Response: The risk of Stevens‐Johnson syndrome and toxic epidermal necrolysis in new users of antiepileptic drugs: Comment on data sparsity

The risk of Stevens‐Johnson syndrome and toxic epidermal necrolysis in new users of antiepileptic drugs: Comment on data sparsity

“…4 Thus, the expected relative risk estimates for SJS in association with new antiepileptic use can be expected to be very high, which was also suggested in the comprehensive hospital-based EuroSCAR case-control study, which reported ORs of 72 (95% CI 26-225) for carbamazepine and 26 (95% CI 7.8-90) for phenytoin. 5 We agree that extremely high relative risks from observational studies need to be interpreted carefully. However, in the absence of any prior evidence suggesting lower ORs, using a penalization prior which artificially corrects ORs toward the null might provide a false sense of certainty.…”

“…The take-home message for the readers is that the sparse data bias is common in medical research, 4,5 and that needs to be reduced by using the advanced statistical methods.…”

Sparse data and use of logistic regression

“…Therefore, it is possible that in this case, penalization would have been the preferred method to stabilize the estimates, as suggested by Safiri and Ahran‐Asgarabad . The response by Frey et al . notes correctly that Safiri and Ahran‐Asgarabad do not include detailed information on the penalization priors.…”