A highly accurate prediction model was developed and validated to determine the probability of refractory immune-mediated thrombotic thrombocytopenic purpura (iTTP) in adults with acquired iTTP, according to research presented in the British Journal of Haematology.
According to the researchers, some patients with iTTP are refractory to treatments such as corticosteroids and therapeutic plasma exchange, and may need intensive therapy. They noted that early identification of refractory iTTP may be critical in order to guide management of the condition.
Development of the predictive tool for probability of refractory iTTP involved the retrospective use of clinical data from 134 patients with iTTP and severe ADAMTS13 deficiency who were treated across 17 medical centers in China. For model development and testing, 94 patients were assigned to a derivation cohort, and 40 patients formed a validation cohort. The researchers used a backward stepwise logistic regression analysis in generating the model.
Six variables had significant associations with refractory iTTP in their model: age, hemoglobin level, presence of fever, acute kidney injury, serum creatinine level, and international normalized ratio.
Ultimately, 3 variables appeared to be significant predictors of refractory iTTP, and these were included in the model. These predictors were age (odds ratio [OR], 1.107; 95% CI, 1.049-1.167; P <.001), hemoglobin level (OR, 0.948; 95% CI, 0.913-0.984; P =.005), and serum creatinine level (OR, 1.027; 95% CI, 1.006-1.049; P =.011). Employing these 3 predictors in the model, the researchers derived a predictive score called the AHC.
The authors reported that the area under the curve for this model when applied to the derivation cohort was 0.886 (95% CI, 0.679-0.974) and it was 0.862 (95% CI, 0.625-0.999) when applied to the validation cohort.
“In conclusion, we have developed and validated a reliable prediction model, the AHC, to accurately assess the probability of refractory iTTP before treatment in adult patients with acquired iTTP and identify patients with a high risk of adverse outcomes,” wrote the investigators.
Gui R-Y, Huang Q-S, Cai X, et al. Development and validation of a prediction model (AHC) for early identification of refractory thrombotic thrombocytopenic purpura using nationally representative data [published online May 26, 2020]. Br J Haematol. doi: 10.1111/bjh.16767