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

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Standard

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.

I: Clinical Epidemiology, Bind 13, 2021, s. 439-451.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Harvard

Lauritsen, TB, Nørgaard, JM, Grønbæk, K, Vallentin, AP, Ahmad, SA, Hannig, LH, Severinsen, MT, Adelborg, K & Østgård, LSG 2021, 'The Danish Myelodysplastic Syndromes Database: Patient Characteristics and Validity of Data Records', Clinical Epidemiology, bind 13, s. 439-451. https://doi.org/10.2147/CLEP.S306857

APA

Lauritsen, T. B., Nørgaard, J. M., Grønbæk, K., Vallentin, A. P., Ahmad, S. A., Hannig, L. H., Severinsen, M. T., Adelborg, K., & Østgård, L. S. G. (2021). The Danish Myelodysplastic Syndromes Database: Patient Characteristics and Validity of Data Records. Clinical Epidemiology, 13, 439-451. https://doi.org/10.2147/CLEP.S306857

Vancouver

Lauritsen TB, Nørgaard JM, Grønbæk K, Vallentin AP, Ahmad SA, Hannig LH o.a. The Danish Myelodysplastic Syndromes Database: Patient Characteristics and Validity of Data Records. Clinical Epidemiology. 2021;13:439-451. https://doi.org/10.2147/CLEP.S306857

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. / The Danish Myelodysplastic Syndromes Database : Patient Characteristics and Validity of Data Records. I: Clinical Epidemiology. 2021 ; Bind 13. s. 439-451.

Bibtex

@article{5591730f5ea34c9aa275f24191fc0bb6,
title = "The Danish Myelodysplastic Syndromes Database: Patient Characteristics and Validity of Data Records",
abstract = "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.",
author = "Lauritsen, {Tine Bichel} and N{\o}rgaard, {Jan Maxwell} and Kirsten Gr{\o}nb{\ae}k and Vallentin, {Anders Pommer} and Ahmad, {Syed Azhar} and Hannig, {Louise Hur} and Severinsen, {Marianne Tang} and Kasper Adelborg and {\O}stg{\aa}rd, {Lene Sofie Granfeldt}",
note = "{\textcopyright} 2021 Lauritsen et al.",
year = "2021",
doi = "10.2147/CLEP.S306857",
language = "English",
volume = "13",
pages = "439--451",
journal = "Clinical Epidemiology",
issn = "1179-1349",
publisher = "Dove Medical Press Ltd",

}

RIS

TY - JOUR

T1 - The Danish Myelodysplastic Syndromes Database

T2 - Patient Characteristics and Validity of Data Records

AU - Lauritsen, Tine Bichel

AU - Nørgaard, Jan Maxwell

AU - Grønbæk, Kirsten

AU - Vallentin, Anders Pommer

AU - Ahmad, Syed Azhar

AU - Hannig, Louise Hur

AU - Severinsen, Marianne Tang

AU - Adelborg, Kasper

AU - Østgård, Lene Sofie Granfeldt

N1 - © 2021 Lauritsen et al.

PY - 2021

Y1 - 2021

N2 - 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.

AB - 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.

U2 - 10.2147/CLEP.S306857

DO - 10.2147/CLEP.S306857

M3 - Journal article

C2 - 34163252

VL - 13

SP - 439

EP - 451

JO - Clinical Epidemiology

JF - Clinical Epidemiology

SN - 1179-1349

ER -

ID: 274225287