Contributions
Abstract: EP1726
Type: ePoster
Abstract Category: Therapy - disease modifying - 29 Risk management for disease modifying treatments
Background: Patient support programs (PSPs) contribute to the adherence to prescribed multiple sclerosis (MS) therapies. Beside therapy-dependent side effects, conscious and unconscious factors as well as personal circumstances are crucial for therapy adherence. By considering these aspects, PSPs for three disease-modifying therapies (DMTs) were established. The aim of this analysis is to evaluate the benefit of patient classification by risk factors to favour adherence through an individualized coaching.
Methods: From February 2014 dimethyl fumarate (DMF), September 2014 peginterferon beta-1a (PEG) and August 2016 daclizumab beta (DAC BETA) patients were recruited and signed a written consent form. Each PSP considers potential adherence barriers for instance prior therapies and personal circumstances. At therapy start patients were stratified into subgroups displaying high, medium and low risk for non-adherence. Contents and frequency were adapted according to expected challenges and patient needs.
Results: As of April 2017, 16480 patients taking any of the three DMTs were recruited. 4871, 2842 and 117 patients were stratified for DMF, PEG and DAC BETA, respectively, according to individual adherence risks. DMF patients were stratified at therapy start into high (24.2%), medium (34.4%) and low (41.0%) adherence subgroups. PEG patients were categorized by cumulative adherence risks into five subgroups from 1 for high up to 5 for low adherence (14.2%, 42.4%, 40.8%, 2.2%, 0.4%). Non-adherence was measured by therapy discontinuation and analyzed. For DMF and PEG dropout rates correlated with assessed adherence risks. After one year DMF therapy discontinuation was 16.5%, 20.9% and 24.7% for high, medium and low adherence subtypes, respectively. PEG subgroups also demonstrated more susceptibility for therapy discontinuation depending on the present adherence risks. One year dropout rates were 15.2%, 19.9%, 23.6%, 43.8% and 45.5% for patient subtypes 1, 2, 3, 4 and 5. For DMF, adherence subtypes were re-classified after 1 year of appropriate coaching displaying a shift of the number of patients from low to the high adherence subtype.
Conclusion: Present data demonstrate that patient stratification based on identified risk factors can predict non-adherence. In turn, subtyping of patients can be useful to provide an adjusted support according to patient needs. Risk-adopted, individualized coaching is suitable to reduce adherence barriers and to promote adherence.
Disclosure:
JA: received funding for medical writing.
YBN: received funding for medical writing.
GN and BS: employees of and hold stock/stock options in Biogen.
MM: received honoraria from Biogen, Boehringer Ingelheim, Bayer Healthcare, Merck Serono, Genzyme, Sanofi Aventis, Talecris, Teva, Novartis.
Abstract: EP1726
Type: ePoster
Abstract Category: Therapy - disease modifying - 29 Risk management for disease modifying treatments
Background: Patient support programs (PSPs) contribute to the adherence to prescribed multiple sclerosis (MS) therapies. Beside therapy-dependent side effects, conscious and unconscious factors as well as personal circumstances are crucial for therapy adherence. By considering these aspects, PSPs for three disease-modifying therapies (DMTs) were established. The aim of this analysis is to evaluate the benefit of patient classification by risk factors to favour adherence through an individualized coaching.
Methods: From February 2014 dimethyl fumarate (DMF), September 2014 peginterferon beta-1a (PEG) and August 2016 daclizumab beta (DAC BETA) patients were recruited and signed a written consent form. Each PSP considers potential adherence barriers for instance prior therapies and personal circumstances. At therapy start patients were stratified into subgroups displaying high, medium and low risk for non-adherence. Contents and frequency were adapted according to expected challenges and patient needs.
Results: As of April 2017, 16480 patients taking any of the three DMTs were recruited. 4871, 2842 and 117 patients were stratified for DMF, PEG and DAC BETA, respectively, according to individual adherence risks. DMF patients were stratified at therapy start into high (24.2%), medium (34.4%) and low (41.0%) adherence subgroups. PEG patients were categorized by cumulative adherence risks into five subgroups from 1 for high up to 5 for low adherence (14.2%, 42.4%, 40.8%, 2.2%, 0.4%). Non-adherence was measured by therapy discontinuation and analyzed. For DMF and PEG dropout rates correlated with assessed adherence risks. After one year DMF therapy discontinuation was 16.5%, 20.9% and 24.7% for high, medium and low adherence subtypes, respectively. PEG subgroups also demonstrated more susceptibility for therapy discontinuation depending on the present adherence risks. One year dropout rates were 15.2%, 19.9%, 23.6%, 43.8% and 45.5% for patient subtypes 1, 2, 3, 4 and 5. For DMF, adherence subtypes were re-classified after 1 year of appropriate coaching displaying a shift of the number of patients from low to the high adherence subtype.
Conclusion: Present data demonstrate that patient stratification based on identified risk factors can predict non-adherence. In turn, subtyping of patients can be useful to provide an adjusted support according to patient needs. Risk-adopted, individualized coaching is suitable to reduce adherence barriers and to promote adherence.
Disclosure:
JA: received funding for medical writing.
YBN: received funding for medical writing.
GN and BS: employees of and hold stock/stock options in Biogen.
MM: received honoraria from Biogen, Boehringer Ingelheim, Bayer Healthcare, Merck Serono, Genzyme, Sanofi Aventis, Talecris, Teva, Novartis.