Aims: To explore the cost-effectiveness of G5 Mobile CGM compared to SMBG alone in Multiple Daily Injection (MDI) using Type 1 diabetes (T1D) patients in Canada from societal perspective.

AIMS:To evaluate the cost-effectiveness of real-time continuous glucose monitoring (CGM) compared to self-monitoring of blood glucose (SMBG) alone in people with type 1 diabetes (T1DM) using multiple daily injections (MDI) from the Canadian societal perspective. METHODS:The IMS CORE Diabetes Model (v.9.0) was used to assess the long-term (50 years) cost-effectiveness of real-time CGM (G5 Mobile CGM System; Dexcom, Inc., San Diego, CA) compared with SMBG alone for a cohort of adults with poorly-controlled T1DM. Treatment effects and baseline characteristics of patients were derived from the DIAMOND randomized controlled clinical trial; all other assumptions and costs were sourced from published research. The accuracy and clinical effectiveness of G5 Mobile CGM is the same as the G4 Platinum CGM used in the DIAMOND randomized clinical trial. Base case assumptions included (a) baseline HbA1c of 8.6%, (b) change in HbA1c of -1.0% for CGM users vs -0.4% for SMBG users, and (c) disutilities of -0.0142 for non-severe hypoglycemic events (NSHEs) and severe hypoglycemic events (SHEs) not requiring medical intervention, and -0.047 for SHEs requiring medical resources. Treatment costs and outcomes were discounted at 1.5% per year. RESULTS:The incremental cost-effectiveness ratio for the base case G5 Mobile CGM vs SMBG was $33,789 CAD/quality-adjusted life-year (QALY). Sensitivity analyses showed that base case results were most sensitive to changes in percentage reduction in hypoglycemic events and disutilities associated with hypoglycemic events. The base case results were minimally impacted by changes in baseline HbA1c level, incorporation of indirect costs, changes in the discount rate, and baseline utility of patients. CONCLUSIONS:The results of this analysis demonstrate that G5 Mobile CGM is cost-effective within the population of adults with T1DM using MDI, assuming a Canadian willingness-to-pay threshold of $50,000 CAD per QALY.

Objective: To assess the economic impact of providing real time continuous glucose monitoring (CGM) for people with type 1 diabetes (T1D) and impaired awareness of hypoglycaemia (IAH) within North West (NW) London clinical commissioning groups (CCGs). Methods: The eligible population for CGM and inputs for the economic budget impact model developed were derived from published data. The model includes cost of CGM; cost savings associated with lower hypoglycaemia related hospital admissions, accidents and emergency visits; self-monitoring of blood glucose (SMBG) strip usage; and glycated haemoglobin (HbA1c) reduction-related avoided complications and insulin pump use. Results: The cost of CGM for T1D-IAH (n=3,036) in the first year is £10,770,671 and in the fourth year is £11,329,095. The combined cost off-sets related to reduced hypoglycaemia admissions, SMBG strip usage and complications are £8,116,912 and £8,741,026 in years one and four, respectively. The net budget impact within the NW London CCGs is £2,653,760; £2,588,068 in years one and four respectively. Conclusions: Introduction of CGM for T1D-IAH patients will have a minimal budget impact on NW London CCGs, driven by cost of CGM and offsets from lower hypoglycaemia-related costs, reduced SMBG strip usage, avoided HbA1c-related complications and lower insulin pump use.

To evaluate the cost-effectiveness of Real-Time CGM (RTCGM (G5)) compared to SMBG alone in Type 1 Diabetes (T1DM) patients using Multiple Daily Injections (MDI) from the Swedish societal perspective. The Quintiles IMS CORE Diabetes Model (CDM) (v. 9.0) was used to assess the long-term (50 year) cost-effectiveness of RTCGM compared to SMBG alone for a T1DM cohort. Treatment effects and base-line characteristics of patients were sourced from the recently published DIAMOND trial while all other assumptions and costs were sourced from earlier publications. The accuracy and clinical effectiveness of RTCGM (G5) is equivalent to that seen in CGM (G4SW505) used in the DIAMOND trial. Base case (BC) assumptions included a) starting HbA1c 8.6%; b) change in HbA1c: -1.0% for CGM group, -0.4% for SMBG alone; c) 50% reduction in severe hypoglycemic events (SHEs) and 33% reduction in non-severe hypoglycemic events (NSHEs) for the CGM group; d) dis-utilities of -0.0142 for NSHEs and SHEs not requiring medical intervention, and -0.047 for SHEs requiring medical resources. Treatment costs and outcomes were discounted at 3%. The Incremental Cost-Effectiveness Ratio (ICER) for RTCGM vs. SMBG was SEK 180,530/QALY in the base-case. Sensitivity analyses showed the results were sensitive to changes in percent reduction in severe hypoglycemic events and its associated dis-utilities. An ICER of SEK 188,697/QALY was the result of the sensitivity analysis using the treatment effects from the recent Swedish GOLD study using an earlier version RTCGM. The base-case results were minimally impacted by changing starting HbA1c levels and discount rates. RTCGM has the potential to improve clinical outcomes, quality of life and healthcare efficiencies for the large cohort of MDI-treated patients. The results of this evaluation show that RTCGM (G5) is cost effective within the MDI-treated T1DM population, assuming a willingness-to-pay threshold of SEK 500,000 per Quality-Adjusted Life Year in Sweden.

A challenge in DCEs is to capture how individuals process choices and attributes. Chorus, Rose & Hensher (2013) put forth the framework and empirical proof that some attributes may be processed using one type of decision rule (e.g., random utility maximization-RUM), while others using another rule (e.g., random regret minimization-RRM) using the hybrid RUM-RRM modeling approach. This study explores if heterogeneity exists in the way community representatives process choice attributes while assessing preferences for hemophilia therapies. Representative members of the US general population from the RAND American Life Survey panel completed a discrete-choice survey in two waves (N1 = 227; N2= 344). The survey presented a series of 5 trade-off questions, each including a pair of hypothetical treatment profiles and an opt out option. The treatment profiles were described using five attributes: 1. costs, 2. dose adjustment, 3. side-effects, 4. efficacy and dosing frequency and 5. type of dosage. Preferences were analyzed using RUM, RRM and hybrid RUM-RRM modeling strategies. Models were compared using the Ben-Akiva and Swait test for comparison of non-nested models, out of sample predictive ability and willingness-to-pay (WTP) estimates. The hybrid RRM-RUM models, containing both regret-based and utility-based attribute decision rules, outperform choice models where all attributes are assumed to be processed by means of one and the same decision rule i.e. either utility maximization or regret minimization rule; in terms of model fit (p <0.01 Ben-Akiva and Swait test) and out-of-sample predictive ability. The hybrid WTP measures also differ substantially from conventional utility-based WTP measures (p<0.05). The community sample processes the ‘cost’ of treatment attribute in order to ‘minimize regret’ while other treatment attributes are processed differently in order to ‘maximize utility’.

We systematically investigate random utility maximization and random regret minimization modeling approaches to establish the impact of differently framed opt-out alternatives in discrete choice experiments. We hypothesize that within the same experiment, when opt out alternatives are framed as a rejection of all the available alternatives, it is likely to have a detrimental impact on the performance of RRM model, while the performance of RUM model suffers more when the opt out is framed as a respondent being indifferent between the alternatives on offer. We used two waves of data from a discrete choice experiment (N1 = 227; N2= 344); the first wave included an opt-out option implying a rejection of choice alternatives (i.e. none of these) while the second wave included an opt-out option implying a position of ‘indifference’ between the choice alternatives. We compared RUM and RRM models of different sophistications (e.g.; multinomial logit and mixed logit) in terms of parameter estimates, log likelihood and the Ben-Akiva and Swait test for non-nested models. In line with hypotheses, RUM models performed significantly better (P<0.01) than RRM models when opt–out alternative implied rejection of choice alternatives i.e. none of these. The RRM models performed significantly better (p<0.01) than the RUM models when the opt-out alternative implied a position of ‘indifference’. RRM models had difficulty in handling the ‘none of these’ opt-out alternative while the RUM models had difficulty in handling the ‘indifference’ opt out alternative as was evident by the suspiciously large value of opt-out constant in the model parameter estimates for these cases. The framing of opt out alternatives influences the type of behavioral framework to be considered for modeling.

Despite the clearly evident better clinical outcomes with prophylaxis compared to on-demand therapy, on average only 55% of patients diagnosed with severe hemophilia receive prophylactic factor replacement therapy in the US. Prophylaxis generally drops with age, partly due to patients becoming more independent and less compliant as they reach adulthood and partly due to reduced perceived benefit. High treatment costs of prophylaxis therapy also remains a barrier. Further, the development of long-acting factor products offering a modest improvement in convenience is likely to drive-up treatment costs. This study aims to understand hemophilia patient preferences and their willingness-to-pay for hemophilia therapies (on-demand, standard prophylaxis, longer-acting prophylaxis). U.S. adult patients and caregivers of children with hemophilia (n = 79) completed a discrete-choice survey that presented a series of trade-off questions, each including a pair of hypothetical treatment profiles, that had an assigned cost for attaining improvement in health states. The relative importance of treatment attributes such as out-of-pocket treatment costs, dose adjustment, treatment related complications and clinical efficacy & dosing regimen was analyzed using mixed logit models. Based on the attribute estimates, patients’ WTP was determined. Out-of-pocket treatment costs (P < .001), treatment complications (P < .001) and clinical efficacy & dosing regimen (P < .001) were perceived to be the most important treatment attributes. Patients were willing to pay on average $150 per/month for improvement in each of the prophylaxis dosing regimens (i.e. 3 times weekly vs 2 times weekly vs. 1 time weekly vs. 1 time in two weeks). The results suggest that patients are willing to pay more for improvements in treatment related complications, clinical efficacy & dosing regimen. These estimates of patients’ willingness-to-pay can be used to provide guidelines for resource allocation. Literature also suggests that patient preferences are likely to directly translate into increased treatment adherence, leading to greater treatment effectiveness.

Published studies suggest that bypass therapy assay testing can be used to effectively predict treatment response and dosing requirements for an individual hemophilia patient with inhibitors. This study aims to evaluate the costs and treatment outcomes of bypass therapy assay testing versus no testing strategy on different treatments for mild to moderate bleeding hemophilia patient with inhibitors. This study also investigates the cost implications if testing assays could predict the optimum dose for new type of therapies like concomitant therapy. A decision tree simulation model was used to simulate inhibitor treatment costs and outcomes from a US third party payer perspective. All estimates of costs were obtained from the literature or expert opinion and were adjusted to 2011 US dollars. Based on a previous published model, the efficacy of APCC and rFVIIa were assumed to be the same in the no testing scenario while assay testing was assumed to improve the efficacy of both the products by 10%. Probabilistic sensitivity analysis was used to determine the robustness of the model's results. The model was developed using Microsoft Excel and @Risk. If bypass therapy assay testing successfully predicts the treatment response and improves treatment efficacy by just 10%, cost savings of $6939 for APCC and $7699 for rFVIIa treatment were observed per bleeding episode. Further, if testing successfully predicts the optimum dose for concomitant therapy on the onset of bleeding, significant cost savings were observed when compared to rFVIIa and APCC therapies alone. The results were sensitive to frequency of dosing, efficacy, rebleed rate and drug price. Bypass therapy assay testing is recommended for reducing costs while optimizing treatment response and dose before administering treatment in hemophilia patients with inhibitors.

The main objective of this study was to analyze the treatment patterns in patients with advanced NSCLC treatment in a regional community setting: The Georgia Cancer Specialists Network. Patients were included in the study if they were newly diagnosed with NSCLC as of the first practice visit and diagnosed with stage III or stage IV disease between January 1, 2005 and June 2010. Patients treated with chemotherapy were followed from initial NSCLC diagnosis until death, end of study period or lost to follow up. The network's Electronic Medical Record (EMR) was used to identify chemotherapy agents and sequencing of therapy. A total of 291 patients were identified with advanced NSCLC (Stage IIIB or IV). Patients ranged in the age of 40 to 85 years with 125 females and 166 males. Of the 291 patients who received first line therapy, 122 (41.9%) were treated with Carboplatin/Paclitaxel, 45 (15.5%) with Carboplatin/Paclitaxel/Bevacizumab, 24 (8.2%) with Paclitaxel and 19 (6.5%) with Bevacizumab. Of the 125 patients who received second line therapy, 52(17.9%) were treated with Pemetrexed, 13 (4.5%) with Docetaxel and 8(2.7%) with Carboplatin/Gemcitabine. The most common therapies used in the 40 patients who received third line were Pemetrexed with 11 patients (3.8%), Docetaxel with 10 patients (3.4%), Gemcitabine with 4 patients (1.4%) and Vinorelbine with 3 patients (1%). Of these patients with advanced NSCLC, 13.7% received third line therapy after previous treatment with first and second line therapies. The majority of the agents prescribed follow NCCN guidelines. In the third line the wide variation suggests a lack of standard of care. Additional rigorous clinical effectiveness trials of drugs in third line treatment are warranted to understand the benefit in NSCLC patients.

Cetuximab, a chimeric monoclonal antibody, improved the overall survival and progression free survival of chemorefractory metastatic colorectal cancer (mCRC) KRAS wild (unmutated) type patients in the National Cancer Institute of Canada Clinical Trials Group (NCIC CTG) CO.17 study. The objective of our study was to conduct the cost-effectiveness analysis of cetuximab plus best supportive care versus best supportive care alone in KRAS wild type mCRC patients. A Markov cohort simulation model was used to simulate therapy costs and effectiveness from the US societal perspective. All estimates of costs and effectiveness were obtained from the literature. The cost-effectiveness ratio was reported as incremental cost per quality-adjusted life-year (QALY) gained. A life time horizon was used. Base case costs and QALYs were discounted at an annual rate of 3%. All costs were adjusted to 2011 US dollars. One-way and probabilistic sensitivity analyses were used to determine the robustness of the model's results using @Risk. The model was developed using Microsoft Excel. The incremental cost with cetuximab compared with best supportive care alone was $93,934 and the mean gains in quality adjusted survival were 0.30 QALYS. This resulted in base case ICER of $313,113 per QALY gained. The results were highly sensitive to the cost of cetuximab and health state utility values. The incremental cost effectiveness ratio of $313,113 per QALY gained for cetuximab plus BSC compared with BSC alone suggests that cetuximab is not cost effective in KRAS wild type patients with metastatic colorectal cancer even with a willingness-to-pay cut-off threshold of $120-$150,000 per QALY gained.