ALBERT

Description: Abstract 5071 Background: Multiple myeloma (MM) is de second most common haematological malignancy in adults worldwide. MM is common in the elderly. While the general life expectancy is increasing an ever increasing number of patients has to be expected. In the last decade treatment strategies are changed continuously because of the introduction of novel agents and allogeneic and autologous stem cell transplantation. In randomized controlled trials, overall survival in patients up to 65 years is improving convincing. In contrast with results in older patients. We studied data of patients treated outside clinical trials derived from the population based registry in the Netherlands to recognize trends in incidence en survival during 1989–2009. Patients and methods: We included all patients with newly diagnosed MM in the period 1989 – 2009 who were recorded in the Netherlands Cancer Registry (n =16.822 ). Follow-up was until January, 2010. We calculated the yearly age-standardised incidence rates for males and females and age-specific incidence rates in 10 year age groups for both sexes separately and combined. Changes in incidence were evaluated by calculating the estimated annual percentage change (EAPC). We then calculated relative survival, which may be interpreted as disease-specific survival within a cancer patient population. Traditional cohort-based, relative survival analysis was applied for patients diagnosed during 1989–2009. Since follow-up was available until 2010, 5 year relative survival for patients diagnosed in 2004–2009 was estimated using period-based relative survival analysis. Results: The number of newly diagnosed MM cases rose between 1989 and 2009 from 631 to 968 cases respectively. Significantly more males were diagnosed than females over time (p=0.01). Furthermore the proportion of male patients increased slightly over these time periods. However, the overall age standardised incidence rate for males and females remained stable over time but was higher among males than females. The median age at diagnosis was 71 years (p10-P90 range 53–84) and stable over time (p=0.07). Incidence was highest in the 70–79 age group for both sexes. However, because of the aging population the age-specific incidence rates (ASIR) were highest for patients aged 80+ years for both sexes. Within specific age groups significant changes were seen. In the population 50–59 years, the ASIR increased from 5.0 per 100,000 in 1989 to 6.9 in 2009 (EAPC 1989–2009 = + 0.7%; 95% CI: 0.0 –1.3). A decrease was seen in females aged 80+ years from 25.1 per 100,000 in 1989 to 22.4 in 2009 (EAPC 1989–2009 = −1,0; 95% CI: −1.8; −0.2). In the overall patient population the 1-year relative survival increased only slightly from 72% to 77% between 1989 and 2009. 5-year relative survival increased from 28% to 37%. Small improvements in survival were observed for all age groups in the past two decades except for patients aged 80+ years. Relative survival decreased with increasing age. In contrast, in the group aged 40–64 years improvements are already detectable from 1994 on. In 2004–2009 the highest 5-year relative survival, 62%, was seen in patients 40–49 year of age. However the strongest improvement over time was observed among the group 50–59 years. Conclusion: Although the average annual age-adjusted incidence rate remained stable from 1989–2009, the number of newly diagnosed MM patients increased because of the aging population. Relative survival increased slowly but continuously in time for patients until 80 years of age with strongest increase seen in patients up to 64 years of age. Improvement for these younger patients is most likely caused by the introduction of novel agents based regiments as well as by the introduction of high dose chemotherapy followed by stem cell transplantation. Our findings in trends of incidence and survival of MM are similar to those reported in other western populations. Disclosures: Sonneveld: Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen-Cilag: Membership on an entity's Board of Directors or advisory committees, Research Funding; Onyx: Membership on an entity's Board of Directors or advisory committees, Research Funding; Millennium: Membership on an entity's Board of Directors or advisory committees.

Description: Abstract 2079 Background: Peripheral blood stem cell transplantations (PBSCT) are very expensive life-saving medical procedures carried out in patients with hematological disease. The current tariffs are expected to be too low due to developments in the treatment protocols. A revision of the tariffs is urgently necessary. We calculated the daily practice cost of PBSCT for treating hematological diseases in Dutch practice, to provide a proper basis for revising hospital budgets. Patients and methods: From three Dutch university hospitals, we randomly selected 191 who underwent an autologous (auto) or allogeneic (allo) PBSCT in 2008 or 2009. The alloPBSCT were subcategorized into sibling, matched unrelated donor (MUD) and unrelated cord blood (UCB). We obtained data from hospital registrations to study all treatment related activities. Unit prices were based both on real costs and tariffs (base year 2010). Thereafter, the average costs per patient per PBSCT and per period were calculated. The total cost included the selection and harvesting, transplantation and 1-year follow-up. Results: The average cost per patient of autoPBSCT were € 45,670. The cost of sibling alloPBSCT were € 101,919. The average cost of transplantations from an unrelated donor was much higher: € 171,478 for MUD and € 254,689 for UCB alloPBSCT. Hospital days, laboratory procedures and donor search were the largest cost components and mainly responsible for differences between the four types of PBSCT. None of the patient characteristics were correlated with average cost. The costs calculated in this study are above current reimbursement. The difference is significant (p=0.043) and depending on the type of PBSCT, the shortfall varied between 2% and 100%. Conclusion: Average cost of AutoSCT and alloSCT lay above current reimbursement levels. Appropriate financing is necessary to guarantee the continuation of PBSCT in Dutch patients according to current indications. The costs calculated in this study provide reliable input for economic evaluations and cost-effectiveness studies. Disclosures: No relevant conflicts of interest to declare.

Description: Background As with many types of cancer, treatment of multiple myeloma (MM) is characterised by sequential treatment lines consisting of innovative expensive drugs such as thalidomide, bortezomib and lenalidomide. While the cost-effectiveness of single treatments has been studied, a full disease model evaluating treatments sequentially is currently lacking. Therefore, we aimed to take a look at the big picture and calculate real-world costs and effects for commonly used treatment pathways for MM. Methods We developed a patient-level simulation (PLS) model for elderly (〉65) MM patients diagnosed since 2004. Real-world data (N=621) including patient and disease characteristics, treatment information and outcomes as well as resource use was obtained from the Population based HAematological Registry for Observational Studies, PHAROS. Based on this information, a patient population was simulated. Parametric survival models including patient characteristics such as age, performance status, comorbidities, laboratory values and treatment were used to predict overall survival of commonly used treatment pathways. Five treatment categories were distinguished; Melphalan/Prednison, Thalidomide based regimens, Bortezomib based regimens, Lenalidomide based regimens and Other regimens not including a novel agent. Monthly costs, per treatment per line, were calculated based on real-world data. The sensitivity of parameters was explored through sensitivity analyses. Results Mean age of our simulated population was 76 [SD: 6.25, Range 66-93] and 19 commonly used treatment pathways were observed. Average total costs from diagnosis till death ranged from $54,200 [SD: $10,990] (Melphalan/Prednison-Thalidomide-Other) to $172,346 [SD: $27,887] (Lenalidomide-Bortezomib-Other) while overall survival ranged from 29 [SD: 1.02] to 50 [SD 1.75] months for Melphalan/Prednison-Bortezomib-Lenalidomide and Lenalidomide-Bortezomib-Other, respectively. Total costs were especially induced by drug costs and inpatient hospital days. Substantial variation among the treatment pathways was observed with drug costs ranging from 7% ($3,980) of the total costs for Melphalan/Prednison-Thalidomide-Other compared to 53% ($88,058) of the total costs for Lenalidomide-Bortezomib-Thalidomide. In addition, inpatient day costs ranged from 68% ($37,113) of total costs for Melphalan/Prednison-Thalidomide-Bortezomib to 25% ($41,347) of the total costs for Lenalidomide-Bortezomib-Thalidomide. Costs per quality-adjusted-life-year (QALY) were between $29,060 [SD: $5,623] (Melphalan/Prednison-Thalidomide-Other) and $56,179 [SD: $9,190] (Lenalidomide-Bortezomib-Other). In addition to the 19 treatment pathways, we calculated the total costs and overall survival of treatment as observed in daily clinical practice, $79,203 [SD: $12,001] and 32 [SD: 1.33] months, respectively. Compared to real-world prescription, survival could be improved at a cost of $48,543 per QALY and $31,902 per life-year gained (Lenalidomide-Thalidomide-Bortezomib). Conclusion Real-world costs and effects of 19 treatment pathways for MM patients were calculated and revealed that real-world treatment could be improved at a cost of $48,543 per QALY and $31,902 per life-year gained. Our PLS model proved to be a reliable and robust approach to study entire treatment pathways for MM. Disclosures: Sonneveld: Jansssen: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees, Research Funding; Celgene: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees, Research Funding; Onyx: Consultancy, Membership on an entity’s Board of Directors or advisory committees, Research Funding.