Daniel F Hayes

Concordia University–Ann Arbor, Ann Arbor, Michigan, United States

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Publications (345)3267.87 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: Circulating Tumor cells (CTC) are prognostic in metastatic breast cancer (MBC). We tested whether EpCAM based capture system (CellSearch®) is effective in patients with triple negative (TN) MBC, and whether CTC-apoptosis and clustering enhances the prognostic role of CTC. CTC enumeration and apoptosis was determined using the CXC CellSearch® kit at baseline and days 15 and 29 in blood drawn from TN MBC patients who participated in a prospective randomized phase II trial of nanoparticle albumin-bound paclitaxel (nab-PAC) with or without tigatuzumab (TIG). Association between levels of CTC and patient outcomes was assessed using logistic regression, Kaplan Meier curves, and Cox proportional hazards modeling. Nineteen of 52 (36.5%), 14/52 (26.9%), and 13/49 (26.5%) patients who were evaluable had elevated CTC (≥5CTC/7.5 ml WB) at baseline, days 15 and 29, respectively. Patients with elevated vs. not elevated CTC at each time point had worse progression free survival (PFS) (p=0.005, 0.0003, 0.0002, respectively). The odds of clinical benefit response for those who had elevated vs. low CTC at baseline and days 15 and 29 were 0.25 (95% CI: 0.08-0.84, p=0.024), 0.19 (95% CI: 0.05-0.17, p=0.014), and 0.06 (95% CI: 0.01-0.33, p=0.001), respectively. There was no apparent prognostic effect comparing CTC-apoptosis vs. non-apoptosis. Presence of CTC-cluster at day 15, and day 29 was associated with shorter PFS. CTC were detected using CellSearch® assay in approximately one-third of TN MBC patients. Elevated CTC at baseline and days 15 and 29 were prognostic, and reductions in CTC levels reflected response. Copyright © 2015, American Association for Cancer Research.
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    ABSTRACT: Although an important biomarker in breast cancer, Ki67 lacks scoring standardization, which has limited its clinical use. Our previous study found variability when laboratories used their own scoring methods on centrally stained tissue microarray slides. In this current study, 16 laboratories from eight countries calibrated to a specific Ki67 scoring method and then scored 50 centrally MIB-1 stained tissue microarray cases. Simple instructions prescribed scoring pattern and staining thresholds for determination of the percentage of stained tumor cells. To calibrate, laboratories scored 18 'training' and 'test' web-based images. Software tracked object selection and scoring. Success for the calibration was prespecified as Root Mean Square Error of scores compared with reference <0.6 and Maximum Absolute Deviation from reference <1.0 (log2-transformed data). Prespecified success criteria for tissue microarray scoring required intraclass correlation significantly >0.70 but aiming for observed intraclass correlation ≥0.90. Laboratory performance showed non-significant but promising trends of improvement through the calibration exercise (mean Root Mean Square Error decreased from 0.6 to 0.4, Maximum Absolute Deviation from 1.6 to 0.9; paired t-test: P=0.07 for Root Mean Square Error, 0.06 for Maximum Absolute Deviation). For tissue microarray scoring, the intraclass correlation estimate was 0.94 (95% credible interval: 0.90-0.97), markedly and significantly >0.70, the prespecified minimum target for success. Some discrepancies persisted, including around clinically relevant cutoffs. After calibrating to a common scoring method via a web-based tool, laboratories can achieve high inter-laboratory reproducibility in Ki67 scoring on centrally stained tissue microarray slides. Although these data are potentially encouraging, suggesting that it may be possible to standardize scoring of Ki67 among pathology laboratories, clinically important discrepancies persist. Before this biomarker could be recommended for clinical use, future research will need to extend this approach to biopsies and whole sections, account for staining variability, and link to outcomes.Modern Pathology advance online publication, 20 February 2015; doi:10.1038/modpathol.2015.38.
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    ABSTRACT: Purpose: Endocrine therapy (ET) fails to induce a response in one-half of patients with hormone receptor (HR) positive metastatic breast cancer (MBC) and almost all will eventually become refractory to ET. Circulating Tumor Cells (CTC) are associated with worse prognosis in MBC patients, but enumeration alone is insufficient to predict the absolute odds of benefit from any therapy, including ET. We developed a multi-parameter CTC-Endocrine Therapy Index (CTC-ETI), which we hypothesize may predict resistance to ET in patients with HR positive MBC. Experimental Design: The CTC-ETI combines enumeration and CTC expression of four markers: estrogen receptor (ER), B-cell lymphoma 2 (BCL-2), Human Epidermal Growth Factor Receptor 2 (HER2), and Ki67. The CellSearch® System and reagents were used to capture CTC and measure protein expression by immunofluorescent staining on CTC. Results: The feasibility of determining CTC-ETI was initially established in vitro and then in a prospective single-institution pilot study in MBC patients. CTC-ETI was successfully determined in 44/50 (88%) patients. Eighteen (41%), 9 (20%), and 17 (39%) patients had low, intermediate, and high CTC-ETI scores, respectively. Inter-observer concordance of CTC-ETI determination was 94-95% (Kappa statistic 0.90-0.91). Inter- and cell-to-cell intra-patient heterogeneity of expression of each of the CTC-markers was observed. CTC biomarker expression was discordant from both primary and metastatic tissue. Conclusions: CTC expression of ER, BCL-2, HER2, and Ki67 can be reproducibly measured with high analytical validity using the CellSearch® System. The clinical implications of CTC-ETI, and of the heterogeneity of CTC-biomarker expression, are being evaluated in an ongoing prospective trial.
    Clinical Cancer Research 11/2014; DOI:10.1158/1078-0432.CCR-14-1913 · 8.19 Impact Factor
  • Daniel F Hayes
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    ABSTRACT: A tumor biomarker is a molecular or process-based change that reflects the status of an underlying malignancy. A tumor biomarker may be identified and measured by one or more assays, or tests, for the biomarker. Increasingly, tumor biomarker tests are being used to drive patient management, either by identifying patients who do not require any, or any further, treatment, or by identifying patients whose tumors are so unlikely to respond to a given type of treatment that it will cause more harm than good. A tumor biomarker assay should only be used to guide management if it has analytical validity, meaning that it is accurate, reproducible, and reliable, and if it has been shown to have clinical utility. The latter implies that high levels of evidence are available that demonstrate that application of the tumor biomarker test for a given use context results in better outcomes, or similar outcomes with less cost, than if the assay were not applied. Use contexts include risk categorization, screening, differential diagnosis, prognosis, prediction of therapeutic activity or monitoring disease course. Very few tumor biomarker tests have passed these high bars for routine clinical application. However, if tumor biomarker tests are going to be used to drive patient care, than an understanding, and careful assessment, of these concepts are essential, since "A Bad Tumor Biomarker Test Is as Bad as a Bad Drug." Copyright © 2014 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.
    Molecular Oncology 10/2014; DOI:10.1016/j.molonc.2014.10.004 · 5.94 Impact Factor
  • N Lynn Henry, Anne F Schott, Daniel F Hayes
    Journal of Clinical Oncology 09/2014; 32(29). DOI:10.1200/JCO.2014.57.6132 · 17.88 Impact Factor
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    ABSTRACT: The aim of this study is to use functional magnetic resonance imaging (fMRI) to prospectively examine pre-treatment predictors of post-treatment fatigue and cognitive dysfunction in women treated with adjuvant chemotherapy for breast cancer. Fatigue and cognitive dysfunction often co-occur in women treated for breast cancer. We hypothesized that pre-treatment factors, unrelated to chemotherapy per se, might increase vulnerability to post-treatment fatigue and cognitive dysfunction. Patients treated with (n = 28) or without chemotherapy (n = 37) and healthy controls (n = 32) were scanned coincident with pre- and one-month post-chemotherapy during a verbal working memory task (VWMT) and assessed for fatigue, worry, and cognitive dysfunction. fMRI activity measures in the frontoparietal executive network were used in multiple linear regression to predict post-treatment fatigue and cognitive function. The chemotherapy group reported greater pre-treatment fatigue than controls and showed compromised neural response, characterized by higher spatial variance in executive network activity, than the non-chemotherapy group. Also, the chemotherapy group reported greater post-treatment fatigue than the other groups. Linear regression indicated that pre-treatment spatial variance in executive network activation predicted post-treatment fatigue severity and cognitive complaints, while treatment group, age, hemoglobin, worry, and mean executive network activity levels did not predict these outcomes. Pre-treatment neural inefficiency (indexed by high spatial variance) in the executive network, which supports attention and working memory, was a better predictor of post-treatment cognitive and fatigue complaints than exposure to chemotherapy per se. This executive network compromise could be a pre-treatment neuromarker of risk, indicating patients most likely to benefit from early intervention for fatigue and cognitive dysfunction.
    Breast Cancer Research and Treatment 08/2014; 147(2). DOI:10.1007/s10549-014-3092-6 · 4.47 Impact Factor
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    ABSTRACT: BACKGROUND Aromatase inhibitor (AI) therapy results in substantial survival benefits for patients with hormone receptor-positive breast cancer. The rates of poor adherence and discontinuation of AI therapy are high, primarily because of treatment-related toxicities like musculoskeletal pain. Although pain-related symptoms may worsen during AI therapy, the authors hypothesized that nonpersistence with AI therapy was associated with symptoms that were present before treatment initiation.METHODS Postmenopausal women initiating AI therapy who were enrolled in a prospective clinical trial completed questionnaires at baseline to assess sleep, fatigue, mood, and pain. Reasons for treatment discontinuation during the first year of treatment were recorded. Associations between baseline patient-reported symptoms and treatment discontinuation because of toxicity were identified using logistic regression.RESULTSFour hundred forty-nine patients were evaluable. The odds of treatment discontinuation were higher in patients who reported a greater number of symptoms before AI initiation. Baseline poor sleep quality was associated with early treatment discontinuation, with an odds ratio (OR) of 1.91 (95% confidence interval [CI], 1.26-2.89; P = .002). Baseline presence of tired feeling and forgetfulness had similar ORs for discontinuation (tired feeling: OR, 1.76; 95% CI, 1.15-2.67; P = .009; forgetfulness: OR, 1.66; 95% CI, 1.11-2.48; P = .015). An increasing total number of baseline symptoms was associated with an increased likelihood of treatment discontinuation, with an OR of 1.89 (95% CI, 1.20-2.96; P = .006) for 3 to 5 symptoms versus 0 to 2 symptoms.CONCLUSIONS Symptom clusters in breast cancer survivors that are present before the initiation of adjuvant AI therapy may have a negative impact on a patient's persistence with therapy. Interventions to manage these symptoms may improve breast cancer outcomes and quality of life. Cancer 2014. © 2014 American Cancer Society.
    Cancer 08/2014; 120(16). DOI:10.1002/cncr.28756 · 5.20 Impact Factor
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    ABSTRACT: Purpose Increased circulating tumor cells (CTCs; five or more CTCs per 7.5 mL of whole blood) are associated with poor prognosis in metastatic breast cancer (MBC). A randomized trial of patients with persistent increase in CTCs tested whether changing chemotherapy after one cycle of first-line chemotherapy would improve the primary outcome of overall survival (OS). Patients and Methods Patients with MBC who did not have increased CTCs at baseline remained on initial therapy until progression (arm A). Patients with initially increased CTCs that decreased after 21 days of therapy remained on initial therapy (arm B). Patients with persistently increased CTCs after 21 days of therapy were randomly assigned to continue initial therapy (arm C1) or change to an alternative chemotherapy (arm C2). Results Of 595 eligible and evaluable patients, 276 (46%) did not have increased CTCs (arm A). Of those with initially increased CTCs, 31 (10%) were not retested, 165 were assigned to arm B, and 123 were randomly assigned to arm C1 or C2. No difference in median OS was observed between arm C1 and C2 (10.7 and 12.5 months, respectively; P = .98). CTCs were strongly prognostic. Median OS for arms A, B, and C (C1 and C2 combined) were 35 months, 23 months, and 13 months, respectively (P < .001). Conclusion This study confirms the prognostic significance of CTCs in patients with MBC receiving first-line chemotherapy. For patients with persistently increased CTCs after 21 days of first-line chemotherapy, early switching to an alternate cytotoxic therapy was not effective in prolonging OS. For this population, there is a need for more effective treatment than standard chemotherapy. (C) 2014 by American Society of Clinical Oncology
    Journal of Clinical Oncology 06/2014; 32(31). DOI:10.1200/JCO.2014.56.2561 · 17.88 Impact Factor
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    Journal of Clinical Oncology 04/2014; DOI:10.1200/JCO.2014.55.0673 · 17.88 Impact Factor
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    ABSTRACT: Breast cancer is the most common malignancy in women in the United States and is second only to lung cancer as a cause of cancer death. The overall management of breast cancer includes the treatment of local disease with surgery, radiation therapy, or both, and the treatment of systemic disease with cytotoxic chemotherapy, endocrine therapy, biologic therapy, or combinations of these. The NCCN Guidelines specific to management of large clinical stage II and III tumors are discussed in this article. These guidelines are the work of the members of the NCCN Breast Cancer Panel. Expert medical clinical judgment is required to apply these guidelines in the context of an individual patient to provide optimal care. Although not stated at every decision point of the guidelines, patient participation in prospective clinical trials is the preferred option of treatment for all stages of breast cancer.
    Journal of the National Comprehensive Cancer Network: JNCCN 04/2014; 12(4):542-90. · 4.24 Impact Factor
  • Cancer Research 03/2014; 73(24 Supplement):PD6-4-PD6-4. DOI:10.1158/0008-5472.SABCS13-PD6-4 · 9.28 Impact Factor
  • Cancer Research 03/2014; 73(24 Supplement):P1-08-11-P1-08-11. DOI:10.1158/0008-5472.SABCS13-P1-08-11 · 9.28 Impact Factor
  • Cancer Research 03/2014; 73(24 Supplement):P1-04-01-P1-04-01. DOI:10.1158/0008-5472.SABCS13-P1-04-01 · 9.28 Impact Factor
  • Cancer Research 03/2014; 73(24 Supplement):S5-07-S5-07. DOI:10.1158/0008-5472.SABCS13-S5-07 · 9.28 Impact Factor
  • Cancer Research 03/2014; 73(24 Supplement):S3-02-S3-02. DOI:10.1158/0008-5472.SABCS13-S3-02 · 9.28 Impact Factor
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    ABSTRACT: Evidence-based guidelines for long-term follow-up of early-stage breast cancer patients developed by oncology societies in the United States and Europe recommend that breast cancer survivors undergo regular evaluation with history and physical examination, as well as annual mammography. Routine blood tests, circulating tumor markers, and/or surveillance imaging studies beyond mammography are not recommended in the absence of concerning symptoms or physical examination findings because of lack of supportive clinical evidence. Despite these guidelines, studies have shown that 20% to 40% of oncologists assess serum tumor markers as part of routine monitoring of early-stage breast cancer patients. As part of efforts to both address the financial challenges confronting the health-care system and optimize patient outcomes, the American Society of Clinical Oncology's Cost of Care Task Force identified adherence to breast cancer surveillance guidelines as an opportunity to improve care and reduce cost. However, these recommendations are based on trials done in an era of outdated technology and limited therapeutic options. It is possible that recent improvements in diagnostics and treatments could make earlier detection of recurrent disease important for improving both survival and quality of life outcomes. Research is necessary to further inform optimal breast cancer follow-up strategies, which could impact these recommendations. At this time, outside of well-conducted clinical trials, there is no role for ordering routine serial blood or imaging tests in monitoring for recurrence in early-stage breast cancer patients.
    CancerSpectrum Knowledge Environment 03/2014; 106(5). DOI:10.1093/jnci/dju034 · 14.07 Impact Factor
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    ABSTRACT: Personalized medicine is increasingly being employed across many areas of clinical practice, as genes associated with specific diseases are discovered and targeted therapies are developed. Mobile apps are also beginning to be used in medicine with the aim of providing a personalized approach to disease management. In some areas of medicine, patient-tailored risk prediction and treatment are applied routinely in the clinic, whereas in other fields, more work is required to translate scientific advances into individualized treatment. In this forum article, we asked specialists in oncology, neurology, endocrinology and mobile health technology to discuss where we are in terms of personalized medicine, and address their visions for the future and the challenges that remain in their respective fields.
    BMC Medicine 02/2014; 12(1):37. DOI:10.1186/1741-7015-12-37 · 7.28 Impact Factor
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    ABSTRACT: Aromatase inhibitors (AI), which are used to treat breast cancer, inhibit estrogen production in postmenopausal women. AI-associated musculoskeletal symptoms (AIMSS) occur in approximately half of treated women, and lead to treatment discontinuation in 20-30%. The etiology may be due in part to estrogen deprivation. In premenopausal women, lower estrogen levels have been associated with increased pain, as well as with impairment of descending pain inhibitory pathways, which may be a risk factor for developing chronic pain. We prospectively tested whether AI-induced estrogen deprivation alters pain sensitivity, thereby increasing the risk of developing AIMSS. Fifty postmenopausal breast cancer patients underwent pressure pain testing and conditioned pain modulation (CPM) assessment prior to AI initiation and after 3 and 6 months. At baseline, 26 of 40 (65%) assessed patients demonstrated impaired CPM, which was greater in those who had previously received chemotherapy (p=0.006). No statistically significant change in pressure pain threshold or CPM was identified following estrogen deprivation. In addition, there was no association with either measure of pain sensitivity and change in patient-reported pain with AI therapy. AIMSS are not likely due to decreased pain threshold or impaired CPM prior to treatment initiation, or to effects of estrogen depletion on pain sensitivity. Clinicaltrials.gov NCT01814397. This article presents our findings of the effect of estrogen deprivation on objective measures of pain sensitivity. In postmenopausal women, medication-induced estrogen depletion did not result in an identifiable change in pressure pain threshold or conditioned pain modulation. Impaired conditioned pain modulation may be associated with chemotherapy.
    The journal of pain: official journal of the American Pain Society 01/2014; DOI:10.1016/j.jpain.2014.01.487 · 4.22 Impact Factor
  • Costanza Paoletti, Daniel F Hayes
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    ABSTRACT: Tumor biomarker tests are critical to implementation of personalized medicine for patients at risk for or affected by breast cancer. A tumor biomarker test must have high analytical validity and clinical utility to be used to guide clinical care in standard practice. Few tumor biomarkers meet these high standards. These include germline DNA single-nucleotide polymorphisms in the BRCA1 and -2 genes to determine high risk in unaffected women, selected tissue-based markers to determine prognosis and predict benefit from therapy, and circulating MUC1, CEA and perhaps tumor cells to monitor patients with metastatic disease. Efforts to discover biomarkers that predict therapeutic toxicity are promising but not yet successful. Further research is needed to enhance the number of tumor biomarker tests so that patients with breast cancer can get the correct treatment at the appropriate time.
    Annual review of medicine 01/2014; 65:95-110. DOI:10.1146/annurev-med-070912-143853 · 9.94 Impact Factor

Publication Stats

22k Citations
3,267.87 Total Impact Points

Institutions

  • 2001–2015
    • Concordia University–Ann Arbor
      Ann Arbor, Michigan, United States
    • Washington DC VA Medical Center
      Washington, Washington, D.C., United States
  • 2003–2013
    • University of Michigan
      • • Department of Internal Medicine
      • • Division of Hematology and Oncology
      Ann Arbor, Michigan, United States
  • 2012
    • American Society of Clinical Oncology
      Alexandria, Virginia, United States
    • Comprehensive Cancer Centers of Nevada
      Las Vegas, Nevada, United States
  • 2010
    • University of Utah
      Salt Lake City, Utah, United States
  • 2004–2010
    • Indiana University-Purdue University Indianapolis
      • Department of Medicine
      Indianapolis, Indiana, United States
    • University of Texas MD Anderson Cancer Center
      Houston, Texas, United States
  • 2009
    • Loyola University Medical Center
      Maywood, Illinois, United States
    • Brigham and Women's Hospital
      • Department of Pathology
      Boston, MA, United States
    • National Cancer Institute (USA)
      • Biometrics Research Branch
      Maryland, United States
  • 2007
    • Fred Hutchinson Cancer Research Center
      Seattle, Washington, United States
  • 1998–2007
    • Georgetown University
      • Lombardi Cancer Center
      Washington, Washington, D.C., United States
  • 2006
    • Johns Hopkins Medicine
      • Department of Medicine
      Baltimore, Maryland, United States
  • 2005
    • Stanford Medicine
      • Stanford Emergency Department (Hospitals and Clinics)
      Stanford, California, United States
    • University of North Carolina at Chapel Hill
      • Lineberger Comprehensive Cancer Center
      Chapel Hill, NC, United States
  • 2000–2002
    • North Shore Medical Center
      Salem, Massachusetts, United States
  • 1986–1999
    • Dana-Farber Cancer Institute
      • • Department of Radiation Oncology
      • • Lank Center for Genitourinary Oncology
      Boston, Massachusetts, United States
  • 1996
    • Beth Israel Deaconess Medical Center
      Boston, Massachusetts, United States
  • 1990–1993
    • Harvard Medical School
      • • Department of Pathology
      • • Department of Radiation Oncology
      Boston, Massachusetts, United States
  • 1987
    • University of Massachusetts Boston
      Boston, Massachusetts, United States