Defining the Oligometastatic State and Predicting Overall Survival in Uterine Cancers using a Recursive Partitioning Analysis: A National Cancer Database Analysis

Abstract

Oligometastatic disease is an intermediate state between locoregional disease and widely metastatic disease. Studies have shown an overall survival advantage in oligometastatic patients treated aggressively in multiple cancers. However, few studies have explored this relationship in oligometastatic gynecological cancers. In this study, we sought to identify if an oligometastatic state with improved overall survival exists in uterine cancer and whether treatment patterns, or patient factors play a role in survival. The National Cancer Database was retrospectively analyzed in patients diagnosed with uterine cancer between 2004-2019. We excluded patients with non-metastatic disease at diagnosis, lack of metastatic sites listed, multiple primaries and missing survival data. Survival analyses were performed using Cox proportional hazards analyses and the Kaplan-Meier method and differences between groups were evaluated with log-rank tests. Recursive partitioning analysis (RPA) was performed using the rpart package in R. Amongst 641,276 women with uterine cancer, 17,343 were ultimately in our study population after exclusion who had a median age of 64 (range 18-90), median overall survival of 11.1 months, and a total of 24,337 metastases that represented the following metastatic sites: lung (35%), other (24%) (sites "other" than bone, brain liver or lung), liver (15%), bone (12%), distant lymph nodes (10%), brain (3%) and carcinomatosis (1%). Multivariate cox proportional hazards analysis identified the following variables as significantly associated with survival, which were then used for RPA: one metastatic site, treatment, grade, age, race, Charlson-Deyo score. The data was split 70/30% for training and validation, respectively. A survival model was built using RPA on the training data with 10-fold cross-validation and had accuracy of 76.25% (p = 3.393e-0.5). Survival prediction was performed on the internal validation data set with 76.69% accuracy (p = 0.004). RPA stratified 4 groups with the following median survivals: 5.9, 8.6, 29.5, and 43.8 months (log-rank test p<0.0001). The group with the best overall survival was defined by 1 metastatic site (carcinomatosis, distant lymph nodes and "other"), combination treatment with systemic therapy and radiation or surgery and low-grade histology. An oligometastatic state with involvement of one metastatic site does exist with improved survival in uterine cancer. The RPA defined groups may aid in identifying patients that are best suited for aggressive definitive combination therapy versus those that would be better suited for comfort care. Analysis is ongoing and will further delineate the relationship between specific treatment modalities and overall survival in patients with one metastatic site. This study may set the foundation for a prospective clinical trial.