Contributions
Abstract: P739
Type: Poster
Abstract Category: Therapy - disease modifying - Tools for detecting therapeutic response
Background: Severe relapses (those requiring treatment) were important outcomes in the sentinel trials of disease-modifying therapy (DMTs). Identifying such relapses in administrative data would allow comparative-effectiveness studies of DMTs in real-world clinical settings.
Methods: All relapsing-remitting multiple sclerosis (RRMS) patients living in Manitoba between 1999-2014 were identified using a validated case definition and crosslinking to the Manitoba MS clinic database. All health-care interactions potentially due to relapse were extracted from province-wide hospital, physician-claims and drug dispensation databases. These “relapse markers” included varying thresholds of outpatient prednisone scripts, day-hospital or emergency room (ER) codes for intravenous (IV) methylprednisolone therapy, family physician, neurologist or ER physician billing codes and hospital admissions due to MS. Algorithms using combinations of these markers were compared with a gold standard list of MS neurologist-defined relapses. The analyses were repeated limiting the timeframe to 2009-2014; representing a period when relapse treatment shifted to predominant use of outpatient high-dose oral prednisone.
Results: 1224 RRMS patients (72% female) were found from 1999-2014 and 312 (73% female) from 2009-2014. Analysis of the 1999-2014 cohort was limited by inconsistent coding of same-day admissions for IV methylprednisolone. 208 relapses, of which 101 had documented treatment, were found in an unselected sample of MS Clinic patients from 2009-2014. After eliminating relapse markers with low sensitivity/specificity, 40 algorithms were tested. Of these, the best match to MS clinic-documented severe relapses consisted of outpatient oral prednisone prescriptions >50mg/day for between 3-30 days and same-day hospital or ER assessment codes with MS as the most responsible diagnosis (sensitivity 53%, specificity 94%, positive predictive value 93%, negative predictive value 55%, kappa 0.41).
Conclusions: Severe relapses can be abstracted from administrative datasets with a reasonable accuracy. The trend since 2009 towards outpatient relapse treatment will improve the sensitivity of relapse detection with longitudinal follow-up of this cohort and will allow comparison of severe relapse rates between different DMTs. In conjunction with planned analyses of health resource utilization, this will enable comparison of the effectiveness and health resource costs of standard and emerging DMTs.
Disclosure:
J.J. Marriott: Study was supported by a grant from the Multiple Sclerosis Society of Canada, has also received research support from Research Manitoba, Multiple Sclerosis Scientific Foundation, Consortium of MS Centers and Manitoba Medical Service Foundation and for MS trials from Biogen Idec, Roche, Sanofi-Aventis and honoraria from Biogen Idec, Roche, and EMD Serono.
R.A. Marrie: receives research funding from Canadian Institutes of Health Research, Public Health Agency of Canada, Research Manitoba, Health Sciences Centre Foundation, Multiple Sclerosis Society of Canada, Multiple Sclerosis Scientific Foundation, Rx & D Health Research Foundation, and National Multiple Sclerosis Society, and has conducted clinical trials funded by sanofi-aventis.
Hui Chen: nothing to disclose.
Randall Fransoo: nothing to disclose.
Abstract: P739
Type: Poster
Abstract Category: Therapy - disease modifying - Tools for detecting therapeutic response
Background: Severe relapses (those requiring treatment) were important outcomes in the sentinel trials of disease-modifying therapy (DMTs). Identifying such relapses in administrative data would allow comparative-effectiveness studies of DMTs in real-world clinical settings.
Methods: All relapsing-remitting multiple sclerosis (RRMS) patients living in Manitoba between 1999-2014 were identified using a validated case definition and crosslinking to the Manitoba MS clinic database. All health-care interactions potentially due to relapse were extracted from province-wide hospital, physician-claims and drug dispensation databases. These “relapse markers” included varying thresholds of outpatient prednisone scripts, day-hospital or emergency room (ER) codes for intravenous (IV) methylprednisolone therapy, family physician, neurologist or ER physician billing codes and hospital admissions due to MS. Algorithms using combinations of these markers were compared with a gold standard list of MS neurologist-defined relapses. The analyses were repeated limiting the timeframe to 2009-2014; representing a period when relapse treatment shifted to predominant use of outpatient high-dose oral prednisone.
Results: 1224 RRMS patients (72% female) were found from 1999-2014 and 312 (73% female) from 2009-2014. Analysis of the 1999-2014 cohort was limited by inconsistent coding of same-day admissions for IV methylprednisolone. 208 relapses, of which 101 had documented treatment, were found in an unselected sample of MS Clinic patients from 2009-2014. After eliminating relapse markers with low sensitivity/specificity, 40 algorithms were tested. Of these, the best match to MS clinic-documented severe relapses consisted of outpatient oral prednisone prescriptions >50mg/day for between 3-30 days and same-day hospital or ER assessment codes with MS as the most responsible diagnosis (sensitivity 53%, specificity 94%, positive predictive value 93%, negative predictive value 55%, kappa 0.41).
Conclusions: Severe relapses can be abstracted from administrative datasets with a reasonable accuracy. The trend since 2009 towards outpatient relapse treatment will improve the sensitivity of relapse detection with longitudinal follow-up of this cohort and will allow comparison of severe relapse rates between different DMTs. In conjunction with planned analyses of health resource utilization, this will enable comparison of the effectiveness and health resource costs of standard and emerging DMTs.
Disclosure:
J.J. Marriott: Study was supported by a grant from the Multiple Sclerosis Society of Canada, has also received research support from Research Manitoba, Multiple Sclerosis Scientific Foundation, Consortium of MS Centers and Manitoba Medical Service Foundation and for MS trials from Biogen Idec, Roche, Sanofi-Aventis and honoraria from Biogen Idec, Roche, and EMD Serono.
R.A. Marrie: receives research funding from Canadian Institutes of Health Research, Public Health Agency of Canada, Research Manitoba, Health Sciences Centre Foundation, Multiple Sclerosis Society of Canada, Multiple Sclerosis Scientific Foundation, Rx & D Health Research Foundation, and National Multiple Sclerosis Society, and has conducted clinical trials funded by sanofi-aventis.
Hui Chen: nothing to disclose.
Randall Fransoo: nothing to disclose.