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Record W2303235479 · doi:10.1158/1538-7755.disp13-b85

Abstract B85: Racial differences in false-positive mammogram rates: Results from the ACRIN Digital Mammographic Imaging Screening Trial (DMIST)

2014· article· en· W2303235479 on OpenAlexaboutno aff
Anne Marie McCarthy, Jianing Yang, Mirar N. Bristol, Emily F. Conant, Katrina Armstrong

Bibliographic record

VenueCancer Epidemiology Biomarkers & Prevention · 2014
Typearticle
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBreast cancerMammographyBreast cancer screeningLogistic regressionFalse positive paradoxCancerObstetricsGynecologyDemographyInternal medicineStatistics

Abstract

fetched live from OpenAlex

Abstract Introduction: Though screening mammography reduces breast cancer mortality, it carries a significant burden of false-positives, which may lead to unnecessary procedures, anxiety, and increased costs. Because of the relatively low risk of cancer and high level of false-positives in younger women, the U.S. Preventative Services Task Force recommends against routine screening for women younger than 50. This guideline is controversial, and some have raised concerns about its application to black women, who tend to be diagnosed with breast cancer at younger ages and with more advanced disease than whites. However, few studies have quantified the burden of false-positive mammograms among black women. Methods: The ACRIN DMIST trial compared the diagnostic accuracy of digital versus screen-film mammography among 49,528 asymptomatic women enrolled from 2001-2003 at 33 sites in the U.S. and Canada. The current study includes a subset of participants who self-identified as white (N=26,446) or black/African American (N=3176) with no prior history of breast cancer. We compared screening outcomes for white and black women based on the results of digital mammography. False-positive mammograms were defined as those with BIRADS 0, 4, or 5 designation with no subsequent cancer diagnosis in the 15-month follow-up period. Logistic regression was used to estimate the odds of false-positive mammogram by race, breast cancer risk factors, and prior films. A generalized linear mixed model was also fit to account for study site as a random effect. Results: Black participants were slightly younger than white participants (mean 53.7 vs. 55.0). As expected, black and white women differed in terms of reproductive history, with black women having higher parity, lower age at first birth, and lower prevalence of breastfeeding. Black women were also less likely to have prior films available at mammogram interpretation than whites (86.8% vs. 91.3%). The cancer detection rate did not differ significantly by race (whites 0.95%, blacks 0.79% p=0.359). The false-positive rate was higher among blacks (9.2%) than whites (7.8%, p=0.009). Higher false-positive rates were also associated with lack of prior films, higher breast density, and being seen at a study site that enrolled a larger proportion of black participants (r=0.34, p=0.05). After adjusting for age, black women had 17% increased odds of false-positive mammograms compared to whites (OR=1.17, p=0.017). We sequentially added breast cancer risk factors (menopause status, age at menarche, age at first birth, breastfeeding, birth control use, estrogen replacement therapy, prior biopsy, family history of breast cancer), breast density, prior films, and study site to the model. Breast cancer risk factors, prior films, and study site each attenuated the coefficient for race by more than 20%. In the fully adjusted model including study site as a random effect, there was no significant difference in the odds of false-positive mammogram between black and white women (OR=1.04, p=0.561). There were no significant interactions between race and prior films, breast density, age, or menopause status with respect to false-positives. Conclusions: Black women enrolled in the ACRIN DMIST trial had a 1.4% higher false-positive rate than whites. This higher burden of false-positives for black women is clinically significant, given the large numbers of women who undergo screening mammography in the U.S. The higher rate of false-positives among black women was explained by differences in breast cancer risk factors, lower availability of prior mammogram films, and differences in mammogram facility false-positive rates between black and white women in the ACRIN DMIST trial. Citation Format: Anne Marie McCarthy, Jianing Yang, Mirar Bristol, Emily Conant, Katrina Armstrong. Racial differences in false-positive mammogram rates: Results from the ACRIN Digital Mammographic Imaging Screening Trial (DMIST). [abstract]. In: Proceedings of the Sixth AACR Conference: The Science of Cancer Health Disparities; Dec 6–9, 2013; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2014;23(11 Suppl):Abstract nr B85. doi:10.1158/1538-7755.DISP13-B85

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)0.003
metaresearch head score (Gemma)0.009
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 score0.004
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.114
GPT teacher head0.393
Teacher spread0.280 · 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".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

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