Overexpression of macrophage-colony stimulating factor-1 receptor as a prognostic factor for survival in cancer
Bibliographic record
Abstract
BACKGROUND: The relation between the expression of macrophage-colony stimulating factor-1 receptor (CSF-1R) and prognosis of cancer patients has been evaluated in multiple studies, but the results remain controversial. We, therefore, performed a meta-analysis and systematic review to figure out the role of CSF-1R in the prognosis of patients with cancer. METHODS: Several databases were searched, including Web of Science, PubMed, and EMBASE. All human studies were published as full text. The Newcastle-Ottawa risk of bias scale was applied to evaluate the research. We extracted hazard ratios (HRs) with 95% confidence interval (95% CI) which assessed progression-free survival (PFS) and overall survival (OS) in order to assess the impacts of CSF-1R on the prognosis of cancer patients. RESULTS: A total of 12 citations were identified, with studies including 2260 patients in different cancer types that met the eligibility criteria. It was suggested in a pooled analysis that the over-expression of CSF-1R was significantly related to worse PFS (HR: 1.68; P < .001, 1.25-2.10, 95% CI) and also poorer OS (HR=1.28; P < .001, 1.03-1.54, 95% CI). Analysis in subgroups indicated over-expressed CSF-1R was significantly associated with worse OS in hematological malignancy (HR = 2.29; P < .001, 1.49-3.09, 95% CI; model of fixed-effects; I2 = 0.0%, P < .001). Sensitivity analysis suggested that there was no study influencing the stability of the results. CONCLUSIONS: The overexpression of CSF-1R was significantly predictive of worse prognosis in those who suffer from different kinds of malignancies, particularly in hematological malignancy, which indicates that it might be a potential biomarker of prognosis in cancer survival and a potential molecular target in the treatment of malignant tumors.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".