• Gastric carcinoma
• Nomogram
• Overall survival
• Prediction
• Prospective

• Colon cancer
• Early-onset colon cancer
• Late-onset colon cancer
• Nomogram
• SEER

• Humans
• Nomograms
• Carcinoembryonic Antigen
• Prognosis
• Neoplasm Staging
• Colonic Neoplasms/pathology
• SEER Program

• 2021JH2/10300106 Minsheng Science and Technology Program Joint Program

• cancer
• risk factors

• Humans
• Nomograms
• Osteosarcoma/therapy
• Patients
• Calibration
• Bone Neoplasms
• SEER Program
• Prognosis
• Neoplasm Staging

• The Medical Science and Technology Project of Henan Province
• The Medical Science Research Project of Henan Province

• SEER
• bladder cancer
• cancer-specific survival
• nomogram
• overall survival
• prognosis

• feces
• gastric juice
• saliva
• stomach neoplasms
• urine

• SEER database
• elderly patients
• nomogram
• online application
• pancreatic cancer

• Age Factors
• Aged
• Humans
• Nomograms
• Pancreatic Neoplasms/therapy
• Proportional Hazards Models
• SEER Program
• United States/epidemiology
• Pancreatic Neoplasms

Higher methylation levels of RNA-binding protein for multiple splicing 2 (RBPMS2) was reported to be related with unfavorable outcome in gastric cancer (GC). However, molecular function and diagnostic significance of DNA methylation of RBPMS2 remains indistinct. Here we aimed to whether DNA methylation of RBPMS2 acts as a diagnosis biomarker in GC pathogenesis and its potential clinical significance. Western blot and immunochemistry assays were carried out to explore the level of RBPMS2. GC malignancy behaviors were determined by cell counting kit-8, Transwell, flow cytometry analysis and terminal-deoxynucleoitidyl transferase mediated nick end labeling staining. The inflammatory cell infiltration in xenograft model was observed by hematoxylin and eosin staining. CpG Islands was predicted by MethPrimer and the DNA methylation of RBPMS2 was evaluated by methylation-specific polymerase chain reaction. The results showed that RBPMS2 was downregulated in GC specimens. Poor survival rates were associated with low RBPMS2 expression. Overexpression of RBPMS2 inhibited GC growth while facilitated apoptosis in GC cells. In addition, level of DNA methylation of RBPMS2 in GC tissues was increased and DNA methylation of RBPMS2 was strongly associated with tumor invasion, Borrmann classification and TNM stage. We also observed that DNA methylation inhibitors counteracted the role of RBPMS2 in restraining GC development and tumorigenesis. To sum, our data demonstrated that DNA methylation of RBPMS2 was responsible for its downregulation in GC and promoted tumor progression, indicating DNA methylation of RBPMS2 might serve as a valuable potential parameter in GC pathogenesis.

• DNA methylation
• Gastric cancer (GC)
• RBPMS2
• diagnostic significance

• Gastric cancer
• Prognosis
• Recurrence
• Surgery
• Survival

• gastrointestinal stromal tumors in esophagogastric junction
• laparoscopic surgery
• logistic regression
• nomogram
• resection of cardiac structure

• Guangdong Provincial Hospital of Traditional Chinese Medicine

Nomograms are currently used in predicting individualized outcomes in clinical oncology of several cancers. However, nomograms for evaluating occult nodal metastasis of patients with squamous cell carcinoma of lateral tongue (SCCLT) have not been widely investigated for their functionality. This retrospective cohort study was designed to address this question.

This study was divided into primary and validation cohorts. The primary cohort comprised 120 patients diagnosed between 2012 and 2017, whereas the validation cohort included 41 patients diagnosed thereafter. The diagnostic value of multiparametric MRI, including radiologic tumor thickness threshold (rTTT) in three-dimensions, paralingual distance, and sublingual distance were investigated. A nomogram was developed based on stepwise logistic regression of potential predictors associated with nodal metastasis in the primary cohort and then tested for predictive accuracy in the validation cohort using area under the curve (AUC) and goodness-of-fit tests.

Multivariate analysis, tumor size (odd ratio [OR] 15.175, 95% confidence interval [CI] 1.436–160.329, P = 0.024), rTTT (OR 11.528, 95% CI 2.483–53.530, P = 0.002), paralingual distance (OR 11.976, 95% CI 1.981–72.413, P = 0.005), and tumor location (OR 6.311, 95% CI 1.514–26.304, P = 0.011) were included in the nomogram to predict the likelihood of having cervical metastasis. A nomogram cutoff value of 210 points (sensitivity 93.8%, specificity 87.5%) was significantly different to classify the patients metastasis risk group (P < 0.001). Nomogram showed predictive accuracy with AUC 0.881 (95% CI 0.779–0.983, P < 0.001) and good calibration after the validation.

A preoperative nomogram incorporating multiparametric MRI demonstrated good prediction and performed adequately in our study. Three-dimensional assessment of occult metastasis risk value obtained from this nomogram can assist in preoperative decision making for individual patients with early-stage SCCLT. The probability of nodal metastasis tended to be greater than 20% in patients with high metastasis risk or nomogram total score > 210 points.

• Cohort studies
• Magnetic resonance imaging
• Neoplasm invasion
• Neoplasm metastasis
• Nomograms
• Squamous cell carcinoma
• Tongue cancer
• Tumor thickness

• Machine learning
• Nomogram
• Predict
• overall survival
• tongue cancer

This retrospective study aimed to investigate ethnic disparities in demographic, clinicopathologic, and biological behaviours of gastric cancer (GC) in a high GC incidence area of China. There were 5022 GC patients, including 3987 Han (79.4%) and 987 Hui (14.4%) patients from Northwest China. All patient data were retrieved from 2009 to 2017. Median survival was estimated using the Kaplan‐Meier method and compared using the log‐rank test. A Cox proportional hazards model was used to assess the impact of covariates. Similarly, low 5‐year OS rates were observed in both the Hui and Han groups (23.8% and 24.2% respectively). Hui patients with stage T1 or N0 or with tumours <5 cm had 2.144‐fold, 1.426‐fold and 1.305‐fold increased risks of poor prognosis compared with Han patients with these characteristics respectively (all p < 0.05). Further, Hui patients had 1.265‐fold, 1.364‐fold and 1.401‐fold increased risks of poor prognosis compared with Han patients among those with high expression of Ki67, EGFR and VEGF respectively (all p < 0.05). There are ethnic disparities in the prognosis of GC patients in Northwest China. Understanding the effects of ethnicity on GC will guide reasonable evaluations of prognosis and future interventions to equalise access to high‐quality care for GC patients of different ethnicities in China.

• EGFR
• Ki67
• VEGF
• ethnic disparity
• gastric cancer
• prognosis

• calibration curve
• cancer-specific survival
• c-index
• nomogram
• oropharyngeal squamous cell carcinoma
• overall survival
• surveillance, epidemiology and end results

• Adolescent
• Adult
• Aged
• Aged, 80 and over
• Carcinoma, Squamous Cell/mortality
• Female
• Humans
• Male
• Middle Aged
• Nomograms
• Oropharyngeal Neoplasms/mortality
• Retrospective Studies
• SEER Program
• Survival Analysis
• United States/epidemiology
• Young Adult

Background: To identify associated risk factors and develop a predictive nomogram for the early death of metastatic gastric cancer patients.

Methods: A total of 4575 patients in the SEER cohort and 220 patients in the Chinese cohort diagnosed with metastatic gastric cancer in our Cancer Center were obtained. Univariate and multivariate logistic regression models were used to identify independent risk variables for early death. A predictive nomogram and a web-based probability calculator were developed and then validated by receiver operating characteristics (ROCs) curve and calibration plot in a Chinese cohort.

Results: Eight independent variables, including race, grade, surgery, chemotherapy, and metastases of bone, brain, liver, lung were recognized by using univariate and multivariate logistic regression models for identifying independent risk variables of early death about metastatic gastric cancer patients. By comprising these variables, a predictive nomogram and a web-based probability calculator were constructed in the SEER cohort. Then, it could be validated well in the Chinese cohort by receiver operating characteristics (ROCs) curve and calibration plot.

Conclusion: Using this nomogram model provided an insightful and applicable tool to distinguish the early death of metastatic gastric cancer patients.

• Early death
• Nomogram
• SEER
• Stage IV
• Stomach neoplasm

This study aimed to establish and independently validate a prognostic nomogram for individual risk prediction in patients with early-onset diffuse gastric cancer (EODGC). Data for 794 patients with EODGC from the SEER database were randomly assigned to training (N=558) and internal validation (N=236) sets, and data for 82 patients from the Renmin Hospital of Wuhan University (RMHWHU) were used as an independent validation cohort. Our LASSO regression analyses of the training set yielded five clinicopathological features (race, AJCC stage, surgery for primary site, chemotherapy and tumor size), which were used to create a survival nomogram. Our survival nomogram achieved better predictive performance than the AJCC staging system, the current standard. Additionally, the calibration curves of the prognostic nomogram revealed good agreement between the predicted survival probabilities and the ground truth values. Indeed, our nomogram, which estimates individualized survival probabilities for patients with EODGC, shows good predictive accuracy and calibration ability for both the SEER and RMHWHU cohorts. These results suggest that a survival nomogram may be better at predicting OS for EODGC patients than the AJCC staging system.

• AJCC stage
• SEER database
• early-onset diffuse gastric cancer
• overall survival
• prognostic nomogram

Lymph node metastases evaluation is important for assessing gastric cancer prognosis. In patients not undergoing adequate lymph node biopsy, lymph node stage migration occurs with the use of the existing staging system. This study established a prediction model to improve prognostication in patients undergoing fewer than 16 lymph nodes biopsy.

In total, 3036 eligible patients from the Surveillance, Epidemiology, and End Results Program database were evaluated. They were randomized into development and validation sets in a 1:1 ratio (n=1520 and 1516, respectively). To avoid model overfitting and loss of important factors, prognostic factors related to overall survival (OS) were screened according to the Akaike information criterion. The nomogram was assessed using discrimination and consistency tests in the development and validation sets; the concordance index (C-index), calibration curves, and receiver operating characteristic (ROC) curves were also evaluated. Comparison with the 7th American Joint Committee on Cancer (AJCC) staging system was based on Kaplan–Meier curves, ROC, risk stratification, and decision curve analysis (DCA).

Age, race, degree of differentiation, invasion depth, chemotherapy, radiotherapy, and lymph node ratio were independent prognostic factors in OS. C-indices of the development and validation sets were 0.759 (95% CI: 0.741–0.777) and 0.742 (95% CI: 0.713–0.771), respectively; calibration curves were approximately 45° diagonal, indicating good predictive ability of the nomogram. In contrast to the 7th AJCC staging system, the Kaplan–Meier curves and risk stratification of the nomogram had better discrimination ability, the ROC curves of the nomogram achieved more predictive accuracy, and the DCA indicated that the nomogram conferred higher net benefit.

Our constructed nomogram predicts the prognosis of patients with resectable gastric cancer undergoing biopsy of fewer than 16 lymph nodes more precisely and has better clinical applicability than the 7th AJCC staging system.

• gastric cancer
• lymph node ratio
• nomogram
• overall survival

• cancer-specific survival
• lip carcinoma
• nomogram
• overall survival
• surveillance, epidemiology, and end results

• Adolescent
• Adult
• Aged
• Aged, 80 and over
• Carcinoma/mortality
• Case-Control Studies
• Female
• Humans
• Kaplan-Meier Estimate
• Lip Neoplasms/mortality
• Male
• Middle Aged
• Multivariate Analysis
• Nomograms
• Prognosis
• Proportional Hazards Models
• Retrospective Studies
• SEER Program
• Survival Rate
• Young Adult

• Nomogram
• Overall survival
• Pancreatic carcinoma
• Prognosis

• Adult
• Age Factors
• Aged
• Aged, 80 and over
• Clinical Decision-Making/methods
• Female
• Follow-Up Studies
• Humans
• Kaplan-Meier Estimate
• Lymph Nodes/pathology
• Male
• Middle Aged
• Neoplasm Grading
• Neoplasm Staging
• Nomograms
• Pancreas/pathology
• Pancreas/surgery
• Pancreatectomy
• Pancreatic Neoplasms/mortality
• Pancreatic Neoplasms/pathology
• Pancreatic Neoplasms/surgery
• ROC Curve
• SEER Program/statistics & numerical data
• Treatment Outcome
• Pancreatic Neoplasms

• SHDC12018629 Shanghai Shenkang hospital development center
• Shanghai Shenkang hospital development center

• Cancer-specific survival
• Colon cancer
• Nomogram
• Overall survival

• database
• nomogram
• osteosarcoma
• prediction
• survival

• Adolescent
• Adult
• Child
• Child, Preschool
• Cohort Studies
• Female
• Humans
• Infant
• Infant, Newborn
• Male
• Middle Aged
• Nomograms
• Osteosarcoma/diagnosis
• Osteosarcoma/mortality
• Osteosarcoma/pathology
• Osteosarcoma/therapy
• SEER Program
• Survival Analysis
• Young Adult

The goal of this study was to establish and validate two nomograms for predicting the long‐term overall survival (OS) and cancer‐specific survival (CSS) in lip squamous cell carcinoma (LSCC).

This study selected 4175 patients who were diagnosed with LSCC between 2004 and 2015 in the SEER (Surveillance, Epidemiology, and End Results) database. The patients were allocated randomly to a training cohort and validation cohort. Variables were selected using a backward stepwise method in a Cox regression model. Based on the predictive model with the identified prognostic factors, nomograms were established to predict the 3‐, 5‐, and 8‐year survival OS and CSS rates of LSCC patients. The accuracy of the nomograms was evaluated based on the consistency index (C‐index), while their prediction accuracy was evaluated using calibration plots. Decision curve analyses (DCAs) were used to evaluate the performance of our survival model.

The multivariate analyses demonstrated that age at diagnosis, marital status, sex, race, American Joint Committee on Cancer stage, surgery status, and radiotherapy status were risk factors for both OS and CSS. The C‐index, area under the time‐dependent receiver operating characteristic curve, and calibration plots demonstrated the good performance of the nomograms. DCAs of both nomograms further showed that they exhibited good 3‐, 5‐, and 8‐year net benefits.

We have developed and validated LSCC prognosis nomograms for OS and CSS for the first time. These nomograms can be valuable tools for clinical practice when clinicians are helping patients to understand their survival risk for the next 3, 5, and 8 years.

• SEER
• cancer-specific survival
• lip squamous cell carcinoma
• nomogram
• overall survival

A prognostic model to predict the individual disease-specific survival (DSS) rates of non-metastatic esophageal cancer (nMEC) patients after preoperative radiotherapy (pRT) has not been established. In the current study, we aimed to establish a survival nomogram for nMEC patients after pRT.

We identified 2,424 nMEC patients who underwent pRT from the Surveillance, Epidemiology, and End Results database. Approximately, 80% (n=1,948) of the included patients were randomly selected and designated as training data set, and the remaining patients (n=476) were defined as external validation set. Nomogram was established by the training set and validated by the validation set.

According to the results of the multivariate analysis, a nomogram combined with age at diagnosis, sex, tumor location, yp-T stage, yp metastatic lymph node ratio stage (yp-mLNRS), and grade was developed. The C-index of the model was significantly higher than that of yp-TNM staging system (0.62, 95% CI, 0.58 to 0.66 vs 0.55, 95% CI, 0.51 to 0.60; p<0.001). Calibration plots of the nomogram showed that the probability of DSS rates optimally corresponded to the survival rates were observed.

The proposed nomogram resulted in more reliable DSS prediction for nMEC patients in general population, regardless of the patient’s histological type. Upon validation, it will aid in individualized survival prediction and prove useful in clinical decision making in nMECs after pRT.

• SEER
• esophageal cancer
• nomogram
• preoperative radiotherapy

• Cancer-specific survival
• Gastrointestinal stromal tumours
• Nomogram
• Overall survival

BACKGROUND: The objective of current study was to develop and validate a nomogram to predict overall survival in pancreatic neuroendocrine tumors (PNETs). METHODS: The Surveillance, Epidemiology, and End Results (SEER) database was queried for patients with PNETs between 2004 and 2015. Patients were randomly separated into the training set and the validation set. Cox regression model was used in training set to obtain independent prognostic factors to develop a nomogram for predicting overall survival (OS). The discrimination and calibration plots were used to evaluate the predictive accuracy of the nomogram. RESULTS: A total of 3142 patients with PNETs were collected from the SEER database. Sex, age, marital status, primary site, TNM stage, tumor grade, and therapy were associated with OS in the multivariate models. A nomogram was constructed based on these variables. The nomogram for predicting OS displayed better discrimination power than the Tumor-Node-Metastasis (TNM) stage systems 7th edition in the training set and validation set. The calibration curve indicated that the nomogram was able to accurately predict 3- and 5-year OS. CONCLUSIONS: The nomogram which could predict 3- and 5-year OS were established in this study. Our nomogram showed a good performance, suggesting that it could be served as an effective tool for prognostic evaluation of patients with PNETs.

The aim of the study was to develop and validate a nomogram to predict overall survival (OS) in biliary tract cancer (BTC).

Patients diagnosed with BTC between 2004 and 2014 were selected for the study from the Surveillance, Epidemiology, and End Results (SEER) database. All patients were randomly allocated to 2 sets, the training set (n = 8,869) and the validation set (n = 8,766), for the purposes of validation. The prognostic effects of each variable were examined using univariate and multivariate analyses. Cox regression models and a nomogram were developed based on significant prognostic factors. The predictive and discriminatory capacity of the nomogram was evaluated by Harrell’s concordance index (C-index) and calibration plots.

Data of 17,635 patients with BTC were collected from the SEER database. Age; race; tumor site; tumor grade; T, N, and M stage; marital status; and therapy were associated with survival in the multivariate models. All these factors were integrated to construct the nomogram. The nomogram for predicting OS displayed better discrimination power than the tumor-node-metastasis (TNM) stage system 6th edition in the training set and validation set. The calibration curve indicated that the nomogram was able to accurately predict 3- and 5-year OS.

This predictive model has the potential to provide an individualized risk estimate of survival in patients with BTC.

• SEER
• biliary tract cancer
• nomogram
• prognosis

• AJCC
• Gastric cancer
• SEER
• prognosis

To estimate survival in non-metastatic breast cancer patients who failed to achieve a pathological complete response (pCR) more effectively, we combined the clinicpathological characteristics after preoperative radiation therapy (pRT) and established a novel nomogram.

Using the Surveillance, Epidemiology, and End Results (SEER) database, we identified 2,545 non-metastatic breast cancer patients who underwent pRT between 1998 and 2013. Based on the registries of patients, the primary cohort divided into training set (n = 1,692) and validation set (n = 853). Nomograms were established by training set and validated by validation set.

According to the multivariate analysis of training set, nomogram which combined age at diagnosed, marital status, location, grade, ER status, yp-T status, yp-N status and whether received breast conservation surgery (BCS) was developed. Calibration plots of the nomograms showed that the probability of DSS corresponded to actual observation closely. The C-index was 0.78 in validation set, which was significantly higher than that of yp-TNM staging system (0.75, p = 0.004).

The proposed nomogram resulted in more–reliable DSS prediction for non-metastatic breast cancer patients in general population, it would be helpful in individualized survival prediction and better treatment allocation after pRT.

• breast cancer
• nomogram
• preoperative radiotherapy

Exfoliative cytology has been widely used for early diagnosis of oral squamous cell carcinoma. We have developed an oral cancer risk index using DNA index value to quantitatively assess cancer risk in patients with oral leukoplakia, but with limited success. In order to improve the performance of the risk index, we collected exfoliative cytology, histopathology, and clinical follow-up data from two independent cohorts of normal, leukoplakia and cancer subjects (training set and validation set). Peaks were defined on the basis of first derivatives with positives, and modern machine learning techniques were utilized to build statistical prediction models on the reconstructed data. Random forest was found to be the best model with high sensitivity (100%) and specificity (99.2%). Using the Peaks-Random Forest model, we constructed an index (OCRI2) as a quantitative measurement of cancer risk. Among 11 leukoplakia patients with an OCRI2 over 0.5, 4 (36.4%) developed cancer during follow-up (23 ± 20 months), whereas 3 (5.3%) of 57 leukoplakia patients with an OCRI2 less than 0.5 developed cancer (32 ± 31 months). OCRI2 is better than other methods in predicting oral squamous cell carcinoma during follow-up. In conclusion, we have developed an exfoliative cytology-based method for quantitative prediction of cancer risk in patients with oral leukoplakia.

• exfoliative cytology
• oral cancer risk
• oral leukoplakia
• oral squamous cell carcinoma
• quantitative prediction

• curative resection
• gastric cancer
• lymph nodes ratio
• nomogram
• prognosis

• SEER
• Cancer-specific survival
• nomogram
• oral squamous cell carcinoma
• overall survival

• Adolescent
• Adult
• Aged
• Aged, 80 and over
• Carcinoma, Squamous Cell/diagnosis
• Carcinoma, Squamous Cell/epidemiology
• Carcinoma, Squamous Cell/mortality
• Female
• Humans
• Male
• Middle Aged
• Mouth Neoplasms/diagnosis
• Mouth Neoplasms/epidemiology
• Mouth Neoplasms/mortality
• Neoplasm Grading
• Neoplasm Staging
• Nomograms
• SEER Program
• Survival Analysis
• Young Adult

The widely validated Memorial Sloan Kettering Cancer Center (MSKCC) nomogram for gastric carcinoma (GC) was developed based on patients who received R0 resection only. The purpose of the current study was to assess the performance of this nomogram in Chinese patients who received postoperative chemoradiotherapy (CRT) after an R0 resection for GC. From 2006 to 2015, the clinical data of 150 eligible patients were retrospectively collected from the Fudan University Shanghai Cancer Center (FUSCC) and used for external validation. The nomogram was validated by means of the concordance index (CI) and a calibration plot. The CI for the nomogram was 0.657, which was lower than the CI of the nomogram for patients who received surgery alone (0.80). In the calibration plot, the gap between the observed and the predicted survival gradually increased as the predicted 5-year disease-specific survival (DSS) decreased. Thus the MSKCC nomogram for GC significantly underestimated the survival of patients in the FUSCC cohort, especially the survival of patients whose predicted 5-year DSS was less than 50%. The current study indicates the potential for the nomogram to be developed as an ideal tool to identify target patients for postoperative CRT.

• gastric carcinoma
• nomogram
• patient selection
• postoperative chemoradiation
• prognosis

Clinical prediction models are increasingly used to predict outcomes such as survival in cancer patients. The aim of this study was threefold. First, to perform a systematic review to identify available clinical prediction models for patients with esophageal and/or gastric cancer. Second, to evaluate sources of bias in the included studies. Third, to investigate the predictive performance of the prediction models using meta-analysis.

MEDLINE, EMBASE, PsycINFO, CINAHL, and The Cochrane Library were searched for publications from the year 2000 onwards. Studies describing models predicting survival, adverse events and/or health-related quality of life (HRQoL) for esophageal or gastric cancer patients were included. Potential sources of bias were assessed and a meta-analysis, pooled per prediction model, was performed on the discriminative abilities (c-indices).

A total of 61 studies were included (45 development and 16 validation studies), describing 47 prediction models. Most models predicted survival after a curative resection. Nearly 75% of the studies exhibited bias in at least 3 areas and model calibration was rarely reported. The meta-analysis showed that the averaged c-index of the models is fair (0.75) and ranges from 0.65 to 0.85.

Most available prediction models only focus on survival after a curative resection, which is only relevant to a limited patient population. Few models predicted adverse events after resection, and none focused on patient’s HRQoL, despite its relevance. Generally, the quality of reporting is poor and external model validation is limited. We conclude that there is a need for prediction models that better meet patients’ information needs, and provide information on both the benefits and harms of the various treatment options in terms of survival, adverse events and HRQoL.

• Esophageal Neoplasms/pathology
• Esophageal Neoplasms/physiopathology
• Humans
• Models, Theoretical
• Quality of Life
• Stomach Neoplasms/pathology
• Stomach Neoplasms/physiopathology
• Survival Analysis

• KWF Kankerbestrijding

• cancer-specific survival
• head and neck squamous cell carcinoma
• nomogram
• overall survival
• prognosis

• SEER
• cancer-specific survival
• nomogram
• pancreatic cancer
• prognosis

• Surveillance, Epidemiology, and End Results (SEER).
• adjuvant radiotherapy
• gastric cancer
• nomogram
• survival

• R01 AA020103 NIAAA NIH HHS

• Head and neck
• nomogram
• overall survival
• tongue cancer-specific survival
• tongue squamous cell carcinoma

• Adult
• Aged
• Carcinoma, Squamous Cell/mortality
• Carcinoma, Squamous Cell/pathology
• Carcinoma, Squamous Cell/surgery
• Disease-Free Survival
• Female
• Humans
• Male
• Middle Aged
• Neoplasm Grading
• Neoplasm Staging
• Nomograms
• Prognosis
• SEER Program
• Tongue Neoplasms/mortality
• Tongue Neoplasms/pathology
• Tongue Neoplasms/surgery
• Young Adult