Matrix metalloproteinase 2 expression and disease-free survival of patients with osteosarcoma: a meta-analysis.
Bibliographic record
Abstract
Abstract. Numerous studies indicate the influence of matrix metallopro-teinase-2 (MMP-2) overexpression in osteosarcoma (OS) outcomes. A previous study has systematically analyzed the correlation between MMP-2 expression and the prognosis of OS. However, the results of subsequent studies remain in-consistent. Therefore, a meta-analysis in terms of the prognostic value of MMP-2 expression in OS was conducted. We employed the Newcastle-Ottawa scale (NOS) to evaluate the quality of the studies. Five studies involving 284 patients were included. The relative risk (RR) with a corresponding 95% confidence in-terval (95%CI) was calculated to appraise the predictive value of MMP-2 positive expression for OS recurrence and metastasis, and lower disease-free survival.It was indicated by the results that MMP-2 positive individuals with OS had higher recurrence and metastasis rates than negative individuals (RR=1.85, 95%CI:1.16-2.93, p<0.01). Sensitivity analysis showed that the combined RR was stable. There was no significant change, independently of whichever article was excluded.
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
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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.028 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".