N -nitrosodimethylamine-Contaminated Valsartan and Risk of Cancer: A Nationwide Study of 1.4 Million Valsartan Users.
Imène MansouriJérémie BottonLaura SemenzatoNadia HaddyMahmoud ZureikPublished in: Journal of the American Heart Association (2022)
Background Since July 2018, numerous lots of valsartan have been found to be contaminated with N -nitrosodimethylamine (NDMA). We aimed to assess the association between exposure to valsartan products contaminated with NDMA and the risk of cancer. Methods and Results This study was based on data from the Système National des Données de Santé, which is a national database that includes all French residents' health-related expenses. The target population was consumers of valsartan between January 1, 2013 and December 31, 2017, aged between 40 and 80 years old. The association of exposure to contaminated valsartan with the occurrence of any malignancy and cancer by location was evaluated by fitting Cox proportional hazards models weighted by the inverse probability of treatment. A total of 1.4 million subjects without any history of cancer were included. A total of 986 126 and 670 388 patients were exposed to NDMA-contaminated and uncontaminated valsartan, respectively. The use of the NDMA-contaminated valsartan did not increase the overall risk of cancer (adjusted hazard ratio [aHR], 0.99 [95% CI, 0.98-1.0]). However, exposed patients had a higher risk of liver cancer (aHR, 1.12 [95% CI, 1.04-1.22]) and melanoma (aHR, 1.10 [95% CI, 1.03-1.18]). We estimated a mean of 3.7 and 5.8 extra cases per year per 100 000 person-years of liver cancer and melanoma, respectively. Conclusions Our study was the largest to date to examine cancer risks associated with exposure to NDMA-contaminated valsartan. Our findings suggest a slight increased risk of liver cancer and melanoma in patients exposed to NDMA in regularly taken medications.
Keyphrases
- papillary thyroid
- heavy metals
- end stage renal disease
- squamous cell
- ejection fraction
- newly diagnosed
- chronic kidney disease
- risk assessment
- prognostic factors
- peritoneal dialysis
- squamous cell carcinoma
- emergency department
- machine learning
- magnetic resonance imaging
- computed tomography
- quality improvement
- big data
- artificial intelligence