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Abstract P2-05-03: Perceived Guideline Clarity & Deferral to Patient Preferences impact guideline concordant care for breast cancer screening in women age 40-49

2023· article· en· W4322771259 on OpenAlexaffabout
Michelle B. Nadler, Ann Marie Corrado, Brooke E. Wilson, Alexandra Desnoyers, Eitan Amir, Noah Ivers, Laura Desveaux

Bibliographic record

VenueCancer Research · 2023
Typearticle
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsTrillium Health CentreQuebec - Clinical Research Organization in CancerKingston Health Sciences CentrePrincess Margaret Cancer CentreWomen's College HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineGuidelineReferralCLARITYFamily medicinePopulationCancer screeningConcordanceBreast cancer screeningQualitative researchBreast cancerMammographyPsychologyCancerPathologyEnvironmental health

Abstract

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Abstract Background: Canadian and US Task Forces recommend against routine mammography screening for women age 40-49 at average breast cancer risk on the basis that harms outweigh the benefits. Both cite the importance of supporting women’s individualized decisions based on the relative value placed on potential benefits and harms of screening (2, 4). Population-based data reveal that screening rates in this age group are influenced by the woman’s primary care provider (PCP), suggesting some providers refer more often than others. This highlights the need to explore PCP perspectives on screening and how this informs clinical behaviour. Methods: Qualitative semi-structured interviews were performed by phone with PCPs in Ontario, Canada. Interviews were structured using the Theoretical Domains Framework (TDF) to explore determinants (barriers/facilitators) of three screening-related behaviours: 1) conducting a risk assessment; 2) discussion regarding benefits and harms; and 3) making a decision regarding referral for mammographic screening. Analysis: Interviews were transcribed and analyzed iteratively until saturation was reached. Two independent researchers coded all transcripts deductively both by behaviour and according to TDF domain. Findings that did not fit within a TDF code were coded inductively. Data were then grouped by screening behaviour and the associated codes were used to generate descriptive narratives of the determinants influencing PCP behaviour. Results: Eighteen physicians (mean age 48, 72% identified female) were interviewed. Table 1 outlines the determinants of the three screening behaviours. Analysis of inductive codes revealed two key contextual themes that influenced behaviours and moderated TDF codes: perceived guideline clarity (a lack of clarity on which behaviours (if any) were guideline-concordant) and deferral to patient preference (patient decision regarding screening without a complete discussion of benefits and harms). PCPs who perceived that the guidelines stated definitively that screening was not recommended had improved knowledge of harms and stronger beliefs about capabilities to educate patients about why screening was not recommended routinely. Deferral to patient preference seemed to occur when PCP’s knowledge was low and/or if they were impacted by experience of a younger woman diagnosed with breast cancer, which often led to anticipated regret (TDF domain: emotion). Discussion/Conclusion: Low knowledge related to formal breast cancer risk assessment, combined with a tendency to over-estimate benefits of screening relative to harms could explain some inappropriate variation in practice. All 3 PCP screening behaviours appeared to be affected by both perceived guideline clarity and deferral to patient preferences. These may all be effective targets for future interventions to address variation in care. Table 1: Unique Barriers and Facilitators of Three Screening Behaviours Citation Format: Michelle Nadler, Ann Marie Corrado, Brooke E. Wilson, Alexandra Desnoyers, Eitan Amir, Noah Ivers, Laura Desveaux. Perceived Guideline Clarity & Deferral to Patient Preferences impact guideline concordant care for breast cancer screening in women age 40-49 [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P2-05-03.

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 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)0.006
metaresearch head score (Gemma)0.044
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 score0.090
Threshold uncertainty score0.178

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.044
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0300.001

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 head0.297
GPT teacher head0.517
Teacher spread0.220 · 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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Citations0
Published2023
Admission routes2
Has abstractyes

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