Surveillance, Epidemiology, And End Results Research Articles

Incident cardiovascular disease risk among older Asian, Native Hawaiian and Pacific Islander liver cancer survivors

BackgroundCardiovascular disease (CVD) is a significant global health concern, particularly among Asian, Native Hawaiian, and Pacific Islander (ANHPI) communities that face unique health challenges. Liver cancer disproportionately affects ANHPI populations and has intricate associations with CVD risks due to shared pathophysiological mechanisms and metabolic disturbances. However, the specific CVD risk profile of ANHPI liver cancer patients remains poorly understood. MethodsUsing Surveillance, Epidemiology, and End Results (SEER)-Medicare data, we identified and matched 1150 ANHPI and 2070 Non-Hispanic White (NHW) liver cancer patients diagnosed between 2000 and 2017. We used the Fine-Gray sub-distribution hazard model to estimate hazard ratios (HRs) and 95 % confidence intervals (95 % CIs) for CVD risks, including ischemic heart disease (IHD), heart failure, and stroke, among ANHPI liver cancer patients compared to NHW counterparts and among ANHPI subgroups. ResultsANHPI liver cancer patients demonstrated a lower risk of IHD compared to NHW counterparts (HR, 0.65, 95 % CI, 0.50, 0.86), aligning with broader trends. Subgroup analysis revealed notable heterogeneity within ANHPI populations, with Southeast Asian (HR, 0.65, 95 % CI, 0.42, 1.00) and Chinese patients (HR, 0.53, 95 % CI, 0.33–0.83) exhibiting lower IHD risks compared to their NHW counterparts. However, Native Hawaiian and Pacific Islander liver cancer patients showed elevated risks of heart failure (HR, 3.16, 95 % CI, 1.35–7.39) and IHD (HR, 5.64, 95 % CI, 2.19–14.53) compared to their Chinese counterparts. ConclusionOur study highlights the complexity of CVD risks among ANHPI liver cancer patients. Addressing these disparities is crucial for improving cardiovascular outcomes and reducing the burden of CVD among ANHPI liver cancer patients.

Prostate cancer incidence rates, trends, and treatment related to prostate-specific antigen screening recommendations in the United States

BackgroundChanges in US prostate-specific antigen (PSA) screening guidelines have impacted prostate cancer (PCa) incidence rates and trends. This study shows corresponding changes in PCa incidence rates and describes treatment patterns by tumor stage, age, and race/ethnicity. MethodsAnalyses were based on 777,152 cases diagnosed in 17 population-based tumor registries in the SEER Program of the US National Cancer Institute, 2007–2021. Rates were age adjusted and trends assessed using annual percent change and joinpoint regression. ResultsPCa age-adjusted incidence rates (per 100,000) fell from 165.8 in 2007 to 101 in 2014 (APC=-6.51, p<0.05) and then rose to 121.2 in 2021 (APC=1.87, p< 0.05). The significant fall and rise in rates appeared in ages 55–69 and ≥70, all racial/ethnic groups (except in Hispanics during 2014–2021), and in local/regional stage. PCa incidence rates by tumor stage, age, and race/ethnicity were presented and discussed. A few PCa cases were identified through autopsy or death certificate among the racial/ethnic groups (0.68 %-1.37 %). Unstaged cases identified through sources other than autopsy or death certificate significantly varied by race/ethnicity, ranging from 4.13 % for non-Hispanic (NH) Whites to 9.5 % for Hispanic (Chi-square p <.0001). In 2017–2021, surgery occurred in 33 % of cases (primarily in local/regional cases, inversely associated with age), radiation in 30 % of cases (increasing with age in local/regional stage cases and decreasing with age in distant stage cases), and chemotherapy in 2 % of cases (<1 % in local/regional stage cases and 9 %-38 % for age groups in distant stage cases). Several racial/ethnic differences in treatment exist, such as NH Blacks (vs. NH Whites) with local/regional disease were significantly less likely to receive surgery and more likely to receive radiation. ConclusionsUnderstanding trends and patterns of PCa rates and treatment among patients by tumor stage, age, and race/ethnicity can guide public health planning in relation to screening and treatment.

Demographic, Disease, and Treatment Characteristics of Primary Tracheal Cancers

Abstract Background Primary tracheal cancers (PTCs) are rare neoplasms underreported in the literature. No consensus guidelines exist for the treatment of these cancers and multimodal management of these cancers has not been adequately explored for cases diagnosed over the past 2 decades. Methods The Surveillance, Epidemiology, and End Results (SEER) database was queried to identify patients with PTC. Cox proportional hazards and log-rank testing was used to assess the association between demographic and treatment variables and 5-year cause-specific survival (CSS). Results Among the 689 identified patients, age &lt; 65 years at diagnosis (hazard ratio [HR] 0.64, p &lt; 0.001), non-squamous cell carcinoma (SCC) histology (HR 0.22, p &lt; 0.001), and treatment with surgery (HR 0.43, p &lt; 0.001) were all associated with increased 5-year CSS. Regarding disease histology, patients with adenoid cystic carcinomas (ACCs) had increased 5-year CSS compared with those with neither SCC nor ACC histology and those with SCC histology (83.4% [76.0%, 90.8%] versus 50.3% [42.5%, 58.1%] and 28.8% [23.2%, 34.4%]; p &lt; 0.001) based on univariate analysis. Despite the improved CSS associated with surgery, 55% of the identified cohort did not undergo surgery, with only 5.5% of these patients having ACC compared with 58% having SCC (p &lt; 0.001). Conclusions Age &lt; 65 years, ACC histology, and treatment with surgery were associated with improved 5-year CSS among patients with PTC, although the significant proportion of this group not receiving surgery represents an opportunity for improved outcomes.

Clustering of gastroenteropancreatic neuroendocrine neoplasms (GEP-NEN) using machine learning (ML) and comparison with Tumour, Node, Metastasis (TNM) staging: a retrospective, population-based study using Surveillance, Epidemiology, and end results (SEER)

Clustering of gastroenteropancreatic neuroendocrine neoplasms (GEP-NEN) using machine learning (ML) and comparison with Tumour, Node, Metastasis (TNM) staging: a retrospective, population-based study using Surveillance, Epidemiology, and end results (SEER)

Guiding adjuvant radiotherapy in stage III endometrial cancer: a prognostic model based on SEER

BackgroundThe effect of overall survival (OS) with adjuvant radiotherapy in stage III endometrial cancer (EC) remains controversial, and the adverse invents were unignorable.MethodsA total of 4,064 stage III EC patients who underwent adjuvant chemotherapy post-operatively were selected from Surveillance, Epidemiology, and End Results (SEER) Program. Independent risk factors were identified through Cox regression models. A nomogram was developed accordingly to predict OS. The concordance index (C-index), calibration, and Receiver Operating Characteristic (ROC) curves were applied to assess the model. Patients were divided into the low- and high-risk groups based on the optimal risk cutoff. Stratified analysis was conducted by radiation in both groups, and interactions between radiation and the risk groups were conducted to explore if any benefit less from adjuvant radiotherapy.ResultsA total of five candidate factors were identified from the model showing good calibration and consistency discriminative power in the training (C-index: 0.73; 95% CI: 0.70–0.75), testing (C-index: 0.73; 95% CI: 0.69–0.77), and external validation cohorts (C-index: 0.88, 95% CI, 0.78–0.97). Patients were categorized into the low- and high-risk groups based on the optimal risk cutoff of 2.1048630. The women in the high-risk group experience significantly less (42% vs. 63% reduction) or none (0 vs. 63%) benefit (p-interaction = 0.049 vs. 0.016 in training and testing cohorts, respectively).ConclusionA nomogram incorporating five variables was established to predict OS in stage III EC patients with adjuvant chemotherapy. The high-risk groups benefit less or none from adjuvant radiotherapy, which may serve as a useful reference for better guidance of radiotherapy in stage III EC patients.

Nomograms Predicting Survival, Recurrence and Beneficiary Identification of Adjuvant Chemotherapy in Treatment-naïve Patients with Rectal Cancer who Underwent Upfront Curative Resection: A multi-institutional study

Objective: To create and validate nomograms predicting overall survival and recurrence in treatment-naïve rectal cancer (RC) patients who underwent upfront surgery. Background: Although multidisciplinary treatment is standard for locally advanced RC, understanding surgical efficacy is important for determining indications for perioperative adjuvant therapy. Methods: RC patients who underwent upfront surgery at the Japanese Society for Cancer of the Colon and Rectum institutions were analyzed. A training cohort (n = 1925) of treatment-naïve patients who underwent surgery between 2007 and 2008 was analyzed to construct prognostic models predicting postoperative survival and recurrence. Discrimination and calibration were performed using an external validation cohort (n = 2957; Japanese colorectal cancer registry, procedures in 2005–2006). Effects of adjuvant chemotherapy on survival were evaluated based on nomogram prediction and Surveillance, Epidemiology, and End Results (SEER) data (n = 10,482; upfront surgery for RC in 2010–2015). Results: In the training cohort, age predicted survival, venous invasion predicted recurrence, and sex, tumor location, histological type, preoperative carcinoembryonic antigen, invasion depth, lymphatic invasion, positive radial margin, and numbers of metastatic nodes and examined nodes predicted both. Internal and external validated Harrell’s C-index values were respectively 0.77 and 0.75 for survival and 0.75 and 0.74 for recurrence. RC patients who underwent upfront surgery in the SEER database were stratified into 3 risk levels by nomogram score. Adjuvant chemotherapy did not improve 5-year survival in low-risk patients, but did so for middle-risk (62.4% vs 76.8%) and high-risk (39.4% vs 63.5%) patients. Conclusion: These nomograms could predict survival and recurrence after upfront curative resection of RC and identify cases expected to benefit more from adjuvant chemotherapy.

Development and validation of survival nomograms for patients with anaplastic thyroid carcinoma: a SEER program-based study.

We aimed to study the prognostic risk factors affecting patients with anaplastic thyroid carcinoma (ATC), develop a clinical prognostic model, and assess patient survival outcomes. Patients with anaplastic thyroid carcinoma from 2000 to 2019 were selected from the Surveillance, Epidemiology, and End Results (SEER) Program to extract the clinical variables used for analysis. The dataset was divided into training (70%) and validation (30%) sets based on a 7:3 ratio. Univariate and LASSO regression analyses were performed on clinical variables from the training set to identify independent prognostic factors. Independent prognostic factors were determined by Univariate and lasso regression according to the clinical variables of the training set, and a nomogram model was established to construct a prognostic model based on the contribution degree of the predictors. The prognostic model was evaluated and internally verified by C-index, ROC curve and calibration curve. A total of 713 ATC patients were included in the SEER database. LASSO regression results indicated that age, marital status, race, tumor size, whether the primary lesion was limited to the thyroid gland, surgery, radiotherapy and chemotherapy, were associated with overall survival(OS) prognosis of ATC, and were used to construct nomograms. In the training cohort, the OS nomogram's C-index was 0.708 (95% CI 0.672-0.745); in the internal validation cohort, the C-index was 0.677 (95% CI 0.620-0.735). ROC curves demonstrated that the OS nomogram exhibits excellent predictive accuracy and discriminative ability. Calibration curves indicated strong consistency between the OS nomogram's predicted survival rates and actual survival rates. We established a survival prediction model for ATC, which can assist clinicians in assessing patient prognosis and making personalized treatment decisions.

Comparison of treatment models for single primary advanced gallbladder cancer

PurposeTreatment for advanced gallbladder cancer (GBC) remains controversial, with various recommendations regarding the choice and combination of surgery and adjuvant therapy. The present article is targeting for the exploration of optimal treatment models for advanced GBC.MethodsAJCC (American Joint Committee on Cancer, 8th edition) stage III and stage IV GBC, were defined as advanced GBC. Patients with advanced GBC were identified using the Surveillance, Epidemiology, and End Results (SEER) database and departmental cohort. Because of the most representative, only gallbladder adenocarcinoma (GBAC) patients were selected. Based on their surgical status (No, Non-radical and Radical surgery), chemotherapy status (Chemotherapy, No chemotherapy), and radiotherapy status (Radiotherapy, No radiotherapy), treatment models were categorized. For the purposes of evaluating the treatment outcomes of various treatment models and determining the risk element for cancer-specific survival (CSS), Cox regression analysis was applied. Kaplan-Meier curves were used before and after adjusting for covariates, with log-rank tests used to analyze discrepancies between curves. Immunotherapy was analyzed using clinical data from departmental cohort. Finally, to compensate for the limitations of the database, a review examines the progress in treatment models for advanced GBC.Results5,154 patients aged over 18 years with solitary primary advanced GBC were identified from the SEER database. In advanced GBC patients, the treatment model has emerged as a significant prognostic factor. “Radical surgery + Chemotherapy + Radiotherapy” models maximally improved the CSS of advanced GBC before and after adjusting for covariates, while “No surgery + No chemotherapy + No radiotherapy” model had the lowest CSS. The present conclusions were supported even after subgroup analysis by AJCC stage. The efficacy of immunotherapy was demonstrated in the departmental cohort analysis. Additionally, this article provides a comprehensive overview of recent advancements in various emerging treatment strategies.ConclusionEven when optimal treatment model cannot be pursued, providing comprehensive combinations of treatments to advanced GBC patients whenever possible is always beneficial for their survival.

Abstract PR006: The potential of multi-cancer early detection screening for reducing cancer mortality

Abstract Background: Currently, routine screening is recommended for only four cancer types (i.e., breast, cervical, colorectal, and lung) by the United States Preventive Services Task Force (USPSTF), and two-thirds of incident cancers have no screening guidelines. Emerging liquid biopsy multi-cancer early detection (MCED) tests have the potential to revolutionize early cancer detection. Their impact on cancer mortality remains uncertain. Computer models are needed to forecast long-term outcomes. Methods: We developed Simulation Model for MCED (SiMCED), a continuous-time, discrete-event microsimulation model of 14 solid tumor cancers: breast, cervical, colorectal, endometrial, esophageal, gastric, head and neck, kidney, liver, lung, ovarian, pancreatic, prostate, and urinary bladder. Cancer type- and stage-specific dwell times informed the transitions between cancer stages I-IV. Cancer type- and stage-specific MCED test sensitivities were derived from a large, multi-center, prospective, case-control study: Ascertaining Serial Cancer patients to Enable New Diagnostic 2 (ASCEND-2). The model was calibrated to reproduce annual incidence rates of cancer diagnosis as captured in the Surveillance, Epidemiology, and End Results (SEER) database, while accounting for the unobserved cancer burden. Using a 10-year time horizon, we simulated the life course of 5 million US adults aged 50-84 years, representative of the US population age distribution. Cancer diagnosis could arise from usual care or annual MCED screening. The MCED test was administered at the beginning of each year to individuals aged 50-84 years. After a cancer diagnosis, individuals followed SEER survival curves to determine the time and cause of death (cancer- or non-cancer-related). Results: Over the 10-year time horizon, the supplemental use of MCED screening reduced stage IV incidence by 876 (42%) per 100,000, relative to usual care. The 10-year reduction in cancer mortality was 439 (17%) per 100,000, which translates to 505,600 cancer-related deaths averted among US adults aged 50-84 years. Lung cancer had the highest absolute 10-year cancer mortality reduction at 126 (13%) per 100,000. Among the cancer types for which there is no routine screening, the 10-year cancer mortality reduction was 175 (15%) per 100,000, equating to 201,500 cancer-related deaths averted among US adults aged 50-84 years. Within the 10-year time window, earlier diagnosis by MCED led to an aggregated life-year gain of 1,165 per 100,000, which translates to a gain of 1,340,000 life-years among US adults aged 50-84 years. Conclusion: Our study suggests that MCED screening could be effective for reducing both stage IV incidence and cancer mortality. The real-world impact of MCED tests and their cost-effectiveness require further investigation. Citation Format: Jagpreet Chhatwal, Jade Xiao, Andrew ElHabr, Christopher Tyson, Xiting Cao, Sana Raoof, A. Mark Fendrick, A. Burak Ozbay, Paul Limburg, Tomasz M. Beer, Ashish Deshmukh, Andrew Briggs. The potential of multi-cancer early detection screening for reducing cancer mortality [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr PR006.

Changing treatment patterns for hepatocellular carcinoma: A Surveillance, Epidemiology, and End Results-Medicare study.

From 2007 to 2017, sorafenib was the sole systemic therapy for hepatocellular carcinoma (HCC), but nine new therapies were approved from 2017 to 2022. No studies have yet examined population-level treatment patterns for HCC since these approvals. For this retrospective cohort, Surveillance, Epidemiology, and End Results (SEER)-Medicare data were used to identify patients who had HCC diagnosed between 2014 and 2019 with claims through 2020. The authors examined patient characteristics, comorbidities, and receipt of local (e.g., transplantation, resection, embolization) and systemic (e.g., sorafenib, lenvatinib, atezolizumab plus bevacizumab) therapies. Cohort characteristics, treatment patterns, and overall survival (OS) were analyzed, and χ2 tests and t-tests were used to compare treatments between the 2014-2017 and 2018-209 cohorts. Adjusted Cox models were used to compare median OS between treatment groups. Among 11,766 patients (men, 69.2%; White, 76.9%; median age, 71 years), 60.5% received treatment within 1 year, which remained stable over time (2014-2017, 60.4%; 2018-2019, 61.0%; p = .84). The use of local therapy also remained stable (2014-2017, 52.1%; 2018-2019, 52.8%; p = .43), whereas the use of systemic therapy slightly decreased (2014-2017, 17.0%; 2018-2019, 15.2%; p = .01). First-line systemic treatments shifted significantly, with sorafenib use dropping from 84.5% (2014-2017) to 41.3% (2018-2019). The median OS among patients who received no treatment, systemic therapies first, or local therapies first was 2.2, 12.0, and 23.6 months, respectively. Patients who were diagnosed in 2019 had better OS (hazard ratio [HR], 0.80; 95% confidence interval [CI], 0.74-0.86) as did those who received systemic therapy first (HR, 0.33; 95% CI, 0.18-0.61), but survival was worse for those who received local therapy first (HR, 1.41; 95% CI, 1.08-1.84) compared with those who were diagnosed in 2014. Local therapy patterns remained stable, but novel therapies replaced sorafenib as the preferred first-line treatment, improving survival.

Nasopharyngeal carcinoma survival by histology in endemic and non-endemic areas

Background To investigate the prognostic implications of histology among nasopharyngeal carcinoma (NPC) using the data from a Chinese cohort and the Surveillance, Epidemiology, and End Results (SEER) database. Methods We included patients diagnosed with WHO II and III subtypes NPC from two independent cohorts (Xiamen [XM]-NPC cohort and SEER-NPC cohort). Results We identified 726 patients in the XM-NPC cohort and 1334 patients in the SEER cohort. In the XM-NPC cohort, 94 (12.9%) and 632 (87.1%) patients had WHO II and III subtypes, respectively. In the SEER-NPC cohort, 839 (62.9%) and 495 (37.1%) patients had WHO II and III subtypes, respectively. WHO II subtype patients had a higher smoking rate than the WHO III subtype (57.4% vs. 43.4%) in the XM-NPC cohort. There were no significant differences in age, gender, tumor stage, or nodal stage between the two subtypes in both cohorts. In the XM-NPC cohort, patients with the WHO II subtype had worse locoregional relapse-free survival (82.2% vs. 89.5%, p = 0.063), distant metastasis-free survival (72.4% vs. 85.9%, p = 0.028), disease-free survival (61.6% vs. 78.8%, p = 0.003), and overall survival (OS) (71.7% vs. 84.0%, p = 0.035) than those with WHO III subtype. In the SEER-NPC cohort, patients with the WHO II subtype had worse NPC-specific survival (81.1% vs. 89.4%, p < 0.001) and OS (71.6% vs. 78.8%, p < 0.001) than those with WHO III subtype. The multivariate analysis showed that histology was an independent prognostic factor associated with outcomes in both cohorts. Conclusions Our study demonstrates the significant influence of histological subtypes on outcomes in NPC among various populations, highlighting substantial disparities between the WHO II and WHO III subtypes.

Causes of death after oral cancer diagnosis: a population based study

BackgroundNowadays, the number of oral cancer survivors is increasing, emphasizing the importance of thoroughly understanding diverse causes of death in oral cancer survivors. Our study aimed to investigate the distribution of causes of death after oral cancer diagnosis.MethodsEligible patients were identified between 2004 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database. We calculated the number of deaths in different demographic and clinicopathological variables during each follow-up period. Standardized mortality ratios(SMRs) were generated for each cause of death after oral cancer diagnosis.ResultsA total of 30538 patients diagnosed with oral cancer were included, and 17654 deaths were reported during follow-up period. 27.08% of deaths were caused by non-caner reasons. The proportion of non-cancer related deaths increased with the extension of survival time, and non-cancer death accounted for 57.93% of all deaths when followed up more than 10 years. The most common non-cancer cause of death was cardiovascular disease (SMR 4.68#; 95%CI 4.46-4.92).ConclusionsNon-cancer causes of death should not be ignored in oral cancer patients. For oral cancer survivors, multidisciplinary follow-up strategy should be recommended to achieve longer survival time.

Abstract 4112775: Demographics and Cardiovascular Mortality Among Kaposi Sarcoma Patients in the United States: An Analysis of the SEER Database

Aims and Background: Kaposi sarcoma (KS) is a vascular neoplasm caused by human herpesvirus. Despite its significance, there is limited data regarding the causes and mortality factors associated with KS, particularly concerning cardiovascular mortality rates and specific influencing factors. Methods: The Surveillance, Epidemiology, and End Results (SEER) database was used to gather data from 2000 to 2020. The primary endpoint was overall survival, assessed via log-rank analysis and Kaplan-Meier plots. Hazard ratios (HR) with 95% confidence intervals (CIs) were calculated using SAS v9.4, with significance set at p&lt;0.05. Results: We identified 8,247 patients with KS. Most were male (90.6%) and aged 40-59 years old (38.5%). Mortality data from KS showed that 56.3% of diagnosed patients were alive. Among those who died, 49.8% died of infectious causes, 11.4% died of cardiac causes, and the remaining died of other causes, such as leukemias and complications. Advanced age (&gt;80 years) vs. 0-19 year age group (HR: 2.263; 95% CI: 1.068-4.795; p=0.033), non-Hispanic Black race vs. non-Hispanic White race (HR 1.492; 95% CI: 1.369-1.627; p=0.001), and visceral involvement vs. cutaneous KS (HR 1.709; 95% CI: 1.487-1.963; p=0.001) were factors associated with increased mortality. Females had a slightly lower long-term survival than males (p&lt;0.001). Married individuals, higher incomes (≥$75,000), and urban areas of living had higher survival rates compared to widowed patients, lower-income patients (&lt;$75,000), and those in rural locations, respectively (p&lt;0.001, for all). In the subgroup analysis, females (24.3%; n=112) had significantly higher cardiac-related deaths than males (9.5%; n=297) (p&lt;0.0001). Cardiac-related deaths were highest in White patients (16.1%; n=279), followed by Hispanics (10.4%; n=79). Conclusions: Cardiac causes accounted for 11.4% of deaths. Various factors are associated with an increased mortality risk.

Abstract 4137737: Demographics and Factors Influencing Mortality Among Cardiac Angiosarcoma Patients: An Analysis of the SEER Database

Background and Aims: Cardiac angiosarcoma is a rare and highly aggressive cancer originating from the endothelial cells lining the heart. It accounts for approximately 30% of all primary cardiac tumors. Given its aggressive nature and poor prognosis, it is critical to enhance our understanding of its epidemiology and the factors influencing mortality. Methods: The Surveillance, Epidemiology, and End Results (SEER) database was utilized to gather data spanning from 2000 to 2021 using the International Classification of Diseases for Oncology (ICD-O-3), anatomical codes (C38.0-Heart), and histological code 9120. Results: We identified 194 patients with cardiac angiosarcoma, of which 102 were males and 92 were females. The majority of patients were aged 50 years or younger (59%). Non-Hispanic whites constituted the largest group (56%), followed by non-Hispanic blacks (18%), and Hispanics (16%). Mortality data showed that 91% of the diagnosed patients died (n=176), with a mean survival period of 15 months after diagnosis. The overall survival rate at 1 year was 0.461 (95% CI: 0.39-0.53), at 3 years was 0.09 (95% CI: 0.05-0.14) and at 5 years was 0.052 (95% CI: 0.03-0.10). Advanced age (51-70 years) compared to the 0-50 year age group (HR: 0.57; 95% CI: 0.003-1.14; p=0.049), distant stage (HR: 0.91; 95% CI: 0.01-1.83; p=0.047), patients who did not receive therapeutic radiation therapy compared to those who did (HR: 2.69; 95% CI: 0.10-5.28; p=0.042), and patients who did not undergo surgical resection for angiosarcoma compared to those who did (HR=1.232; 95% CI: 0.69-1,77; p&lt;0.001) were factors associated with increased mortality. Female gender (p=0.248, as compared to males), different races of non-Hispanic White (p=0.849), non-Hispanic Black (p=0.34), non-Hispanic Asian or Pacific Islander (p=0.24), as compared to Hispanics, tumor sizes of 6-10 cms (p=0.957), or more than 10 cm (p=0.273), as compared to &lt; 5 cm, grade of tumor (III; p=0.682, and grade IV; p=0.281, as compared to grade I), median household income of more than 65000 USD (p=0.069) as compared to less than that, and no chemotherapy (p=0.851) compared to those that received chemotherapy, were not associated with a significant increase in mortality. Conclusions: Cardiac angiosarcoma is associated with a high mortality rate. Factors contributing to increased mortality include advanced age, distant stage of disease at diagnosis, not receiving radiation therapy, and not undergoing surgical resection.

A population-based study using nomograms to predict overall and cancer-specific survival in HPV-associated CSCC.

Constructing and validating two nomograms to predict the overall survival (OS) and cancer-specific survival (CSS) in cutaneous squamous cell carcinoma (CSCC) correlated with human papillomavirus (HPV) infection was the main goal of this study. We constructed predictive models for OS and CSS incidence in HPV infection-associated CSCC using information from 2238 patients in the Surveillance, Epidemiology, and End Results (SEER) database and screened the variables by LASSO regression, Cox univariate regression, and Cox multifactorial regression models, which were calibrated and validated by internal and external cohorts. Finally, all patients were categorized into intermediate-risk, low-risk, and high-risk groups based on the optimal threshold calculated from the total score. Multivariate analysis showed that HPV infection status, marital status, tumor metastatic stage, surgical status, radiotherapy status, lymph node biopsy, local lymph node dissection, primary tumor status, and bone metastasis were risk factors for OS and CSS. The C index, the time-dependent area under the receiver-operating characteristic curve, and the column-line diagrams of the calibration plot were among the excellent-performance metrics that were effectively displayed. Moreover, the decision curve analysis of the two nomograms consistently revealed their favorable net benefits spanning 1, 2, and 3 years. In addition, the survival curves indicate that each of the two risk classification systems clearly differentiates high, medium, and low risk groups. These meticulously crafted nomograms stand poised to serve as indispensable instruments in clinical practice, empowering clinicians to adeptly communicate with patients regarding their prognostic outlook over the forthcoming 1, 2, and 3 years.

Risk for second primary ovarian cancer: a large population based on Surveillance, Epidemiology, and End Results database.

This study aims to evaluate the likelihood of developing a second primary ovarian cancer (OC) considering factors including age, race, and the types of initial malignancies encountered. This study employed a retrospective cohort approach, compiling data on individuals diagnosed with OC from the Surveillance, Epidemiology, and End Results (SEER) program databases spanning the years 1975 to 2019. The analysis used standardized incidence ratios (SIR) with 95% confidence intervals (CI) to determine the likelihood of developing OC. The result was further refined by categorizing the data based on patient age, race background, first primary cancer types, the time elapsed since the second primary cancer diagnosis, and radiotherapy treatment. A total of 1,536,151 patients with second primary cancer being OC were included. The SIR of the second primary OC was observed to be elevated among patients between the ages of 18 to 64 years (SIR: 1.09, 95% CI: 1.06-1.13). In contrast, for patients who were 65 years of age or older, the SIR for a second primary OC was found to be relatively lower (SIR: 0.87, 95% CI: 0.83-0.91). A lowering, however not statistically significant, of the SIR of the second primary OC in patients with white race was presented. Within 2 months to 1-year diagnosis interval, the SIR of the second primary OC was highest (SIR: 1.48, 95% CI: 1.37-1.61). Liver, gallbladder, intrahepatic, and other bile ducts (SIR: 2.00, 95% CI: 1.38-2.81), and breast cancer (SIR: 1.20, 95% CI: 1.15-1.25) had higher SIRs of second primary OC. This study identifies age, ethnicity, the time span between the diagnoses, and the types of initial cancers as factors correlated with the occurrence of a second primary OC. Our findings suggest that targeted surveillance should be considered for high-risk groups.

EPID-23. HISTORY OF TYPE III IMMUNE HYPERSENSITIVITY IMPROVES SURVIVAL IN GLIOBLASTOMA

Abstract Preexisting atopy, particularly allergic rhinitis, is consistently associated with decreased risk of glioma, and there is evidence that preexisting autoimmune conditions may also decrease risk. Glioblastoma is both locally and systemically immunosuppressive and, unlike many other forms of cancer, its initiation is not strongly linked with chronic inflammation. Therefore, history of immune hypersensitivity could be associated with improved anti-glioma immunosurveillance. We leveraged Surveillance, Epidemiology and End Results (SEER) data combined with Medicare claims to investigate the effect of preexisting immune hypersensitivities on overall survival of glioblastoma patients receiving resection, radiation, and temozolomide (standard of care, or SOC) from 2008-2019. Patients &amp;lt;66 years of age, enrolled in Medicare Advantage, not continuously enrolled in Medicare Part A/B, missing follow-up, reported by autopsy/death certificate only, or who did not receive surgery were excluded. Prior history of immune hypersensitivity (≥6 months prior to primary cancer diagnosis) was identified by ICD-9/ICD-10 codes. Treatment pattern was determined using ICD-9/ICD-10 and HCPCS/CPT codes. Conditions were classified into broad immune hypersensitivity types: type I (IgE-mediated, including atopy), type II (IgG- or IgM-mediated), type III (immune complex-mediated, including lupus and rheumatoid arthritis), and type IV (cell-mediated). Survival comparisons were made using Cox proportional hazard models adjusted for demographics, extent of resection, and Charlson comorbidity score (excluding immune conditions) to estimate hazard ratios, 95% confidence intervals, and p-values. Overall, 44% of 3,426 glioblastoma patients who received SOC had an immune hypersensitivity (type I: 33%, type II: 4%, type III: 8%, and type IV: 15%). These conditions were significantly more common in females (47% vs 41%, p&amp;lt;0.001). After adjustment, only type III immune sensitivity was associated with improved OS (HR=0.81, 95% CI:0.71-0.92, p=0.002). These results suggest that underlying immune-complex mediated hypersensitivity may improve treatment response and prognosis in glioblastoma, and that these pathways could potentially be exploited for therapy.

Sex differences in prognosis of primary bone cancer: a propensity score-matched study

Abstract Objectives Sex differences in survival in primary bone cancer have not been fully explored. Hence, this study was conducted to investigate the impact of sex on survival outcomes in patients with primary bone cancer. Methods The Surveillance, Epidemiology, and End Results (SEER)-17 database was used to identify patients with primary bone cancer. One-to-one propensity score matching (PSM) was employed to balance baseline characteristics. Kaplan-Meier curves and log-rank tests were used to evaluate differences in cancer-specific survival (CSS) and overall survival (OS) between sexes. Multivariate Cox regression analysis was performed to verify the independent effect of sex on survival, and sensitivity analysis was performed to determine the robustness of the results. Results A total of 8,791 patients were included, with 4,928 males (56.1 %) and 3,863 females (43.9 %), and a median follow-up time of 38 months. After PSM, 3,812 males and 3,812 females were included in the study, with balanced baseline characteristics between the groups. Post-PSM, females show significantly better CSS (HR=0.88, 95 % CI, 0.81–0.96, p=0.004) and OS (HR=0.87, 95 % CI, 0.81–0.94, p&lt;0.001) compared to males. In multivariable Cox regression, the female sex was identified as an independent protective factor for both CSS (HR=0.86, 95 % CI, 0.79–0.94, p&lt;0.001) and OS (HR=0.83, 95 % CI, 0.77–0.89, p&lt;0.001). Conclusions Based on the analysis of SEER data with a large sample size, this study revealed that female patients with primary bone cancer have significantly better survival compared to males.

The Demographic and Clinical Characteristics, Prognostic Factors, and Survival Outcomes of Head and Neck Carcinosarcoma: A SEER Database Analysis

Background: Head and neck carcinosarcoma (HNCS) is a rare and highly aggressive malignancy with limited research, resulting in an incomplete understanding of disease progression and a lack of reliable prognostic tools. This study aimed to retrospectively analyze the clinical characteristics and outcomes of HNCS patients using data from the Surveillance, Epidemiology, and End Results (SEER) database and to develop a nomogram to predict overall survival (OS) and cancer-specific survival (CSS). Methods: Patients diagnosed with HNCS from 1975 to 2020 were identified in the SEER database. Univariate and multivariate Cox regression analyses were conducted to identify independent prognostic indicators, with the optimal model selected using the minimal Akaike Information Criterion (AIC). The identified prognostic factors were incorporated into nomograms to predict OS and CSS. Model performance was assessed using the concordance index (C-index), area under the curve (AUC), calibration curves, and decision curve analysis (DCA). Survival curves were generated using Kaplan–Meier analysis and compared via the log-rank test. Results: A total of 152 HNCS patients were included, with 108 assigned to the training cohort and 44 to the validation cohort in a 7:3 ratio. Prognostic factors including age, primary tumor site, marital status, radiotherapy, chemotherapy, tumor size, pathological grade, and tumor stage were incorporated into the nomogram models. The models demonstrated strong predictive performance, with C-index values for OS and CSS of 0.757 and 0.779 in the training group, and 0.777 and 0.776 in the validation group, respectively. AUC values for predicting 3-, 5-, and 10-year OS were 0.662, 0.713, and 0.761, and for CSS the values were 0.726, 0.703, and 0.693. Kaplan–Meier analysis indicated significantly improved survival for patients with lower risk scores. The 3-, 5-, and 10-year OS rates for the entire cohort were 54.1%, 45.6%, and 35.1%, respectively, and the CSS rates were 62.9%, 57.5%, and 52.2%, respectively. Conclusions: This study provides validated nomograms for predicting OS and CSS in HNCS patients, offering a reliable tool to support clinical decision-making for this challenging malignancy. These nomograms enhance the ability to predict patient prognosis and personalize treatment strategies.

Individualised prediction of chemotherapy benefit in early-onset colorectal cancer

PurposesWhether patients with early-onset colorectal cancer (EOCRC) receive chemotherapy has been controversial, so our study aimed to screen patients with EOCRC who benefit from chemotherapy.MethodsA total of 2166 EOCRC patients were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Patients were divided into chemotherapy and non-chemotherapy groups, propensity score matching (PSM) was performed to balance the differences between the groups, and the Kaplan–Meier method was used to calculate the cancer-specific survival (CSS) of EOCRC patients. Multifactorial COX regression analysis was used to identify independent prognostic factors for CSS and to construct a nomogram for predicting CSS in EOCRC patients. The overall risk score was calculated based on Nomogram, and EOCRC patients were classified into high-risk and low-risk groups to assess further chemotherapy's therapeutic effect on patients with different risk stratification.ResultsBefore PSM, patients in the chemotherapy group had poorer CSS (p < 0.001). After PSM, there was no significant difference in patient CSS between the two groups (p = 0.057). Independent prognostic factors (Race, Grade, Pathology, AJCC.N, AJCC.M, CEA, Marital. Status) were screened according to multifactorial COX regression analyses and included in the Nomogram predicting CSS in EOCRC patients. A risk stratification system for EOCRC patients was further developed, and the results showed that chemotherapy had no significant effect on CSS in the low-risk group of patients, but in the high-risk group, chemotherapy significantly improved CSS in EOCRC patients.ConclusionsWe developed a clinical risk model by combining different risk factors, which can accurately screen those with high-risk EOCRC for benefit from chemotherapy. For low-risk EOCRC patients, our results did not observe a better survival benefit from chemotherapy, and more prospective studies are needed in the future to prove our conclusions.