Interleukin 17F Level and Interferon Beta Response in Patients With Multiple Sclerosis
Why this work is in the frame
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Bibliographic record
Abstract
IMPORTANCE: High serum levels of interleukin 17F (IL-17F) at baseline have been associated with suboptimal response to interferon beta in patients with relapsing-remitting multiple sclerosis. OBJECTIVE: To further investigate the role of IL-17F in predicting treatment response to interferon beta-1b in patients with relapsing-remitting multiple sclerosis using the Singulex Erenna IL-17F immunoassay. DESIGN, SETTING, AND PATIENTS: Serum samples were analyzed from 239 randomly selected patients treated with interferon beta-1b, 250 μg, for at least 2 years in the Betaferon Efficacy Yielding Outcomes of a New Dose Study. EXPOSURE: Treatment with interferon beta-1b, 250 μg, for at least 2 years. MAIN OUTCOME MEASURES: Levels of IL-17F at baseline and month 6 as well as the difference between the IL-17F levels at month 6 and baseline were compared between the following: (1) patients with less disease activity vs more disease activity; (2) patients with no disease activity vs some disease activity; and (3) responders vs nonresponders. RESULTS: Levels of IL-17F measured at baseline and month 6 did not correlate with lack of response to treatment after 2 years using clinical and magnetic resonance imaging criteria. Relapses and new lesions on magnetic resonance imaging were not associated with pretreatment serum IL-17F levels. When patients with neutralizing antibodies were excluded, the results did not change. All patients with levels of IL-17F greater than 200 pg/mL were associated with poor response with some clinical or radiological activity. CONCLUSIONS AND RELEVANCE: An increase of IL-17F before and early after treatment with interferon beta-1b was not associated with poor response. These data do not support the value of IL-17F as a treatment response indicator for therapy of patients with multiple sclerosis with interferon beta, although high levels of IL-17F greater than 200 pg/mL may predict nonresponsiveness.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it