Français
Albanian
Arabic
Armenian
Azerbaijani
Belarusian
Bengali
Bosnian
Catalan
Czech
Danish
Deutsch
Dutch
English
Estonian
Finnish
Français
Greek
Haitian Creole
Hebrew
Hindi
Hungarian
Icelandic
Indonesian
Irish
Italian
Japanese
Korean
Latvian
Lithuanian
Macedonian
Mongolian
Norwegian
Persian
Polish
Portuguese
Romanian
Russian
Serbian
Slovak
Slovenian
Spanish
Swahili
Swedish
Turkish
Ukrainian
Vietnamese
Български
中文(简体)
中文(繁體)
Nutrition and Cancer 2018-Sep

Serum Albumin at Diagnosis is an Independent Predictor of Early Mortality in Veteran Patients with Esophageal Cancer.

Seuls les utilisateurs enregistrés peuvent traduire des articles
Se connecter S'inscrire
Le lien est enregistré dans le presse-papiers
Ammar Nassri
Hong Zhu
David H Wang
Zeeshan Ramzan

Mots clés

Abstrait

OBJECTIVE

To identify independent factors that could predict mortality within 6 months in a cohort of patients with esophageal cancer.

METHODS

Esophageal cancer patients were grouped into early (≤6 months, n = 41) and late (>6 months, n = 81) mortality groups. 52 variables were analyzed by univariable analysis (UA). A multivariable (MVA) regression model was created to identify predictors of early mortality.

RESULTS

When comparing early and late mortality groups, there was no difference in age, BMI, race, histology, or anatomic location between the two groups. UA demonstrated that the early mortality group had a lower mean albumin level (3.3 ± 0.1 g/dl vs. 3.8 ± 0.1 g/dl; P < 0.001), poorer ECOG performance status (1.9 ± 0.2 vs. 1.1 ± 0.1, P = 0.02), higher WBC count (9.6 ± 0.7 K/µL vs. 8.2 ± 0.3 K/µL, P = 0.04), and were less likely to receive surgery (2.4% vs. 22.2%; P = 0.003), neoadjuvant treatment (4.9% vs. 28.4%; P = 0.009) and definitive chemoradiation (7.3% vs. 27.2%; P = 0.01). MVA revealed that only low albumin at diagnosis was an independent predictor of survival (P = 0.016).

CONCLUSIONS

Albumin level at diagnosis is an independent predictor of early mortality and might be used with other variables to provide prognostic information for patients and to guide treatment.

Rejoignez notre
page facebook

La base de données d'herbes médicinales la plus complète soutenue par la science

  • Fonctionne en 55 langues
  • Cures à base de plantes soutenues par la science
  • Reconnaissance des herbes par image
  • Carte GPS interactive - étiquetez les herbes sur place (à venir)
  • Lisez les publications scientifiques liées à votre recherche
  • Rechercher les herbes médicinales par leurs effets
  • Organisez vos intérêts et restez à jour avec les nouvelles recherches, essais cliniques et brevets

Tapez un symptôme ou une maladie et lisez des informations sur les herbes qui pourraient aider, tapez une herbe et voyez les maladies et symptômes contre lesquels elle est utilisée.
* Toutes les informations sont basées sur des recherches scientifiques publiées

Google Play badgeApp Store badge