PT  - JOURNAL ARTICLE
AU  - Michela Dalmartello
AU  - Jeroen Vermunt
AU  - Fabio Parazzini
AU  - Diego Serraino
AU  - Attilio Giacosa
AU  - Anna Crispo
AU  - Eva Negri
AU  - Fabio Levi
AU  - Claudio Pelucchi
AU  - Carlo La Vecchia
TI  - Comorbidity patterns, family history and breast cancer risk: a latent class analysis
AID  - 10.1136/jech-2022-219279
DP  - 2022 Oct 01
TA  - Journal of Epidemiology and Community Health
PG  - 867--872
VI  - 76
IP  - 10
4099  - http://jech.bmj.com/content/76/10/867.short
4100  - http://jech.bmj.com/content/76/10/867.full
SO  - J Epidemiol Community Health2022 Oct 01; 76
AB  - Background Limited evidence exists on how the presence of multiple conditions affects breast cancer (BC) risk.Methods We used data from a network hospital-based case–control study conducted in Italy and Switzerland, including 3034 BC cases and 3392 controls. Comorbidity patterns were identified using latent class analysis on a set of specific health conditions/diseases. A multiple logistic regression model was used to derive ORs and the corresponding 95% CIs for BC according to the patterns, adjusting for several covariates. A second model was fitted including an additional effect of FH on the comorbidity patterns.Results With respect to the ‘healthy’ pattern, the ‘metabolic disorders’ one reported an OR of 1.23 (95% CI 1.02 to 1.49) and the ‘breast diseases’ an OR of 1.86 (95% CI 1.23 to 2.83). The remaining two patterns reported an inverse association with BC, with ORs of 0.77, significant only for the ‘hysterectomy, uterine fibroids and bilateral ovariectomy’. In the second model, FH was associated with an increased risk of the ‘breast diseases’ pattern (OR=4.09, 95% CI 2.48 to 6.74). Non-significant increased risk of the other patterns according to FH emerged.Conclusion We identified mutually exclusive patterns of comorbidity, confirming the unfavourable role of those related to metabolic and breast disorders on the risk of BC, and the protective effect of those related to common surgical procedures. FH reported an incremented risk of all the comorbidity patterns.Impact Identifying clusters of comorbidity in patients with BC may help understand their effects and enable clinicians and policymakers to better organise patient and healthcare management.Data are available upon reasonable request.