Establishment and Validation of Prognostic Nomograms for Nonmetastatic Melanoma of the Limbs-A SEER-Based Study.

BACKGROUND: Malignant melanoma, a highly aggressive skin cancer, has remarkable incidence and mortality nowadays. This study aims to explore prognostic factors associated with nonmetastatic cutaneous melanoma of the limbs and to develop nomograms for predicting overall survival (OS) and cancer-specific survival (CSS). METHODS: The study cohort was derived from the Surveillance, Epidemiology, and End Results database. Univariate Cox regression, Lasso regression, and multivariate Cox regression analyses were conducted to identify prognostic factors and construct nomograms. The receiver operating characteristic (ROC) curve, time-dependent C-index, calibration curve, decision curve analysis (DCA) and Kaplan-Meier method were used to evaluate the accuracy and clinical applicability of the nomograms. RESULTS: A total of 15,606 patients were enrolled. Multivariate analysis identified several prognostic factors for OS and CSS including age, sex, histologic type, N stage, tumor thickness, depth of invasion, mitotic rate, ulceration, surgery of primary site, systemic therapy, race, and number of lymph nodes examined. A nomogram incorporating 12 independent predictors for OS was developed, with a C-index of 0.866 (95% confidence interval [CI]: 0.858-0.874) in the training cohort and 0.853 (95% CI: 0.839-0.867) in validation. For CSS, 10 independent predictors and one related factor were included, yielding a C-index of 0.913 (95% CI: 0.903-0.923) in the training cohort and 0.922 (95% CI: 0.908-0.936) in validation. The ROC curve, time-dependent C-index, calibration curve, DCA, and K-M plot demonstrated favorable discrimination, calibration, and clinical utility. CONCLUSION: The developed nomograms provide a precise and personalized predictive tool for risk management of patients with nonmetastatic limb melanoma.

Survival Difference of Colorectal Adenocarcinoma Among Racial and Ethnic Minority Groups: A SEER Database Study.

Despite advances in diagnosis and treatment, racial disparities continue to exist in colorectal cancer (CRC) survival. This study aims to characterize the CRC survival differences among racial and ethnic minority groups. The Surveillance, Epidemiology, and End Results (SEER) database was used to identify adults diagnosed with CRC from 2015 to 2019. Demographics, disease characteristics, surgical treatment, stages, and survival data for individuals who are Hispanic, Black, Southeast Asian, Chinese, American Indian and Alaskan Native (AIAN), Asian Indian and Pakistani (AIP), and Native Hawaiian and Other Pacific Islanders (NHOPI) were extracted. Survival analysis was done using the Kaplan-Meier survival curve. Multivariate analysis was done with the Cox proportional hazard model. There were 40 091 individuals with CRC. NHOPI had the youngest median age of 59 years, while Chinese individuals had the oldest median age of 65 years. From the total sample of their respective subgroups, 43.8% of Black patients and 36.7% of AIAN patients had a median household income of <$60 000, while 55.3% of Southeast Asian patients, 59.7% of Chinese patients, 55.8% of AIP patients, and 65.6% of NHOPI patient had a median household income >$70 000. The 1-year survival rate was lower for patients who were Hispanic (62.0%), Black (60.9%), and AIAN (63.1%). Even after multivariate analysis, Black patients had a significant hazard ratio (HR) of 1.21 (95% confidence interval [95% CI]: 1.05-1.38), while AIP had a HR of 0.68 (95% CI 0.55-0.84), compared to AIAN. Other significant variables that were linked with survival included older age, advanced stage of CRC, a median household income <$60 000, male sex, no surgery, subtotal colectomy/hemicolectomy, and total colectomy. Further studies are needed to elucidate the specific causes of these differences and create appropriate strategies to reduce this survival disparity.

Geographically weighted accelerated failure time model for spatial survival data: application to ovarian cancer survival data in New Jersey.

BACKGROUND: In large multiregional cohort studies, survival data is often collected at small geographical levels (such as counties) and aggregated at larger levels, leading to correlated patterns that are associated with location. Traditional studies typically analyze such data globally or locally by region, often neglecting the spatial information inherent in the data, which can introduce bias in effect estimates and potentially reduce statistical power. METHOD: We propose a Geographically Weighted Accelerated Failure Time Model for spatial survival data to investigate spatial heterogeneity. We establish a weighting scheme and bandwidth selection based on quasi-likelihood information criteria. Theoretical properties of the proposed estimators are thoroughly examined. To demonstrate the efficacy of the model in various scenarios, we conduct a simulation study with different sample sizes and adherence to the proportional hazards assumption or not. Additionally, we apply the proposed method to analyze ovarian cancer survival data from the Surveillance, Epidemiology, and End Results cancer registry in the state of New Jersey. RESULTS: Our simulation results indicate that the proposed model exhibits superior performance in terms of four measurements compared to existing methods, including the geographically weighted Cox model, when the proportional hazards assumption is violated. Furthermore, in scenarios where the sample size per location is 20-25, the simulation data failed to fit the local model, while our proposed model still demonstrates satisfactory performance. In the empirical study, we identify clear spatial variations in the effects of all three covariates. CONCLUSION: Our proposed model offers a novel approach to exploring spatial heterogeneity of survival data compared to global and local models, providing an alternative to geographically weighted Cox regression when the proportional hazards assumption is not met. It addresses the issue of certain counties' survival data being unable to fit the model due to limited samples, particularly in the context of rare diseases.

Prognostic factors of cutaneous soft tissue sarcomas in children: a SEER population-based study.

This study aims to analyze the clinicopathological characteristics and survival outcomes of cutaneous soft tissue sarcomas (CSTS) in children. We selected pediatric cases of CSTS diagnosed between 2000 and 2019 from the Surveillance, Epidemiology, and End Results (SEER) database. Survival rates were calculated using Kaplan-Meier methods. We performed univariate analyses with the log-rank test and multivariate survival analyses using Cox proportional-hazards models to determine factors affecting overall survival (OS). Additionally, we constructed a predictive nomogram based on the outcomes of the Cox regression. A total of 148 pediatric patients with CSTS were reviewed. The median age at diagnosis was 13 years (range: 0-18 years). Prognostically, tumors located on the extremities showed better outcomes compared to those on the head, neck, or trunk. Among the histological types, angiosarcoma had the lowest five-year survival rate at 51.3%, which was substantially lower compared to fibrous histiocytoma and leiomyosarcoma. Cox regression analysis highlighted surgical intervention as the only significant independent prognostic factor for OS, with an increased risk of mortality observed in patients not undergoing surgery. Additionally, patients with distant-stage disease exhibited significantly lower survival rates than those with localized conditions. Pediatric CSTS represents a diverse and infrequent group of tumors, predominantly fibrous histiocytoma and leiomyosarcoma. Surgery was identified as the crucial determinant of survival, underscoring its role in effectively managing these patients.

Prognostic Nomograms for Patients With NF-Pan-NET After Pancreatectomy: A Retrospective Analysis Based on SEER Database.

AIMS: Surgical resection is the primary treatment option for patients diagnosed with nonfunctional pancreatic neuroendocrine tumors (NF-Pan-NETs). However, the postoperative prognostic evaluation for NF-Pan-NET patients remains obscure. This study aimed to construct an efficient model to predict the prognosis of NF-Pan-NET patients who have received surgical resection. METHODS: NF-Pan-NET patients after pancreatectomy were retrieved from the SEER database for the period of 2010 to 2019. A total of 2844 patients with NF-Pan-NET from SEER database were included in our study. After careful screening, six clinicopathological variables including age, grade, AJCC T stage, AJCC N stage, AJCC M stage, and chemotherapy were selected to develop nomograms to predict overall survival (OS) and cancer-specific survival (CSS) respectively of the patients. RESULTS: The novel models demonstrated high accuracy and discrimination in prognosticating resected NF-Pan-NET through various validation methods. Furthermore, the risk subgroups classified by the newly developed risk stratification systems based on the nomograms exhibited significant differences in both OS and CSS, surpassing the efficacy of the AJCC 8th TNM staging system. Novel nomograms and corresponding risk classification systems were developed to predict OS and CSS in patients with NF-Pan-NET after pancreatectomy. CONCLUSION: The models demonstrated superior performance compared to traditional staging systems, providing clinicians with more accurate and personalized guidance for postoperative surveillance and treatment.

Demographics, Histopathology, and Treatment Outcomes of Squamous Cell Carcinoma of the Prostate.

BACKGROUND: Squamous cell carcinoma of the prostate (SCCP) is a neoplasm that comprises fewer than 1% of all primary prostate cancer diagnoses. Given its rarity, there is a paucity of data regarding the treatment of this disease. The limited literature points to the potential of local therapy in conjunction with chemotherapy to improve patient mortality. METHODS: Using the National Cancer Initiative's Surveillance, Epidemiology, and End Results (SEER) database, a retrospective review of patients diagnosed with primary SCCP between 2000 and 2018 was performed. Patient demographics, tumor characteristics, and patient outcomes based on treatment modality were analyzed. Univariate and survival analyses were conducted with p < 0.05 indicating statistical significance. RESULTS: A total of 66 patients were identified. Five-year overall survival (5y OS) was 24%; mean and median survival were 2.2 years (1.8, 2.7) and 1.2 years (0.3, 2.1), respectively. Patients with Grade I or Grade II disease had an increased 5y OS of 55% (27%, 83%). In comparison, 5y OS was 13% (-2%, 29%) for patients with Grade III and Grade IV disease (p = 0.017). Analysis of 5y OS based on disease histology revealed patients with papillary SCC had a 5y OS of 50% [9.2%, 91%], compared to 21% [9%, 34%] for patients with SCC, not otherwise specified and 0% for those with lymphoepithelial carcinoma (p = 0.048). Analysis of 5y OS stratified by treatment modality revealed no statistically significant change with any treatment (surgery, radiotherapy, and chemotherapy). No difference in 5y OS was seen between those treated with radical prostatectomy versus external beam radiation therapy. CONCLUSIONS: The literature on SCCP remains sparse; the rarity of this disease limits analysis. While the investigation undertaken in this paper does not find any change in 5y OS regardless of treatment modality, the variation in 5y OS based on histologic classification of SCCP points to a potential route for the future treatment of this disease.

Colorectal Leiomyosarcoma: Demographics Patterns, Treatment Characteristics, and Survival Analysis in the U.S. Population.

BACKGROUND: Colorectal leiomyosarcoma (CR-LMS) is a rare neoplasm arising from smooth muscle cells. It accounts for less than 0.1% of all colorectal malignancies. In this population-based study, we aim to understand the demographics, treatment characteristics, and pathologic factors associated with survival in CR-LMS. METHODS: Data from the SEER Program (2000-2018) were analyzed using SEER*Stat and SPSS. Statistical methods included descriptive analysis, Kaplan-Meier survival curves, log-rank tests, and Cox proportional hazards regression to assess the impact of various factors on disease-specific and overall survival. RESULTS: A total of 191 cases of CR-LMS were identified. Most patients were 60-69 years of age (median: 64 years) and Caucasian (78%). There was nearly the same distribution in sex (M:F ratio; 1:1.2). The overall 5-year observed survival was 50.3% (95% C.I., 46.3-54.2). The 5-year disease-specific survival (DSS) was 66.1% (95% C.I., 62.0-70.1). The 5-year overall survival after resection was 60.8% (95% C.I., 56.3-65.3). Multivariable analysis identified grades III and IV (p = 0.028) as negative predictors of overall survival. Regional spread and distant stage are negative predictors of overall survival (p < 0.01). CONCLUSION: Our data reveals that colorectal leiomyosarcoma (CR-LMS) often presents in patients around 64 years old with advanced stages and poor differentiation. Key adverse prognostic factors include older age, high tumor grade, large tumor size, and distant metastases, with surgical resection showing the best survival outcomes. To improve outcomes, further research and consolidation of data are essential for developing targeted therapies and comprehensive guidelines.

Survival Outcomes and Prognostic Factors in Therapy-Related Acute Myeloid Leukemia: A SEER Database Study, 2000-2020.

INTRODUCTION: With advances in therapeutics and longer survival across different cancer spectrums, the incidence of therapy-related acute myeloid leukemia (tAML) has continued to rise. This study aims to evaluate the trend of survival outcomes and their association with sociodemographic factors in tAML over the last 20 years. METHODS: We identified tAML patients between 2000 and 2020 from the Surveillance, Epidemiology, and End Results database. Patients were divided into 4 age groups: 18-39, 40-59, 60-69, and >= 70 years, and 4 diagnostic periods: 2000-2005, 2006-2010, 2011-2015, and 2016-2020. Overall survival (OS) was compared using Kaplan Meier and log-rank methods. RESULTS: The 1-year (and 5-year) OS in patients with tAML was 59.3% (33.7%), 48.2% (24.8%), 37.2% (11.1%), and 32.9% (5.5%) in age groups 18-39, 40-59, 60-69, and >=70 years, respectively. The 1-year (and 5-year) OS based on the year of diagnosis was 20.9% (13.2%), 36.8% (15.2%), 41.9% (13.88%), and 40.4% (not reached) for 2000-2005, 2006-2010, 2011-2015, and 2016-2020 respectively. Among the youngest cohort aged 18-39 years, 1-year OS was 35.7%, 57.7%, 66.7%, and 59.6%, respectively, in 4 diagnostic periods, whereas 1-year OS was 10.5%, 23.9%, 32.2%, and 36.9%, respectively, in the oldest cohort aged >=70 years. Age, year of diagnosis, and geographic location were independent prognostic markers of OS. CONCLUSION: Our study demonstrates a significant improvement in the 1-year OS of tAML patients over the last decade, but the long-term prognosis remains dismal. Older patients continue to show improved survival in recent years with the addition of newer intensive and nonintensive options.

Trends in Mortality for Anaplastic Thyroid Cancer: Have We Made Progress?

INTRODUCTION: Anaplastic thyroid cancer (ATC) has one of the highest mortality rates of all human malignancies, accounting for two-thirds of all thyroid cancer deaths. Despite multimodal treatment, ATC still has a reported median survival period of 6 mo. Recent single-center studies have reported improved survival with the approval of new treatments for ATC. In this study, we sought to investigate whether the approval of new treatments and use of multimodal treatments was associated with reduced risk of mortality over time nationally. METHODS: Eight hundred and seventy four patients in the National Cancer Institute's Surveillance, Epidemiology, and End Results database that were diagnosed with ATC from 1990 to 2020 were included in this study. Cox proportional hazards models were used to assess the change in 2-y survival over time and to identify characteristics associated with survival. Overall survival (OS) and cancer specific survival (CSS) were both evaluated. RESULTS: The OS within 2 y of diagnosis was 14% and the CSS was 19%. For every 3-y increase in diagnosis year from 1990 to 2020, there was no significant change in the CSS (adjusted hazard ratio [95% confidence interval]: 0.98 [0.94, 1.01]). Patients who received treatment (surgery, chemotherapy, and/or radiation) had an increased CSS (adjusted hazard ratio [95% confidence interval]: 0.42 [0.32, 0.55]). CONCLUSIONS: We observed no significant change in OS or CSS after adjusting for confounders by year of diagnosis. Though receiving treatment was associated with increased CSS, more effective treatments are needed in the future to increase survival time in patients with ATC.

Changes in Incidence of Cirrhotic and Noncirrhotic Hepatocellular Carcinoma in the United States.

INTRODUCTION: Hepatocellular carcinoma (HCC) occurs most often in a background of cirrhosis. Patients with noncirrhotic HCC represent a distinct population, which has been characterized in single-center studies, but has not been fully evaluated on a population level in the United States. MATERIALS AND METHODS: HCC cases from Surveillance, Epidemiology, and End-Results diagnosed between 2000 and 2020 were categorized as cirrhotic or noncirrhotic. Clinical and pathologic factors, age-adjusted incidence rates (AAIR), and the overall HCC-specific survival were compared between groups. RESULTS: There were 18,592 patients with cirrhosis (80.4%) and 4545 without (19.6%). AAIRs for noncirrhotic HCC remained relatively unchanged from 2010 to 2020, with a mean incidence of 0.35 per 100,000. The AAIR for cirrhotic HCC declined from 1.59 to 0.85 per 100,000 during the same period. Patients with cirrhosis were younger (median age 62 versus 65 y, P < 0.001). Patients without cirrhosis, compared to those with cirrhosis, were less likely to have elevated alpha fetoprotein (53.9% versus 62.0%, P < 0.001), had larger tumors (median tumor size 5.0 versus 3.5 cm, P < 0.001), presented more frequently with localized disease (59.9% versus 55.8%, P < 0.001), were more likely to undergo surgery (OR 2.21, 95% CI 2.07-2.36), and had better HCC-specific survival (median 40 versus 27 mo, P < 0.001). CONCLUSIONS: The relative increase in the proportion of noncirrhotic HCC in the Untied States may be due to a decline in the incidence of cirrhotic HCC. Patients with noncirrhotic HCC have larger tumors, are more likely to undergo surgical resection, and have improved cancer-specific survival.

A Bayesian competing risk analysis of renal cancer patients based on SEER database.

BACKGROUND: Renal cell carcinoma (RCC) remains a global health concern due to its poor survival rate. This study aimed to investigate the influence of medical determinants and socioeconomic status on survival outcomes of RCC patients. We analyzed the survival data of 41,563 RCC patients recorded under the Surveillance, Epidemiology, and End Results (SEER) program from 2012 to 2020. METHODS: We employed a competing risk model, assuming lifetime of RCC patients under various risks follows Chen distribution. This model accounts for uncertainty related to survival time as well as causes of death, including missing cause of death. For model analysis, we utilized Bayesian inference and obtained the estimate of various key parameters such as cumulative incidence function (CIF) and cause-specific hazard. Additionally, we performed Bayesian hypothesis testing to assess the impact of multiple factors on the survival time of RCC patients. RESULTS: Our findings revealed that the survival time of RCC patients is significantly influenced by gender, income, marital status, chemotherapy, tumor size, and laterality. However, we observed no significant effect of race and origin on patient's survival time. The CIF plots indicated a number of important distinctions in incidence of causes of death corresponding to factors income, marital status, race, chemotherapy, and tumor size. CONCLUSIONS: The study highlights the impact of various medical and socioeconomic factors on survival time of RCC patients. Moreover, it also demonstrates the utility of competing risk model for survival analysis of RCC patients under Bayesian paradigm. This model provides a robust and flexible framework to deal with missing data, which can be particularly useful in real-life situations where patients information might be incomplete.

Incidence of prostate, colorectal and male breast cancers in relation with statins and testosterone replacement therapy: SEER-Medicare 2007-2015.

INTRODUCTION: Statins and testosterone replacement therapy (TTh) have been inconsistently associated with a reduced risk of hormone-related cancers (HRCs, prostate [PCa], colorectal [CRC], and male breast cancers [BrCa]). Yet, the joint association of statins and TTh with the incidence of these cancers, and whether these associations vary by race, remains poorly understood. The objective of this retrospective cohort study is to examine the independent and joint effects of pre-diagnostic use of statins and TTh on the risk of HRCs, including PCa, CRC, and male BrCa. MATERIALS: and Methods: In 105,690 men (≥65 yrs) identified using the SEER-Medicare 2007-2015 data, we identified 82,578 White and 10,256 Black men. Pre-diagnostic prescription of statins and TTh was ascertained for this analysis and categorized into four groups (Neither users, statins alone, TTh alone and Dual users). Multivariable Time-varying Cox proportional hazards and Accelerated Failure Time (AFT) models were performed. RESULTS: We found inverse joint associations of statins and TTh with incident HRCs before (aHR: 0.39; 95 % CI: 0.35-0.44) and after 3 years of follow-up (aHR: 0.74; 95 % CI: 0.67-0.82). This included a lower risk for advanced stage HRC (only <3 years follow-up). Similar joint associations were identified with incident PCa, aggressive PCa, incident CRC, and its specific right- and left-sided CRC (only <3 years follow-up). In general, the inverse associations persisted among White (mainly <3 years follow-up) and Black men (high-grade HRC and <3 years follow-up). Findings from the AFT analysis were similar. DISCUSSION: Pre-diagnostic use of statins and TTh were, independently and jointly, associated with reduced risks of HRC and specific cancer sites at three years of follow-up overall, and among White and Black men. Greatest associations of HRCs risk reduction were observed among dual users (statins plus TTh). Further studies are needed to validate these findings, including larger samples of Black men, and male BrCa sites.

Description of census-tract-level social determinants of health in cancer surveillance data.

BACKGROUND: Disparities in cancer incidence, stage at diagnosis, and mortality persist by race, ethnicity, and many other social determinants, such as census-tract-level socioeconomic status (SES), poverty, and rurality. Census-tract-level measures of these determinants are useful for analyzing trends in cancer disparities. METHODS: The purpose of this paper was to demonstrate the availability of the Surveillance, Epidemiology, and End Results Program's specialized census-tract-level dataset and provide basic descriptive cancer incidence, stage at diagnosis, and survival for 8 cancer sites, which can be screened regularly or associated with infectious agents. We present these analyses according to several census-tract-level measures, including the newly available persistent poverty as well as SES quintile, rurality, and race and ethnicity. RESULTS: Census tracts with persistent poverty and low SES had higher cancer incidence rates (except for breast and prostate cancer), higher percentages of cases diagnosed with regional or distant-stage disease, and lower survival than non-persistent-poverty and higher-SES tracts. Outcomes varied by cancer site when analyzing based on rurality as well as race and ethnicity. Analyses stratified by multiple determinants showed unique patterns of outcomes, which bear further investigation. CONCLUSIONS: This article introduces the Surveillance, Epidemiology, and End Results specialized dataset, which contains census-tract-level social determinants measures, including persistent poverty, rurality, SES quintile, and race and ethnicity. We demonstrate the capacity of these variables for use in producing trends and analyses focusing on cancer health disparities. Analyses may inform interventions and policy changes that improve cancer outcomes among populations living in disadvantaged areas, such as persistent-poverty tracts.

Development of a prognostic model for patients with nodular melanoma of the lower extremities: a study based on the SEER database.

Lower extremity nodular melanoma (NM) is a common malignant tumor with a poor prognosis. We aims to identify the prognostic factors and develop a nomogram model to predict overall survival (OS) in patients with lower extremity NM. A total of 746 patients with lower extremity NM were selected and randomly divided into a training set (522 cases) and a validation set (224 cases) from the Surveillance, Epidemiology, and End Results(SEER) database. The training set underwent univariate and multivariate Cox regression analyses to identify independent prognostic factors associated with patient outcomes, and to develop a nomogram model. The effectiveness of the nomogram was subsequently validated using the validation set. Multivariable Cox regression analysis of the training set indicated that age, ulceration, radiotherapy, chemotherapy, primary site of first malignant tumor, and Breslow thickness were independent variables associated with OS. In the training set, the area under the curve (AUC) of the nomogram for predicting 3-year and 5-year OS was 0.796 and 0.811, respectively. In the validation set, the AUC for predicting 3-year and 5-year OS was 0.694 and 0.702, respectively. The Harrell's C-index for the training set and validation set were 0.754 (95% CI: 0.721-0.787) and 0.670 (95% CI: 0.607-0.733), respectively. Calibration curves for both training and validation sets showed good agreement. In this study, we develop and validate a nomogram to predict OS in patients with lower extremity NM. The nomogram demonstrated reasonable reliability and clinical applicability. Nomograms are important tools assessing prognosis and aiding clinical decision-making.

Assessment of Treatment Sequence in Patients With Stage III Breast Cancer.

INTRODUCTION: Stage III breast cancer is defined as locally advanced breast cancer and is treated with curative intent. Historically, overall survival (OS) did not differ based on treatment sequence (neoadjuvant chemotherapy [NAC] followed by surgery versus surgery followed by chemotherapy). Given recent advancements, we examined if treatment sequence may be associated with improved OS in a contemporary cohort of patients with stage III breast cancer. METHODS: Patients aged 18-80 years with prognostic stage III breast cancer who received chemotherapy and surgery were selected from the Surveillance, Epidemiology, and End Results database. Patients were stratified by treatment sequence (NAC versus surgery first). Unadjusted OS and breast cancer-specific survival (BCSS) were estimated using the Kaplan-Meier method and compared with log-rank tests. Cox proportional hazards models were used to estimate the association of treatment sequence with OS and BCSS after adjustment for selected covariates. RESULTS: The study included 26,573 patients; median follow-up was 62.0 months (95% confidence interval [CI] 61.0-63.0). Patients receiving NAC had a worse OS and BCSS compared to those who underwent surgery first (5-year OS rates 0.66 versus 0.73; 5-year BCSS rates 0.70 versus 0.77; both log-rank P < 0.001). After adjustment for tumor subtype, receipt of NAC (versus surgery first) remained associated with a worse OS (hazard ratio 1.27, 95% CI 1.2-1.34, P < 0.001) and BCSS (hazard ratio 1.35, 95% CI 1.27-1.43, P < 0.001). CONCLUSIONS: Based on data from patients treated largely before 2020, undergoing surgery first may be associated with improved survival, even after adjustment for known covariates including tumor subtype. These findings may inform treatment when caring for patients with operable, locally advanced breast cancer.

Survival in patients with rheumatoid arthritis and early breast cancer treated with tumor necrosis factor inhibitors.

BACKGROUND: There have been concerns about the use of tumor necrosis factor inhibitors (TNFi) for autoimmune disease in patients with recently diagnosed cancer. We assessed the survival of patients with rheumatoid arthritis (RA) and newly diagnosed early breast cancer (BC) treated with TNFi in the first two years after BC diagnosis. METHODS: We identified patients in two datasets: (1) Optum's de-identified Clinformatics® Data Mart Database (CDM), (2) Surveillance, Epidemiology, and End Results program (SEER) and Texas Cancer Registry (TCR) Medicare-linked cohort. We grouped patients according to whether they received TNFi, conventional synthetic disease-modifying antirheumatic drugs (csDMARDs) only, or no DMARDs within 2 years after BC. Outcomes were overall survival (OS) and BC-specific survival (BCSS). We conducted landmark analyses at years 1 and 2, with multivariable Cox regressions using propensity scores for adjustment. RESULTS: In the first year after BC, 165/970 (17.0%) and 201/1246 (16.1%) patients received TNFi in CDM and SEER/TCR-Medicare respectively. In the 1 year landmark, no significant differences in OS were observed between patients treated with TNFi and patients treated with csDMARDs only in CDM (hazard ratio [HR] = 0.77, 95% confidence interval [CI] 0.42-1.40) or SEER/TCR-Medicare (HR = 0.84, 95% CI 0.54-1.31). BCSS (SEER/TCR-Medicare) was better in patients receiving TNFi than in those receiving csDMARDs only (HR = 0.28, 95% CI 0.08-0.98). In CDM, glucocorticoid therapy had worse OS than those without glucocorticoids (HR = 2.18, 95% CI 1.13-4.18). This was also observed in SEER/TCR-Medicare (not statistically significant). Similar results were observed for the 2 year landmark. CONCLUSIONS: TNFi treatment during the first two years after early BC was not associated with worse survival.

Pelvic organ-preserving radical cystectomy versus standard radical cystectomy in female patients diagnosed with bladder cancer.

BACKGROUND: Pelvic organ-preserving radical cystectomy (POPRC) has been reported to result in a better postoperative quality of life in female with bladder cancer compared to standard radical cystectomy (SRC). However, its oncological outcomes remain a concern. PATIENTS AND METHODS: Female patients with bladder cancer who underwent POPRC or SRC were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Logistic regression was used to identify predictors of POPRC usage. To avoid the potential impact of baseline differences between groups on survival, a 1:2 propensity score matching (PSM) was implemented. After that, Kaplan-Meier curves and Log-rank tests were used to determine the significance of overall survival (OS) differences between patients in the SRC group and POPRC group. Finally, subgroup analysis based on predetermined indicators was performed. RESULTS: A total of 2193 patients were included with a median follow-up of 53 months, of whom 233 (10.6%) received POPRC and 1960 (89.4%) received SRC. No definitive predictors of POPRC were identified. Before PSM, POPRC resulted in comparable OS to SRC (HR = 1.09, p = 0.309), while after PSM, POPRC was associated with significantly worse OS (HR = 1.23, p = 0.038). In subgroup analyses, POPRC led to non-inferior OS (HR = 1.18, 95%CI 0.71-1.95, p = 0.531) in patients with non-muscle invasive bladder cancer (NMIBC) and T2 patients (HR = 1.07, p = 0.669), but significantly worse OS in T3 patients (HR = 1.41, p = 0.02). CONCLUSION: Currently, patients undergoing POPRC have not undergone strict screening, and candidates for POPRC should have more stringent criteria in the future to achieve satisfactory oncological outcomes. However, flaws in the study make more evidence needed to support our findings.

History of the Surveillance, Epidemiology, and End Results (SEER) Program.

The Surveillance, Epidemiology, and End Results (SEER) Program established in 1973 was the first laboratory for experimenting with new methods for cancer data collection and translating the data into population-based cancer statistics. The SEER Program staff have been instrumental in the development of the International Classification of Disease-Oncology and successfully implemented the routine collection of anatomic and prognostic cancer stage at diagnosis. Currently the program consists of 21 central registries that generate cancer statistics covering more than 48% of the US population and an additional 10 research support registries contributing to certain research projects, such as the National Childhood Cancer Registry. In parallel with the geographical expansion, the program built an architecture of methods and tools for population-based cancer statistics, with SEER*Explorer as the most recent online tool for descriptive statistics. In addition, SEER releases annual updates for a comprehensive data product line, which includes SEER*Stat databases with an annual caseload of more than 800 000 incident cases. Furthermore, the program developed a full suite of analytical applications for population-based cancer statistics that include Joinpoint (regression-based trend analysis), DevCan (risk of diagnosis and death), CanSurv (survival models), and ComPrev and PrejPrev (cancer prevalence), among others. The future of the SEER Program is closely aligned to the overall goals of the "war on cancer." The program aims to release longitudinal treatment data coupled with a comprehensive genomic characterization of cancers with a declared goal of decreasing the cancer burden and disparities across a wide spectrum of diseases and communities.

Landscape analysis of environmental data sources for linkage with SEER cancer patients database.

One of the challenges associated with understanding environmental impacts on cancer risk and outcomes is estimating potential exposures of individuals diagnosed with cancer to adverse environmental conditions over the life course. Historically, this has been partly due to the lack of reliable measures of cancer patients' potential environmental exposures before a cancer diagnosis. The emerging sources of cancer-related spatiotemporal environmental data and residential history information, coupled with novel technologies for data extraction and linkage, present an opportunity to integrate these data into the existing cancer surveillance data infrastructure, thereby facilitating more comprehensive assessment of cancer risk and outcomes. In this paper, we performed a landscape analysis of the available environmental data sources that could be linked to historical residential address information of cancer patients' records collected by the National Cancer Institute's Surveillance, Epidemiology, and End Results Program. The objective is to enable researchers to use these data to assess potential exposures at the time of cancer initiation through the time of diagnosis and even after diagnosis. The paper addresses the challenges associated with data collection and completeness at various spatial and temporal scales, as well as opportunities and directions for future research.