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Underutilization of GnRH analogues (G) and exemestane (E) in young patients with early-stage breast cancer (BC) in Ontario.

2018· article· en· W2892968865 on OpenAlexaffabout
James Keech, Maureen Trudeau, Phillip Blanchette, Annie Ngan, Andrea Eisen

Bibliographic record

VenueJournal of Clinical Oncology · 2018
Typearticle
Languageen
FieldMedicine
TopicAdvanced Breast Cancer Therapies
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreCancer Care Ontario
Fundersnot available
KeywordsMedicineTamoxifenExemestaneBreast cancerPopulationInternal medicineGynecologyAdjuvantOncologyAdjuvant therapyStage (stratigraphy)CancerOophorectomySurgeryHysterectomy

Abstract

fetched live from OpenAlex

73 Background: In 2014-15, the randomized control trials SOFT and TEXT showed that premenopausal women with hormone receptor-positive, early stage BC treated with ovarian suppression (G or oophorectomy) in combination with E had improved outcomes compared to those treated with tamoxifen (T) alone. The largest benefit was observed in women younger than 35 ( < 35y). In Ontario, these regimens are not fully publicly funded for premenopausal women. We examined the utilization of adjuvant G + E for premenopausal BC patients in Ontario, as underutilization might reflect difficulty accessing these drugs. Methods: We determined the current utilization of adjuvant endocrine therapy for patients with BC through Ontario’s systemic therapy database. In particular, we examined the utilization of T, E and E + G in BC patients < 35y as these patients are expected to have the highest rates of uptake based on the outcomes of SOFT and TEXT. Results: In the first year following the publication of SOFT and TEXT, 20% of BC patients receiving adjuvant endocrine therapy received E + ovarian suppression (G or oophorectomy). This value was 14% in the following year, reflecting low uptake of the optimal treatment strategy. Conclusions: In Ontario, uptake of G + E is low in BC patients < 35y. One possible barrier to access is the lack of public funding for these drugs in this population. The low uptake may also reflect the toxicity associated with this treatment and the need for further knowledge translation. A 2017 provincial prioritization process ranked this unmet funding need as a high priority. Thus, a funding submission will be prepared to promote access to this evidence informed therapy. The submission will include a full evidence review and pharmacoeconomic analysis.[Table: see text]

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.416
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.065
GPT teacher head0.417
Teacher spread0.352 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2018
Admission routes2
Has abstractyes

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