IgA levels at diagnosis predict for infections, time to treatment, and survival in chronic lymphocytic leukemia
Bibliographic record
Abstract
Abstract To better understand the relationship between baseline immunoglobulin measurements and subsequent clinical outcomes in chronic lymphocytic leukemia (CLL), we performed a retrospective analysis on 660 patients with CLL (72%), monoclonal B-cell lymphocytosis (MBL) (13%), and small lymphocytic lymphoma (SLL) (14%), diagnosed between 2005 and 2014 at CancerCare Manitoba. Of 511 patients who had their first immunoglobulin level determined within 3 months of diagnosis, abnormal (either increased or decreased) immunoglobulin M (IgM), IgG, and IgA values were observed in 58% of patients with CLL, 27% of patients with MBL, and 20% of patients with SLL. Immunoglobulin deviances were similar for MBL and CLL Rai stage 0 and for SLL and Rai stages I and II; for CLL, IgG and IgA abnormalities occurred with increasing frequency with advancing Rai stage. In contrast, the frequency of IgM abnormalities was similar in all patient groups. IgA abnormalities significantly correlated with high β2-microglobulin (B2M) expression, whereas abnormal IgG and IgA levels were associated with the use of IGHV1-69, 3-21, and 3-49 subtypes. Increases in IgG or IgM were commonly associated with the presence of a CLL-type M-band, whereas oligoclonal bands were frequently observed with increased IgA levels. Although abnormal levels of IgG and IgA at diagnosis were independent predictors for future immunoglobulin replacement, only abnormal IgA levels were associated with shorter time to first treatment and overall survival. These findings indicate that both reduced and elevated levels of IgG and IgA at diagnosis are important and independent prognostic markers for infection in CLL, with IgA being more relevant as a marker of disease progression and survival.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 0.001 |
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 teacher head, 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".