SEER Limited-Use cancer incidence data with associated population data. Geographic areas available are county and SEER registry. The Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute collects and distributes high quality, comprehensive cancer data from a number of population-based cancer registries. Data include patient demographics, primary tumor site, morphology, stage at diagnosis, first course of treatment, and follow-up for vital status. The SEER Program is the only comprehensive source of population-based information in the United States that includes stage of cancer at the time of diagnosis and survival rates within each stage.

Users can access data about cancer statistics in the United States including but not limited to searches by type of cancer and race, sex, ethnicity, age at diagnosis, and age at death. Background Surveillance Epidemiology and End Results (SEER) database’s mission is to provide information on cancer statistics to help reduce the burden of disease in the U.S. population. The SEER database is a project to the National Cancer Institute. The SEER database collects information on incidence, prevalence, and survival from specific geographic areas representing 28 percent of the United States population. User functionality Users can access a variety of reso urces. Cancer Stat Fact Sheets allow users to look at summaries of statistics by major cancer type. Cancer Statistic Reviews are available from 1975-2008 in table format. Users are also able to build their own tables and graphs using Fast Stats. The Cancer Query system provides more flexibility and a larger set of cancer statistics than F ast Stats but requires more input from the user. State Cancer Profiles include dynamic maps and graphs enabling the investigation of cancer trends at the county, state, and national levels. SEER research data files and SEER*Stat software are available to download through your Internet connection (SEER*Stat’s client-server mode) or via discs shipped directly to you. A signed data agreement form is required to access the SEER data Data Notes Data is available in different formats depending on which type of data is accessed. Some data is available in table, PDF, and html formats. Detailed information about the data is available under “Data Documentation and Variable Recodes”.

This dataset of breast cancer patients was obtained from the 2017 November update of the SEER Program of the NCI, which provides information on population-based cancer statistics. The dataset involved female patients with invasive breast cancer who were diagnosed between 2000 and 2017. The dataset includes information on the patient's age, race, ethnicity, stage of cancer, tumor size, grade, and treatment.

The data is available for sharing under the Creative Commons Attribution 4.0 International License. To share the data, please cite the dataset as follows:

Citation: JING TENG, January 18, 2019, "SEER Breast Cancer Data", IEEE Dataport, doi: https://dx.doi.org/10.21227/a9qy-ph35.

examined regional LNs

IntroductionTriple-negative breast cancer (TNBC) is linked to a poorer outlook, heightened aggressiveness relative to other breast cancer variants, and limited treatment choices. The absence of conventional treatment methods makes TNBC patients susceptible to metastasis. The objective of this research was to assess the clinical and pathological traits of TNBC patients, predict the influence of risk elements on their outlook, and create a prediction model to assist doctors in treating TNBC patients and enhancing their prognosis.MethodsWe included 23,394 individuals with complete baseline clinical data and survival information who were diagnosed with primary TNBC between 2010 and 2015 based on the SEER database. External validation utilised a group from The Affiliated Lihuili Hospital of Ningbo University. Independent risk factors linked to TNBC prognosis were identified through univariate, multivariate, and least absolute shrinkage and selection operator regression methods. These characteristics were chosen as parameters to develop 3- and 5-year overall survival (OS) and breast cancer-specific survival (BCSS) nomogram models. Model accuracy was assessed using calibration curves, consistency indices (C-indices), receiver operating characteristic curves (ROCs), and decision curve analyses (DCAs). Finally, TNBC patients were divided into groups of high, medium, and low risk, employing the nomogram model for conducting a Kaplan-Meier survival analysis.ResultsIn the training cohort, variables such as age at diagnosis, marital status, grade, T stage, N stage, M stage, surgery, radiation, and chemotherapy were linked to OS and BCSS. For the nomogram, the C-indices stood at 0.762, 0.747, and 0.764 in forecasting OS across the training, internal validation, and external validation groups, respectively. Additionally, the C-index values for the training, internal validation, and external validation groups in BCSS prediction stood at 0.793, 0.755, and 0.811, in that order. The findings revealed that the calibration of our nomogram model was successful, and the time-variant ROC curves highlighted its effectiveness in clinical settings. Ultimately, the clinical DCA showcased the prospective clinical advantages of the suggested model. Furthermore, the online version was simple to use, and nomogram classification may enhance the differentiation of TNBC prognosis and distinguish risk groups more accurately.ConclusionThese nomograms are precise tools for assessing risk in patients with TNBC and forecasting survival. They can help doctors identify prognostic markers and create more effective treatment plans for patients with TNBC, providing more accurate assessments of their 3- and 5-year OS and BCSS.

Dataset

This dataset was created by Ahmed Ashraf

Released under Apache 2.0

Contents

The Surveillance, Epidemiology, and End Results (SEER) Program provides information on cancer statistics in an effort to reduce the cancer burden among the U.S. population. SEER is supported by the Surveillance Research Program (SRP) in NCI's Division of Cancer Control and Population Sciences (DCCPS).

This dataset contains data for cancers known or suspected to be associated with environmental hazards, and is used to present cancer indicators and measures. It contains counts by state FIPS code, county FIPS code, year(s) of diagnosis, sex, age group, race, and ethnicity. This dataset was generated using data from the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) and the Centers for Disease Control and Prevention's National Program of Cancer Registries (NPCR). SEER collects information on incidence, survival, and prevalence from specific geographic areas representing 26 percent of the US population and compiles reports on all of these plus cancer mortality for the entire US. NPCR includes population-based data about the occurrence of cancer (incidence), the types of cancer (morphology), the site in the body where the cancer first occurred (primary site), the extent of disease at the time of diagnosis (stage), the planned first course of treatment, and the outcome of treatment and clinical management (survival and vital status). Cancer incidence data are reported to metropolitan area, regional, and statewide cancer registries from a variety of medical facilities, including hospitals, physicians' offices, radiation facilities, freestanding surgical centers, and pathology laboratories. The primary source of data on cancer incidence is medical records. Staff at health care facilities abstract data from patients' medical records, enter it into the facility's own cancer registry if it has one, and then send the data to the regional or state registry. Both NPCR and SEER registries collect data using uniform data items and codes as documented by the North American Association of Central Cancer Registries (NAACCR). This dataset contains confidential information. Small numbers suppression has been applied to data available. Five year aggregation is applied.

This dataset contains Cancer Incidence data for Breast Cancer (All Stages^) including: Age-Adjusted Rate, Confidence Interval, Average Annual Count, and Trend field information for US States for the average 5 year span from 2018 to 2022.Data are segmented by Females and age (All Ages, Ages Under 50, Ages 50 & Over, Ages Under 65, and Ages 65 & Over), with field names and aliases describing the sex and age group tabulated.For more information, visit statecancerprofiles.cancer.govData NotationsState Cancer Registries may provide more current or more local data.TrendRising when 95% confidence interval of average annual percent change is above 0.Stable when 95% confidence interval of average annual percent change includes 0.Falling when 95% confidence interval of average annual percent change is below 0. † Incidence rates (cases per 100,000 population per year) are age-adjusted to the 2000 US standard population (SEER areas use 20 age groups and NPCR areas use 19 age groups). Rates are for invasive cancer only (except for bladder cancer which is invasive and in situ) or unless otherwise specified. Rates calculated using SEER*Stat. Population counts for denominators are based on Census populations as modified by NCI. The US Population Data File is used for SEER and NPCR incidence rates.‡ Incidence Trend data come from different sources. Due to different years of data availability, most of the trends are AAPCs based on APCs but some are APCs calculated in SEER*Stat. Please refer to the source for each area for additional information.Rates and trends are computed using different standards for malignancy. For more information see malignant.^ All Stages refers to any stage. Due to changes in stage coding, Combined Summary Stage with Expanded Regional Codes (2004+) is used for data from Surveillance, Epidemiology, and End Results (SEER) databases and Merged Summary Stage is used for data from National Program of Cancer Registries databases. Due to the increased complexity with staging, other staging variables maybe used if necessary.Data Source Field Key(2) Source: National Program of Cancer Registries SEER*Stat Database - United States Department of Health and Human Services, Centers for Disease Control and Prevention (based on the 2024 submission).(7) Source: SEER November 2024 submission.

PurposeTo determine the prevalence of nipple-sparing mastectomy (NSM) and its long-term survival outcomes in breast cancer patients.MethodWe used the Surveillance, Epidemiology, and End Results database and identified 2,440 breast cancer patients who received NSM during 1998–2013. We used chi-square and binary logistic regression to identify factors associated with the use of radiotherapy after NSM. We used Kaplan-Meier analysis to estimate cancer-specific survival (CSS) and overall survival (OS). We used the log-rank test and Cox regression to identify factors associated with CSS and OS.ResultsThe median age of the population was 50 years. There were 725 (29.7%), 1064 (43.6%) and 651 (26.7%) patients who had Tis, T1 and T2-3 disease and 1943 (79.6%), 401 (16.4%) and 96 (3.9%) patients who had N0, N1 and N2-3 disease, respectively. The rates of RT use were 61.4%, 39.6% and 10.9% in patients with N2-3 disease, N1 or T3/N0 disease and Tis/T1-2N0 disease, respectively. Elderly age, African American race, and higher T-stage and N-stage were associated with receiving radiotherapy. For patients diagnosed between 1998–2010 (N = 763), the median follow-up was 69 months. The 5- and 10-yr CSS were 96.9% and 94.9%, respectively. The 5- and 10-yr OS were 94.1% and 88.0%, respectively. Ethnicity, T-stage and N-stage were factors independently associated with CSS, and age and T-stage were factors independently associated with OS.ConclusionsThe use of NSM has increased, and it is oncologically safe for breast cancer patients.

SEER collects cancer incidence data from population-based cancer registries covering approximately 47.9 percent of the U.S. population. The SEER registries collect data on patient demographics, primary tumor site, tumor morphology, stage at diagnosis, and first course of treatment, and they follow up with patients for vital status.There are two data products available: SEER Research and SEER Research Plus. This was motivated because of concerns about the increasing risk of re-identifiability of individuals. The Research Plus databases require more rigorous process for access that includes user authentication through Institutional Account or multiple-step request process for Non-Institutional users.

IntroductionCutaneous angiosarcoma (cAS) is an aggressive vascular tumor that originates from vascular or lymphatic epithelial cells. To date, the cAS literature has been limited in a small number with single-center experiences or reports due to its rarity and the optimal treatment strategy is still in dispute. This study aimed to conduct a systematic review and compare the effect of available treatments retrieved from observational studies and Surveillance, Epidemiology, and End Results (SEER) program.MethodsThe authors performed a systematic review in the PubMed, Embase and MEDLINE database identifying the researches assessing the treatment for cAS patients. Clinical and treatment information of patients who had been diagnosed with a primary cAS were also obtained from the SEER program.ResultsThirty-two studies were eligible but only 5 of which with 276 patients were included in meta-analysis since the unclear or unavailable information. The risk ratio of 5-year death for surgery, surgery with radiotherapy and surgery with chemotherapy were 0.84, 0.96, and 0.69. Meanwhile, in SEER database, there are 291 metastatic and 437 localized patients with cAS. The localized patients receiving surgery showed a significantly worse overall survival result when compared with the surgery combined with RT: hazard ratio: 1.6, 95% confidential interval: 1.05, 2.42, P = 0.03.ConclusionIn conclusion, our study provided a detailed picture of the effectiveness of present treatments for localized and metastatic cAS patients. The CT could be inappropriate in localized patients. For metastatic patients, the surgery combined RT was recommended compared with surgery alone since its enhanced OS prognosis. Yet, more novel-designed clinical trials with specific targeted populations and rigorous conducting are needed for a solid conclusion on which would be a better treatment strategy.

IntroductionLittle research has investigated the prevalence and distribution of the diverse pathologies of non-squamous cell carcinoma (non-SCC) of the penis. Although rare in clinical practice, these cancers have become a focus of greater importance among patients, clinicians, and researchers, particularly in developing countries. The principal objective of this study was to analyze the major types of penile non-SCC, elucidate common treatment pathways, and highlight outcomes including 5-year survival.Materials/methodsThe Surveillance, Epidemiology, and End Results (SEER) database was queried between 2000 and 2018 to identify a retrospective cohort of patients with penile non-SCC. Demographic information, cancer characteristics, diagnostic methods, treatments administered, and survival were investigated.ResultsA total of 547 cases of penile non-SCC were included in the analysis. The most prevalent non-SCC cancers included epithelial neoplasms, not otherwise specified (NOS) (15.4%), unspecified neoplasms (15.2%), basal cell neoplasms (13.9%), blood vessel tumors (13.0%), nevi and melanomas (11.7%), and ductal and lobular neoplasms (9.9%). Over half (56.7%) of patients elected to undergo surgical intervention. Patients rarely received systemic therapy (3.8%) or radiation (4.0%). Five-year survival was 35.5%. Patients who underwent surgery had greater annual survival for 0–10 years compared to those who did not have surgery. Significant differences in survival were found between patients who had regional, localized, and distant metastases (p < 0.05). A significant difference in survival was found for patients married at diagnosis versus those who were unmarried at diagnosis (p < 0.05). Lower survival rates were observed for patients older than 70 years.DiscussionAlthough less prevalent than SCC, penile non-SCC encompasses a diverse set of neoplasms. Patients in this cohort had a high utilization of surgical management leading to superior outcomes compared to those not receiving surgery. Radiation is an uncommonly pursued treatment pathway. Patient demographics and socioeconomic variables such as marital status may be valuable when investigating cancer outcomes. This updated database analysis can help inform diagnosis, management, and clinical outcomes for this rare group of malignancies.

PurposeThe lung is the most common distant metastatic organ in patients with endometrial cancer (EC) but is rarely reported. This study examines the association between clinical characteristics and overall survival (OS) in EC with lung metastasis.MethodsPatients with EC who had accompanying lung metastasis were selected from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2017. Univariate and multivariate Cox regression were used to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs) and assess OS outcomes related to EC with lung metastasis. A Cox proportional hazards nomogram model for OS was constructed and validated. The calibration plot, receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were used to evaluate the discriminative ability and clinical benefit of the novel nomogram. Kaplan–Meier curves and scatter diagram analysis were used to investigate the risk stratifications of the nomogram.ResultsOverall, 1542 EC patients with lung metastasis between 2010 and 2017 were included and randomly divided into training and validation cohorts. A nomogram model was constructed using the clinical characteristics of tumor grade, histological type, surgery, adjuvant chemotherapy, adjuvant radiation, brain metastasis and liver metastasis. The concordance indexes (C-indexes) were 0.750 (95% CI, 0.732-0.767) and 0.743 (95% CI, 0.719-0.767) for the training cohort and validation cohort, respectively. Calibration plots and DCA showed good clinical applicability of the nomogram. The areas under the curves (AUCs) were 0.803 and 0.766 for 1-year and 3-year OS, respectively, indicating that the nomogram model had a stable discriminative ability. An online calculator of our nomogram is available on the internet at https://endometrialcancer.shinyapps.io/DynNomapp/. Additionally, patients in the high-risk group had a significantly worse OS than those in the low-risk group.ConclusionAn easy-to-use, highly accurate nomogram was developed for predicting the prognosis of EC patients with lung metastasis.

Background and aimThe incidence of early-onset colorectal cancer (EOCRC) is rising, yet intensive postoperative adjuvant chemotherapy (ACT) often results in overtreatment with minimal prognostic benefit. This study aims to assess the therapeutic necessity of ACT in stage II EOCRC patients and to identify potential ACT candidates.MethodsA total of 296 non-ACT and 50 ACT patients with stage II EOCRC were included from Xijing Hospital (XJCRC), and 2067 non-ACT and 1163 ACT patients were enrolled from the Surveillance, Epidemiology, and End Results (SEER) cohort. To address selection bias and confounding, propensity score matching, inverse probability treatment weighting (IPTW), and multivariate Cox regression analyses were utilized. Survival curves and landmark analysis were employed to compare Overall Survival (OS) differences.ResultsSimilar OS were observed between ACT and non-ACT groups in both cohorts before and after adjustment for confounders. No significant survival differences were noted in dMMR (P = 0.48), pMMR (P = 0.07), and T3 (P = 0.83) subgroups. However, T4 stage patients receiving ACT demonstrated prolonged survival compared to non-ACT counterparts, particularly after three years (P = 0.007), as identified by landmark analysis.ConclusionsMost stage II EOCRC patients might yield limited benefits from postoperative ACT, with the sole exception of those at T4 stage, who could experience long-term clinical advantages.Clinical Trial Registrationhttps://clinicaltrials.gov/study/, identifier NCT06308354.

This dataset contains Cancer Incidence data for Colorectal Cancer (All Stages^) including: Age-Adjusted Rate, Confidence Interval, Average Annual Count, and Trend field information for US States for the average 5 year span from 2018 to 2022.Data are segmented by sex (Both Sexes, Male, and Female) and age (All Ages, Ages Under 50, Ages 50 & Over, Ages Under 65, and Ages 65 & Over), with field names and aliases describing the sex and age group tabulated.For more information, visit statecancerprofiles.cancer.govData NotationsState Cancer Registries may provide more current or more local data.TrendRising when 95% confidence interval of average annual percent change is above 0.Stable when 95% confidence interval of average annual percent change includes 0.Falling when 95% confidence interval of average annual percent change is below 0. † Incidence rates (cases per 100,000 population per year) are age-adjusted to the 2000 US standard population (SEER areas use 20 age groups and NPCR areas use 19 age groups). Rates are for invasive cancer only (except for bladder cancer which is invasive and in situ) or unless otherwise specified. Rates calculated using SEER*Stat. Population counts for denominators are based on Census populations as modified by NCI. The US Population Data File is used for SEER and NPCR incidence rates.‡ Incidence Trend data come from different sources. Due to different years of data availability, most of the trends are AAPCs based on APCs but some are APCs calculated in SEER*Stat. Please refer to the source for each area for additional information.Rates and trends are computed using different standards for malignancy. For more information see malignant.^ All Stages refers to any stage. Due to changes in stage coding, Combined Summary Stage with Expanded Regional Codes (2004+) is used for data from Surveillance, Epidemiology, and End Results (SEER) databases and Merged Summary Stage is used for data from National Program of Cancer Registries databases. Due to the increased complexity with staging, other staging variables maybe used if necessary.Data Source Field Key(2) Source: National Program of Cancer Registries SEER*Stat Database - United States Department of Health and Human Services, Centers for Disease Control and Prevention (based on the 2024 submission).(7) Source: SEER November 2024 submission.

The county population estimates currently used in the SEER*Stat software to calculate cancer incidence and mortality rates are available for download (see Download U.S. Population Data). They represent a modification of the intercensal and Vintage 2019 annual time series of July 1, county population estimates by age, sex, race, and Hispanic origin produced by the U.S. Census Bureau's Population Estimates Program, in collaboration with the National Center for Health Statistics, and with support from the NCI through an interagency agreement. The files were downloaded and archived on July 28, 2021 by the American Economic Association's Data Editor.

This study aimed to compare the effectiveness of chemotherapy in different histological types of pancreatic cancer using data collected from the Surveillance, Epidemiology, and End Results (SEER) database. Patients who were diagnosed with pancreatic cancer between 2004 and 2015 were selected from the SEER database. Propensity score matching (PSM) was employed to minimize the selection bias. The Kaplan-Meier survival curves and the log-rank test were utilized to compare the overall survival (OS) and cancer-specific survival (CSS) among different groups. Of the 7,653 pancreatic cancer patients, both OS and CSS were higher in the chemotherapy group than those in the non-chemotherapy group (p < 0.001). After PSM, 2381 pairs were generated. The Kaplan-Meier survival curved indicated that both OS and CSS for pancreatic ductal adenocarcinoma (PDAC), pancreatic adenosquamous carcinoma (PASC), and pancreatic mucin-producing adenocarcinoma (PMPAC) (p < 0.001) in the chemotherapy group were superior to those in the non-chemotherapy group, while there was no significant difference in pancreatic mucinous adenocarcinoma (PMAC) (p = 0.2586). Compared with PASC and PMPAC, PDAC exhibited longer OS and CSS. The results of statistical analysis showed that PASC tumors were mainly poorly differentiated, and the majority of patients with PMPAC had distant metastasis. Chemotherapy could prolong pancreatic cancer patients’ survival, especially for patients with advanced disease. PMPAC patients had a higher rate of metastasis, accompanying with the worse survival.

ObjectivePulmonary enteric adenocarcinoma (PEAC) is a rare subtype of pulmonary adenocarcinoma that lacks effective treatment. The purpose of this research was to investigate the clinical characteristics, treatment, and prognosis of PEAC, as well as the impact of relevant factors on survival, thus providing a reference for the clinical management of patients with this disease.MethodsFor this study, we gathered clinical data from 26 patients with PEAC in the Affiliated Cancer Hospital of Zhengzhou University from June 2014 to June 2021. We used SEER*Stat software V8.3.5 to download the PEAC patients from the Surveillance, Epidemiology, and End Results (SEER) database. In total, 20 patients were identified. Clinical data, including general information, imaging findings, and treatment protocols, were obtained, together with a follow-up of disease regression. The relevant clinical data were then analyzed.ResultsIt included 12 males and 14 females out of 26 patients from China, whose mean age was (62.73 ± 11.89) years; 20 were in the lower lung, 11 were stage I-II, and 15 were stage III-IV. Five had EGFR mutations, and four had KRAS mutations. In terms of treatment, patients with stage I-II were primarily treated by surgery, and patients with stage III-IV were treated mostly by chemotherapy. We extended the follow-up date to January 2022. On completion of the follow-up visit, 11 patients died, and the remaining 15 patients survived. The overall survival (OS) of 26 patients was 2.0-76.0 months, while the mean was 53.1 months, and the median OS (mOS) was 38.0 months (95% CI:1.727-74.273). In the case of progression-free survival (PFS) times, it was 2.0-76.0 months, with a mean PFS of 31.0 months and a median PFS (mPFS) of 8.0 months (95% CI:4.333-11.667). The PFS of the 15 patients in stage III-IV was 2.0-17 months, while the mean PFS was 6.5 months and the mPFS was 6.0 months (95% CI:4.512-7.488). Out of the 20 patients identified in the SEER database, the average age was 69.9 years, with 14 males and 6 females. Of these patients, 8 were diagnosed with stage I-II, while the remaining 11 were diagnosed with stage III-IV. 10 underwent surgery, 4 received radiation therapy, and 9 received chemotherapy. The mean OS of the 20 patients was 67.5 months, mOS was 28.0 months (95% CI: 9.664- 46.336). For patients diagnosed with stage III-IV, the mean OS was 14.8 months and mOS was 20 months (95% CI: 4.713-35.287).ConclusionPEAC is rare, and the prognosis is determined mainly by the stage; patients who undergo surgery in stage I-II have a better prognosis.

This dataset contains Cancer Incidence data for Breast Cancer (Late Stage^) including: Age-Adjusted Rate, Confidence Interval, Average Annual Count, and Trend field information for US States for the average 5 year span from 2018 to 2022.Data are segmented by Females and age (All Ages, Ages Under 50, Ages 50 & Over, Ages Under 65, and Ages 65 & Over), with field names and aliases describing the sex and age group tabulated.For more information, visit statecancerprofiles.cancer.govData NotationsState Cancer Registries may provide more current or more local data.TrendRising when 95% confidence interval of average annual percent change is above 0.Stable when 95% confidence interval of average annual percent change includes 0.Falling when 95% confidence interval of average annual percent change is below 0. † Incidence rates (cases per 100,000 population per year) are age-adjusted to the 2000 US standard population (SEER areas use 20 age groups and NPCR areas use 19 age groups). Rates are for invasive cancer only (except for bladder cancer which is invasive and in situ) or unless otherwise specified. Rates calculated using SEER*Stat. Population counts for denominators are based on Census populations as modified by NCI. The US Population Data File is used for SEER and NPCR incidence rates.‡ Incidence Trend data come from different sources. Due to different years of data availability, most of the trends are AAPCs based on APCs but some are APCs calculated in SEER*Stat. Please refer to the source for each area for additional information.Rates and trends are computed using different standards for malignancy. For more information see malignant.^ Late Stage is defined as cases determined to be regional or distant. Due to changes in stage coding, Combined Summary Stage with Expanded Regional Codes (2004+) is used for data from Surveillance, Epidemiology, and End Results (SEER) databases and Merged Summary Stage is used for data from National Program of Cancer Registries databases. Due to the increased complexity with staging, other staging variables maybe used if necessary.Data Source Field Key(2) Source: National Program of Cancer Registries SEER*Stat Database - United States Department of Health and Human Services, Centers for Disease Control and Prevention (based on the 2024 submission).(7) Source: SEER November 2024 submission.