Lessons Learned From the Study of 10,000 Patients With Soft Tissue Sarcoma

被引:359
作者
Brennan, Murray F. [1 ]
Antonescu, Cristina R. [2 ]
Moraco, Nicole [1 ]
Singer, Samuel [1 ]
机构
[1] Mem Sloan Kettering Canc Ctr, Dept Surg, New York, NY 10065 USA
[2] Mem Sloan Kettering Canc Ctr, Dept Pathol, New York, NY 10065 USA
关键词
database; soft tissue sarcoma; outcomes; GASTROINTESTINAL STROMAL TUMOR; ADJUVANT IMATINIB MESYLATE; SYNOVIAL SARCOMA; POSTOPERATIVE NOMOGRAM; LOCAL RECURRENCE; DEDIFFERENTIATED LIPOSARCOMA; PROGNOSTIC NOMOGRAM; EXTREMITY; SURVIVAL; SUBTYPE;
D O I
10.1097/SLA.0000000000000869
中图分类号
R61 [外科手术学];
学科分类号
摘要
Background and Objective: The management of rare tumors is difficult because of limited information on natural history. Our objective was to describe a long-term comprehensive prospective database with the assumption that with careful attention to patient, predisposing tumor and treatment variables, valuable knowledge could be obtained that could guide management. Methods: In July of 1982, we began a prospective database of all adult patients admitted to our institution for a surgical procedure for soft tissue sarcoma. Patients were included if they had primary, locally recurrent or metastatic disease undergoing a surgical procedure. Results: Over 3 decades, we entered 10,000 patients into our prospective soft tissue sarcoma database. Data were entered on a weekly or biweekly schedule with full participation of a multidisciplinary team and a dedicated sarcoma pathologist. Extensive information is available from this database. In this article, we describe distribution by site, histopathology, sex, size, and grade. We utilize this information along with outcome data for local recurrence, distant recurrence, disease specific, and overall survival. The value of molecular diagnosis is illustrated. Conclusions: Continuous prospective long-term databases are important to obtain knowledge particularly for rare tumors. Such data can be a rich resource for the development of prognostic indicators including nomograms and can be analyzed by Bayesian Belief Networks. These long-term data linked to collection of tumor and germ-line tissue at the time of an initial procedure will remain a resource for future decades.
引用
收藏
页码:416 / 422
页数:7
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