Contributions
Abstract: P760
Type: Poster
Abstract Category: Therapy - disease modifying - 29 Risk management for disease modifying treatments
Background: Patients with Multiple Sclerosis (MS) are faced with complex risk-benefit profiles of disease-modifying drugs (DMDs), often involving clinical trial data. Accurately understanding DMD information from clinical trials is necessary for effective decision-making and adherence.
Goal: To identify the most effective method of communicating clinical trial data to improve treatment understanding in MS patients.
Method: 45 relapsing-remitting MS patients (mean age: 46.76, 36 females) were presented with information from faux clinical trials (e.g. “150 patients taking drug A will experience risk B and 50 patients taking the placebo will experience risk B”). Clinical trial data were communicated using absolute terms (e.g. “100 more patients taking drug A will experience risk B”), relative terms (e.g. “2 times as many patients taking drug A will experience risk B”) and numbers needed to treat or harm (e.g. “10 patients would have to take drug A to experience risk B”).
Treatment understanding was recorded. Fatigue (FSS), depression and anxiety (HADS), numerical reasoning (VESPAR), pre-morbid IQ (WTAR); information processing speed, and verbal and visual memory (BICAMS), were also assessed.
Results: Understanding of treatment information was significantly affected by methods of communicating clinical trial data (two-way ANOVA, (F(2,88)=36.49, P< .001). Pairwise comparisons revealed greater understanding for clinical trial data presented in absolute terms compared to relative terms (t(44)=2.53, p< .05), and numbers needed to treat or harm (t(44)=2.58, p< .05). Adding background information about research patients in the treatment and placebo group improved understanding for all methods of presenting clinical trial data (F(1,44)=501.96, p< .001).
There were significant correlations between understanding of clinical trial data and numerical reasoning (r=.509, p< .001), pre-morbid IQ (r=.415, p< .001), information processing speed (r=.423, p< .01) and verbal memory (r=.409, p< .01).
Conclusion: Clinical trial data can be communicated more effectively to MS patients by using absolute terms. Cognitive factors can influence understanding of treatment information from clinical trials. Cognition should be assessed and accommodated as part of DMD education.
Disclosure:
GR nothing to disclose.
ES has acted as an advisor or received financial support for research and for educational purposes, and hospitality, from Merck-Serono, Biogen, TEVA, Bayer-Schering and Novartis; and through his NHS trust has also received financial support for projects/service developments from some of these companies. He has been an investigator in commercial trials sponsored by Biogen Idec, Novartis, TEVA, Receptos, Roche, GW Pharma and GSK.
DL has participated on advisory boards/received consultancy/research grants or is in the speaker Bureau for: Bayer, Novartis, Teva, Excemed, Roche, Merck and Biogen.
This study was supported by an investigator initiated research grant from Biogen. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of this abstract.
Abstract: P760
Type: Poster
Abstract Category: Therapy - disease modifying - 29 Risk management for disease modifying treatments
Background: Patients with Multiple Sclerosis (MS) are faced with complex risk-benefit profiles of disease-modifying drugs (DMDs), often involving clinical trial data. Accurately understanding DMD information from clinical trials is necessary for effective decision-making and adherence.
Goal: To identify the most effective method of communicating clinical trial data to improve treatment understanding in MS patients.
Method: 45 relapsing-remitting MS patients (mean age: 46.76, 36 females) were presented with information from faux clinical trials (e.g. “150 patients taking drug A will experience risk B and 50 patients taking the placebo will experience risk B”). Clinical trial data were communicated using absolute terms (e.g. “100 more patients taking drug A will experience risk B”), relative terms (e.g. “2 times as many patients taking drug A will experience risk B”) and numbers needed to treat or harm (e.g. “10 patients would have to take drug A to experience risk B”).
Treatment understanding was recorded. Fatigue (FSS), depression and anxiety (HADS), numerical reasoning (VESPAR), pre-morbid IQ (WTAR); information processing speed, and verbal and visual memory (BICAMS), were also assessed.
Results: Understanding of treatment information was significantly affected by methods of communicating clinical trial data (two-way ANOVA, (F(2,88)=36.49, P< .001). Pairwise comparisons revealed greater understanding for clinical trial data presented in absolute terms compared to relative terms (t(44)=2.53, p< .05), and numbers needed to treat or harm (t(44)=2.58, p< .05). Adding background information about research patients in the treatment and placebo group improved understanding for all methods of presenting clinical trial data (F(1,44)=501.96, p< .001).
There were significant correlations between understanding of clinical trial data and numerical reasoning (r=.509, p< .001), pre-morbid IQ (r=.415, p< .001), information processing speed (r=.423, p< .01) and verbal memory (r=.409, p< .01).
Conclusion: Clinical trial data can be communicated more effectively to MS patients by using absolute terms. Cognitive factors can influence understanding of treatment information from clinical trials. Cognition should be assessed and accommodated as part of DMD education.
Disclosure:
GR nothing to disclose.
ES has acted as an advisor or received financial support for research and for educational purposes, and hospitality, from Merck-Serono, Biogen, TEVA, Bayer-Schering and Novartis; and through his NHS trust has also received financial support for projects/service developments from some of these companies. He has been an investigator in commercial trials sponsored by Biogen Idec, Novartis, TEVA, Receptos, Roche, GW Pharma and GSK.
DL has participated on advisory boards/received consultancy/research grants or is in the speaker Bureau for: Bayer, Novartis, Teva, Excemed, Roche, Merck and Biogen.
This study was supported by an investigator initiated research grant from Biogen. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of this abstract.