Light Chain Deposition Disease: Impact of Stem Cell Tranplant on Hematological Response Achievement.
Bibliographic record
Abstract
Abstract Abstract 4600 Light chain deposition disease (LCDD) is a systemic disorder characterized by deposition of monoclonal light chains (LC) in different organs. A single clone of plasma cells is responsible for the overproduction of either kappa or rarely lambda LC. Renal dysfunction generally is the main feature but many organs could be affected. The treatment of LCDD has not been standardized and remains controversial because of the small number of patients reported in the literature. However, as LCDD is associated with plasma cell dyscrasias, patients have typically been treated with regimens used for multiple myeloma, most commonly melphalan (mel) and prednisone and VAD (Vincristine, Adriamycin and Dexamethasone). Here, we report our experience using High Dose Melphalan (HDM) with Autologous Stem Cell Transplant (ASCT) in five patients (pts) with LCDD. In addition, we report the use of Velcade (vel) as induction therapy in two patients before undergoing ASCT. Patients and Methods We retrospectively reviewed the records of all pts treated with HDM/ASCT at Princess Margaret Hospital between January 2004 and December 2009 and identified five pts with LCDD. Pretreatment evaluation included staging investigations: 1) complete blood cell counts, 2) complete biochemistry panel, 3) albumin and β2-microglobulin, 4) Blood and Urinary Monoclonal protein assessment including Free LC Assay; 5) skeletal survey. 6) Bone marrow aspirate and biopsy. Pts with LCDD and concurrent multiple myeloma were excluded. LCDD was diagnosed by renal biopsy in all pts with histology confirming characteristic linear monoclonal LC deposits along the tubular membrane staining for kappa and lambda chains on inmunofluorescence. All pts received induction therapy prior to consolidation with HDM/ASCT [dexamethasone (n=3) and vel plus dexamethasone (n=2)]. Assessment of hematologic response (HR) to treatment was based on modified EORTC consensus criteria. Results Pts characteristics are shown in Table 1. Two pts were male subjects; the median age was 55 (range 45–65). All five pts, had elevated serum FLC and an abnormal κ-to- λ ratio. All of the pts presented with kidney involvement. The monoclonal protein deposited in the kidney consisted of free κ-LC in four pts and free lambda LC in 1. Two pts received vel and dexamethasone (3 cycles) induction therapy achieving PR after 6 weeks of therapy and three received dexamethasone alone: 1 pt achieving a PR and 2 SD. All of them received a conditioning regimen of mel 200 mg/m2. Complete HR was seen in 3 pts and PR in 1 patient (ORR 80%, CR 60%). Transplanted pts had a median time to ANC ≥0.5 ×109/L of 12d (Range 12–13) and time to platelets ≥ 20 ×109/L was 14 days (Range 12–17). Median time to discharge was 17 days (range 13–30) and no pts exhibited engraftment syndrome. There was no mortality related to transplant. The most common grade 3/4 adverse events included: neutropenic fever (n=5); mucositis (n=2); and transient worsening in kidney function (n=1). All pts are alive and progression-free at a median follow-up of 20 months (range 7–37) from transplant. As kidney dysfunction represents the most prominent morbidity in LCDD, it is important to emphasize that the elevated serum creatinine was ameliorated in these pts after ASCT Conclusions LCDD is a rare condition and its management is controversial. In a few small series, investigators have reported that high-dose melphalan (HDM) followed by ASCT can be associated with beneficial results whereas toxicity remains acceptable in this group of pts. We report our experience using HDM and ASCT in pts with LCDD without concurrent myeloma, demonstrating feasibility and tolerability. Disclosures: Reece: Celgene: Honoraria, Research Funding. Chen:Celgene Corporation: Consultancy, Honoraria, Research Funding. Kukreti:Celgene: Honoraria.
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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 | 0.000 | 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 | 0.000 |
| 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".