A Diverse Spectrum of Immune Complex– and Complement-Mediated Kidney Diseases Is Associated With Mantle Cell Lymphoma
Bibliographic record
Abstract
Introduction: There are limited reports on kidney biopsy findings in patients with mantle cell lymphoma (MCL). Methods: We initiated a multi-institutional, retrospective review of kidney biopsy findings in patients with active and treated MCL. Results: A total of 30 patients with MCL and kidney biopsies were identified, with a median age of 67 (range 48-87) years, 73% of whom were men. A total of 20 patients had active MCL at the time of biopsy, of whom 14 (70%) presented with acute kidney injury (AKI), proteinuria and/or hematuria, and biopsy findings potentially attributable to lymphoma. Of the 14, 11 had immune complex (IC) or complement-mediated (C3) disease including proliferative glomerulonephritis (GN) with monotypic Ig deposits (PGNMID [2]), C3GN, (2), secondary membranous nephropathy (MN [3]), tubular basement membrane (TBM) deposits (2), and modest lupus-like GN (2). Lymphomatous infiltration was present in 8 of the 20 patients, 5 with coincident IC or C3 lesions. A total of 6 patients with available follow-up were treated for MCL, all with clinical remission of GN (2 PGNMID, 2 C3GN, and 2 MN). Conclusion: MCL is associated with diverse monoclonal and polyclonal glomerular and extra-glomerular IC and C3 disease. For patients with active MCL and kidney dysfunction requiring biopsy, 70% had findings due or potentially due to lymphoma, including 55% with IC or C3 disease and 40% had lymphomatous kidney infiltration. IC and C3GN in the setting of active MCL was responsive to lymphoma-directed therapy.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".