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BACKGROUND  In this era of individualized cancer treatment, data that could be applied to predicting the survival of patients with osteosarcoma are still limited because of the rarity of the disease and the difficulty in accumulating a sufficient number of patients. Therefore, a multi‐institutional collaboration was implemented to develop and externally validate nomograms that would predict metastasis‐free survival (MFS) and overall survival (OAS) for patients with nonmetastatic osteosarcoma.    METHODS  This study retrospectively examined 1070 patients treated with neoadjuvant chemotherapy and surgery for nonmetastatic osteosarcoma. Data from Japanese patients (n = 557) were used to develop multivariate nomograms based on Cox regression. Six clinical and pathologic variables were built into nomograms estimating the probability of MFS and OAS 3 and 5 years after diagnosis. The model was internally validated for discrimination and calibration with bootstrap resampling and was externally validated with an independent patient cohort from Korea (n = 513).    RESULTS  A patient's age, tumor site, and histologic response were found to have a stronger influence on MFS and OAS in the model than sex, tumor size, or pathologic fracture. The nomograms and calibration plots based on these results well predicted the probability of MFS (concordance index, 0.631) and OAS (concordance index, 0.679). The concordance indices for external validation were 0.682 for MFS and 0.665 for OAS.    CONCLUSIONS  The nomograms were externally validated and verified to be useful for the prediction of MFS and OAS and for the assessment of the postoperative prognosis. They can be used for counseling patients and for establishing appropriate surveillance strategies after surgery.   Cancer  2015;121:3844–3852.  ©  2015 American Cancer Society .

cancer

Development and external validation of nomograms predicting distant metastases and overall survival after neoadjuvant chemotherapy and surgery for patients with nonmetastatic osteosarcoma: A multi‐institutional study