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Cogan JC, Raghunathan RR, Beauchemin MP, Accordino MK, Huang Y, Elkin EB, Melamed A, Wright JD, Hershman DL. New and Persistent Sedative-Hypnotic Use After Adjuvant Chemotherapy for Breast Cancer. J Natl Cancer Inst 2022; 114:1698-1705. [PMID: 36130058 PMCID: PMC9745429 DOI: 10.1093/jnci/djac170] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Revised: 04/19/2022] [Accepted: 08/23/2022] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND Sedative-hypnotic medications are used to treat chemotherapy-related nausea, anxiety, and insomnia. However, prolonged sedative-hypnotic use can lead to dependence, misuse, and increased health-care use. We aimed to estimate the rates at which patients who receive adjuvant chemotherapy for breast cancer become new persistent users of sedative-hypnotic medications, specifically benzodiazepines and nonbenzodiazepine sedative-hypnotics (Z-drugs). METHODS Using the MarketScan health-care claims database, we identified sedative-hypnotic-naïve patients who received adjuvant chemotherapy for breast cancer. Patients who filled 1 and more prescriptions during chemotherapy and 2 and more prescriptions up to 1 year after chemotherapy were classified as new persistent users. Univariate and multivariable logistic regression analyses were used to estimate odds of new persistent use and associated characteristics. RESULTS We identified 22 039 benzodiazepine-naïve patients and 23 816 Z-drug-naïve patients who received adjuvant chemotherapy from 2008 to 2017. Among benzodiazepine-naïve patients, 6159 (27.9%) filled 1 and more benzodiazepine prescriptions during chemotherapy, and 963 of those (15.6%) went on to become new persistent users. Among Z-drug-naïve patients, 1769 (7.4%) filled 1 and more prescriptions during chemotherapy, and 483 (27.3%) became new persistent users. In both groups, shorter durations of chemotherapy and receipt of opioid prescriptions were associated with new persistent use. Medicaid insurance was associated with new persistent benzodiazepine use (odds ratio = 1.88, 95% confidence interval = 1.43 to 2.47) compared with commercial or Medicare insurance. CONCLUSIONS Patients who receive sedative-hypnotic medications during adjuvant chemotherapy for breast cancer are at risk of becoming new persistent users of these medications after chemotherapy. Providers should ensure appropriate sedative-hypnotic use through tapering dosages and encouraging nonpharmacologic strategies when appropriate.
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Affiliation(s)
- Jacob C Cogan
- Division of Hematology, Oncology and Transplantation, University of Minnesota, Minneapolis, MN, USA
- Columbia University College of Physicians and Surgeons, New York, NY, USA
- Herbert Irving Comprehensive Cancer Center, New York, NY, USA
- New York Presbyterian Hospital, New York, NY, USA
| | - Rohit R Raghunathan
- Joseph L. Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Melissa P Beauchemin
- Columbia University College of Physicians and Surgeons, New York, NY, USA
- New York Presbyterian Hospital, New York, NY, USA
- Joseph L. Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Melissa K Accordino
- Columbia University College of Physicians and Surgeons, New York, NY, USA
- Herbert Irving Comprehensive Cancer Center, New York, NY, USA
- New York Presbyterian Hospital, New York, NY, USA
| | - Yongmei Huang
- Columbia University College of Physicians and Surgeons, New York, NY, USA
| | - Elena B Elkin
- Herbert Irving Comprehensive Cancer Center, New York, NY, USA
- Joseph L. Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Alexander Melamed
- Columbia University College of Physicians and Surgeons, New York, NY, USA
- Herbert Irving Comprehensive Cancer Center, New York, NY, USA
- New York Presbyterian Hospital, New York, NY, USA
| | - Jason D Wright
- Columbia University College of Physicians and Surgeons, New York, NY, USA
- Herbert Irving Comprehensive Cancer Center, New York, NY, USA
- New York Presbyterian Hospital, New York, NY, USA
| | - Dawn L Hershman
- Columbia University College of Physicians and Surgeons, New York, NY, USA
- Herbert Irving Comprehensive Cancer Center, New York, NY, USA
- New York Presbyterian Hospital, New York, NY, USA
- Joseph L. Mailman School of Public Health, Columbia University, New York, NY, USA
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Chen C, Hennessy S, Brensinger CM, Acton EK, Bilker WB, Chung SP, Dawwas GK, Horn JR, Miano TA, Pham Nguyen TP, Leonard CE. Population-based screening to detect benzodiazepine drug-drug-drug interaction signals associated with unintentional traumatic injury. Sci Rep 2022; 12:15569. [PMID: 36114250 PMCID: PMC9481644 DOI: 10.1038/s41598-022-19551-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Accepted: 08/31/2022] [Indexed: 11/08/2022] Open
Abstract
Drug interactions involving benzodiazepines and related drugs (BZDs) are increasingly recognized as a contributor to increased risk of unintentional traumatic injury. Yet, it remains unknown to what extent drug interaction triads (3DIs) may amplify BZDs' inherent injury risk. We identified BZD 3DI signals associated with increased injury rates by conducting high-throughput pharmacoepidemiologic screening of 2000-2019 Optum's health insurance data. Using self-controlled case series design, we included patients aged ≥ 16 years with an injury while using a BZD + co-dispensed medication (i.e., base pair). During base pair-exposed observation time, we identified other co-dispensed medications as candidate interacting precipitants. Within each patient, we compared injury rates during time exposed to the drug triad versus to the base pair only using conditional Poisson regression, adjusting for time-varying covariates. We calculated rate ratios (RRs) with 95% confidence intervals (CIs) and accounted for multiple estimation via semi-Bayes shrinkage. Among the 65,123 BZD triads examined, 79 (0.1%) were associated with increased injury rates and considered 3DI signals. Adjusted RRs for signals ranged from 3.01 (95% CI = 1.53-5.94) for clonazepam + atorvastatin with cefuroxime to 1.42 (95% CI = 1.00-2.02, p = 0.049) for alprazolam + hydrocodone with tizanidine. These signals may help researchers prioritize future etiologic studies to investigate higher-order BZD interactions.
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Affiliation(s)
- Cheng Chen
- Center for Real-World Effectiveness and Safety of Therapeutics, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Sean Hennessy
- Center for Real-World Effectiveness and Safety of Therapeutics, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Colleen M Brensinger
- Center for Real-World Effectiveness and Safety of Therapeutics, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Emily K Acton
- Center for Real-World Effectiveness and Safety of Therapeutics, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Translational Center of Excellence for Neuroepidemiology and Neurology Outcomes Research, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Warren B Bilker
- Center for Real-World Effectiveness and Safety of Therapeutics, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Ghadeer K Dawwas
- Center for Real-World Effectiveness and Safety of Therapeutics, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA
| | - John R Horn
- Department of Pharmacy, School of Pharmacy, University of Washington, Seattle, WA, USA
| | - Todd A Miano
- Center for Real-World Effectiveness and Safety of Therapeutics, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Thanh Phuong Pham Nguyen
- Center for Real-World Effectiveness and Safety of Therapeutics, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA
- Translational Center of Excellence for Neuroepidemiology and Neurology Outcomes Research, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Charles E Leonard
- Center for Real-World Effectiveness and Safety of Therapeutics, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA.
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Torres EL, Evoy KE, Thomas LO. Outpatient Opioid and Naloxone Prescribing Practices at an Academic Medical Center during the COVID-19 Pandemic. J Pain Palliat Care Pharmacother 2022; 36:178-186. [PMID: 35916655 DOI: 10.1080/15360288.2022.2105471] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/16/2022]
Abstract
While improving opioid safety has been a national priority, the coronavirus disease 2019 (COVID-19) pandemic has been associated with increased rates of opioid overdose. The present study characterized outpatient opioid and naloxone prescribing patterns during the COVID-19 pandemic. A retrospective chart review was conducted of adult patients receiving opioid therapy between August 2020 through October 2020 from outpatient clinics within a Texas health system. The primary outcome was naloxone co-prescription during the study period or within the year prior. During the study period, 1,368 patients received an opioid prescription, most of which were prescribed for chronic pain treatment (63.0%). Most opioid prescriptions (91.5%) were written for < 50 MME/day. For prescriptions written for acute pain, 78% were written for ≤ 10 days supply. While 31.1% of patients received gabapentinoid prescriptions, few (7.9%) received benzodiazepine or Z-hypnotic prescriptions. Twenty-two (1.6%) patients were co-prescribed naloxone. In this study, naloxone was rarely prescribed for outpatients receiving opioid prescriptions during the COVID-19 pandemic. Health systems should continue to prioritize adherence to evidence-based clinical guidelines and increase access to naloxone.
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Acton EK, Hennessy S, Brensinger CM, Bilker WB, Miano TA, Dublin S, Horn JR, Chung S, Wiebe DJ, Willis AW, Leonard CE. Opioid Drug-Drug-Drug Interactions and Unintentional Traumatic Injury: Screening to Detect Three-Way Drug Interaction Signals. Front Pharmacol 2022; 13:845485. [PMID: 35620282 PMCID: PMC9127150 DOI: 10.3389/fphar.2022.845485] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Accepted: 04/18/2022] [Indexed: 12/02/2022] Open
Abstract
Growing evidence suggests that drug interactions may be responsible for much of the known association between opioid use and unintentional traumatic injury. While prior research has focused on pairwise drug interactions, the role of higher-order (i.e., drug-drug-drug) interactions (3DIs) has not been examined. We aimed to identify signals of opioid 3DIs with commonly co-dispensed medications leading to unintentional traumatic injury, using semi-automated high-throughput screening of US commercial health insurance data. We conducted bi-directional, self-controlled case series studies using 2000-2015 Optum Data Mart database. Rates of unintentional traumatic injury were examined in individuals dispensed opioid-precipitant base pairs during time exposed vs unexposed to a candidate interacting precipitant. Underlying cohorts consisted of 16-90-year-olds with new use of opioid-precipitant base pairs and ≥1 injury during observation periods. We used conditional Poisson regression to estimate rate ratios adjusted for time-varying confounders, and semi-Bayes shrinkage to address multiple estimation. For hydrocodone, tramadol, and oxycodone (the most commonly used opioids), we examined 16,024, 8185, and 9330 drug triplets, respectively. Among these, 75 (0.5%; hydrocodone), 57 (0.7%; tramadol), and 42 (0.5%; oxycodone) were significantly positively associated with unintentional traumatic injury (50 unique base precipitants, 34 unique candidate precipitants) and therefore deemed potential 3DI signals. The signals found in this study provide valuable foundations for future research into opioid 3DIs, generating hypotheses to motivate crucially needed etiologic investigations. Further, this study applies a novel approach for 3DI signal detection using pharmacoepidemiologic screening of health insurance data, which could have broad applicability across drug classes and databases.
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Affiliation(s)
- Emily K. Acton
- Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Translational Center of Excellence for Neuroepidemiology and Neurology Outcomes Research, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Sean Hennessy
- Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, United States
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Colleen M. Brensinger
- Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Warren B. Bilker
- Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Todd A. Miano
- Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Sascha Dublin
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, WA, United States
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, United States
| | - John R. Horn
- Department of Pharmacy, School of Pharmacy, University of Washington, Seattle, WA, United States
| | - Sophie Chung
- AthenaHealth, Inc., Watertown, MA, United States
| | - Douglas J. Wiebe
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, United States
- Penn Injury Science Center, University of Pennsylvania, Philadelphia, PA, United States
| | - Allison W. Willis
- Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Translational Center of Excellence for Neuroepidemiology and Neurology Outcomes Research, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, United States
| | - Charles E. Leonard
- Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, United States
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Bergen AW, Cil G, Sargent LJ, Dave CV. Frailty Risks of Prescription Analgesics and Sedatives across Frailty Models: the Health and Retirement Study. Drugs Aging 2022; 39:377-387. [PMID: 35590086 DOI: 10.1007/s40266-022-00941-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/02/2022] [Indexed: 11/03/2022]
Abstract
INTRODUCTION Limited evidence for incident frailty risks associated with prescription analgesics and sedatives in older (≥ 65 years) community-living adults prompted a more comprehensive investigation. METHODS We used data from older Health and Retirement Study respondents and three frailty models (frailty index, functional domain, frailty phenotype with 8803, 10,470, and 6850 non-frail individuals, respectively) and estimated sub-hazard ratios of regular prescription drug use (co-use, analgesic use, and sedative use), by frailty model. We addressed confounding with covariate adjustment and propensity score matching approaches. RESULTS The baseline prevalence of analgesic and sedative co-use, analgesic use, and sedative use among non-frail respondents was 1.8%, 12.8%, and 4.7% for the frailty index model, 4.2%, 16.2%, and 5.3% for the functional domain model, and 4.3%, 15.4%, and 6.1% for the frailty phenotype model, respectively. Cumulative frailty incidence over 10 years was 39.3%, 36.1%, and 14.2% for frailty index, functional domain, and frailty phenotype models, respectively; covariate-adjusted sub-hazard ratio estimates were 2.00 (1.63-2.45), 1.83 (1.57-2.13), and 1.68 (1.21-2.33) for co-use; 1.72 (1.56-1.89), 1.38 (1.27-1.51), and 1.51 (1.27-1.79) for analgesic use; and 1.46 (1.24-1.72), 1.25 (1.07-1.46), and 1.31 (0.97-1.76) for sedative use. Frailty risk ranking (co-use > analgesic use > sedative use) persisted across all model sensitivity analyses. DISCUSSION Consistently significant frailty risk estimates of regular prescription analgesic and sedative co-use and of prescription analgesic use support existing clinical, public health, and regulatory guidance on opioid and benzodiazepine co-prescription, on opioid prescription, and on NSAID prescription. Frailty phenotype measurement administration limited power to detect significant frailty risks. Research into specific pharmaceutical exposures and comparison of results across cohorts will be required to contribute to the deprescribing evidence base.
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Affiliation(s)
| | - Gulcan Cil
- Oregon Research Institute, Eugene, OR, USA
| | - Lana J Sargent
- School of Nursing, Virginia Commonwealth University, Richmond, VA, USA.,Geriatric Pharmacotherapy Program, School of Pharmacy, Virginia Commonwealth University, Richmond, VA, USA
| | - Chintan V Dave
- Center for Pharmacoepidemiology and Treatment Science, Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ, USA.,Department of Pharmacy Practice and Administration, Ernest Mario School of Pharmacy, Rutgers University, Piscataway, NJ, USA
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Cogan JC, Raghunathan RR, Beauchemin MP, Accordino MK, Elkin EB, Melamed A, Wright JD, Hershman DL. New and persistent controlled substance use among patients undergoing mastectomy and reconstructive surgery. Breast Cancer Res Treat 2021; 189:445-454. [PMID: 34089118 DOI: 10.1007/s10549-021-06275-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2021] [Accepted: 05/27/2021] [Indexed: 10/21/2022]
Abstract
PURPOSE Prolonged use of controlled substances can place patients at increased risk of dependence and complications. Women who have mastectomy and reconstructive surgery (M + R) may be vulnerable to becoming new persistent users (NPUs) of opioid and sedative-hypnotic medications. METHODS Using the MarketScan health-care claims database, we identified opioid- and sedative-hypnotic-naïve women who had M + R from 2008 to 2017. Women who filled ≥ 1 peri-operative prescription and ≥ 2 post-operative prescriptions within one year after surgery were classified as NPUs. Univariate and multivariable logistic regression analyses were used to estimate rates of new persistent use and predictive factors. Risk summary scores were created based on the sum of associated factors. RESULTS We evaluated 23,025 opioid-naïve women and 25,046 sedative-hypnotic-naïve women. We found that 17,174 opioid-naïve women filled a peri-operative opioid prescription, and of those, 2962 (17.2%) became opioid NPUs post-operatively. Additionally, 9426 sedative-hypnotic-naïve women filled a peri-operative sedative-hypnotic prescription, and of those, 1612 (17.1%) became sedative-hypnotic NPUs. Development of new persistent sedative-hypnotic use was associated with age ≤ 49 [OR 1.77 (95% CI 1.40-2.24)] and age 50-64 [1.60 (1.27-2.03)] compared to age ≥ 65; Medicaid insurance [2.34 (1.40-3.90)]; southern residence [1.42 (1.22-1.64)]; breast cancer diagnosis [2.24 (1.28-3.91)]; and chemotherapy [2.17 (1.94-2.42)]. Risk of NPU increased with higher risk score. Women with ≥ 3 of these risk factors were three times more likely to become sedative-hypnotic NPUs than patients with 0 or 1 factors [2.94 (2.51-3.43)]. Comparable findings were seen regarding new persistent opioid use. CONCLUSION Women who have M + R are at risk of developing both new persistent opioid and new persistent sedative-hypnotic use. A patient's risk of becoming an NPU increases as their number of risk factors increases. Non-pharmacologic strategies are needed to manage pain and anxiety following cancer-related surgery.
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Affiliation(s)
- Jacob C Cogan
- Columbia University College of Physicians and Surgeons, New York, USA.,Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, USA.,NewYork-Presbyterian Hospital, New York, USA
| | - Rohit R Raghunathan
- Joseph L. Mailman School of Public Health, Columbia University, New York, USA
| | - Melissa P Beauchemin
- Columbia University College of Physicians and Surgeons, New York, USA.,Joseph L. Mailman School of Public Health, Columbia University, New York, USA.,NewYork-Presbyterian Hospital, New York, USA
| | - Melissa K Accordino
- Columbia University College of Physicians and Surgeons, New York, USA.,Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, USA.,NewYork-Presbyterian Hospital, New York, USA
| | - Elena B Elkin
- Joseph L. Mailman School of Public Health, Columbia University, New York, USA.,Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, USA
| | - Alexander Melamed
- Columbia University College of Physicians and Surgeons, New York, USA.,Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, USA.,NewYork-Presbyterian Hospital, New York, USA
| | - Jason D Wright
- Columbia University College of Physicians and Surgeons, New York, USA.,Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, USA.,NewYork-Presbyterian Hospital, New York, USA
| | - Dawn L Hershman
- Columbia University College of Physicians and Surgeons, New York, USA. .,Joseph L. Mailman School of Public Health, Columbia University, New York, USA. .,Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, USA. .,NewYork-Presbyterian Hospital, New York, USA.
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