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Comorbidity patterns, family history and breast cancer risk: a latent class analysis
  1. Michela Dalmartello1,
  2. Jeroen Vermunt2,
  3. Fabio Parazzini1,
  4. Diego Serraino3,
  5. Attilio Giacosa4,
  6. Anna Crispo5,
  7. Eva Negri1,6,
  8. Fabio Levi7,
  9. Claudio Pelucchi1,
  10. Carlo La Vecchia1
  1. 1Department of Clinical Sciences and Community Health, University of Milan, Milan, Italy
  2. 2Department of Methodology and Statistics, Tilburg University, Tilburg, The Netherlands
  3. 3Unit of Cancer Epidemiology, CRO Aviano National Cancer Institute, Aviano, Italy
  4. 4Department of Gastroenterology and Clinical Nutrition, Policlinico di Monza, Monza, Italy
  5. 5Epidemiology and Biostatistics Unit, Istituto Nazionale dei Tumori IRCCS Fondazione 'G.Pascale', Napoli, Italy
  6. 6Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy
  7. 7Institute of Social and Preventive Medicine (IUMSP), University of Lausanne, Lausanne, Switzerland
  1. Correspondence to Michela Dalmartello, Department of Clinical Sciences and Community Health, University of Milan, Milan 20122, Italy; michela.dalmartello{at}unimi.it

Abstract

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.

  • PREVENTION
  • BREAST NEOPLASMS
  • STATISTICS

Data availability statement

Data are available upon reasonable request.

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Data availability statement

Data are available upon reasonable request.

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Footnotes

  • Contributors MD: conceptualisation, formal analysis, writing (original draft), and responsible for the overall content as guarantor; JV: methodology, software, supervision, writing (review and editing); FP: writing (review and editing); DS: investigation, resources, project administration, writing (review and editing); AG: project administration, writing (review and editing); AC: project administration, writing (review and editing); EN: project administration, writing (review and editing); FL: project administration, writing (review & editing);CP: conceptualisation, writing (review and editing); CLV: conceptualisation, funding acquisition, investigation, methodology, resources, supervision, validation, writing (review and editing).

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.