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Abstract P1-10-05: The Impact of Resource Setting and Guidelines on Global Early Breast Cancer Practice

2010· article· en· W2327814134 on OpenAlexaff
Sonal Gandhi, Shabbir M.H. Alibhai, JC Victor, Christine Simmons, Sunil Verma

Bibliographic record

VenueCancer Research · 2010
Typearticle
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsUniversity of TorontoUniversity Health NetworkSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineBreast cancerFamily medicineGuidelineTamoxifenInternal medicineGynecologyCancerPathology

Abstract

fetched live from OpenAlex

Abstract Background: We developed an international physician survey to identify variations in early breast cancer practice, use of guidelines, and key challenges facing clinicians (MDs) globally in implementing guideline-based care. Methods: The survey was administered at an international breast oncology meeting, and also online using a secure platform. Results were analyzed using descriptive statistics and the chi-squared test was used for bivariate analysis. Results: 691 respondents from 70 countries completed the survey. 38% of respondents were from low income (LIC) or middle income (MIC) countries. More respondents in LICs (89%) and MICs (74%) practice in academic centres; 34% of MDs in high income countries (HICs) practice in community settings (P<0.001). More LIC physicians (74%) rely on clinical breast exam for diagnosis versus in MICs (58%) and HICs (55%) (P<0.001). 87% of LIC physicians say that hormone receptor status is routinely reported on pathology, versus in MICs (91%) and HICs (95%) (p=0.011). The reporting of HER2 status also varies by income setting: 83% in LICs, 89% in MICs, and 95% in HICs (P<0.001). Reporting seems to be the lowest in African nations (78% for hormone and 74% for HER2 status, p <0.001 for each). 46% of LIC and 61% of MIC physicians offer sentinel lymph node dissection, versus 94% in HICs (P<0.001). Adjuvant radiation is available in 93% of all surveyed practices. 99% of respondents give eligible patients endocrine treatment; tamoxifen is prescribed almost universally (>96% of respondents). Aromatase inhibitors are given by 87% of LIC, 93% of MIC, and 94% of HIC physicians (p=0.042). 75% of MDs in LICs give chemotherapy to high risk patients; 81% of those in MICs and HICs do the same (NS). More LIC oncologists give classical CMF (21%, p=0.006), and 77% give anthracycline-taxane combinations, compared to 84% of MIC and 88% of HIC physicians (p=0.017). Trastuzumab is given to a majority (>75%) of eligible patients by only 11% of LIC and 36% of MIC physicians, compared to 80% of HIC clinicians (P<0.001). Trastuzumab use is most prominent in North America (85%) and Europe (75%), and lowest in Africa (19%) and Asia (32%) (P<0.001). 94% of LIC and 63% of MIC physicians said trastuzumab use is limited by drug cost (P<0.001); lack of HER2 testing was cited as an issue by only 8-9% of all respondents. 63% of LIC and 76% of MIC physicians say international guidelines impact their clinical practice, compared to 56% of HIC physicians (P<0.001), who are more likely to rely on local/regional guidelines (33%, P<0.001). Conclusions: Global practice patterns in early breast cancer care vary by resource setting but also by continent. More costly therapies such as trastuzumab are used less often in LICs and MICs. Surveyed physicians from LICs and MICs also rely on international guidelines to direct their practice more than HIC physicians. This may reflect that many guidelines with international influence are created in HICs. In order to improve breast cancer outcomes worldwide, global collaboration is required to create guidelines which not only recommend best practice, but are applicable in various resource and cultural settings, and are followed by implementation research efforts. Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr P1-10-05.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.042
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.012
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.042
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.184
GPT teacher head0.540
Teacher spread0.356 · 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 source (direct Gemma or distilled Codex), 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".

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Citations4
Published2010
Admission routes1
Has abstractyes

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