Clonal hematopoiesis of indeterminate potential (CHIP): Outcomes and adverse events in patients with solid tumors.
Bibliographic record
Abstract
3521 Background: CHIP is the clonal expansion of hematopoietic stem cells following acquisition of somatic mutations. It is a common incidental finding in cell-free DNA (cfDNA). We investigated the incidence of CHIP in cfDNA from patients with solid tumors and explored its association with outcomes and adverse events (AEs). Methods: We reviewed cfDNA results from a local prospective solid tumor cohort (PREDICT-L) and two randomized trials: CCTG CO.26 (durvalumab + tremelimumab [D+T] or best supportive care [BSC] in metastatic colorectal cancer [mCRC]) and CCTG PA.7 (gemcitabine and nab-paclitaxel [GN] +/- D+T in metastatic pancreatic adenocarcinoma [mPDAC]). CHIP+ was defined as any mutation in DNMT3A, TET2, ASXL1or ATM with a variant allele frequency (VAF) 2% or higher. Variants were considered germline if the VAF was >40%, or were annotated as germline by respective assays. The first line of treatment after cfDNA was reviewed for grade 3 or higher and dose-limiting AEs. Results: The prevalence of CHIP was 10%-21% and was more common in older patients (p=0.003). There was no association between CHIP and sex (p=0.80) or ECOG status (p=0.31). The VAF of CHIP variants was similar across all panels, and DNMT3A was the gene most frequently mutated in all cohorts. Patients with CHIP in PA.7 treated with immunotherapy (IO) had improved progression-free survival (PFS) versus patients without CHIP (p=0.036, p-interaction=0.061 [multivariable]). However, patients with CHIP treated with chemotherapy (Chemo) showed a trend towards worse overall survival (OS) in the PREDICT-L cohort (p=0.057). There was no significant difference in the rates of AEs between the CHIP+ versus CHIP- groups for those treated with Chemo or IO. Conclusions: CHIP is common in patients with solid tumors. Although not appearing to impact rates of AEs, CHIP may impact outcomes from Chemo or IO. [Table: see text]
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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 | 0.001 | 0.003 |
| 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".