Abstract Number: PB1871
Meeting: ISTH 2020 Congress
Background: Acquired thrombotic thrombocytopenic purpura (TTP) is a rare and life-threatening hematologic emergency. Despite proven efficacy of therapeutic plasma exchange plus corticosteroids, a considerable number of patients remain refractory to this treatment and require early intensive therapy. However, a method for the early identification of refractory TTP is not available.
Aims: To develop and validate a model for predicting the probability of refractory TTP.
Methods: The model was based on 265 acquired TTP patients with severe ADAMTS13 deficiency from 17 different tertiary medical centers between Jan 2009 and Nov 2019 in China. They covered four main Chinese geographic regions: Northern China, Eastern China, Middle & Western China and Southern China. We externally validated the model by geographical validation.
Results: In the multivariable logistic analysis of derivation cohort, three candidate predictors entered the final prediction model: age ≥ 45 years, hemoglobin < 60 g/L and creatinine ≥ 106 µmol/l. It was named AHC on the basis of the first letters of the included parameters. We assigned point values to these items according to the β coefficient obtained from the multivariable regression (table 1). We defined three categories of risk for refractoriness: an AHC score of 0 denoted low risk, a score of 1 or 2 denoted intermediate risk, and a score of 3-5 denoted high risk. There was increasing risk of refractory TTP with increasing AHC risk group (figure 1). AHC model had an AUC of 0.862 (95% CI 0.643-0.943) in the internal validation cohort and 0.818 (95% CI 0.611-0.947) in the external validation cohort. The calibration plots showed a high agreement between the predicted and observed probability.
Conclusions: We developed and validated an accurate prediction model for the early identification of refractory TTP at diagnosis. The AHC model contributes to guide tailored therapy and is a step towards more personalized medicine.
|β||SE||OR (95%CI)||P value||Points|
|Age ≥ 45 (years)||3.79||1.15||44.24 (4.63, 422.61)||0.001||2|
|Hemoglobin < 60 (g/L)||3.89||1.11||48.73 (5.49, 432.59)||<0.001||2|
|Creatinine ≥ 106 (µmol/L)||2.09||0.71||8.12 (2.04, 32.41)||0.003||1|
[Table 1. Multivariable logistic regression model of the predictors of refractory TTP]
To cite this abstract in AMA style:Huang Q-, Gui R-, Liu Y, Liu H, Fang M-, Yang L-, Zhang J-, Cheng Y-, Jiang M, Mao M, Wang L-, Wang Z, Zhou H-, Lan H, Jiang Z-, Shen X-, Zhang L, Fan S-, Huang X-, Zhang X-. Development and Validation of a Prediction Model (AHC) for Early Identification of Refractory Thrombotic Thrombocytopenic Purpura Using Nationally Representative Data [abstract]. Res Pract Thromb Haemost. 2020; 4 (Suppl 1). https://abstracts.isth.org/abstract/development-and-validation-of-a-prediction-model-ahc-for-early-identification-of-refractory-thrombotic-thrombocytopenic-purpura-using-nationally-representative-data/. Accessed January 28, 2022.
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