Construction and validation of a nomogram of risk factors and cancer-specific survival prognosis for combined lymphatic metastases in patients with early-onset colorectal cancer.
International journal of colorectal disease
PURPOSE:This study aimed to investigate the risk and prognostic factors of lymph node metastasis (LNM) in early-onset colorectal cancer (EO-CRC) and to develop nomograms for quantitatively predicting LNM and the cancer-specific survival (CSS). METHODS:A total of 22,405 EO-CRC patients were included in this study using the SEER database from 2010 to 2017. Logistic and Cox regression were used to identify risk and the potential prognostic factors, respectively, for EO-CRC with LNM. Subsequently, nomograms regarding the risk of LNM in EO-CRC patients and its corresponding CSS were constructed based on these factors. The discriminative ability, calibration and clinical usefulness of the nomograms were assessed by the area under the receiver operating characteristic (ROC) curves (AUC), calibration curves, and decision curve analysis (DCA). RESULTS:T-stage and pathological grade were the most represented factors in the predicted LNM nomogram, while histological type and combined distant metastases were the most represented in the nomogram for CSS in EO-CRC patients with LNM (all P < 0.05). The nomogram constructed based on the prognostic factors screened by Cox regression had good performance with C-index of 0.807 and 0.802 for the training and validation cohorts, respectively. The calibration curve showed that the nomograms' predictions were in line with actual observations. Additionally, the ROC curves indicated good discrimination, and the DCA curves implied significant clinical utility of the nomograms. CONCLUSION:The nomograms we constructed have significant performance in predicting the incidence and prognosis of LNM in EO-CRC patients, which may help clinicians to make better treatment decision making.
10.1007/s00384-023-04432-7
Prediction models for overall and cancer-specific survival in patients with metastatic early-onset colorectal cancer: a population-based study.
International journal of colorectal disease
PURPOSE:Metastatic early-onset colorectal cancer (EO-CRC) is on the rise, yet there is a dearth of predictive models for this disease. Therefore, it is crucial to develop a nomogram to aid in the early detection and management of metastatic colorectal cancer in young patients. METHODS:We retrieved data from the SEER database on patients with metastatic colorectal cancer aged 50 or younger between 2010 and 2017. The data were randomly allocated in a 7:3 ratio to training and validation cohorts, and univariate and multivariate Cox regression analyses were used to identify independent prognostic factors for overall survival (OS) and cancer-specific survival (CSS) at 1, 3, and 5 years. The nomograms were developed based on these factors, and their discriminatory and calibration capabilities were validated. Using the nomogram risk scores, patients were stratified into low-risk and high-risk groups. RESULTS:The study included 2470 patients with metastatic EO-CRC. Univariate and multivariate Cox regression analysis identified 12 independent risk factors that were included in the nomogram. The training cohort had a consistency index (C-index) of 0.71, while the validation cohort had a C-index of 0.70, demonstrating good predictive accuracy. Calibration plots showed a high level of consistency between the observed and predicted values, with overlapping plots along the diagonal. The decision curve analysis (DCA) revealed that the nomogram had a high clinical application value. CONCLUSIONS:The novel nomograms were created to predict the prognosis of patients with metastatic EO-CRC, which can aid clinicians in developing more effective treatment strategies and contribute to more accurate prognostic assessments.
10.1007/s00384-023-04369-x
Sex differences in survival outcomes of early-onset colorectal cancer.
Scientific reports
Colorectal cancer (CRC) is one of the most fatal cancers in the United States. Although the overall incidence and mortality rates are declining, an alarming rise in early-onset colorectal cancer (EOCRC), defined as CRC diagnosis in patients aged < 50 years, was previously reported. Our study focuses on analyzing sex-specific differences in survival among EOCRC patients and comparing sex-specific predictors of survival in both males and females in the United States. We retrieved and utilized data from the Surveillance, Epidemiology, and End Results (SEER) program. EOCRC patients, between the ages of 20 and 49, were exclusively included. We conducted thorough survival analyses using Kaplan-Meier curves, log-rank tests, Cox regression models, and propensity score matching to control for potential biases. Our study included 58,667 EOCRC patients (27,662 females, 31,005 males) diagnosed between 2000 and 2017. The baseline characteristics at the time of diagnosis were significantly heterogeneous between males and females. Males exhibited significantly worse overall survival (OS), cancer-specific survival (CSS), and noncancer-specific survival (NCSS) in comparison to females in both the general cohort, and the matched cohort. Predictors of survival outcomes generally followed a similar pattern in both sexes except for minor differences. In conclusion, we identified sex as an independent prognostic factor of EOCRC, suggesting disparities in survival between sexes. Further understanding of the epidemiological and genetic bases of these differences could facilitate targeted, personalized therapeutic approaches for EOCRC.
10.1038/s41598-024-71999-8
Nomogram model for predicting cancer-specific mortality in patients with early-onset colorectal cancer: a competing risk analysis insight from the SEER database and an external validation cohort.
Translational cancer research
Background:Early-onset colorectal cancer (EOCRC) is increasing in incidence and poses a growing threat. Urgent research is needed, especially in survival analysis, to enhance comprehension and treatment strategies. This study aimed to explore the risk factors associated with cancer-specific mortality (CSM) and other-cause mortality (OCM) in patients with EOCRC. Additionally, the study aimed to develop a nomogram predicting CSM using a competitive risk model and validate its accuracy through the use of training, using internal and external cohorts. Methods:Data from EOCRC patients were collected from the Surveillance, Epidemiology, and End Results (SEER) database (2008-2017). EOCRC patients who were treated at a tertiary hospital in northeast China between 2014 and 2020 were also included in the study. The SEER data were divided into the training and validation sets at a 7:3 ratio. A univariate Cox regression model was employed to identify prognostic factors. Subsequently, multivariate Cox regression models were applied to ascertain the presence of independent risk factors. A nomogram was generated to visualize the results, which were evaluated using the concordance index (C-index), area under the curve (AUC), and calibration curves. The clinical utility was assessed via decision curve analysis (DCA). Results:Multivariable Cox regression analysis demonstrated that factors such as race, tumor differentiation, levels of carcinoembryonic antigen (CEA), marital status, histological type, American Joint Committee on Cancer (AJCC) stage, and surgical status were independent risk factors for CSM in EOCRC patients. In addition, age, gender, chemotherapy details, CEA levels, marital status, and AJCC stage were established as independent risk factors for OCM in individuals diagnosed with EOCRC. A nomogram was developed using the identified independent risk factors, demonstrating excellent performance with a C-index of 0.806, 0.801, and 0.810 for the training, internal validation, and external validation cohorts, respectively. The calibration curves and AUC further confirmed the accuracy and discriminative ability of the nomogram. Furthermore, the DCA results indicated that the model had good clinical value. Conclusions:In this study, a competing risk model for CSM was developed in EOCRC patients. The model demonstrates a high level of predictive accuracy, providing valuable insights into the treatment decision-making process.
10.21037/tcr-23-2023
Construction and validation of a nomogram for predicting overall survival of patients with stage III/IV early-onset colorectal cancer.
Frontiers in oncology
Purpose:This study aimed to identify prognostic factors and develop a nomogram for predicting overall survival (OS) in stage III/IV early-onset colorectal cancer (EO-CRC). Methods:Stage III/IV EO-CRC patients were identified from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015. The datasets were randomly divided (2:1) into training and validation sets. A nomogram predicting OS was developed based on the prognostic factors identified by Cox regression analysis in the training cohort. Moreover, the predictive performance of the nomogram was assessed using the receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). Subsequently, the internal validation was performed using the validation cohort. Finally, a risk stratification system was established based on the constructed nomogram. Results:Of the 10,387 patients diagnosed with stage III/IV EO-CRC between 2010 and 2015 in the SEER database, 8,130 patients were included. In the training cohort (n=3,071), sex, marital status, race/ethnicity, primary site, histologic subtypes, grade, T stage, and N stage were identified as independent prognostic variables for OS. The 1-, 3-, and 5-year area under the curve (AUC) values of the nomogram were robust in both the training (0.751, 0.739, and 0.723) and validation cohorts (0.748, 0.733, and 0.720). ROC, calibration plots, and DCA indicated good predictive performance of the nomogram in both the training and validation sets. Furthermore, patients were categorized into low-, middle-, and high-risk groups based on the nomogram risk score. Kaplan-Meier curve showed significant survival differences between the three groups. Conclusion:We developed a prognostic nomogram and risk stratification system for stage III/IV EO-CRC, which may facilitate clinical decision-making and individual prognosis prediction.
10.3389/fonc.2024.1332499
Survival Analysis of Metastatic Early-Onset Colorectal Cancer Compared to Metastatic Average-Onset Colorectal Cancer: A SEER Database Analysis.
Cancers
BACKGROUND:Early-onset colorectal cancer (EO-CRC) is defined as colorectal cancer diagnosed before the age of 50 years, and its incidence has been increasing over the last decade, now accounting for 10% of all new CRC diagnoses. Average-onset colorectal cancer (AO-CRC) has shown a steady decline in its incidence and related mortality over the past 20 years. The disparities in outcomes and overall survival (OS) between EO-CRC and AO-CRC are controversial. Our study compared OS and cause-specific survival (CSS) between metastatic EO-CRC (mEO-CRC) and metastatic AO-CRC (mAO-CRC) and identified the associated factors. METHODS:Data on patient characteristics, tumor characteristics, incidence, and mortality were obtained from the SEER database from 2010 to 2020. We identified 23,278 individuals aged > 18 years with a confirmed diagnosis of all histological subtypes of metastatic CRC (M1 on TNM stage) using ICD-O-3 site codes. mEO-CRC and mAO-CRC were compared. OS distributions and CCS were analyzed using the Kaplan-Meier method and log-rank test to assess differences. A Cox regression model was used to assess the associations between variables. RESULTS:mEO-CRC constituted 17.79% of the cases, whereas 82.21% had mAO-CRC. Most patients with mEO-CRC were 45-49 years old (47.66%), male (52.16%) and White (72.57%) and had adenocarcinoma histology (87.30%). Left colon tumors were most prevalent in both groups (40.26%) but were more prevalent in mEO-CRC patients than in mAO-CRC patients (49.63% vs. 38.23%, < 0.001). Patients with mEO-CRC had higher OS ( < 0.001) and CSS ( < 0.001) than those with mAO-CRC. Patients with mEO-CRC also had significantly better median overall survival (30 months vs. 18 months, < 0.001). The factors associated with worse OS included mAO-CRC ( < 0.001), mucinous adenocarcinoma ( < 0.001), male sex ( = 0.003), and a lack of surgical intervention ( < 0.001). CONCLUSIONS:Most patients with mEO-CRC fall within the range of 45 to 49 years of age. Patients with mEO-CRC were more likely to receive cancer-directed therapy (including chemotherapy and radiotherapy) and had better OS and CSS than those with mAO-CRC. This is likely attributable to the better performance status, fewer comorbidities, and better tolerance to cancer-directed therapy in mEO-CRC patients. The factors associated with worse OS and CSS were age > 50 years, mucinous adenocarcinoma, male sex, and no surgical treatment.
10.3390/cancers16112004
Nomogram predicting cancer-specific mortality in early-onset rectal cancer: a competing risk analysis.
Wang Yufeng,Wu Jiayuan,He Hairong,Ma Huan,Hu Liren,Wen Jiyu,Lyu Jun
International journal of colorectal disease
BACKGROUND:The incidence of rectal cancer has meaningfully increased in young patients. However, quantitative evaluation for the competing data of early-onset rectal cancer is lacking. So, we performed a competing risk analysis to calculate the cumulative incidence of death for patients with early-onset rectal cancer and developed a nomogram to predict the probability of cancer-specific mortality for these patients. METHODS:We abstracted data of patients with early-onset rectal cancer between 2004 and 2016 by using the Surveillance, Epidemiology, and End Results program database. The cumulative incidence function was used to calculate the crude cancer-specific mortality of early-onset rectal cancer. Fine and Gray's proportional sub-distribution hazard model was adopted to explore the risk factors of cancer-specific death. Then, we establish a nomogram to predict their 3-, 5-, and 10-year probabilities. RESULTS:We identified 9917 patients with early-onset rectal cancer, and they were randomly divided into training (n = 6941) and validation (n = 2976) cohorts. In the training cohort, the 3-, 5-, and 10-year cumulative incidences of cancer-specific death after diagnosis for early-onset rectal cancer were 11.4%, 19.9%, and 28.8%, respectively. Fine and Gray's model showed that sex, race, marital status, histology, T stage, N stage, M stage, examined lymph nodes, and pretreatment carcinoembryonic antigen were independently associated with cancer-specific mortality. Such factors were selected to develop a prognostic nomogram. CONCLUSION:The competing risk nomogram has an ideal performance for predictive cancer-specific mortality in early-onset rectal cancer.
10.1007/s00384-020-03527-9
Early-onset locally advanced rectal cancer characteristics, a practical nomogram and risk stratification system: a population-based study.
Frontiers in oncology
Background:The purpose of this study is to construct a novel and practical nomogram and risk stratification system to accurately predict cancer-specific survival (CSS) of early-onset locally advanced rectal cancer (EO-LARC) patients. Methods:A total of 2440 patients diagnosed with EO-LARC between 2010 and 2019 were screened from the Surveillance, Epidemiology, and End Results (SEER) database. The pool of potentially eligible patients was randomly divided into two groups: a training cohort (N=1708) and a validation cohort (N=732). The nomogram was developed and calibrated using various methods, including the coherence index (C-index), receiver operating characteristic curve (ROC), calibration curves, and decision curves (DCA). A new risk classification system was established based on the nomogram. To compare the performance of this nomogram to that of the American Joint Committee on Cancer (AJCC) staging system, DCA, net reclassification index (NRI), and integrated discrimination improvement (IDI) were employed. Result:Seven variables were included in the model. The area under the ROC curve (AUC) for the training cohort was 0.766, 0.736, and 0.731 at 3, 6, and 9 years, respectively. Calibration plots displayed good consistency between actual observations and the nomogram's predictions. The DCA curve further demonstrated the validity of the nomination form in clinical practice. Based on the scores of the nomogram, all patients were divided into a low-risk group, a middle-risk group, and a high-risk group. NRI for the 3-, 6-, and 9-year CSS(training cohort: 0.48, 0.45, 0.52; validation cohort: 0.42, 0.37, 0.37), IDI for the 3-, 6-, and 9-year CSS (training cohort: 0.09, 0.10, 0.11; validation cohort: 0.07, 0.08, 0.08). The Kaplan-Meier curve revealed that the new risk classification system possesses a more extraordinary ability to identify patients in different risk groups than the AJCC staging. Conclusion:A practical prognostic nomogram and novel risk classification system have been developed to efficiently predict the prognosis of EO-LARC. These tools can serve as a guide to individualize patient treatment and improve clinical decision-making.
10.3389/fonc.2023.1190327