Construction and validation of a nomogram for predicting the prognosis of breast cancer patients who received adjuvant therapy: an analysis based on the SEER database
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ABSTRACT:
SUBMITTER: Jiang Q
PROVIDER: S-EPMC11247573 | biostudies-literature | 2024 Jun
REPOSITORIES: biostudies-literature
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Project description: Not available
| S-EPMC10635422 | biostudies-literature
Project description:BackgroundOsteosarcoma is one of the most common malignant bone tumors, with a high incidence in adolescence. The objective of this study was to construct prognostic nomograms for predicting the prognosis of juvenile osteosarcoma.MethodsPatients with osteosarcoma diagnosed between 2004 and 2015 were identified in the Surveillance, Epidemiology, and End Results (SEER) database. The essential clinical predictors were identified with univariate and multivariate Cox analysis. Nomograms were constructed to predict the 3- and 5-year cancer- specific survival (CSS) and overall survival (OS). Concordance index (C-index) and calibration plots were performed to validate the predictive performance of nomograms.ResultsWe enrolled 736 adolescents with osteosarcoma from the SEER database, with 516 samples grouped into a training cohort and 220 samples grouped into a validation cohort. In multivariate analysis of the training cohort, predictors including tumor size, surgery treatment and AJCC stage were found to be associated with OS and CSS, while age was only associated with CSS. Construction of nomograms based on these predictors was performed to evaluate the prognosis of adolescents with osteosarcoma. The C-index and calibration curves also showed the satisfactory performance of these nomograms for prognosis prediction.ConclusionThe developed nomograms are useful tools for precisely predicting the prognosis of adolescents with osteosarcoma, which could enable patients to be more accurately managed in clinical practice.
| S-EPMC7570778 | biostudies-literature
Project description:ObjectivesThe prognosis of invasive micropapillary carcinoma (IMPC) of the breast is determined by many clinicopathological factors. This study aims to identify prognostic factors and develop reliable nomogram to predict the overall survival (OS) in patients with IMPC.DesignLog-rank test and Cox proportional hazards analysis were used to identify variables and construct a nomogram based on the training cohort. C-index and calibration curves were performed to evaluate the performance of the model in the training cohort and validation cohorts.SettingWe collected the patient data from the Surveillance, Epidemiology and End Results (SEER) database. This database holds data related to the cancer incidence from 18 population-based cancer registries in the USA.ParticipantsThe SEER database was used to screen 754 eligible patients as the study cohort. The whole cohort was randomly divided into a training cohort (n=377) and a validation cohort (n=377).ResultsAge at diagnosis, hormone receptors, number of positive regional lymph nodes and clinical stage were independent prognostic factors for patients with IMPC. The calibration curves presented excellent consistency between the actual and nomogram-predict survival probabilities in the training and validation cohorts. The C-index values of the nomogram were 0.794 and 0.774 for OS in the training and validation cohorts, respectively.ConclusionsThe novel nomogram provides new insights of the risk of each prognostic factor and can assist doctors in predicting the 1-year, 3-year and 5-year OS in patients with IMPC.
| S-EPMC10407354 | biostudies-literature
Project description: Not available
| S-EPMC7214910 | biostudies-literature
Project description:As primary duodenal adenocarcinoma is rare, the prognostic factors of this disease remain insufficiently explored, especially in China. We identified postoperative duodenal adenocarcinoma patients at a Chinese double-center (from 2006 to 2016) or who were registered with the Surveillance, Epidemiology, and End Results (SEER) database (from 2004 to 2014). Clinicopathological features and significant prognostic factors for cancer-specific survival (CSS) were reviewed and analyzed by using univariate and multivariate Cox proportional hazards regression. Then, a nomogram predicting CSS was constructed based on the SEER database and validated externally by using the separate Chinese cohort. Totally, 137 patients from the Chinese double-center and 698 patients from the SEER database were included for analysis. The multivariate analyses showed that age, tumor grade and TNM stage were independent prognostic factors. The nomogram constructed using these factors showed a clear prognostic superiority to the AJCC-TNM classification, 7th ed. (C-index: SEER cohort, 0.693 vs 0.625, P < 0.001; Chinese cohort, 0.677 vs 0.659, P < 0.001, respectively). In summary, the valuable prognostic factors in patients with duodenal adenocarcinoma were age, tumor grade and TNM stage. This study developed a nomogram that can precisely predict the CSS for postoperative duodenal adenocarcinoma patients.
| S-EPMC5962558 | biostudies-literature
Project description:IntroductionCancer in patients of childbearing age continues to become increasingly common. The purpose of this study was to explore the impact of metastatic breast cancer (MBC) on overall survival (OS) and cancer-specifific survival (CSS) in patients of childbearing age and to construct prognostic nomograms to predict OS and CSS.MethodsData from MBC patients of childbearing age were obtained from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015, and the patients were randomly assigned into the training and validation cohorts. Univariate and multivariate Cox analyses were used to search for independent prognostic factors impacting OS and CSS, and these data were used to construct nomograms. The concordance index (C-index), area under the curve (AUC), and calibration curves were used to determine the predictive accuracy and discriminative ability of the nomograms. Additional data were obtained from patients at the Yunnan Cancer Hospital to further verify the accuracy of the nomograms.ResultsA total of 1,700 MBC patients of childbearing age were identifified from the SEER database, and an additional 92 eligible patients were enrolled at the Yunnan Cancer Hospital. Multivariate Cox analyses identifified 10 prognostic factors for OS and CSS that were used to construct the nomograms. The calibration curve for the probabilities of OS and CSS showed good agreement between nomogram prediction and clinical observations. The C-index of the nomogram for OS was 0.735 (95% CI = 0.725-0.744); the AUC at 3 years was 0.806 and 0.794 at 5 years.The nomogram predicted that the C-index of the CSS was 0.740 (95% CI = 0.730- 0.750); the AUC at 3 years was 0.811 and 0.789 at 5 years. The same results were observed in the validation cohort. Kaplan- Meier curves comparing the low-,medium-, and high-risk groups showed strong prediction results for the prognostic nomogram.ConclusionWe identifified several independent prognostic factors and constructed nomograms to predict the OS and CSS for MBC patients of childbearing age.These prognostic models should be considered in clinical practice to individualize treatments for this group of patients.
| S-EPMC9732809 | biostudies-literature
Project description:Most cases of endometrial adenocarcinoma (EAC) are diagnosed early and have a good prognosis; however, grade 3 (G3) EACs have poor outcomes. We retrospectively analyzed the data of 11,519 patients with G3 EACs registered between 2004 and 2015 in the Surveillance, Epidemiology, and End Results Program database and constructed a nomogram to guide clinicians in decision-making and accurate prediction of the prognosis. The caret package was used to divide samples into a training set and a validation set. Univariate and multivariate Cox regression analyses were performed, and a nomogram was constructed. A calibration curve was plotted, and a decision curve analysis was performed to verify the accuracy and clinical utility in both cohorts. The Cox regression analysis revealed that age, race, tumor size, number of lymph nodes resected, International Federation of Gynecology and Obstetrics stage, tumor/node stage, and adjuvant therapy were the prognostic factors for G3 EAC, and these were included in the nomogram. The area under the curve values of the training cohort for 1-, 3-, and 5-year were 0.832, 0.798, and 0.784, respectively for the overall survival (OS) group, and 0.858, 0.812, and 0.799, respectively for the cancer specific survival (CSS) group. A nomogram was constructed to predict the survival rate of patients with G3 EACs more accurately. The predictive nomogram will help clinicians manage patients with G3 EACs more effectively in terms of clinical prognosis.
| S-EPMC8806337 | biostudies-literature
Project description:AimTo establish and validate a nomogram for predicting prognosis of breast cancer patients with pN0-1 who were treated with mastectomy and without adjuvant radiotherapy.Material and methodsThe LASSO regression was performed to identify predictors of breast cancer-specific survival (BCSS), local regional recurrence (LRR) and distant metastasis (DM). Model performance was evaluated by the concordance index (C-index) and calibration plot.ResultsThe 5-year BCSS, LRR and DM rates for the entire cohort were 98%, 2% and 4%, respectively. LASSO regression analysis found that pathological T stage, number of positive LN, grade and Ki-67 were significant predictors for both BCSS and DM-free survival, while number of resected LN and PR status were predictors for DM-free survival. In addition, number of positive LN was the only significant predictor for developing LRR. The C-indexes for the 5-year BCSS and DM nomograms were 0.81 and 0.78 in the training data set, 0.65 and 0.70 in the testing set and 0.72 and 0.69 in the external validation set, respectively.ConclusionOur prognostic nomograms accurately predict 5-year BCSS and DM-free survival in post-mastectomy breast cancer without adjuvant radiotherapy, which provides a useful tool to identify high-risk patients who could benefit from additional adjuvant therapy.
| S-EPMC8079251 | biostudies-literature
Project description:BackgroundThe prognostic factors for survival in patients with ependymoma (EPN) remain controversial. The aim of this study was to establish a prognostic model for 5- and 10-year survival probability nomograms for patients with EPN.MethodsClinical data from the Surveillance, Epidemiology, and End Results (SEER) database were used for patients diagnosed with ependymoma between 2000 and 2018 and were randomized 7:3 into a development set and a validation set. Factors significantly associated with prognosis were screened out using the least absolute shrinkage and selection operator (LASSO) regression. The calibration chart and consistency index (C-index) are used to evaluate the discrimination and consistency of the prediction model. Decision curve analysis (DCA) was used to further evaluate the established model. Finally, prognostic factors selected by LASSO regression were evaluated using Kaplan-Meier (KM) survival curves.ResultsA total of 3820 patients were included in the prognostic model. Seven survival predictors were obtained by LASSO regression screening, including age, gender, morphology, location, size, laterality, and resection. The prognostic model of the nomogram showed moderate discriminative ability in the development group and the validation group, with a C-index of 0.642 and 0.615, respectively. In the development set and validation set survival curves, the prognosis index of high risk was less effective than low risk (p < 0.001).ConclusionsOur nomograms may play an important role in predicting 5 and 10-year outcomes for patients with ependymoma. This will help assist clinicians in personalized medicine.
| S-EPMC8419756 | biostudies-literature
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