J. Chhatwal, S. Jayasuriya, and E. H. Elbasha. 2016. “Changing Cycle Lengths in State-Transition Models: Challenges and Solutions.” Med Decis Making, 36, 8, Pp. 952-64.
J. Chhatwal, X. Wang, T. Ayer, M. Kabiri, R. T. Chung, C. Hur, J. M. Donohue, M. S. Roberts, and F. Kanwal. 2016. “Hepatitis C Disease Burden in the United States in the era of oral direct-acting antivirals.” Hepatology, 64, 5, Pp. 1442-1450.
C. Besa, S. Lewis, P. V. Pandharipande, J. Chhatwal, A. Kamath, N. Cooper, A. Knight-Greenfield, J. S. Babb, P. Boffetta, N. Padron, C. B. Sirlin, and B. Taouli. 2016. “Hepatocellular carcinoma detection: diagnostic performance of a simulated abbreviated MRI protocol combining diffusion-weighted and T1-weighted imaging at the delayed phase post gadoxetic acid.” Abdom Radiol (NY).
E. H. Elbasha and J. Chhatwal. 2016. “Myths and Misconceptions of Within-Cycle Correction: A Guide for Modelers and Decision Makers.” Pharmacoeconomics, 34, 1, Pp. 13-22.
T. He, K. Li, M. S. Roberts, A. C. Spaulding, T. Ayer, J. J. Grefenstette, and J. Chhatwal. 2016. “Prevention of Hepatitis C by Screening and Treatment in U.S. Prisons.” Ann Intern Med, 164, 2, Pp. 84-92.
J. Chhatwal, T. He, and M. A. Lopez-Olivo. 2016. “Systematic Review of Modelling Approaches for the Cost Effectiveness of Hepatitis C Treatment with Direct-Acting Antivirals.” Pharmacoeconomics, 34, 6, Pp. 551-67.
J. Chhatwal, M. Mathisen, and H. Kantarjian. 2015. “Are high drug prices for hematologic malignancies justified? A critical analysis.” Cancer, 121, Pp. 3372-9.Abstract
In the past 15 years, treatment outcomes for hematologic malignancies have improved substantially. However, drug prices have also increased drastically. This commentary examines the value of the treatment of hematologic malignancies at current prices in the United States through a reanalysis of a systematic review evaluating 29 studies of 9 treatments for 4 hematologic malignancies. Incremental cost-effectiveness ratios (ICERs) were calculated on the basis of drug prices in the United States in 2014. Sixty-three percent of the studies (15 of 24) had ICERs higher than $50,000 per quality-adjusted life-year (QALY), the benchmark widely used by health economists to define cost-effectiveness. In studies evaluating the current standard-of-care treatments for chronic myeloid leukemia, the ICERs for tyrosine kinase inhibitors versus hydroxyurea or interferon ranged from $210,000 to $426,000/QALY. The lower ICER values were mostly obtained from 11 studies evaluating rituximab, which was approved by the Food and Drug Administration in 1997 (ICER range, $37,000-$69,000/QALY). In conclusion, the costs of the majority of new treatments for hematologic cancers are too high to be deemed cost-effective in the United States. Cancer 2015;121:3435-43. (c) 2015 American Cancer Society.
E. H. Elbasha and J. Chhatwal. 2015. “Characterizing Heterogeneity Bias in Cohort-Based Models.” Pharmacoeconomics, 33, Pp. 857-65.Abstract
PURPOSE: Previous research using numerical methods suggested that use of a cohort-based model instead of an individual-based model can result in significant heterogeneity bias. However, the direction of the bias is not known a priori. We characterized mathematically the conditions that lead to upward or downward bias. METHOD: We used a standard three-state disease progression model to evaluate the cost effectiveness of a hypothetical intervention. We solved the model analytically and derived expressions for life expectancy, discounted quality-adjusted life years (QALYs), discounted lifetime costs and incremental net monetary benefits (INMB). An outcome was calculated using the mean of the input under the cohort-based approach and the whole input distribution for all persons under the individual-based approach. We investigated the impact of heterogeneity on outcomes by varying one parameter at a time while keeping all others constant. We evaluated the curvature of outcome functions and used Jensen's inequality to determine the direction of the bias. RESULTS: Both life expectancy and QALYs were underestimated by the cohort-based approach. If there was heterogeneity only in disease progression, total costs were overestimated, whereas QALYs gained, incremental costs and INMB were under- or overestimated, depending on the progression rate. INMB was underestimated when only efficacy was heterogeneous. Both approaches yielded the same outcome when the heterogeneity was only in cost or utilities. CONCLUSION: A cohort-based approach that does not adjust for heterogeneity underestimates life expectancy and may underestimate or overestimate other outcomes. Characterizing the bias is useful for comparative assessment of models and informing decision making.
J. Guirguis, J. Chhatwal, J. Dasarathy, J. Rivas, D. McMichael, L. E. Nagy, A. J. McCullough, and S. Dasarathy. 2015. “Clinical Impact of Alcohol-Related Cirrhosis in the Next Decade: Estimates Based on Current Epidemiological Trends in the United States.” Alcohol Clin Exp Res, 39, Pp. 2085-94.Abstract
BACKGROUND: Identifying changes in the epidemiology of liver disease is critical for establishing healthcare priorities and allocating resources to develop therapies. The projected contribution of different etiologies toward development of cirrhosis in the United States was estimated based on current publications on epidemiological data and advances in therapy. Given the heterogeneity of published reports and the different perceptions that are not always reconcilable, a critical overview rather than a formal meta-analysis of the existing data and projections for the next decade was performed. METHODS: Data from the World Health Organization Global Status Report on Alcohol and Health of 2014, Scientific Registry of Transplant Recipients from 1999 to 2012, National Institute on Alcohol Abuse and Alcoholism, and the Centers for Disease Control and Prevention were inquired to determine future changes in the epidemiology of liver disease. RESULTS: Alcohol consumption has increased over the past 60 years. In 2010, transplant-related costs for liver recipients were the highest for hepatitis C ( $124 million) followed by alcohol-related cirrhosis ( $86 million). We anticipate a significant reduction in incidence cirrhosis due to causes other than alcohol because of the availability of high efficiency antiviral agents for hepatitis C, universal and effective vaccination for hepatitis B, relative stabilization of the obesity trends in the United States, and novel, potentially effective therapies for nonalcoholic steatohepatitis. The proportion of alcohol-related liver disease is therefore likely to increase in both the population as a whole and the liver transplant wait list. CONCLUSIONS: Alcohol-related cirrhosis and alcohol-related liver disorders will be the major cause of liver disease in the coming decades. There is an urgent need to allocate resources aimed toward understanding the pathogenesis of the disease and its complications so that effective therapies can be developed.
J. Chhatwal, F. Kanwal, M. S. Roberts, and M. A. Dunn. 2015. “Cost-effectiveness and budget impact of hepatitis C virus treatment with sofosbuvir and ledipasvir in the United States.” Ann Intern Med, 162, Pp. 397-406.Abstract
BACKGROUND: Sofosbuvir and ledipasvir, which have recently been approved for treatment of chronic hepatitis C virus (HCV) infection, are more efficacious and safer than the old standard of care (oSOC) but are substantially more expensive. Whether and in which patients their improved efficacy justifies their increased cost is unclear. OBJECTIVE: To evaluate the cost-effectiveness and budget impact of sofosbuvir and ledipasvir. DESIGN: Microsimulation model of the natural history of HCV infection. DATA SOURCES: Published literature. TARGET POPULATION: Treatment-naive and treatment-experienced HCV population defined on the basis of HCV genotype, age, and fibrosis distribution in the United States. TIME HORIZON: Lifetime. PERSPECTIVE: Third-party payer. INTERVENTION: Simulation of sofosbuvir-ledipasvir compared with the oSOC (interferon-based therapies). OUTCOME MEASURES: Quality-adjusted life-years (QALYs), incremental cost-effectiveness ratios (ICERs), and 5-year spending on antiviral drugs. RESULTS OF BASE-CASE ANALYSIS: Sofosbuvir-based therapies added 0.56 QALY relative to the oSOC at an ICER of $55 400 per additional QALY. The ICERs ranged from $9700 to $284 300 per QALY depending on the patient's status with respect to treatment history, HCV genotype, and presence of cirrhosis. At a willingness-to-pay threshold of $100 000 per QALY, sofosbuvir-based therapies were cost-effective in 83% of treatment-naive and 81% of treatment-experienced patients. Compared with the oSOC, treating eligible HCV-infected persons in the United States with the new drugs would cost an additional $65 billion in the next 5 years, whereas the resulting cost offsets would be $16 billion. RESULTS OF SENSITIVITY ANALYSIS: Results were sensitive to drug price, drug efficacy, and quality of life after successful treatment. LIMITATION: Data on real-world effectiveness of new antivirals are lacking. CONCLUSION: Treatment of HCV is cost-effective in most patients, but additional resources and value-based patient prioritization are needed to manage patients with HCV. PRIMARY FUNDING SOURCE: National Institutes of Health.
C. W. Seymour, O. Alotaik, D. J. Wallace, A. E. Elhabashy, J. Chhatwal, T. D. Rea, D. C. Angus, G. Nichol, and J. M. Kahn. 2015. “County-Level Effects of Prehospital Regionalization of Critically Ill Patients: A Simulation Study.” Crit Care Med, 43, Pp. 1807-15.Abstract
OBJECTIVE: Regionalization may improve critical care delivery, yet stakeholders cite concerns about its feasibility. We sought to determine the operational effects of prehospital regionalization of nontrauma, nonarrest critical illness. SETTING: King County, Washington. DESIGN: Discrete event simulation study. PATIENTS: All 2006 hospital discharge data, linked to all adult, eligible patients transported by county emergency medical services agencies. INTERVENTIONS: We simulated active triage of high-risk patients to designated referral centers using a validated prehospital risk score; we studied three regionalization scenarios: 1) up triage, 2) up and down triage, and 3) up and down triage after reducing ICU beds by 25%. We determined the effect on patient routing, ICU occupancy at referral and nonreferral hospitals, and emergency medical services transport times. MEASUREMENTS AND MAIN RESULTS: A total of 119,117 patients were hospitalized at 11 nonreferral centers and 76,817 patients were hospitalized at three referral centers. Among 20,835 emergency medical services patients, 7,817 patients (43%) were eligible for up triage and 10,242 patients (57%) were eligible for down triage. At baseline, mean daily ICU bed occupancy was 61% referral and 47% at nonreferral hospitals. Up triage increased referral ICU occupancy to 68%, up and down triage to 64%, and up and down triage with bed reduction to 74%. Mean daily nonreferral ICU occupancy did not exceed 60%. Total emergency medical services transport time increased by less than 3% with up and down triage. CONCLUSIONS: Regionalization based on prehospital triage of the critically ill can allocate high-risk patients to referral hospitals without adversely affecting ICU occupancy or prehospital travel time.
Jagpreet Chhatwal. 2015. “Direct-acting antivirals for hepatitis C treatment: effectiveness versus cost–effectiveness.” Future Virology, Pp. 1-4. Publisher's Version
J. Chhatwal and T. He. 2015. “Economic evaluations with agent-based modelling: an introduction.” Pharmacoeconomics, 33, 33, Pp. 423-33.Abstract

Agent-based modelling (ABM) is a relatively new technique, which overcomes some of the limitations of other methods commonly used for economic evaluations. These limitations include linearity, homogeneity and stationarity. Agents in ABMs are autonomous entities, who interact with each other and with the environment. ABMs provide an inductive or 'bottom-up' approach, i.e. individual-level behaviours define system-level components. ABMs have a unique property to capture emergence phenomena that otherwise cannot be predicted by the combination of individual-level interactions. In this tutorial, we discuss the basic concepts and important features of ABMs. We present a case study of an application of a simple ABM to evaluate the cost effectiveness of screening of an infectious disease. We also provide our model, which was developed using an open-source software program, NetLogo. We discuss software, resources, challenges and future research opportunities of ABMs for economic evaluations.

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A. A. Deshmukh, J. Chhatwal, E. Y. Chiao, A. G. Nyitray, P. Das, and S. B. Cantor. 2015. “Long-Term Outcomes of Adding HPV Vaccine to the Anal Intraepithelial Neoplasia Treatment Regimen in HIV-Positive Men Who Have Sex With Men.” Clin Infect Dis, 61, Pp. 1527-35.Abstract
BACKGROUND: Recent evidence shows that quadrivalent human papillomavirus (qHPV) vaccination in men who have sex with men (MSM) who have a history of high-grade anal intraepithelial neoplasia (HGAIN) was associated with a 50% reduction in the risk of recurrent HGAIN. We evaluated the long-term clinical and economic outcomes of adding the qHPV vaccine to the treatment regimen for HGAIN in human immunodeficiency virus (HIV)-positive MSM aged >/=27 years. METHODS: We constructed a Markov model based on anal histology in HIV-positive MSM comparing qHPV vaccination with no vaccination after treatment for HGAIN, the current practice. The model parameters, including baseline prevalence, disease transitions, costs, and utilities, were either obtained from the literature or calibrated using a natural history model of anal carcinogenesis. The model outputs included lifetime costs, quality-adjusted life years, and lifetime risk of developing anal cancer. We estimated the incremental cost-effectiveness ratio of qHPV vaccination compared to no qHPV vaccination and decrease in lifetime risk of anal cancer. We also conducted deterministic and probabilistic sensitivity analyses to evaluate the robustness of the results. RESULTS: Use of qHPV vaccination after treatment for HGAIN decreased the lifetime risk of anal cancer by 63% compared with no vaccination. The qHPV vaccination strategy was cost saving; it decreased lifetime costs by $419 and increased quality-adjusted life years by 0.16. Results were robust to the sensitivity analysis. CONCLUSIONS: Vaccinating HIV-positive MSM aged >/=27 years with qHPV vaccine after treatment for HGAIN is a cost-saving strategy. Therefore, expansion of current vaccination guidelines to include this population should be a high priority.
Q. Chen, T. Ayer, L. J. Nastoupil, J. L. Koff, A. D. Staton, J. Chhatwal, and C. R. Flowers. 2015. “Population-specific prognostic models are needed to stratify outcomes for African-Americans with diffuse large B-cell lymphoma.” Leuk Lymphoma, Pp. 1-26.Abstract
Diffuse large B-cell lymphoma (DLBCL) demonstrates significant racial differences in age of onset, stage, and survival. To examine whether population-specific models improve prediction of outcomes for African-American (AA) DLBCL patients, we utilized Surveillance, Epidemiology, and End Results data and compared stratification by the international prognostic index (IPI) in general and AA populations. We also constructed and compared prognostic models for general and AA populations using multivariable logistic regression (LR) and artificial neural network approaches. While the IPI adequately stratified outcomes for the general population, it failed to separate AA DLBCL patients into distinct risk groups. Our AA LR model identified age>/=55 (odds ratio 0.45, [95% CI: 0.36, 0.56], male sex (0.75, [0.60, 0.93]), and stage III/IV disease (0.43, [0.34, 0.54]) as adverse predictors of 5-year survival for AA patients. In addition, general-population prognostic models were poorly calibrated for AAs with DLBCL, indicating a need for validated AA-specific prognostic models.
J. Chhatwal, M. S. Mathisen, and H. M. Kantarjian. 2015. “Reply to price and value in cancer care.” Cancer.
E. H. Elbasha and J. Chhatwal. 2015. “Theoretical Foundations and Practical Applications of Within-Cycle Correction Methods.” Med Decis Making.Abstract
BACKGROUND: . Modeling guidelines recommend applying a half-cycle correction (HCC) to outcomes from discrete-time state-transition models (DTSTMs). However, there is still no consensus on why and how to perform the correction. The objective was to provide theoretical foundations for HCC and to compare (both mathematically and numerically) the performance of different correction methods in reducing errors in outcomes from DTSTMs. METHODS: . We defined 7 methods from the field of numerical integration: Riemann sum of rectangles (left, midpoint, right), trapezoids, life-table, and Simpson's 1/3rd and 3/8th rules. We applied these methods to a standard 3-state disease progression Markov chain to evaluate the cost-effectiveness of a hypothetical intervention. We solved the discrete- and continuous-time (our gold standard) versions of the model analytically and derived expressions for various outcomes including discounted quality-adjusted life-years, discounted costs, and incremental cost-effectiveness ratios. RESULTS: . The standard HCC method gave the same results as the trapezoidal rule and life-table method. We found situations where applying the standard HCC can do more harm than good. Compared with the gold standard, all correction methods resulted in approximation errors. Contrary to conventional wisdom, the errors need not cancel each other out or become insignificant when incremental outcomes are calculated. We found that a wrong decision can be made with a less accurate method. The performance of each correction method vastly improved when a shorter cycle length was selected; Simpson's 1/3rd rule was the fastest method to converge to the gold standard. CONCLUSION: . Cumulative outcomes in DTSTMs are prone to errors that can be reduced with more accurate methods like Simpson's rules. We clarified several misconceptions and provided recommendations and algorithms for practical implementation of these methods.
J. Chhatwal, Q. Chen, and F. Kanwal. 2015. “Why We Should Be Willing to Pay for Hepatitis C Treatment.” Clin Gastroenterol Hepatol, 13, Pp. 1711-3.
D. J. Wallace, J. M. Kahn, D. C. Angus, C. Martin-Gill, C. W. Callaway, T. D. Rea, J. Chhatwal, K. Kurland, and C. W. Seymour. 2014. “Accuracy of prehospital transport time estimation.” Acad Emerg Med, 21, Pp. 9-16.Abstract
OBJECTIVES: Estimates of prehospital transport times are an important part of emergency care system research and planning; however, the accuracy of these estimates is unknown. The authors examined the accuracy of three estimation methods against observed transport times in a large cohort of prehospital patient transports. METHODS: This was a validation study using prehospital records in King County, Washington, and southwestern Pennsylvania from 2002 to 2006 and 2005 to 2011, respectively. Transport time estimates were generated using three methods: linear arc distance, Google Maps, and ArcGIS Network Analyst. Estimation error, defined as the absolute difference between observed and estimated transport time, was assessed, as well as the proportion of estimated times that were within specified error thresholds. Based on the primary results, a regression estimate was used that incorporated population density, time of day, and season to assess improved accuracy. Finally, hospital catchment areas were compared using each method with a fixed drive time. RESULTS: The authors analyzed 29,935 prehospital transports to 44 hospitals. The mean (+/- standard deviation [+/-SD]) absolute error was 4.8 (+/-7.3) minutes using linear arc, 3.5 (+/-5.4) minutes using Google Maps, and 4.4 (+/-5.7) minutes using ArcGIS. All pairwise comparisons were statistically significant (p < 0.01). Estimation accuracy was lower for each method among transports more than 20 minutes (mean [+/-SD] absolute error was 12.7 [+/-11.7] minutes for linear arc, 9.8 [+/-10.5] minutes for Google Maps, and 11.6 [+/-10.9] minutes for ArcGIS). Estimates were within 5 minutes of observed transport time for 79% of linear arc estimates, 86.6% of Google Maps estimates, and 81.3% of ArcGIS estimates. The regression-based approach did not substantially improve estimation. There were large differences in hospital catchment areas estimated by each method. CONCLUSIONS: Route-based transport time estimates demonstrate moderate accuracy. These methods can be valuable for informing a host of decisions related to the system organization and patient access to emergency medical care; however, they should be employed with sensitivity to their limitations.
M. Kabiri, A. B. Jazwinski, M. S. Roberts, A. J. Schaefer, and J. Chhatwal. 2014. “The changing burden of hepatitis C virus infection in the United States: model-based predictions.” Ann Intern Med, 161, Pp. 170-80.Abstract
BACKGROUND: Chronic hepatitis C virus (HCV) infection causes a substantial health and economic burden in the United States. With the availability of direct-acting antiviral agents, recently approved therapies and those under development, and 1-time birth-cohort screening, the burden of this disease is expected to decrease. OBJECTIVE: To predict the effect of new therapies and screening on chronic HCV infection and associated disease outcomes. DESIGN: Individual-level state-transition model. SETTING: Existing and anticipated therapies and screening for HCV infection in the United States. PATIENTS: Total HCV-infected population in the United States. MEASUREMENTS: The number of cases of chronic HCV infection and outcomes of advanced-stage HCV infection. RESULTS: The number of cases of chronic HCV infection decreased from 3.2 million in 2001 to 2.3 million in 2013. One-time birth-cohort screening beginning in 2013 is expected to identify 487,000 cases of HCV infection in the next 10 years. In contrast, 1-time universal screening could identify 933,700 cases. With the availability of highly effective therapies, HCV infection could become a rare disease in the next 22 years. Recently approved therapies for HCV infection and 1-time birth-cohort screening could prevent approximately 124,200 cases of decompensated cirrhosis, 78,800 cases of hepatocellular carcinoma, 126,500 liver-related deaths, and 9900 liver transplantations by 2050. Increasing the treatment capacity would further reduce the burden of HCV disease. LIMITATION: Institutionalized patients with HCV infection were excluded, and empirical data on the effectiveness of future therapies and on the future annual incidence and treatment capacity of HCV infection are lacking. CONCLUSION: New therapies for HCV infection and widespread implementation of screening and treatment will play an important role in reducing the burden of HCV disease. More aggressive screening recommendations are needed to identify a large pool of infected patients. PRIMARY FUNDING SOURCE: National Institutes of Health.