世界経済・社会統計 = World development indicators

WRITING GROUP MEMBERS Emelia J. Benjamin, MD, SCM, FAHA Michael J. Blaha, MD, MPH Stephanie E. Chiuve, ScD Mary Cushman, MD, MSc, FAHA Sandeep R. Das, MD, MPH, FAHA Rajat Deo, MD, MTR Sarah D. de Ferranti, MD, MPH James Floyd, MD, MS Myriam Fornage, PhD, FAHA Cathleen Gillespie, MS Carmen R. Isasi, MD, PhD, FAHA Monik C. Jiménez, ScD, SM Lori Chaffin Jordan, MD, PhD Suzanne E. Judd, PhD Daniel Lackland, DrPH, FAHA Judith H. Lichtman, PhD, MPH, FAHA Lynda Lisabeth, PhD, MPH, FAHA Simin Liu, MD, ScD, FAHA Chris T. Longenecker, MD Rachel H. Mackey, PhD, MPH, FAHA Kunihiro Matsushita, MD, PhD, FAHA Dariush Mozaffarian, MD, DrPH, FAHA Michael E. Mussolino, PhD, FAHA Khurram Nasir, MD, MPH, FAHA Robert W. Neumar, MD, PhD, FAHA Latha Palaniappan, MD, MS, FAHA Dilip K. Pandey, MBBS, MS, PhD, FAHA Ravi R. Thiagarajan, MD, MPH Mathew J. Reeves, PhD Matthew Ritchey, PT, DPT, OCS, MPH Carlos J. Rodriguez, MD, MPH, FAHA Gregory A. Roth, MD, MPH Wayne D. Rosamond, PhD, FAHA Comilla Sasson, MD, PhD, FAHA Amytis Towfighi, MD Connie W. Tsao, MD, MPH Melanie B. Turner, MPH Salim S. Virani, MD, PhD, FAHA Jenifer H. Voeks, PhD Joshua Z. Willey, MD, MS John T. Wilkins, MD Jason HY. Wu, MSc, PhD, FAHA Heather M. Alger, PhD Sally S. Wong, PhD, RD, CDN, FAHA Paul Muntner, PhD, MHSc On behalf of the American Heart Association Statistics Committee and Stroke Statistics Subcommittee Heart Disease and Stroke Statistics—2017 Update

Heart Disease and Stroke Statistics—2017 Update: A Report From the American Heart Association

Author(s): Writing Group Members; Mozaffarian, Dariush; Benjamin, Emelia J; Go, Alan S; Arnett, Donna K; Blaha, Michael J; Cushman, Mary; Das, Sandeep R; de Ferranti, Sarah; Despres, Jean-Pierre; Fullerton, Heather J; Howard, Virginia J; Huffman, Mark D; Isasi, Carmen R; Jimenez, Monik C; Judd, Suzanne E; Kissela, Brett M; Lichtman, Judith H; Lisabeth, Lynda D; Liu, Simin; Mackey, Rachel H; Magid, David J; McGuire, Darren K; Mohler, Emile R; Moy, Claudia S; Muntner, Paul; Mussolino, Michael E; Nasir, Khurram; Neumar, Robert W; Nichol, Graham; Palaniappan, Latha; Pandey, Dilip K; Reeves, Mathew J; Rodriguez, Carlos J; Rosamond, Wayne; Sorlie, Paul D; Stein, Joel; Towfighi, Amytis; Turan, Tanya N; Virani, Salim S; Woo, Daniel; Yeh, Robert W; Turner, Melanie B; American Heart Association Statistics Committee; Stroke Statistics Subcommittee

Heart Disease and Stroke Statistics—2016 Update: A Report From the American Heart Association

March 5, 2019 e1 WRITING GROUP MEMBERS Emelia J. Benjamin, MD, ScM, FAHA, Chair Paul Muntner, PhD, MHS, FAHA, Vice Chair Alvaro Alonso, MD, PhD, FAHA Marcio S. Bittencourt, MD, PhD, MPH Clifton W. Callaway, MD, FAHA April P. Carson, PhD, MSPH, FAHA Alanna M. Chamberlain, PhD Alexander R. Chang, MD, MS Susan Cheng, MD, MMSc, MPH, FAHA Sandeep R. Das, MD, MPH, MBA, FAHA Francesca N. Delling, MD, MPH Luc Djousse, MD, ScD, MPH Mitchell S.V. Elkind, MD, MS, FAHA Jane F. Ferguson, PhD, FAHA Myriam Fornage, PhD, FAHA Lori Chaffin Jordan, MD, PhD, FAHA Sadiya S. Khan, MD, MSc Brett M. Kissela, MD, MS Kristen L. Knutson, PhD Tak W. Kwan, MD, FAHA Daniel T. Lackland, DrPH, FAHA Tené T. Lewis, PhD Judith H. Lichtman, PhD, MPH, FAHA Chris T. Longenecker, MD Matthew Shane Loop, PhD Pamela L. Lutsey, PhD, MPH, FAHA Seth S. Martin, MD, MHS, FAHA Kunihiro Matsushita, MD, PhD, FAHA Andrew E. Moran, MD, MPH, FAHA Michael E. Mussolino, PhD, FAHA Martin O’Flaherty, MD, MSc, PhD Ambarish Pandey, MD, MSCS Amanda M. Perak, MD, MS Wayne D. Rosamond, PhD, MS, FAHA Gregory A. Roth, MD, MPH, FAHA Uchechukwu K.A. Sampson, MD, MBA, MPH, FAHA Gary M. Satou, MD, FAHA Emily B. Schroeder, MD, PhD, FAHA Svati H. Shah, MD, MHS, FAHA Nicole L. Spartano, PhD Andrew Stokes, PhD David L. Tirschwell, MD, MS, MSc, FAHA Connie W. Tsao, MD, MPH, Vice Chair Elect Mintu P. Turakhia, MD, MAS, FAHA Lisa B. VanWagner, MD, MSc, FAST John T. Wilkins, MD, MS, FAHA Sally S. Wong, PhD, RD, CDN, FAHA Salim S. Virani, MD, PhD, FAHA, Chair Elect On behalf of the American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee

Heart Disease and Stroke Statistics—2019 Update: A Report From the American Heart Association

Each chapter listed in the Table of Contents (see next page) is a hyperlink to that chapter. The reader clicks the chapter name to access that chapter.

Each chapter listed here is a hyperlink. Click on the chapter name to be taken to that chapter. 

Each year, the American Heart Association (AHA), in conjunction with the Centers for Disease Control and Prevention, the National Institutes of Health, and other government agencies, brings together in a single document the most up-to-date statistics related to heart disease, stroke, and the cardiovascular risk factors listed in the AHA’s My Life Check - Life’s Simple 7 (Figure1), which include core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure [BP], and glucose control) that contribute to cardiovascular health. The Statistical Update represents …

Heart Disease and Stroke Statistics-2018 Update: A Report From the American Heart Association.

Distributional Cost-Effectiveness Analysis of Treatments for Non-Small Cell Lung Cancer: An Illustration of an Aggregate Analysis and its Key Drivers

BACKGROUND
Two pivotal randomized controlled trials (RCTs) demonstrate that abiraterone acetate + prednisone (AAP) combined with androgen deprivation therapy (ADT) significantly extends the survival of men with metastatic hormone-sensitive prostate cancer (mHSPC) compared with ADT alone. Their subgroup analyses indicate that the survival benefit is significant for younger men but not older men. We aimed to assess whether publication of the RCTs was associated with differential real-world AAP utilization by age groups.


METHODS
Using TriNetX electronic medical records data collected from 43 healthcare organizations across the United States, we performed a difference-in-differences event study among men with newly diagnosed mHSPC observed from June 2014 to June 2019. Eligible subjects were identified based on a comprehensive published algorithm. We analyzed the change in utilization rate of AAP before versus after publication of the RCTs among men aged <70 years versus ≥70 years, adjusting for demographic factors and clinical conditions.


RESULTS
Our study included 6,888 men with newly diagnosed mHSPC with 12,738 observations, of whom 46% were aged <70 years. The prepublication trends of AAP utilization were similar between the age groups, whereas publication of the RCTs was associated with a 3.5% higher adjusted uptake rate of AAP among younger men (95% CI, 1.2%-5.8%) relative to older men. This estimate reflects an uptake rate nearly 3 times higher than would have been expected had younger men followed the same utilization trends as older men. The estimates remained consistent throughout the postpublication period.


CONCLUSIONS
Our study suggests that publication of the RCTs was associated with faster uptake of AAP among younger versus older men with newly diagnosed mHSPC, despite the absence of clinical guidance for differential treatment selection. This finding highlights the importance of confirmatory studies among older men, considering the uncertainties of subgroup analyses in RCTs.

/pdf/does-clinical-evidence-of-heterogeneity-impact-treatment-177o63y6.pdf

Does Clinical Evidence of Heterogeneity Impact Treatment Selection? A Case Study of Abiraterone for Metastatic Prostate Cancer.

e24004 Background: Survival benefit from current anticancer treatments, even if modest, improves a patient’s chances of accessing and benefiting from future innovations currently in clinical development. No studies to date have evaluated the potential impact of future innovations on oncologists’ treatment recommendations. Methods: We conducted a national survey of medical and hematologic oncologists (n = 200) on how expectations about future innovations may influence their treatment recommendations today. The survey described a hypothetical patient with metastatic cancer, whose median overall survival (OS) was approximately 6 months with most dying within 2 years. We presented four alternative hypothetical scenarios of new innovations in the clinical development pipeline with varying (a) expected efficacy—“modest” (improvement in median OS of 2 months} or “breakthrough” (improvement in median OS of 6 months) and (b) time of arrival (in 6 months or 1 year). We asked the oncologists about the likelihood (using a 5-point Likert scale) (1) that they would discuss these new innovations with the hypothetical metastatic patient, and (2) that these new innovations would influence their recommended treatment for the patient today. We descriptively summarized percentages of oncologists who responded “likely” or “very likely” and examined their associations (using multivariate logistic regression) with the expected efficacy and time of arrival of future innovations as well as the characteristics of oncologists and their practice. Results: When future innovations were expected to have modest efficacy and arrive in 6 months, 61% of oncologists reported that they would be likely or very likely discuss them with their patients, and 52% reported new innovations would influence their treatment recommendations today. With modest efficacy and time of arrival in 1 year, percentages dropped to 49% and 41%, respectively. With breakthrough efficacy and arrival in 6 months, 76% would discuss and 68% would consider new innovations. With breakthrough efficacy and arrival in 1 year, percentages dropped to 62% and 55%, respectively. Greater expected efficacy and shorter time to arrival were associated with a significantly greater likelihood of discussing a future innovations with patients across oncologist and practice characteristics (adjusted odds ratios: breakthrough vs. modest = 1.75; 6 month vs. 1 year = 1.72). Conclusions: Future treatment innovations in clinical development are relevant for decision-making today even when anticipated time to arrival is two times the current median OS. results indicate that it is important to include future innovations in shared decision-making in addition to the benefit-risk balance of current treatments.

Do future innovations in development influence oncologists’ treatment recommendations today? A survey of U.S. oncologists.

We thank Dr. Garattini and Mr. Curto for their comments and will gladly provide further clarification [1]. The original article from which the taxonomy used in our current article was taken focused on health outcomes arrangements and excluded non-outcomes-based schemes [2, 3]. Therefore, the original article includes definitions for coverage with evidence development (CED), conditional treatment continuation (CTC), and performance-linked reimbursement (PLR) categories but not financial/utilization (FU). The FU category is represented by the non-outcomes schemes, which are included in the taxonomy figure, but not explicitly defined in the figure or in the text. We apologize if this caused some confusion. We define the FU category as arrangements where the reimbursement is tied to the measure of financial or utilization outcomes as opposed to explicit clinical outcomes. Subsequent to our original article and taxonomy publication, there have been both derivative and independently created taxonomies. One example—the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Task Force taxonomy—is similar to the original taxonomy, though it differs somewhat, as you have noted [4]. We did not choose to use the ISPOR Task Force taxonomy for our most recent work, opting to stay with our original. Regarding the CTC for Alzheimer’s drugs in Italy, the arrangement would not need to be officially listed as a management entry agreement (MEA) by AIFA, the Italian Medicines Agency, to be included in our review if it meets our criterion, i.e., continuation of coverage for individual patients is conditional upon meeting short-term treatment goals. Our information about this article came from a previously published news article [5]. To the extent this reference is accurate, the Alzheimer’s arrangement meets our criteria. Finally, we classified the arrangements in the UK and Italy according to the aforementioned taxonomy. The current paper provides the relevant numbers according to each of the taxonomic components. Most of the arrangements in Italy contained multiple components. For example, a common arrangement for a cancer therapy in Italy entails a treatment initiation period (often with a financial component with free product or a discounted price, i.e., an FU component), followed by evaluation of short-term response (CTC) with a refund for those not responding according to the predetermined response criteria (PLR). The UK has utilized multiple types of arrangements, but the last 25 Patient Access Schemes have been confidential discounts, suggesting a movement away from performance-based risk-sharing arrangements.

Authors’ Reply to Curto and Garattini: “Current Status and Trends in Performance-Based Risk-Sharing Arrangements Between Healthcare Payers and Medical Product Manufacturers”

Abstract Recent experience with COVID-19 has reminded us of the importance of scientific progress in enabling pharmaceutical innovation. Developing novel therapies is a highly risky but rewarding process: it not only produces innovative drugs, but also valuable scientific knowledge that benefits the community of innovators. This paper examines whether the existing reward system for pharmaceutical research and development (R&D) leads to socially optimal levels of scientific knowledge generation and sharing, with a particular focus on the value of failures in the pharmaceutical R&D efforts. We first outline a conceptual approach based on the idea that pharmaceutical R&D efforts produce both medicines and scientific knowledge, and illustrate this with some examples of how failures may generate information beneficial to concurrent and subsequent R&D efforts. We then summarize the relatively small literature on failures in pharmaceutical R&D and their impact on R&D decision making. Lastly, we discuss several market-based and nonmarket-based policy approaches that can address potential shortcomings in the current reward system which may lead to suboptimal R&D and knowledge sharing.

Louis P. Garrison

Papers

Distributional Cost-Effectiveness Analysis of Treatments for Non-Small Cell Lung Cancer: An Illustration of an Aggregate Analysis and its Key Drivers

Does Clinical Evidence of Heterogeneity Impact Treatment Selection? A Case Study of Abiraterone for Metastatic Prostate Cancer.

Do future innovations in development influence oncologists’ treatment recommendations today? A survey of U.S. oncologists.

Authors’ Reply to Curto and Garattini: “Current Status and Trends in Performance-Based Risk-Sharing Arrangements Between Healthcare Payers and Medical Product Manufacturers”

Should We Pay for Scientific Knowledge Spillovers? The Underappreciated Value of “Failed” R&D Efforts