Postoperative nomogram to predict the probability of metastasis in enneking stage IIB extremity osteosarcoma

Seung H. Kim, Kyoo Ho Shin, Ha Y. Kim, Yong J. Cho, Jae K. Noh, Jin Suck Suh, Woo Ick Yang

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29 Citations (Scopus)

Abstract

Background: Metastasis is the most crucial prognostic factor in osteosarcoma. The goal of this study was to develop a new nomogram to predict the probability of metastasis in Enneking stage IIB extremity osteosarcoma after neoadjuvant chemotherapy and limb salvage surgery.Methods: We examined medical records of 91 patients who had undergone surgery between March 1994 and March 2007. A nomogram was developed using multivariate logistic regression. The nomogram was validated internally by bootstrapping-method (200 repetitions) and externally in independent validation set (n = 34). A Youden-derived cutoff value was assigned to the nomogram to predict dichotomous outcomes for metastasis.Results: The nomogram was built from four predictors of tumor site, serum alkaline phosphatase, intracapsular extension, and Huvos grade, and an additional clause that the cutoff value should be added to the total points in the cases of incomplete surgical resection. P-value of Hosmer and Lemshow Goodness-of-fit test of this model was 0.649. Area under receiver operating curve values of 0.83 (95% confidence interval [CI], 0.75 to 0.92) in the training set and 0.80 (95% CI, 0.63 to 0.96) in the validation set were obtained. The accuracy of dichotomous outcomes was 79.1% (95% CI, 0.69 to 0.86) and 82.4% (95% CI, 0.63 to 0.92) in the training and validation sets.Conclusions: We have developed a new high-performance nomogram to predict the probability of metastasis in Enneking stage IIB extremity osteosarcoma after limb salvage surgery.

Original languageEnglish
Article number666
JournalBMC cancer
Volume14
Issue number1
DOIs
Publication statusPublished - 2014 Sept 12

Bibliographical note

Funding Information:
The authors would like to thank all the patients enrolled in this study. We wish to thank Jun Young Kim who assisted in collecting preliminary clinical data. This research has not been supported by any grant or fund.

Publisher Copyright:
© 2014 Kim et al.; licensee BioMed Central Ltd.

All Science Journal Classification (ASJC) codes

  • Oncology
  • Genetics
  • Cancer Research

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