The detection of circulating tumor cells indicates poor therapeutic efficacy and prognosis in patients with nonsmall cell lung cancer: A systematic review and meta‐analysis
Bibliographic record
Abstract
Abstract Objective The efficacy and prognostic value of circulating tumor cells (CTCs) in nonsmall cell lung cancer (NSCLC) are controversial based on the existing research. This systematic review and meta‐analysis evaluated the significance of CTCs in NSCLC therapy monitoring and prognosis prediction, supporting their potential as clinical biomarkers. Methods We conducted a comprehensive search of PubMed, Embase, Web of Science, The Cochrane Library, WanFang Data, CNKI, and VIP through September 20, 2023. Inclusion criteria were cohort studies involving NSCLC patients, focusing on peripheral blood CTCs, and assessing outcomes such as pre‐ and posttreatment CTC rates or levels, progression‐free survival (PFS), and overall survival (OS). Two reviewers independently extracted the data and assessed risk of bias using the Newcastle‐Ottawa Scale. We utilized Review Manager 5.4.1 for meta‐analysis, calculating pooled odds ratios (ORs) for dichotomous outcomes, mean differences for continuous variables and hazard ratios (HRs) for survival data, applying fixed‐ or random‐effects models based on heterogeneity assessed by the I 2 statistic. This study was registered in PROSPERO (No. CRD42023450035). Results Twenty‐two eligible studies with a total of 1674 NSCLC patients were included. Meta‐analysis results showed that the CTCs‐positive rate (OR = 0.59, 95% CI 0.45 to 0.77, p = 0.0001) and CTCs count (mean difference = –3.10, 95% CI –5.52 to –0.69, p = 0.01) were significantly decreased after antitumor treatment. Compared with the CTCs nonreduced group, the CTC‐reduced group showed better PFS (HR = 1.71, 95% CI 1.35 to 2.17, p < 0.00001) and OS (HR = 1.50, 95% CI 1.21 to 1.86, p = 0.0003) after treatment. PFS and OS in CTC‐positive groups were lower than those in the CTCs‐negative group pretreatment (HR = 2.49, 95% CI 1.78 to 3.47, p < 0.00001; HR = 1.80, 95% CI 1.29 to 2.52, p = 0.0006) and posttreatment (HR = 3.36, 95% CI 2.12 to 5.33, p < 0.00001; HR = 3.31, 95% CI 1.75 to 6.27, p = 0.0002). Conclusions CTCs can be used as a biomarker to monitor NSCLC efficacy, predict prognosis and guide follow‐up treatment.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Meta-analysis | low |
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Meta-analysis | high |
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 | 0.014 | 0.038 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.039 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".