Abstract 2411: A multidisciplinary approach for HCC risk prediction in patients with cirrhosis utilizing elastography, imaging, circulating tumor cells and genomics
Notice bibliographique
Résumé
Background: HCV induced HCC is increasing in the United States. Therefore, it is imperative that we understand the genetic and cellular based mechanisms underpinning the linkages between HCV and HCC and the impact of race/ethnicity on the development of this deadly tumor. The aims of our study were to assess changes in transient elastography (TE) and Fibrosis-4 (FIB-4) score in a large cohort of patients and identify risk based on race/ethnicity. Patients were also stratified for HCC risk based on the Toronto HCC Risk Index (THRI), genomics, imaging data with inclusion of screening for circulating tumor cells.Methods: Our cohort included 1,943 patients with liver disease, including HCV, HBV, NASH, etc., were assessed by Fibroscan and comparisons made with clinical parameters of liver disease. Approximately 500 patients had liver biopsies. Statistical analysis with Kruskal-Wallis and Chi-Square tests was carried out. Values reported are mean ± standard deviation. The estimated stage of liver fibrosis based on TE was categorized as F0-F2 (<9.4kpa), or F3 (9.5 - 12.4 Kpa), or F4/cirrhotics (TE >12.5 kpa).Results: In our cohort, African Americans (AAs) had higher BMIs (27.8±5.2, p<0.01) and lower albumin levels (4.2±0.5 g/dl, p=0.01). Platelet (p=0.79) and AST values (p=0.17) were comparable between races; however, ALT was highest among non-Hispanic whites (67±68, p=0.02). TE measurement was highest in AAs and Hispanics (12.2±12 and 12.2±12 kPa, respectively) and lowest in non-Hispanic whites (12.2±12 kPa) (p<0.01), while FIB4 Index was not statistically different (p=0.23). Risk of developing HCC, as measured by THRI, was highest in AAs (234±65) and lowest in Hispanics (214±68, p<0.01). Stratifying by Hepatitis C (HCV) status, the majority of non-Hispanics had HCV, whereas most Hispanics had non-HCV liver disease (p<0.01). HCV positive patients were older (59±11 vs 54±14 years, p<0.01), had higher AST (60±71 vs 45±58, p<0.01), ALT (67±67 vs 55±75, p<0.01), THRI (238±64 vs 189±68, p<0.01), TE scores (12.4±11.6 vs 10.6±11.5 kPa, p<0.01), and FIB4 (3.0±3.2 vs 2.0±1.7, p<0.01), but lower BMI (26.4±4.5 vs 27.4±4.9, p<0.01), platelets (187.0±72 vs 204.1±74 109/L, p<0.01), and albumin (4.2±0.5 vs 4.4±2.3 g/dl, p<0.01).Conclusions: Liver fibrosis stage, as determined by TE, increased with HCC risk as determined by THRI. THRI identified the subpopulation of African Americans as having generally greater risk of HCC, despite comparable platelet and FIB4 levels. Hispanics had similarly high TE scores as AAs, but lower risk of developing HCC. The patients who remain at risk for HCC will be further stratified for increased propensity to develop HCC utilizing genomics, advanced imaging and screening for circulating tumor cells. These results suggest the need for enhanced investigation of key drivers of HCC, with particular attention to racial/ethnic disparities.Citation Format: Emmanuel Thomas, Deukwoo Kwon, Sid Rawal, Ashutosh Agarwal, Beatrice Madrazo, Steven Chen, Eugene Schiff. A multidisciplinary approach for HCC risk prediction in patients with cirrhosis utilizing elastography, imaging, circulating tumor cells and genomics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2411.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 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 ».