Immature platelet fraction based diagnostic predictive scoring model for immune thrombocytopenia

Abstract

Background/aims: The diagnosis of immune thrombocytopenia (ITP) is based on clinical manifestations and there is no gold standard. Thus, even hematologic malignancy is sometimes misdiagnosed as ITP and adequate treatment is delayed. Therefore, novel diagnostic parameters are needed to distinguish ITP from other causes of thrombocytopenia. Immature platelet fraction (IPF) has been proposed as one of new parameters. In this study, we assessed the usefulness of IPF and developed a diagnostic predictive scoring model for ITP.

Methods: We retrospectively studied 568 patients with thrombocytopenia. Blood samples were collected and IPF quantified using a fully-automated hematology analyzer. We also estimated other variables that could affect thrombocytopenia by logistic regression analysis.

Results: The median IPF was significantly higher in the ITP group than in the non-ITP group (8.7% vs. 5.1%). The optimal cut-off value of IPF for differentiating ITP was 7.0%. We evaluated other laboratory variables via logistic regression analysis. IPF, hemoglobin, lactate dehydrogenase (LDH), and ferritin were statistically significant and comprised a diagnostic predictive scoring model. Our model gave points to each of variables: 1 to high hemoglobin (> 12 g/dL), low ferritin (≤ 177 ng/ mL), normal LDH (≤ upper limit of normal) and IPF ≥ 7 and < 10, 2 to IPF ≥ 10. The final score was obtained by summing the points. We defined that ITP could be predicted in patients with more than 3 points.

Conclusion: IPF could be a useful parameter to distinguish ITP from other causes of thrombocytopenia. We developed the predictive scoring model. This model could predict ITP with high probability.

Keywords: Immature platelet fraction; Immune thrombocytopenia; Thrombocytopenia.

Figure 1.

(A) Receiver-operating characteristic (ROC) curve of immature platelet fraction (IPF) in the immune thrombocytopenic purpura (ITP) group and non-ITP group. The optimal cut-off value of IPF (%) for differentiating ITP was 7.0% with a sensitivity of 61% and specificity of 70%. (B) ROC curve of IPF in the ITP group and non-ITP subgroups of patients subjected to a bone marrow examination. The optimal cut-off value was 7.8%, with a sensitivity of 75% and a specificity of 76.7%. The median IPF was higher in this subgroup and the sensitivity and specificity of the cut-off value were also higher than the former group.

Figure 2.

Receiver-operating characteristic (ROC) curve of immature platelet fraction (IPF), hemoglobin, lactate dehydrogenase (LDH), and ferritin. We determined an optimal cut-off value using ROC curve analysis. The optimal cut-off values were 7%, 12 g/dL, 420 IU/L, and 177 mg/mL, respectively (p < 0.001, p < 0.001, p = 0.047, and p = 0.001, respectively).