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Record W4411219742 · doi:10.1016/j.jbo.2025.100694

Management of aromatase inhibitor-associated bone loss (AIBL) in women with hormone-sensitive breast cancer: An updated joint position statement of the IOF, CABS, ECTS, IEG, ESCEO, IMS, and SIOG

2025· review· en· W4411219742 on OpenAlex
Peyman Hadji, Nasser Al-Dagri, Majed S. Alokail, Emmanuel Biver, Jean-Jacques Body, Maria Luisa Brandi, Janet E. Brown, Cyrille B. Confavreux, Bernard Cortet, Matthew T. Drake, Peter R. Ebeling, Erik Fink Eriksen, Ghada El‐Hajj Fuleihan, Theresa Guise, Andreas Kurth, Bente Langdahl, Willem F. Lems, Radmila Matijević, Eugène McCloskey, Rossella E. Nappi, Santiago Palacios, Georg Pfeiler, Jean-Yves Reginster, René Rizzoli, Daniele Santini, Şansın Tüzün, Catherine Van Poznak, Tobias De Villiers, M. Carola Zillikens, Robert E. Coleman

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of bone oncology · 2025
Typereview
Languageen
FieldMedicine
TopicBone health and treatments
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineAromatase inhibitorAromataseBreast cancerGynecologyEstrogenOncologyCancerInternal medicine

Abstract

fetched live from OpenAlex

Background: Women with hormone-responsive breast cancer who receive adjuvant endocrine treatment with aromatase inhibitors (AI) are known to be at higher fracture risk due to a marked increase in bone resorption. In 2017, several interdisciplinary cancer and bone societies involved in the management of women with AI-associated bone loss (AIBL) published a joint position statement comprising evidence-based recommendations and a practical management algorithm for the assessment of fracture risk and optimal treatment of this patient population. Patients and methods: In order to provide updated recommendations that reflect recent advances in the assessment and management of AIBL since publication of the 2017 joint position statement, a systematic literature review was undertaken to identify relevant studies for analysis, including systematic reviews and meta-analyses. Individual trials identified were assessed for their level of evidence based on design, size, follow-up, and evaluation of safety, as well as the impact of bone directed treatments on breast cancer outcomes. Results: New evidence was combined with the existing recommendations to provide an updated joint position statement regarding fracture risk assessment and implementation of bone-directed therapy. Conclusion: Current published literature, including recent clinical trial reports, systematic reviews and meta-analyses, continue to affirm the high risk of fractures in women with breast cancer who are receiving adjuvant AI treatment, a risk which has been observed to increase with the commonly used approach of extended duration AI therapy (>5 years). Risk factors for fracture and risk assessment in this patient population as well as the most suitable treatment modalities have been updated. Finally, the influence of bone protective treatments on breast cancer outcomes such as incidence of bone metastasis and breast cancer related overall survival have been included.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.922
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.331
Teacher spread0.316 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it