A web-based prognostic tool for extremity and trunk wall soft tissue sarcomas and its external validation.
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ABSTRACT:
SUBMITTER: Sampo M
PROVIDER: S-EPMC3304417 | biostudies-other | 2012 Mar
REPOSITORIES: biostudies-other
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Project description:BackgroundPrognostic nomograms for patients with extremity soft tissue sarcoma (eSTS) typically predict survival or the occurrence of local recurrence or distant metastasis at time of surgery. Our aim was to develop and externally validate a dynamic prognostic nomogram for overall survival in eSTS survivors for use during follow-up.MethodsAll primary eSTS patients operated with curative intent between 1994 and 2013 at three European and one Canadian sarcoma centers formed the development cohort. Patients with Fédération Française des Centres de Lutte Contre le Cancer (FNCLCC) grade II and grade III eSTS operated between 2000 and 2016 at seven other European reference centers formed the external validation cohort. We used a landmark analysis approach and a multivariable Cox model to create a dynamic nomogram; the prediction window was fixed at five years. A backward procedure based on the Akaike Information Criterion was adopted for variable selection. We tested the nomogram performance in terms of calibration and discrimination.FindingsThe development and validation cohorts included 3740 and 893 patients, respectively. The variables selected applying the backward procedure were patient's age, tumor size and its interaction with landmark time, tumor FNCLCC grade and its interaction with landmark time, histology, and both local recurrence and distant metastasis (as first event) indicator variables. The nomogram showed good calibration and discrimination. Harrell C indexes at different landmark times were between 0.776 (0.761-0.790) and 0.845 (0.823-0.862) in the development series and between 0.675 (0.643-0.704) and 0.810 (0.775-0.844) in the validation series.InterpretationA new dynamic nomogram is available to predict 5-year overall survival at different times during the first three years of follow-up in patients operated for primary eSTS. This nomogram allows physicians to update the individual survival prediction during follow-up on the basis of baseline variables, time elapsed from surgery and first-event history.
| S-EPMC6933187 | biostudies-literature
Project description:BackgroundThe use of nomograms for prognostication of individual cancer patients has been recommended in order to facilitate precision medicine. However, models for patients with soft tissue sarcomas (STSs) are limited because of the rarity and heterogeneity of such cancers. In addition, no model has been developed on the basis of an Asian cohort. Here, we attempted to develop and internally validate nomograms for patients with localized STSs of the trunk and extremity.MethodsThis study retrospectively extracted 2827 patients with primary trunk and extremity STSs after definitive surgery using the Bone and Soft Tissue Tumor Registry, which is a nationwide sarcoma database in Japan. We developed three nomograms predicting the probability of local recurrence-free survival (LRFS), distant metastasis-free survival (DMFS) and disease-specific survival (DSS) at 2 years after surgery, using the Cox multivariate model. The nomograms were internally validated for discrimination and calibration using bootstrap resampling and assessed for their clinical applicability by decision curve analysis (DCA).ResultsLocal recurrence, distant metastasis and disease-specific death occurred in 241 patients (8.5%), 554 patients (19.6%) and 230 patients (8.1%), respectively. Histological diagnosis, grade and tumor size strongly influenced all three endpoints. The nomograms predicted accurately the probability of LRFS, DMFS and DSS (concordance index: 0.73, 0.70 and 0.75, respectively). DCA demonstrated that our nomograms had clinical applicability.ConclusionWe have developed the first nomograms for STSs based on an Asian cohort. These nomograms allowed accurate prediction of LRFS, DMFS and DSS at 2 years after definitive surgery, and can be used as a guide by clinicians for appropriate follow-up and counseling of patients.
| S-EPMC6610844 | biostudies-literature
Project description:Soft tissue sarcoma (STS) of the extremities is typically treated with limb-sparing surgery and radiation therapy; with this treatment approach, high local control rates can be achieved. However, postradiation bone fractures, fractures occurring in the prior radiation field with minimal or no trauma, are a serious late complication that occurs in 2-22% of patients who receive surgery and radiation for STS. Multiple risk factors for sustaining a postradiation fracture exist, including high radiation dose, female sex, periosteal stripping, older age, femur location, and chemotherapy administration. The treatment of these pathological fractures can be difficult, with complications including delayed union, nonunion, and infection posing particular challenges. Here, we review the mechanisms, risk factors, and treatment challenges associated with postradiation fractures in STS patients.
| S-EPMC7984930 | biostudies-literature
Project description:Soft tissue sarcomas (STS) are rare and heterogeneous tumours comprising over 80 different histological subtypes. Treatment options remain limited in advanced STS with high rates of recurrence following resection of localised disease. Prognostication in clinical practice relies predominantly on histological grading systems as well as sarcoma nomograms. Rapid developments in gene expression profiling technologies presented opportunities for applications in sarcoma. Molecular profiling of sarcomas has improved our understanding of the cancer biology of these rare cancers and identified potential novel therapeutic targets. In particular, transcriptomic signatures could play a role in risk classification in sarcoma to aid prognostication. Unlike other solid and haematological malignancies, transcriptomic signatures have not yet reached routine clinical use in sarcomas. Herein, we evaluate early developments in gene expression profiling in sarcomas that laid the foundations for transcriptomic signature development. We discuss the development and clinical evaluation of key transcriptomic biomarker signatures in sarcomas, including Complexity INdex in SARComas (CINSARC), Genomic Grade Index, and hypoxia-associated signatures. Prospective validation of these transcriptomic signatures is required, and prospective trials are in progress to evaluate reliability for clinical application. We anticipate that integration of these gene expression signatures alongside existing prognosticators and other Omics methodologies, including proteomics and DNA methylation analysis, could improve the identification of 'high-risk' patients who would benefit from more aggressive or selective treatment strategies. Moving forward, the incorporation of these transcriptomic prognostication signatures in clinical practice will undoubtedly advance precision medicine in the routine clinical management of sarcoma patients.
| S-EPMC7935908 | biostudies-literature
Project description:BackgroundThe rapid spread of coronavirus disease 2019 (COVID-19) revealed significant constraints in critical care capacity. In anticipation of subsequent waves, reliable prediction of disease severity is essential for critical care capacity management and may enable earlier targeted interventions to improve patient outcomes. The purpose of this study is to develop and externally validate a prognostic model/clinical tool for predicting COVID-19 critical disease at presentation to medical care.MethodsThis is a retrospective study of a prognostic model for the prediction of COVID-19 critical disease where critical disease was defined as ICU admission, ventilation, and/or death. The derivation cohort was used to develop a multivariable logistic regression model. Covariates included patient comorbidities, presenting vital signs, and laboratory values. Model performance was assessed on the validation cohort by concordance statistics. The model was developed with consecutive patients with COVID-19 who presented to University of California Irvine Medical Center in Orange County, California. External validation was performed with a random sample of patients with COVID-19 at Emory Healthcare in Atlanta, Georgia.ResultsOf a total 3208 patients tested in the derivation cohort, 9% (299/3028) were positive for COVID-19. Clinical data including past medical history and presenting laboratory values were available for 29% (87/299) of patients (median age, 48 years [range, 21-88 years]; 64% [36/55] male). The most common comorbidities included obesity (37%, 31/87), hypertension (37%, 32/87), and diabetes (24%, 24/87). Critical disease was present in 24% (21/87). After backward stepwise selection, the following factors were associated with greatest increased risk of critical disease: number of comorbidities, body mass index, respiratory rate, white blood cell count, % lymphocytes, serum creatinine, lactate dehydrogenase, high sensitivity troponin I, ferritin, procalcitonin, and C-reactive protein. Of a total of 40 patients in the validation cohort (median age, 60 years [range, 27-88 years]; 55% [22/40] male), critical disease was present in 65% (26/40). Model discrimination in the validation cohort was high (concordance statistic: 0.94, 95% confidence interval 0.87-1.01). A web-based tool was developed to enable clinicians to input patient data and view likelihood of critical disease.Conclusions and relevanceWe present a model which accurately predicted COVID-19 critical disease risk using comorbidities and presenting vital signs and laboratory values, on derivation and validation cohorts from two different institutions. If further validated on additional cohorts of patients, this model/clinical tool may provide useful prognostication of critical care needs.
| S-EPMC7725393 | biostudies-literature
Project description:To develop a machine learning model and nomogram to predict the probability of persistent virus shedding (PVS) in hospitalized patients with coronavirus disease 2019 (COVID-19), the clinical symptoms and signs, laboratory parameters, cytokines, and immune cell data of 429 patients with nonsevere COVID-19 were retrospectively reviewed. Two models were developed using the Akaike information criterion (AIC). The performance of these two models was analyzed and compared by the receiver operating characteristic (ROC) curve, calibration curve, net reclassification index (NRI), and integrated discrimination improvement (IDI). The final model included the following independent predictors of PVS: sex, C-reactive protein (CRP) level, interleukin-6 (IL-6) level, the neutrophil-lymphocyte ratio (NLR), monocyte count (MC), albumin (ALB) level, and serum potassium level. The model performed well in both the internal validation (corrected C-statistic = 0.748, corrected Brier score = 0.201) and external validation datasets (corrected C-statistic = 0.793, corrected Brier score = 0.190). The internal calibration was very good (corrected slope = 0.910). The model developed in this study showed high discriminant performance in predicting PVS in nonsevere COVID-19 patients. Because of the availability and accessibility of the model, the nomogram designed in this study could provide a useful prognostic tool for clinicians and medical decision-makers.
| S-EPMC10540186 | biostudies-literature
Project description:Background Recent studies have suggested that the quantity and quality of adipose tissue and muscle, assessed on non-contrast computed tomography (CT), may serve as imaging biomarkers of survival in patients with and without neoplasms. Purpose To assess body composition measures that could serve as predictors of therapy response in patients with extremity soft tissue sarcomas treated with radiation therapy and surgery. Material and Methods The study was IRB-approved. Sixty patients had a history of extremity soft tissue sarcoma and underwent FDG-PET/CT prior to radiation therapy and surgical resection. Cross-sectional areas and CT attenuation (HU) of abdominal subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and psoas muscle were assessed on non-contrast CT. Clinical information on predictors of tumor recurrence and post-surgical wound infections were recorded. Cox proportional hazard models were used to determine longitudinal associations between body composition and tumor recurrence/wound infections. Results Twenty-three tumor recurrences occurred over a follow-up period of 43?±?35 months. Higher SAT and lower psoas attenuation were associated with tumor recurrence which remained significant after adjustment for covariates ( P???0.01). There were 13 post-surgical wound infections. Higher VAT and SAT attenuation were associated with post-surgical wound infections ( P?<?0.04); however, VAT attenuation lost significance after adjustment for covariates. Conclusion Abdominal adipose tissue and psoas muscle attenuation assessed on non-contrast CT may predict tumor recurrence and post-surgical infections in patients with extremity soft tissue sarcomas.
| S-EPMC6063528 | biostudies-literature
Project description:The use of upfront chemotherapy for primary localized soft tissue sarcoma (STS) of the extremity and trunk is debated. It remains unclear if chemotherapy adds clinical benefit, which patients are likely to benefit, and whether the timing of therapy affects outcomes. We used the National Cancer Database (NCDB) to examine the association between overall survival (OS) and chemotherapy in 5436 patients with the five most common subtypes of STS with primary disease localized to the extremity or trunk, mirroring the patient population of a modern phase 3 clinical trial of neoadjuvant chemotherapy. We then examined associations between timing of multi-agent chemotherapy (neoadjuvant or adjuvant) and OS. We used a Cox proportional hazards model and propensity score matching (PSM) to account for covariates including demographic, patient, clinical, treatment, and facility factors. In the overall cohort, we observed no association between multi-agent chemotherapy or its timing and improved OS. Multi-agent chemotherapy was associated with improved OS in several subgroups, including patients with larger tumors (>5 cm), those treated at high-volume centers, or those who received radiation. We also identified an OS benefit to multi-agent chemotherapy among the elderly (>70 years) and African American patients. Multi-agent chemotherapy was associated with improved survival for patients with tumors >5 cm, who receive radiation, or who receive care at high-volume centers. Neither younger age nor chemotherapy timing was associated with better outcomes. These 'real-world' findings align with recent randomized trial data supporting the use of multi-agent chemotherapy in high-risk patients with localized STS.
| S-EPMC7564235 | biostudies-literature
Project description:ObjectiveRecent studies have investigated the significance of GATA3 expression in patients with various malignant tumors. However, no previous studies have evaluated the clinicopathological importance of GATA3 expression in soft tissue sarcomas (STS) patients.MethodsWe evaluated GATA3 expression in 76 STS cases using immunohistochemical analysis, and statistically compared clinicopathological characteristics between GATA3-positive and GATA3-negative cases.ResultGATA3-positive expression was significantly associated with a higher mitotic count (P < 0.0001). Disease-free survival (DFS) of GATA3-positive cases was significantly shorter than that of cases without GATA3 expression (P = 0.0104). Overall survival (OS) of GATA3-positive cases was significantly shorter than that of cases without GATA3 expression (P = 0.0006). GATA3-positive expression was significantly associated with shorter DFS in both univariate analysis (hazard ratio [HR], 2.719; P = 0.012) and multivariate analysis (HR, 2.711; P = 0.014). GATA3-positive expression was also significantly associated with worse OS in both univariate analysis (HR, 5.730; P = 0.0007) and multivariate analysis (HR, 5.789; P = 0.0008).ConclusionThese results indicate that GATA3 is an independent prognostic factor and suggest that evaluation of GATA3 expression might enable more effective clinical follow-up using prognostic stratification of STS patients.
| S-EPMC4889143 | biostudies-literature
Project description:Background Although clinicians and patients with extremity bone and soft tissue (EBST) are increasingly interested in limb salvage surgery (LSS), because of the minimal damage to physical appearance and function, however, there is still a lack of large-scale population studies on whether LSS improves the prognosis of patients. Purpose The aim of this study was to compare the survival of patients with EBST sarcomas after receiving LSS and amputation. Methods To conduct the population-based study, we identified 6,717 patients with a histologically diagnosed bone sarcoma and 24,378 patients with a histologically diagnosed soft tissue sarcoma from the Surveillance, Epidemiology, and End Results database. We analyzed overall survival (OS), cancer-specific survival (CSS), and non-sarcoma survival (NSS) using the Kaplan–Meier method, log-rank test or Gray test, Cox regression model, propensity score-matched analysis, and landmark analysis. Results LSS could improve the prognosis in patients with most EBST subtypes, except for Ewing sarcomas and MPNST. However, in the subgroup without distant metastases, limb salvage increased CSS only for patients with osteosarcoma, Ewing sarcoma, and leiomyosarcoma, as well as NSS for patients with chondrosarcoma and synovial sarcoma. Landmark analysis further demonstrated that sarcoma survivors surviving <10 years could benefit from LSS but not for long-term survivors ≥10 years. Moreover, for patients with distant metastases, LSS could improve survival of osteosarcoma patients but worsen CSS among patients with MPNST. Landmark analysis further demonstrated that LSS improved survival among osteosarcomas patients with distant metastases only within 1 year after surgery. Moreover, patients receiving LSS and those receiving amputation had a high risk of dying from different non-sarcoma diseases during the postoperative follow-up. Conclusions The impact of limb salvage on the prognosis of patients depends on the pathological subtype and stage of EBST sarcomas.
| S-EPMC9208618 | biostudies-literature