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Prognostic factors for local recurrence and mortality in adult soft tissue sarcoma of the extremities and trunk wall: A cohort study of 922 consecutive patients

BACKGROUND AND PURPOSE: Previous studies of soft tissue sarcoma (STS) have identified a number of possible prognostic factors; however, the majority of these include highly selected populations, with unclear validation of data and insufficient statistical methods. We identified prognostic factors in...

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Detalles Bibliográficos
Autores principales: Maretty-Nielsen, Katja, Aggerholm-Pedersen, Ninna, Safwat, Akmal, Jørgensen, Peter Holmberg, Hansen, Bjarne H, Baerentzen, Steen, Pedersen, Alma B, Keller, Johnny
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Informa Healthcare 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4062802/
https://www.ncbi.nlm.nih.gov/pubmed/24694277
http://dx.doi.org/10.3109/17453674.2014.908341
Descripción
Sumario:BACKGROUND AND PURPOSE: Previous studies of soft tissue sarcoma (STS) have identified a number of possible prognostic factors; however, the majority of these include highly selected populations, with unclear validation of data and insufficient statistical methods. We identified prognostic factors in a validated, population-based 30-year series of STS treated at a single institution, using an advanced statistical approach. PATIENTS AND METHODS: Between 1979 and 2008, 922 adult patients from western Denmark were treated at the Aarhus Sarcoma Center for non-metastatic STS in the extremities or trunk. The endpoints were local recurrence (LR) and disease-specific mortality (DSM). Prognostic factors were analyzed using a proportional hazard model, including continuous variables as cubic splines. Directed acyclic graphs were used to depict the causal structure. RESULTS: The 5-year LR was 16% and the 5-year DSM was 24%. Important prognostic factors for both LR and DSM were age, duration of symptoms, tumor size, grade, margin, and radiotherapy, while anatomical location (upper, lower extremity, trunk) was prognostic for DSM. INTERPRETATION: In this population-based series of adult, non-metastatic STS, we included directed acyclic graphs, cubic splines, and a competing risk model in order to minimize bias, and demonstrated that these statistical methods are feasible. Using these statistical methods on a large, validated dataset, we excluded depth as a prognostic factor and established that age, duration of symptoms, size, grade, margin, and radiotherapy were important prognostic factors for both local recurrence and disease-specific mortality.