| Zdroj: |
Sørup, S, Darvalics, B, Knudsen, J S, Rasmussen, A S, Hjorth, C F, Vestergaard, S V, Khalil, A A, Russo, L, Oksen, D, Boutmy, E, Verpillat, P, Rørth, M & Cronin-Fenton, D 2022, ' Identifying Valid Algorithms for Number of Lines of Anti-Neoplastic Therapy in the Danish National Patient Registry Among Patients with Advanced Ovarian, Gastric, Renal Cell, Urothelial, and Non-Small Cell Lung Cancer Attending a Danish University Hospital ', Clinical Epidemiology, vol. 14, pp. 159-171 . https://doi.org/10.2147/CLEP.S342238 |
| Popis: |
Signe Sørup,1 Bianka Darvalics,1 Jakob Schöllhammer Knudsen,1 Anne Staub Rasmussen,1 Cathrine Fonnesbech Hjorth,1 Søren Viborg Vestergaard,1 Azza Ahmed Khalil,2 Leo Russo,3 Dina Oksen,4 Emmanuelle Boutmy,4 Patrice Verpillat,4 Mikael Rørth,1,5 Deirdre Cronin-Fenton1 1Department of Clinical Epidemiology, Department of Clinical Medicine, Aarhus University & Aarhus University Hospital, Aarhus, Denmark; 2Department of Oncology, Aarhus University Hospital, Aarhus, Denmark; 3Worldwide Medical and Safety, Pfizer, Collegeville, PA, USA; 4Global Epidemiology, Merck Healthcare KGaA, Darmstadt, Germany; 5Department of Oncology, Rigshospitalet, Copenhagen, DenmarkCorrespondence: Signe Sørup, Department of Clinical Epidemiology, Aarhus University Hospital, Olof Palmes Allé 43-45, Aarhus, DK-8200, Denmark, Tel +45 871 68230, Fax +45 87 16 72 15, Email SigneSorup@clin.au.dkPurpose: To develop algorithms to identify number of lines of anti-neoplastic therapy per patient based on the Danish National Patient Registry (DNPR) and identify which algorithm has the highest percentage agreement with a reference standard of documentation in medical records.Patients and Methods: We included 179 patients diagnosed between January 1, 2012, and December 31, 2016, with stage II, III, or IV urothelial cell carcinoma or stage III or IV epithelial ovarian cancer, gastric adenocarcinoma, renal cell carcinoma, or non-small cell lung cancer (NSCLC). We developed two algorithms for number of lines of anti-neoplastic therapy based on dates and treatment codes (eg, âtreatment with cisplatinâ or âcytostatic treatmentâ) in the DNPR. First, to denote a change in line of therapy the âTime-based algorithmâ used the number of days between consecutive administrations. Second, the âDrug-based algorithmâ used information on drug names if available or the number of days between consecutive administrations if no drug names were specified. We calculated the percentage agreement between the algorithms setting the number of allowed days between consecutive administrations from 28 to 50 and the reference standard â information on anti-neoplastic therapy drugs abstracted from medical records and subsequently coded according to lines of anti-neoplastic therapy.Results: For the âTime-based algorithmâ, the highest percentage agreement with the reference standard was found when using < 45 days between consecutive administrations (67.6%; 95% CI: 60.1â 73.8%). However, the percentage agreement was higher for the âDrug-based algorithmâ using < 45 days between consecutive administrations for registrations where the drug name was unspecified (90.5%; 95% CI: 85.0â 93.7%).Conclusion: The algorithm for number of lines of anti-neoplastic therapy that had the highest percentage agreement with the reference standard (medical records) incorporated both registration of specific drug names and < 45 days between consecutive administrations if the drug name was unspecified in routinely recorded data from DNPR.Keywords: positive predictive value, medical records review, duration of chemotherapy, medical oncologic treatments, Denmark |
