Insulin Therapy And Breast Cancer Risk

Some observational studies have suggested an association between insulin therapy and cancer risk. Using a meta-analytical approach, the risk of breast cancer in diabetic patients treated with insulin was compared to the risk in diabetic patients treated with a non-insulin therapy (NIT). A systematic literature search was conducted in the PubMed database from inception to October 2017. Studies with a prospective design including nested case-control and case-cohort studies were selected. Summary relative risks (SRR) of breast cancer associated with the use of any type of insulin therapy compared to NIT were computed using a random-effect model. Three sub-analyses were carried out: one according to the adoption of a new-user design (i.e., including only new users of a drug) vs. a prevalent user design (i.e., including both new and past users of a drug); one according to the type of comparator (specific NIT vs. any type of NITs); and one according to the type of diabetes. A total of 12 studies, representing 1,392,040 diabetics and 15,430 breast cancer cases, were included in the analysis. Overall, the SRR of breast cancer associated with insulin use was 0.97 (95% CI: 0.87, 1.08) with a high degree of heterogeneity between studies (I²=60%, p<0.01) and no evidence for publication bias. In all three sub-analyses, the SRR remained close to 1.0 and statistically non-significant. The heterogeneity was reduced in studies restricted to T2DM patients, in studies with a new-user design and in studies with a specific NIT used as comparator (I²=0%, 21% and 0%, respectively). Heterogeneity was increased in studies using a prevalent user design and in studies with a no/never use as comparator (I²=70% and 73%, respectively). This meta-analysis showed no evidence for an association between breast cancer occurrence and insulin therapy prescription history when the comparators are other NITs. The marked differences in heterogeneity indicate that studies with a new-user design or with a specific NIT as comparator are probably less affected by confounding and biases. Disclosure C. Pizot: None. M. Dragomir: None. P. Boyle: Other Relationship; Self; Sanofi. P. Autier: Other Relationship; Self; Sanofi.