Clinical Significance of Pim-1 in Human Cancers: A Meta-analysis of Association with Prognosis and Clinicopathological Characteristics
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background Pim-1 is overexpressed in cancer tissues and plays a vital role in carcinogenesis. However, its clinical significance in cancers is not fully verified by meta-analysis, especially in relation to prognosis and clinicopathological features. Methods Four databases, PubMed, Embase, Cochrane Library, and Web of Science, were searched. Literature screening and data extraction according to the inclusion and exclusion criteria. The quality of the included literatures was evaluated using the Newcastle-Ottawa scale and the data analysis was performed using STATA and Review Manager software. Results 15 articles were finally included for meta-analysis, involving 1651 patients. Effect-size pooling analysis showed that high Pim-1 was related to poor overall survival (OS) (HR 1.68 [95% CI 1.17-2.40], P = .004) and disease-free survival (DFS) (HR 2.15 [95 %CI 1.15-4.01], P = .000). Subgroup analysis indicated that the detection techniques of Pim-1 were the main sources of heterogeneity, and 2 literatures using quantitative polymerase chain reaction (qPCR) for Pim-1mRNA had high homogeneity (I 2 = .0%, P = .321) in OS. Another 13 studies that applied immunohistochemistry (IHC) for Pim-1 protein had significant heterogeneity (I 2 =82.2%, P = .000; I 2 =92%, P = .000) in OS and DFS, respectively, and further analysis demonstrated that ethnicity, sample size, and histopathological origin were considered to be the main factors affecting their heterogeneity. In addition, high Pim-1 was associated with lymph node metastasis (OR 1.40 [95% CI 1.02-1.92], P = .04), distant metastasis (OR 2.69 [95%CI 1.67-4.35], P < .0001), and clinical stage III-IV (OR .7 [95% CI .50-.96, P = .03). Sensitivity analysis suggested that the pooled results of each effect-size were stable and reliable, and there was no significant publication bias ( P = .138) in all included articles. Conclusion High Pim-1 can not only predict poor OS and DFS of cancer, but also help to infer the malignant clinical characteristics of tumor metastasis. Pim-1 may be a potential and promising biomarker for early diagnosis, prognostic analysis and targeted therapy of tumors.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.002 |
| 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 | 0.001 |
| 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 it