M Franken

CN7 TREATMENT VARIATION COMPLICATES REAL-WORLD PHARMACOECONOMICS: DAILY CLINICAL PRACTICE OF BORTEZOMIB IN RELAPSED OR REFRACTORY MULTIPLE MYELOMA

patients. A typical PCU admits patients in the final phase of life. A high quality of care by a multi disciplinary team (including nurses, physicians, psychologists, music therapy, physiotherapy and others) results in substantial costs (recent survey in German PCUs: on average ~a400/day). The average length of stay is in the range of 11–15 days, the proportion of discharged patients varies between 40–70%, for the remaining patients the admission ends not unexpectedly with the death of the patients. The gain in utility close to death is difficult to estimate, but even high assumptions (e.g. 0,5) result in costs for QALYs, which are unexpectedly high. Scenario 1: 14, 0.5, 30, 0.5, 400, 192455 a; scenario 2: 14, 0.7,30, 0.5, 400, 172545 a; scenario 3: 14, 0.5, 30, 0.3, 400, 320758 a; scenario 4: 10, 0.5, 30, 0.5, 400, 182500 a for length of stay (d), proportion surviving, survival after discharge (d), gain in utility, cost/day, resulting cost / QALY. People experiencing the sheer necessity of palliative care for a death with dignity may use these data as an argument against the QALY concept. Only by including longterm changes e.g. in the utility gain experienced by relatives (small gains over a long period in several persons, e.g. by avoiding pathological grief) the model results in costs/QALY which seem acceptable.

Matching the model with the evidence: comparing discrete event simulation and state-transition modeling for time-to-event predictions in a cost-effectiveness analysis of treatment in metastatic colorectal cancer patients

BACKGROUND Individual patient data, e.g. from clinical trials, often need to be extrapolated or combined with additional evidence when assessing long-term impact in cost-effectiveness modeling studies. Different modeling methods can be used to represent the complex dynamics of clinical practice; the choice of which may impact cost-effectiveness outcomes. We compare the use of a previously designed cohort discrete-time state-transition model (DT-STM) with a discrete event simulation (DES) model. METHODS The original DT-STM was replicated and a DES model developed using AnyLogic software. Models were populated using individual patient data of a phase III study in metastatic colorectal cancer patients, and compared based on their evidence structure, internal validity, and cost-effectiveness outcomes. The DT-STM used time-dependent transition probabilities, whereas the DES model was populated using parametric distributions. RESULTS The estimated time-dependent transition probabilities for the DT-STM were irregular and more sensitive to single events due to the required small cycle length and limited number of event observations, whereas parametric distributions resulted in smooth time-to-event curves for the DES model. Although the DT-STM and DES model both yielded similar time-to-event curves, the DES model represented the trial data more accurately in terms of mean health-state durations. The incremental cost-effectiveness ratio (ICER) was €172,443 and €168,383 per Quality Adjusted Life Year gained for the DT-STM and DES model, respectively. CONCLUSION DES represents time-to-event data from clinical trials more naturally and accurately than DT-STM when few events are observed per time cycle. As a consequence, DES is expected to yield a more accurate ICER.

Cetuximab as First-line Treatment for Metastatic Colorectal Cancer : Caution With Interpretation of Cost-Effectiveness Results Toward Medical Decision Making

To the Editor: Shankaran and colleagues are to be complimented for their excellent and important work to address the cost-effectiveness of FOLFIRI plus cetuximab as first-line treatment for metastatic colorectal cancer. The reported cost-effectiveness model was based on the randomized clinical phase-3 FIRE-3 study. An incremental cost per effect ratio (ICER) of

A Triple Aim Framework For the Performance Assessment of Disease Management Programs

86,487 per life year gained (LY) for FOLFIRI plus cetuximab compared with FOLFIRI plus bevacizumab was presented. Interestingly, Shankaran and colleagues performed an additional analysis using CALGB/SWOG 80405 results (table 4); the results of this additional analysis seem conflicting with the data presented by Schrag and colleagures in their ASCO 2015 presentation. The benefit of chemotherapy plus cetuximab compared with chemotherapy plus bevacizumab remains a matter of debate due to conflicting overall survival results of the FIRE-3 and CALGB/ SWOG80405 study. Influence of the subsequent treatment regimens has been suggested as a possible explanation for the overall survival difference demonstrated in the FIRE-3 study. Shankaran and colleagues have calculated costeffectiveness in a scenario using the CALGB/SWOG 80405 outcomes, yielding an ICER of

Performance Score Extraction from Panel Data for Multi-Criteria Decision Analysis (Mcda) Using a Regression-Based Approach

121,501/LY. It is important to realize that for this ICER calculation, the FOLFIRI plus cetuximab strategy resulted in an increment cost of

PCN18 OUTCOMES RESEARCH OF BORTEZOMIB INDICATED FOR MULTIPLE MYELOMA IN THE CONTEXT OF THE DUTCH REIMBURSEMENT POLICY FOR EXPENSIVE MEDICINES: THREATS TO THE INTERNAL VALIDITY OF THE INCREMENTAL EFFECTIVENESS ESTIMATE

37,191. This incremental cost is subsequently divided by the increment in effect (life years or quality adjusted life years gained) to calculate an ICER. According to Venook et al, both strategies yield similar survival results; we can only conclude that the cetuximabcontaining strategy results in more costs, while this strategy does not provide a clinically meaningful benefit (median survival difference of 0.9 mo, P = 0.34). Calculating an ICER over treatment strategies that do not yield a difference in clinical outcomes does neither seem meaningful nor appropriate. The FIRE-3 study design did not include a cost-effectiveness evaluation, thus information on resource utilization and possible differences between treatment arms was not readily available. As a consequence, Shankaran and colleagues needed to make assumptions on medical resource use based on reported adverse events only. However, differences in medical resource utilization may exist between treatment arms, such as differences in diagnostic work-up, number and type of imaging used, paracentesis, etc. These differences are yet unaccounted for. Finally, the difference in life years gained between FOLFIRI plus cetuximab and FOLFIRI plus bevacizumab used for the model calculations seems large compared with the medians reported in both the FIRE-3 and the CALGB/SWOG 80405 studies. We recognize that costeffectiveness outcomes are calculated based on the incremental difference between mean costs and mean effects. However, the difference in means between treatment arms should be within range of the difference between medians. In example, the difference between means of the FIRE-3 scenario (or base case) was 0.63 LY, whereas we calculate a difference in medians of 0.31 LY between study arms. A difference in effect of 0.31 LY would yield an ICER of

Cost-effectiveness in colorectal cancer: challenges on quality and comparability

175,912/LY instead of the reported

PCN154 Are Population-Based Registries a Suitable Tool for Outcomes Research in Cancer? Experiences from Four Registries

86,487. For the scenario calculation based on the CALGB/SWOG 80405 study, a mean difference of 0.31 LY was reported, whereas we calculated a median difference of 0.075 LY yielding an ICER of

Healthcare Costs of Ipilimumab in Patients with Advanced Cutaneous Melanoma in Dutch Clinical Practice

495,880/LY. In our opinion, this difference is mainly caused by the fact that the (Kaplan-Meier) survival curves are skewed and this cannot be disregarded in the considerations and interpretation of cost-effectiveness outcomes comparing both treatment strategies. Even though this cost-effectiveness study was very well performed, reported results again illustrate that cost-effectiveness models are complex. We should be cautious in interpreting cost-effectiveness results toward clinical decision making.

Comparative Effectiveness Of Novel Treatments For Advanced Melanoma: A Systematic Literature Review And Network Meta-Analysis Of Effectiveness And Safety Outcomes

markdownabstractObjectives: A structured and comprehensive assessment of disease management implementations is not straightforward due to the broadness of the interventions and the various evaluation possibilities. The aim of this study was to develop a comprehensive framework for outcome measurement of disease management programs based on the triple aim framework of the Institute for Healthcare Improvement to facilitate future performance assessment using multi-criteria decision analysis (MCDA). Methods: Based on literature review and our expertise in performing economic evaluations in disease management we identified domains of outcomes for each aim of the triple aim framework. For each domain we identified indicators to assess the performance of disease management programs. Results: The first aim of the framework, population health improvement, was subdivided into the domains health-adjusted life years, mortality, wellbeing, health-related quality of life (HrQol), complications, symptoms, clinical outcomes, healthy behaviour, knowledge, and self-management skills. The second aim, improvement of patient experience, was subdivided into patient involvement, patient centeredness, continuity of care, coordination, communication, information systems, safety and access. The third aim of cost reductions distinguished program, medical and nonmedical costs. Potential Indicators of the identified sub-criteria include the ASCOT (Adult Social Care Outcomes Toolkit) for measuring wellbeing, smoking rates and BMI (Body Mass Index) to measure healthy behaviour, the EuroQol-5D and Short Form-36 for measuring physical, mental and social HrQol, different dimensions of the PACIC (Patient Assessment of Chronic Illness Care) and CAHPS (Consumer Assessment of Healthcare Providers and Systems) for measuring patient experience and several measurement tools for measuring friction costs and costs of informal care. Conclusions: In designing a structured outcome-based framework for the performance evaluation of disease management programs we paved the way for future work including a comprehensive evaluation of disease management using MCDA. MCDA not only requires measurement of indicators but also weighting of their relative importance.