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Enregistrement W4386271964 · doi:10.1111/jgh.16334

How can we improve surveillance system for alcohol‐associated hepatocellular carcinoma?

2023· letter· en· W4386271964 sur OpenAlexaboutno aff
K. Kim, Hye Won Lee, Sang Hoon Ahn

Notice bibliographique

RevueJournal of Gastroenterology and Hepatology · 2023
Typeletter
Langueen
DomaineMedicine
ThématiqueLiver Disease Diagnosis and Treatment
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicineHepatocellular carcinomaAlcoholic liver diseaseCirrhosisLiver diseaseInternal medicineLiver transplantationFatty liverGastroenterologySteatosisAlcoholic hepatitisDiseaseTransplantation

Résumé

récupéré en direct d'OpenAlex

Promoting compliance with hepatocellular carcinoma (HCC) surveillance in alcoholic patients is challenging. As Jacob et al.1 stated, alcohol is one of the leading causes of chronic liver diseases, which range from the initial stages of steatosis to hepatitis, cirrhosis, and HCC. With the rise in global adult per-capital alcohol consumption, reducing HCC mortality is an important. Currently, the American Association for the Study of Liver Diseases (AASLD) and European Association for the Study of Liver Diseases (EASL) recommend screening for HCC in patients with liver cirrhosis of Child-Pugh A, B, or C who are candiates for transplantation.2, 3 The recommended screening frequency is every 6 months using ultrasound with or without analysis of the alpha-fetoprotein level. Surveillance can lead to earlier detection of HCC, thereby lowering the mortality rate. At the time of diagnosis, most patients with alcohol-associated HCC have advanced disease, and they are frequently identified outside the surveillance program. This might be associated with late referrals, suboptimal compliance with surveillance, insufficient disease awareness, provider perceptinos of the likelihood of patient complaince, and alcohol dependence. It is important to estimate the risk of HCC in patients with alcohol-associated liver diseases. The risk factors for alcohol-associated HCC include the level of alcohol consumption, female sex, smoking, concomitant liver disease, obesity, diabetes, and genetics. The genetic polymorphisms associated with alcohol-associated HCC include those in patatin-like phospholipase domain containing 3 variants in the transmembrane 6 superfamily 2, and membrane-bound O-acyltransferase domain containing 7.4 Incorporating these clinical and genetic risk factors in risk scores would benefit patients undergoing screening for HCC. As reviewed by Jacob et al.,1 several risk scores for HCC are available for use in cirrhotic patients. The ADRESS-HCC model predicts the 1-year probability of HCC in cirrhotic patients. This model was developed using a national liver transplant waitlist cohort (n = 17,124 patients); its c-index was 0.691 in the validation set.5 The Toronto HCC risk index (THRI) in cirrhotic patients showed good c-index of 0.77 in the external validation set.6 The aMAP risk score was developed based on 11 cohorts, and showed strong performance (c-incex of 0.82–0.87).7 However, the cohorts were composed mainly of patients with chronic viral hepatitis: only one included patients with non-viral hepatitis. Furthermore, the non-viral hepatitis cohort was composed, primarily, of patients with nonalcoholic fatty liver disease, and excessive alcohol was considered an additional risk factor in only 11% of the patients. The aMAP score yielded a c-index of 0.85 in the non-viral hepatitis cohort, which was validated in a study involving of 269 patients with alcohol-assocaited cirrhosis (c-index 0.82–0.83). Further validation in a greater number of patients with alcohol-associated cirrhosis is needed.8 The above-mentioned scores are useful for assessing the HCC risk in cirrhotic patients. However, these scores were developed for mixed etiologies, and do not incorporate genetic risk factors. Further studies should focus on developing alcohol-associated HCC risk scores, which could potentially include genetic risk factors. According to a systematic review, a small proportion of patients with cirrhosis undergo the recommended surveillance (pooled surveillance rate 18.4%).9 Pharmacological psychosocial, and combined strategies for maintaining alcohol abstinence are used in primary care clinics. Mail-based outreach has been shown to be effective in multiple randomized clinical trials (RCT). In a recent RCT by Singal et al.,10 1436 patients in the mail-based outreach arm and 1436 in the visit-based surveillance arm were compared, and all etiologies of liver disease were included. In the mail-based outreach arm, reminder telephone calls were made to patients who did not respond within 2 weeks. The mail-based outreach arm had a significantly higher recommended surveillance rate (35.1% vs. 21.9%), a lower no surveillance rate (29.8% vs. 43.5%) and a greater proportion of time covered by surveillance (41.3% vs. 31.0%) than the visit-based survellance arm. Other RCTs using the mail-based outreach method revealed higher surveillance rates in the mailed outreach arm, compared to the usual-care arm.11, 12 Other types of interventions include patient education, clinical reminders for providers, HCC surveillance compliance reporting, provider education, chronic disease management software, and outreach nurses. Although the mail-based outreach method has been demonstrated to be effective in several RCTs, the surveillance rate needs to be increased further. Patient education and chronic disease management software have been evaluated in RCTs, but the results are controversial; therefore, more RCTs are needed. Additionally, all the above-mentioned methods were developed and validated for chronic liver disease of any cause. Therefore, they need to be validated in patients with alcohol-associated cirrhosis. Implementation of multiple strategies to enhance the surveillance rate will be challenging. For instance, a digital intervention using a smartphone application is a possibility, because such a system used in the management of other chronic liver diseases.13 In conclusion, effective management alcohol-associated liver diseases is vital. It is important to identify patients at high risk for alcohol-associated HCC and to assess the HCC risk continuously in these patients. Moreover, increasing the rate of compliance with surveillance is an important task, which will require the development of novel methods as well as further research studies.

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,010
score de la tête « metaresearch » (Gemma)0,040
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,020
Score d'incertitude au seuil0,067

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0100,040
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,002
Bibliométrie0,0030,001
Études des sciences et des technologies0,0010,001
Communication savante0,0030,007
Science ouverte0,0020,003
Intégrité de la recherche0,0040,004
Charge utile insuffisante (le modèle a refusé de juger)0,0200,008

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.

Tête enseignante Opus0,023
Tête enseignante GPT0,243
Écart entre enseignants0,220 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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