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Identification of risk features for complication in Gaucher’s Disease patients: A Machine Learning analysis of the Spanish Registry of Gaucher Disease.
Pilar Giraldo
CIBERER and Instituto Investigación Sanitaria Aragon (IIS Aragon)
Corresponding Author
ORCiD: https://orcid.org/0000-0002-8791-1901
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published version at Orphanet Journal of Rare Diseases.
Background : Since enzyme replacement therapy for Gaucher disease (MIM#230800) has become available, both awareness of and the natural history of the disease have changed. However, there remain unmet needs such as the identification of patients at risk of developing bone crisis during therapy and late complications such as cancer or parkinsonism. The Spanish Gaucher Disease Registry has worked since 1993 to compile demographic, clinical, genetic, analytical, imaging and follow-up data from more than 400 patients. The aims of this study were to discover correlations between patients’ characteristics at diagnosis and to identify risk features for the development of late complications; for this a machine learning approach involving correlation networks and decision trees analyses was applied.
Results : A total of 358 patients, 340 type 1 Gaucher disease and 18 type 3 cases were selected. 18% were splenectomyzed and 39% had advanced bone disease. 81% of cases carried heterozygous genotype. 47% of them were diagnosed before the year 2000. Mean age at diagnosis and therapy were 28 and 31.5 years old (y.o.) respectively. 4% developed monoclonal gammopathy undetermined significance or Parkinson Disease, 6% cancer, and 10% died before this study. Previous splenectomy correlates with the development of skeletal complications and severe bone disease (p=0.005); serum levels of IgA, delayed age at start therapy (>9.5 y.o. since diagnosis) also correlates with severe bone disease at diagnosis and with the incidence of bone crisis during therapy. High IgG (>1750mg/dL) levels and age over 60 y.o. at diagnosis were found to be related with the development of cancer. When modelling the decision tree, patients with a delayed diagnosis and therapy were the most severe and with higher risk of complications.
Conclusions : Our work confirms previous observations, highlights the importance of early diagnosis and therapy and identifies new risk features such as high IgA and IgG levels for long-term complications.
Keywords
Gaucher Disease, Machine Learning, Bone Crisis, Neoplasia, ERT
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CURRENT STATUS: Published
Version 2
Posted 17 Aug, 2020
Published
On 22 Sep, 2020
No community comments so far
Editorial decision: Accept
On 22 Aug, 2020
Reviewer #2 agreed
On 18 Aug, 2020
Review #2 received
Received 18 Aug, 2020
Reviewers invited
Invitations sent on 17 Aug, 2020
Reviewer #1 agreed
On 17 Aug, 2020
Review #1 received
Received 17 Aug, 2020
Editor assigned
On 13 Aug, 2020
Submission checks complete
On 12 Aug, 2020
Editor invited
On 12 Aug, 2020
No comments provided
Editorial decision: Major revision
On 02 Aug, 2020
Review #2 received
Received 29 Jul, 2020
Reviewer #2 agreed
On 16 Jul, 2020
Reviewers invited
Invitations sent on 13 Jul, 2020
Reviewer #1 agreed
On 13 Jul, 2020
Review #1 received
Received 13 Jul, 2020
Editor assigned
On 12 Jul, 2020
Submission checks complete
On 11 Jul, 2020
Editor invited
On 11 Jul, 2020
First submitted
On 10 Jul, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
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This preprint is under consideration at Orphanet Journal of Rare Diseases. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research
Identification of risk features for complication in Gaucher’s Disease patients: A Machine Learning analysis of the Spanish Registry of Gaucher Disease.
Pilar Giraldo
CIBERER and Instituto Investigación Sanitaria Aragon (IIS Aragon)
Corresponding Author
ORCiD: https://orcid.org/0000-0002-8791-1901
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
Version 2
Posted 17 Aug, 2020
Published
On 22 Sep, 2020
No community comments so far
Editorial decision: Accept
On 22 Aug, 2020
Reviewer #2 agreed
On 18 Aug, 2020
Review #2 received
Received 18 Aug, 2020
Reviewers invited
Invitations sent on 17 Aug, 2020
Reviewer #1 agreed
On 17 Aug, 2020
Review #1 received
Received 17 Aug, 2020
Editor assigned
On 13 Aug, 2020
Submission checks complete
On 12 Aug, 2020
Editor invited
On 12 Aug, 2020
No comments provided
Editorial decision: Major revision
On 02 Aug, 2020
Review #2 received
Received 29 Jul, 2020
Reviewer #2 agreed
On 16 Jul, 2020
Reviewers invited
Invitations sent on 13 Jul, 2020
Reviewer #1 agreed
On 13 Jul, 2020
Review #1 received
Received 13 Jul, 2020
Editor assigned
On 12 Jul, 2020
Submission checks complete
On 11 Jul, 2020
Editor invited
On 11 Jul, 2020
First submitted
On 10 Jul, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published version at Orphanet Journal of Rare Diseases.
Background : Since enzyme replacement therapy for Gaucher disease (MIM#230800) has become available, both awareness of and the natural history of the disease have changed. However, there remain unmet needs such as the identification of patients at risk of developing bone crisis during therapy and late complications such as cancer or parkinsonism. The Spanish Gaucher Disease Registry has worked since 1993 to compile demographic, clinical, genetic, analytical, imaging and follow-up data from more than 400 patients. The aims of this study were to discover correlations between patients’ characteristics at diagnosis and to identify risk features for the development of late complications; for this a machine learning approach involving correlation networks and decision trees analyses was applied.
Results : A total of 358 patients, 340 type 1 Gaucher disease and 18 type 3 cases were selected. 18% were splenectomyzed and 39% had advanced bone disease. 81% of cases carried heterozygous genotype. 47% of them were diagnosed before the year 2000. Mean age at diagnosis and therapy were 28 and 31.5 years old (y.o.) respectively. 4% developed monoclonal gammopathy undetermined significance or Parkinson Disease, 6% cancer, and 10% died before this study. Previous splenectomy correlates with the development of skeletal complications and severe bone disease (p=0.005); serum levels of IgA, delayed age at start therapy (>9.5 y.o. since diagnosis) also correlates with severe bone disease at diagnosis and with the incidence of bone crisis during therapy. High IgG (>1750mg/dL) levels and age over 60 y.o. at diagnosis were found to be related with the development of cancer. When modelling the decision tree, patients with a delayed diagnosis and therapy were the most severe and with higher risk of complications.
Conclusions : Our work confirms previous observations, highlights the importance of early diagnosis and therapy and identifies new risk features such as high IgA and IgG levels for long-term complications.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5