Evidence map›Paper›PMID 37637230›Full record

ReviewBreast cancer : basic and clinical research2023

Hormone Receptor-Positive / HER2-Negative Early Breast Cancer High-Risk Population: An Algorithm for Optimization Systemic Adjuvant Treatment Based on 2022 Updates.

Daniel González-Hurtado, Sergio Rivero, Juan Carlos Samamé Pérez-Vargas, Fernando E Petracci

Abstract readReview
In one paragraph

Review in Breast cancer : basic and clinical research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Guideline
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

4 authors.

Daniel González-HurtadoClínica de Oncología Astorga, Medellín, Colombia.
Sergio RiveroInstituto Alexander Fleming, Buenos Aires, Argentina.
Juan Carlos Samamé Pérez-VargasClínica San Felipe, Hospital Nacional Arzobispo Loayza, Lima, Perú.
Fernando E PetracciInstituto Alexander Fleming, Clínica San Camilo, Buenos Aires, Argentina.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Prognostic and predictive factors for early and late distant distance recurrence risk in estrogen-receptor positive and HER2-receptor negative early breast cancer are well known, but not all these variables work equally for the prediction. The following are the most widely accepted variables for categorizing risk levels: clinic-pathologic features (tumor size, lymph node involvement, histological grade, age, menopausal status, Ki-67 expression, estrogen, and progesterone expression), primary systemic treatment response (pathologic response and/or Ki-67 downstaging), and gene expression signatures stratification. Treatment guidelines from cancer societies and collaborative groups, online predict-tools, real-world data and experts' opinion recommends different adjuvant strategies (chemotherapy, endocrine therapy, ovarian suppression, olaparib, or abemaciclib) depending on the low (< 10%), intermediate (10%-20%) or high-risk of distance recurrence at least in the first 5 years. Multiple randomized prospective trials were updated in 2022, that evidence allow us to perform a stratification of risk in pre- and postmenopausal women with estrogen-receptor positive and HER2-receptor negative early breast cancer based on a combination of clinic-pathologic features and genomic assays and guide the adjuvant systemic treatment recommendation for those with high risk.

Indexed as

adjuvant treatmentearly breast cancerEstrogen-receptor positivehigh risk

Identifiers

PMID37637230
PMCPMC10450458

What OpenQuestion holds

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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.