Dataset Information

Establishment of prognostic nomogram for elderly colorectal cancer patients: a SEER database analysis.

ABSTRACT: BACKGROUND:This study aimed to establish nomogram models of overall survival (OS) and cancer-specific survival (CSS) in elderly colorectal cancer (ECRC) patients (Age???70). METHODS:The clinical variables of patients confirmed as ECRC between 2004 and 2016 were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate analysis were performed, followed by the construction of nomograms in OS and CSS. RESULTS:A total of 44,761 cases were finally included in this study. Both C-index and calibration plots indicated noticeable performance of newly established nomograms. Moreover, nomograms also showed higher outcomes of decision curve analysis (DCA) and the area under the curve (AUC) compared to American Joint Committee on Cancer (AJCC) tumor-node-metastasis (TNM) stage and SEER stage. CONCLUSIONS:This study established nomograms of elderly colorectal cancer patients with distinct clinical values compared to AJCC TNM and SEER stages regarding both OS and CSS.

SUBMITTER: Yu C

PROVIDER: S-EPMC7576842 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Establishment of prognostic nomogram for elderly colorectal cancer patients: a SEER database analysis.

Yu Chaoran C Zhang Yujie Y

BMC gastroenterology 20201020 1

<h4>Background</h4>This study aimed to establish nomogram models of overall survival (OS) and cancer-specific survival (CSS) in elderly colorectal cancer (ECRC) patients (Age ≥ 70).<h4>Methods</h4>The clinical variables of patients confirmed as ECRC between 2004 and 2016 were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate analysis were performed, followed by the construction of nomograms in OS and CSS.<h4>Results</h4>A total of 44,761 ...[more]

PMID: 33081695

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Project description:Purpose The 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. Methods Patients 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. Results Overall, 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. Conclusion An easy-to-use, highly accurate nomogram was developed for predicting the prognosis of EC patients with lung metastasis.

Project description:BackgroundThe number of elderly patients diagnosed with breast cancer is increasing worldwide. However, treatment decisions for these patients are highly variable. Although researchers have identified the effects of surgery, radiotherapy, endocrine therapy, and chemotherapy in elderly patients with breast cancer, clinicians still struggle to make appropriate decisions for these patients.MethodsWe identified 75,525 female breast cancer patients aged ≥ 70 years in the Surveillance, Epidemiology, and End Results (SEER) database treated between January 1, 2010, and December 31, 2016. The patients were further divided into training and testing cohorts. The cumulative occurrence of breast cancer-specific deaths (BCSDs) and other cause-specific deaths (OCSD) was calculated using the cumulative incidence function. In the univariate analysis, risk factors were screened using the Fine-Gray model. In the multivariate analysis for competing risks, the sub-distribution hazard ratio with a 95% confidence interval for each independent predictor associated with BCSD was calculated for the construction of nomograms. Based on the above analyses, a competing risk nomogram was constructed to predict the probability of BCSD in the 1st, 3rd, and 5th years after treatment. During validation, the concordance index (C-index) was selected to quantify the predictive ability of the competing risk model.ResultsA total of 33,118 patients were included in this study, with 24,838 in the training group and 8,280 in the testing group. Age, race, marital status, cancer grade, tumor stage, node stage, estrogen receptor status, progesterone receptor status, human epidermal growth factor receptor--2 status, and treatment including surgery, radiation, and chemotherapy were used to establish a nomogram. The C-index of 0.852 (0.842-0.862) in the training cohort and 0.876 (0.868-0.892) in the testing cohort indicated satisfactory discriminative ability of the nomogram. Calibration plots showed favorable consistency between the nomogram predictions and actual observations in both the training and validation cohorts.ConclusionsOur study identified independent predictors of BCSD in elderly patients with breast cancer. A prognostic nomogram was developed and validated to aid clinical decision-making.

Project description:BackgroundSynchronous multiple primary colorectal cancer (SMPCC) involves the simultaneous occurrence of 2 or more independent primary malignant tumors in the colon or rectum. Although SMPCC is rare, it results in a higher incidence of postoperative complications and mortality compared to patients with single primary colorectal cancer (SPCRC).MethodsThe clinical factors and survival outcomes of SMPCC patients registered on the Surveillance, Epidemiology, and End Results (SEER) database between 2000 and 2017 were extracted. The patients were divided into the training and validation cohorts using a ratio of 7:3. Univariate and multivariate logistic regression analyses were used to identify the independent risk factors for early death. The performance of the nomogram was evaluated using the concordance index (C-index), calibration curves, and the area under the curve (AUC) of a receiver operating characteristics curve (ROC). A decision curve analysis (DCA) was used to evaluate the clinical utility of the nomogram and standard TNM system.ResultsA total of 4386 SMPCC patients were enrolled in the study and randomly assigned to the training (n = 3070) and validation (n = 1316) cohorts. The multivariate logistic analysis identified age, chemotherapy, radiotherapy, T stage, N stage, and M stage as independent risk factors for all-cause and cancer-specific early death. The marital status was associated with all-cause early death, and the tumor grade was associated with cancer-specific early death. In the training cohort, the nomogram achieved a C-index of 0.808 (95% CI, 0.784-0.832) and 0.843 (95% CI, 0.816-0.870) for all-cause and cancer-specific early death, respectively. Following validation, the C-index was 0.797 (95% CI, 0.758-0.837) for all-cause early death and 0.832 (95% CI, 0.789-0.875) for cancer-specific early death. The ROC and calibration curves indicated that the model had good stability and reliability. The DCA showed that the nomogram had a better clinical net value than the TNM staging system.ConclusionOur nomogram can provide a simple and accurate tool for clinicians to predict the risk of early death in SMPCC patients undergoing surgery and could be used to optimize the treatment according to the patient's needs.

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Establishment of prognostic nomogram for elderly colorectal cancer patients: a SEER database analysis.

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Establishment of prognostic nomogram for elderly colorectal cancer patients: a SEER database analysis.

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