Carcinoembryonic antigen as a predictor of treatment outcomes in cancer patients receiving immune checkpoint inhibitors
Bibliographic record
Abstract
Objective Carcinoembryonic antigen (CEA) is a widely used tumor marker and is associated with traditional therapeutic efficacy. Our study aims to assess the predictive significance of baseline carcinoembryonic antigen (CEA) levels and CEA level changes on the efficacy of immune checkpoint inhibitors (ICIs) in cancer patients.Methods A systemic literature search was conducted in three digital repositories—Embase, PubMed, and the Cochrane Library—to obtain studies linking CEA with clinical results in cancer patients receiving ICIs from the year of inception of each database until 20 August 2024. Studies were included if they involved cancer patients treated with ICIs, assessed the prognostic significance of baseline CEA levels or CEA level changes, and reported at least one outcome metric, including overall survival (OS), progression-free survival (PFS), disease control rate (DCR), pathological complete response (pCR), or objective response rate (ORR). Duplicate studies were identified and removed using Covidence software following Cochrane collaboration guidelines. The Newcastle-Ottawa Scale was applied to evaluate study quality. Pooled hazard ratios (HRs) for OS and PFS, as well as odds ratios (ORs) for DCR, pCR, and ORR, were calculated with 95% confidence intervals (CIs).Results The analysis included 27 studies, comprising a total cohort of 3662 patients. The findings revealed that cancer patients receiving ICIs with lower CEA levels had significantly improved OS (HR: 1.84, p < 0.001) and PFS (HR: 1.64, p < 0.001), along with higher DCR (OR: 1.81, p = 0.001), ORR (OR: 0.53, p = 0.001), and pCR (OR: 0.58, p < 0.001) compared to those with elevated CEA levels. Additionally, a reduction in CEA levels during immunotherapy was significantly associated with prolonged OS (HR: 0.507, p < 0.001) and PFS (HR: 0.501, p < 0.001), as well as increased ORR (OR: 2.39, p = 0.005) and DCR (OR: 2.94, p < 0.001).Conclusion The results advocate for integrating CEA level assessments into the prognostic analysis for cancer patients.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| 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".