New diagnostic techniques for the differential diagnosis of a pancreatic mass: Contrast-enhanced EUS… It doesn't help me…
Notice bibliographique
Résumé
There is empirical proof that contrast-enhanced endoscopic ultrasound EUS (C-EUS) is not indispensable; since there are entire continents where contrast is not even available, yet there is no evidence that the outcomes of EUS are better where contrast is available. Obviously, the primary differential diagnosis in patients with a pancreatic mass is cancer. Therapeutic options for cancer (surgery, chemotherapy radiotherapy) generally have potentially serious consequences. Therefore, management decisions in patients with cancer generally require diagnostic certainty. Cancer is a histological diagnosis, and histology requires a biopsy! C-EUS would be of true value if it provided sufficient certainty to avoid biopsy – meaning it would have to be a very accurate and reproducible form of “optical biopsy.” Unfortunately, the experience with other forms of optical biopsy has shown that while interesting, for whatever reason, they have not come into widespread use in clinical practice. It is possible that the added time, expense, and added medicolegal responsibility (of replacing a pathologist) may not be justifiable (financially or otherwise). Meta-analysis reports that the accuracy of C-EUS is approximately 90%.[1] This is high but still means that C-EUS is mistaken in 1 of 10 cases. This is unacceptable when making decisions in patients with suspected cancer. The reported accuracy of C-EUS is encouraging but is not better than that of other forms of optical biopsy. In addition, there are several issues that may limit or overestimate its true ability to diagnose or exclude cancer. EUS-fine-needle aspiration (FNA) is the gold standard for the diagnosis of pancreatic cancer. It is safe, extremely effective and provides a true issue diagnosis.[2] Therefore, EUS-FNA provides a diagnosis in the great majority of cases. Optical biopsy should be used in cases where EUS-FNA is contraindicated or “indeterminate”. Therein lies the major problem with studies comparing C-EUS to EUS-FNA. In these studies, obvious cancers (or cancers that are FNA positive) were not excluded. The accuracy for obvious lesions is higher than for equivocal cases including these cases introduces “spectrum bias.” The spectrum of the patients does not represent the true spectrum of disease in which C-EUS is likely to be used. In patients with truly indeterminate (FNA-negative) lesions, the accuracy and interobserver agreement of C-EUS is likely lower. In addition, the endosonographer performing C-EUS cannot be blinded to the EUS b-mode appearance. It is unclear whether this may also artificially increase its reported accuracy. Finally, what is the true “incremental” value of C-EUS? In other words, what is the true added clinical decision-making value of the information provided by C-EUS over the available clinical information: Clinical suspicion for cancer (e.g., the presence or absence of systemic symptoms, pain, jaundice, etc.), computed tomography scan results, the b-mode EUS image (including the presence or absence of indirect signs of cancer such as pancreatic duct obstruction), and EUS-FNA results. If the C-EUS agrees with above, that is reassuring. If it disagrees, will management truly change? Will it really prevent surgery? It is unclear, but quite possible that except for very select indications, the answer is “No.”
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 | 0,000 | 0,010 |
| 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 | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».