Citations

Summary Late relapse [>3 years from complete remission (CR)] in acute lymphoblastic leukaemia (ALL), is unusual. Data from the MRC UKALLXII/ECOG E2993 trial are presented to evaluate the incidence and characteristics of late relapse in adult ALL. Of 1,909 patients, 1,752 (92%) achieved CR and among these 757 (43·2%) relapsed; 691 (91·3%) within three years and 66 (8·7%) beyond. Among these 66 patients, median time to relapse was 47 (37–144) months. Relapse beyond three years occurred in 3·8% of all who achieved CR. The cumulative risk of relapse was 40%, 43% and 45% at three, five and ten years respectively. Out of the 1 752 patients who achieved CR, 11·7% underwent autologous and 40·6% allogeneic transplant, while in CR1. Of the autologous patients, 43·2% relapsed early and 3·4% relapsed late. However, among the allogeneic patients, 13·2% relapsed early and only 1·3% late. The five‐year overall survival from relapse was 5·8% and 20% in the early and late relapse patients respectively. In conclusion, late relapse in adults with ALL is not uncommon, and is associated with better outcome after relapse compared to early relapse.

Abstract Background: In an adaptive randomized trial, when new treatment combinations are being tested, it is important to be able to identify patients who are progressing on treatment so that they can be changed to a different therapeutic regimen. We know that even within the molecularly high risk patients in I-SPY 2, there is considerable variation in biology. In this study, we will present results of using MRI-calculated functional tumor volume (FTV) to identify tumor progression for each breast cancer subtype. Methods: Patients (n=990) enrolled in the I-SPY 2 TRIAL who were randomized to the graduated experimental drug arms or controls from 2010 to 2016 were analyzed. Four MRI exams were performed for each patient: pre-NAC (T0), after 3 weeks of NAC (T1), between regimens (T2), and post-NAC (T3). Functional tumor volume (FTV) was calculated at each exam by summing voxels meeting enhancement thresholds. Tumor progression at T1, T2 or T3 was identified by a positive FTV change relative to T0. Visual inspection was used to exclude false progression due to strong background parenchymal enhancement post-contrast, prominent vessels, motion, or insufficient image quality. pCR was defined as no invasive disease in the breast and lymph nodes. Negative predictive value for pCR was defined as:NPV=number of true non-pCRs / number of patients with MRI assessed tumor progressions, where “true non-pCRs” referred to patients who were non-pCRs at surgery and were assessed as progressors by MRI. The analysis was performed in the full cohort and in sub-cohorts defined by HR and HER2 statuses. Results: Out of 990 patients, 878 had pCR outcome data (pCR or non-pCR, pCR rate = 35%). Total and non-pCR numbers for each subtype, number of patients with tumor progression assessed by MRI at T1, T2, and T3, and NPVs, are shown in Table 1. In the full cohort, the NPV increased consistently over treatment, from T1 (NPV=83%) to T2 (93%), and to T3 (100%). The HER2+ cancer subtypes showed fewer MRI-assessed tumor progressions than HER2- subtypes: e.g. 10/209 (5%) vs. 108/669 (16%) at T1. NPV was 100% for HER2+ subtypes at T1 and T2 except for a single misclassification of a HR- tumor at T1. Only 6 tumor progressors, all HER2- were identified at T3, and all were confirmed at surgery as non-pCRs (NPV=100%). For HR+/HER2-, the NPV increased slightly from 89% at T1 to 91% at T2, while triple negative subtype had a more substantial increase, from 78% to 92%. Conclusions: Our study showed strong association between tumor progressors assessed by MRI with true non-pCRs after NAC. For HER2+ tumors, although MRI progressors are rare, they strongly indicate non-pCR at all treatment time points, while HER2- subtypes show more accurate results later in treatment. We are evaluating MRI change at 6 weeks to determine if that time point is sufficient to predict progressors. Table 1 MRI assessed tumor progression at different treatment time pointN/non-pCRs/%non-pCRMRI assessed tumor progressionT1 (after 3 weeks)T2 (inter-regimen)T3 (post-NAC)NNPV (%)NNPV (%)NNPV (%)Full cohort878/572/65%11883.14192.76100%HR+/HER2-344/280/81%4588.91190.93100%HR+/HER2+134/85/63%610021000N/AHR-/HER2+75/23/31%47521000N/Atriple negative325/184/57%6377.82692.33100% Citation Format: Wen Li, Natsuko Onishi, David C Newitt, Jessica Gibbs, Lisa J Wilmes, Ella F Jones, Bonnie N Joe, Laura S Sit, Christina Yau, A. Jo Chien, Elissa Price, Kathy S Albain, Theresa Kuritza, Kevin Morley, Judy C Boughey, Kathy Brandt, Sadia Choudhery, Amy S Clark, Mark Rosen, Elizabeth S McDonald, Anthony D Elias, Dulcy Wolverton, Kelly Fountain, David M Euhus, Heather S Han, Bethany Niell, Jennifer Drukteinis, Julie E Lang, Janice Lu, Jane L Meisel, Zaha Mitri, Rita Nanda, Donald W Northfelt, Tara Sanft, Erica Stringer-Reasor, Rebecca K Viscusi, Anne M Wallace, Douglas Yee, Rachel Yung, Smita M Asare, Michelle E Melisko, Jane Perlmutter, Hope S Rugo, Richard Schwab, W. Fraser Symmans, Laura J van't Veer, Donald A Berry, Angela DeMichele, Hiroyuki Abe, Deepa Sheth, Kirsten K Edmiston, Erin D Ellis, Richard Ha, Ralph Wynn, Erin P Crane, Charlotte Dillis, Michael Nelson, An Church, Claudine Isaacs, Qamar J Khan, Karen Y Oh, Neda Jafarian, Dae Hee Bang, Christiane Mullins, Stefanie Woodard, Kathryn W Zamora, Haydee Ojeda-Fornier, Pulin Sheth, Linda Hovanessian-Larsen, Mohammad Eghtedari, Michael Spektor, Marina Giurescu, Mary S Newell, Michael A Cohen, Elise Berman, Constance Lehman, William Smith, Kim Fitzpatrick, Marisa H Borders, Wei Yang, Basak Dogan, Sally Goudreau, Thelma Brown, Laura J Esserman, Nola M Hylton. Breast cancer subtype specific association of pCR with MRI assessed tumor volume progression during NAC in the I-SPY 2 trial [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr PD9-04.

Abstract Background: Young women with breast cancer (BC) often receive aggressive local therapy and are more likely to undergo (bilateral) mastectomy and receive postmastectomy radiation (RT) than older women. Our previous work suggested better quality of life (QOL) outcomes among women undergoing breast conserving therapy (BCT) vs. mastectomy, even with reconstruction (recon), although limited data was available regarding recon. In the current analysis, we sought to understand the impact of recon, accounting for RT, on long-term satisfaction and QOL. Methods: Between 10/2016-11/2017, we administered the BREAST-Q, a validated patient-reported outcomes measure designed to evaluate satisfaction and QOL after breast cancer surgery and recon, to 743 women in the Young Women’s Breast Cancer Study, a multi-site prospective cohort that enrolled women diagnosed (dx’d) at age < 40 from 2006-2016. Demographic and treatment information was obtained by surveys and chart review. Recon was defined as autologous, implant or complex (combination of autologous and implant). Mean BREAST-Q scores for each domain (breast satisfaction, physical, psychosocial, and sexual) were compared by recon types and stratified by receipt of RT; higher BREAST-Q scores (range: 0-100) indicate better QOL. Linear regression was used to identify predictors of BREAST-Q scores. Results: 584 women with Stage 0-3 BC completed the Breast-Q at a median of 5.7 [range 2-10] years from dx), 357 (61%) had mastectomy and recon and were included in the analytic sample. Median age at dx was 36 years; 85% had stage 0, 1 or 2 disease; 41% received RT and 76% underwent bilateral mastectomy. 90.5% underwent immediate recon; of which 65.5% were tissue expander placement. Definitive recon included autologous tissue in 16%; implants in 81% and complex recon in 3%. Mean BREAST-Q breast satisfaction, psychosocial, and physical well-being scores differed based on recon type accounting for RT (Table 1). Significantly lower scores for breast satisfaction were seen in women having implant +RT. Scores were not impacted by bilateral procedure, timing of recon, use of tissue expander, extent of axillary surgery, cancer stage or other treatment factors. In multivariate analyses, receipt of RT, lymphedema and implant-based recon were associated with lower breast satisfaction scores. Physical well-being scores were lower for those with complex recon, for non-White women, for women who reported being financially uncomfortable, for those with lymphedema, and for those <5 years from surgery. Psychosocial well-being scores were lower for women who received RT, had BMI >25, and for those who reported being financially uncomfortable. Sexual well-being scores were lower for women with a BMI >25 and for those who reported being financially uncomfortable. Conclusion Type of recon and receipt of radiation among young survivors who undergo mastectomy and recon for early breast cancer appears to have a differential impact on satisfaction and QOL. Our finding of lower breast satisfaction among young women who received RT, particularly after implant recon, underscores the importance of counseling regarding surgical options, especially for women who may receive RT after mastectomy and who are candidates for BCT. Table 1. Unadjusted BREAST-Q scores stratified by RTBREAST-Q DomainAutologous -RT N=29Autologous +RT N=27Implant -RT N=174Implant +RT N=113Complex N=13Global p-valueSatisfaction with Breasts, mean (sd)67 (19)63 (18)64 (18)53 (18)58 (22)<0.01Physical well-being, mean (sd)81 (13)80 (14)80 (15)77 (14)67 (18)0.01Psychosocial well-being, mean (sd)71 (18)64 (18)72 (20)66 (23)62 (20)0.03Sexual well-being, mean (sd)54 (21)50 (24)52 (20)47 (22)48 (27)0.26RT= radiation Citation Format: Laura Dominici, Jiani Hu, Hee Jeong Kim, Tari King, Kathryn Ruddy, Rulla Tamimi, Jeffrey Peppercorn, Lidia Schapira, Virginia Borges, Stephen Come, Ellen Warner, Julia Wong, Ann Partridge, Shoshana Rosenberg. BREAST-Q satisfaction and quality of life outcomes in young women undergoing mastectomy and reconstruction for breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr PD6-1.

Abstract Purpose: To determine the sensitivity of germline hereditary cancer genetic testing recommendations for detection of pathogenic mutations in breast cancer predisposition genes in an unselected cohort of breast cancer patients. Patients and Methods: The study population included patients enrolled in a prospective breast cancer registry after being seen at Mayo Clinic for newly diagnosed breast cancer between 2004 and 2016. All patients were subjected to germline mutation testing for 12 known breast cancer predisposition genes (ATM, BARD1, BRCA1, BRCA2, CDH1, CHEK2, NF1, PALB2, PTEN, RAD51C, RAD51D and TP53). Results from testing of all breast cancer patients according to American Society of Breast Surgeons (ASBrS) genetic testing recommendations and patients meeting National Comprehensive Cancer Network (NCCN) criteria for BRCA1/2 testing, based on age at diagnosis and personal and family history of cancer, were compared. Results: Among the 4516 patients in the cohort, the median age at diagnosis of breast cancer was 57 years, 80.5% had estrogen receptor positive tumors, and 43% had a family history of breast cancer. All patients in the cohort met ASBrS criteria for hereditary cancergenetic testing, 2050 (45.4%) met NCCN criteria, 1892 (41.9%) did not meet NCCN criteria, and 574 (12.7%) patients could not be fully evaluated for NCCN testing criteria due to missing data. The frequencies of pathogenic variants in the cohort are shown in Table 1. Patients meeting NCCN criteria were more likely to carry a pathogenic variant compared to those who did not (9.8% vs. 3.8%, p<0.001, Table 1). However, 72 (26.5%) out of the 272 patients with mutations in 12 breast cancer predisposition genes and 15 (12.4%) out of 121 with mutations in BRCA1/2 were overlooked when NCCN selection criteria alone were applied. When testing was expanded to include all patients with breast cancer diagnosed at age ≤65 and/or meeting NCCN testing criteria, only 20 (7.4%) out of 272 mutation carriers in 12 breast cancer genes and 2 (1.6%) out of 121 BRCA1/2 mutation carriers were overlooked. However, this increased the number tested to detect one mutation carrier on average from 17 to 25 for BRCA1/2 and from 9 to 12 for the 12 breast cancer predisposition genes. In total, this age cutoff led to an increase in the number of patients tested by 28% while the number of patients in the cohort that need not undergo germline genetic testing was 20%. Conclusions: Although NCCN criteria for BRCA1/2 germline genetic testing detect the majority of predisposition gene mutation carriers, a significant number of carriers are missed in an unselected cohort of breast cancer patients using these criteria. Expanding the current NCCN criteria to include all women with breast cancer diagnosed ≤ 65 years of age, will substantially improve the sensitivity of mutation testing, without the need for evaluation of all breast cancer patients. Table 1: Comparison of frequency of germline mutations between patients who met and did not meet NCCN guidelines for germline genetic testing#Total, Meets ASBrS guidelines N=3942Meets NCCN guidelines, N=2050Did not meet NCCN guidelines, N=1892P-value€ NCCN vs non-NCCNPercent mutation carriers missed by NCCN criteria* BRCA1/2121 (3.1%)106 (5.2%)15 (0.8%)<0.00112.4%6 High risk genes$150 (3.8%)120 (5.8%)30 (1.6%)<0.00120.0%12 Breast cancer genes:272 (6.9%)200 (9.8%)72 (3.8%)<0.00126.5%ATM45 (1.1%)32 (1.56%)13 (0.69%)28.9%BARD16 (0.2%)5 (0.24%)1 (0.05%)16.7%BRCA158 (1.5%)53 (2.59%)5 (0.26%)8.6%BRCA263 (1.6%)53 (2.59%)10 (0.53%)15.9%CDH16 (0.2%)3 (0.15%)3 (0.16%)50.0%CHEK267 (1.7%)41 (2.00%)26 (1.36%)38.8%NF10 (0.0%)0 (0.00%)0 (0.00%)0.0%PALB216 (0.4%)7 (0.34%)9 (0.48%)56.3%PTEN1 (0.0%)1 (0.05%)0 (0.00%)0.0%RAD51C6 (0.2%)6 (0.29%)0 (0.00%)0.0%RAD51D4 (0.1%)2 (0.10%)2 (0.11%)50.0%TP537 (0.2%)3 (0.15%)4 (0.21%)57.1%#: Patients who did not meet NCCN criteria excluded from analysis$: BRCA1, BRCA2, CDH1, PALB2, PTEN and TP53;€: Fisher exact test comparing frequency of germline mutations between those who met NCCN guidelines and those who did not;*: Denominators for percentages are the total mutation carriers in respective categories. Citation Format: Siddhartha Yadav, Chunling Hu, Steven N. Hart, Nicholas Boddicker, Eric C. Polley, Jie Na, Rohan Gnanaolivu, Kun Y. Lee, Janet E. Olson, Kathryn J. Ruddy, Fergus J. Couch. Comparison of recommendations for germline genetic testing in an unselected cohort of patients with breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P6-08-01.

Abstract Background: Strong background parenchymal enhancement (BPE) may cause overestimation in tumor volume measured from dynamic contrast-enhanced (DCE) MRI, which may adversely affect the ability of MR tumor volume to predict treatment outcome for patients undergoing neoadjuvant chemotherapy (NAC). Specifically, an overestimation of tumor volume can result in misclassification of patients with complete pathologic response (pCR) as non-responders, leading to less confidence in MRI prediction. As well, overestimation of extent of disease might lead to more aggressive surgical therapy than necessary. This study investigated whether high BPE in the contralateral breast influences the predictive performance of MRI-measured functional tumor volume (FTV) for patients with locally advanced breast cancer undergoing NAC. Methods: patients (n=990) enrolled in the I-SPY 2 TRIAL who were randomized to the graduated experimental drug arms or controls from 2010 to 2016 were analyzed. Each patient had 4 MRI exams: pre-NAC (T0), after 3 weeks of NAC (T1), between NAC regimens (T2), and post-NAC (T3). FTV was calculated at each MRI exam by summing voxels meeting enhancement thresholds. Background parenchymal enhancement (BPE) in the contralateral breast was calculated automatically as mean percentage enhancement on the early (nominal 150sec post-contrast) image in the fibroglandular tissue segmented from 5 continuous axial slices centered in the inferior-to-superior stack. For each treatment time point, patients having both FTV and BPE measurements were included in the analysis. The area under the ROC curve (AUC) was estimated as the association between FTV and pCR at T1, T2, and T3. The analysis was conducted in the full patient cohort and in sub-cohorts defined by hormone receptor (HR) and HER2 status. In each patient cohort, a cut-off BPE value was selected to classify patients with high vs. low BPE by testing AUCs estimated with low-BPE patients reached maximum when the cut-off value varied from median to maximum in steps of 10%. Results: Out of 990 patients, 878 had pCR outcome data (pCR or non-pCR, pCR rate = 35%). Table 1 shows the number of patients, pCR rate, and AUC of FTV for predicting pCR using all patients available vs. a subset patients with low BPE (< BPE cut-off). In the full cohort, AUC increased slightly across all time points after patients with high BPE were removed. In the HR+/HER2- subtype, AUC increased at T1 after removal of cases with high BPE (0.65 vs. 0.71). For HR-/HER2+, AUC increased substantially after removal of high BPE cases (0.65 to 0.86 at T1, 0.71 to 0.87 at T2, and 0.71 to 0.89 at T3), with greater improvement at the early time point (T1) compared to later time points (T2 and T3). Only a slight improvement in the AUC was observed in the HR+/HER2+ and HR-/HER2- subtypes across all time points. Conclusions: High background parenchymal enhancement adversely affected the predictive performance of functional tumor volume measured by DCE-MRI, at early treatment time point for HR+/HER2- and across all time points for HR-/HER2+ cancer subtype. The adverse effect might be offset using subtype-optimized enhancement threshold in calculating functional tumor volume. Table 1 Effect of BPE on the prediction of pCR using FTV at various treatment time pointsT1T2T3npCR rateAUCBPE cut-offnpCR rateAUCBPE cut-offnpCR rateAUCBPE cut-offFullAll64734%0.662762334%0.701761134%0.6925Subset45334%0.6831133%0.7230534%0.72HR+/HER2-All26218%0.651924918%0.718225518%0.7519Subset13118%0.7124818%0.7120419%0.76HR+/HER2+All10636%0.642110538%0.62269634%0.7120Subset5332%0.668438%0.665740%0.73HR-/HER2+All5175%0.65204774%0.71204973%0.7116Subset3073%0.862871%0.872475%0.89HR-/HER2-All22842%0.682822243%0.751821143%0.6916Subset15940%0.7111137%0.7810540%0.75 Citation Format: Wen Li, Natsuko Onishi, David C Newitt, Roy Harnish, Ella F Jones, Lisa J Wilmes, Jessica Gibbs, Elissa Price, Bonnie N Joe, A. Jo Chien, Donald A Berry, Judy C Boughey, Kathy S Albain, Amy S Clark, Kirsten K Edmiston, Anthony D Elias, Erin D Ellis, David M Euhus, Heather S Han, Claudine Isaacs, Qamar J Khan, Julie E Lang, Janice Lu, Jane L Meisel, Zaha Mitri, Rita Nanda, Donald W Northfelt, Tara Sanft, Erica Stringer-Reasor, Rebecca K Viscusi, Anne M Wallace, Douglas Yee, Rachel Yung, Michelle E Melisko, Jane Perlmutter, Hope S Rugo, Richard Schwab, W. Fraser Symmans, Laura J van't Veer, Christina Yau, Smita M Asare, Angela DeMichele, Sally Goudreau, Hiroyuki Abe, Deepa Sheth, Dulcy Wolverton, Kelly Fountain, Richard Ha, Ralph Wynn, Erin P Crane, Charlotte Dillis, Theresa Kuritza, Kevin Morley, Michael Nelson, An Church, Bethany Niell, Jennifer Drukteinis, Karen Y Oh, Neda Jafarian, Kathy Brandt, Sadia Choudhery, Dae Hee Bang, Christiane Mullins, Stefanie Woodard, Kathryn W Zamora, Haydee Ojeda-Fornier, Mohammad Eghedari, Pulin Sheth, Linda Hovanessian-Larsen, Mark Rosen, Elizabeth S McDonald, Michael Spektor, Marina Giurescu, Mary S Newell, Michael A Cohen, Elise Berman, Constance Lehman, William Smith, Kim Fitzpatrick, Marisa H Borders, Wei Yang, Basak Dogan, Laura J Esserman, Nola M Hylton. The effect of background parenchymal enhancement on the predictive performance of functional tumor volume measured in MRI [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P6-02-01.

Abstract Background: Anthracycline and cyclophosphamide (AC) is a highly emetogenic chemotherapy (HEC) regimen. Combination netupitant/palonosetron (NEPA) + dexamethasone (DEX) is guideline-recommended for prophylaxis of chemotherapy-induced nausea and vomiting (CINV) in HEC and moderately emetogenic chemotherapy. CMS’ OP-35 measure deems 30-day post-chemotherapy acute care as avoidable if involving nausea and emesis (NV) or any of 8 other toxicities. Results will be publicly reported and impact Medicare reimbursement. CMS (2017) found that 10% of >58,000 patients with avoidable acute care after chemotherapy involved NV. Because NEPA is new, insufficient real world data exist to assess its CINV resource use. CINV-related acute-care after NEPA prophylaxis in AC has been reported in a prospective clinical trial. Our aim was to compare these rates to those seen after prophylaxis with other antiemetics for AC outside of a clinical trial. Methods: Pre-specified endpoints in a prospective trial of oral or IV NEPA + DEX in AC included acute-care use (emergency [ED] visits or inpatient admissions [IP]) involving CINV, defined as emesis or rescue drug use ≤5 days after AC, and concomitant ED/IP in the same period. We also evaluated CINV-related acute care after non-NEPA prophylaxis for AC in breast cancer from 10/2012-8/2018 in IBM Explorys electronic health records. We age-matched patients 3:1 to the NEPA trial. We further adjusted the event rate to address under-reporting of a) CINV rates (vs. 49.2% for aprepitant in AC in a clinical trial [Warr 2005]) and b) acute-care use, projected at 17-50% at sites external to the dataset. To compare the resulting adjusted event rate to the NEPA study, we conducted 10,000 Monte Carlo simulations, using random probabilities from 5.2-8.7% for Explorys patients, and from 0-2% for NEPA patients to address potential reporting variability, despite the trial including daily patient diaries. Analysis of data was limited to the first two cycles, the median duration in the NEPA trial. Results: In the NEPA trial, 402 patients received ≥1 cycle; 391 completed two cycles. Nine patients had IP admissions; none involved CINV. Five patients had 6 total ED visits; one met criteria for involving CINV; the resulting rate of acute care rate involving CINV was 0.25 per 100 patients. For other antiemetics, 2598 patients received AC (excluding NEPA prophylaxis). Among 1206 age-matched to the NEPA trial, 15 patients had acute-care events in the first 2 cycles, (1.24 per 100 patients), an odds ratio of 1:5.1 (CI 0.7-38.5) in favor of NEPA. After adjusting via the simulation, the odds ratio was 1:8.3 (CI: 2.43-24.21) in favor of NEPA. Conclusions: Comparing CINV-related acute care seen in a large prospective trial relative to real-world evidence in patients with breast cancer treated with AC, <1% of patients receiving NEPA prophylaxis required acute care for CINV; the CINV-related acute-care risks seen with other antiemetic prophylaxis were 5 times (unadjusted) to 8 times (adjusted) the levels for NEPA. A similar comparison using only real world data should be conducted as data permit. Citation Format: Lee Schwartzberg, Kathryn J Ruddy, Rudolph M Navari, Thomas W LeBlanc, Rebecca Clark-Snow, Rita Wickham, Gary Binder, William L. Bailey, Ravi Potluri, Luke M Schmerold, Eros Papademetriou, Eric J Roeland. Avoidable acute care involving chemotherapy-induced nausea and vomiting (CINV) among patients with breast cancer receiving anthracycline + cyclophosphamide (AC) with NEPA prophylaxis relative to other antiemetics: An external control arm analysis [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P5-14-07.

Abstract Background: Polygenic risk scores (PRS) based on a large number of SNPs associated with breast cancer have recently been made available in combination with multigene panel testing for clinical management of breast cancer risk. Breast cancer risk assessment has historically been performed using various non-genetic risk models, which predict lifetime risk of breast cancer in unaffected women based on personal and family history information. While clinical use of PRS in combination with these models continues to increase, the predictive performance of a PRS combined with clinical information in real-world patient populations has not been thoroughly investigated. Methods: We assessed a 100-SNP breast cancer PRS in combination with the Tyrer-Cuzick model-estimated lifetime breast cancer risk in 5,374 Caucasian women from the case-control Mayo Clinic Breast Cancer Study (MCBCS), comprised of 3,373 breast cancer cases and 2,001 unaffected controls seen at Mayo Clinic from 2004 to 2016. Clinical, family history, and demographic information was collected on all MCBCS participants via questionnaires and medical record review. SNPs were selected for the PRS if they exceeded genome-wide significance in ≥2 large-scale breast cancer genome wide association studies (GWAS) in women of European descent. Selected SNPs were then used to construct a population standardized PRS, accounting for per-allele odds ratios reported in the largest GWAS to date and population-specific allele frequencies. PRS and Tyrer-Cuzick model associations with breast cancer and related clinical features were tested using multivariate logistic regression. Results: Among cases and controls, mean±SD age at diagnosis and study enrollment was 56.4±12.4 and 56.2±14.1, respectively. Approximately 36.9% of cases and 16.9% of controls had ≥1 first- or second-degree relative with breast or ovarian cancer, respectively. Among unaffected women, the median (IQR) estimated lifetime risk of breast cancer to age 85 based on Tyrer-Cuzick alone was 8.3% (6.9%), and 2.6% had a clinically actionable lifetime risk of ≥20%. The mean±SD sum of the risk alleles across 100 SNPs was significantly higher for cases vs. controls (94.8±6.3 vs. 92.7±6.2, p<0.001). Compared to women in the lowest quartile of PRS, those in the 2nd, 3rd and 4th quartiles were 1.47 (95% CI: 1.26-1.72), 1.87 (95% CI: 1.60-2.19), and 2.22 (95% CI: 1.89-2.61) times more likely to have breast cancer after adjustment for age and family history. The AUC was 0.59 (95% CI: 0.58-0.61) for PRS and 0.60 (95% CI: 0.58-0.61) for Tyrer-Cuzick model estimated risk alone; but when combined, the model achieved an AUC of 0.63 (95% CI: 0.62-0.65). Among unaffected women, 6.7% had ≥20% lifetime risk of breast cancer based on the combined PRS-clinical model. Conclusions: These findings suggest that the 100-SNP PRS significantly improves estimation of breast cancer risk based on non-genetic models, and can be used to further identify women at increased lifetime risk who would otherwise not be identified by clinical assessment alone. Citation Format: Mary Helen Black, Shuwei Li, Holly LaDuca, Sebastian Armasu, Eric C. Polley, Patrick Fitz-Gibbon, Chris G. Scott, Stacey J. Winham, Janet E. Olson, Kathryn J. Ruddy, Celine M. Vachon, Fergus J. Couch. Performance of a polygenic risk score combined with clinical assessment for breast cancer risk [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P5-07-06.

Abstract Background The Circulating Cell-free Genome Atlas (CCGA; NCT02889978) study is a prospective, multi-center, observational, case-control study with longitudinal follow-up to support the development of a plasma cfDNA-based multi-cancer early detection assay. We previously reported that the fraction of tumor-derived cfDNA fragments in plasma (estimated tumor fraction [TF]) is associated with detection of multiple cancer types using a prototype whole-genome bisulfite sequencing (WGBS) assay in a pre-specified substudy. In addition, detectability of breast cancer varied by hormone-receptor (HR) status: HR negative (HR-) breast cancer had a higher detection rate than the overall breast cancer cohort. Here, we performed a planned in-depth analysis of the breast cancer cohort to understand the main clinical and biological determinants of detectability using our WGBS assay. Methods Blood samples were prospectively collected from participants (pts) with newly-diagnosed, untreated breast cancer. In a pre-specified CCGA substudy, 511 (31.4%) of 1,628 pts had a clinicopathologic diagnosis of breast cancer (any stage, excluding stage 0) and a WGBS result. Pre-specified biological and clinical factors were assessed for correlation with TF: clinical stage, pathologic N stage, lesion size (by imaging), T stage, histologic grade, hormone receptor (HR) status, and proliferative rate (Ki-67 by IHC [MIB-1 clone]) via univariate and multivariate analyses. Ki-67 was obtained from pathology reports provided by enrollment sites and also assessed centrally (Mayo Clinic [Rochester, MN]). Stage-specific differences in detection rates between HR positive (HR+) and HR- breast cancers due to biological differences such as histologic grade and/or proliferative rate was also assessed. Results Of 511 pts, 94 (18.4%; 48.9% HR- and 12.3% in HR+) had WGBS-detected cancer. Higher TF was significantly associated with cancer detection (p<0.001). In univariate analyses, the variables significantly associated with TF were clinical stage, pathological N stage, and histologic grade (p<0.001 each). Primary lesion size was modestly correlated with TF (all stages combined: Spearman's correlation coefficient rs=0.4, p<0.001), and when grouped by early and late stages (stages I/II: rs=0.27, p<0.01; stages III/IV: rs=0.50, p<0.01); clinical T stage was significantly associated with TF only when all stages were combined (p<0.001). Proliferative rate (Ki-67) was positively correlated with TF at stages I/II (rs=0.29, p<0.05) but not III/IV (rs=-0.24, p=0.34); Ki-67 results obtained through Mayo were similar to that from enrollment sites (Pearson’s correlation coefficient rp=0.68, p<0.001). HR- breast cancers had significantly higher TF versus HR+ breast cancers only at stage II (p<0.001). In addition, compared to HR+ breast cancers, HR- breast cancers had a significantly higher proportion of high histologic grade (p<0.001 at stages I and II) and proliferative rate at earlier stages (p<0.05 at stages I, II, and III). In the multivariate analysis, clinical stage (stage III vs I and IV vs I) and HR status remained the most significantly associated with TF (p<0.001 each). Conclusions Using a prototype methylation-based plasma cfDNA cancer detection assay, TF was found to be associated with detection, and with clinical and biological features of breast cancer. Features routinely used to assess clinical aggressiveness (eg, HR- status and histologic grade) also demonstrated stage-specific associations with TF. Given the known relationship between TF and detection, these data suggest that clinical and biological cancer features may also provide insight into the variability of cancer detection using plasma-based cfDNA tests. Citation Format: Minetta C. Liu, Jodi M. Carter, Daniel W. Visscher, Karla Kopp, Rita Shaknovich, Xiaoji Chen, Kathryn N. Kurtzman, Shilpen Patel, Jacqueline D. Brooks, Carlo R. Cosenza, Jafi A. Lipson, Donald A. Richards, Fergus J. Couch, Zhao Dong, Hai Liu, Oliver Venn, Joerg Bredno, Eric T. Fung, Anne-Renee Hartman. Blood-based cancer detection in plasma cell-free DNA (cfDNA): Evaluating clinical and pathologic tumor characteristics in participants with breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P5-01-01.

Abstract Background: The clinical utility of routine annual mammogram after curative-intent treatment for male breast cancer is uncertain. There is potentially greater value after lumpectomy (as surveillance for ipsilateral recurrence) than mastectomy (as screening for a new contralateral cancer). The goal of this study was to assess real world use of mammography in men during the first year after lumpectomy or mastectomy to treat breast cancer. Methods: Administrative claims data from OptumLabs Data Warehouse (a large US database that includes privately insured patients and Medicare Advantage-insured enrollees from all 50 states and of all ages and ethnic and racial groups) were used to identify men treated with breast surgery for a new diagnosis of breast cancer between 2007 and 2017. We required continuous coverage starting at least 6 months prior to the non-metastatic breast cancer diagnosis and continuing until at least 13 months after the breast surgery. Our primary endpoint was the proportion of patients who had at least one mammogram during the year (13-month period, to allow for scheduling and other logistical delays) after lumpectomy or mastectomy. Univariate and multivariate testing were performed to identify predictors of mammography (with p<0.05 used as the threshold for statistical significance for both). Our secondary endpoint was the proportion with at least one mammogram within 24 months of surgery, performed in a subset who maintained their insurance coverage for at least that duration. Results: The 13-month analysis included 730 men with a median age at diagnosis of 62 years (Range: 25 to 87 years) and a median follow-up duration of 35 months (Range: 13 to 134 months). 209 (29%) of these men underwent mammography within 13 months after surgery. The characteristics of patients who underwent mammography and those who did not are shown in Table 1. Mammography was more likely after lumpectomy than mastectomy (41% vs. 27%) and after radiation therapy (41% vs. 32% in those who did not receive radiation). In a multivariate logistic regression model, more recent diagnosis (2015+) was associated with lower odds of undergoing mammography, while receipt of radiation was associated with higher odds of undergoing mammography. In the subset of patients with two or more years of post-surgery coverage (n=527), the proportion who had at least one mammogram during that 24-month period was 49% after lumpectomy and 40% after mastectomy. Conclusions: In this insured cohort, 73% of men did not undergo mammography within a year after mastectomy, and 59% did not within a year after lumpectomy. Mammography was less likely in patients diagnosed more recently (perhaps due to acknowledgment of the unique aspects of male breast cancer including a relatively low risk of contralateral second primary tumors), and more likely in those who received radiation. These variations in practice likely result from the paucity of evidence-based guidelines for male breast cancer survivorship care. More research is needed pertaining to whether or not mammograms improve clinical outcomes after curative intent treatment for male breast cancer. Table 1: Patient characteristics associated with receipt of mammogram within first 13 months after male breast cancer surgeryUnivariate AnalysisMultivariate AnalysisNo Mammogram (N=521)Mammogram (N=209)P-value, chi-square testOdds Ratio (OR) and 95% CIP-value for ORAge Group:0.1225-4966 (12.7%)32 (15.3%)Reference50-64216 (41.5%)98 (46.9%)0.99 (0.60, 1.63)0.9665-74112 (21.5%)44 (21.1%)0.87 (0.48, 1.57)0.6575+127 (24.4%)35 (16.7%)0.57 (0.30, 1.07)0.08Census Region:0.52Midwest138 (26.5%)59 (28.2%)ReferenceNortheast97 (18.6%)47 (22.5%)1.10 (0.68, 1.78)0.69South223 (42.8%)79 (37.8%)0.74 (0.49, 1.11)0.15West63 (12.1%)24 (11.5%)0.83 (0.47, 1.47)0.51Year of diagnosis:0.072007-2010126 (24.2%)65 (31.1%)Reference2011-2014199 (38.2%)82 (39.2%)0.80 (0.54, 1.20)0.292015+196 (37.6%)62 (29.7%)0.63 (0.41, 0.96)0.03Elixhauser Category:0.250148 (28.4%)69 (33.0%)Reference1-2218 (41.8%)74 (35.4%)0.85 (0.56, 1.28)0.433+155 (29.8%)66 (31.6%)1.18 (0.75, 1.87)0.47Surgery Type:0.005Lumpectomy55 (10.6%)38 (18.2%)ReferenceMastectomy466 (89.4%)171 (81.8%)1.57 (0.97, 2.55)0.07Chemotherapy:0.79No301 (57.8%)123 (58.9%)ReferenceYes220 (42.2%)86 (41.1%)0.79 (0.54, 1.16)0.23Radiation:0.02No355 (68.1%)124 (59.3%)ReferenceYes166 (31.9%)85 (40.7%)1.51 (1.03, 2.20)0.03 Citation Format: Siddhartha Yadav, Lindsey Sangaralingham, Stephanie R. Payne, Karthik V. Giridhar, Tina J. Hieken, Judy C. Boughey, Robert W. Mutter, John R. Hawse, Rafael E. Jimenez, Rachel A. Freedman, Sadia Choudhery, Fergus J. Couch, Celine M. Vachon, Nilay Shah, Roberto A. Leon-Ferre, Kathryn J. Ruddy. Surveillance mammography after treatment for male breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P4-17-08.