Karen M Kuntz

University of Minnesota Duluth, Duluth, Minnesota, United States

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Publications (190)1548.42 Total impact

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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 11/2014; · 6.20 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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    ABSTRACT: 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).
    Health Services Research 10/2014; · 2.29 Impact Factor
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    ABSTRACT: 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.
    Journal of the National Cancer Institute. 08/2014; 106(8).
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    ABSTRACT: Harms and benefits of cancer screening depend on age and comorbid conditions, but reliable estimates are lacking.
    Annals of internal medicine 07/2014; 161(2):104-12. · 13.98 Impact Factor
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    ABSTRACT: To evaluate and update the safety data from randomized controlled trials of TNF inhibitors (TNFis) in patients treated for rheumatoid arthritis.
    The American journal of medicine. 06/2014;
  • 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 01/2014; · 2.19 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.
    CancerSpectrum Knowledge Environment 10/2013; · 14.07 Impact Factor
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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; · 1.83 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; · 3.15 Impact Factor
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    ABSTRACT: In the 1990s, several organizations began recommending evaluation of > 12 lymph nodes during colon resection because of its association with improved survival. We examined practice implications of multispecialty quality guidelines over the past 20 years recommending evaluation of ≥ 12 lymph nodes during colon resection for adequate staging. We used the 1988 to 2009 Surveillance, Epidemiology, and End Results program to conduct a retrospective observational cohort study of 90,203 surgically treated patients with colon cancer. We used Cochran-Armitage tests to examine trends in lymph node examination over time and multivariate logistic regression to identify patient characteristics associated with guideline-recommended lymph node evaluation. The introduction of practice guidelines was associated with gradual increases in guideline-recommended lymph node evaluation. From 1988 to 1990, 34% of patients had > 12 lymph nodes evaluated, increasing to 38% in 1994 to 1996 and to > 75% from 2006 to 2009. Younger, white patients and those with more-extensive bowel penetration (T3/4 nonmetastatic) and high tumor grade saw more-rapid increases in lymph node evaluation (P < .001). Multivariate analyses demonstrated a significant interaction between year of diagnosis and both T stage and grade, indicating that those with higher T stage and higher grade were more likely to receive guideline-recommended care earlier. The implementation of lymph node evaluation guidelines was accepted gradually into practice but adopted more quickly among higher risk patients. By identifying patients who are least likely to receive guideline-recommended care, these findings present a starting point for promoting targeted improvements in cancer care and further understanding underlying contributors to these disparities.
    Journal of Oncology Practice 07/2013; 9(4):e164-71.
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    ABSTRACT: . Modelers lack a tool to systematically and clearly present complex model results, including those from sensitivity analyses. The objective was to propose linear regression metamodeling as a tool to increase transparency of decision analytic models and better communicate their results. . We used a simplified cancer cure model to demonstrate our approach. The model computed the lifetime cost and benefit of 3 treatment options for cancer patients. We simulated 10,000 cohorts in a probabilistic sensitivity analysis (PSA) and regressed the model outcomes on the standardized input parameter values in a set of regression analyses. We used the regression coefficients to describe measures of sensitivity analyses, including threshold and parameter sensitivity analyses. We also compared the results of the PSA to deterministic full-factorial and one-factor-at-a-time designs. . The regression intercept represented the estimated base-case outcome, and the other coefficients described the relative parameter uncertainty in the model. We defined simple relationships that compute the average and incremental net benefit of each intervention. Metamodeling produced outputs similar to traditional deterministic 1-way or 2-way sensitivity analyses but was more reliable since it used all parameter values. . Linear regression metamodeling is a simple, yet powerful, tool that can assist modelers in communicating model characteristics and sensitivity analyses.
    Medical Decision Making 06/2013; · 2.89 Impact Factor
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    ABSTRACT: Although gastric cancer has declined dramatically in the US, the disease remains the second leading cause of cancer mortality worldwide. A better understanding of reasons for the decline can provide important insights into effective preventive strategies. We sought to estimate the contribution of risk factor trends on past and future intestinal-type noncardia gastric adenocarcinoma (NCGA) incidence. We developed a population-based microsimulation model of intestinal-type NCGA and calibrated it to US epidemiologic data on precancerous lesions and cancer. The model explicitly incorporated the impact of Helicobacter pylori and smoking on disease natural history, for which birth cohort-specific trends were derived from the National Health and Nutrition Examination Survey (NHANES) and National Health Interview Survey (NHIS). Between 1978 and 2008, the model estimated that intestinal-type NCGA incidence declined 60% from 11.0 to 4.4 per 100,000 men, <3% discrepancy from national statistics. H. pylori and smoking trends combined accounted for 47% (range = 30%-58%) of the observed decline. With no tobacco control, incidence would have declined only 56%, suggesting that lower smoking initiation and higher cessation rates observed after the 1960s accelerated the relative decline in cancer incidence by 7% (range = 0%-21%). With continued risk factor trends, incidence is projected to decline an additional 47% between 2008 and 2040, the majority of which will be attributable to H. pylori and smoking (81%; range = 61%-100%). Limitations include assuming all other risk factors influenced gastric carcinogenesis as one factor and restricting the analysis to men. Trends in modifiable risk factors explain a significant proportion of the decline of intestinal-type NCGA incidence in the US, and are projected to continue. Although past tobacco control efforts have hastened the decline, full benefits will take decades to be realized, and further discouragement of smoking and reduction of H. pylori should be priorities for gastric cancer control efforts. Please see later in the article for the Editors' Summary.
    PLoS Medicine 05/2013; 10(5):e1001451. · 15.25 Impact Factor
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    ABSTRACT: BACKGROUND:: Checklists can standardize patient care, reduce errors, and improve health outcomes. For meningitis in resource-limited settings, with high patient loads and limited financial resources, CNS diagnostic algorithms may be useful to guide diagnosis and treatment. However, the cost-effectiveness of such algorithms is unknown. METHODS:: We used decision analysis methodology to evaluate the costs, diagnostic yield, and cost-effectiveness of diagnostic strategies for adults with suspected meningitis in resource limited settings with moderate/high HIV prevalence. We considered three strategies: 1) comprehensive "shotgun" approach of utilizing all routine tests; 2) "stepwise" strategy with tests performed in a specific order with additional TB diagnostics; 3) "minimalist" strategy of sequential ordering of high-yield tests only.Each strategy resulted in one of four meningitis diagnoses: bacterial (4%), cryptococcal (59%), TB (8%), or other (aseptic) meningitis (29%). In model development, we utilized prevalence data from two Ugandan sites and published data on test performance. We validated the strategies with data from Malawi, South Africa, and Zimbabwe. RESULTS:: The current comprehensive testing strategy resulted in 93.3% correct meningitis diagnoses costing $32.00/patient. A stepwise strategy had 93.8% correct diagnoses costing an average of $9.72/patient, and a minimalist strategy had 91.1% correct diagnoses costing an average of $6.17/patient. The incremental cost effectiveness ratio was $133 per additional correct diagnosis for the stepwise over minimalist strategy. CONCLUSIONS:: Through strategically choosing the order and type of testing coupled with disease prevalence rates, algorithms can deliver more care more efficiently. The algorithms presented herein are generalizable to East Africa and Southern Africa.
    JAIDS Journal of Acquired Immune Deficiency Syndromes 03/2013; · 4.65 Impact Factor
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    ABSTRACT: To evaluate the association between preoperative breast magnetic resonance imaging (MRI) utilization and the rate of multiple surgeries, and to investigate the extent of any variation of rates of multiple surgeries among physicians. We identified patients with stage 0, I, or II breast cancer diagnosed between 2002 and 2007 in the Surveillance, Epidemiology, and End Results-Medicare database. Using diagnosis and procedure codes, we defined that the initial treatment episode had ended when a gap in surgery occurred at least 90 days after primary surgery. Surgical procedures of partial mastectomy or mastectomy during the initial treatment period were calculated to identify patients who received multiple surgeries. Multilevel logistic regression models were used to identify patient- and physician-level predictors of multiple surgeries. Of 45,453 women with early stage breast cancer who were treated by 2,595 surgeons during the study period, 9,462 patients (20.8 %) received multiple breast surgeries; of these patients, 8,318 (87.9 %) underwent one additional surgery, 988 (10.4 %) received two additional surgeries, and 156 (1.6 %) received three or more additional surgeries. Among 2,997 (6.6 % of the entire cohort) women who underwent preoperative breast MRI evaluation, 770 received multiple breast surgeries. After we adjusted for patient and tumor characteristics associated with multiple surgeries, we found that the rate of multiple surgeries was not significantly different between the two groups with or without preoperative breast MRI. Furthermore, the median odds ratio of 2.0, corresponding with the median value of the relative odds of receiving multiple surgeries between two randomly chosen physicians after controlling for other confounders, indicated a large individual surgeon effect. Substantial variation was observed in the rates of multiple surgeries in women aged 66 and older with early stage breast cancer. Evidence does not support that preoperative breast MRI reduces the incidence of multiple surgeries.
    Breast Cancer Research and Treatment 01/2013; · 4.47 Impact Factor
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    ABSTRACT: Decision models are sometimes used alongside systematic reviews to synthesize evidence. Clarity, however, is lacking about when and how to conduct modeling studies in tandem with systematic reviews, as well as about how to evaluate and present model results. The objective of this study was to collect and analyze information from various sources to inform the development of a framework for deciding when and how a decision model should be added to a systematic review. We collected data through 1) review and analysis of evidence reports that used decision models; 2) review and synthesis of current best practices for the development of decision models; 3) interviews of Evidence-Based Practice Center directors and selected staff, United States Preventive Services Task Force members, and decision modelers who developed models used by the United States Preventive Services Task Force; and 4) a focus group of expert modelers. Models are well suited to address gaps in the literature, better suited for certain types of research questions, and essential for determining the value of information relating to future research. Opinions differ regarding whether model outputs constitute evidence, but interviewees expressed concern over the lack of standards and directions in grading and reporting such "evidence." Interviews of stakeholders and modelers revealed the importance of communication and presentation of model results as well as the importance of model literacy and involvement of stakeholders. The study demonstrates the need for a framework for deciding when and how to use models alongside systematic reviews and provides information to develop such a framework.
    Value in Health 01/2013; 16(1):133-9. · 2.19 Impact Factor
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    ABSTRACT: Persons with a negative result on screening colonoscopy are recommended to repeat the procedure in 10 years. To assess the effectiveness and costs of colonoscopy versus other rescreening strategies after an initial negative colonoscopy result. Microsimulation model. Literature and data from the Surveillance, Epidemiology, and End Results program. Persons aged 50 years who had no adenomas or cancer detected on screening colonoscopy. Lifetime. Societal. No further screening or rescreening starting at age 60 years with colonoscopy every 10 years, annual highly sensitive guaiac fecal occult blood testing (HSFOBT), annual fecal immunochemical testing (FIT), or computed tomographic colonography (CTC) every 5 years. Lifetime cases of colorectal cancer, life expectancy, and lifetime costs per 1000 persons, assuming either perfect or imperfect adherence. Rescreening with any method substantially reduced the risk for colorectal cancer compared with no further screening (range, 7.7 to 12.6 lifetime cases per 1000 persons [perfect adherence] and 17.7 to 20.9 lifetime cases per 1000 persons [imperfect adherence] vs. 31.3 lifetime cases per 1000 persons with no further screening). In both adherence scenarios, the differences in life-years across rescreening strategies were small (range, 30 893 to 30 902 life-years per 1000 persons [perfect adherence] vs. 30 865 to 30 869 life-years per 1000 persons [imperfect adherence]). Rescreening with HSFOBT, FIT, or CTC had fewer complications and was less costly than continuing colonoscopy. Results were sensitive to test-specific adherence rates. Data on adherence to rescreening were limited. Compared with the currently recommended strategy of continuing colonoscopy every 10 years after an initial negative examination, rescreening at age 60 years with annual HSFOBT, annual FIT, or CTC every 5 years provides approximately the same benefit in life-years with fewer complications at a lower cost. Therefore, it is reasonable to use other methods to rescreen persons with negative colonoscopy results. National Cancer Institute.
    Annals of internal medicine 11/2012; 157(9):611-20. · 13.98 Impact Factor
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    ABSTRACT: BACKGROUND: Simulation models designed to evaluate cancer prevention strategies make assumptions on background mortality-the competing risk of death from causes other than the cancer being studied. Researchers often use the U.S. life tables and assume homogeneous other-cause mortality rates. However, this can lead to bias because common risk factors such as smoking and obesity also predispose individuals for deaths from other causes such as cardiovascular disease. METHODS: We obtained calendar year-, age-, and sex-specific other-cause mortality rates by removing deaths due to a specific cancer from U.S. all-cause life tables. Prevalence across 12 risk factor groups (3 smoking [never, past, and current smoker] and 4 body mass index [BMI] categories [<25, 25-30, 30-35, 35+ kg/m(2)]) were estimated from national surveys (National Health and Nutrition Examination Surveys [NHANES] 1971-2004). Using NHANES linked mortality data, we estimated hazard ratios for death by BMI/smoking using a Poisson regression model. Finally, we combined these results to create 12 sets of BMI and smoking-specific other-cause life tables for U.S. adults aged 40 years and older that can be used in simulation models of lung, colorectal, or breast cancer. RESULTS: We found substantial differences in background mortality when accounting for BMI and smoking. Ignoring the heterogeneity in background mortality in cancer simulation models can lead to underestimation of competing risk of deaths for higher-risk individuals (e.g., male, 60-year old, white obese smokers) by as high as 45%. CONCLUSION: Not properly accounting for competing risks of death may introduce bias when using simulation modeling to evaluate population health strategies for prevention, screening, or treatment. Further research is warranted on how these biases may affect cancer-screening strategies targeted at high-risk individuals.
    Medical Decision Making 11/2012; · 2.89 Impact Factor
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    ABSTRACT: Purpose: To determine the cost-effectiveness of biologics for rheumatoid arthritis (RA) by age and disability level as measured by the Health Assessment Questionnaire-Disability Index (HAQ). Method: We developed a finite-horizon discrete-time Markov decision processes (MDP) model to identify decision sequences that maximize the net health benefit for hypothetical RA patients, defined by age and HAQ quintile. We assumed six month cycles and a lifetime horizon. We modeled transitions among a set of mutually exclusive and collectively exhaustive health states defined by levels of disability as measured by HAQ quintiles. Higher quintiles of HAQ indicate more disability. Transition probabilities for biologics and nonbiologics were estimated from the National Data Bank for Rheumatic Diseases. Direct and indirect costs (as productivity losses) were estimated from the literature. We calculated an average quality of life weight using the EQ5D instrument for each HAQ quintile. Both costs and benefits were discounted 3% annually. Result: For a willingness to pay threshold (WTP) of $100,000/QALY, biologics could be cost effective for mildly disabled elderly patients if their cost was reduced by 60%. The figure illustrates the cost-effectiveness of biologics versus nonbiologics by patient age, HAQ quintile, and WTP, assuming a reduced biologics cost. As shown in the figure, when the WTP is further increased up to $300,000/QALY, biologics become cost-effective for younger and more disabled patients. In a sensitivity analysis, we restricted our analysis to newly diagnosed patients (<2 years) and found that biologics were more cost-effective for the more disabled patients. Conclusion: We adopted a novel approach to model the use of biologics in RA as a sequential decision problem.
    The 34th Annual Meeting of the Society for Medical Decision Making; 10/2012

Publication Stats

6k Citations
1,548.42 Total Impact Points

Institutions

  • 2007–2014
    • University of Minnesota Duluth
      • College of Pharmacy
      Duluth, Minnesota, United States
    • Columbia University
      • Department of Health Policy and Management
      New York City, NY, United States
  • 2012–2013
    • University of Texas Health Science Center at San Antonio
      • Department of Epidemiology and Biostatistics
      San Antonio, TX, United States
    • United BioSource Corporation
      Maryland, United States
    • German Cancer Research Center
      • Division of Preventive Oncology
      Heidelberg, Baden-Wuerttemberg, Germany
  • 2001–2013
    • Yale-New Haven Hospital
      New Haven, Connecticut, United States
    • University of Cincinnati
      Cincinnati, Ohio, United States
  • 1995–2013
    • Harvard Medical School
      • • Department of Medicine
      • • Department of Radiation Oncology
      Boston, Massachusetts, United States
  • 2011–2012
    • University of Minnesota Twin Cities
      • • Division of Health Policy and Management
      • • School of Public Health
      Minneapolis, MN, United States
    • Erasmus MC
      • Research Group for Public Health
      Rotterdam, South Holland, Netherlands
  • 1999–2010
    • Harvard University
      • • Center for Health Decision Science
      • • Faculty of Arts and Sciences
      • • Department of Health Policy and Management
      • • Center for Risk Analysis
      Boston, MA, United States
  • 1994–2010
    • Massachusetts General Hospital
      • • Institute for Technology Assessment
      • • Department of Radiology
      • • Department of Medicine
      Boston, MA, United States
  • 2009
    • University of Washington Seattle
      Seattle, Washington, United States
  • 2004–2008
    • Memorial Sloan-Kettering Cancer Center
      • Epidemiology & Biostatistics Group
      New York City, NY, United States
    • Partners HealthCare
      Boston, Massachusetts, United States
  • 2003–2007
    • Massachusetts Department of Public Health
      Boston, Massachusetts, United States
  • 1997–2007
    • Dana-Farber Cancer Institute
      • Center for Outcomes and Policy Research
      Boston, Massachusetts, United States
  • 2006
    • University of Texas MD Anderson Cancer Center
      • Division of Radiation Oncology
      Houston, TX, United States
    • The University of Calgary
      • Department of Community Health Sciences
      Calgary, Alberta, Canada
  • 1996–2003
    • Brigham and Women's Hospital
      • Department of Medicine
      Boston, MA, United States
    • Beth Israel Medical Center
      • Department of Surgery
      New York City, New York, United States
  • 2002
    • Miami Children's Hospital
      • Department of Radiology
      Miami, Florida, United States
  • 2000
    • Beth Israel Deaconess Medical Center
      • Department of Radiology
      Boston, MA, United States
  • 1998
    • Laval University
      • Département de Médecine
      Québec, Quebec, Canada