Clinical Epidemiology (Jun 2021)

The Danish Myelodysplastic Syndromes Database: Patient Characteristics and Validity of Data Records

  • Lauritsen TB,
  • Nørgaard JM,
  • Grønbæk K,
  • Vallentin AP,
  • Ahmad SA,
  • Hannig LH,
  • Severinsen MT,
  • Adelborg K,
  • Østgård LSG

Journal volume & issue
Vol. Volume 13
pp. 439 – 451

Abstract

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Tine Bichel Lauritsen,1 Jan Maxwell Nørgaard,1 Kirsten Grønbæk,2– 4 Anders Pommer Vallentin,5 Syed Azhar Ahmad,6 Louise Hur Hannig,7 Marianne Tang Severinsen,8,9 Kasper Adelborg,10,11 Lene Sofie Granfeldt Østgård11,12 1Department of Hematology, Aarhus University Hospital, Aarhus, Denmark; 2Department of Hematology, Rigshospitalet, Copenhagen, Denmark; 3Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark; 4Novo Nordisk Foundation Center for Stem Cell Biology (DanStem), Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark; 5Zealand University Hospital, Roskilde, Denmark; 6Department of Hematology, Herlev Hospital, Herlev, Denmark; 7Department of Hematology, Vejle Hospital, Vejle, Denmark; 8Department of Hematology, Clinical Cancer Research Center, Aalborg University Hospital, Aalborg, Denmark; 9Department of Clinical Medicine, Aalborg University, Aalborg, Denmark; 10Department of Clinical Biochemistry, Aarhus University Hospital, Aarhus, Denmark; 11Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark; 12Department of Hematology, Odense University Hospital, Odense, DenmarkCorrespondence: Tine Bichel LauritsenDepartment of Hematology, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, Aarhus N, 8200 Email [email protected]: The Danish Myelodysplastic Syndromes Database (DMDSD) comprises nearly all patients diagnosed with myelodysplastic syndromes (MDS) in Denmark since 2010. The DMDSD has not yet been used for epidemiological research and the quality of registered variables remains to be investigated.Objective: To describe characteristics of the patients registered in the DMDSD and to calculate predictive values and the proportion of missing values of registered data records.Methods: We performed a nationwide cross-sectional validation study of recorded disease and treatment data on MDS patients during 2010– 2019. Patient characteristics and the proportion of missing values were tabulated. A random sample of 12% was drawn to calculate predictive values with 95% confidence intervals (CIs) of 48 variables using information from medical records as a reference standard.Results: Overall, 2284 patients were identified (median age: 76 years, men 62%). Of these, 10% had therapy-related MDS, and 6% had an antecedent hematological disease. Hemoglobin level was less than 6.2 mmol/L for 59% of patients. Within the first two years of treatment, 59% received transfusions, 35% received erythropoiesis-stimulating agents, and 15% were treated with a hypomethylating agent. For the majority of variables (around 80%), there were no missing data. A total of 260 medical records were available for validation. The positive predictive value of the MDS diagnosis was 92% (95% CI: 88– 95). Predictive values ranged from 64% to 100% and exceeded 90% for 36 out of 48 variables. Stratification by year of diagnosis suggested that the positive predictive value of the MDS diagnosis improved from 88% before 2015 to 95% after.Conclusion: In this study, there was a high accuracy of recorded data and a low proportion of missing data. Thus, the DMDSD serves as a valuable data source for future epidemiological studies on MDS.Keywords: myelodysplastic syndromes, cohort, validation, accuracy, database

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