Survival Outcomes in Thyroid Cancer Patients with Co-Occurring Breast Cancer: Evidence of Mortality Risk Attenuation

BACKGROUND

Previous studies have reported a strong correlation between breast cancer (BC) and thyroid cancer (TC) incidence. However, the clinical and oncological impact of these associations are not yet fully understood. Here, we aimed to explore the differences in clinicopathological characteristics between TC patients with and without BC, and the effect of a history of positive BC on TC survival.

METHODS

We retrospectively compared the clinical characteristics and survival rates of patients with TC alone and those with TC and BC in a primary cohort at our institution and in a second cohort using the Surveillance, Epidemiology, and End Results (SEER) database.

RESULTS

In our institutional cohort, survival rates were similar between patients with TC alone and those with TC-associated BC. However, using SEER data, we found that BC had a protective effect on TC patients and was associated with reduced TC mortality rates (hazard ratio [HR] = 0.72, 95% confidence interval [CI] 0.57 to 0.92; P = .026). After stratifying the TC patients according to co-occurring BC subtypes, we observed that higher survival rates were restricted to patients with coexisting luminal A BC (P = .015), which exhibit positive hormone receptors and do not express HER-2.

CONCLUSION

These findings suggest that hormone pathways may play a role in the co-occurrence of thyroid and breast cancers. Patients with TC coexisting with luminal A BC have higher survival rates. However, further studies on the mechanisms underlying the association between BC and TC are warranted.

A survival nomogram model for patients with resectable non-small cell lung cancer and lymph node metastasis (N1 or N2) based on the Surveillance, Epidemiology, and End Results Database and single-center data

Background

The ability to predict survival in patients with lymph node metastasis has long been elusive. After surgery, the basis for decision-making on the combination treatment of patients is not clear. The purpose of this study was thus to build a survival nomogram model to effectively predict the overall survival (OS) of patients with non-small cell lung cancer (NSCLC) and lymph node metastasis. The number of dissected lymph nodes (NDLN), number of positive lymph nodes (NPLN), lymph node ratio (LNR), and log odds of positive lymph nodes (LODDS) were included in this study to determine the risk factors in patients with advanced NSCLC.

Methods

The data of 5,132 patients with NSCLC and lymph node metastasis (N1 or N2) were extracted from the Surveillance, Epidemiology, and End Results (SEER) database according to inclusion and exclusion criteria and used as the training cohort. We enrolled 117 patients from the First Affiliated Hospital, Zhejiang University School of Medicine as the external validation cohort. Receiver operating characteristic (ROC) analyses were performed to determine the best cutoff values for predicting the prognosis of patients with NSCLC. Based on the risk factors affecting prognosis, a nomogram was constructed using univariate and multivariate Cox proportional hazard regression models. The discrimination ability of the nomogram was evaluated with the concordance index (C-index) and calibration curves. For the independent risk factors, survival curves were drawn using Kaplan-Meier analysis.

Results

ROC curve analysis showed that the optimal NPLN cut-off value was 4, LNR was 0.26, and LODDS was -0.25, respectively. However, LNR was nonsignificant in multivariate analysis, with a P value of 0.274. The novel survival nomogram model included seven independent risk factors, among which were NPLN, LODDS, and chemotherapy. Model 4, which included N stage, NPLN, and LODDS, had a higher likelihood ratio (LR) and C-index than did the other models. The C-index was 0.648 [95% confidence interval (CI): 0.636-0.659] in the training cohort and 0.807 (95% CI: 0.751-0.863) in the external validation cohort, showing good prognostic accuracy and discrimination ability. According to the median risk score, the patients in the training cohort and external validation cohort were divided into high-risk and low-risk groups, between which significant differences in OS were found. In the training cohort, age, sex, T stage, N stage, NPLN, LODDS, and chemotherapy were significantly associated with OS (P<0.001). In the external validation cohort, T stage, NPLN, LODDS, and chemotherapy were found to be correlated with OS.

Conclusions

The NPLN and LODDS nomogram is an accurate survival prediction tool for patients with N1 or N2 NSCLC. Patients with lymph node metastasis can benefit from chemotherapy, but no evidence shows that radiotherapy is necessary for patients with resectable NSCLC.

The changing landscape of small cell lung cancer

BACKGROUND

Small-cell lung cancer (SCLC) is characterized by rapid proliferation and early dissemination. The objective of this study was to examine the demographic trends and outcomes in SCLC.

METHODS

The authors queried the National Cancer Institute's Surveillance, Epidemiology, and End Results database to assess the trends in incidence, demographics, staging, and survival for SCLC from 1975 to 2019. Trends were determined using joinpoint analysis according to the year of diagnosis.

RESULTS

Among the 530,198 patients with lung cancer, there were 73,362 (13.8%) with SCLC. The incidence per 100,000 population peaked at 15.3 in 1986 followed by a decline to 6.5 in 2019. The percentage of SCLC among all lung tumors increased from 13.3% in 1975 to a peak of 17.5% in 1986, declining to 11.1% by 2019. There was an increased median age at diagnosis from 63 to 69 years and an increased percentage of women from 31.4% to 51.2%. The percentage of stage IV increased from 58.6% in 1988 to 70.8% in 2010, without further increase. The most common sites of metastasis at diagnosis were mediastinal lymph nodes (75.3%) liver (31.6%), bone (23.7%), and brain (16.4%). The 1-year and 5-year overall survival rate increased from 23% and 3.6%, respectively, in 1975-1979 to 30.8% and 6.8%, respectively, in 2010-2019.

CONCLUSIONS

The incidence of SCLC peaked in 1988 followed by a gradual decline. Other notable changes include increased median age at diagnosis, the percentage of women, and the percentage of stage IV at diagnosis. The improvement in 5-year overall survival has been statistically significant but clinically modest.

Clinicopathological, metastatic and prognostic features of stage IV esophageal adenocarcinoma versus squamous cell carcinoma: a SEER database analysis

BACKGROUND

It is important to note that although the current treatment for advanced esophageal cancer (EC) has made great technological advances, patients' 5-year survival rates do not appear to be encouraging. Therefore, understanding the clinicopathological features and metastasis patterns of the patients with stage IV EC, combined with the prognosis of these patients, can aid in choosing the optimal treatment plan. It is well known that esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC) are the two most common pathological types. The aim of this study is to examine and compare the clinicopathological features and metastatic modes of stage IV ESCC and EAC, as well as their prognosis and survival.

METHODS

Based on the Surveillance, Epidemiology, and End Results (SEER) database, we assessed the characteristics of ESCCs and EACs associated with prognosis using the Kaplan-Meier survival analysis, and the Cox regression model. Furthermore, the clinical data of 217 patients with stage IV ESCC and EAC in the Department of Gastroenterology of the Second Affiliated Hospital of Nantong University between 2014 and 2016 were reviewed.

RESULTS

A total of 3,707 cases treated between 2010 and 2016 were included. The incidence of EAC in the United States is much higher than that of ESCC. Common metastasis patterns were lungs only, liver only, bones only, and lung & liver. The multivariate Cox analysis showed that treatment mode and metastasis patterns were independent risk factors affecting the overall survival (OS) time of patients (stage IV ESCC & EAC). EAC patients with only lung metastases may have a longer survival if chose treatment options that included surgery. In the external cohort, a total of 217 cases were included. The prevalence of ESCC is much higher than that of EAC, and the common metastasis patterns are liver only, lung only, and liver & lung. The multivariate Cox analysis showed that treatment mode was independent risk factor affecting the OS time of patients (stage IV ESCC & EAC). EAC patients treated with surgery combined with chemoradiotherapy may have a better prognosis.

CONCLUSIONS

In general, the prognosis of patients with stage IV ESCC and EAC are poor. However, surgery was found to significantly improve the OS time of patients with stage IV EAC in this study.

Survival difference between secondary and de novo acute myeloid leukemia by age, antecedent cancer types, and chemotherapy receipt

BACKGROUND

This study compared the survival of persons with secondary acute myeloid leukemia (sAML) to those with de novo AML (dnAML) by age at AML diagnosis, chemotherapy receipt, and cancer type preceding sAML diagnosis.

METHODS

Data from Surveillance, Epidemiology, and End Results 17 Registries were used, which included 47,704 individuals diagnosed with AML between 2001 and 2018. Multivariable Cox proportional hazards regression was used to compare AML-specific survival between sAML and dnAML. Trends in 5-year age-standardized relative survival were examined via the Joinpoint survival model.

RESULTS

Overall, individuals with sAML had an 8% higher risk of dying from AML (hazard ratio [HR], 1.08; 95% confidence interval [CI], 1.05-1.11) compared to those with dnAML. Disparities widened with younger age at diagnosis, particularly in those who received chemotherapy for AML (HR, 1.14; 95% CI, 1.10-1.19). In persons aged 20-64 years and who received chemotherapy, HRs were greatest for those with antecedent myelodysplastic syndrome (HR, 2.04; 95% CI, 1.83-2.28), ovarian cancer (HR, 1.91; 95% CI, 1.19-3.08), head and neck cancer (HR, 1.55; 95% CI, 1.02-2.36), leukemia (HR, 1.45; 95% CI, 1.12-1.89), and non-Hodgkin lymphoma (HR, 1.42; 95% CI, 1.20-1.69). Among those aged ≥65 years and who received chemotherapy, HRs were highest for those with antecedent cervical cancer (HR, 2.42; 95% CI, 1.15-5.10) and myelodysplastic syndrome (HR, 1.28; 95% CI, 1.19-1.38). The 5-year relative survival improved 0.3% per year for sAML slower than 0.86% per year for dnAML. Consequently, the survival gap widened from 7.2% (95% CI, 5.4%-9.0%) during the period 2001-2003 to 14.3% (95% CI, 12.8%-15.8%) during the period 2012-2014.

CONCLUSIONS

Significant survival disparities exist between sAML and dnAML on the basis of age at diagnosis, chemotherapy receipt, and antecedent cancer, which highlights opportunities to improve outcomes among those diagnosed with sAML.

Development and validation of a nomogram for predicting the overall survival in non-small cell lung cancer patients with liver metastasis

Background

Among all metastatic lesions in non-small cell lung cancer (NSCLC), liver metastasis (LM) is the most lethal site with a median survival of less than 5 months. Few studies exclusively report on prognostic factors for these unique patients. We aimed to construct and validate a practical model to predict the prognosis of NSCLC patients with LM.

Methods

Cases of NSCLC with LM diagnosed between 2010 and 2015 were collected from the Surveillance, Epidemiology, and End Results (SEER) database, and were randomly split into training and validation cohort (7:3). The overall survival (OS) was measured from diagnosis until date of death or last follow-up. Cox regression analyses were performed to identify potential predictors of the model. A nomogram incorporating those independent factors was constructed and validated by the concordance index (C-index) and calibration plots. The decision curve analysis (DCA) and a risk stratification system were used to evaluate its clinical value.

Results

A total of 2,367 cases were selected for analysis and randomized to the training cohort (n=1,677) and the validation cohort (n=690). The patients were mainly male (59.3%), married (83.1%) and White (77.3%). Apart from LM, 54.2%, 26.7%, and 36.7% of patients also present with bone, brain, and lung metastases, respectively. The median follow-up was 4.0 months for all patients and 23 months for alive cases. The median OS was 5 months [interquartile range (IQR), 2-11 months]. Sex, age, race, grade, T stage, bone metastasis, brain metastasis, surgery, and chemotherapy were identified as the independent risk factors of the OS and used to develop the nomogram. The calibration curves exhibited excellent agreement between the predicted and actual survival in both the training and validation set, with a C-index of 0.700 [95% confidence interval (CI): 0.684-0.716] and 0.677 (95% CI: 0.653-0.701), respectively. The DCA and the risk classification system further supported that the prediction model was clinically effective.

Conclusions

This is the first study to build a prediction model for NSCLC patients with LM. It aids in treatment decisions, focused care, and physician-patient communication. The global prospective data is needed to further improve this model.

Survival trends and conditional survival in primary non-metastatic esophageal cancer: a SEER population-based study and external validation

Background

The dynamic survival trend of patients with primary non-metastatic esophageal cancer (nMEC) is unknown. We conducted a conditional survival (CS) analysis and developed a novel nomogram to predict it.

Methods

Patients with primary nMEC were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Independent prognostic factors of cancer-specific survival (CSS) were identified. The log-rank test and Cox analysis were used to calculate probabilities of CS. We constructed nomograms to predict survival trends and CS probabilities based on the prognostic factors. Calibration curves and C-indexes were used for internal and external validation.

Results

A total of 9,008 patients were identified from the SEER database and 37 patients were recruited as an external validation cohort. The 1- and 3-year CS rates were 69.6% and 43.1% at diagnosis, rising to 95.2% and 86.2% at the fifth conditional year. CS probabilities by different variables continuously improved over time. The calibration curves of the CS nomograms fit well. The C-indexes were 0.700 (95% CI: 0.693-0.709) in the training cohort, 0.693 (95% CI: 0.669-0.717) in the internal validation cohort, and 0.683 (95% CI: 0.556-0.810) in the external validation cohort.

Conclusions

CS rates are more dynamic than traditional survival rates for patients surviving for a relatively longer period. The CS rates of patients with nMEC improved over time and became stable after surviving for a few years. We developed and validated nomograms to predict CS probabilities.

Risk of second cancer in esophageal squamous cell carcinoma and adenocarcinoma survivors: a population-based analysis in SEER dataset

Background

Previous studies have reported increased risk of second cancer in both esophageal squamous cell cancer (ESCC) and esophageal adenocarcinoma (EAC) survivors. This study aimed to examine the risk and influential factors of second cancer in ESCC and EAC patients.

Methods

This population-based cohort study included 7,297 ESCC patients and 11,812 EAC patients who were in 1992-2019 from the Surveillance, Epidemiology, and End Results (SEER) program in the United States. These patients were followed up until diagnosis of second cancer, death, or end of the study (December 31, 2019). We calculated standard incidence ratio (SIR) and 95% confidence interval (CI) of second cancer and performed competing-risk regression to estimate the subdistribution hazard ratios (sHR) comparing categories of patients' characteristics.

Results

After a total of 49,509.38 person-years of follow-up, 431 (5.9%) ESCC patients and 636 (5.9%) EAC patients developed a second cancer. An overall increased risk of second cancer was observed in both ESCC patients (SIR: 1.66, 95% CI: 1.51-1.83) and EAC patients (SIR: 1.11, 95% CI: 1.02-1.20). ESCC patients were at increased risk of second malignancy in oral cavity and pharynx (SIR: 12.57, 95% CI: 9.87-15.79), stomach (SIR: 3.03, 95% CI: 1.77-4.85), nose and larynx (SIR: 4.79, 95% CI: 2.47-8.37), and lung and bronchus (SIR: 2.44, 95% CI: 1.96-2.99), but decreased risk of prostate cancer (SIR: 0.73, 95% CI: 0.52-0.99). EAC patients had increased risk of second malignancies in stomach (SIR: 4.41, 95% CI: 3.23-5.89), lung and bronchus (SIR: 1.26, 95% CI: 1.02-1.54), and kidney (SIR: 1.57, 95% CI: 1.05-2.25). The risk of second cancer was higher in female ESCC patients than in males (sHR: 1.34, 95% CI: 1.11-1.63) and decreased with more advanced tumor stage in both ESCC patients (sHR: 0.62, 95% CI: 0.50-0.76 for regional stage; sHR: 0.27, 95% CI: 0.20-0.36 for distant stage) and EAC patients (sHR: 0.47, 95% CI: 0.40-0.56 for regional stage; sHR: 0.10, 95% CI: 0.07-0.13 for distant stage).

Conclusions

Both ESCC and EAC patients are at considerable risk of certain types of second cancer.

Clinicopathological Features and Survival Trends of Non-Epithelial Ovarian Cancer: Analysis of the Surveillance, Epidemiology, and End Results (SEER) Database

INTRODUCTION

Owing to their low incidence, no reliable statistics about prognostication derived from large sample sizes have been reported of malignant ovarian germ cell tumors (MOGCTs) and sex cord-stromal tumors (SCSTs). The present study aimed to investigate the clinicopathological prognostic factors and the survival trends of MOGCTs and SCSTs.

MATERIALS AND METHODS

Patients with MOGCTs and SCSTs were recorded in the Surveillance, Epidemiology, and End Results (SEER) database diagnosed between 2000 and 2019. Clinical, demographic, and treatment characteristics were compared between groups of MOGCTs and SCSTs. Cox risk regression analysis and Kaplan-Meier survival curves were used to compare overall survival (OS) and cancer-specific survival (CSS) and to assess the prognostic factors.

RESULTS

Information about 2,506 patients with MOGCTs and 1,556 patients with SCSTs was extracted from the SEER database, respectively. Aged <40 years and single were more common in patients with MOGCTs than in those with SCSTs. The vast majority of patients with MOGCTs and SCSTs underwent surgery (98.1% vs. 94.5%; p < 0.001), and women with MOGCTs were more likely to receive chemotherapy than women with SCSTs (56.1% vs. 32.2%; p < 0.001). For both patients before and after propensity-score matching, the 5-year OS rates of patients with SCSTs were lower than those of patients with MOGCTs (p < 0.05). In multivariate Cox regression analysis, both age and surgery were independent predictors of OS in patients with MOGCTs and SCSTs. FIGO staging was an independent predictor of CSS in MOGCT patients. Tumor size and chemotherapy were also independent predictors of CSS in patients with SCSTs.

CONCLUSION

Compared to patients with SCSTs, those with MOGCTs tended to be younger and had a higher OS and CSS. Adjuvant chemotherapy after surgery did not prolong OS and CSS in patients with SCSTs.

Analysis of the distinct features of metastasis male breast cancer and its effect on overall survival based on the SEER database compared with female breast cancer

Background

Male breast cancer (MBC) is a rare disease and differs from female breast cancer (FBC) in clinicopathological and immune tissue types. Given the limited research on MBC due to its rarity, an understanding of the shared and distinct features of MBC and FBC is vital for formulating efficacious treatment strategies.

Methods

Data of patients diagnosed with metastatic breast cancer in the Surveillance, Epidemiology, and End Results (SEER) database from 2012 to 2017 were analysed. Chi-square test was used to compare clinicopathological characteristics between male and female patients. Kaplan-Meier analysis was utilized to compare differences in overall survival (OS).

Results

A total of 2,858 patients with MBC were studied, 134 of whom had distant metastasis. Compared with 8,698 patients with metastatic FBC, a higher proportion of metastatic MBC patients had tumors located in the center of the breast, received surgical treatment, and had bone + lung metastasis. Survival analysis revealed no difference in OS between metastatic MBC and FBC patients (P=0.27), but there was a significant difference in OS between metastatic and nonmetastatic MBC (P=0.004). Compared with metastatic FBC, MBC patients with bone metastasis alone, lung metastasis alone, liver metastasis alone, and bone + lung metastasis also had worse prognosis (P=0.021, 0.019, 0.024, 0.011, respectively).

Conclusions

Metastatic MBC has unique clinicopathological disease features and patterns of metastasis. No significant difference between the survival of metastatic MBC and FBC patients was observed. Distant metastasis was an independent risk factor impacting the prognosis of MBC patients.

A new prognostic model of esophageal squamous cell carcinoma based on Cloud-least squares support vector machine

Background

In view of the low accuracy of the prognosis model of esophageal squamous cell carcinoma (ESCC), this study aimed to optimize the least squares support vector machine (LSSVM) algorithm to determine the uncertain prognostic factors using a Cloud model, and consequently, to establish a new high-precision prognosis model of ESCC.

Methods

We studied 4,771 ESCC patients(training samples) from the Surveillance, Epidemiology, and End Results (SEER) database and 635 ESCC patients(validation samples) from the Henan Provincial Center for Disease Control and Prevention (HCDC) database, with the same exclusion criteria and inclusion criteria for both databases, and obtained permission to obtain a research data file in the SEER database from the National Cancer Institute. The independent risk factors were analyzed using the log-rank method, survival curves, univariate and multivariate Cox analysis. Finally, the independent prognostic factors were used to construct the nomogram, random forest and Cloud-LSSVM prognostic models were utilized for validation.

Results

The overall median survival time of the SEER database was 14 months (HCDC samples was 46 months), the mean survival time was 26.5 months (HCDC samples was 36.8 months), and the 3-year survival rate was 65.8%. This is because most of the patients with Henan samples are early ESCC, and most of the Seer patients are T3 and T4 people. The multivariate Cox analysis showed that age at diagnosis (P<0.001), sex (P=0.001), race (P=0.002), differentiation grade (P<0.001), pathologic T category (P<0.001), and pathologic M category (P<0.001) were the factors affecting the prognosis of ESCC patients. The SEER data and HCDC database results showed that the accuracy of the Cloud-LSSVM (C-index =0.71, 0.689) model is higher than the differentiation grade (C-index =0.548, 0.506), random forest (C-index =0.649, 0.498), and nomogram (C-index =0.659, 0.563). This new model can realize the unity of the randomness and fuzziness of the Cloud model and utilize the powerful learning and non-linear mapping abilities of LSSVM.

Conclusions

Due to the difference of clans between training samples and test samples, the accuracy of prediction is generally not high, but the accuracy of Cloud-LSSVM model is much higher than other models. The new model provides a clear prognostic superiority over the random forest, nomogram, and other models.

Causes of death after testicular cancer diagnosis: a US population-based analysis

BACKGROUND

After the introduction of cisplatin-based chemotherapy, the survival time of testicular cancer (TC) patients has improved dramatically. However, the overall risk of death in patients with TC remains significantly higher than in the general population. The aim of this study was to assess and quantify the causes of death after TC diagnosis.

METHOD

In total, 44,975 men with TC in the United States diagnosed and registered by the Surveillance, Epidemiology, and End Results (SEER) database during 2000 to 2018 were studied. In this study, standardized mortality rates (SMRs) were calculated for each cause of death in TC individuals and further analyzed in strata according to age and race.

RESULT

Of the included participants, 3,573 (7.94%) died during the follow-up period. The greatest proportion of deaths (38.20%) occurred within 1 to 5 years after diagnosis. Most deaths occurred from TC itself and other cancers. For non-malignant conditions, the most common causes of death within 1 years after diagnosis were accidents and adverse effects (53, 4.75%) followed by diseases of heart (45, 4.04%). However, > 1 years after diagnosis, the most common noncancer causes of death were heart diseases. Results of stratified analysis show that non-Hispanic White TC participants have a lower SMR (0.68, 95% CI, 33.39-38.67) from Cerebrovascular Diseases than the general U.S.

POPULATION

CONCLUSIONS

Although TC remains the most common cause of death after TC diagnosis, other non-TC causes of death represent a significant number of deaths among TC men. These findings help TC survivors understand the various health risks that may occur at different follow-up periods.

Epidemiological and survival outcomes of neuroendocrine carcinoma of the breast: a SEER data analysis

Background

Neuroendocrine carcinoma of the breast (NECB) is a rare subtype of breast cancer, comprising only 0.1% to 5% of all breast cancer cases. Despite its rarity, it is important to gain a better understanding of the epidemiological, clinical, and prognostic features of NECB. The purpose of the study was to obtain population-based evaluations of the epidemiological and survival outcomes of NECB.

Methods

The data of patients with neuroendocrine carcinoma diagnosed and enrolled between 2000 and 2017 were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Descriptive statistical analyses were used to assess the distribution and tumor-related characteristics of these patients. Kaplan-Meier curves and univariate and multivariate Cox proportional risk models were used to analyze variables that might be associated with prognosis.

Results

This study included 7,856 patients with neuroendocrine carcinoma. The median age of the patients was 64 years, and most of them were female, White, and diagnosed at ≥60 years old. The most common pathological type was neoplasm. Survival analysis indicated that there were significant differences in age, marital status, registration location, American Joint Committee on Cancer (AJCC) stage, breast subtype, surgery of primary tumor, and no cancer cause surgery patients with NECB. The results also indicated that treatment with surgery, including surgery of primary tumor, surgery combined with radiation, and no cancer cause surgery, were all effective in improving the prognosis compared with not providing surgical treatment.

Conclusions

In conclusion, NECB is a very rare lesion for which age, marital status, registration location, and surgery, AJCC stage, breast subtype were found to be independent prognostic factors.

Age and treatment disparities in survival of primary malignant cardiac tumors: an analysis of over 40 years and 500 patients

Background

Primary malignant cardiac tumors (PMCTs) are rare and tend to have a poor prognosis, due to their aggressive biological behavior and the inadequate expertise with the disease. This article compares the survival of patients with PMCT subtypes in the United States across age and treatment groups.

Methods

Data of 529 patients diagnosed with PMCTs were analyzed. Chi-squared test was used to assess significance of the differences between proportions in demographic and tumor characteristics by age and treatment. Cox regression analysis was used to estimate survival from the Surveillance, Epidemiology, and End Results (SEER) follow-up data.

Results

Survival rates for PMCTs differed significantly between age groups, with patients younger than 20 years surviving significantly longer than those older than 80 years. The median survival times of all patients with PMCTs were 22.5, 11, 5, and 1 month for ages less than 20, 20-50, 51-80, and greater than 80 years, respectively (global log-rank P=0.0026). In the treatment cohort, for all tumors [hazard ratio (HR) 1.52, P<0.001], sarcomas (HR 1.83, P=0.002), and other tumors (HR 2.24, P=0.017), survival was lower in patients who did not receive treatment than in those who received only surgery. Survival after diagnosis of sarcoma was lower in patients who received radiotherapy only than in those who received surgery only (HR 1.49, P=0.046). However, there was no significant association between treatment and survival for lymphoma and mesothelioma.

Conclusions

This study confirms that PMCTs have limited treatment options and poor patient survival, especially for elderly patients and patients who receive no treatment. And patients with PMCTs of any age, whether treated or not, have poor survival rates. Techniques for early diagnosis and treatment may be necessary. Surgical treatment should have a higher priority for future treatment of patients with sarcomas.

Treatments associated with all-cause mortality among children with primary brain and central nervous system tumors: a retrospective cohort study from the SEER database

Background

Evidence on treatment modalities and survival in childhood primary brain and central nervous system (CNS) tumors remains contradictory, with previous studies often lacking sufficient patient cohort sizes to assess the differences in histological subtypes. This cohort study based on a large population investigated the effects of various treatments on the mortality of patients with different histological types of primary brain and CNS tumors from the Surveillance, Epidemiology, and End Results (SEER) database.

Methods

Data of demography, primary tumor site, histology, tumor grade and treatments from all pediatric patients with primary brain and CNS tumors were extracted in this retrospective cohort. The outcomes were overall, 1-, 5-, and 10-year all-cause mortality. Multivariate Cox proportional hazards models were to explore the associations of treatment with overall, 1-, 5-, and 10-year all-cause mortality, with hazard ratios (HRs) and 95% confidence intervals (CIs).

Results

Totally 10,994 children were included, with the mean age at diagnosis of 7.3 years, and the median follow-up time of 5.0 years. Of which, 2,003 (18.2%) were diffuse astrocytoma, 3,188 (29.0%) were embryonal tumors, and 3,691 (33.5%) were malignant glioma. Then 4,333 (39.41%) children died during the follow-up. For diffuse astrocytomas and malignant gliomas, patients who received all other treatments were associated with overall, 1-, 5- and 10-year all-cause mortality compared to those only received resection. Embryonal tumors patients receiving resection with radiation only and those receiving resection with both chemotherapy and radiation were associated with lower odds of overall, 1-, 5- and 10-year all-cause mortality compared to patients who only received resection. For ependymal tumors, no surgery/only biopsy with chemotherapy, resection with chemotherapy only, resection with both chemotherapy and radiation, and other treatments had increased risks of overall all-cause mortality compared with resection. The risk of 1-year all-cause mortality increased in ependymal tumors with treatment involving resection and radiation. However, resection with both chemotherapy and radiation was not significantly associated with the 1- nor 5-year all-cause mortality.

Conclusions

Resection may be recommended for children with diffuse astrocytoma, ependymal tumors, and malignant glioma, while resection with radiotherapy or chemoradiation may be recommended for children with embryonal tumors.

Construction and validation of a prognostic nomogram for locally recurrent rectal cancer: a population-based study

Background

Postoperative recurrence was a life-threatening condition for patients with rectal cancer. Due to the heterogeneity of locally recurrent rectal cancer (LRRC) and controversy of the optimal treatment for patients, it was difficult to predict the prognosis of LRRC. This study aimed to develop and validate a nomogram that could accurately predict the survival probability of LRRC.

Methods

Patients diagnosed with LRRC between 2004 and 2019 from the Surveillance, Epidemiology, and End Results (SEER) database were included in the analysis. Multiple imputations with chained equations were used for missing values. These patients were further randomized into training set and testing set. Cox regression was used for univariate and multivariate analysis. Potential predictors were screened by the least absolute shrinkage and selection operator (LASSO). The Cox hazards regression model was constructed and it was visualized by nomogram. C-index, calibration curve, and decision curve were used to evaluate the model's predictive ability. Then X-tile was used to calculate the optimal cut-off values for all patients and the cohort was divided into three groups.

Results

A total of 744 LRRC patients were enrolled and allocated to the training set (n=503) and the testing set (n=241). Cox regression analysis of the training set yielded meaningfully clinicopathological variables. A survival nomogram was created based on the identification of ten clinicopathological features in the LASSO regression analyses of the training set. The C-index of 3-, 5-year survival probabilities were 0.756, 0.747 in training set, and 0.719, 0.726 in testing set, respectively. The calibration curve and decision curve both demonstrated the satisfactory performance of the nomogram for prognosis prediction. Moreover, the prognosis of LRRC could be well distinguished according to the grouping of risk scores (P<0.001 in three groups).

Conclusions

This nomogram was the first prediction model to preliminarily evaluate the survival of LRRC patients, which could provide more accurate and efficient treatment in clinical practice.

Surgical resection of primary tumors improves survival in patients with lung metastases: a population-based SEER analysis

Background

The lung is a common site for cancer metastasis. Some cancer patients would develop lung metastases throughout the course of their illness. However, choosing surgical resection of the primary tumor (SRPT) or palliative treatment in patients with lung metastases remains controversial.

Methods

Lung metastatic patients diagnosed from 2010 to 2016 were selected from the Surveillance, Epidemiology, and End Results (SEER) database. Selected patients were divided into two subgroups (surgery and non-surgery). Further, all the 58 tumor types were classified into 13 subtypes. The clinical and demographic features were examined by the Fisher's exact test, chi-squared test, or z-test. Overall survival (OS) was analyzed using the Kaplan-Meier (K-M) estimator and a log-rank test for each primary tumor type. Multivariable survival analyses of OS were performed using the Cox proportional hazards model.

Results

Among the 118,088 patients selected for study, 18,688 (15.83%) patients had undergone surgery. The analyses demonstrated that there was a significant association between SRPT and better OS in patients with lung metastases. The median survival time increased from 4.0 months in the non-surgery group to 19.0 months in the surgery group. Multivariate Cox regression analyses further validated that patients who underwent SRPT had an improved OS.

Conclusions

The current study demonstrated that patients with lung metastases can benefit from SRPT. SRPT should be considered in patients with lung metastases. Properly designed prospective randomized clinical trials would be required to further verify the conclusion.

Establishment and validation of nomograms for predicting survival of lung invasive adenocarcinoma based on the level of pathological differentiation: a SEER cohort-based analysis

Background

The pathological differentiation of invasive adenocarcinoma (IAC) has been linked closely with epidemiological characteristics and clinical prognosis. However, the current models cannot accurately predict IAC outcomes and the role of pathological differentiation is confused. This study aimed to establish differentiation-specific nomograms to explore the effect of IAC pathological differentiation on overall survival (OS) and cancer-specific survival (CSS).

Methods

The data of eligible IAC patients between 1975 and 2019 were collected from the Surveillance, Epidemiology, and End Results (SEER) database, and randomly divided in a ratio of 7:3 into a training cohort and a validation cohort. The associations between pathological differentiation and other clinical characteristics were evaluated using chi-squared test. The OS and CSS analyses were performed using the Kaplan-Meier estimator, and the log-rank test was used for nonparametric group comparisons. Multivariate survival analysis was performed using a Cox proportional hazards regression model. The discrimination, calibration, and clinical performance of nomograms were assessed by area under receiver operating characteristic curve (AUC), calibration plots, and decision curve analysis (DCA).

Results

A total of 4,418 IAC patients (1,001 high-differentiation, 1,866 moderate-differentiation, and 1,551 low-differentiation) were identified. Seven risk factors [age, sex, race, tumor-node-metastasis (TNM) stage, tumor size, marital status, and surgery] were screened to construct differentiation-specific nomograms. Subgroup analyses showed that disparate pathological differentiation played distinct roles in prognosis, especially in patients with older age, white race, and higher TNM stage. The AUC of nomograms for OS and CSS in the training cohort were 0.817 and 0.835, while in the validation cohort were 0.784 and 0.813. The calibration curves showed good conformity between the prediction of the nomograms and the actual observations. DCA results indicated that these nomogram models could be used as a supplement to the prediction of the TNM stage.

Conclusions

Pathological differentiation should be considered as an independent risk factor for OS and CSS of IAC. Differentiation-specific nomogram models with good discrimination and calibration capacity were developed in the study to predict the OS and CSS in 1-, 3- and 5-year, which could be used predict prognosis and select appropriate treatment options.

Neoadjuvant and adjuvant chemotherapy share equivalent efficacy in improving overall survival and cancer-specific survival among muscle invasive bladder cancer patients who undergo radical cystectomy: a retrospective cohort study based on SEER database

Background

Although neoadjuvant chemotherapy (NAC) followed by radical cystectomy (RC) have been reported an 6% absolute improvement in 5-year overall survival (OS) for muscle invasive bladder cancer (MIBC), criticism still exists including the delay of surgery and the lack of accurate pathological evidence guidance. Trials have instead focused on adjuvant chemotherapy (AC) but encountered with many difficulties. Convincing data directly compared the treatment efficacy of these 2 strategies are lacking.

Methods

We conducted a retrospective cohort study to compare the effectiveness of NAC versus AC among patients with T2-4N0-3M0 bladder cancer using the Surveillance, Epidemiology, and End Results (SEER) database. OS and cancer-specific survival (CSS) were compared using Kaplan-Meier (KM) survival estimators and univariate Cox proportional hazards regression models adjusted for inverse probability of treatment weighting (IPTW). The baseline between groups were compared using standardized mean differences (SMD) approach and kernel density plot. Sensitivity analysis was performed to test the robustness of our results.

Results

In total, 1,620 (38.9%) of all eligible patients (4,169) received NAC and 2,549 (61.1%) received AC. After adjusted for propensity score, all baseline characteristics were balanced with SMD <10%. The IPTW-adjusted survival analyses revealed no significant difference in OS between the 2 groups [adjusted hazard ratio (AHR) 1.09, 95% confidence interval (CI): 0.99-1.20, P=0.1]. Exploratory subgroup analysis indicated longer OS among lymph node-negative patients treated with NAC (AHR 1.25, 95% CI: 1.1-1.4, P=0.001), whereas lymph node-positive patients were in favor of AC (AHR 0.85, 95% CI: 0.72-0.99, P=0.043). This treatment heterogeneity according to lymph node status is associated with better prognosis in Stage II (T2N0) patients receiving NAC (AHR 1.28, 95% CI: 1.1-1.6, P=0.014). Meanwhile, in stage III-IV (T3-T4 and/or N+) diseases, NAC shares similar treatment efficacy to AC (AHR 0.98, 95% CI: 0.87-1.1, P=0.762). The analyses of CSS yielded similar, robust results on the effect of potential unmeasured confounding variables.

Conclusions

Our population-based study suggests that NAC and AC might be interchangeable in MIBC management, especially in patients with Stage III-IV (T3-T4 and/or N+) diseases. However, this conclusion needs further validation from powerful, robust randomized trials.

Removing different number of regional lymph nodes affects survival outcomes of operable patients at stage IIA non-small cell lung cancer (according to the 8th edition staging)

Background

Surgery combined with chemotherapy (CT) is the best treatment for tumor patients at stage I to IIIA. But there are only few studies specifically evaluated the survival benefits of removing different number of regional lymph nodes (RLNs) for patients with stage IIA non-small cell lung cancer (NSCLC). The objective of this study is to discuss the effect of removing different number of RLNs on survival outcomes in operable patients at stage IIA NSCLC.

Methods

Through the use of the Surveillance, Epidemiology, and End Results (SEER) registry, satisfactory patients at stage IIA NSCLC, who had complete clinical information from 2004 to 2015, were identified. Lung cancer-specific survival (LCSS) and overall survival (OS) were compared by the Kaplan-Meier analysis and Cox regression analyses to determine the impact of the confounding factors on the survival outcomes. LCSS and OS as the primary endpoints were compared among patients with different number of RLNs removed.

Results

A total of 3,362 patients at stage IIA NSCLC met our criteria, including 173 (5.1%), 486 (14.5%), 2,703 (80.4%) patients without RLNs removed, with 1 to 3 RLNs removed and with greater than or equal to 4 RLNs removed, respectively. Kaplan-Meier survival analyses and Univariate Cox regression analyses revealed that there was a statistically significant difference on survival curve (log rank P<0.001) among the stage IIA NSCLC patients with different number of RLNs removed. Furthermore, multivariable Cox regression analyses on LCSS showed that the hazard ratio (HR) and 95% confidence interval (95% CI) of the 1 to 3 RLNs removed group and greater than or equal to 4 RLNs removed group were 0.622 (0.484-0.800, P<0.001) and 0.545 (0.437-0.680, P<0.001), respectively, compared to without any RLNs removed group.

Conclusions

This study illustrated that removing different number of RLNs can affect survival outcomes of operable patients at stage IIA NSCLC. Whether more radical lymphadenectomy is beneficial to patients at stage IIA NSCLC still needs to be researched.

Identification of risk and prognostic factors for intrahepatic vascular invasion in patients with hepatocellular carcinoma: a population-based study

Background

The aim of this study was to develop nomograms to predict the risk of intrahepatic vascular invasion (IVI) of hepatocellular carcinoma (HCC) patients and estimate the overall survival (OS) and cancer-specific survival (CSS) of HCC patients with IVI.

Methods

The Surveillance, Epidemiology, and End Results (SEER) database was used to identify patients with HCC from 2010 to 2015. Ultimately, 1,287 HCC patients with IVI were included in this study and randomly divided into training (n=901) and validation (n=386) cohorts. Multivariate logistic regression analysis and multivariate Cox proportional hazards regression analysis were performed to construct nomograms to visually quantify the risk of IVI in patients with HCC and predict the prognosis. The prediction effect of nomograms was evaluated using Harrell's concordance index (C-index), receiver operating characteristic (ROC) curve, calibration plots, and decision curve analysis (DCA), respectively.

Results

The C-index of the nomogram for risk prediction was 0.730. The C-indices based on the nomogram were 0.762 [95% confidence interval (CI): 0.745-0.779] and 0.770 (95% CI: 0.753-0.787) for OS and CSS prediction in the training cohort, respectively. In the validation cohort, the C-indices were 0.779 (95% CI: 0.752-0.806) and 0.795 (95% CI: 0.768-0.822) for OS prediction and CSS prediction, respectively. Overall, the ROC curve, calibration plots, and DCA indicated the good performance of nomograms.

Conclusions

We identified the relevant risk and prognostic factors for IVI in patients with HCC. The nomograms performed well on validation and may help to facilitate clinical decision-making.

Establishment and verification of a nomogram to predict tumor-specific mortality risk in triple-negative breast cancer: a competing risk model based on the SEER cohort study

Background

Triple-negative breast cancer (TNBC) is the subtype of breast cancer with the worst prognosis, and traditional survival analysis methods are biased when predicting mortality. To predict the risk of death in patients with triple-negative breast cancer more precisely, a competing risk model was developed.

Methods

The clinicopathological data of the TNBC patients from 2010 to 2015 were collected from the Surveillance, Epidemiology, and End Results (SEER) database. The data were assigned into a training set and testing set at a ratio of 7:3 in a randomized pattern. Univariate and multivariate competing risk models were applied to find the independent prognostic factors. A prediction nomogram for cancer-specific mortality (CSM) risk was constructed. The accuracy and discrimination of the nomogram were assessed using receiver operating characteristic (ROC) area under the curve (AUC), concordance index (C-index), and a calibration curve using the training and testing sets, respectively.

Results

A total of 28,430 TNBC patients were randomly grouped into the training set (n=19,900) and the testing set (n=8,530). The median time for follow-up was 59 [1-107] months. A total of 7,014 (24.67%) patients died, among whom 4,801 (68.45%) died from breast cancer and 2,213 (31.55%) due to non-breast cancer events. The independent risk factors were primary site of tumor, grade, tumor-node-metastasis (TNM) stage, T stage, approach of surgery, chemotherapy, axillary lymph node metastases, brain metastases, and liver metastases. The prediction nomogram was constructed by using the aforementioned variables. The 1-, 3-, and 5-year AUC of CSM were predicted to be 0.856, 0.81, and 0.782, respectively, in the training set, and 0.856, 0.81, and 0.782 in the testing set, respectively. The C-index of the nomogram was 0.801 and 0.799 in the training and testing sets, respectively. As confirmed by the validation and training calibration curves, the nomogram was consistent with the results.

Conclusions

We used competing risk models to identify risk factors for CSM and constructed a CSM risk prediction nomogram for TNBC patients, that may be utilized to predict CSM risk in TNBC patients clinically and assist in the creation of individualised clinical treatment options.

Establishment and validation of a nomogram for predicting immune-related prognostic features in trunk melanoma-specific death

Background

Trunk melanoma is one of the most common and deadly types of melanomas. Multiple factors are associated with the prognosis of patients with trunk melanoma. Currently, direct, and reliable clinical tools for early assessment of individual specific risk of death are limited, and most of them are prediction models for all-cause death. Their accuracy in predicting competitiveness events, which make up a relatively large portion, may be substantially compromised. Hence, we conducted this study to investigate the risk factors of trunk melanoma-specific death to establish a comprehensive prediction model suitable for clinical application.

Methods

Patients with trunk melanoma analyzed in this study were from the SEER program [2010-2015]. The random sampling method was used to split the included cases into the training and validation cohorts at a ratio of 7:3. Univariate and multivariate competing risk models were used to screen the independent influencing factors of specific death, and then a nomogram covering these independent predictors was constructed. The concordance index (C-index) and a calibration curve were used to evaluate the calibration degree and accuracy of the nomogram.

Results

We identified 21,198 patients with trunk melanoma from the SEER database, and 3,814 of them died (17.99%). Among the death cases, deaths from other causes accounted for 66.50%The prognostic nomogram included 8 variables and 16 independent influencing factors. The overall C-index in the training set was 0.89, and the receiver operating characteristic (ROC) curve for predicting 1-, 3-, and 5-year survival was 0.928 [95% confidence interval (CI): 0.911-0.945], 0.907 (95% CI: 0.895-0.918), and 0.891 (95% CI: 0.879-0.902), respectively. The C-index of the model in the validation set was 0.89, and the area under the ROC curve (AUC) for predicting 1-, 3-, and 5-year cancer-specific death (CSD) was 0.927 (95% CI: 0.899-0.955), 0.916 (95% CI: 0.901-0.930), and 0.905 (95% CI: 0.899-0.921). Both the training set and the validation set showed the ideal calibration degree.

Conclusions

This model can be used as a potential tool for prognostic risk management of trunk melanoma in the presence of many competing events.

Development and validation of an XGBoost model to predict 5-year survival in elderly patients with intrahepatic cholangiocarcinoma after surgery: a SEER-based study

Background

Nomograms have been established to predict survival in postoperative or elderly intrahepatic cholangiocarcinoma (ICC) patients. There are no models to predict postoperative survival in elderly ICC patients. Extreme gradient boosting (XGBoost) can adjust the errors generated by existing models. This retrospective cohort study aimed to develop and validate an XGBoost model to predict postoperative 5-year survival in elderly ICC patients.

Methods

The Surveillance, Epidemiology, and End Results (SEER) program provided data on elderly ICC patients aged 60 years or older and undergoing surgery. The median follow-up time was 20 months. Totally 1,055 patients were classified as training (n=738) and testing (n=317) sets at a ratio of 7:3. The outcome was postoperative 5-year survival. Demographic, tumor-related and treatment-related variables were collected. Variables were screened using the XGBoost model. The predictive performance of the model was assessed by the area under the receiver operating characteristic (ROC) curve (AUC), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and Kaplan-Meier curve. Cox regression analysis was conducted to estimate the risk of death in the predicted populations. The predictive abilities of the XGBoost model and the American Joint Commission on Cancer (AJCC) system (7th edition) were compared.

Results

The XGBoost model achieved an AUC of 0.811, a sensitivity of 0.573, a specificity of 0.890, and a PPV of 0.849 in the training set. In the testing set, the model had an AUC of 0.713, a sensitivity of 0.478, a specificity of 0.814, and a PPV of 0.726. The 5-year mortality risk of patients predicted to die was 2.91 times that of patients predicted to survive [hazard ratio (HR) =2.91, 95% confidence interval (CI): 2.42-3.50]. The XGBoost model showed a better predictive performance than the AJCC staging system both in the training and testing sets. AJCC stage, multiple (satellite) tumors/nodules, tumor-node-metastasis (TNM) stage, more than one lobe invaded, direct invasion of adjacent organs, tumor size, and radiotherapy were relatively important features in survival prediction.

Conclusions

The XGBoost model exhibited some predictive capacity, which may be applied to predict postoperative 5-year survival for elderly ICC patients.

Chemotherapy exacerbates the survival paradox of colon cancer: a propensity score matching analysis

Background

Colon cancer is one of the most common tumor diseases in the world. Currently, clinicians usually evaluate the survival and prognosis of patients according to their tumor-node-metastasis (TNM) stage. However, current studies have found that there is a certain survival paradox in TNM staging.

Methods

In the Surveillance, Epidemiology, and End Results (SEER) database, patients diagnosed with colon cancer by surgical pathology from 2004 to 2011 were selected for analysis of 5-year overall survival (OS). Propensity score matching (PSM) was performed to analyze the difference in survival between different stages and the effect of chemotherapy on prognosis.

Results

The OS of stage IIIA colon cancer sufferers was significantly superior to stage IIB/IIC and separate stage IIB or IIC colon cancer patients before and after PSM analysis (P<0.05 for all). Moreover, the difference in survival was more significant when stage IIB/IIC patients were compared with stage IIIA patients with chemotherapy.

Conclusions

The survival paradox existed both in all stage IIB/IIC patients, or individual stage IIB or IIC patients compared with stage IIIA sufferers, and the survival paradox between stage IIIA and stage IIC was more obvious. Moreover, chemotherapy had a positive effect on the prognosis of patients with stage IIIA, IIC and IIB in this study. Chemotherapy exacerbates the survival paradox of colon cancer, even if it is not the cause of the survival paradox.

A novel nomogram predicting cancer-specific survival in small cell lung cancer patients with brain metastasis

Background

Brain metastasis (BM) is one of the most common metastatic sites in patients with small cell lung cancer (SCLC), and the prognosis remains very poor. This study aimed to establish a novel nomogram for predicting the cancer-specific survival (CSS) in SCLC patients with BM.

Methods

SCLC patients with BM from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015 were retrospectively collected. Univariate and multivariate Cox regression analyses were performed to identify independent prognostic factors, which were further used to construct the prognostic nomogram. The discrimination and calibration of nomogram were evaluated by concordance index (C-index), receiver operating characteristic (ROC) curve, the area under ROC curve (AUC) and calibration plot. Decision curve analysis (DCA) was used to assess the clinical usefulness. Kaplan-Meier survival curve was applied to analyze the survival outcome.

Results

A total of 2,462 patients were enrolled in this study, and randomly assigned into training cohort (n=1,723) and validation cohort (n=739). Age, N stage, surgery, radiation, chemotherapy, bone metastasis, liver metastasis and lung metastasis were identified as independent prognostic factors of CSS. The C-indexes of nomogram was 0.683 [95% confidence interval (CI): 0.667-0.699] in the training cohort, and 0.659 (95% CI: 0.634-0.684) in the validation cohort. The AUC values of 6-, 9- and 12-month CSS were 0.723, 0.742 and 0.737 respectively in the training cohort, while 0.715, 0.737 and 0.739 in the validation cohort. The ROC, calibration and DCA curves showed good discrimination, calibration and clinical applicability of this nomogram in predicting prognosis. Moreover, patients in high-risk group had a worse survival outcome than patients in medium-risk and low-risk groups.

Conclusions

A novel nomogram was constructed and validated for predicting individual prognosis in SCLC patients with BM. This nomogram could help clinicians make effective treatment strategies for patients.

Patterns of care and prognostic evaluation for stage I-III upper esophageal squamous cell carcinoma: a population-based study

Background

There is no strong evidence regarding the optimal treatment and specific prognosis prediction model for upper esophageal squamous cell carcinoma (UESCC). This study aimed to investigate the real-world treatment patterns and develop models to predict overall survival (OS) and esophageal cancer-specific survival (ECSS) in patients with stage I-III UESCC.

Methods

Patients with T1-4N0-3M0 UESCC in the Surveillance, Epidemiology, and End Results (SEER) database were identified from 2010 to 2017, and randomized to a training cohort and a validation cohort. The effect of treatment patterns on survival were comprehensively analyzed. Nomograms were developed by incorporating independent prognostic factors analyzed by Cox regression in the training cohort and evaluated by the concordance index (C-index), receiver operating characteristic (ROC) curves, calibration curves, and decision curve analyses (DCA) in two cohorts.

Results

A total of 677 patients were identified, including 452 in the training cohort and 225 in the validation cohort. Among all populations, 71.9% (487) received chemoradiotherapy without surgery, and chemoradiotherapy or/and surgery showed better survival than other treatments. However, surgery was rarely carried out for patients with stage II-III. T stage, N stage, surgery, chemotherapy, and radiotherapy were independent risks for both OS and ECSS, while age was also an independent risk for OS. The C-indexes for nomograms to predict OS (0.71 and 0.72) and ECSS (0.70 and 0.73) were greater than 7th AJCC staging system to predict OS (0.61 and 0.64) and ECSS (0.64 and 0.64) in both the training cohort and the validation cohort. Time-dependent ROC curves and DCA also suggested that nomograms performed consistently better than 7th AJCC staging system. The calibration curves demonstrated good consistency in predicting survival.

Conclusions

Chemoradiotherapy was a major treatment with preferable survival for patients with stage I-III UESCC. We have firstly developed and validated prognostic nomograms in patients with stage I-III UESCC, which would play a supplementary role in the current staging system.

An Interpretable Two-Phase Modeling Approach for Lung Cancer Survivability Prediction

Although lung cancer survival status and survival length predictions have primarily been studied individually, a scheme that leverages both fields in an interpretable way for physicians remains elusive. We propose a two-phase data analytic framework that is capable of classifying survival status for 0.5-, 1-, 1.5-, 2-, 2.5-, and 3-year time-points (phase I) and predicting the number of survival months within 3 years (phase II) using recent Surveillance, Epidemiology, and End Results data from 2010 to 2017. In this study, we employ three analytical models (general linear model, extreme gradient boosting, and artificial neural networks), five data balancing techniques (synthetic minority oversampling technique (SMOTE), relocating safe level SMOTE, borderline SMOTE, adaptive synthetic sampling, and majority weighted minority oversampling technique), two feature selection methods (least absolute shrinkage and selection operator (LASSO) and random forest), and the one-hot encoding approach. By implementing a comprehensive data preparation phase, we demonstrate that a computationally efficient and interpretable method such as GLM performs comparably to more complex models. Moreover, we quantify the effects of individual features in phase I and II by exploiting GLM coefficients. To the best of our knowledge, this study is the first to (a) implement a comprehensive data processing approach to develop performant, computationally efficient, and interpretable methods in comparison to black-box models, (b) visualize top factors impacting survival odds by utilizing the change in odds ratio, and (c) comprehensively explore short-term lung cancer survival using a two-phase approach.

Development and Validation of Survival Nomograms in Patients with Primary Bladder Lymphoma

Background: The existing studies on primary bladder lymphoma (PBL) are retrospective analyses based on individual cases or small series studies, and the research on PBL is not unified and in-depth enough at present because of the scarcity of PBL and the lack of relevant literature. This study is designed to develop and validate nomograms for overall survival (OS) and cancer-specific survival (CSS) prediction in patients with PBL. Methods: According to the Surveillance, Epidemiology, and End Results (SEER) database, 405 patients diagnosed with PBL from 1975 to 2016 were collected and randomly assigned to training (n = 283) and validation (n = 122) cohort. After the multivariable Cox regression, the OS and CSS nomograms were developed. The discrimination, calibration and clinical usefulness of the nomograms were assessed and validated, respectively, by the training and validation cohort. Furthermore, all of the patients were reclassified into high- and low-risk groups and their survival were compared through Kaplan-Meier method and log-rank test. Results: Age, subtype, Ann Arbor stage, radiation and chemotherapy were identified as independent prognostic factors for OS and age, sex, and subtype for CSS, then corresponding nomograms predicting the 3- and 5-year survival were constructed. The presented nomograms demonstrated good discrimination and calibration, which the C-index in the training and validation cohort were 0.744 (95% confidence interval [CI], 0.705–0.783) and 0.675 (95% CI, 0.603–0.747) for OS nomogram and 0.692 (95% CI, 0.632–0.752) and 0.646 (95% CI, 0.549–0.743) for CSS nomogram, respectively. Furthermore, the nomograms can be used to effectively distinguish Patients with PBL at high risk of death. The clinical usefulness of the nomograms was visually displayed by decision curve analysis. Conclusion: We updated the baseline characteristics of patients with PBL and constructed OS and CSS nomograms to predict their 3- and 5-year survival. Using these nomograms, it would be convenient to individually predict the prognosis of patients with PBL and provide guidance for clinical treatment.

Comparisons of prognosis prediction accuracy between modified and unmodified versions of 8th edition ypTNM

Background

The prognostic value of the existing 8^th edition post-neoadjuvant treatment (ypTNM) appears to be limited, and necessary reassessment and modification should be carried out as needed. This study aimed to compare the prognosis prediction accuracy of modified and unmodified versions of the 8^th edition ypTNM.

Methods

Esophageal cancer patients who had received neoadjuvant therapy from the Surveillance, Epidemiology, and End Results (SEER) database were included in this observational longitudinal study. The median follow-up time was 26 months. All-cause mortality was the outcome variable. Demographic and clinical variables were collected as covariates. Kaplan-Meier (log-rank test) and Cox proportional hazards models were conducted for developing modified ypTNM staging. The concordance index (C-index) was calculated to analyze the discriminative ability of modified ypTNM staging.

Results

Overall, 3,595 patients met inclusion criteria. The 8^th edition staging was not able to significantly discriminate between patients with ypT1- and ypT2-, ypT3- and ypT4-, ypN2- and ypN3- disease, respectively. Using the modified staging, we found that patients with ypT0–2 [hazard ratio (HR) =1.232; 95% confidence interval (CI): 1.053–1.441] and ypT3–4 (HR =1.257; 95% CI: 1.136–1.390) with grade III + IV had a significant risk of death compared to those with grade I + II. As was the case for the ypN0 (HR =1.295; 95% CI: 1.073–1.562) group with middle and upper tumor locations compared to those with low tumor location. The modified staging possessed better homogeneity in terms of the chi-square likelihood ratio (143.443 vs. 102.044), Akaike information criterion (AIC) (32,683.716 vs. 32,719.115), and Schwarz’s Bayesian criterion (SBC) (32,723.496 vs. 32,741.847), as well as better discriminatory ability (C-index of 0.577 vs. 0.560, P=0.045) compared to the 8^th edition staging.

Conclusions

Although the modified ypTNM staging system we created by incorporating tumor grade and location to the original T and N displayed certain prognosis prediction accuracy compared with the 8^th edition ypTNM staging, a larger sample size and prospective studies are needed to explore.

Comparison of prognostic factors of esophageal cancer between a Chinese cohort and the Surveillance, Epidemiology, and End Results (SEER) database: a retrospective cohort study

Background

Esophageal cancer is a highly aggressive, early metastasis gastrointestinal malignancy, with geographic differences in prognosis. It is unknown whether there are differences in the survival in different regions among esophageal cancer patients who underwent the treatments. This study was to explore the influencing factors of esophageal cancer survival in patients from China and the Surveillance, Epidemiology, and End Results (SEER) database.

Methods

The retrospective cohort study were conducted with 605 Chinese esophageal cancer patients in the Wuxi People's Hospital and 2,351 patients from the SEER database. The demographic and clinical data were collected from the two cohort, respectively. The outcome was the death during the follow-up. The follow-up ended on November 30, 2021. The Cox proportional hazards model was used in the univariate and multivariate survival analyses, with hazard ratio (HR) and 95% confidence interval (CI).

Results

In group one, the following were identified as the prognostic factors: female gender (HR =0.568; 95% CI: 0.398-0.811), T3 and T4 stages (HR =3.312; 95% CI: 2.493-4.401), N2 and N3 stages (HR =3.562; 95% CI: 2.631-4.824), and other subtypes of cancer (HR =0.393; 95% CI: 0.223-0.693). The following prognostic were factors identified in group two: age ≥65 years (HR =1.16; 95% CI: 1.058-1.276), female gender (HR =0.843; 95% CI: 0.752-0.945), T3 and T4 stages (HR =1.523; 95% CI: 1.373-1.690), M1 stage (HR =2.554; 95% CI: 2.303-2.832), treatment with surgery and chemotherapy (HR =0.507; 95% CI: 0.457-0.562), and other subtypes of cancer (HR =1.432; 95% CI: 1.298-1.581).

Conclusions

There may be some differences in prognostic factors between Chinese and American patients with esophageal cancer. It is indicated that different management strategies of esophageal cancer should be considered in different populations to improve the prognosis of patients.

Incidence and survival outcomes of secondary liver cancer: a Surveillance Epidemiology and End Results database analysis

Background

The global incidence and mortality rates of liver cancer, which is the second leading cause of cancer-related deaths worldwide, are increasing. However, information on its epidemiology and clinical prognosis is limited. This study aimed to characterize the epidemiology and prognostic factors of secondary liver cancer to aid in the pretreatment evaluation of the disease.

Methods

Patients diagnosed with secondary liver cancer between 2010 and 2014 in the Surveillance, Epidemiology, and End Results (SEER) database were retrospectively included. Kaplan-Meier analysis and Multivariate Cox regression analysis were performed to screen for significant factors associated with secondary liver cancer.

Results

A total of 85,738 secondary liver cancer patients were identified; in this population, the first primary site was the lung (25.9%), followed by the colorectum, pancreas, stomach, breast, and cecum. Patients with primary tumors of the colorectum, cecum and breast had longer median survival time. Advanced age, male gender, black race, poor differentiation or lack of differentiation, regional lymph node metastases, and presence of distant metastasis were associated with poor prognosis.

Conclusions

In this study, novel findings on the role of the primary site and synchronous distant metastasis to specific organs in patients with secondary liver cancer were described. These findings have significant implications in clinical diagnosis and treatment, and provide a better understanding of secondary liver cancer in the general population.

Application of machine learning approaches to predict the 5-year survival status of patients with esophageal cancer

Background

Accurate prognostic estimation for esophageal cancer (EC) patients plays an important role in the process of clinical decision-making. The objective of this study was to develop an effective model to predict the 5-year survival status of EC patients using machine learning (ML) algorithms.

Methods

We retrieved the information of patients diagnosed with EC between 2010 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) Program, including 24 features. A total of 8 ML models were applied to the selected dataset to classify the EC patients in terms of 5-year survival status, including 3 newly developed gradient boosting models (GBM), XGBoost, CatBoost, and LightGBM, 2 commonly used tree-based models, gradient boosting decision trees (GBDT) and random forest (RF), and 3 other ML models, artificial neural networks (ANN), naive Bayes (NB), and support vector machines (SVM). A 5-fold cross-validation was used in model performance measurement.

Results

After excluding records with missing data, the final study population comprised 10,588 patients. Feature selection was conducted based on the χ² test, however, the experiment results showed that the complete dataset provided better prediction of outcomes than the dataset with removal of non-significant features. Among the 8 models, XGBoost had the best performance [area under the receiver operating characteristic (ROC) curve (AUC): 0.852 for XGBoost, 0.849 for CatBoost, 0.850 for LightGBM, 0.846 for GBDT, 0.838 for RF, 0.844 for ANN, 0.833 for NB, and 0.789 for SVM]. The accuracy and logistic loss of XGBoost were 0.875 and 0.301, respectively, which were also the best performances. In the XGBoost model, the SHapley Additive exPlanations (SHAP) value was calculated and the result indicated that the four features: reason no cancer-directed surgery, Surg Prim Site, age, and stage group had the greatest impact on predicting the outcomes.

Conclusions

The XGBoost model and the complete dataset can be used to construct an accurate prognostic model for patients diagnosed with EC which may be applicable in clinical practice in the future.

Breast-conserving in centrally located breast cancer patients confirmed safe by SEER based study

BACKGROUND

Due to the lack of high-level data, there is still controversy over the oncological safety of breast conservation in patients with centrally located breast cancer. This study aimed to assess the safety of breast-conserving surgery in patients with centrally located breast cancer based on the data from the Surveillance, Epidemiology, and End Results (SEER) database.

METHODS

We collected data for all cases diagnosed with breast cancer who underwent breast-conserving surgery from 2012-2014 in the SEER database. The primary outcome of our study was disease-specific survival (DSS) and overall survival (OS). The PSM was used to eliminate the effects of non-random statistics. Chi-square test, Kaplan-Meier method and Cox proportional hazards regression model on univariate and multivariate analysis were used to analyze the data.

RESULTS

Data from 79,214 patients who had undergone breast-conserving surgery were analyzed in this study, including those with breast cancer in the central region (n=3,128) and outside the central region (n=76,086). The DSS of central breast cancer patients and outside the central breast cancer patients was 58.1 months versus 58.0 months (P>0.05), respectively, while the OS of the 2 groups was 58.0 months versus 58.0 months (P>0.05), respectively.

CONCLUSIONS

Breast cancer in the central region should not be contraindicated for breast conserving surgery and breast-conserving surgery can benefit a wider range of patients.

Sex disparities in thyroid cancer: a SEER population study

BACKGROUND

The incidence and mortality of thyroid cancer vary based on race as well as gender. Both gender thyroid cancer patients give variable clinical characteristics, such as tumor size and distant metastasis. However, sex differences in the prognosis of thyroid cancer remain controversial. Therefore, the present study explored the relationship between gender and prognosis of patients with thyroid cancer for conducive personalized treatment.

METHODS

A retrospective analysis was carried out on patients with pathologically proven thyroid cancer from the Surveillance, Epidemiology, and End Results (SEER) database. The gender disparities in the prognosis of different cohorts, derived by propensity score matching were investigated using Cox proportional hazards models and Kaplan-Meier curves.

RESULTS

Among the studied 41,270 female and 13,188 males with thyroid cancer, gender was an independent prognostic factor for overall (OS) and cancer-specific (CSS) survival (HR =1.632, 95% CI: 1.499-1.777, P<0.001; HR =1.473, 95% CI: 1.245-1.741, P<0.001). Though, male patients had a larger tumor size (17.4 vs. 23.5 cm) and a larger proportion of metastasis [lymph nodes (LNs): 33.2% vs. 21.0%; distant: 2.3% vs. 0.9%], female had a higher incidence and earlier age diagnosis with thyroid cancer (48.0 vs. 52.5 years old). Survival Time (in months) of male patients was also significantly lower than female patients (72.4 vs. 76.8 months). In the Kaplan-Meier curves of cohorts derived by propensity score matching, OS and CSS declined much sharply for male (P<0.001). The mean number (2.0 vs. 4.0) and mean ratio (0.192 vs. 0.297) of positive nodes supported worse prognosis for male patients. Whereas factors including race, age, surgery, histology recodes, T, N, M stage and combined summary stage affected the CSS of male and female patients, however plus median income had an extra impact on male population (≥$55,000 vs. <$55,000: HR =0.739, 95% CI: 0.574-0.953, P=0.020).

CONCLUSIONS

Our study demonstrated that male patients had a prognostic factor for poorer OS and CSS. Other factors including race, age, income, histological type, surgery, T, N, M stage influenced OS of male and female thyroid cancer patients. Interestingly, race had no impact on CSS of thyroid cancer patients, whereas median income affected only the male patients CSS.

Pattern of distant metastases and predictive nomograms in colorectal mucinous adenocarcinoma: a SEER analysis

BACKGROUND

We evaluated the metastatic patterns and explored the prognostic value of distant metastasis pattern in patients with metastatic colorectal mucinous adenocarcinoma (MC) using the Surveillance, Epidemiology, and End Results (SEER) database.

METHODS

Between 2010 and 2015, newly diagnosed colorectal MC patients were selected using the SEER database. Patient prognosis was compared based on the clinicopathological parameters, treatment method, and the site and number of metastatic organs. Cox analyses were used to identify factors associated with overall survival (OS). A nomogram was built to predict the patient's survival. Harrell's concordance index (c-index) and calibration curves were used to analyze the discriminative ability of the prognostic factors.

RESULTS

Of 3,088 patients diagnosed with colorectal MC, the liver was the only metastatic organ in 78.4% (997/1,271) of all liver metastasis cases, the lung was the only metastatic organ in 41.0% (164/400) of all lung metastasis cases, bone was the only metastatic organ in 26.6% (29/109) of all bone metastasis cases, and the brain was the only metastatic organ in 23.5% (4/17) of all brain metastasis cases. Compared with the untreated cases, those treated with chemotherapy, surgery, and radiotherapy had better OS (P<0.001). There were marked OS differences (P<0.001) between patients with and without liver and bone metastases. Patients with bone metastasis had the best survival, while those with brain metastasis had the worst survival (P<0.001). Patients with one metastatic site had better prognosis compared to those with two or three (P<0.001). Patients with liver metastasis had the best survival, while those with bone and brain metastasis had the worst survival (P<0.001). Multivariate analysis showed that age <65 years, non-black race, grade I, N0 stage, chemotherapy, radiation, surgery, liver metastasis, and bone metastasis were independent prognostic factors. A nomogram was constructed to predict survival probability. The c-index value was up to 0.745. The calibration plot showed that the nomogram was clinically useful.

CONCLUSIONS

Metastatic MC (mMC) patients had a characteristic distant metastasis pattern. This study constructed a new and sufficiently accurate prognostic model of mMC based on population-based data. These findings can be utilized to predict prognosis and guide mMC patient management.

Effects of radical cystectomy, radiotherapy, and chemotherapy on the risk of long-term heart-specific death in bladder cancer patients

Background

At present, the low risk of bladder cancer (BCa)-specific death has allowed for investigation into treatment-related cardiotoxicity. To aid clinicians in selecting appropriate cardiovascular disease screening strategies and interventions, this study explored the heart-specific mortality and prognostic factors of patients with BCa after radical cystectomy (RC), radiotherapy (RT), or chemotherapy (CT), and compared their long-term heart-specific mortality with that of the general male population.

Methods

We identified three different treatments for BCa patients from the Surveillance, Epidemiology, and End Results (SEER) database: RC, RT, and CT. Patients were included from 2000 to 2012 and followed through 2015. A cumulative mortality curve and competitive risk regression model were applied to evaluate the prognostic factors of heart-specific mortality, and standardized mortality ratios (SMRs) were calculated.

Results

Of 39,500 men, 30.3%, 18.8%, and 50.9% received RC, RT, and CT, respectively. For patients with a survival period of less than 50 months, tumor-specific death exhibited a rapidly increasing trend, which subsequently flatlined. However, the rates heart-specific mortality and other causes exhibited a tendency to increase stably. The heart-specific and all-cause mortality rates of patients in any age group treated with the three abovementioned strategies were higher than those of the general population. The heart-specific mortality of patients with carcinoma in situ treated with RC and CT exceeded their all-cause mortality, while that of other tumor stages did not. The risks of heart-specific [sub-distribution hazard ratio (SHR) =1.38; 95% confidence interval (CI): 1.22–1.57] and tumor-specific (SHR =1.68; 95% CI: 1.60–1.77) deaths in patients who received RT were higher than those of patients who underwent CT.

Conclusions

The risks of heart-specific and tumor-specific deaths in patients who received RT were higher than those of the RC and CT groups, especially in patients over 65 years of age who received RT.

Prognostic nomogram for predicting long-term survival in bronchopulmonary carcinoid tumor patients receiving resection

Background

We analyzed bronchopulmonary carcinoid tumor (BPC) patients receiving resection from the Surveillance, Epidemiology, and End Results (SEER) database to identify the predictive factors of their survival. Then, we developed and validated nomograms to predict overall survival (OS) and cancer-specific survival (CSS) in BPC patients.

Methods

BPC patients registered in the SEER database were included. They were divided into a training set and an internal validation set (7:3). BPC patients from our center were included as an external validation set. Independent prognostic factors identified by a Cox regression model in the training set were used to construct nomograms to predict survival. Discrimination and calibration plots were used to evaluate the predictive accuracy of the nomograms. The nomograms were evaluated in both the internal and the external validation datasets.

Results

Age, pathological type, and N stage were identified as independent prognostic factors of OS and CSS by Cox analyses (all P<0.05). Tumor size ≥2.5 cm (P=0.045) was an independent factor for unfavorable CSS. Based on these variables, nomograms were constructed. All concordance indexes of the training set, internal validation set, and external validation set indicated that the nomograms had the preferable discriminatory ability. The calibration plots for predictions of the 1-, 3-, and 5-year OS and CSS were in excellent agreement.

Conclusions

Age, pathological type, N stage, and tumor size were independent predictive factors of prognosis in BPC patients receiving resection. These nomograms could serve as effective and accurate tools for the prognostic evaluation of patients with BPCs.

Evaluating anthracycline + taxane versus taxane-based chemotherapy in older women with node-negative triple-negative breast cancer: a SEER-Medicare study

Purpose

Adjuvant chemotherapy reduces recurrence in early-stage triple-negative breast cancer (TNBC). However, data are lacking evaluating anthracycline + taxane (ATAX) versus taxane-based (TAX) chemotherapy in older women with node-negative TNBC, as they are often excluded from trials. The purpose of this study was to evaluate the effect of adjuvant ATAX versus TAX on cancer-specific (CSS) and overall survival (OS) in older patients with node-negative TNBC.

Patients and methods

Using the SEER-Medicare database, we selected patients aged ≥ 66 years diagnosed with Stage T1-4N0M0 TNBC between 2010 and 2015 (N = 3348). Kaplan–Meier survival curves and adjusted Cox proportional hazards models were used to estimate 3-year OS and CSS. Multivariant Cox regression analysis was used to identify independent factors associated with use of ATAX compared to TAX.

Results

Approximately half (N = 1679) of patients identified received chemotherapy and of these, 58.6% (N = 984) received TAX, 25.0% (N = 420) received ATAX, and 16.4% (N = 275) received another regimen. Three-year CSS and OS was improved with any adjuvant chemotherapy from 88.9 to 92.2% (p = 0.0018) for CSS and 77.2% to 88.6% for OS (p < 0.0001). In contrast, treatment with ATAX compared to TAX was associated with inferior 3-year CSS and OS. Three-year CSS was 93.7% with TAX compared to 89.8% (p = 0.048) for ATAX and OS was 91.0% for TAX and 86.4% for ATAX (p = 0.032).

Conclusion

While adjuvant chemotherapy was associated with improved clinical outcomes, the administration of ATAX compared to TAX was associated with inferior 3-year OS and CSS in older women with node-negative TNBC. The use of adjuvant ATAX should be considered carefully in this patient population.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10549-021-06424-z.

Nomograms-based prediction of overall and cancer-specific survivals for patients diagnosed with major salivary gland carcinoma

Background

Major salivary glands carcinoma (MSGC) is a relatively rare cancer with diverse histological types and biological behavior. The treatment planning and prognosis prediction are challenging for clinicians. The aim of the current study was to establish a reliable and effective nomogram to predict the overall survival (OS) and cancer-specific survival (CSS) for MSGC patients.

Methods

Patients pathologically diagnosed with MSGC were recruited from Surveillance, Epidemiology, and End Results (SEER) database and randomly divided into training and validation groups (7:3 ratio). Univariate, multivariate Cox proportional hazard models, and least absolute shrinkage and selection operator (LASSO) regression were adopted for the selection of risk factors. Nomograms were developed using R software. The model performance was evaluated by drawing receiver operating characteristic (ROC), overtime C-index curves, and calibration curves. Harrell C-index, areas under the curves (AUC), and Brier score were also calculated. The decision curve analysis (DCA) was conducted to measure the net clinical benefit.

Results

A total of 11,362 patients were identified and divided into training (n=7,953) and validation (n=3,409) dataset. Sex, age, race, marital status, site, differentiation grade, American Joint Committee on Cancer (AJCC) stage, T/N/M stage, tumor size, surgery, and histological type were incorporated into the Cox hazard model for OS prediction after variable selection, while all predictors, except for marital status and site, were selected for CSS prediction. For 5-year prediction, the AUC of the nomogram for OS and CSS was 83.5 and 82.7 in the training and validation dataset, respectively. The C-index was 0.787 for OS and 0.798 for CSS in the validation group. The Brier score was 0.0153 and 0.0130 for OS and CSS, respectively. The calibration curves showed that the nomogram had well prediction accuracy. From the perspective of DCA, a nomogram was superior to the AJCC stage and TNM stage in net benefit. In general, the performance of the nomogram was consistently better compared to the AJCC stage and TNM stage across all settings.

Conclusions

The performance of the novel nomogram for predicting OS and CSS of MSGC patients was further verified, revealing that it could be used as a valuable tool in assisting clinical decision-making.

The impact of liver fibrosis on microvascular invasion and prognosis of hepatocellular carcinoma with a solitary nodule: a Surveillance, Epidemiology, and End Results (SEER) database analysis

Background

The pathogenesis of non-cirrhotic hepatocellular carcinoma (HCC) with a high recurrence remains controversial, while microvascular invasion (MVI) is highly suggestive of tumor recurrence. This study aimed to investigate the effects of liver fibrosis on MVI and prognosis in HCC.

Methods

Based on the data of HCC in the Surveillance, Epidemiology, and End Results (SEER) database [2004–2015], multivariate logistic regression was used for correlation analysis. Survival was analyzed by Log-Rank test and Cox regression, and decision curve analysis and receiver operating characteristic curves were established to evaluate alternative diagnostic and prognostic strategies.

Results

The study included 1,492 patients with MVI (17.8%) or without MVI (82.2%) for HCC with a solitary nodule. Liver fibrosis was significantly correlated with the occurrence of MVI, and the risk of MVI in patients with a fibrosis score F5–6 was lower than in those with a score of F0–4 (OR =0.651, 95% CI: 0.492–0.860). Combining liver fibrosis could improve the prediction performance of MVI risk models, but liver fibrosis was less associated with survival outcomes in comparison with other tumor characteristics.

Conclusions

Lower liver fibrosis correlated with a higher risk of MVI in HCC with a solitary nodule and was a good indicator for improving the performance of MVI risk models. However, it was not a prognostic sensitive indicator.

Metastatic patterns and prognosis of young lung cancer patients: a population-based study by age

Background

We aimed to examine the different metastatic patterns and corresponding survival outcomes between all ages of young (aged <60 years) and elderly lung cancer patients.

Methods

Lung cancer patients from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015 were divided into a young and elderly group. The young group was subdivided into four consecutive subgroups. Baseline characteristics were analyzed by the Chi-square test. Survival differences were evaluated by Kaplan-Meier curves and Cox proportional hazards models.

Results

Of the total 200,362 lung cancer patients, 155,348 were elderly patients and 45,014 were young patients, including 3,461 aged <45 years, 5,697 aged 45–49 years, 13,645 aged 50–54 years, and 22,211 aged 55–59 years. Compared with elderly lung cancer patients, extrathoracic metastases were significantly more frequent in each younger group, irrespective of the site and number of extrathoracic metastatic organs. Regardless of metastasis patterns, young ages were independent prognostic factors of lung cancer-specific survival (LCSS) [<45 years: hazard ratio (HR): 0.70; 45–49 years: HR: 0.87; 50–54 years: HR: 0.90; 55–59 years: HR: 0.93, all P values were <0.001]. In each age subgroup, patients with multi-organ extrathoracic metastasis had the worst LCSS.

Conclusions

Young lung cancer patients across all ages were at increased risk of extrathoracic metastasis, especially multi-organ patterns, but had a reduced risk of lung cancer-related death compared to elderly patients. Regular and meticulous monitoring of potential metastasized organs is required in young lung cancer patients throughout the follow-up period.

Survival outcomes for cancer types with the highest death rates for adolescents and young adults, 1975-2016

BACKGROUND

Five-year relative survival for adolescent and young adult (AYA) patients with cancer diagnosed at the ages of 15 to 39 years is 85%. Survival rates vary considerably according to the cancer type. The purpose of this study was to analyze long-term survival trends for cancer types with the highest mortality among AYAs to determine where the greatest burden is and to identify areas for future research.

METHODS

Using data from the Surveillance, Epidemiology, and End Results cancer registry and the National Center for Health Statistics, the authors examined the incidence, mortality, and survival for the 9 cancer types with the highest mortality rates in this age group from 1975 to 2016. JPSurv, new survival trend software, was used in the analysis.

RESULTS

Results suggested significant improvements in 5-year relative survival for brain and other nervous system tumors, colon and rectum cancer, lung and bronchus cancer, acute myeloid leukemia, and non-Hodgkin lymphoma (all P values < .05). Limited or no improvement in survival was found for female breast cancer, cervical cancer, ovarian cancer, and bone and joint sarcomas.

CONCLUSIONS

Five-year relative survival for multiple cancer types in AYAs has improved, but some common cancer types in this group still show limited survival improvements (eg, ovarian cancer). Survival improvements in colorectal cancer have been overshadowed by its rising incidence, which suggests a substantial disease burden. Future research should focus on female breast, bone, ovarian, and cervical cancers, which have seen minimal or no improvements in survival.

LAY SUMMARY

Survival trends for adolescents and young adults with cancer are presented from a 40-year period. Although survival progress is noted for brain cancer, lung cancer, acute myeloid leukemia, and colon and rectum cancer, the incidence of colon and rectum cancer remains high. Minimal progress is evident for female breast, bone, ovarian, and cervical cancers, which are in need of renewed focus.

Survival outcomes for patients with four treatments in stages I-III esophageal squamous cell carcinoma: a SEER analysis

Background

Esophageal cancer (EC) is globally acknowledged as one of the most common malignancies among all gastrointestinal cancers. Furthermore, in Eastern Asia, squamous cell carcinoma is the main pathological type of EC. There are different treatments for esophageal squamous cell carcinoma (ESCC), but there is still a lack of large-sample analysis of prognosis among different treatments, especially for different tumor stages. The analysis of the prognosis of ESCC patients with different treatments may be helpful to choose the treatment methods for different stages ESCC.

Methods

A total of 3,346 patients with pathological ESCC between 1976 and 2016 were derived from the Surveillance, Epidemiology, and End Results (SEER) database. All clinical factors associated with prognosis were collected and analyzed to achieve the difference of prognosis among different treatments in ESCC patients, such as ages, sex, race, tumor grade, anatomic location and so on. Kaplan-Meier and Cox proportional hazard analysis were used to compare survival of different treatments in ESCC patients with stage I–III.

Results

The overall survival (OS) in all ESCC patients who had received surgery and surgery plus radiation therapy or/and chemotherapy are superior than that had not received any treatments and radiation therapy or/and chemotherapy. The OS in ESCC patients with stage I who had received surgery and surgery plus radiation therapy or/and chemotherapy are superior than that had not received any treatments and radiation therapy or/and chemotherapy. The OS in ESCC patients with stage II/III who had received surgery and surgery plus radiation therapy or/and chemotherapy are superior than that in other groups. Age, race and grade as an independent predictive factor for survival (P<0.05). A nomogram model was constructed to show surgery group had better 1-, 3- and 5-year OS than radiation therapy or/and chemotherapy group (OS: 78.5% vs. 59.2%, 37.9% vs. 18.4%, 16.9% vs. 6.1%).

Conclusions

Surgery is still the first choice for all ESCC patients with stage I–III. Radiotherapy and chemotherapy could improve the survival rate in ESCC patients with stage II–III who have received surgery.

A nomogram for predicting brain metastasis in patients with de novo stage IV breast cancer

Background

Brain metastasis (BM) is a very serious event in patients with breast cancer. The aim of this study was to establish a nomogram to predict the risk of BM in patients with de novo stage IV breast cancer.

Methods

We gathered female patients diagnosed with de novo stage IV breast cancer between 2010 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database. After randomly allocating the patients to the training set and verification set, we used univariate and multivariate logistic regression to analyze the relationship between BM and clinicopathological features. Finally, we developed a nomogram which was validated by the analysis of calibration curve and receiver operating characteristic curve.

Results

Of 7,154 patients with de novo stage IV breast cancer, 422 developed BM. Age, tumor size, subtype, and the degree of lung involvement were significantly correlated with BM. The nomogram had discriminatory ability with an area under curve (AUC) of 0.640 [95% confidence interval (CI): 0.607 to 0.673] in the training set, and 0.644 (95% CI: 0.595 to 0.693) in the validation set.

Conclusions

Our study developed a nomogram to predict BM for de novo stage IV breast cancer, thus helping clinicians to identify patients at high-risk of BM and implement early preventive interventions to improve their prognoses.

Association of race and health care system with disease stage and survival in veterans with larynx cancer

BACKGROUND

Black patients with laryngeal squamous cell carcinoma (LSCC) historically have inferior outcomes in comparison with White patients. The authors investigated these racial disparities within the Veterans Health Administration (VHA), an equal-access system, and within the Surveillance, Epidemiology, and End Results (SEER) program, which is representative of the US hybrid-payer system.

METHODS

Patients with invasive (T1 or greater) LSCC were included from SEER (2004-2015) and the VHA (2000-2017). The primary outcomes of overall survival (OS) and larynx cancer-specific survival (LCS) were evaluated in Cox and Fine-Gray models.

RESULTS

In the SEER cohort (7122 patients: 82.6% White and 17.4% Black), Black patients were more likely to present with advanced disease and had inferior OS (hazard ratio [HR], 1.37; 95% CI, 1.26-1.50; P < .0001) in a multivariable analysis. Black LCS was worse in a univariable analysis (HR, 1.42; 95% CI, 1.27-1.58; P < .0001), but this effect was attenuated by 83% when the authors controlled for the TNM category and was found to be insignificant in a multivariable analysis (HR, 1.05; 95% CI, 0.93-1.18; P = .42). In the VHA cohort (9248 patients: 79.7% White and 20.3% Black), the 2 racial cohorts presented with similar tumor characteristics and similar OS (HR, 0.95; 95% CI, 0.89-1.02; P = .14). Black LCS was similar in univariable (HR, 1.10; 95% CI, 1.00-1.22; P = .05) and multivariable analyses (HR, 1.02; 95% CI, 0.92-1.14; P = .67).

CONCLUSIONS

Black patients with LSCC had a tumor burden at diagnosis and survival outcomes comparable to those of White patients within the VHA; this was counter to what was observed in the SEER analysis and prior national trends. This study's findings point toward the notable role of health care access in contributing to racial health disparities in the realm of larynx cancer.

Differential prognostic implications of gastric adenocarcinoma based on Lauren's classification: a Surveillance, Epidemiology, and End Results (SEER)-based cohort study

Background

Our study aims to analyze the association between Lauren's classification and gastric adenocarcinoma prognosis using comprehensive statistical analyses.

Methods

According to the selection criteria, patients were included from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox regression, propensity score matching, and a multivariate competing risk model were used to investigate the association between Lauren's classification and prognosis. Subgroup analysis was used to investigate the role of confounding factors on the association between Lauren types and prognosis.

Results

After exclusion, a total of 20,218 patients from the SEER database were included, with 14,374 intestinal types and 5,844 diffuse types. The univariate Cox regression analysis revealed that the diffuse type had a poorer cancer-specific survival (CSS) rate [hazard ratio (HR), 1.44; 95% confidence interval (CI), 1.38-1.50]. After adjusting for confounding variables, the diffuse type also showed a higher risk of cancer-specific death (HR, 1.20; 95% CI, 1.15-1.20). Sensitivity analysis showed that after propensity score matching, the diffuse type had a poorer CSS rate (HR, 1.23; 95% CI, 1.10-1.36), and the competing risk model further validated these results [subdistribution HR (SHR), 1.32; 95% CI, 1.23-1.41]. Moreover, subgroup analysis demonstrated stable results in the subgroups, except for patients with T1 stage (HR, 1.06; 95% CI, 0.87-1.28) and a tumor size <2 cm (HR, 1.00; 95% CI, 0.83-1.21).

Conclusions

Diffuse-type gastric adenocarcinoma had an overall poorer prognosis compared to the intestinal type. However, in patients with T1 stage and tumor size <2 cm, the diffuse type had a comparable survival rate with the intestinal type.

Clinical Characteristics and Prognosis of Patients With Pulmonary Mucoepidermoid Carcinoma: A SEER-Based Analysis

Background

Primary pulmonary mucoepidermoid carcinoma (PMEC) is an extremely rare malignancy. Its clinical characteristics and prognosis are not fully understood. This study evaluated clinical characteristics and prognostic factors of PMEC and established a nomogram to predict its 1-, 3-, 5- and 10-year cancer-specific survival (CSS) rates.

Methods

In the Surveillance, Epidemiology, and End Results database from January 1, 2016 to December 31, 2016, patients pathologically diagnosed with PMEC were identified. Kaplan-Meier analysis and Cox regression were performed to evaluate the CSS stratified by different covariates. A predictive nomogram model was built and validated by the concordance index (C-index) and calibration curves.

Results

A total of 585 PMEC patients were identified. A total of 408 (70%) of patients were placed into the training cohort, and 177 (30%) patients were placed into the validation cohort. The 5- and 10-year CSS rates of stage I-II PMEC patients were 91.4 and 88.9, respectively. The 1-, 3- and 5-year CSS rates of stage III-IV PMEC were 56.5, 39.45, and 32.1%, respectively. Survival curves showed that older age, large tumor size, poor differentiation, and high TNM stage were associated with a significantly worse prognosis. CSS outcomes were significantly better in patients who received surgical treatments (surgical alone, surgery plus radiation and/or chemotherapy). Patients who received radiation and/or chemotherapy had the worst prognosis. Multivariate Cox results revealed that covariates, including age, tumor laterality, tumor sizes, pathological differentiation, lymph node metastasis, distant metastasis, TNM stage and therapy, were independent prognostic factors for PMEC. These factors were used to construct a nomogram. The C-index of the nomogram was 0.921. The calibration curve presented favorable consistency between the predicted CSS and actual observations. This nomogram was validated by the validation cohort. The C-index of the validation cohort was 0.968.

Conclusion

Age, bilateral tumors, tumor size, pathological differentiation grade, lymph node metastasis, distant metastasis, TNM stage and therapy were independent prognostic factors of PMEC patients. The first nomogram for predicting the CSS of PMEC was built and validated, showing its potential value in practice.

Nomogram for predicting the survival rate of primary pulmonary mucoepidermoid carcinoma patients: a retrospective study based on SEER database

Background

Primary pulmonary mucoepidermoid carcinoma (PMEC) is a rare malignant tumor, and the clinical manifestations lack specificity. The study evaluates the prognostic factors and constructs a practicable nomogram to estimate the individualized survival status for PMEC patients.

Methods

Surveillance, Epidemiology, and End Results (SEER) database was used to selected eligible patients between 1975 and 2016. The baseline characteristics including age, sex, race, marital status, tumor stage, differentiated degree, tumor laterality, primary tumor site, tumor size, lymph node metastases status, distant metastases status, surgery, chemotherapy, and radiation. We identified independent variables to build 3-, 5-, 10-year overall survival (OS) and cancer-specific survival (CSS) nomograms by univariate and multivariate analyses.

Results

A total of 438 PMEC patients met our selection criteria. In multivariate analysis, age, tumor stage, differentiated grade, tumor size, lymph node metastases status, distant metastases status, surgery and radiation were involved in the nomogram. The C-index (0.887 (95% CI: 0.863-0.911), calibrate plots and ROC curves (AUC =0.941, 0.951, 0.935 for 3-, 5-, 10-year OS, respectively) indicated the satisfied accuracy and practicability of our nomograms. Compared to TNM system, our model also showed a superior prediction (IDI =0.167, 0.171, 0.172, P<0.001).

Conclusions

We built OS (CSS) nomograms that can accurately estimate individualized survival time and identify the risk classification of PMEC.

Population-based survival of pediatric rhabdomyosarcoma of the head and neck over four decades

OBJECTIVES

Clinical trials have reported increases in the survival of pediatric rhabdomyosarcoma (RMS) from 25% in 1970 to 73% in 2001. The purpose of this study was to examine whether survival of pediatric patients with RMS of the head and neck improved at the US population level.

METHODS

A population-based cohort of patients with rhabdomyosarcoma of the head and neck aged 0-19 years in the Surveillance, Epidemiology, and End Results (SEER) registry from 1973 to 2013 was queried. The cumulative incidence competing risks (CICR) method was used to estimate risk and survival trends.

RESULTS

718 cases were identified for analysis. Survival rates at 1-, 5-, and 10-years after diagnosis were 91.2%, 73.2%, and 69.4% respectively. Survival rates at 1 year after diagnosis increased from 82.6% to 93.1% during the study period. In the subdistributional hazard analysis, there was a significantly improved disease-specific risk of death in the first year after diagnosis. Overall risk of death did not improve significantly. Favorable prognostic factors included age <10 years at diagnosis, smaller tumor size, absence of distant metastasis, localized tumors, earlier stage at presentation, grossly complete surgical resection, and embryonal or botryoid histology.

CONCLUSIONS

Disease-specific survival in the first year following diagnosis improved, but the change in overall survival at the population level was not statistically significant. These findings should be interpreted in light of the inclusion of patients with distant metastasis at diagnosis, who have poor prognoses, together with the limited statistical power afforded in studies of rare diseases.