ArticleBMC proceedings2021
Optimizing treatment selection, and sequencing decisions for Management of HR-Positive, HER2-Negative advanced breast cancer - Proceedings from breast cancer expert group meeting.
Article in BMC proceedings, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed, 8 citations in OpenAlex.
- Optimizing axillary lymph node management in early-stage HR+/HER2- breast cancer: Practical strategies for enhanced detection rates.Breast (Edinburgh, Scotland) · 2026Article
- Comparative efficacy of CDK4/6 inhibitors palbociclib, ribociclib, and abemaciclib in HRAmerican journal of cancer research · 2026Article
- Predictive, preventive, and personalized medicine in breast cancer: targeting the PI3K pathway.Journal of translational medicine · 2024Review
- Breast Cancer in the Arabian Gulf Countries.Cancers · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 9 institutions in 9 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThe therapeutic landscape of hormone receptor-positive (HR+), human epidermal growth factor receptor 2-negative (HER2-) metastatic breast cancer (mBC) has evolved considerably with the introduction of newer targeted agents and their combinations with endocrine therapies. In this scenario, optimizing treatment selection and sequencing is daunting for clinicians. The purpose of this review is to provide evidence-based answers to key clinical questions on treatment selection and sequencing for the management of HR + HER2 - mBC.
designA panel of nine key opinion leaders from Argentina, Brazil, Colombia, Mexico, Moscow, Singapore, South Korea, Taiwan, and UAE convened in October 2018. They reviewed the literature and formulated answers to clinical questions on optimizing the management of HR + HER2 - mBC.
resultsEvidence-based answers were formulated for: (1) optimal initial treatment choice; (2) ovarian function suppression, optimal endocrine partner, and role of cyclin-dependent kinase 4/6 (CDK4/6) inhibitors (in premenopausal women); (3) better first-line standard of care than aromatase inhibitors; (4) preferred second-line treatment; (5) treatment of oligometastatic disease; (6) factors influencing first-line single-agent endocrine therapy choice; (7) influence of endocrine resistance on treatment selection; (8) optimal maintenance regimen in visceral crisis; and (9) need for a breast cancer registry for patients with HR + HER2 - mBC. The panel also proposed a treatment-sequencing algorithm for the management of HR + HER2 - mBC.
conclusionThe current article will serve as a comprehensive guide for optimizing the management of HR + HER2 - mBC. The proposed breast cancer registry will help identify unmet needs and develop strategic regional policies to help improve access to optimized care for HR + HER2 - mBC.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.