Liquid-based kidney injury molecule-1 (KIM-1) as a diagnostic and prognostic indicator in renal cell carcinoma: A systematic review and meta-analysis.
Bibliographic record
Abstract
e16515 Background: Noninvasive biomarkers for renal cell carcinoma are vital but scarce. Kidney injury molecule-1 (KM-1) is a transmembranous glycoprotein that is sensitive and specific in kidney injury. KIM-1 is overexpressed in renal cell carcinoma (RCC), and its ectodomain can be detected in plasma and urine. Here, we explore whether KIM-1 is a diagnostic or prognostic indicator in RCC. Methods: A comprehensive online literature search was performed in PubMed, Web of Science, Embase, Cochrane Library, ClinicalTrails, and Database of major urological or oncological congress. We screened the literature and extracted the data according to the selection criteria. The quality of eligible studies was measured by using the Quality Assessment of Diagnostic Accuracy Studies-2 tool and the Newcastle-Ottawa scale. The certainty of the evidence (CoE) was assessed by the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) score. Then, sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), area under the curve of the summary receiver operating characteristic curve (AUROC), and survival outcomes were estimated in Stata and MetaDisc. Subgroup analysis, meta-regression, and sensitivity analysis were performed to reveal the source of heterogeneity. Results: A total of eight studies were included for further analysis. The pooled sensitivity of KIM-1 to diagnosis RCC was 0.78 (95% CI: 0.69-0.85, I2 = 84.61%, p < 0.01), and the pooled specificity was 0.79 (95% CI: 0.65-0.89, I2 = 90.72%, p < 0.01). The AUROC was 0.85 (95% CI: 0.82-0.88). A moderate CoE was indicated by GRADE score. Then, a higher KIM-1 level is associated with worse disease-free survival (HR = 1.76, 95% CI: 1.48-2.09, I 2 = 0.00%, p < 0.001). Study continent, number of study center, and sample type are the potential contributors of heterogeneity. Conclusions: liquid-based KIM-1 is a promising non-invasive biomarker for RCC early detection, surveillance, and prognosis prediction. More validations in large cohorts are needed to confirm these findings.
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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 | 0.011 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.032 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".