TY - JOUR
T1 - Using the Gaucher Earlier Diagnosis Consensus (GED-C) Delphi Score in a Real-World Dataset
AU - Revel-Vilk, Shoshana
AU - Chodick, Gabriel
AU - Shalev, Varda
AU - Lotan, Roni
AU - Zarakowska, Kaja
AU - Gadir, Noga
N1 - Publisher Copyright:
© 2022 by the authors.
PY - 2022/9
Y1 - 2022/9
N2 - Early and accurate diagnosis of Gaucher disease, a rare, autosomal recessive condition characterized by hepatosplenomegaly, thrombocytopenia, and anemia, is essential to facilitate earlier decision-making and prevent unnecessary tests and procedures. However, diagnosis can be challenging for non-specialists, owing to a wide variability in age, severity of disease, and types of clinical manifestation. The Gaucher Earlier Diagnosis Consensus (GED-C) scoring system was developed by a panel of 22 expert physicians using Delphi methodology on the signs and covariables considered important for diagnosing Gaucher disease. This study aimed to use the scoring system in a real-world dataset. We applied the GED-C scoring system to 265 confirmed cases of Gaucher disease identified in the Maccabi Health Services (MHS) database from 1998 to 2022. Overall Delphi scores were calculated using features applicable to type 1 Gaucher disease. Based on all available patient data up to one year after diagnosis, the median (interquartile range (IQR)) Delphi score was 8.0 (5.5–11.5), with patients reporting up to 15 variables each. A score of 9.5 (6.5–12.5) was determined for 205 patients diagnosed from 2000 to 2022. The overall GED-C score was highly dependent on the extraction of all relevant data. The number of features collected in the MHS database was fewer than those required to achieve a high score on the GED-C score.
AB - Early and accurate diagnosis of Gaucher disease, a rare, autosomal recessive condition characterized by hepatosplenomegaly, thrombocytopenia, and anemia, is essential to facilitate earlier decision-making and prevent unnecessary tests and procedures. However, diagnosis can be challenging for non-specialists, owing to a wide variability in age, severity of disease, and types of clinical manifestation. The Gaucher Earlier Diagnosis Consensus (GED-C) scoring system was developed by a panel of 22 expert physicians using Delphi methodology on the signs and covariables considered important for diagnosing Gaucher disease. This study aimed to use the scoring system in a real-world dataset. We applied the GED-C scoring system to 265 confirmed cases of Gaucher disease identified in the Maccabi Health Services (MHS) database from 1998 to 2022. Overall Delphi scores were calculated using features applicable to type 1 Gaucher disease. Based on all available patient data up to one year after diagnosis, the median (interquartile range (IQR)) Delphi score was 8.0 (5.5–11.5), with patients reporting up to 15 variables each. A score of 9.5 (6.5–12.5) was determined for 205 patients diagnosed from 2000 to 2022. The overall GED-C score was highly dependent on the extraction of all relevant data. The number of features collected in the MHS database was fewer than those required to achieve a high score on the GED-C score.
KW - Gaucher disease
KW - early diagnosis
KW - machine learning
KW - real-world data
UR - http://www.scopus.com/inward/record.url?scp=85180730755&partnerID=8YFLogxK
U2 - 10.3390/ijtm2030037
DO - 10.3390/ijtm2030037
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AN - SCOPUS:85180730755
SN - 2673-8937
VL - 2
SP - 506
EP - 514
JO - International Journal of Translational Medicine
JF - International Journal of Translational Medicine
IS - 3
ER -