Post-infusion Costs Associated with Idecabtagene Vicleucel Treatment for Patients with Relapsed/Refractory Multiple Myeloma in the KarMMa Trial.

INTRODUCTION: Patients with triple-class exposed relapsed/refractory multiple myeloma (RRMM) have poor outcomes with substantial healthcare costs. Idecabtagene vicleucel (ide-cel), a B-cell maturation antigen (BCMA)-directed chimeric antigen receptor (CAR) T cell therapy, showed deep, durable responses in patients with RRMM in the pivotal phase 2 KarMMa trial (NCT03361748). Healthcare resource utilization (HCRU) and costs were estimated for ide-cel-treated patients in the KarMMa trial. METHODS: Post-infusion costs were estimated based on HCRU data, including facility care, diagnostics, medications, and procedures. Length of stay (LOS) was extracted for inpatient and intensive care unit (ICU) care. All patients had a 14-day post-infusion inpatient stay per trial protocol. Analyses were conducted for patients treated in the United States (US), who received the ide-cel target dose of 450 × 106 CAR + T cells and assuming a 7-day inpatient stay. RESULTS: Overall, 128 patients received ide-cel and were included in this analysis. Mean age was 60 years, 59% were men, and 81% were white. Mean total LOS was 23.9 days. Total estimated costs over 24 months post-infusion were US$115,614 per patient, driven by facility costs (75%; $86,385). Most costs were incurred in the first month (58%; $67,259). The scenario analysis assuming a 7-day inpatient stay showed estimated 24-month costs of $92,294. For the 54 (42%) patients who received ide-cel high dose, total costs over 24 months were $113,298 per patient. CONCLUSIONS: Extrapolation of costs based on HCRU data from patients receiving single-infusion of ide-cel in the KarMMa trial showed substantially reduced HCRU and costs over 2 years after initial treatment. Most costs were incurred during the first month after ide-cel infusion, likely attributable to the 14-day inpatient stay required by the trial protocol. These findings suggest a nominal, incremental monthly cost of care immediately after treatment, which may be lower in routine clinical practice.

3D Printed Skull Cap and Benchtop Fabricated Microwire-Based Microelectrode Array for Custom Rat Brain Recordings.

Microwire microelectrode arrays (MEAs) have been a popular low-cost tool for chronic electrophysiological recordings and are an inexpensive means to record the electrical dynamics crucial to brain function. However, both the fabrication and implantation procedures for multi-MEAs on a single rodent are time-consuming and the accuracy and quality are highly manual skill-dependent. To address the fabrication and implantation challenges for microwire MEAs, (1) a computer-aided designed and 3D printed skull cap for the pre-determined implantation locations of each MEA and (2) a benchtop fabrication approach for low-cost custom microwire MEAs were developed. A proof-of-concept design of a 32-channel 4-MEA (8-wire each) recording system was prototyped and tested through Sprague Dawley rat recordings. The skull cap design, based on the CT-scan of a single rat conforms well with multiple Sprague Dawley rats of various sizes, ages, and weight with a minimal bregma alignment error (A/P axis standard error of the mean = 0.25 mm, M/L axis standard error of the mean = 0.07 mm, n = 6). The prototyped 32-channel system was able to record the spiking activities over five months. The developed benchtop fabrication method and the 3D printed skull cap implantation platform would enable neuroscience groups to conduct in-house design, fabrication, and implantation of customizable microwire MEAs at a lower cost than the current commercial options and experience a shorter lead time for the design modifications and iterations.

Switch rates and total cost associated with apremilast and biologics in biologic-naive patients with psoriatic arthritis.

Aim: Real-world treatment data for psoriatic arthritis are limited. We evaluated switch rates, adherence, and costs for patients initiating apremilast versus tumor necrosis factor inhibitor (TNFi) and interleukin inhibitor (ILi) among biologic-naive psoriatic arthritis patients. Materials & methods: This retrospective analysis used IBM MarketScan claims data to assess treatment switches, adherence and costs. Results: Twelve-month switch rates were significantly lower for apremilast versus TNFi (15.5% vs 26.6%; p < 0.0001) and similar to ILi (15.5% vs 14.0%; p = 0.71). Apremilast initiators had lower total costs versus TNFi and ILi (US$39,854 vs US$57,243 and US$65,687; p < 0.05) and adherence was slightly lower versus TNFi and higher versus ILi. Conclusion: Biologic-naive apremilast initiators had lower switch rates versus TNFi initiators and lower total costs versus TNFi or ILi initiators.

Switch Rates and Total Cost of Care Associated with Apremilast and Biologic Therapies in Biologic-Naive Patients with Plaque Psoriasis.

PURPOSE: Compare treatment switching rates and costs among biologic-naive psoriasis patients initiating apremilast or biologics. METHODS: This retrospective claims analysis used IBM MarketScan Commercial and Medicare Supplemental databases to identify patients who initiated apremilast or a biologic (ie, tumor necrosis factor [TNF] or interleukin [IL] inhibitor) for psoriasis treatment between January 1, 2015, and December 31, 2016. A 1:1 propensity score matching was used to adjust for possible selection bias and maximize the number of patients available for analysis. Treatment switching, days to switch, and healthcare costs were assessed at 12 months. T-test and chi-square test were used to evaluate differences between cohorts for continuous and categorical variables as appropriate; Wilcoxon rank-sum tests were used to assess cost differences. RESULTS: In total, 88,025 patients newly initiated apremilast, a TNF inhibitor, or an IL inhibitor. After inclusion/exclusion criteria were applied and patients were propensity score matched, 1645 (apremilast), 1207 (TNF inhibitor), and 438 (IL inhibitor) patients were included in this analysis. Twelve-month switch rates were significantly lower for apremilast initiators compared with TNF inhibitor initiators (14% vs 25%; p<0.01) and comparable to IL inhibitors (14% vs 11%; p>0.05). No statistical difference was observed in days to switch at 12 months for any treatment group. Total healthcare costs were lower for apremilast initiators compared with TNF and IL inhibitor initiators ($34,028 vs $55,973 and $64,430; p<0.0001). Per-patient per-month (PPPM) costs were significantly lower for apremilast initiators compared with TNF inhibitor and IL inhibitor initiators ($2834 vs $4662 and $5366; p<0.0001). CONCLUSION: Over a 12-month follow-up, biologic-naive psoriasis patients initiating apremilast had significantly lower switching rates compared with patients on TNF inhibitors and similar rates as patients on IL inhibitors. PPPM and total healthcare costs were significantly lower for patients initiating apremilast vs TNF or IL inhibitors, primarily due to lower pharmacy costs.

Real-world switch patterns and healthcare costs in biologic-naive psoriasis patients initiating apremilast or biologics.

Aim: Treatment switching and healthcare costs were compared among biologic-naive psoriasis patients initiating apremilast or biologics with ≥12 months pre-/post-index continuous enrollment in Optum Clinformatics™ Data Mart. Methods: After propensity score matching, switch rates (new therapy post-index) and days between index and switch were assessed. Total and per-patient per-month costs by service type were assessed. Results: Apremilast initiators (n = 533) were matched and compared with biologic initiators (n = 955). Twelve-month cumulative switch rates and days to switch were similar. Apremilast initiators had significantly lower total healthcare costs than biologic initiators; apremilast switchers and nonswitchers had significantly lower per-patient per-month costs than biologic switchers and nonswitchers, driven mainly by reduced outpatient pharmacy costs. Conclusion: Apremilast initiators had lower healthcare costs even with treatment switching.

Treatment Switch Patterns and Healthcare Costs in Biologic-Naive Patients with Psoriatic Arthritis.

INTRODUCTION: We compared treatment switch patterns and healthcare costs among biologic-naive patients with psoriatic arthritis (PsA) who initiated apremilast or biologics. METHODS: A 1:2 propensity score match was used to adjust administrative claims data for adults initiating apremilast or biologics from January 1, 2014, to September 30, 2016, for possible selection bias. Patients had at least 12 months of pre- and post-index continuous enrollment in the Optum Clinformatics™ Data Mart database. Outcomes included switch frequency, days to switch, adherence on index treatment, and healthcare costs (total and per patient per month). Switch rate was defined as the proportion of patients who switched to a new treatment after initiation of the index treatment, and days to switch was calculated as the days between initiation of the index treatment and initiation of the new treatment. Adherence was calculated using the proportion of days covered and the medication possession ratio. The t test and chi-square, Kaplan-Meier, and Wilcoxon rank-sum tests were used to evaluate differences between the cohorts. RESULTS: Patient characteristics and switch rates were similar between the matched apremilast (n = 170) and biologic (n = 327) cohorts. After matching, patient characteristics were similar between the matched cohorts. The 12-month switch rates were similar for patients initiating apremilast versus those on biologics (17.7% vs. 25.1%, P = 0.06). This trend was similar at 6 months (7.7% vs. 13.2%, P = 0.07) and 18 months (24.4% vs. 29.3%, P = 0.33). Regardless of treatment switching, 12-month total healthcare costs were lower with apremilast versus biologics (all: $28,423 vs. $41,178, P < 0.0001; switched: $39,803 vs. $51,517, P = 0.0040; did not switch: $25,984 vs. $37,717, P < 0.0001). CONCLUSIONS: Biologic-naive patients with PsA who initiated apremilast had switch rates similar to biologic users and significantly lower healthcare costs, regardless of treatment switching.

Psoriatic arthritis (PsA) is a chronic inflammatory disease that affects an estimated 30% of psoriasis patients who use systemic therapy. Symptoms of PsA, such as joint swelling and tenderness, can be painful and disabling and may worsen quality of life. PsA can also impart a substantial economic burden. Treatment for moderate to severe PsA often involves the use of systemic oral medications (e.g., conventional systemic treatments such as methotrexate or targeted systemic treatments such as apremilast) or biologic therapy given by injection or infusion. Because PsA symptoms and responses to treatment can vary, patients may switch treatments over time. More research is needed to better understand how switching treatments affects healthcare costs among patients starting treatment with apremilast or a biologic for PsA. This study compared treatment switching and healthcare costs among patients with PsA who had never been treated with a biologic and who started treatment with apremilast or a biologic for PsA. Rates of treatment switching at 12 months were similar for patients starting treatment with apremilast versus those starting a biologic. Patients starting treatment with apremilast had significantly lower total healthcare costs compared with those starting a biologic, even if they later switched to a biologic. Healthcare costs calculated per patient per month (PPPM) were also lower with apremilast versus biologics, driven by lower PPPM pharmacy costs. These findings suggest that starting treatment with apremilast may be an effective and cost-effective strategy for managing PsA, even for patients who later switch to a biologic.

Treatment patterns and healthcare costs among biologic-naive patients initiating apremilast or biologics for the treatment of psoriatic arthritis: results from a US claims analysis.

Objective: Information on treatment costs for psoriatic arthritis (PsA) can be valuable for payers and providers who make treatment and formulary decisions. This study compared real-world treatment patterns and healthcare costs among biologic-naive patients with PsA initiating apremilast or biologics.Methods: A retrospective cohort study was conducted using the Optum Clinformatics™ claims database. The study included biologic-naive patients with PsA who initiated treatment with apremilast or a biologic between 1 January 2014, and 31 December 2015. Propensity score matching was used to adjust for selection bias. Treatment persistence/adherence and all-cause healthcare costs were evaluated. Cost differences were determined using Wilcoxon rank-sum tests.Results: In all, 125 biologic-naive patients initiating treatment with apremilast were matched to 245 biologic-naive patients initiating treatment with a biologic. Twelve-month treatment persistence was similar for apremilast vs. biologic users (43.2 vs. 36.7%; p = .2277). While persistent on treatment for up to 12 months, total healthcare costs (from all utilizations) were significantly lower among apremilast vs. biologic users ($28,130 vs. $37,093; p < .0001). Likewise, per-patient per-month costs while persistent on treatment were significantly lower among apremilast vs. biologic users whether they switched treatments ($2,455 vs. $3,497; p = .0103), remained persistent on treatment ($2,434 vs. $3,521; p < .0001), or discontinued but did not switch treatments ($2,178 vs. $2,696; p = .0082).Conclusions: Apremilast patients had significantly lower healthcare costs than biologic patients, even when they switched to a biologic, during the 12-month post-index period. These results may be useful to payers and providers seeking to optimize PsA care while reducing healthcare costs.

Lenalidomide maintenance post-transplantation in newly diagnosed multiple myeloma: real-world outcomes and costs.

Aim: To compare real-world outcomes and costs among patients with newly diagnosed multiple myeloma receiving lenalidomide-only maintenance (Len-Mt) versus no maintenance after autologous hematopoietic stem cell transplantation. Patients & methods: Time to next treatment (TTNT) was evaluated; costs were calculated for 0-12, 12-24 and 24-36 months postindex date. Results: Len-Mt cohort had longer TTNT (HR: 0.43; p < 0.0001). Per-patient per-month costs during months 0-12 were higher among patients, receiving Len-Mt (USD 13,095 vs USD 8910; p < 0.0001), due to higher pharmacy costs - outpatient costs were lower. During months 12-24 and 24-36, outpatient costs were similar in both cohorts; total and pharmacy costs remained elevated for patients receiving Len-Mt. Conclusion: Len-Mt improved TTNT, initially reduced outpatient costs, but resulted in higher overall and pharmacy costs.

Real-world treatment patterns and healthcare costs among biologic-naive patients initiating apremilast or biologics for the treatment of psoriasis.

OBJECTIVE: This study compared real-world treatment patterns and healthcare costs among biologic-naive psoriasis patients initiating apremilast or biologics. METHODS: A retrospective cohort study was conducted using the Optum Clinformatics™ claims database. Patients with psoriasis were selected if they had initiated apremilast or biologics between January 1, 2014, and December 31, 2015; had 12 months of pre-index and post-index continuous enrollment in the database; and were biologic-naive. The index date was defined as the date of the first claim for apremilast or biologic, and occurred between January 1, 2014, and December 31, 2015. Treatment persistence was defined as continuous treatment without a > 60-day gap in therapy (discontinuation) or a switch to a different psoriasis treatment during the 12-month post-index period. Adherence was defined as a medication possession ratio (MPR) of ≥ 80% while persistent on the index treatment. Persistence-based MPR was defined as the number of days with the medication on hand measured during the patients' period of treatment persistence divided by the duration of the period of treatment persistence. Because patients were not randomized, apremilast patients were propensity score matched up to 1:2 to biologic patients to adjust for possible selection bias. Treatment persistence/adherence and all-cause healthcare costs were evaluated. Cost differences were determined using Wilcoxon rank-sum tests. RESULTS: In all, 343 biologic-naive patients initiating apremilast were matched to 680 biologic-naive patients initiating biologics. After matching, patient characteristics were similar between cohorts. Twelve-month treatment persistence was similar for biologic-naive patients initiating apremilast vs biologics (32.1% vs 33.2%; p = 0.7079). While persistent on therapy up to 12 months, per-patient per-month (PPPM) total healthcare costs were significantly lower among biologic-naive cohorts initiating apremilast vs biologics ($2,214 vs $5,184; p < 0.0001). Likewise, PPPM costs while persistent on therapy were significantly lower among patients initiating apremilast vs biologics, whether they switched treatments ($2,475 vs $4,422; p < 0.0001), remained persistent ($2,279 vs $3,883; p < 0.0001), or discontinued but did not switch treatments ($2,104 vs $6,294; p < 0.0001). LIMITATIONS: Data were limited to individuals with United Healthcare commercial and Medicare Advantage insurance plans, and may not be generalizable to psoriasis patients with other insurance or without health insurance coverage. CONCLUSION: Biologic-naive patients with similar patient characteristics receiving apremilast vs biologics had significantly lower PPPM costs, even when they switched to biologics during the 12-month post-index period. These results may be useful to payers and providers seeking to optimize psoriasis care while reducing healthcare costs.

Comparative Effectiveness of nab-Paclitaxel Plus Gemcitabine vs FOLFIRINOX in Metastatic Pancreatic Cancer: A Retrospective Nationwide Chart Review in the United States.

INTRODUCTION: nab-Paclitaxel plus gemcitabine (nab-P + G) and FOLFIRINOX (FFX) are among the most common first-line (1L) therapies for metastatic adenocarcinoma of the pancreas (MPAC), but real-world data on their comparative effectiveness are limited. METHODS: This retrospective cohort study compared the efficacy and safety of 1L nab-P + G versus FFX, overall and under specific treatment sequences. Medical records were reviewed by 215 US physicians who provided information on MPAC patients who initiated 1L therapy with nab-P + G or FFX between April 1, 2015 and December 31, 2015. Study outcomes were overall survival (OS) and tolerability. OS was compared using Kaplan-Meier curves and adjusted Cox proportional hazards models. RESULTS: In total, 654 medical records were reviewed, including those of 337 and 317 patients initiated on nab-P + G and FFX as 1L MPAC therapy, respectively. nab-P + G-initiated patients were older, less likely to have ECOG ≤ 1, and had more comorbidities than FFX-initiated patients. Median OS (mOS) was 12.1 and 13.8 months for nab-P + G- and FFX-initiated patients, respectively (HR = 0.99, P = 0.96). Among patients with ECOG ≤ 1, mOS was 14.1 and 13.7 months, respectively (HR = 1.00, P = 0.99). Among patients with 1L nab-P + G and FFX, 36.1% and 41.3% received 2L therapy and experienced mOS of 16.3 and 16.6 months, respectively (HR = 1.04, P = 0.76). The rates of diarrhea, fatigue, mucositis, and nausea and vomiting were significantly higher in the FFX than nab-P + G cohort. CONCLUSION: The real-world survival was similar between patients receiving 1L nab-P + G or FFX both overall and among patients who received active 2L treatments. In addition, nab-P + G was associated with significantly lower rates of common AEs compared with FFX. FUNDING: Celgene.

Assessing the Effect of Adherence on Patient-reported Outcomes and Out of Pocket Costs Among Patients With Multiple Myeloma.

BACKGROUND: The present study characterized the effect of multiple myeloma (MM) on work productivity, health care resource usage, and out of pocket costs (OOPCs) and examined the association of adherence with quality of life (QoL) and productivity loss. MATERIALS AND METHODS: The present cross-sectional study included 162 patients categorized by their 4-item Morisky Medication Adherence Scale (MMAS-4) score (4 vs. ≤ 3). Online surveys included the Work Productivity and Activity Impairment questionnaire, Functional Assessment of Cancer Therapy-Multiple Myeloma (FACT-MM), and MM-specific questions. RESULTS: On average, patients reported FACT-MM scores of 98.5 ± 29.3, absenteeism of 18.3% ± 17.8%, presenteeism of 51.8% ± 30.2%, overall work productivity impairment of 57.3% ± 31.7%, and activity impairment of 49.9% ± 29.5% in the previous 7 days. During the previous 3 months, the mean OOPCs were $709 ± $1307; prescription medications accounted for 55% of these costs. Patients attended 4.1 ± 4.6 visits to oncologists or hematologists during that time, which accounted for 45% of the OOPCs. Patients spent an average of 6.8 ± 8.3 hours at MM-related monthly appointments, and 35.2% reported frustration while at the doctor's office. Patients with an MMAS-4 score of 4 reported higher FACT-MM scores (106.9 vs. 89.2; P < .001). Patients with an MMAS-4 score of ≤ 3 reported greater activity impairment (56.5% vs. 39.8%; P = .015) and feeling overwhelmed or frustrated with rescheduling MM appointments (64.0% vs. 26.0%; P = .002). CONCLUSION: MM was associated with significant workplace and functional impairment, high OOPCs, and frequent office visits. High medication adherence was associated with better outcomes across these domains. As survival for patients with MM improves, patient QoL should be considered to enhance these outcomes.

Performance-Based Risk-Sharing Arrangements: U.S. Payer Experience.

BACKGROUND: As a result of global concern about rising drug costs, many U.S. payers and European agencies such as the National Health Service have partnered with pharmaceutical companies in performance-based risk-sharing arrangements (PBRSAs) by which manufacturers share financial risk with health care purchasing entities and authorities. However, PBRSAs present many administrative and legal challenges that have minimized successful contract experiences in the United States. OBJECTIVE: To (a) identify drug and disease characteristics and contract components that contribute to successful PBRSA experiences and the primary barriers to PBRSA execution and (b) explore solutions to facilitate contract negotiation and execution. METHODS: A 37-item, web-based survey instrument (Qualtrics), approximately 20 minutes in duration, was open during July and August 2016. The survey was emailed to 90 pharmacy and medical directors of various health care organizations. Statistical analysis included the Kruskal-Wallis test and chi-square tests to examine differences among payer responses. Survey responses were anonymized and data were aggregated. RESULTS: Twenty-seven individuals completed the survey (30% completion rate). The majority of respondents worked for regional health plans (52%, n = 14), covering at least 1 million lives (63%, n = 17), with at least 7 years of managed care experience (81%, n = 22). A total of 51 PBRSAs were active among respondents at the time of the survey. Easily obtainable and evaluable drug data and medical data were the most important drug and disease attributes for successful PBRSAs, respectively. Pharmacy claims and patient demographic data were assessed as "very easy and inexpensive" to collect. Type and amount of manufacturer payment for drug outcome performance failure, endpoint measurement, and necessary clinical data for drug performance measurement were all critical factors for successful PBRSAs. Standardized contract templates and transparent contract financial risk evaluation and modeling ranked highest among methods of manufacturer facilitation of PBRSAs. This study was limited by sample size and survey questions were limited to explanation of PBRSAs at the disease state level. CONCLUSIONS: On the basis of PBRSA experiences, respondents noted that drug use in chronic medical conditions and objective drug outcome performance measurements were favorable drug characteristics and serve as the primary source of satisfaction for these types of contracts. Third parties and manufacturers can facilitate the uptake and success of PBRSAs by developing standardized contracting templates in addition to other methods that increase their stake in the arrangement. Looking forward, mounting perceptions of success in this realm of contracting for pharmaceuticals may contribute in the quest for value-based payments in the U.S. health care system. DISCLOSURES: The construction of the survey and payment for survey respondents were supported by Charles River Associates. Parece is an employee of Charles River Associates. Goble and Ung are completing fellowship training sponsored by Novartis and Celgene, respectively, but do not have any conflicts of interest and did not receive any funding related to this study. Navarro reports consulting fees from Analysis Group, TEVA, and Amgen, unrelated to this study. Van Boemmel-Wegmann declares no conflict of interest. Study concept and design were contributed by Navarro, Goble, Ung, and Parece. Navarro took the lead in data collection, along with Goble and Ung, and data interpretation was performed by van Boemmel-Wegmann, Goble, and Ung. The manuscript was written by Goble, Ung, Navarro, and van Boemmel-Wegmann and revised by all of the authors.

The Affordable Care Act, health care reform, prescription drug formularies and utilization management tools.

The U.S. Patient Protection and Affordable Care Act (hence, Affordable Care Act, or ACA) was signed into law on March 23, 2010. Goals of the ACA include decreasing the number of uninsured people, controlling cost and spending on health care, increasing the quality of care provided, and increasing insurance coverage benefits. This manuscript focuses on how the ACA affects pharmacy benefit managers and consumers when they have prescriptions dispensed. PBMs use formularies and utilization control tools to steer drug usage toward cost-effective and efficacious agents. A logic model was developed to explain the effects of the new legislation. The model draws from peer-reviewed and gray literature commentary about current and future U.S. healthcare reform. Outcomes were identified as desired and undesired effects, and expected unintended consequences. The ACA extends health insurance benefits to almost 32 million people and provides financial assistance to those up to 400% of the poverty level. Increased access to care leads to a similar increase in overall health care demand and usage. This short-term increase is projected to decrease downstream spending on disease treatment and stunt the continued growth of health care costs, but may unintentionally exacerbate the current primary care physician shortage. The ACA eliminates limitations on insurance and increases the scope of benefits. Online health care insurance exchanges give patients a central location with multiple insurance options. Problems with prescription drug affordability and control utilization tools used by PBMs were not addressed by the ACA. Improving communication within the U.S. healthcare system either by innovative health care delivery models or increased usage of health information technology will help alleviate problems of health care spending and affordability.