Glasgow Prognostic Score and modified Glasgow Prognostic Score and survival in patients with hepatocellular carcinoma: a meta-analysis
Bibliographic record
Abstract
Objective To evaluate the association between inflammation-related markers, modified Glasgow Prognostic Score (mGPS) and Glasgow Prognostic Score (GPS), and survival outcome and recurrence risk in patients with hepatocellular carcinoma (HCC) after treatment. Design Systematic reviews and meta-analysis of cohort studies. Date sources Embase, Scopus, Web of Science and PubMed were searched through 10 March 2021. Eligibility criteria We included cohort studies that assessed the effect of pretreatment mGPS/GPS levels on survival outcomes in patients with HCC. Data extraction and synthesis Two researchers independently selected the data and reached a consensus. In case of disagreement, a third researcher was required to assist. The HRs and 95% CIs were used as the effect size indexes. Newcastle-Ottawa Scale was used to assess risk of bias and quality assessment of the included studies. Results The meta-analysis included 23 studies, most of which were retrospective. Participants were grouped according to the score of mGPS/GPS. When analysed into two groups (1/2 vs 0), the results showed that patients with a mGPS/GPS of 1 or 2 had poorer overall survival (OS) than those with a score of 0 (both p<0.001). When analysed into three groups (1 vs 0 and 2 vs 0), the results revealed that an mGPS/GPS of 2 is related to poorer OS in patients with HCC (HR=2.46, 95% CI 2.06 to 2.95, and HR=3.45, 95% CI 1.68 to 7.10, respectively). However, a GPS of 1 (p=0.005) but not an mGPS of 1 (p=0.177) had a significant association with OS. No association was found between mGPS/GPS and disease-free survival or recurrence-free survival. Conclusion GPS was more closely associated the survival in patients with HCC than mGPS. A higher GPS has an association with poorer survival. It can be combined with tumour staging to assess the OS of HCC more accurately. PROSPERO registration number CRD42021242049.
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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 | 0.017 | 0.030 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.053 |
| Bibliometrics | 0.006 | 0.007 |
| 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) | 0.002 | 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".