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Original Investigation |

Disparities by Race, Age, and Sex in the Improvement of Survival for Major Cancers Results From the National Cancer Institute Surveillance, Epidemiology, and End Results (SEER) Program in the United States, 1990 to 2010 FREE

Chenjie Zeng, MPH1; Wanqing Wen, MD, MPH1; Alicia K. Morgans, MD2; William Pao, MD2; Xiao-Ou Shu, MD, PhD1; Wei Zheng, MD, PhD1
[+] Author Affiliations
1Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee
2Division of Hematology and Oncology, Department of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee
JAMA Oncol. 2015;1(1):88-96. doi:10.1001/jamaoncol.2014.161.
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Importance  Substantial progress has been made in cancer diagnosis and treatment, resulting in a steady improvement in cancer survival. The degree of improvement by age, race, and sex remains unclear.

Objective  To quantify the degree of survival improvement over time by age, race, and sex in the United States.

Design, Setting, and Participants  Longitudinal analyses of cancer follow-up data from 1990 to 2010, from 1.02 million patients who had been diagnosed as having cancer of the colon or rectum, breast, prostate, lung, liver, pancreas, or ovary from 1990 to 2009 and who were included in 1 of 9 population-based registries of the National Cancer Institute Surveillance, Epidemiology, and End Results (SEER) program.

Main Outcomes and Measures  Hazard ratios (HRs) and 95% CIs for cancer-specific death were estimated for patients diagnosed as having any of these cancers during 1995 to 1999, 2000 to 2004, and 2005 to 2009, compared with those diagnosed in 1990 to 1994.

Results  Significant improvements in survival were found for cancers of the colon or rectum, breast, prostate, lung, and liver. Improvements were more pronounced for younger patients. For patients aged 50 to 64 years and diagnosed from 2005 to 2009, adjusted HRs (95% CIs) were 0.57 (95% CI, 0.55-0.60), 0.48 (95% CI, 0.45-0.51), 0.61 (95% CI, 0.57-0.69), and 0.32 (95% CI, 0.30-0.36), for cancer of the colon or rectum, breast, liver, and prostate, respectively, compared with the same age groups of patients diagnosed during 1990 to 1994. However, the corresponding HRs (95% CIs) for elderly patients (those 75-85 years old) were only 0.88 (95% CI, 0.84-0.92), 0.88 (95% CI, 0.82-0.95), 0.76 (95% CI, 0.69-0.84), and 0.65 (95% CI, 0.61-0.70), for the same 4 cancer sites, respectively. A similar, although weaker, age-related period effect was observed for lung and pancreatic cancers. The adjusted HRs (95% CIs) for lung cancer were 0.75 (95% CI, 0.73-0.77) and 0.84 (95% CI, 0.81-0.86), respectively, for patients aged 50 to 64 years and 75 to 85 years diagnosed between 2005 and 2009, compared with the same age groups of patients diagnosed between 1990 and 1994 (0.73 [95% CI, 0.69-0.77] and 0.90 [95% CI, 0.85-0.95], respectively. Compared with whites or Asians, African Americans experienced greater improvement in prostate cancer survival. From 1990 to 2009, ovarian cancer survival declined among African Americans but improved among whites. No apparent sex difference in the degree of improvement for any non–sex-specific cancer was noted.

Conclusions and Relevance  Younger patients experienced greater benefit from recent oncology advances than elderly patients. African Americans experienced poorer survival than whites for all cancers, and the racial difference decreased for prostate cancer but increased for ovarian cancer. Identifying factors associated with varied improvement in cancer survival can inform future improvements in cancer care for all.

Figures in this Article

Cancer is a leading cause of death in the United States and many other countries.1,2 Substantial progress has been made in cancer diagnosis and treatment during the past few decades, with significant advances in surgery, radiotherapy, chemotherapy, and targeted therapies.35 These improvements in cancer treatments, along with advances in cancer screening and diagnosis, have led to steady improvements in survival of several common cancers over the past few decades.1

The impact of advances in oncology may differ by race, sex, or age.69 It has been reported that African Americans, women, and elderly individuals may benefit less than their white, male, younger counterparts from recent therapeutic advances.68 In addition, the survival gap is widening for several common cancers, including breast and colorectal cancer, by race and age,10,11 and narrowing for some cancers, such as colorectal cancer, by sex.12,13 It has been suggested that patients who are African American, female, or elderly are less likely to receive novel therapies owing to their underrepresentation in clinical trials, causing clinicians uncertainty about the relative efficacy or toxicity of newer therapies in these populations.4,1417 Patient preferences also may lead to avoidance of newer therapies they believe to be more aggressive or toxic.

Many studies have evaluated differences in cancer mortality by race, sex, and age.10,1822 Because mortality is affected by both incidence and case fatality, it is not a direct measure of survival. Several cross-sectional studies have compared cancer survival rates by race, sex, and age.12,23 However, these studies did not address the secular trend of cancer survival, which measures the improvement of cancer survival (or the benefit from recent advances in oncology) over time. In this study, we sought to quantify the differences in the improvement of cancer survival by race, age, and sex in the past 2 decades. We evaluated data from 9 registries participating in the Surveillance, Epidemiology, and End Results (SEER) program (hereinafter, SEER 9) to determine whether improvements in cancer survival differ by race, sex, and age in the United States. For this analysis we selected 7 cancer sites, which are estimated to account for approximately 60% of US cancer deaths in 20141: colon or rectum, female breast, prostate, liver or intrahepatic bile duct, lung, pancreas, and ovary. Advances in cancer treatment differ among these cancer types. We assessed a spectrum of cancers to compare varying degrees of treatment improvement and to explore reasons for differences in survival over time across different cancer patient populations.

Box Section Ref ID

At a Glance
  • Over the past 2 decades, elderly patients (75-85 years) experienced smaller improvements in survival for most common solid tumors compared with younger patients.

  • Black Americans experienced poorer survival than white Americans for all cancers.

  • Greater improvement in prostate cancer survival in blacks than whites decreased the racial difference.

  • Survival rates declined in blacks but slightly increased in whites, increasing the racial difference.

  • Age- and race-related disparities observed in improvement of cancer survival is, in part, due to differences in cancer care in subpopulations.

The current study was conducted in compliance with the National Cancer Institute SEER limited-use data end user agreement. It was determined to be exempt from the institutional review board oversight at Vanderbilt University because the data used in this analysis had been deidentified. We analyzed data from 9 population-based cancer registries included in the SEER program of the National Cancer Institute: Atlanta, Georgia; Connecticut; Detroit, Michigan; Hawaii; Iowa; New Mexico; San Francisco-Oakland, California; Seattle–Puget Sound, Washington; and Utah.24 We selected patients with a single primary diagnosis (sequence number = 00) of cancer of the colon or rectum (International Classification of Diseases for Oncology, 3rd edition25 site codes: C180 to C189; C199, C209), female breast (C500 to C509), liver or intrahepatic bile duct (C220 to C221), lung (C340 to 349), pancreas (C250 to C259), prostate (C619), or ovary (C569) from 1990 through 2009. Individuals were 20 to 85 years old at the time of diagnosis, and were followed through 2010. We excluded patients whose death was reported by autopsy only or death certification only (<1% of total patients for each cancer). Demographic variables (age at diagnosis, year of diagnosis, race, sex, and marital status) and tumor characteristics (stage and histologic types) were obtained from the registry databases. SEER collected race information from medical records, face sheet, and physician and nurse notes, and recoded the information into the following categories: white, black, American Indian/Alaskan Native, Asian/Pacific Islander, and unknown in the SEER 9 datasets.24 Owing to a small sample size of patients of American Indian/Alaskan Native origins,24 we did not analyze data specifically for this group of patients. SEER does not collect information on Hispanic ethnicity directly. SEER codes the Hispanic origin variable based on NAACCR (North American Association of Central Cancer Registries) Hispanic Identification Algorithm (NHIA), which searches the surname as well as maiden-name to determine the Hispanic ethnicity. Some data on the Hispanic origin at one of the SEER 9 registries (Connecticut) are considered unreliable and, thus, are often excluded from race/ethnicity-specific analyses.1,26 Therefore, we decided not to analyze data specifically for Hispanic ethnicity.

The primary outcome in this study was a measure of cancer-specific death, defined as a death with the specific cancer of interest listed as the primary cause of death in the SEER 9 registries.27 Patients still alive on December 31, 2010, or who had died of other causes were censored. Survival rates (at 1, 3, and 5 years) by cancer-specific death by age, sex, or race for patients diagnosed between 1990 and 1994 (the baseline period) were calculated using the Kaplan-Meier method. Hazard ratios (HRs) and 95% CIs for cancer-specific death associated with age, sex, or race were calculated using Cox proportional hazards models, for patients diagnosed during the time periods 1995 to 1999, 2000 to 2004, and 2005 to 2009, and were compared with those diagnosed at the baseline. The time scale for the proportional hazards model is the time from cancer diagnosis to cancer-specific death or the last day of follow up (December 31, 2010) in months. We also calculated HRs and 95% CIs for each 5-year increment by year of diagnosis to measure the average cancer-specific death rate from 1990 to 2010. Potential confounders were initially identified by reviewing the literature and were then evaluated in our study. Variables that affected the point estimates by 5% were considered potential confounders. In the final analyses, all models were adjusted for marital status, common histologic types, and SEER registry site. Additional adjustments were made for SEER historic stages (localized, regional, distant, and unstaged), age (20-49, 50-64, 65-74, or 75-85 years), race (white, African American, Asian, or other), and sex when appropriate.

Distributions of patients’ demographic factors and cancer characteristics at diagnosis are provided in eTables 1 to 8 in the Supplement. Because prostate cancer was classified into 3 stages (localized/regional, distant, and unstaged), and 93% of patients were diagnosed at the localized or regional stage, the SEER historic stage variable was not included in any of the prostate cancer models. Possible interactions between year of diagnosis and age, sex, or race were assessed using likelihood ratio tests in the Cox models. Stratified analyses by SEER registry sites were also performed, and 3-way interactions of SEER sites and year of diagnosis with age, sex, or race were evaluated. The proportional hazard assumption was evaluated by plotting scaled Schoenfeld residuals and log-log survival plots for each variable evaluated in the study. To account for large sample size and multiple tests performed in this study, a 2-sided P value of .001, equivalent to a significance level of .05 after Bonferroni correction for 50 comparisons, was used to indicate statistical significance. All statistical analyses were performed using SAS software (version 9.3; SAS Institute Inc). All P values were 2-sided.

Analyses included 1 020 382 patients who were diagnosed as having cancers of the colon or rectum, breast, liver or intrahepatic bile duct, lung or bronchus, pancreas, prostate, or ovary from 1990 through 2009 (eTable 1 in the Supplement). During this period, the percentage of cancer cases diagnosed at a localized stage increased for all cancer sites except ovarian cancer (eTables 2-8 in the Supplement). For ovarian cancer, 27.7% of cases were diagnosed at a localized stage from 1990 through 1994; by the period 2005 through 2009, only 19.3% of cases were diagnosed at the localized stage (eTable 8 in the Supplement). The distribution of other patient characteristics also changed over the 20-year study period (eTables 2-8 in the Supplement). In general, the percentage of white patients decreased and the percentage of African American patients increased for all cancer sites. The percentage of Asian patients also increased for all but liver cancer. The percentage of male patients increased for all non–sex-specific cancers except for lung cancer. For patients diagnosed from 1990 to 1994, survival rates for African Americans were the lowest for all cancers except for ovarian and pancreatic cancers (Table). For all cancer sites, survival rates were lowest in the oldest age group (75-85 years) and were lower among men than among women (Table).

Table Graphic Jump LocationTable.  Cancer-Specific Survival Rates for 230 449 Patients Diagnosed From 1990 to 1994 According to Age Group, Race/Ethnicity, and Sex, in 9 SEER Registries

With the exception of ovarian cancer among African American women, significant improvements in survival, shown by decreasing HRs over time, were observed for 6 other cancers from 1990 to 2009 in all 3 racial groups (Figure 1, eTable 9 in the Supplement). The largest improvement in survival was observed for prostate cancer patients, followed by those with breast, liver, colorectal, pancreatic, and lung cancers. However, white, African American, and Asian cancer patients experienced different degrees of improvement in survival from 1990 to 2009 for ovarian and prostate cancers. During the 20-year study period, there was a statistically significant decrease in ovarian cancer survival among African Americans, no improvement in survival in Asians, and a slight but significant improvement in survival among whites (P for interaction: 1.41×10-5). Over the study period, African Americans experienced a greater improvement in survival of prostate cancer than whites or Asians (HR for 5-year increment of year of diagnosis: African Americans, 0.66 [95% CI, 0.64-0.68]; whites, 0.72 [95% CI, 0.71-0.73]; and Asians, 0.73 [95% CI, 0.69-0.77]). No apparent racial differences in survival improvements were seen for the other cancers evaluated in this study.

Place holder to copy figure label and caption
Figure 1.
Multivariate-Adjusted Hazard Ratios (HRs) and 95% CIs for Cancer-Specific Death Associated With Year of Diagnosis According to Race, in 9 SEER Registries, 1990-2009

The HRs and 95% CIs were adjusted for marital status, common histologic types, SEER registry sites, SEER historic stage, age, and sex (if applicable), using the time period 1990-1994 as the reference. P values for interaction for year of diagnosis and race are presented. SEER indicates Surveillance, Epidemiology, and End Results.

Graphic Jump Location

From 1990 to 2009, all age groups demonstrated improved survival for all cancer sites with the exception of ovarian cancer (Figure 2, eTable 10 in the Supplement). Improvements in survival were greater for younger age groups, and tests for interaction were statistically significant for 5 of the 7 cancer sites (P <.001 for all interactions). For example, compared with those diagnosed from 1990 to 1994, the improvement in survival for colorectal cancer among patients younger than 75 years began among patients diagnosed from 1995 to 1999, whereas among patients 75 years or older, the improvement occurred later and was only evident in the cohort with cancer diagnoses after 2000. In addition, the degree of improvement in survival was greater among the younger age groups, with approximately a 45% reduction in colorectal cancer–specific deaths among patients younger than 65 years, compared with only a 12% reduction among those aged 75 to 85 years. A similar pattern of association was observed for breast, liver, lung, pancreatic, and prostate cancers. For ovarian cancer, a slight improvement in survival was observed only in the 50- to 64-year-old and 65- to 74-year-old age groups. However, the interaction between age and year of diagnosis was not statistically significant (P = .10).

Place holder to copy figure label and caption
Figure 2.
Multivariate-Adjusted Hazard Ratios (HRs) and 95% CIs for Cancer-Specific Death Associated With Year of Diagnosis According to Age at Diagnosis, in 9 SEER Registries, 1990-2009

The HRs and 95% CIs were adjusted for marital status, common histologic types, SEER registry sites, SEER historic stage, race, and sex (if applicable), using the time period 1990 to 1994 as the reference. P values for interaction for year of diagnosis and age groups are presented. SEER indicates Surveillance, Epidemiology, and End Results.

Graphic Jump Location

There was a statistically significant improvement in cancer-specific survival for both men and women for all cancers studied (P < .001 for trend for all comparisons) (eTable 11 in the Supplement), and no statistically significant interactions between sex and year of diagnosis were found for any cancer.

Stratified analyses by cancer stage were performed to evaluate the possible influence of cancer stage at the time of diagnosis in the results related to age disparity for cancer survival (Figure 3, eTable 12 in the Supplement). Greater improvements in survival over time were observed for younger age groups for all stages of colorectal, breast, and lung cancers. For breast and colorectal cancer, it seems that the age-related difference in survival improvement was somewhat more evident for localized and regional disease than for distant disease, although the test for heterogeneity across cancer stages was statistically significant for breast cancer only (P = .02). For lung cancer, the age-related difference in survival improvement was seen primarily for localized and regional disease (P = .01 for heterogeneity across cancer stages) (eTable 12 in the Supplement). For liver cancer, the difference for a greater survival improvement in the younger age group compared with the older age group over the study period was statistically significant only for localized stage cancer; and for pancreatic cancer, only for distant stage cancer; however, heterogeneity tests across cancer stages were not statistically significant were not statistically significant (P = .16 and P = .23 for pancreatic and liver cancer, respectively). For ovarian cancer, no significant improvement in survival over the study period was found, regardless of stage or age group. Similar stratified analyses evaluated possible influence of cancer stage at the time of diagnosis in the results related to sex and race disparity for cancer survival, and no statistically significant modifying effect by stages was observed (eTables 13 and 14 in the Supplement). Stratified analyses by SEER registry sites were performed to evaluate possible influence of geographic locations on our study results. Little evidence was identified for a possible modifying effect of geographic locations on the results found related to age at cancer diagnosis, race, or sex (eTable 15 in the Supplement).

Place holder to copy figure label and caption
Figure 3.
Multivariate-Adjusted Hazard Ratios (HRs) and 95% CIs for Cancer-Specific Death Associated With Every 5-Year Change in Years of Cancer Diagnosis From 1990 to 2009, According to Age at Diagnosis Stratified by Cancer Stage at Diagnosis, in 9 SEER Registries, 1990-2009

HRs and 95% CIs were adjusted for marital status, common histologic types, SEER registry sites, race, and sex (if applicable), using the time period 1990-1994 as the reference. P values for heterogeneity across cancer stages are presented. SEER indicates Surveillance, Epidemiology, and End Results.

Graphic Jump Location

Using data from the SEER, we have showed a slower improvement in cancer survival over the past 20 years in the United States among older cancer patients, resulting in a widening gap in cancer survival for 6 of the 7 cancers evaluated in our study. We observed that the age-related gap was most pronounced for cancers with the largest diagnosis and treatment advances during the study period, including colorectal, breast, and prostate cancers. Furthermore, in the stage-specific analyses of colorectal and breast cancer, there was a suggestion of greater differences in survival over time between younger and older age groups for localized and regional cancers than for advanced cancer. This is consistent with clinical trial data demonstrating improved survival with improved surgical techniques and novel adjuvant treatment for patients with localized and locally advanced colorectal28 and breast cancer.29 Among patients with liver, lung, pancreatic, or ovarian cancer, for which treatment improvements have been modest, the gap in improved survival between younger and older patients was also less evident. We observed an improvement in survival for liver cancer patients with localized disease, particularly for younger patients, consistent with more frequent use of surgical advances like liver transplantation.30 These findings suggest that the widening gap in cancer survival between younger and older patients may be due to differential utilization of newer treatments for elderly patients.

There is ample evidence that elderly patients are less likely to receive potentially morbid treatments like surgery or chemotherapy regardless of disease stage. Older age has been associated with higher rates of toxic effects from treatment for both chemotherapy and radiotherapy.3133 Functional impairment,34 malnutrition,34 and comorbidity35 among older patients may induce treating physicians to choose less aggressive therapy or abbreviated treatment courses in an effort to “do no harm” to a more frail patient population.36 In addition, because elderly patients have been underrepresented in clinical trials,3739 there is insufficient evidence to determine how they will respond to novel targeted therapies or combinations of chemotherapeutic agents.37,38 There is concern that treatments that may be effective in younger patients in clinical trials may be more toxic and less effective in the elderly.40 Our findings demonstrate that age-associated disparities exist and underscore the importance of conducting clinical trials and postmarketing studies to identify optimal treatment regimens, necessary dose adjustments, and distinct toxic effects for elderly patients with cancer. This is particularly pressing because this population constitutes the fastest growing subpopulation of cancer patients in the United States.41

We observed a widening gap in survival by race only in ovarian cancer. In several studies, racial disparities in ovarian cancer survival have been linked to stage at diagnosis and quality of care (adherence to National Comprehensive Cancer Network and other guidelines).4244 Notably, we found that African American prostate cancer patients had larger improvements in survival over time than did whites. This result is supported by previous studies,45,46 which have shown narrower differences in prostate cancer mortality between African Americans and whites since the 1990s. One explanation for the greater improvement in prostate cancer survival among African Americans may be the targeted prostate cancer educational campaigns aimed at increasing prostate cancer awareness in the African American community during the past decade.47

It has been reported that women may have lower mortality for almost all non–sex-specific cancers than do men.13,26,48 Our study shows that improvements in cancer survival over time were similar between men and women for all non–sex-specific cancers evaluated in this study except for localized liver cancer, for which women had smaller improvements than men. Previous studies have shown that women are equally likely to receive surgical interventions for localized liver cancers.49,50 However, it has been reported that women may be less likely to benefit from localized tumor destruction than are men.51 The underlying mechanisms driving this sex disparity remain to be investigated.

When considering the underlying reasons for the age- and race-related disparities reported in our study, it is important to discern whether improvements in screening may explain the change over time. We did not have data from the SEER registries for the evaluation of the impact of cancer screening and diagnosis on our results. In particular, lead-time bias could be a potential concern for this study, particularly where there are differences in the secular trend of cancer screening and early diagnosis among the comparison groups analyzed in this study. However, to our knowledge, no data are available to indicate that these differences exist.52 Our analyses by stages showed that the age-related disparities in degree of survival improvements over the past 20 years were present for virtually all stages, including late-stage cancer, suggesting that these disparities cannot be entirely explained by cancer screening practices during the study period, particularly since the late-stage diseases were less likely to be affected by screening. Although our data argue against changes in cancer screening and diagnosis patterns driving the age-related differences in cancer survival improvements, we could not exclude entirely the possibility for some influence of difference in screenings and diagnosis by age on our study findings.

The SEER 9 registries cover approximately 10% of the US population, and the population covered by the SEER program is, in general, similar to the general US population in terms of education and socioeconomic levels. However, SEER oversamples urban and foreign-born populations,24 which may affect the generalizability of our findings to the general US population. Other limitations include those inherent in retrospective database analyses. Data on individual socioeconomic status, lifestyle factors, and comorbidities were not available, and thus these variables cannot be adjusted in our study. Therefore, potential confounding effects by these variables on our results cannot be excluded.

Our data suggest that age- and race-related differences in survival improvements over time may be explained, at least in part, by differences in cancer care across these subpopulations. By demonstrating these disparities, we have taken an initial step toward acknowledging the possibility of differential care and/or responses to new therapies for different patients. We hypothesize that some differences in care, particularly those suggesting less improvement in survival among elderly and African American patients, may be related to the lack of evidence specific to these populations. Our findings are a call to action; future studies should strive to include diverse populations, particularly the elderly and African Americans, in order to establish an evidence base for treatment of all patients. Understanding differences in the rates of improvement in survival among these specific populations and addressing these differences in future studies is a crucial part of improving cancer care for all.

Corresponding Author: Wei Zheng, MD, PhD, Vanderbilt Epidemiology Center and Vanderbilt-Ingram Cancer Center, 2525 West End Ave, Ste 800, Nashville, TN 37203-1738 (wei.zheng@vanderbilt.edu).

Accepted for Publication: December 6, 2014.

Published Online: February 19, 2015. doi:10.1001/jamaoncol.2014.161.

Author Contributions: Dr Zheng had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Zeng, Zheng.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Zeng, Morgans, Zheng.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Zeng, Wen.

Obtained funding: Zheng.

Administrative, technical, or material support: Shu, Zheng.

Study supervision: Morgans, Pao, Zheng.

Conflict of Interest Disclosures: None reported.

Funding/Support: This study was supported in part by US National Institutes of Health grant R37CA70867, Ingram Professorship, and Anne Potter Wilson Chair funds. Ms Zeng is supported by the Vanderbilt International Scholarship Program.

Role of the Funder/Sponsor: The funding organizations had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data, or preparation and approval of the manuscript.

Disclaimer: The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Additional Contributions: We thank Bethanie Rammer, BA, and Kimberly Kreth, MBA, Vanderbilt University, for their assistance in editing and preparing the manuscript. They received salary support from the Division of Epidemiology at Vanderbilt University.

Siegel  R, Ma  J, Zou  Z, Jemal  A.  Cancer statistics, 2014. CA Cancer J Clin. 2014;64(1):9-29.
PubMed   |  Link to Article
Jemal  A, Bray  F, Center  MM, Ferlay  J, Ward  E, Forman  D.  Global cancer statistics. CA Cancer J Clin. 2011;61(2):69-90.
PubMed   |  Link to Article
Herbst  RS, Bajorin  DF, Bleiberg  H,  et al; American Society of Clinical Oncology.  Clinical Cancer Advances 2005: major research advances in cancer treatment, prevention, and screening: a report from the American Society of Clinical Oncology. J Clin Oncol. 2006;24(1):190-205.
PubMed   |  Link to Article
Griggs  JJ, Culakova  E, Sorbero  ME,  et al.  Social and racial differences in selection of breast cancer adjuvant chemotherapy regimens. J Clin Oncol. 2007;25(18):2522-2527.
PubMed   |  Link to Article
Gralow  J, Ozols  RF, Bajorin  DF,  et al; American Society of Clinical Oncology.  Clinical cancer advances 2007: major research advances in cancer treatment, prevention, and screening: a report from the American Society of Clinical Oncology. J Clin Oncol. 2008;26(2):313-325.
PubMed   |  Link to Article
Edwards  BK, Brown  ML, Wingo  PA,  et al.  Annual report to the nation on the status of cancer, 1975-2002, featuring population-based trends in cancer treatment. J Natl Cancer Inst. 2005;97(19):1407-1427.
PubMed   |  Link to Article
Jemal  A, Clegg  LX, Ward  E,  et al.  Annual report to the nation on the status of cancer, 1975-2001, with a special feature regarding survival. Cancer. 2004;101(1):3-27.
PubMed   |  Link to Article
Siegel  R, Ward  E, Brawley  O, Jemal  A.  Cancer statistics, 2011: the impact of eliminating socioeconomic and racial disparities on premature cancer deaths. CA Cancer J Clin. 2011;61(4):212-236.
PubMed   |  Link to Article
Siegel  R, Desantis  C, Jemal  A.  Colorectal cancer statistics, 2014. CA Cancer J Clin. 2014;64(2):104-117.
PubMed   |  Link to Article
Smith  BD, Jiang  J, McLaughlin  SS,  et al.  Improvement in breast cancer outcomes over time: are older women missing out? J Clin Oncol. 2011;29(35):4647-4653.
PubMed   |  Link to Article
Robbins  AS, Siegel  RL, Jemal  A.  Racial disparities in stage-specific colorectal cancer mortality rates from 1985 to 2008. J Clin Oncol. 2012;30(4):401-405.
PubMed   |  Link to Article
Cook  MB, McGlynn  KA, Devesa  SS, Freedman  ND, Anderson  WF.  Sex disparities in cancer mortality and survival. Cancer Epidemiol Biomarkers Prev. 2011;20(8):1629-1637.
PubMed   |  Link to Article
Jemal  A, Simard  EP, Dorell  C,  et al.  Annual Report to the Nation on the Status of Cancer, 1975-2009, featuring the burden and trends in human papillomavirus (HPV)-associated cancers and HPV vaccination coverage levels. J Natl Cancer Inst. 2013;105(3):175-201.
PubMed   |  Link to Article
Hershman  DL, Unger  JM, Barlow  WE,  et al.  Treatment quality and outcomes of African American versus white breast cancer patients: retrospective analysis of Southwest Oncology studies S8814/S8897. J Clin Oncol. 2009;27(13):2157-2162.
PubMed   |  Link to Article
Freedman  RA, He  Y, Winer  EP, Keating  NL.  Trends in racial and age disparities in definitive local therapy of early-stage breast cancer. J Clin Oncol. 2009;27(5):713-719.
PubMed   |  Link to Article
Gross  CP, Smith  BD, Wolf  E, Andersen  M.  Racial disparities in cancer therapy: did the gap narrow between 1992 and 2002? Cancer. 2008;112(4):900-908.
PubMed   |  Link to Article
van de Water  W, Markopoulos  C, van de Velde  CJ,  et al.  Association between age at diagnosis and disease-specific mortality among postmenopausal women with hormone receptor-positive breast cancer. JAMA. 2012;307(6):590-597.
PubMed   |  Link to Article
Harper  S, Lynch  J, Meersman  SC, Breen  N, Davis  WW, Reichman  MC.  Trends in area-socioeconomic and race-ethnic disparities in breast cancer incidence, stage at diagnosis, screening, mortality, and survival among women ages 50 years and over (1987-2005). Cancer Epidemiol Biomarkers Prev. 2009;18(1):121-131.
PubMed   |  Link to Article
Castleberry  AW, Güller  U, Tarantino  I,  et al.  Discrete improvement in racial disparity in survival among patients with stage IV colorectal cancer: a 21-year population-based analysis. J Gastrointest Surg. 2014;18(6):1194-1204.
PubMed   |  Link to Article
Jafari  MD, Jafari  F, Halabi  WJ,  et al.  Colorectal cancer resections in the aging US population: a trend toward decreasing rates and improved outcomes [published online April 9, 2014]. JAMA Surg. doi:10.1001/jamasurg.2013.4930.
PubMed
Ma  J, Siegel  R, Jemal  A.  Pancreatic cancer death rates by race among US men and women, 1970-2009. J Natl Cancer Inst. 2013;105(22):1694-1700.
PubMed   |  Link to Article
Shao  YH, Demissie  K, Shih  W,  et al.  Contemporary risk profile of prostate cancer in the United States. J Natl Cancer Inst. 2009;101(18):1280-1283.
PubMed   |  Link to Article
Tannenbaum  SL, Koru-Sengul  T, Zhao  W, Miao  F, Byrne  MM.  Survival disparities in non-small cell lung cancer by race, ethnicity, and socioeconomic status. Cancer J. 2014;20(4):237-245.
PubMed   |  Link to Article
SEER Research Data 1973-2010—ASCII Text Data. National Cancer Institute, DCCPS, Surveillance Research Program, Surveillance Systems Branch; 2013. http://www.seer.cancer.gov. Accessed January 1, 2014.
World Health Organization. International Classification of Diseases for Oncology. 3rd ed. Geneva, Switzerland: World Health Organization; 2000.
Siegel  R, Naishadham  D, Jemal  A.  Cancer statistics, 2013. CA Cancer J Clin. 2013;63(1):11-30.
PubMed   |  Link to Article
Howlader  N, Ries  LA, Mariotto  AB, Reichman  ME, Ruhl  J, Cronin  KA.  Improved estimates of cancer-specific survival rates from population-based data. J Natl Cancer Inst. 2010;102(20):1584-1598.
PubMed   |  Link to Article
Gill  S, Loprinzi  CL, Sargent  DJ,  et al.  Pooled analysis of fluorouracil-based adjuvant therapy for stage II and III colon cancer: who benefits and by how much? J Clin Oncol. 2004;22(10):1797-1806.
PubMed   |  Link to Article
Clarke  M.  Meta-analyses of adjuvant therapies for women with early breast cancer: the Early Breast Cancer Trialists’ Collaborative Group overview. Ann Oncol. 2006;17(suppl 10):x59-x62.
PubMed   |  Link to Article
El-Serag  HB.  Hepatocellular carcinoma. N Engl J Med. 2011;365(12):1118-1127.
PubMed   |  Link to Article
Shayne  M, Culakova  E, Poniewierski  MS,  et al.  Dose intensity and hematologic toxicity in older cancer patients receiving systemic chemotherapy. Cancer. 2007;110(7):1611-1620.
PubMed   |  Link to Article
Muss  HB, Berry  DA, Cirrincione  C,  et al; Cancer and Leukemia Group B Experience.  Toxicity of older and younger patients treated with adjuvant chemotherapy for node-positive breast cancer: the Cancer and Leukemia Group B Experience. J Clin Oncol. 2007;25(24):3699-3704.
PubMed   |  Link to Article
Hurria  A, Fleming  MT, Baker  SD,  et al.  Pharmacokinetics and toxicity of weekly docetaxel in older patients. Clin Cancer Res. 2006;12(20, pt 1):6100-6105.
PubMed   |  Link to Article
Caillet  P, Canoui-Poitrine  F, Vouriot  J,  et al.  Comprehensive geriatric assessment in the decision-making process in elderly patients with cancer: ELCAPA study. J Clin Oncol. 2011;29(27):3636-3642.
PubMed   |  Link to Article
Lee  L, Cheung  WY, Atkinson  E, Krzyzanowska  MK.  Impact of comorbidity on chemotherapy use and outcomes in solid tumors: a systematic review. J Clin Oncol. 2011;29(1):106-117.
PubMed   |  Link to Article
Foster  JA, Salinas  GD, Mansell  D, Williamson  JC, Casebeer  LL.  How does older age influence oncologists’ cancer management? Oncologist. 2010;15(6):584-592.
PubMed   |  Link to Article
Talarico  L, Chen  G, Pazdur  R.  Enrollment of elderly patients in clinical trials for cancer drug registration: a 7-year experience by the US Food and Drug Administration. J Clin Oncol. 2004;22(22):4626-4631.
PubMed   |  Link to Article
Murthy  VH, Krumholz  HM, Gross  CP.  Participation in cancer clinical trials: race-, sex-, and age-based disparities. JAMA. 2004;291(22):2720-2726.
PubMed   |  Link to Article
Lewis  JH, Kilgore  ML, Goldman  DP,  et al.  Participation of patients 65 years of age or older in cancer clinical trials. J Clin Oncol. 2003;21(7):1383-1389.
PubMed   |  Link to Article
Owusu  C, Buist  DS, Field  TS,  et al.  Predictors of tamoxifen discontinuation among older women with estrogen receptor-positive breast cancer. J Clin Oncol. 2008;26(4):549-555.
PubMed   |  Link to Article
Edwards  BK, Howe  HL, Ries  LA,  et al.  Annual report to the nation on the status of cancer, 1973-1999, featuring implications of age and aging on U.S. cancer burden. Cancer. 2002;94(10):2766-2792.
PubMed   |  Link to Article
Barnholtz-Sloan  JS, Schwartz  AG, Qureshi  F, Jacques  S, Malone  J, Munkarah  AR.  Ovarian cancer: changes in patterns at diagnosis and relative survival over the last three decades. Am J Obstet Gynecol. 2003;189(4):1120-1127.
PubMed   |  Link to Article
Bristow  RE, Powell  MA, Al-Hammadi  N,  et al.  Disparities in ovarian cancer care quality and survival according to race and socioeconomic status. J Natl Cancer Inst. 2013;105(11):823-832.
PubMed   |  Link to Article
Aranda  MA, McGory  M, Sekeris  E, Maggard  M, Ko  C, Zingmond  DS.  Do racial/ethnic disparities exist in the utilization of high-volume surgeons for women with ovarian cancer? Gynecol Oncol. 2008;111(2):166-172.
PubMed   |  Link to Article
DeLancey  JO, Thun  MJ, Jemal  A, Ward  EM.  Recent trends in black-white disparities in cancer mortality. Cancer Epidemiol Biomarkers Prev. 2008;17(11):2908-2912.
PubMed   |  Link to Article
DeSantis  C, Naishadham  D, Jemal  A.  Cancer statistics for African Americans, 2013. CA Cancer J Clin. 2013;63(3):151-166.
PubMed   |  Link to Article
Taylor  KL, Davis  JL  III, Turner  RO,  et al.  Educating African American men about the prostate cancer screening dilemma: a randomized intervention. Cancer Epidemiol Biomarkers Prev. 2006;15(11):2179-2188.
PubMed   |  Link to Article
Najari  BB, Rink  M, Li  PS,  et al.  Sex disparities in cancer mortality: the risks of being a man in the United States. J Urol. 2013;189(4):1470-1474.
PubMed   |  Link to Article
Zak  Y, Rhoads  KF, Visser  BC.  Predictors of surgical intervention for hepatocellular carcinoma: race, socioeconomic status, and hospital type. Arch Surg. 2011;146(7):778-784.
PubMed   |  Link to Article
Sonnenday  CJ, Dimick  JB, Schulick  RD, Choti  MA.  Racial and geographic disparities in the utilization of surgical therapy for hepatocellular carcinoma. J Gastrointest Surg. 2007;11(12):1636-1646.
PubMed   |  Link to Article
Wong  RJ, Corley  DA.  Survival differences by race/ethnicity and treatment for localized hepatocellular carcinoma within the United States. Dig Dis Sci. 2009;54(9):2031-2039.
PubMed   |  Link to Article
Swan  J, Breen  N, Coates  RJ, Rimer  BK, Lee  NC.  Progress in cancer screening practices in the United States: results from the 2000 National Health Interview Survey. Cancer. 2003;97(6):1528-1540.
PubMed   |  Link to Article

Figures

Place holder to copy figure label and caption
Figure 1.
Multivariate-Adjusted Hazard Ratios (HRs) and 95% CIs for Cancer-Specific Death Associated With Year of Diagnosis According to Race, in 9 SEER Registries, 1990-2009

The HRs and 95% CIs were adjusted for marital status, common histologic types, SEER registry sites, SEER historic stage, age, and sex (if applicable), using the time period 1990-1994 as the reference. P values for interaction for year of diagnosis and race are presented. SEER indicates Surveillance, Epidemiology, and End Results.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.
Multivariate-Adjusted Hazard Ratios (HRs) and 95% CIs for Cancer-Specific Death Associated With Year of Diagnosis According to Age at Diagnosis, in 9 SEER Registries, 1990-2009

The HRs and 95% CIs were adjusted for marital status, common histologic types, SEER registry sites, SEER historic stage, race, and sex (if applicable), using the time period 1990 to 1994 as the reference. P values for interaction for year of diagnosis and age groups are presented. SEER indicates Surveillance, Epidemiology, and End Results.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 3.
Multivariate-Adjusted Hazard Ratios (HRs) and 95% CIs for Cancer-Specific Death Associated With Every 5-Year Change in Years of Cancer Diagnosis From 1990 to 2009, According to Age at Diagnosis Stratified by Cancer Stage at Diagnosis, in 9 SEER Registries, 1990-2009

HRs and 95% CIs were adjusted for marital status, common histologic types, SEER registry sites, race, and sex (if applicable), using the time period 1990-1994 as the reference. P values for heterogeneity across cancer stages are presented. SEER indicates Surveillance, Epidemiology, and End Results.

Graphic Jump Location

Tables

Table Graphic Jump LocationTable.  Cancer-Specific Survival Rates for 230 449 Patients Diagnosed From 1990 to 1994 According to Age Group, Race/Ethnicity, and Sex, in 9 SEER Registries

References

Siegel  R, Ma  J, Zou  Z, Jemal  A.  Cancer statistics, 2014. CA Cancer J Clin. 2014;64(1):9-29.
PubMed   |  Link to Article
Jemal  A, Bray  F, Center  MM, Ferlay  J, Ward  E, Forman  D.  Global cancer statistics. CA Cancer J Clin. 2011;61(2):69-90.
PubMed   |  Link to Article
Herbst  RS, Bajorin  DF, Bleiberg  H,  et al; American Society of Clinical Oncology.  Clinical Cancer Advances 2005: major research advances in cancer treatment, prevention, and screening: a report from the American Society of Clinical Oncology. J Clin Oncol. 2006;24(1):190-205.
PubMed   |  Link to Article
Griggs  JJ, Culakova  E, Sorbero  ME,  et al.  Social and racial differences in selection of breast cancer adjuvant chemotherapy regimens. J Clin Oncol. 2007;25(18):2522-2527.
PubMed   |  Link to Article
Gralow  J, Ozols  RF, Bajorin  DF,  et al; American Society of Clinical Oncology.  Clinical cancer advances 2007: major research advances in cancer treatment, prevention, and screening: a report from the American Society of Clinical Oncology. J Clin Oncol. 2008;26(2):313-325.
PubMed   |  Link to Article
Edwards  BK, Brown  ML, Wingo  PA,  et al.  Annual report to the nation on the status of cancer, 1975-2002, featuring population-based trends in cancer treatment. J Natl Cancer Inst. 2005;97(19):1407-1427.
PubMed   |  Link to Article
Jemal  A, Clegg  LX, Ward  E,  et al.  Annual report to the nation on the status of cancer, 1975-2001, with a special feature regarding survival. Cancer. 2004;101(1):3-27.
PubMed   |  Link to Article
Siegel  R, Ward  E, Brawley  O, Jemal  A.  Cancer statistics, 2011: the impact of eliminating socioeconomic and racial disparities on premature cancer deaths. CA Cancer J Clin. 2011;61(4):212-236.
PubMed   |  Link to Article
Siegel  R, Desantis  C, Jemal  A.  Colorectal cancer statistics, 2014. CA Cancer J Clin. 2014;64(2):104-117.
PubMed   |  Link to Article
Smith  BD, Jiang  J, McLaughlin  SS,  et al.  Improvement in breast cancer outcomes over time: are older women missing out? J Clin Oncol. 2011;29(35):4647-4653.
PubMed   |  Link to Article
Robbins  AS, Siegel  RL, Jemal  A.  Racial disparities in stage-specific colorectal cancer mortality rates from 1985 to 2008. J Clin Oncol. 2012;30(4):401-405.
PubMed   |  Link to Article
Cook  MB, McGlynn  KA, Devesa  SS, Freedman  ND, Anderson  WF.  Sex disparities in cancer mortality and survival. Cancer Epidemiol Biomarkers Prev. 2011;20(8):1629-1637.
PubMed   |  Link to Article
Jemal  A, Simard  EP, Dorell  C,  et al.  Annual Report to the Nation on the Status of Cancer, 1975-2009, featuring the burden and trends in human papillomavirus (HPV)-associated cancers and HPV vaccination coverage levels. J Natl Cancer Inst. 2013;105(3):175-201.
PubMed   |  Link to Article
Hershman  DL, Unger  JM, Barlow  WE,  et al.  Treatment quality and outcomes of African American versus white breast cancer patients: retrospective analysis of Southwest Oncology studies S8814/S8897. J Clin Oncol. 2009;27(13):2157-2162.
PubMed   |  Link to Article
Freedman  RA, He  Y, Winer  EP, Keating  NL.  Trends in racial and age disparities in definitive local therapy of early-stage breast cancer. J Clin Oncol. 2009;27(5):713-719.
PubMed   |  Link to Article
Gross  CP, Smith  BD, Wolf  E, Andersen  M.  Racial disparities in cancer therapy: did the gap narrow between 1992 and 2002? Cancer. 2008;112(4):900-908.
PubMed   |  Link to Article
van de Water  W, Markopoulos  C, van de Velde  CJ,  et al.  Association between age at diagnosis and disease-specific mortality among postmenopausal women with hormone receptor-positive breast cancer. JAMA. 2012;307(6):590-597.
PubMed   |  Link to Article
Harper  S, Lynch  J, Meersman  SC, Breen  N, Davis  WW, Reichman  MC.  Trends in area-socioeconomic and race-ethnic disparities in breast cancer incidence, stage at diagnosis, screening, mortality, and survival among women ages 50 years and over (1987-2005). Cancer Epidemiol Biomarkers Prev. 2009;18(1):121-131.
PubMed   |  Link to Article
Castleberry  AW, Güller  U, Tarantino  I,  et al.  Discrete improvement in racial disparity in survival among patients with stage IV colorectal cancer: a 21-year population-based analysis. J Gastrointest Surg. 2014;18(6):1194-1204.
PubMed   |  Link to Article
Jafari  MD, Jafari  F, Halabi  WJ,  et al.  Colorectal cancer resections in the aging US population: a trend toward decreasing rates and improved outcomes [published online April 9, 2014]. JAMA Surg. doi:10.1001/jamasurg.2013.4930.
PubMed
Ma  J, Siegel  R, Jemal  A.  Pancreatic cancer death rates by race among US men and women, 1970-2009. J Natl Cancer Inst. 2013;105(22):1694-1700.
PubMed   |  Link to Article
Shao  YH, Demissie  K, Shih  W,  et al.  Contemporary risk profile of prostate cancer in the United States. J Natl Cancer Inst. 2009;101(18):1280-1283.
PubMed   |  Link to Article
Tannenbaum  SL, Koru-Sengul  T, Zhao  W, Miao  F, Byrne  MM.  Survival disparities in non-small cell lung cancer by race, ethnicity, and socioeconomic status. Cancer J. 2014;20(4):237-245.
PubMed   |  Link to Article
SEER Research Data 1973-2010—ASCII Text Data. National Cancer Institute, DCCPS, Surveillance Research Program, Surveillance Systems Branch; 2013. http://www.seer.cancer.gov. Accessed January 1, 2014.
World Health Organization. International Classification of Diseases for Oncology. 3rd ed. Geneva, Switzerland: World Health Organization; 2000.
Siegel  R, Naishadham  D, Jemal  A.  Cancer statistics, 2013. CA Cancer J Clin. 2013;63(1):11-30.
PubMed   |  Link to Article
Howlader  N, Ries  LA, Mariotto  AB, Reichman  ME, Ruhl  J, Cronin  KA.  Improved estimates of cancer-specific survival rates from population-based data. J Natl Cancer Inst. 2010;102(20):1584-1598.
PubMed   |  Link to Article
Gill  S, Loprinzi  CL, Sargent  DJ,  et al.  Pooled analysis of fluorouracil-based adjuvant therapy for stage II and III colon cancer: who benefits and by how much? J Clin Oncol. 2004;22(10):1797-1806.
PubMed   |  Link to Article
Clarke  M.  Meta-analyses of adjuvant therapies for women with early breast cancer: the Early Breast Cancer Trialists’ Collaborative Group overview. Ann Oncol. 2006;17(suppl 10):x59-x62.
PubMed   |  Link to Article
El-Serag  HB.  Hepatocellular carcinoma. N Engl J Med. 2011;365(12):1118-1127.
PubMed   |  Link to Article
Shayne  M, Culakova  E, Poniewierski  MS,  et al.  Dose intensity and hematologic toxicity in older cancer patients receiving systemic chemotherapy. Cancer. 2007;110(7):1611-1620.
PubMed   |  Link to Article
Muss  HB, Berry  DA, Cirrincione  C,  et al; Cancer and Leukemia Group B Experience.  Toxicity of older and younger patients treated with adjuvant chemotherapy for node-positive breast cancer: the Cancer and Leukemia Group B Experience. J Clin Oncol. 2007;25(24):3699-3704.
PubMed   |  Link to Article
Hurria  A, Fleming  MT, Baker  SD,  et al.  Pharmacokinetics and toxicity of weekly docetaxel in older patients. Clin Cancer Res. 2006;12(20, pt 1):6100-6105.
PubMed   |  Link to Article
Caillet  P, Canoui-Poitrine  F, Vouriot  J,  et al.  Comprehensive geriatric assessment in the decision-making process in elderly patients with cancer: ELCAPA study. J Clin Oncol. 2011;29(27):3636-3642.
PubMed   |  Link to Article
Lee  L, Cheung  WY, Atkinson  E, Krzyzanowska  MK.  Impact of comorbidity on chemotherapy use and outcomes in solid tumors: a systematic review. J Clin Oncol. 2011;29(1):106-117.
PubMed   |  Link to Article
Foster  JA, Salinas  GD, Mansell  D, Williamson  JC, Casebeer  LL.  How does older age influence oncologists’ cancer management? Oncologist. 2010;15(6):584-592.
PubMed   |  Link to Article
Talarico  L, Chen  G, Pazdur  R.  Enrollment of elderly patients in clinical trials for cancer drug registration: a 7-year experience by the US Food and Drug Administration. J Clin Oncol. 2004;22(22):4626-4631.
PubMed   |  Link to Article
Murthy  VH, Krumholz  HM, Gross  CP.  Participation in cancer clinical trials: race-, sex-, and age-based disparities. JAMA. 2004;291(22):2720-2726.
PubMed   |  Link to Article
Lewis  JH, Kilgore  ML, Goldman  DP,  et al.  Participation of patients 65 years of age or older in cancer clinical trials. J Clin Oncol. 2003;21(7):1383-1389.
PubMed   |  Link to Article
Owusu  C, Buist  DS, Field  TS,  et al.  Predictors of tamoxifen discontinuation among older women with estrogen receptor-positive breast cancer. J Clin Oncol. 2008;26(4):549-555.
PubMed   |  Link to Article
Edwards  BK, Howe  HL, Ries  LA,  et al.  Annual report to the nation on the status of cancer, 1973-1999, featuring implications of age and aging on U.S. cancer burden. Cancer. 2002;94(10):2766-2792.
PubMed   |  Link to Article
Barnholtz-Sloan  JS, Schwartz  AG, Qureshi  F, Jacques  S, Malone  J, Munkarah  AR.  Ovarian cancer: changes in patterns at diagnosis and relative survival over the last three decades. Am J Obstet Gynecol. 2003;189(4):1120-1127.
PubMed   |  Link to Article
Bristow  RE, Powell  MA, Al-Hammadi  N,  et al.  Disparities in ovarian cancer care quality and survival according to race and socioeconomic status. J Natl Cancer Inst. 2013;105(11):823-832.
PubMed   |  Link to Article
Aranda  MA, McGory  M, Sekeris  E, Maggard  M, Ko  C, Zingmond  DS.  Do racial/ethnic disparities exist in the utilization of high-volume surgeons for women with ovarian cancer? Gynecol Oncol. 2008;111(2):166-172.
PubMed   |  Link to Article
DeLancey  JO, Thun  MJ, Jemal  A, Ward  EM.  Recent trends in black-white disparities in cancer mortality. Cancer Epidemiol Biomarkers Prev. 2008;17(11):2908-2912.
PubMed   |  Link to Article
DeSantis  C, Naishadham  D, Jemal  A.  Cancer statistics for African Americans, 2013. CA Cancer J Clin. 2013;63(3):151-166.
PubMed   |  Link to Article
Taylor  KL, Davis  JL  III, Turner  RO,  et al.  Educating African American men about the prostate cancer screening dilemma: a randomized intervention. Cancer Epidemiol Biomarkers Prev. 2006;15(11):2179-2188.
PubMed   |  Link to Article
Najari  BB, Rink  M, Li  PS,  et al.  Sex disparities in cancer mortality: the risks of being a man in the United States. J Urol. 2013;189(4):1470-1474.
PubMed   |  Link to Article
Zak  Y, Rhoads  KF, Visser  BC.  Predictors of surgical intervention for hepatocellular carcinoma: race, socioeconomic status, and hospital type. Arch Surg. 2011;146(7):778-784.
PubMed   |  Link to Article
Sonnenday  CJ, Dimick  JB, Schulick  RD, Choti  MA.  Racial and geographic disparities in the utilization of surgical therapy for hepatocellular carcinoma. J Gastrointest Surg. 2007;11(12):1636-1646.
PubMed   |  Link to Article
Wong  RJ, Corley  DA.  Survival differences by race/ethnicity and treatment for localized hepatocellular carcinoma within the United States. Dig Dis Sci. 2009;54(9):2031-2039.
PubMed   |  Link to Article
Swan  J, Breen  N, Coates  RJ, Rimer  BK, Lee  NC.  Progress in cancer screening practices in the United States: results from the 2000 National Health Interview Survey. Cancer. 2003;97(6):1528-1540.
PubMed   |  Link to Article

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Disparities in the Improvement of Survival for Major Cancers
Posted on May 14, 2015
Kailin Yang, PhD
Cleveland Clinic Lerner College of Medicine
Conflict of Interest: None Declared

The study by Zeng and colleagues (1) systematically analyzed the survival of patients with seven major types of solid tumors, using a dataset from 1990 to 2009 from the Surveillance, Epidemiology, and End Results (SEER) program by National Cancer Institute (NCI). They argued that younger patients and those diagnosed from 2005-2009 benefited the most from recent advances in cancer treatment. However, one major concern with this study is the underestimation of lead-time bias when reaching the above conclusion. During the past two decades, novel diagnostic test and imaging modality have greatly improved the detection of cancer at early stage. Therefore, a higher proportion of latent and slow-growing tumors would be included in recent time periods such as 2005-2009.Taking prostate cancer as an example, the wide application of prostate specific antigen (PSA) testing since the 1990s has resulted in significant downward stage and grade migration (2,3). Lead-time bias caused by PSA testing is estimated to be as high as 12 years (4), according to the European Randomized Study of Screening for Prostate Cancer (ERSPC). Such change would generate a high risk of overdiagnosis and overtreatment, especially in men who would otherwise have no clinical symptoms during their lifetime. Because survival rate by cancer-specific death was used as the major outcome in this study, the presence of a higher percentage of early stage patients and those with low potential to progress clinically in the cohort of recent time period would confound data interpretation. Although the SEER program has crude information for tumor characteristics (for example, tumor grade and histology were used for adjustment in prostate cancer), these factors might not be sensitive enough to correct for lead-time bias, given the wide range of molecular complexity between tumors of low and high risks. Demographic changes among the 9 SEER registries might further confound the analysis in this study. The authors corrected for SEER registry site, race, sex, and marital status when calculating hazard ratios. However, information such as body mass index or other comorbidities were not collected. Since 1990, the prevalence of overweight and obesity has dramatically increased in the United States (5), and higher BMI is known to be associated with higher cancer incidence especially for breast and colon cancers. Similarly, the evolution of clinical management for other comorbidities linked to cancer, such as diabetes or chronic inflammation, might also contribute to the improved cancer survival seen in this study.

References:

1. Zeng C, Wen W, Morgans AK, Pao W, Shu X-O, ZHeng W. Disparities by Race, Age, and Sex in the Improvement of Survival for Major Cancers: Results From the National Cancer Institute Surveillance, Epidemiology, and End Results (SEER) Program in the United States, 1990 to 2010. JAMA Oncology. 2015;1(1):88-96.

2. Catalona WJ, Smith DS, Ratliff TL, Basler JW. Detection of organ-confined prostate cancer is increased through prostate-specific antigen-based screening. JAMA. 1993;270(8):948-954.

3. Moore AL, Dimitropoulou P, Lane A, et al. Population-based prostate-specific antigen testing in the UK leads to a stage migration of prostate cancer. BJU Int. 2009;104(11):1592-1598.

4. Draisma G, Boer R, Otto SJ, et al. Lead times and overdetection due to prostate-specific antigen screening: estimates from the European Randomized Study of Screening for Prostate Cancer. J Natl Cancer Inst. 2003;95(12):868-878.

5. Ogden CL, Carroll MD, Curtin LR, McDowell MA, Tabak CJ, Flegal KM. Prevalence of overweight and obesity in the United States, 1999-2004. JAMA. 2006;295(13):1549-1555.

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Multimedia

Supplement.

eTable 1. Number of cancer cases by sex and year of diagnosis, nine SEER registries, 1990-2009

eTable 2. Baseline demographic and tumor characteristics of colorectal cancer patients according to year of diagnosis, nine SEER registries, 1990-2009

eTable 3. Baseline demographic and tumor characteristics of female breast cancer patients according to year of diagnosis, nine SEER registries, 1990-2009

eTable 4. Baseline demographic and tumor characteristics of liver and intrahepatic bile duct cancer patients according to year of diagnosis, nine SEER registries, 1990-2009

eTable 5. Baseline demographic and tumor characteristics of lung cancer patients according to year of diagnosis, nine SEER registries, 1990-2009

eTable 6. Baseline demographic and tumor characteristics of pancreatic cancer patients according to year of diagnosis, nine SEER registries, 1990-2009

eTable 7. Baseline demographic and tumor characteristics of prostate cancer patients according to year of diagnosis, nine SEER registries, 1990-2009

eTable 8. Baseline demographic and tumor characteristics of ovarian cancer patients according to year of diagnosis, nine SEER registries, 1990-2009

eTable 9. Multivariate-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for cancer-specific death associated with year of diagnosis according to race, nine SEER registries, 1990-2009

eTable 10. Multivariate-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for cancer-specific death associated with year of diagnosis according to age at diagnosis, nine SEER registries, 1990-2009

eTable 11. Multivariate-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for cancer-specific death associated with year of diagnosis according to sex, nine SEER registries, 1990-2009

eTable 12. Stage-specific multivariate-adjusted HRs and 95% CIs for cancer-specific death per 5-year increment in year of diagnosis according to age at diagnosis, nine SEER registries, 1990-2009

eTable 13. Stage-specific multivariate-adjusted HRs and 95% CIs for cancer-specific death per 5-year increment in year of diagnosis according to race, nine SEER registries, 1990-2009

eTable 14. Stage-specific multivariate-adjusted HRs and 95% CIs for cancer-specific death per 5-year increment in year of diagnosis according to sex, nine SEER registries, 1990-2009

eTable 15. P-values for three-way interactions of SEER registry sites, year of diagnosis and race, age groups, or sex, nine SEER registries, 1990-2009

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