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The cross-validation MEK inhibitor cancer procedure was selected in model validation procedure, whose advantages were allowing to access the entire dataset for model validation. Medicine (2017) 96:3(e5909) Received: 15 August 2016 / Received in final form: 21 December 2016 / Accepted: 24 December 2016 http://dx.doi.org/10.1097/MD.Wang et al. Medicine (2017) 96:Medicinethrough pathological examinations for tissues obtained via operations or biopsies. The following factors were studied: patient age, gender (male vs female), primary tumor size, tumor location (femur, tibia, humerus, fibula, and others), tumor grade (1?), and histological classification (osteoblastic, chondroblastic, and others). WHO classification was used for the determination of pathological diagnosis and tumor grade. All pathological diagnoses were established after examining and confirming by 2 independent experienced pathologists. The calculation of monocyte ratio was the absolute monocyte count after initial treatment divided by the absolute monocyte count before initial treatment.E current study protocol. All patients have signed written informed consents: including tissue analysis and potential therapeutic research. Medical records from 290 consecutive OS patients between July 2001 and May 2013 were reviewed. Characteristics of patients and tumors at initial diagnosis of OS and development of metastases were collected. Metastases were definitively diagnosedCopyright ?2017 the Author(s). Published by Wolters Kluwer Health, Inc. This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Medicine (2017) 96:3(e5909) Received: 15 August 2016 / Received in final form: 21 December 2016 / Accepted: 24 December 2016 http://dx.doi.org/10.1097/MD.Wang et al. Medicine (2017) 96:Medicinethrough pathological examinations for tissues obtained via operations or biopsies. NLR ratio was calculated as NLR after initial treatment divided by NLR before initial treatment. 2.1. Statistical analysis For categorical data, the Fisher exact test or Pearson x2 test were used. Accordingly, the Mann hitney U test or independent sample t test were employed. To develop the predictive model, stepwise logistic regression was used, where the final diagnosis was set as the dependent variable and the following characteristics as independent variables: patient age, gender, primary tumor size, tumor location, tumor grade, histological classification, monocyte ratio, and NLR ratio. The final model was established through eliminating variables by backward selection, where the selective criterion was statistically significant level of 0.05. If using a relevantly more liberal P value of 0.10, similar results would be observed. After tested all potential clinical interactions, since no statistically significant results were found, all of them were eliminated in the final model. Furthermore, all predictors entered in the final model were reported their odds ratios (ORs) and 95 confidence intervals (CIs). The final model could be applied to compute the estimated probabilities of metastases for study individuals. To construct the receiver-operating characteristic curve, the predicted probabilities and definitive diagnoses of metastases were used. Then, in order to describe the accuracy of the model, the AUCs and their 95 CI were reported. To estimate model fit, the Hosmer emeshow goodness-of-fit statistic (P > 0.05) was used. The cross-validation procedure was selected in model validation procedure, whose advantages were allowing to access the entire dataset for model validation.
