Background Metastatic Merkel cell carcinoma (mMCC) is a rare and aggressive skin cancer. Until recently, there were no licensed treatment options for patients with mMCC, and prognosis was poor. A cost-effectiveness analysis was conducted for avelumab, a newly available treatment option for mMCC, versus standard care (SC), from a UK National Health Service perspective. Methods A partitioned survival model was developed to assess the lifetime costs and effects of avelumab versus SC. Data from the JAVELIN Merkel 200 trial (NCT02155647) were used to inform estimates of quality-adjusted life-years (QALYs). Unit costs and associated frequencies of use were informed by published literature and clinical expert opinion. Results were presented as incremental cost-effectiveness ratios (ICERs, i.e. the cost per QALY gained) for treatment-experienced (TE) and treatment-naïve (TN) patients. Uncertainty was explored through a range of sensitivity analyses. Results Discounting costs and QALYs at 3.5% per annum, avelumab was associated with ICERs of £35,274 (TE)/£39,178 (TN) per QALY gained. Probabilistic sensitivity analysis results demonstrated that avelumab was associated with an 88.3% (TE)/69.3% (TN) probability of being cost effective at a willingness-to-pay threshold for end-of-life treatments of £50,000 per QALY gained. Results were most sensitive to alternative survival extrapolations and dosing assumptions. Conclusions The analysis results suggest that avelumab is likely to be a cost-effective treatment option for UK mMCC patients. The results for TN patients are subject to some uncertainty, and a confirmatory analysis will be conducted with more mature data.

Background: Due to limited duration of follow up in clinical trials of cancer treatments, estimates of lifetime survival benefits are typically derived using statistical extrapolation methods. To justify the method used, a range of approaches have been proposed including statistical goodness-of-fit tests and comparing estimates against a previous data cut (i.e. interim data collected). In this study, we extend these approaches by presenting a range of extrapolations fitted to four pre-planned data cuts from the JAVELIN Merkel 200 (JM200) trial. By comparing different estimates of survival and goodness-of-fit as JM200 data mature, we undertook an iterative process of fitting and re-fitting survival models to retrospectively identify early indications of likely long-term survival. Methods: Standard and spline-based parametric models were fitted to overall survival data from each JM200 data cut. Goodness-of-fit was determined using an assessment of the estimated hazard function, information theorybased methods and objective comparisons of estimation accuracy. Best-fitting extrapolations were compared to establish which one provided the most accurate estimation, and how statistical goodness-of-fit differed. Results: Spline-based models provided the closest fit to the final JM200 data cut, though all extrapolation methods based on the earliest data cut underestimated the 'true' long-term survival (difference in restricted mean survival time [RMST] at 36 months: − 1.1 to − 0.5 months). Goodness-of-fit scores illustrated that an increasingly flexible model was favored as data matured. Given an early data cut, a more flexible model better aligned with clinical expectations could be reasonably justified using a range of metrics, including RMST and goodness-of-fit scores (which were typically within a 2-point range of the statistically 'best-fitting' model). Conclusions: Survival estimates from the spline-based models are more aligned with clinical expectation and provided a better fit to the JM200 data, despite not exhibiting the definitively 'best' statistical goodness-of-fit. Longer-term data are required to further validate extrapolations, though this study illustrates the importance of clinical plausibility when selecting the most appropriate model. In addition, hazard-based plots and goodness-of-fit tests from multiple data cuts present useful approaches to identify when a more flexible model may be advantageous.

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Study (IES). Health effects were expressed in terms of quality adjusted life years (QALYS). Direct medical costs were obtained from the governmental hospitals in Egypt. All costs and effects were discounted at 3.5% annually according to the Egyptian pharmacoeconomic guidelines. Deterministic sensitivity analyses were conducted. Results: The study revealed that Exemestane yielded an additional gain of 0.23 QALYs at lower cost estimated by EGP 24,976 than Tamoxifen over 15-years, Exemestane is the dominant therapy. Deterministic sensitivity analyses indicated that the transition probability between health states of no recurrence to distant metastasis for Exemestane arm had the greatest impact on the results. ConClusions: Exemestane 25mg is a cost saving strategy compared to Tamoxifen 20mg in post-menopausal women with early breast cancer.

Introduction: Multiple myeloma (MM) is an incurable disease characterized by the proliferation of malignant plasma cells within the bone marrow, causing a wide range of burdensome symptoms. Patients initiating treatment typically receive a combination of drugs across various classes with or without autologous stem cell transplantation (ASCT). However, patients will invariably relapse following initial treatment, and often require many lines of drug treatment over the course of their disease. Real-word data showed that a significant proportion of newly diagnosed MM patients that receive frontline (FL) treatment did not receive subsequent treatment. These high attrition rates suggest that using the best treatment upfront is crucial in delaying disease progression. The CASSIOPEIA (transplant-eligible [TE] setting), MAIA and ALCYONE (transplant-ineligible [TIE] setting) trials demonstrate that the addition of daratumumab (DARA) to standard of care treatments in FL significantly improves patient outcomes. Based on data from these trials, the European marketing authorization for DARA has been extended to the FL setting. To ensure the best possible long-term patient outcomes in clinical practice, the availability of new FL treatment options requires a redefinition of treatment patterns. Thus, we aim to investigate whether the adoption of DARA as a FL, as opposed to later-line, treatment of MM leads to better outcomes and improved clinical practice. Methods: In the absence of real-world sequencing data, we developed a clinical sequencing simulation using individual patient data from the DARA trials and indirect comparative evidence, across all indications in MM. We used progression-free survival curves to simulate health state transition probabilities across four lines of active treatment, to capture the efficacy of treatment sequences in MM. Patients start with initiation of FL treatment, and ASCT eligibility determines the sequences patients receive. Clinical expert opinion was sought to determine 1) the full range of meaningful treatment sequences and 2) which of these are used most in Italian clinical practice. Based on the clinical simulation outcomes, we calculated average time spent in each line of treatment, percentage of patients alive at different timepoints, and the total survival for patients initiating a sequence. This analysis included conservative attrition rates from trial data, 14% for TE (CASSIOPEIA) and 24% for TIE (MAIA/ALCYONE), assumed as similar across regimens in each setting. Results: In the TE setting, the best outcomes were achieved when using the DARA-based regimen (DVTd) as FL treatment, followed by either a LEN-based regimen (KRd) or a BOR-based regimen (PVd), resulting in a total survival of 14.2 and 14.1 years, respectively. In the TIE setting, the best outcomes were achieved when DRd or DVMP were used as FL treatment, followed by either a BOR-based regimen (PVd, for DRd) or a LEN-based regimen (KRd, for DVMP), resulting in a total survival of 11.7 and 10.9 years, respectively. In both the FL and second line (2L) settings, there was a clear survival benefit of using DARA. When comparing the DARA-based sequence with the current FL TE benchmark sequence (DVTd + KRd + Pd + Vd versus VTd + DRd + Kd + Pd), an additional survival of 1.5 years was observed in TE patients. When DARA was added to the current FL TIE benchmark sequence (DRd + PVd + Kd + Vd versus VMP + DRd + Kd + Pd), TIE patients lived on average 2.8 years longer. For TE patients, time spent progression-free ranged from an average of 4.83 to 7.99 years at FL, 1.42 to 5.40 years in 2L, 0.23 to 2.24 years in 3L and 0.17 to 1.53 years on 4L. For TIE patients, the variation was higher, leaving more room for optimization: 1.97 to 7.31 years at FL, 0.68 to 4.76 years in 2L, 0.17 to 3.25 years in 3L and 0.19 to 0.51 years in 4L. Conclusion: To our knowledge, this is the first sequencing simulation to consider optimal patient outcomes across several lines of MM treatment. The results show that the longest time in remission is achieved with the use of DARA-based regimens as FL treatment, significantly improving patient outcomes. Time spent progression free decreases with each subsequent line of treatment and the magnitude of the effect seen in the third and fourth treatment lines is not as significant as that of the effect seen in earlier treatment lines. Therefore, patients should be treated with the most effective treatment upfront. Disclosures Petrucci: Celgene: Honoraria, Other: Advisory Board; Janssen-Cilag: Honoraria, Other: Advisory Board; BMS: Honoraria, Other: Advisory Board; Takeda: Honoraria, Other: Advisory Board; Amgen: Honoraria, Other: Advisory Board; GSK: Honoraria, Other: Advisory Board; Karyopharm: Honoraria, Other: Advisory Board. Mendes: Janssen-Cilag Farmacêutica: Current Employment. Boer: Janssen: Consultancy. Casamassima: Janssen: Current Employment. Willis: Janssen: Consultancy. Wadlund: Janssen: Current Employment. Matthijsse: Janssen: Consultancy. Armeni: Astrazeneca: Consultancy; Boehringer Ingelheim: Consultancy; Novartis: Consultancy; Sanofi: Consultancy; Johnson & Johnson: Consultancy; Amgen: Consultancy; Janssen: Consultancy.