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Prognosis for primary retroperitoneal sarcoma survivors
Author(s) -
Abbott Andrea M.,
Habermann Elizabeth B.,
Parsons Helen M.,
Tuttle Todd,
AlRefaie Waddah
Publication year - 2012
Publication title -
cancer
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.052
H-Index - 304
eISSN - 1097-0142
pISSN - 0008-543X
DOI - 10.1002/cncr.26665
Subject(s) - medicine , nomogram , proportional hazards model , sarcoma , survival analysis , oncology , prognostic variable , population , cancer , overall survival , surgery , pathology , environmental health
Abstract BACKGROUND: The AJCC staging system and post‐operative nomograms use patient and tumor characteristics to provide prognostic estimates after resection of retroperitoneal sarcoma (RPS). While these variables help to predict survival at the time of diagnosis and resection, the applicability of these prognostic factors to survivors of RPS remains unknown. We hypothesized that the variables evaluated in the current staging system and post‐operative nomograms would have limited ability to predict conditional survival in patients surgically treated for RPS. METHODS: A retrospective study was conducted using National Cancer Institute‐sponsored tumor registries. We identified 1,199 patients who underwent surgical resection for non‐metastatic RPS from 1988 to 2007. Conditional survival was defined as time‐specific estimates conditioned on living a certain number of years post‐diagnosis. Cox proportional hazards regression was used to assess the impact of various factors on sarcoma‐specific survival (SSS) at baseline and up to 5 years after diagnosis. RESULTS: Older age, male gender, histologic subtype, and high tumor grade predicted worse SSS at the time of diagnosis. After 1 year of survival, older age, male gender, and histologic subtype were no longer significant predictors of conditional survival. Only high grade tumors remained a significant predictor of worse prognosis after 5 years of survival (HR 1.95). CONCLUSIONS: This population‐based study demonstrates that the factors which are predictive of survival at baseline lose significance after one year of survival. Conditional survival estimates allow clinicians to provide survivors with more meaningful prognostic estimates that may impact surveillance schedules and streamline adjuvant therapy decisions and design of future clinical trials. Cancer 2012. © 2012 American Cancer Society.