Prognostic Factors for Clinical Response in Systemic Lupus Erythematosus Patients Treated by Allogeneic Mesenchymal Stem Cells
Bibliographic record
Abstract
Systemic lupus erythematosus (SLE) is an autoimmune disease with a broad range of clinical manifestations and a heterogeneous disease course. There is no cure for SLE, but current standard pharmacotherapies can improve disease prognosis in most patients. However, some patients are refractory to conventional treatments and require alternative treatment options. The present study is aimed at identifying predictors of clinical response to allogeneic bone marrow-derived or umbilical cord-derived mesenchymal stem cell (BM-/UC-MSC) transplant in SLE. All adult patients identified in the Nanjing database with an SLE Disease Activity Index (SLEDAI) score≥8 at baseline that had undergone MSC transplant and who had at least 1 year of follow-up after one or two successive intravenous injections of allogeneic BM-/UC-MSCs (1 million/kg) were analyzed. SLE symptoms and SLEDAI were assessed at baseline and during follow-up to determine low disease activity (LDA) and clinical remission (CR) at 1, 3, 6, and 12 months. Sixty-nine patients were included in the study, with a median (range) SLEDAI of 13 (8-34) at baseline. Among the 69 patients, 40 (58%) achieved LDA and 16 (23%) achieved CR with a SLEDAI of 9 (4–20), 8 (0-16), 6 (0-18), and 5 (0-18) after 1, 3, 6, and 12 months, respectively. Older age ( p=0.006 ) and no arthralgia/arthritis at baseline ( p=0.03 ) were associated with a higher rate of LDA. Achieving CR was associated with older age ( p=0.033 ), no arthralgia/arthritis at baseline ( p=0.001 ), and no prior use of cyclophosphamide ( p=0.003 ) or hydroxychloroquine ( p=0.016 ). Future studies using unique immunosuppressive regimens and allogeneic MSC sources will further elucidate determinants of clinical response to MSC transplant in SLE.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".