Sunday, January 10, 2016: 11:00-12:30
Kai Chong Tong Auditorium, G/F (Jockey Club School of Public Health and Primary Care Building at Prince of Wales Hospital)

Haibo Qiu, MD1, Dipen Patel2, Yixi Chen, MSc3, Dong Peng, MD3, Seema Haider, PhD4 and Jennifer Stephens, PharmD2, (1)Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China, (2)Pharmerit International, Bethesda, MD, (3)Pfizer Inc., Beijing, China, (4)Pfizer Inc., Groton, CT

Appropriate and timely empiric treatment is critical for methicillin-resistant Staphylococcus aureus (MRSA)-related infections. Inadequate empiric treatment is associated with increased mortality and longer hospital stay. This study compared economic impact of empiric linezolid (Emp-LIN) vs. vancomycin (Emp-VAN) vs. no empiric MRSA coverage (NE-MRSA) before culture-confirmed treatment, for suspected MRSA nosocomial pneumonia (NP) from a Chinese payer perspective.

Method(s): A 4-week decision model was developed capturing empiric, 1st and 2nd line therapy. Published literature and expert opinion provided clinical and resource use data, including efficacy, incremental mortality for NE-MRSA, adverse events, and length of hospital/ICU stay. Cost and health utilities data were obtained from published literature. Base-case analysis used 3-day empiric, 10-day 1st/2nd-line treatment duration, 27% MRSA rate, and 1st-line linezolid for NE-MRSA after culture confirmation. MRSA negative patients exited the model after empiric treatment, and were assigned a fixed cost for remaining treatment. Univariate and probabilistic sensitivity analyses were conducted. Costs were reported in 2015 Chinese Yuan.


Emp-LIN was associated with marginally lower total costs (¥73,880 vs. ¥73,969), and greater QALY gain and overall treatment success compared to Emp-VAN, resulting in Emp-LIN ‘dominating’ Emp-VAN. Compared to NE-MRSA, Emp-LIN was more costly by ¥3,629, but had greater QALY gain (+0.75) and incremental treatment success (+5.3%), resulting in an incremental cost effectiveness ratio (ICER) of ¥4,825 per QALY gain, and ¥68,821 per additional successfully treated patient. Days in ICU stay, clinical efficacy, and MRSA rate impacted most on ICER. Probability of Emp-LIN being cost-effective was 73% (vs. Emp-VAN) and 99% (vs. NE-MRSA) assuming a willingness-to-pay (WTP) of ¥50,000 per additional successfully treated patients and QALY gain, respectively.

Conclusion(s): Early treatment with Emp-LIN is a cost-effective alternative to Emp-VAN and NE-MRSA at reasonable WTP threshold, and should be considered a preferred treatment choice, especially at hospitals with high MRSA rate.


Florian Miksch, PhD1, Beate Jahn, PhD2, Uwe Siebert, Prof., MD, MPH, MSc, ScD3, Barbara Glock, MSc1, Martin Bicher, MSc4, GŁnter Schneckenreither, MSc4, Christoph Urach, MSc1 and Niki Popper, PhD5, (1)dwh Simulation Services, Wien, Austria, (2)UMIT - University for Health Sciences, Medical Informatics and Technology, Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health and Health Technology Assessment, Hall in Tyrol, Austria, (3)UMIT, Dept. Public Health&HTA/ ONCOTYROL, Area 4 HTA&Bioinformatics/ Harvard T.H. Chan School Public Health, Center for Health Decision Science, Dept. Health Policy&Management/ Harvard Medical School, Institute for Technology Assessment&Dept. Radiology, Hall in Tyrol/ Innsbruck/ Boston, Austria, (4)TU Wien, Inst. f. Analysis & Scientific Computing, Wien, Austria, (5)dwh Simulation Services /Technical University Vienna, Institute for Analysis and Scientific Computing / DEXHELPP (Decision Support for Health Policy and Planning), Vienna, Austria
Purpose: Simulating aspects of the health system, such as number of diseases, people needing a treatment, or nation-wide costs often require a valid representation of the population. We present two population models that can be used as a basis for simulations in the health system and show how they can be parameterized based on given data and simulate the population accurately.
Method(s): We developed two different models for the simulation of a population: an agent-based model, which simulates individuals over discrete time steps, and a system dynamics model, which simulates aggregates that represent population groups over a continuous time. Both models include the characteristics age and gender, as well as births, deaths, immigrations and emigrations, and both models and are designed to simulate a changing population over time. In a first step, we defined model structures for both models to incorporate the population characteristics valid and accurately. In a second step, we gathered data from Statistics Austria, including assumptions about birth, death, immigration, and emigration rates until 2076. This data was used to calculate parameter values. The computations rely on statistical methods, mostly for aggregation and computing probabilities over specific intervals or for continuous changes. In a third step, the Austrian population is simulated until 2076.
Result(s): Results: The two models simulate the same system but their structures and parameters are fundamentally different. The computations of all model parameters are possible. Results are presented as the population and its demographics for each year. As the prognostic model starts in 2000, it was possible to validate the first 15 years of the simulation with real aggregated data, also gained from statistics Austria. Both model results only differ by less than one percent from the real population in 2015 as well as from the prognosis for 2076.
Conclusion(s): In our comparative analysis, both modeling methods are eligible to model and simulate populations over time. Small deviations are caused by structural model differences. For example, there are different ways to define and compute the mean population in a year. In our explorative example, the differences are small enough to accept both results as correct. For further simulation studies, this allows to integrate the population in a standardized, valid way if one of the two methods is used.


Rowan Iskandar, MA and Karen M. Kuntz, ScD, University of Minnesota, Minneapolis, MN
Purpose: Mammography aims to detect breast tumors (BTs) prior to becoming clinically symptomatic. Sojourn time (ST), the length of time when cancer is screen-detectable, is an important measure for determining the optimal screening interval. Several authors have estimated mean sojourn times (MSTs) by fitting parametric distributions to screening trial data. These estimates vary considerably across studies. Our study introduces a novel method for estimating MST by using a stochastic tumor growth model.

Method(s):  We adopted a biological-process-based modeling approach to estimate the MST by using a birth-death process (BDP) of BT cells in an oblate spherical tumor. The forward Kolmogorov equation (FKE) for the BDP was formulated and solved analytically.  The solution to the FKE gives the probability density function (pdf) of the number of tumor cells at any given time following tumor initiation. By defining two threshold sizes of 10^4 and 10^7 for screen-detected and clinically-detected tumors, respectively, we estimated the pdf for ST. We derived a simple analytical expression for calculating MST by using the estimated pdf. We also solved the FKE by using the tau-leap simulation method to validate the results from the analytical method. A tumor doubling time of 130 days was used to parameterize the BDP, based on a literature review.

Result(s): The analytical and tau-leap simulation methods yielded MST estimates of 734 and 743 days, respectively. Our method gave an estimate comparable to the lower MST estimate of 767 days reported by a study using data from the Swedish two-county study and to the result from a simulation-based estimation method using piecewise pdf for the ST and data from the HIP trial (730 days). Our estimate was significantly lower than those based on the Nijmegen trial data (1131 days). In contrast, our estimate was higher compared to the MST estimates from a statistical model using exponential pdf for the ST to fit the HIP trial data (621 days). 

Conclusion(s):   The incorporation of a simple biological process to estimate MST may be valuable for reducing the uncertainty in the estimates based on parametric assumptions. Moreover, the modeling approach exemplifies the potential linkage between modeling at the cellular level and patient or clinical intervention level.


Ruoyan Gai, MSc., PhD, National Center for Child Health and Development, Tokyo, Japan
Purpose: Pulse oximetry screening is a highly accurate tool for the early detection of congenital heart disease (CHD) in newborn infants. As the technique is simple, non-invasive and inexpensive, it has high potential benefits for developing countries. However, certain barriers may impede its wider implementation. In this study, we aim to inform clinical and health policy decisions by assessing the cost-effectiveness of CHD screening in China.

Method(s): We developed a cohort model to evaluate the cost-effectiveness of screening all Chinese newborns annually using three possible screening options compared to no intervention: (1) pulse oximetry alone, (2) clinical assessment alone, and (3) pulse oximetry as an adjunct to clinical assessment. We calculated the incremental cost per averted disability-adjusted life years (DALYs) in 2015 US dollars to measure cost-effectiveness. One-way sensitivity analyses and multivariate probabilistic sensitivity analysis were performed to test robustness of the model.

Result(s): We found that clinical assessment is the most cost-effective strategy compared to no intervention with an incremental cost-effectiveness ratio (ICER) of USD22,079/DALY, while pulse oximetry plus clinical assessment with the highest ICER yielded the best health outcomes. Sensitivity analysis showed that when the treatment rate increased up to 68%, pulse oximetry plus clinical assessment showed the best expected values among the three screening options. Cost-effectiveness acceptability curve analysis showed a 95% probability of clinical assessment to be cost-effective at a willingness-to-pay threshold of three times the GDP per capita.

Conclusion(s): In China, clinical assessment is currently the most cost-effective screening approach for neonatal CHD. Improvement of accessibility to treatment is crucial to expand the potential health benefits of screening.


Nina Lei Kuang1, Benny Zee1, Guotao Hu2 and Hailan Hu2, (1)Division of Biostatistics, Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, (2)Longgang Central Hospital of Shenzhen, Shenzhen, China


Diabetic neuropathy is one of the most common complications found in diabetes patients with a prevalence ranging from 7%-68%. Estimation from a multi-hospital survey in China indicated that 18% of diabetes patients and 6.4% of newly diagnosed patients had perception defects. Moreover, only one-third of the studied subjects had previously gone through neuropathy screening, and more than two third among those diagnosed with diabetic neuropathy undertook formal treatment.†


Several reasons may account for the low screening rate small proportion receiving treatment for this disease.† One of which could be related to the complexity of current screening process, which not only requires various equipments but also trained and experienced doctors. Secondly, lack of objective measurements in clinical or family care's setting affect the ability to identify the problems. Also, as the disease progresses slowly with bearable discomfort, patients usually ignore the symptoms until a late stage.† Thus, an assessment tool that is objective, easy to operate and accurate will not only help increase the screening and diagnostic capability but also raise patients' awareness of the disease.†

Microvascular abnormality has been studied extensively over the past decades. Both animal models and pathological anatomy had shown the abnormal structural changes in the microcirculation as the earliest pathological sign around the impaired nerve. Thus, it was proposed that vessel assessment be used as a potential tool for early risk assessment and detection of the neuropathy.† Retina was viewed as the most promising site for microcirculation evaluation because it is the only place where microcirculation can be view noninvasively.† Large population-based cohort studies, including The Atherosclerosis Risk in Communities Study (ARIC), The Wisconsin Epidemiologic Study of Diabetic Retinopathy (WESDR) and EURODIAB Prospective Complications Study all reported a moderately positive association between diabetic retinopathy and neuropathy. Our study with 2,127 type 2 diabetes subjects collected from the U.S Nutrition and Health Examination Study (NHANES) dataset also confirmed these findings.


The development of sophisticated image analysis technology made it possible to extract detail information from retinal vessels such as caliber, tortuosity, and bifurcation angles. These measurements can provide accurate and objective assessment of the vessel abnormity.† Studies using WESDR, ARIC data found an association between retinal vessel caliber and diabetic retinopathy, nephropathy and even early metabolic symptom.† We further conducted a pilot study to investigate the association between retinal vessel measurements and neuropathy severity. The statistics from our pilot study showed a U-shape change of the vessel caliber in the early stage of neuropathy. Interestingly, similar trend was found in a study investigating retinal vessel caliber and diabetic peripheral neuropathy using 608 patients from Malaysia eye study.


Based on all the information, we proposed that retinal vessel measurement could be used as a promising tool for the early detection of diabetic neuropathy.