Evidence map›Paper›PMID 39682268›Full record

ReviewCancers2024

Predictive Factors of Antibody-Drug Conjugate Treatment in Metastatic Breast Cancer: A Narrative Review.

Gennaro Gadaleta-Caldarola, Laura Lanotte, Anna Natalizia Santoro, Antonello Pinto, Arianna Gadaleta-Caldarola, Luca Giacomelli, Palma Fedele

Abstract readReview
In one paragraph

Review in Cancers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Gennaro Gadaleta-CaldarolaOncology Unit, "Mons. A. R. Dimiccoli" Hospital, 70051 Barletta, Italy.
Laura LanotteOncology Unit, "Mons. A. R. Dimiccoli" Hospital, 70051 Barletta, Italy.
Anna Natalizia SantoroOncology Unit, "Dario Camberlingo" Hospital, 72021 Francavilla Fontana, Italy.
Antonello PintoOncology Unit, "Dario Camberlingo" Hospital, 72021 Francavilla Fontana, Italy.
Arianna Gadaleta-CaldarolaMedicine and Surgery, Università degli Studi di Siena, 53100 Siena, Italy.
Luca GiacomelliPolistudium SRL, 20121 Milan, Italy.
Palma FedeleOncology Unit, "Dario Camberlingo" Hospital, 72021 Francavilla Fontana, Italy.ORCID 0000-0002-7437-4676

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Antibody-drug conjugates (ADCs) have revolutionized the treatment landscape for metastatic breast cancer, offering targeted delivery of cytotoxic agents with improved efficacy and tolerability compared to conventional chemotherapy. This narrative review explores key predictive factors influencing the efficacy of ADCs, focusing on HER2-targeted therapies, such as trastuzumab emtansine and trastuzumab deruxtecan, as well as sacituzumab govitecan for triple-negative breast cancer. HER2 expression, TROP-2 levels, hormone receptor status, and the tumor microenvironment emerge as critical biomarkers for patient selection and therapeutic outcomes. Additionally, we discuss resistance mechanisms, such as antigen loss, impaired drug internalization, and the role of circulating tumor DNA in predicting ADC response. Finally, future perspectives on the sequential use of ADCs and potential combination therapies are highlighted, along with emerging agents targeting alternative antigens like HER3 and LIV-1. Overall, identifying predictive biomarkers and overcoming resistance mechanisms are essential for optimizing the use of ADCs in metastatic breast cancer, thereby improving patient outcomes.

Indexed as

antibody–drug conjugatesHER2metastatic breast cancerpredictive factorssacituzumab govitecantrastuzumab deruxtecantrastuzumab emtansineTROP-2

Identifiers

PMID39682268
PMCPMC11640339

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.