Citations

Abstract Background: Bone disease in myeloma occurs as a result of complex interactions between myeloma cells and the bone marrow microenvironment. To date, no studies have evaluated the potential impact of genetic polymorphisms upon and/or within this microenvironment. Patients and Methods: Peripheral blood DNA from 282 patients enrolled in the Total Therapy 2 (TT2) protocol was studied using the previously reported Affymetrix 3k BOAC custom chip to evaluate relevant genetic polymorphisms. DKK1 gene expression and high risk GEP gene signatures were assessed as previously reported (Blood109:4470–4477 and 109:2276–2284 2007). Patients were classified using both full skeletal x-rays and MRI findings. The lower cut-off used was absence of focal abnormalities on x-ray and/or <7 focal lesions on MRI (see JCO25:1121–1128 2007). Results: The top 200 SNPs were first evaluated based upon univariate P values linked to limited or extensive bone disease. The top 50 SNPs with the smallest P values were then selected (eliminating closely linked genes) for recursive partitioning analysis. The recursive partitioning was conducted both with and without the insertion of known biologically relevant SNPs. The pruned tree developed with recursive partitioning proved to be quite stable and incorporated 4 dominant SNPs: rs 3766934 Epoxide hydrolase (EPHX1); sr3783408 MAP kinase; sr 1062637 RNA helicase DDX18; and sr3181366 TNFSF8-TNF-α. No alternate SNP substituted for EPHX1 in the recursive model. The 4 SNP signature of EPHX1 GG, MAP4K5 AG/AA, DDX18 GG/CC plus TNFSF8 CT/TT was highly correlated with the number of MRI lesions: mean 8.66 lesions versus 3.33 for alternate SNPs (P<.001). In the univariate association of standard prognostic factors, 4 SNP signature and 70 and 17 gene models for high risk, the best correlation with bone disease was with the 4 SNPs (P<.0001) followed by the 17 gene GEP model (P=0.05). Using stepwise multivariate regression analysis the best correlation with bone disease was Log2DKK-1 expression (P=.0001) but closely followed by SNPs EPHX1 (P=.0009); MAP4K5 (P=.0071) plus TNFSF8 and serum LDH (P=.02). The various analyses training (2/3) and validation sets were used with assessment of sensitivity and specificity. The microenvironmental 4 SNP signature combined with GEP DKK1 provided the best prediction of myeloma bone disease and overall outcome. Conclusions: This first assessment of genetic polymorphisms linked to myeloma bone disease in myeloma has led to the identification of polymorphisms with both potential biologic relevance and utility in prognostic models of myeloma bone disease including risk stratification for bisphosphonate use. Validation of these findings may allow a search for potential therapeutic targets.

Key Points Early progression of disease within 2 years of initial therapy independently predicts inferior survival in CLL. Early progression of disease is a robust clinical end point and a useful posttreatment risk stratification tool.

Abstract The majority of pts with newly diagnosed CLL are classified with Rai stage 0 or 1 disease and typically experience an indolent clinical course. However, little is known regarding the reasons for initiating therapy in this population or patterns of initial treatment in the contemporary era of our practicing community. We utilized data from the Connect CLL registry, a US-based multi-center, prospective observational cohort study that is aimed at understanding patterns of CLL management without a study-specific intervention. Eligible pts were adults with a clinical diagnosis of CLL who initiated therapy ≤2 months prior to enrollment, and were enrolled from academic (n=155), community (n=1311), or government (n=28) sites between 2010-2014. Descriptive statistics were applied to examine data on demographics, baseline characteristics, treatment selection, early treatment outcomes, and reasons for initiating therapy that were reported for pts with Rai 0/1 CLL receiving first-line therapy. Multivariable logistic regression models were constructed to evaluate predictors of complete response (CR) and event-free survival (EFS) defined as the occurrence of the first of disease progression, relapse or death within 24 months of enrollment. Among 684 pts who received first-line therapy at enrollment and for whom Rai stage was available, 363 had Rai 0/1 CLL. This group had a median age of 68 years (range 41-90); 94% were white, 60% male, 98% insured, and 93% were treated in community practices; 47% had Rai stage 0 disease (54% Binet A); 33% had ≥1 constitutional symptoms; 96% had ECOG performance status of 0 or 1; 35% had conventional cytogenetics and 53% had FISH analysis performed. Among pts for whom cytogenetic or FISH analysis were performed, 159 (72%) were abnormal, of them 37 pts (23%) had del(11q), 104 pts (65%) had del(13q), 33 pts (21%) had trisomy 12, and 20 pts (13%) had del(17p) by conventional cytogenetics and/or FISH, including 8% with del(17p) by FISH. The median time from diagnosis to initiation of therapy was 2.5 years (range 0-20 years) for Rai 0/1 pts compared with 0.5 years for pts enrolled with Rai stage ≥2 (range 0-32). The most common reasons for initiating therapy (with >1 reason possible) in Rai 0/1 CLL were: bulky or progressive or lymphadenopathy (40%), progressive lymphocytosis (39%), any disease-related symptom (weight loss, fatigue, fever, night sweats; 28%), anemia (20%), and thrombocytopenia (15%); 42% of pts had >1 reason for initiation. The most common first-line regimens used in this cohort were: fludarabine/cyclophosphamide/rituximab (FCR; 29%), bendamustine/rituximab (BR; 20%), and rituximab alone (12%). Of the 317 pts who either responded to treatment during the first 24 months of enrollment or were followed ≥24 months, 143 pts (45%) achieved CR (investigator assessed as per protocol) and 264 (83%) achieved CR or partial response. Female gender (odds ratio [OR] = 2.22), treatment with BR or FCR (OR = 3.41), and time from diagnosis to therapy (OR = 0.92; with each year increase in time from diagnosis to initiation of therapy, relative odds of CR decreases by 8%), were independent predictors of CR. Of the 311 evaluable pts, 82 pts (26%) experienced an EFS event during the 24 months on study, of which 19 (23%) were deaths and 48 (59%) were progressions. Age ≥75 years (OR = 4.46), lymphocytosis as a reason for therapy initiation (OR = 1.89), and male gender (OR = 1.73) were independent predictors of an EFS event within 24 months. The Connect CLL registry represents the largest comprehensive prospective cohort of CLL pts collected from multiple practices across the US. In concordance with other studies, pts with Rai 0/1 initiated therapy approximately 2.5 years following CLL diagnosis and included a cohort of pts with poor prognostic FISH characteristics. Although chemoimmunotherapy was associated with a significantly higher likelihood of CR, progressive lymphocytosis as a reason for initiating therapy (and not any form of treatment) was more likely to predict an early EFS event. Approaches using novel agents or combination therapies aimed towards addressing pts with progressive lymphocytosis should be considered in future studies. Disclosures Flowers: Seattle Genetics: Consultancy; OptumRx: Consultancy; AbbVie: Research Funding; Pharmacyclics: Research Funding; Gilead Sciences: Research Funding; Genentech: Research Funding; AbbVie: Research Funding; Celegene: Other: Unpaid consultant, Research Funding; Spectrum: Research Funding; Onyx Pharmaceuticals: Research Funding; Spectrum: Research Funding; Acerta: Research Funding; Gilead Sciences: Research Funding; Janssen: Research Funding; Infinity Pharmaceuticals: Research Funding; Infinity Pharmaceuticals: Research Funding; Janssen: Research Funding; Millennium/Takeda: Research Funding; Onyx Pharmaceuticals: Research Funding; Pharmacyclics: Research Funding; Acerta: Research Funding; Millennium/Takeda: Research Funding. Nabhan:Celgene Corporation: Honoraria, Research Funding. Kay:Pharmacyclics: Research Funding; Genentech: Research Funding; Celgene Corporation: Membership on an entity's Board of Directors or advisory committees, Research Funding; Hospira: Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees, Research Funding; Tolero Pharma: Research Funding. Mato:AbbVie: Consultancy, Research Funding; Janssen: Consultancy; Celgene Corporation: Consultancy, Research Funding; Pronai Pharmaceuticals: Research Funding; Pharmacyclics: Consultancy, Research Funding; TG Therapeutics: Research Funding; Gilead: Consultancy, Research Funding; Genentech: Consultancy. Lamanna:Genentech-Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene Corporation: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Infinity: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Grinblatt:Celgene Corporation: Consultancy, Honoraria, Speakers Bureau. Kipps:Pharmacyclics Abbvie Celgene Genentech Astra Zeneca Gilead Sciences: Other: Advisor; Pharmacyclics Abbvie Celgene Genentech Astra Zeneca Gilead Sciences: Other: Advisor. Kozloff:Roche: Consultancy, Speakers Bureau; Celgene: Consultancy, Speakers Bureau; Genentech: Consultancy, Speakers Bureau; AbbVie: Consultancy. Sullivan:Celgene Corporation: Employment, Equity Ownership. Flick:Celgene Corporation: Employment, Equity Ownership. Kiselev:Celgene Corporation: Consultancy. Bhushan:Celgene Corporation: Employment, Equity Ownership. Swern:Celgene Corporation: Employment, Equity Ownership. Sharman:TG Therapeutics, Inc.: Research Funding; Gilead: Consultancy, Honoraria, Research Funding, Speakers Bureau; Janssen: Research Funding; Calistoga: Honoraria; Celgene Corporation: Consultancy, Research Funding; Pharmacyclics: Consultancy, Honoraria, Research Funding; Roche: Research Funding.

Abstract Lineage-specific growth factors mobilize peripheral blood progenitor cells (PBPC) and accelerate hematopoietic recovery after high-dose chemotherapy. Recombinant human thrombopoietin (rhTPO) may further increase the progenitor-cell content and regenerating potential of PBPC products. We evaluated the safety and activity of rhTPO as a PBPC mobilizer in combination with granulocyte colony-stimulating factor (G-CSF) in 29 breast cancer patients treated with high-dose chemotherapy followed by PBPC reinfusion. Initially, patients received escalating single doses of rhTPO intravenously (IV) at 0.6, 1.2, or 2.4 μg/kg, on day 1. Subsequent patients received rhTPO 0.6 or 0.3 μg/kg on days −3, −1, and 1, or 0.6 μg/kg on days −1 and 1. G-CSF, 5 μg/kg IV or subcutaneously (SC) twice daily, was started on day 3 and continued through aphereses. Twenty comparable, concurrently and identically treated patients (who were eligible and would have been treated on protocol but for the lack of study opening) mobilized with G-CSF alone served as comparisons. CD34+ cell yields were substantially higher with the first apheresis following rhTPO and G-CSF versus G-CSF alone: 4.1 × 106/kg (range, 1.3 to 17.6) versus 0.8 × 106/ kg (range, 0.3 to 4.2), P = .0003. The targeted minimum yield of 3 × 106CD34+ cells/kg was procured following a single apheresis procedure in 61% of the rhTPO and G-CSF–mobilized group versus 10% of G-CSF–mobilized patients (P = .001). In rhTPO and G-CSF mobilized patients, granulocyte (day 8 v 9, P= .0001) and platelet recovery (day 9 v 10, P= .07) were accelerated, and fewer erythrocyte (3 v 4,P = .02) and platelet (4 v 5, P = .02) transfusions were needed compared with G-CSF–mobilized patients. Peripheral blood platelet counts, following rhTPO and G-CSF, were increased by greater than 100% and the platelet content of PBPC products by 60% to 110% on the first and second days of aphereses (P &lt; .0001) with the greatest effect seen with repeated dosing of rhTPO at 0.6 μg/kg. rhTPO is safe and well tolerated as a mobilizing agent before PBPC collection. Mobilization with rhTPO and G-CSF, in comparison to a comparable, nonrandomized G-CSF–mobilized group of patients, decreases the number of apheresis procedures required, may accelerate hematopoietic recovery, and may reduce the number of transfusions required following high-dose chemotherapy for breast cancer.

Abstract Abstract 2059 Introduction: Two randomized trials have demonstrated a benefit in progression free survival (PFS) of 18–20 mofor maintenance treatment with lenalidomide after auto-PBSCT for multiple myeloma (MM). Although results on survival benefit are conflicting and quality of life (QOL) data is lacking, some have begun to recommend maintenance. No study has evaluated patient perceptions of maintenance. We conducted a systematic survey of MM patients (pts) regarding what constitutes a meaningful benefit that would make burdens of maintenance (toxicity and cost) acceptable. Methods: We mailed a brief self-administered survey in 3 waves to 1159 consecutive living pts evaluated at Mayo Clinic. The survey provided background on the standard of care for MM in transplant eligible pts and data on maintenance. Pts were asked to estimate the magnitude of OS benefit that would be acceptable for varying degrees of toxicity and cost. Results: Of the 1159 surveys sent, 886 pts (83.2%) responded, including 150 notifying us of a decision not to participate. 736 pts returned a completed survey (66% raw response rate). (56%) male, 407 (55%) had undergone auto-PBSCT, 467 (63%) had discussed maintenance with a physician, and 9 (1%) pts had received no treatment. 10% of pts had MM for 3–12 mo, 14% for 1–2 yr, 13% for 2–3 yr, 20% for 3–5 yr, 44% for 5 yr or more. Pt age: 4% 18–49 yr, 24% 50–59 yr, 40% 60–69 yr, 27% 70–79 yr, and 6% >80 yrs. The most worrisome potential toxicity was identified as peripheral neuropathy by 27% of pts, cytopenias by 24%, LE DVT 20%, fatigue 15%, nausea 8%, diarrhea/constipation 7%. In response to a question about whether they would choose maintenance if there was a PFS benefit but no improvement in OS, 92% would opt for maintenance if it were known to cause mild toxicity, while 77% would opt for maintenance despite moderate toxicity. Subsequent questions included cost and toxicity considerations and required pts to identify minimum acceptable duration of OS benefit to estimate more precisely a meaningful clinical benefit. If treatment was free, had no toxicity, and the OS benefit was 1 yr or less, 49% would choose maintenance (see Figure). In the same scenario, if toxicities were mild, the proportion of pts who choose maintenance was similar (46%). If pts experienced moderate toxicity, 42% choose maintenance. With rising financial burden (out-of-pocket) and toxicity, the proportion of pts who choose maintenance declined (see Table). For example, if the cost was $25/mo, mild toxicity experienced, and the OS benefit was one year or less, 46% would choose maintenance, while 39% of pts would choose maintenance if it cost $250/month and there was moderate toxicity. If maintenance cost $10,000/mo and was associated with mild or moderate toxicity, 18% and 17% of pts would choose treatment, respectively. Conclusions: For the first time, we have described the broad range of patient perspectives regarding trade-offs in the treatment of MM with maintenance therapy. We found that willingness to be treated with maintenance declined when actual benefits were provided in concrete numeric terms compared with a general statement of PFS benefit. The discrepancy between the 92% of pts choosing to undergo maintenance if free and mild toxicity when there is a PFS benefit but no OS benefit, compared to 49% of pts choosing maintenance if free, mild toxicity, and associated with an OS benefit of 1 yror less; suggests pts have difficulty understanding the concept of PFS. We also found that the magnitude of benefit required to consider maintenance was affected by cost and toxicity. In our experience, pts typically incur a cost of approximately $25/mo and experience mild toxicity. In this study, nearly half (46%) of such pts would opt for maintenance if the OS benefit was 1 year or less while only 33% of pts would opt for maintenance if the OS benefit was 6 months or less. Our data implies that good care in MM requires detailed conversations about each and every patient's priorities and expectations prior to making recommendations for or against such treatments. Disclosures: No relevant conflicts of interest to declare.

Abstract Abstract 743 Background There has been considerable recent focus upon the molecular classification of myeloma. However, the prognostic impact of molecular changes has mostly been assessed from small and/or incomplete studies from single institutions or groups. There has been no large scale analysis of molecular features linked to ISS stage. Methods In order to clarify the overall impact of molecular changes we undertook a collective analysis of 9,897 patients through the International Myeloma Working Group (IMWG). Within this population 2,295 patients had presence of cytogenetic abnormalities (Any CA); 1,713 hypodiploidy; 1,673 hyperdiploidy; 2,309 cytogenetic deletion 13; 3,226 deletion 13 by FISH; 1,573 FISH t(4;14); 1,486 FISH del p17; 1, 683 FISH t(11:14); and 366 FISH t(4;16). Enrolled patients had complete clinical and treatment details available including baseline standard prognostic factors, ISS stage, as well as both progression free survival (PFS) and overall survival (OS) information. Data came from 14 sites: 3 from the US and the remainder from Europe, Asia, and Latin America as for the ISS staging system analyses. Univariate and multivariate analyses were performed. Results Each of the known adverse molecular features had a negative impact upon both PFS and OS (p=002 - <0.0001). Among the deleterious FISH abnormalities the t(4;14) abnormality was the most highly correlated with poorer outcomes by PFS: 4 year estimate: 32% vs. 60% (p<0.0001). The t(4;14) abnormality combined with ISS Stage also significantly enhanced predictive capability: ISS Stage I without t(4;14) OS 81% @ 4 years; ISS Stage III with t(4;14) OS 22% @ 4 years (P<0.0001) [Figure 1]. The best outcomes were for ISS Stage I in the presence of t(11;14): OS 89% @ 4 years. Absence of any one adverse feature correlated with 80-81% OS @ 4 years for Stage I. Presence of any one adverse feature had a more variable impact and correlated with 22%-40% OS at 4 years for Stage III. In univariate correlations the most predictive correlations with OS were presence of Any CA, t(4;14), 17p-, hypodiploidy, cytogenetic 13q- with R2 values of 6.9%, 4.5%, 4.1% and 3.8% respectively. In multivariate analyses, ISS stage provided the best predictions: R2 values = 13.3%. The added contributions from molecular features were: t(4;14) 3.8%; cytogenetic 13q- 2.9%; Any CA 2.3%; and 17p- 1.0%. The maximum total R2 for OS was 22%. Conclusions This large multicenter analysis confirms the correlations between abnormal molecular findings and outcomes. Combinations with ISS Stage provide the best predictive capability. Presence of Any CA, t(4;14), 17p-, hypodiploidy and cytogenetic 13q- contribute to poorer outcomes by ISS stage. The presence of hyperdiploidy and/or t(11;14) contribute to better outcomes. There is thus validation of prior molecular studies related to prognosis utilizing this large IMWG database. Disclosures: No relevant conflicts of interest to declare.

Abstract Abstract 3926 Introduction. Chronic lymphocytic leukemia (CLL) patients will have significant variation in signs and symptoms at initial presentation and across lines of therapy, with concomitant effect on patient health-related quality of life (HRQOL). HRQOL and other patient-reported outcomes, together with clinical outcomes, provide a more complete perspective on the burden of disease and facilitate a broader view of the impact of treatment regimens. This analysis evaluates whether the HRQOL of patients with CLL in the United States (US) varies at the time the patients are about to embark on various lines of therapy, and offers a baseline report from which subsequent longitudinal analysis post-treatment will be possible. Methods. Clinical and HRQOL data were collected in Connect®CLL, a prospective observational registry initiated in March 2010 involving centers in the US. Physicians provided data on the demographics and clinical characteristics of patients receiving therapy. HRQOL was self-reported by patients at enrollment using the Brief Fatigue Inventory (BFI, a symptom assessment tool), the EQ-5D (a non-disease-specific HRQOL instrument), and the Functional Assessment of Cancer Therapy-Leukemia (FACT-Leu, a leukemia-specific HRQOL instrument). We characterized patients who had initial (First Line), second (Second Line) or subsequent (Higher Line) treatment regimens prior to initiation of regimens. Reported mean overall and/or domain-specific BFI, EQ-5D and FACT-Leu scores were analyzed by line of therapy. Statistical significance of score differences among sub-cohorts was ascertained by ANOVA using SAS 9.1. Results. Evaluable data were reported on 1005 patients, enrolled from 161 centers (93% community, 7% academic). Patients were predominantly male (62%) and white (89%) with mean age at 69 (standard deviation [SD] 11) years. HRQOL scores by line of therapy are presented: The total FACT-Leu and FACT-G results, and the total EQ-5D Index and Visual Analogue Scale (VAS) results, consistently suggest that patients initiating first line therapy have somewhat better HRQOL compared with those initiating subsequent lines of therapy. FACT-Leu total scores of patients initiating first line therapy were associated with better physical and leukemia-specific considerations, and the EQ-5D total score was associated with better mobility and pain/discomfort. Conclusions. Initial results from the Connect® CLL Registry indicate that HRQOL prior to treatment is better among patients initiating first line therapy compared to patients initiating later lines of treatment. Future analyses should be conducted to determine what clinical or other factors may be associated with the HRQOL deterioration in patients initiating subsequent lines of therapy, so as to inform clinician decision making. Also, subsequent longitudinal analyses should be undertaken to determine how HRQOL might be affected by the different lines of therapy and the specific treatment regimens, as well as by their initial HRQOL and other patient factors. Disclosures: Kay: Celgene: Research Funding. Flowers:Celgene: Consultancy; Prescription Solutions: Consultancy; Seattle Genetics: Consultancy; Millennium: Research Funding, Unpaid consultancy, Unpaid consultancy Other; Genentech: Unpaid consultancy, Unpaid consultancy Other; Gilead: Research Funding; Spectrum: Research Funding; Janssen lymphoma research foundation: Membership on an entity's Board of Directors or advisory committees. Weiss:Celgene: Consultancy. Lamanna:Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding. Flinn:Celgene: Research Funding. Grinblatt:Celgene: Honoraria, Speakers Bureau. Kipps:Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding. Kozloff:Celgene: Consultancy. Lerner:Celgene Connect: Membership on an entity's Board of Directors or advisory committees. Sharman:Celgene: Consultancy; Pharmacyclics: Honoraria; Calistoga: Honoraria; Portola pharmaceuticals: Consultancy. Khan:Celgene Corporation: Employment, Equity Ownership. Street:Celgene: Employment, Equity Ownership. Swern:Celgene: Employment. Sullivan:Celgene: Employment. Pashos:Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding.

Abstract BACKGROUND The impact of treatment on both the quality and the quantity of life, i.e. the ‘net clinical benefit’, should be considered to inform glioma patients and facilitate shared decision making. We applied two methods (i.e. Quality Adjusted Effect Sizes (QASES) and Joint Modelling (JM)) that combine survival and health-related quality of life (HRQoL) data into one outcome, to gain insight in the net clinical benefit of a treatment strategy. In addition, we assessed if both methods result in similar interpretations. MATERIAL AND METHODS We calculated the net clinical benefit in one randomized controlled trial, EORTC 26951 comparing radiotherapy (RT) + PCV chemotherapy versus RT alone, as a proof of concept for other trials. With the QASES method, effect sizes for differences in survival and HRQoL between treatment arms were calculated. Next, the combined effect size can be determined by weighing the emphasis put on survival or HRQoL (e.g. survival more important). JM allows simultaneous modeling of a longitudinal outcome (HRQoL), and a time-to event outcome (survival). HRQoL scales/items that were selected for primary analysis in the main study were also selected for this analysis: fatigue, global health, social functioning, communication deficit, seizures, physical functioning, and nausea/vomiting. RESULTS 288/386 patients completed baseline HRQoL forms and were included in the analysis. Overall survival (OS) was significantly longer with combined treatment (difference of 10.8 months). In contrast, the percentage of patients who experienced a clinically relevant deterioration (≥10 points) in nausea/vomiting, fatigue, social functioning and global health up to one year after treatment compared to baseline was larger in the RT+PCV arm. The QASES corresponded to a reduction in the median OS difference from 10.8 months to 6.8 months when adjusted for the HRQoL scales/items, when given equal weights to OS and HRQoL. JM analyses resulted in a theoretical loss of treatment effect in OS of 2–6% when adjusting for HRQoL. CONCLUSION Both methods showed that adjusting for the impact of treatment on a relevant HRQoL parameter reduced the survival benefit in the experimental treatment arm compared to standard treatment arm. Applying these methods may facilitate communicating the impact of treatment to patients in clinical practice.

Abstract Background: Mammographic breast density (MBD) is a strong breast cancer (BC) risk factor, but its biologic underpinnings are poorly understood. Use of estrogen plus progestin menopausal hormone therapy is linked to increased MBD and BC risk. Experimental data suggest that ratios of tumor promoting (5α-dihydroprogesterone [5αP]) and anti-tumorigenic (3α-dihydroprogesterone [3αP]) progesterone metabolite levels may be related to BC risk. However, relationships of endogenous progesterone and its metabolites with MBD and BC risk have not been established. Accordingly, we assessed levels of circulating progesterone and its metabolites with MBD. Methods: In this cross-sectional study, serum progesterone and its metabolites were quantified using a novel liquid chromatography-tandem mass spectrometry assay in 103 postmenopausal and 52 premenopausal (luteal menstrual cycle phase) women, ages 40-65, undergoing diagnostic image-guided ipsilateral breast biopsy. MBD was measured as percent fibroglandular volume (MBD-V) on pre-biopsy digital mammograms using single X-ray absorptiometry. Square-root transformed MBD-V was examined across tertile categories of progesterone/progesterone metabolites using age and body mass index (BMI)-adjusted linear regression models. Results: Concentrations of the hormones were as follows among postmenopausal women: progesterone [mean: 12.6 pmol/L (range: 5.2-45.8)], 3αP [5.6 pmol/L (1.4-18.8)], 5αP [100 pmol/L (16.7-388)], and 5αP/3αP ratio [26.1 (2.1-150)]; and among luteal phase premenopausal women: progesterone [2063 pmol/L (13.6-7098), 3αP [12.7 pmol/L (2.4-64.4)], 5αP [243 pmol/L (25.3-774)], 5αP/3αP ratio [25.9 (2.3-73.7)]. Among postmenopausal women, progesterone was positively associated with MBD-V (Tertile 3 vs. 1: β=0.68, p-trend=0.02). A similar borderline positive association was observed among premenopausal women (β=0.74, p-trend=0.10). Additional adjustment for circulating estradiol did not substantively alter observed associations. Levels of 3αP, 5αP and the 5αP/3αP ratio were not associated with MBD-V among pre- or postmenopausal women. Conclusions: Concentrations of progesterone and it metabolites show substantial inter-woman variation. We observed a positive association between endogenous progesterone and MBD-V among both postmenopausal and premenopausal luteal phase women. We did not observe an association with the ratio of 5αP to 3αP levels and MBD-V. These findings suggest the need for additional studies to understand the biological basis of the role of progesterone and its metabolites in MBD and BC risk. Citation Format: Manila Hada, Hannah Oh, Sharon Fan, Roni T. Falk, Berta Geller, Pamela Vacek, Donald Weaver, John Shepherd, Jeff Wang, Bo Fan, Amir P. Mahmoudzadeh, Serghei Malkov, Sally Herschorn, Louise A. Brinton, Xia Xu, Mark E. Sherman, Britton Trabert, Gretchen L. Gierach. Relationship of serum progesterone and progesterone metabolites with mammographic density [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 588.