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  • American Association for Cancer Research (AACR)  (10)
  • 1
    Online Resource
    Online Resource
    Contributions of Subtypes of Non-Hodgkin Lymphoma to Mortality Trends
    American Association for Cancer Research (AACR) ; 2016
    In:  Cancer Epidemiology, Biomarkers & Prevention Vol. 25, No. 1 ( 2016-01-01), p. 174-179
    Details
    In: Cancer Epidemiology, Biomarkers & Prevention, American Association for Cancer Research (AACR), Vol. 25, No. 1 ( 2016-01-01), p. 174-179
    Abstract: Background: Non-Hodgkin lymphoma (NHL) comprises distinct tumor subtypes. Although mortality from NHL overall has changed dramatically in the United States over time, little is known about trends for subtypes, because death certificates do not record this information. Methods: Using data from U.S. Surveillance, Epidemiology, and End Results (SEER) areas, we assessed NHL mortality rates and mapped NHL deaths to incident NHL cases in SEER cancer registries. This allowed us to evaluate population-level mortality trends attributed to specific NHL subtypes (incidence-based mortality; IBM). We also describe NHL incidence and survival after NHL diagnosis by calendar year. We used Joinpoint to identify years when IBM and incidence rate trends changed slope. Results: Overall NHL mortality rates increased during 1975–1997, peaking at 10.9 per 100,000 person-years, then decreased subsequently in 1997–2011. Overall IBM rates mirror this trend during 1990–2011. For B-cell NHL subtypes, IBM rates decreased beginning in the mid-1990s, with yearly declines of −3.0% for diffuse large B-cell lymphoma (DLBCL), −2.7% for chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL), and −5.3% for follicular lymphoma. Incidence rates for these subtypes did not decrease until after 2003. Corresponding 5-year cancer-specific survival increased dramatically over time for DLBCL (from 37%–66%), CLL/SLL (69%–84%), and follicular lymphoma (69%–82%). IBM for peripheral T-cell lymphoma was flat during 2006–2011, although incidence increased. Conclusions: Mortality due to three common B-cell NHL subtypes has fallen over time in the United States. Impact: This decline reflects better survival after NHL diagnosis, likely from improved therapies, because the decline in NHL incidence occurred later. Cancer Epidemiol Biomarkers Prev; 25(1); 174–9. ©2015 AACR.
    Type of Medium: Online Resource
    ISSN: 1055-9965 , 1538-7755
    URL: Article
    DOI: 10.1158/1055-9965.EPI-15-0921
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2016
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  • 2
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    Long-Term Survivors of Childhood Cancers in the United States
    American Association for Cancer Research (AACR) ; 2009
    In:  Cancer Epidemiology, Biomarkers & Prevention Vol. 18, No. 4 ( 2009-04-01), p. 1033-1040
    Details
    In: Cancer Epidemiology, Biomarkers & Prevention, American Association for Cancer Research (AACR), Vol. 18, No. 4 ( 2009-04-01), p. 1033-1040
    Abstract: Purpose: To estimate the number of individuals in the United States diagnosed with cancer as children (ages 0-19 years) as of 2005, with a focus on those surviving for & gt;30 years. Methods: To estimate the national prevalence of survivors of childhood cancers, we used data from the Surveillance Epidemiology and End Results program from 1975 to 2004. Long-term childhood cancer survivors, diagnosed before 1975, were estimated using incidence and survival models extrapolated into years before 1975. Results: We estimated that there are a total of 328,652 survivors of childhood cancer in the United States as of January 1, 2005, of these, 24% have survived & gt;30 years since diagnosis. The cancer sites with the largest number of survivors are brain (51,650), acute lymphoblastic leukemia (49,271), germ cell tumors (34,169), and Hodgkin lymphoma (31,598). Sites with higher proportions of survivors diagnosed & gt;30 years ago are germ cell (43%), soft tissue (38%), renal (34%), and bone (26%). Historical trends from Connecticut data show major improvements in survival for all of the childhood cancer sites. Conclusion: The number of survivors of childhood cancers is expected to increase in the future consequent to the lifesaving advances in treatment introduced after 1970, especially for acute lymphoblastic leukemia. Because this population is at increased risk for illness-related morbidity and mortality, appreciating the number of survivors who were treated as children is important both to determining the national cancer burden and planning for the future health care needs of these individuals. (Cancer Epidemiol Biomarkers Prev 2009;18(4):1033–40)
    Type of Medium: Online Resource
    ISSN: 1055-9965 , 1538-7755
    URL: Article
    DOI: 10.1158/1055-9965.EPI-08-0988
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2009
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  • 3
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    Use of Multiple Imputation to Correct for Bias in Lung Cancer Incidence Trends by Histologic Subtype
    American Association for Cancer Research (AACR) ; 2014
    In:  Cancer Epidemiology, Biomarkers & Prevention Vol. 23, No. 8 ( 2014-08-01), p. 1546-1558
    Details
    In: Cancer Epidemiology, Biomarkers & Prevention, American Association for Cancer Research (AACR), Vol. 23, No. 8 ( 2014-08-01), p. 1546-1558
    Abstract: Background: Over the past several decades, advances in lung cancer research and practice have led to refinements of histologic diagnosis of lung cancer. The differential use and subsequent alterations of nonspecific morphology codes, however, may have caused artifactual fluctuations in the incidence rates for histologic subtypes, thus biasing temporal trends. Methods: We developed a multiple imputation (MI) method to correct lung cancer incidence for nonspecific histology using data from the Surveillance, Epidemiology, and End Results Program during 1975 to 2010. Results: For adenocarcinoma in men and squamous in both genders, the change to an increasing trend around 2005, after more than 10 years of decreasing incidence, is apparently an artifact of the changes in histopathology practice and coding system. After imputation, the rates remained decreasing for adenocarcinoma and squamous in men, and became constant for squamous in women. Conclusions: As molecular features of distinct histologies are increasingly identified by new technologies, accurate histologic distinctions are becoming increasingly relevant to more effective “targeted” therapies, and therefore, are important to track in patients. However, without incorporating the coding changes, the incidence trends estimated for histologic subtypes could be misleading. Impact: The MI approach provides a valuable tool for bridging the different histology definitions, thus permitting meaningful inferences about the long-term trends of lung cancer by histologic subtype. Cancer Epidemiol Biomarkers Prev; 23(8); 1546–58. ©2014 AACR.
    Type of Medium: Online Resource
    ISSN: 1055-9965 , 1538-7755
    URL: Article
    DOI: 10.1158/1055-9965.EPI-14-0130
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2014
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  • 4
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    Updated Methodology for Projecting U.S.- and State-Level Cancer Counts for the Current Calendar Year: Part II: Evaluation of Incidence and Mortality Projection Methods
    American Association for Cancer Research (AACR) ; 2021
    In:  Cancer Epidemiology, Biomarkers & Prevention Vol. 30, No. 11 ( 2021-11-01), p. 1993-2000
    Details
    In: Cancer Epidemiology, Biomarkers & Prevention, American Association for Cancer Research (AACR), Vol. 30, No. 11 ( 2021-11-01), p. 1993-2000
    Abstract: The American Cancer Society (ACS) and the NCI collaborate every 5 to 8 years to update the methods for estimating the numbers of new cancer cases and deaths in the current year for the U.S. and individual states. Herein, we compare our current projection methodology with the next generation of statistical models. Methods: A validation study was conducted comparing current projection methods (vector autoregression for incidence; Joinpoint regression for mortality) with the Bayes state-space method and novel Joinpoint algorithms. Incidence data from 1996–2010 were projected to 2014 using two inputs: modeled data and observed data with modeled where observed were missing. For mortality, observed data from 1995 to 2009, 1996 to 2010, 1997 to 2011, and 1998 to 2012, each projected 3 years forward to 2012 to 2015. Projection methods were evaluated using the average absolute relative deviation (AARD) between observed counts (2014 for incidence, 2012–2015 for mortality) and estimates for 47 cancer sites nationally and 21 sites by state. Results: A novel Joinpoint model provided a good fit for both incidence and mortality, particularly for the most common cancers in the U.S. Notably, the AARD for cancers with cases in 2014 exceeding 49,000 for this model was 3.4%, nearly half that of the current method (6.3%). Conclusions: A data-driven Joinpoint algorithm had versatile performance at the national and state levels and will replace the ACS's current methods. Impact: This methodology provides estimates of cancer data that are not available for the current year, thus continuing to fill an important gap for advocacy, research, and public health planning.
    Type of Medium: Online Resource
    ISSN: 1055-9965 , 1538-7755
    URL: Article
    DOI: 10.1158/1055-9965.EPI-20-1780
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2021
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  • 5
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    Abstract CN03-01: The role of NCI's Cancer Intervention and Surveillance Modeling Network (CISNET) in guiding cancer control planning and priorities
    American Association for Cancer Research (AACR) ; 2013
    In:  Cancer Prevention Research Vol. 6, No. 11_Supplement ( 2013-11-01), p. CN03-01-CN03-01
    Details
    In: Cancer Prevention Research, American Association for Cancer Research (AACR), Vol. 6, No. 11_Supplement ( 2013-11-01), p. CN03-01-CN03-01
    Abstract: CISNET is a consortium of NCI-sponsored investigators that use simulation modeling to understand past trends in cancer incidence and mortality, and to guide public health research and priorities. In this talk we describe the role of simulation modeling in understanding the population impact of interventions (i.e. screening, treatment and prevention). We review some of the unique aspects of modeling as carried out by CISNET, i.e. the development of flexible broad-based disease models, the ability to model multiple birth cohorts, comparative modeling, transparency in model structure and assumptions, and outreach to partners to make the modeling relevant. Finally, we summarize some of the major accomplishments of CISNET. Citation Format: Eric J. Feuer. The role of NCI's Cancer Intervention and Surveillance Modeling Network (CISNET) in guiding cancer control planning and priorities. [abstract]. In: Proceedings of the Twelfth Annual AACR International Conference on Frontiers in Cancer Prevention Research; 2013 Oct 27-30; National Harbor, MD. Philadelphia (PA): AACR; Can Prev Res 2013;6(11 Suppl): Abstract nr CN03-01.
    Type of Medium: Online Resource
    ISSN: 1940-6207 , 1940-6215
    URL: Article
    DOI: 10.1158/1940-6215.PREV-13-CN03-01
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2013
    detail.hit.zdb_id: 2422346-3
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  • 6
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    Exploring the Recent Trend in Esophageal Adenocarcinoma Incidence and Mortality Using Comparative Simulation Modeling
    American Association for Cancer Research (AACR) ; 2014
    In:  Cancer Epidemiology, Biomarkers & Prevention Vol. 23, No. 6 ( 2014-06-01), p. 997-1006
    Details
    In: Cancer Epidemiology, Biomarkers & Prevention, American Association for Cancer Research (AACR), Vol. 23, No. 6 ( 2014-06-01), p. 997-1006
    Abstract: Background: The incidence of esophageal adenocarcinoma (EAC) has increased five-fold in the United States since 1975. The aim of our study was to estimate future U.S. EAC incidence and mortality and to shed light on the potential drivers in the disease process that are conduits for the dramatic increase in EAC incidence. Methods: A consortium of three research groups calibrated independent mathematical models to clinical and epidemiologic data including EAC incidence from the Surveillance, Epidemiology, and End Results (SEER 9) registry from 1975 to 2010. We then used a comparative modeling approach to project EAC incidence and mortality to year 2030. Results: Importantly, all three models identified birth cohort trends affecting cancer progression as a major driver of the observed increases in EAC incidence and mortality. All models predict that incidence and mortality rates will continue to increase until 2030 but with a plateauing trend for recent male cohorts. The predicted ranges of incidence and mortality rates (cases per 100,000 person years) in 2030 are 8.4 to 10.1 and 5.4 to 7.4, respectively, for males, and 1.3 to 1.8 and 0.9 to 1.2 for females. Estimates of cumulative cause-specific EAC deaths between both sexes for years 2011 to 2030 range between 142,300 and 186,298, almost double the number of deaths in the past 20 years. Conclusions: Through comparative modeling, the projected increases in EAC cases and deaths represent a critical public health concern that warrants attention from cancer control planners to prepare potential interventions. Impact: Quantifying this burden of disease will aid health policy makers to plan appropriate cancer control measures. Cancer Epidemiol Biomarkers Prev; 23(6); 997–1006. ©2014 AACR.
    Type of Medium: Online Resource
    ISSN: 1055-9965 , 1538-7755
    URL: Article
    DOI: 10.1158/1055-9965.EPI-13-1233
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2014
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  • 7
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    Multiple Cancer Prevalence: A Growing Challenge in Long-term Survivorship
    American Association for Cancer Research (AACR) ; 2007
    In:  Cancer Epidemiology, Biomarkers & Prevention Vol. 16, No. 3 ( 2007-03-01), p. 566-571
    Details
    In: Cancer Epidemiology, Biomarkers & Prevention, American Association for Cancer Research (AACR), Vol. 16, No. 3 ( 2007-03-01), p. 566-571
    Abstract: Objective: The present study was designed to estimate the number of and describe the pattern of disease among cancer survivors living with a history of multiple malignant tumors in the United States. Methods: Incidence and follow-up data from the Surveillance, Epidemiology, and End Results program (1975-2001) were used to calculate the number of survivors with more than one malignant primary at January 1, 2002. U.S. prevalence counts were calculated by multiplying the age, sex, and race-specific prevalence proportions from the Surveillance, Epidemiology, and End Results program by the corresponding U.S. populations. Results: We estimate that 756,467 people in the United States have been affected by cancer more than once between 1975 and 2001, representing almost 8% of the current cancer survivor population. Women whose first primary in that period was breast cancer represent 25% of survivors with multiple cancers, followed by men and women (15%) whose first primary was colorectal cancer and men (13%) whose first primary was prostate cancer. Discussion: The findings in this report have important implications for public health practice. With individuals diagnosed with cancer living longer and the aging of the U.S. population, the number who will develop multiple malignancies is expected to increase. As a consequence, there is a growing need to promote effective cancer screening along with healthy life-styles among these at-risk populations if we are to ensure optimal physical and psychosocial well-being of these long-term cancer survivors and their families. Efforts to design and evaluate effective, efficient, and equitable approaches to surveillance for second malignancies will be critical in reducing the national burden of cancer. (Cancer Epidemiol Biomarkers Prev 2007;16(3):566–71)
    Type of Medium: Online Resource
    ISSN: 1055-9965 , 1538-7755
    URL: Article
    DOI: 10.1158/1055-9965.EPI-06-0782
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2007
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  • 8
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    Characterizing Trends in Cancer Patients' Survival Using the JPSurv Software
    American Association for Cancer Research (AACR) ; 2021
    In:  Cancer Epidemiology, Biomarkers & Prevention Vol. 30, No. 11 ( 2021-11-01), p. 2001-2009
    Details
    In: Cancer Epidemiology, Biomarkers & Prevention, American Association for Cancer Research (AACR), Vol. 30, No. 11 ( 2021-11-01), p. 2001-2009
    Abstract: Improvements in cancer survival are usually assessed by comparing survival in grouped years of diagnosis. To enhance analyses of survival trends, we present the joinpoint survival model webtool (JPSurv) that analyzes survival data by single year of diagnosis and estimates changes in survival trends and year-over-year trend measures. Methods: We apply JPSurv to relative survival data for individuals diagnosed with female breast cancer, melanoma cancer, non–Hodgkin lymphoma (NHL), and chronic myeloid leukemia (CML) between 1975 and 2015 in the Surveillance, Epidemiology, and End Results Program. We estimate the number and location of joinpoints and the trend measures and provide interpretation. Results: In general, relative survival has substantially improved at least since the mid-1990s for all cancer sites. The largest improvements in 5-year relative survival were observed for distant-stage melanoma after 2009, which increased by almost 3 survival percentage points for each subsequent year of diagnosis, followed by CML in 1995–2010, and NHL in 1995–2003. The modeling also showed that for patients diagnosed with CML after 1995 (compared with before), there was a greater decrease in the probability of dying of the disease in the 4th and 5th years after diagnosis compared with the initial years since diagnosis. Conclusions: The greatest increases in trends for distant melanoma, NHL, and CML coincided with the introduction of novel treatments, demonstrating the value of JPSurv for estimating and interpreting cancer survival trends. Impact: The JPSurv webtool provides a suite of estimates for analyzing trends in cancer survival that complement traditional descriptive survival analyses.
    Type of Medium: Online Resource
    ISSN: 1055-9965 , 1538-7755
    URL: Article
    DOI: 10.1158/1055-9965.EPI-21-0423
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2021
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  • 9
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    Bias Associated With Self-Report of Prior Screening Mammography
    American Association for Cancer Research (AACR) ; 2009
    In:  Cancer Epidemiology, Biomarkers & Prevention Vol. 18, No. 6 ( 2009-06-01), p. 1699-1705
    Details
    In: Cancer Epidemiology, Biomarkers & Prevention, American Association for Cancer Research (AACR), Vol. 18, No. 6 ( 2009-06-01), p. 1699-1705
    Abstract: Background: Self-reported screening behaviors from national surveys often overestimate screening use, and the amount of overestimation may vary by demographic characteristics. We examine self-report bias in mammography screening rates overall, by age, and by race/ethnicity. Methods: We use mammography registry data (1999-2000) from the Breast Cancer Surveillance Consortium to estimate the validity of self-reported mammography screening collected by two national surveys. First, we compare mammography use from 1999 to 2000 for a geographically defined population (Vermont) with self-reported rates in the prior two years from the 2000 Vermont Behavioral Risk Factor Surveillance System. We then use a screening dissemination simulation model to assess estimates of mammography screening from the 2000 National Health Interview Survey. Results: Self-report estimates of mammography use in the prior 2 years from the Vermont Behavioral Risk Factor Surveillance System are 15 to 25 percentage points higher than actual screening rates across age groups. The differences in National Health Interview Survey screening estimates from models are similar for women 40 to 49 and 50 to 59 years and greater than for those 60 to 69, or 70 to 79 (27 and 26 percentage points versus 14, and 14, respectively). Overreporting is highest among African American women (24.4 percentage points) and lowest among Hispanic women (17.9) with non-Hispanic White women in between (19.3). Values of sensitivity and specificity consistent with our results are similar to previous validation studies of mammography. Conclusion: Overestimation of self-reported mammography usage from national surveys varies by age and race/ethnicity. A more nuanced approach that accounts for demographic differences is needed when adjusting for overestimation or assessing disparities between populations. (Cancer Epidemiol Biomarkers Prev 2009;18(6):1699–705)
    Type of Medium: Online Resource
    ISSN: 1055-9965 , 1538-7755
    URL: Article
    DOI: 10.1158/1055-9965.EPI-09-0020
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2009
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  • 10
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    Updated Methodology for Projecting U.S.- and State-Level Cancer Counts for the Current Calendar Year: Part I: Spatio-temporal Modeling for Cancer Incidence
    American Association for Cancer Research (AACR) ; 2021
    In:  Cancer Epidemiology, Biomarkers & Prevention Vol. 30, No. 9 ( 2021-09-01), p. 1620-1626
    Details
    In: Cancer Epidemiology, Biomarkers & Prevention, American Association for Cancer Research (AACR), Vol. 30, No. 9 ( 2021-09-01), p. 1620-1626
    Abstract: The American Cancer Society (ACS) and the NCI collaborate every 5–8 years to update the methods for estimating numbers of new cancer cases and deaths in the current year in the United States and in every state and the District of Columbia. In this article, we reevaluate the statistical method for estimating unavailable historical incident cases which are needed for projecting the current year counts. Methods: We compared the current county-level model developed in 2012 (M0) with three new models, including a state-level mixed effect model (M1) and two state-level hierarchical Bayes models with varying random effects (M2 and M3). We used 1996–2014 incidence data for 16 sex-specific cancer sites to fit the models. An average absolute relative deviation (AARD) comparing the observed with the model-specific predicted counts was calculated for each site. Models were also cross-validated for six selected sex-specific cancer sites. Results: For the cross-validation, the AARD ranged from 2.8% to 33.0% for M0, 3.3% to 31.1% for M1, 6.6% to 30.5% for M2, and 10.4% to 393.2% for M3. M1 encountered the least technical issues in terms of model convergence and running time. Conclusions: The state-level mixed effect model (M1) was overall superior in accuracy and computational efficiency and will be the new model for the ACS current year projection project. Impact: In addition to predicting the unavailable state-level historical incidence counts for cancer surveillance, the updated algorithms have broad applicability for disease mapping and other activities of public health planning, advocacy, and research.
    Type of Medium: Online Resource
    ISSN: 1055-9965 , 1538-7755
    URL: Article
    DOI: 10.1158/1055-9965.EPI-20-1727
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2021
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