Modeling the Prognostic Impact of Circulating Tumor Cells Enumeration in Metastatic Breast Cancer for Clinical Trial Design Simulation

Despite the strong prognostic stratification of circulating tumor cells (CTCs) enumeration in metastatic breast cancer (MBC), current clinical trials usually do not include a baseline CTCs in their design. This study aimed to generate a classifier for CTCs prognostic simulation in existing datasets for hypothesis generation in patients with MBC. A K-nearest neighbor machine learning algorithm was trained on a pooled dataset comprising 2436 individual MBC patients from the European Pooled Analysis Consortium and the MD Anderson Cancer Center to identify patients likely to have CTCs >= 5/7 mL blood (StageIV(aggressive) vs StageIV(indolent)). The model had a 65.1% accuracy and its prognostic impact resulted in a hazard ratio (HR) of 1.89 (Simulated(aggressive) vs Simulated(indolent) P < .001), similar to patients with actual CTCs enumeration (HR 2.76; P < .001). The classifier's performance was then tested on an independent retrospective database comprising 446 consecutive hormone receptor (HR)-positive HER2-negative MBC patients. The model further stratified clinical subgroups usually considered prognostically homogeneous such as patients with bone-only or liver metastases. Bone-only disease classified as Simulated(aggressive) had a significantly worse overall survival (OS; P < .0001), while patients with liver metastases classified as Simulated(indolent) had a significantly better prognosis (P < .0001). Consistent results were observed for patients who had undergone CTCs enumeration in the pooled population. The differential prognostic impact of endocrine- (ET) and chemotherapy (CT) was explored across the simulated subgroups. No significant differences were observed between ET and CT in the overall population, both in terms of progression-free survival (PFS) and OS. In contrast, a statistically significant difference, favoring CT over ET was observed among Simulated(aggressive) patients (HR: 0.62; P = .030 and HR: 0.60; P = .037, respectively, for PFS and OS).

Automated summary

This study developed a classifier for prognostic simulation of circulating tumor cells (CTCs) in metastatic breast cancer (MBC) patients. The classifier accurately predicted patients' prognosis and stratified them into different clinical subgroups. It also revealed differential prognostic impact of endocrine therapy (ET) and chemotherapy (CT) in different subgroups.