Karen M Kuntz

Minnesota Department of Health, Saint Paul, Minnesota, United States

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Publications (210)2009.55 Total impact

  • Hawre Jalal · Jeremy D Goldhaber-Fiebert · Karen M Kuntz ·
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    ABSTRACT: Decision makers often desire both guidance on the most cost-effective interventions given current knowledge and also the value of collecting additional information to improve the decisions made (i.e., from value of information [VOI] analysis). Unfortunately, VOI analysis remains underused due to the conceptual, mathematical, and computational challenges of implementing Bayesian decision-theoretic approaches in models of sufficient complexity for real-world decision making. In this study, we propose a novel practical approach for conducting VOI analysis using a combination of probabilistic sensitivity analysis, linear regression metamodeling, and unit normal loss integral function-a parametric approach to VOI analysis. We adopt a linear approximation and leverage a fundamental assumption of VOI analysis, which requires that all sources of prior uncertainties be accurately specified. We provide examples of the approach and show that the assumptions we make do not induce substantial bias but greatly reduce the computational time needed to perform VOI analysis. Our approach avoids the need to analytically solve or approximate joint Bayesian updating, requires only one set of probabilistic sensitivity analysis simulations, and can be applied in models with correlated input parameters. © The Author(s) 2015.
    Medical Decision Making 04/2015; 35(5). DOI:10.1177/0272989X15578125 · 3.24 Impact Factor
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    ABSTRACT: An increasing proportion of breast cancer patients undergo contralateral prophylactic mastectomy (CPM) to reduce their risk of contralateral breast cancer (CBC). Our goal was to evaluate CBC risk perception changes over time among breast cancer patients. We conducted a prospective, longitudinal study of women with newly diagnosed unilateral breast cancer. Patients completed a survey before and approximately 2 years after treatment. Survey questions used open-ended responses or 5-point Likert scale scoring (e.g., 5 = very likely, 1 = not at all likely). A total of 74 women completed the presurgical treatment survey, and 43 completed the postsurgical treatment survey. Baseline characteristics were not significantly different between responders and nonresponders of the follow-up survey. The mean estimated 10-year risk of CBC was 35.7 % on the presurgical treatment survey and 13.8 % on the postsurgical treatment survey (p < 0.001). The perceived risks of developing cancer in the same breast and elsewhere in the body significantly decreased between surveys. Both CPM and non-CPM (breast-conserving surgery or unilateral mastectomy) patients' perceived risk of CBC significantly decreased from pre- to postsurgical treatment surveys. Compared with non-CPM patients, CPM patients had a significantly lower perceived 10-year risk of CBC (5.8 vs. 17.3 %, p = 0.046) on postsurgical treatment surveys. The perceived risk of CBC significantly attenuated over time for both CPM and non-CPM patients. These data emphasize the importance of early physician counseling and improvement in patient education to provide women with accurate risk information before they make surgical treatment decisions.
    Annals of Surgical Oncology 03/2015; 22(12). DOI:10.1245/s10434-015-4442-2 · 3.93 Impact Factor
  • Article: Response.
    Pamela R Portschy · Karen M Kuntz · Todd M Tuttle ·

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    ABSTRACT: Clinical practice guidelines should be based on the best scientific evidence derived from systematic reviews of primary research. However, these studies often do not provide evidence needed by guideline development groups to evaluate the tradeoffs between benefits and harms. In this article, the authors identify 4 areas where models can bridge the gaps between published evidence and the information needed for guideline development applying new or updated information on disease risk, diagnostic test properties, and treatment efficacy; exploring a more complete array of alternative intervention strategies; assessing benefits and harms over a lifetime horizon; and projecting outcomes for the conditions for which the guideline is intended. The use of modeling as an approach to bridge these gaps (provided that the models are high-quality and adequately validated) is considered. Colorectal and breast cancer screening are used as examples to show the utility of models for these purposes. The authors propose that a modeling study is most useful when strong primary evidence is available to inform the model but critical gaps remain between the evidence and the questions that the guideline group must address. In these cases, model results have a place alongside the findings of systematic reviews to inform health care practice and policy.
    Annals of internal medicine 12/2014; 161(11):812-8. DOI:10.7326/M14-0845 · 17.81 Impact Factor
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    ABSTRACT: Researchers are actively pursuing the development of a new non-invasive test (NIT) for colorectal cancer (CRC) screening as an alternative to fecal occult blood tests (FOBTs). The majority of pilot studies focus on the detection of invasive CRC rather than precursor lesions (i.e., adenomas). We aimed to explore the relevance of adenoma detection for the viability of an NIT for CRC screening by considering a hypothetical test that does not detect adenomas beyond chance.We used the Simulation Model of Colorectal Cancer (SimCRC) to estimate the effectiveness of CRC screening and the lifetime costs (payers' perspective) for a cohort of US 50-year-olds to whom CRC screening is offered from age 50-75. We compared annual screening with guaiac and immunochemical FOBTs (with sensitivities up to 70% and 24% for CRC and adenomas, respectively) to annual screening with a hypothetical NIT (sensitivity of 90% for CRC, no detection of adenomas beyond chance, specificity and cost similar to FOBTs).Screening with the NIT was not more effective, but was 29-44% more costly than screening with FOBTs. The findings were robust to varying the screening interval, the NIT's sensitivity for CRC, adherence rates favoring the NIT, and the NIT's unit cost. A comparative modelling approach using a model that assumes a shorter adenoma dwell time (MISCAN-COLON) confirmed the superiority of the immunochemical FOBT over a NIT with no ability to detect adenomas.Information on adenoma detection is crucial to determine whether a new NIT is a viable alternative to FOBTs for CRC screening. Current evidence thus lacks an important piece of information to identify marker candidates that hold real promise and deserve further (large-scale) evaluation. This article is protected by copyright. All rights reserved.
    International Journal of Cancer 12/2014; 136(12). DOI:10.1002/ijc.29343 · 5.09 Impact Factor
  • Eric Jutkowitz · Hyon K Choi · Laura T Pizzi · Karen M Kuntz ·
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    ABSTRACT: Gout is the most common inflammatory arthritis in the United States.
    Annals of internal medicine 11/2014; 161(9):617-26. DOI:10.7326/M14-0227 · 17.81 Impact Factor
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    ABSTRACT: Purpose: Relative survival, as reported by the Surveillance, Epidemiology, and End Results (SEER) Program, represents cancer survival in the absence of other causes of death. Often, cancer Markov models have a distant metastasis state, a state not directly observed in SEER, from which cancer deaths are presumed to occur. The aim of this research is to use a novel approach to calibrate the transition probabilities to and from an unobserved state of a Markov model to fit a relative survival curve. Methods: We modeled relative survival through a three-piecewise Markov model (i.e., with a specific Markov chain within each specified pieces) for stage 3 colorectal cancer patients. For each piece we used a constant transition matrix with three states: 1) recurrence free, 2) metastatic recurrence and 3) dead from cancer. We estimated the optimal cutoff time points using a Bayesian Markov chain Monte Carlo (MCMC) change-point model. This technique allowed us to estimate the time points at which the slope of the relative survival changes. We calibrated the transition probabilities using a two-step iterative convex optimization algorithm previously published. The dynamics of the disease can be defined as xt+1= xtM, where xt+1 is the state vector that results from the transformation given by the monthly transition matrix M. The matrix M is a piecewise block-diagonal matrix that includes in each piece a block-diagonal matrix for each Markov chain. Results: We applied our method to calibrate a Markov model to fit a relative survival curve for stage 3 colorectal cancer patients younger than 75 years old. We compared our piecewise calibration method to a single-piece approach (i.e., a Markov chain). While the single-piece converged faster, the piecewise method improved the goodness of fit by 60%. The mean of the change points estimated from the Bayesian change-point model was at months 3 and 24 (see figure). The observed, and the piecewise and single-piece calibrated relative survival curves are shown in the figure. Conclusions: By estimating the change points in the relative survival curve we were able to find the optimal transition probabilities for a piecewise Markov model that allowed us to impose a particular structure defined by the progression of the disease. We propose a piecewise calibration method that produces more accurate solutions compared to a single-piece approach.
    The 36th Annual Meeting of the Society for Medical Decision Making; 10/2014
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    Fernando Alarid-Escudero · Karen M Kuntz ·
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    ABSTRACT: Purpose: Clinical trials often report treatment efficacy in terms of the reduction of all-cause mortality [i.e., overall hazard ratio (OHR)], and not the reduction in disease-specific mortality [i.e., disease-specific hazard ratio (DSHR)]. Using an OHR to reduce all-cause mortality beyond the time horizon of the clinical trial may introduce bias if the relative proportion of other-cause mortality increases with age. We aim to quantify this bias. Methods: We simulated a hypothetical cohort of patients with a generic disease that increases the age-, sex-, and race-specific mortality rate (μASR) by a constant additive disease-specific rate (μDis). We assumed a DSHR of 0.75 (unreported) and an OHR of 0.80 (reported, derived from DSHR and assumptions of clinical trial population). We quantified the bias in terms of the difference in life expectancy (LE) gains with treatment between using an OHR approach to reduce all-cause mortality over a lifetime [(μASR+ μDis)xOHR] compared with using a DSHR approach to reduce disease-specific mortality [μASR+(μDis)xDSHR]. We varied the starting age of the cohort from 40 to 70 years old. Results: The OHR bias increases as DSHR decreases and with younger starting ages of the cohort. For a cohort of 60-year-old sick patients, the mortality rate under OHR approach crosses μASR at the age of 90 (see figure) and LE gain is overestimated by 0.6 years (a 3.7% increase). We also used OHR as an estimate of DSHR [μASR+(μDis) × OHR] (as the latter is not often reported). This resulted in a slight shift in the mortality rate compared to the DSHR approach (see figure), yielding in an underestimation of the LE gain. Conclusions: The use of an OHR approach to model treatment effectiveness beyond the time horizon of the trial overestimates the effectiveness of the treatment. Under an OHR approach, it is possible that sick individuals at some point will face a lower mortality rate compared with healthy individuals. We recommend either deriving a DSHR from trials and using the DSHR approach, or using the OHR as an estimate of DSHR in the model, which is a conservative assumption.
    The 36th Annual Meeting of the Society for Medical Decision Making, Miami, FL; 10/2014
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    ABSTRACT: Objective To determine whether, given a limited budget, a state's low-income uninsured population would have greater benefit from a colorectal cancer (CRC) screening program using colonoscopy or fecal immunochemical testing (FIT).Data Sources/Study SettingSouth Carolina's low-income, uninsured population.Study DesignComparative effectiveness analysis using microsimulation modeling to estimate the number of individuals screened, CRC cases prevented, CRC deaths prevented, and life-years gained from a screening program using colonoscopy versus a program using annual FIT in South Carolina's low-income, uninsured population. This analysis assumed an annual budget of $1 million and a budget availability of 2 years as a base case.Principal FindingsThe annual FIT screening program resulted in nearly eight times more individuals being screened, and more important, approximately four times as many CRC deaths prevented and life-years gained than the colonoscopy screening program. Our results were robust for assumptions concerning economic perspective and the target population, and they may therefore be generalized to other states and populations.ConclusionsA FIT screening program will prevent more CRC deaths than a colonoscopy-based program when a state's budget for CRC screening supports screening of only a fraction of the target population.
    Health Services Research 10/2014; 50(3). DOI:10.1111/1475-6773.12246 · 2.78 Impact Factor
  • Pamela R Portschy · Karen M Kuntz · Todd M Tuttle ·
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    ABSTRACT: Background: Contralateral prophylactic mastectomy (CPM) rates have substantially increased in recent years and may reflect an exaggerated perceived benefit from the procedure. The objective of this study was to evaluate the magnitude of the survival benefit of CPM for women with unilateral breast cancer. Methods: We developed a Markov model to simulate survival outcomes after CPM and no CPM among women with stage I or II breast cancer without a BRCA mutation. Probabilities for developing contralateral breast cancer (CBC), dying from CBC, dying from primary breast cancer, and age-specific mortality rates were estimated from published studies. We estimated life expectancy (LE) gain, 20-year overall survival, and disease-free survival with each intervention strategy among cohorts of women defined by age, estrogen receptor (ER) status, and stage of cancer. Results: Predicted LE gain from CPM ranged from 0.13 to 0.59 years for women with stage I breast cancer and 0.08 to 0.29 years for those with stage II breast cancer. Absolute 20-year survival differences ranged from 0.56% to 0.94% for women with stage I breast cancer and 0.36% to 0.61% for women with stage II breast cancer. CPM was more beneficial among younger women, stage I, and ER-negative breast cancer. Sensitivity analyses yielded a maximum 20-year survival difference with CPM of only 1.45%. Conclusions: The absolute 20-year survival benefit from CPM was less than 1% among all age, ER status, and cancer stage groups. Estimates of LE gains and survival differences derived from decision models may provide more realistic expectations of CPM.
    JNCI Journal of the National Cancer Institute 08/2014; 106(8). DOI:10.1093/jnci/dju160 · 12.58 Impact Factor
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    ABSTRACT: Background: Harms and benefits of cancer screening depend on age and comorbid conditions, but reliable estimates are lacking. Objective: To estimate the harms and benefits of cancer screening by age and comorbid conditions to inform decisions about screening cessation. Design: Collaborative modeling with 7 cancer simulation models and common data on average and comorbid condition level-specific life expectancy. Setting: U. S. population. Patients: U. S. cohorts aged 66 to 90 years in 2010 with average health or 1 of 4 comorbid condition levels: none, mild, moderate, or severe. Intervention: Mammography, prostate-specific antigen testing, or fecal immunochemical testing. Measurements: Lifetime cancer deaths prevented and life-years gained (benefits); false-positive test results and overdiagnosed cancer cases (harms). For each comorbid condition level, the age at which harms and benefits of screening were similar to that for persons with average health having screening at age 74 years. Results: Screening 1000 women with average life expectancy at age 74 years for breast cancer resulted in 79 to 96 (range across models) false-positive results, 0.5 to 0.8 overdiagnosed cancer cases, and 0.7 to 0.9 prevented cancer deaths. Although absolute numbers of harms and benefits differed across cancer sites, the ages at which to cease screening were consistent across models and cancer sites. For persons with no, mild, moderate, and severe comorbid conditions, screening until ages 76, 74, 72, and 66 years, respectively, resulted in harms and benefits similar to average-health persons. Limitation: Comorbid conditions influenced only life expectancy. Conclusion: Comorbid conditions are an important determinant of harms and benefits of screening. Estimates of screening benefits and harms by comorbid condition can inform discussions between providers and patients about personalizing screening cessation decisions.
    Annals of internal medicine 07/2014; 161(2):104-12. DOI:10.7326/M13-2867 · 17.81 Impact Factor
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    ABSTRACT: OBJECTIVE: The study objective was to evaluate and update the safety data from randomized controlled trials of tumor necrosis factor inhibitors in patients treated for rheumatoid arthritis. METHODS: A systematic literature search was conducted from 1990 to May 2013. All studies included were randomized, double-blind, controlled trials of patients with rheumatoid arthritis that evaluated adalimumab, certolizumab pegol, etanercept, golimumab, or infliximab treatment. The serious adverse events and discontinuation rates were abstracted, and risk estimates were calculated by Peto odds ratios (ORs). RESULTS: Forty-four randomized controlled trials involving 11,700 subjects receiving tumor necrosis factor inhibitors and 5901 subjects receiving placebo or traditional disease-modifying antirheumatic drugs were included. Tumor necrosis factor inhibitor treatment as a group was associated with a higher risk of serious infection (OR, 1.42; 95% confidence interval [CI], 1.13-1.78) and treatment discontinuation due to adverse events (OR, 1.23; 95% CI, 1.06-1.43) compared with placebo and traditional disease-modifying anti- rheumatic drug treatments. Specifically, patients taking adalimumab, certolizumab pegol, and infliximab had an increased risk of serious infection (OR, 1.69, 1.98, and 1.63, respectively) and showed an increased risk of discontinuation due to adverse events (OR, 1.38, 1.67, and 2.04, respectively). In contrast, patients taking etanercept had a decreased risk of discontinuation due to adverse events (OR, 0.72; 95% CI, 0.55- 0.93). Although ORs for malignancy varied across the different tumor necrosis factor inhibitors, none reached statistical significance. CONCLUSIONS: These meta-analysis updates of the comparative safety of tumor necrosis factor inhibitors suggest a higher risk of serious infection associated with adalimumab, certolizumab pegol, and infliximab, which seems to contribute to higher rates of discontinuation. In contrast, etanercept use showed a lower rate of discontinuation. These data may help guide clinical comparative decision making in the management of rheumatoid arthritis.
    The American Journal of Medicine 06/2014; 127(12). DOI:10.1016/j.amjmed.2014.06.012 · 5.00 Impact Factor
  • Taehwan Park · Karen M. Kuntz ·
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    ABSTRACT: Objective To compare the cost-effectiveness of alternate treatment strategies using second-generation antipsychotics (SGAs) for patients with schizophrenia. Methods We developed a Markov model to estimate the costs and quality-adjusted life-years (QALYs) for different sequences of treatments for 40-year-old patients with schizophrenia. We considered first-line treatment with one of the four SGAs: olanzapine (OLZ), risperidone (RSP), quetiapine (QTP), and ziprasidone (ZSD). Patients could switch to another of these antipsychotics as second-line therapy, and only clozapine (CLZ) was allowed as third-line treatment. We derived parameter estimates from the Clinical Antipsychotic Trial of Intervention Effectiveness (CATIE) study and published sources. Results The ZSD-QTP strategy (first-line treatment with ZSD, change to QTP if ZSD is discontinued, and switch to CLZ if QTP is discontinued) was most costly while yielding the greatest QALYs, with an incremental cost-effective ratio (ICER) of $542,500 per QALY gained compared with the ZSD-RSP strategy. However, the ZSD-RSP strategy had an ICER of $5,200/QALY gained versus the RSP-ZSD strategy and had the greatest probability of being cost-effective given a willingness-to-pay threshold between $50,000 and $100,000 per QALY. All other treatment strategies were more costly and less effective than another strategy or combination of other strategies. Results varied by different time horizons adopted. Conclusions The ZSD-RSP strategy was most cost-effective at a willingness-to-pay threshold between $5,200 and $542,500 per QALY. Our results should be interpreted with caution because they are based largely on the CATIE trial with potentially limited generalizability to all patient populations and doses of SGAs used in practice.
    Value in Health 06/2014; 17(4). DOI:10.1016/j.jval.2014.02.008 · 3.28 Impact Factor
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    ABSTRACT: Treatment options for colorectal cancer (CRC) have improved substantially over the past 25 years. Measuring the impact of these improvements on survival outcomes is challenging, however, against the background of overall survival gains from advancements in the prevention, screening, and treatment of other conditions. Relative survival is a metric that accounts for these concurrent changes, allowing assessment of changes in CRC survival. We describe stage- and location-specific trends in relative survival after CRC diagnosis. We analyzed survival outcomes for 233965 people in the Surveillance Epidemiology and End Results (SEER) program who were diagnosed with CRC between January 1, 1975, and December 31, 2003. All models were adjusted for sex, race (black vs white), age at diagnosis, time since diagnosis, and diagnosis year. We estimated the proportional difference in survival for CRC patients compared with overall survival for age-, sex-, race-, and period-matched controls to account for concurrent changes in overall survival using two-sided Wald tests. We found statistically significant reductions in excess hazard of mortality from CRC in 2003 relative to 1975, with excess hazard ratios ranging from 0.75 (stage IV colon cancer; P < .001) to 0.32 (stage I rectal cancer; P < .001), indicating improvements in relative survival for all stages and cancer locations. These improvements occurred in earlier years for patients diagnosed with stage I cancers, with smaller but continuing improvements for later-stage cancers. Our results demonstrate a steady trend toward improved relative survival for CRC, indicating that treatment and surveillance improvements have had an impact at the population level.
    Journal of the National Cancer Institute 10/2013; 105(23). DOI:10.1093/jnci/djt299 · 12.58 Impact Factor
  • Hawre Jalal · Jeremy D. Goldhaber-Fiebert · Karen M. Kuntz ·
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    ABSTRACT: Purpose: Regression metamodeling (RM) is a useful technique for efficiently revealing parameter sensitivities in a model in terms of marginal effects of each parameter on policy-relevant outcomes using the output from probabilistic sensitivity analysis (PSA). The present study examined the performance of RM when model parameters are correlated. Methods: A metamodel is a statistical model that can summarize model parameter sensitivities from PSA by regressing model outcomes on the model input parameters. Coefficients from RM can be interpreted as changes in the model outcome due to a change in the corresponding input. Decision models with two or more parameters that are highly correlated may present an important limitation of RM, as collinear variables do in multivariate regression. Increased correlation in RM parameters may widen the confidence intervals of the coefficient estimates. We used a previously published model of treating herpes simplex encephalopathy, where the outcome is the expected utility of undergoing a brain biopsy. We incorporated a correlation between two of the model parameters: the probability of dying because of biopsy (pDieBiopsy) and the probability of developing severe complications following biopsy (pSevereBiopsy). We ran 10,000 PSA simulations for each hypothetical correlation level between these two parameters, varying the correlation value (rho) from 0 to 1. We then examined the precision of the estimated RM coefficients at each value of rho. Results: The figure shows the RM coefficients of pDieBiopsy and pSevereBiopsy (solid line), and their confidence intervals (gray region) for various correlation coefficient values. The negative coefficients indicate that an increase in the value of either parameter results in a reduction in the expected utility of biopsy. The confidence intervals maintains the same width at various correlation levels except for near exact correlation (i.e., when rho = 1). We found similar results with other correlated parameters. Conclusion: We found RM to accurately predict parameter sensitivities except when these parameters are in near perfect correlation. In these situations, including correlated parameters in the model may be unnecessary because one of the correlated parameters can be expressed as a function of the other one. Using standard regression diagnostics (e.g., the condition index) to identify situations of high multicollinearity may be appropriate when performing RM.
    The 35th Annual Meeting of the Society for Medical Decision Making; 10/2013
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    ABSTRACT: While magnetic resonance imaging (MRI) is frequently used following breast cancer diagnosis, routine use of breast MRI for preoperative evaluation remains contentious. We identified factors associated with preoperative breast MRI utilization and investigated the variation among physicians. We used the surveillance, epidemiology, and end Results (SEER)-Medicare linked database to analyze the preoperative breast MRI utilization among patients with stage 0, I, or II breast cancer diagnosed between 2002 and 2007. Multilevel logistic regression models were used to identify patient- and physician-level predictors of preoperative MRI utilization. Of 56,743 women with early-stage breast cancer who were treated with surgery and evaluated by a preoperative mammogram and/or ultrasound during the study period, 8.7% (n = 4,913) received preoperative breast MRI. While patient and tumor characteristics did predict preoperative breast MRI utilization, they explained only 15.4% of the variation in utilization rates. Differences in preoperative breast MRI utilization across physicians were large, after controlling patient-level factors and physicians' volumes. Accounting for clustering of patients within individual physicians (n = 3,144), the multilevel logistic regression models explained 36.4% of variation. The median odds ratio of 3.2, corresponding with the median value of the relative odds of receiving preoperative breast MRI between two randomly chosen physicians, indicated a large individual physician effect. Our study found that preoperative breast MRI has been adopted rapidly and variably. Although patient characteristics were associated with preoperative breast MRI utilization, physician practice was a major determinant of whether women received preoperative breast MRI. Future studies should evaluate whether routine use of preoperative breast MRI in newly diagnosed early-stage breast cancer improves clinical outcomes.
    The Breast Journal 09/2013; 19(6). DOI:10.1111/tbj.12177 · 1.41 Impact Factor

  • Journal of the American College of Surgeons 09/2013; 217(3):S126. DOI:10.1016/j.jamcollsurg.2013.07.290 · 5.12 Impact Factor

  • Value in Health 09/2013; 16(6):1108. DOI:10.1016/j.jval.2013.06.016 · 3.28 Impact Factor
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    ABSTRACT: Advances in hematopoietic cell transplantation (HCT) have led to an increasing number of transplant survivors. In order to adequately support their healthcare needs, there is a need to know the prevalence of HCT survivors. We used data on 170,628 recipients of autologous and allogeneic HCT reported to the Center for International Blood and Marrow Transplant Research from 1968 to 2009 to estimate the current and future number of HCT survivors in the United States. Stacked cohort simulation models were used to estimate the number of HCT survivors in the US in 2009 and make projections for HCT survivors by the year 2030. There were 108,900 (range, 100,500-115,200) HCT survivors in the United States in 2009. This included 67,000 autologous HCT and 41,900 allogeneic HCT survivors. The number of HCT survivors is estimated to increase by 2.5 times by the year 2020 (242,000 survivors) and 5 times by the year 2030 (502,000 survivors). By 2030, the age at transplant will be <18 years for 14% of all survivors (N=64,000), 18-59 years for 61% survivors (N=276,000) and 60 years and older for 25% of survivors (N=113,000). In coming decades, a large number of individuals will be HCT survivors. Transplant center providers, hematologists, oncologists, primary care physicians and other specialty providers will need to be familiar with the unique and complex health issues faced by this population.
    Biology of blood and marrow transplantation: journal of the American Society for Blood and Marrow Transplantation 07/2013; 19(10). DOI:10.1016/j.bbmt.2013.07.020 · 3.40 Impact Factor

Publication Stats

9k Citations
2,009.55 Total Impact Points


  • 2015
    • Minnesota Department of Health
      Saint Paul, Minnesota, United States
    • Stanford University
      Palo Alto, California, United States
  • 2007-2015
    • University of Minnesota Duluth
      • • College of Pharmacy
      • • Medical School
      Duluth, Minnesota, United States
  • 2013
    • University of Texas Health Science Center at San Antonio
      • Department of Epidemiology and Biostatistics
      San Antonio, TX, United States
  • 2011
    • German Cancer Research Center
      • Division of Preventive Oncology
      Heidelberg, Baden-Wuerttemberg, Germany
  • 2000-2010
    • Massachusetts General Hospital
      • Institute for Technology Assessment
      Boston, Massachusetts, United States
  • 1996-2009
    • Harvard University
      • Department of Health Policy and Management
      Cambridge, Massachusetts, United States
    • Beth Israel Medical Center
      • Department of Surgery
      New York City, New York, United States
  • 2008
    • Memorial Sloan-Kettering Cancer Center
      • Epidemiology & Biostatistics Group
      New York City, NY, United States
  • 1997-2008
    • Harvard Medical School
      • • Department of Medicine
      • • Department of Radiology
      Boston, Massachusetts, United States
  • 2003-2006
    • Massachusetts Department of Public Health
      Boston, Massachusetts, United States
  • 2005
    • University of Groningen
      Groningen, Groningen, Netherlands
    • University of Washington Seattle
      Seattle, Washington, United States
  • 2002
    • Hôpitaux Universitaires de Genève
      Genève, Geneva, Switzerland
  • 2001
    • Oak Ridge Center For Risk Analysis
      オーク・リッジ, Tennessee, United States
    • Yale-New Haven Hospital
      New Haven, Connecticut, United States
  • 1999
    • Dana-Farber Cancer Institute
      • Center for Outcomes and Policy Research
      Boston, Massachusetts, United States
  • 1998
    • New York Downtown Hospital
      New York, New York, United States
    • Laval University
      • Département de Médecine
      Québec, Quebec, Canada
  • 1996-1998
    • Brigham and Women's Hospital
      • Department of Medicine
      Boston, MA, United States
  • 1995
    • Beverly Hospital, Boston MA
      BVY, Massachusetts, United States