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Record W4412520073 · doi:10.3390/pharmacy13040097

The Role of Pharmacists in Delivering Pharmaceutical Services to Breast Cancer Patients in Clinical and Community Settings: A Scoping Review

2025· review· en· W4412520073 on OpenAlexaff
Yuyao Pei, Feng Chang, Yuanhui Hu, Sarah G. Versteeg, Yufen Zheng

Bibliographic record

VenuePharmacy · 2025
Typereview
Languageen
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsBreast cancerClinical pharmacyPharmaceutical careMedicineFamily medicinePharmacyCancerInternal medicine

Abstract

fetched live from OpenAlex

(1) Background: Patient-centered care for individuals with breast cancer requires multidisciplinary cooperation to ensure the appropriate use of medication and prevent medication-related problems. Pharmaceutical care has been associated with improved adherence in breast cancer management, a factor linked to patient outcomes and mortality. This study aims to summarize and explore the provision and utilization of pharmaceutical services for breast cancer patients by pharmacists. (2) Methods: A scoping review was performed to assess the pharmacist's role in providing pharmaceutical services for patients with breast cancer. A comprehensive review of four databases (PubMed, Ovid Embase, Ovid International Pharmaceutical Abstracts, and Scopus) was completed between 1 January 2012 and 8 April 2025 according to PRISMA-ScR framework. (3) Results: A total of 46 articles met the inclusion criteria, which included RCTs, observatory studies, cohort studies, and reviews. Findings suggest that both clinical and community pharmacists play an important role in prevention, management, and education for breast cancer patients. (4) Conclusions: Pharmacists can improve health outcomes by providing pharmaceutical service in breast cancer care. Optimizing interventions, expanding services, and evaluating long-term cost-effectiveness is needed in the future.

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.

How this classification was reachedexpand

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.690
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.003
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 head0.209
GPT teacher head0.564
Teacher spread0.355 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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