Delays to surgery and worse outcomes: The compounding effects of social determinants of health in non–small cell lung cancerCentral MessagePerspective
Objective: To quantify the compounding effects of social determinants of health on time to surgery (T2S) and clinical outcomes. Methods: The National Cancer Database was queried for treatment-naïve patients with cT1-4N0-1M0 non–small cell lung cancer undergoing (bi)lobectomy or pneumonectomy between...
Ausführliche Beschreibung
Autor*in: |
Arman Ashrafi, BA [verfasserIn] Li Ding, MD, MPH [verfasserIn] Scott M. Atay, MD [verfasserIn] Sean C. Wightman, MD [verfasserIn] Takashi Harano, MD [verfasserIn] Anthony W. Kim, MD [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2023 |
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Schlagwörter: |
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Übergeordnetes Werk: |
In: JTCVS Open - Elsevier, 2022, 15(2023), Seite 468-478 |
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Übergeordnetes Werk: |
volume:15 ; year:2023 ; pages:468-478 |
Links: |
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DOI / URN: |
10.1016/j.xjon.2023.05.015 |
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Katalog-ID: |
DOAJ090743016 |
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520 | |a Objective: To quantify the compounding effects of social determinants of health on time to surgery (T2S) and clinical outcomes. Methods: The National Cancer Database was queried for treatment-naïve patients with cT1-4N0-1M0 non–small cell lung cancer undergoing (bi)lobectomy or pneumonectomy between 2006 and 2016 with 1 to 180 days T2S, the number of days between diagnosis and surgery; surgical delays were defined as statistically significant increased T2S compared with a reference cohort. Social determinants of health factors prognostic for surgical delays were identified using multivariable regression. The 30-/90-day mortality and 5-year survival estimates were calculated using logistic and Cox regressions, respectively. Results: In total, 110,005 patients met inclusionary criteria. Multivariable analysis identified race, insurance, and facility type as factors with significant 3-way interaction: T2S of one depended on the others. Income and education also contributed to delays. Privately insured (private) non-Hispanic White patients at academic medical centers (AMCs) were the reference with T2S of 44.1 days. At AMCs, private Black patients had significant delays to surgery (54.7 days; P < .0001), as did Medicaid and uninsured Black patients (58.5 days; P < .0001, 59.4 days; P < .0001, respectively). The 15-day surgical delays were associated with statistically significant 5% increased 30-day mortality odds (confidence interval [CI], 1.03-1.08), 6% increased 90-day mortality odds (CI, 1.04-1.08), and 4% decrease in hazard of death at 5 years (CI, 1.04-1.05). Conclusions: In treatment-naïve patients with cT1-4N0-1M0 non–small cell lung cancer, Black race, Medicaid, uninsured status, and AMCs generate compounding surgical delays with increased 30-/90-day mortality and decreased 5-year survival. Thoracic surgeons can leverage these facility and demographic-specific insights to standardize time to surgery and begin mitigating underlying disparities. | ||
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10.1016/j.xjon.2023.05.015 doi (DE-627)DOAJ090743016 (DE-599)DOAJ865336b3d01042548aac5d04c662d171 DE-627 ger DE-627 rakwb eng RC666-701 RD1-811 Arman Ashrafi, BA verfasserin aut Delays to surgery and worse outcomes: The compounding effects of social determinants of health in non–small cell lung cancerCentral MessagePerspective 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Objective: To quantify the compounding effects of social determinants of health on time to surgery (T2S) and clinical outcomes. Methods: The National Cancer Database was queried for treatment-naïve patients with cT1-4N0-1M0 non–small cell lung cancer undergoing (bi)lobectomy or pneumonectomy between 2006 and 2016 with 1 to 180 days T2S, the number of days between diagnosis and surgery; surgical delays were defined as statistically significant increased T2S compared with a reference cohort. Social determinants of health factors prognostic for surgical delays were identified using multivariable regression. The 30-/90-day mortality and 5-year survival estimates were calculated using logistic and Cox regressions, respectively. Results: In total, 110,005 patients met inclusionary criteria. Multivariable analysis identified race, insurance, and facility type as factors with significant 3-way interaction: T2S of one depended on the others. Income and education also contributed to delays. Privately insured (private) non-Hispanic White patients at academic medical centers (AMCs) were the reference with T2S of 44.1 days. At AMCs, private Black patients had significant delays to surgery (54.7 days; P < .0001), as did Medicaid and uninsured Black patients (58.5 days; P < .0001, 59.4 days; P < .0001, respectively). The 15-day surgical delays were associated with statistically significant 5% increased 30-day mortality odds (confidence interval [CI], 1.03-1.08), 6% increased 90-day mortality odds (CI, 1.04-1.08), and 4% decrease in hazard of death at 5 years (CI, 1.04-1.05). Conclusions: In treatment-naïve patients with cT1-4N0-1M0 non–small cell lung cancer, Black race, Medicaid, uninsured status, and AMCs generate compounding surgical delays with increased 30-/90-day mortality and decreased 5-year survival. Thoracic surgeons can leverage these facility and demographic-specific insights to standardize time to surgery and begin mitigating underlying disparities. thoracic surgery NSCLC social determinants of health time to surgery clinical outcomes disparities Diseases of the circulatory (Cardiovascular) system Surgery Li Ding, MD, MPH verfasserin aut Scott M. Atay, MD verfasserin aut Sean C. Wightman, MD verfasserin aut Takashi Harano, MD verfasserin aut Anthony W. Kim, MD verfasserin aut In JTCVS Open Elsevier, 2022 15(2023), Seite 468-478 (DE-627)1702642518 26662736 nnns volume:15 year:2023 pages:468-478 https://doi.org/10.1016/j.xjon.2023.05.015 kostenfrei https://doaj.org/article/865336b3d01042548aac5d04c662d171 kostenfrei http://www.sciencedirect.com/science/article/pii/S2666273623001663 kostenfrei https://doaj.org/toc/2666-2736 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 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_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 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_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 15 2023 468-478 |
spelling |
10.1016/j.xjon.2023.05.015 doi (DE-627)DOAJ090743016 (DE-599)DOAJ865336b3d01042548aac5d04c662d171 DE-627 ger DE-627 rakwb eng RC666-701 RD1-811 Arman Ashrafi, BA verfasserin aut Delays to surgery and worse outcomes: The compounding effects of social determinants of health in non–small cell lung cancerCentral MessagePerspective 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Objective: To quantify the compounding effects of social determinants of health on time to surgery (T2S) and clinical outcomes. Methods: The National Cancer Database was queried for treatment-naïve patients with cT1-4N0-1M0 non–small cell lung cancer undergoing (bi)lobectomy or pneumonectomy between 2006 and 2016 with 1 to 180 days T2S, the number of days between diagnosis and surgery; surgical delays were defined as statistically significant increased T2S compared with a reference cohort. Social determinants of health factors prognostic for surgical delays were identified using multivariable regression. The 30-/90-day mortality and 5-year survival estimates were calculated using logistic and Cox regressions, respectively. Results: In total, 110,005 patients met inclusionary criteria. Multivariable analysis identified race, insurance, and facility type as factors with significant 3-way interaction: T2S of one depended on the others. Income and education also contributed to delays. Privately insured (private) non-Hispanic White patients at academic medical centers (AMCs) were the reference with T2S of 44.1 days. At AMCs, private Black patients had significant delays to surgery (54.7 days; P < .0001), as did Medicaid and uninsured Black patients (58.5 days; P < .0001, 59.4 days; P < .0001, respectively). The 15-day surgical delays were associated with statistically significant 5% increased 30-day mortality odds (confidence interval [CI], 1.03-1.08), 6% increased 90-day mortality odds (CI, 1.04-1.08), and 4% decrease in hazard of death at 5 years (CI, 1.04-1.05). Conclusions: In treatment-naïve patients with cT1-4N0-1M0 non–small cell lung cancer, Black race, Medicaid, uninsured status, and AMCs generate compounding surgical delays with increased 30-/90-day mortality and decreased 5-year survival. Thoracic surgeons can leverage these facility and demographic-specific insights to standardize time to surgery and begin mitigating underlying disparities. thoracic surgery NSCLC social determinants of health time to surgery clinical outcomes disparities Diseases of the circulatory (Cardiovascular) system Surgery Li Ding, MD, MPH verfasserin aut Scott M. Atay, MD verfasserin aut Sean C. Wightman, MD verfasserin aut Takashi Harano, MD verfasserin aut Anthony W. Kim, MD verfasserin aut In JTCVS Open Elsevier, 2022 15(2023), Seite 468-478 (DE-627)1702642518 26662736 nnns volume:15 year:2023 pages:468-478 https://doi.org/10.1016/j.xjon.2023.05.015 kostenfrei https://doaj.org/article/865336b3d01042548aac5d04c662d171 kostenfrei http://www.sciencedirect.com/science/article/pii/S2666273623001663 kostenfrei https://doaj.org/toc/2666-2736 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 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_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 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_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 15 2023 468-478 |
allfields_unstemmed |
10.1016/j.xjon.2023.05.015 doi (DE-627)DOAJ090743016 (DE-599)DOAJ865336b3d01042548aac5d04c662d171 DE-627 ger DE-627 rakwb eng RC666-701 RD1-811 Arman Ashrafi, BA verfasserin aut Delays to surgery and worse outcomes: The compounding effects of social determinants of health in non–small cell lung cancerCentral MessagePerspective 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Objective: To quantify the compounding effects of social determinants of health on time to surgery (T2S) and clinical outcomes. Methods: The National Cancer Database was queried for treatment-naïve patients with cT1-4N0-1M0 non–small cell lung cancer undergoing (bi)lobectomy or pneumonectomy between 2006 and 2016 with 1 to 180 days T2S, the number of days between diagnosis and surgery; surgical delays were defined as statistically significant increased T2S compared with a reference cohort. Social determinants of health factors prognostic for surgical delays were identified using multivariable regression. The 30-/90-day mortality and 5-year survival estimates were calculated using logistic and Cox regressions, respectively. Results: In total, 110,005 patients met inclusionary criteria. Multivariable analysis identified race, insurance, and facility type as factors with significant 3-way interaction: T2S of one depended on the others. Income and education also contributed to delays. Privately insured (private) non-Hispanic White patients at academic medical centers (AMCs) were the reference with T2S of 44.1 days. At AMCs, private Black patients had significant delays to surgery (54.7 days; P < .0001), as did Medicaid and uninsured Black patients (58.5 days; P < .0001, 59.4 days; P < .0001, respectively). The 15-day surgical delays were associated with statistically significant 5% increased 30-day mortality odds (confidence interval [CI], 1.03-1.08), 6% increased 90-day mortality odds (CI, 1.04-1.08), and 4% decrease in hazard of death at 5 years (CI, 1.04-1.05). Conclusions: In treatment-naïve patients with cT1-4N0-1M0 non–small cell lung cancer, Black race, Medicaid, uninsured status, and AMCs generate compounding surgical delays with increased 30-/90-day mortality and decreased 5-year survival. Thoracic surgeons can leverage these facility and demographic-specific insights to standardize time to surgery and begin mitigating underlying disparities. thoracic surgery NSCLC social determinants of health time to surgery clinical outcomes disparities Diseases of the circulatory (Cardiovascular) system Surgery Li Ding, MD, MPH verfasserin aut Scott M. Atay, MD verfasserin aut Sean C. Wightman, MD verfasserin aut Takashi Harano, MD verfasserin aut Anthony W. Kim, MD verfasserin aut In JTCVS Open Elsevier, 2022 15(2023), Seite 468-478 (DE-627)1702642518 26662736 nnns volume:15 year:2023 pages:468-478 https://doi.org/10.1016/j.xjon.2023.05.015 kostenfrei https://doaj.org/article/865336b3d01042548aac5d04c662d171 kostenfrei http://www.sciencedirect.com/science/article/pii/S2666273623001663 kostenfrei https://doaj.org/toc/2666-2736 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 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_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 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_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 15 2023 468-478 |
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10.1016/j.xjon.2023.05.015 doi (DE-627)DOAJ090743016 (DE-599)DOAJ865336b3d01042548aac5d04c662d171 DE-627 ger DE-627 rakwb eng RC666-701 RD1-811 Arman Ashrafi, BA verfasserin aut Delays to surgery and worse outcomes: The compounding effects of social determinants of health in non–small cell lung cancerCentral MessagePerspective 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Objective: To quantify the compounding effects of social determinants of health on time to surgery (T2S) and clinical outcomes. Methods: The National Cancer Database was queried for treatment-naïve patients with cT1-4N0-1M0 non–small cell lung cancer undergoing (bi)lobectomy or pneumonectomy between 2006 and 2016 with 1 to 180 days T2S, the number of days between diagnosis and surgery; surgical delays were defined as statistically significant increased T2S compared with a reference cohort. Social determinants of health factors prognostic for surgical delays were identified using multivariable regression. The 30-/90-day mortality and 5-year survival estimates were calculated using logistic and Cox regressions, respectively. Results: In total, 110,005 patients met inclusionary criteria. Multivariable analysis identified race, insurance, and facility type as factors with significant 3-way interaction: T2S of one depended on the others. Income and education also contributed to delays. Privately insured (private) non-Hispanic White patients at academic medical centers (AMCs) were the reference with T2S of 44.1 days. At AMCs, private Black patients had significant delays to surgery (54.7 days; P < .0001), as did Medicaid and uninsured Black patients (58.5 days; P < .0001, 59.4 days; P < .0001, respectively). The 15-day surgical delays were associated with statistically significant 5% increased 30-day mortality odds (confidence interval [CI], 1.03-1.08), 6% increased 90-day mortality odds (CI, 1.04-1.08), and 4% decrease in hazard of death at 5 years (CI, 1.04-1.05). Conclusions: In treatment-naïve patients with cT1-4N0-1M0 non–small cell lung cancer, Black race, Medicaid, uninsured status, and AMCs generate compounding surgical delays with increased 30-/90-day mortality and decreased 5-year survival. Thoracic surgeons can leverage these facility and demographic-specific insights to standardize time to surgery and begin mitigating underlying disparities. thoracic surgery NSCLC social determinants of health time to surgery clinical outcomes disparities Diseases of the circulatory (Cardiovascular) system Surgery Li Ding, MD, MPH verfasserin aut Scott M. Atay, MD verfasserin aut Sean C. Wightman, MD verfasserin aut Takashi Harano, MD verfasserin aut Anthony W. Kim, MD verfasserin aut In JTCVS Open Elsevier, 2022 15(2023), Seite 468-478 (DE-627)1702642518 26662736 nnns volume:15 year:2023 pages:468-478 https://doi.org/10.1016/j.xjon.2023.05.015 kostenfrei https://doaj.org/article/865336b3d01042548aac5d04c662d171 kostenfrei http://www.sciencedirect.com/science/article/pii/S2666273623001663 kostenfrei https://doaj.org/toc/2666-2736 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 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_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 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_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 15 2023 468-478 |
allfieldsSound |
10.1016/j.xjon.2023.05.015 doi (DE-627)DOAJ090743016 (DE-599)DOAJ865336b3d01042548aac5d04c662d171 DE-627 ger DE-627 rakwb eng RC666-701 RD1-811 Arman Ashrafi, BA verfasserin aut Delays to surgery and worse outcomes: The compounding effects of social determinants of health in non–small cell lung cancerCentral MessagePerspective 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Objective: To quantify the compounding effects of social determinants of health on time to surgery (T2S) and clinical outcomes. Methods: The National Cancer Database was queried for treatment-naïve patients with cT1-4N0-1M0 non–small cell lung cancer undergoing (bi)lobectomy or pneumonectomy between 2006 and 2016 with 1 to 180 days T2S, the number of days between diagnosis and surgery; surgical delays were defined as statistically significant increased T2S compared with a reference cohort. Social determinants of health factors prognostic for surgical delays were identified using multivariable regression. The 30-/90-day mortality and 5-year survival estimates were calculated using logistic and Cox regressions, respectively. Results: In total, 110,005 patients met inclusionary criteria. Multivariable analysis identified race, insurance, and facility type as factors with significant 3-way interaction: T2S of one depended on the others. Income and education also contributed to delays. Privately insured (private) non-Hispanic White patients at academic medical centers (AMCs) were the reference with T2S of 44.1 days. At AMCs, private Black patients had significant delays to surgery (54.7 days; P < .0001), as did Medicaid and uninsured Black patients (58.5 days; P < .0001, 59.4 days; P < .0001, respectively). The 15-day surgical delays were associated with statistically significant 5% increased 30-day mortality odds (confidence interval [CI], 1.03-1.08), 6% increased 90-day mortality odds (CI, 1.04-1.08), and 4% decrease in hazard of death at 5 years (CI, 1.04-1.05). Conclusions: In treatment-naïve patients with cT1-4N0-1M0 non–small cell lung cancer, Black race, Medicaid, uninsured status, and AMCs generate compounding surgical delays with increased 30-/90-day mortality and decreased 5-year survival. Thoracic surgeons can leverage these facility and demographic-specific insights to standardize time to surgery and begin mitigating underlying disparities. thoracic surgery NSCLC social determinants of health time to surgery clinical outcomes disparities Diseases of the circulatory (Cardiovascular) system Surgery Li Ding, MD, MPH verfasserin aut Scott M. Atay, MD verfasserin aut Sean C. Wightman, MD verfasserin aut Takashi Harano, MD verfasserin aut Anthony W. Kim, MD verfasserin aut In JTCVS Open Elsevier, 2022 15(2023), Seite 468-478 (DE-627)1702642518 26662736 nnns volume:15 year:2023 pages:468-478 https://doi.org/10.1016/j.xjon.2023.05.015 kostenfrei https://doaj.org/article/865336b3d01042548aac5d04c662d171 kostenfrei http://www.sciencedirect.com/science/article/pii/S2666273623001663 kostenfrei https://doaj.org/toc/2666-2736 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 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_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 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_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 15 2023 468-478 |
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RC666-701 RD1-811 Delays to surgery and worse outcomes: The compounding effects of social determinants of health in non–small cell lung cancerCentral MessagePerspective thoracic surgery NSCLC social determinants of health time to surgery clinical outcomes disparities |
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Delays to surgery and worse outcomes: The compounding effects of social determinants of health in non–small cell lung cancerCentral MessagePerspective |
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Arman Ashrafi, BA Li Ding, MD, MPH Scott M. Atay, MD Sean C. Wightman, MD Takashi Harano, MD Anthony W. Kim, MD |
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delays to surgery and worse outcomes: the compounding effects of social determinants of health in non–small cell lung cancercentral messageperspective |
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Delays to surgery and worse outcomes: The compounding effects of social determinants of health in non–small cell lung cancerCentral MessagePerspective |
abstract |
Objective: To quantify the compounding effects of social determinants of health on time to surgery (T2S) and clinical outcomes. Methods: The National Cancer Database was queried for treatment-naïve patients with cT1-4N0-1M0 non–small cell lung cancer undergoing (bi)lobectomy or pneumonectomy between 2006 and 2016 with 1 to 180 days T2S, the number of days between diagnosis and surgery; surgical delays were defined as statistically significant increased T2S compared with a reference cohort. Social determinants of health factors prognostic for surgical delays were identified using multivariable regression. The 30-/90-day mortality and 5-year survival estimates were calculated using logistic and Cox regressions, respectively. Results: In total, 110,005 patients met inclusionary criteria. Multivariable analysis identified race, insurance, and facility type as factors with significant 3-way interaction: T2S of one depended on the others. Income and education also contributed to delays. Privately insured (private) non-Hispanic White patients at academic medical centers (AMCs) were the reference with T2S of 44.1 days. At AMCs, private Black patients had significant delays to surgery (54.7 days; P < .0001), as did Medicaid and uninsured Black patients (58.5 days; P < .0001, 59.4 days; P < .0001, respectively). The 15-day surgical delays were associated with statistically significant 5% increased 30-day mortality odds (confidence interval [CI], 1.03-1.08), 6% increased 90-day mortality odds (CI, 1.04-1.08), and 4% decrease in hazard of death at 5 years (CI, 1.04-1.05). Conclusions: In treatment-naïve patients with cT1-4N0-1M0 non–small cell lung cancer, Black race, Medicaid, uninsured status, and AMCs generate compounding surgical delays with increased 30-/90-day mortality and decreased 5-year survival. Thoracic surgeons can leverage these facility and demographic-specific insights to standardize time to surgery and begin mitigating underlying disparities. |
abstractGer |
Objective: To quantify the compounding effects of social determinants of health on time to surgery (T2S) and clinical outcomes. Methods: The National Cancer Database was queried for treatment-naïve patients with cT1-4N0-1M0 non–small cell lung cancer undergoing (bi)lobectomy or pneumonectomy between 2006 and 2016 with 1 to 180 days T2S, the number of days between diagnosis and surgery; surgical delays were defined as statistically significant increased T2S compared with a reference cohort. Social determinants of health factors prognostic for surgical delays were identified using multivariable regression. The 30-/90-day mortality and 5-year survival estimates were calculated using logistic and Cox regressions, respectively. Results: In total, 110,005 patients met inclusionary criteria. Multivariable analysis identified race, insurance, and facility type as factors with significant 3-way interaction: T2S of one depended on the others. Income and education also contributed to delays. Privately insured (private) non-Hispanic White patients at academic medical centers (AMCs) were the reference with T2S of 44.1 days. At AMCs, private Black patients had significant delays to surgery (54.7 days; P < .0001), as did Medicaid and uninsured Black patients (58.5 days; P < .0001, 59.4 days; P < .0001, respectively). The 15-day surgical delays were associated with statistically significant 5% increased 30-day mortality odds (confidence interval [CI], 1.03-1.08), 6% increased 90-day mortality odds (CI, 1.04-1.08), and 4% decrease in hazard of death at 5 years (CI, 1.04-1.05). Conclusions: In treatment-naïve patients with cT1-4N0-1M0 non–small cell lung cancer, Black race, Medicaid, uninsured status, and AMCs generate compounding surgical delays with increased 30-/90-day mortality and decreased 5-year survival. Thoracic surgeons can leverage these facility and demographic-specific insights to standardize time to surgery and begin mitigating underlying disparities. |
abstract_unstemmed |
Objective: To quantify the compounding effects of social determinants of health on time to surgery (T2S) and clinical outcomes. Methods: The National Cancer Database was queried for treatment-naïve patients with cT1-4N0-1M0 non–small cell lung cancer undergoing (bi)lobectomy or pneumonectomy between 2006 and 2016 with 1 to 180 days T2S, the number of days between diagnosis and surgery; surgical delays were defined as statistically significant increased T2S compared with a reference cohort. Social determinants of health factors prognostic for surgical delays were identified using multivariable regression. The 30-/90-day mortality and 5-year survival estimates were calculated using logistic and Cox regressions, respectively. Results: In total, 110,005 patients met inclusionary criteria. Multivariable analysis identified race, insurance, and facility type as factors with significant 3-way interaction: T2S of one depended on the others. Income and education also contributed to delays. Privately insured (private) non-Hispanic White patients at academic medical centers (AMCs) were the reference with T2S of 44.1 days. At AMCs, private Black patients had significant delays to surgery (54.7 days; P < .0001), as did Medicaid and uninsured Black patients (58.5 days; P < .0001, 59.4 days; P < .0001, respectively). The 15-day surgical delays were associated with statistically significant 5% increased 30-day mortality odds (confidence interval [CI], 1.03-1.08), 6% increased 90-day mortality odds (CI, 1.04-1.08), and 4% decrease in hazard of death at 5 years (CI, 1.04-1.05). Conclusions: In treatment-naïve patients with cT1-4N0-1M0 non–small cell lung cancer, Black race, Medicaid, uninsured status, and AMCs generate compounding surgical delays with increased 30-/90-day mortality and decreased 5-year survival. Thoracic surgeons can leverage these facility and demographic-specific insights to standardize time to surgery and begin mitigating underlying disparities. |
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Delays to surgery and worse outcomes: The compounding effects of social determinants of health in non–small cell lung cancerCentral MessagePerspective |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ090743016</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20240414090323.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">240412s2023 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.xjon.2023.05.015</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ090743016</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJ865336b3d01042548aac5d04c662d171</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">RC666-701</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">RD1-811</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Arman Ashrafi, BA</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Delays to surgery and worse outcomes: The compounding effects of social determinants of health in non–small cell lung cancerCentral MessagePerspective</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2023</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Objective: To quantify the compounding effects of social determinants of health on time to surgery (T2S) and clinical outcomes. Methods: The National Cancer Database was queried for treatment-naïve patients with cT1-4N0-1M0 non–small cell lung cancer undergoing (bi)lobectomy or pneumonectomy between 2006 and 2016 with 1 to 180 days T2S, the number of days between diagnosis and surgery; surgical delays were defined as statistically significant increased T2S compared with a reference cohort. Social determinants of health factors prognostic for surgical delays were identified using multivariable regression. The 30-/90-day mortality and 5-year survival estimates were calculated using logistic and Cox regressions, respectively. Results: In total, 110,005 patients met inclusionary criteria. Multivariable analysis identified race, insurance, and facility type as factors with significant 3-way interaction: T2S of one depended on the others. Income and education also contributed to delays. Privately insured (private) non-Hispanic White patients at academic medical centers (AMCs) were the reference with T2S of 44.1 days. At AMCs, private Black patients had significant delays to surgery (54.7 days; P < .0001), as did Medicaid and uninsured Black patients (58.5 days; P < .0001, 59.4 days; P < .0001, respectively). The 15-day surgical delays were associated with statistically significant 5% increased 30-day mortality odds (confidence interval [CI], 1.03-1.08), 6% increased 90-day mortality odds (CI, 1.04-1.08), and 4% decrease in hazard of death at 5 years (CI, 1.04-1.05). Conclusions: In treatment-naïve patients with cT1-4N0-1M0 non–small cell lung cancer, Black race, Medicaid, uninsured status, and AMCs generate compounding surgical delays with increased 30-/90-day mortality and decreased 5-year survival. Thoracic surgeons can leverage these facility and demographic-specific insights to standardize time to surgery and begin mitigating underlying disparities.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">thoracic surgery</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">NSCLC</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">social determinants of health</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">time to surgery</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">clinical outcomes</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">disparities</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Diseases of the circulatory (Cardiovascular) system</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Surgery</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Li Ding, MD, MPH</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Scott M. Atay, MD</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Sean C. Wightman, MD</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Takashi Harano, MD</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Anthony W. Kim, MD</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">JTCVS Open</subfield><subfield code="d">Elsevier, 2022</subfield><subfield code="g">15(2023), Seite 468-478</subfield><subfield code="w">(DE-627)1702642518</subfield><subfield code="x">26662736</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:15</subfield><subfield code="g">year:2023</subfield><subfield code="g">pages:468-478</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.xjon.2023.05.015</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/865336b3d01042548aac5d04c662d171</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" 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