Tumor burden with AFP improves survival prediction for TACE-treated patients with HCC: An international observational study☆
Notice bibliographique
Résumé
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.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».