase in the number of respiratory-related deaths. Patients with low-PF volume require careful follow-up after surgery. Otsuki, Ryo verfasserin aut Kobayashi, Kenichi verfasserin aut Matsuo, Masaki verfasserin aut Harada, Ken verfasserin aut Sugaya, Masakazu verfasserin aut Nakagawa, Makoto verfasserin aut Enthalten in Annals of surgical oncology Berlin [u.a.] : Springer, 1994 27(2019), 2 vom: 12. Aug., Seite 481-489 (DE-627)343969947 (DE-600)2074021-9 1534-4681 nnns volume:27 year:2019 number:2 day:12 month:08 pages:481-489 https://dx.doi.org/10.1245/s10434-019-07703-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.81 ASE 44.65 ASE AR 27 2019 2 12 08 481-489 |
allfieldsSound |
10.1245/s10434-019-07703-2 doi (DE-627)SPR010009531 (SPR)s10434-019-07703-2-e DE-627 ger DE-627 rakwb eng 610 ASE 44.81 bkl 44.65 bkl Shinohara, Shuichi verfasserin aut The Prognostic Impact of Pericardial Fat Volumes in Resected Non-small Cell Lung Cancer 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background Pericardial fat (PF) has not been considered a prognostic biomarker for overall survival (OS) in lung cancer. This study was designed to elucidate the impact of PF on prognosis of resected non-small cell lung cancer patients. Methods We retrospectively reviewed a total of 349 patients who underwent lung resection and received high-resolution computed tomography in our institute. PF volume was calculated. PF extended vertically from the diaphragm to the bifurcation of the right main pulmonary artery. Propensity score matched analysis was used to compare OS between the high- and low-PF groups. Results PF volume increased according to body mass index (p < 0.001). Receiver operating characteristics (ROC) curve analysis for 3-year OS showed the possibility of better predictivity of PF than body-mass index (area under the curve, 0.66 vs. 0.61, p = 0.010). Cutoff level of PF volume was determined based on the ROC with 122 $ cm^{3} $. Five-year OS was poorer in the low-PF group (63.5% vs. 73.4%; p = 0.002). After propensity score matching, each group consisted of 89 cases. Five-year OS was poorer in the low-PF group (66.5% vs. 82.7%; p = 0.008). A Cox proportional hazards model showed low-PF volume was associated with poorer OS (hazard ratio, 2.14; p = 0.009). The number of respiratory-related deaths was higher in the low-PF group (10/89 vs. 2/89, p = 0.032). Conclusions Low-PF volume may be associated with poor OS with an increase in the number of respiratory-related deaths. Patients with low-PF volume require careful follow-up after surgery. Otsuki, Ryo verfasserin aut Kobayashi, Kenichi verfasserin aut Matsuo, Masaki verfasserin aut Harada, Ken verfasserin aut Sugaya, Masakazu verfasserin aut Nakagawa, Makoto verfasserin aut Enthalten in Annals of surgical oncology Berlin [u.a.] : Springer, 1994 27(2019), 2 vom: 12. Aug., Seite 481-489 (DE-627)343969947 (DE-600)2074021-9 1534-4681 nnns volume:27 year:2019 number:2 day:12 month:08 pages:481-489 https://dx.doi.org/10.1245/s10434-019-07703-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.81 ASE 44.65 ASE AR 27 2019 2 12 08 481-489 |
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Shinohara, Shuichi @@aut@@ Otsuki, Ryo @@aut@@ Kobayashi, Kenichi @@aut@@ Matsuo, Masaki @@aut@@ Harada, Ken @@aut@@ Sugaya, Masakazu @@aut@@ Nakagawa, Makoto @@aut@@ |
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This study was designed to elucidate the impact of PF on prognosis of resected non-small cell lung cancer patients. Methods We retrospectively reviewed a total of 349 patients who underwent lung resection and received high-resolution computed tomography in our institute. PF volume was calculated. PF extended vertically from the diaphragm to the bifurcation of the right main pulmonary artery. Propensity score matched analysis was used to compare OS between the high- and low-PF groups. Results PF volume increased according to body mass index (p < 0.001). Receiver operating characteristics (ROC) curve analysis for 3-year OS showed the possibility of better predictivity of PF than body-mass index (area under the curve, 0.66 vs. 0.61, p = 0.010). Cutoff level of PF volume was determined based on the ROC with 122 $ cm^{3} $. Five-year OS was poorer in the low-PF group (63.5% vs. 73.4%; p = 0.002). After propensity score matching, each group consisted of 89 cases. Five-year OS was poorer in the low-PF group (66.5% vs. 82.7%; p = 0.008). A Cox proportional hazards model showed low-PF volume was associated with poorer OS (hazard ratio, 2.14; p = 0.009). The number of respiratory-related deaths was higher in the low-PF group (10/89 vs. 2/89, p = 0.032). Conclusions Low-PF volume may be associated with poor OS with an increase in the number of respiratory-related deaths. Patients with low-PF volume require careful follow-up after surgery.</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Otsuki, Ryo</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Kobayashi, Kenichi</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Matsuo, Masaki</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Harada, Ken</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Sugaya, Masakazu</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Nakagawa, Makoto</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Annals of surgical oncology</subfield><subfield code="d">Berlin [u.a.] : Springer, 1994</subfield><subfield code="g">27(2019), 2 vom: 12. 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Shinohara, Shuichi |
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Shinohara, Shuichi ddc 610 bkl 44.81 bkl 44.65 The Prognostic Impact of Pericardial Fat Volumes in Resected Non-small Cell Lung Cancer |
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610 ASE 44.81 bkl 44.65 bkl The Prognostic Impact of Pericardial Fat Volumes in Resected Non-small Cell Lung Cancer |
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The Prognostic Impact of Pericardial Fat Volumes in Resected Non-small Cell Lung Cancer |
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The Prognostic Impact of Pericardial Fat Volumes in Resected Non-small Cell Lung Cancer |
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Shinohara, Shuichi Otsuki, Ryo Kobayashi, Kenichi Matsuo, Masaki Harada, Ken Sugaya, Masakazu Nakagawa, Makoto |
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prognostic impact of pericardial fat volumes in resected non-small cell lung cancer |
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The Prognostic Impact of Pericardial Fat Volumes in Resected Non-small Cell Lung Cancer |
abstract |
Background Pericardial fat (PF) has not been considered a prognostic biomarker for overall survival (OS) in lung cancer. This study was designed to elucidate the impact of PF on prognosis of resected non-small cell lung cancer patients. Methods We retrospectively reviewed a total of 349 patients who underwent lung resection and received high-resolution computed tomography in our institute. PF volume was calculated. PF extended vertically from the diaphragm to the bifurcation of the right main pulmonary artery. Propensity score matched analysis was used to compare OS between the high- and low-PF groups. Results PF volume increased according to body mass index (p < 0.001). Receiver operating characteristics (ROC) curve analysis for 3-year OS showed the possibility of better predictivity of PF than body-mass index (area under the curve, 0.66 vs. 0.61, p = 0.010). Cutoff level of PF volume was determined based on the ROC with 122 $ cm^{3} $. Five-year OS was poorer in the low-PF group (63.5% vs. 73.4%; p = 0.002). After propensity score matching, each group consisted of 89 cases. Five-year OS was poorer in the low-PF group (66.5% vs. 82.7%; p = 0.008). A Cox proportional hazards model showed low-PF volume was associated with poorer OS (hazard ratio, 2.14; p = 0.009). The number of respiratory-related deaths was higher in the low-PF group (10/89 vs. 2/89, p = 0.032). Conclusions Low-PF volume may be associated with poor OS with an increase in the number of respiratory-related deaths. Patients with low-PF volume require careful follow-up after surgery. |
abstractGer |
Background Pericardial fat (PF) has not been considered a prognostic biomarker for overall survival (OS) in lung cancer. This study was designed to elucidate the impact of PF on prognosis of resected non-small cell lung cancer patients. Methods We retrospectively reviewed a total of 349 patients who underwent lung resection and received high-resolution computed tomography in our institute. PF volume was calculated. PF extended vertically from the diaphragm to the bifurcation of the right main pulmonary artery. Propensity score matched analysis was used to compare OS between the high- and low-PF groups. Results PF volume increased according to body mass index (p < 0.001). Receiver operating characteristics (ROC) curve analysis for 3-year OS showed the possibility of better predictivity of PF than body-mass index (area under the curve, 0.66 vs. 0.61, p = 0.010). Cutoff level of PF volume was determined based on the ROC with 122 $ cm^{3} $. Five-year OS was poorer in the low-PF group (63.5% vs. 73.4%; p = 0.002). After propensity score matching, each group consisted of 89 cases. Five-year OS was poorer in the low-PF group (66.5% vs. 82.7%; p = 0.008). A Cox proportional hazards model showed low-PF volume was associated with poorer OS (hazard ratio, 2.14; p = 0.009). The number of respiratory-related deaths was higher in the low-PF group (10/89 vs. 2/89, p = 0.032). Conclusions Low-PF volume may be associated with poor OS with an increase in the number of respiratory-related deaths. Patients with low-PF volume require careful follow-up after surgery. |
abstract_unstemmed |
Background Pericardial fat (PF) has not been considered a prognostic biomarker for overall survival (OS) in lung cancer. This study was designed to elucidate the impact of PF on prognosis of resected non-small cell lung cancer patients. Methods We retrospectively reviewed a total of 349 patients who underwent lung resection and received high-resolution computed tomography in our institute. PF volume was calculated. PF extended vertically from the diaphragm to the bifurcation of the right main pulmonary artery. Propensity score matched analysis was used to compare OS between the high- and low-PF groups. Results PF volume increased according to body mass index (p < 0.001). Receiver operating characteristics (ROC) curve analysis for 3-year OS showed the possibility of better predictivity of PF than body-mass index (area under the curve, 0.66 vs. 0.61, p = 0.010). Cutoff level of PF volume was determined based on the ROC with 122 $ cm^{3} $. Five-year OS was poorer in the low-PF group (63.5% vs. 73.4%; p = 0.002). After propensity score matching, each group consisted of 89 cases. Five-year OS was poorer in the low-PF group (66.5% vs. 82.7%; p = 0.008). A Cox proportional hazards model showed low-PF volume was associated with poorer OS (hazard ratio, 2.14; p = 0.009). The number of respiratory-related deaths was higher in the low-PF group (10/89 vs. 2/89, p = 0.032). Conclusions Low-PF volume may be associated with poor OS with an increase in the number of respiratory-related deaths. Patients with low-PF volume require careful follow-up after surgery. |
collection_details |
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container_issue |
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title_short |
The Prognostic Impact of Pericardial Fat Volumes in Resected Non-small Cell Lung Cancer |
url |
https://dx.doi.org/10.1245/s10434-019-07703-2 |
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author2 |
Otsuki, Ryo Kobayashi, Kenichi Matsuo, Masaki Harada, Ken Sugaya, Masakazu Nakagawa, Makoto |
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Otsuki, Ryo Kobayashi, Kenichi Matsuo, Masaki Harada, Ken Sugaya, Masakazu Nakagawa, Makoto |
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doi_str |
10.1245/s10434-019-07703-2 |
up_date |
2024-07-03T13:24:00.090Z |
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score |
7.3992643 |