Oligoclonal Bands in Spinal Fluid Improve the Specificity of Different MRI Criteria for Dissemination in Space to Predict a First Clinical Event in Children with the Radiologically Isolated Syndrome (S51.002)
Bibliographic record
Abstract
Objective: To determine whether the addition of oligoclonal band (OCB) status (present/absent in cerebrospinal fluid [CSF]) improved the performance of 2005 and proposed MAGNIMS 2016 MRI criteria for dissemination in space (DIS) to predict a first clinical event consistent with central nervous system demyelination in children with the radiologically isolated syndrome (RIS), defined using 2010 MRI criteria for DIS (RIS-2010). Background: Improved diagnostic criteria for RIS are needed to predict which children will develop a first clinical event. We reported that neither the 2005 nor the 2016 MAGNIMS MRI criteria for DIS had both high sensitivity and specificity to predict a first clinical event in children with RIS-2010. Design/Methods: We analyzed a historical cohort of children (<18 years) with RIS-2010 in an international longitudinal study. We determined whether children also met 2005 and 2016 MAGNIMS MRI criteria for DIS at baseline and whether ≥2 unique OCBs were present in CSF. We calculated sensitivity and specificity for different MRI criteria for DIS with and without the addition of OCB status. Results: Of 55 children with RIS-2010, 33 (60%) had OCB status determined and were included (6M/27F, mean follow-up=5.3 ± 5.2 years). 19/33 children tested OCB+ (58%) and 15/33 children (45%) developed a first clinical event. Diagnostic indices and 95% C.I.s for the 2005 DIS criteria with and without OCBs status were: sensitivity 67% (38%–88%) vs. 67% (41%–87%); specificity 83% (59%–96%) vs. 53% (35%–70%). For the 2016 MAGNIMS DIS criteria diagnostic indices were: sensitivity 87% (60%–98%) vs. 100% (82%–100%) and specificity 72% (46%–90%) vs. 25% (11%–41%). Conclusions: The addition of OCB status improved the specificity of both the 2005 and the 2016 MAGNIMS MRI criteria for DIS to predict a first clinical event in children with RIS-2010. The 2016 MAGNIMS DIS criteria plus OCB status had the best combination of sensitivity and specificity. Study Supported by: This study was funded, in part, by Grant Number K23NS101099 from the National Institute of Neurological Diseases and Stroke (NINDS) and CTSA Grant Number UL1 TR000142 from the National Center for Advancing Translational Science (NCATS) at the National Institutes of Health and NIH roadmap for Medical Research. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of NIH. Disclosure: Dr. Makhani has nothing to disclose. Dr. Lebrun-Freney has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Consulting fees, honoraria or scientific committee support: Bayer Schering, Biogen, Genzyme, Merck Serono, Novartis, Teva. Dr. Siva has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Merck, Novartis, Teva, Genzyme, Bayer, Roche. Dr. Narula has nothing to disclose. Dr. Wassmer has nothing to disclose. Dr Brenton has nothing to disclose. Dr. Brassat has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Bayer, Biogen, MedDay, Merck Serono, Novartis, Sanofi-Genzyme, Roche, Teva. Dr. Carra-Dalliere has nothing to disclose. Dr. De Seze has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Sanofi. Dr. De Seze has received research support from Sanofi. Dr. Durand Dubief has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Biogen, Sanofi-Genzyme, Novartis, Teva, Merck, Roche. Dr. Langille has nothing to disclose. Dr. Neuteboom has nothing to disclose. Dr. Pelletier has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Biogen, Sanofi-Genzyme, Novartis, Teva, Merck-Serono, Roche, MedDay. Dr. Pelletier has received research support from Biogen, Novartis, Roche, Merck-Serono. Dr. Pohl has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Novartis, Forward. Dr. Reich has nothing to disclose. Dr. Rojas has nothing to disclose. Dr. Shabanova has nothing to disclose. Dr. Shapiro has nothing to disclose. Dr. Thompson-Stone has nothing to disclose. Dr. Tenembaum has nothing to disclose. Dr. Tintoré has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Bayer Schering Pharma, Merck-Serono, Biogen-Idec, Teva Pharmaceuticals, Sanofi-Aventis, Novartis, Almirall, Genzyme, and Roche. Dr. Uygunoglu has nothing to disclose. Dr. Vargas has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Alexion Pharmaceuticals. Dr. Vargas has received research support from Teva Pharmaceuticals. Dr. Venkateswaran has nothing to disclose. Dr. Kantarci has nothing to disclose. Dr. Okuda has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Acorda, EMD Serono, Genentech, Genzyme, Novartis, and Teva. Dr. Pelletier has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Biogen, Merck Serono, Novartis, Roche, and Sanofi. Dr. Pelletier has received research support from Biogen, Merck Serono, Novartis, Roche, and Sanofi. Dr. (OFSEP) has nothing to disclose. Dr. (SFSEP) has nothing to disclose. Dr. (RISC) has nothing to disclose. Dr. Consortium (PARIS) has nothing to disclose.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".