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Understanding the patient journey to diagnosis of lung cancer
OBJECTIVE: This research describes the clinical pathway and characteristics of two cohorts of patients. The first cohort consists of patients with a confirmed diagnosis of lung cancer while the second consists of patients with a solitary pulmonary nodule (SPN) and no evidence of lung cancer. Linked...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8045203/ https://www.ncbi.nlm.nih.gov/pubmed/33853552 http://dx.doi.org/10.1186/s12885-021-08067-1 |
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author | Zhang, Yichen Simoff, Michael J. Ost, David Wagner, Oliver J. Lavin, James Nauman, Beth Hsieh, Mei-Chin Wu, Xiao-Cheng Pettiford, Brian Shi, Lizheng |
author_facet | Zhang, Yichen Simoff, Michael J. Ost, David Wagner, Oliver J. Lavin, James Nauman, Beth Hsieh, Mei-Chin Wu, Xiao-Cheng Pettiford, Brian Shi, Lizheng |
author_sort | Zhang, Yichen |
collection | PubMed |
description | OBJECTIVE: This research describes the clinical pathway and characteristics of two cohorts of patients. The first cohort consists of patients with a confirmed diagnosis of lung cancer while the second consists of patients with a solitary pulmonary nodule (SPN) and no evidence of lung cancer. Linked data from an electronic medical record and the Louisiana Tumor Registry were used in this investigation. MATERIALS AND METHODS: REACHnet is one of 9 clinical research networks (CRNs) in PCORnet®, the National Patient-Centered Clinical Research Network and includes electronic health records for over 8 million patients from multiple partner health systems. Data from Ochsner Health System and Tulane Medical Center were linked to Louisiana Tumor Registry (LTR), a statewide population-based cancer registry, for analysis of patient’s clinical pathways between July 2013 and 2017. Patient characteristics and health services utilization rates by cancer stage were reported as frequency distributions. The Kaplan-Meier product limit method was used to estimate the time from index date to diagnosis by stage in lung cancer cohort. RESULTS: A total of 30,559 potentially eligible patients were identified and 2929 (9.58%) had primary lung cancer. Of these, 1496 (51.1%) were documented in LTR and their clinical pathway to diagnosis was further studied. Time to diagnosis varied significantly by cancer stage. A total of 24,140 patients with an SPN were identified in REACHnet and 15,978 (66.6%) had documented follow up care for 1 year. 1612 (10%) had no evidence of any work up for their SPN. The remaining 14,366 had some evidence of follow up, primarily office visits and additional chest imaging. CONCLUSION: In both cohorts multiple biopsies were evident in the clinical pathway. Despite clinical workup, 70% of patients in the lung cancer cohort had stage III or IV disease. In the SPN cohort, only 66% were identified as receiving a diagnostic work-up. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-021-08067-1. |
format | Online Article Text |
id | pubmed-8045203 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-80452032021-04-14 Understanding the patient journey to diagnosis of lung cancer Zhang, Yichen Simoff, Michael J. Ost, David Wagner, Oliver J. Lavin, James Nauman, Beth Hsieh, Mei-Chin Wu, Xiao-Cheng Pettiford, Brian Shi, Lizheng BMC Cancer Research Article OBJECTIVE: This research describes the clinical pathway and characteristics of two cohorts of patients. The first cohort consists of patients with a confirmed diagnosis of lung cancer while the second consists of patients with a solitary pulmonary nodule (SPN) and no evidence of lung cancer. Linked data from an electronic medical record and the Louisiana Tumor Registry were used in this investigation. MATERIALS AND METHODS: REACHnet is one of 9 clinical research networks (CRNs) in PCORnet®, the National Patient-Centered Clinical Research Network and includes electronic health records for over 8 million patients from multiple partner health systems. Data from Ochsner Health System and Tulane Medical Center were linked to Louisiana Tumor Registry (LTR), a statewide population-based cancer registry, for analysis of patient’s clinical pathways between July 2013 and 2017. Patient characteristics and health services utilization rates by cancer stage were reported as frequency distributions. The Kaplan-Meier product limit method was used to estimate the time from index date to diagnosis by stage in lung cancer cohort. RESULTS: A total of 30,559 potentially eligible patients were identified and 2929 (9.58%) had primary lung cancer. Of these, 1496 (51.1%) were documented in LTR and their clinical pathway to diagnosis was further studied. Time to diagnosis varied significantly by cancer stage. A total of 24,140 patients with an SPN were identified in REACHnet and 15,978 (66.6%) had documented follow up care for 1 year. 1612 (10%) had no evidence of any work up for their SPN. The remaining 14,366 had some evidence of follow up, primarily office visits and additional chest imaging. CONCLUSION: In both cohorts multiple biopsies were evident in the clinical pathway. Despite clinical workup, 70% of patients in the lung cancer cohort had stage III or IV disease. In the SPN cohort, only 66% were identified as receiving a diagnostic work-up. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-021-08067-1. BioMed Central 2021-04-14 /pmc/articles/PMC8045203/ /pubmed/33853552 http://dx.doi.org/10.1186/s12885-021-08067-1 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Zhang, Yichen Simoff, Michael J. Ost, David Wagner, Oliver J. Lavin, James Nauman, Beth Hsieh, Mei-Chin Wu, Xiao-Cheng Pettiford, Brian Shi, Lizheng Understanding the patient journey to diagnosis of lung cancer |
title | Understanding the patient journey to diagnosis of lung cancer |
title_full | Understanding the patient journey to diagnosis of lung cancer |
title_fullStr | Understanding the patient journey to diagnosis of lung cancer |
title_full_unstemmed | Understanding the patient journey to diagnosis of lung cancer |
title_short | Understanding the patient journey to diagnosis of lung cancer |
title_sort | understanding the patient journey to diagnosis of lung cancer |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8045203/ https://www.ncbi.nlm.nih.gov/pubmed/33853552 http://dx.doi.org/10.1186/s12885-021-08067-1 |
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