We consider random variables which can be subject to both censoring and measurement errors. We focus on the case where the measurement errors affect both the variable of interest and the censoring variable, which is the case of the timing of spontaneous delivery among pregnant women. We propose an estimation strategy to estimate the hazard rate of the underlying variable of interest. We explain the model and this strategy and provide L2-risk bound for the data driven resulting estimator. Simulations illustrate the performances of the estimator. Lastly, the method is applied to a real data set of length of pregnancy