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      Risk-stratified patients with resectable soft tissue sarcoma benefit from epirubicin-based adjuvant chemotherapy

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          Abstract

          As adjuvant chemotherapy (AC) for soft tissue sarcomas is controversial, we performed a retrospective analysis of patients seen at Washington University in St. Louis to evaluate whether it benefited our patient population. Patients were risk-assessed using the Memorial Sloan Kettering Predictive Nomogram (MSKPN). We defined high-risk patients by a MSKPN 4-year postoperative probability of sarcoma-specific death of ≥0.3 and investigated if they benefited from AC. Retrospective review was performed on patients seen between 15 February 1996 and 6 February 2010. A propensity score method in the logistic regression framework was used to model the likelihood of receiving AC. To make causal inference on the effect of AC on survival outcomes, a propensity score inverse probability of treatment weighting approach was applied to survival analysis. Overall, 135 high-grade patients were assessed, 33 were treated with Ifosfamide/Epirubicin (I/Epi) and 102 were non AC patients. The stratified MSKPN risk was not significantly associated with any survival endpoint in the whole cohort, but trended for overall survival (OS) when evaluated against non AC patients. After adjustment for MSKPN risk and other variables, patients not receiving chemotherapy had significantly worse OS, recurrent free survival, and disease-specific survival (DSS) with adjusted hazard ratios of 4.18 (95% CI: 2.22–7.90), 8.96 (95% CI: 3.85–20.83), and 5.42 (95% CI: 2.09–14.06), respectively. In retrospective analyses, risk-stratified patients with soft tissue sarcoma benefited from I/Epi-based AC. Randomized I/Epi versus I/Doxorubicin clinical trials may determine the optimal adjuvant treatment.

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          Modeling Survival Data: Extending the Cox Model

          This is a book for statistical practitioners, particularly those who design and analyze studies for survival and event history data. Its goal is to extend the toolkit beyond the basic triad provided by most statistical packages: the Kaplan-Meier estimator, log-rank test, and Cox regression model. Building on recent developments motivated by counting process and martingale theory, it shows the reader how to extend the Cox model to analyse multiple/correlated event data using marginal and random effects (frailty) models. It covers the use of residuals and diagnostic plots to identify influential or outlying observations, assess proportional hazards and examine other aspects of goodness of fit. Other topics include time-dependent covariates and strata, discontinuous intervals of risk, multiple time scales, smoothing and regression splines, and the computation of expected survival curves. A knowledge of counting processes and martingales is not assumed as the early chapters provide an introduction to this area. The focus of the book is on actual data examples, the analysis and interpretation of the results, and computation. The methods are now readily available in SAS and S-Plus and this book gives a hands-on introduction, showing how to implement them in both packages, with worked examples for many data sets. The authors call on their extensive experience and give practical advice, including pitfalls to be avoided. Terry Therneau is Head of the Section of Biostatistics, Mayo Clinic, Rochester, Minnesota. He is actively involved in medical consulting, with emphasis in the areas of chronic liver disease, physical medicine, hematology, and laboratory medicine, and is an author on numerous papers in medical and statistical journals. He wrote two of the original SAS procedures for survival analysis (coxregr and survtest), as well as the majority of the S-Plus survival functions. Patricia Grambsch is Associate Professor in the Division of Biostatistics, School of Public Health, University of Minnesota. She has collaborated extensively with physicians and public health researchers in chronic liver disease, cancer prevention, hypertension clinical trials and psychiatric research. She is a fellow the American Statistical Association and the author of many papers in medical and statistical journals.
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            A Language and Environment for Statistical Computing

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              Randomized prospective study of the benefit of adjuvant radiation therapy in the treatment of soft tissue sarcomas of the extremity.

              This randomized, prospective study assesses the impact of postoperative external-beam radiation therapy on local recurrence (LR), overall survival (OS), and quality of life after limb-sparing resection of extremity sarcomas. Patients with extremity tumors and a limb-sparing surgical option were randomized to receive or not receive postoperative adjuvant external-beam radiotherapy. Patients with high-grade sarcomas received postoperative adjuvant chemotherapy whereas patients with low-grade sarcomas or locally aggressive nonmalignant tumors were randomized after surgery alone. Ninety-one patients with high-grade lesions were randomized; 47 to receive radiotherapy (XRT) and 44 to not receive XRT. With a median follow-up of 9.6 years, a highly significant decrease (P2 = .0028) in the probability of LR was seen with radiation, but no difference in OS was shown. Of 50 patients with low-grade lesions (24 randomized to resection alone and 26 to resection and postoperative XRT), there was also a lower probability of LR (P2 = .016) in patients receiving XRT, again, without a difference in OS. A concurrent quality-of-life study showed that extremity radiotherapy resulted in significantly worse limb strength, edema, and range of motion, but these deficits were often transient and had few measurable effects on activities of daily life or global quality of life. This study indicates that although postoperative external-beam radiotherapy is highly effective in preventing LRs, selected patients with extremity soft tissue sarcoma who have a low risk of LR may not require adjuvant XRT after limb-sparing surgery (LSS).
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                Author and article information

                Journal
                Cancer Med
                Cancer Med
                cam4
                Cancer Medicine
                BlackWell Publishing Ltd (Oxford, UK )
                2045-7634
                2045-7634
                June 2014
                27 February 2014
                : 3
                : 3
                : 603-612
                Affiliations
                [1 ]Division of Medical Oncology, Washington University in St. Louis St. Louis, 63110, Missouri
                [2 ]College of Medicine, Des Moines University Des Moines, 50312, Iowa
                [3 ]Division of Biostatistics, Washington University in St. Louis St. Louis, 63110, Missouri
                [4 ]Siteman Cancer Center, Washington University in St. Louis St. Louis, 63110, Missouri
                [5 ]Loyola University Chicago, 60626, Illinois
                Author notes
                Brian A. Van Tine, Assistant Professor of Medicine, Division of Medical Oncology, Washington University in St. Louis,, 660 S Euclid, Campus Box 8007, St. Louis, MO 63110. Tel: 314-747-8475; Fax: 314-747-9320; E-mail: bvantine@ 123456dom.wustl.edu

                Funding Information Funding for this publication was provided by the Sarcoma Tumor Board at Washington University in St. Louis.

                [*]

                Co-First Authors.

                Article
                10.1002/cam4.209
                4101751
                24574357
                726cc4bf-6394-47ea-ab15-d848ddcd2394
                © 2014 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 01 January 2014
                : 18 January 2014
                : 20 January 2014
                Categories
                Original Research

                Oncology & Radiotherapy
                adjuvant chemotherapy,doxorubicin,epirubicin,sarcoma
                Oncology & Radiotherapy
                adjuvant chemotherapy, doxorubicin, epirubicin, sarcoma

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