Abstract PS3-17: Patient and provider determinants of breast cancer screening among Ontario women age 40-49: A population based retrospective cohort study
Bibliographic record
Abstract
Abstract Background: For women aged 40-49, Canadian guidelines recommend individualized-decision making (based on risk assessment, values, and preferences) rather than routine screening mammography (SM). In this age group, family physicians are the gatekeepers to access SM; however, studies indicate substantial variability in practice patterns. There are few population-based data regarding uptake and patient/provider determinants of SM in this age group. We describe the uptake and frequency of SM and identify patient and provider level associations with SM in Ontario women aged 40-49. We hypothesized that SM would vary by provider characteristics and women’s demographics, suggesting lack of guideline-concordant care. Methods: This population-based retrospective cohort study linked health administrative databases to form a cohort of all Ontario women aged 40-49 between April 1, 2009 to March 31, 2019. Mammograms were identified using Ontario Health Billing codes. In order to identify mammograms that were specifically for screening, women were excluded if they had any prior breast MRI, mammogram, cancer diagnosis, oncologist visit, or breast surgical procedure. Sub-cohorts were created to identify women who had (a) at least one SM (“screen cohort”) and (b) 3 or more SM (“routine screen cohort”). Following SM, women were censored from cohorts if they had any cancer diagnosis, breast surgical procedure, oncologist visit, or death; however, breast cancer related outcomes were tracked for 6 months following SM, regardless of whether a censoring event occurred. Patient and provider characteristics were extracted for women in each cohort. A multivariable regression model was used to identify predictors of routine SM. Results: Of 2 million eligible women, 743 274 (35.6%) received a mammogram, 532 782 (25.5%) received at least one SM, and 90 651 (4.3%) received routine SM (3 or more). Table 1 demonstrates cohort characteristics. There were 0.32 and 0.52 mammograms per woman per year in the screen and routine screen cohort respectively. Call-backs were similar for women after the first SM compared to the third SM (9.5% vs 9.3%); however, there were more biopsies (3.2% vs 1.8%) and breast cancers diagnosed (1.2% vs 0.45%) within six months of the first SM. Compared to the full cohort, women in the routine screen cohort were more likely to have a family physician at cohort entry, be in higher-income quintiles, receive annual health exams, and receive have pap smears (p<0.001). Women in the screen cohort were more likely to have female providers and providers that were primarily paid fee for service versus capitation (p<0.001). Multivariable analysis will be reported at the meeting. Conclusions: Less than 5% of Ontario women 40-49 undergo routine SM. SM is associated with patient demographics related to higher socioeconomic status which could be related to higher risk of breast cancer and/or increased access to care. SM is also associated with some provider demographics which could be independent of breast cancer risk, suggesting lack of individualized risk assessment. Qualitative work is ongoing to explore this hypothesis. This information can inform guideline implementation strategies. Table 1: Patient and Provider Characteristics of ScreeningCharacteristicpercent (%) unless otherwise notedAll Women 40-49Screen Cohort (1 or more SM)Routine Screen Cohort (3 or more SM)Patient CharacteristicsAge at Cohort entryMean (median)42.5 (40)42.8 (42)41.7 (41)Age at Cohort exitMean (median)47.3 (50)48.5 (50)49.1 (50)Family Physician at Cohort entry90.0 %92.3%94.8%Income – top quintile20.7%22.3%24%Rurality Category – most urban76.3%79.0%81.2%Birth Location – Canada74.4%72.2%71.6%Annual Health Exams: at least one51.1%72.1%75.3%Pap Smear: at least one68.4%86.6%92.9%Provider CharacteristicsFemale44.8%47.2%52.1%Canadian Graduates70.3%70.3%72.1%Fee for Service model48.0%55.0%58.8% Citation Format: Michelle B Nadler, Alex Marchand-Austin, Peter C. Austin, Alexandra Desnoyers, Brooke E. Wilson, Aisha Lofters, Noah Ivers, Eitan Amir. Patient and provider determinants of breast cancer screening among Ontario women age 40-49: A population based retrospective cohort study [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS3-17.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".