ArticleThe oncologist2024
Circulating Tumor Cells Prediction in Hormone Receptor Positive HER2-Negative Advanced Breast Cancer: A Retrospective Analysis of the MONARCH 2 Trial.
Article in The oncologist, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02107703 (MONARCH 2), which is not on this map. Cited by 2 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
MONARCH 2: A Randomized, Double-Blind, Placebo-Controlled, Phase 3 Study of Fulvestrant With or Without Abemaciclib, a CDK4/6 Inhibitor, for Women With Hormone Receptor Positive, HER2 Negative Locally Advanced or Metastatic Breast Cancer
Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.
- Circulating Tumor Cell Detection for Therapeutic and Prognostic Roles in Breast Cancer.Cancer medicine · 2025Pooled it
- A scoping review of artificial intelligence applications in clinical trial risk assessment.NPJ digital medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 5 institutions in 2 countries.
Funding
Abstract
backgroundThe MONARCH 2 trial (NCT02107703) showed the efficacy of abemaciclib, a cyclin-dependent kinase 4 & 6 inhibitor (CDK4/6i), in combination with fulvestrant for hormone receptor-positive, HER2-negative metastatic breast cancer (MBC). The aim of this analysis was to explore the prediction of circulating tumor cells (CTCs) stratification using machine learning for hypothesis generation of biomarker-driven clinical trials. PATIENTS AND
methodsPredicted CTCs were computed in the MONARCH 2 trial through a K nearest neighbor (KNN) classifier trained on a dataset comprising 2436 patients with MBC. Patients were categorized into predicted Stage IVaggressive (pStage IVaggressive, ≥5 predicted CTCs) or predicted Stage IVindolent (pStage IVindolent, <5 predicted CTCs). Prognosis was tested in terms of progression-free-survival (PFS) and overall survival (OS) through Cox regression.
resultsPatients classified as predicted pStage IVaggressive and predicted pStage Stage IVindolent were, respectively, 183 (28%) and 461 (72%). After multivariable Cox regression, predicted CTCs were confirmed as independently associated with prognosis in terms of OS, together with ECOG performance status, liver involvement, bone-only disease, and treatment arm. Patients in the pStage Stage IVindolent subgroup treated with abemaciclib experienced the best prognosis both in terms of PFS and OS. The treatment effect of abemaciclib on OS was then explored through subgroup analysis, showing a consistent benefit across all subgroups.
conclusionThis study is the first analysis of CTCs modeling for stage IV disease stratification. These results show the need to expand biomarker profiling in combination with CTCs stratification for improved biomarker-driven drug development.
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Registered trials
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