Survival analysis of 3 different age groups and prognostic factors among 402 patients with skeletal high-grade osteosarcoma: real world data from a single tertiary sarcoma center

Simple SummaryAge is one of many prognostic factors for overall survival in patients with skeletal osteosarcoma. This retrospective study provides an overview of survival in patients with high-grade osteosarcoma in different age groups. It shows prognostic variables for survival and local control among the overall cohort. In this study, in which 402 patients with skeletal high-grade osteosarcoma were included, poor survival was associated with increasing age. Age groups, tumor size, poor histopathological response, distant metastasis at presentation, and local recurrence were independent prognostic factors associated to overall survival and event-free survival. Differences in outcome among different age groups can be partially explained by patient characteristics and treatment characteristics.Age is a known prognostic factor for many sarcoma subtypes, however in the literature there are limited data on the different risk profiles of different age groups for osteosarcoma survival. This study aims to provide an overview of survival in patients with high-grade osteosarcoma in different age groups and prognostic variables for survival and local control among the entire cohort. In this single center retrospective cohort study, 402 patients with skeletal high-grade osteosarcoma were diagnosed and treated with curative intent between 1978 and 2017 at the Leiden University Medical Center (LUMC). Prognostic factors for survival were analyzed using a Cox proportional hazard model. In this study poor overall survival (OS) and event-free survival (EFS) were associated with increasing age. Age groups, tumor size, poor histopathological response, distant metastasis (DM) at presentation and local recurrence (LR) were important independent prognostic factors influencing OS and EFS. Differences in outcome among different age groups can be partially explained by patient and treatment characteristics.Experimentele farmacotherapi

Age-related differences of oncological outcomes in primary extremity soft tissue sarcoma: a multistate model including 6260 patients

Abstract Purpose: No studies extensively compared the young adults (YA, 18e39 years), middle-aged (40e69 year

Investigating hospital heterogeneity with a competing risks frailty model

Development and application of statistical models for medical scientific researc

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

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 fur Padiatrische Onkologie und Hamatologie 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.Development and application of statistical models for medical scientific researc

Dynamic prediction of overall survival for patients with high-grade extremity soft tissue sarcoma

Development and application of statistical models for medical scientific researc

Incidence, outcomes and prognostic factors during 25 years of treatment of chondrosarcomas.

Contains fulltext : 200183.pdf (publisher's version ) (Open Access)BACKGROUND: There are few studies detailing the incidence, patient outcomes and prognostic factors for chondrosarcomas (CS). Those that do exist have small sample sizes and/or use older datasets. The purpose of this study was to determine the incidence, overall survival (OS) and prognostic factors for OS of CS patients, as well as investigate the efficacy of curettage. METHODS: We analyzed data of 2186 patients diagnosed with chondrosarcomas between '89-'13 from the Netherlands Cancer Registry. The effect of risk factors on OS was assessed with a multivariate Cox regression. Median Follow-up was determined with reversed Kaplan-Meier. OS was estimated using Kaplan-Meier method. RESULTS: The relative incidence of CS was 2.88 per million citizens between '89-'96, 4.15 between '96-'04 and 8.78 between '05-'13. Most of the increase in incidence came from atypical cartilaginous tumours/grade I chondrosarcoma (ACT/CS I). The 3-, 5- and 10-years survival were, respectively, 96%, 93% and 88% for ACT/CS I, 82%, 74% and 62% for grade II CS and 38%, 31% and 26% for grade III CS. Prognostics factors significantly associated with OS were age, histological grade, year of diagnosis, tumour location and size. CONCLUSION: The incidence of CS, and especially ACT/CS I, has increased over time, which could be driven by both an ageing population and increased diagnostic imaging. With the increased number of diagnosed ACT/CS I, the number of preventative curettages of this tumour has also increased. Despite the supposed preventative character of this treatment, the incidence of high-grade CS did not decrease.1 september 201

External validation and adaptation of a dynamic prediction model for patients with high-grade extremity soft tissue sarcoma

Background and Objectives A dynamic prediction model for patients with soft tissue sarcoma of the extremities was previously developed to predict updated overall survival probabilities throughout patient follow-up. This study updates and externally validates the dynamic model.Methods Data from 3826 patients with high-grade extremity soft tissue sarcoma, treated surgically with curative intent were used to update the dynamic PERsonalised SARcoma Care (PERSARC) model. Patients were added to the model development cohort and grade was included in the model. External validation was performed with data from 1111 patients treated at a single tertiary center.Results Calibration plots show good model calibration. Dynamic C-indices suggest that the model can discriminate between high- and low-risk patients. The dynamic C-indices at 0, 1, 2, 3, 4, and 5 years after surgery were equal to 0.697, 0.790, 0.822, 0.818, 0.812, and 0.827, respectively.Conclusion Results from the external validation show that the dynamic PERSARC model is reliable in predicting the probability of surviving an additional 5 years from a specific prediction time point during follow-up. The model combines patient-, treatment-specific and time-dependent variables such as local recurrence and distant metastasis to provide accurate survival predictions throughout follow-up and is available through the PERSARC app.Development and application of statistical models for medical scientific researc

External validation and adaptation of a dynamic prediction model for patients with high-grade extremity soft tissue sarcoma

Background and Objectives: A dynamic prediction model for patients with soft tissue sarcoma of the extremities was previously developed to predict updated overall survival probabilities throughout patient follow-up. This study updates and externally validates the dynamic model. Methods: Data from 3826 patients with high-grade extremity soft tissue sarcoma, treated surgically with curative intent were used to update the dynamic PERsonalised SARcoma Care (PERSARC) model. Patients were added to the model development cohort and grade was included in the model. External validation was performed with data from 1111 patients treated at a single tertiary center. Results: Calibration plots show good model calibration. Dynamic C-indices suggest that the model can discriminate between high- and low-risk patients. The dynamic C-indices at 0, 1, 2, 3, 4, and 5 years after surgery were equal to 0.697, 0.790, 0.822, 0.818, 0.812, and 0.827, respectively. Conclusion: Results from the external validation show that the dynamic PERSARC model is reliable in predicting the probability of surviving an additional 5 years from a specific prediction time point during follow-up. The model combines patient-, treatment-specific and time-dependent variables such as local recurrence and distant metastasis to provide accurate survival predictions throughout follow-up and is available through the PERSARC app

Age-related differences of oncological outcomes in primary extremity soft tissue sarcoma: a multistate model including 6260 patients (vol 141, pg 128, 2020)

Orthopaedics, Trauma Surgery and Rehabilitatio

Age-related differences of oncological outcomes in primary extremity soft tissue sarcoma: a multistate model including 6260 patients

PURPOSE: No studies extensively compared the young adults (YA, 18-39 years), middle-aged (40-69 years), and elderly (≥70 years) population with primary high-grade extremity soft tissue sarcoma (eSTS). This study aimed to determine whether the known effect of age on overall survival (OS) and disease progression can be explained by differences in tumour characteristics and treatment protocol among the YA, middle-aged and elderly population in patients with primary high-grade eSTS treated with curative intent. METHODS: In this retrospective multicentre study, inclusion criteria were patients with primary high-grade eSTS of 18 years and older, surgically treated with curative intent between 2000 and 2016. Cox proportional hazard models and a multistate model were used to determine the association of age on OS and disease progression. RESULTS: A total of 6260 patients were included in this study. YA presented more often after 'whoops'-surgery or for reresection due to residual disease, and with more deep-seated tumours. Elderly patients presented more often with grade III and larger (≥10 cm) tumours. After adjustment for the imbalance in tumour and treatment characteristics the hazard ratio for OS of the middle-aged population is 1.47 (95% confidence interval [CI]: 1.23-1.76) and 3.13 (95% CI: 2.59-3.78) in the elderly population, compared with YA. DISCUSSION: The effect of age on OS could only partially be explained by the imbalance in the tumour characteristics and treatment variables. The threefold higher risk of elderly could, at least partially, be explained by a higher other-cause mortality. The results might also be explained by a different tumour behaviour or suboptimal treatment in elderly compared with the younger population