Morbidity and Mortality of Total Pelvic Exenteration for Malignancy in the US.

BACKGROUND: Total pelvic exenterations (TPEs) for malignancies are complex operations often performed by multidisciplinary teams. The differences among primary cancer for TPE and multicentered results are not well described. We aimed to describe TPE outcomes for different malignant origins in a national multicentered sample. METHODS: Patients from the National Surgical Quality Improvement Program (NSQIP) database who underwent TPE between 2005 and 2016 for all malignant indications (colorectal, gynecologic, urologic, or other) were included. Chi square and Kruskal-Wallis tests were used to compare patient characteristics by primary malignancy. Multivariate logistic and linear regression models were used to determine factors associated with any 30-day Clavien-Dindo grade 3 or higher complication, length of hospital stay (LOS; days), 30-day wound infection, and 30-day mortality. RESULTS: Overall, 2305 patients underwent TPE. Indications for surgery included 33% (749) colorectal, 15% (335) gynecologic, 9% (196) other, and 45% (1025) urologic malignancies. Median LOS decreased from 10 to 8 days during the study period (p < 0.001), 36% were males, and 50% required blood transfusion. High-grade complications occurred in 15% of patients and were associated with bowel diversion [odds ratio (OR) 1.6, 95% confidence interval (CI) 1.1-2.4], disseminated cancer (OR 1.8, 95% CI 1.4-2.3), and gynecologic cancers (OR 2.9, 95% CI 1.8-4.7). Mortality was 2% and was associated with disseminated cancer (OR 2.2, 95% CI 1.1-4.3) and male sex (OR 2.4, 95% CI 1.3-4.4). CONCLUSIONS: TPE is associated with high rates of complications, however mortality rates remain low. Preoperative and perioperative outcomes differ depending on the origin of the primary malignancy.

Validated limited gene predictor for cervical cancer lymph node metastases.

PURPOSE: Recognizing the prognostic significance of lymph node (LN) involvement for cervical cancer, we aimed to identify genes that are differentially expressed in LN+ versus LN- cervical cancer and to potentially create a validated predictive gene signature for LN involvement. MATERIALS AND METHODS: Primary tumor biopsies were collected from 74 cervical cancer patients. RNA was extracted and RNA sequencing was performed. The samples were divided by institution into a training set (n = 57) and a testing set (n = 17). Differentially expressed genes were identified among the training cohort and used to train a Random Forest classifier. RESULTS: 22 genes showed > 1.5 fold difference in expression between the LN+ and LN- groups. Using forward selection 5 genes were identified and, based on the clinical knowledge of these genes and testing of the different combinations, a 2-gene Random Forest model of BIRC3 and CD300LG was developed. The classification accuracy of lymph node (LN) status on the test set was 88.2%, with an Area under the Receiver Operating Characteristic curve (ROC-AUC) of 98.6%. CONCLUSIONS: We identified a 2 gene Random Forest model of BIRC3 and CD300LG that predicted lymph node involvement in a validation cohort. This validated model, following testing in additional cohorts, could be used to create a reverse transcription-quantitative polymerase chain reaction (RT-qPCR) tool that would be useful for helping to identify patients with LN involvement in resource-limited settings.