Tumor burden with AFP improves survival prediction for TACE-treated patients with HCC: An international observational study☆
Bibliographic record
Abstract
Background & Aims Current prognostic models for patients with hepatocellular carcinoma (HCC) undergoing transarterial chemoembolization (TACE) are not extensively validated and widely accepted. We aimed to develop and validate a continuous model incorporating tumor burden and biology for individual survival prediction and risk stratification. Methods Overall, 4,377 treatment-naive candidates for whom TACE was recommended, from 39 centers in five countries, were enrolled and divided into training, internal validation, and two external validation datasets. The novel model was developed using a Cox multivariable regression analysis and compared with our original 6-and-12 model (the largest tumor size [ts, centimetres] + tumor number [tn]) and other available models in terms of predictive accuracy. Results The proposed model, named the ‘6-and-12 model 2.0', was generated as ‘ts + tn + 1.5×log 10 alpha-fetoprotein (AFP)', showed good discrimination (C-index 0.674) and calibration (Hosmer–Lemeshow test p = 0.147), and outperformed current existing models. An easy-to-use stratification was proposed according to the different AFP levels (≤100, 100–400, 400–2,000, 2,000–10,000, 10,000–40,000, and >40,000 ng/ml) along with the corresponding tumor burden cutoffs (8/14, 7/13, 6/12, 5/11, 4/10, and any tumor burden); that is, if the AFP level was 400–2,000 ng/ml, the stratification should be low-(≤6)/intermediate-(6–12)/high-risk (>12) strata. Hence, it could divide the patients into three distinct risk categories with a median overall survival of 45.0 (95% CI, 40.1–49.9), 30.0 (95% CI, 26.1–33.9), and 15.4 (95% CI, 13.4–17.4) months ( p <0.001) from low-risk to high-risk strata, respectively. These findings were confirmed in validation and subgroup analyses. Conclusions The 6-and-12 model 2.0 significantly improved individual outcome predictions and better stratified the candidates recommended for TACE; thus, this model could be used in both clinical practice and trial design. Impact and implications: In this international multicentre study, we developed and internally and externally validated a novel outcome prediction model for candidates with HCC who would be ideal for TACE. The model, called the 6-and-12 model 2.0, was based on 4,377 patients from 39 centers in five countries. The model offers individualized outcome prediction, outperforming the original 6-and-12 model score and other existing metrics across all datasets and subsets. Based on different levels of alpha-fetoprotein (AFP) and corresponding cut-offs of tumor burden, patients could be stratified into three risk strata with significantly different survival prognoses, which could provide a referential framework to control study heterogeneity and define the target population in future trial designs.
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.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".