Identifying Determinants of Disparities in Lung Cancer Survival Rates from Electronic Health Record Data

Wanting Cui; Joseph Finkelstein

doi:10.3233/SHTI220567

Identifying Determinants of Disparities in Lung Cancer Survival Rates from Electronic Health Record Data

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The goal of this pilot study was to identify significant factors that affect disparities in lung cancer survival. A de-identified dataset was generated by querying electronic health records (EHR) from an academic medical center in New York City between January 2003 and November 2020. Socio-demographic characteristics, cancer stage, and genetic profile were analyzed using logistic regression. Two subsets of adult patients were identified: patients who were deceased less than 1 year after diagnosis and patients who survived over 5 years after diagnosis. Male, Black and Hispanic patients and those who were diagnosed in later stages were the people most susceptible to a shorter length of survival after cancer diagnoses. In addition, we identified three genetic oncodrivers (KRAS, EGFR and TP53) which were highly correlated with the length of survival after lung cancer diagnoses and their distribution was associated with race. We concluded that EHR data provide important insights on cancer survival disparities.

Original language	English
Title of host publication	Challenges of Trustable AI and Added-Value on Health - Proceedings of MIE 2022
Editors	Brigitte Seroussi, Patrick Weber, Ferdinand Dhombres, Cyril Grouin, Jan-David Liebe, Jan-David Liebe, Jan-David Liebe, Sylvia Pelayo, Andrea Pinna, Bastien Rance, Bastien Rance, Lucia Sacchi, Adrien Ugon, Adrien Ugon, Arriel Benis, Parisis Gallos
Publisher	IOS Press BV
Pages	715-716
Number of pages	2
ISBN (Electronic)	9781643682846
DOIs	https://doi.org/10.3233/SHTI220567
State	Published - 25 May 2022
Event	32nd Medical Informatics Europe Conference, MIE 2022 - Nice, France Duration: 27 May 2022 → 30 May 2022

Publication series

Name	Studies in Health Technology and Informatics
Volume	294
ISSN (Print)	0926-9630
ISSN (Electronic)	1879-8365

Conference

Conference	32nd Medical Informatics Europe Conference, MIE 2022
Country/Territory	France
City	Nice
Period	27/05/22 → 30/05/22

Keywords

Lung cancer
disparity
electronic health records
gene

Access to Document

10.3233/SHTI220567

Cite this

Cui, W., & Finkelstein, J. (2022). Identifying Determinants of Disparities in Lung Cancer Survival Rates from Electronic Health Record Data. In B. Seroussi, P. Weber, F. Dhombres, C. Grouin, J-D. Liebe, J-D. Liebe, J-D. Liebe, S. Pelayo, A. Pinna, B. Rance, B. Rance, L. Sacchi, A. Ugon, A. Ugon, A. Benis, & P. Gallos (Eds.), Challenges of Trustable AI and Added-Value on Health - Proceedings of MIE 2022 (pp. 715-716). (Studies in Health Technology and Informatics; Vol. 294). IOS Press BV. https://doi.org/10.3233/SHTI220567

Cui, Wanting ; Finkelstein, Joseph. / Identifying Determinants of Disparities in Lung Cancer Survival Rates from Electronic Health Record Data. Challenges of Trustable AI and Added-Value on Health - Proceedings of MIE 2022. editor / Brigitte Seroussi ; Patrick Weber ; Ferdinand Dhombres ; Cyril Grouin ; Jan-David Liebe ; Jan-David Liebe ; Jan-David Liebe ; Sylvia Pelayo ; Andrea Pinna ; Bastien Rance ; Bastien Rance ; Lucia Sacchi ; Adrien Ugon ; Adrien Ugon ; Arriel Benis ; Parisis Gallos. IOS Press BV, 2022. pp. 715-716 (Studies in Health Technology and Informatics).

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title = "Identifying Determinants of Disparities in Lung Cancer Survival Rates from Electronic Health Record Data",

abstract = "The goal of this pilot study was to identify significant factors that affect disparities in lung cancer survival. A de-identified dataset was generated by querying electronic health records (EHR) from an academic medical center in New York City between January 2003 and November 2020. Socio-demographic characteristics, cancer stage, and genetic profile were analyzed using logistic regression. Two subsets of adult patients were identified: patients who were deceased less than 1 year after diagnosis and patients who survived over 5 years after diagnosis. Male, Black and Hispanic patients and those who were diagnosed in later stages were the people most susceptible to a shorter length of survival after cancer diagnoses. In addition, we identified three genetic oncodrivers (KRAS, EGFR and TP53) which were highly correlated with the length of survival after lung cancer diagnoses and their distribution was associated with race. We concluded that EHR data provide important insights on cancer survival disparities.",

keywords = "Lung cancer, disparity, electronic health records, gene",

author = "Wanting Cui and Joseph Finkelstein",

note = "Publisher Copyright: {\textcopyright} 2022 European Federation for Medical Informatics (EFMI) and IOS Press.; 32nd Medical Informatics Europe Conference, MIE 2022 ; Conference date: 27-05-2022 Through 30-05-2022",

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doi = "10.3233/SHTI220567",

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editor = "Brigitte Seroussi and Patrick Weber and Ferdinand Dhombres and Cyril Grouin and Jan-David Liebe and Jan-David Liebe and Jan-David Liebe and Sylvia Pelayo and Andrea Pinna and Bastien Rance and Bastien Rance and Lucia Sacchi and Adrien Ugon and Adrien Ugon and Arriel Benis and Parisis Gallos",

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Cui, W & Finkelstein, J 2022, Identifying Determinants of Disparities in Lung Cancer Survival Rates from Electronic Health Record Data. in B Seroussi, P Weber, F Dhombres, C Grouin, J-D Liebe, J-D Liebe, J-D Liebe, S Pelayo, A Pinna, B Rance, B Rance, L Sacchi, A Ugon, A Ugon, A Benis & P Gallos (eds), Challenges of Trustable AI and Added-Value on Health - Proceedings of MIE 2022. Studies in Health Technology and Informatics, vol. 294, IOS Press BV, pp. 715-716, 32nd Medical Informatics Europe Conference, MIE 2022, Nice, France, 27/05/22. https://doi.org/10.3233/SHTI220567

Identifying Determinants of Disparities in Lung Cancer Survival Rates from Electronic Health Record Data. / Cui, Wanting; Finkelstein, Joseph.
Challenges of Trustable AI and Added-Value on Health - Proceedings of MIE 2022. ed. / Brigitte Seroussi; Patrick Weber; Ferdinand Dhombres; Cyril Grouin; Jan-David Liebe; Jan-David Liebe; Jan-David Liebe; Sylvia Pelayo; Andrea Pinna; Bastien Rance; Bastien Rance; Lucia Sacchi; Adrien Ugon; Adrien Ugon; Arriel Benis; Parisis Gallos. IOS Press BV, 2022. p. 715-716 (Studies in Health Technology and Informatics; Vol. 294).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Cui W, Finkelstein J. Identifying Determinants of Disparities in Lung Cancer Survival Rates from Electronic Health Record Data. In Seroussi B, Weber P, Dhombres F, Grouin C, Liebe J-D, Liebe J-D, Liebe J-D, Pelayo S, Pinna A, Rance B, Rance B, Sacchi L, Ugon A, Ugon A, Benis A, Gallos P, editors, Challenges of Trustable AI and Added-Value on Health - Proceedings of MIE 2022. IOS Press BV. 2022. p. 715-716. (Studies in Health Technology and Informatics). doi: 10.3233/SHTI220567

Identifying Determinants of Disparities in Lung Cancer Survival Rates from Electronic Health Record Data

Abstract

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