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

• Published in: Clinical epidemiology 2021-06, Vol.13, p.439
• Main Authors: Lauritsen, Tine Bichel, Norgaard, Jan Maxwell, Gronbaek, Kirsten, Vallentin, Anders Pommer, Ahmad, Syed Azhar, Hannig, Louise Hur, Severinsen, Marianne Tang, Adelborg, Kasper, Ostgard, Lene Sofie Granfeldt
• Format: Article
• Language: English
• Subjects: Epidemiology; Health aspects; Hemoglobin; Medical records; Medical research; Medicine, Experimental; Myelodysplastic syndromes
• ISSN: 1179-1349; 1179-1349
• DOI: 10.2l47/CLEP.S306857

Background: 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