Myeloid clonal hematopoiesis of indeterminate potential in patients with chronic lymphocytic leukemia
Bibliographic record
Abstract
ABSTRACT: Clonal hematopoiesis of indeterminate potential (CHIP) in patients with chronic lymphocytic leukemia (CLL) has not been extensively characterized. The objective of this study was to describe the prevalence of myeloid CHIP (M-CHIP) in patients with CLL, and to determine its association with time to first treatment (TTFT) and overall survival (OS). We retrospectively analyzed data from patients participating in a prospective CLL database at the Dana-Farber Cancer Institute who had standard-of-care targeted 95-gene next-generation sequencing (NGS) performed. A schema was devised to classify mutations as M-CHIP related. M-CHIP was analyzed as a binary (present/absent) and categorical (≥2 vs 1 vs 0 mutations) predictor. We included 966 patients (median age at time of NGS, 65 years; 38% female). Overall, 747 (77%) patients had NGS performed before CLL treatment, whereas 219 (23%) had it performed after receiving treatment. Median follow-up time from NGS was 1.9 years. The prevalence of M-CHIP in untreated (12%) and treated (24%) patients with CLL was similar to that described in previous literature. M-CHIP prevalence appeared to increase with age in untreated patients, but appeared consistent across age in treated patients, suggesting that treatment (85% had prior chemotherapy) may have an impact on M-CHIP emergence even in younger patients. The presence of ≥2 M-CHIP mutations was associated with OS, even accounting for prior treatment and age, but was driven by a small subset of patients (n = 28). M-CHIP was not associated with TTFT. These findings support continued work into characterizing the effects of M-CHIP in patients with CLL.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 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".