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Development of a clinical calculator to aid the identification of MODY in pediatric patients at the time of diabetes diagnosis

Shields, Beverley M. ; Carlsson, Annelie LU orcid ; Patel, Kashyap ; Knupp, Julieanne ; Kaur, Akaal ; Johnston, Des ; Colclough, Kevin ; Larsson, Helena Elding LU ; Forsander, Gun and Samuelsson, Ulf , et al. (2024) In Scientific Reports 14(1).
Abstract

Maturity Onset Diabetes of the Young (MODY) is a young-onset, monogenic form of diabetes without needing insulin treatment. Diagnostic testing is expensive. To aid decisions on who to test, we aimed to develop a MODY probability calculator for paediatric cases at the time of diabetes diagnosis, when the existing “MODY calculator” cannot be used. Firth logistic regression models were developed on data from 3541 paediatric patients from the Swedish ‘Better Diabetes Diagnosis’ (BDD) population study (n = 46 (1.3%) MODY (HNF1A, HNF4A, GCK)). Model performance was compared to using islet autoantibody testing. HbA1c, parent with diabetes, and absence of polyuria were significant independent predictors of MODY. The model showed excellent... (More)

Maturity Onset Diabetes of the Young (MODY) is a young-onset, monogenic form of diabetes without needing insulin treatment. Diagnostic testing is expensive. To aid decisions on who to test, we aimed to develop a MODY probability calculator for paediatric cases at the time of diabetes diagnosis, when the existing “MODY calculator” cannot be used. Firth logistic regression models were developed on data from 3541 paediatric patients from the Swedish ‘Better Diabetes Diagnosis’ (BDD) population study (n = 46 (1.3%) MODY (HNF1A, HNF4A, GCK)). Model performance was compared to using islet autoantibody testing. HbA1c, parent with diabetes, and absence of polyuria were significant independent predictors of MODY. The model showed excellent discrimination (c-statistic = 0.963) and calibrated well (Brier score = 0.01). MODY probability > 1.3% (ie. above background prevalence) had similar performance to being negative for all 3 antibodies (positive predictive value (PPV) = 10% v 11% respectively i.e. ~ 1 in 10 positive test rate). Probability > 1.3% and negative for 3 islet autoantibodies narrowed down to 4% of the cohort, and detected 96% of MODY cases (PPV = 31%). This MODY calculator for paediatric patients at time of diabetes diagnosis will help target genetic testing to those most likely to benefit, to get the right diagnosis.

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organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Scientific Reports
volume
14
issue
1
article number
10589
publisher
Nature Publishing Group
external identifiers
  • scopus:85192520662
  • pmid:38719926
ISSN
2045-2322
DOI
10.1038/s41598-024-60160-0
language
English
LU publication?
yes
id
cbda3673-02ad-4e33-867d-95f7ea95a03d
date added to LUP
2024-05-22 15:39:14
date last changed
2024-06-19 17:22:37
@article{cbda3673-02ad-4e33-867d-95f7ea95a03d,
  abstract     = {{<p>Maturity Onset Diabetes of the Young (MODY) is a young-onset, monogenic form of diabetes without needing insulin treatment. Diagnostic testing is expensive. To aid decisions on who to test, we aimed to develop a MODY probability calculator for paediatric cases at the time of diabetes diagnosis, when the existing “MODY calculator” cannot be used. Firth logistic regression models were developed on data from 3541 paediatric patients from the Swedish ‘Better Diabetes Diagnosis’ (BDD) population study (n = 46 (1.3%) MODY (HNF1A, HNF4A, GCK)). Model performance was compared to using islet autoantibody testing. HbA1c, parent with diabetes, and absence of polyuria were significant independent predictors of MODY. The model showed excellent discrimination (c-statistic = 0.963) and calibrated well (Brier score = 0.01). MODY probability &gt; 1.3% (ie. above background prevalence) had similar performance to being negative for all 3 antibodies (positive predictive value (PPV) = 10% v 11% respectively i.e. ~ 1 in 10 positive test rate). Probability &gt; 1.3% and negative for 3 islet autoantibodies narrowed down to 4% of the cohort, and detected 96% of MODY cases (PPV = 31%). This MODY calculator for paediatric patients at time of diabetes diagnosis will help target genetic testing to those most likely to benefit, to get the right diagnosis.</p>}},
  author       = {{Shields, Beverley M. and Carlsson, Annelie and Patel, Kashyap and Knupp, Julieanne and Kaur, Akaal and Johnston, Des and Colclough, Kevin and Larsson, Helena Elding and Forsander, Gun and Samuelsson, Ulf and Hattersley, Andrew and Ludvigsson, Johnny}},
  issn         = {{2045-2322}},
  language     = {{eng}},
  number       = {{1}},
  publisher    = {{Nature Publishing Group}},
  series       = {{Scientific Reports}},
  title        = {{Development of a clinical calculator to aid the identification of MODY in pediatric patients at the time of diabetes diagnosis}},
  url          = {{http://dx.doi.org/10.1038/s41598-024-60160-0}},
  doi          = {{10.1038/s41598-024-60160-0}},
  volume       = {{14}},
  year         = {{2024}},
}