Search

Your search keyword '"Mariotto, Angela"' showing total 677 results
Start Over Author "Mariotto, Angela"
677 results on '"Mariotto, Angela"'

151. The efficacy of prostate‐specific antigen screening: Impact of key components in the ERSPC and PLCO trials

Author

de Koning, Harry J., primary, Gulati, Roman, additional, Moss, Sue M., additional, Hugosson, Jonas, additional, Pinsky, Paul F., additional, Berg, Christine D., additional, Auvinen, Anssi, additional, Andriole, Gerald L., additional, Roobol, Monique J., additional, Crawford, E. David, additional, Nelen, Vera, additional, Kwiatkowski, Maciej, additional, Zappa, Marco, additional, Luján, Marcos, additional, Villers, Arnauld, additional, de Carvalho, Tiago M., additional, Feuer, Eric J., additional, Tsodikov, Alex, additional, Mariotto, Angela B., additional, Heijnsdijk, Eveline A. M., additional, and Etzioni, Ruth, additional

Published
2017
Full Text
View/download PDF

156. Differences in Cancer Survival with Relative versus Cause-Specific Approaches: An Update Using More Accurate Life Tables.

Author

de Lacerda, Gonçalo Forjaz, Howlader, Nadia, and Mariotto, Angela B.

Abstract

Background: We investigated differences in net cancer survival (survival observed if the only possible cause of death was the cancer under study) estimated using new approaches for relative survival (RS) and cause-specific survival (CSS). Methods: We used SEER data for patients diagnosed in 2000 to 2013, followed-up through December 31, 2014. For RS, we used new life tables accounting for geography and socio-economic status. For CSS, we used the SEER cause of death algorithm for attributing cancer-specific death. Estimates were compared by site, age, stage, race, and time since diagnosis. Results: Differences between 5-year RS and CSS were generally small. RS was always higher in screen-detectable cancers, for example, female breast (89.2% vs. 87.8%) and prostate (98.5% vs. 93.7%) cancers; differences increased with age or time since diagnosis. CSS was usually higher in the remaining cancer sites, particularly those related to specific risk factors, for example, cervix (70.9% vs. 68.3%) and liver (20.7% vs. 17.1%) cancers. For most cancer sites, the gap between estimates was smaller with more advanced stage. Conclusion: RS is the preferred approach to report cancer survival from registry data because cause of death may be inaccurate, particularly for older patients and long-term survivors as comorbidities increase challenges in determining cause of death. However, CSS proved to be more reliable in patients diagnosed with localized disease or cancers related to specific risk factors as general population life tables may not capture other causes of mortality. [ABSTRACT FROM AUTHOR]

Published
2019
Full Text
View/download PDF

158. Expected population impacts of discontinued prostate-specific antigen screening

Author

Gulati, Roman, Tsodikov, Alex, Etzioni, Ruth, Hunter-Merrill, Rachel A, Gore, John L, Mariotto, Angela B, and Cooperberg, Matthew R

Subjects
mass screening, Aged, 80 and over, Male, Oncology and Carcinogenesis, Prostatic Neoplasms, and over, Middle Aged, Models, Theoretical, Prostate-Specific Antigen, Article, models, Theoretical, 80 and over, surveillance, Public Health and Health Services, Humans, Oncology & Carcinogenesis, statistical, Early Detection of Cancer, Aged, SEER Program
Abstract

© 2014 American Cancer Society. BACKGROUND: Prostate-specific antigen (PSA) screening for prostate cancer has high risks of overdiagnosis, particularly among older men, and reports from screening trials indicate that it saves few lives after 11 to 13 years of follow-up. New clinical guidelines recommend against PSA screening for all men or for men aged >70 years, but, to the authors' knowledge, the expected population effects of these guidelines have not been studied to date. METHODS: Two models of prostate cancer natural history and diagnosis were previously developed using reconstructed PSA screening patterns and prostate cancer incidence in the United States. Assuming a survival benefit of PSA screening consistent with the screening trials, the authors used the models to predict incidence and mortality rates for the period from 2013 through 2025 under continued PSA screening and under discontinued PSA screening for all men or for men aged >70 years. RESULTS: The models predicted that continuation of recent screening rates will overdiagnose 710,000 to 1,120,000 men (range between models) but will avoid 36,000 to 57,000 cancer deaths over the period 2013 through 2025. Discontinued screening for all men eliminated 100% of overdiagnoses but failed to prevent 100% of avoidable cancer deaths. Continued screening for men aged

Published
2014

161. Cancer treatment and survivorship statistics, 2016

Author

Miller, Kimberly D., primary, Siegel, Rebecca L., additional, Lin, Chun Chieh, additional, Mariotto, Angela B., additional, Kramer, Joan L., additional, Rowland, Julia H., additional, Stein, Kevin D., additional, Alteri, Rick, additional, and Jemal, Ahmedin, additional

Published
2016
Full Text
View/download PDF

163. Economic Burden of Cancer in the United States: Estimates, Projections, and Future Research

Author

Lund, Jennifer, Kepka, Deanna, Yabroff, K. Robin, and Mariotto, Angela

Abstract

The economic burden of cancer in the US is substantial and expected to increase significantly in the future due to expected growth and aging of the population and improvements in survival as well as trends in treatment patterns and costs of care following cancer diagnosis. In this paper, we describe measures of the economic burden of cancer and present current estimates and projections of the national burden of cancer in the US. We discuss ongoing efforts to characterize the economic burden of cancer in the US and identify key areas for future work, including developing and enhancing research resources, improving estimates and projections of economic burden, evaluating targeted therapies, and assessing the financial burden for patients and their families. This work will inform efforts by health care policy makers, healthcare systems, and employers to improve the cancer survivorship experience in the US.

Published
2011
Full Text
View/download PDF

164. Survivors of Childhood Cancer in the United States: Prevalence and Burden of Morbidity

Author

Phillips, Siobhan M., primary, Padgett, Lynne S., additional, Leisenring, Wendy M., additional, Stratton, Kayla K., additional, Bishop, Ken, additional, Krull, Kevin R., additional, Alfano, Catherine M., additional, Gibson, Todd M., additional, de Moor, Janet S., additional, Hartigan, Danielle Blanch, additional, Armstrong, Gregory T., additional, Robison, Leslie L., additional, Rowland, Julia H., additional, Oeffinger, Kevin C., additional, and Mariotto, Angela B., additional

Published
2015
Full Text
View/download PDF

168. Cancer treatment and survivorship statistics, 2014

Author

DeSantis, Carol E., primary, Lin, Chun Chieh, additional, Mariotto, Angela B., additional, Siegel, Rebecca L., additional, Stein, Kevin D., additional, Kramer, Joan L., additional, Alteri, Rick, additional, Robbins, Anthony S., additional, and Jemal, Ahmedin, additional

Published
2014
Full Text
View/download PDF

171. Annual Report to the Nation on the status of cancer, 1975‐2010, featuring prevalence of comorbidity and impact on survival among persons with lung, colorectal, breast, or prostate cancer

Author

Edwards, Brenda K., primary, Noone, Anne‐Michelle, additional, Mariotto, Angela B., additional, Simard, Edgar P., additional, Boscoe, Francis P., additional, Henley, S. Jane, additional, Jemal, Ahmedin, additional, Cho, Hyunsoon, additional, Anderson, Robert N., additional, Kohler, Betsy A., additional, Eheman, Christie R., additional, and Ward, Elizabeth M., additional

Published
2013
Full Text
View/download PDF

172. Complete and limited duration cancer prevalence estimates

Author

Mariotto Angela, Gigli Anna, Capocaccia Riccardo, Tavilla Andrea, Clegg Limin X, Depry Michael, Scoppa Steve, Ries Lynn A.G., Rowland Julia H, Tesauro Gina, and Feuer Eric J.

Abstract

Prevalence is an indicator of primary interest in public health because it measures the burden of cancer in a population and on the health care system. Prevalence is defined as thenumber or percent of people alive on a certain date in a population who previously had a diagnosis of the disease. It includes new (incidence) and pre-existing cases and is a function of both past incidence and survival. Information on prevalence can be used for health planning,resource allocation and an estimate of cancer survivorship. In past reports of the Cancer Statistics Review, US cancer prevalence was estimated by multiplying the Connecticut cancer prevalence proportions to the US population. This year, US cancer prevalence is estimated by applying SEER-9 and SEER-11 prevalence proportions to the US population. SEER proportion rates are more representative of the US and permit estimation of prevalence by racial/ethnic groups. Other changes with respect to previous reports are in the methods for tumor inclusion and complete prevalence calculation.

Published
2002

178. Anticipating the "Silver Tsunami": Prevalence Trajectories and Comorbidity Burden among Older Cancer Survivors in the United States.

Author

Bluethmann, Shirley M., Mariotto, Angela B., and Rowland, Julia H.

Abstract

Background: Cancer survivors are a growing population, due in large part to the aging of the baby boomer generation and the related "silver tsunami" facing the U.S. health care system. Understanding the impact of a graying nation on cancer prevalence and comorbidity burden is critical in informing efforts to design and implement quality cancer care for this population. Methods: Incidence and survival data from 1975 to 2011 were obtained from the Surveillance, Epidemiology, and End Results (SEER) Program to estimate current cancer prevalence. SEER-Medicare claims data were used to estimate comorbidity burden. Prevalence projections were made using U.S. Census Bureau data and the Prevalence Incidence Approach Model, assuming constant future incidence and survival trends but dynamic projections of the U.S. population. Results: In 2016, there were an estimated 15.5 million cancer survivors living in the United States, 62% of whom were 65 years or older. The prevalent population is projected to grow to 26.1 million by 2040, and include 73% of survivors who are 65 years and older. Comorbidity burden was highest in the oldest survivors (those ≥ 85 years) and worst among lung cancer survivors. Conclusions: Older adults, who often present with complex health needs, now constitute the majority of cancer survivors and will continue to dominate the survivor population over the next 24 years. Impact: The oldest adults (i.e., those >75 years) should be priority populations in a pressing cancer control and prevention research agenda that includes expanding criteria for clinical trials to recruit more elderly participants and developing relevant supportive care interventions. [ABSTRACT FROM AUTHOR]

Published
2016
Full Text
View/download PDF

179. Cancer treatment and survivorship statistics, 2012

Author

Siegel, Rebecca, primary, DeSantis, Carol, additional, Virgo, Katherine, additional, Stein, Kevin, additional, Mariotto, Angela, additional, Smith, Tenbroeck, additional, Cooper, Dexter, additional, Gansler, Ted, additional, Lerro, Catherine, additional, Fedewa, Stacey, additional, Lin, Chunchieh, additional, Leach, Corinne, additional, Cannady, Rachel Spillers, additional, Cho, Hyunsoon, additional, Scoppa, Steve, additional, Hachey, Mark, additional, Kirch, Rebecca, additional, Jemal, Ahmedin, additional, and Ward, Elizabeth, additional

Published
2012
Full Text
View/download PDF

197. Comorbidity-Adjusted Life Expectancy: A New Tool to Inform Recommendations for Optimal Screening Strategies.

Author

Hyunsoon Cho, Klabunde, Carrie N., Yabroff, K. Robin, Zhuoqiao Wang, Meekins, Angela, Lansdrop-Vogelaar, Iris, and Mariotto, Angela B.

Subjects
LUNG diseases, COMORBIDITY, LIFE expectancy, OBSTRUCTIVE lung diseases, EPIDEMIOLOGICAL research
Abstract

Background: Many guidelines recommend considering health status and life expectancy when making cancer screening decisions for elderly persons. Objective: To estimate life expectancy for elderly persons without a history of cancer, taking into account comorbid conditions. Design: Population-based cohort study. Setting: A 5% sample of Medicare beneficiaries in selected geographic areas, including their claims and vital status information. Participants: Medicare beneficiaries aged 66 years or older between 1992 and 2005 without a history of cancer (n = 407 749). Measurements: Medicare claims were used to identify comorbid conditions included in the Charlson index. Survival probabilities were estimated by comorbidity group (no, low/medium, and high) and for the 3 most prevalent conditions (diabetes, chronic obstructive pulmonary disease, and congestive heart failure) by using the Cox proportional hazards model. Comorbidity-adjusted life expectancy was calculated based on comparisons of survival models with U.S. life tables. Survival probabilities from the U.S. life tables providing the most similar survival experience to the cohort of interest were used. Results: Persons with higher levels of comorbidity had shorter life expectancies, whereas those with no comorbid conditions, including very elderly persons, had favorable life expectancies relative to an average person of the same chronological age. The estimated life expectancy at age 75 years was approximately 3 years longer for persons with no comorbid conditions and approximately 3 years shorter for those with high comorbidity relative to the average U.S. population. Limitations: The cohort was limited to Medicare fee-for-service beneficiaries aged 66 years or older living in selected geographic areas. Data from the Surveillance, Epidemiology, and End Results cancer registry and Medicare claims lack information on functional status and severity of comorbidity, which might influence life expectancy in elderly persons. Conclusion: Life expectancy varies considerably by comorbidity status in elderly persons. Comorbidity-adjusted life expectancy may help physicians tailor recommendations for stopping or continuing cancer screening for individual patients. Primary Funding Source: None. [ABSTRACT FROM AUTHOR]

Published
2013
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results