PREDICTION OF INHIBITORS IN UKRAINIAN HAEMOPHILIA PATIENTS
(Abstract release date: 05/19/16)
EHA Library. Stasyshyn O. 06/09/16; 132545; E996
Assoc. Prof. Oleksandra Stasyshyn
Contributions
Contributions
Abstract
Abstract: E996
Type: Eposter Presentation
Background
Replacement therapy in hemophilia patients (pts) is complicated by the factor VIII (IX) inhibitors among 30% of hemophilia A pts and 3-5% of hemophilia B pts. The treatment of bleeding and elimination of inhibitors is complicated, costly and not always successful.
Aims
To develop a simple score that stratifies hemophilia pts according to their risk of developing inhibitors.
Methods
135 pts with hemophilia A and B was divided into two groups: I -74 pts with inhibitor and II –61 pts without inhibitor. We analyzed 16 risk factors to develop inhibitor: type of hemophilia (A or B), severity, age, age at diagnosis, hereditary or sporadic, family history of inhibitors, intensive treatment at initial treatment- days of exposure (ED) /1 episode), age at first exposure to FVIII/IX, reason for first treatment with FVIII, FVIII/IX product type, prophylaxis or “on demand” treatment, factor concentrate switching, significant and life-threatening bleeding localization; surgery: I – urgent or selective; II - major or minor, the purulent complications. To examine the relationship between risk factors and the likelihood of inhibitor development, we used regression models of discrete choice. Specifically, we estimate the range of one factor binomial choice models to study the individual effects of each factor on the probability of inhibitor development. In addition, we analyze the joint impact of risk factors using multiple logit regression that allows to explore the effects and importance of each factor, controlling for the presence of other factors. Adequacy of logit models was conducted using chi-square test, and the significance of regression coefficients was based on Student Wald statistics. Finally, we calculated the theoretical values of probability of an inhibitor development for each patient and ranges (95% CI) of predicted risk of inhibitor development in pts with the value of the dependent variable “yes” and “no”.
Results
The first model includes the following factors: age, clotting factor concentrate switching, FVIII/IX product type, purulent complications and the number of ED / 1 episode of bleeding. At 5% significance level, the type of surgery (minor/major) as well as positive 'inhibitory' history are added. At the 10% significance level, the model additionally contains a variable characterizing the urgency of surgery (urgent or planned). In this approach, the factors that determine the type of hemophilia, age, diagnosis and life-threatening bleeding are not significant and therefore, we do not include them in the final multivariate regression. The number ED / 1 episode has the highest impact on the probability of inhibitor development: if it increases, the likelihood of inhibitor development increases by 27%. For patients who changed the type of concentrates, the likelihood of inhibitor development increases by 23%. The effect of the FVIII/IX product type, the age and the type of the surgery - is negative and significant, while purulent complications and 'inhibitory' history result in the increase in the likelihood of inhibitor development by 21% and 12%, respectively. This multivariate logit model allows to predict the likelihood of developing an inhibitor for a pts based on the information about the values of each of these factors.
Conclusion
According to our model, the factors associated with treatment have the highest impact on the probability of inhibitor development. Based on the results, reducing the frequency of inhibitors can be achieved by changing the approaches to the treatment of pts with hemophilia.
Session topic: E-poster
Keyword(s): Hemophilia, Inhibitor, Prognosis, Risk factor
Type: Eposter Presentation
Background
Replacement therapy in hemophilia patients (pts) is complicated by the factor VIII (IX) inhibitors among 30% of hemophilia A pts and 3-5% of hemophilia B pts. The treatment of bleeding and elimination of inhibitors is complicated, costly and not always successful.
Aims
To develop a simple score that stratifies hemophilia pts according to their risk of developing inhibitors.
Methods
135 pts with hemophilia A and B was divided into two groups: I -74 pts with inhibitor and II –61 pts without inhibitor. We analyzed 16 risk factors to develop inhibitor: type of hemophilia (A or B), severity, age, age at diagnosis, hereditary or sporadic, family history of inhibitors, intensive treatment at initial treatment- days of exposure (ED) /1 episode), age at first exposure to FVIII/IX, reason for first treatment with FVIII, FVIII/IX product type, prophylaxis or “on demand” treatment, factor concentrate switching, significant and life-threatening bleeding localization; surgery: I – urgent or selective; II - major or minor, the purulent complications. To examine the relationship between risk factors and the likelihood of inhibitor development, we used regression models of discrete choice. Specifically, we estimate the range of one factor binomial choice models to study the individual effects of each factor on the probability of inhibitor development. In addition, we analyze the joint impact of risk factors using multiple logit regression that allows to explore the effects and importance of each factor, controlling for the presence of other factors. Adequacy of logit models was conducted using chi-square test, and the significance of regression coefficients was based on Student Wald statistics. Finally, we calculated the theoretical values of probability of an inhibitor development for each patient and ranges (95% CI) of predicted risk of inhibitor development in pts with the value of the dependent variable “yes” and “no”.
Results
The first model includes the following factors: age, clotting factor concentrate switching, FVIII/IX product type, purulent complications and the number of ED / 1 episode of bleeding. At 5% significance level, the type of surgery (minor/major) as well as positive 'inhibitory' history are added. At the 10% significance level, the model additionally contains a variable characterizing the urgency of surgery (urgent or planned). In this approach, the factors that determine the type of hemophilia, age, diagnosis and life-threatening bleeding are not significant and therefore, we do not include them in the final multivariate regression. The number ED / 1 episode has the highest impact on the probability of inhibitor development: if it increases, the likelihood of inhibitor development increases by 27%. For patients who changed the type of concentrates, the likelihood of inhibitor development increases by 23%. The effect of the FVIII/IX product type, the age and the type of the surgery - is negative and significant, while purulent complications and 'inhibitory' history result in the increase in the likelihood of inhibitor development by 21% and 12%, respectively. This multivariate logit model allows to predict the likelihood of developing an inhibitor for a pts based on the information about the values of each of these factors.
Conclusion
According to our model, the factors associated with treatment have the highest impact on the probability of inhibitor development. Based on the results, reducing the frequency of inhibitors can be achieved by changing the approaches to the treatment of pts with hemophilia.
Session topic: E-poster
Keyword(s): Hemophilia, Inhibitor, Prognosis, Risk factor
Abstract: E996
Type: Eposter Presentation
Background
Replacement therapy in hemophilia patients (pts) is complicated by the factor VIII (IX) inhibitors among 30% of hemophilia A pts and 3-5% of hemophilia B pts. The treatment of bleeding and elimination of inhibitors is complicated, costly and not always successful.
Aims
To develop a simple score that stratifies hemophilia pts according to their risk of developing inhibitors.
Methods
135 pts with hemophilia A and B was divided into two groups: I -74 pts with inhibitor and II –61 pts without inhibitor. We analyzed 16 risk factors to develop inhibitor: type of hemophilia (A or B), severity, age, age at diagnosis, hereditary or sporadic, family history of inhibitors, intensive treatment at initial treatment- days of exposure (ED) /1 episode), age at first exposure to FVIII/IX, reason for first treatment with FVIII, FVIII/IX product type, prophylaxis or “on demand” treatment, factor concentrate switching, significant and life-threatening bleeding localization; surgery: I – urgent or selective; II - major or minor, the purulent complications. To examine the relationship between risk factors and the likelihood of inhibitor development, we used regression models of discrete choice. Specifically, we estimate the range of one factor binomial choice models to study the individual effects of each factor on the probability of inhibitor development. In addition, we analyze the joint impact of risk factors using multiple logit regression that allows to explore the effects and importance of each factor, controlling for the presence of other factors. Adequacy of logit models was conducted using chi-square test, and the significance of regression coefficients was based on Student Wald statistics. Finally, we calculated the theoretical values of probability of an inhibitor development for each patient and ranges (95% CI) of predicted risk of inhibitor development in pts with the value of the dependent variable “yes” and “no”.
Results
The first model includes the following factors: age, clotting factor concentrate switching, FVIII/IX product type, purulent complications and the number of ED / 1 episode of bleeding. At 5% significance level, the type of surgery (minor/major) as well as positive 'inhibitory' history are added. At the 10% significance level, the model additionally contains a variable characterizing the urgency of surgery (urgent or planned). In this approach, the factors that determine the type of hemophilia, age, diagnosis and life-threatening bleeding are not significant and therefore, we do not include them in the final multivariate regression. The number ED / 1 episode has the highest impact on the probability of inhibitor development: if it increases, the likelihood of inhibitor development increases by 27%. For patients who changed the type of concentrates, the likelihood of inhibitor development increases by 23%. The effect of the FVIII/IX product type, the age and the type of the surgery - is negative and significant, while purulent complications and 'inhibitory' history result in the increase in the likelihood of inhibitor development by 21% and 12%, respectively. This multivariate logit model allows to predict the likelihood of developing an inhibitor for a pts based on the information about the values of each of these factors.
Conclusion
According to our model, the factors associated with treatment have the highest impact on the probability of inhibitor development. Based on the results, reducing the frequency of inhibitors can be achieved by changing the approaches to the treatment of pts with hemophilia.
Session topic: E-poster
Keyword(s): Hemophilia, Inhibitor, Prognosis, Risk factor
Type: Eposter Presentation
Background
Replacement therapy in hemophilia patients (pts) is complicated by the factor VIII (IX) inhibitors among 30% of hemophilia A pts and 3-5% of hemophilia B pts. The treatment of bleeding and elimination of inhibitors is complicated, costly and not always successful.
Aims
To develop a simple score that stratifies hemophilia pts according to their risk of developing inhibitors.
Methods
135 pts with hemophilia A and B was divided into two groups: I -74 pts with inhibitor and II –61 pts without inhibitor. We analyzed 16 risk factors to develop inhibitor: type of hemophilia (A or B), severity, age, age at diagnosis, hereditary or sporadic, family history of inhibitors, intensive treatment at initial treatment- days of exposure (ED) /1 episode), age at first exposure to FVIII/IX, reason for first treatment with FVIII, FVIII/IX product type, prophylaxis or “on demand” treatment, factor concentrate switching, significant and life-threatening bleeding localization; surgery: I – urgent or selective; II - major or minor, the purulent complications. To examine the relationship between risk factors and the likelihood of inhibitor development, we used regression models of discrete choice. Specifically, we estimate the range of one factor binomial choice models to study the individual effects of each factor on the probability of inhibitor development. In addition, we analyze the joint impact of risk factors using multiple logit regression that allows to explore the effects and importance of each factor, controlling for the presence of other factors. Adequacy of logit models was conducted using chi-square test, and the significance of regression coefficients was based on Student Wald statistics. Finally, we calculated the theoretical values of probability of an inhibitor development for each patient and ranges (95% CI) of predicted risk of inhibitor development in pts with the value of the dependent variable “yes” and “no”.
Results
The first model includes the following factors: age, clotting factor concentrate switching, FVIII/IX product type, purulent complications and the number of ED / 1 episode of bleeding. At 5% significance level, the type of surgery (minor/major) as well as positive 'inhibitory' history are added. At the 10% significance level, the model additionally contains a variable characterizing the urgency of surgery (urgent or planned). In this approach, the factors that determine the type of hemophilia, age, diagnosis and life-threatening bleeding are not significant and therefore, we do not include them in the final multivariate regression. The number ED / 1 episode has the highest impact on the probability of inhibitor development: if it increases, the likelihood of inhibitor development increases by 27%. For patients who changed the type of concentrates, the likelihood of inhibitor development increases by 23%. The effect of the FVIII/IX product type, the age and the type of the surgery - is negative and significant, while purulent complications and 'inhibitory' history result in the increase in the likelihood of inhibitor development by 21% and 12%, respectively. This multivariate logit model allows to predict the likelihood of developing an inhibitor for a pts based on the information about the values of each of these factors.
Conclusion
According to our model, the factors associated with treatment have the highest impact on the probability of inhibitor development. Based on the results, reducing the frequency of inhibitors can be achieved by changing the approaches to the treatment of pts with hemophilia.
Session topic: E-poster
Keyword(s): Hemophilia, Inhibitor, Prognosis, Risk factor
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