Multiple Sclerosis Therapy With Disease-Modifying Treatments in Germany: The PEARL (ProspEctive phArmacoeconomic cohoRt evaluation) Noninterventional Study Protocol
Bibliographic record
Abstract
BACKGROUND: Patients with multiple sclerosis (MS) require long-term therapy and have a wide variety of needs for health-related support. The efficacy and safety of MS therapy, as assessed by both clinicians and patients, are important parameters that need to be considered. However, few studies combine data on efficacy and safety outcomes with pharmacoeconomic data. OBJECTIVE: Here, we present the study design of the ProspEctive phArmacoeconomic cohoRt evaluation (PEARL), a prospective, multicenter, noninterventional cohort study on patients with relapsing-remitting MS (RRMS) treated with disease-modifying treatments (DMTs). METHODS: During a prospective observational phase of 24 months per patient, PEARL evaluated clinical and patient-perceived efficacy and safety measures, as well as pharmacoeconomic data on RRMS patients treated with DMTs-interferon beta and glatiramer acetate. Measurements of the patients' perceptions included the assessment of patient-reported quality of life, treatment satisfaction, and compliance. The study was planned to include 1800 outpatients from 180 German neurological practices who had continuously been treated with an approved DMT for at least 30 days. The primary statistical analyses of the PEARL study will be descriptive. Particular focus will be on specific subgroups, such as patients who switched DMTs during therapy and patients with disease worsening or disease activity. Subgroups will be compared using stratified analyses. RESULTS: Data collection for PEARL started in September 2010 and ended in July 2013. As of July 2015, the study is completed and is currently being analyzed and written up. CONCLUSIONS: PEARL is evaluating both the health status and resource utilization of RRMS patients treated with DMTs in Germany. The combination of pharmacoeconomic data with clinical and patients' self-perceived efficacy and safety outcomes will add useful information to the currently incomplete picture of the overall RRMS burden in Germany.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.011 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".