Clinical Epidemiology (Mar 2024)

Extracting Systemic Anticancer Treatment Lines from the Danish National Patient Registry for Solid Tumour Patients Treated in the North Denmark Region Between 2009 and 2019

  • Vesteghem C,
  • Bøgsted M,
  • Cronin-Fenton D,
  • Poulsen LØ

Journal volume & issue
Vol. Volume 16
pp. 165 – 174

Abstract

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Charles Vesteghem,1,2 Martin Bøgsted,1,2 Deirdre Cronin-Fenton,3 Laurids Østergaard Poulsen2,4 1Center for Clinical Data Science, Aalborg University and Aalborg University Hospital, Aalborg, Denmark; 2Clinical Cancer Research Centre, Aalborg University Hospital, Aalborg, Denmark; 3Department of Clinical Epidemiology, Department of Clinical Medicine, Aarhus University and Aarhus University Hospital, Aarhus, Denmark; 4Department of Oncology, Aalborg University Hospital, Aalborg, DenmarkCorrespondence: Charles Vesteghem, Center for Clinical Data Science, Aalborg University and Aalborg University Hospital, Selma Lagerløfs Vej 249, Gistrup, 9260, Denmark, Email [email protected]: Reconstructing patient treatment trajectories is important to generate real-world evidence for epidemiological studies. The Danish National Patient Registry (DNPR) contains information about drug prescriptions and could therefore be used to reconstruct treatment trajectories. We aimed to evaluate and enhance two existing methods to reconstruct systemic anticancer treatment trajectories.Methods: This study was based on data from 8738 consecutive patients with solid tumors treated in the North Denmark Region between 2009 and 2019. Two approaches found in the literature as well as two new approaches were applied to the DNPR data. All methods relied on time intervals between two consecutive drug administrations to determine if they belonged to the same treatment line. MedOnc, a local dataset from the Department of Oncology, Aalborg University Hospital was used as a reference. To evaluate the performance of each method, F1-scores were calculated after matching the lines identified in both datasets. We used three different matching strategies: stringent matching, loose matching, and matching based on line numbers, controlling for overfitting.Results: Overall, the two new approaches outperformed the simpler and best performing of the two existing methods, with F1-scores of 0.47 and 0.45 vs 0.44 for stringent matching and 0.84 and 0.83 vs 0.82 for loose matching. Nevertheless, only one of the new methods outperformed the existing simpler method when matching on the number of lines (0.73 vs 0.72). Large differences were seen by cancer site, especially for the stringent and line number matchings. Performances were relatively stable by calendar year.Conclusion: The high F1-scores for the new methods confirm that they should be generally preferred to reconstruct systemic anticancer treatment trajectories using the DNPR.Keywords: anticancer treatment, epidemiology, patient trajectory, Danish National Patient Register, treatment line

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