Cancer and COVID-19: US cancer incidence rates during the first year of the pandemic.

BACKGROUND: The COVID-19 pandemic has had a profound global impact on health-care systems and patient outcomes. However, the specific effects of the pandemic on cancer incidence rates in the United States during its initial year remain unknown. METHODS: In this study, we analyzed data from the Surveillance, Epidemiology, and End Results-22 registries, which encompass approximately 50% of the US population. We investigated changes in monthly incidence rates stratified by various factors, including cancer type, stage, age group, sex, race and ethnicity, socioeconomic status, rural-urban status, and registry locations. We compared the incidence rates observed during the pandemic with those from the previous year. RESULTS: Our findings revealed a decline in incidence rates for all cancer sites combined starting in March 2020, coinciding with the implementation of stay-at-home orders. This decline reached its lowest point in April 2020 and persisted at a lower level until May 2020. Notably, compared with April 2019, the incidence rates in April 2020 dropped by 48.1% and did not consistently return to prepandemic levels. The reduction in cancer rates was more pronounced in urban and affluent counties. Across all cancer types, there was a statistically significant decrease in incidence rates during the pandemic, with the largest declines observed in thyroid (71.2%), prostate (57.9%), breast (54.9%), and colon and rectum cancers (54.1%). Furthermore, these decreases were primarily observed in early stage rather than late-stage disease. CONCLUSIONS: The COVID-19 pandemic had a statistically significant impact on cancer outcomes. Monitoring long-term consequences of the pandemic on cancer incidence, stage at diagnosis, and mortality trends will be crucial.

Increase in the Life Expectancy of Patients with Cancer in the United States.

BACKGROUND: Cancer is becoming more of a chronic disease due to improvements in treatment and early detection for multiple cancer sites. To gain insight on increased life expectancy due to these improvements, we quantified trends in the loss in expectation of life (LEL) due to a cancer diagnosis for six cancer sites from 1975 through 2018. METHODS: We focused on patients diagnosed with female breast cancer, chronic myeloid leukemia (CML), colon and rectum cancer, diffuse large B-cell lymphoma (DLBCL), lung cancer, or melanoma between 1975 and 2018 from nine Surveillance, Epidemiology, and End Results cancer registries. Life expectancies for patients with cancer ages 50+ were modeled using flexible parametric survival models. LEL was calculated as the difference between general population life expectancy and life expectancy for patients with cancer. RESULTS: Over 2 million patients were diagnosed with one of the six cancers between 1975 and 2018. Large increases in life expectancy were observed between 1990 and 2010 for female breast, DLBCL, and CML. Patients with colon and rectum cancer and melanoma had more gradual improvements in life expectancy. Lung cancer LEL only began decreasing after 2005. Increases in life expectancy corresponded with decreases in LEL for patients with cancer. CONCLUSIONS: The reported gains in life expectancy largely correspond to progress in the screening, management, and treatment of these six cancers since 1975. IMPACT: LEL provides an important public health perspective on how improvements in treatment and early detection and their impacts on survival translate into changes in cancer patients' life expectancy.

Interpreting cancer incidence trends: challenges due to the COVID-19 pandemic.

The considerable deficit in cancer diagnoses in 2020 due to COVID-19 pandemic disruptions in health care can pose challenges in the estimation and interpretation of long-term cancer trends. Using Surveillance, Epidemiology, and End Results (SEER) (2000-2020) data, we demonstrate that inclusion of the 2020 incidence rates in joinpoint models to estimate trends can result in a poorer fit to the data and less accurate or less precise trend estimates, providing challenges in the interpretation of the estimates as a cancer control measure. To measure the decline in 2020 relative to 2019 cancer incidence rates, we used the percent change of rates in 2020 compared with 2019. Overall, SEER cancer incidence rates dropped approximately 10% in 2020, but for thyroid cancer the decrease was as large as 18% after adjusting for reporting delay. The 2020 SEER incidence data are available in all SEER released products, except for joinpoint estimates of trends and lifetime risk of developing cancer.

The Impact of Improved Treatments on Survival of Adult U.S. Leukemia Patients: 1990-2018.

INTRODUCTION: Molecularly targeted therapies such as tyrosine kinase inhibitors (TKI) are effective treatments for B-cell receptor (BCR)-ABL-bearing leukemias. We evaluated the impact of TKIs on historical chronic myeloid leukemia (CML) mortality trends compared with acute lymphoblastic leukemia (ALL) and chronic lymphoblastic leukemia (CLL). METHODS: Because mortality trends reflect combined effects of leukemia incidence and survival, we also evaluated the contribution of incidence and survival trends to mortality trends by subtypes. We used data from 13 U.S. (SEER) registries (1992-2017) among U.S. adults. We utilized histology codes to identify cases of CML, ALL, and CLL and death certificate data to calculate mortality. We used Joinpoint to characterize incidence (1992-2017) and mortality (1992-2018) trends by subtype and diagnosis year. RESULTS: For CML, mortality rates started declining in 1998 at an average rate of 12% annually. Imatinib was approved by the FDA for treating CML and ALL in 2001, leading to clear benefits for patients with CML. Five-year CML survival increased dramatically over time, especially between 1996 to 2011, 2.3% per year on average. ALL incidence increased 1.5% annually from 1992 to 2017. ALL mortality decreased 0.6% annually during 1992 to 2012 and then stopped declining. CLL incidence fluctuated during 1992 to 2017 while mortality decreased 1.1% annually during 1992 to 2011 and at a faster rate of 3.6% per year from 2011. Five-year survival increased 0.7% per year on average during 1992 to 2016. CONCLUSIONS: Survival benefit from TKIs and other novel therapies for treating leukemia subtypes has been demonstrated in clinical trials. IMPACT: Our study highlights the impact of molecularly targeted therapies at the population level.

Impact of including second and later cancers in cause-specific survival estimates using population-based registry data.

BACKGROUND: Second or later primary cancers account for approximately 20% of incident cases in the United States. Currently, cause-specific survival (CSS) analyses exclude these cancers because the cause of death (COD) classification algorithm was available only for first cancers. The authors added rules for later cancers to the Surveillance, Epidemiology, and End Results cause-specific death classification algorithm and evaluated CSS to include individuals with prior tumors. METHODS: The authors constructed 2 cohorts: 1) the first ever primary cohort, including patients whose first cancer was diagnosed during 2000 through 2016) and 2) the earliest matching primary cohort, including patients with any cancer who matched the selection criteria irrespective of whether it was the first or a later cancer diagnosed during 2000 through 2016. The cohorts' CSS estimates were compared using follow-up through December 31, 2017. The new rules were used in the second cohort for patients whose first cancers during 2000 through 2016 were their second or later cancers. RESULTS: Overall, there were no statistically significant differences in CSS estimates between the 2 cohorts. Estimates were similar by age, stage, race, and time since diagnosis, except for patients with leukemia and those aged 65 to 74 years (3.4 percentage point absolute difference). CONCLUSIONS: The absolute difference in CSS estimates for the first cancer ever cohort versus earliest of any cancers cohort in the study period was small for most cancer types. As the number of newly diagnosed patients with prior cancers increases, the algorithm will make CSS more inclusive and enable estimating survival for a group of patients with cancer for whom life tables are not available or life tables are available but do not capture other-cause mortality appropriately.

Measuring progress against cancer in the Azores, Portugal: Incidence, survival, and mortality trends and projections to 2025.

BACKGROUND: Measuring progress against cancer is more accurate when trends in incidence, survival, and mortality are interpreted simultaneously. Our study aims to analyze how these key metrics have evolved over time in the Azores, Portugal. METHODS: Data for incident cases diagnosed in 1997-2016 and followed up through December 31, 2017 were obtained from the Azores Cancer Registry. Data for cancer deaths that occurred in 1991-2016 were obtained from Statistics Portugal. To estimate temporal trends, we applied a joinpoint model to age-adjusted rates. We estimated five-year net survival within the framework of relative survival using the Pohar-Perme estimator and predicted the number of cases and deaths in 2025. RESULTS: In men, incidence and mortality decreased for stomach, larynx, and prostate cancer. In women, mortality decreased for breast and cervical cancer. Five-year relative survival improved for several cancers, with the most pronounced improvements for prostate cancer in men and colorectal cancer in women (24.1 and 27.9 percentage point absolute increase, respectively). Conversely, incidence and mortality increased for colorectal cancer in men and lung cancer in women. The incidence and mortality burdens are both expected to increase in 2025. CONCLUSION: Overall, progress against cancer in the Azores has been mixed, and much of the progress has been driven by advances in treatment. Statistics for lung cancer in women and colorectal cancer in men are a call to action for policymakers. Reducing tobacco use and tackling the obesity epidemic are the two public health priorities for cancer control within the region.

The Effect of Advances in Lung-Cancer Treatment on Population Mortality.

BACKGROUND: Lung cancer is made up of distinct subtypes, including non-small-cell lung cancer (NSCLC) and small-cell lung cancer (SCLC). Although overall mortality from lung cancer has been declining in the United States, little is known about mortality trends according to cancer subtype at the population level because death certificates do not record subtype information. METHODS: Using data from Surveillance, Epidemiology, and End Results (SEER) areas, we assessed lung-cancer mortality and linked deaths from lung cancer to incident cases in SEER cancer registries. This allowed us to evaluate population-level mortality trends attributed to specific subtypes (incidence-based mortality). We also evaluated lung-cancer incidence and survival according to cancer subtype, sex, and calendar year. Joinpoint software was used to assess changes in incidence and trends in incidence-based mortality. RESULTS: Mortality from NSCLC decreased even faster than the incidence of this subtype, and this decrease was associated with a substantial improvement in survival over time that corresponded to the timing of approval of targeted therapy. Among men, incidence-based mortality from NSCLC decreased 6.3% annually from 2013 through 2016, whereas the incidence decreased 3.1% annually from 2008 through 2016. Corresponding lung cancer-specific survival improved from 26% among men with NSCLC that was diagnosed in 2001 to 35% among those in whom it was diagnosed in 2014. This improvement in survival was found across all races and ethnic groups. Similar patterns were found among women with NSCLC. In contrast, mortality from SCLC declined almost entirely as a result of declining incidence, with no improvement in survival. This result correlates with limited treatment advances for SCLC in the time frame we examined. CONCLUSIONS: Population-level mortality from NSCLC in the United States fell sharply from 2013 to 2016, and survival after diagnosis improved substantially. Our analysis suggests that a reduction in incidence along with treatment advances - particularly approvals for and use of targeted therapies - is likely to explain the reduction in mortality observed during this period.

Assessment of Oncology Practice Billing Claims for Supplementing Chemotherapy: A Pilot Study in the Georgia SEER Cancer Registry.

BACKGROUND: Chemotherapy information in the population-based cancer registries is underascertained and lacks detail. We conducted a pilot study in the Georgia SEER Cancer Registry (GCR) to investigate the feasibility of supplementing chemotherapy information using billing claims from six private oncology practices (OP). METHODS: To assess cancer patients' representativeness from OP, we compared individuals with invasive first primary cancers diagnosed during 2013-2015 in the GCR (cohort 1) with those who had at least one OP claim in the 12 months after diagnosis (cohort 2). To assess completeness of OP claims to capture chemotherapy (yes or no), we further restricted cohort 2 to patients ages 65 years and older enrolled in fee-for-service Medicare Part A and B from the diagnosis date through 12 months follow-up or to the date of death. With Medicare data serving as the gold standard, sensitivity, specificity, and kappa statistics for the receipt of chemotherapy per OP claims were calculated by demographic and clinical characteristics. RESULTS: Cancer patients seeking care in the OP included in our analysis were not representative of the underlying patient population in the GCR. The practices underrepresented minorities and uninsured while overrepresenting females, persons with high socioeconomic status, patients residing outside the metropolitan Atlanta area, and persons with advance staged disease. The ability of practice claims to identify chemotherapy receipt was moderate (76.1% sensitivity) but varied by demographic and clinical characteristics (76.1-83.0%). CONCLUSIONS: Given the limited ability of OP claims to identify chemotherapy receipt, we suggest analyzing these data for hypothesis generation, but inference should be limited to this patient cohort.

Estimates of Overall Survival in Patients With Cancer Receiving Different Treatment Regimens: Emulating Hypothetical Target Trials in the Surveillance, Epidemiology, and End Results (SEER)-Medicare Linked Database.

Importance: The Surveillance, Epidemiology, and End Results (SEER)-Medicare linked database may provide insights into the comparative effectiveness of oncological treatments for elderly individuals who are underrepresented in clinical trials. Objective: To evaluate the suitability of SEER-Medicare data for assessing the effectiveness of adding a drug to an existing treatment regimen on the overall survival of elderly patients with cancer. Design, Setting, and Participants: This comparative effectiveness study analyzed SEER-Medicare data from 9549 individuals who received a new diagnosis of stage II colorectal cancer (2008-2012) and 940 patients who received a new diagnosis of advanced pancreatic adenocarcinoma (2007-2012), with follow-up to December 31, 2013 (SEER-Medicare data released in 2015). Two (hypothetical) target trials were designed and emulated based on 2 existing randomized clinical trials: (1) adjuvant fluorouracil after curative surgery for individuals with stage II colorectal cancer and (2) erlotinib added to gemcitabine for individuals with advanced pancreatic adenocarcinoma. Data were analyzed January 2018 to March 2019. Exposures: The following treatment strategies were compared: (1) fluorouracil initiation vs no initiation within 3 months of tumor resection and (2) erlotinib initiation vs no initiation within 12 weeks of gemcitabine initiation. Main Outcomes and Measures: All-cause mortality within 60 months of baseline for the fluorouracil trial and within 72 weeks for the erlotinib trial. Results: Compared with 3293 individuals in the existing fluorouracil trial, 9549 eligible individuals included in the present analyses were more likely to have colon cancer (8565 [90%] vs 2291 [71%]) and were older (median [interquartile range], 79 [73-84] vs 63 [56-68] years). The 5-year risk difference for initiation vs noninitiation of fluorouracil after surgery was -3.8% (95% CI, -14.8% to 12.6%), and the mortality hazard ratio (HR) was 0.95 (95% CI, 0.85-1.04). Compared with 569 individuals in the existing erlotinib trial, 940 eligible patients included in the present analysis were older (median [range], 74 [66-93] vs 64 [36-92] years) and more likely to be male (547 [58%] vs 298 [52%]). The 1-year risk difference for initiation vs noninitiation of erlotinib was 4.7% (95% CI, -9.4% to 18.0%), and the corresponding mortality HR was 1.04 (95% CI, 0.86-1.42). In naive analyses, the mortality HR estimate was 1.14 (95% CI, 0.95-1.36) for the fluorouracil emulation and 0.68 (95% CI, 0.54-0.87) for the erlotinib emulation. Conclusions and Relevance: The present estimates were similar to those from randomized clinical trials that studied adding the same cancer drugs to existing regimens. The published HR was 1.02 (95% CI, 0.70-1.48) in the fluorouracil trial for individuals aged 70 or older and 0.96 (95% CI, 0.74-1.24) in the erlotinib trial for individuals aged 65 years or older. The SEER-Medicare database may be adequate for studying the real-world effectiveness of adding a drug to treatment regimens used for elderly individuals with cancer.

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

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. IMPACT: Different approaches for net survival estimation should be considered depending on cancer under study.

Genetic Testing and Results in a Population-Based Cohort of Breast Cancer Patients and Ovarian Cancer Patients.

PURPOSE: Genetic testing for cancer risk has expanded rapidly. We examined clinical genetic testing and results among population-based patients with breast and ovarian cancer. METHODS: The study included all women 20 years of age or older diagnosed with breast or ovarian cancer in California and Georgia between 2013 and 2014 and reported to the SEER registries covering the entire state populations. SEER data were linked to results from four laboratories that performed nearly all germline cancer genetic testing. Testing use and results were analyzed at the gene level. RESULTS: There were 77,085 patients with breast cancer and 6,001 with ovarian cancer. Nearly one quarter of those with breast cancer (24.1%) and one third of those with ovarian cancer (30.9%) had genetic test results. Among patients with ovarian cancer, testing was lower in blacks (21.6%; 95% CI, 18.1% to 25.4%; v whites, 33.8%; 95% CI, 32.3% to 35.3%) and uninsured patients (20.8%; 95% CI, 15.5% to 26.9%; v insured patients, 35.3%; 95% CI, 33.8% to 36.9%). Prevalent pathogenic variants in patients with breast cancer were BRCA1 (3.2%), BRCA2 (3.1%), CHEK 2 (1.6%), PALB2 (1.0%), ATM (0.7%), and NBN (0.4%); in patients with ovarian cancer, prevalent pathogenic variants were BRCA1 (8.7%), BRCA2 (5.8%), CHEK2 (1.4%), BRIP1 (0.9%), MSH2 (0.8%), and ATM (0.6%). Racial/ethnic differences in pathogenic variants included BRCA1 (ovarian cancer: whites, 7.2%; 95% CI, 5.9% to 8.8%; v Hispanics, 16.1%; 95% CI, 11.8% to 21.2%) and CHEK2 (breast cancer: whites, 2.3%; 95% CI, 1.8% to 2.8%; v blacks, 0.1%; 95% CI, 0% to 0.8%). When tested for all genes that current guidelines designate as associated with their cancer type, 7.8% of patients with breast cancer and 14.5% of patients with ovarian cancer had pathogenic variants. CONCLUSION: Clinically-tested patients with breast and ovarian cancer in two large, diverse states had 8% to 15% prevalence of actionable pathogenic variants. Substantial testing gaps and disparities among patients with ovarian cancer are targets for improvement.

Racial Disparities in the Receipt of Guideline Care and Cancer Deaths for Women with Ovarian Cancer.

BACKGROUND: Black women with ovarian cancer experience worse survival than white women. Receipt of guideline care improves survival, yet care may vary by race. We assessed rates of guideline care and role of guideline treatment on survival disparities. METHODS: This retrospective cohort analysis used the NCI's Patterns of Care data for women diagnosed with ovarian cancer, 2002 and 2011 (weighted n = 3,999), with follow-up through December 12, 2014. Logistic regression included patient characteristics, insurance, and gynecologic oncologist (GO) consultation to produce adjusted standardized percentages of women receiving guideline treatment by race. Cox proportional hazards analysis assessed risk of ovarian cancer death. RESULTS: Guideline care was significantly lower for black women compared with white women (adjusted 27.5% vs. 34.1%). Increased receipt of guideline care was associated with GO consultation, younger ages, stage, and insurance. Rates of GO consultation were comparable for black and white women, approximately 60%. Black women were more likely to receive no surgery or no chemotherapy if they did not consult a GO. The unadjusted death risk was significantly higher in black women (HR = 1.33). After adjusting for receipt of guideline care and other factors, black and white women had similar risk of death (HR = 1.05). CONCLUSIONS: Race was not associated with risk of death when guideline care was included in multivariate survival models. However, black patients received less guideline care. GO consultation significantly increased receipt of guideline care. IMPACT: Research is needed to understand treatment perspectives for black patients and their providers to increase the receipt of guideline care and reduce survival disparities.

Can We Use Survival Data from Cancer Registries to Learn about Disease Recurrence? The Case of Breast Cancer.

Background: Population-representative risks of metastatic recurrence are not generally available because cancer registries do not collect data on recurrence. This article presents a novel method that estimates the risk of recurrence using cancer registry disease-specific survival.Methods: The method is based on an illness-death process coupled with a mixture cure model for net cancer survival. The risk of recurrence is inferred from the estimated survival among the noncured fraction and published data on survival after recurrence. We apply the method to disease-specific survival curves from female breast cancer cases without a prior cancer diagnosis and with complete stage and hormone receptor (HR) status in Surveillance, Epidemiology and End Results registries (1992-2013).Results: The risk of recurrence is higher for women diagnosed with breast cancer at older age, earlier period, more advanced stage, and HR-negative tumors. For women diagnosed at ages 60-74 in 2000-2013, the projected percent recurring within 5 years is 2.5%, 9.6%, and 34.5% for stages I, II, and III HR-positive, and 6.5%, 20.2%, and 48.5% for stages I, II, and III HR-negative tumors. Although HR-positive cases have lower risk of recurrence soon after diagnosis, their risk persists longer than for HR-negative cases. Results show a high degree of robustness to model assumptions.Conclusions: The results show that it is possible to extract information about the risk of recurrence using disease-specific survival, and the methods can in principle be extended to other cancer sites.Impact: This study provides the first population-based summaries of the risk of breast cancer recurrence in U.S. women. Cancer Epidemiol Biomarkers Prev; 27(11); 1332-41. ©2018 AACR.

Erratum: Author Correction: Breast-cancer-specific mortality in patients treated based on the 21-gene assay: a SEER population-based study.

[This corrects the article DOI: 10.1038/npjbcancer.2016.17.].

Annual Report to the Nation on the Status of Cancer, part I: National cancer statistics.

BACKGROUND: The American Cancer Society (ACS), the Centers for Disease Control and Prevention (CDC), the National Cancer Institute (NCI), and the North American Association of Central Cancer Registries (NAACCR) collaborate to provide annual updates on cancer occurrence and trends in the United States. METHODS: Incidence data were obtained from the CDC-funded and NCI-funded population-based cancer registry programs and compiled by NAACCR. Data on cancer deaths were obtained from the National Center for Health Statistics National Vital Statistics System. Trends in age-standardized incidence and death rates for all cancers combined and for the leading cancer types by sex, race, and ethnicity were estimated by joinpoint analysis and expressed as the annual percent change. Stage distribution and 5-year survival by stage at diagnosis were calculated for breast cancer, colon and rectum (colorectal) cancer, lung and bronchus cancer, and melanoma of the skin. RESULTS: Overall cancer incidence rates from 2008 to 2014 decreased by 2.2% per year among men but were stable among women. Overall cancer death rates from 1999 to 2015 decreased by 1.8% per year among men and by 1.4% per year among women. Among men, incidence rates during the most recent 5-year period (2010-2014) decreased for 7 of the 17 most common cancer types, and death rates (2011-2015) decreased for 11 of the 18 most common types. Among women, incidence rates declined for 7 of the 18 most common cancers, and death rates declined for 14 of the 20 most common cancers. Death rates decreased for cancer sites, including lung and bronchus (men and women), colorectal (men and women), female breast, and prostate. Death rates increased for cancers of the liver (men and women); pancreas (men and women); brain and other nervous system (men and women); oral cavity and pharynx (men only); soft tissue, including heart (men only); nonmelanoma skin (men only); and uterus. Incidence and death rates were higher among men than among women for all racial and ethnic groups. For all cancer sites combined, black men and white women had the highest incidence rates compared with other racial groups, and black men and black women had the highest death rates compared with other racial groups. Non-Hispanic men and women had higher incidence and mortality rates than those of Hispanic ethnicity. Five-year survival for cases diagnosed from 2007 through 2013 ranged from 100% (stage I) to 26.5% (stage IV) for female breast cancer, from 88.1% (stage I) to 12.6% (stage IV) for colorectal cancer, from 55.1% (stage I) to 4.2% (stage IV) for lung and bronchus cancer, and from 99.5% (stage I) to 16% (stage IV) for melanoma of the skin. Among children, overall cancer incidence rates increased by 0.8% per year from 2010 to 2014, and overall cancer death rates decreased by 1.5% per year from 2011 to 2015. CONCLUSIONS: For all cancer sites combined, cancer incidence rates decreased among men but were stable among women. Overall, there continue to be significant declines in cancer death rates among both men and women. Differences in rates and trends by race and ethnic group remain. Progress in reducing cancer mortality has not occurred for all sites. Examining stage distribution and 5-year survival by stage highlights the potential benefits associated with early detection and treatment. Cancer 2018;124:2785-2800. © 2018 American Cancer Society.

Differences in Breast Cancer Survival by Molecular Subtypes in the United States.

Background: Although incidence rates of breast cancer molecular subtypes are well documented, effects of molecular subtypes on breast cancer-specific survival using the largest population coverage to date are unknown in the U.S. POPULATION: Methods: Using Surveillance, Epidemiology and End Results cancer registry data, we assessed survival after breast cancer diagnosis among women diagnosed during 2010 to 2013 and followed through December 31, 2014. Breast cancer molecular subtypes defined by joint hormone receptor [HR, estrogen receptor (ER) and/or progesterone receptor (PR)] and HER2 status were assessed. Multiple imputation was used to fill in missing receptor status. Four-year breast cancer-specific survival per molecular subtypes and clinical/demographic factors were calculated. A Cox proportional hazards model was used to evaluate survival while controlling for clinical and demographic factors.Results: The best survival pattern was observed among women with HR+/HER2- subtype (survival rate of 92.5% at 4 years), followed by HR+/HER2+ (90.3%), HR-/HER2+ (82.7%), and finally worst survival for triple-negative subtype (77.0%). Notably, failing to impute cases with missing receptor status leads to overestimation of survival because those with missing receptor status tend to have worse prognostic features. Survival differed substantially by stage at diagnosis. Among de novo stage IV disease, women with HR+/HER2+ subtype experienced better survival than those with HR+/HER2- subtype (45.5% vs. 35.9%), even after controlling for other factors.Conclusions: Divergence of survival curves in stage IV HR+/HER2+ versus HR+/HER2- subtype is likely attributable to major advances in HER2-targeted treatment.Impact: Contrary to conventional thought, HR+/HER2+ subtype experienced better survival than HR+/HER2- in advanced-stage disease. Cancer Epidemiol Biomarkers Prev; 27(6); 619-26. ©2018 AACR.

Cancer-specific mortality, cure fraction, and noncancer causes of death among diffuse large B-cell lymphoma patients in the immunochemotherapy era.

BACKGROUND: Survival after the diagnosis of diffuse large B-cell lymphoma (DLBCL) has been increasing since 2002 because of improved therapies; however, long-term outcomes for these patients in the modern treatment era are still unknown. METHODS: Using Surveillance, Epidemiology, and End Results data, this study first assessed factors associated with DLBCL-specific mortality during 2002-2012. An epidemiologic risk profile, based on clinical and demographic characteristics, was used to stratify DLBCL cases into low-, medium-, and high-risk groups. The proportions of DLBCL cases that might be considered cured in these 3 risk groups was estimated. Risks of death due to various noncancer causes among DLBCL cases versus the general population were also calculated with standardized mortality ratios (SMRs). RESULTS: Overall, 8274 deaths were recorded among 18,047 DLBCL cases; 76% of the total deaths were attributed to DLBCL, and 24% were attributed to noncancer causes. The 10-year survival rates for the low-, medium-, and high-risk groups were 80%, 60%, and 36%, respectively. The estimated cure proportions for the low-, medium-, and high-risk groups were 73%, 49%, and 27%, respectively; however, these cure estimates were uncertain because of the need to extrapolate the survival curves beyond the follow-up time. Mortality risks calculated with SMRs were elevated for conditions including vascular diseases (SMR, 1.3), infections (SMR, 3.1), gastrointestinal diseases (SMR, 2.5), and blood diseases (SMR, 4.6). These mortality risks were especially high within the initial 5 years after the diagnosis and declined after 5 years. CONCLUSIONS: Some DLBCL patients may be cured of their cancer, but they continue to experience excess mortality from lymphoma and other noncancer causes. Cancer 2017;123:3326-34. © 2017 American Cancer Society.

Cancer Incidence and Survival Trends by Subtype Using Data from the Surveillance Epidemiology and End Results Program, 1992-2013.

Background: Cancers are heterogeneous, comprising distinct tumor subtypes. Therefore, presenting the burden of cancer in the population and trends over time by these tumor subtypes is important to identify patterns and differences in the occurrence of these subtypes, especially to generalize findings to the U.S. general population.Methods: Using SEER Cancer Registry Data, we present incidence rates according to subtypes for diagnosis years (1992-2013) among men and women for five major cancer sites: breast (female only), esophagus, kidney and renal pelvis, lung and bronchus, and thyroid. We also describe estimates of 5-year relative survival according to subtypes and diagnosis year (1992-2008). We used Joinpoint models to identify years when incidence rate trends changed slope. Finally, recent 5-year age-adjusted incidence rates (2009-2013) are presented for each subtype by race and age.Results: Hormone receptor-positive and HER2-negative was the most common subtype (about 74%) of breast cancers. Adenocarcinoma made up about 69% of esophagus cases among men. Adenocarcinoma also is the most common lung subtype (43% in men and 52% in women). Ninety percent of thyroid subtypes were papillary. Distinct incidence and survival patterns emerged by these subtypes over time among men and women.Conclusions: Histologic or molecular subtype revealed different incidence and/or survival trends that are masked when cancer is considered as a single disease on the basis of anatomic site.Impact: Presenting incidence and survival trends by subtype, whenever possible, is critical to provide more detailed and meaningful data to patients, providers, and the public. Cancer Epidemiol Biomarkers Prev; 26(4); 632-41. ©2016 AACR.

Imputing estrogen receptor (ER) status in a population-based cancer registry: a sensitivity analysis.

Breast cancers are clinically heterogeneous based on tumor markers. The National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) Program provides baseline data on these tumor markers for reporting cancer burden and trends over time in the US general population. These tumor markers, however, are often prone to missing observations. In particular, estrogen receptor (ER) status, a key biomarker in the study of breast cancer, has been collected since 1992 but historically was not well-reported, with missingness rates as high as 25% in early years. Previous methods used to correct estimates of breast cancer incidence or ER-related odds or prevalence ratios for unknown ER status have relied on a missing-at-random (MAR) assumption. In this paper, we explore the sensitivity of these key estimates to departures from MAR. We develop a predictive mean matching procedure that can be used to multiply impute missing ER status under either an MAR or a missing not at random assumption and apply it to the SEER breast cancer data (1992-2012). The imputation procedure uses the predictive power of the rich set of covariates available in the SEER registry while also allowing us to investigate the impact of departures from MAR. We find some differences in inference under the two assumptions, although the magnitude of differences tends to be small. For the types of analyses typically of primary interest, we recommend imputing SEER breast cancer biomarkers under an MAR assumption, given the small apparent differences under MAR and missing not at random assumptions. Copyright © 2016 John Wiley & Sons, Ltd.

Contributions of HIV to Non-Hodgkin Lymphoma Mortality Trends in the United States.

BACKGROUND: The human immunodeficiency virus (HIV) epidemic has strongly influenced non-Hodgkin lymphoma (NHL) incidence in the U.S. general population, but its effects on NHL mortality trends are unknown. METHODS: Using SEER cancer registry data, we assessed NHL mortality rates in the United States (2005-2012) and mapped NHL deaths to prior incident cases. Data included HIV status at NHL diagnosis. We describe the proportion of NHL deaths linked to an HIV-infected case, for 3 AIDS-defining subtypes [diffuse large B-cell lymphoma (DLBCL), Burkitt lymphoma, and central nervous system (CNS) lymphoma] and within demographic categories. We also present incidence-based mortality (IBM) rates showing the impact of HIV on mortality trends and describe survival after NHL diagnosis by calendar year. RESULTS: Of 11,071 NHL deaths, 517 (4.6%) were in HIV-infected persons. This proportion was higher in deaths mapped to DLBCL (7.3% with HIV), Burkitt lymphoma (33.3%), and CNS lymphoma (17.6%), and among deaths from these subtypes, for people aged 20-49 years (46.6%), males (15.2%), and blacks (39.3%). IBM rates declined steeply during 2005-2012 for HIV-infected NHL cases (-7.6% per year, P = 0.001). This trend reflects a steep decline in incident NHL among HIV-infected people after 1996, when highly active antiretroviral therapy was introduced. Five-year cancer-specific survival improved more markedly among HIV-infected cases (9%-54%) than HIV-uninfected cases (62%-76%) during 1990-2008. CONCLUSIONS: The HIV epidemic has strongly contributed to NHL deaths, especially for AIDS-defining NHL subtypes and groups with high HIV prevalence. IMPACT: Declining NHL mortality rates for HIV-infected cases reflect both declining incidence and improving survival. Cancer Epidemiol Biomarkers Prev; 25(9); 1289-96. ©2016 AACR.