Laurel A. Habel

Background: We compared performance across 3 breast cancer risk domains—clinical, polygenic, and mammography artificial intelligence—alone and in combination over a 10-year time horizon among women with a negative screening mammogram within a Kaiser Permanente Research Bank (KPRB) prospective cohort. Methods: The study included 82 957 women (61 962 non-Hispanic White, 7256 Asian, 3414 Black, and 5466 Latina) who enrolled in KPRB between 2003 to 2020. Women with a prior history of breast cancer or high/moderate-penetrant gene mutation were excluded. The negative screening mammogram (no clinically visible cancer) closest to enrollment was used to generate the Mirai mammography AI risk score. KPRB survey and electronic health record data were used to generate the Breast Cancer Surveillance Consortium version 3 (BCSCv3) clinical risk score. Genome-wide genotypes were used to compute the 313-SNP polygenic risk score, adjusted for genetic ancestry (PRS313adj). Risks of breast cancer (invasive or ductal carcinoma in situ) at 0 to 10 years after the mammogram were estimated using Cox models, with 5-fold cross-validation used to estimate the C-index. Results: During 10 years of follow-up, 2471 women developed breast cancer. The C-index (95% CI) for the combined model with all 3 risk scores (0.70; 95% CI = 0.69 to 0.71) was significantly higher than for univariate models with only the BCSCv3 (0.62; 95% CI = 0.61 to 0.63), PRS313adj (0.61; 95% CI = 0.60 to 0.62), or Mirai (0.66; 95% CI = 0.65 to 0.67) risk score. Conclusions: Integrating mammographic AI and polygenic risk scores with clinical risk models significantly improved breast cancer risk discrimination, supporting use of combined models for personalized screening and prevention.

Background: Trial Assigning Individualized Options for Treatment (TAILORx) redefined the Oncotype DX (ODX) risk stratification scores. This study describes the clinical application of ODX in the post‐TAILORx era in relation to chemotherapy. Methods: A cohort of 8017 early‐stage breast cancer patients considered guideline‐eligible for ODX testing were identified between 2015 and 2021. Clinical factors associated with ODX testing and adjuvant chemotherapy were found through descriptive analysis and multivariable logistic regression modeling. Models were adjusted for age, race/ethnicity, tumor size and grade, progesterone (PR) status, and Charlson Comorbidity Index. The Cochran‐Armitage test was used to evaluate the probability of ODX testing during the study period. Results: ODX testing increased over time (from 45% in 2015 to 80% in 2021; p < .0001). The likelihood of chemotherapy use increased by an estimated 5% annually (adjusted odds ratio [aOR], 1.05; 95% CI, 1.01–1.09). Testing was more likely in younger than older patients (e.g., aOR 1.90 among 18 to p value for interaction <.001). Conclusions: In the post‐TAILORx era, younger age was associated with substantially more ODX testing. The association of testing with chemotherapy varied substantially by age. The impact of age on ODX testing and use of chemotherapy is substantial and warrants further study.

Background: Understanding the relative contributions of SARS-CoV-2 infection-induced and vaccine-induced seroprevalence is key to measuring overall population-level seroprevalence and help guide policy decisions. Methods: Using a series of six population-based cross-sectional surveys conducted among persons aged ≥7 years in a large health system with over 4.5 million members between May 2021 and April 2022, we combined data from the electronic health record (EHR), an electronic survey and SARS-CoV-2 spike antibody binding assay, to assess the relative contributions of infection and vaccination to population-level SARS-CoV-2 seroprevalence. EHR and survey data were incorporated to determine spike antibody positivity due to SARS-CoV-2 infection and COVID-19 vaccination. We used sampling and non-response weighting to create population-level estimates. Results: We enrolled 4,319 persons over six recruitment waves. SARS-CoV-2 spike antibody seroprevalence increased from 83.3% (CI 77.0–88.9) in May 2021 to 93.5% (CI 89.5–97.5) in April 2022. By April 2022, 68.5% (CI 61.9–74.3) of the population was seropositive from COVID-19 vaccination only, 13.9% (10.7–17.9) from COVID-19 vaccination and prior diagnosed SARS-CoV-2 infection, 8.2% (CI 4.5–14.5) from prior diagnosed SARS-CoV-2 infection only and 2.9% (CI 1.1–7.6) from prior undiagnosed SARS-CoV-2 infection only. We found high agreement (≥97%) between EHR and survey data for ascertaining COVID-19 vaccination and SARS-CoV-2 infection status. Conclusions: By April 2022, 93.5% of persons had detectable SARS-CoV-2 spike antibody, predominantly from COVID-19 vaccination. In this highly vaccinated population and over 18 months into the pandemic, SARS-CoV-2 infection without COVID-19 vaccination was a small contributor to overall population-level seroprevalence.

Background: Understanding the relative contributions of SARS-CoV-2 infection-induced and vaccine- induced seroprevalence is key to measuring overall population-level seroprevalence and help guide policy decisions. Methods: Using a series of six population-based cross-sectional surveys conducted among persons aged ≥7 years in a large health system with over 4.5 million members between May 2021 and April 2022, we combined data from the electronic health record (EHR), an electronic survey and SARS-CoV-2 spike antibody binding assay, to assess the relative contributions of infection and vaccination to population- level SARS-CoV-2 seroprevalence. EHR and survey data were incorporated to determine spike antibody positivity due to SARS-CoV-2 infection and COVID-19 vaccination. We used sampling and non-response weighting to create population-level estimates. Results: We enrolled 4,319 persons over six recruitment waves. SARS-CoV-2 spike antibody seroprevalence increased from 83.3% (CI 77.0-88.9) in May 2021 to 93.5% (CI 89.5-97.5) in April 2022. By April 2022, 68.5% (CI 61.9-74.3) of the population was seropositive from COVID-19 vaccination only, 13.9% (10.7-17.9) from COVID-19 vaccination and prior diagnosed SARS-CoV-2 infection, 8.2% (CI 4.5- 14.5) from prior diagnosed SARS-CoV-2 infection only and 2.9% (CI 1.1-7.6) from prior undiagnosed SARS-CoV-2 infection only. We found high agreement (≥97%) between EHR and survey data for ascertaining COVID-19 vaccination and SARS-CoV-2 infection status. Conclusions: By April 2022, 93.5% of persons had detectable SARS-CoV-2 spike antibody, predominantly from COVID-19 vaccination. In this highly vaccinated population and over 18 months into the pandemic, SARS-CoV-2 infection without COVID-19 vaccination was a small contributor to overall population-level seroprevalence. Article summary: By April 2022, >93% of people had antibodies to SARS-CoV-2 with COVID-19 vaccination as the main driver of overall population-level seroprevalence in our healthcare system. SARS-CoV-2 infection without vaccination made a small contribution to population-level seroprevalence in our healthcare system.

Demographics of patients with wt and mut TP53.

Demographics of patients wt and mut Rb1.

Demographics of patients with wt and mut ATRX.

Demographics of patients with wt and mut PTEN.

OS comparison between Stanford and KPNC cohort

OS comparison between Stanford and KPNC cohort