The prognostic and predictive value of syntactic structure analysis in serous carcinoma of the ovary
Palmer, Julia E., Cassia, Louis J. Sant, Irwin, Clive J., Morris, A. G., Janssen, Emiel, Baak, J. P. A. and Rollason, Terence P.. (2008) The prognostic and predictive value of syntactic structure analysis in serous carcinoma of the ovary. International Journal of Gynecological Pathology, Volume 27 (Number 2). pp. 191-198. ISSN 0277-1691Full text not available from this repository.
Official URL: http://dx.doi.org/10.1097/PGP.0b013e31815699f6
The objective of this study was to determine whether syntactic structure analysis (SSA) can predict survival outcome and chemotherapeutic response in ovarian carcinoma. Syntactic structure analysis parameters, blindly determined in archived hematoxylin and eosin sections of 132, International Federation of Gynecology and Obstetrics (FIGO) stage I to IV serous ovarian tumors, and clinicopathologic parameters were evaluated as to their univariate and multivariate prognostic value and ability to predict chemotherapy response as measured by changes in CA125 levels. Univariate analysis revealed FIGO stage, tumor grade, preoperative CA125, presence of ascites, extent of disease residuum, and the SSA parameters minimum spanning tree (min MST), maximum MST (max MST), percent connectivity to 1, and 2 nearest neighbors to be significant predictors of overall survival and disease-free survival. Tumor grade, FIGO stage, extent of disease residuum, presence of ascites, and percent connectivity to 2 nearest neighbors were found to be significant predictors of chemotherapy response. Multivariate analysis revealed extent of disease residuum to be a significant predictor for overall survival (P <= 0.01) and prediction of chemotherapy response (P = 0.05). International Federation of Gynecology and Obstetrics stage was a significant predictor for disease-free survival (P <= 0.01). Syntactic structure analysis parameters did not retain independent significance. Syntactic structure analysis features can predict survival outcome and chemotherapy response in ovarian carcinoma but, with multivariate analysis, are overshadowed by FIGO stage and residual disease.
|Item Type:||Journal Article|
|Subjects:||R Medicine > RG Gynecology and obstetrics
R Medicine > RB Pathology
|Divisions:||Faculty of Medicine > Warwick Medical School|
|Library of Congress Subject Headings (LCSH):||Carcinoma, Ovaries -- Cancer, Spanning trees (Graph theory)|
|Journal or Publication Title:||International Journal of Gynecological Pathology|
|Publisher:||Lippincott Williams & Wilkins|
|Official Date:||April 2008|
|Number of Pages:||8|
|Page Range:||pp. 191-198|
|Access rights to Published version:||Restricted or Subscription Access|
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