Cargando…

Metformin use and risk of cancer in patients with type 2 diabetes: a cohort study of primary care records using inverse probability weighting of marginal structural models

BACKGROUND: Previous studies provide conflicting evidence on whether metformin is protective against cancer. When studying time-varying exposure to metformin, covariates such as body mass index (BMI) and glycated haemoglobin (HbA1c) may act as both confounders and causal pathway variables, and so ca...

Descripción completa

Detalles Bibliográficos
Autores principales: Farmer, Ruth E, Ford, Deborah, Mathur, Rohini, Chaturvedi, Nish, Kaplan, Rick, Smeeth, Liam, Bhaskaran, Krishnan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6469299/
https://www.ncbi.nlm.nih.gov/pubmed/30753459
http://dx.doi.org/10.1093/ije/dyz005
_version_ 1783411618941501440
author Farmer, Ruth E
Ford, Deborah
Mathur, Rohini
Chaturvedi, Nish
Kaplan, Rick
Smeeth, Liam
Bhaskaran, Krishnan
author_facet Farmer, Ruth E
Ford, Deborah
Mathur, Rohini
Chaturvedi, Nish
Kaplan, Rick
Smeeth, Liam
Bhaskaran, Krishnan
author_sort Farmer, Ruth E
collection PubMed
description BACKGROUND: Previous studies provide conflicting evidence on whether metformin is protective against cancer. When studying time-varying exposure to metformin, covariates such as body mass index (BMI) and glycated haemoglobin (HbA1c) may act as both confounders and causal pathway variables, and so cannot be handled adequately by standard regression methods. Marginal structural models (MSMs) with inverse probability of treatment weights (IPTW) can correctly adjust for such confounders. Using this approach, the main objective of this study was to estimate the effect of metformin on cancer risk compared with risk in patients with T2DM taking no medication. METHODS: Patients with incident type 2 diabetes (T2DM) were identified in the Clinical Practice Research Datalink (CPRD), a database of electronic health records derived from primary care in the UK. Patients entered the study at diabetes diagnosis or the first point after this when they had valid HbA1c and BMI measurements, and follow-up was split into 1-month intervals. Logistic regression was used to calculate IPTW; then the effect of metformin on all cancers (including and excluding non-melanoma skin cancer) and breast, prostate, lung, colorectal and pancreatic cancers was estimated in the weighted population. RESULTS: A total of 55 629 T2DM patients were alive and cancer-free at their study entry; 2530 people had incident cancer during a median follow-up time of 2.9 years [interquartile range (IQR) 1.3–5.4 years]. Using the MSM approach, the hazard ratio (HR) for all cancers, comparing treatment with metformin with no glucose-lowering treatment, was 1.02 (0.88–1.18). Results were robust to a range of sensitivity analyses and remained consistent when estimating the treatment effect by length of exposure. We also found no evidence of a protective effect of metformin on individual cancer outcomes. CONCLUSIONS: We find no evidence that metformin has a causal association with cancer risk.
format Online
Article
Text
id pubmed-6469299
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-64692992019-04-22 Metformin use and risk of cancer in patients with type 2 diabetes: a cohort study of primary care records using inverse probability weighting of marginal structural models Farmer, Ruth E Ford, Deborah Mathur, Rohini Chaturvedi, Nish Kaplan, Rick Smeeth, Liam Bhaskaran, Krishnan Int J Epidemiol Risk Factors for Cancer BACKGROUND: Previous studies provide conflicting evidence on whether metformin is protective against cancer. When studying time-varying exposure to metformin, covariates such as body mass index (BMI) and glycated haemoglobin (HbA1c) may act as both confounders and causal pathway variables, and so cannot be handled adequately by standard regression methods. Marginal structural models (MSMs) with inverse probability of treatment weights (IPTW) can correctly adjust for such confounders. Using this approach, the main objective of this study was to estimate the effect of metformin on cancer risk compared with risk in patients with T2DM taking no medication. METHODS: Patients with incident type 2 diabetes (T2DM) were identified in the Clinical Practice Research Datalink (CPRD), a database of electronic health records derived from primary care in the UK. Patients entered the study at diabetes diagnosis or the first point after this when they had valid HbA1c and BMI measurements, and follow-up was split into 1-month intervals. Logistic regression was used to calculate IPTW; then the effect of metformin on all cancers (including and excluding non-melanoma skin cancer) and breast, prostate, lung, colorectal and pancreatic cancers was estimated in the weighted population. RESULTS: A total of 55 629 T2DM patients were alive and cancer-free at their study entry; 2530 people had incident cancer during a median follow-up time of 2.9 years [interquartile range (IQR) 1.3–5.4 years]. Using the MSM approach, the hazard ratio (HR) for all cancers, comparing treatment with metformin with no glucose-lowering treatment, was 1.02 (0.88–1.18). Results were robust to a range of sensitivity analyses and remained consistent when estimating the treatment effect by length of exposure. We also found no evidence of a protective effect of metformin on individual cancer outcomes. CONCLUSIONS: We find no evidence that metformin has a causal association with cancer risk. Oxford University Press 2019-04 2019-02-06 /pmc/articles/PMC6469299/ /pubmed/30753459 http://dx.doi.org/10.1093/ije/dyz005 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of the International Epidemiological Association. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Risk Factors for Cancer
Farmer, Ruth E
Ford, Deborah
Mathur, Rohini
Chaturvedi, Nish
Kaplan, Rick
Smeeth, Liam
Bhaskaran, Krishnan
Metformin use and risk of cancer in patients with type 2 diabetes: a cohort study of primary care records using inverse probability weighting of marginal structural models
title Metformin use and risk of cancer in patients with type 2 diabetes: a cohort study of primary care records using inverse probability weighting of marginal structural models
title_full Metformin use and risk of cancer in patients with type 2 diabetes: a cohort study of primary care records using inverse probability weighting of marginal structural models
title_fullStr Metformin use and risk of cancer in patients with type 2 diabetes: a cohort study of primary care records using inverse probability weighting of marginal structural models
title_full_unstemmed Metformin use and risk of cancer in patients with type 2 diabetes: a cohort study of primary care records using inverse probability weighting of marginal structural models
title_short Metformin use and risk of cancer in patients with type 2 diabetes: a cohort study of primary care records using inverse probability weighting of marginal structural models
title_sort metformin use and risk of cancer in patients with type 2 diabetes: a cohort study of primary care records using inverse probability weighting of marginal structural models
topic Risk Factors for Cancer
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6469299/
https://www.ncbi.nlm.nih.gov/pubmed/30753459
http://dx.doi.org/10.1093/ije/dyz005
work_keys_str_mv AT farmerruthe metforminuseandriskofcancerinpatientswithtype2diabetesacohortstudyofprimarycarerecordsusinginverseprobabilityweightingofmarginalstructuralmodels
AT forddeborah metforminuseandriskofcancerinpatientswithtype2diabetesacohortstudyofprimarycarerecordsusinginverseprobabilityweightingofmarginalstructuralmodels
AT mathurrohini metforminuseandriskofcancerinpatientswithtype2diabetesacohortstudyofprimarycarerecordsusinginverseprobabilityweightingofmarginalstructuralmodels
AT chaturvedinish metforminuseandriskofcancerinpatientswithtype2diabetesacohortstudyofprimarycarerecordsusinginverseprobabilityweightingofmarginalstructuralmodels
AT kaplanrick metforminuseandriskofcancerinpatientswithtype2diabetesacohortstudyofprimarycarerecordsusinginverseprobabilityweightingofmarginalstructuralmodels
AT smeethliam metforminuseandriskofcancerinpatientswithtype2diabetesacohortstudyofprimarycarerecordsusinginverseprobabilityweightingofmarginalstructuralmodels
AT bhaskarankrishnan metforminuseandriskofcancerinpatientswithtype2diabetesacohortstudyofprimarycarerecordsusinginverseprobabilityweightingofmarginalstructuralmodels