Optimal cutoff age for predicting prognosis associated with serous epithelial ovarian cancer: what is the best age cutoff? / 부인종양
Journal of Gynecologic Oncology
; : e11-2019.
Article
Dans En
| WPRIM
| ID: wpr-719310
Responsable en Bibliothèque :
WPRO
ABSTRACT
OBJECTIVE:
Elderly age is one of the poor prognostic factors in epithelial ovarian cancer (EOC), but the optimal age cut-off is not known. The present study sought to identify the ideal age cutoff that represents a negative prognostic factor in EOC, considering the geriatric assessment.METHODS:
Hazard ratios (HRs) with p-values were calculated using all possible age cutoffs with stage, histology, grade, optimality and comorbidities as covariates in multivariate Cox regression model. The trends of p-value and HR by age cutoff were further evaluated in a subgroup of histology and in The Cancer Genome Atlas (TCGA) dataset. In addition, propensity score-matching analysis using the identified age cutoff was performed.RESULTS:
An age of 66 years was shown to be the most significant cutoff for defining old age with independent prognostic power (HR=1.45; 95% confidence interval=1.04–2.03; p=0.027). This result was also observed with the analyses of serous histology subgroup and with the analysis of a TCGA dataset with serous EOC. In survival analysis, patients aged ≥66 years had significantly worse overall survival compared with younger individuals (56 months vs. 87 months; p=0.006), even following propensity score matching (57 vs. 78 months; p=0.038).CONCLUSION:
An age of 66 years is the best cutoff to define elderly age in serous EOC patients considering the geriatric assessment, and this information can be used in the administration of individualized therapies in elderly EOC patients.
Texte intégral:
1
Indice:
WPRIM
Sujet Principal:
Tumeurs de l'ovaire
/
Pronostic
/
Comorbidité
/
Évaluation gériatrique
/
Génome
/
Score de propension
/
Ensemble de données
Type d'étude:
Prognostic_studies
Limites du sujet:
Aged
/
Humans
langue:
En
Texte intégral:
Journal of Gynecologic Oncology
Année:
2019
Type:
Article