Research Spotlight

Jongeneel, G., M. J. E. Greuter, F. N. van Erning, M. Koopman, J. P. Medema, R. Kandimalla, A. Goel, L. Bujanda, G. A. Meijer, R. J. A. Fijneman, M. G. H. van Oijen, J. Ijzermans, C. J. A. Punt, G. R. Vink and V. M. H. Coupé (2020). “Modeling Personalized Adjuvant TreaTment in EaRly stage coloN cancer (PATTERN).” Eur J Health Econ May 26. [Epub ahead of print].

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AIM: To develop a decision model for the population-level evaluation of strategies to improve the selection of stage II colon cancer (CC) patients who benefit from adjuvant chemotherapy. METHODS: A Markov cohort model with a one-month cycle length and a lifelong time horizon was developed. Five health states were included; diagnosis, 90-day mortality, death other causes, recurrence and CC death. Data from the Netherlands Cancer Registry were used to parameterize the model. Transition probabilities were estimated using parametric survival models including relevant clinical and pathological covariates. Subsequently, biomarker status was implemented using external data. Treatment effect was incorporated using pooled trial data. Model development, data sources used, parameter estimation, and internal and external validation are described in detail. To illustrate the use of the model, three example strategies were evaluated in which allocation of treatment was based on (A) 100% adherence to the Dutch guidelines, (B) observed adherence to guideline recommendations and (C) a biomarker-driven strategy. RESULTS: Overall, the model showed good internal and external validity. Age, tumor growth, tumor sidedness, evaluated lymph nodes, and biomarker status were included as covariates. For the example strategies, the model predicted 83, 87 and 77 CC deaths after 5 years in a cohort of 1000 patients for strategies A, B and C, respectively. CONCLUSION: This model can be used to evaluate strategies for the allocation of adjuvant chemotherapy in stage II CC patients. In future studies, the model will be used to estimate population-level long-term health gain and cost-effectiveness of biomarker-based selection strategies.

Johannesson, L., G. Testa, R. Flyckt, R. Farrell, C. Quintini, A. Wall, K. O’Neill, A. Tzakis, E. G. Richards, S. M. Gordon and P. M. Porrett (2020). “Guidelines for standardized nomenclature and reporting in uterus transplantation: An opinion from the United States Uterus Transplant Consortium.” Am J Transplant May 7. [Epub ahead of print].

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Uterus transplantation is a nascent but growing field. To support this growth, the United States Uterus Transplant Consortium proposes guidelines for nomenclature related to operative technique, vascular anatomy, and donor, recipient, and offspring outcomes. In terms of anatomy, the group recommends reporting donor arterial inflow and recipient anastomotic site delivering inflow to the graft and offers standardization of the names for the 4 veins originating from the uterus because of current inconsistency in this particular nomenclature. Seven progressive stages with milestones of success are defined for reporting on uterus transplantation outcomes: (1) technical, (2) menstruation, (3) embryo implantation, (4) pregnancy, (5) delivery, (6) graft removal, and (7) long-term follow-up. The 3 primary metrics for success are recipient survival (as reported for other organ transplant recipients), graft survival, and uterus transplant live birth rate (defined as live birth per transplanted recipient). A number of secondary outcomes should also be reported, most of which capture stage-specific milestones, as well as data on graft failure. Outcome metrics for living donors include patient survival, survival free of operative intervention, and data on complications and hospitalizations. Finally, we make specific recommendations on follow-up for offspring born from uterine grafts, which includes specialty surveillance as well as collection and reporting of routine pediatric outcomes. The goal of standardization in reporting is to create consistency and improve the quality of evidence available on the efficacy and value of the procedure.

Holmes, D. R., Jr., M. J. Mack, M. Alkhouli and S. Vemulapalli (2020). “Racial disparities and democratization of health care: A focus on TAVR in the United States.” Am Heart J 224: 166-170.

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What can be said with certainty is that there are real and documented disparities in care involving TAVR in the increasing population of patients with aortic stenosis.1–8,28–32These disparities may become more prominent as TAVR becomes the standard of care. There are multiple issues relating to this disparity including socioeconomic,genetic, personal valuations and expectations, access to care, and follow-up. Approaches to resolution need to take into consideration of these multiple issues from many angles and include multiple stakeholders – hospital systems to promote culturally competent team based care, reimbursement agencies, patient education, family support systems access to community based educational programs, industry resources working to develop trials with specific focus and recruitment goals to include racialand ethnic groups, and social services.29-32The CMS Accountable Health Communities Model project has been implemented and could potentially be used by the centers involved to focus on one limb of unmet needs. [No abstract; excerpt from article p.169-170].

Goldsweig, A. M., H. J. Tak, L. W. Chen, H. D. Aronow, B. Shah, D. Kolte, N. R. Desai, M. Szerlip, P. Velagapudi and J. D. Abbott (2020). “Relative Costs of Surgical and Transcatheter Aortic Valve Replacement and Medical Therapy.” Circ Cardiovasc Interv 13(5): e008681.

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BACKGROUND: The number of patients treated for aortic valve disease in the United States is increasing rapidly. Transcatheter aortic valve replacement (TAVR) is supplanting surgical aortic valve replacement (SAVR) and medical therapy (MT). The economic implications of these trends are unknown. Therefore, we undertook to determine the costs, inpatient days, and number of admissions associated with treating aortic valve disease with SAVR, TAVR, or MT. METHODS: Using the Nationwide Readmissions Database, we identified patients with aortic valve disease admitted 2012 to 2016 for SAVR, TAVR, and disease symptoms (congestive heart failure, unstable angina, non-ST-elevation myocardial infarction, syncope). Patients not undergoing SAVR or TAVR were classified as receiving MT. Beginning with the index admission, we estimated inpatient costs, days, and admissions over 6 months. RESULTS: Among 190 563 patients with aortic valve disease, the average aggregate 6-month inpatient costs were $59 743 for SAVR, $64 395 for TAVR, and $23 460 for MT. Mean index admission was longer for SAVR (10.0 days) than for TAVR (7.0 day) or MT (5.3 days), but the average number of unplanned readmission inpatient days was 2.0 for SAVR, 3.0 for TAVR, and 4.3 for MT; the average number of total admissions was 1.3 for SAVR, 1.5 for TAVR, and 1.7 for MT (P<0.01 for all). TAVR index admission costs decreased over time to become similar to SAVR costs by 2016. CONCLUSIONS: Aggregate costs were higher for TAVR than SAVR and were significantly more expensive than MT alone. However, TAVR costs decreased over time while SAVR and MT costs remained unchanged.

Goff, R. R., K. Uccellini, K. Lindblad, S. Hall, R. Davies, M. Farr, S. Silvestry and J. G. Rogers (2020). “A change of heart: Preliminary results of the US 2018 adult heart allocation revision.” Am J Transplant May 14. [Epub ahead of print].

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In 2018, the Organ Procurement and Transplantation Network (OPTN) modified adult heart allocation to better stratify candidates and provide broader access to the most medically urgent candidates. We analyzed OPTN data that included waiting list and transplant characteristics, geographical distribution, and early outcomes 1 year before (pre: October 18, 2017-October 17, 2018) and following (post: October 18, 2018-October 17, 2019) implementation. The number of adult heart transplants increased from 2954 pre- to 3032 postimplementation. Seventy-eight percent of transplants in the post era were for the most medically urgent (statuses 1-3) compared to 68% for status 1A in the pre era. The median distance between the donor hospital and transplant center increased from 83 to 216 nautical miles, with an increase in total ischemic time from 3 to 3.4 hours (all P < .001). Waiting list mortality was not different across eras (14.8 vs 14.9 deaths per 100 patient-years pre vs post respectively). Posttransplant patient survival was not different, 93.6% pre and 92.8% post. There is early evidence that the heart allocation policy has enhanced stratification of candidates by their medical urgency and broader distribution for the most medically urgent candidates with minimal impact on overall waiting list mortality and posttransplant outcomes.