Systematic review of 12 years of thermal ablative therapies of non-resectable colorectal cancer liver metastases
Bibliographic record
Abstract
To compare the effectiveness and complications of various thermal ablative therapies through reviewing the available literature.The preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement was used to report this systematic review.Our PICO (patient group-intervention-comparator-outcomes) question: In patients with unresectable colorectal cancer liver metastasis (CRCLM), what are the comparative effectiveness and complication rates of the various thermal ablative therapies?All study designs published between 2000 and 2012 considered.Search results were screened in duplicate to determine eligible studies.A customized "risk of bias" assessment tool was utilized.Asymmetry of the funnel plot and heterogeneity were quantified.Representative forest plots of the 1, 3, and 5 years survival rates, major complication rates and local recurrence rates were performed.Data not amenable to pooling is presented in a qualitative and tabular manner.Thirty radiofrequency ablation (RFA), 11 cryoablation (CA), and 5 microwave ablation (MWA) studies were finally included in the qualitative synthesis.The number of patients included from all the studies was 3,107 patients; 2,021 in the RFA group, 988 in the CA, and 98 in the MWA.The forest plots confirm the significant heterogeneity of the included studies.Visual assessment of forest plots, as well as qualitative analysis of included papers suggested that between-studies heterogeneity was too great and thus, pooling through meta-analysis was not appropriate.RFA is the most commonly used ablative modality to treat unresectable CRCLM.Significant heterogeneity of the included studies was encountered precluding a meaningful meta-analysis.Future comparisons of local ablative therapies outcome necessitate prospective, randomized controlled studies.
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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 | 0.016 | 0.046 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.018 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 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".