Probability of inclusion | Coefficient from model | OR^{†} | P | |
---|---|---|---|---|

Onset age | 1.00 | β_{1} | 1.110 | <0.0001 |

Duration | 1.00 | β_{2} | 0.701 | <0.001 |

GRS | 0.80 | β_{3} | 0.748 | 0.061 |

Duration * IA–2A | 0.72 | β_{4} | 0.896 | 0.175 |

GRS * ZnT8A | 0.65 | β_{5} | 1.380 | 0.057 |

GADA | 0.58 | β_{6} | 1.230 | 0.128 |

Onset age * ZnT8A | 0.52 | β_{7} | 1.080 | <0.001 |

Duration * ZnT8A | 0.51 | β_{8} | 0.908 | 0.190 |

IA–2A | 0.47 | β_{9} | 1.680 | 0.041 |

ZnT8A | 0.39 | β_{10} | 0.625 | 0.198 |

Disease duration; onset age; GRS; titers for IA–2A, ZnT8A, and GADA; and all two-way interaction effects of predictor variables were tested for inclusion in the C-peptide model simultaneously with penalized logistic regression with repeated 10-fold cross validation for feature selection. The data set was repeatedly partitioned in half for training and testing, and the probability of each predictor (including all two-way interaction effects) being in the model was calculated over 1,000 iterations. All coefficients with at least 50% probability of inclusion and their main effects are reported. Interaction effects are denoted as two variables separated by an asterisk. The glmnet, version 3.0, package in R was used for penalized logistic regression and feature selection.

† Regression coefficients (β

_{i}) are reported in exponentiated form as ORs, such that OR = e^{β}. The coefficient values correspond to the β values from the overall model formula.