Analysis of real-world data to investigate evolving treatment sequencing patterns in advanced non-small cell lung cancers and their impact on survival.

Background: Although optimal sequencing of systemic therapy in cancer care is critical to achieving maximal clinical benefit, there is a lack of analysis of treatment sequencing in advanced non-small cell lung cancer (aNSCLC) in real-world settings. Methods: A retrospective cohort study of 13,340 lung cancer patients within the Mount Sinai Health System (MSHS) was performed. Systemic therapy data of aNSCLC in 2,106 patients was the starting point in our analysis to investigate how treatment sequencing has evolved, the impact of sequencing patterns on clinical outcomes, and the effectiveness of 2nd line chemotherapy after patients progressed on immune checkpoint inhibitor (ICI)-based therapy as the 1st line of therapy (LOT). Results: There is a significant shift to more ICI-based therapy and multiple lines of targeted therapy after 2015. We compared clinical outcomes of two patient populations with different treatment sequencing patterns, with the 1st group receiving chemotherapy as the 1st LOT followed by ICI-based treatment, and the 2nd group treated in the opposite order receiving a 1st line ICI-containing regimen followed by a 2nd line chemotherapy. No statistically significant difference in overall survival (OS) was observed between the two groups [group 2 vs. group 1, adjusted hazard ratio (aHR) =1.36, P=0.39]. We assessed the efficacy of the 2nd line chemotherapy in three patient populations given either 1st line ICI single agent, 1st line ICI-chemotherapy combination, or 1st line chemotherapy alone, there was no statistically significant difference in time-to-next treatment (TTNT) and in OS among the three patient groups. Conclusions: Analysis of real-world data has shown two treatment sequencing patterns in aNSCLC, ICI followed by chemotherapy or chemotherapy followed by ICI, achieved similar clinical benefit. The chemotherapies routinely used following platinum doublet 1st LOT, is effective as the 2nd line option after ICI-chemotherapy combination in the 1st line setting.

Detecting Ground Glass Opacity Features in Patients With Lung Cancer: Automated Extraction and Longitudinal Analysis via Deep Learning-Based Natural Language Processing.

BACKGROUND: Ground-glass opacities (GGOs) appearing in computed tomography (CT) scans may indicate potential lung malignancy. Proper management of GGOs based on their features can prevent the development of lung cancer. Electronic health records are rich sources of information on GGO nodules and their granular features, but most of the valuable information is embedded in unstructured clinical notes. OBJECTIVE: We aimed to develop, test, and validate a deep learning-based natural language processing (NLP) tool that automatically extracts GGO features to inform the longitudinal trajectory of GGO status from large-scale radiology notes. METHODS: We developed a bidirectional long short-term memory with a conditional random field-based deep-learning NLP pipeline to extract GGO and granular features of GGO retrospectively from radiology notes of 13,216 lung cancer patients. We evaluated the pipeline with quality assessments and analyzed cohort characterization of the distribution of nodule features longitudinally to assess changes in size and solidity over time. RESULTS: Our NLP pipeline built on the GGO ontology we developed achieved between 95% and 100% precision, 89% and 100% recall, and 92% and 100% F1-scores on different GGO features. We deployed this GGO NLP model to extract and structure comprehensive characteristics of GGOs from 29,496 radiology notes of 4521 lung cancer patients. Longitudinal analysis revealed that size increased in 16.8% (240/1424) of patients, decreased in 14.6% (208/1424), and remained unchanged in 68.5% (976/1424) in their last note compared to the first note. Among 1127 patients who had longitudinal radiology notes of GGO status, 815 (72.3%) were reported to have stable status, and 259 (23%) had increased/progressed status in the subsequent notes. CONCLUSIONS: Our deep learning-based NLP pipeline can automatically extract granular GGO features at scale from electronic health records when this information is documented in radiology notes and help inform the natural history of GGO. This will open the way for a new paradigm in lung cancer prevention and early detection.

Transforming Healthcare Delivery: Integrating Dynamic Simulation Modelling and Big Data in Health Economics and Outcomes Research.

In the era of the Information Age and personalized medicine, healthcare delivery systems need to be efficient and patient-centred. The health system must be responsive to individual patient choices and preferences about their care, while considering the system consequences. While dynamic simulation modelling (DSM) and big data share characteristics, they present distinct and complementary value in healthcare. Big data and DSM are synergistic-big data offer support to enhance the application of dynamic models, but DSM also can greatly enhance the value conferred by big data. Big data can inform patient-centred care with its high velocity, volume, and variety (the three Vs) over traditional data analytics; however, big data are not sufficient to extract meaningful insights to inform approaches to improve healthcare delivery. DSM can serve as a natural bridge between the wealth of evidence offered by big data and informed decision making as a means of faster, deeper, more consistent learning from that evidence. We discuss the synergies between big data and DSM, practical considerations and challenges, and how integrating big data and DSM can be useful to decision makers to address complex, systemic health economics and outcomes questions and to transform healthcare delivery.

Selecting a dynamic simulation modeling method for health care delivery research-part 2: report of the ISPOR Dynamic Simulation Modeling Emerging Good Practices Task Force.

In a previous report, the ISPOR Task Force on Dynamic Simulation Modeling Applications in Health Care Delivery Research Emerging Good Practices introduced the fundamentals of dynamic simulation modeling and identified the types of health care delivery problems for which dynamic simulation modeling can be used more effectively than other modeling methods. The hierarchical relationship between the health care delivery system, providers, patients, and other stakeholders exhibits a level of complexity that ought to be captured using dynamic simulation modeling methods. As a tool to help researchers decide whether dynamic simulation modeling is an appropriate method for modeling the effects of an intervention on a health care system, we presented the System, Interactions, Multilevel, Understanding, Loops, Agents, Time, Emergence (SIMULATE) checklist consisting of eight elements. This report builds on the previous work, systematically comparing each of the three most commonly used dynamic simulation modeling methods-system dynamics, discrete-event simulation, and agent-based modeling. We review criteria for selecting the most suitable method depending on 1) the purpose-type of problem and research questions being investigated, 2) the object-scope of the model, and 3) the method to model the object to achieve the purpose. Finally, we provide guidance for emerging good practices for dynamic simulation modeling in the health sector, covering all aspects, from the engagement of decision makers in the model design through model maintenance and upkeep. We conclude by providing some recommendations about the application of these methods to add value to informed decision making, with an emphasis on stakeholder engagement, starting with the problem definition. Finally, we identify areas in which further methodological development will likely occur given the growing "volume, velocity and variety" and availability of "big data" to provide empirical evidence and techniques such as machine learning for parameter estimation in dynamic simulation models. Upon reviewing this report in addition to using the SIMULATE checklist, the readers should be able to identify whether dynamic simulation modeling methods are appropriate to address the problem at hand and to recognize the differences of these methods from those of other, more traditional modeling approaches such as Markov models and decision trees. This report provides an overview of these modeling methods and examples of health care system problems in which such methods have been useful. The primary aim of the report was to aid decisions as to whether these simulation methods are appropriate to address specific health systems problems. The report directs readers to other resources for further education on these individual modeling methods for system interventions in the emerging field of health care delivery science and implementation.

Applying dynamic simulation modeling methods in health care delivery research-the SIMULATE checklist: report of the ISPOR simulation modeling emerging good practices task force.

Health care delivery systems are inherently complex, consisting of multiple tiers of interdependent subsystems and processes that are adaptive to changes in the environment and behave in a nonlinear fashion. Traditional health technology assessment and modeling methods often neglect the wider health system impacts that can be critical for achieving desired health system goals and are often of limited usefulness when applied to complex health systems. Researchers and health care decision makers can either underestimate or fail to consider the interactions among the people, processes, technology, and facility designs. Health care delivery system interventions need to incorporate the dynamics and complexities of the health care system context in which the intervention is delivered. This report provides an overview of common dynamic simulation modeling methods and examples of health care system interventions in which such methods could be useful. Three dynamic simulation modeling methods are presented to evaluate system interventions for health care delivery: system dynamics, discrete event simulation, and agent-based modeling. In contrast to conventional evaluations, a dynamic systems approach incorporates the complexity of the system and anticipates the upstream and downstream consequences of changes in complex health care delivery systems. This report assists researchers and decision makers in deciding whether these simulation methods are appropriate to address specific health system problems through an eight-point checklist referred to as the SIMULATE (System, Interactions, Multilevel, Understanding, Loops, Agents, Time, Emergence) tool. It is a primer for researchers and decision makers working in health care delivery and implementation sciences who face complex challenges in delivering effective and efficient care that can be addressed with system interventions. On reviewing this report, the readers should be able to identify whether these simulation modeling methods are appropriate to answer the problem they are addressing and to recognize the differences of these methods from other modeling approaches used typically in health technology assessment applications.

Applying quantitative benefit-risk analysis to aid regulatory decision making in diagnostic imaging: methods, challenges, and opportunities.

RATIONALE AND OBJECTIVES: Health agencies making regulatory marketing-authorization decisions use qualitative and quantitative approaches to assess expected benefits and expected risks associated with medical interventions. There is, however, no universal standard approach that regulatory agencies consistently use to conduct benefit-risk assessment (BRA) for pharmaceuticals or medical devices, including for imaging technologies. Economics, health services research, and health outcomes research use quantitative approaches to elicit preferences of stakeholders, identify priorities, and model health conditions and health intervention effects. MATERIALS AND METHODS: Challenges to BRA in medical devices are outlined, highlighting additional barriers in radiology. Three quantitative methods--multi-criteria decision analysis, health outcomes modeling and stated-choice survey--are assessed using criteria that are important in balancing benefits and risks of medical devices and imaging technologies. RESULTS: To be useful in regulatory BRA, quantitative methods need to: aggregate multiple benefits and risks, incorporate qualitative considerations, account for uncertainty, and make clear whose preferences/priorities are being used. Each quantitative method performs differently across these criteria and little is known about how BRA estimates and conclusions vary by approach. While no specific quantitative method is likely to be the strongest in all of the important areas, quantitative methods may have a place in BRA of medical devices and radiology. DISCUSSION: Quantitative BRA approaches have been more widely applied in medicines, with fewer BRAs in devices. Despite substantial differences in characteristics of pharmaceuticals and devices, BRA methods may be as applicable to medical devices and imaging technologies as they are to pharmaceuticals. Further research to guide the development and selection of quantitative BRA methods for medical devices and imaging technologies is needed.

Feasibility of an online mindfulness program for stress management--a randomized, controlled trial.

BACKGROUND: Chronic stress affects many Americans. Stress management programs may be prohibitively expensive or have limited access. PURPOSE: This study aims to determine feasibility of an 8-week Internet-based stress management program (ISM) based on mindfulness principles in reducing stress in a 12-week, parallel, randomized, controlled trial. METHODS: Participants were randomly allocated to ISM, ISM plus online message board (ISM+), or control groups. Perceived stress, mindfulness, self-transcendence, psychological well-being, vitality, and quality of life were measured at baseline, week 8, and week 12 using standard validated questionnaires. RESULTS: ISM and ISM+ groups demonstrated statistically significant improvements compared with control on all measures except vitality and physical health. CONCLUSIONS: The ISM program effectively and sustainably reduced measures of stress. The magnitude of improvement is comparable to traditional mindfulness programs, although fewer participants were engaged. This feasibility study provides strong support for online stress management programs, which increase access at a fraction of cost of traditional programs.

Innovation in diagnostic imaging services: assessing the potential for value-based reimbursement.

Innovation in the field of diagnostic imaging is based primarily on the availability of new and improved equipment that opens the door for new clinical applications. Payments for these imaging procedures are subject to complex Medicare price control schemes, affecting incentives for appropriate use and innovation. Achieving a "dynamically efficient" health care system-one that elicits a socially optimal amount of innovation-requires that innovators be rewarded in relation to the value they add and can demonstrate with evidence. The authors examine how and whether value-based reimbursement for diagnostic imaging services might better reward innovation explicitly for expected improvements in health and economic outcomes.

Optimizing CAD diagnosis in China with CT angiography.

BACKGROUND: Diagnosis of coronary artery disease (CAD) in China with coronary angiography (CA) can be challenging because of high disease prevalence and limited resources. Coronary computed tomography angiography (CTA) may provide an opportunity to minimize invasive diagnostic procedures among intermediate-risk patients indicated for CA and increase patient access to diagnosis of CAD in a cost-effective manner. OBJECTIVE: This study was conducted to evaluate the potential costs and efficiency of using CTA in combination with CA to optimize diagnosis and care of patients with suspected CAD in China. METHODS: We conducted a cost-consequences analysis from the perspective of Fuwai Hospital in Beijing. We developed a decision-analytic model that compared a diagnostic strategy of CA only with a strategy of CTA in combination with CA for patients with intermediate pretest probability of significant CAD and indicated for CA. RESULTS: In the base-case analysis, use of CTA in combination with CA led to a cost-savings of US $597 per patient evaluated compared with the CA-only diagnostic strategy. The hospital cost per angiography-confirmed diagnosis of CAD was US $8,103 for CTA followed by CA compared with US $9,148 for CA only. The unit cost of CA, and CTA sensitivity were the most influential parameters on the results. The range of cost savings associated with use of CTA followed by CA was US $768 - US $461 per patient over a CAD prevalence range of 14% - 59%. CONCLUSION: The results of our study suggest that CTA implementation in China for intermediate-risk patients indicated for CA may optimize the patient population that undergoes invasive CA procedures and may provide cost savings for Chinese hospitals.

A cost-effectiveness analysis of antibiotic therapy in macrolide-resistant community-acquired pneumonia.

Successful treatment of community-acquired pneumonia (CAP) can have substantial implications. As rates of antibiotic resistance of Streptococcus pneumoniae--the most common pathogen of CAP-increase, so does the likelihood that first-line pharmacotherapy will fail. Thus, the cost effectiveness and budgetary effects of treating CAP with amoxicillin/ clavulanate (AMX/CLA) extended-release (ER) and clarithromycin ER were analyzed. The model considers incidence of macrolide and AMX/ CLA-susceptible and nonsusceptible S. pneumoniae in empiric therapy. Clinical cure rates from multicenter clinical trials and published literature were used to calculate average treatment costs and success. Amoxicillin/ clavulanate ER resulted in a higher percentage of patients cured compared with clarithromycin ER (88.7% vs. 82.4%, respectively) and lower average per-patient treatment costs (dollar 437.70 vs. dollar 548.14, respectively).

The quality of life impact of acute exacerbations of chronic bronchitis (AECB): a literature review.

BACKGROUND: The impact of acute exacerbations of chronic bronchitis (AECB), a common consequence of chronic obstructive pulmonary disease (COPD), is extensive, with symptoms ranging from mild to life threatening. Health-related quality of life (HRQL) is impaired in patients with COPD, but little is known about the direct effect of exacerbations on HRQL. METHODS: MEDLINE and EMBASE literature searches were conducted; reference lists of identified articles were reviewed. RESULTS: Eighteen studies reporting the impact on HRQL of acute exacerbations were identified. Study design and patient population varied. Six studies evaluated HRQL once; only four studies used both generic and disease-specific HRQL measures. Cross-sectional studies reported HRQL decrements during exacerbations and suggested that HRQL is a good predictor of health care resource utilization. Pharmacological treatment led to within-group improvements following AECBs. Non-pharmacological intervention studies were small and inconclusive. Longitudinal studies, assessing pharmacological and non-pharmacological interventions, found that HRQL improved from exacerbation to recovery, with responsiveness depending on sensitivity of the measure. Frequency of exacerbations was a significant predictor of HRQL. CONCLUSIONS: Exacerbations lead to substantial reductions in HRQL, both in physical as well as other domains. Further research should assess the impact of specific treatment regimens and the timeline for the recovery process.

CYP2C9 haplotype structure in European American warfarin patients and association with clinical outcomes.

OBJECTIVE: The goal of this study was to define the haplotype structure of the cytochrome P450 (CYP) 2C9 gene in a European American population and evaluate associations between CYP2C9 haplotypes and anticoagulation-related outcomes. METHODS: Genomic deoxyribonucleic acid from 192 European American patients stabilized on warfarin therapy was resequenced across 60 kilobases of the CYP2C9 genomic region, including all exons, dense sampling of introns, approximately 10 kilobases of the 5'-flanking region, and approximately 1.7 kilobases of the 3'-untranslated region. RESULTS: A total of 132 single nucleotide polymorphisms (SNPs) were detected, of which 47 were present in the 5'-flanking promoter region, 11 in the exonic coding region, and 74 in the intron regions. Nine nonsynonymous SNPs in the coding region consisted of CYP2C9*2 , *3 , *9 , *11 , and *12 ; R125H; and 3 new structural variants. Sixty SNPs were present at a minor allele frequency of greater than 5%, and from this subpopulation, 23 haplotypes were inferred. Clustering analysis identified 6 major groups of related haplotypes that were further designated 1A, 1B, 1C, 1D, 2, or 3. The *2 and *3 SNPs appeared exclusively in groups 2 and 3, and these groups combined were associated with significantly reduced warfarin maintenance doses, longer time to stable dosing, and increased risk of bleeding. In contrast, combinations of haplotypes 1A, 1B, 1C, and 1D were not associated with differences in any of these outcomes. CONCLUSION: These data establish a whole-gene, high-resolution haplotype structure for CYP2C9 in a European American patient population and suggest that genetic variation in exons, rather than the promoter or other regulatory regions, is largely responsible for warfarin sensitivity associated with CYP2C9 variants in this population.

Health economic evaluation of non-melanoma skin cancer and actinic keratosis.

Non-melanoma skin cancer (NMSC) and actinic keratosis are becoming an increasingly important healthcare problem. There are approximately 1 million cases of NMSC in the US each year, primarily basal cell carcinomas, and the incidence is increasing. Although NMSC is significant in terms of both health risk and the resource implications for treatment within healthcare systems, our understanding of the health economics of NMSC is limited. The purpose of this article was to systematically review and assess published health economic studies of the treatment of NMSC and actinic keratosis, taking into consideration key aspects of guidelines set by drug purchasers and key reimbursement agencies, and to provide recommendations for appropriate modelling approaches and data collection for health economic studies of NMSC and actinic keratosis. We systematically reviewed the published literature from 1965 to 2003 for health economic evaluations of treatments of NMSC and actinic keratosis using the search terms: ('skin cancer' or 'non melanoma skin cancer' or 'basal cell carcinoma' or 'actinic keratosis') and ('decision model' or 'decision theoretic' or 'decision analytic' or 'health economic' or 'cost effective'). Studies using one of the following methodologies were included: cost-effectiveness, cost-benefit, cost-utility, cost-minimisation, cost-of-illness, cost-consequence, and treatment cost analysis. We identified eight studies evaluating NMSC. One of these studies also evaluated actinic keratosis. Although several studies satisfied some of the basic requirements of health economic evaluations, the majority had serious shortcomings that limit their usefulness. There are a few high-quality health economic evaluations assessing treatments for NMSC or actinic keratosis. However, our analysis suggests that additional data on treatment practice patterns and epidemiology need to be collected, and incorporated with efficacy and safety data in a formal decision-analytic framework to assist decision makers in allocating scarce healthcare resources.

The workplace impact of acute exacerbations of chronic bronchitis (AECB); A literature review.

Acute exacerbations of chronic bronchitis (AECB) are known to have a substantial economic burden in terms of medical care costs. The objective of this study was to assess workplace-based costs associated with AECB, including absenteeism and decreased productivity, based on a review of published literature. A secondary goal was to identify factors related to workplace-based costs in AECB. A literature search was conducted to identify relevant articles assessing one or more aspects of work loss or workplace costs among patients with chronic bronchitis. A review of the identified literature indicates that patients with chronic bronchitis had more days off work; patients whose exacerbations were treated were less likely to have additional exacerbations and had comparatively less work loss. Findings suggest that clinical outcomes and workplace costs are related. While this relationship is clearer in terms of work loss, further exploration is needed to assess decreased productivity and to evaluate this relationship using objective indicators of absenteeism and productivity rather than recall.

The economic impact of acute exacerbations of chronic bronchitis in the United States and Canada: a literature review.

BACKGROUND: Acute exacerbations of chronic bronchitis (AECB) are recurrent and potentially severe medical events for the 13 million people in the United States who have chronic bronchitis. Medical resource use associated with AECB can have a substantial economic impact on the patients, health care system, and society overall. OBJECTIVE: To evaluate literature on the economic impact of AECB in terms of cost of illness, cost of treatments, and cost-effectiveness. METHODS: A MEDLINE literature search was conducted for studies of chronic bronchitis and costs. Reference lists of identified articles were also retrieved for review. RESULTS: Eight published studies were identified: 2 cost-of-illness studies, 1 comparative cost study, and 5 cost-effectiveness studies. Important drivers of costs associated with AECB include hospitalization and choice of antibiotics. In mild to moderate AECB, patient adherence with therapy is essential to consider when selecting treatment. The antibiotic with the lowest acquisition cost has not been shown to be the most cost effective, as adherence and clinical outcomes, particularly rehospitalization rates, differ. CONCLUSION: Further research in these areas is needed to guide clinical decision making and the conduct of disease management programs.

Managed care in the genomics era: assessing the cost effectiveness of genetic tests.

BACKGROUND: Despite the fact that the Human Genome Project was completed only recently, genetic tests already have entered the marketplace, some with few or no long-term data to support their use. Managed care organizations will face reimbursement decisions for genetic tests on a growing scale, and they should have a framework in place to evaluate the clinical and economic outcomes of this new class of diagnostics. OBJECTIVE: To develop a set of criteria that could assist decision makers in evaluating the cost effectiveness of genetic testing. METHODS: A literature review was conducted of marketed genetic tests and criteria used to evaluate the clinical and economic benefits of genetic testing. Criteria were developed and pilot-tested on currently available genetic tests in colon cancer, periodontitis, acute lymphoblastic leukemia, and anticoagulation. RESULTS: A robust cost-effectiveness analysis requires data demonstrating (1) genotype-phenotype association; (2) genetic variant prevalence; (3) clinical outcome severity and incidence; (4) interventions for the variant group; and (5) sensitivity, specificity, and timing of the assay result. In addition, calculating the number of patients who need to be screened based on the above factors is useful for evaluating genetic tests. CONCLUSIONS: When evaluating a genetic test for reimbursement, these criteria can help to: (1) quantify the potential clinical benefit and economic savings; (2) assess the robustness of a cost-effectiveness analysis; and (3) clarify areas where data are deficient. These criteria should be used to inform the decision-making process in the context of ethical, legal, and social issues related to genetic testing.

Association between CYP2C9 genetic variants and anticoagulation-related outcomes during warfarin therapy.

CONTEXT: Warfarin is a commonly used anticoagulant that requires careful clinical management to balance the risks of overanticoagulation and bleeding with those of underanticoagulation and clotting. The principal enzyme involved in warfarin metabolism is CYP2C9, and 2 relatively common variant forms with reduced activity have been identified, CYP2C9*2 and CYP2C9*3. Patients with these genetic variants have been shown to require lower maintenance doses of warfarin, but a direct association between CYP2C9 genotype and anticoagulation status or bleeding risk has not been established. OBJECTIVE: To determine if CYP2C9*2 and CYP2C9*3 variants are associated with overanticoagulation and bleeding events during warfarin therapy. DESIGN AND SETTING: Retrospective cohort study conducted at 2 anticoagulation clinics based in Seattle, Wash. PARTICIPANTS: Two hundred patients receiving long-term warfarin therapy for various indications during April 3, 1990, to May 31, 2001. Only patients with a complete history of warfarin exposure were included. MAIN OUTCOME MEASURES: Anticoagulation status, measured by time to therapeutic international normalized ratio (INR), rate of above-range INRs, and time to stable warfarin dosing; and time to serious or life-threatening bleeding events. RESULTS: Among 185 patients with analyzable data, 58 (31.4%) had at least 1 variant CYP2C9 allele and 127 (68.6%) had the wild-type (*1/*1) genotype. Mean maintenance dose varied significantly among the 6 genotype groups (*1/*1 [n = 127], *1/*2 [n = 28], *1/*3 [n = 18], *2/*2 [n = 4], *2/*3 [n = 3], *3/*3 [n = 5]) (by Kruskall-Wallis test, chi(2)(5) = 37.348; P<.001). Compared with patients with the wild-type genotype, patients with at least 1 variant allele had an increased risk of above-range INRs (hazard ratio [HR], 1.40; 95% confidence interval [CI], 1.03-1.90). The variant group also required more time to achieve stable dosing (HR, 0.65; 95% CI, 0.45-0.94), with a median difference of 95 days (P =.004). In addition, although numbers were small for some genotypes, representing potentially unstable estimates, patients with a variant genotype had a significantly increased risk of a serious or life-threatening bleeding event (HR, 2.39; 95% CI, 1.18-4.86). CONCLUSIONS: The results of our study suggest that the CYP2C9*2 and CYP2C9*3 polymorphisms are associated with an increased risk of overanticoagulation and of bleeding events among patients in a warfarin anticoagulation clinic setting, although small numbers in some cases would suggest the need for caution in interpretation. Screening for CYP2C9 variants may allow clinicians to develop dosing protocols and surveillance techniques to reduce the risk of adverse drug reactions in patients receiving warfarin.

The cost-effectiveness of interleukin-1 genetic testing for periodontal disease.

BACKGROUND: A genetic test for a composite interleukin-1 (IL-1) genotype is being marketed to predict risk for progression of periodontal disease. The objective of this study was to determine the clinical scenario required to produce cost-effective results with the use of IL-1 testing to identify high-risk patients. METHODS: A disease simulation model was developed using decision-analytic techniques and a 30-year time frame. RESULTS: Using different modeling scenarios, the genetic test produced results ranging from cost savings of $830,140 and 52.8 fewer cases of severe periodontitis to increased costs of $300,430 and 3.6 additional cases of severe periodontitis (per 1,000 patients). Three parameters in the analysis were highly influential: 1) the compliance rate for maintenance therapy in test positive versus non-tested patients; 2) the effectiveness of non-surgical therapy; and 3) the relative risk of disease progression for test positive patients. CONCLUSION: The model produced a wide range of outcomes reflecting our incomplete understanding of the biology, optimal treatment, and genetic susceptibility of periodontal diseases. However, the model demonstrates that three clinical parameters are highly influential in determining if IL-1 testing can be implemented in a primary care setting in a cost-effective manner.