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.

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.

Survival outcomes of neoadjuvant versus adjuvant therapy in patients with T1c, node-negative, human epidermal growth factor receptor 2-positive breast cancer: A Surveillance, Epidemiology, and End Results population-based study.

BACKGROUND: Persistent debates exist regarding the superiority of neoadjuvant therapy (NAT) over adjuvant therapy (AT) for patients with T1c, node-negative, human epidermal growth factor receptor 2-positive (HER2+) breast cancer, and relevant guidelines for these patients are lacking. METHODS: Data on patients with T1cN0M0-stage HER2+ breast cancer who received chemotherapy and surgery were extracted from 2010 to 2020 from the Surveillance, Epidemiology, and End Results database. Propensity score matching (PSM) was used to create well-balanced cohorts for the NAT and AT groups. Kaplan-Meier (KM) analysis and Cox proportional hazards models were used to assess the differences between NAT and AT in terms of overall survival (OS) and breast cancer-specific survival (BCSS). Additionally, logistic regression models were used to explore factors associated with response to NAT. RESULTS: After PSM, 2140 patient pairs were successfully matched, which achieved a balanced distribution between the NAT and AT groups. KM curves revealed similar OS and BCSS between patients receiving NAT and those undergoing AT. A multivariate Cox model identified achieving pathological complete response (pCR) after NAT, compared with AT, as a protective prognostic factor for OS (hazard ratio, 0.52; 95% CI, 0.35-0.77; p < .001) and BCSS (hazard ratio, 0.60; 95% CI, 0.37-0.98; p = .041). A logistic regression model revealed that White race and hormone receptor-negative status independently predicted pCR. CONCLUSIONS: For patients with T1cN0M0-stage HER2+ breast cancer, NAT demonstrated comparable OS and BCSS to AT. Patients who achieved pCR after NAT exhibited significantly better survival outcomes compared with those who received AT.

Cost-of-care discussions for individuals with advanced non-small cell lung cancer and melanoma: Findings from a large, population-based pilot study.

BACKGROUND: Costs of cancer care can result in patient financial hardship; many professional organizations recommend provider discussions about treatment costs as part of high-quality care. In this pilot study, the authors examined patient-provider cost discussions documented in the medical records of individuals who were diagnosed with advanced non-small cell lung cancer (NSCLC) and melanoma-cancers with recently approved, high-cost treatment options. METHODS: Individuals who were newly diagnosed in 2017-2018 with stage III/IV NSCLC (n = 1767) and in 2018 with stage III/IV melanoma (n = 689) from 12 Surveillance, Epidemiology, and End Results regions were randomly selected for the National Cancer Institute Patterns of Care Study. Documentation of cost discussions was abstracted from the medical record. The authors examined patient, treatment, and hospital factors associated with cost discussions in multivariable logistic regression analyses. RESULTS: Cost discussions were documented in the medical records of 20.3% of patients with NSCLC and in 24.0% of those with melanoma. In adjusted analyses, privately insured (vs. publicly insured) patients were less likely to have documented cost discussions (odds ratio [OR], 0.54; 95% confidence interval [CI], 0.37-0.80). Patients who did not receive systemic therapy or did not receive any cancer-directed treatment were less likely to have documented cost discussions than those who did receive systemic therapy (OR, 0.39 [95% CI, 0.19-0.81] and 0.46 [95% CI, 0.30-0.70], respectively), as were patients who were treated at hospitals without residency programs (OR, 0.64; 95% CI, 0.42-0.98). CONCLUSIONS: Cost discussions were infrequently documented in the medical records of patients who were diagnosed with advanced NSCLC and melanoma, which may hinder identifying patient needs and tracking outcomes of associated referrals. Efforts to increase cost-of-care discussions and relevant referrals, as well as their documentation, are warranted.

Natural History and Prognostic Model of Untreated Papillary Thyroid Cancer: A SEER Database Analysis.

PURPOSE: This investigation leveraged the SEER database to delve into the progression patterns of PTC when left untreated. Furthermore, it aimed to devise and authenticate a nomogram for prognosis prediction for such patients. METHODS: We extracted data from the SEER database, focusing on PTC-diagnosed individuals from 2004-2020. To discern disease progression intervals, median survival times across stages were gauged, and the disease progression time was estimated by subtracting the median survival time of a more severe stage from its preceding stage. Prognostic determinants in the training set were pinpointed using both univariate and multivariate Cox regression. Using these determinants, a prognostic nomogram was crafted. RESULTS: In untreated PTC patients, those in stages I and II had a favorable prognosis, with 10-year overall survival rates of 86.34% and 66.03%, respectively. Patients in stages III and IV had a relatively poorer prognosis. The median survival time of stage III, stage IVA, stage IVB and stage IVC patients was 108months, 43 months, 20 months and 8 months, respectively. The deduced progression intervals from stages III-IVC were 65, 23, and 12 months. In the training set, age, tumor stage, gender, and marital status were identified as independent risk factors influencing the prognosis of untreated PTC, and a nomogram was constructed using these variables. CONCLUSION: In the absence of treatment intervention, early-stage PTC progressed slowly with an overall favorable prognosis. However, in mid to advanced-stage PTC, as tumor stage increased, disease progression accelerated, and prognosis gradually worsened. Age, tumor stage, marital status, and gender were independent risk factors influencing the prognosis of untreated PTC, and the nomogram based on these factors demonstrated good prognostic capability.

PurposeThis investigation leveraged the SEER database to delve into the progression patterns of PTC when left untreated. Furthermore, it aimed to devise and authenticate a nomogram for prognosis prediction for such patients.MethodsWe extracted data from the SEER database, focusing on PTC-diagnosed individuals from 2004-2020. To discern disease progression intervals, median survival times across stages were gauged, and the disease progression time was estimated by subtracting the median survival time of a more severe stage from its preceding stage. Prognostic determinants in the training set were pinpointed using both univariate and multivariate Cox regression. Using these determinants, a prognostic nomogram was crafted.ResultsIn untreated PTC patients, those in stages I and II had a favorable prognosis, with ten-year overall survival rates of 86.34% and 66.03%, respectively. Patients in stages III and IV had a relatively poorer prognosis. The median survival time of stage III, stage IVA, stage IVB and stage IVC patients was 108months, 43 months, 20 months and 8 months, respectively. The deduced progression intervals from stages III-IVC were 65, 23, and 12 months. In the training set, age, tumor stage, gender, and marital status were identified as independent risk factors influencing the prognosis of untreated PTC, and a nomogram was constructed using these variables.ConclusionIn the absence of treatment intervention, early-stage PTC progressed slowly with an overall favorable prognosis. However, in mid to advanced-stage PTC, as tumor stage increased, disease progression accelerated, and prognosis gradually worsened. Age, tumor stage, marital status, and gender were independent risk factors influencing the prognosis of untreated PTC, and the nomogram based on these factors demonstrated good prognostic capability.

Survival Predictive Nomograms for Non-Surgical Brain Metastases Patients From Non-Small Cell Lung Cancer Receiving Radiotherapy: A Population-Based Study.

OBJECTIVE: A high number of Non-Small Cell Lung Cancer (NSCLC) patients with brain metastasis who have not had surgery often have a negative outlook. Radiotherapy remains a most common and effective method. Nomograms were developed to forecast the cancer-specific survival (CSS) and overall survival (OS) in NSCLC individuals with nonoperative brain metastases who underwent radiotherapy. METHODS: Information was gathered from the Surveillance, Epidemiology, and End Results (SEER) database about patients diagnosed with NSCLC who had brain metastases not suitable for surgery. Nomograms were created and tested using multivariate Cox regression models to forecast CSS and OS at intervals of 1, 2, and 3 years. RESULTS: The research involved 3413 individuals diagnosed with NSCLC brain metastases who had undergone radiotherapy but had not experienced surgery. These participants were randomly divided into two categories. The analysis revealed that gender, age, ethnicity, marital status, tumor location, tumor laterality, tumor grade, histology, T stage, N stage, chemotherapy, tumor size, lung metastasis, bone metastasis, and liver metastasis were significant independent predictors for OS and CSS. The C-index for the training set for predicting OS was .709 (95% CI, .697-.721), and for the validation set, it was .705 (95% CI, .686-.723), respectively. The C-index for predicting CSS was .710 (95% CI, .697-.722) in the training set and .703 (95% CI, .684-.722) in the validation set, respectively. The nomograms model, as suggested by the impressive C-index, exhibits outstanding differentiation ability. Moreover, the ROC and calibration curves reveal its commendable precision and distinguishing potential. CONCLUSIONS: For the first time, highly accurate and reliable nomograms were developed to predict OS and CSS in NSCLC patients with non-surgical brain metastases, who have undergone radiotherapy treatment. The nomograms may assist in tailoring counseling strategies and choosing the most effective treatment method.

Evaluation and Prediction Analysis of 3- and 5-Year Relative Survival Rates of Patients with Cervical Cancer: A Model-Based Period Analysis.

BACKGROUND: Cervical cancer remains a threat to female health due to high mortality. Clarification of the long-term trend of survival rate over time and the associated risk factors would be greatly informative to improve the prognosis of cervical cancer patients. METHODS: This retrospective study was based on data extracted from the Surveillance, Epidemiology, and End Results (SEER) database of the United States. The 3-year and 5-year overall survival rates of patients with cervical cancer during 2002-2006, 2007-2011, and 2012-2016 were analyzed. Period analysis was used to assess the variation in survival rate stratified by age, race, and socioeconomic status during the 15-year study period and then predicted the relative survival rate in the following period from 2017 to 2021. RESULTS: During 2002-2016, the 3-year relative survival rate of cervical cancer patients increased from 73.1% to 73.5% with a high jump between 2007 and 2011. This upward trend is expected to continue to 74.3% between 2017 and 2021. Patients older than 60 years, black ethnicity, or medium and high poverty status were likely to have a lower relative survival rate. CONCLUSION: This study confirmed the increased relative survival rate of cervical cancer patients over years and identified relevant risk factors. Targeted initiatives for elderly and socially underprivileged individuals may be able to mitigate inequality.

Why was the study conducted? Cervical cancer is one of the most common cancers endangering global women's health. Although there are currently relevant screening methods and vaccines, cervical cancer still leads to a higher risk of death in infected women and poses a serious threat to women's health. Therefore, it would be informative for future policy making if the risk factors affecting prognosis were assessed and the trend of long-term survival rate of patients with cervical cancer over time was predicted.What did the researchers do? We extracted data on cervical cancer patients from the Surveillance, Epidemiology, and End Results (SEER) database between 2002 and 2016 and used a model-based period analysis to assess the characteristics of the 3- and 5-year relative survival rates of cervical cancer patients stratified by age, race, and socioeconomic status. The relative survival rate for the period from 2017 to 2021 was projected.What did the researchers find? Our study found that the 3-year relative survival rate for cervical cancer patients increased from 73.1% to 73.5% between 2002 and 2016, with a jump between 2007 and 2011. Patients older than 60 years, those of black ethnicity, or those with medium and high poverty status were more likely to have a low relative survival rate.What do the findings mean? Our study confirms that the relative survival rate of cervical cancer patients has increased in recent years and has maintained an overall upward trend. Our findings suggest that age, race, and socioeconomic status are relevant risk factors. These findings would help us to predict future trends, better allocate medical resources, and optimize health policies to improve the prognosis of cervical cancer, such as targeting the elderly and other vulnerable groups.

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

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

Impact of lymph node retrieval on prognosis in elderly and non-elderly patients with T3-4/N+ rectal cancer following neoadjuvant therapy: a retrospective cohort study.

PURPOSE: The optimal number of lymph nodes to be resected in patients with rectal cancer who undergo radical surgery after neoadjuvant therapy remains controversial. This study evaluated the prognostic variances between elderly and non-elderly patients and determined the ideal number of lymph nodes to be removed in these patients. METHODS: The Surveillance, Epidemiology, and End Results (SEER) datasets were used to gather information on 7894 patients diagnosed with stage T3-4/N+ rectal cancer who underwent neoadjuvant therapy from 2010 to 2019. Of these patients, 2787 were elderly and 5107 were non-elderly. A total of 152 patients from the Longyan First Affiliated Hospital of Fujian Medical University were used for external validation. Overall survival (OS) and cancer-specific survival (CSS) were evaluated to determine the optimal quantity of lymph nodes for surgical resection. RESULTS: The study found significant differences in OS and CSS between elderly and non-elderly patients, both before and after adjustment for confounders (P < 0.001). The removal of 14 lymph nodes may be considered a benchmark for patients with stage T3-4/N+ rectal cancer who undergo radical surgery following neoadjuvant therapy, as this number provides a more accurate foundation for the personalized treatment of rectal cancer. External data validated the differences in OS and CSS and supported the 14 lymph nodes as a new benchmark in these patients. CONCLUSION: For patients with T3-4/N+ stage rectal cancer who undergo radical surgery following neoadjuvant therapy, the removal of 14 lymph nodes serves as a cutoff point that distinctly separates patients with a favorable prognosis from those with an unfavorable one.

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

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

Development and validation of a nomogram for predicting overall survival in patients with early-onset endometrial cancer.

BACKGROUND: This study aimed to investigate the differences in the clinicopathological characteristics of younger and older patients with endometrial cancer (EC) and develop a nomogram to assess the prognosis of early onset EC in terms of overall survival. METHODS: Patients diagnosed with EC from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015 were selected. Clinicopathological characteristics were compared between younger and older patients, and survival analysis was performed for both groups. Prognostic factors affecting overall survival in young patients with EC were identified using Cox regression. A nomogram was created and internal validation was performed using the consistency index, decision curve analysis, receiver operating characteristic curves, and calibration curves. External validation used data from 70 patients with early onset EC. Finally, Kaplan-Meier curves were plotted to compare survival outcomes across the risk subgroups. RESULTS: A total of 1042 young patients and 12,991 older patients were included in this study. Younger patients were divided into training (732) and validation (310) cohorts in a 7:3 ratio. Cox regression analysis identified age, tumorsize, grade, FIGO stage(International Federation of Gynecology and Obstetrics) and surgery as independent risk factors for overall survival, and a nomogram was constructed based on these factors. Internal and external validations demonstrated the good predictive power of the nomogram. In particular, the C-index for the overall survival nomogram was 0.832 [95% confidence interval (0.797-0.844)] in the training cohort and 0.839 (0.810-0.868) in the internal validation cohort. The differences in the Kaplan-Meier curves between the different risk subgroups were statistically significant. CONCLUSIONS: In this study, a nomogram for predicting overall survival of patients with early onset endometrial cancer based on the SEER database was developed to help assess the prognosis of patients and guide clinical treatment.

Two machine learning-based nomogram to predict risk and prognostic factors for liver metastasis from pancreatic neuroendocrine tumors: a multicenter study.

BACKGROUND: Pancreatic neuroendocrine tumors (PNETs) are one of the most common endocrine tumors, and liver metastasis (LMs) are the most common location of metastasis from PNETS; However, there is no valid nomogram to predict the diagnosis and prognosis of liver metastasis (LMs) from PNETs. Therefore, we aimed to develop a valid predictive model to aid physicians in making better clinical decisions. METHODS: We screened patients in the Surveillance, Epidemiology, and End Results (SEER) database from 2010-2016. Feature selection was performed by machine learning algorithms and then models were constructed. Two nomograms were constructed based on the feature selection algorithm to predict the prognosis and risk of LMs from PNETs. We then used the area under the curve (AUC), receiver operating characteristic (ROC) curve, calibration plot and consistency index (C-index) to evaluate the discrimination and accuracy of the nomograms. Kaplan-Meier (K-M) survival curves and decision curve analysis (DCA) were also used further to validate the clinical efficacy of the nomograms. In the external validation set, the same validation is performed. RESULTS: Of the 1998 patients screened from the SEER database with a pathological diagnosis of PNET, 343 (17.2%) had LMs at the time of diagnosis. The independent risk factors for the occurrence of LMs in PNET patients included histological grade, N stage, surgery, chemotherapy, tumor size and bone metastasis. According to Cox regression analysis, we found that histological subtype, histological grade, surgery, age, and brain metastasis were independent prognostic factors for PNET patients with LMs. Based on these factors, the two nomograms demonstrated good performance in model evaluation. CONCLUSION: We developed two clinically significant predictive models to aid physicians in personalized clinical decision-makings.

Impact of Age at Diagnosis of Bladder Cancer on Survival: A Surveillance, Epidemiology, and End Results-Based Study 2004-2015.

BACKGROUND: An older age contributes to the development of bladder cancer. However, the relationship between advanced age at the diagnosis and prognosis of bladder cancer has been few reported. This study aimed to determine the effect of age on survival in bladder cancer with different subgroups. METHODS: 117,275 patients with bladder cancer, identified from the Surveillance, Epidemiology, and End Results database during 2004-2015 in America, were divided into 4 age groups (≤54, 55 to 64, 65 to 74, and ≥75 years). Multivariable Cox proportional-hazards model and competing risk model were conducted according to different age groups. Heat maps were plotted to show the impact of age on survival in subgroups classified by other clinicopathological variables. Moreover, restricted cubic spline was used to model the association between age and the risk of death. RESULTS: Patients aged ≥75 years had shorter overall survival in comparison with those aged ≤54 years (hazard ratio [HR] = 5.36, 95% confidence interval [CI] = 5.13-5.59). Compared with patients aged ≤54 years, patients older than 75 years experienced a decreased rate of bladder cancer-specific survival (subdistribution HR = 2.15, 95% CI = 2.04-2.25). Heat maps also showed that older ages were associated with worse overall cumulative mortality and bladder cancer-specific cumulative mortality. Similarly, restricted cubic spline verified the impact of age on survival of bladder cancer. CONCLUSIONS: Age at diagnosis of bladder cancer was found to be a significant predictor for the worse overall survival and bladder cancer-specific survival even in an era with more effective therapies. Exploring the reasons why older age contributes to poor outcomes for bladder cancer will be the focus of future research.

A Nomogram to Predict the Overall Survival of Patients With Resected T1-2N0-1M0 Non-Small Cell Lung Cancer and to Identify the Optimal Candidates for Adjuvant Chemotherapy in Stage IB or IIA Non-Small Cell Lung Cancer Patients.

BACKGROUND: The benefit of adjuvant chemotherapy for IB/IIA non-small cell lung cancer (NSCLC) patients remains uncertain. This study aimed to develop a prognostic model to predict overall survival in resected NSCLC patients with T1-2N0-1M0 stage and identify optimal candidates for postoperative chemotherapy among those with stage IB or IIA disease. METHODS: We conducted a retrospective study using the SEER 18 database (2000-2018, November 2020 submission) of patients who underwent radical surgery for T1-2N0-1M0 NSCLC. The patients not receiving adjuvant chemotherapy were randomly divided into training and validation cohorts. A prognostic nomogram was established and evaluated using calibration and receiver operating characteristic curves. Based on the nomogram, stage IB and IIA patients were categorized into two prognostic groups, each further divided into cohorts based on adjuvant chemotherapy status. Kaplan-Meier analysis and log-rank tests were used to compare overall survival between these groups. RESULTS: A total of 14 789 patients were enrolled and randomly assigned to the training cohort (n = 10 352) and validation cohort (n = 4437). Ten independent prognostic factors were identified and integrated into the prognostic model. The area under the receiver operating characteristic curve was .706, .699, and .705 in the training cohort, and .700, .698, and .695 in the validation cohort at 1, 3, and 5 years, respectively. Among stage IB and IIA patients, only those in the high-risk group showed a significant benefit from adjuvant chemotherapy, with a 16.4% absolute increase in 5-year overall survival. CONCLUSIONS: The nomogram developed in the study may help physicians choose the most appropriate management strategy for each patient.

Establishment of a Prognostic Nomogram for Cancer-Specific Survival in Patients With Base-of-Tongue Squamous Cell Carcinoma: A Retrospective Study Based on the SEER Database.

BACKGROUND: The aim of this retrospective study was to construct and clinically apply a nomogram for cancer-specific survival (CSS) in patients diagnosed with base-of-tongue squamous cell carcinoma (BOTSCC) to predict their survival prognosis. METHODS: We collected 8448 patients diagnosed with BOTSCC during 2004-2015 from the Surveillance, Epidemiology, and End Results (SEER) database and divided 30% and 70% of them into validation and training cohorts, respectively. We utilized backward stepwise regression in the Cox model to select variables. Predictive variables were subsequently identified from the variables selected above by using multivariate Cox regression. The new survival model was compared with the American Joint Committee on Cancer (AJCC) prognosis model using the following variables: calibration curve, time-dependent area under the receiver operating characteristic curve (AUC), concordance index (C-index), integrated discrimination improvement (IDI), decision-curve analysis (DCA), and net reclassification improvement (NRI). RESULTS: A nomogram was established for predicting the CSS probability in patients with BOTSCC. Factors including sex, race, age at diagnosis, marital status, radiotherapy status, chemotherapy status, TNM AJCC stage, surgery status, tumor size, and months from diagnosis to treatment were selected through multivariate Cox regression as independent predictors of CSS. Calibration plots indicated that the model we established had satisfactory calibration ability. The AUC, C-index, IDI, DCA, and NRI results illustrated that the nomogram performed explicit prognoses more accurately than did the AJCC system alone. CONCLUSION: We identified the relevant factors affecting the survival of BOTSCC patients and analyzed the data on patients suffering from BOTSCC in the SEER database. These factors were used to construct a new nomogram to give clinical staff a more-visual prediction model for the 3-, 5-, and 8-year probabilities of CSS for patients newly diagnosed with BOTSCC, thereby aiding clinical decision making.

Development and Validation of Prognostic Nomograms for Lung Squamous Cell Carcinoma With Brain Metastasis in Patients Aged 45 Years or Older: A Population-Based Study.

PURPOSE: We aimed to establish nomograms to predict the survival in patients aged ≥45  years with lung squamous cell carcinoma and brain metastasis. METHODS: We collected patients diagnosed as lung squamous cell carcinoma with brain metastasis aged ≥45 years between 2010 and 2019 from the Surveillance, Epidemiology, and End Results database. Prognostic factors were determined by the univariate and multivariate Cox regression analysis, and then the nomogram was constructed to predict cancer-specific survival and overall survival. Nomograms were evaluated by decision curve analysis, the area under the receiver operating characteristic curve, calibration plot, concordance index, and risk group stratification. RESULTS: In total, 2437 patients were included, with 1706 and 731 in the cohorts of training and validation, respectively. The age, N stage, T stage, liver metastasis, chemotherapy, bone metastasis, along with radiotherapy were significant in predicting the survival, and adopted for the establishment of nomograms. In the training and validation sets, the concordance index were .713(95%CI:0.699-.728) & .700(95%CI:0.677-.722) in predicting cancer-specific survival and .715(95%CI:0.701-.729) & .712(95%CI:0.690-.735) in predicting overall survival, respectively. Besides, the area under the receiver operating characteristic curve for predicting cancer-specific survival and overall survival in the training set were all >.7 at 1-, 2-, and 3- years. Calibration plots proved the survival predicted by nomograms were consistent with the actual values. decision curve analysis revealed better clinical validity of the nomogram in predicting cancer-specific survival and overall survival at 1-year than TNM staging. Patients were stratified into the high-/low-risk groups according to the optimal cutoff value of 100.21 for cancer-specific survival and 91.98 for overall survival. A web-based probability calculator was constructed finally. CONCLUSION: Two nomograms were developed for the prognostic prediction of lung squamous cell carcinoma patients with brain metastasis aged ≥45 years, providing guidance for decision-making in clinical practice.

Short- and Long-Term Survival of Metastatic Biliary Tract Cancer in the United States From 2000 to 2018.

INTRODUCTION: Information about survival outcomes in metastatic biliary tract cancer (BTC) is sparse, and the numbers often quoted are based on reports of clinical trials data that may not be representative of patients treated in the real world. Furthermore, the impact of more widespread adoption of a standardized combination chemotherapy regimen since 2010 on survival is unclear. METHODS: We performed an analysis of the Surveillance, Epidemiology, and End Results database to determine the real-world overall survival trends in a cohort of patients with metastatic BTC diagnosed between the years 2000 and 2017 with follow-up until 2018. We analyzed data for the entire cohort, evaluated short-term and long-term survival rates, and compared survival outcomes in the pre-2010 and post-2010 periods. Survival analysis was performed using the Kaplan-Meier method, and Cox proportional hazard models were used to evaluate factors associated with survival. RESULTS: Among 13, 287 patients, the median age was 68 years. There was a preponderance of female (57%) and white (77%) patients. Forty-one percent died within 3 months of diagnosis (short-term survivors) and 20% were long-term survivors (12 months or longer). The median overall survival (OS) for the entire cohort was 4.5 months. Median OS improved post-2010 (4.5 months) compared to pre-2010 (3.5 months) (P < .0001). On multivariate analysis, age <55 years, intrahepatic cholangiocarcinoma, surgical resection, and diagnosis post-2010 were associated with lower hazard of death. CONCLUSION: The real-world prognosis of metastatic BTC is remarkably poorer than described in clinical trials because a large proportion of patients survive less than three months. Over the last decade, the improvement in survival has been minimal.

Incidence and risk outcomes of second primary malignancy of patients with post-operative colorectal cancer.

BACKGROUND AND AIMS: This study aimed to investigate the incidence and the risk factors of incidence for second primary malignancies (SPMs) onset among survivors diagnosed with colorectal cancer (CRC). METHODS: A large population-based cohort study was performed. Data of patients diagnosed with CRC was identified and extracted from 8 cancer registries of Surveillance, Epidemiology, and End Results database from January 1990 to December 2017. The outcome of interest was percentage and common sites of SPM onset after primary CRC diagnosis. The cumulative incidence and standardize incidence rates (SIRs) were also reported. Afterwards, we estimated sub-distribution hazards ratios (SHRs) and relative risks (RRs) for SPM occurrence using multivariable competing-risk and Poisson regression models, respectively. RESULTS: A total of 152,402 patients with CRC were included to analyze. Overall, 23,816 patients of all CRC survivors (15.6%) were reported SPM occurrence. The highest proportion of SPMs development after primary CRC diagnosis was second CRC, followed by lung and bronchus cancer among all survivors. Also, CRC survivors were more susceptible to develop second gastrointestinal cancers (GICs). Besides, pelvic cancers were analyzed with a relative high proportion among patients who received RT in comparison to those without RT. The cumulative incidence of all SPMs onset was 22.16% (95% CI: 21.82-22.49%) after near 30-year follow-up. Several factors including older age, male, married status, and localized stage of CRC were related to the high risk of SPMs onset. In treatment-specific analyses, RT was related to a higher cumulative incidence of SPMs occurrence (all SPMs: 14.08% vs. 8.72%; GICs: 2.67% vs. 2.04%; CRC: 1.01% vs. 1.57%; all p < 0.01). Furthermore, the increased risk of SPMs onset was found among patients who received RT than patients within the NRT group (SHR: 1.50, 95% CI: 1.32-1.71), p < 0.01; RR: 1.61, 95% CI: 1.45-1.79, p < 0.01). CONCLUSION: The present study described the incidence pattern of SPM among CRC survivors and identified the risk factors of the SPM onset. RT treatment for patients diagnosed with CRC may increase the risk of SPMs occurrence. The findings suggest the need for long-term follow-up surveillance for these patients.

Characteristics and outcomes of elderly patients with acute myeloid leukemia who receive no treatment in the Surveillance, Epidemiology and End Results-Medicare database.

Background: Without treatment, acute myeloid leukemia (AML) is rapidly fatal. Nevertheless, a large proportion of elderly AML patients do not receive any treatment. Aim: To characterize the demographics, comorbidities, survival and prognostic factors of elderly AML patients who do not receive any AML treatment or supportive care (SC). Methods: A retrospective cohort analysis of the Surveillance, Epidemiology and End Results-Medicare database (2008-2015). Results: Of 7665 AML patients, 2373 (31%) did not receive any AML treatment or SC. The mean age was 80.4 years, 52.8% were males and 79.7% and 95.3% died within the first 60 and 180 days, respectively; 2.1% survived >12 months and only 5.5% of patients had remission or relapse codes populated. Conclusion: Older age, male gender, concurrent depression, ischemic heart disease, chronic kidney disease and benign prostatic hyperplasia were associated with a decreased likelihood of survival. Multiple factors contribute to the complex clinical status of these patients preventing intensive chemotherapy; they should still ideally be treated, at least with the best SC.

An analysis of the data collected in the Surveillance, Epidemiology and End Results-Medicare database from 2008 to 2015 was performed. This database includes data collected by a national cancer registry on people diagnosed with cancer in the United States and those who enroll in Medicare. This study focused on acute myeloid leukemia (AML) patients who did not receive any AML treatment or supportive care (SC). Of 7665 patients with AML, 2373 (31%) did not receive any AML treatment or SC. At the time the data was indexed for each patient in the database, their mean age was 80.4 years and around 53% were males. Within the first 60 days, around 80% of these patients died; over 95% died within the first 180 days. Only 2% of patients survived more than a year without treatment; these patients were likely in remission. Without treatment, AML patients who were older, were male or who also had depression, ischemic heart disease, chronic kidney disease or benign prostatic hyperplasia had a higher chance of dying early. There could be many reasons why these patients are not treated. The main reasons are their poor health condition and the presence of two or more health conditions in a patient at the same time (comorbidities). However, they should still ideally be treated, at least with the best SC. Additional treatment options are urgently needed for elderly AML patients who have comorbidities and are in poor general health.

Elderly patients with acute myeloid leukemia who only receive supportive care in the Surveillance, Epidemiology and End Results-Medicare database: demographics, treatment patterns and outcomes.

Aim: Elderly acute myeloid leukemia (AML) patients are often not treated with antileukemic therapy due to their poor overall health condition, leaving supportive care as the sole treatment option. Objective: To evaluate patient characteristics, treatment patterns and outcomes of elderly patients with AML who are treated with supportive care only. Methods: A retrospective analysis of elderly AML patients included in the Surveillance, Epidemiology and End Results-Medicare database from 2008 to 2015. Results: Of elderly patients with AML (n = 7665), 3209 (41.9%) received supportive care only. Their mean age was 79 years, 50.5% were males; 48.2% died during the first 3 months and 67.3% died during the first 6 months. 82.2% died within the first year; only 13.2% survived >12 months. 77.9% patients died due to leukemia. Conclusion: In elderly AML patients treated with supportive care only, older age, concurrent hypertension, chronic obstructive pulmonary disease, chronic kidney disease and acute myocardial infarction were identified as prognostic factors associated with decreased likelihood of survival. Ideally, these patients should be treated with antileukemic therapy in addition to supportive care, as most of them die from disease progression.

This study analyzed data on elderly patients with acute myeloid leukemia (AML) who were only treated with supportive care. The source of this data was the Surveillance, Epidemiology and End Results (SEER)-Medicare database. Of the 7665 patients diagnosed with AML during 2008­2015, 3209 (41.9%) received supportive care only. Their mean age at index date was 79 years; slightly more than half of these were males (50.5%). Almost half of these patients (48.2%) died within the first 3 months and approximately two-thirds (67.3%) died within the first 6 months. Only a small proportion (13%) of these patients were alive after 1 year. These patients who were alive after one were likely to be in remission (there was decrease in the signs and symptoms of AML). The results of this study showed that elderly AML patients who only received supportive care were more likely to die early if they also had chronic kidney disease, chronic obstructive pulmonary disease, history of acute myocardial infarction or hypertension. As elderly AML patients may be in poor general health and have other diseases (comorbidities), this could be the reason why they may not be treated with antileukemic therapy. Instead of treatment with supportive care only, these patients should ideally receive antileukemic therapy in addition to supportive care. More research should be done to find alternate treatments for these elderly AML patients.