Vachon, Celine M.

e13538 Background: Breast density is considered a well-established breast cancer risk factor. As quasi-3D, digital breast tomosynthesis (DBT) becomes increasingly utilized for screening, there is an opportunity to routinely estimate volumetric breast density (VBD). However, current methods extrapolate VBD from 2D images acquired with DBT and/or depend on the existence of raw DBT data, which is rarely archived due to cost and storage constraints. Using a racially diverse screening cohort, this study evaluates the potential of deep learning for VBD assessment based solely on 3D reconstructed, “for presentation” DBT images. Methods: We retrospectively analyzed 1,080 negative DBT screening exams obtained between 2011 and 2016 from the Hospital of the University of Pennsylvania (racial makeup, 41.2% White, 54.2% Black, 4.6% Other; mean age ± SD, 57 ± 11 years; mean BMI ± SD, 28.7 ± 7.1 kg/m2), for which both 2D raw and 3D reconstructed DBT images (Selenia Dimensions, Hologic Inc) were available. Corresponding 3D reference-standard tissue segmentations were generated from previously validated software that uses both 3D reconstructed slices and raw 2D DBT data to provide VBD metrics, shown to be strongly correlated with VBD measures from MRI image volumes. We based our deep learning algorithm on the U-Net architecture within the open-source Generally Nuanced Deep Learning Framework (GaNDLF) and created a 3-label image segmentation task (background, dense tissue, and fatty tissue). Our dataset was randomly split into training (70%), validation (15%) and test (15%) sets. We report on the performance of our deep learning algorithm against corresponding reference-standard segmentations for a cranio-caudal (CC) view-only subset. We also stratify our results by the two main racial groups (White and Black). Our evaluation measure was the weighted Dice score (DSC), with 0 signifying no overlap and 1 signifying perfect overlap, overall and separately for each label. Results: Our deep learning algorithm achieved an overall DSC of 0.682 (STD = 0.136). It accurately segmented the three labels of background, fatty tissue, and dense tissue, with DSC scores of 0.995, 0.884, and 0.617, respectively. DSC for White and Black women were 0.688 (STD = 0.127) and 0.680 (STD = 0.146), respectively. Conclusions: Our preliminary analysis suggests that deep learning shows promise in the estimation of VBD using 3D DBT reconstructed, “for presentation” CC view images and does not demonstrate bias among racial groups. Future work involving optimization of performance in other breast views as well as transfer learning based on ground truth masks by clinical radiologists could further enhance this method. In view of rapid clinical conversion to DBT screening, such a tool has the potential to enable large retrospective epidemiological and personalized risk assessment studies of breast density with DBT.

Abstract Mass-spectrometry (MS) assays detect lower levels of monoclonal proteins and result in earlier detection of monoclonal gammopathy of undetermined significance (MGUS). We examined heavy chain MGUS prevalence using matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS among 3 risk groups, ages 50 or older: 327 African Americans (AA) and 1223 European Americans (EA) from a clinical biobank and 1093 unaffected first-degree relatives (FDR) of patients with hematologic disorders. Age- and sex-adjusted prevalence rates were directly standardized to 2010 United States population. Prevalence ratios were estimated for comparisons of AA and FDR to the EA group using the Poisson distribution. Results were also compared with population-based prevalence using conventional gel-based methods. Risk groups had similar sex and age distributions. MALDI-TOF MGUS prevalence was higher in the AA (16.5% [95% confidence interval (CI), 12.2%, 20.8%]) and FDR (18.3% [95% CI, 16.6%, 21.6%]) than in EA (10.8% [95% CI, 8.8%, 12.7%]), translating to prevalence ratios of 1.73 (95% CI, 1.31, 2.29) and 1.90 (95% CI, 1.55, 2.34), respectively. MALDI-TOF EA prevalence was over threefold higher than conventional estimates but showed similar age trends. Thus, the MALDI-TOF assay found greater numbers with MGUS but similar relative differences by race, family history, and age as prior studies.

Abstract Introduction: The risk of specific clinical subtype of breast cancer (defined by ER and HER2 status) among women in the general population who are carriers of germline pathogenic variants (PVs) in cancer predisposition genes is not well-defined. Methods: A total of 13,153 women with breast cancer (ER+/HER2-: 9381; ER+/HER2+: 1462; ER-/HER2+: 690; and ER-/HER2-: 1620) and 25,005 unaffected women (controls) from nine studies within the CAnceR RIsk Estimates Related to Susceptibility (CARRIERS) consortium that were not enriched for family history or early onset disease were included in the present analysis. A multiplex amplicon-based panel was used to perform germline sequencing for cancer predisposition genes. Case-control associations for each of the four clinical subtype of breast cancer was performed for PVs in 5 common breast cancer predisposition genes (ATM, BRCA1, BRCA2, CHEK2 and PALB2) utilizing a logistic regression model adjusting for study, age at diagnosis, race/ethnicity and family history of breast cancer. Results: The frequency of PVs in 5 genes was 3.8% for ER+/HER2-, 6.2% for ER+/HER2+, 4.2% for ER-/HER2+ and 9.3% for ER-/HER2- subtypes. PVs in BRCA1 and BRCA2 were associated with high risk (Odds Ratio (OR) >4) for all clinical subtypes of breast cancer, but the risk was highest (OR>8) for ER-/HER2- breast cancer. PVs in PALB2 were associated with high risk (OR>4) of ER-/HER2- and ER+/HER2+ subtypes and moderate risk (OR: 2-4) of ER+/HER2- breast cancer. Irrespective of the HER2 status, PVs in ATM were associated with a moderately increased risk (OR: 2-4) of ER+ breast cancer but the risk of ER- breast cancer was not elevated. In contrast, PVs in CHEK2 were associated with high risk (OR>4) of ER+/HER2+ breast cancer and moderate risk (OR: 2-4) of ER+/HER2- and ER-/HER2+ breast cancer, but the risk of ER-/HER2- breast cancer was not elevated. Conclusions: This study provides population-based estimates of risk of specific clinical subtypes of breast cancer which will be useful for genetic counseling and targeting appropriate screening strategies in PV carriers based on subtype specific risks of breast cancer. Citation Format: Siddhartha Yadav, Chunling Hu, Nicholas J. Boddicker, Eric Polley, Steven Hart, Rohan Gnanaolivu, Jie Na, Hongyan Huang, Song Yao, Celine M. Vachon, Lauren Teras, Jack A. Taylor, Dale P. Sandler, Julie R. Palmer, Janet E. Olson, Susan Neuhausen, Elena Martinez, Sara Lindstroem, Loic Le Marchand, Charles Kooperberg, Christopher Haiman, Mia M. Gaudet, James V. Lacey, Kimberly A. Bertrand, Leslie Bernstein, Paul W. Auer, Christine Ambrosone, Jeffrey N. Weitzel, Peter Kraft, David E. Goldgar, Katherine L. Nathanson, Susan M. Domchek, Fergus J. Couch, CARRIERS Consortium. Population-based risk estimates of clinical subtypes of breast cancer among carriers of germline pathogenic variants in cancer predisposition genes [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P2-09-01.

Abstract Background:Breast terminal duct lobular units (TDLUs), the source of most breast cancer (BC) precursors, are shaped by age-related involution, a gradual process, and postpartum involution (PPI), a dramatic inflammatory process that restores baseline microanatomy after weaning. Dysregulated PPI is implicated in the pathogenesis of postpartum BCs. We propose that assessment of TDLUs in the postpartum period may have value in risk estimation, but characteristics of these tissues in relation to epidemiological factors are incompletely described.Methods: Using validated Artificial Intelligence and morphometric methods, we analyzed digitized images of tissue sections of normal breast tissues stained with hematoxylin and eosin from donors <45 years from the Komen Tissue Bank (180 parous and 545 nulliparous). Metrics assessed by AI, included: TDLU count; adipose tissue fraction; mean acini count/TDLU; mean dilated acini; mean average acini area; mean “capillary” area; mean epithelial area; mean ratio of epithelial area versus intralobular stroma; mean mononuclear cell count (surrogate of immune cells); mean fat area proximate to TDLUs and TDLU area. We compared epidemiologic characteristics collected via questionnaire by parity status and race, using a Wilcoxon rank sum test or Fisher’s exact test. Histologic features were compared between nulliparous and parous women (overall and by time between last birth and donation [ recent birth: ≤5 years versus remote birth: >5 years]) using multivariable regression models.Results:Normal breast tissues of parous women contained significantly higher TDLU counts and acini counts, more frequent dilated acini, higher mononuclear cell counts in TDLUs and smaller acini area per TDLU than nulliparas (all multivariable analyses p<0.001). Differences in TDLU counts and average acini size persisted for >5 years postpartum whereas increases in immune cells were most marked <5 years of a birth. Relationships were suggestively modified by several other factors, including demographic and reproductive characteristics, ethanol consumption and breastfeeding duration. Conclusions:Our study identified sustained expansion of TDLU numbers and reduced average acini area among parous versus nulliparous women and notable increases in immune responses within five years following childbirth. Further, we show that quantitative characteristics of normal breast samples vary with demographic features and BC risk factors.

BackgroundThe objective of this randomized trial was to evaluate the short‐term effect of bilingual written and interpersonal education regarding mammographic breast density (MBD).MethodsLatinas aged 40 to 74 years who were presenting for screening mammography were recruited and randomized 1:1:1 to receive a letter with their mammogram and MBD results (usual care [UC]), a letter plus a brochure (enhanced care [ENH]), or a letter plus a brochure and telephonic promotora education (interpersonal care [INT]). Surveys were administered at enrollment (T0) and 2 weeks to 6 months after intervention delivery (T1). Differences were assessed with χ2, Kruskal‐Wallis, and McNemar tests and pairwise comparisons as appropriate. INT metrics and audio recordings were analyzed with descriptive statistics and qualitative content analysis.ResultsBetween October 2016 and October 2019, 943 of 1108 Latina participants (85%) completed both surveys. At T1, INT participants were more likely (P < .001) to report seeing their MBD results in the letter (70.2%) than UC (53.1%) or ENH participants (55.1%). The percentage of INT women who reported speaking with a provider about MBD (29.0%) was significantly greater (P < .001) than the percentage of UC (14.7%) or ENH participants (15.6%). All groups saw significant (P < .001) but nondifferential improvements in their knowledge of MBD as a masking and risk factor. In the INT group, the promotora delivered education to 77.1% of the 446 participants randomized to INT and answered questions at 28.3% of the encounters for an average of $4.70 per participant.ConclusionsAmong Latinas in a low‐resource setting, MBD knowledge may increase with written or interpersonal education, but with modest investment, interpersonal education may better improve MBD awareness and prompt patient‐provider discussions.

Abstract Monoclonal B-cell lymphocytosis (MBL) is one of the most common pre-malignant conditions and is characterized by a circulating population of clonal B-cells with an absolute clonal B-cell count &lt; 5x10 9/L and no evidence of lymphadenopathy, organomegaly, or cytopenias. MBL can be classified by the immunophenotype: CLL-like MBL (CD5+, CD20dim), atypical MBL (CD5+, CD20+), or non-CLL-like MBL (CD5-, CD20+), as well as by the size of the clone (low-count or high-count) with low-count MBL (LC-MBL) defined as clonal B-cell &lt;0.5x10 9/L or percent clonal B-cell count &lt;85% out of total B-cell count. The prevalence of MBL varies depending on detection methods and population tested. In a Spanish screening study of 608 individuals, they identified 73 MBLs (12%) with CLL-like MBL; moreover, these authors also evaluated overall survival (OS) compared to 290 individuals without MBL and found a significantly shorter OS among these predominantly LC-MBLs. Here, we evaluate the prevalence and OS of LC-MBL in a large screening cohort of 8,297 individuals. Study participants from the Mayo Clinic Biobank, a large-scale biorepository of adult patients, who had no prior history of hematologic malignancy, provided blood samples between 7/2009 to 4/2021. Stored peripheral blood mononuclear cells were screened for MBL with an eight-color flow cytometry assay capable of detecting clonal B-cell event to the 0.005% level. We classified each MBL by immunophenotype as CLL-like MBL, atypical MBL, and non-CLL-like MBL. Individuals with more than one immunophenotype were classified into one immunophenotype based on the following hierarchy: CLL-like MBL, then atypical MBL, then non-CLL like MBL. Based on previously published evidence, individuals were also classified by clonal counts using the percent clonal B-cell count &lt;85% out of the total B-cell count to define LC-MBL. Individuals were followed from sample date to the earliest of death, loss to follow-up, or 5/31/2021. OS for LC-MBL and controls (individuals who screened negative for MBL) was assessed by Kaplan-Meier method. Age- and sex-adjusted OS was analyzed using inverse weights methods. Cox regression was used to calculate hazard ratios (HR) and 95% confidence intervals (CIs), adjusted for age and sex. We screened 8,297 individuals 40 years or older (median age 67 years, 39% male) and identified 1,326 (16%) with LC-MBL and 6,651 (80%) controls. Those individuals detected with high-count MBL (N=90, 1%) or individuals who had insufficient cells for flow cytometry interpretation (N=230, 3%) were excluded from subsequent analyses. The prevalence of LC-MBL was higher in males (21%) than females (14%; p&lt;0.01) and significantly increased with age (p&lt;0.01) ranging from 3% among those 40-49 years, 10% among those 50-59 years, 15% among those 60-69 years, 23% among those 70-79 years, and 29% for those 80+ years. Sixty-one individuals had clones with more than one type of immunophenotype. Based on our hierarchy, CLL-like MBL was the most common (N=1,155), followed by non-CLL-like (N=168) and atypical MBL (N=67). The median follow-up time in our cohort was 26 months (range 0-142), and 432 individuals had subsequently died. The 5-year and 10-year OS adjusted for age and sex among LC-MBLs was 95% and 87%, respectively; control estimates were 95% and 84%, respectively. We did not observe a significant difference in OS between those individuals with LC-MBL versus controls (HR=0.98, CI=0.77-1.24, P=0.84, Fig 1a), nor when we stratified individuals by age &lt;65 (P=0.77) or age &gt;= 65 (P=0.68). Among females, OS was longer among LC-MBL compared to controls (HR=0.61, CI=0.38-0.97, P=0.04); but no evidence of a difference in OS among males was observed (HR=1.22, CI=0.92-1.62, P=0.17). When we evaluated OS by MBL immunophenotype, we observed no statistically significant difference (Fig 1b, log rank P=0.44). When we stratified the MBLs by immunophenotype versus controls, we also did not observe a difference: CLL-like (HR=0.91, CI=0.71-1.18, P=0.5), atypical (HR=1.73, CI=0.92-3.27, P=0.09), non-CLL like (HR=0.98, CI=0.58-1.66, P=0.95). In the largest MBL screening cohort to date, LC-MBL was a common condition among adults 40 years or older reaching a prevalence as high as 29% among individuals 80 years of age or older. OS among those with and without LC-MBL was similar, regardless of immunophenotype and age. The longer survival in females with MBL versus controls requires further evaluation. Figure 1 Figure 1. Disclosures Parikh: Pharmacyclics, AstraZeneca, Genentech, Gilead, GlaxoSmithKline, Verastem Oncology, and AbbVie: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics, MorphoSys, Janssen, AstraZeneca, TG Therapeutics, Bristol Myers Squibb, Merck, AbbVie, and Ascentage Pharma: Research Funding. Kay: Juno Therapeutics: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol Meyer Squib: Membership on an entity's Board of Directors or advisory committees, Research Funding; Targeted Oncology: Membership on an entity's Board of Directors or advisory committees; TG Therapeutics: Research Funding; Sunesis: Research Funding; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Genentech: Research Funding; Behring: Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Acerta Pharma: Research Funding; MEI Pharma: Research Funding; Tolero Pharmaceuticals: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees; CytomX Therapeutics: Membership on an entity's Board of Directors or advisory committees; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Agios Pharm: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Rigel: Membership on an entity's Board of Directors or advisory committees. Shanafelt: Genentech, Pharmacyclics: Research Funding.

Abstract Introduction: TP53 aberrations, including mutations and deletion of 17p (del17p), are important adverse prognostic markers in chronic lymphocytic leukemia (CLL). Prevalence of TP53 aberrations ranges from 7-11% in untreated CLL and increases with disease progression and treatment. Among CLL patients with TP53 aberrations, co-occurrence of TP53 mutations with del(17p) is common. CLL patients with TP53 mutations or del(17p) have significantly worse outcomes when compared to wild-type patients. Previous studies, focusing on CLL patients at time of treatment, are mixed as to whether a single or more than one TP53 aberration impacts outcomes. TP53 is less well studied in monoclonal B-cell lymphocytosis (MBL), an asymptomatic pre-malignant state of CLL. Del(17p) occurs in 3-4% of MBL individuals, and a study of 54 MBL individuals reported a 2% mutation frequency in TP53. Here we estimated prevalence and evaluated the impact of TP53 aberrations in a large cohort MBL or untreated CLL individuals. Methods : Patients with CLL or MBL diagnosed between 2000 and 2019 from the Mayo Clinic CLL Resource with pre-treatment peripheral blood mononuclear cells (PBMC) collected within two years of diagnosis were considered. DNA was extracted from PBMCs with purity &gt;80% or with sorted CD5+/CD19+ clonal cells. The entire coding regions of 59 CLL driver genes were paired end sequenced. Median coverage depth was &gt;1000x per nucleotide, allowing for detection of mutations with variant allelic fraction (VAF) as low as 1%. Somatic mutations were called using MuTect2 in tumor-only mode, and high impact mutations (frameshift, nonsense, and splicing variants) and missense mutations in CLL hot spots were selected. Somatic mutations and FISH del(17p) were used to define TP53 state for each patient: 1) wild-type [no TP53 mutations and normal del(17p)], 2) single-hit [one TP53 mutation or del(17p)], or 3) multi-hit [multiple TP53 mutations or TP53 mutation and del(17p)]. Time to first treatment (TTFT) and overall survival (OS) were analyzed by TP53 state. TTFT and OS were defined as time from sample collection to first treatment or death, respectively, or last follow-up date. Median TTFT and OS was estimated by the Kaplan-Meier method. We used Cox regression to estimate hazard ratios (HRs) and 95% confidence intervals for TTFT and OS associations. The models were adjusted for known adverse prognostic factors including clinical diagnosis (CLL or MBL), age at diagnosis, Rai stage, b2 microglobulin, and IGHV mutation status. Results: Individuals with CLL (N=597) or MBL (N=285) were analyzed for prevalence of TP53 mutations and del(17p). We found 58 CLL patients (9.7%) and 15 MBL individuals (5.3%) had TP53 mutations. The median VAF in CLL was 30.9% (&lt;10% VAF, n=21) and in MBL was 13.5% (&lt;10% VAF, n=7). Del(17p) was present in 37 patients with CLL (6.2%) and 7 individuals with MBL (2.7%). In total, 86 CLL/MBL patients had a TP53 mutation and/or del(17p): 56.8% (48 patients) were single-hit and 44.2% (38 patients) were multi-hit (Fig. 1a). Patients with any TP53 aberration had shorter TTFT than wild-type patients (median 2.3 vs 9.4 years). Among patients with TP53 aberrations, median TTFT was shorter in multi-hit patients (20 events, 1.8 years) compared to single-hit patients (24 events, 3.2 years) (Fig. 1b). In Cox regression, single-hit (HR = 1.7 [1.1-2.6]) and multi-hit (HR = 1.8 [1.1-2.9]) patients had shorter TTFT compared to wild-type patients after adjusting for covariates (Fig. 1c). Multi-hit patients also had shorter OS compared to wild-type patients, while OS in single-hit patients did not significantly differ from wild-type patients (Fig. 1d). Median OS was 5.5 years in multi-hit patients (22 deaths) compared to 15.1 years in wild-type patients (196 deaths) and 14.3 years in single-hit patients (15 deaths). In the OS model adjusted for covariates, multi-hit patients had a significant increased risk (HR = 2.6 [1.6-4.1]), but single-hit patients did not (HR = 1.4 [0.8-2.5]) compared with wild-type patients (Fig. 1e). OS HRs remained stable after censoring at time of treatment. Both TTFT and OS HRs were consistent when mutations with VAF &lt; 10% were excluded. Conclusions: This study suggests single versus multi-hit TP53 aberrations may be important for prognostic outcomes in untreated CLL and MBL patients. Prognostic metrics may need to consider single versus multi-hit TP53 aberrations and include TP53 mutations with low VAF. Figure 1 Figure 1. Disclosures Cerhan: Regeneron Genetics Center: Other: Research Collaboration; Celgene/BMS: Other: Connect Lymphoma Scientific Steering Committee, Research Funding; NanoString: Research Funding; Genentech: Research Funding. Parikh: Pharmacyclics, MorphoSys, Janssen, AstraZeneca, TG Therapeutics, Bristol Myers Squibb, Merck, AbbVie, and Ascentage Pharma: Research Funding; Pharmacyclics, AstraZeneca, Genentech, Gilead, GlaxoSmithKline, Verastem Oncology, and AbbVie: Membership on an entity's Board of Directors or advisory committees. Kay: MEI Pharma: Research Funding; Bristol Meyer Squib: Membership on an entity's Board of Directors or advisory committees, Research Funding; TG Therapeutics: Research Funding; AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Genentech: Research Funding; Juno Therapeutics: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Tolero Pharmaceuticals: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees; Agios Pharm: Membership on an entity's Board of Directors or advisory committees; Targeted Oncology: Membership on an entity's Board of Directors or advisory committees; CytomX Therapeutics: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Behring: Membership on an entity's Board of Directors or advisory committees; Sunesis: Research Funding; Abbvie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Acerta Pharma: Research Funding; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Rigel: Membership on an entity's Board of Directors or advisory committees.

Abstract Introduction Monoclonal B-cell lymphocytosis (MBL), monoclonal gammopathy of undetermined significance (MGUS), and clonal hematopoiesis (CH) are three common premalignant hematological conditions. MBL is a precursor to chronic lymphocytic leukemia (CLL), MGUS is a precursor to both multiple myeloma (MM) and Waldenström macroglobulinemia (WM), and CH is a possible precursor to myeloid disease. All three conditions are independently associated with aging. Furthermore, there is evidence that all three conditions are associated with increased risk of infection. The relationship among these conditions, the prevalence with which they co-exist, and the association between the number of premalignant conditions and risk of infection is unknown. Methods Study participants from the Mayo Clinic Biobank, a large-scale biorepository of adult patients, provided a peripheral blood sample between 7/14/2009 to 06/18/2015. Individuals were screened for MBL using eight-color flow cytometry capable of detecting clonal B-cells to the 0.005% level. MGUS was screened using a matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) assay. CH was screened using a targeted sequencing panel of 42 CH-associated genes with at least 1000x read depth and the ability to detect variant allele fractions down to 1%. All study participants resided in Olmsted County, Minnesota, the county that includes Mayo Clinic. Serious infection, defined as hospitalization due to infection, was abstracted from medical records from the time of sample collection through 12/31/2020 or date of death. The medical record abstractor collecting data was blinded to condition. Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) for the association between each of the conditions. Cox regression was used to estimate hazard ratios (HR) and 95% CI to assess the association between number of premalignant conditions with risk of infection. All analyses were adjusted for age at sample collection and sex. Results A total of 407 individuals (55% male, median age 68 years) were screened for all three conditions. The prevalence was 19.9% (n=81) for MBL, 14.5% (n=59) for MGUS, and 25.6% (n=104) for CH. When we evaluated the association between each of the conditions, we found no evidence of an association between the prevalence of CH and risk of MBL (OR=0.79, 95% CI: 0.43-1.42), CH and risk of MGUS (OR=1.24, 95% CI: 0.66-2.27), or MGUS and risk of MBL (OR=1.32, 95% CI:0.66-2.52). The prevalence of co-existence of these conditions was assessed by grouping individuals based on their condition or conditions (Figure 1A). We found that 197 (48.4%) study participants had at least one premalignant condition and 10.6% had two or more. Individuals with 2 or more conditions were the oldest (median age 74 years), followed by 1 condition (median 69 years) and 0 conditions (median 67 years, P-trend &lt;0.001). Sex was not significantly different across the groups, with 55%, 58%, and 47% male for 0, 1, and 2 conditions, respectively. Medical record abstraction identified 97 serious infection events in 80 individuals. Medical records were not available on 7 individuals. The most common infections were urinary tract (20 events), pneumonia (14 events), and cellulitis (14 events). Median follow-up time was 10.6 years (range 0.1-11.5 years). Compared to individuals with no condition, MBL (HR=1.75, 95% CI: 1.06-2.88) and MGUS (HR=1.75, 95% CI: 1.04-2.93) were associated with increased risk of serious infection. We found no evidence of an association with CH (HR=1.15, 95% CI: 0.71-1.87). When grouped by the number of conditions, we observed a significant trend (P-trend &lt;0.01, Figure 1B) in risk of serious infections by the number of conditions: individuals with 1 condition had a 35% increased risk of infections (HR=1.35, 95% CI:0.83-2.20) and individuals with 2 or more conditions had a 2.6-fold increased risk (HR=2.58, 95% CI: 1.37-4.84). Discussion At least one premalignant condition was present in nearly 50% of the study population, with CH being the most prevalent. No evidence of a relationship between any of the three conditions was observed. However, we found increased susceptibility to serious infections as the number of conditions increased with individuals with at least two conditions had 2.6-fold increased risk of infections. Figure 1 Figure 1. Disclosures Parikh: Pharmacyclics, AstraZeneca, Genentech, Gilead, GlaxoSmithKline, Verastem Oncology, and AbbVie: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics, MorphoSys, Janssen, AstraZeneca, TG Therapeutics, Bristol Myers Squibb, Merck, AbbVie, and Ascentage Pharma: Research Funding. Dispenzieri: Takeda: Research Funding; Alnylam: Research Funding; Pfizer: Research Funding; Oncopeptides: Consultancy; Sorrento Therapeutics: Consultancy; Janssen: Consultancy, Research Funding. Murray: Mayo Clinic: Other: Has received patents for the Mass-Fix technology which has been licensed to the Binding Site with potential royalties.. Kumar: Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; Oncopeptides: Consultancy; Beigene: Consultancy; Novartis: Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Antengene: Consultancy, Honoraria; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Tenebio: Research Funding; Roche-Genentech: Consultancy, Research Funding; Bluebird Bio: Consultancy; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Carsgen: Research Funding; Amgen: Consultancy, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding. Cerhan: Regeneron Genetics Center: Other: Research Collaboration; Genentech: Research Funding; Celgene/BMS: Other: Connect Lymphoma Scientific Steering Committee, Research Funding; NanoString: Research Funding. Kay: TG Therapeutics: Research Funding; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Agios Pharm: Membership on an entity's Board of Directors or advisory committees; Targeted Oncology: Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Sunesis: Research Funding; MEI Pharma: Research Funding; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol Meyer Squib: Membership on an entity's Board of Directors or advisory committees, Research Funding; Acerta Pharma: Research Funding; Rigel: Membership on an entity's Board of Directors or advisory committees; Tolero Pharmaceuticals: Research Funding; Genentech: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Behring: Membership on an entity's Board of Directors or advisory committees; CytomX Therapeutics: Membership on an entity's Board of Directors or advisory committees; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Juno Therapeutics: Membership on an entity's Board of Directors or advisory committees. Shanafelt: Genentech, Pharmacyclics: Research Funding.

Digital mammography has seen an explosion in the number of radiomic features used for risk-assessment modeling. However, having more features is not necessarily beneficial, as some features may be overly sensitive to imaging physics (contrast, noise, and image sharpness). To measure the effects of imaging physics, we analyzed the feature variation across imaging acquisition settings (kV, mAs) using an anthropomorphic phantom. We also analyzed the intra-woman variation (IWV), a measure of how much a feature varies between breasts with similar parenchymal patterns—a woman’s left and right breasts. From 341 features, we identified “robust” features that minimized the effects of imaging physics and IWV. We also investigated whether robust features offered better case-control classification in an independent data set of 575 images, all with an overall BI-RADS® assessment of 1 (negative) or 2 (benign); 115 images (cases) were of women who developed cancer at least one year after that screening image, matched to 460 controls. We modeled cancer occurrence via logistic regression, using cross-validated area under the receiver-operating-characteristic curve (AUC) to measure model performance. Models using features from the most-robust quartile of features yielded an AUC = 0.59, versus 0.54 for the least-robust, with p < 0.005 for the difference among the quartiles.