Literature DB >> 21228314

Projections of the cost of cancer care in the United States: 2010-2020.

Angela B Mariotto1, K Robin Yabroff, Yongwu Shao, Eric J Feuer, Martin L Brown.   

Abstract

BACKGROUND: Current estimates of the costs of cancer care in the United States are based on data from 2003 and earlier. However, incidence, survival, and practice patterns have been changing for the majority of cancers.
METHODS: Cancer prevalence was estimated and projected by phase of care (initial year following diagnosis, continuing, and last year of life) and tumor site for 13 cancers in men and 16 cancers in women through 2020. Cancer prevalence was calculated from cancer incidence and survival models estimated from Surveillance, Epidemiology, and End Results (SEER) Program data. Annualized net costs were estimated from recent SEER-Medicare linkage data, which included claims through 2006 among beneficiaries aged 65 years and older with a cancer diagnosis. Control subjects without cancer were identified from a 5% random sample of all Medicare beneficiaries residing in the SEER areas to adjust for expenditures not related to cancer. All cost estimates were adjusted to 2010 dollars. Different scenarios for assumptions about future trends in incidence, survival, and cost were assessed with sensitivity analysis.
RESULTS: Assuming constant incidence, survival, and cost, we projected 13.8 and 18.1 million cancer survivors in 2010 and 2020, respectively, with associated costs of cancer care of 124.57 and 157.77 billion 2010 US dollars. This 27% increase in medical costs reflects US population changes only. The largest increases were in the continuing phase of care for prostate cancer (42%) and female breast cancer (32%). Projections of current trends in incidence (declining) and survival (increasing) had small effects on 2020 estimates. However, if costs of care increase annually by 2% in the initial and last year of life phases of care, the total cost in 2020 is projected to be $173 billion, which represents a 39% increase from 2010.
CONCLUSIONS: The national cost of cancer care is substantial and expected to increase because of population changes alone. Our findings have implications for policy makers in planning and allocation of resources.

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Mesh:

Year:  2011        PMID: 21228314      PMCID: PMC3107566          DOI: 10.1093/jnci/djq495

Source DB:  PubMed          Journal:  J Natl Cancer Inst        ISSN: 0027-8874            Impact factor:   13.506


  19 in total

1.  Overview of the SEER-Medicare data: content, research applications, and generalizability to the United States elderly population.

Authors:  Joan L Warren; Carrie N Klabunde; Deborah Schrag; Peter B Bach; Gerald F Riley
Journal:  Med Care       Date:  2002-08       Impact factor: 2.983

2.  The price tag on progress--chemotherapy for colorectal cancer.

Authors:  Deborah Schrag
Journal:  N Engl J Med       Date:  2004-07-22       Impact factor: 91.245

3.  Obtaining long-term disease specific costs of care: application to Medicare enrollees diagnosed with colorectal cancer.

Authors:  M L Brown; G F Riley; A L Potosky; R D Etzioni
Journal:  Med Care       Date:  1999-12       Impact factor: 2.983

4.  Estimation and projections of cancer prevalence from cancer registry data.

Authors:  Arduino Verdecchia; Giovanni De Angelis; Riccardo Capocaccia
Journal:  Stat Med       Date:  2002-11-30       Impact factor: 2.373

5.  Differences in initial treatment patterns and outcomes of lung cancer in the elderly.

Authors:  T J Smith; L Penberthy; C E Desch; M Whittemore; C Newschaffer; B E Hillner; D McClish; S M Retchin
Journal:  Lung Cancer       Date:  1995-12       Impact factor: 5.705

6.  Costs and survival of patients with colorectal cancer in a health maintenance organization and a preferred provider organization.

Authors:  Matthew Kerrigan; Nadia Howlader; Margaret T Mandelson; Robert Harrison; Edward C Mansley; Scott D Ramsey
Journal:  Med Care       Date:  2005-10       Impact factor: 2.983

7.  Mixture models for cancer survival analysis: application to population-based data with covariates.

Authors:  R De Angelis; R Capocaccia; T Hakulinen; B Soderman; A Verdecchia
Journal:  Stat Med       Date:  1999-02-28       Impact factor: 2.373

8.  Health insurance and spending among cancer patients.

Authors:  Kenneth E Thorpe; David Howard
Journal:  Health Aff (Millwood)       Date:  2003 Jan-Jun       Impact factor: 6.301

9.  Stage, age, comorbidity, and direct costs of colon, prostate, and breast cancer care.

Authors:  S H Taplin; W Barlow; N Urban; M T Mandelson; D J Timlin; L Ichikawa; P Nefcy
Journal:  J Natl Cancer Inst       Date:  1995-03-15       Impact factor: 13.506

10.  Cost of care for cancer in a health maintenance organization.

Authors:  B H Fireman; C P Quesenberry; C P Somkin; A S Jacobson; D Baer; D West; A L Potosky; M L Brown
Journal:  Health Care Financ Rev       Date:  1997
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  796 in total

1.  Financial incentives for abstinence among socioeconomically disadvantaged individuals in smoking cessation treatment.

Authors:  Darla E Kendzor; Michael S Businelle; Insiya B Poonawalla; Erica L Cuate; Anshula Kesh; Debra M Rios; Ping Ma; David S Balis
Journal:  Am J Public Health       Date:  2014-11-13       Impact factor: 9.308

2.  Expenditure of hospital care on cancer in China, from 2011 to 2015.

Authors:  Yue Cai; Ming Xue; Wanqing Chen; Maogui Hu; Zhiwen Miao; Lan Lan; Rongshou Zheng; Qun Meng
Journal:  Chin J Cancer Res       Date:  2017-06       Impact factor: 5.087

3.  Cost-effectiveness of MR Imaging-guided Strategies for Detection of Prostate Cancer in Biopsy-Naive Men.

Authors:  Shivani Pahwa; Nicholas K Schiltz; Lee E Ponsky; Ziang Lu; Mark A Griswold; Vikas Gulani
Journal:  Radiology       Date:  2017-05-17       Impact factor: 11.105

4.  Resource Use in the Last Year of Life Among Patients Who Died With Versus of Prostate Cancer.

Authors:  Michaela A Dinan; Yanhong Li; Yinghong Zhang; Suzanne B Stewart; Lesley H Curtis; Daniel J George; Shelby D Reed
Journal:  Clin Genitourin Cancer       Date:  2015-08-06       Impact factor: 2.872

Review 5.  End-of-life care--what do cancer patients want?

Authors:  Shaheen A Khan; Barbara Gomes; Irene J Higginson
Journal:  Nat Rev Clin Oncol       Date:  2013-11-26       Impact factor: 66.675

6.  Global surveillance of trends in cancer survival 2000-14 (CONCORD-3): analysis of individual records for 37 513 025 patients diagnosed with one of 18 cancers from 322 population-based registries in 71 countries.

Authors:  Claudia Allemani; Tomohiro Matsuda; Veronica Di Carlo; Rhea Harewood; Melissa Matz; Maja Nikšić; Audrey Bonaventure; Mikhail Valkov; Christopher J Johnson; Jacques Estève; Olufemi J Ogunbiyi; Gulnar Azevedo E Silva; Wan-Qing Chen; Sultan Eser; Gerda Engholm; Charles A Stiller; Alain Monnereau; Ryan R Woods; Otto Visser; Gek Hsiang Lim; Joanne Aitken; Hannah K Weir; Michel P Coleman
Journal:  Lancet       Date:  2018-01-31       Impact factor: 79.321

Review 7.  Implementing risk-aligned bladder cancer surveillance care.

Authors:  Florian R Schroeck; Nicholas Smith; Jeremy B Shelton
Journal:  Urol Oncol       Date:  2018-02-13       Impact factor: 3.498

8.  General Health Care Utilization Among Nonelderly Cancer Survivors Before and After Affordable Care Act Implementation: Early Results.

Authors:  Amy L Shaver; Ying Cao; Katia Noyes
Journal:  JCO Oncol Pract       Date:  2020-02-18

9.  Steroid Refractory Chronic Graft-Versus-Host Disease: Cost-Effectiveness Analysis.

Authors:  Fevzi F Yalniz; Mohammad H Murad; Stephanie J Lee; Steven Z Pavletic; Nandita Khera; Nilay D Shah; Shahrukh K Hashmi
Journal:  Biol Blood Marrow Transplant       Date:  2018-03-14       Impact factor: 5.742

10.  Evaluating long-term patient-centered outcomes following prostate cancer treatment: findings from the Michigan Prostate Cancer Survivor study.

Authors:  May Darwish-Yassine; Manijeh Berenji; Diane Wing; Glenn Copeland; Raymond Y Demers; Carol Garlinghouse; Angela Fagerlin; Gail E Newth; Laurel Northouse; Margaret Holmes-Rovner; David Rovner; Jerry Sims; John T Wei
Journal:  J Cancer Surviv       Date:  2013-11-10       Impact factor: 4.442

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