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Statistical analysis

ZW Zhiping Wu
YZ Yun Zou
RF Ronghua Fu
PJ Pingliang Jin
HY Hua Yuan
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Quantitative data were displayed by means and standard deviation or median and range. And categorical data were described by number and percentage (N, %). Continuous data were analyzed by independent t test and categorical data were compared using Pearson’s Chi-square or Fisher’s exact test where appropriate. The statistically significant factors for therapeutic response were then used to constructed a multivariable logistic regression model. Based on the multivariable logistic regression model, a predictive nomogram for LMs response was developed. Receiver operating characteristic (ROC) and calibration curves were used to assess the efficacy. Statistically significant levels were two-tailed and set at P < 0.05. Statistical analysis was performed using IBM Statistical Package for the Social Sciences (SPSS) version 22.0 Windows software package. The nomogram and ROC curve were drawn using the “rms” package in R version 3.4.1.

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