A Validated Register-Based Algorithm to Identify Patients Diagnosed with Recurrence of Malignant Melanoma in Denmark

References

• The National Board of Health. Nye kræfttilfælde i Danmark. 2018 [Cancer Incidence in Denmark 2018]. Copenhagen: National Board of health; 2019.
   Google Scholar
• Hewitt ME, Greenfield S, Stovall E. From Cancer Patient to Cancer Survivor: Lost in Transition. Washington DC: The National Academies Press; 2006.
   Google Scholar
• Warren JL, Yabroff KR. Challenges and opportunities in measuring cancer recurrence in the United States. J Natl Cancer Inst. 2015;107(8):djv134–djv134. doi:10.1093/jnci/djv13425971299
   PubMedGoogle Scholar
• Rubin G, Berendsen A, Crawford SM, et al. The expanding role of primary care in cancer control. Lancet Oncol. 2015;16(12):1231–1272.26431866
   PubMed Web of Science ®Google Scholar
• Cohen AT, Goto S, Schreiber K, Torp-Pedersen C. Why do we need observational studies of everyday patients in the real-life setting? Eur Hear J. 2015;17(Suppl D):D2–D8. doi:10.1093/eurheartj/suv035
   Web of Science ®Google Scholar
• Hassett MJ, Uno H, Cronin AM, Carroll NM, Hornbrook MC, Ritzwoller D. Detecting lung and colorectal cancer recurrence using structured clinical/administrative data to enable outcomes research and population health management. Med Care. 2017;55(12):e88–e98. doi:10.1097/MLR.000000000000040429135771
   PubMed Web of Science ®Google Scholar
• Deshpande AD, Schootman M, Mayer A. Development of a claims-based algorithm to identify colorectal cancer recurrence. Ann Epidemiol. 2015;25(4):297–300. doi:10.1016/j.annepidem.2015.01.00525794767
   PubMed Web of Science ®Google Scholar
• Warren JL, Mariotto A, Melbert D, et al. Sensitivity of medicare claims to identify cancer recurrence in elderly colorectal and breast cancer patients. Med Care. 2016;54(8):e47–e54. doi:10.1097/MLR.000000000000005824374419
   PubMed Web of Science ®Google Scholar
• Xu Y, Kong S, Cheung WY, et al. Development and validation of case-finding algorithms for recurrence of breast cancer using routinely collected administrative data. BMC Cancer. 2019;19(1):210. doi:10.1186/s12885-019-5432-830849954
   PubMed Web of Science ®Google Scholar
• Ritzwoller DP, Hassett MJ, Uno H, et al. Development, validation, and dissemination of a breast cancer recurrence detection and timing informatics algorithm. J Natl Cancer Inst. 2018;110(3):273–281. doi:10.1093/jnci/djx20029873757
   PubMedGoogle Scholar
• Uno H, Ritzwoller DP, Cronin AM, Carroll NM, Hornbrook MC, Hassett MJ. Determining the time of cancer recurrence using claims or electronic medical record data. JCO Clin Cancer Inform. 2018;2(2):1–10.
   PubMed Web of Science ®Google Scholar
• Izci H, Tambuyzer T, Tuand K, et al. A systematic review of estimating breast cancer recurrence at the population level with administrative data. J Natl Cancer Inst. 2020;112(10):djaa050. doi:10.1093/jnci/djaa050
   Google Scholar
• Lash TL, Riis AH, Ostenfeld EB, Erichsen R, Vyberg M, Thorlacius-Ussing O. A validated algorithm to ascertain colorectal cancer recurrence using registry resources in Denmark. Int J Cancer. 2015;136(9):2210–2215. doi:10.1002/ijc.2926725307704
   PubMed Web of Science ®Google Scholar
• Cronin-Fenton D, Kjærsgaard A, Nørgaard M, et al. Breast cancer recurrence, bone metastases, and visceral metastases in women with stage II and III breast cancer in Denmark. Breast Cancer Res Treat. 2018;167(2):517–528. doi:10.1007/s10549-017-4510-328948396
   PubMed Web of Science ®Google Scholar
• Rasmussen LA, Jensen H, Flytkjær Virgilsen L, Jellesmark Thorsen LB, Offersen BV, Vedsted P. A validated algorithm for register-based identification of patients with recurrence of breast cancer—Based on Danish Breast Cancer Group (DBCG) data. Cancer Epidemiol. 2019;59:129–134. doi:10.1016/j.canep.2019.01.01630743224
   PubMed Web of Science ®Google Scholar
• Pedersen RN, Öztürk B, Mellemkjær L, et al. Validation of an algorithm to ascertain late breast cancer recurrence using Danish medical registries. Clin Epidemiol. 2020;12:1083–1093. doi:10.2147/CLEP.S26996233116902
   PubMed Web of Science ®Google Scholar
• Rasmussen LA, Jensen H, Virgilsen LF, Jensen JB, Vedsted P. A validated algorithm to identify recurrence of bladder cancer: a register-based study in Denmark. Clin Epidemiol. 2018;10:1755–1763. doi:10.2147/CLEP.S17730530538579
   PubMed Web of Science ®Google Scholar
• Rasmussen LA, Jensen H, Virgilsen LF, et al. Identification of endometrial cancer recurrence – a validated algorithm based on nationwide Danish registries. Acta Oncol. 2020. doi:10.1080/0284186X.2020.1859133
   Web of Science ®Google Scholar
• Schmidt M, Pedersen L, Sørensen HT. The Danish civil registration system as a tool in epidemiology. Eur J Epidemiol. 2014;29(8):541–549. doi:10.1007/s10654-014-9930-324965263
   PubMed Web of Science ®Google Scholar
• Rosenkrantz Hölmich L, Klausen S, Spaun E, et al. The Danish melanoma database. Clin Epidemiol. 2016;8:543–548. doi:10.2147/CLEP.S9948427822097
   PubMed Web of Science ®Google Scholar
• Gjerstorff ML. The Danish cancer registry. Scand J Public Health. 2011;39(Suppl 7):42–45. doi:10.1177/140349481039356221775350
   PubMed Web of Science ®Google Scholar
• Schmidt M, Schmidt SAJ, Sandegaard JL, Ehrenstein V, Pedersen L, Sørensen HT. The Danish national patient registry: a review of content, data quality, and research potential. Clin Epidemiol. 2015;7:449–490. doi:10.2147/CLEP.S9112526604824
   PubMed Web of Science ®Google Scholar
• Erichsen R, Lash TL, Hamilton-Dutoit SJ, Bjerregaard B, Vyberg M, Pedersen L. Existing data sources for clinical epidemiology: the Danish national pathology registry and data bank. Clin Epidemiol. 2010;2:51–56. doi:10.2147/CLEP.S990820865103
   PubMedGoogle Scholar
• Pedersen CB. The Danish civil registration system. Scand J Public Health. 2011;39(Suppl 7):22–25. doi:10.1177/140349481038796521775345
   PubMed Web of Science ®Google Scholar
• Union for International Cancer Control. TNM classification of malignant tumours. Available from: https://www.uicc.org/resources/tnm. Accessed 1224, 2020.
   Google Scholar
• Lin LI. A concordance correlation coefficient to evaluate reproducibility. Biometrics. 1989;45(1):255–268. doi:10.2307/25320512720055
   PubMed Web of Science ®Google Scholar
• McBride GB. A Proposal for Strength of Agreement Criteria for Lin’s Concordance Correlation Coefficient. New Zealand: National Institute of Water & Atmospheric Reseach; 2005.
   Google Scholar
• Danish Melanoma Group. Available from: https://www.melanoma.dk/index.html#header1-1. Accessed 124, 2020.
   Google Scholar
• The Danish Clinical Quality Program and Clinical Registries (RKKP) and Danish Melanoma Database. Dansk melanom databases national årsrapport 2014 [Danish melanoma database annual report 2014]. Aarhus, Denmark. 2015. Available from: https://www.melanoma.dk/assets/files/DMG_Aarsrapport_2014.pdf. Accessed 124, 2020.
   Google Scholar
• Leiter U, Buettner PG, Eigentler TK, et al. Hazard rates for recurrent and secondary cutaneous melanoma: an analysis of 33,384 patients in the German central malignant melanoma registry. J Am Acad Dermatol. 2012;66(1):37–45. doi:10.1016/j.jaad.2010.09.77221700361
   PubMed Web of Science ®Google Scholar
• Tas F, Erturk K. Early and late relapses of cutaneous melanoma patients. Postgrad Med. 2019;131(3):207–211. doi:10.1080/00325481.2019.156935430644788
   PubMed Web of Science ®Google Scholar
• The Danish Clinical Quality Program and Clinical Registries (RKKP) and Danish Melanoma Database. Dansk melanom database national årsrapport 2017 [Danish melanoma database annual report 2017]. Aarhus, Denmark. 2018. Available from: https://www.melanoma.dk/assets/files/DMG_Aarsrapport_2018.pdf. Accessed 124, 2020.
   Google Scholar