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The Danish Myelodysplastic Syndromes Database: Patient Characteristics and Validity of Data Records
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. OBJEC...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8213953/ https://www.ncbi.nlm.nih.gov/pubmed/34163252 http://dx.doi.org/10.2147/CLEP.S306857 |
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author | Lauritsen, Tine Bichel Nørgaard, Jan Maxwell Grønbæk, Kirsten Vallentin, Anders Pommer Ahmad, Syed Azhar Hannig, Louise Hur Severinsen, Marianne Tang Adelborg, Kasper Østgård, Lene Sofie Granfeldt |
author_facet | Lauritsen, Tine Bichel Nørgaard, Jan Maxwell Grønbæk, Kirsten Vallentin, Anders Pommer Ahmad, Syed Azhar Hannig, Louise Hur Severinsen, Marianne Tang Adelborg, Kasper Østgård, Lene Sofie Granfeldt |
author_sort | Lauritsen, Tine Bichel |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8213953 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Dove |
record_format | MEDLINE/PubMed |
spelling | pubmed-82139532021-06-22 The Danish Myelodysplastic Syndromes Database: Patient Characteristics and Validity of Data Records Lauritsen, Tine Bichel Nørgaard, Jan Maxwell Grønbæk, Kirsten Vallentin, Anders Pommer Ahmad, Syed Azhar Hannig, Louise Hur Severinsen, Marianne Tang Adelborg, Kasper Østgård, Lene Sofie Granfeldt Clin Epidemiol Original Research 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. Dove 2021-06-14 /pmc/articles/PMC8213953/ /pubmed/34163252 http://dx.doi.org/10.2147/CLEP.S306857 Text en © 2021 Lauritsen et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). |
spellingShingle | Original Research Lauritsen, Tine Bichel Nørgaard, Jan Maxwell Grønbæk, Kirsten Vallentin, Anders Pommer Ahmad, Syed Azhar Hannig, Louise Hur Severinsen, Marianne Tang Adelborg, Kasper Østgård, Lene Sofie Granfeldt The Danish Myelodysplastic Syndromes Database: Patient Characteristics and Validity of Data Records |
title | The Danish Myelodysplastic Syndromes Database: Patient Characteristics and Validity of Data Records |
title_full | The Danish Myelodysplastic Syndromes Database: Patient Characteristics and Validity of Data Records |
title_fullStr | The Danish Myelodysplastic Syndromes Database: Patient Characteristics and Validity of Data Records |
title_full_unstemmed | The Danish Myelodysplastic Syndromes Database: Patient Characteristics and Validity of Data Records |
title_short | The Danish Myelodysplastic Syndromes Database: Patient Characteristics and Validity of Data Records |
title_sort | danish myelodysplastic syndromes database: patient characteristics and validity of data records |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8213953/ https://www.ncbi.nlm.nih.gov/pubmed/34163252 http://dx.doi.org/10.2147/CLEP.S306857 |
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