Prognostic Role of Platelet to Lymphocyte Ratio in Solid Tumors: A Systematic Review and Meta-Analysis
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: Inflammation influences cancer development and progression. An elevated platelet to lymphocyte ratio (PLR), a marker of inflammation, has been linked to poor prognosis in several malignancies. Here, we quantify the prognostic impact of this biomarker. METHODS: A systematic review of databases was conducted to identify publications exploring the association of blood PLR and overall survival (OS) in solid tumors. Data were pooled in a meta-analysis. Pooled HRs for OS by disease group and by PLR cutoff groups were computed and weighted using generic inverse-variance and random-effect modeling. RESULTS: Twenty studies comprising 12,754 patients were assessed. Cutoffs for PLR defining risk groups ranged from 150 to 300 and were dichotomous (12 studies; group 1) or split into three groups (<150/150-300/>300, 8 studies; group 2). Higher PLR was associated with significantly worse OS in group 1 [HR = 1.87; 95% confidence interval (CI, 1.49-2.34); P < 0.001] and with a nonsignificant association in group 2 (HR per higher category = 1.21; 95%CI, 0.97-1.50; P = 0.10). The size of effect of PLR on OS was greater for metastatic disease (HR[group 1] = 2.0; 95% CI, 1.6-2.7; HR[group 2] = 1.6; 95% CI, 1.1-2.4) than for early-stage disease (HR[group 1] = 1.5; 95% CI, 1.0-2.2; HR[group 2] = 1.0; 95% CI, 0.8-1.3). A significant association was observed for colorectal, hepatocellular, gastroesophageal, ovarian, and pancreatic carcinoma in group 1 and for colorectal cancers in group 2. CONCLUSION: A high PLR is associated with worse OS in various solid tumors. Further research of its regulation and relevance in daily practice is warranted. IMPACT: PLR is a readily available and inexpensive biomarker with independent prognostic value in solid tumors.
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.
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 | 0.008 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.004 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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