Prognostic impact of body composition in hepatocellular carcinoma patients with immunotherapy
Bibliographic record
Abstract
Objective This study aims to examine the possible relationship between body composition parameters, sarcopenia, and clinical outcomes in hepatocellular carcinoma (HCC) patients who received immune checkpoint inhibitor (ICI) treatment.Methods Three online databases, including Embase, PubMed, and the Cochrane Library, were thoroughly searched for literature describing the relationship between body composition parameters, sarcopenia, and outcomes of ICI-treated HCC patients from the start of each database to 21 January 2024. The Newcastle-Ottawa Scale was used to rate the quality of the studies. The assessed outcomes included hazard ratio (HR) for OS and PFS, as well as odds ratio (OR) for ORR and DCR.Results This analysis included a total of 15 articles with a combined patient cohort of 1543 individuals. The results demonstrated that HCC patients with low skeletal muscle index (SMI) had significantly inferior OS (HR: 1.68, p < 0.001), PFS (HR: 1.45, p < 0.001), ORR (OR: 0.64, p = 0.044), and DCR (OR: 0.58, p = 0.009) compared to those with high SMI. The presence of sarcopenia in HCC patients was significantly related to poorer OS (HR: 1.63, p < 0.001) and PFS (HR: 1.48, p < 0.001), as well as a lower ORR (OR: 0.64, p = 0.020) and DCR (OR: 0.58, p = 0.007) in comparison to those without sarcopenia. Subgroup analysis demonstrated that these findings were consistent with the multivariate analysis. Moreover, high subcutaneous adipose index (SAI) levels were associated with better OS (HR: 0.46, p = 0.001) and PFS (HR: 0.68, p = 0.021) than those with low SAI levels.Conclusion The presence of sarcopenia and low SMI in HCC patients undergoing treatment with ICIs was found to be related to inferior treatment response and reduced long-term effectiveness.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".