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Background Systemic corticosteroids (SCS) remain the cornerstone of eosinophilic granulomatosis with polyangiitis (EGPA) and hypereosinophilic syndrome (HES) therapy but are associated with substantial toxicity. Mepolizumab, an anti-interleukin-5 biologic, has demonstrated steroid-sparing effects in addition to EGPA and HES disease control, yet evidence of reductions in SCS-related complications is limited. Methods This retrospective cohort study used US claims data from the Komodo Research Database to quantify SCS-related complications, healthcare resource utilization, and costs in patients with EGPA or HES treated with mepolizumab vs. chronic SCS. Patients were stratified as mepolizumab (300 mg) or chronic SCS users (≥6 months continuous SCS use with >7.5 mg/day for EGPA and >10 mg/day for HES) based on treatment received during a 6-month landmark period post-index (first claim of mepolizumab or SCS). An inverse probability of treatment weighting approach was applied to the cohorts to minimize confounding. Outcomes were assessed up to 12 months post-landmark. Results 578 patients with EGPA (305 mepolizumab users vs. 273 chronic SCS users) and 272 patients with HES (161 vs. 111) were included. In patients with EGPA, rates of any SCS-related complications were 39% lower with mepolizumab compared with chronic SCS (rate ratio [95% confidence interval]: 0.61 [0.49, 0.76], p < 0.001). Mepolizumab users had 57% lower rate of all-cause hospitalizations (0.43 [0.27, 0.69], p < 0.001), and lower outpatient and emergency department (ED) visits vs. chronic SCS. Patients with HES had significantly lower rates of any SCS-related complications with mepolizumab vs. chronic SCS (0.59 [0.42, 0.82], p = 0.002). Mepolizumab users had 66% lower rates of all-cause hospitalizations (0.34 [0.17, 0.65], p = 0.001), and lower outpatient visits relative to chronic SCS users. In EGPA and HES SCS-complication-related hospitalizations and ED visits were lower with mepolizumab compared with chronic SCS. SCS-complication-related medical costs per patient per year were $16,194 ( p = 0.008) and $3,976 ( p = 0.676) lower, in the mepolizumab vs. chronic SCS cohort of patients with EGPA and HES, respectively. Conclusion This first of its kind study suggests that real-world mepolizumab use is associated with reduced SCS-related complications in EGPA and HES, reinforcing its clinical and economic steroid-sparing benefits in reducing healthcare burden among EGPA and HES populations.

Abstract Introduction Incorporation of mammographic density to breast cancer risk models could improve risk stratification to tailor screening and prevention strategies according to risk. Robust evaluation of the value of adding mammographic density to models with comprehensive information on questionnaire-based risk factors and polygenic risk score is needed to determine its effectiveness in improving risk stratification of such models. Methods We used the Individualized Coherent Absolute Risk Estimator (iCARE) tool for risk model building and validation to incorporate density to a previously validated literature-based model with questionnaire-based risk factors and a 313-variant polygenic risk score (PRS). The model was evaluated for calibration and discrimination in three prospective cohorts of European-ancestry women (1,468 cases, 19,104 controls): US-based Nurses’ Health Study (NHS I and II) and Mayo Mammography Health Study (MMHS); and Sweden-based Karolinska Mammography Project for Risk Prediction of Breast Cancer (KARMA) study. Analyses were done separately for women younger (NHS II, KARMA) and older than 50 years (NHS I, MMHS, KARMA). Improvements in terms of risk stratification and reclassification proportions were assessed among European-ancestry women aged 50–70 years in US and Sweden. Results For women younger and older than 50 years, the model with questionnaire-based risk factors, PRS and density was generally well calibrated across risk with some evidence of miscalibration at the extremes of the risk distribution. Incorporation of density led to modest improvements risk discrimination beyond the model with questionnaire-based risk factors and PRS: the area under the curve (AUC) among younger women was 67.0% (95% CI: 63.5–70.6%) vs. 65.6% (95% CI: 61.9–69.3%) for models with and without density; and 66.1% (95% CI 64.4–67.8%) vs. 65.5% (95% CI: 63.8–67.2%) among older women. The model with density identified 18.4% of US women 50–70 years old ≥ 3% 5-year predicted risk (threshold used for recommending risk-reducing medication in the US), with 42.4% of future cases expected to occur in this group. At this threshold, 7.9% of US women were reclassified by adding density to the model, resulting in the identification of 2.8% of additional future cases. The model with density identified 10.3% of Swedish women ≥ 3% 5-year predicted risk, with 29.4% of future cases expected to occur in this group. At this threshold, 5.3% of women were reclassified with the addition of density, leading to the identification of an additional 4.4% of future cases. Conclusion Integrating density with questionnaire-based risk factors and PRS could potentially identify more women of European-ancestry with elevated risk of breast cancer in the United States and Sweden. Further investigations of the integrated model in non-European ancestry populations are needed prior to considering clinical applications.

Aim: Patients with R/R LBCL after first-line treatment have poor prognosis. Multiple novel therapies have been approved for R/R LBCL in recent years, but CIT regimens are still commonly used. This study evaluated the effectiveness of CIT and novel therapies in 2L+ in patients with R/R LBCL and the association between patient clinical characteristics and real-world outcomes. Methods: This was a multi-site retrospective observational study of patients aged ≥18 years with R/R LBCL in the Lymphoma Epidemiology of Outcomes (LEO) Consortium of Real-World Evidence (CReWE) cohort (patients followed from 1/1/2015 to 2/15/2023) who were treated with CIT or novel therapy in 2L+. CIT regimens included salvage/palliative chemotherapy, lenalidomide, rituximab, or obinutuzumab, used alone or in combination. Novel therapies included polatuzumab vedotin plus bendamustine and rituximab or variations thereof (i.e., pola-based regimen), tafasitamab plus lenalidomide or variations thereof (tafa-based regimen), and loncastuximab tesirine (lonca). Patients' demographic and clinical characteristics were assessed from the first confirmed R/R disease diagnosis and initiation of 2L+ therapy. When multiple lines of therapy (LOTs) were eligible for inclusion in the analysis, one was randomly selected as the index LOT. Real-world outcomes, determined by investigators at each clinical site, including overall response rate (ORR), complete response (CR) rate, duration of response (DOR), duration of complete response (DOCR), progression-free survival (PFS), and overall survival (OS) were described for all patients in each treatment group and for the subgroup of patients with prior chimeric antigen receptor (CAR) T-cell therapy. Multivariable Cox Proportional Hazards models were used to assess associations between select patient clinical characteristics and real-world outcomes. Results: The study population included patients treated with CIT (N=653), pola-based regimen (N=116), tafa-based regimen (N=55), and lonca (N=42) ( Figure 1A). The median (m) age at date of index treatment initiation across groups ranged from 63 to 74 years. Across groups, most patients had primary refractory disease-i.e., were refractory to the first LOT (69.5% CIT vs. 73.3% pola vs. 58.2% tafa vs. 71.4% lonca), whereas variable proportions had one prior LOT (65.5% vs. 17.2% vs. 43.6% vs. 7.1%) and prior CAR T-cell therapy (5.1% vs. 43.1% vs. 32.7% vs. 47.6%). In the CIT group, ORR was 33.8%, 15.5% of patients achieved CR, mPFS (95% CI) was 1.9 (1.7, 2.1) months, and mOS was 9.1 (8.1, 10.5) months. In the pola group, ORR was 42.2%, 24.1% of patients achieved CR, mPFS was 2.5 (2, 3.2) months and mOS was 7.8 (6.4, 11.8) months. In the tafa group, ORR was 25.5%, 14.5% of patients achieved CR, mPFS was 2.7 (2.1, 4.2) months, and mOS was 8 (5.3, 12.7) months. In the lonca group, ORR was 40.5%, 21.4% of patients achieved CR, mPFS was 3 (2.1, 5.1) months, and mOS was 4.7 (3.7, 10.8) months. Demographics and outcomes for all patients and those who received prior CAR T-cell therapy are summarized in Figure 1A. In the multivariable Cox regression analysis, International Prognostic Index (IPI) risk score ≥3, CIT as the index treatment type, and primary refractory status were significantly associated with time from response to progression/death (P<0.05; Figure 1B). IPI risk score ≥3, CIT as the index treatment type, and primary refractory status were significantly associated with worse PFS. IPI risk ≥3, ≥3 prior LOTs, and primary refractory status were significantly associated with OS. Conclusion: In this large clinical cohort of patients with R/R LBCL with high proportions having primary refractory disease, all common treatments were associated with modest ORR/CR and poor OS. Receiving CIT treatments, higher IPI score, primary refractory status, and higher number of prior LOTs were significantly associated with poor clinical outcomes. A study with larger sample size and longer follow-up may be warranted to further understand the clinical effectiveness of novel treatments. Thus, despite the availability of novel treatments during the study period, these findings highlight the need for more effective treatment alternatives beyond currently available options to improve outcomes.

Abstract Introduction: Incorporation of mammographic density to breast cancer risk models could improve risk stratification to tailor screening and prevention strategies according to risk. However, robust validation of such models in prospective cohort studies is needed to determine their accuracy in identifying women at different risk levels. Methods: We incorporated Breast Imaging and Reporting Data System (BI-RADS) breast density to a literature-based model with questionnaire-based risk factors and a 313-variant polygenic risk score (PRS). The Individualized Coherent Absolute Risk Estimator (iCARE) tool was used to build and validate a 5-year absolute risk model for breast cancer. The model was evaluated for calibration and discrimination in three prospective cohorts of women of European ancestry (1,468 cases, 19,104 controls): US-based Nurses’ Health Study (NHS I and II) and Mayo Mammography Health Study (MMHS); and Sweden-based Karolinska Mammography Project for Risk Prediction of Breast Cancer (KARMA) study. Analyses were done separately for women younger (NHS II, KARMA) and older than 50 years (NHS I, MMHS, KARMA). Improvements in risk stratification were assessed among US non-Hispanic White women aged 50-70 years. Results: For women younger than 50 years, the model with questionnaire-based risk factors, PRS and BI-RADS was well calibrated across risk deciles in NHS II, but overestimated risk at the highest risk decile in KARMA. For women 50 years or older, the model showed good calibration in all studies, with evidence of slight overestimation at the highest risk decile and underestimation at the lowest risk decile. The model with PRS and BI-RADS was well calibrated for women at high-risk in both age groups. Incorporation of BI-RADS to questionnaire-based risk factors and PRS improved risk discrimination: area under the curves (AUC) 67.0% (95% CI: 63.5-70.6%) vs. 65.6% (95% CI: 61.9-69.3%) for models with and without BI-RADS for younger women and 66.1% (95% CI 64.4-67.8%) vs. 65.5% (95% CI: 63.8-67.2%) for older women. The model with BI-RADS identified 18.4% population of non-Hispanic US women 50-70 years old above 3% 5-year risk (used for recommending risk-reducing medication in the US), with 42.4% of future cases expected to occur in this group. Addition of BI-RADS led to the reclassification of ~8.0% of US non-Hispanic White women aged 50-70 years at the high-risk threshold (3% 5-year risk), resulting in identification of 4.2% of additional future cases. Conclusion: Integrating BI-RADS with questionnaire-based risk factors and PRS resulted in improved risk stratification among women of European ancestry, with evidence of slight overestimation of risk for women at elevated risk. Additional validation of the integrated model in diverse populations is needed prior to considering clinical applications. Citation Format: Charlotta V. Mulder, Yon Ho Jee, Xin Yang, Christopher G. Scott, Chi Gao, Amber N. Hurson, Mikael Eriksson, Per Hall, Peter Kraft, Celine M. Vachon, Antonis C. Antoniou, Gretchen Gierach, Montserrat Garcia-Closas, Parichoy Pal Choudhury. Validation of an integrated breast cancer risk model with mammographic density in three prospective cohort studies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2256.

PURPOSETo determine the contribution of germline pathogenic variants (PVs) in hereditary cancer testing panel genes to invasive lobular carcinoma (ILC) of the breast.MATERIALS AND METHODSThe study included 2,999 women with ILC from a population-based cohort and 3,796 women with ILC undergoing clinical multigene panel testing (clinical cohort). Frequencies of germline PVs in breast cancer predisposition genes ( ATM, BARD1, BRCA1, BRCA2, BRIP1, CDH1, CHEK2, PALB2, PTEN, RAD51C, RAD51D, and TP53) were compared between women with ILC and unaffected female controls and between women with ILC and infiltrating ductal carcinoma (IDC).RESULTSThe frequency of PVs in breast cancer predisposition genes among women with ILC was 6.5% in the clinical cohort and 5.2% in the population-based cohort. In case-control analysis, CDH1 and BRCA2 PVs were associated with high risks of ILC (odds ratio [OR] > 4) and CHEK2, ATM, and PALB2 PVs were associated with moderate (OR = 2-4) risks. BRCA1 PVs and CHEK2 p.Ile157Thr were not associated with clinically relevant risks (OR < 2) of ILC. Compared with IDC, CDH1 PVs were > 10-fold enriched, whereas PVs in BRCA1 were substantially reduced in ILC.CONCLUSIONThe study establishes that PVs in ATM, BRCA2, CDH1, CHEK2, and PALB2 are associated with an increased risk of ILC, whereas BRCA1 PVs are not. The similar overall PV frequencies for ILC and IDC suggest that cancer histology should not influence the decision to proceed with genetic testing. Similar to IDC, multigene panel testing may be appropriate for women with ILC, but CDH1 should be specifically discussed because of low prevalence and gastric cancer risk.

PURPOSE The prevalence of germline pathogenic variants (PVs) in established breast cancer predisposition genes in women in the general population over age 65 years is not well-defined. However, testing guidelines suggest that women diagnosed with breast cancer over age 65 years might have < 2.5% likelihood of a PV in a high-penetrance gene. This study aimed to establish the frequency of PVs and remaining risks of breast cancer for each gene in women over age 65 years. METHODS A total of 26,707 women over age 65 years from population-based studies (51.5% with breast cancer and 48.5% unaffected) were tested for PVs in germline predisposition gene. Frequencies of PVs and associations between PVs in each gene and breast cancer were assessed, and remaining lifetime breast cancer risks were estimated for non-Hispanic White women with PVs. RESULTS The frequency of PVs in predisposition genes was 3.18% for women with breast cancer and 1.48% for unaffected women over age 65 years. PVs in BRCA1, BRCA2, and PALB2 were found in 3.42% of women diagnosed with estrogen receptor (ER)–negative, 1.0% with ER-positive, and 3.01% with triple-negative breast cancer. Frequencies of PVs were lower among women with no first-degree relatives with breast cancer. PVs in CHEK2, PALB2, BRCA2, and BRCA1 were associated with increased risks (odds ratio = 2.9-4.0) of breast cancer. Remaining lifetime risks of breast cancer were ≥ 15% for those with PVs in BRCA1, BRCA2, and PALB2. CONCLUSION This study suggests that all women diagnosed with triple-negative breast cancer or ER-negative breast cancer should receive genetic testing and that women over age 65 years with BRCA1 and BRCA2 PVs and perhaps with PALB2 and CHEK2 PVs should be considered for magnetic resonance imaging screening.

PURPOSE This study assessed the joint association of pathogenic variants (PVs) in breast cancer (BC) predisposition genes and polygenic risk scores (PRS) with BC in the general population. METHODS A total of 26,798 non-Hispanic white BC cases and 26,127 controls from predominately population-based studies in the Cancer Risk Estimates Related to Susceptibility consortium were evaluated for PVs in BRCA1, BRCA2, ATM, CHEK2, PALB2, BARD1, BRIP1, CDH1, and NF1. PRS based on 105 common variants were created using effect estimates from BC genome-wide association studies; the performance of an overall BC PRS and estrogen receptor–specific PRS were evaluated. The odds of BC based on the PVs and PRS were estimated using penalized logistic regression. The results were combined with age-specific incidence rates to estimate 5-year and lifetime absolute risks of BC across percentiles of PRS by PV status and first-degree family history of BC. RESULTS The estimated lifetime risks of BC among general-population noncarriers, based on 10th and 90th percentiles of PRS, were 9.1%-23.9% and 6.7%-18.2% for women with or without first-degree relatives with BC, respectively. Taking PRS into account, more than 95% of BRCA1, BRCA2, and PALB2 carriers had > 20% lifetime risks of BC, whereas, respectively, 52.5% and 69.7% of ATM and CHEK2 carriers without first-degree relatives with BC, and 78.8% and 89.9% of those with a first-degree relative with BC had > 20% risk. CONCLUSION PRS facilitates personalization of BC risk among carriers of PVs in predisposition genes. Incorporating PRS into BC risk estimation may help identify > 30% of CHEK2 and nearly half of ATM carriers below the 20% lifetime risk threshold, suggesting the addition of PRS may prevent overscreening and enable more personalized risk management approaches.

Abstract Background Rigorous evaluation of the calibration and discrimination of breast-cancer risk-prediction models in prospective cohorts is critical for applications under clinical guidelines. We comprehensively evaluated an integrated model incorporating classical risk factors and a 313-variant polygenic risk score (PRS) to predict breast-cancer risk. Methods Fifteen prospective cohorts from six countries with 239 340 women (7646 incident breast-cancer cases) of European ancestry aged 19–75 years were included. Calibration of 5-year risk was assessed by comparing expected and observed proportions of cases overall and within risk categories. Risk stratification for women of European ancestry aged 50–70 years in those countries was evaluated by the proportion of women and future cases crossing clinically relevant risk thresholds. Results Among women &lt;50 years old, the median (range) expected-to-observed ratio for the integrated model across 15 cohorts was 0.9 (0.7–1.0) overall and 0.9 (0.7–1.4) at the highest-risk decile; among women ≥50 years old, these were 1.0 (0.7–1.3) and 1.2 (0.7–1.6), respectively. The proportion of women identified above a 3% 5-year risk threshold (used for recommending risk-reducing medications in the USA) ranged from 7.0% in Germany (∼841 000 of 12 million) to 17.7% in the USA (∼5.3 of 30 million). At this threshold, 14.7% of US women were reclassified by adding the PRS to classical risk factors, with identification of 12.2% of additional future cases. Conclusion Integrating a 313-variant PRS with classical risk factors can improve the identification of European-ancestry women at elevated risk who could benefit from targeted risk-reducing strategies under current clinical guidelines.

Abstract Background: Clinical use of breast cancer risk prediction requires simplified models. We evaluate a simplified version of the validated Rosner–Colditz model and add percent mammographic density (MD) and polygenic risk score (PRS), to assess performance from ages 45–74. We validate using the Mayo Mammography Health Study (MMHS). Methods: We derived the model in the Nurses' Health Study (NHS) based on: MD, 77 SNP PRS and a questionnaire score (QS; lifestyle and reproductive factors). A total of 2,799 invasive breast cancer cases were diagnosed from 1990–2000. MD (using Cumulus software) and PRS were assessed in a nested case–control study. We assess model performance using this case–control dataset and evaluate 10-year absolute breast cancer risk. The prospective MMHS validation dataset includes 21.8% of women age &lt;50, and 434 incident cases identified over 10 years of follow-up. Results: In the NHS, MD has the highest odds ratio (OR) for 10-year risk prediction: ORper SD = 1.48 [95% confidence interval (CI): 1.31–1.68], followed by PRS, ORper SD = 1.37 (95% CI: 1.21–1.55) and QS, ORper SD = 1.25 (95% CI: 1.11–1.41). In MMHS, the AUC adjusted for age + MD + QS 0.650; for age + MD + QS + PRS 0.687, and the NRI was 6% in cases and 16% in controls. Conclusion: A simplified assessment of QS, MD, and PRS performs consistently to discriminate those at high 10-year breast cancer risk. Impact: This simplified model provides accurate estimation of 10-year risk of invasive breast cancer that can be used in a clinical setting to identify women who may benefit from chemopreventive intervention. See related commentary by Tehranifar et al., p. 587