Search

Background Although several clinical breast cancer risk models are used to guide screening and prevention, they have only moderate discrimination. Purpose To compare selected existing mammography artificial intelligence (AI) algorithms and the Breast Cancer Surveillance Consortium (BCSC) risk model for prediction of 5-year risk. Materials and Methods This retrospective case-cohort study included data in women with a negative screening mammographic examination (no visible evidence of cancer) in 2016, who were followed until 2021 at Kaiser Permanente Northern California. Women with prior breast cancer or a highly penetrant gene mutation were excluded. Of the 324 009 eligible women, a random subcohort was selected, regardless of cancer status, to which all additional patients with breast cancer were added. The index screening mammographic examination was used as input for five AI algorithms to generate continuous scores that were compared with the BCSC clinical risk score. Risk estimates for incident breast cancer 0 to 5 years after the initial mammographic examination were calculated using a time-dependent area under the receiver operating characteristic curve (AUC). Results The subcohort included 13 628 patients, of whom 193 had incident cancer. Incident cancers in eligible patients (additional 4391 of 324 009) were also included. For incident cancers at 0 to 5 years, the time-dependent AUC for BCSC was 0.61 (95% CI: 0.60, 0.62). AI algorithms had higher time-dependent AUCs than did BCSC, ranging from 0.63 to 0.67 (Bonferroni-adjusted P < .0016). Time-dependent AUCs for combined BCSC and AI models were slightly higher than AI alone (AI with BCSC time-dependent AUC range, 0.66-0.68; Bonferroni-adjusted P < .0016). Conclusion When using a negative screening examination, AI algorithms performed better than the BCSC risk model for predicting breast cancer risk at 0 to 5 years. Combined AI and BCSC models further improved prediction. © RSNA, 2023 Supplemental material is available for this article.

Mammographic density (MD) phenotypes are strongly associated with breast cancer risk and highly heritable. In this GWAS meta-analysis of 24,192 women, we identify 31 MD loci at P

PurposeRe-examine association of fluoxetine and paroxetine with risk of testicular cancer noted in drug screening, with 4 years more follow-up and expanded study of these and other antidepressant drugs.MethodsIn the Kaiser Permanente Medical Care Program in Northern California, 906 men with testicular cancer diagnosed August 1996-December 2010 were compared with 38,253 matched controls with race/ethnicity recorded regarding receipt of antidepressant drugs at least 2 years before diagnosis or control index date. Analyses emphasized duration of use and histological subgroups.ResultsWith control for race/ethnicity and use of other antidepressant drugs, odds ratios (OR) and 95 % confidence intervals (CI) for associations with testicular cancer were as follows: fluoxetine 1.22 (0.88-1.71), paroxetine 1.19 (0.78-1.83), and 1.21 (0.92-1.58) for all serotonin reuptake inhibitors. There was no statistically significant association with risk of all testicular cancers or their histological subtypes for any individual drug or for tricyclics or all antidepressants combined except for citalopram with all testicular cancers 2.55 (1.43-4.52) and those of mixed histology 4.36 (1.50-12.68) and nefazodone with embryonal cancers 9.79 (1.85-51.81). These could readily be chance findings in the context of the many analyses that were performed. Duration of use was not associated with risk of the drugs and drug groups with sufficient numbers of exposed cases for analysis.ConclusionsWe found little evidence to support a testicular carcinogenic effect of fluoxetine, paroxetine, or other antidepressant drugs, but a weakly positive association is not ruled out. The signals in prior screening may have been due to chance and/or uncontrolled confounding.

The article discusses a study which examined whether glycemic control measured by serial homoglobin A1c was linked with colorectal adenoma risk. Patients with type 2 diabetes mellitus who were included in the study had at least one colorectal adenoma identified at either colonoscopy or sigmoidoscopy. Results showed that the adjusted mean HbA1c levels among those without adenomas was 8.20% versus 8.26% among those with at least one adenoma. It was concluded that glycemic control was not linked with the risk of colorectal adenoma.

BACKGROUND/OBJECTIVES Determining long-term trends in tumor biomarker expression is essential for understanding aspects of tumor biology amenable to change. Limiting the availability of such data, currently used assays for biomarkers are relatively new. For example, assays for the estrogen receptor (ER), which are the oldest, extend back only to the 1970s. METHODS To extend scant knowledge about the feasibility of obtaining long-term data on tumor biomarkers, we randomly selected 60 breast cancer cases (10 per decade) diagnosed between 1947–2009 among women members of the Kaiser Permanente Northern California health plan to obtain and analyze their formalin-fixed paraffin-embedded (FFPE) tumor specimens. For each tumor specimen, we created duplicate tissue microarrays for analysis. RESULTS We located tumor blocks and pathology reports for 50 of the 60 cases (83%), from which we randomly sampled 5 cases per decade for biomarker analysis (n = 30). All 30 cases displayed excellent morphology and exhibited biomarkers compatible with histologic type and grade. Test–retest reliability was also excellent: 100% for ER; 97% for human epidermal growth factor receptor 2 and epidermal growth factor receptor; 93% for progesterone receptor and cytokeratin 5/6; and 90% for Ki67 and molecular phenotype; the kappa statistic was excellent (>0.9) for 4 of the 7 biomarkers, strong (0.6–0.8) for 2, and fair for only 1 (owing to low prevalence). CONCLUSIONS These results indicate immunostaining for biomarkers commonly used to evaluate breast cancer biology and assign surrogate molecular phenotypes can reliably be employed on archival FFPE specimens up to 60 years old.

Objective: To examine whether use of adjuvant therapy varies by race/ethnicity among patients with ductal carcinoma in situ (DCIS) at 3 integrated health plan delivery sites based in California and Massachusetts., Study Design: Cross-sectional study nested within a cohort of women diagnosed as having DCIS between 1990 and 2001., Methods: We reviewed medical records of 3000 non-Hispanic white (69%), black (10%), Hispanic (9%), and Asian or Pacific Islander (12%) women diagnosed as having DCIS between 1990 and 2001 and treated with breast-conserving therapy. chi(2) Test and multinomial logistic regression analysis were used to examine the association between race/ethnicity and use of adjuvant treatments after controlling for patient and clinical variables, including certain pathologic factors., Results: We found no significant differences in DCIS adjuvant treatment among racial/ethnic groups in bivariate or multinomial analyses after adjusting for demographic characteristics, comorbidity, and clinical factors. Minority women were as likely to undergo adjuvant radiation therapy as non-Hispanic white women. However, women 70 years or older (odds ratio, 0.40; 95% confidence interval, 0.31-0.51) and women who lived in areas with low geocoded median family income (odds ratio, 0.65; 95% confidence interval, 0.48-0.89) were less likely to receive adjuvant radiation therapy. Tumor size and comedo histologic growth pattern were associated with increased likelihood of receiving radiation therapy., Conclusion: Use of adjuvant therapy by minority women in these managed care plans is similar to that by non-Hispanic white women, although use was less among older women and among women who lived in poorer neighborhoods.