Dataset Information

Stratification of risk groups according to survival after recurrence in endometrial cancer patients.

ABSTRACT: To identify prognostic factors for overall survival after recurrence (OSr) in endometrioid endometrial cancer (EC) patients and categorize patient subgroups that predict outcomes using these variables.Consecutive patients with recurrent endometrioid EC seen in our institution from 1989 to 2013 were retrospectively reviewed. Cox regression models were used to identify the clinicopathological factors associated with OSr. By summing scores proportionate to the hazard ratio (HR) for each significant variable, we stratified patients into 3 risk groups.Enrolled patients (n?=?108) had a median time to recurrence of 15 (range, 3-163) months after initial treatment and a median OSr of 22 (range, 1-207) months. Twenty patients (18.5%) had locoregional recurrence, and 88 (81.5%) distant. One hundred three patients underwent salvage therapy; 51 (47.2%) received chemotherapy only, 22 (20.3%) received radiotherapy either alone or combined with chemotherapy, and 29 (26.9%) underwent salvage cytoreductive surgery. Multivariate regression analysis revealed that time to relapse after initial treatment, cancer antigen-125 level at recurrence, and the number of recurrent lesions were independent predictors of OSr. Incorporating these factors, we stratified patients into low-risk (n?=?19), intermediate-risk (n?=?43), and high-risk (n?=?46) groups. The likelihood of cancer-specific death was higher in both the high-risk (HR?=?8.948, 95% confidence interval [CI]?=?3.498-22.893, P?

SUBMITTER: Shim SH

PROVIDER: S-EPMC5457863 | biostudies-other | 2017 May

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Stratification of risk groups according to survival after recurrence in endometrial cancer patients.

Shim Seung-Hyuk SH Kim Dae-Yeon DY Kim Hyun Jung HJ Lee Shin-Wha SW Park Jeong-Yeol JY Suh Dae-Shik DS Kim Jong-Hyeok JH Kim Yong-Man YM Kim Young-Tak YT Nam Joo-Hyun JH

Medicine 20170501 21

To identify prognostic factors for overall survival after recurrence (OSr) in endometrioid endometrial cancer (EC) patients and categorize patient subgroups that predict outcomes using these variables.Consecutive patients with recurrent endometrioid EC seen in our institution from 1989 to 2013 were retrospectively reviewed. Cox regression models were used to identify the clinicopathological factors associated with OSr. By summing scores proportionate to the hazard ratio (HR) for each significant ...[more]

PMID: 28538383

Similar Datasets

Project description:BackgroundSite-specific postoperative risk models for localized upper tract urothelial carcinoma (UTUC) are unavailable.ObjectiveTo create specific risk models for renal pelvic urothelial carcinoma (RPUC) and ureteral urothelial carcinoma (UUC), and to compare the predictive accuracy with the overall UTUC risk model.Design setting and participantsA multi-institutional database retrospective study of 1917 UTUC patients who underwent radical nephroureterectomy (RNU) between 2000 and 2018 was conducted.Outcome measurements and statistical analysisA multivariate hazard model was used to identify the prognostic factors for extraurinary tract recurrence (EUTR), cancer-specific death (CSD), and intravesical recurrence (IVR) after RNU. Patients were stratified into low-, intermediate-, high-, and highest-risk groups. External validation was performed to estimate a concordance index of the created risk models. We investigated whether our risk models could aid decision-making regarding adjuvant chemotherapy (AC) after RNU.Results and limitationsThe UTUC risk models could stratify the risk of cumulative incidence of three endpoints. The RPUC- and UUC-specific risk models showed better stratification than the overall UTUC risk model for all the three endpoints, EUTR, CSD, and IVR (RPUC: concordance index, 0.719 vs 0.770, 0.714 vs 0.794, and 0.538 vs 0.569, respectively; UUC: 0.716 vs 0.767, 0.766 vs 0.809, and 0.553 vs 0.594, respectively). The UUC-specific risk model can identify the high- and highest-risk patients likely to benefit from AC after RNU. A major limitation was the potential selection bias owing to the retrospective nature of this study.ConclusionsWe recommend using site-specific risk models instead of the overall UTUC risk model for better risk stratification and decision-making for AC after RNU.Patient summaryUpper tract urothelial carcinoma comprises renal pelvic and ureteral carcinomas. We recommend using site-specific risk models instead of the overall upper tract urothelial carcinoma risk model in risk prediction and decision-making for adjuvant therapy after radical surgery.

Dataset Information

Stratification of risk groups according to survival after recurrence in endometrial cancer patients.

Publications

Stratification of risk groups according to survival after recurrence in endometrial cancer patients.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure