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

  • Lorenzo Gerratana
  • Jean-Yves Pierga
  • James M Reuben
  • Andrew A Davis
  • Firas H Wehbe
  • Luc Dirix
  • Tanja Fehm
  • Franco Nolé
  • Rafael Gisbert-Criado
  • Dimitrios Mavroudis
  • Salvatore Grisanti
  • Jose A Garcia-Saenz
  • Justin Stebbing
  • Carlos Caldas
  • Paola Gazzaniga
  • Luis Manso
  • Rita Zamarchi
  • Marta Bonotto
  • Angela Fernandez de Lascoiti
  • Leticia De Mattos-Arruda
  • Michail Ignatiadis
  • Maria-Teresa Sandri
  • Daniele Generali
  • Carmine De Angelis
  • Sarah-Jane Dawson
  • Wolfgang Janni
  • Vicente Carañana
  • Sabine Riethdorf
  • Erich-Franz Solomayer
  • Fabio Puglisi
  • Mario Giuliano
  • Klaus Pantel
  • François-Clément Bidard
  • Massimo Cristofanilli

Beteiligte Einrichtungen

Abstract

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 (StageIVaggressive vs StageIVindolent). The model had a 65.1% accuracy and its prognostic impact resulted in a hazard ratio (HR) of 1.89 (Simulatedaggressive vs Simulatedindolent 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 Simulatedaggressive had a significantly worse overall survival (OS; P < .0001), while patients with liver metastases classified as Simulatedindolent 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 Simulatedaggressive patients (HR: 0.62; P = .030 and HR: 0.60; P = .037, respectively, for PFS and OS).

Bibliografische Daten

OriginalspracheEnglisch
ISSN1083-7159
DOIs
StatusVeröffentlicht - 05.07.2022

Anmerkungen des Dekanats

© The Author(s) 2022. Published by Oxford University Press.

PubMed 35278078