We propose an information-matrix-based goodness-of-fit statistic to test the validity of the logistic regression model based on case-control data by extending the information matrix test of White (1982) for detecting one-sample parametric model misspecification to the semiparametric profile likelihood setting under a two-sample semiparametric model, which is equivalent to the assumed logistic regression model. The proposed test statistic requires a high-dimensional matrix inversion, but is otherwise easily computed and has an asymptotic chi-squared distribution