FLOODLIGHT: smartphone-based self-monitoring is accepted by patients and provides meaningful, continuous digital outcomes augmenting conventional in-clinic multiple sclerosis measures
Author(s): ,
X. Montalban
Affiliations:
Division of Neurology, University of Toronto, Toronto, ON, Canada; Vall d`Hebron University Hospital, Barcelona, Spain
,
P. Mulero
Affiliations:
Vall d`Hebron University Hospital, Barcelona, Spain
,
L. Midaglia
Affiliations:
Vall d`Hebron University Hospital, Barcelona, Spain
,
J. Graves
Affiliations:
University of California, San Francisco
,
S.L. Hauser
Affiliations:
University of California, San Francisco
,
L. Julian
Affiliations:
Genentech, Inc., South San Francisco, CA, United States
,
M. Baker
Affiliations:
F. Hoffmann-La Roche Ltd, Basel, Switzerland
,
J. Schadrack
Affiliations:
F. Hoffmann-La Roche Ltd, Basel, Switzerland
,
C. Gossens
Affiliations:
F. Hoffmann-La Roche Ltd, Basel, Switzerland
,
A. Scotland
Affiliations:
F. Hoffmann-La Roche Ltd, Basel, Switzerland
,
F. Lipsmeier
Affiliations:
F. Hoffmann-La Roche Ltd, Basel, Switzerland
,
C. Bernasconi
Affiliations:
F. Hoffmann-La Roche Ltd, Basel, Switzerland
,
S. Belachew
Affiliations:
F. Hoffmann-La Roche Ltd, Basel, Switzerland
M. Lindemann
Affiliations:
F. Hoffmann-La Roche Ltd, Basel, Switzerland; Baden-Wuerttemberg Cooperative State University, Loerrach, Germany
ECTRIMS Online Library. Montalban X. 10/10/18; 228468; P624
Xavier Montalban
Xavier Montalban
Contributions
Abstract

Abstract: P624

Type: Poster Sessions

Abstract Category: Therapy - Tools for detecting therapeutic response

Background: Sensor-based, active and passive smartphone-based self-monitoring (SSM) may be more sensitive and specific than periodic in-clinic assessments to measure progression in multiple sclerosis (MS).
Objective: To report an analysis of adherence, results from a patient satisfaction questionnaire and correlations between in-clinic tests and FLOODLIGHT SSM measures (NCT02952911).
Methods: Patients with MS (18-55 years; Expanded Disability Status Scale score 0-5.5; n=76) and healthy controls (n=25) received a preconfigured smartphone and smartwatch that prompt the user to perform the FLOODLIGHT SSM, comprising 'active tests' and 'passive monitoring' for 24 weeks. The primary analysis assessed participants' adherence (proportion of study weeks with at least 3 days of completed testing and at least 4 hours/day of passive monitoring) and patient satisfaction with the FLOODLIGHT SSM solution. In-clinic tests and brain MRI assessments were performed. Secondary analyses compared FLOODLIGHT SSM outcomes 1) between patients with MS and healthy controls and 2) with in-clinic outcomes in patients with MS. The correlation between FLOODLIGHT SSM outcomes and in-clinic tests was reported using Spearman's correlation coefficient (SCC).
Results: As of 4 May 2018, the interim analysis of adherence of 61 patients who completed the study showed 76.5% adherence to active tests and 83.2% to passive monitoring. Satisfaction amongst patients with MS who completed the study (n=61) was good to excellent (73.33 average score out of a possible 100 at termination visit). Correlations between FLOODLIGHT SSM and conventional in-clinic assessments at baseline (Spearman's rank correlation) were as follows: Correct responses from smartphone-based Symbol Digit Modalities Test (SDMT) vs oral SDMT: SCC=0.635, p< 0.001, n=53; Time between two consecutive pinch attempts in the FLOODLIGHT Pinching Test vs 9-Hole Peg Test: SCC=0.508, p< 0.001, n=54; Turning speed measured with the FLOODLIGHT Five-U-Turn Test vs Timed 25-Foot Walk test: SCC=-0.524, p< 0.001, n=55. Further comparisons between baseline FLOODLIGHT SSM and in-clinic testing MS outcomes will be presented.
Conclusions: Patients' adherence and satisfaction combined with correlations observed between in-clinic assessments and digital outcomes show promising potential for the FLOODLIGHT SSM solution to capture meaningful and relevant outcomes augmenting the clinical picture in patients with MS.
Disclosure: Sponsored by F. Hoffmann-La Roche Ltd; writing and editorial assistance was provided by Articulate Science, UK.
X. Montalban has received speaker honoraria and travel expense reimbursement for participation in scientific meetings, been a steering committee member of clinical trials or served on advisory boards of clinical trials for Actelion, Biogen, Celgene, Merck, Novartis, Oryzon, Roche, Sanofi-Genzyme and Teva Pharmaceutical.
P. Mulero has nothing to disclose.
L. Midaglia has nothing to disclose.
J. Graves has received grants or research support from Biogen, Genentech, Inc., and S3 Group and has received compensation for a nonbranded resident and fellow education seminar supported by Biogen.
S.L. Hauser serves on the board of trustees for Neurona and on scientific advisory boards for Annexon, Bionure and Symbiotix, and has received travel reimbursement and writing assistance from F. Hoffmann-La Roche Ltd for CD20-related meetings and presentations.
L. Julian is an employee of Genentech, Inc., and a shareholder of F. Hoffmann-La Roche Ltd.
M. Baker is an employee and shareholder of F. Hoffmann-La Roche Ltd.
J. Schadrack is an employee and shareholder of F. Hoffmann-La Roche Ltd.
C. Gossens is an employee and shareholder of F. Hoffmann-La Roche Ltd.
A. Scotland is an employee of F. Hoffmann-La Roche Ltd.
F. Lipsmeier is an employee of F. Hoffmann-La Roche Ltd.
C. Bernasconi is a contractor for F. Hoffmann-La Roche Ltd.
S. Belachew is an employee and shareholder of F. Hoffmann-La Roche Ltd.
M. Lindemann has nothing to disclose.

Abstract: P624

Type: Poster Sessions

Abstract Category: Therapy - Tools for detecting therapeutic response

Background: Sensor-based, active and passive smartphone-based self-monitoring (SSM) may be more sensitive and specific than periodic in-clinic assessments to measure progression in multiple sclerosis (MS).
Objective: To report an analysis of adherence, results from a patient satisfaction questionnaire and correlations between in-clinic tests and FLOODLIGHT SSM measures (NCT02952911).
Methods: Patients with MS (18-55 years; Expanded Disability Status Scale score 0-5.5; n=76) and healthy controls (n=25) received a preconfigured smartphone and smartwatch that prompt the user to perform the FLOODLIGHT SSM, comprising 'active tests' and 'passive monitoring' for 24 weeks. The primary analysis assessed participants' adherence (proportion of study weeks with at least 3 days of completed testing and at least 4 hours/day of passive monitoring) and patient satisfaction with the FLOODLIGHT SSM solution. In-clinic tests and brain MRI assessments were performed. Secondary analyses compared FLOODLIGHT SSM outcomes 1) between patients with MS and healthy controls and 2) with in-clinic outcomes in patients with MS. The correlation between FLOODLIGHT SSM outcomes and in-clinic tests was reported using Spearman's correlation coefficient (SCC).
Results: As of 4 May 2018, the interim analysis of adherence of 61 patients who completed the study showed 76.5% adherence to active tests and 83.2% to passive monitoring. Satisfaction amongst patients with MS who completed the study (n=61) was good to excellent (73.33 average score out of a possible 100 at termination visit). Correlations between FLOODLIGHT SSM and conventional in-clinic assessments at baseline (Spearman's rank correlation) were as follows: Correct responses from smartphone-based Symbol Digit Modalities Test (SDMT) vs oral SDMT: SCC=0.635, p< 0.001, n=53; Time between two consecutive pinch attempts in the FLOODLIGHT Pinching Test vs 9-Hole Peg Test: SCC=0.508, p< 0.001, n=54; Turning speed measured with the FLOODLIGHT Five-U-Turn Test vs Timed 25-Foot Walk test: SCC=-0.524, p< 0.001, n=55. Further comparisons between baseline FLOODLIGHT SSM and in-clinic testing MS outcomes will be presented.
Conclusions: Patients' adherence and satisfaction combined with correlations observed between in-clinic assessments and digital outcomes show promising potential for the FLOODLIGHT SSM solution to capture meaningful and relevant outcomes augmenting the clinical picture in patients with MS.
Disclosure: Sponsored by F. Hoffmann-La Roche Ltd; writing and editorial assistance was provided by Articulate Science, UK.
X. Montalban has received speaker honoraria and travel expense reimbursement for participation in scientific meetings, been a steering committee member of clinical trials or served on advisory boards of clinical trials for Actelion, Biogen, Celgene, Merck, Novartis, Oryzon, Roche, Sanofi-Genzyme and Teva Pharmaceutical.
P. Mulero has nothing to disclose.
L. Midaglia has nothing to disclose.
J. Graves has received grants or research support from Biogen, Genentech, Inc., and S3 Group and has received compensation for a nonbranded resident and fellow education seminar supported by Biogen.
S.L. Hauser serves on the board of trustees for Neurona and on scientific advisory boards for Annexon, Bionure and Symbiotix, and has received travel reimbursement and writing assistance from F. Hoffmann-La Roche Ltd for CD20-related meetings and presentations.
L. Julian is an employee of Genentech, Inc., and a shareholder of F. Hoffmann-La Roche Ltd.
M. Baker is an employee and shareholder of F. Hoffmann-La Roche Ltd.
J. Schadrack is an employee and shareholder of F. Hoffmann-La Roche Ltd.
C. Gossens is an employee and shareholder of F. Hoffmann-La Roche Ltd.
A. Scotland is an employee of F. Hoffmann-La Roche Ltd.
F. Lipsmeier is an employee of F. Hoffmann-La Roche Ltd.
C. Bernasconi is a contractor for F. Hoffmann-La Roche Ltd.
S. Belachew is an employee and shareholder of F. Hoffmann-La Roche Ltd.
M. Lindemann has nothing to disclose.

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