Developing and validating a nomogram for penile cancer survival: A comprehensive study based on SEER and Chinese data.

OBJECTIVE: The primary aim of this study was to create a nomogram for predicting survival outcomes in penile cancer patients, utilizing data from the Surveillance, Epidemiology, and End Results (SEER) and a Chinese organization. METHODS: Our study involved a cohort of 5744 patients diagnosed with penile cancer from the SEER database, spanning from 2004 to 2019. In addition, 103 patients with penile cancer from Sun Yat-sen Memorial Hospital of Sun Yat-sen University were included during the same period. Based on the results of regression analysis, a nomogram is constructed and validated internally and externally. The predictive performance of the model was evaluated by concordance index (c-index), area under the curve, decision curve analysis, and calibration curve, in internal and external datasets. Finally, the prediction efficiency is compared with the TNM staging model. RESULTS: A total of 3154 penile patients were randomly divided into the training group and the internal validation group at a ratio of 2:1. Nine independent risk factors were identified, including age, race, marital status, tumor grade, histology, TNM stage, and the surgical approach. Based on these factors, a nomogram was constructed to predict OS. The nomogram demonstrated relatively better consistency, predictive accuracy, and clinical relevance, with a c-index over 0.73 (in the training cohort, the validation cohort, and externally validation cohort.) These evaluation indexes are far better than the TNM staging system. CONCLUSION: Penile cancer, often overlooked in research, has lacked detailed investigative focus and guidelines. This study stands as the first to validate penile cancer prognosis using extensive data from the SEER database, supplemented by data from our own institution. Our findings equip surgeons with an essential tool to predict the prognosis of penile cancer better suited than TNM, thereby enhancing clinical decision-making processes.

Conditional survival analysis and real-time prognosis prediction in stage III T3-T4 colon cancer patients after surgical resection: a SEER database analysis.

BACKGROUND: Conditional survival (CS) takes into consideration the duration of survival post-surgery and can provide valuable additional insights. The aim of this study was to investigate the risk factors associated with reduced one-year postoperative conditional survival in patients diagnosed with stage III T3-T4 colon cancer and real-time prognosis prediction. Furthermore, we aim to develop pertinent nomograms and predictive models. METHODS: Clinical data and survival outcomes of patients diagnosed with stage III T3-T4 colon cancer were obtained from the Surveillance, Epidemiology, and End Results (SEER) database, covering the period from 2010 to 2019. Patients were divided into training and validation cohorts at a ratio of 7:3. The training set consisted of a total of 11,386 patients for conditional overall survival (cOS) and 11,800 patients for conditional cancer-specific survival (cCSS), while the validation set comprised 4876 patients for cOS and 5055 patients for cCSS. Univariate and multivariate Cox regression analyses were employed to identify independent risk factors influencing one-year postoperative cOS and cCSS. Subsequently, predictive nomograms for cOS and cCSS at 2-year, 3-year, 4-year, and 5-year intervals were constructed based on the identified prognostic factors. The performance of these nomograms was rigorously assessed through metrics including the concordance index (C-index), calibration curves, and the area under curve (AUC) derived from the receiver operating characteristic (ROC) analysis. Clinical utility was further evaluated using decision curve analysis (DCA). RESULTS: A total of 18,190 patients diagnosed with stage III T3-T4 colon cancer were included in this study. Independent risk factors for one-year postoperative cOS and cCSS included age, pT stage, pN stage, pretreatment carcinoembryonic antigen (CEA) levels, receipt of chemotherapy, perineural invasion (PNI), presence of tumor deposits, the number of harvested lymph nodes, and marital status. Sex and tumor site were significantly associated with one-year postoperative cOS, while radiation therapy was notably associated with one-year postoperative cCSS. In the training cohort, the developed nomogram demonstrated a C-index of 0.701 (95% CI, 0.711-0.691) for predicting one-year postoperative cOS and 0.701 (95% CI, 0.713-0.689) for one-year postoperative cCSS. Following validation, the C-index remained robust at 0.707 (95% CI, 0.721-0.693) for one-year postoperative cOS and 0.700 (95% CI, 0.716-0.684) for one-year postoperative cCSS. ROC and calibration curves provided evidence of the model's stability and reliability. Furthermore, DCA underscored the nomogram's superior clinical utility. CONCLUSIONS: Our study developed nomograms and predictive models for postoperative stage III survival in T3-T4 colon cancer with the aim of accurately estimating conditional survival. Survival bias in our analyses may lead to overestimation of survival outcomes, which may limit the applicability of our findings.

Patterns of Care for Medicare Beneficiaries With Metastatic Prostate Cancer.

INTRODUCTION: Therapeutic options for men with metastatic prostate cancer have increased in the past decade. We studied recent treatment patterns for men with metastatic prostate cancer and how treatment patterns have changed over time. METHODS: Using the Surveillance, Epidemiology, and End Results‒Medicare database, we identified fee-for-service Medicare beneficiaries who either were diagnosed with metastatic prostate cancer or developed metastases following diagnosis, as indicated by the presence of claims with diagnoses codes for metastatic disease, between 2007 and 2017. We evaluated treatment patterns using claims. RESULTS: We identified 29,800 men with metastatic disease, of whom 4721 (18.8%) had metastatic disease at their initial diagnosis. The mean age was 77 years, and 77.9% of patients were non-Hispanic White. The proportion receiving antineoplastic agents within 3 years of the index date increased over time (from 9.7% in 2007 to 25.9% in 2017; P < .001). Opioid use within 3 years of prostate cancer diagnosis was stable during 2007 to 2013 (around 73%) but decreased through 2017 to 65.5% (P < .001). Patients diagnosed during 2015 to 2017 had longer median survival (32.6 months) compared to those diagnosed during 2007 to 2010 (26.6 months; P < .001). CONCLUSIONS: Most metastatic prostate cancer patients do not receive life-prolonging antineoplastic therapies. Improved adoption of effective cancer therapies when appropriate may increase length and quality of survival among metastatic prostate cancer patients.

Development and validation of prognostic nomographs for patients with cervical cancer: SEER-based Asian population study.

To develop and validate a nomograph to predict the long-term survival probability of cervical cancer (CC) patients in Asia, Surveillance, Epidemiology, and End Results (SEER) were used to collect information about CC patients in Asia. The patient data were randomly sampled and divided into a training group and a validation group by 7:3. Least absolute shrinkage and selection operator (LASSO) regression was used to screen key indicators, and multivariate Cox regression model was used to establish a prognostic risk prediction model for CC patients. The receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were adopted to comprehensively evaluate the nomogram model. LASSO regression and multivariate Cox proportional hazards model analysis showed that age, American Joint Committee on Cancer (AJCC) Stage, AJCC T, tumor size, and surgery were independent risk factors for prognosis. The ROC curve results proved that the area under curve (AUC) values of the training group in 3 and 5 years were 0.837 and 0.818, The AUC values of the validation group in 3 and 5 years were 0.796 and 0.783. DCA showed that the 3- and 5-year overall survival (OS) nomograms had good clinical potential value. The nomogram model developed in this study can effectively predict the prognosis of Asian patients with CC, and the risk stratification system based on this nomogram prediction model has some clinical value for discriminating high-risk patients.

Epidemiological characteristics and influencing factors of acute leukemia in children and adolescents and adults: a large population-based study.

OBJECTIVE: To assess the epidemiological characteristics and prognostic factors of acute leukemia (AL) in children and adolescents, and make comparisons between pediatric and adult patients. METHODS: This retrospective cohort study enrolled AL patients from the Surveillance, Epidemiology, and End Results (SEER) 1975-2016. OS in children and adolescents and adults with AL was compared and analyzed separately by age and AL subtype. RESULTS: Totally 61,694 AL patients were identified, with 45,411 (73.6%) adults and 16,283 (26.4%) children and adolescents. From 2000 to 2016, the incidence rates of AL [annual percent changes (APC) = 1.2, 95%CI = 0.9-1.6, P < 0.05] and acute lymphoblastic leukemia (ALL) (APC = 1.5, 95%CI = 1.1-1.8, P < 0.05) in children and adolescents were significantly increasing. For adults, AL (APC = 0.9, 95%CI = 0.3-1.5, P < 0.05), ALL (APC = 2.5, 95%CI = 2.0-3.1, P < 0.05) and acute myeloid leukemia (AML) (APC = 0.9, 95%CI = 0.4-1.5, P < 0.05) had significantly elevated incidence rates. Overall survival (OS) in children and adolescents with AL was significantly higher than that in adults with AL (log-rank P < 0.0001). OS in children and adolescents and adults with ALL, AML and AUL decreased with age (all log-rank P < 0.0001). Older age, male sex and black race were risk factors for the survival of children and adolescents and adults with ALL, AML and AUL. CONCLUSION: From 2000 to 2016, the incidence rates of AL in children and adolescents and adults were increasing. Children and adolescents with AL had significantly better OS than adults with AL, and OS declined with age in both children and adolescents and adults with ALL, AML and AUL.

[Establishment of a prognostic nomogram and discussion on optimal treatment for cervical adenocarcinoma:a retrospective study based on SEER database and Chinese single-center data].

Objective: To establish and validate a predicting nomogram for cervical adenocarcinoma based on surveillance, epidemiology and end results (SEER) database and Chinese single-center data, and to explore the optimal treatment for cervical adenocarcinoma. Methods: This study selected 2 478 cervical adenocarcinoma patients from the SEER database as the training cohort, and 195 cervical adenocarcinoma patients from Cancer Hospital of Dalian University of Technology, Liaouing Cancer Hospital and Institute as an external validation cohort. Clinicopathological information and follow-up data of the two cohorts were collected. The radiotherapy group was defined as receiving comprehensive treatment based on concurrent chemoradiotherapy after initial diagnosis, while the surgery group was defined as receiving comprehensive treatment based on radical surgery. Log-rank test and cox regression were used to evaluate factors affecting the prognosis of cervical adenocarcinoma patients. A nomogram was drawn to predict the 3-year and 5-year overall survival rates of cervical adenocarcinoma patients, and then internal validation of the training cohort from SEER database and external validation of the hospital cohort were conducted. Results: (1) In the SEER database training cohort, there were 385 patients (15.54%, 385/2 478) in the radiotherapy group and 2 093 patients (84.46%, 2 093/2 478) in the surgery group. Overall survival time of the radiotherapy group was (55.8±51.3) months, while that of the surgery roup was (94.4±61.7) months, the difference between the two groups was statistically significant (χ2=256.44, P<0.001). Log-rank test showed that age, marital status, maximum of tumor diameters, pathological grade, International Federation of Gynecology and Obstetrics (FIGO) stage, and treatments were all significant factors affecting the overall survival time of cervical adenocarcinoma patients (all P<0.001). Multivariate Cox regression analysis showed that elder (>50 years old), single status, huge tumors (>4 cm), high pathological grades (G2, G3), and advanced FIGO stages (≥Ⅱa2 stage) were independent risk factors for the overall survival time of cervical adenocarcinoma patients (all P<0.05); compared with radiotherapy, surgery was a protective factor for the prognosis of cervical adenocarcinoma patients (HR=0.619, 95%CI: 0.494-0.777; P<0.001). Further analysis of locally advanced stage and Ⅲc stage of patients showed that surgery was a protective factor for the prognosis of cervical adenocarcinoma patients with a maximum tumor diameter >4 to <6 cm (HR=0.414, 95%CI: 0.182-0.942; P=0.036) in locally advanced stage and Ⅲc T1 to T2 stage (HR=0.473, 95%CI: 0.307-0.728; P=0.001). (2) The external validation cohort consisted of 39 patients (20.00%, 39/195) in the radiotherapy group and 156 patients (80.00%, 156/195) in the surgery group. The overall survival time of patients in the radiotherapy group was (51.7±34.3) months, while that of the surgery group was (63.1±26.6) months (χ2=28.41, P<0.001). Further analysis was conducted on locally advanced stage and Ⅲc stage patients, and multivariate Cox regression analysis was performed after propensity score matching, which showed that surgery was a protective factor for the prognosis of cervical adenocarcinoma patients with a maximum tumor diameter >4 to <6 cm in locally advanced stage (HR=0.141, 95%CI: 0.023-0.843; P=0.032) and Ⅲc T1 to T2 stage (HR=0.184, 95%CI: 0.036-0.947; P=0.043). (3) Establishment and internal and external validation of nomogram: based on the six factors screened out by the multivariate Cox regression model, the nomogram was developed to predict the prognosis of cervical adenocarcinoma patients. The consistency index of the internal and external validation were 0.801 and 0.766, respectively, and the calibration curves matched well with the ideal fitting line. Conclusions: The key to the treatment of cervical adenocarcinoma is to prioritize radical surgery for patients with conditions for radical tumor resection. Compared with concurrent chemoradiotherapy, patients with locally advanced stages (Ⅰb3, Ⅱa2), and Ⅲc (T1, T2) stages cervical adenocarcinoma could benefit from comprehensive treatment based on radical surgery. The nomogram of this study has been validated internally and externally, and show good survival prediction efficacy for cervical adenocarcinoma patients.

Metastasis patterns and prognosis in young gastric cancer patients: A propensity score­matched SEER database analysis.

BACKGROUND: Whether young patients with metastatic gastric cancer (GC) had distinct metastasis patterns and survival outcomes from older patients remains controversial. The aim of the present study was to explore the metastasis patterns and prognostic factors in young patients and evaluate the survival outcome in comparison to their older counterparts. MATERIALS AND METHODS: We identified patients with metastatic GC in the surveillance, epidemiology, and end results (SEER) database from 2010 to 2015. The patients were divided into two groups based on age at diagnosis: younger (≤40 years old) and older (>40 years old). We employed the chi-squared test to compare the clinicopathological characteristics between the two age groups. Furthermore, we conducted survival analyses using Kaplan-Meier and Cox regression analyses. To balance disparities in baseline characteristics, we employed propensity score matching (PSM). RESULTS: We identified 5,580 metastatic GC patients from the SEER database, with 237 (4.2%) classified as younger and 5343 (95.8%) as older patients. A total of 237 pairs of patients were generated after adjustment by PSM. Patients in the younger group exhibited a higher proportion of bone-only metastases and a lower proportion of liver-only metastases compared with patients in the older group. Multivariate Cox regression analysis demonstrated that youth was an independent protective factor for overall survival (OS) before and after PSM, but not for gastric cancer-specific survival (GCSS). Among the younger group, patients with liver-only metastasis demonstrated the best prognosis, whereas patients with lung-only metastasis exhibited significantly worse survival outcomes compared with liver-only metastases, even comparable to that of bone metastasis. CONCLUSIONS: Compared with the older group, the metastatic GC patients in the younger group exhibited more aggressive tumors but better prognoses. The metastasis pattern and its effect on the prognosis of GC varied by age group.

Prognostic and predictive value of tumor deposits in advanced signet ring cell colorectal cancer: SEER database analysis and multicenter validation.

BACKGROUND: Colorectal signet-ring cell carcinoma (SRCC) is a rare cancer with a bleak prognosis. The relationship between its clinicopathological features and survival remains incompletely elucidated. Tumor deposits (TD) have been utilized to guide the N staging in the 8th edition of American Joint Committee on Cancer (AJCC) staging manual, but their prognostic significance remains to be established in colorectal SRCC. PATIENTS AND METHODS: The subjects of this study were patients with stage III/IV colorectal SRCC who underwent surgical treatment. The research comprised two cohorts: a training cohort and a validation cohort. The training cohort consisted of 631 qualified patients from the SEER database, while the validation cohort included 135 eligible patients from four independent hospitals in China. The study assessed the impact of TD on Cancer-Specific Survival (CSS) and Overall Survival (OS) using Kaplan-Meier survival curves and Cox regression models. Additionally, a prognostic nomogram model was constructed for further evaluation. RESULTS: In both cohorts, TD-positive patients were typically in the stage IV and exhibited the presence of perineural invasion (PNI) (P < 0.05). Compared to the TD-negative group, the TD-positive group showed significantly poorer CSS (the training cohort: HR, 1.87; 95% CI, 1.52-2.31; the validation cohort: HR, 2.43; 95% CI, 1.55-3.81; all P values < 0.001). This association was significant in stage III but not in stage IV. In the multivariate model, after adjusting for covariates, TD maintained an independent prognostic value (P < 0.05). A nomogram model including TD, N stage, T stage, TNM stage, CEA, and chemotherapy was constructed. Through internal and external validation, the model demonstrated good calibration and accuracy. Further survival curve analysis based on individual scores from the model showed good discrimination. CONCLUSION: TD positivity is an independent factor of poor prognosis in colorectal SRCC patients, and it is more effective to predict the prognosis of colorectal SRCC by building a model with TD and other clinically related variables.

A novel web-based dynamic prognostic nomogram for gastric signet ring cell carcinoma: a multicenter population-based study.

Background: Gastric signet ring cell carcinoma (GSRCC) is a rare and highly malignant disease with a poor prognosis. To assess the overall survival (OS) and cancer-specific survival (CSS) of patients with GSRCC, prognostic nomograms were developed and validated using common clinical factors. Methods: This retrospective cohort study included patients diagnosed with GSRCC between 2011 and 2018 from the National Cancer Center (n = 1453) and SEER databases (n = 2745). Prognostic nomograms were established by identifying independent prognostic factors using univariate and multivariate Cox regression analyses. The calibration curve and C-index were used to assess the predictions. The clinical usefulness of the survival prediction model was further evaluated using the DCA and ROC curves. The models were internally validated in the training cohort and externally validated in the validation cohort. Two web servers were created to make the nomogram easier to use. Results: Patients with GSRCC were divided into training (n = 2938) and validation (n = 1260) cohorts. The nomograms incorporated six predictors: age, race, tumor site, tumor size, N stage, T stage, and AJCC stage. Excellent agreement was observed between the internal and exterior calibration plots for the GSRCC survival estimates. The C-index and area under the ROC curve were roughly greater than 0.7. Both nomograms had adequate clinical efficacy, as demonstrated by the DCA plots. Furthermore, we developed a dynamic web application utilizing the constructed nomograms available at https://jiangyujuan.shinyapps.io/OS-nomogram/ and https://jiangyujuan.shinyapps.io/DynNomapp-DFS/. Conclusion: We developed web-based dynamic nomograms utilizing six independent prognostic variables that assist physicians in estimating the OS and CSS of patients with GSRCC.

Disparities in incidence and survival for patients with Ewing sarcoma in Florida.

BACKGROUND: Ewing sarcoma (ES) is a malignant bone tumor most commonly affecting non-Hispanic White (NHW) adolescent males, though recognition among Hispanic individuals is rising. Prior population-based studies in the United States (US), utilizing Surveillance, Epidemiology, and End Results (SEER) have shown higher all-cause mortality among White Hispanics, Blacks, and those of low socioeconomic status (SES). Florida is not part of SEER but is home to unique Hispanic populations including Cubans, Puerto Ricans, South Americans that contrasts with the Mexican Hispanic majority in other US states. This study aimed to assess racial/ethnic disparities on incidence and survival outcomes among this diverse Florida patient population. METHODOLOGY: Our study examined all patients diagnosed with osseous ES (2005-2018) in Florida (n = 411) based on the state's population-based cancer registry dataset. Florida Age-adjusted Incidence Rates (AAIRs) were computed by sex and race-ethnicity and compared to the equivalent populations in SEER. Cause-specific survival disparities among Florida patients were examined using Kaplan-Meier analysis. Univariable and multivariable analyses using Cox regression were performed for race/ethnicity, with adjustment for age, sex, year of diagnosis, site of disease, staging, SES, and insurance type. RESULTS: There was a significantly higher incidence of osseous ES in Florida Hispanic males (AAIR 2.6/1,000,000); (95% CI: 2.0-3.2 per 1,000,000; n = 84) compared to the SEER Hispanic males (AAIR 1.2/1,000,000;1.1-1.4 per 1,000,000; n = 382). Older age, distant metastasis, lack of chemotherapy or surgical resection were statistically significant determinants of poor survival while SES, insurance status and race-ethnicity were not. However, among nonmetastatic ES, Florida Hispanics had an increased risk of death compared to Florida NHW (adjusted Hazard Ratio 2.32; 95%CI: 1.20-4.46; p = 0.012). CONCLUSIONS: Florida Hispanic males have a higher-than-expected incidence of osseous ES compared to the US. Hispanics of both sexes show remarkably worse survival for nonmetastatic disease compared to NHW. This disparity is likely multifactorial and requires further in-depth studies.

Comparing symptom clusters in cancer survivors by cancer diagnosis: A latent class profile analysis.

PURPOSE: Research on symptom clusters in oncology is progressing, but knowledge gaps remain. One question is whether the number and types of symptom subgroups (i.e., latent classes) differ based on cancer diagnosis. The purpose of this study was to: (1) identify and compare latent class subgroups based on four highly prevalent symptoms (pain, fatigue, sleep disturbance, and depression), and (2) examine the differences in sociodemographic and clinical factors in the identified latent classes across the seven cancer types (i.e., prostate, non-small cell lung, non-Hodgkin's lymphoma, breast, uterine, cervical, and colorectal cancer). METHODS: This study is a cross-sectional secondary analysis of data obtained from the My-Health study in partnership with four Surveillance, Epidemiology, and End Results (SEER) cancer registries located in California (two), Louisiana, and New Jersey. The sample included 4,762 cancer survivors 6-13 months following diagnosis of one of the seven cancer types mentioned. Latent class profile analysis was used. RESULTS: Subjects were primarily young (59% age 21-64 years), Caucasian (41%), married/cohabitating (58%) and unemployed (55%). The number and types of symptom subgroups varied across these seven cancer populations: four-subgroups were the common in prostate, lung, non-Hodgkin's lymphoma, and breast cancer survivors. Unmarried, low education, and unemployment status were associated with high risk of symptom burden across the cancer types. CONCLUSION: Identifying symptom subgroups by cancer diagnosis has the potential to develop innovative and effective targeted interventions in cancer survivors. Further research is needed to establish extensive knowledge in symptom clustering between treatment regimens, and short-term and long-term cancer survivors.

[Construction and Validation of Prediction Models of Risk Factors for Early Death in Patients With Metastatic Melanoma]. / è½¬ç§»æ€§é»‘è‰²ç´ ç˜¤æ‚£è€ æ—©æœŸæ­»äº¡é£Žé™©çš„é¢„æµ‹æ¨¡åž‹æž„å»ºåŠéªŒè¯.

Objective: To construct nomogram models to predict the risk factors for early death in patients with metastatic melanoma (MM). Methods: The study covered 2138 cases from the Surveillance, Epidemiology, and End Results Program (SEER) database and all these patients were diagnosed with MM between 2010 and 2015. Logistic regression was performed to identify independent risk factors affecting early death in MM patients. These risk factors were then used to construct nomograms of all-cause early death and cancer-specific early death. The efficacy of the model was assessed with receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). In addition, external validation of the model was performed with clinicopathologic data of 105 patients diagnosed with MM at Sichuan Cancer Hospital between January 2015 and January 2020. Results: According to the results of logistic regression, marital status, the primary site, N staging, surgery, chemotherapy, bone metastases, liver metastases, lung metastases, and brain metastases could be defined as independent predictive factors for early death. Based on these factors, 2 nomograms were plotted to predict the risks of all-cause early death and cancer-specific early death, respectively. For the models for all-cause and cancer-specific early death, the areas under the curve (AUCs) for the training group were 0.751 (95% confidence interval [CI]: 0.726-0.776) and 0.740 (95% CI: 0.714-0.765), respectively. The AUCs for the internal validation group were 0.759 (95% CI: 0.722-0.797) and 0.757 (95% CI: 0.718-0.780), respectively, while the AUCs for the external validation group were 0.750 (95% CI: 0.649-0.850) and 0.741 (95% CI: 0.644-0.838), respectively. The calibration curves showed high agreement between the predicted and the observed probabilities. DCA analysis indicated high clinical application value of the models. Conclusion: The nomogram models demonstrated good performance in predicting early death in MM patients and can be used to help clinical oncologists develop more individualized treatment strategies.

Development and validation of a nomogram to predict cancer-specific survival of elderly patients with unresected gastric cancer who received chemotherapy.

This investigation aimed to explore the prognostic factors in elderly patients with unresected gastric cancer (GC) who have received chemotherapy and to develop a nomogram for predicting their cancer-specific survival (CSS). Elderly gastric cancer patients who have received chemotherapy but no surgery in the Surveillance, Epidemiology, and End Results Database between 2004 and 2015 were included in this study. Cox analyses were conducted to identify prognostic factors, leading to the formulation of a nomogram. The nomogram was validated using receiver operating characteristic (ROC) and calibration curves. The findings elucidated six prognostic factors encompassing grade, histology, M stage, radiotherapy, tumor size, and T stage, culminating in the development of a nomogram. The ROC curve indicated that the area under curve of the nomogram used to predict CSS for 3, 4, and 5 years in the training queue as 0.689, 0.708, and 0.731, and in the validation queue, as 0.666, 0.693, and 0.708. The calibration curve indicated a high degree of consistency between actual and predicted CSS for 3, 4, and 5 years. This nomogram created to predict the CSS of elderly patients with unresected GC who have received chemotherapy could significantly enhance treatment accuracy.

Survival Outcome and Prognostic Factors of Primary Spinal Cord Lymphoma.

AIM: To identify the predictive factors associated with the survival of patients with a diagnosis of primary spinal cord lymphoma (PSCL). MATERIAL AND METHODS: The Surveillance, Epidemiology, and End Results (SEER) database was used in this study, which involved 254 patients with PSCL. Data on the patients' age, sex, race, pathology, Ann Arbor stage, adjuvant therapy, and year of diagnosis were collected. Univariate and multivariate Cox regression models were conducted to detect the predictive variables. RESULTS: Of the 254 patients, 67 (26.4%) die from lymphoma at the time of data collection. Cancer-specific survival at 1, 3, and 5 years was 81.0%, 74.6%, and 74.1%, respectively. Diffuse large B-cell lymphoma (DLBL) was the highest prevalent histotype (n=140, 55.1%). The multivariate Cox regression models revealed that chemotherapy (hazard ratio (HR): 0.47; 95% confidence interval (CI), 0.16-0.82; p=0.040) and radiochemotherapy (HR: 0.43; 95% CI, 0.10-0.57; p=0.045) were independent predictors of favorable cancer-specific survival, whereas age - 80 years (HR: 6.51; 95% CI, 1.65-25.64; p=0.003) and DLBL (HR:1.71; 95% CI, 1.02-2.88; p=0.030) were independently associated with poor cancer-specific survival. CONCLUSION: The survival outcome of PSCL is favorable in the current treatment strategy. Chemotherapy and radiochemotherapy were predictors of favorable outcomes, whereas older age and DLBL were associated with poor prognosis.

Adjuvant chemotherapy and survival in males aged 70 years or older with breast cancer: a population-based retrospective study.

BACKGROUND: Male breast cancer constitutes a minority of breast cancer diagnoses, yet its incidence has been on the rise in recent decades. However, elderly male breast cancer patients have been inadequately represented in clinical trials, posing challenges in treatment decisions. This study seeks to clarify the efficacy of chemotherapy in this demographic and identify the population most likely to benefit from such intervention. METHODS: We conducted a retrospective analysis using the Surveillance, Epidemiology, and End Results (SEER) database, encompassing a total of 1900 male breast cancer patients aged 70 years or older. Among them, 1652 were categorized in the no-chemotherapy group, while 248 were in the chemotherapy group. A multifactorial logistic regression model was employed to investigate the determinants influencing the administration of chemotherapy in elderly male breast cancer patients. Additionally, the multivariate Cox proportional hazards regression model was applied to identify factors associated with outcomes, with overall survival (OS) as the primary endpoint. RESULTS: Multivariate logistic regression analysis revealed that grade, tumor size, and nodal status were robust predictors for elderly male breast cancer patients receiving chemotherapy. Furthermore, the multivariate analysis demonstrated that chemotherapy conferred benefits compared to the no-chemotherapy group (HR = 0.822, 95% CI: 0.682-0.991, p = 0.040). Stratified analyses indicated that individuals with N+, poorly/undifferentiated grade, and stage II/III disease could derive benefits from chemotherapy. Upon further investigation of progesterone receptor (PR) positive patients, it was found that only stage III patients experienced significant benefits from chemotherapy (HR = 0.571, 95% CI: 0.372-0.875, p = 0.010). Conversely, in PR negative patients, both stage II (HR = 0.201, 95% CI: 0.051-0.792, p = 0.022) and stage III patients (HR = 0.242, 95% CI: 0.060-0.972, p = 0.046) derived benefits from chemotherapy. CONCLUSION: Adjuvant chemotherapy may benefit certain elderly male breast cancer patients, specifically those with positive lymph node status, poorly/undifferentiated grade, and PR-positive in stage III, as well as PR-negative expression in stage II/III. Given favorable physical tolerance, it is advisable not to hastily dismiss chemotherapy for these elderly male breast cancer patients.

Adjuvant chemotherapy and survival outcomes in older women with HR+/HER2- breast cancer: a propensity score-matched retrospective cohort study using the SEER database.

OBJECTIVES: This study aimed to investigate the impact of adjuvant chemotherapy (ACT) on survival outcomes in older women with hormone receptor-positive and human epidermal growth factor receptor 2-negative (HR+/HER2-) breast cancer (BC). DESIGN: A retrospective cohort study using data from the Surveillance, Epidemiology, and End Results database, which contains publicly available information from US cancer registries. SETTING AND PARTICIPANTS: The study included 45 762 older patients with BC aged over 65 years diagnosed between 2010 and 2015. METHODS: Patients were divided into two groups based on age: 65-79 years and ≥80 years. Propensity score matching (PSM) was employed to balance clinicopathological characteristics between patients who received ACT and those who did not. Data analysis used the χ2 test and Kaplan-Meier method, with a subgroup analysis conducted to identify potential beneficiaries of ACT. OUTCOME MEASURES: Overall survival (OS) and cancer-specific survival (CSS). RESULTS: Due to clinicopathological characteristic imbalances between patients with BC aged 65-79 years and those aged ≥80 years, PSM was used to categorise the population into two groups for analysis: the 65-79 years age group (n=38 128) and the ≥80 years age group (n=7634). Among patients aged 65-79 years, Kaplan-Meier analysis post-PSM indicated that ACT was effective in improving OS (p<0.05, HR=0.80, 95% CI 0.73 to 0.88), particularly in those with advanced disease stages, but did not show a significant benefit in CSS (p=0.09, HR=1.13, 95% CI 0.98 to 1.31). Conversely, for patients aged ≥80 years, ACT did not demonstrate any improvement in OS (p=0.79, HR=1.04, 95% CI 0.79 to 1.36) or CSS (p=0.09, HR=1.46, 95% CI 0.69 to 2.26) after matching. Subgroup analysis also revealed no positive impact on OS and CSS. CONCLUSIONS: Patients with HR+/HER2- BC ≥80 years of age may be considered exempt from ACT because no benefits were found in terms of OS and CSS.

Prognostic factors for liver metastasis in patients with small intestinal stromal tumor: A retrospective analysis of surveillance, epidemiology, and end results.

BACKGROUND: Liver metastasis (LIM) is the most common distant site of metastasis in small intestinal stromal tumors (SISTs). The aim of this study was to determine the risk and prognostic factors associated with LIM in patients with SISTs. METHODS: Patients diagnosed with gastrointestinal stromal tumors between 2010 and 2019 were selected from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate logistic regression models, as well as a Cox regression model were used to explore the risk factors associated with the development and prognosis of LIM. Additionally, the overall survival (OS) of patients with LIM was analyzed using the Kaplan-Meier method. Furthermore, a predictive nomogram was constructed, and the model's performance was evaluated using receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). RESULTS: A total of 1582 eligible patients with SISTs were included, among whom 146 (9.2%) were diagnosed with LIM. Poor tumor grade, absence of surgery, later T-stage, and no chemotherapy were associated with an increased risk of developing LIM. The nomogram prediction model achieved an AUC of 0.810, 95% Confidence Interval (CI) 0.773-0.846, indicating good performance, and the calibration curve showed excellent accuracy in predicting LIM. The OS rate of patients with LIM was significantly lower than that of patients without LIM (p < 0.001). CONCLUSIONS: Patients with SISTs who are at high risk of developing LIM deserve more attention during follow-up, as LIM can significantly affect patient prognosis. The nomogram demonstrated good calibration and discrimination for predicting LIM.

Identifying the Best Candidate for Primary Tumor Resection in Patients With Advanced Osteosarcoma.

OBJECTIVES: Not all patients with stage III and IV osteosarcoma who undergo surgery to remove the primary tumor will benefit from surgery; therefore, we developed a nomogram model to test the hypothesis that only a subset of patients will benefit from surgery. METHODS: 412 patients were screened from the Surveillance, Epidemiology and End Results (SEER) database. Subsequently, 1:1 propensity score matching (PSM) was used to screen and balance confounders. We first made the hypothesis that patients who underwent the procedure would benefit more. A multivariate Cox model was used to explore the independent influencing factors of CSS in two groups (benefit group and non-benefit group) and constructed nomograms with predicted prognosis. Finally, receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) were used to verify the performance of the nomogram. RESULTS: Of these patients, approximately 110 did not undergo primary tumour resection. After passing PSM, they were divided into a surgical group and a non-surgical group. Age, primary site and chemotherapy as calculated independent factors were used to construct a nomogra. The predicted nomogram showed good consistency in terms of the ROC curve and the calibration curve, and the DCA curve showed a certain clinical utility. Finally, dividing the surgical patients into surgical beneficiaries and surgical non-beneficiaries, a Kaplan-Meier analysis showed that the nomogram can identify patients with osteosarcoma who can benefit from surgery. CONCLUSION: A practical predictive model was established to determine whether patients with stage III or IV osteosarcoma would benefit from surgery.

Predicting the Survival Benefit of Radiotherapy in Elderly Breast Cancer Patients: A Population-Based Analysis.

INTRODUCTION: This study aimed to establish two prediction tools predicting cancer-specific survival (CSS) and overall survival (OS) in elderly breast cancer patients with or without radiotherapy. METHODS: Clinicopathological data of breast cancer patients aged more than 70 y from 2010 to 2018 were retrospectively collected from the Surveillance, Epidemiology, and End Results database. Patients were randomly divided into the training and validation cohorts at 7:3, and the Cox proportional risk model was used to construct the nomograms. The concordance index, the area under the receiver operating characteristic curve, and the calibration plot are used to evaluate the discrimination and accuracy of the nomograms. RESULTS: One lakh twenty eight thousand two hundred twenty three elderly breast cancer patients were enrolled, including 57,915 who received radiotherapy. The Cox regression model was used to identify independent factors. These independent influencing factors are used to construct the prediction models. The calibration plots reflect the excellent consistency between the predicted and actual survival rates. The concordance index of nomograms for CSS and OS was more than 0.7 in both the radiotherapy group and the nonradiotherapy group, and similar results are also shown in area under the receiver operating characteristic curve. Decision curve analysis showed that the prognostication accuracy of the model was much higher than that of the traditional tumor, node, metastasis staging. CONCLUSIONS: Radiotherapy can benefit elderly breast cancer patients significantly. The two prediction tools provide a personalized survival scale for evaluating the CSS and OS of elderly breast cancer patients, which can better provide clinicians with better-individualized management for these patients.

The influence of marital status at diagnosis on survival of adult patients with mantle cell lymphoma.

PURPOSE: Marital status has been reported to influence the survival outcomes of various cancers, but its impact on patients with mantle cell lymphoma (MCL) remains unclear. This study aimed to assess the influence of marital status at diagnosis on overall survival (OS) and cancer-specific survival (CSS) in patients with MCL. METHODS: The study utilized data from the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER)-18 databases, including 6437 eligible individuals diagnosed with MCL from 2000 to 2018. A 1:1 propensity matching method (PSM) minimized confounding factor. Univariate and multivariate analyses determined hazard ratios (HR). Stratified hazard models were developed for married and unmarried statuses across time intervals. RESULTS: Married patients exhibited better 5-year OS and CSS rates compared to unmarried patients (54.2% vs. 39.7%, log-rank p < 0.001; 62.6% vs. 49.3%, log-rank p < 0.001). Multivariate analysis indicated that being unmarried was an independent risk factor for OS (adjusted HR 1.420, 95% CI 1.329-1.517) and CSS (adjusted HR 1.388, 95% CI 1.286-1.498). After PSM, being unmarried remained an independent risk factor for both OS and CSS. Among unmarried patients, widowed individuals exhibited the poorest survival outcomes compared to patients with other marital statuses, with 5-year OS and CSS rates of 28.5% and 41.0%, respectively. Furthermore, in the 10-year OS and CSS hazard model for widowed individuals had a significantly higher risk of mortality, with the probability of overall and cancer-specific mortality increased by 1.7-fold and 1.6-fold, respectively. CONCLUSION: Marital status at diagnosis is an independent prognostic factor for MCL patients, with widowed individuals showing worse OS and CSS than those who are married, single, or divorced/separated. Adequate psychological and social support for widowed patients is crucial for improving outcomes in this patient population.