Association of Major Adverse Financial Events and Later-Stage Cancer Diagnosis in the United States.

PURPOSE: This study assessed the prevalence of specific major adverse financial events (AFEs)-bankruptcies, liens, and evictions-before a cancer diagnosis and their association with later-stage cancer at diagnosis. METHODS: Patients age 20-69 years diagnosed with cancer during 2014-2015 were identified from the Seattle, Louisiana, and Georgia SEER population-based cancer registries. Registry data were linked with LexisNexis consumer data to identify patients with a history of court-documented AFEs before cancer diagnosis. The association of AFEs and later-stage cancer diagnoses (stages III/IV) was assessed using separate sex-specific multivariable logistic regression. RESULTS: Among 101,649 patients with cancer linked to LexisNexis data, 36,791 (36.2%) had a major AFE reported before diagnosis. The mean and median timing of the AFE closest to diagnosis were 93 and 77 months, respectively. AFEs were most common among non-Hispanic Black, unmarried, and low-income patients. Individuals with previous AFEs were more likely to be diagnosed with later-stage cancer than individuals with no AFE (males-odds ratio [OR], 1.09 [95% CI, 1.03 to 1.14]; P < .001; females-OR, 1.18 [95% CI, 1.13 to 1.24]; P < .0001) after adjusting for age, race, marital status, income, registry, and cancer type. Associations between AFEs prediagnosis and later-stage disease did not vary by AFE timing. CONCLUSION: One third of newly diagnosed patients with cancer had a major AFE before their diagnosis. Patients with AFEs were more likely to have later-stage diagnosis, even accounting for traditional measures of socioeconomic status that influence the stage at diagnosis. The prevalence of prediagnosis AFEs underscores financial vulnerability of patients with cancer before their diagnosis, before any subsequent financial burden associated with cancer treatment.

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.

Use of pembrolizumab among older adults with cancer in the United States, before and after FDA approval of its tumor-agnostic indication.

INTRODUCTION: Pembrolizumab, an anticancer immunotherapy agent, has received multiple approvals since its first approval by the U.S. Food and Drug Administration (FDA) in 2014. Limited data exist on its real-world use and shifts post tumor-agnostic approval in 2017 for the treatment of patients with any microsatellite instability-high/mismatch repair deficient (MSI-H/dMMR) solid tumors. This study analyzes pembrolizumab's pre and post-tumor-agnostic approval use among older U.S. adults, revealing its evolving role in oncology practice. METHODS: Using the Surveillance, Epidemiology and End Results (SEER)-Medicare data (2014-2019), we examined the cancer sites of pembrolizumab recipients before and after tumor-agnostic approval. Cancer sites were classified based on the timing of site-specific approvals (before/after tumor-agnostic approval) or no site-specific approval, and inclusion in MSI-H/dMMR clinical trials. RESULTS: The total number of pembrolizumab recipients increased from 4221 in the pre-agnostic period to 20 479 in the post-agnostic period. Pembrolizumab was used for a broad range of cancer types, including cancers that had no FDA-approved site-specific indications at the time of use (25.8% in pre- and 24.6% in post-agnostic periods). The proportion of pembrolizumab recipients receiving pembrolizumab for cancers with site-specific approvals before tumor-agnostic approval decreased from 77.3% to 70.8%. The proportion of pembrolizumab recipients receiving pembrolizumab for cancers that gained site-specific approvals following tumor-agnostic approval almost doubled (6.8% to 13.0%). The proportion of pembrolizumab recipients with cancers included in MSI-H/dMMR trials also doubled (12.3% to 25.5%) following tumor-agnostic approval. CONCLUSIONS: Pembrolizumab use has expanded over time among older adults with cancer, extending beyond those with FDA-approved site-specific indications.

Evaluation of the Completeness of Managed Care Data to Identify Cancer Diagnoses and Treatments for Patients in the SEER-Medicare Data.

BACKGROUND: The utility of codes on Medicare Advantage (MA) data to capture cancer diagnoses and treatment for cancer patients is unknown. OBJECTIVE: This study compared cancer diagnoses and treatments on MA encounter data (MA data) with the Surveillance, Epidemiology, and End-Results (SEER) data. SUBJECTS: Subjects were patients enrolled in either MA or Medicare fee-for-service (MFFS) when diagnosed with incident breast, colorectal, prostate, or lung cancer, 2015-2017, in a SEER cancer registry. MEASURES: MA data, from 2 months before to 12 months following SEER diagnosis, were reviewed to identify cancer diagnoses, surgery, chemotherapy, and radiotherapy (RT). MA data were compared with SEER to determine their sensitivity to capture cancer diagnoses and sensitivity/specificity to identify surgeries. The agreement between SEER and Medicare data regarding receipt of chemotherapy and RT was measured by Kappa statistics. A similar comparison to SEER diagnoses/treatments was made using MFFS claims to provide context for the SEER-MA comparison. RESULTS: The study included 186,449 patients, 38% in MA. MA data had 92%+ sensitivity to identify SEER cancer diagnosis and 90%+ sensitivity for cancer surgery. Specificity for surgery was >84%, except for breast cancer (52%). Kappa statistics for agreement between SEER and MA data regarding chemotherapy varied by cancer, 0.61-0.82, and for receipt of RT exceeded 0.75 for all cancers. Results observed for MFFS claims were similar to those in MA data. CONCLUSION: For 4 common cancers, MA data included most cancer diagnoses and general types of cancer treatment reported in the SEER data. More research is needed to assess additional cancers and detailed treatments.

Prediction of Risk of Metastatic Recurrence for Female Breast Cancer Patients in the Presence of Competing Causes of Death.

BACKGROUND: To estimate risk of recurrence for women diagnosed with nonmetastatic breast cancer considering the risks of other causes mortality. METHODS: We extend a method based on the diagnosis-metastasis-death pathway to include risks of other causes mortality. We estimate three probabilities as cumulative incidence of: (i) being alive and recurrence-free, (ii) death for other causes before a recurrence, and (iii) recurrence. We apply the method to female breast cancer relative survival from the Surveillance, Epidemiology, and End Results Program registries (2000-2018) data. RESULTS: The cumulative incidence of recurrence shows a higher increase with more advanced cancer stage and is less influenced by age at diagnosis. At 5 years from diagnosis, the cumulative incidence of recurrence is less than 3% for those diagnosed with stage I, 10% to 13% for those diagnosed with stage II, and 37% to 47% for those diagnosed with stage III breast cancer. The estimates of recurrence considering versus ignoring the risks of dying from other causes were generally consistent, except for older women with more advanced stage, and longer time since diagnosis. In these groups, the net probability of recurrence, excluding the risks of dying from other causes, were overestimated. CONCLUSIONS: For patients with cancer who are older or long-term survivors, it is important to include the risks of other cause mortality as the crude cumulative incidence of recurrence is a more appropriate measure. IMPACT: These estimates are important in clinical decision making, as higher competing mortality may preclude the benefits of aggressive treatments.

Long-term Cancer Survival Trends by Updated Summary Stage.

BACKGROUND: Stage is the most important prognostic factor for understanding cancer survival trends. Summary stage (SS) classifies cancer based on the extent of spread: In situ, Localized, Regional, or Distant. Continual updating of staging systems poses challenges to stage comparisons over time. We use a consistent summary stage classification and present survival trends for 25 cancer sites using the joinpoint survival (JPSurv) model. METHODS: We developed a modified summary stage variable, Long-Term Site-Specific Summary Stage, based on as consistent a definition as possible and applied it to a maximum number of diagnosis years, 1975-2019. We estimated trends by stage by applying JPSurv to relative survival data for 25 cancer sites in SEER-8, 1975-2018, followed through December 31, 2019. To help interpret survival trends, we report incidence and mortality trends using the joinpoint model. RESULTS: Five-year relative survival improved for nearly all sites and stages. Large improvements were observed for localized pancreatic cancer [4.25 percentage points annually, 2007-2012 (95% confidence interval, 3.40-5.10)], distant skin melanoma [2.15 percentage points annually, 2008-2018 (1.73-2.57)], and localized esophagus cancer [1.18 percentage points annually, 1975-2018 (1.11-1.26)]. CONCLUSIONS: This is the first analysis of survival trends by summary stage for multiple cancer sites. The largest survival increases were seen for cancers with a traditionally poor prognosis and no organized screening, which likely reflects clinical management advances. IMPACT: Our study will be particularly useful for understanding the population-level impact of new treatments and identifying emerging trends in health disparities research.

Breast and colorectal cancer recurrence-free survival estimates in the US: Modeling versus active data collection.

BACKGROUND: A modeling method was developed to estimate recurrence-free survival using cancer registry survival data. This study aims to validate the modeled recurrence-free survival against "gold-standard" estimates from data collected by the National Program of Cancer Registries (NPCR) Patient-Centered Outcomes Research (PCOR) project. METHODS: We compared 5-year metastatic recurrence-free survival using modeling and empirical estimates from the PCOR project that collected disease-free status, tumor progression and recurrence for colorectal and female breast cancer cases diagnosed in 2011 in 5 U.S. state registries. To estimate empirical recurrence-free survival, we developed an algorithm that combined disease-free, recurrence, progression, and date information from NPCR-PCOR data. We applied the modeling method to relative survival for patients diagnosed with female breast and colorectal cancer in 2000-2015 in the SEER-18 areas. RESULTS: When grouping patients with stages I-III, the 5-year metastatic recurrence-free modeled and NPCR-PCOR estimates are very similar being respectively, 90.2 % and 88.6 % for female breast cancer, 74.6 % and 75.3 % for colon cancer, and 68.8 % and 68.5 % for rectum cancer. In general, the 5-year recurrence-free NPCR-PCOR and modeled estimates are still similar when controlling by stage. The modeled estimates, however, are not as accurate for recurrence-free survival in years 1-3 from diagnosis. CONCLUSIONS: The alignment between NPCR-PCOR and modeled estimates supports their validity and provides robust population-based estimates of 5-year metastatic recurrence-free survival for female breast, colon, and rectum cancers. The modeling approach can in principle be extended to other cancer sites to provide provisional population-based estimates of 5-year recurrence free survival.

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.

Estimating the Number of Men Living with Metastatic Prostate Cancer in the United States.

BACKGROUND: Metastatic prostate cancer (MPC) includes metastases detected at diagnosis (de novo) and those occurring after diagnosis with early-stage disease (recurrent). Cancer registries collect data only on de novo MPC, providing a partial picture of the burden of MPC. We use cancer registry data to estimate the number of men living with MPC in the United States including both de novo and recurrent cases. METHODS: We apply a back-calculation method to estimate MPC incidence and prevalence from U.S. prostate cancer mortality and de novo MPC relative survival for cases diagnosed between 2000 and 2017 in 18 Surveillance, Epidemiology, and End Results registries. We hold overall prostate cancer mortality and MPC survival constant for future prevalence projections. RESULTS: On January 1, 2018, we estimated 120,400 U.S. men living with MPC (45% de novo, 55% recurrent). The age-adjusted prevalence in 2018 for Black men was over double that of White men (137.1 vs. 62.2 per 100,000 men). By 2030, 192,500 men are expected to be living with MPC, with the increase being driven by population growth projections. CONCLUSIONS: The number of men living with MPC in the United States exceeds 100,000 and represents a small fraction of the >3 million men living with a prior diagnosis of prostate cancer. IMPACT: Relatively similar fractions of de novo and recurrent MPC among prevalent cases highlight opportunities for management of localized disease in reducing the MPC burden. Changes in diagnostic technologies could lead to greater growth in MPC cases in the United States than projected. See related commentary by Stopsack et al., p. 585.

Cancer treatment and survivorship statistics, 2022.

The number of cancer survivors continues to increase in the United States due to the growth and aging of the population as well as advances in early detection and treatment. To assist the public health community in better serving these individuals, the American Cancer Society and the National Cancer Institute collaborate triennially to estimate cancer prevalence in the United States using incidence and survival data from the Surveillance, Epidemiology, and End Results cancer registries, vital statistics from the Centers for Disease Control and Prevention's National Center for Health Statistics, and population projections from the US Census Bureau. Current treatment patterns based on information in the National Cancer Database are presented for the most prevalent cancer types by race, and cancer-related and treatment-related side-effects are also briefly described. More than 18 million Americans (8.3 million males and 9.7 million females) with a history of cancer were alive on January 1, 2022. The 3 most prevalent cancers are prostate (3,523,230), melanoma of the skin (760,640), and colon and rectum (726,450) among males and breast (4,055,770), uterine corpus (891,560), and thyroid (823,800) among females. More than one-half (53%) of survivors were diagnosed within the past 10 years, and two-thirds (67%) were aged 65 years or older. One of the largest racial disparities in treatment is for rectal cancer, for which 41% of Black patients with stage I disease receive proctectomy or proctocolectomy compared to 66% of White patients. Surgical receipt is also substantially lower among Black patients with non-small cell lung cancer, 49% for stages I-II and 16% for stage III versus 55% and 22% for White patients, respectively. These treatment disparities are exacerbated by the fact that Black patients continue to be less likely to be diagnosed with stage I disease than White patients for most cancers, with some of the largest disparities for female breast (53% vs 68%) and endometrial (59% vs 73%). Although there are a growing number of tools that can assist patients, caregivers, and clinicians in navigating the various phases of cancer survivorship, further evidence-based strategies and equitable access to available resources are needed to mitigate disparities for communities of color and optimize care for people with a history of cancer. CA Cancer J Clin. 2022;72:409-436.

Workforce Caring for Cancer Survivors in the United States: Estimates and Projections of Use.

BACKGROUND: This study aims to quantify the extent and diversity of the cancer care workforce, beyond medical oncologists, to inform future demand because the number of cancer survivors is expected to grow in the United States. METHODS: Surveillance, Epidemiology, and End Results-Medicare data were used to evaluate health-care use of cancer survivors diagnosed between 2000 and 2014, enrolled in fee-for-service Medicare Parts A and B, and 65 years or older in 2008-2015. We calculated percentage of cancer survivors who saw each clinician specialty and their average annual number of visits in each phase of care. We projected the national number of individuals receiving care and number of annual visits by clinician specialty and phase of care through 2040. RESULTS: Cancer survivors had higher care use in the first year after diagnosis and last year of life phases. During the initial year after cancer diagnosis, most survivors were seen for cancer-related care by a medical oncologist (59.1%), primary care provider (55.9%), and/or other cancer-treating physicians (42.2%). The percentage of survivors with cancer-related visits to each specialty declined after the first year after diagnosis, plateauing after year 6-7. However, at 10 or more years after diagnosis, approximately 20% of cancer survivors had visits to medical oncologists and an average of 4 visits a year. CONCLUSIONS: Cancer survivors had higher care use in the first year after diagnosis and last year of life. High levels of care use across specialties in all phases of care have important implications for models of survivorship care coordination and workforce planning.

Estimating life expectancy adjusted by self-rated health status in the United States: national health interview survey linked to the mortality.

BACKGROUND: Life expectancy is increasingly incorporated in evidence-based screening and treatment guidelines to facilitate patient-centered clinical decision-making. However, life expectancy estimates from standard life tables do not account for health status, an important prognostic factor for premature death. This study aims to address this research gap and develop life tables incorporating the health status of adults in the United States. METHODS: Data from the National Health Interview Survey (1986-2004) linked to mortality follow-up through to 2006 (age ≥ 40, n = 729,531) were used to develop life tables. The impact of self-rated health (excellent, very good, good, fair, poor) on survival was quantified in 5-year age groups, incorporating complex survey design and weights. Life expectancies were estimated by extrapolating the modeled survival probabilities. RESULTS: Life expectancies incorporating health status differed substantially from standard US life tables and by health status. Poor self-rated health more significantly affected the survival of younger compared to older individuals, resulting in substantial decreases in life expectancy. At age 40 years, hazards of dying for white men who reported poor vs. excellent health was 8.5 (95% CI: 7.0,10.3) times greater, resulting in a 23-year difference in life expectancy (poor vs. excellent: 22 vs. 45), while at age 80 years, the hazards ratio was 2.4 (95% CI: 2.1, 2.8) and life expectancy difference was 5 years (5 vs. 10). Relative to the US general population, life expectancies of adults (age < 65) with poor health were approximately 5-15 years shorter. CONCLUSIONS: Considerable shortage in life expectancy due to poor self-rated health existed. The life table developed can be helpful by including a patient perspective on their health and be used in conjunction with other predictive models in clinical decision making, particularly for younger adults in poor health, for whom life tables including comorbid conditions are limited.

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.

The Utility of Pathology Reports to Identify Persons With Cancer Recurrence.

BACKGROUND: Cancer recurrence is an important measure of the impact of cancer treatment. However, no population-based data on recurrence are available. Pathology reports could potentially identify cancer recurrences. Their utility to capture recurrences is unknown. OBJECTIVE: This analysis assesses the sensitivity of pathology reports to identify patients with cancer recurrence and the stage at recurrence. SUBJECTS: The study includes patients with recurrent breast (n=214) or colorectal (n=203) cancers. RESEARCH DESIGN: This retrospective analysis included patients from a population-based cancer registry who were part of the Patient-Centered Outcomes Research (PCOR) Study, a project that followed cancer patients in-depth for 5 years after diagnosis to identify recurrences. MEASURES: Information abstracted from pathology reports for patients with recurrence was compared with their PCOR data (gold standard) to determine what percent had a pathology report at the time of recurrence, the sensitivity of text in the report to identify recurrence, and if the stage at recurrence could be determined from the pathology report. RESULTS: One half of cancer patients had a pathology report near the time of recurrence. For patients with a pathology report, the report's sensitivity to identify recurrence was 98.1% for breast cancer cases and 95.7% for colorectal cancer cases. The specific stage at recurrence from the pathology report had a moderate agreement with gold-standard data. CONCLUSIONS: Pathology reports alone cannot measure population-based recurrence of solid cancers but can identify specific cohorts of recurrent cancer patients. As electronic submission of pathology reports increases, these reports may identify specific recurrent patients in near real-time.

Population-Based Cancer Survival in Canada and the United States by Socioeconomic Status: Findings from the CONCORD-2 Study.

Background: Population-based cancer survival provides insight into the effectiveness of health systems to care for all residents with cancer, including those in marginalized groups. Methods: Using CONCORD-2 data, we estimated 5-year net survival among patients diagnosed 2004-2009 with one of 10 common cancers, and children diagnosed with acute lymphoblastic leukemia (ALL), by socioeconomic status (SES) quintile, age (0-14, 15-64, ≥65 years), and country (Canada or United States). Results: In the lowest SES quintile, survival was higher among younger Canadian adults diagnosed with liver (23% vs 15%) and cervical (78% vs 68%) cancers and with leukemia (62% vs 56%), including children diagnosed with ALL (92% vs 86%); and higher among older Americans diagnosed with colon (62% vs 56%), female breast (87% vs 80%), and prostate (97% vs 85%) cancers. In the highest SES quintile, survival was higher among younger Americans diagnosed with stomach cancer (33% vs 27%) and younger Canadians diagnosed with liver cancer (31% vs 23%); and higher among older Americans diagnosed with stomach (27% vs 22%) and prostate (99% vs 92%) cancers. Conclusions: Among younger Canadian cancer patients in the lowest SES group, greater access to health care may have resulted in higher cancer survival, while higher screening prevalence and access to health insurance (Medicare) among older Americans during the period of this study may have resulted in higher survival for some screen-detected cancers. Higher survival in the highest SES group for stomach and liver may relate to treatment differences. Survival differences by age and SES between Canada and the United States may help inform cancer control strategies.

Determining Fitness for Use of SEER Cause-Specific Cause of Death in Analyses of Cause-Specific Survival.

Background: Net and crude cancer survival statistics can be calculated using cause of death or expected survival from life tables. In some instances, using cause of death information may be advantageous. The Surveillance, Epidemiology, and End Results (SEER) Program cause-specific cause of death variable (North American Association of Central Cancer Registries [NAACCR] item #1914) designates that a patient died of their cancer. We evaluated how miss-ingness in NAACCR item #1914 impacted survival estimates to determine fitness for use in NAACCR Cancer in North America (CiNA) products. Methods: We used CiNA survival and prevalence data (November 2020 submission) to calculate 60-month cause-specific survival among persons aged 15-99 years at time of diagnosis using NAACCR item #1914. We treated missing/unknown causes of death in 3 ways: excluded from analysis, included as dead from this cancer, or included as censored at time of last follow-up. Autopsy/death-certificate-only cases were excluded from survival analyses. We calculated the proportion of deaths with unknown/missing cause of death by registry and demographic variables. Results: Generally, 60-month cause-specific survival estimates differed by <1% between the 3 approaches when NAACCR item #1914 was missing/unknown for <3% of deaths. When applying a <3% fit-for-use standard to SEER cause-specific cause of death, data from 34 registries were included in cause-specific survival analyses. The proportion of deaths with missing/unknown cause of death varied by primary site, age at diagnosis, race/ethnicity, year of diagnosis, and registry. Conclusion: We have identified missingness cut points for NAACCR item #1914, which strike a balance between scientific integrity and registry inclusiveness, to designate data in NAACCR CiNA data products as fit for use in cause-specific survival analyses.

Characterizing Trends in Cancer Patients' Survival Using the JPSurv Software.

BACKGROUND: Improvements in cancer survival are usually assessed by comparing survival in grouped years of diagnosis. To enhance analyses of survival trends, we present the joinpoint survival model webtool (JPSurv) that analyzes survival data by single year of diagnosis and estimates changes in survival trends and year-over-year trend measures. METHODS: We apply JPSurv to relative survival data for individuals diagnosed with female breast cancer, melanoma cancer, non-Hodgkin lymphoma (NHL), and chronic myeloid leukemia (CML) between 1975 and 2015 in the Surveillance, Epidemiology, and End Results Program. We estimate the number and location of joinpoints and the trend measures and provide interpretation. RESULTS: In general, relative survival has substantially improved at least since the mid-1990s for all cancer sites. The largest improvements in 5-year relative survival were observed for distant-stage melanoma after 2009, which increased by almost 3 survival percentage points for each subsequent year of diagnosis, followed by CML in 1995-2010, and NHL in 1995-2003. The modeling also showed that for patients diagnosed with CML after 1995 (compared with before), there was a greater decrease in the probability of dying of the disease in the 4th and 5th years after diagnosis compared with the initial years since diagnosis. CONCLUSIONS: The greatest increases in trends for distant melanoma, NHL, and CML coincided with the introduction of novel treatments, demonstrating the value of JPSurv for estimating and interpreting cancer survival trends. IMPACT: The JPSurv webtool provides a suite of estimates for analyzing trends in cancer survival that complement traditional descriptive survival analyses.

Survival outcomes for cancer types with the highest death rates for adolescents and young adults, 1975-2016.

BACKGROUND: Five-year relative survival for adolescent and young adult (AYA) patients with cancer diagnosed at the ages of 15 to 39 years is 85%. Survival rates vary considerably according to the cancer type. The purpose of this study was to analyze long-term survival trends for cancer types with the highest mortality among AYAs to determine where the greatest burden is and to identify areas for future research. METHODS: Using data from the Surveillance, Epidemiology, and End Results cancer registry and the National Center for Health Statistics, the authors examined the incidence, mortality, and survival for the 9 cancer types with the highest mortality rates in this age group from 1975 to 2016. JPSurv, new survival trend software, was used in the analysis. RESULTS: Results suggested significant improvements in 5-year relative survival for brain and other nervous system tumors, colon and rectum cancer, lung and bronchus cancer, acute myeloid leukemia, and non-Hodgkin lymphoma (all P values < .05). Limited or no improvement in survival was found for female breast cancer, cervical cancer, ovarian cancer, and bone and joint sarcomas. CONCLUSIONS: Five-year relative survival for multiple cancer types in AYAs has improved, but some common cancer types in this group still show limited survival improvements (eg, ovarian cancer). Survival improvements in colorectal cancer have been overshadowed by its rising incidence, which suggests a substantial disease burden. Future research should focus on female breast, bone, ovarian, and cervical cancers, which have seen minimal or no improvements in survival. LAY SUMMARY: Survival trends for adolescents and young adults with cancer are presented from a 40-year period. Although survival progress is noted for brain cancer, lung cancer, acute myeloid leukemia, and colon and rectum cancer, the incidence of colon and rectum cancer remains high. Minimal progress is evident for female breast, bone, ovarian, and cervical cancers, which are in need of renewed focus.

Machine Learning Methods to Identify Missed Cases of Bladder Cancer in Population-Based Registries.

PURPOSE: Population-based cancer incidence rates of bladder cancer may be underestimated. Accurate estimates are needed for understanding the burden of bladder cancer in the United States. We developed and evaluated the feasibility of a machine learning-based classifier to identify bladder cancer cases missed by cancer registries, and estimated the rate of bladder cancer cases potentially missed. METHODS: Data were from population-based cohort of 37,940 bladder cancer cases 65 years of age and older in the SEER cancer registries linked with Medicare claims (2007-2013). Cases with other urologic cancers, abdominal cancers, and unrelated cancers were included as control groups. A cohort of cancer-free controls was also selected using the Medicare 5% random sample. We used five supervised machine learning methods: classification and regression trees, random forest, logic regression, support vector machines, and logistic regression, for predicting bladder cancer. RESULTS: Registry linkages yielded 37,940 bladder cancer cases and 766,303 cancer-free controls. Using health insurance claims, classification and regression trees distinguished bladder cancer cases from noncancer controls with very high accuracy (95%). Bacille Calmette-Guerin, cystectomy, and mitomycin were the most important predictors for identifying bladder cancer. From 2007 to 2013, we estimated that up to 3,300 bladder cancer cases in the United States may have been missed by the SEER registries. This would result in an average of 3.5% increase in the reported incidence rate. CONCLUSION: SEER cancer registries may potentially miss bladder cancer cases during routine reporting. These missed cases can be identified leveraging Medicare claims and data analytics, leading to more accurate estimates of bladder cancer incidence.