Evidence map›Paper›PMID 40623476›Full record

ArticleAnnals of oncology : official journal of the European Society for Medical Oncology2025

Prognostic significance of early on-treatment evolution of circulating tumor DNA in advanced ER-positive/HER2-negative breast cancer.

A Mamann, Y Pradat, F C Bidard, S Delaloge, L Cabel, I Faull, S Marques, T Bachelot, F Dalenc, T de la Motte Rouge and 15 more

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Article in Annals of oncology : official journal of the European Society for Medical Oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Liquid biopsy in solid tumours: expert opinion paper of the European society of pathology.Virchows Archiv : an international journal of pathology · 2026
    Review
  6. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

25 authors.

A MamannLaboratory of Mathematics and Computer Science MICS, CentraleSupélec, Université Paris-Saclay, Gif-sur-Yvette, France; Oncostat, Inserm U1018, CESP, La Ligue Contre le Cancer, Université Paris-Saclay, Villejuif, France.
Y PradatUMR 981, Gustave Roussy, Villejuif, France; IHU PRISM National Precision Medicine Center in Oncology, Gustave Roussy, Villejuif, France.
F C BidardInserm CIC-BT 1428, Institut Curie, Saint-Cloud, France; UVSQ, Paris-Saclay University, Saint-Cloud, France.
S DelalogeDepartment of Medical Oncology, Gustave Roussy, Villejuif, France.
L CabelDepartment of Medical Oncology, Institut Curie, Saint-Cloud, France.
I FaullMedical Affairs Department, Guardant Health Europe, Barcelona, Spain.
S MarquesResearch and Development Department, Unicancer, Paris, France.
T BachelotMedical Oncology Department, Centre Léon Bérard, Lyon, France.
F DalencCancer Research Center Toulouse, UMR 1037, Inserm, Toulouse, France; Medical Oncology Department, Oncopole Claudius Regaud, IUCT, Toulouse, France; Paul Sabatier University, Toulouse, France.
T de la Motte RougeMedical Oncology Department, Centre Eugène Marquis, Rennes, France.
B PistilliDepartment of Medical Oncology, Gustave Roussy, Villejuif, France.
J SamaniegoUMR 981, Gustave Roussy, Villejuif, France; IHU PRISM National Precision Medicine Center in Oncology, Gustave Roussy, Villejuif, France.
J S FrenelMedical Oncology Department, Institut de Cancerologie de L'Ouest, Saint-Herblain, France; Nantes Université, Inserm, CRCI2NA, Nantes, France.
C LevyDepartment of Medical Oncology, Centre François Baclesse, Caen, France.
J M FerreroDepartment of Medical Oncology, Centre Antoine Lacassagne, Nice, France.
R SabatierDepartment of Medical Oncology, Institut Paoli Calmettes, CRCM, Predictive Oncology Laboratory, Aix-Marseille Université, Inserm, CNRS, Marseille, France.
S LadoireDepartment of Medical Oncology, Centre Georges François Leclerc, Dijon, France.
C ChakibaDepartment of Medical Oncology, Institut Bergonié, Bordeaux, France.
A C HardyDepartment of Medical Oncology, Centre Armoricain d'Oncologie, Plérin, France.
J LemonnierResearch and Development Department, Unicancer, Paris, France.
Y MahiMedical Affairs Department, Guardant Health Europe, Paris.
F AndreUMR 981, Gustave Roussy, Villejuif, France; IHU PRISM National Precision Medicine Center in Oncology, Gustave Roussy, Villejuif, France; Department of Medical Oncology, Gustave Roussy, Villejuif, France.
P H CournedeLaboratory of Mathematics and Computer Science MICS, CentraleSupélec, Université Paris-Saclay, Gif-sur-Yvette, France.
S MichielsOncostat, Inserm U1018, CESP, La Ligue Contre le Cancer, Université Paris-Saclay, Villejuif, France; Department of Biostatistics and Epidemiology, Gustave Roussy, Villejuif.
E BernardUMR 981, Gustave Roussy, Villejuif, France; IHU PRISM National Precision Medicine Center in Oncology, Gustave Roussy, Villejuif, France. Electronic address: elsa.bernard@gustaveroussy.fr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPatients with advanced estrogen receptor-positive, HER2-negative breast cancer commonly develop resistance to treatment with hormone therapy and cyclin-dependent kinase 4/6 (CDK4/6) inhibitors. Responders cannot be distinguished from nonresponders after the first cycle of treatment under current practice. We assessed circulating tumor DNA (ctDNA) measures at early timepoints as prognostic markers. PATIENTS AND

methodsPaired plasma samples were collected at baseline and early on-treatment (median 28 days) from 369 patients with advanced ER-positive/HER2-negative breast cancer treated in the PADA-1 trial with hormone therapy and a CDK4/6 inhibitor. Cell-free DNA was profiled with a 497-gene panel (Guardant360 LDT).

resultsBaseline ctDNA levels, including the mean variant allele frequency (VAF) [progression-free survival (PFS) hazard ratio (HR) 1.07, 95% confidence interval (CI) 1.05-1.09), P < 0.001; overall survival (OS) HR 1.08, 95% CI 1.05-1.11, P < 0.001] and the number of driver somatic mutations (PFS HR 1.13, 95% CI 1.07-1.19, P < 0.001; OS HR 1.16, 95% CI 1.07-1.24, P < 0.001) were prognostic. Early on-treatment ctDNA dynamics were also associated with outcomes, including the number of driver somatic mutations with VAF > 0.5% at both timepoints (PFS HR 1.39, 95% CI 1.27-1.53, P < 0.001; OS HR 1.51, 95% CI 1.35-1.68, P < 0.001) and the number of driver somatic mutations with a VAF increase (PFS HR 1.31, 95% CI 1.19-1.44, P < 0.001; OS HR 1.10, 95% CI 1.02-1.18, P = 0.02). A ctDNA-based risk model incorporating baseline and dynamic ctDNA features was independently prognostic from RECIST in multivariable models (test set: OS HR 4.10, 95% CI 1.93-8.72, P < 0.001; PFS HR 1.86, 95% CI 1.16-2.97, P = 0.009). The integration of ctDNA features into a clinical model improved survival discrimination for PFS [C-index 64.7% (± 2.5%) for a ctDNA and clinical model versus 59.3% (± 2.2%) for a clinical-only model, P = 0.027] and for OS [C-index 70.0% (± 3.4%) versus 60.3% (± 4.2%), P = 0.035].

conclusionsEarly on-treatment evolution of ctDNA is prognostic for both PFS and OS in advanced ER-positive/HER2-negative breast cancer. A ctDNA-based risk model improves upon traditional RECIST and clinical parameters, advocating for ctDNA as a prognostic biomarker in clinical practice.

Indexed as

Antineoplastic Combined Chemotherapy ProtocolsBiomarkers, TumorBreast NeoplasmsCirculating Tumor DNAAdultAgedErb-b2 Receptor Tyrosine KinasesFemaleHumansMiddle AgedPrognosisProgression-Free SurvivalReceptors, EstrogenBiomarkers, TumorCirculating Tumor DNAERBB2 protein, humanErb-b2 Receptor Tyrosine KinasesReceptors, Estrogencirculating tumor DNAER+/HER2− advanced breast canceron-treatment dynamicsprognostic modelrisk scoresurvival analysis

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.