Round Table Discussion on Optimal Clinical Trial Design in Precursor Multiple Myeloma

SUMMARY

While the current approach to precursor hematologic conditions is to "watch and wait," this may change with the development of therapies that are safe and extend survival or delay the onset of symptomatic disease. The goal of future therapies in precursor hematologic conditions is to improve survival and prevent or delay the development of symptomatic disease while maximizing safety. Clinical trial considerations in this field include identifying an appropriate at-risk population, safety assessments, dose selection, primary and secondary trial endpoints including surrogate endpoints, control arms, and quality-of-life metrics, all of which may enable more precise benefit-risk assessment.

Mass spectrometry-detected MGUS is associated with obesity and other novel modifiable risk factors in a high-risk population

ABSTRACT

Monoclonal gammopathy of undetermined significance (MGUS) is a premalignant condition of multiple myeloma with few known risk factors. The emergence of mass spectrometry (MS) for the detection of MGUS has provided new opportunities to evaluate its risk factors. In total, 2628 individuals at elevated risk for multiple myeloma were enrolled in a screening study and completed an exposure survey (PROMISE trial). Participant samples were screened by MS, and monoclonal proteins (M-proteins) with concentrations of ≥0.2 g/L were categorized as MS-MGUS. Multivariable logistic models evaluated associations between exposures and MS outcomes. Compared with normal weight (body mass index [BMI] of 18.5 to <25 kg/m2), obesity (BMI of ≥30 kg/m2) was associated with MS-MGUS, adjusting for age, sex, Black race, education, and income (odds ratio [OR], 1.73; 95% confidence interval [CI], 1.21-2.47; P = .003). High physical activity (≥73.5 metabolic equivalent of task (MET)-hours per week vs <10.5 MET-hours per week) had a decreased likelihood of MS-MGUS (OR, 0.45, 95% CI, 0.24-0.80; P = .009), whereas heavy smoking and short sleep had increased likelihood of MS-MGUS (>30 pack-years vs never smoker: OR, 2.19; 95% CI, 1.24-3.74; P = .005, and sleep <6 vs ≥6 hours per day: OR, 2.11; 95% CI, 1.26-3.42; P = .003). In the analysis of all MS-detected monoclonal gammopathies, which are inclusive of M-proteins with concentrations of <0.2 g/L, elevated BMI and smoking were associated with all MS-positive cases. Findings suggest MS-detected monoclonal gammopathies are associated with a broader range of modifiable risk factors than what has been previously identified. This trial was registered at www.clinicaltrials.gov as #NCT03689595.

Design and Rationale of Prolonged Nightly Fasting for Multiple Myeloma Prevention (PROFAST): Protocol for a Randomized Controlled Pilot Trial

BACKGROUND

Obesity is an established, modifiable risk factor of multiple myeloma (MM); yet, no lifestyle interventions are routinely recommended for patients with overweight or obesity with MM precursor conditions. Prolonged nightly fasting is a simple, practical dietary regimen supported by research, suggesting that the synchronization of feeding-fasting timing with sleep-wake cycles favorably affects metabolic pathways implicated in MM. We describe the design and rationale of a randomized controlled pilot trial evaluating the efficacy of a regular, prolonged nighttime fasting schedule among individuals with overweight or obesity at high risk for developing MM or a related lymphoid malignancy.

OBJECTIVE

We aim to investigate the effects of 4-month prolonged nightly fasting on body composition and tumor biomarkers among individuals with overweight or obesity with monoclonal gammopathy of undetermined significance (MGUS), smoldering multiple myeloma (SMM), or smoldering Waldenström macroglobulinemia (SWM).

METHODS

Individuals with MGUS, SMM, or SWM aged ≥18 years and a BMI of ≥25 kg/m2 are randomized to either a 14-hour nighttime fasting intervention or a healthy lifestyle education control group. Participants' baseline diet and lifestyle patterns are characterized through two 24-hour dietary recalls: questionnaires querying demographic, comorbidity, lifestyle, and quality-of-life information; and wrist actigraphy measurements for 7 days. Fasting intervention participants are supported through one-on-one telephone counseling by a health coach and automated SMS text messaging to support fasting goals. Primary end points of body composition, including visceral and subcutaneous fat (by dual-energy x-ray absorptiometry); bone marrow adiposity (by bone marrow histology); and tumor biomarkers, specifically M-proteins and serum free light-chain concentrations (by gel-based and serum free light-chain assays), are assessed at baseline and after the 4-month study period; changes therein from baseline are evaluated using a repeated measures mixed-effects model that accounts for the correlation between baseline and follow-up measures and is generally robust to missing data. Feasibility is assessed as participant retention (percent dropout in each arm) and percentage of days participants achieved a ≥14-hour fast.

RESULTS

The PROlonged nightly FASTing (PROFAST) study was funded in June 2022. Participant recruitment commenced in April 2023. As of July 2023, six participants consented to the study. The study is expected to be completed by April 2024, and data analysis and results are expected to be published in the first quarter of 2025.

CONCLUSIONS

PROFAST serves as an important first step in exploring the premise that prolonged nightly fasting is a strategy to control obesity and obesity-related mechanisms of myelomagenesis. In evaluating the feasibility and impact of prolonged nightly fasting on body composition, bone marrow adipose tissue, and biomarkers of tumor burden, this pilot study may generate hypotheses regarding metabolic mechanisms underlying MM development and ultimately inform clinical and public health strategies for MM prevention.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05565638; http://clinicaltrials.gov/ct2/show/NCT05565638.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/51368.

Blood-based tests for multicancer early detection (PATHFINDER): a prospective cohort study

BACKGROUND

Multicancer early detection (MCED) blood tests can detect a cancer signal from circulating cell-free DNA (cfDNA). PATHFINDER was a prospective cohort study investigating the feasibility of MCED testing for cancer screening.

METHODS

In this prospective cohort study done in oncology and primary care outpatient clinics at seven US health networks, a convenience sample of adults aged 50 years or older without signs or symptoms of cancer consented to MCED testing. We collected blood, analysed cfDNA, and returned results to participants' doctors. If a methylation signature indicative of cancer was detected, predicted cancer signal origin(s) informed diagnostic assessment. The primary outcome was time to, and extent of, diagnostic testing required to confirm the presence or absence of cancer. This trial is registered at ClinicalTrials.gov, NCT04241796, and is completed.

FINDINGS

Between Dec 12, 2019, and Dec 4, 2020, we recruited 6662 participants. 4204 (63·5%) of 6621 participants with analysable results were women, 2417 (36·5%) were men, and 6071 (91·7%) were White. A cancer signal was detected in 92 (1·4%) of 6621 participants with analysable results. 35 (38%) participants were diagnosed with cancer (true positives) and 57 (62%) had no cancer diagnosis (false positives). Excluding two participants whose diagnostic assessments began before MCED test results were reported, median time to diagnostic resolution was 79 days (IQR 37-219): 57 days (33-143) in true-positive and 162 days (44-248) in false-positive participants. Most participants had both laboratory tests (26 [79%] of 33 with true-positive results and 50 [88%] of 57 with false-positive results) and imaging (30 [91%] of 33 with true-positive results and 53 [93%] of 57 with false-positive results). Fewer procedures were done in participants with false-positive results (17 [30%] of 57) than true-positive results (27 [82%] of 33) and few had surgery (one with a false-positive result and three with a true-positive result).

INTERPRETATION

This study supports the feasibility of MCED screening for cancer and underscores the need for further research investigating the test's clinical utility.

FUNDING

GRAIL.

Targeting the fatty acid binding proteins disrupts multiple myeloma cell cycle progression and MYC signaling

Multiple myeloma is an incurable plasma cell malignancy with only a 53% 5-year survival rate. There is a critical need to find new multiple myeloma vulnerabilities and therapeutic avenues. Herein, we identified and explored a novel multiple myeloma target: the fatty acid binding protein (FABP) family. In our work, myeloma cells were treated with FABP inhibitors (BMS3094013 and SBFI-26) and examined in vivo and in vitro for cell cycle state, proliferation, apoptosis, mitochondrial membrane potential, cellular metabolism (oxygen consumption rates and fatty acid oxidation), and DNA methylation properties. Myeloma cell responses to BMS309403, SBFI-26, or both, were also assessed with RNA sequencing (RNA-Seq) and proteomic analysis, and confirmed with western blotting and qRT-PCR. Myeloma cell dependency on FABPs was assessed using the Cancer Dependency Map (DepMap). Finally, MM patient datasets (CoMMpass and GEO) were mined for FABP expression correlations with clinical outcomes. We found that myeloma cells treated with FABPi or with FABP5 knockout (generated via CRISPR/Cas9 editing) exhibited diminished proliferation, increased apoptosis, and metabolic changes in vitro. FABPi had mixed results in vivo, in two pre-clinical MM mouse models, suggesting optimization of in vivo delivery, dosing, or type of FABP inhibitors will be needed before clinical applicability. FABPi negatively impacted mitochondrial respiration and reduced expression of MYC and other key signaling pathways in MM cells in vitro. Clinical data demonstrated worse overall and progression-free survival in patients with high FABP5 expression in tumor cells. Overall, this study establishes the FABP family as a potentially new target in multiple myeloma. In MM cells, FABPs have a multitude of actions and cellular roles that result in the support of myeloma progression. Further research into the FABP family in MM is warrented, especially into the effective translation of targeting these in vivo.

Personalised progression prediction in patients with monoclonal gammopathy of undetermined significance or smouldering multiple myeloma (PANGEA): a retrospective, multicohort study

BACKGROUND

Patients with precursors to multiple myeloma are dichotomised as having monoclonal gammopathy of undetermined significance or smouldering multiple myeloma on the basis of monoclonal protein concentrations or bone marrow plasma cell percentage. Current risk stratifications use laboratory measurements at diagnosis and do not incorporate time-varying biomarkers. Our goal was to develop a monoclonal gammopathy of undetermined significance and smouldering multiple myeloma stratification algorithm that utilised accessible, time-varying biomarkers to model risk of progression to multiple myeloma.

METHODS

In this retrospective, multicohort study, we included patients who were 18 years or older with monoclonal gammopathy of undetermined significance or smouldering multiple myeloma. We evaluated several modelling approaches for predicting disease progression to multiple myeloma using a training cohort (with patients at Dana-Farber Cancer Institute, Boston, MA, USA; annotated from Nov, 13, 2019, to April, 13, 2022). We created the PANGEA models, which used data on biomarkers (monoclonal protein concentration, free light chain ratio, age, creatinine concentration, and bone marrow plasma cell percentage) and haemoglobin trajectories from medical records to predict progression from precursor disease to multiple myeloma. The models were validated in two independent validation cohorts from National and Kapodistrian University of Athens (Athens, Greece; from Jan 26, 2020, to Feb 7, 2022; validation cohort 1), University College London (London, UK; from June 9, 2020, to April 10, 2022; validation cohort 1), and Registry of Monoclonal Gammopathies (Czech Republic, Czech Republic; Jan 5, 2004, to March 10, 2022; validation cohort 2). We compared the PANGEA models (with bone marrow [BM] data and without bone marrow [no BM] data) to current criteria (International Myeloma Working Group [IMWG] monoclonal gammopathy of undetermined significance and 20/2/20 smouldering multiple myeloma risk criteria).

FINDINGS

We included 6441 patients, 4931 (77%) with monoclonal gammopathy of undetermined significance and 1510 (23%) with smouldering multiple myeloma. 3430 (53%) of 6441 participants were female. The PANGEA model (BM) improved prediction of progression from smouldering multiple myeloma to multiple myeloma compared with the 20/2/20 model, with a C-statistic increase from 0·533 (0·480-0·709) to 0·756 (0·629-0·785) at patient visit 1 to the clinic, 0·613 (0·504-0·704) to 0·720 (0·592-0·775) at visit 2, and 0·637 (0·386-0·841) to 0·756 (0·547-0·830) at visit three in validation cohort 1. The PANGEA model (no BM) improved prediction of smouldering multiple myeloma progression to multiple myeloma compared with the 20/2/20 model with a C-statistic increase from 0·534 (0·501-0·672) to 0·692 (0·614-0·736) at visit 1, 0·573 (0·518-0·647) to 0·693 (0·605-0·734) at visit 2, and 0·560 (0·497-0·645) to 0·692 (0·570-0·708) at visit 3 in validation cohort 1. The PANGEA models improved prediction of monoclonal gammopathy of undetermined significance progression to multiple myeloma compared with the IMWG rolling model at visit 1 in validation cohort 2, with C-statistics increases from 0·640 (0·518-0·718) to 0·729 (0·643-0·941) for the PANGEA model (BM) and 0·670 (0·523-0·729) to 0·879 (0·586-0·938) for the PANGEA model (no BM).

INTERPRETATION

Use of the PANGEA models in clinical practice will allow patients with precursor disease to receive more accurate measures of their risk of progression to multiple myeloma, thus prompting for more appropriate treatment strategies.

FUNDING

SU2C Dream Team and Cancer Research UK.

Abstract 641: Single-cell RNA sequencing of rare circulating tumor cells in precursor myeloma patients reveals molecular underpinnings of tumor cell circulation

Background: Multiple Myeloma (MM) is a hematological malignancy characterized by abnormal proliferation of terminally differentiated plasma cells (PCs) in the bone marrow (BM). MM is almost always preceded by the precursor stage smoldering multiple myeloma (SMM). BM biopsies are useful to monitor disease progression, but they are invasive and not routinely collected from patients for disease monitoring during precursor stages. Profiling circulating tumor cells (CTCs) from peripheral blood (PB) could aid early detection, disease monitoring, and biomarker identification to predict patients at high risk of progression that may benefit from early therapeutic intervention.

Methods: Paired PB and BM aspirates were collected from 40 SMM patients enrolled in the PCROWD study (IRB #14-174) at Dana-Farber Cancer Institute. Malignant PCs were enriched by magnetic bead-based methods and underwent 5’ single-cell RNA sequencing (scRNA-seq) and single-cell B-cell receptor sequencing (scBCR-seq) (10x Genomics).

Results: We analyzed 105,246 BM PCs and 33,234 PB PCs from 15 patients. To differentiate malignant from normal PCs, we used clonal V(D)J rearrangements, assessed by concurrent scBCR-seq. A total of 86,986 BM tumor cells and 8,718 CTCs were captured. A median of 5, 26, and 47 CTCs were present per mL of blood from low, intermediate, and high-risk SMM patients as defined by the International Myeloma Working Group (IMWG) “20/2/20” criteria, suggesting sequencing-based CTC enumeration corresponds to prognosis. High levels of driver genes commonly upregulated in patients with specific translocations, including CCND1 and MAF, were detected in both BM tumor and CTC clusters in 3 patients with t(11;14) and t(14;16) confirmed by fluorescence in situ hybridization (FISH) clinical testing, and 2 additional patients with inconclusive FISH results (Wilcoxon, q &lt;10-3), supporting the idea of CTC-based prognostication. Differential expression (DE) analysis revealed 8 genes that were significantly upregulated and 3 genes that were significantly downregulated in CTCs compared to BM tumor cells robustly across 15 paired samples. Gene set enrichment analysis (GSEA) revealed genes DE in CTCs are associated with TNF-α and NF-κB signaling, which are commonly induced by extrinsic factors in the bone marrow milieu, providing insight into the biology of tumor cell circulation.

Conclusions: This study highlights the utility of scRNA-seq for molecular profiling of CTCs, even in asymptomatic low tumor burden disease. Additional analyses are ongoing in the expanded cohort of 40 patients with paired samples to help gain further insight into CTC heterogeneity. Overall, this study will help enable the design of new molecular liquid biopsy-based approaches to diagnosis, disease monitoring, and biological insights to improve treatment strategies for precursor myeloma patients.

Citation Format: Elizabeth D. Lightbody, Danielle T. Firer, Romanos Sklavenitis-Pistofidis, Michael Agius, Ankit K. Dutta, Michelle Aranha, Jean-Baptiste Alberge, Laura Hevenor, Nang Kham Su, Cody Boehner, Erica Horowitz, Jacqueline Perry, Anna Cowan, Hadley Barr, Anna Justis, Daniel Auclair, Catherine R. Marinac, Gad Getz, Irene Ghobrial. Single-cell RNA sequencing of rare circulating tumor cells in precursor myeloma patients reveals molecular underpinnings of tumor cell circulation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 641.

Abstract 3582: Single-cell RNA-sequencing for immune profiling of SARS-CoV2 vaccine response in healthy individuals and patients with precursor plasma cell malignancies

Introduction: Patients with hematological malignancies exhibit inferior response to SARS-CoV2 vaccination, compared to healthy individuals, however little is known about patients with precursor hematological malignancies and the cellular underpinnings of vaccination response. Monoclonal Gammopathy of Undetermined Significance (MGUS) and Smoldering Myeloma (SMM) are plasma cell premalignancies that precede Multiple Myeloma (MM) and exhibit signs of immune dysregulation; they affect approximately 5% of the population over 50 years of age, who remain largely undiagnosed, due to lack of screening. In November 2019, we launched the IMPACT study to characterize the immune response to SARS-CoV2 vaccination in patients with plasma cell dyscrasias and healthy individuals.

Methods: We performed single-cell RNA-sequencing on 224 peripheral blood mononuclear cell samples drawn from 118 IMPACT (IRB #20-332) participants with MGUS (n=20), SMM (n=48), or MM (n=24), as well as healthy individuals (n=26). Samples were collected before vaccination and after 2 doses of BNT162b2 (Pfizer-BioNtech) (n=123), mRNA-1273 (Moderna) (n=83) or 1 dose of Ad26.COV2.S (Janssen) (n=14).

Results: Overall, we sequenced 2,025,611 cells from 224 samples of 118 patients with MGUS, SMM, MM and healthy individuals pre- and post-vaccination for SARS-CoV2, and profiled 553,082 T-cells, 95,392 B-cells, 74,394 NK cells, 195,371 Monocytes, and 35,236 Dendritic cells (DC). We identified activated clusters of B-cells, NK cells and DCs expressing genes such as CD83, CD69, CXCR4, and genes related to the NF-kB and AP-1 pathways. We compared cell type abundances pre- and post-vaccination within each participant population and found that activated CD83+ cells significantly increased post-vaccination in healthy individuals and patients with MGUS (paired t-test, q &lt; 0.1), but not in patients with SMM or overt MM. At baseline, patients with SMM and MM had significantly fewer memory B-cells and significantly more cytotoxic T-cells and NK cells, compared to healthy individuals (Wilcoxon, q &lt; 0.1), which could partly explain the differences observed post-vaccination. Patients with MM also had significantly higher levels of tolerogenic IL-10-expressing DCs (DC10) at baseline (Wilcoxon, q &lt; 0.1), which could be dampening antigen-specific T-cell responses.

Conclusion: We identified a significant expansion of activated B-cell, NK cell and DC subpopulations expressing CD83, CD69 and CXCR4, following vaccination in healthy individuals and patients with MGUS, but less so in patients with SMM and overt MM. Our results provide insight into the cellular mechanisms of immune response to SARS-CoV2 vaccination in healthy individuals and patients with precursor plasma cell malignancies and suggest that asymptomatic individuals with SMM may exhibit inferior response to vaccination.

Citation Format: Romanos Sklavenitis-Pistofidis, Yoshinobu Konishi, Michelle Aranha, Mahshid Rahmat, Ting Wu, Michael Timonian, Shohreh Varmeh, Daniel Heilpern-Mallory, Michael P. Agius, Nang K. Su, Elizabeth D. Lightbody, Jacqueline Perry, Erica M. Horowitz, Anna V. Justis, Daniel Auclair, Catherine R. Marinac, Eric S. Fischer, Gad Getz, Irene M. Ghobrial. Single-cell RNA-sequencing for immune profiling of SARS-CoV2 vaccine response in healthy individuals and patients with precursor plasma cell malignancies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3582.

Abstract 3651: Obesity, metabolic comorbidities, and lifestyle factors and their association with monoclonal gammopathies in a high-risk screened population: Results of the PROMISE study

Background: Monoclonal gammopathy of undetermined significance (MGUS) is a premalignant condition of multiple myeloma (MM) traditionally identified by serum protein electrophoresis (SPEP) and immunofixation (IFX). Recently, novel, ultra-sensitive mass spectrometry (MS)-based approaches have allowed for monoclonal (M)-protein detection at concentrations below SPEP levels.

MGUS has only few known risk factors implicated in its development and progression. Thus, we analyze MS results of the PROMISE nationwide U.S. screening study to evaluate risk factors for (1) MGUS at traditional SPEP/IFX levels of detection and (2) low-level monoclonal gammopathies, which bear uncertain etiology and clinical significance.

Methods: PROMISE enrolled individuals age ≥40 who are Black and/or have a first-degree relative with a blood cancer or MM precursor condition. Those with ≥2 first-degree relatives were eligible at age ≥18. Participants were screened for monoclonal gammopathy by MALDI-TOF MS and provided a survey querying metabolic comorbidities and lifestyle. M-protein concentrations ≥0.02 g/dL were considered traditionally-defined MGUS, whereas M-proteins &lt;0.02 g/dL are hereafter referred to as monoclonal gammopathy of indeterminate potential (MGIP). Multivariable logistic regression models estimated odds ratios (OR) and 95% confidence intervals (CI) for exposure and MGUS/MGIP associations.

Results: 1,893 screened participants completed the survey. MGUS and MGIP were detected in 13.4% and 22.0% of Blacks and 8.6% and 26.7% of individuals with family history. Adjusting for sex, age at screening, income, and education, obesity or BMI of ≥30 was associated with MGUS (OR, 1.55; 95% CI, 1.08-2.21), compared to BMI &lt;30. Clinician-diagnosed hypertension (yes/no) and diabetes mellitus (yes/no) were associated with MGUS with ORs 1.44 (95% CI, 1.01-2.04) and 1.88 (95% CI, 1.004-3.51). There were no significant associations between MGUS and high cholesterol, high triglycerides, heart disease, myocardial infarction, or stroke. Short sleep of ≤6 hours/day was associated with MGUS (OR, 1.43; 95% CI, 1.01-2.03), compared to &gt;6 hours/day. Physical activity (metabolic equivalents/week), smoking status (current, past, never), alcohol consumption (g/day) had no associations with MGUS. No risk factor associations were found for MGIP.

Conclusion: In screening a high-risk population by mass spectrometry, we found associations of both traditionally established (obesity) and novel risk factors (diabetes, hypertension, short sleep) with MGUS. None of these exposures were associated with MGIP despite finding a high prevalence of MGIP in Blacks and individuals with family history, suggesting that these risk factors may not be etiologically involved in MGIP development but possibly its clonal expansion to more advanced stages.

Citation Format: David J. Lee, Habib El-Khoury, Jean-Baptiste Alberge, D.J. Sakrikar, David Barnidge, Mark C. Perkins, Stephen Harding, Jacqueline Perry, Maya I. Davis, Julia Amstutz, Erica Horowitz, Timothy R. Rebbeck, Irene M. Ghobrial, Catherine R. Marinac. Obesity, metabolic comorbidities, and lifestyle factors and their association with monoclonal gammopathies in a high-risk screened population: Results of the PROMISE study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3651.

Abstract 5277: Humoral SARS-CoV-2 response in asymptomatic precursor plasma cell dyscrasia patients: IMPACT study results

Introduction: Patients with hematologic malignancies, including multiple myeloma (MM), experience worse SARS-CoV-2 infection outcomes and sub-optimal vaccine responses. Monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM) precede MM and affect ~5% of individuals age &gt;=50. We previously showed that individuals with MGUS and SMM exhibit immune dysregulation. Here, we investigate the immune response to SARS-CoV-2 vaccination in these asymptomatic but potentially immunocompromised individuals.

Methods: The IMPACT study (IRB #20-332) is a prospective study at Dana-Farber Cancer Institute in collaboration with MMRF, which enrolled individuals nationwide with a diagnosed plasma cell dyscrasia and healthy individuals. As of October 2021, 3,005 individuals completed a questionnaire regarding prior infection or vaccination. We obtained 1,350 blood samples from 628 participants and analyzed anti-SARS-CoV-2 IgG antibody titer by ELISA.

Results: 2,771 (92%) participants were fully vaccinated (2 doses BNT162b2 or mRNA-1273; 1 dose Ad26.COV2.s), 269 (9%) had received a 3rd mRNA vaccine dose, and 234 (8%) were unvaccinated. 1,387 (46%) and 1,093 (36%) participants received mRNA vaccines (BNT162b2 and mRNA-1273), and 139 (5%) participants received an adenovirus vector vaccine (Ad26.COV2.S). 34 (1%) individuals reported SARS-CoV-2 infection after full vaccination.

We measured antibody titers in 201 MGUS, 223 SMM, 40 smoldering Waldenstrom macroglobulinemia (SWM), 64 MM, and 100 healthy controls. Multiple linear regression model estimated the association between various clinical variables and post-vaccination antibody titers. As previously reported, having MM was associated with low antibody titer (p &lt; 0.001). Of note, having SMM, regardless of risk stratification by 2/20/20 criteria, was also associated with low antibody titers, indicating that even low-risk SMM patients have a poor response to vaccination. MGUS and SWM diagnoses were not significantly associated with antibody titers. Additionally, male sex (p &lt; 0.010), elapsed time after vaccination (p &lt; 0.001), and BNT162b2 vaccine (p &lt; 0.001) were associated with low antibody titers. SARS-CoV-2 infection prior to vaccination was associated with high antibody titers.

We identified 25 patients (6 MGUS, 10 SMM, 2 SWM, 7 MM) who submitted blood samples after both the 2nd and 3rd dose. In these patients we observed a significant increase in antibody titer after a 3rd dose (p = 0.002). We also observed that antibody titers of patients after a 3rd dose (13 MGUS, 12 SMM, 2 SWM, 31 MM) were comparable to that of healthy individuals after a 2nd dose (p = 0.833).

Conclusion: Our data indicates that suboptimal response to SARS-CoV-2 does not only occur with MM and cancer patients receiving therapy but also in precursor asymptomatic patients including low-risk SMM.

Citation Format: Yoshinobu Konishi, Romanos Sklavenitis-Pistofidis, Hong Yue, Federico Ferrari, Massimiliano Russo, Robert A. Redd, Jacqueline Perry, Erica Horowitz, Anna V. Justis, Nader A. Shayegh, Elizabeth D. Lightbody, Shohreh Varmeh, Radoslaw P. Nowak, Mark Hamilton, Daniel Auclair, Catherine R. Marinac, Lorenzo Trippa, Eric S. Fischer, Irene M. Ghobrial. Humoral SARS-CoV-2 response in asymptomatic precursor plasma cell dyscrasia patients: IMPACT study results [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5277.

Prevalence of monoclonal gammopathies and clinical outcomes in a high-risk US population screened by mass spectrometry: a multicentre cohort study

BACKGROUND

Prevalence estimates for monoclonal gammopathy of undetermined significance (MGUS) are based on predominantly White study populations screened by serum protein electrophoresis supplemented with immunofixation electrophoresis. A prevalence of 3% is reported for MGUS in the general population of European ancestry aged 50 years or older. MGUS prevalence is two times higher in individuals of African descent or with a family history of conditions related to multiple myeloma. We aimed to evaluate the prevalence and clinical implications of monoclonal gammopathies in a high-risk US population screened by quantitative mass spectrometry.

METHODS

We used quantitative matrix-assisted laser desorption ionisation-time of flight (MALDI-TOF) mass spectrometry and EXENT-iQ software to screen for and quantify monoclonal gammopathies in serum from 7622 individuals who consented to the PROMISE screening study between Feb 26, 2019, and Nov 4, 2021, and the Mass General Brigham Biobank (MGBB) between July 28, 2010, and July 1, 2021. M-protein concentrations at the monoclonal gammopathy of indeterminate potential (MGIP) level were confirmed by liquid chromatography mass spectrometry testing. 6305 (83%; 2211 from PROMISE, 4094 from MGBB) of 7622 participants in the cohorts were at high risk for developing a monoclonal gammopathy on the basis of Black race or a family history of haematological malignancies and fell within the eligible high-risk age range (30 years or older for PROMISE cohort and 18 years or older for MGBB cohort); those over 18 years were also eligible if they had two or more family members with a blood cancer (PROMISE cohort). Participants with a plasma cell malignancy diagnosed before screening were excluded. Longitudinal clinical data were available for MGBB participants with a median follow-up time from serum sample screening of 4·5 years (IQR 2·4-6·7). The PROMISE study is registered with ClinicalTrials.gov, NCT03689595.

FINDINGS

The median age at time of screening was 56·0 years (IQR 46·8-64·1). 5013 (66%) of 7622 participants were female, 2570 (34%) male, and 39 (<1%) unknown. 2439 (32%) self-identified as Black, 4986 (65%) as White, 119 (2%) as other, and 78 (1%) unknown. Using serum protein electrophoresis with immunofixation electrophoresis, the MGUS prevalence was 6% (101 of 1714) in high-risk individuals aged 50 years or older. Using mass spectrometry, we observed a total prevalence of monoclonal gammopathies of 43% (1788 of 4207) in this group. We termed monoclonal gammopathies below the clinical immunofixation electrophoresis detection level (<0·2 g/L) MGIPs, to differentiate them from those with higher concentrations, termed mass-spectrometry MGUS, which had a 13% (592 of 4207) prevalence by mass spectrometry in high-risk individuals aged 50 years or older. MGIP was predominantly of immunoglobulin M isotype, and its prevalence increased with age (19% [488 of 2564] for individuals aged <50 years, 29% [1464 of 5058] for those aged ≥50 years, and 37% [347 of 946] for those aged ≥70 years). Mass-spectrometry MGUS prevalence increased with age (5% [127 of 2564] for individuals aged <50 years, 13% [678 of 5058] for those aged ≥50 years, and 18% [173 of 946] for those aged ≥70 years) and was higher in men (314 [12%] of 2570) compared with women (485 [10%] 5013; p=0·0002), whereas MGIP prevalence did not differ significantly by gender. In those aged 50 years or older, the prevalence of mass spectrometry was significantly higher in Black participants (224 [17%] of 1356) compared with the controls (p=0·0012) but not in those with family history (368 [13%] of 2851) compared with the controls (p=0·1008). Screen-detected monoclonal gammopathies correlated with increased all-cause mortality in MGBB participants (hazard ratio 1·55, 95% CI 1·16-2·08; p=0·0035). All monoclonal gammopathies were associated with an increased likelihood of comorbidities, including myocardial infarction (odds ratio 1·60, 95% CI 1·26-2·02; p=0·00016 for MGIP-high and 1·39, 1·07-1·80; p=0·015 for mass-spectrometry MGUS).

INTERPRETATION

We detected a high prevalence of monoclonal gammopathies, including age-associated MGIP, and made more precise estimates of mass-spectrometry MGUS compared with conventional gel-based methods. The use of mass spectrometry also highlighted the potential hidden clinical significance of MGIP. Our study suggests the association of monoclonal gammopathies with a variety of clinical phenotypes and decreased overall survival.

FUNDING

Stand Up To Cancer Dream Team, the Multiple Myeloma Research Foundation, and National Institutes of Health.

A comprehensive review of the impact of obesity on plasma cell disorders

Multiple myeloma (MM) remains an incurable plasma cell malignancy. Although little is known about the etiology of MM, several metabolic risk factors such as obesity, diabetes, poor nutrition, many of which are modifiable, have been linked to the pathogenesis of numerous neoplasms including MM. In this article, we provide a detailed summary of what is known about the impact of obesity on the pathogenesis of MM, its influence on outcomes in MM patients, and discuss potential mechanisms through which obesity is postulated to influence MM risk and prognosis. Along with advancements in treatment modalities to improve survival in MM patients, focused efforts are needed to prevent or intercept MM at its earliest stages. The consolidated findings presented in this review highlight the need for clinical trials to assess if lifestyle modifications can reduce the incidence and improve outcomes of MM in high-risk populations. Data generated from such studies can help formulate evidence-based lifestyle recommendations for the prevention and control of MM.

Regular Aspirin Use and Mortality in Multiple Myeloma Patients

BACKGROUND

Inflammation is important in multiple myeloma (MM) pathogenesis, and regular aspirin use has been shown to confer a reduced risk of MM. The influence of aspirin on survival after MM diagnosis is unknown.

METHODS

We identified 436 men and women diagnosed with MM between 1980 and 2016 in the Health Professionals Follow-up Study (HPFS) and the Nurses' Health Study (NHS) who reported aspirin intake biennially on follow-up questionnaires. Using multivariable Cox proportional hazards regression models, we estimated hazard ratios (HR) and 95% confidence intervals (CI) associated with aspirin use on MM-specific and overall mortality.

RESULTS

Compared with nonusers, participants who used aspirin after diagnosis had a multivariable HR for MM-specific mortality of 0·61 (95% confidence interval [CI], 0·46, 0·79) and for overall mortality of 0·63 (95% CI, 0·49, 0·80), after adjustment for age at diagnosis, year of diagnosis, sex, body mass index, pre-diagnosis aspirin use, and number of comorbidities. For post-diagnosis aspirin quantity, we observed a modest trend of reduction in MM-specific and all-cause mortality with increasing number of 325 mg tablets of aspirin per week, although the confidence intervals for 1 to <6 and {greater than or equal to}6 tablets overlapped. Results were not materially different before or after the availability of novel therapies (before vs. after the year 2000). Pre-diagnosis frequency or duration of aspirin use was not significantly associated with MM-specific or overall mortality.

CONCLUSIONS

Findings support the use of aspirin as a complementary strategy to enhance MM survival.

IMPACT

Confirmation in samples that have comprehensive clinical information is encouraged.

The PATHFINDER Study: Assessment of the Implementation of an Investigational Multi-Cancer Early Detection Test into Clinical Practice

To examine the extent of the evaluation required to achieve diagnostic resolution and the test performance characteristics of a targeted methylation cell-free DNA (cfDNA)-based multi-cancer early detection (MCED) test, ~6200 participants ≥50 years with (cohort A) or without (cohort B) ≥1 of 3 additional specific cancer risk factors will be enrolled in PATHFINDER (NCT04241796), a prospective, longitudinal, interventional, multi-center study. Plasma cfDNA from blood samples will be analyzed to detect abnormally methylated DNA associated with cancer (i.e., cancer "signal") and a cancer signal origin (i.e., tissue of origin). Participants with a "signal detected" will undergo further diagnostic evaluation per guiding physician discretion; those with a "signal not detected" will be advised to continue guideline-recommended screening. The primary objective will be to assess the number and types of subsequent diagnostic tests needed for diagnostic resolution. Based on microsimulations (using estimates of cancer incidence and dwell times) of the typical risk profiles of anticipated participants, the median (95% CI) number of participants with a "signal detected" result is expected to be 106 (87-128). Subsequent diagnostic evaluation is expected to detect 52 (39-67) cancers. The positive predictive value of the MCED test is expected to be 49% (39-58%). PATHFINDER will evaluate the integration of a cfDNA-based MCED test into existing clinical cancer diagnostic pathways. The study design of PATHFINDER is described here.

The COronavirus Pandemic Epidemiology (COPE) Consortium: A Call to Action

The rapid pace of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; COVID-19) pandemic presents challenges to the real-time collection of population-scale data to inform near-term public health needs as well as future investigations. We established the COronavirus Pandemic Epidemiology (COPE) consortium to address this unprecedented crisis on behalf of the epidemiology research community. As a central component of this initiative, we have developed a COVID Symptom Study (previously known as the COVID Symptom Tracker) mobile application as a common data collection tool for epidemiologic cohort studies with active study participants. This mobile application collects information on risk factors, daily symptoms, and outcomes through a user-friendly interface that minimizes participant burden. Combined with our efforts within the general population, data collected from nearly 3 million participants in the United States and United Kingdom are being used to address critical needs in the emergency response, including identifying potential hot spots of disease and clinically actionable risk factors. The linkage of symptom data collected in the app with information and biospecimens already collected in epidemiology cohorts will position us to address key questions related to diet, lifestyle, environmental, and socioeconomic factors on susceptibility to COVID-19, clinical outcomes related to infection, and long-term physical, mental health, and financial sequalae. We call upon additional epidemiology cohorts to join this collective effort to strengthen our impact on the current health crisis and generate a new model for a collaborative and nimble research infrastructure that will lead to more rapid translation of our work for the betterment of public health.

Prediagnosis dietary pattern and survival in patients with multiple myeloma

Inflammation and endogenous growth factors are important in multiple myeloma (MM) pathogenesis. Although diets that modulate these biologic pathways may influence MM patient survival, studies have not examined the association of dietary patterns with MM survival. We conducted pooled prospective survival analyses of 423 MM patients from the Nurses' Health Study (1986-2016) and the Health Professionals Follow-up Study (1988-2016) using Cox regression models. We used data from repeated food frequency questionnaires (FFQ) to compute dietary patterns as of the last prediagnosis FFQ, including the Alternate Healthy Eating Index (AHEI)-2010, alternate Mediterranean Diet, Dietary Approaches to Stop Hypertension, Prudent, Western and empirical dietary inflammatory patterns and empirical dietary indices for insulin resistance and hyperinsulinemia. During follow-up, we documented 295 MM-related deaths among 345 total deaths. MM-specific mortality was 15-24% lower per one standard deviation (SD) increase (e.g., toward healthier habits) in favorable dietary pattern scores. For example, the multivariable-adjusted hazard ratio [HR] and 95% confidence interval [CI] per 1-SD increase in AHEI-2010 score were 0.76, 0.67-0.87 (p < 0.001). In contrast, MM-specific mortality was 16-24% higher per 1-SD increase (e.g., toward less healthy habits) in "unhealthy" diet scores; for example, the multivariable-adjusted HR, 95% CI per 1-SD increase in Western pattern score were 1.24, 1.07-1.44 (p = 0.005). Associations were similar for all-cause mortality. In conclusion, our consistent findings for multiple dietary patterns provide the first evidence that MM patients with healthier prediagnosis dietary habits may have longer survival than those with less healthy diets.

Dissecting racial disparities in multiple myeloma

Multiple myeloma (MM) is a fatal plasma cell dyscrasia with a median overall survival of 5 to 10 years. MM progresses from the more common but often subclinical precursor states of monoclonal gammopathy of undetermined significance (MGUS), and smoldering multiple myeloma (SMM) to overt MM. There are large racial disparities in all stages of the disease. Compared with Whites, Blacks have an increased MGUS and MM risk and higher mortality rate, and have not experienced the same survival gains over time. The roots of this disparity are likely multifactorial in nature. Comparisons of Black and White MGUS and MM patients suggest that differences in risk factors, biology, and clinical characteristics exist by race or ancestry, which may explain some of the observed disparity in MM. However, poor accrual of Black MGUS and MM patients in clinical and epidemiological studies has limited our understanding of this disparity and hindered its elimination. Disparities in MM survival also exist but appear to stem from inferior treatment utilization and access rather than underlying pathogenesis. Innovative and multidisciplinary approaches are urgently needed to enhance our understanding of disparities that exist at each stage of the MM disease continuum and facilitate their elimination.

Research-based PAM50 signature and long-term breast cancer survival

Purpose

Multi-gene signatures provide biological insight and risk stratification in breast cancer. Intrinsic molecular subtypes defined by mRNA expression of 50 genes (PAM50) are prognostic in hormone-receptor positive postmenopausal breast cancer. Yet, for 25–40% in the PAM50 intermediate risk group, long-term risk remains uncertain. Our study aimed to (i) test the long-term prognostic value of the PAM50 signature in pre- and post-menopausal breast cancer; (ii) investigate if the PAM50 model could be improved by addition of other mRNAs implicated in oncogenesis.

Methods

We used archived FFPE samples from 1723 breast cancer survivors; high quality reads were obtained on 1253 samples. Transcript expression was quantified using a custom codeset with probes for > 100 targets. Cox models assessed gene signatures for breast cancer relapse and survival.

Results

Over 15 + years of follow-up, PAM50 subtypes were (P < 0.01) associated with breast cancer outcomes after accounting for tumor stage, grade and age at diagnosis. Results did not differ by menopausal status at diagnosis. Women with Luminal B (versus Luminal A) subtype had a > 60% higher hazard. Addition of a 13-gene hypoxia signature improved prognostication with > 40% higher hazard in the highest vs lowest hypoxia tertiles.

Conclusions

PAM50 intrinsic subtypes were independently prognostic for long-term breast cancer survival, irrespective of menopausal status. Addition of hypoxia signatures improved risk prediction. If replicated, incorporating the 13-gene hypoxia signature into the existing PAM50 risk assessment tool, may refine risk stratification and further clarify treatment for breast cancer.

Electronic supplementary material

The online version of this article (10.1007/s10549-019-05446-y) contains supplementary material, which is available to authorized users.

The effects of weight loss and metformin on cognition among breast cancer survivors: Evidence from the Reach for Health study

OBJECTIVE

Breast cancer survivors experience problems with cognition that interfere with daily life and can last for years. In the general population, obesity and diabetes are risk factors for cognitive decline, and weight loss can improve cognition; however, the impact of intentional weight loss on cancer survivors' cognition has not been tested. We investigated the impact of weight loss and metformin on changes in cognitive function in a sample of breast cancer survivors.

METHODS

Overweight/obese postmenopausal breast cancer survivors (n = 333) were randomized to a weight loss intervention versus control and metformin versus placebo in a 2 × 2 factorial design. Outcomes were changes in five cognitive domains from baseline to 6 months measured by objective neurocognitive tests.

RESULTS

There were no statistically significant intervention effects for the metformin or weight loss interventions in five neurocognitive domains. Baseline body mass index (BMI) was a significant effect modifier of the changes in verbal functioning for the weight loss (P = 0.009) and metformin interventions (P = 0.0125). These effect modifications were independent of percent weight loss achieved during the 6-month study period.

CONCLUSIONS

This randomized controlled trial of weight loss and metformin interventions that examined changes to cognition among breast cancer survivors suggests that these interventions may not improve cognitive functioning among breast cancer survivors in general. However, weight loss may improve verbal functioning among individuals with a higher BMI.

Elucidating Under-Studied Aspects of the Link Between Obesity and Multiple Myeloma: Weight Pattern, Body Shape Trajectory, and Body Fat Distribution

Background

Although obesity is an established modifiable risk factor for multiple myeloma (MM), several nuanced aspects of its relation to MM remain unelucidated, limiting public health and prevention messages.

Methods

We analyzed prospective data from the Nurses' Health Study and Health Professionals Follow-Up Study to examine MM risk associated with 20-year weight patterns in adulthood, body shape trajectory from ages 5 to 60 years, and body fat distribution. For each aforementioned risk factor, we report hazard ratios (HRs) and 95% confidence intervals (CIs) for incident MM from multivariable Cox proportional-hazards models.

Results

We documented 582 incident MM cases during 4 280 712 person-years of follow-up. Persons who exhibited extreme weight cycling, for example, those with net weight gain and one or more episodes of intentional loss of at least 20 pounds or whose cumulative intentional weight loss exceeded net weight loss with at least one episode of intentional loss of 20 pounds or more had an increased MM risk compared with individuals who maintained their weight (HR = 1.71, 95% CI = 1.05 to 2.80); the association was statistically nonsignificant after adjustment for body mass index. We identified four body shape trajectories: lean-stable, lean-increase, medium-stable, and medium-increase. MM risk was higher in the medium-increase group than in the lean-stable group (HR = 1.62, 95% CI = 1.22 to 2.14). Additionally, MM risk increased with increasing hip circumference (HR per 1-inch increase: 1.03, 95% CI = 1.01 to 1.06) but was not associated with other body fat distribution measures.

Conclusions

Maintaining a lean and stable weight throughout life may provide the strongest benefit in terms of MM prevention.

miRNAs and Long-term Breast Cancer Survival: Evidence from the WHEL Study

BACKGROUND

There is substantial variation in breast cancer survival rates, even among patients with similar clinical and genomic profiles. New biomarkers are needed to improve risk stratification and inform treatment options. Our aim was to identify novel miRNAs associated with breast cancer survival and quantify their prognostic value after adjusting for established clinical factors and genomic markers.

METHODS

Using the Women's Healthy Eating and Living (WHEL) breast cancer cohort with >15 years of follow-up and archived tumor specimens, we assayed PAM50 mRNAs and 25 miRNAs using the Nanostring nCounter platform.

RESULTS

We obtained high-quality reads on 1,253 samples (75% of available specimens) and used an existing research-use algorithm to ascertain PAM50 subtypes and risk scores (ROR-PT). We identified miRNAs significantly associated with breast cancer outcomes and then tested these in independent TCGA samples. miRNAs that were also prognostic in TCGA samples were further evaluated in multiple regression Cox models. We also used penalized regression for unbiased discovery.

CONCLUSIONS

Two miRNAs, 210 and 29c, were associated with breast cancer outcomes in the WHEL and TCGA studies and further improved risk stratification within PAM50 risk groups: 10-year survival was 62% in the node-negative high miR-210-high ROR-PT group versus 75% in the low miR-210- high ROR-PT group. Similar results were obtained for miR-29c. We identified three additional miRNAs, 187-3p, 143-3p, and 205-5p, via penalized regression.

IMPACT

Our findings suggest that miRNAs might be prognostic for long-term breast cancer survival and might improve risk stratification. Further research to incorporate miRNAs into existing clinicogenomic signatures is needed.

Physical Activity Change in an RCT: Comparison of Measurement Methods

Objectives: We aimed to quantify the agreement between self-report, standard cut-point accelerometer, and machine learning accelerometer estimates of physical activity (PA), and exam- ine how agreement changes over time among older adults in an intervention setting. Methods: Data were from a randomized weight loss trial that encouraged increased PA among 333 postmenopausal breast cancer survivors. PA was estimated using accelerometry and a validated questionnaire at baseline and 6-months. Accelerometer data were processed using standard cut-points and a validated machine learning algorithm. Agreement of PA at each time-point and change was assessed using mixed effects regression models and concordance correlation. Results: At baseline, self-report and machine learning provided similar PA estimates (mean dif- ference = 11.5 min/day) unlike self-report and standard cut-points (mean difference = 36.3 min/ day). Cut-point and machine learning methods assessed PA change over time more similarly than other comparisons. Specifically, the mean difference of PA change for the cut-point versus machine learning methods was 5.1 min/day for intervention group and 2.9 in controls, whereas it was ≥ 24.7 min/day for other comparisons. Conclusions: Intervention researchers are facing the issue of self-report measures introducing bias and accelerometer cut-points being insensi- tive. Machine learning approaches may bridge this gap.

Progression Risk Stratification of Asymptomatic Waldenström Macroglobulinemia

BACKGROUND

Waldenström macroglobulinemia (WM) is preceded by asymptomatic WM (AWM), for which the risk of progression to overt disease is not well defined.

METHODS

We studied 439 patients with AWM, who were diagnosed and observed at Dana-Farber Cancer Institute between 1992 and 2014.

RESULTS

During the 23-year study period, with a median follow-up of 7.8 years, 317 patients progressed to symptomatic WM (72%). Immunoglobulin M 4,500 mg/dL or greater, bone marrow lymphoplasmacytic infiltration 70% or greater, β2-microglobulin 4.0 mg/dL or greater, and albumin 3.5 g/dL or less were all identified as independent predictors of disease progression. To assess progression risk in patients with AWM, we trained and cross-validated a proportional hazards model using bone marrow infiltration, immunoglobulin M, albumin, and beta-2 microglobulin values as continuous measures. The model divided the cohort into three distinct risk groups: a high-risk group with a median time to progression (TTP) of 1.8 years, an intermediate-risk group with a median TTP of 4.8 years, and a low-risk group with a median TTP of 9.3 years. We validated this model in two external cohorts, demonstrating robustness and generalizability. For clinical applicability, we made the model available as a Web page application ( www.awmrisk.com ). By combining two cohorts, we were powered to identify wild type MYD88 as an independent predictor of progression (hazard ratio, 2.7).

CONCLUSION

This classification system is positioned to inform patient monitoring and care and, for the first time to our knowledge, to identify patients with high-risk AWM who may need closer follow-up or benefit from early intervention.

Actigraphy-Derived Daily Rest-Activity Patterns and Body Mass Index in Community-Dwelling Adults

Study Objectives

To examine associations between 24-hour rest-activity patterns and body mass index (BMI) among community-dwelling US adults. Rest-activity patterns provide a field method to study exposures related to circadian rhythms.

Methods

Adults (N = 578) wore an actigraph on their nondominant wrist for 7 days. Intradaily variability and interdaily stability (IS), M10 (most active 10-hours), L5 (least active 5-hours), and relative amplitude (RA) were derived using nonparametric rhythm analysis. Mesor, acrophase, and amplitude were calculated from log-transformed count data using the parametric cosinor approach.

Results

Participants were 80% female and mean (standard deviation) age was 52 (15) years. Participants with higher BMI had lower values for magnitude, RA, IS, total sleep time (TST), and sleep efficiency. In multivariable analyses, less robust 24-hour rest-activity patterns as represented by lower RA were consistently associated with higher BMI: comparing the bottom quintile (least robust) to the top quintile (most robust 24-hour rest-activity pattern) of RA, BMI was 3-kg/m2 higher (p = .02). Associations were similar in magnitude to an hour less of TST (1-kg/m2 higher BMI) or a 10% decrease in sleep efficiency (2-kg/m2 higher BMI), and independent of age, sex, race, education, and the duration of rest and/or activity.

Conclusions

Lower RA, reflecting both higher night activity and lower daytime activity, was associated with higher BMI. Independent of the duration of rest or activity during the day or night, 24-hour rest, and activity patterns from actigraphy provide aggregated measures of activity that associate with BMI in community-dwelling adults.

The Effects of Metformin and Weight Loss on Biomarkers Associated With Breast Cancer Outcomes

Background

This study investigated the effects of metformin and weight loss on biomarkers associated with breast cancer prognosis.

Methods

Overweight/obese postmenopausal breast cancer survivors (n = 333) were randomly assigned to metformin vs placebo and to a weight loss intervention vs control (ie, usual care). The 2 × 2 factorial design allows a single randomized trial to investigate the effect of two factors and interactions between them. Outcomes were changes in fasting insulin, glucose, C-reactive protein (CRP), estradiol, testosterone, and sex-hormone binding globulin (SHBG). The trial was powered for a main effects analysis of metformin vs placebo and weight loss vs control. All tests of statistical significance were two-sided.

Results

A total of 313 women (94.0%) completed the six-month trial. High prescription adherence (ie, ≥80% of pills taken) ranged from 65.9% of participants in the metformin group to 81.3% of those in the placebo group (P < .002). Mean percent weight loss was statistically significantly higher in the weight loss group (-5.5%, 95% confidence interval [CI] = -6.3% to -4.8%) compared with the control group (-2.7%, 95% CI = -3.5% to -1.9%). Statistically significant group differences (ie, percent change in metformin group minus placebo group) were -7.9% (95% CI = -15.0% to -0.8%) for insulin, -10.0% (95% CI = -18.5% to -1.5%) for estradiol, -9.5% (95% CI = -15.2% to -3.8%) for testosterone, and 7.5% (95% CI = 2.4% to 12.6%) for SHBG. Statistically significant group differences (ie, percent change in weight loss group minus placebo group) were -12.5% (95% CI = -19.6% to -5.3%) for insulin and 5.3% (95% CI = 0.2% to 10.4%) for SHBG.

Conclusions

As adjuvant therapy, weight loss and metformin were found to be a safe combination strategy that modestly lowered estrogen levels and advantageously affected other biomarkers thought to be on the pathway for reducing breast cancer recurrence and mortality.

Zeitgebers and their association with rest-activity patterns

Zeitgebers such as light, eating and physical activity provide input to the circadian clock. Chronic circadian misalignment is associated with significant adverse health effects. An improved understanding of the impact of the timing of zeitgebers on the stability of 24-hour rest-activity rhythm in free-living settings may identify behavioural and environmental intervention targets. A total of 133 healthy adults, aged 21-60 years, wore a wrist actigraph for 7 consecutive days. We applied a non-parametric analysis to activity counts to derive rest-activity patterns. We administered a questionnaire through a smartphone app to collect self-reported timing of light exposure, eating episodes and physical activity. To assess the relationship between timing exposures (first and last exposure to outdoor light, first exposure to indoor light, last eating episode, first eating episode, morning physical activity proportion, evening physical activity proportion) and rest-activity or sleep outcomes (bedtimes, total sleep time, inter-daily stability, intra-daily variability, L5 and M10 midpoint), we first calculated Spearman correlations, using the false discovery rate method to control for multiple comparisons. From those significant associations, we then fit regression models adjusting for age, sex, race, household income, education level, study site, body mass index, as well as physical activity. Finally, we tested for interaction between chronotype and each timing-related exposure and stratified the analysis by morning type. All zeitgebers, except for evening physical activity proportion, were correlated with at least four of the seven sleep and rest-activity outcomes. In adjusted analysis, later timing of first (after 6:30 to 7:45 AM versus earlier) and last exposure to indoor light (after 11:00 PM versus earlier) and first (after 7:45-9:45 AM versus earlier) and last eating episode (after 8:00-09:00 PM versus earlier) were associated with a shift of 0.60-1.39 hours to later bedtimes, M10 and L5 midpoints (i.e. timing of peak activities or inactivities). Later timing of first exposure to outdoor light (after 09:30 AM versus earlier) was also associated with 0.51 (95% CI: 0.19 to 0.83) hours longer total sleep time. Higher morning physical activity proportion (> 33%) was associated with 0.95 (95% CI: -1.38 to -0.53) hours earlier in-bed time and 0.69 (95% CI: -1.14 to -0.24) hours earlier out-of-bed time, 0.92 (95% CI: -1.41 to -0.42) hours earlier M10 and 0.96 (95% CI: -1.42 to -0.49) min earlier L5 midpoint. The results did not change substantially with further adjustment for total activity. There was a significant interaction between morning chronotype and first eating episode with rest-activity patterns (p < 0.05), with first eating episode associating with timing of activities only in non-morning type adults. Timing of zeitgebers was associated with sleep and rest-activity patterns, including bedtimes, L5 and M10 midpoint. Future research should evaluate the impact of manipulating zeitgebers on both circadian rhythms and health outcomes.

Dimensions of sedentary behavior and objective cognitive functioning in breast cancer survivors

PURPOSE

To examine associations between dimensions of sedentary behavior and cognitive function in breast cancer survivors.

METHODS

Sedentary behavior variables were measured using thigh-worn activPALs, and included total daily sitting time, time in long sitting bouts, sit-to-stand transitions, and standing time. Cognitive function was assessed using the NIH Toolbox Cognitive Domain. Separate multivariable linear regression models were used to examine associations between sedentary behavior variables with the cognitive domain scores of attention, executive functioning, episodic memory, working memory, and information processing speed.

RESULTS

Thirty breast cancer survivors with a mean age of 62.2 (SD = 7.8) years who were 2.6 (SD = 1.1) years since diagnosis completed study assessments. In multivariable linear regression models, more time spent standing was associated with faster information processing (b: 5.78; p = 0.03), and more time spent in long sitting bouts was associated with worse executive function (b: -2.82; p = 0.02), after adjustment for covariates. No other sedentary behavior variables were statistically significantly associated with the cognitive domains examined in this study.

CONCLUSIONS

Two important sedentary constructs that are amenable to intervention, including time in prolonged sitting bouts and standing time, may be associated with cognitive function in breast cancer survivors. More research is needed to determine whether modifying these dimensions of sedentary behavior will improve cognitive function in women with a history of breast cancer, or prevent it from declining in breast cancer patients.

Comparison of Accelerometry Methods for Estimating Physical Activity

PURPOSE

This study aimed to compare physical activity estimates across different accelerometer wear locations, wear time protocols, and data processing techniques.

METHODS

A convenience sample of middle-age to older women wore a GT3X+ accelerometer at the wrist and hip for 7 d. Physical activity estimates were calculated using three data processing techniques: single-axis cut points, raw vector magnitude thresholds, and machine learning algorithms applied to the raw data from the three axes. Daily estimates were compared for the 321 women using generalized estimating equations.

RESULTS

A total of 1420 d were analyzed. Compliance rates for the hip versus wrist location only varied by 2.7%. All differences between techniques, wear locations, and wear time protocols were statistically different (P < 0.05). Mean minutes per day in physical activity varied from 22 to 67 depending on location and method. On the hip, the 1952-count cut point found at least 150 min·wk of physical activity in 22% of participants, raw vector magnitude found 32%, and the machine-learned algorithm found 74% of participants with 150 min of walking/running per week. The wrist algorithms found 59% and 60% of participants with 150 min of physical activity per week using the raw vector magnitude and machine-learned techniques, respectively. When the wrist device was worn overnight, up to 4% more participants met guidelines.

CONCLUSION

Estimates varied by 52% across techniques and by as much as 41% across wear locations. Findings suggest that researchers should be cautious when comparing physical activity estimates from different studies. Efforts to standardize accelerometry-based estimates of physical activity are needed. A first step might be to report on multiple procedures until a consensus is achieved.

Mediators of a physical activity intervention among women with a family history of breast cancer

The current study examined mediators of an efficacious physical activity intervention. Women with a mean age of 42.6 (range 23-61) years and a family history of breast cancer were randomized to either an Internet-based physical activity intervention (n = 28) or an active control condition (n = 27) for three months. Data were collected between November 2010 and August 2011. Hypothesized mediators were examined using a product of coefficients model with bootstrapped standard errors. Significant mediation was observed for both self-efficacy and behavioral processes. Specifically, the regression coefficients of the indirect effects ("ab path": unstandardized effect of the intervention on physical activity that occurred through the mediator) were ab = 38.58 (95% confidence interval [CI]: 8.66-92.76) for self-efficacy, and ab = 42.02 (95% CI: 6.76-104.84) for behavioral processes. Other factors examined in this study, including cognitive processes, decisional balance, and perceived risk of breast cancer, were not statistically significant mediators. Findings suggest that self-efficacy and behavioral processes may be key constructs to use in targeting future physical activity interventions among women with a family history of breast cancer.

Variation in actigraphy-estimated rest-activity patterns by demographic factors

Rest-activity patterns provide an indication of circadian rhythmicity in the free-living setting. We aimed to describe the distributions of rest-activity patterns in a sample of adults and children across demographic variables. A sample of adults (N = 590) and children (N = 58) wore an actigraph on their nondominant wrist for 7 days and nights. We generated rest-activity patterns from cosinor analysis (MESOR, acrophase and magnitude) and nonparametric circadian rhythm analysis (IS: interdaily stability; IV: intradaily variability; L5: least active 5-hour period; M10: most active 10-hour period; and RA: relative amplitude). Demographic variables included age, sex, race, education, marital status, and income. Linear mixed-effects models were used to test for demographic differences in rest-activity patterns. Adolescents, compared to younger children, had (1) later M10 midpoints (β = 1.12 hours [95% CI: 0.43, 1.18] and lower M10 activity levels; (2) later L5 midpoints (β = 1.6 hours [95% CI: 0.9, 2.3]) and lower L5 activity levels; (3) less regular rest-activity patterns (lower IS and higher IV); and 4) lower magnitudes (β = -0.95 [95% CI: -1.28, -0.63]) and relative amplitudes (β = -0.1 [95% CI: -0.14, -0.06]). Mid-to-older adults, compared to younger adults (aged 18-29 years), had (1) earlier M10 midpoints (β = -1.0 hours [95% CI: -1.6, -0.4]; (2) earlier L5 midpoints (β = -0.7 hours [95% CI: -1.2, -0.2]); and (3) more regular rest-activity patterns (higher IS and lower IV). The magnitudes and relative amplitudes were similar across the adult age categories. Sex, race and education level rest-activity differences were also observed. Rest-activity patterns vary across the lifespan, and differ by race, sex and education. Understanding population variation in these patterns provides a foundation for further elucidating the health implications of rest-activity patterns across the lifespan.

Prolonged Nightly Fasting and Breast Cancer Prognosis

IMPORTANCE

Rodent studies demonstrate that prolonged fasting during the sleep phase positively influences carcinogenesis and metabolic processes that are putatively associated with risk and prognosis of breast cancer. To our knowledge, no studies in humans have examined nightly fasting duration and cancer outcomes.

OBJECTIVE

To investigate whether duration of nightly fasting predicted recurrence and mortality among women with early-stage breast cancer and, if so, whether it was associated with risk factors for poor outcomes, including glucoregulation (hemoglobin A1c), chronic inflammation (C-reactive protein), obesity, and sleep.

DESIGN, SETTING, AND PARTICIPANTS

Data were collected from 2413 women with breast cancer but without diabetes mellitus who were aged 27 to 70 years at diagnosis and participated in the prospective Women's Healthy Eating and Living study between March 1, 1995, and May 3, 2007. Data analysis was conducted from May 18 to October 5, 2015.

EXPOSURES

Nightly fasting duration was estimated from 24-hour dietary recalls collected at baseline, year 1, and year 4.

MAIN OUTCOMES AND MEASURES

Clinical outcomes were invasive breast cancer recurrence and new primary breast tumors during a mean of 7.3 years of study follow-up as well as death from breast cancer or any cause during a mean of 11.4 years of surveillance. Baseline sleep duration was self-reported, and archived blood samples were used to assess concentrations of hemoglobin A1c and C-reactive protein.

RESULTS

The cohort of 2413 women (mean [SD] age, 52.4 [8.9] years) reported a mean (SD) fasting duration of 12.5 (1.7) hours per night. In repeated-measures Cox proportional hazards regression models, fasting less than 13 hours per night (lower 2 tertiles of nightly fasting distribution) was associated with an increase in the risk of breast cancer recurrence compared with fasting 13 or more hours per night (hazard ratio, 1.36; 95% CI, 1.05-1.76). Nightly fasting less than 13 hours was not associated with a statistically significant higher risk of breast cancer mortality (hazard ratio, 1.21; 95% CI, 0.91-1.60) or a statistically significant higher risk of all-cause mortality (hazard ratio, 1.22; 95% CI, 0.95-1.56). In multivariable linear regression models, each 2-hour increase in the nightly fasting duration was associated with significantly lower hemoglobin A1c levels (β = -0.37; 95% CI, -0.72 to -0.01) and a longer duration of nighttime sleep (β = 0.20; 95% CI, 0.14-0.26).

CONCLUSIONS AND RELEVANCE

Prolonging the length of the nightly fasting interval may be a simple, nonpharmacologic strategy for reducing the risk of breast cancer recurrence. Improvements in glucoregulation and sleep may be mechanisms linking nightly fasting with breast cancer prognosis.

Influence of Day Length and Physical Activity on Sleep Patterns in Older Icelandic Men and Women

STUDY OBJECTIVES

To identify cross-sectional and seasonal patterns of sleep and physical activity (PA) in community-dwelling, older Icelandic adults using accelerometers.

METHODS

A seven-day free-living protocol of 244 (110 female) adults aged 79.7 ± 4.9 years was conducted as part of a larger population-based longitudinal observational-cohort study in the greater Reykjavik area of Iceland. A subpopulation (n = 72) repeated the 7-day measurement during seasonal periods with greater (13.4 ± 1.4 h) and lesser (7.7 ± 1.8 h) daylight.

RESULTS

Cross-sectional analyses using multiple linear regression models revealed that day length was a significant independent predictor of sleep duration, mid-sleep, and rise time (all p < 0.05). However, the actual within-individual differences in sleep patterns of the repeaters were rather subtle between periods of longer and shorter day-lengths. Compared to women, men had a shorter sleep duration (462 ± 80 vs. 487 ± 68 minutes, p = 0.008), earlier rise time, and a greater number of awakenings per night (46.5 ± 18.3 vs. 40.2 ± 15.7, p = 0.007), but sleep efficiency and onset latency were similar between the two sexes. Daily PA was also similar between men and women and between periods of longer and shorter day-lengths. BMI, age, gender, and overall PA all contributed to the variations in sleep parameters using multiple regression analysis.

CONCLUSIONS

The sleep and PA characteristics of this unique population revealed some gender differences, but there was limited variation in response to significant daylight changes which may be due to long-term adaptation.

Internet-based physical activity intervention for women with a family history of breast cancer

OBJECTIVE

Physical inactivity is a modifiable risk factor for breast cancer. Physical activity interventions that can be delivered through the Internet have the potential to increase participant reach. The efficacy of an Internet-based physical activity intervention was tested in a sample of women at an elevated risk for breast cancer.

METHOD

A total of 55 women with at least 1 first-degree relative with breast cancer (but no personal history of breast cancer) were randomized to a 3-month theoretically grounded Internet-based physical activity intervention or an active control arm. Minutes of moderate to vigorous physical activity, psychosocial mediators of physical activity adoption and maintenance, as well as worry and perceived risk of developing breast cancer were assessed at baseline, 3-month, and 5-month follow up.

RESULTS

Participants were on average 46.2 (SD = 11.4) years old with a body mass index of 27.3 (SD = 4.8) kg/m2. The intervention arm significantly increased minutes of moderate to vigorous physical activity compared to the active control arm at 3 months (213 vs. 129 min/week) and 5 months (208 vs. 119 min/week; both ps < .001). Regression models indicated that participants in the intervention had significantly higher self-efficacy for physical activity at 3 months (p < .01) and borderline significantly higher self-efficacy at 5 months (p = .05). Baseline breast cancer worry and perceived risk were not associated with physical activity.

CONCLUSION

Findings from this study suggest that an Internet-based physical activity intervention may substantially increase physical activity in women with a family history of breast cancer.

Abstract PD4-08: Post-diagnosis physical activity and comorbidities, not BMI, explain mortality risk in the after breast cancer pooling project

Background: In its 2014 position statement, ASCO concluded that obesity is associated with worse prognosis after cancer diagnosis. However in the same year, a comprehensive review by the World Cancer Research Fund concluded that there was limited evidence that greater body fatness increases risk of overall or breast cancer mortality, indicating that further investigation into lifestyle factors are needed. The After Breast Cancer (ABC) Pooling Project has reported, separately, significant mortality effects of pre-diagnosis BMI and of post-diagnosis physical activity (PA). We investigate whether the effect of BMI can be limited to subgroups characterized by comorbidities and physical activity.

Methods: Data are from the three US cohorts that were harmonized in the ABCPP (n=9513) including: the Women's Healthy Eating and Living (WHEL), Life After Cancer Epidemiology (LACE), and Nurses' Health (NHS) studies. Stepwise delayed entry Cox proportional hazards models examined each lifestyle predictor (BMI, PA, and comorbidities assessed after diagnosis) sequentially and together in multivariate models for breast cancer and all-cause mortality.

Results: In multivariate models without the other two target variables, PA was significantly associated with a 17% decrease in the risk of breast cancer mortality among women in the highest quartile of PA (MET hr/wk &gt; 21.4), compared to the lowest quartile (MET hr/wk &lt; 2.7) (HR=0.81,95% CI= 0.67,0.97). In the model with major comorbidities, there was a significant 40% increase in the risk of breast cancer mortality among women diagnosed with both diabetes and hypertension (HR=1.40, 95% CI= 1.01,1.93). In the model with BMI, there was no significant association with risk of breast cancer mortality. These results were essentially unchanged with all variables in a single model.

For all-cause mortality, the PA-only model showed a significant PA effect with the hazard decreasing from 20% to 40% across quartiles (Q2 HR=0.80, 95% CI=0.71,0.90, Q4 HR=0.62, 95% CI=0.54,0.71). In the comorbidity-only model, both diabetes and hypertension significantly increased hazard of all-cause mortality 80% and 33%, respectively. Having both diagnoses was associated with a significant, 2.3 fold increase in all-cause mortality (HR=2.34, 95% CI= 1.95,2.81).

In the BMI-only model, being underweight was associated with a significant 2.4 fold increase in risk of all-cause mortality, and there was a 20 and 37% increase in risk associated with being categorized as obese I or II (Obese I HR=1.23, 95% CI=1.07,1.40, Obese II HR=1.37, 95% CI=1.16,1.61).

With all three variables in the model, the risk associated with being obese decreased and became non-significant (Obese I HR=1.06, Obese II HR=1.05), while the significance, strength, and direction of the association of comorbidities and PA with all-cause mortality remained constant.

Conclusion: These data suggest that post-diagnosis comorbidities and lack of physical activity, rather than high BMI , are the important risk factors for all-cause and breast cancer specific mortality. While needing further validation, these suggest that physical activity interventions and monitoring treatment for comorbidities should become standard of care for breast cancer survivors.

Citation Format: Nelson SH, Marinac CR, Patterson RE, Nachuta SJ, Caan BJ, Chen WY, Shu X-O, Pierce JP. Post-diagnosis physical activity and comorbidities, not BMI, explain mortality risk in the after breast cancer pooling project. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr PD4-08.

Abstract P3-09-01: Intermittent fasting in breast cancer risk and survivorship: Insight from the women's healthy eating and living study

Intermittent fasting (IF) regimens have gained widespread attention in recent years for their possible role in human health and disease risk. In mice, IF schedules that are aligned with sleep-wake cycles appear to positively influence metabolic processes related to cancer risk and may have direct effects on carcinogenesis; however the impact of these regimens on cancer risk in humans remain unclear. We examined associations between nighttime fasting duration (a form of IF aligned with sleep-wake cycles) and (1) biomarkers demonstrated to be associated with breast cancer prognosis; and (2) long-term clinical outcomes in a sample of breast cancer survivors from the Women's Healthy Eating and Living (WHEL) Study.

Dietary data were available for 3,061 non-diabetic women enrolled in the WHEL Study. Nighttime fasting duration was calculated using time-stamped 24-hour dietary recalls collected at the baseline, Year 1, and Year 4 study assessment periods. Approximately 3-4 dietary records were collected per subject at each assessment period, and these records were averaged to yield a single estimate of nighttime fasting duration per time point. Glycosylated hemoglobin (HbA1c) and C-reactive protein (CRP) levels were ascertained from blood specimen collected at baseline. Clinical outcomes recorded during the study follow-up include breast cancer events (recurrence or new primary) and mortality. Linear regression models examined the associations of nighttime fasting with baseline concentrations of HbA1c and CRP. Delayed-entry Cox proportional hazard models were used to assess the association between nighttime fasting duration, recorded at the baseline, Year 1, and Year 4 assessments, with clinical outcomes. These models used a counting process method to account for repeated measures. All models controlled for basic demographic factors, participant characteristics (BMI, comorbidity status, sleep duration), breast cancer characteristics (stage, grade, anti-estrogen use), and dietary variables (total calories, evening calories, eating frequency).

Women fasted an average of 12.5 hours per night (SD=1.6 hours). There were 520 new breast cancer events, and 569 deaths during study follow up. HbA1c level was significantly and inversely related to nighttime fasting duration. Each 2-hour increase in the nighttime fasting duration was associated with a 0.2-unit decrease in HbA1c (β=-0.21; p=0.03 with HbA1c expressed as mmol/mol), and there was no evidence of mediation or effect modification by participant characteristics, e.g., BMI. No associations were observed between nighttime fasting duration and CRP. In longitudinal models, women who fasted less than 13.1 hours per night (bottom two tertiles of nightly fasting distribution) had roughly a 50% higher hazard for experiencing a breast cancer event, compared to women who fasted at least 13.1 hours per night (HR: 1.46; 95%CI: 1.11-1.93; p&lt;0.01). Nighttime fasting duration was not associated with mortality.

Findings suggest that increasing the length of the nighttime fasting interval could be a simple, feasible, and novel strategy to improve glucose control and reduce breast cancer risk. Randomized trials confirming the link between nighttime fasting duration and breast cancer risk are warranted.

Citation Format: Marinac CR, Neslon SH, Natarajan L, Sears DD, Breen CI, Pierce JP, Patterson RE. Intermittent fasting in breast cancer risk and survivorship: Insight from the women's healthy eating and living study. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P3-09-01.

Impact of very low physical activity, BMI, and comorbidities on mortality among breast cancer survivors

The purpose of this study was to examine post-diagnosis BMI, very low physical activity, and comorbidities, as predictors of breast cancer-specific and all-cause mortality. Data from three female US breast cancer survivor cohorts were harmonized in the After Breast Cancer Pooling Project (n = 9513). Delayed entry Cox proportional hazards models were used to examine the impact of three post-diagnosis lifestyle factors: body mass index (BMI), select comorbidities (diabetes only, hypertension only, or both), and very low physical activity (defined as physical activity <1.5 MET h/week) in individual models and together in multivariate models for breast cancer and all-cause mortality. For breast cancer mortality, the individual lifestyle models demonstrated a significant association with very low physical activity but not with the selected comorbidities or BMI. In the model that included all three lifestyle variables, very low physical activity was associated with a 22 % increased risk of breast cancer mortality (HR 1.22, 95 % CI 1.05, 1.42). For all-cause mortality, the three individual models demonstrated significant associations for all three lifestyle predictors. In the combined model, the strength and significance of the association of comorbidities (both hypertension and diabetes versus neither: HR 2.16, 95 % CI 1.79, 2.60) and very low physical activity (HR 1.35, 95 % CI 1.22, 1.51) remained unchanged, but the association with obesity was completely attenuated. These data indicate that after active treatment, very low physical activity, consistent with a sedentary lifestyle (and comorbidities for all-cause mortality), may account for the increased risk of mortality, with higher BMI, that is seen in other studies.

Recruitment strategies, design, and participant characteristics in a trial of weight-loss and metformin in breast cancer survivors

Weight loss and metformin are hypothesized to improve breast cancer outcomes; however the joint impacts of these treatments have not been investigated. Reach for Health is a randomized trial using a 2 × 2 factorial design to investigate the effects of weight loss and metformin on biomarkers associated with breast cancer prognosis among overweight/obese postmenopausal breast cancer survivors. This paper describes the trial recruitment strategies, design, and baseline sample characteristics. Participants were randomized in equal numbers to (1) placebo, (2) metformin, (3) weight loss intervention and placebo, or (4) weight-loss intervention and metformin. The lifestyle intervention was a personalized, telephone-based program targeting a 7% weight-loss in the intervention arm. The metformin dose was 1500 mg/day. The duration of the intervention was 6 months. Main outcomes were biomarkers representing 3 metabolic systems putatively related to breast cancer mortality: glucoregulation, inflammation, and sex hormones. Between August 2011 and May 2015, we randomized 333 breast cancer survivors. Mass mailings from the California Cancer Registry were the most successful recruitment strategy with over 25,000 letters sent at a cost of $191 per randomized participant. At baseline, higher levels of obesity were significantly associated with worse sleep disturbance and impairment scores, lower levels of physical activity and higher levels of sedentary behavior, hypertension, hypercholesterolemia, and lower quality of life (p<0.05 for all). These results illustrate the health burden of obesity. Results of this trial will provide mechanistic data on biological pathways and circulating biomarkers associated with lifestyle and pharmacologic interventions to improve breast cancer prognosis.

Abstract 1874: Prolonged nightly fasting and breast cancer risk: findings from NHANES (2009-2010)

A novel line of research has emerged suggesting that daily feeding-fasting schedules have metabolic implications that are highly relevant to breast cancer. In rodents, a habitual daily fasting schedule that is aligned with sleep-wake cycles appears to have favorable effects on a variety of cancer risk factors and may reduce cell proliferation. While data from rodent models are compelling, no human studies have explored the potential impact of this type of fasting schedule on cancer risk factors such as hyperglycemia (a possible facilitator of neoplastic proliferation). We examined cross-sectional associations of nighttime fasting duration with glycemic control biomarkers associated with increased breast cancer risk in a population-based sample of women in the 2009-2010 U.S. National Health and Nutrition Examination Survey.

Dietary, anthropometric and glycosylated hemoglobin (HbA1c) data were available for 2,212 women, and 2-hour postprandial glucose concentrations were available for 1,066 women. Nighttime fasting duration was calculated using time-stamped 24-hour food records. Separate linear regression models examined associations of nighttime fasting with HbA1c and 2-hour glucose concentrations. Logistic regression modeled associations of nighttime fasting duration with elevated HbA1c (HbA1c ≥ 39 mmol/mol or 5.7%) and elevated 2-hour glucose (glucose ≥ 140 mg/dL). All models adjusted for age, education, race/ethnicity, BMI, total kcal intake, evening kcal intake, and the number of eating episodes per day. All analyses used sample weights to account for differential probabilities of selection into the sample, nonresponse, and noncoverage. Standard errors were estimated using Taylor Series Linearization.

Women in this sample were an average of 46.8 years of age (SE = 0.66) and fasted approximately 12.4 (SE = 0.08) hours per night. Each 3-hour increase in nighttime fasting (roughly one standard deviation) was associated with a 4% lower 2-hour postprandial glucose measurement (β 0.96, 95% CI 0.93 - 1.00; p&lt;0.05), and a non-statistically significant 0.4 unit decrease in HbA1c (β -0.39, 95% CI -0.84 - -0.05; p = 0.08). Logistic regression models indicate that each 3-hour increase in nighttime fasting duration was associated with roughly a 20% reduced odds of elevated HbA1c (OR 0.81, 95% CI 0.68, 0.97; p&lt;0.05) and non-significantly reduced odds of elevated 2-hour glucose (OR 0.78, 95%CI 0.53-1.54).

Randomized trials are needed to confirm whether a prolonged nighttime fasting schedule could improve biomarkers of glycemic control, thereby reducing breast cancer risk among women.

Citation Format: Catherine R. Marinac, Loki Natarajan, Dorothy D. Sears, Linda C. Gallo, Sheri J. Hartman, Elva Arredondo, Ruth E. Patterson. Prolonged nightly fasting and breast cancer risk: findings from NHANES (2009-2010). [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1874. doi:10.1158/1538-7445.AM2015-1874

Prolonged Nightly Fasting and Breast Cancer Risk: Findings from NHANES (2009-2010)

BACKGROUND

A novel line of research has emerged, suggesting that daily feeding-fasting schedules that are synchronized with sleep-wake cycles have metabolic implications that are highly relevant to breast cancer. We examined associations of nighttime fasting duration with biomarkers of breast cancer risk among women in the 2009-2010 U.S. National Health and Nutrition Examination Survey.

METHODS

Dietary, anthropometric, and HbA1c data were available for 2,212 women, and 2-hour postprandial glucose concentrations were available for 1,066 women. Nighttime fasting duration was calculated using 24-hour food records. Separate linear regression models examined associations of nighttime fasting with HbA1c and 2-hour glucose concentrations. Logistic regression modeled associations of nighttime fasting with elevated HbA1c (HbA1c ≥ 39 mmol/mol or 5.7%) and elevated 2-hour glucose (glucose ≥ 140 mg/dL). All models adjusted for age, education, race/ethnicity, body mass index, total kcal intake, evening kcal intake, and the number of eating episodes per day.

RESULTS

Each 3-hour increase in nighttime fasting (roughly 1 SD) was associated with a 4% lower 2-hour glucose measurement [β, 0.96; 95% confidence interval (CI), 0.93-1.00; P < 0.05], and a nonstatistically significant decrease in HbA1c. Logistic regression models indicate that each 3-hour increase in nighttime fasting duration was associated with roughly a 20% reduced odds of elevated HbA1c (OR, 0.81; 95% CI, 0.68-0.97; P < 0.05) and nonsignificantly reduced odds of elevated 2-hour glucose.

CONCLUSIONS

A longer nighttime duration was significantly associated with improved glycemic regulation.

IMPACT

Randomized trials are needed to confirm whether prolonged nighttime fasting could improve biomarkers of glucose control, thereby reducing breast cancer risk.

Objectively measured physical activity and cognitive functioning in breast cancer survivors

PURPOSE

This study aimed to explore the relationship between objectively measured physical activity and cognitive functioning in breast cancer survivors.

METHODS

Participants were 136 postmenopausal breast cancer survivors. Cognitive functioning was assessed using a comprehensive computerized neuropsychological test. Seven-day physical activity was assessed using hip-worn accelerometers. Linear regression models examined associations of minutes per day of physical activity at various intensities on individual cognitive functioning domains. The partially adjusted model controlled for primary confounders (model 1), and subsequent adjustments were made for chemotherapy history (model 2) and body mass index (BMI) (model 3). Interaction and stratified models examined BMI as an effect modifier.

RESULTS

Moderate-to-vigorous physical activity (MVPA) was associated with information processing speed. Specifically, 10 min of MVPA was associated with a 1.35-point higher score (out of 100) on the information processing speed domain in the partially adjusted model and a 1.29-point higher score when chemotherapy was added to the model (both p < 0.05). There was a significant BMI × MVPA interaction (p = 0.051). In models stratified by BMI (<25 vs. ≥25 kg/m(2)), the favorable association between MVPA and information processing speed was stronger in the subsample of overweight and obese women (p < 0.05) but not statistically significant in the leaner subsample. Light-intensity physical activity was not significantly associated with any of the measured domains of cognitive function.

CONCLUSIONS

MVPA may have favorable effects on information processing speed in breast cancer survivors, particularly among overweight or obese women.

IMPLICATIONS FOR CANCER SURVIVORS

Interventions targeting increased physical activity may enhance aspects of cognitive function among breast cancer survivors.

Lifestyle factors associated with cognitive functioning in breast cancer survivors

OBJECTIVE

Weight, physical activity, and sleep are modifiable lifestyle factors that impact cognitive functioning in noncancer populations but have yet to be examined in cancer survivors. The aim of the study was to assess the relationship of obesity, physical activity, and sleep, with cognitive functioning among breast cancer survivors.

METHODS

Participants were 136 early-stage postmenopausal breast cancer survivors who completed an assessment of neuropsychological testing, height, weight, physical activity, and sleep. Linear regression models examined the associations of the seven neuropsychological domains with obesity, physical activity, and sleep. Logistic regression models examined odd of impairment in each domain. All models controlled for breast cancer treatment variables and relevant demographic and clinical variables.

RESULTS

Obese participants had significantly worse performance (β = -5.04, standard error (SE) = 2.53) and were almost three times more likely to be impaired (odds ratio (OR) = 2.87; 95% CI: 1.02-8.10) on the Information processing domain. The highest tertile of physical activity was significantly related to better performance on the executive functioning domain (β = 5.13, SE = 2.42) and attention domain (β = 4.26, SE = 2.07). The middle tertile of physical activity was significantly related to better performance (β = 9.00, SE = 3.09) and decreased odds of impairment (OR = 0.89, 95% CI: 0.07-0.91) on the visual-spatial domain. More hours of sleep per night was significantly associated with better performance (β = 2.69, SE = 0.98) and decreased odds of impairment (OR = 0.52; 95% CI: 0.33-0.82) on the verbal functioning domain.

CONCLUSIONS

These findings suggest that obesity, physical activity, and sleep are related to cognitive functioning among breast cancer survivors and have potential to be intervention targets to improve cognitive functioning.

Objectively measured physical activity is related to cognitive function in older adults

OBJECTIVES

To explore the relationship between cognitive functioning and time spent at different intensities of physical activity (PA) in free-living older adults.

DESIGN

Cross sectional analyses.

SETTING

Continuing care retirement communities.

PARTICIPANTS

Older adults residing in seven continuing care retirement communities in San Diego County with an average age of 83; 70% were female, and 35% had a graduate-level education (N = 217).

MEASUREMENTS

PA was measured objectively using hip worn accelerometers with data aggregated to the minute level. Three cut points were used to assess low light-intensity PA (LLPA), high light-intensity PA (HLPA), and moderate- to vigorous-intensity PA (MVPA). The Trail Making Test (TMT) Parts A and B were completed, and time for each test (seconds) and time for Part B minus time for Part A (seconds) were used as measures of cognitive function. Variables were log-transformed and entered into linear regression models adjusting for demographic factors (age, education, sex) and other PA intensity variables.

RESULTS

LLPA was not related to any TMT test score. HLPA was significantly related to TMT A, B, and B minus A but only in unadjusted models. MVPA was related to TMT B and B minus A after adjusting for demographic variables.

CONCLUSION

There may be a dose response between PA intensity and cognitive functioning in older adults. The stronger findings supporting a relationship between MVPA and cognitive functioning are consistent with previous observational and intervention studies.