Dataset Information

Dynamic prediction of overall survival: a retrospective analysis on 979 patients with Ewing sarcoma from the German registry.

ABSTRACT: OBJECTIVES:This study aimed at developing a dynamic prediction model for patients with Ewing sarcoma (ES) to provide predictions at different follow-up times. During follow-up, disease-related information becomes available, which has an impact on a patient's prognosis. Many prediction models include predictors available at baseline and do not consider the evolution of disease over time. SETTING:In the analysis, 979 patients with ES from the Gesellschaft für Pädiatrische Onkologie und Hämatologie registry, who underwent surgery and treatment between 1999 and 2009, were included. DESIGN:A dynamic prediction model was developed to predict updated 5-year survival probabilities from different prediction time points during follow-up. Time-dependent variables, such as local recurrence (LR) and distant metastasis (DM), as well as covariates measured at baseline, were included in the model. The time effects of covariates were investigated by using interaction terms between each variable and time. RESULTS:Developing LR, DM in the lungs (DMp) or extrapulmonary DM (DMo) has a strong effect on the probability of surviving an additional 5 years with HRs and 95% CIs equal to 20.881 (14.365 to 30.353), 6.759 (4.465 to 10.230) and 17.532 (13.210 to 23.268), respectively. The effects of primary tumour location, postoperative radiotherapy (PORT), histological response and disease extent at diagnosis on survival were found to change over time. The HR of PORT versus no PORT at the time of surgery is equal to 0.774 (0.594 to 1.008). One year after surgery, the HR is equal to 1.091 (0.851 to 1.397). CONCLUSIONS:The time-varying effects of several baseline variables, as well as the strong impact of time-dependent variables, show the importance of including updated information collected during follow-up in the prediction model to provide accurate predictions of survival.

SUBMITTER: Liu C

PROVIDER: S-EPMC7552850 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Dynamic prediction of overall survival: a retrospective analysis on 979 patients with Ewing sarcoma from the German registry.

Liu Chuchu C Rueten-Budde Anja J AJ Ranft Andreas A Dirksen Uta U Gelderblom Hans H Fiocco Marta M

BMJ open 20201012 10

<h4>Objectives</h4>This study aimed at developing a dynamic prediction model for patients with Ewing sarcoma (ES) to provide predictions at different follow-up times. During follow-up, disease-related information becomes available, which has an impact on a patient's prognosis. Many prediction models include predictors available at baseline and do not consider the evolution of disease over time.<h4>Setting</h4>In the analysis, 979 patients with ES from the Gesellschaft für Pädiatrische Onkologie ...[more]

PMID: 33046463

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Project description:AimLung metastases are a negative prognostic factor in Ewing sarcoma, however, the incidence and significance of sub-centimetre pulmonary nodules at diagnosis is unclear. The aims of this study were to (1): determine the incidence of indeterminate pulmonary nodules (IPNs) in patients diagnosed with Ewing sarcoma (2); establish the impact of IPNs on overall and metastasis-free survival and (3) identify patient, oncological and radiological factors that correlate with poorer prognosis in patients that present with IPNs on their staging chest CT.Materials & methodsBetween 2008 and 2016, 173 patients with a first presentation of Ewing sarcoma of bone were retrospectively identified from an institutional database. Staging and follow-up chest CTs for all patients with IPN were reviewed by a senior radiologist. Clinical and radiologic course were examined to determine overall- and metastasis-free survival for IPN patients and to identify demographic, oncological or nodule-specific features that predict which IPN represent true lung metastases.ResultsFollowing radiologic re-review, IPN were found in 8.7% of patients. Overall survival for IPN patients was comparable to those with a normal staging chest CT (2-year overall survival of 73.3% [95% CI 43.6-89] and 89.4% [95% CI 81.6-94], respectively; p = 0.34) and was significantly better than for patients with clear metastases (46.0% [95% CI 31.9-59]; p < 0.0001). Similarly, there was no difference in metastasis-free survival between 'No Metastases' and 'IPN' patients (p = 0.16). Lung metastases developed in 40% of IPN patients at a median 9.6 months. Reduction of nodule size on neoadjuvant chemotherapy was associated with worse overall survival in IPN patients (p = 0.0084).ConclusionIPN are not uncommon in patients diagnosed with Ewing sarcoma. In this study, we were unable to detect a difference in overall- or metastasis-free survival between patients with IPN at diagnosis and patients with normal staging chest CTs.

Project description:BackgroundPrimary retroperitoneal sarcoma (RPS) comprises over 70 histologic subtypes, yet there are limited studies that have developed prognostic nomograms for RPS patients to predict overall survival (OS) and cancer-specific survival (CSS). The objective of this study was to construct prognostic nomograms for predicting OS and CSS in RPS patients.MethodsWe identified a total of 1166 RPS patients from the Surveillance, Epidemiology and End Results (SEER) database, and an additional 261 cases were collected from a tertiary cancer center. The study incorporated various clinicopathological and epidemiologic features as variables, and prediction windows for overall survival (OS) and cancer-specific survival (CSS) were set at 3, 5, and 7 years. Multivariable Cox models were utilized to develop the nomograms, and variable selection was performed using a backward procedure based on the Akaike Information Criterion. To evaluate the performance of the nomograms in terms of calibration and discrimination, we used calibration plots, coherence index, and area under the curve.FindingsThe study included 818 patients in the development cohort, 348 patients in the internal validation cohort, and 261 patients in the external validation cohort. The backward procedure selected the following variables: age, French Federation of Cancer Centers Sarcoma Group (FNCLCC) grade, pre-/postoperative chemotherapy, tumor size, primary site surgery, and tumor multifocality. The validation results demonstrated that the nomograms had good calibration and discrimination, with C-indices of 0.76 for OS and 0.81 for CSS. Calibration plots also showed good consistency between the predicted and actual survival rates. Furthermore, the areas under the time-dependent receiver operating characteristic curves for the 3-, 5-, and 7-year OS (0.84, 0.82, and 0.78, respectively) and CSS (0.88, 0.88, and 0.85, respectively) confirmed the accuracy of the nomograms.InterpretationOur study developed accurate nomograms to predict OS and CSS in patients with RPS. These nomograms have important clinical implications and can assist healthcare providers in making informed decisions regarding patient care and treatment options. They may also aid in patient counseling and stratification in clinical trials.

Project description:The therapeutic strategy of Ewing sarcoma (EWS) remains largely unchanged over the past few decades. Hypoxia is reported to have an impact on tumor cell progression and is regarded as a novel potential therapeutic target in tumor treatment. This study aimed at developing a prognostic gene signature based on hypoxia-related genes (HRGs). EWS patients from GSE17674 in the GEO database were analyzed as a training cohort, and differently expressed HRGs between tumor and normal samples were identified. The univariate Cox regression, Least Absolute Shrinkage and Selection Operator (LASSO) and multivariate Cox regression analyses were used in this study. A total of 57 EWS patients from the International Cancer Genome Consortium (ICGC) database were set as the validation cohort. A total of 506 differently expressed HRGs between tumor and normal tissues were identified, among which 52 were associated with the prognoses of EWS patients. Based on 52 HRGs, EWS patients were divided into two molecular subgroups with different survival statuses. In addition, a prognostic signature based on 4 HRGs (WSB1, RXYLT1, GLCE and RORA) was constructed, dividing EWS patients into low- and high-risk groups. The 2-, 3- and 5-years area under the receiver operator characteristic curve of this signature was 0.913, 0.97 and 0.985, respectively. It was found that the survival rates of patients in the high-risk group were significantly lower than those in the low-risk group (p < 0.001). The risk level based on the risk score could serve as an independent clinical factor for predicting the survival probabilities of EWS patients. Additionally, antigen-presenting cell (APC) related pathways and T cell co-inhibition were differently activated in two risk groups, which may result in different prognoses. CTLA4 may be an effective immune checkpoint inhibitor to treat EWS patients. All results were verified in the validation cohort. This study constructed 4-HRGs as a novel prognostic marker for predicting survival in EWS patients.

Dataset Information

Dynamic prediction of overall survival: a retrospective analysis on 979 patients with Ewing sarcoma from the German registry.

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Dynamic prediction of overall survival: a retrospective analysis on 979 patients with Ewing sarcoma from the German registry.

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