Dataset Information

Nomogram for Predicting Individual Survival After Recurrence of Advanced-Stage, High-Grade Ovarian Carcinoma.

ABSTRACT: OBJECTIVE:To analyze clinical prognostic factors for survival after recurrence of high-grade, advanced-stage ovarian-peritoneal-tubal carcinoma and to develop a nomogram to predict individual survival after recurrence. METHODS:We retrospectively analyzed patients treated in multicenter Gynecologic Oncology Group protocols for stage III and IV ovarian-peritoneal-tubal carcinoma who underwent primary debulking surgery, received chemotherapy with paclitaxel and a platinum compound, and subsequently developed recurrence. Prognostic factors affecting survival were identified and used to develop a nomogram, which was both internally and externally validated. RESULTS:There were 4,739 patients included in this analysis, of whom, 84% had stage III and 16% had stage IV ovarian carcinoma. At a median follow-up of 88.8 months (95% CI 86.2-92.0 months), the vast majority of patients (89.4%) had died. The median survival after recurrence was 21.4 months (95% CI 20.5-21.9 months). Time to recurrence after initial chemotherapy, clear cell or mucinous histology, performance status, stage IV disease, and age were significant variables used to develop a nomogram for survival after recurrence, which had a concordance index of 0.67. The time to recurrence alone accounted for 85% of the prognostic information. Similar results were found for patients who underwent second look laparotomy and had a complete pathologic response or received intraperitoneal chemotherapy. CONCLUSION:For individuals with advanced-stage ovarian carcinoma who recur after standard first-line therapy, estimated survivals after recurrence are closely related to the time to recurrence after chemotherapy and prognostic variables can be used to predict subsequent survival. CLINICAL TRIAL REGISTRATION:ClinialTrials.gov, NCT00002568, NCT00837993, NCT00002717, NCT01074398, and NCT00011986.

SUBMITTER: Rose PG

PROVIDER: S-EPMC6551603 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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Nomogram for Predicting Individual Survival After Recurrence of Advanced-Stage, High-Grade Ovarian Carcinoma.

Rose Peter G PG Java James J JJ Salani Ritu R Geller Melissa A MA Secord Angeles Alvarez AA Tewari Krishnansu S KS Bender David P DP Mutch David G DG Friedlander Michael L ML Van Le Linda L Method Michael W MW Hamilton Chad A CA Lee Roger B RB Wenham Robert M RM Guntupalli Saketh R SR Markman Maurie M Muggia Franco M FM Armstrong Deborah K DK Bookman Michael A MA Burger Robert A RA Copeland Larry J LJ

Obstetrics and gynecology 20190201 2

<h4>Objective</h4>To analyze clinical prognostic factors for survival after recurrence of high-grade, advanced-stage ovarian-peritoneal-tubal carcinoma and to develop a nomogram to predict individual survival after recurrence.<h4>Methods</h4>We retrospectively analyzed patients treated in multicenter Gynecologic Oncology Group protocols for stage III and IV ovarian-peritoneal-tubal carcinoma who underwent primary debulking surgery, received chemotherapy with paclitaxel and a platinum compound, a ...[more]

PMID: 30633128

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Project description:BackgroundVarious studies reported that the prognosis of patients with cervical cancer (CC) was significantly associated with immunity, whereas limited studies have explored whether immune-associated genes could be classifiers for recurrence-free survival (RFS) of stage I CC. Thus, an improved immune-related gene signature for stage I CC patients' prognosis is urgently required.Materials and methodsWe retrospectively analyzed the gene expression profiles of stage I CC patients in the GSE44001 set from the Gene Expression Omnibus (GEO) database. The stage I CC patients were randomly divided into the training group and the internal validation group. The training patients were adopted to develop a prognostic immune gene-based signature; meanwhile, the internal validation patients were used to validate the power of the selected immune gene-related signature using univariate Cox proportional hazard analysis, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis. The accuracy and reliability of the immune gene-related signature were evaluated based on Kaplan-Meier analysis and time-dependent receiver operating characteristic (ROC) curves.ResultsHigh power of the 8-immune gene signature was found on the basis of ROC analysis (AUC at 1, 3, and 5 years were exhibited in the internal validation group (0.702, 0.715, and 0.728, respectively), external validation group (0.702, 0.825, and 0.842, respectively), and entire GEO dataset (0.840, 0.894, and 0.852, respectively)). Besides, C-index, ROC, calibration plots, and decision curve analysis (DCA) also acted well in our nomogram, suggestive of a high ability of the nomogram to elevate the prognostic prediction of stage I CC patients.ConclusionsIn this study, we successfully constructed an integrated 8-immune gene-based signature which could accurately identify patients with low prognostic risk from those with high prognostic risk. In addition, we developed an immune-related nomogram which can elevate the prognostic prediction of stage I CC patients.

Dataset Information

Nomogram for Predicting Individual Survival After Recurrence of Advanced-Stage, High-Grade Ovarian Carcinoma.

Publications

Nomogram for Predicting Individual Survival After Recurrence of Advanced-Stage, High-Grade Ovarian Carcinoma.

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