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Purpose: The study aimed to develop a nomogram model for individual prognosis prediction in patients with hormone receptors positive (HR+) mucinous breast carcinoma (MBC) and assess the value of neoadjuvant chemotherapy (NAC) in this context. Methods: A total of 6,850 HR+ MBC patients from the SEER database were identified and randomly (in a 7:3 ratio) divided into training cohorts and internal validation cohorts. 77 patients were enrolled from the Chongqing University Cancer Hospital as the external validation cohort. Independent risk factors affecting overall survival (OS) were selected using univariate and multivariate Cox regression analysis, and nomogram models were constructed and validated. A propensity score matching (PSM) approach was used in the exploration of the value of NAC versus adjuvant chemocherapy (AC) for long-term prognosis in HR+ MBC patients. Results: Multivariate Cox regression analysis showed 8 independent prognostic factors: age, race, marital status, tumor size, distant metastasis, surgery, radiotherapy, and chemotherapy. The constructed nomogram model based on these 8 factors exhibited good consistency and accuracy. In the training group, internal validation group and external validation group, the high-risk groups demonstrated worse OS (p<0.0001). Subgroup analysis revealed that NAC had no impact on OS (p = 0.18), or cancer specific survival (CSS) (p = 0.26) compared with AC after PSM. Conclusions: The established nomogram model provides an accurate prognostic prediction for HR+ MBC patients. NAC does not confer long-term survival benefits compared to AC. These findings provide a novel approach for prognostic prediction and clinical practice. [ABSTRACT FROM AUTHOR]

Hodgkin lymphoma (HL) is a rare malignancy affecting the lymphatic system. Our study examined the incidence rates of adult HL based on sex, race/ethnicity, age, and histological subgroups in the United States (US) from 2000 to 2020. Data for this study were extracted from the Surveillance, Epidemiology, and End Results 22 database. HL patients were identified utilizing the International Classification of Diseases for Oncology version 3 and categorized as classical HL, lymphocyte-rich/mixed cell/lymphocyte depleted, nodular sclerosis, classical HL, not otherwise specified, and nodular lymphocyte-predominant HL. The study reported average annual percent change (AAPC). All estimates were presented as counts and age-standardized incidence rates (ASIRs) per 100,000 individuals. Between 2000 and 2019, a total of 70,924 cases of HL were reported in the US. Classical HL was the predominant subtype (94.27%), and most incident cases were among non-Hispanic Whites (66.92%) and those aged 20–29 years (24.86%). The ASIR per 100,000 population was 3.83 for men and 2.92 for women. Both sexes showed declines in the AAPCs between 2000 and 2019 (− 0.64% [− 0.99, − 0.28] and − 0.40% [− 0.77, − 0.03] for men and women, respectively). There was a significant decrease in ASIRs after COVID-19 among both sexes (percent change: − 7.49% [− 11.58, − 3.40]). Throughout all age groups, men had a higher incidence rate compared to women, except for those aged 20–29 years. Although the overall HL incidence rate was lowered in the study period from 2000 to 2019, a dramatic decrease in ASIRs of HL patients following COVID-19 pandemic was observed. [ABSTRACT FROM AUTHOR]

Our goal was to assess the impact of childhood/adolescent cancer history on overall survival (OS) and disease-specific survival (DSS) in patients with parotid mucoepidermoid carcinoma (MEC). Patients who underwent surgical treatment for primary parotid MEC and those with a second malignancy of parotid MEC were retrospectively identified from the Surveillance, Epidemiology, and End Results (SEER) database. The primary outcome variables were OS and DSS. The hazard ratios (HRs) of these survival rates associated with cancer history were analysed using Cox regression models. In total, 2681 patients were included, 263 of whom had a second malignancy. The 10-year OS rates in the primary (72%) and second malignancy groups (59%) were significantly different. Cox regression confirmed that a history of cancer tended to decrease OS (p = 0.062, HR: 1.28, 95% confidence interval: 0.99 to 1.64). Subgroup analyses showed that a history of solid tumour as opposed to haematological cancer predicted worse OS, with central nervous system tumours exhibiting a more significant influence than others (p = 0.030 vs p = 0.088). Cancer history was not related to DSS. A history of childhood/adolescent cancer negatively influenced the prognosis of patients with parotid MEC, and this effect was primarily driven by a history of solid malignancy. [ABSTRACT FROM AUTHOR]

Asian American, Native Hawaiian, and Pacific Islander (AANHPI) patient populations are often defined as one monolithic group in medical research despite cultural, socioeconomic, and clinical heterogeneity. Although the general AANHPI population is underrepresented in reception of postmastectomy breast reconstruction, existing literature has not characterized the disaggregation of such rates for AANHPI ethnic subgroups. Patients who underwent mastectomy were identified in the 2007 to 2020 registries within the Surveillance, Epidemiology and End Results database. Patients were stratified by race and ethnicity, and additional demographic and oncologic variables were collected. Multivariate binary logistic regression was conducted to assess for reception of postmastectomy immediate breast reconstruction (p < 0.05). Among 33,422 AANHPI patients who underwent mastectomy, South Asian patients were associated with the highest breast reconstruction rates (33%) and Melanesians with the lowest (15%). Overall, AANHPI patients were associated with a lower breast reconstruction rate than non-Hispanic Whites (27% vs. 35%; p < 0.001). This difference increased from 6.4% in 2007 to 10% in 2020. After controlling for demographic and oncologic covariates, all AANHPI ethnic subgroups predicted a lower likelihood of breast reconstruction than non-Hispanic Whites (p < 0.001). Odds ratios for reconstruction ranged from 0.17 [95% confidence interval (95% CI), 0.11–0.27] for Melanesian patients to 0.45 (95% CI, 0.42–0.48) for South Asian patients. Disparities in the receipt of immediate breast reconstruction exist within the AANHPI patient population in the United States. This analysis supported the need for disaggregation in plastic surgery research for improved knowledge and targeted interventions. [ABSTRACT FROM AUTHOR]

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Purpose: Adrenocortical carcinoma (ACC) is an uncommon adrenal gland endocrine tumor that has a poor prognosis in children. We aimed to conduct a population-based cohort study to predict overall survival (OS) in pediatric patients with ACC. Methods: We used the Surveillance, Epidemiology, and End Results (SEER) database to conduct a retrospective cohort research on pediatric patients diagnosed with ACC between 1975 and 2018. We examined demographic characteristics, tumor stage and size, treatment options, and survival results. Kaplane-Meier estimations were used to generate survival curves based on several parameters. To compare survival curves, the log-rank test was applied.Cox proportional-hazards regression was used to determine the variables related with OS. In addition, we created a nomogram to predict overall survival in pediatric ACC patients. Results: A total of 143 pediatric ACC patients were identified. Females were the most impacted (60.8%). Overall 1 year, 3 year, and 5 year survival rates were 75.0%, 57.6%, and 53.7% for all patients, respectively. In comparison to older patients (5–19 years), younger patients (≤ 4 years) were shown to have more positive characteristics, including a higher likelihood of local disease (29.4% vs. 14%, P < 0.001), tumors less than 10 cm (23.1% vs. 14.7%, P < 0.001), and improved overall survival (5 year OS 89.6% vs. 27.7%, P < 0.001). Age at diagnosis, SEER stage, and surgery were significant independent predictors of OS in this model, according to the results of Cox proportional hazard regression. After that, we developed a nomogram for predicting OS in children with ACC. Patients older than 4 years old had a higher chance of dying. Furthermore, the higher the SEER stage, the higher the risk of death. Patients who do not have surgery have a worse survival rate than those who do. Conclusions: Our study revealed that age at diagnosis, SEER stage, and surgery were found to be the most important predictors of the overall survival of pediatric ACC. These findings contribute to the existing body of knowledge and emphasize the importance of continued research to advance our understanding of pediatric ACC and improve patient care. [ABSTRACT FROM AUTHOR]

Background: Colorectal adenosquamous carcinoma (ASC) is a rare subtype of colorectal carcinoma. This study presents findings from a large database query to highlight the demographic, clinical, and pathological factors, prognosis, and survival of colorectal ASC. Methods: The Surveillance, Epidemiology, and End Results (SEER) database was used to identify patients with colorectal ASC diagnosed between 2000 and 2020 and assess factors associated with overall survival (OS) and cause-specific survival (CSS). Results: Among 284 identified cases, the median age of diagnosis was 64 years. The majority of patients were White (69.0%), with income ≤ $70,000 (62.3%), and lived in metropolitan areas (85.6%). Regarding tumor characteristics, the majority of tumors were poorly differentiated (49.6%), regional stage (39.8%), size of > 4.0 cm (41.5%), and had a negative lymph node status (47.2%). Primary sites were the rectum (35.2%) and colon (64.8%). In patients with primary site to the rectum, the majority of treatment modality was multimodal therapy (40.0%). The main treatment modality for the primary site to the colon was surgery only (46.2%), followed by surgery + chemotherapy (34.2%). The overall 5-year survival was 31.3 (95% C.I. 28.4–34.2) and the 5-year cause-specific survival (CSS) was 40.1% (95% C.I. 36.9–43.3). Multivariate analysis showed age ≥ 60 years, regional stage, and distant stage were negative prognostic factors. An income of > $70,000, multimodal therapy, and surgery with chemotherapy were positive prognostic factors. Conclusion: Colorectal adenosquamous carcinomas are more common in the non-Hispanic White populations and appear more frequently later in life (based on the median age of diagnosis at 64). Factors that contributed to a worse prognosis were an age of diagnosis ≥ 60 years, regional stage, and distant stage. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to compare the prognostic value of rectal cancer by comparing different lymph node staging systems, and a nomogram was constructed based on superior lymph node staging. Methods: Overall, 8700 patients with rectal cancer was obtained from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015. The area under the curve (AUC), the C index, and the Akaike informativeness criteria (AIC) were used to examine the predict ability of various lymph node staging methods. Prognostic indicators were assessed using univariate and multivariate COX regression, and further correlation nomograms were created after the data were randomly split into training and validation cohorts. To evaluate the effectiveness of the model, the C index, calibration curves, decision curves (DCA), and receiver operating characteristic curve (ROC) were used. We ran Kaplan-Meier survival analyses to look for variations in risk classification. Results: While compared to the N-stage positive lymph node ratio (LNR), the log odds ratio of positive lymph nodes (LODDS) had the highest predictive effectiveness. Multifactorial COX regression analyses were used to create nomograms for overall survival (OS) and cancer-specific survival (CSS). The C indices of OS and CSS for this model were considerably higher than those for TNM staging in the training cohort. The created nomograms demonstrated good efficacy based on ROC, rectification, and decision curves. Kaplan-Meier survival analysis revealed notable variations in patient survival across various patient strata. Conclusions: Compared to AJCC staging, the LODDS-based nomograms have a more accurate predictive effectiveness in predicting OS and CSS in patients with rectal cancer. [ABSTRACT FROM AUTHOR]

Background: Comprehensive investigations of the prognosis factors and treatment strategies with adjustment of competing causes of death for patients with malignant meningioma (MM) is still lacking. Patient and method: The surveillance, Epidemiology, and End Results (SEER) database were used to include adult patients with this rare disease between 2004 and 2018. The probability of MM-caused mortality (MMCM) and non-MM-caused mortality (non-MMCM) were presented by cumulative incidence function curves. Then, the association between variates with non-MMCM was evaluated by the cox proportional hazard model, and the prognostic factors of MMCM were identified by Fine-Gray competing risk regression model. Furthermore, a nomogram was developed to predict the 1-year, 2-year, and 5-year MMCM and the performance was tested by a time-dependent area under the receiver operating characteristic (ROC) curve and calibration. Result: 577 patients were included, with a median age of 62 (18–100) years old and a median overall survival time of 36 (0–176) months. The percentage of non-MMCM was 15.4% (n = 89) in the entire population and 21.7% (n = 54) in elderly patients. The multivariable Cox proportional hazard regression model revealed that older age and other tumor(s) before or after MM had an independently significant association with higher non-MMCM. After adjustment of competing causes of death, the multivariable Fine-gray regression model identified age group ≥ 65 year, tumor size > 5.3 cm, recurrent MM, and histologic type 9530/3 (Meningioma, malignant) had an independently significant association with higher MMCM. Compared with gross total (GTR) of tumor, subtotal resection of tumor (HR 1.66, 95%CI 1.08–2.56, P = 0.02), partial resection of lobe (HR 2.26, 95%CI 1.32–3.87, P = 0.003), and gross total resection of lobe (HR 1.69, 95%CI 1.12–2.51, P = 0.01) had an independently significant association with higher MMCM. Conclusion: The competing risk nomogram including age group, tumor size, initial status, histologic type, and extent of resection is discriminative and clinically useful. This study emphasized the importance of the GTR of tumor in the treatment of MM patients, which had a significantly lower incidence of MMCM compared with biopsy, STR of tumor, partial resection of lobe, and GTR of lobe. [ABSTRACT FROM AUTHOR]

Background: The prevalence of papillary thyroid cancer is gradually increasing and the trend of youthfulness is obvious. Some patients may not be able to undergo surgery, which is the mainstay of treatment, due to physical or financial reasons. Therefore, the prediction of cancer-specific survival (CSS) in patients with non-operated papillary thyroid cancer is necessary. Methods: Patients’ demographic and clinical information was extracted from the Surveillance, Epidemiology, and End Results database. SPSS software was used to perform Cox regression analyses as well as propensity score matching analyses. R software was used to construct and validate the nomogram. X-tile software was used to select the best cutoff point for patient risk stratification. Results: A total of 1319 patients were included in this retrospective study. After Cox regression analysis, age, grade, T stage, M stage, radiotherapy, and chemotherapy were used to construct the nomogram. C-index, calibration curves, and receiver operating characteristic curves all verified the high predictive accuracy of the nomogram. The decision curve analysis demonstrated that patients could gain clinical benefit from this predictive model. Survival curve analysis after propensity score matching demonstrated the positive effects of radiotherapy on CSS in non-operated patients. Conclusion: Our retrospective study successfully established a nomogram that accurately predicts CSS in patients with non-operated papillary thyroid cancer and demonstrated that radiotherapy for operated patients can still help improve prognosis. These findings can help clinicians make better choices. [ABSTRACT FROM AUTHOR]

Background: This retrospective study aims to examine the patient demographics, survival rates, and treatment methods for small-cell neuroendocrine carcinoma (SCNEC) and large-cell neuroendocrine carcinoma (LCNEC) of prostate origin while also identifying the main differences between common types of prostate cancer with comparative analysis for survival. Methods: Our analysis utilized the Surveillance, Epidemiology, and End Results database (SEER), and data was collected from 2000–2020. Cox proportional hazards and chi-squared analysis were used for statistical analysis. Results: A total of 718 cases of prostate small and large neuroendocrine carcinoma were identified. The median age was 71.5 years, and the median follow-up was 11.0 years (95% confidence interval (95% CI) = 9.2–12.8). Most patients were over the age of 80 years (33.8%) and Caucasian (74.4%). The overall 5-year survival was 8.0% (95% CI = 6.8–9.2). The 5-year OS for Caucasians was 7.3% (95% C.I. 6.0–8.3). For Black Americans, the 5-year OS was 11.9% (95% C.I. 7.3–16.5). For Hispanics, the 5-year OS was 12.2% (95% C.I. 7.7–16.7). The 5-year cause-specific survival (CSS) was 16.2% (95% CI = 14.3–18.1). For treatment modality, the five-year survival for each were as follows: chemotherapy, 3.5% (95% CI = 2.1–4.9); surgery, 18.2% (95% CI = 13.6–22.8); multimodality therapy (surgery and chemotherapy), 4.8% (95% CI = 1.7–7.9); and combination (chemoradiation with surgery), 5.0% (95% CI = 1.0–9.0). The prognostic nomogram created to predict patient survivability matched the findings from the statistical analysis with a statistical difference found in race, income, housing, stage, and nodal status. The nomogram also indicated a slight increase in mortality with tumors of greater size. This analysis showed a slight increase in mortality for patients of Asian race. In addition, there was a significant increase in death for patients with stage 3 tumors, as well as patients who underwent surgery and radiation. Furthermore, we performed propensity score matching for survival differences, and no survival difference was found between SCNEC and LCNEC. Conclusions: Asian patients, larger tumor size, and distant disease were associated with worse long-term clinical outcomes. By leveraging insights from registry-based studies, clinicians can better strategize treatment options, improving patient outcomes in this challenging oncology arena. [ABSTRACT FROM AUTHOR]

To examine the potential correlation between chemotherapy and the risk of individual of second primary endometrial cancer (SEC) in patients with rectal cancer (RC) and assess survival outcomes. The study employed the Surveillance, Epidemiology, and End Results database (SEER) as the primary data source, it encompasses a substantial cohort of patients diagnosed with RC between 1975 and 2018. This study involved a total of 30,847 individuals diagnosed with RC, of whom 168 individuals (5.45‰) experienced SEC. Among them, 107 patients (3.47‰) received chemotherapy treatment, while 61 patients (1.98‰) did not receive chemotherapy. The analysis of the overall occurrence of SEC revealed a significant association between SEC and chemotherapy treatment. Univariate and multivariate analyses confirmed a significant association between chemotherapy treatment and an increased risk of developing SEC in RC patients. Upon implementation of a dynamic analysis on the variables of relative risk and standardized incidence ratios, the results revealed that the likelihood of SEC escalated in tandem with advancing age. The examination of patients who developed SEC after receiving and not receiving chemotherapy revealed no substantial disparities in the 10-year overall survival (OS) and (cancer-specific survival) CSS rates. The results were the same after propensity score matching. Nevertheless, a notable discrepancy emerged when comparing the OS and CSS rates at 10 years between patients afflicted with SEC subsequent to chemotherapy and those afflicted with primary endometrial cancer, and the result was the same situation in the no-chemotherapy group. The use of chemotherapy in RC patients has been associated with an increased probability of developing specific SEC. Therefore, it is imperative to prioritize efforts aimed at reducing chemotherapy-related SEC occurrences and improving the prognosis of affected individuals. [ABSTRACT FROM AUTHOR]

Background and Aim Methods Results Conclusion Currently, the primary treatment modality for patients with colorectal adenocarcinoma (CRA) is radical surgery combined with postoperative adjuvant chemotherapy (PAC). However, many elderly patients decline PAC due to concerns about their underlying physiological condition, and the impact of PAC on the prognosis of elderly patients remains uncertain.We extracted data from the SEER database for CRA patients aged 75 and above between 2010 and 2019. Utilizing propensity score matching (PSM), we stratified the patients into a PAC group and a non‐PAC group, enabling us to compare the differences in Kaplan–Meier survival curves between these two groups. Furthermore, through univariate and multivariate Cox regression analyses, we identified the clinical factors that influence the survival of elderly CRA patients and compared the prognostic disparities between the two patient groups within specific subgroups of these clinical factors.Following PSM, a total of 3668 patients were included and divided into the PAC group and the non‐PAC group, with no statistically significant differences observed in crucial clinical characteristics between the two groups. Kaplan–Meier analysis revealed a significantly better prognosis for patients in the PAC group compared with those in the non‐PAC group. In addition, age, chemotherapy, TNM staging, gender, and preoperative CEA levels were all identified as important factors affecting patient prognosis. Moreover, PAC provided survival benefits across the majority of levels within the aforementioned subgroups. However, in specific subgroups (age > 90, Grade IV stage, median household income < $40 000), PAC did not confer any survival benefits.PAC can significantly improve the prognosis of elderly CRA patients. Nonetheless, in certain population subsets characterized by specific clinical features, PAC does not provide any survival benefits. [ABSTRACT FROM AUTHOR]

The role of neoadjuvant chemotherapy and its benefits in patients with triple-negative breast cancer (TNBC) and small tumors are unclear. This study aims to compare survival differences between clinical T1 TNBC receiving neoadjuvant chemotherapy (NAC) and adjuvant chemotherapy (AC). Data for patients with clinical T1 TNBC were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Patients were categorized according to whether they received chemotherapy before or after surgery. Propensity Score Matching (PSM) was used to minimize the influence of confounding factors. OS and BCSS were compared between the two treatment sequences using Kaplan–Meier and univariate and multivariable Cox proportional hazards regression analyses. The study included 6249 women with T1 TNBC. In multivariate analysis, compared with that in the AC group, the hazard ratio for death in the NAC group was 1.54 (95% confidence interval 1.26–1.89, p < 0.001). NAC offers no additional benefits in any age group or T, N subgroups. Our findings suggest that NAC does not provide additional benefit to patients with clinical T1 TNBC, even in the presence of lymph node metastasis, or T1c. [ABSTRACT FROM AUTHOR]

Background: Recent data reveal a marked rise in the detection and mortality rates of Desmoplastic Malignant Melanoma (DMM). This trend underscores the imperative for an in-depth analysis of DMM’s epidemiology, which is crucial for the formulation of precise medical and public health strategies. This investigation seeks to elucidate the variations in the incidence and mortality of DMM over a 15-year period (2005–2019). Methods: Data on DMM patients was sourced from the Surveillance, Epidemiology, and End Results (SEER) database. Both incidence and incidence-based mortality rates (IBM) were directly extracted from the SEER database. Joinpoint regression was used to analyze and calculate the average annual percent change (AAPC) and its 95% confidence interval (CI). Results: Between 2005 and 2019, 3,384 DMM cases were identified, boasting an age-adjusted incidence rate of 36.3 cases per 1000,000 person-years (95% CI 3.51–3.76) and an IBM of 1.65cases per 1000,000 person-years (95% CI 1.57–1.74). Of these, 2,353 were males (69.53%) and 1,031 were females (30.47%). There were 1894 patients (55.97%) who were over 70 years old. Predominantly, DMM lesions manifested in exposed areas: Limbs (955, 28.22%), Face (906, 26.77%), and Scalp and Neck (865, 25.56%). The incidence of DMM increased significantly at a rate of APC = 0.9% during 2005–2019, while the incidence-based mortality showed a significant upward trend (APC = 7%) during 2005–2012, and slowly increasing trend (APC = 0.6%) during 2012–2019. In contrast to the modest upward trajectory in female incidence and mortality, male incidence initially surged, later declining, while male mortality peaked and stabilized post-2012. The primary sites for incidence and mortality were chronically sun-exposed areas: Face, Scalp and Neck, and Limbs. Conclusions: In recent years, the incidence and incidence-based mortality of DMM have significantly increased. Each subgroup analysis has different trends, and these trends can provide better support for our exploration of DMM. [ABSTRACT FROM AUTHOR]

Purpose: We intended to investigate the risk for second primary malignancy (SPM) development in Laryngeal Cancer (LC) survivors. We conducted a population-based analysis of SPM risk using the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) database. Methods: Data of selected LC survivors from the SEER database between 2000 and 2020 were examined. Standardized Incidence ratios (SIRs) for SPM development were calculated, followed by detailed stratification according to anatomical site and different latency periods. Results: A total of 8413 SPMs were observed in our extracted cohort. The collective standardized incidence of SPMs was 2.12 (95% CI 2.07–2.17) compared to the US population, with an absolute excess risk (AER) of 201.73 per 10,000 individuals. The highest SPM risks were observed in patients with young age at diagnosis, females, and American Indians/Alaska natives. Increased SPM risks were reported in patients receiving all modalities of treatment including surgery, chemotherapy, and radiotherapy. Most SPMs were detected in solid organs such as the lungs and bronchus, oral cavity and pharynx, and prostate. The highest increased risks of developing SPMs were observed in Trachea, larynx, oral cavity and pharynx, lung and bronchus, and esophagus. Conclusions: The risk of SPMs in LC survivors was significantly increased compared to the general US population. Accordingly, a more impactful cancer surveillance strategy for LC patients should be implemented. [ABSTRACT FROM AUTHOR]

Background: While treatment advancements have prolonged the lives of patients with head and neck cancer, the subgroups of these patients at higher risk for cardiovascular disease (CVD) mortality remain unclear. Methods: We analyzed data from the Surveillance, Epidemiology, and End Results (SEER) database for patients diagnosed with head and neck cancer from 2000 to 2019. We compared their CVD mortality against the general US population using standardized mortality ratios (SMRs). Results: Our analysis included 474,366 patients, identifying that 14% of deaths were due to CVD, with an SMR of 1.19. Notably, patients under the age of 39 had a CVD SMR increase of over 100-fold. Those with distant tumor stages showed the highest CVD SMR of 1.52 (95% CI 1.50–1.54). An upward trend in SMR to 2.53 (95% CI 2.51–2.56) was observed from 2011 to 2019. Within the initial 5-year post-diagnosis, the SMR for CVD was 3.17 (95% CI 3.14–3.20), which exceeded the general population's rates but declined in the 5–20-year range after diagnosis. Patients who did not any therapy had the greatest CVD SMR of 2.26 (95% CI 2.24–2.28). Hypopharyngeal cancer patients exhibited the highest CVD SMR of 1.54 (95% CI 1.52–1.56). Conclusions: The study highlights that head and neck cancer patients, especially younger individuals and those with advanced disease stages, face substantial CVD mortality risks. The CVD SMR peaks within 5 years following diagnosis. Patients abstaining from treatment bear the highest risk of CVD mortality. Cardioprotective measures should be considered critical for this patient population. [ABSTRACT FROM AUTHOR]

Purpose: Many T1-2N0-1M0 triple-negative breast cancer (TNBC) patients who undergo neoadjuvant chemotherapy (NAC) do not receive breast-conserving therapy (BCT) due to concerns about non-pCR or lymph node metastasis presence. Methods: T1-2N0-1M0 TNBC patients who underwent NAC between 2010 and 2017 were collected from the SEER database. Factors affecting surgical modalities were analyzed by multinomial logistic regression. The overall survival (OS) and breast cancer-specific survival (BCSS) were evaluated by Kaplan-Meier curves and Cox proportional hazards models. Further stratified subgroup analyses were performed based on the response to NAC and N-stage. Adjusted-hazard ratios were also calculated to exclude potential bias. Results: A total of 1112 patients were enrolled (median follow-up: 81 months), 58.5% received BCT, 23.6% received reconstruction and 17.9% received mastectomy. Response to NAC and N-stage not only influenced the choice of surgical modality but also were independent predictors for OS and BCSS. The surgery-induced survival differences mainly affect OS. Survival analyses demonstrated that the 10-year OS of BCT was superior or equal to that of mastectomy even in patients with partial response (PR) (77.4% vs. 64.1%, P = 0.013), no response (NR) (44.9% vs. 64.2%, P = 0.33), or N1 stage (75.7% vs. 57.4%, P = 0.0021). In the N1-PR cohort, mastectomy may lead to worse OS (P = 0.0012). Besides, between reconstruction and BCT, there was no statistical difference in OS or BCSS (P > 0.05). Conclusion: Our study reveals the necessity of breast surgical de-escalation. Besides, physicians should actively recommend reconstruction for individuals who strongly desire mastectomy. [ABSTRACT FROM AUTHOR]

Background Methods Results Conclusions Accurate prognostic factors for primary ocular adnexal lymphoma (POAL) are scarce. Survival models and prognostic factors derived without considering competing risk factors suffer from major statistical errors. This study aimed to accurately assess prognostic factors in POAL patients using competing risk models, and compare this to the traditional COX proportional hazards model.This retrospective study utilised data from the Surveillance, Epidemiology, and End Results (SEER) program 2010–2015 and included patients with B‐cell POAL. The cumulative incidence function and Gray's test for cause‐specific survival were calculated as univariate analysis. The competing risk models were a Fine‐Gray subdistribution hazard model and a cause‐specific model, and a traditional COX model was employed as a multivariate analysis.This study enrolled 846 eligible patients with POAL: 60 patients (7.09%) died from POAL and 123 patients (14.54%) died from other causes. Multivariate competing risk models indicated that age, laterality, histology subtype, the 7th edition of American Joint Committee on Cancer stage T, and radiotherapy were independent predictors for cause‐specific survival of patients with POAL. There was high consistency between the two competing risk models. The COX model made several misestimations on the statistical significance and hazard ratios of prognostic factors.This study established competing risk models as a method to assess POAL prognostic factors, which was more accurate than traditional methods that do not consider competing risk elements. [ABSTRACT FROM AUTHOR]

Background: Cancer burden from the elderly has been rising largely due to the aging population. However, research on the long‐term epidemiological trends in cancer of the elderly is lacking. Methods: Registry data of this population‐based cross‐sectional study were from the Surveillance, Epidemiology, and End Results (SEER) database. The study population aged 65 years or more, from geographically distinct regions. Joinpoint regression and JP Surv method were used to analyze cancer trends and survival. Results: Mortality rate during 1975–2020 decreased from 995.20 to 824.99 per 100,000 elderly persons, with an average annual decrease of 0.421% (95% CI, 0.378–0.464). While overall incidence increased with no significance. Prostate (29%) and breast (26%) cancer were the most common malignancies, respectively, in elderly males and females, and the mortality for both of the two (prostate 15%, breast 14%) ranked just behind lung and bronchus cancer, which had the highest mortality rates in males (29%) and females (23%). Many cancers showed adverse trends in the latest follow‐up periods (the last period calculated by the Joinpoint method). For intrahepatic cholangiocarcinoma, incidence (male Annual Percentage Change [APC] = 7.4*; female APC = 6.7*) and mortality (male APC = 3.0*; female APC = 3.3*) increased relatively fast, and its survival was also terrible (3‐year survival only 10%). Other cancers with recent increasing mortality included cancer of anus, anal canal and anorectum, retroperitoneum, pleura, peritoneum, etc. Most cancers had favorable trends of survival during the nearest follow‐up period. Conclusion: Against the background of overall improvement, many cancers showed adverse trends. Further research for the underlying mechanisms and targeted implements towards adverse trends is also urgent. [ABSTRACT FROM AUTHOR]

• In this population-based study that patients with MB, age-adjusted incidence rates remained relatively stable between 1975 and 2019. • Female incidence was stabilizing over time, while male incidence was increasing, with an APC of 0.35.This study evaluated independent prognostic factors associated with survival in patients with MB. • Patients with MB in the high-risk group may benefit from chemotherapy. Medulloblastoma (MB) is a primary brain malignancy. However, updated epidemiological data and long-term outcomes are lacking.The clinical and epidemiological datasets of patients with MB in the current study were obtained from the Surveillance, Epidemiology, and End Results (SEER) databases. Joinpoint regression models were used to assess the rate of changes in the incidence, prevalence, and treatment trends in patients with MB. Cox hazard and competition risk model analyses were used to assess overall survival (OS) and cancer-specific survival (CSS).The age-adjusted incidence of MB remained relatively stable at 0.15 per 100,000 individuals in 2019. The annual percentage change (APC) of females remained stable, whereas that of males increased over time. The 20-year limited-duration prevalence of patients with MB increased significantly from 0.00016 % in 1999 to 0.00203 % in 2018. Patients aged 5–19 years accounted for 46.7 % of all age groups, and the trend for the three treatments was increased. Average annual percentage change (AAPC) for the chemotherapy group was increased in patients aged 20 + years MB [AAPC = 2.66 (95 % CI 0.93–6.31)]. Multivariate analysis revealed that OS and CSS varied significantly according to age, year of diagnosis, histology, stage, surgery, and radiotherapy. Subgroup analysis showed that chemotherapy was associated with a favorable prognosis in high-risk groups.The incidence of MB remained relatively stable, and its prevalence increased significantly. This current population-based study further identified the prognostic factors in patients with MB. Moreover, the use of chemotherapy was associated with better survival in high-risk groups. [ABSTRACT FROM AUTHOR]

Aims/Background Generally, pelvic osteosarcoma has a worse prognosis compared with limb osteosarcoma. This study aims to create and validate a new nomogram for predicting the prognosis of pelvic osteosarcoma. Methods Clinical data of 62 patients derived from the Surveillance, Epidemiology, and End Results (SEER) database and 31 Chinese patients diagnosed with pelvic osteosarcoma were gathered. Kaplan-Meier survival analysis was utilized to calculate the median survival time for all variables. Univariate and multivariate Cox regression models were employed to identify the prognostic factors of pelvic osteosarcoma. A nomogram was constructed using data gleaned from the SEER cohort and verified using the receiver operating characteristic (ROC) curve and calibration plot in the Chinese cohort. Results Kaplan-Meier analysis revealed that individuals of other races (Asians) (hazard ratio (HR) = 0.24, 95% confidence interval (CI): 0.1–0.57, p = 0.001), aged ≤51 years old (HR = 0.4, 95% CI: 0.22–0.73, p = 0.003), and with tumor size ≤160 mm (HR = 0.37, 95% CI: 0.2–0.71, p = 0.03) had better survival outcomes. Conversely, factors such as no primary surgery (HR = 3.6, 95% CI: 1.81–7.15, p < 0.001), lung metastasis (HR = 1.96, 95% CI: 1.17–3.28, p = 0.010), and radiotherapy (HR = 1.89, 95% CI: 1.10–3.25, p = 0.021) were associated with poorer survival. Multivariate Cox analysis indicated that lung metastasis (HR = 2.57, 95% CI: 1.29–5.13, p = 0.008), other races (Asians) (HR = 0.23, 95% CI: 0.07–0.75, p = 0.015), tumor size (HR = 0.28, 95% CI: 0.13–0.62, p = 0.001) and age (HR = 0.3, 95% CI: 0.16–0.59, p < 0.001) were independent prognostic factors for pelvic osteosarcoma. Univariate and multivariate Cox regression models identified three independent variables in the training cohort: age, lung metastasis, and tumor size. A predictive nomogram was developed based on the data from the SEER cohort and validated in the Chinese cohort. The areas under the curves (AUCs) that are used to predict 1-year, 2-year, and 3-year survival rates were 0.81 (95% CI: 0.68–0.94), 0.75 (95% CI: 0.63–0.86), and 0.80 (95% CI: 0.70–0.89) in the training cohort, and 0.67 (95% CI: 0.30–1.04), 0.66 (95% CI: 0.43–0.90) and 0.71 (95% CI: 0.50–0.93) in the validation cohort. Conclusion The predictive nomogram constructed in this study facilitates accurate and effective prediction of the overall survival of patients with pelvic osteosarcoma and helps enhance the clinical decision-making process. [ABSTRACT FROM AUTHOR]

Lymph node metastasis (LNM) is one of the crucial factors in determining the optimal treatment approach for colorectal cancer. The objective of this study was to establish and validate a column chart for predicting LNM in colon cancer patients. We extracted a total of 83,430 cases of colon cancer from the Surveillance, Epidemiology, and End Results (SEER) database, spanning the years 2010–2017. These cases were divided into a training group and a testing group in a 7:3 ratio. An additional 8545 patients from the years 2018–2019 were used for external validation. Univariate and multivariate logistic regression models were employed in the training set to identify predictive factors. Models were developed using logistic regression, LASSO regression, ridge regression, and elastic net regression algorithms. Model performance was quantified by calculating the area under the ROC curve (AUC) and its corresponding 95% confidence interval. The results demonstrated that tumor location, grade, age, tumor size, T stage, race, and CEA were independent predictors of LNM in CRC patients. The logistic regression model yielded an AUC of 0.708 (0.7038–0.7122), outperforming ridge regression and achieving similar AUC values as LASSO regression and elastic net regression. Based on the logistic regression algorithm, we constructed a column chart for predicting LNM in CRC patients. Further subgroup analysis based on gender, age, and grade indicated that the logistic prediction model exhibited good adaptability across all subgroups. Our column chart displayed excellent predictive capability and serves as a useful tool for clinicians in predicting LNM in colorectal cancer patients. [ABSTRACT FROM AUTHOR]

For patients with hepatoblastoma (HB), current staging system is not accurate in predicting survival outcomes. The aim of this study was to develop two accurate survival prediction models to guide clinical decision making. A retrospective analysis of 424 HB patients was performed from 2004 to 2015 using the Surveillance, Epidemiology and End Results (SEER) database. Univariate and multivariate Cox regression analysis was used to screen for variables. The identified variables were used to build survival prediction model. The performance of the nomogram models was assessed based on the concordance index (C-index), calibration plot, and receiver operating characteristic (ROC) curve. The Cox regression analysis identified six variables affecting overall survival (OS) in HB patients, including race, tumor size, lymph node involvement, distant metastases, surgery and chemotherapy. And the Cox regression analysis identified five variables including race, lymph node involvement, distant metastases, surgery, and chemotherapy that affect cancer-specific survival (CCS) in HB patients. In the training cohort, the C-index of the nomogram in predicting the OS was 0.791 [95% confidence intervals (95% CI) 0.717–0.865], CSS was 0.805(95% CI 0.728–0.882). In the validation cohort, the C-index of the nomogram in predicting the OS was 0.712 (95% CI 0.511–0.913), the CSS was 0.751 (95% CI 0.566–0.936). In the training cohort, the area under the receiver operator characteristics curve (AUC) values of the nomogram in prediction of the 1-, 3-, and 5-year OS were 0.842 (95% CI 0.739–0.944), 0.759 (95% CI 0.670–0.849), and 0.770 (95% CI 0.686–0.852), respectively. In the validation cohort, the AUC values for prediction of the 1-, 3-, and 5-year OS were 0.920 (95% CI 0.806–1.034), 0.863 (95% CI 0.750–0.976), and 0.844 (95% CI 0.721–0.967), respectively. Two nomogram models were developed and validated in this study which provided accurate prediction of the OS and CSS in HB patients. The constructed models can be used for predicting survival outcomes and guide treatment for HB patients. [ABSTRACT FROM AUTHOR]

Background: Oncology databases that integrate genomic and clinical data have become valuable resources for precision medicine. However, the generalizability of these databases has not been comprehensively assessed. Objectives: To describe the demographics, clinical characteristics, treatments, and overall survival of breast cancer cohorts in GENIE‐BPC and three other databases. Methods: This study utilized GENIE‐BPC, SEER, SEER‐Medicare, and Merative MarketScan Research Databases. Women with invasive breast cancer were identified through EHR, cancer registries or ICD‐9/10‐CM codes. The ages were 18+ years or per database requirement. Treatments were based on EHR or HCPCS/NDC codes in claims. Overall survival was estimated as time from diagnosis to death. Results: Of female breast cancer patients in GENIE‐BPC (n = 775), SEER (n = 548 336), SEER‐Medicare (n = 68 914), and Marketscan (n = 109 499) databases, the median ages at initial diagnosis were 44, 62, 74, and 57 years, respectively. A greater proportion of patients in GENIE‐BPC, compared to SEER/SEER‐Medicare, had higher nuclear grades (%III–%IV: 57% vs. 26%/24%), advanced disease stage (%IV: 25.3% vs. 5%/3.6%), percent of triple negative breast cancer (19.7% vs. 10.2%/8.5%), and receipt of chemotherapy (85.0% vs. NA/22.3%). The 1‐, 3‐, and 5‐year overall survival rates were lower in GENIE‐BPC (78.5%, 60.5%, 55.5%) than in SEER (95.8%, 89.5%, 85.5%) and SEER‐Medicare (91.6%, 81.4%, 75.0%). Conclusion: Breast cancer patients in GENIE‐BPC were younger, had more advanced disease, had a higher proportion of triple negative breast cancer and recipients of chemotherapy, and had poorer overall survival. Researchers must use statistical adjustment when extrapolating results (e.g., biomarker prevalence) from GENIE‐BPC to the larger breast cancer population. [ABSTRACT FROM AUTHOR]

This study aimed to explore the factors affecting the overall survival (OS) of giant hepatocellular carcinoma (G-HCC) patients and establish a nomogram and an Internet-based OS calculator for evaluating the OS of G-HCC patients. A total of 2445 G-HCC patients were searched in the SEER database. The independent variables affecting OS of G-HCC patients were determined by univariate and multivariate analyses, and a nomogram and Internet-based OS calculator were established. The accuracy of the nomogram was evaluated by the C-index, the AUC curve, and calibration curve. Grade, surgery, radiotherapy, chemotherapy, T-staging, M-staging, AFP, and fibrosis were identified as independent variables affecting OS. These variables were included in the nomogram model and Internet-based OS calculator to evaluate OS in G-HCC patients. The C-indices and AUC of the nomogram are better than AJCC-staging system. Similarly, the calibration curves revealed that the actual survival was consistent with nomogram-based survival. The nomogram and Internet-based OS calculator are superior to the traditional AJCC-staging system in the reliability and convenience of prognosis assessment for G-HCC patients, which is more conducive for clinicians to predict the survival of G-HCC patients and make the best treatment strategy. [ABSTRACT FROM AUTHOR]

Currently, there is no consensus regarding the extent of surgery for stage I pulmonary carcinoid (PC) tumors, which encompass typical carcinoid (TC) and atypical carcinoid (AC) tumors. Sublobar resection includes segmental resection and wedge resection; the former is regarded as a type of anatomical resection that is better suited for tumor treatment. Therefore, it needs to be further verified whether differences exist in the effects of the two surgical methods on the survival time of patients. Propensity score matching (PSM) was used. The primary endpoints were cancer-specific survival (CSS) and overall survival (OS) time. Survival differences were analyzed via the Kaplan–Meier method and the log-rank test. There was no significant difference in survival between the sublobar resection and lobectomy groups after PSM in either the TC or AC tumor groups (all p > 0.05). A total of 1680 patients underwent pulmonary wedge resection (TC: n = 1547, AC: n = 133), and 398 patients underwent segmental resection (TC: n = 365, AC: n = 33). After PSM, there were no statistically significant differences in survival, regardless of whether OS or CSS was considered the primary endpoint (OS: p = 0.337; CSS: p = 0.470). Furthermore, segmental resection did not prolong patient survival time compared with wedge resection in different subgroup analyses on the basis of histology, age, and tumor size (all p > 0.05). Finally, the same results were obtained via multivariate Cox analysis (OS: p = 0.153; HR = 1.21; CSS: p = 0.351, HR = 1.32). Sublobar resection could be considered for patients with early-stage typical or atypical pulmonary carcinoid, provided that a rigorous lymph node evaluation is conducted. If the tumor is distant from the pulmonary hilum, either segmentectomy or wedge resection may be performed depending on the specific location of the tumor and the clinical condition of the patient. [ABSTRACT FROM AUTHOR]

We aimed to assess the cumulative incidences of cancer-specific mortality (CSM) in non-metastatic patients with non‑muscle invasive urothelial bladder cancer (NMIUBC) and establish competing risk nomograms to predict CSM. Patient data was sourced from the Surveillance, Epidemiology, and End Results database, as well as the electronic medical record system in our institution to form the external validation cohort. Sub-distribution proportional hazards model was utilized to determine independent risk factors influencing CSM in non-metastatic NMIUBC patients. Competitive risk nomograms were constructed to predict 3-year, 5-year, and 8-year cancer-specific survival (CSS) in all patients group, TURBT group and cystectomy group, respectively. The discrimination and accuracy of the model were validated through the concordance index (C-index), the area under the receiver operating characteristic curve (AUC), and calibration curves. Decision curve analysis (DCA) and a risk stratification system was employed to evaluate the clinical utility of the model. Race, age, marital status, surgery in other sites, tumor size, histological type, histological grade, T stage and N stage were identified as independent risk factors to predict CSS in all patients group. The C-index for 3-year CSS was 0.771, 0.770 and 0.846 in the training, testing and external validation sets, respectively. The ROC curves showed well discrimination and the calibration plots were well fitted and consistent. Moreover, DCA demonstrated well clinical effectiveness. Altogether, the competing risk nomogram displayed excellent discrimination and accuracy for predicting CSS in non-metastatic NMIUBC patients, which can be applied in clinical practice to help tailor treatment plans and make clinical decisions. [ABSTRACT FROM AUTHOR]

Few studies have investigated the impact of primary tumor resection (PTR) on patients with distant metastasis medullary thyroid carcinoma (DMMTC). This population-based study aims to assess the application of PTR in DMMTC patients, ascertain its benefits, and identify optimal surgical indications. DMMTC Patients diagnosed between 2010 and 2020 were included through the Surveillance, Epidemiology, and End Results (SEER) program. Logistic regression analysis identified driving factors of surgical decision-making. Propensity score matching (PSM), Kaplan–Meier method, and Cox regression were utilized to compare overall survival (OS) and disease-specific survival (DSS) between surgical and non-surgical groups. Subgroup analyses were performed to determine optimal surgical indications. Of 238 DMMTC patients included, 122 (51.3%) patients underwent PTR. Extrathyroidal extension and N1 stage emerged as independent factors promoting the surgical decision. PSM-adjusted survival analyses revealed significant advantages in both OS and DSS for the surgical group. Moreover, subgroup analyses indicated that except for patients aged ≥ 65 years, tumors ≤ 20 mm, or with multiple metastasized sites (> 1), the others significantly benefit from PTR. PTR significantly improves prognosis in selected DMMTC patients. The decision to undergo PTR in other patients should be based on a comprehensive assessment of the disease, surgeon's experience, and family discussions for potential survival benefits. [ABSTRACT FROM AUTHOR]

Objective Methods Results Conclusions Investigating treatment modalities' association with second primary malignancy risk in early‐stage head and neck squamous cell carcinoma (HNSCC).Data of 5‐year survivors of early‐stage (stages I–II, seventh TNM staging manual) HNSCC from 2000 to 2020 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Standardized incidence ratio and excess absolute risk were used to assess second primary malignancy (SPM) development externally. Relative risk was estimated to compare SPM risk within groups. Fine‐Gray's model estimated cumulative incidence of second primary malignancy.Overall, 8957 5‐year survivors with early‐stage HNSCC were enrolled. Patients receiving definitive radiotherapy had poorer survival than surgery patients. Surgery correlated with lower risk of second primary malignancy (RR = 0.89, 95% CI 0.80–0.99), especially for oropharyngeal squamous cell carcinoma (RR = 0.56, 95% CI 0.39–0.82). Differences in the risk of second primary malignancy among subgroups based on clinical characteristics were not significant. Treatment modalities did not significantly affect risk of second primary malignancy within each subgroup.Surgery led to better survival and lower risk of second primary malignancy compared to definitive radiotherapy in 5‐year survivors. Incidence and sites of second primary malignancy varied by primary sites, emphasizing targeted long‐term surveillance's importance. [ABSTRACT FROM AUTHOR]

Background and Purpose: The tumour-node metastasis (TNM) classification is a common model for evaluating the prognostic value of tumour patients. However, few models have been used to predict the survival outcomes of patients with colorectal cancer liver metastasis (CRLM) with unresectable metastases who received the primary local surgery. Thus, we utilized the Surveillance, Epidemiology, and End Results (SEER) database to establish novel nomograms for predicting the overall survival (OS) and cancer-specific survival (CSS) of these patients. Methods: Extracted primary data on CRLM patients by local surgery from SEER database. All prognostic factors of OS and CSS were determined by Cox regression analysis. The concordance index (C-index), receiver operating characteristic (ROC) curves and calibration curves were used to further evaluate the accuracy and discrimination of these nomograms. Decision curve analysis (DCA) was executed to evaluate the nomograms for the clinical net benefit. Risk stratification analysis (RSA) was used to evaluate the reliability of them in clinical. Results: 3622 eligible patients were screened and assigned to training cohort (1812) or validation cohort (1810). The age, chemotherapy, tumour grade, primary tumour site, tumour size, lymph node positive rate (LNR), marital status, and carcinoembryonic antigen (CEA) were independent prognostic factors of OS. Additionally, the age, chemotherapy, tumour grade, primary tumour site, tumour size, LNR, and CEA were independent prognostic factors of CSS. The results of C-indexes and ROC curves indicated that the established nomograms exhibited better discrimination power than TNM classification. The calibration curves demonstrated excellent agreement between the predicted and actual survival rates for 1-, 3-, and 5 year OS and CSS. Meanwhile, the validation cohort demonstrated similar results. Background the clinic context, the DCA showed that these nomograms have higher net benefits, and the RSA showed that patients were further divided into low risk, medium risk, and high risk groups according to the predicted scores from nomograms. And, the Kaplan–Meier curve and log-rank test showed that the survival differences among the three groups are statistically significant. Conclusions: The prognostic nomograms showed very high accuracy, identifiability, and clinical practicality in predicting the OS and CSS of CRLM patients with unresectable metastases treated by local surgery at 1-, 3-, and 5 years, which might improve individualized predictions of survival risks and help clinicians formulate treatment plans. [ABSTRACT FROM AUTHOR]

Objective: The prognostic factors of diffuse GC patients were screened the prognostic nomogram was constructed, and the prediction accuracy was verified. Methods: From 2006 to 2018, there were 2877 individuals pathologically diagnosed with diffuse gastric cancer; the clinicopathological features of these patients were obtained from the SEER database & randomly divided into a training cohort (1439) & validation cohort (1438).To create prognostic nomograms & choose independent prognostic indicators to predict the overall survival (OS) of 1, 3, & 5 years, log-rank & multivariate COX analysis were utilized & discrimination ability of nomogram prediction using consistency index and calibration curve. Results: Age, T, N, M, TNM, surgical status, chemotherapy status, & all seven markers were independent predictors of OS (P < 0.05), & a nomogram of OS at 1, 3, & 5 years was created using these independent predictors. The nomogram's c-index was 0.750 (95% CI 0.734 ~ 0.766), greater than the TNM staging framework 0.658 (95%CI 0.639 ~ 0.677); the c-index was 0.753 (95% CI 0.737 ~ 0.769) as well as superior to the TNM staging mechanism 0.679 (95% CI 0.503–0.697). According to the calibration curve, the projected survival rate using the nomogram & the actual survival rate are in good agreement. Conclusions: Prognostic nomograms are useful tools for physicians to assess every individual's individualised prognosis & create treatment strategies for those with diffuse gastric cancer. They can reliably predict the prognosis for individuals with diffuse gastrointestinal carcinoma. [ABSTRACT FROM AUTHOR]

Background: Anaplastic thyroid cancer (ATC) is highly invasive, prone to distant metastasis (DM), and has a very poor prognosis. This study aims to construct an accurate survival prediction model for ATC patients with DM, providing reference for comprehensive assessment and treatment planning. Methods: We extracted data of ATC patients with DM diagnosed between 2004 and 2019 from the SEER database, randomly dividing them into a training set and a validation set in a ratio of 7:3. Univariate and multivariate Cox regression analyses were sequentially performed on the training set to identify independent prognostic factors for overall survival (OS) and construct nomograms for 3-month, 6-month, and 8-month OS for ATC patients with DM based on all identified independent prognostic factors. Receiver operating characteristic (ROC) curve analysis, decision curve analysis (DCA) curve analysis, and calibration curves were separately plotted on the training and validation sets to demonstrate the model's performance. Furthermore, patients were stratified into high- and low-risk groups based on their risk scores, and the Kaplan-Meier (KM) survival curves were used to illustrate the survival differences between the two groups. Results: A total of 322 patients were included in this study. Univariate and multivariate Cox regression analyses identified five independent prognostic factors for OS in ATC patients with DM: surgery, tumor size, age, chemotherapy, and radiotherapy. Nomograms for 3-month, 6-month, and 8- month OS were established based on these factors. The training set AUC values (3-month AUC: 0.767, 6-month AUC: 0.789, 8-month AUC: 0.795) and validation set AUC values (3-month AUC: 0.753, 6-month AUC: 0.798, 8-month AUC: 0.806) as well as the calibration curves demonstrated excellent applicability and accuracy of the model. Additionally, the DCA curves indicated substantial clinical net benefit of the model. The KM curves also confirmed the model's excellent stratification ability for patient OS. Conclusion: The nomogram developed in this study accurately predicts OS for ATC patients with DM. It can assist clinicians in formulating appropriate treatment strategies for these patients. [ABSTRACT FROM AUTHOR]

Introduction: Laryngeal cancers account for one-third of all head and neck cancers. We aimed to report the incidence trends of laryngeal cancer over 2000–2020 in the United States (US), by age, sex, race/ethnicity, and histological subtypes. Methods: Data from the Surveillance, Epidemiology, and End Results 22 database were used to identify patients with laryngeal cancer based on the International Classification of Diseases for Oncology, version 3. Age-standardized incidence rates (ASIRs) for laryngeal cancer, adjusted for reporting delays, were calculated. The Joinpoint Regression Program was then utilized to determine annual percent changes (APCs) and average annual percent changes (AAPCs) in the trends. The analysis excluded data from 2020 to prevent potential bias related to the COVID-19 pandemic. Results: A total of 104,991 cases of laryngeal cancer were identified in the US from 2000 to 2019. Squamous cell carcinoma was the predominant subtype, accounting for 94.53% of cases. Above 73.20% occurred among non-Hispanic whites, with the highest incidence observed among individuals aged 55–69 years (46.71%). The ASIRs were 5.98 and 1.25 per 100,000 population for men and women, respectively. Over 2000–2019, there was a significant reduction in ASIRs for laryngeal cancer in both sexes. Non-Hispanic black men exhibited the highest ASIR (9.13 per 100,000) and the largest decline in the ASIRs over 2000–2019 (AAPC: -3.26%). Conclusions: Laryngeal cancer incidence rates showed a decline from 2000 to 2019, in addition to 2020, during the COVID-19 pandemic. Additional research is required to investigate risk factors and their influence on incidence rates of laryngeal cancer. [ABSTRACT FROM AUTHOR]

Small cell lung cancer (SCLC) patients exhibit significant heterogeneity in tumor burden, physical condition, and responses to initial treatment. This diversity in treatment responses can result in varying treatment outcomes. The primary objective of this study was to explore the patient demographics associated with improved survival outcomes through radiotherapy. Based on the SEER database, we identified 42,824 SCLC patients enrolled between 2004 and 2015. These patients were stratified into radiotherapy (n = 20,360) and non-radiotherapy groups (n = 22,464). We controlled for confounding factors using propensity score matching (PSM) analysis. Subsequently, Kaplan–Meier (KM) analysis was employed to evaluate the impact of radiotherapy on patients' overall survival (OS) and cancer-specific survival (CSS). Cancer-specific mortality was further analyzed using competitive risk models. Cox analysis was also conducted to examine additional variables potentially affecting the survival of SCLC patients. We identified a total of 42,824 eligible patients, and following PSM, 13,329 patients were successfully matched in both the radiotherapy and non-radiotherapy groups. The KM analysis showed that the median OS was 9 months in the radiotherapy group and 6 months in the non-radiotherapy group. The median CSS was 10 months in the radiotherapy group and 7 months in the non-radiotherapy group. The 5-year OS and 10-year OS rates were 6.2% versus 1.6% in the radiotherapy group and 2.6% versus 0.8% in the non-radiotherapy group (P < 0.001). Competitive risk analysis showed that cancer-specific mortality was significantly higher in the non-radiotherapy group than in the radiotherapy group (P < 0.001). Multivariate Cox analysis showed that the radiotherapy group (relative non-radiotherapy group) showed a significant positive effect on survival outcomes (OS: HR 0.658 95% CI [0.642, 0.675] P < 0.001; CSS: HR 0.662 95% CI [0.645, 0.679], P < 0.001). In addition, age, gender, race, primary tumor site, T stage, N stage, M stage, chemotherapy, and surgery were also considered as important predictors of SCLC outcome. The results of the subgroup analysis showed that the radiotherapy group showed a significant survival advantage regardless of age, sex, race, primary tumor site, M stage, chemotherapy, and surgery (P < 0.001). Radiotherapy may improve both OS and CSS in SCLC patients. Patients with SCLC may benefit from radiotherapy regardless of age, sex, race, primary tumor site, M stage, chemotherapy, and surgery. [ABSTRACT FROM AUTHOR]

Anaplastic oligodendroglioma (AOD) is a rare high-grade central nervous system tumor. The current research on prognostic prediction of AOD remains limited. This study aimed to identify prognostic factors and establish the nomograms to predict overall survival (OS) and cancer-specific survival (CSS) for patients with AOD. Patients diagnosed with AOD between 1992 and 2020 were extracted from the Surveillance, Epidemiology, and End Result database. We performed univariate and multivariate Cox regression analyses to identify independent prognostic factors based on the training group. Kaplan-Meier survival curves were used to compare the impact of various independent factors on patient prognosis. For OS and CSS, the nomograms were constructed and verified by the validation group. Harrell''s concordance index, receiver operating characteristic curves, calibration curves, and decision curve analyses were used to assess the discrimination, consistency, and clinical value of the nomograms. A total of 1202 AOD patients were enrolled, being randomly divided into training (n = 841) and validation (n = 361) groups (7:3 ratio). Univariate and multivariate Cox analysis identified 4 significant independent factors (tumor site, age, surgery, and chemotherapy). For OS and CSS, Harrell''s concordance index were 0.731 (0.705–0.757) and 0.728 (0.701–0.754) in the training group, 0.688 (0.646–0.731) and 0.684 (0.639–0.729) in the validation group, respectively. Receiver operating characteristic curves and Calibration curves showed good discrimination and consistency, respectively. In addition, the decision curve analyses curves showed the nomograms have good clinical benefits. We successfully established the nomograms to predict the OS and CSS for AOD patients. The nomograms showed good performance in prognostic prediction, assisting clinicians in evaluating patient prognosis and personalizing treatment plans. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to construct a competing risk prediction model for predicting specific mortality risks in endometrial cancer patients from the SEER database based on their demographic characteristics and tumor information. Methods: We collected relevant clinical data on patients with histologically confirmed endometrial cancer in the SEER database between 2010 and 2015. Univariate and multivariate competing risk models were used to analyze the risk factors for endometrial cancer‐specific death, and a predictive nomogram was constructed. C‐index and receiver operating characteristic curve (ROC) at different time points were used to verify the accuracy of the constructed nomogram. Results: There were 26 109 eligible endometrial cancer patients in the training cohort and 11 189 in the validation cohort. Univariate and multivariate analyses revealed that Age, Marriage, Grade, Behav, FIGO, Size, Surgery, SurgOth, Radiation, ParaAortic_Nodes, Peritonea, N positive, DX_liver, and DX_lung were independent prognostic factors for specific mortality in endometrial cancer patients. Based on these factors, a nomogram was constructed. Internal validation showed that the nomogram had a good discriminative ability (C‐index = 0.883 [95% confidence interval [CI]: 0.881–0.884]), and the 1‐, 3‐, and 5‐year AUC values were 0.901, 0.886 and 0.874, respectively. External validation indicated similar results (C‐index = 0.883 [95%CI: 0.882–0.883]), and the 1‐, 3‐, and 5‐ AUC values were 0.908, 0.885 and 0.870, respectively. Conclusion: We constructed a competing risk model to predict the specific mortality risk among endometrial cancer patients. This model has favorable accuracy and reliability and can provide a reference for the development and update of endometrial cancer prognostic risk assessment tools. [ABSTRACT FROM AUTHOR]

Background: Small intestinal stromal tumors (SISTs) are a rare type of mesenchymal tumor. Gender is known to influence the incidence and prognosis of various tumors, but its role on the survival of SISTs at the population level remains unclear. Therefore, we aim to explore the relationship between gender and the prognosis of SISTs using the Surveillance, Epidemiology, and End Results (SEER) database. Methods: Data on SISTs patients from 2000 to 2019 were derived from the SEER database. Multiple imputation was used to address missing data. Kaplan–Meier analyses and Cox proportional hazard models were applied to evaluate the impact of demographic and clinical characteristics on overall survival (OS) and cancer-specific survival (CSS). Results: A total of 3513 patients with SISTs were analyzed, including 1921 males and 1592 females. Kaplan–Meier analysis coupled with log-rank testing demonstrated a significantly higher mortality rate among male patients compared to females (P < 0.001). Notably, female patients exhibited superior OS (hazard ratio [HR] 0.808, 95% confidence interval [CI] 0.724–0.902, P < 0.001) and CSS (HR 0.801, 95% CI 0.692–0.927, P = 0.003) compared to male patients. While the mean 1-year CSS rates were comparable between genders (95.3% for males vs. 96.0% for females, P = 0.332), male patients consistently showed lower mean survival rates at 3-, 5-, and 10-year intervals. Surgical intervention significantly boosted 5-year OS and CSS rates in both male and female patients (P < 0.001). Multivariate Cox regression analysis identified age, sex, grade, TNM stage, surgery, and mitotic rate as independent risk factors for OS and CSS in patients with SISTs. Conclusions: Our findings suggest that male patients with SISTs have a higher risk of mortality compared to female patients, indicating that gender may serve as a predictive indicator for survival in this patient population. [ABSTRACT FROM AUTHOR]

Background: Small intestinal stromal tumors (SISTs) typically require surgical treatment. However, the impact of lymphadenectomy (LA) on long-term prognosis in patients remains unclear. Therefore, we plan to analyze the effect of LA on the prognosis of patients with SISTs using the Surveillance, Epidemiology, and End Results (SEER) database. Methods: Data on SISTs patients between 2000 and 2019 were obtained from the SEER database. Multiple imputation (MI) was employed to handle missing data, while propensity score matching (PSM) was conducted to mitigate selection bias in the comparative assessments between the LA group and the No-LA group. Kaplan–Meier analyses and multivariate Cox proportional hazards models were utilized to evaluate both overall survival (OS) and cancer-specific survival (CSS). Results: A total of 2412 patients diagnosed with SISTs were included in the study, with 879 undergoing LA and 1533 not undergoing LA. There were no significant differences observed between the two cohorts concerning long-term OS (hazard ratio [HR] 0.97, 95% confidence interval [CI] 0.84–1.13, P = 0.720) and CSS (HR 1.05, 95% CI 0.86–1.29, P = 0.622). After PSM, 1596 patients (798 in the LA group and 789 in the No-LA group) were matched for comparison. There was also no difference in long-term OS and CSS between the two groups. Subgroup analysis revealed that in the age group > 60 years, the CSS in the No-LA group was superior to that in the LA group. Multivariate Cox regression analysis revealed that age, M stage, marital status, and mitotic rate are significant risk factors influencing OS and CSS. Conclusions: Conducting LA in patients with SISTs does not enhance long-term prognosis. For patients aged over 60 years, it may be more advisable to refrain from performing LA. [ABSTRACT FROM AUTHOR]

Introduction: Right hemicolectomy (RHC) remains the treatment standard for goblet cell adenocarcinoma (GCA), despite limited evidence supporting survival benefit. This study aims to explore factors influencing surgical management and survival outcomes among patients treated with RHC or appendicectomy using NCRAS (UK) and SEER (USA) data. Methods: A retrospective analysis was conducted using 998 (NCRAS) and 1703 (SEER) cases. Factors influencing procedure type were explored using logistic regression analyses. Overall survival (OS) probabilities and Kaplan–Meier (KM) plots were generated using KM analysis and the log-rank test compared survival between groups. Cox regression analyses were performed to assess hazard ratios. Results: The NCRAS analysis revealed that age and regional stage disease were determinants of undergoing RHC, with all age groups showing similar odds of receiving RHC, excluding the 75+ age group. The SEER analysis revealed tumour size > 2 cm, and receipt of chemotherapy were determinants of undergoing RHC, unlike the distant stage, which was associated with appendicectomy. Surgery type was not a significant predictor of OS in both analyses. In NCRAS, age and stage were significant predictors of OS. In SEER, age, stage, and Black race were significant predictors of worse OS. Conclusions: The study shows variations in the surgical management of GCA, with limited evidence to support a widespread recommendation for RHC. [ABSTRACT FROM AUTHOR]

Sentinel lymph node biopsy (SLNB) has gained considerable attention in the management of head and neck cutaneous squamous cell carcinoma (HNcSCC). The aim of this study was to compare the oncologic outcomes between observation and SLNB in cN0 high-risk HNcSCC patients. We retrospectively enrolled patients from the SEER database and evaluated the impact of observation versus SLNB on disease-specific survival (DSS) and overall survival (OS) using a Propensity Score Matching (PSM) analysis. A total of 9804 patients were included, with 1169 cases treated by SLNB. Successful retrieval of the sentinel lymph node was achieved in 1130 procedures. After PSM and subsequent multivariate analysis, SLNB was found to be an independent predictor for improved DSS, with a hazard ratio of 0.70 (95% confidence interval: 0.56–0.86). In patients presenting with two or three high-risk factors, SLNB was associated with better DSS (p = 0.021 and p = 0.044), but similar OS (p = 0.506 and p = 0.801) when compared to observation. However, in patients exhibiting four high-risk factors, SLNB demonstrated significantly improved DSS (p = 0.040) and OS (p = 0.028) compared to observation. Our findings suggest that SLNB is a highly feasible technique in HNcSCC and provides significant survival benefits. It is strongly recommended in patients with two or more high-risk factors, as it can help guide treatment decisions and improve patient outcomes. [ABSTRACT FROM AUTHOR]

Purpose: Signet ring cell carcinoma (SRCC) is a rare type of lung cancer. The conventional survival nomogram used to predict lung cancer performs poorly for SRCC. Therefore, a novel nomogram specifically for studying SRCC is highly required. Methods: Baseline characteristics of lung signet ring cell carcinoma were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox regression and random forest analysis were performed on the training group data, respectively. Subsequently, we compared results from these two types of analyses. A nomogram model was developed to predict 1-year, 3-year, and 5-year overall survival (OS) for patients, and receiver operating characteristic (ROC) curves and calibration curves were used to assess the prediction accuracy. Decision curve analysis (DCA) was used to assess the clinical applicability of the proposed model. For treatment modalities, Kaplan-Meier curves were adopted to analyze condition-specific effects. Results: We obtained 731 patients diagnosed with lung signet ring cell carcinoma (LSRCC) in the SEER database and randomized the patients into a training group (551) and a validation group (220) with a ratio of 7:3. Eight factors including age, primary site, T, N, and M.Stage, surgery, chemotherapy, and radiation were included in the nomogram analysis. Results suggested that treatment methods (like surgery, chemotherapy, and radiation) and T-Stage factors had significant prognostic effects. The results of ROC curves, calibration curves, and DCA in the training and validation groups demonstrated that the nomogram we constructed could precisely predict survival and prognosis in LSRCC patients. Through deep verification, we found the constructed model had a high C-index, indicating that the model had a strong predictive power. Further, we found that all surgical interventions had good effects on OS and cancer-specific survival (CSS). The survival curves showed a relatively favorable prognosis for T0 patients overall, regardless of the treatment modality. Conclusions: Our nomogram is demonstrated to be clinically beneficial for the prognosis of LSRCC patients. The surgical intervention was successful regardless of the tumor stage, and the Cox proportional hazard (CPH) model had better performance than the machine learning model in terms of effectiveness. [ABSTRACT FROM AUTHOR]

Lung cancer, the second most prevalent form of cancer with the highest mortality rate, necessitates the stratification of patients based on their survival rates to develop effective treatment strategies. This study presents a two-stage framework for predicting lung cancer survival. The initial stage, classification, focuses on forecasting the five-year survival probability of lung cancer patients. Subsequent analysis was conducted on patients accurately classified as deceased during this stage. The second stage, regression, predicts the actual survival duration in months for deceased patients. This analysis employs the widely recognized Surveillance, Epidemiology, and End Results (SEER) database. To reduce dimensionality, two feature selection techniques, Recursive Feature Elimination with Random Forest (RFE-RF) and the Least Absolute Shrinkage and Selection Operator (LASSO), were adopted. Machine learning models were then trained using five-fold cross-validation for both classification and regression. Experimental results demonstrate that ensemble methods outperform other algorithms, including Logistic Regression (LR), Random Forest (RF), Multilayer Perceptron (MLP), Adaboost, and Naïve Bayes (NB), in terms of performance metrics. The existing techniques offer high accuracy for shorter survival periods, particularly for survival times of up to 6 months. Notably, the Light Gradient Boosting Machine (LGBM) classifier combined with RFE-RF achieves the highest classification accuracy of 89.6% and an area under the receiver operating characteristic (ROC) curve (AUC) score of 92.03 for survival durations up to 11 months. In regression analysis, the LGBM regressor outperforms its counterparts with a Mean Absolute Error (MAE) value of 7.53 and a Root Mean Squared Error (RMSE) value of 10.49. The study critically evaluates various cost functions' effectiveness in regression, validating the accuracy of survival duration predictions for the given dataset. [ABSTRACT FROM AUTHOR]

Abstract Hodgkin lymphoma (HL) is a rare malignancy affecting the lymphatic system. Our study examined the incidence rates of adult HL based on sex, race/ethnicity, age, and histological subgroups in the United States (US) from 2000 to 2020. Data for this study were extracted from the Surveillance, Epidemiology, and End Results 22 database. HL patients were identified utilizing the International Classification of Diseases for Oncology version 3 and categorized as classical HL, lymphocyte-rich/mixed cell/lymphocyte depleted, nodular sclerosis, classical HL, not otherwise specified, and nodular lymphocyte-predominant HL. The study reported average annual percent change (AAPC). All estimates were presented as counts and age-standardized incidence rates (ASIRs) per 100,000 individuals. Between 2000 and 2019, a total of 70,924 cases of HL were reported in the US. Classical HL was the predominant subtype (94.27%), and most incident cases were among non-Hispanic Whites (66.92%) and those aged 20–29 years (24.86%). The ASIR per 100,000 population was 3.83 for men and 2.92 for women. Both sexes showed declines in the AAPCs between 2000 and 2019 (− 0.64% [− 0.99, − 0.28] and − 0.40% [− 0.77, − 0.03] for men and women, respectively). There was a significant decrease in ASIRs after COVID-19 among both sexes (percent change: − 7.49% [− 11.58, − 3.40]). Throughout all age groups, men had a higher incidence rate compared to women, except for those aged 20–29 years. Although the overall HL incidence rate was lowered in the study period from 2000 to 2019, a dramatic decrease in ASIRs of HL patients following COVID-19 pandemic was observed.

Abstract Background Comprehensive investigations of the prognosis factors and treatment strategies with adjustment of competing causes of death for patients with malignant meningioma (MM) is still lacking. Patient and method The surveillance, Epidemiology, and End Results (SEER) database were used to include adult patients with this rare disease between 2004 and 2018. The probability of MM-caused mortality (MMCM) and non-MM-caused mortality (non-MMCM) were presented by cumulative incidence function curves. Then, the association between variates with non-MMCM was evaluated by the cox proportional hazard model, and the prognostic factors of MMCM were identified by Fine-Gray competing risk regression model. Furthermore, a nomogram was developed to predict the 1-year, 2-year, and 5-year MMCM and the performance was tested by a time-dependent area under the receiver operating characteristic (ROC) curve and calibration. Result 577 patients were included, with a median age of 62 (18–100) years old and a median overall survival time of 36 (0–176) months. The percentage of non-MMCM was 15.4% (n = 89) in the entire population and 21.7% (n = 54) in elderly patients. The multivariable Cox proportional hazard regression model revealed that older age and other tumor(s) before or after MM had an independently significant association with higher non-MMCM. After adjustment of competing causes of death, the multivariable Fine-gray regression model identified age group ≥ 65 year, tumor size > 5.3 cm, recurrent MM, and histologic type 9530/3 (Meningioma, malignant) had an independently significant association with higher MMCM. Compared with gross total (GTR) of tumor, subtotal resection of tumor (HR 1.66, 95%CI 1.08–2.56, P = 0.02), partial resection of lobe (HR 2.26, 95%CI 1.32–3.87, P = 0.003), and gross total resection of lobe (HR 1.69, 95%CI 1.12–2.51, P = 0.01) had an independently significant association with higher MMCM. Conclusion The competing risk nomogram including age group, tumor size, initial status, histologic type, and extent of resection is discriminative and clinically useful. This study emphasized the importance of the GTR of tumor in the treatment of MM patients, which had a significantly lower incidence of MMCM compared with biopsy, STR of tumor, partial resection of lobe, and GTR of lobe.

Abstract To examine the potential correlation between chemotherapy and the risk of individual of second primary endometrial cancer (SEC) in patients with rectal cancer (RC) and assess survival outcomes. The study employed the Surveillance, Epidemiology, and End Results database (SEER) as the primary data source, it encompasses a substantial cohort of patients diagnosed with RC between 1975 and 2018. This study involved a total of 30,847 individuals diagnosed with RC, of whom 168 individuals (5.45‰) experienced SEC. Among them, 107 patients (3.47‰) received chemotherapy treatment, while 61 patients (1.98‰) did not receive chemotherapy. The analysis of the overall occurrence of SEC revealed a significant association between SEC and chemotherapy treatment. Univariate and multivariate analyses confirmed a significant association between chemotherapy treatment and an increased risk of developing SEC in RC patients. Upon implementation of a dynamic analysis on the variables of relative risk and standardized incidence ratios, the results revealed that the likelihood of SEC escalated in tandem with advancing age. The examination of patients who developed SEC after receiving and not receiving chemotherapy revealed no substantial disparities in the 10-year overall survival (OS) and (cancer-specific survival) CSS rates. The results were the same after propensity score matching. Nevertheless, a notable discrepancy emerged when comparing the OS and CSS rates at 10 years between patients afflicted with SEC subsequent to chemotherapy and those afflicted with primary endometrial cancer, and the result was the same situation in the no-chemotherapy group. The use of chemotherapy in RC patients has been associated with an increased probability of developing specific SEC. Therefore, it is imperative to prioritize efforts aimed at reducing chemotherapy-related SEC occurrences and improving the prognosis of affected individuals.

Abstract The role of neoadjuvant chemotherapy and its benefits in patients with triple-negative breast cancer (TNBC) and small tumors are unclear. This study aims to compare survival differences between clinical T1 TNBC receiving neoadjuvant chemotherapy (NAC) and adjuvant chemotherapy (AC). Data for patients with clinical T1 TNBC were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Patients were categorized according to whether they received chemotherapy before or after surgery. Propensity Score Matching (PSM) was used to minimize the influence of confounding factors. OS and BCSS were compared between the two treatment sequences using Kaplan–Meier and univariate and multivariable Cox proportional hazards regression analyses. The study included 6249 women with T1 TNBC. In multivariate analysis, compared with that in the AC group, the hazard ratio for death in the NAC group was 1.54 (95% confidence interval 1.26–1.89, p

Abstract Background and Purpose The tumour-node metastasis (TNM) classification is a common model for evaluating the prognostic value of tumour patients. However, few models have been used to predict the survival outcomes of patients with colorectal cancer liver metastasis (CRLM) with unresectable metastases who received the primary local surgery. Thus, we utilized the Surveillance, Epidemiology, and End Results (SEER) database to establish novel nomograms for predicting the overall survival (OS) and cancer-specific survival (CSS) of these patients. Methods Extracted primary data on CRLM patients by local surgery from SEER database. All prognostic factors of OS and CSS were determined by Cox regression analysis. The concordance index (C-index), receiver operating characteristic (ROC) curves and calibration curves were used to further evaluate the accuracy and discrimination of these nomograms. Decision curve analysis (DCA) was executed to evaluate the nomograms for the clinical net benefit. Risk stratification analysis (RSA) was used to evaluate the reliability of them in clinical. Results 3622 eligible patients were screened and assigned to training cohort (1812) or validation cohort (1810). The age, chemotherapy, tumour grade, primary tumour site, tumour size, lymph node positive rate (LNR), marital status, and carcinoembryonic antigen (CEA) were independent prognostic factors of OS. Additionally, the age, chemotherapy, tumour grade, primary tumour site, tumour size, LNR, and CEA were independent prognostic factors of CSS. The results of C-indexes and ROC curves indicated that the established nomograms exhibited better discrimination power than TNM classification. The calibration curves demonstrated excellent agreement between the predicted and actual survival rates for 1-, 3-, and 5 year OS and CSS. Meanwhile, the validation cohort demonstrated similar results. Background the clinic context, the DCA showed that these nomograms have higher net benefits, and the RSA showed that patients were further divided into low risk, medium risk, and high risk groups according to the predicted scores from nomograms. And, the Kaplan–Meier curve and log-rank test showed that the survival differences among the three groups are statistically significant. Conclusions The prognostic nomograms showed very high accuracy, identifiability, and clinical practicality in predicting the OS and CSS of CRLM patients with unresectable metastases treated by local surgery at 1-, 3-, and 5 years, which might improve individualized predictions of survival risks and help clinicians formulate treatment plans.

Abstract Currently, there is no consensus regarding the extent of surgery for stage I pulmonary carcinoid (PC) tumors, which encompass typical carcinoid (TC) and atypical carcinoid (AC) tumors. Sublobar resection includes segmental resection and wedge resection; the former is regarded as a type of anatomical resection that is better suited for tumor treatment. Therefore, it needs to be further verified whether differences exist in the effects of the two surgical methods on the survival time of patients. Propensity score matching (PSM) was used. The primary endpoints were cancer-specific survival (CSS) and overall survival (OS) time. Survival differences were analyzed via the Kaplan–Meier method and the log-rank test. There was no significant difference in survival between the sublobar resection and lobectomy groups after PSM in either the TC or AC tumor groups (all p > 0.05). A total of 1680 patients underwent pulmonary wedge resection (TC: n = 1547, AC: n = 133), and 398 patients underwent segmental resection (TC: n = 365, AC: n = 33). After PSM, there were no statistically significant differences in survival, regardless of whether OS or CSS was considered the primary endpoint (OS: p = 0.337; CSS: p = 0.470). Furthermore, segmental resection did not prolong patient survival time compared with wedge resection in different subgroup analyses on the basis of histology, age, and tumor size (all p > 0.05). Finally, the same results were obtained via multivariate Cox analysis (OS: p = 0.153; HR = 1.21; CSS: p = 0.351, HR = 1.32). Sublobar resection could be considered for patients with early-stage typical or atypical pulmonary carcinoid, provided that a rigorous lymph node evaluation is conducted. If the tumor is distant from the pulmonary hilum, either segmentectomy or wedge resection may be performed depending on the specific location of the tumor and the clinical condition of the patient.

Abstract We aimed to assess the cumulative incidences of cancer-specific mortality (CSM) in non-metastatic patients with non‑muscle invasive urothelial bladder cancer (NMIUBC) and establish competing risk nomograms to predict CSM. Patient data was sourced from the Surveillance, Epidemiology, and End Results database, as well as the electronic medical record system in our institution to form the external validation cohort. Sub-distribution proportional hazards model was utilized to determine independent risk factors influencing CSM in non-metastatic NMIUBC patients. Competitive risk nomograms were constructed to predict 3-year, 5-year, and 8-year cancer-specific survival (CSS) in all patients group, TURBT group and cystectomy group, respectively. The discrimination and accuracy of the model were validated through the concordance index (C-index), the area under the receiver operating characteristic curve (AUC), and calibration curves. Decision curve analysis (DCA) and a risk stratification system was employed to evaluate the clinical utility of the model. Race, age, marital status, surgery in other sites, tumor size, histological type, histological grade, T stage and N stage were identified as independent risk factors to predict CSS in all patients group. The C-index for 3-year CSS was 0.771, 0.770 and 0.846 in the training, testing and external validation sets, respectively. The ROC curves showed well discrimination and the calibration plots were well fitted and consistent. Moreover, DCA demonstrated well clinical effectiveness. Altogether, the competing risk nomogram displayed excellent discrimination and accuracy for predicting CSS in non-metastatic NMIUBC patients, which can be applied in clinical practice to help tailor treatment plans and make clinical decisions.