Drug-induced tooth discoloration: An analysis of the US food and drug administration adverse event reporting system

Abstract

Background: Certain drugs can cause intrinsic or extrinsic tooth discoloration, which is not only a clinical issue but also an esthetic problem. However, limited investigations have focused on drug-induced tooth discoloration. The present work aimed to determine the drugs causing tooth discoloration and to estimate their risks of causing tooth discoloration. Methods: An observational, retrospective, and pharmacovigilance analysis was conducted, in which we extracted adverse event (AE) reports involving tooth discoloration by using the data of the US Food and Drug Administration's Adverse Event Reporting System (FAERS) from the first quarter (Q1) of 2004 to the third quarter (Q3) of 2021. Disproportionality analyses were performed to examine risk signals for tooth discoloration and determine the drugs inducing tooth discoloration. Results: Based on predefined inclusion criteria, 1188 AE reports involving 302 suspected drugs were identified. After data mining, 25 drugs generated positive risk signals for tooth discoloration, of which 10 were anti-infectives for systemic use. The top reported drug was tetracycline (n = 106), followed by salmeterol and fluticasone (n = 68), amoxicillin (n = 60), chlorhexidine (n = 54), and nicotine (n = 52). Cetylpyridinium (PRR = 472.2, ROR = 502.5), tetracycline (PRR = 220.4, ROR = 277), stannous fluoride (PRR = 254.3, ROR = 262.8), hydrogen peroxide (PRR = 240.0, ROR = 247.6), and chlorhexidine (PRR = 107.0, ROR = 108.4) showed stronger associations with tooth discoloration than the remaining drugs. Of 625 AE reports involving 25 drugs with positive risk signals, tooth discoloration was mostly reported in patients aged 45-64 (n = 110) and ≤18 (n = 95), and 29.4% (192/652) of the reports recorded serious outcomes. Conclusion: This study revealed that certain drugs are significantly associated with tooth discoloration. Caution should be exercised when using these drugs, especially during pregnancy and early childhood.

Keywords: FAERS; data mining; disproportionality analyses; drugs; tooth discoloration.

FIGURE 1

Flow diagram of drug identification in the FAERS.

FIGURE 2

Radical tree of drugs grouped by ATC class. The height of each column represents the number of submitted AE reports (J: anti-infectives for systemic use, R: respiratory system, N: nervous system, A: alimentary tract and metabolism, M: musculo-skeletal system, V: various, D: dermatologicals, C: cardiovascular system).