| Zdroj: |
Nors, J, Mattesen, T B, Cronin-Fenton, D, Mailhac, A, Bramsen, J B, Gotschalck, K A, Erichsen, R & Andersen, C L 2023, ' Identifying Recurrences Among Non-Metastatic Colorectal Cancer Patients Using National Health Data Registries : Validation and Optimization of a Registry-Based Algorithm in a Modern Danish Cohort ', Clinical epidemiology, vol. 15, pp. 241-250 . https://doi.org/10.2147/CLEP.S396140 |
| Popis: |
Jesper Nors,1,2,* Trine Block Mattesen,1,* Deirdre Cronin-Fenton,3 Aurélie Mailhac,3 Jesper Bertram Bramsen,1,2 KÃ¥re Andersson Gotschalck,2,4 Rune Erichsen,2,3,5 Claus Lindbjerg Andersen1,2 1Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark; 2Department of Clinical Medicine, Aarhus University Hospital, Aarhus, Denmark; 3Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark; 4Department of Surgery, Horsens Regional Hospital, Horsens, Denmark; 5Department of Surgery, Randers Regional Hospital, Horsens, Denmark*These authors contributed equally to this workCorrespondence: Claus Lindbjerg Andersen, Department of Molecular Medicine, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, Aarhus N, DK-8200, Denmark, Tel +45 78455319, Email cla@clin.au.dkPurpose: Colorectal cancer (CRC) recurrence is not routinely recorded in Danish health data registries. Here, we aimed to revalidate a registry-based algorithm to identify recurrences in a contemporary cohort and to investigate the accuracy of estimating the time to recurrence (TTR).Patients and Methods: We ascertained data on 1129 patients operated for UICC TNM stage IâIII CRC during 2012â 2017 registered in the CRC biobank at the Department of Molecular Medicine, Aarhus University Hospital, Denmark. Individual-level data were linked with data from the Danish Colorectal Cancer Group database, Danish Cancer Registry, Danish National Registry of Patients, and Danish Pathology Registry. The algorithm identified recurrence based on diagnosis codes of local recurrence or metastases, the receipt of chemotherapy, or a pathological tissue assessment code of recurrence more than 180 days after CRC surgery. A subgroup was selected for validation of the algorithm using medical record reviews as a reference standard.Results: We found a 3-year cumulative recurrence rate of 20% (95% CI: 17â 22%). Manual medical record review identified 80 recurrences in the validation cohort of 522 patients. The algorithm detected recurrence with 94% sensitivity (75/80; 95% CI: 86â 98%) and 98% specificity (431/442; 95% CI: 96â 99%). The positive and negative predictive values of the algorithm were 87% (95% CI: 78â 93%) and 99% (95% CI: 97â 100%), respectively. The median difference in TTR (TTRMedical_chart-TTRalgorithm) was â 8 days (IQR: â 21 to +3 days). Restricting the algorithm to chemotherapy codes from oncology departments increased the positive predictive value from 87% to 94% without changing the negative predictive value (99%).Conclusion: The algorithm detected recurrence and TTR with high precision in this contemporary cohort. Restriction to chemotherapy codes from oncology departments using department classifications improves the algorithm. The algorithm is suitable for use in future observational studies.Keywords: time to recurrence, surveillance, chemotherapy, oncology |
