Nomogram predicts risk and prognostic factors for lung metastasis of anaplastic thyroid carcinoma: a retrospective study in the Surveillance Epidemiology and End Results (SEER) database
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PROVIDER: S-EPMC10774033 | biostudies-literature | 2023 Dec
REPOSITORIES: biostudies-literature
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Project description:BackgroundLung cancer remains the leading cause of cancer death globally. In 2015, the cancer classification guidelines of the World Health Organization were updated. The term "invasive mucinous adenocarcinoma (IMA)" aroused people's attention, while the clinicopathological factors that may influence survival were unclear.MethodsData of IMA patients was downloaded from SEER database. Kaplan-Meier methods and log-rank tests were used to compare the differences in OS and LCSS. The nomogram was developed based on the result of the multivariable analysis. The discrimination and accuracy were tested by Harrell's concordance index (C-index), receiver operating characteristic (ROC) curve, calibration curve and decision curve analyses (DCA). Integrated discrimination improvement (IDI) index was used to evaluate the clinical efficacy.ResultsAccording to multivariate analysis, the prognosis of IMAs was associated with age, differentiation grade, TNM stage and treatments. Surgery might be the only way that would improve survival. Area under the curve (AUC) of the training cohort was 0.834and 0.830 for3-and 5-year OS, respectively. AUC for 3-and 5-year LCSS were separately 0.839 and 0.839. The new model was then evaluated by calibration curve, DCA and IDI index.ConclusionBased on this study, prognosis of IMAs was systematically reviewed, and a new nomogram was developed and validated. This model helps us understand IMA in depth and provides new ideas for IMA treatment.
| S-EPMC7877040 | biostudies-literature
Project description:BackgroundMedullary thyroid carcinoma (MTC) has been separated into its own chapter in the 8th edition of the American Joint Committee on Cancer (AJCC) staging system. However, controversies still exist for the staging of MTC. This study aimed to identify prognostic differences among patients with MTC to define a more accurate staging system.MethodsData on cancer-specific survival from the Surveillance, Epidemiology, and End Results database between 2010 and 2014 were used for this study. Kaplan-Meier (K-M) curves, Cox proportional hazards regression analysis, and mortality per 1000-person-years were used to evaluate the mortality rate to create the new staging system.ResultsA total of 960 cases were included in this analysis. The mortality rates of 24 different groups, which were classified using T stage (T1-4), N stage (N0-1b), and M stage (M0-1) were assessed using K-M curves. Cox proportional hazards regression analysis and mortality per 1000-person-years were used to classify patients, as stage I (T1-3N0-1aM0, 654, 68.34%), stage II (T1-3N1bM0, 181, 18.91%), stage III (T4N0-1bM0, 58, 6.06%), and stage IV (T1-4N0-1bM1, 64, 6.69%). The hazard ratios of stages II, III, and IV, using stage I as a reference, were 5.281 (95% confidence interval [CI], 1.236-22.562), 20.603 (95% CI, 4.400-96.467), and 55.717 (95% CI, 14.307-216.988), respectively. The mortality rates per 1000-person-years of stages I, II, III, and IV were 2.036 (95% CI, 0.657-6.312), 14.867 (95% CI, 6.679-33.092), 98.287 (95% CI, 54.432-177.478), and 224.199 (95% CI, 146.180-343.860), respectively.ConclusionsCompared with the current AJCC tumor-node-metastasis (TNM) staging system for MTC, this new proposed TNM staging system, which is based on cancer-specific mortality rate analysis, provides more accurate risk stratification and can ensure more rational treatment measures.
| S-EPMC7344094 | biostudies-literature
Project description:BackgroundThis study aimed to establish a novel nomogram prognostic model to predict death probability for non-small cell lung cancer (NSCLC) patients who received surgery..MethodsWe collected data from the Surveillance, Epidemiology, and End Results (SEER) database of the National Cancer Institute in the United States. A nomogram prognostic model was constructed to predict mortality of NSCLC patients who received surgery.ResultsA total of 44,880 NSCLC patients who received surgery from 2004 to 2014 were included in this study. Gender, ethnicity, tumor anatomic sites, histologic subtype, tumor differentiation, clinical stage, tumor size, tumor extent, lymph node stage, examined lymph node, positive lymph node, type of surgery showed significant associations with lung cancer related death rate (P < 0.001). Patients who received chemotherapy and radiotherapy had significant higher lung cancer related death rate but were associated with significant lower non-cancer related mortality (P<0.001). A nomogram model was established based on multivariate models of training data set. In the validation cohort, the unadjusted C-index was 0.73 (95% CI, 0.72-0.74), 0.71 (95% CI, 0.66-0.75) and 0.69 (95% CI, 0.68-0.70) for lung cancer related death, other cancer related death and non-cancer related death.ConclusionsA prognostic nomogram model was constructed to give information about the risk of death for NSCLC patients who received surgery.
| S-EPMC7367407 | biostudies-literature
Project description:BackgroundAnaplastic thyroid cancer (ATC) is highly invasive, prone to distant metastasis (DM), and has a very poor prognosis. This study aims to construct an accurate survival prediction model for ATC patients with DM, providing reference for comprehensive assessment and treatment planning.MethodsWe extracted data of ATC patients with DM diagnosed between 2004 and 2019 from the SEER database, randomly dividing them into a training set and a validation set in a ratio of 7:3. Univariate and multivariate Cox regression analyses were sequentially performed on the training set to identify independent prognostic factors for overall survival (OS) and construct nomograms for 3-month, 6-month, and 8-month OS for ATC patients with DM based on all identified independent prognostic factors. Receiver operating characteristic (ROC) curve analysis, decision curve analysis (DCA) curve analysis, and calibration curves were separately plotted on the training and validation sets to demonstrate the model's performance. Furthermore, patients were stratified into high- and low-risk groups based on their risk scores, and the Kaplan-Meier (KM) survival curves were used to illustrate the survival differences between the two groups.ResultsA total of 322 patients were included in this study. Univariate and multivariate Cox regression analyses identified five independent prognostic factors for OS in ATC patients with DM: surgery, tumor size, age, chemotherapy, and radiotherapy. Nomograms for 3-month, 6-month, and 8-month OS were established based on these factors. The training set AUC values (3-month AUC: 0.767, 6-month AUC: 0.789, 8-month AUC: 0.795) and validation set AUC values (3-month AUC: 0.753, 6-month AUC: 0.798, 8-month AUC: 0.806) as well as the calibration curves demonstrated excellent applicability and accuracy of the model. Additionally, the DCA curves indicated substantial clinical net benefit of the model. The KM curves also confirmed the model's excellent stratification ability for patient OS.ConclusionThe nomogram developed in this study accurately predicts OS for ATC patients with DM. It can assist clinicians in formulating appropriate treatment strategies for these patients.
| S-EPMC11254621 | biostudies-literature
Project description:Introduction: A prediction model for the 1-, 3-, and 5-year survival rates of metastatic colon cancer (mCC) patients was developed by analyzing important risk factors for the prognosis of mCC patients based on the SEER database. Method: The characteristic of 10,946 patients diagnosed with mCC between 2010 and 2015 was obtained from the SEER database. The population was randomly divided into a training cohort and an internal validation cohort in a 7:3 ratio. Univariate and multivariate cox for independent predictors of mCC prognosis were performed, and nomogram was constructed. The accuracy of the model was verified by calibration curves, ROC curves, and C-index, and the clinical utility of the model was analyzed using decision analysis curves. Result: Age, primary site, grade, surgery, and other eight factors were significantly associated with the prognosis of mCC patients, and these predictors were included in the construction of the nomogram. The C-index was 0.731 (95% CI 0.725-0.737) and 0.736 (95% CI 0.726-0.746) for the training cohort and the validation set, respectively. The results of the ROC curve analysis indicated that the area under the curve (AUC) exceeded 0.7 for both the training cohort and the validation set at 1, 3, and 5 years. Conclusion: The constructed prediction model had an excellent predictive accuracy, which will help clinical decision-making of mCC patients after surgery and individualized treatment.
| S-EPMC8864078 | biostudies-literature
Project description:BackgroundMalignant cutaneous granular cell tumors (mcGCTs) are rare and associated with substantial morbidity and mortality. The literature includes single-institution studies.ObjectiveTo examine the incidence, secondary malignancies, treatment, overall survival, and disease-specific survival (DSS) of patients with mcGCT.MethodsA population-based cohort analysis was conducted in the Surveillance, Epidemiology, and End Results database from 1973 to 2013 for patients with a diagnosis of mcGCT. Risk-adjusted associations between overall survival/DSS and patient characteristics and treatment modalities were assessed by Cox proportional hazard regression. Quantile regression was used to determine median survival times.ResultsThe 5-year DSS rate was 62.8%. Patients demonstrated an increased risk for renal and pancreatic cancers. In risk-adjusted models, male sex (hazard ratio [HR], 0.21; 95% confidence interval [CI], 0.06-0.82; P = .02), advanced cancer stage (HR, 2.29; 95% CI, 1.40-3.72; P < .01), and surgical resection (HR, 0.06; 95% CI, 0.01-0.59; P = .02) predicted DSS. Median survival time in years increased for males (1.39), earlier stage (0.60), and surgical intervention (5.34).LimitationsAbsent or incorrect reporting in retrospective Surveillance, Epidemiology, and End Results data is possible. The database is more likely to include academic centers. Some subanalyses may be underpowered because of the limited sample size for a rare cancer.ConclusionsOur study presents an in-depth assessment of factors that identify high-risk patients. Residency in a nonmetro area, black race, female sex, and no surgical resection were each associated with poorer DSS.
| S-EPMC5815907 | biostudies-literature
Project description:BackgroundThe incidence of brain metastasis (BM) in patients suffering from lung squamous cell carcinoma (LUSC) is lower than that in patients suffering from non-squamous cell carcinoma (NSCC) and there are few studies on BM of LUSC. The purpose of this investigation was to ascertain the risk factors of LUSC, as well as to establish a nomogram prognostic model to predict the incidence of BM in patients with LUSC.MethodsPatients diagnosed with LUSC between 2010 and 2015 were identified from the Surveillance, Epidemiology, and End Results (SEER) database and the patient data were collated. All patients diagnosed from 2010-2012 were allocated into the training cohort, and the remaining patients diagnosed from 2013-2015 formed the test cohort. Using factors that were screened out through logistic regression analyses, the nomogram in the training cohort was established. It was then evaluated for discrimination and calibration using the test cohort. The performance of the nomogram was assessed by quantifying the area under the receiver operating characteristic (ROC) curve and evaluating the calibration curve.ResultsA total of 26,154 LUSC patients were included in the study. The training cohort consisted of 16,543 patients and there were 8611 patients in the test cohort. Age, marital status, insurance status, histological grade, tumor location, laterality, stage of the cancer, number of metastatic organs, chemotherapy, surgery, and radiotherapy were highly correlated with the incidence of BM. The area under the ROC curve (AUC) of the nomogram for the training cohort and the test cohort were 0.810 [95% confidence interval (CI): 0.796 to 0.823] and 0.805 (95% CI: 0.784 to 0.825), respectively. The slope of the calibration curve was close to 1.ConclusionsThe nomogram was able to accurately predict the incidence of BM. This may be beneficial for the early identification of high-risk LUSC patients and the establishment of individualized treatments.
| S-EPMC7867817 | biostudies-literature
Project description:BackgroundTelangiectatic osteosarcoma (TOS) is a rare type of osteosarcoma for which limited clinical data is available. Furthermore, the clinical characteristics and prognosis of TOS remain unclear.MethodsA large population-based cohort analysis was conducted using the Surveillance, Epidemiology and End Results (SEER) registry. The data of TOS and conventional osteosarcoma (COS) patients from 2000 to 2017 were collected. The categorical variables were assessed by Chi-squared tests. Kaplan-Meier curves and log-rank (Mantel-Cox) tests were used to examine the survival outcomes between the groups. Cox proportional hazard models were used for univariate and multivariate analyses of TOS patient survival-related variables.ResultsA total of 141 TOS patients and 2961 COS patients were included in this analysis, and the mean age at diagnosis was 23.5 and 29.4 years, respectively. Compared to COS patients, TOS patients were more likely to be under 20 years old (61.7% vs. 51.7%, P=0.022), and without a second peak of incidence after 60 years of age. The median overall survival (mOS) of TOS patients was not reached compared to a median survival of 84 months for COS patients (hazard ratio 0.75, 95% confidence interval 0.59 to 0.95, P=0.0175). After adjusting these data for age at diagnosis, stage, and surgery at the primary site, no significant differences in mOS were observed between the two groups. In univariate analyses, being under 20 years of age, having localized or regional stage disease, and having undergone surgery were associated with a decreased risk of death. Subsequent multivariate analysis indicated that age at diagnosis, stage, and surgery at the primary site were all independent predictors of prognosis in TOS patients.ConclusionsPatients with TOS were younger than patients with COS and did not show a second peak after 60 years of age. Age, summary stage at diagnosis, and surgery at the primary site were independent predictors of survival for TOS patients.
| S-EPMC8246211 | biostudies-literature
Project description:BackgroundRecently, immunotherapy (IO) has shown striking survival improvement in unresectable stage III non-small cell lung cancer (NSCLC). However, the role of chemo-radiotherapy (CRT) for improvement in outcomes should not be disregarded. This study aimed to compare the treatment patterns and illustrate the impact of radiotherapy on the cancer-specific survival (CSS) and overall survival (OS) of patients with unresected locally advanced stage III NSCLC.MethodsWe retrospectively analyzed the data of patients with stage III NSCLC patients who did not undergo surgery from the National Cancer Institute Surveillance, Epidemiology, and End Results (SEER) database between 2001 and 2016, and three continuous years were regarded as one unit. Using the Kaplan-Meier method, we identified the CSS and OS. Then, a linear regression model was graphed to analyze the correlation between median survival of CSS or OS and calendar years in the radiotherapy alone, chemotherapy alone, and CRT groups.ResultsA total of 20986 patients were included in this study. In the overall cohort, CSS and OS improved consistently. To explore the reason for the improved survival, patients were divided into three different cohorts: radiotherapy alone, chemotherapy alone, and CRT. From 2001 to 2015, the median CSS improved persistently, 7, 8, 8, 9, and 11 months in the radiotherapy alone group and 12, 13, 15, 17, 19 months in the CRT group, but improvement in outcomes was less consistent in the chemotherapy alone group (10, 9, 11, 12, 12 months). To better visualize the correlation between CSS and calendar year, linear regression was performed, yielding r2 = 0.8032, P = 0.0395 for the radiotherapy alone group; r2 = 0.7206, P = 0.0689 for the chemotherapy alone group; and r2 = 0.9878, P = 0.0006 for the CRT group. Similar findings were observed in the OS data. In addition to this, we also analyzed different pathological types and also obtained the same results.ConclusionsThe survival of patients with unresectable stage III NSCLC has improved substantially, and the most pronounced and consistent improvements were observed in the CRT group. In addition to IO, radiotherapy played an essential role in the treatment of unresectable stage III NSCLC in the past years and should be considered in the design of clinical trials.
| S-EPMC9248867 | biostudies-literature
Project description:PurposeThe lung is the most common distant metastatic organ in patients with endometrial cancer (EC) but is rarely reported. This study examines the association between clinical characteristics and overall survival (OS) in EC with lung metastasis.MethodsPatients with EC who had accompanying lung metastasis were selected from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2017. Univariate and multivariate Cox regression were used to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs) and assess OS outcomes related to EC with lung metastasis. A Cox proportional hazards nomogram model for OS was constructed and validated. The calibration plot, receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were used to evaluate the discriminative ability and clinical benefit of the novel nomogram. Kaplan-Meier curves and scatter diagram analysis were used to investigate the risk stratifications of the nomogram.ResultsOverall, 1542 EC patients with lung metastasis between 2010 and 2017 were included and randomly divided into training and validation cohorts. A nomogram model was constructed using the clinical characteristics of tumor grade, histological type, surgery, adjuvant chemotherapy, adjuvant radiation, brain metastasis and liver metastasis. The concordance indexes (C-indexes) were 0.750 (95% CI, 0.732-0.767) and 0.743 (95% CI, 0.719-0.767) for the training cohort and validation cohort, respectively. Calibration plots and DCA showed good clinical applicability of the nomogram. The areas under the curves (AUCs) were 0.803 and 0.766 for 1-year and 3-year OS, respectively, indicating that the nomogram model had a stable discriminative ability. An online calculator of our nomogram is available on the internet at https://endometrialcancer.shinyapps.io/DynNomapp/. Additionally, patients in the high-risk group had a significantly worse OS than those in the low-risk group.ConclusionAn easy-to-use, highly accurate nomogram was developed for predicting the prognosis of EC patients with lung metastasis.
| S-EPMC9585205 | biostudies-literature