The Objective Response and Disease Control Rates in Patients with Liver Metastastic Breast Cancer Receiving Transarterial Radioembolization: A Meta-Analysis
Bibliographic record
Abstract
AIM: To meta-analyze the utility of transarterial radioembolization (TARE) in patients with liver metastatic breast cancer (BC), based on the objective response rate (ORR) and disease control rate (DCR). METHODS: A literature search was performed retrieving studies with (1) at least 10 patients with liver metastatic BC treated with TARE and (2) adequate information to derive ORR and DCR. The ORR is the ratio between patients with liver lesions showing complete response (CR) or partial response (PR) over the total number of patients treated with TARE; the DCR is the ratio between patients with CR, PR, or stable disease (SD) over the total number of patients treated with TARE. RESULTS: Eighteen studies (650 patients) were eligible; the ORR of TARE resulted 50.71% (95% C.I.: 40.04-61.36) and the DCR resulted 88.37% (95% C.I.: 81.89-93.57). Taking into account resin spheres (395 patients), the ORR was 60.35% (95% C.I.: 46.55-73.36) and the DCR was 92.73% (95% C.I.: 87.17-96.80%). Considering glass spheres (144 patients), the ORR was 32.38% (95% C.I.: 18.43-48.16) and the DCR was 82.69% (95% C.I.: 59.29-97.26). CONCLUSIONS: This meta-analysis favors the use of TARE in patients with liver metastatic BC either with resin or glass spheres.
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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 | 0.021 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.062 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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".