Pancreatic cancer symptom trajectories from Danish registry data and free text in electronic health records
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Pancreatic cancer symptom trajectories from Danish registry data and free text in electronic health records. / Hjaltelin, Jessica Xin; Novitski, Sif Ingibergsdóttir; Jørgensen, Isabella Friis; Siggaard, Troels; Vulpius, Siri Amalie; Westergaard, David; Johansen, Julia Sidenius; Chen, Inna M.; Juhl Jensen, Lars; Brunak, Søren.
In: eLife, Vol. 12, e84919, 2023.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Pancreatic cancer symptom trajectories from Danish registry data and free text in electronic health records
AU - Hjaltelin, Jessica Xin
AU - Novitski, Sif Ingibergsdóttir
AU - Jørgensen, Isabella Friis
AU - Siggaard, Troels
AU - Vulpius, Siri Amalie
AU - Westergaard, David
AU - Johansen, Julia Sidenius
AU - Chen, Inna M.
AU - Juhl Jensen, Lars
AU - Brunak, Søren
N1 - Publisher Copyright: © 2023, Hjaltelin et al.
PY - 2023
Y1 - 2023
N2 - Pancreatic cancer is one of the deadliest cancer types with poor treatment options. Better detection of early symptoms and relevant disease correlations could improve pancreatic cancer prognosis. In this retrospective study, we used symptom and disease codes (ICD-10) from the Danish National Patient Registry (NPR) encompassing 6.9 million patients from 1994 to 2018,, of whom 23,592 were diagnosed with pancreatic cancer. The Danish cancer registry included 18,523 of these patients. To complement and compare the registry diagnosis codes with deeper clinical data, we used a text mining approach to extract symptoms from free text clinical notes in electronic health records (3078 pancreatic cancer patients and 30,780 controls). We used both data sources to generate and compare symptom disease trajectories to uncover temporal patterns of symptoms prior to pancreatic cancer diagnosis for the same patients. We show that the text mining of the clinical notes was able to complement the registry-based symptoms by capturing more symptoms prior to pancreatic cancer diagnosis. For example, 'Blood pressure reading without diagnosis', 'Abnormalities of heartbeat', and 'Intestinal obstruction' were not found for the registry-based analysis. Chaining symptoms together in trajectories identified two groups of patients with lower median survival (<90 days) following the trajectories 'Cough→Jaundice→Intestinal obstruction' and 'Pain→Jaundice→Abnormal results of function studies'. These results provide a comprehensive comparison of the two types of pancreatic cancer symptom trajectories, which in combination can leverage the full potential of the health data and ultimately provide a fuller picture for detection of early risk factors for pancreatic cancer.
AB - Pancreatic cancer is one of the deadliest cancer types with poor treatment options. Better detection of early symptoms and relevant disease correlations could improve pancreatic cancer prognosis. In this retrospective study, we used symptom and disease codes (ICD-10) from the Danish National Patient Registry (NPR) encompassing 6.9 million patients from 1994 to 2018,, of whom 23,592 were diagnosed with pancreatic cancer. The Danish cancer registry included 18,523 of these patients. To complement and compare the registry diagnosis codes with deeper clinical data, we used a text mining approach to extract symptoms from free text clinical notes in electronic health records (3078 pancreatic cancer patients and 30,780 controls). We used both data sources to generate and compare symptom disease trajectories to uncover temporal patterns of symptoms prior to pancreatic cancer diagnosis for the same patients. We show that the text mining of the clinical notes was able to complement the registry-based symptoms by capturing more symptoms prior to pancreatic cancer diagnosis. For example, 'Blood pressure reading without diagnosis', 'Abnormalities of heartbeat', and 'Intestinal obstruction' were not found for the registry-based analysis. Chaining symptoms together in trajectories identified two groups of patients with lower median survival (<90 days) following the trajectories 'Cough→Jaundice→Intestinal obstruction' and 'Pain→Jaundice→Abnormal results of function studies'. These results provide a comprehensive comparison of the two types of pancreatic cancer symptom trajectories, which in combination can leverage the full potential of the health data and ultimately provide a fuller picture for detection of early risk factors for pancreatic cancer.
KW - cancer biology
KW - computational biology
KW - disease progression
KW - human
KW - longitudinal analysis
KW - pancreas cancer
KW - patient stratification
KW - symptomology
KW - systems biology
U2 - 10.7554/eLife.84919
DO - 10.7554/eLife.84919
M3 - Journal article
C2 - 37988407
AN - SCOPUS:85177681796
VL - 12
JO - eLife
JF - eLife
SN - 2050-084X
M1 - e84919
ER -
ID: 375308604