Skip to main content
PMC home page
The Oncologist logoLink to The Oncologist
. 2012 May 29;17(6):813–822. doi: 10.1634/theoncologist.2011-0462

Cancer Risk Associated with Use of Metformin and Sulfonylurea in Type 2 Diabetes: A Meta-Analysis

Davide Soranna a, Lorenza Scotti a, Antonella Zambon a, Cristina Bosetti c, Guido Grassi b, Alberico Catapano d, Carlo La Vecchia c,e,f,✉, Giuseppe Mancia b, Giovanni Corrao a
PMCID: PMC3380880  PMID: 22643536

Oral antidiabetic drugs (including metformin and sulfonylurea) may play a role in the relationship between type 2 diabetes and cancer. To quantify the association between metformin and sulfonylurea and the risk of cancer, we performed a meta-analysis of available studies on the issue. Metformin, but not sulfonylurea, appears to reduce subsequent cancer risk. This has relevant implications in light of the exploding global epidemic of diabetes.

Keywords: Cancer, Diabetes, Meta-analysis, Metformin, Oral antidiabetic therapy, Sulfonylurea

Abstract

Objective.

Oral antidiabetic drugs (including metformin and sulfonylurea) may play a role in the relationship between type 2 diabetes and cancer. To quantify the association between metformin and sulfonylurea and the risk of cancer, we performed a meta-analysis of available studies on the issue.

Materials and Methods.

We performed a MEDLINE search for observational studies that investigated the risk of all cancers and specific cancer sites in relation to use of metformin and/or sulfonylurea among patients with type 2 diabetes mellitus. Fixed- and random-effect models were fitted to estimate the summary relative risk (RR). Between-study heterogeneity was tested using χ2 statistics and measured with the I2 statistic. Publication bias was evaluated using funnel plot and Egger's regression asymmetry test.

Results.

Seventeen studies satisfying inclusion criteria and including 37,632 cancers were evaluated after reviewing 401 citations. Use of metformin was associated with significantly decreased RR of all cancers (summary RR 0.61, 95% confidence interval [CI] 0.54–0.70), colorectal cancer (0.64, 95% CI 0.54–0.76), and pancreatic cancer (0.38, 95% CI 0.14–0.91). With the exception of colorectal cancer, significant between-study heterogeneity was observed. Evidence of publication bias for metformin-cancer association was also observed. There was no evidence that metformin affects the risk of breast and prostate cancers, nor that sulfonylurea affects the risk of cancer at any site.

Conclusions.

Metformin, but not sulfonylurea, appears to reduce subsequent cancer risk. This has relevant implications in light of the exploding global epidemic of diabetes.

Introduction

Type 2 diabetes is a condition affecting a substantial and increasing proportion of the population worldwide [1]. Much evidence has been accumulating to suggest that diabetes is associated with an increased risk of cancer [2]. The mechanisms are yet to be investigated, but insulin resistance with secondary hyperinsulinemia is the most frequently proposed hypothesis [3–5], although hyperglycemia itself seems to promote carcinogenesis [6].

Different mechanisms, activated by endogenous hyperinsulinemia or exogenous insulin, can promote cancer progression. First, insulin resistance may favor the availability of insulin-like growth factor (IGF-I), overactivating the IGF-I receptors, which may contribute to the cancerogenesis and cancer promotion in hyperinsulinemic patients [7]. Second, IGF-I might increase the risk of cancer through its anti-apoptotic activity [8]. Finally, insulin activity may affect the mitogenic pathways that include an overactivation of the mammalian target of rapamycin (mTOR) enzyme [9].

Consequently, the treatments that may cause hyperinsulinemia, such as sulfonylurea and exogenous insulin, are thought to increase the risk of cancer [10, 11]. Conversely, treatments that decrease insulin resistance, such as metformin, which act as growth inhibitors for epithelial cells by reducing mTOR activity, are thought to reduce the risk of cancer development [12–15].

The results from epidemiologic studies have been inconsistent, however, and the reasons underlying this heterogeneity, including differences between cancer sites, study populations, and design, need to be further investigated. In light of the increasing prevalence of patients under treatment with oral anti-diabetic drugs, efforts aimed at elucidating the association between use of these drugs and cancer risk have major implications for public health. With these premises, we performed a systematic review and meta-analysis of available studies to better define and quantify the effect of metformin and sulfonylurea on risk of cancer overall, as well as of different cancer sites, in patients with type 2 diabetes.

Materials and Methods

Search Strategy and Study Selection

We carried out a MEDLINE search of the literature to identify observational studies published up to May 2011 that investigated the association between metformin or sulfonylurea and cancer. The following keywords and/or corresponding MeSH terms were used: “diabetes mellitus, type 2” AND (“metformin” OR “sulfonylurea” OR “biguanides” OR “hypoglycemic agents”) AND (“neoplasms” OR “cancer”). In addition, the reference lists of reviews and meta-analyses published on this issue were hand-checked to identify additional relevant publications [2, 3, 16–18].

Inclusion and Exclusion Criteria

The search was restricted to observational studies due to the absence of meaningful data from randomized clinical trials. Studies were included if based on cohort or case-control design provided that they (a) specifically mentioned that participants were affected by type 2 diabetes mellitus; (b) investigated exposure to metformin and/or sulfonylurea; (c) assessed either the risk of all cancers (main outcome) or the risk of cancer at specific sites (secondary outcome), with the exclusion of studies including prevalent or recurrent cases of cancer; and (d) reported crude or adjusted estimates of the association between exposure and outcome (that is, relative risk [RR], odds ratio, hazard or rate ratio, and the corresponding 95% confidence interval [CI] or p-value), or sufficient raw data to allow their calculation. When data were published more than once, the most recent and complete publication was considered. Two readers (D.S. and L.S.) independently determined the eligibility of each article for inclusion. Discrepancies between readers were resolved in conference.

Data Collection

For each included study, we extracted details on study design, country, publication year, exposure and reference therapy (e.g., no use of metformin and no use of sulfonylurea, insulin, metformin, or sulfonylurea), cancer site, adjustment and stratification variables, number of cancer cases, exposure definition (monotherapy or use of more than one therapy), RR (or other association measures), and the corresponding 95% CI.

Statistical Methods

The summary RR for exposure to metformin or sulfonylurea was the measure of interest. Analyses were performed for specific reference therapies and cancer sites on condition that the corresponding estimates were reported by at least three studies. Whenever possible, we pooled adjusted estimates from the original studies; otherwise we used raw data and computed unadjusted RRs. We pooled the original estimates by using both the fixed-effects model and the random-effects model proposed by DerSimonian and Laird [19]. Under the fixed-effects model, it is assumed that there is one true effect size that is shared by all the included studies. It follows that the combined effect is the estimate of this common effect size. Conversely, in the random-effects model, the true effect could vary from study to study; thus, the study-specific estimates are assumed to be a random sample of the relevant distribution of effects, and the combined effect estimates the mean effect in this distribution. In this case, it is important to evaluate between-study variability and incorporate it in the summary-estimate calculation to provide a more accurate measure of the summary-estimate variability. Heterogeneity between study-specific estimates was tested using the Q statistic, which is computed by summing the weighted squared deviations of each study estimate from the fixed-effects summary estimate [20]. When a significant heterogeneity was found, the results from the random-effects model were presented. Moreover, the total variation across studies that is due to heterogeneity rather than chance was evaluated using the I2 statistic [21].

Between-study sources of heterogeneity were investigated by stratifying original estimates according to some study characteristics potentially relevant in causing heterogeneity, i.e., study design (cohort or case-control), geographic area (Europe, Asia, or North America), control for possible confounders (adjusted or unadjusted estimates), exposure definition (monotherapy versus use of more than one therapy), and reference therapy (any or specific other antidiabetic agent). In the presence of a significant summary RR, an influence analysis was conducted by omitting one study at a time, to identify to what extent the results were influenced by a single study. Finally, publication bias was evaluated through funnel plot analysis and the Egger's test [22].

For all hypothesis tests, evidence was based on p < .05, and the 95% CIs were therefore presented. The corresponding calculations and graphical visualizations of forest and funnel plots were respectively carried out using RevMan version 5.1 (Nordic Cochrane Center) and STATA Software Program version 9 (STATA, College Station, TX).

Results

Figure 1 shows the flow diagram for the study inclusion. On the basis of title and abstract, we identified 401 papers. We excluded 241 of them because they were not related to the study objective. The remaining 160 articles were considered of interest, and their full text was retrieved for detailed evaluation. Of these, 143 articles were further excluded because they did not satisfy the inclusion criteria. The remaining 17 studies [23–39] complied with the inclusion criteria and were considered for meta-analysis. The main characteristics of the studies included are reported in Table 1. They investigated the risk of cancer associated with use of both metformin and sulfonylurea (11 studies) or metformin alone (6 studies). They were based on 37,632 cancers at any site (3,931 cases, 7 studies), colon and rectum (972 cases, 5 studies), prostate (26,234 cases, 4 studies), pancreas (1,192 cases, 4 studies), breast (1,068 cases, 4 studies), or other specified sites (1,474 cases, 5 studies).

Figure 1.

Figure 1.

Open in a new tab

Flow chart of the selection of studies for inclusion in the meta-analysis.

Table 1.

Chronological summary of literature on oral antidiabetic medications (metformin and sulfonylurea) and cancer risk, and their main characteristics

graphic file with name onc00612-1079-t01.jpg

Open in a new tab

Table 1.

(Continued)

graphic file with name onc00612-1079-t01a.jpg

Open in a new tab

aPatients treated in monotherapy regimen.

Abbreviations: A1C, glycated hemoglobiņ BMI, body mass index; CCI, Charlson comorbidity index; CI, confidence interval; M, men; MW, men and women together; NSAID, nonsteroidal anti-inflammatory drugs; PSA, prostate-specific antigen; RR, relative risk; W, women.

Figure 2 shows the study-specific and summary RRs of cancer associated with metformin. The summary RRs and the corresponding 95% CIs were, respectively, 0.60 (95% CI, 0.50–0.73), 0.65 (95% CI, 0.50–0.83), and 0.56 (95% CI, 0.40–0.78) when the reference therapy was no use of metformin, sulfonylurea, and insulin. When all reference therapies taken together, the summary RR was 0.61 (95% CI, 0.54–0.70). In both cohort and case-control studies, a significant difference in the summary estimates was detected. However, no significant difference was found between summary estimates considering all reference categories together (p = .49). Moreover, a high between-study heterogeneity was found; in fact, the I2 statistic was 85% for metformin versus no use of metformin, 81% for metformin versus sulfonylurea, 86% for metformin versus insulin, and 84% for metformin versus all reference therapies. Among the sources of heterogeneity, the adjustment of original estimates significantly modified the investigated effect: RRs of 0.60 (0.55–0.73) and 0.34 (0.24–0.49) were observed, respectively, for adjusted and unadjusted estimates (p = .004).

Figure 2.

Figure 2.

Open in a new tab

Forest plot of study-specific relative risk estimates for any cancer site when comparing use of metformin versus various reference therapies by study design. Squares represent study-specific relative risk estimates (size of the square reflects the study-specific statistical weight, that is, the inverse of the variance); horizontal lines represent 95% CIs; diamonds represent summary relative risk estimates with corresponding 95% CIs; p-values are from testing for heterogeneity across study-specific estimates.

Abbreviations: CI, confidence interval; RR, relative risk.

The association between use of metformin and specific cancer sites is shown in Figure 3. A significant reduction of colorectal cancer risk was observed (summary RR, 0.64; 95% CI, 0.54–0.76), without any evidence of between-study heterogeneity (p = .291 and I2 = 19%). Also for pancreatic cancer there was evidence of significant risk reduction (summary RR, 0.38; 95% CI, 0.14–0.91), but significant between-study heterogeneity was noted (p < .001 and I2 = 89%). No differences were found between the summary estimate calculated using different exposure definition (monotherapy versus use of more than one therapy) for metformin (p = .33). Influence analysis showed that heterogeneity was in large part due to one study [24]; when omitting it, the I2 dropped to 28% and the summary RR dropped to 0.27 (95% CI, 0.18–0.40). There was no evidence that use of metformin is associated with the risk of breast and prostate cancers, with the summary RRs being 0.87 (95% CI, 0.69–1.10) and 0.92 (95% CI, 0.73–1.17), respectively. Significant between-study heterogeneity was noted for these two cancer sites, and the I2 statistics were 56% and 78%, respectively, for breast and prostate cancer.

Figure 3.

Figure 3.

Open in a new tab

Forest plot of study-specific relative risk estimates for use of metformin, versus all reference therapies, and specific sites of cancer. Squares represent study-specific relative risk estimates (size of the square reflects the study-specific statistical weight, that is, the inverse of the variance); horizontal lines represent 95% CIs; diamonds represent summary relative risk estimates with corresponding 95% CIs; p-values are from testing for heterogeneity between study-specific estimates.

Abbreviations: CI, confidence interval; RR, relative risk.

Figure 4 shows study-specific and summary RRs of cancer associated with use of sulfonylurea versus no use of sulfonylurea or insulin taken together stratified for study design. The summary RR was 0.97 (95% CI, 0.82–1.14) overall, 1.02 (95% CI, 0.90–1.17) for cohort studies, and 1.00 (95% CI, 0.76–1.33) for case-control studies. As for metformin, no differences between estimates were highlighted (p = .89). Significant between-study heterogeneity was noted with an I2 statistic of 72%. However, none of the investigated sources of heterogeneity showed evidence of modifying the pooled estimate. The evaluation of the difference between the summary estimates calculated using different exposure definition was not possible for sulfonylurea because only one study reported the use of this drug as monotherapy [24]. The summary associations for use of metformin and the risk of other cancer sites, for use of sulfonylurea and the risk of specific cancer sites, as well as for sulfonylurea compared with single reference therapies, were not considered because of the limited number of studies investigating these issues.

Figure 4.

Figure 4.

Open in a new tab

Forest plot of study-specific relative risk estimates for any site of cancer when comparing use of sulfonylurea versus all reference therapies. Squares represent study-specific relative risk estimates (size of the square reflects the study-specific statistical weight, that is, the inverse of the variance); horizontal lines represent 95% CIs; diamonds represent summary relative risk estimates with corresponding 95% CIs; p-values are from testing for heterogeneity between study-specific estimates.

Abbreviations: CI, confidence interval; RR, relative risk.

There was evidence of publication bias for studies investigating use of metformin and cancer risk either from visualization of the funnel plot (Fig. 5A) and from the corresponding Egger's test (p = .008), thus suggesting that studies reporting strong protective effects were more likely published. Conversely, visualization of the funnel plot (Fig. 5B) suggests that studies reporting an increased risk of cancer among sulfonylurea users are more frequently published, although the Egger's test (p = .102) does not detect the presence of publication bias for studies investigating the use of sulfonylurea and cancer.

Figure 5.

Figure 5.

Open in a new tab

Funnel plot for publication bias in the study investigating cancer risk associated with use of metformin (A) and sulfonylurea (B).

Abbreviations: RR, relative risk; SE, standard error.

Discussion

In this comprehensive meta-analysis, metformin was associated with a 39% significantly decreased risk of cancer compared with no use of metformin, whereas there was no evidence that sulfonylurea was associated with cancer risk. When specific cancer sites were analyzed separately, metformin was associated with a reduced risk of colorectal and pancreatic cancers of 36% and 62%, respectively. There was no evidence that use of metformin was associated with the risk of breast and prostate cancer.

Metformin might be associated with carcinogenesis through direct and indirect (reducing hyperinsulinemia and glycemic levels) mechanisms. Hyperinsulinemia was associated with increased cancer risk at many sites including colorectal, liver, gallbladder, pancreas, and endometrial [40–44]. High glycemic levels are also considered a risk factor for selected cancers including colon and breast [40, 41].

Consistently, high levels of C-peptide/insulin and glycemia have been associated with colorectal and pancreatic cancers in a recent meta-analysis [45]. Direct mechanisms have been also implicated in preclinical studies showing that metformin can inhibit the growth of cancer cell in vitro and in vivo [46–50]. It is therefore not surprising that the use of metformin is associated with a decreased risk of cancer, and in particular of colorectal and pancreatic cancer. The inverse relation for colorectal cancer was not noticed in a previous meta-analysis [16], which however included only three studies.

A protective effect of metformin on breast cancer was expected because metformin showed a significant growth cell inhibitory effect in mouse and cancer cell models. A study based on cell culture highlighted that metformin seems to inhibit the proliferation of cancer cells including breast cancer [9]. However, the results of this meta-analysis do not support a reduced risk of breast cancer in metformin users consistently with another meta-analysis [16].

To the best of our knowledge, no other meta-analyses have been performed on the use of sulfonylurea and cancer risk. Sulfonylurea has been associated with elevated cancer risk [27, 32, 51–53], but this might due to the nature of the comparator group. A large portion of patients who were not on therapy with sulfonylurea (that is, those included in the reference therapy group) were on metformin therapy, and increased cancer risk by comparing users of sulfonylurea with those on metformin is possible. On the other hand, a reduced cancer risk is expected by comparing sulfonylurea and other antidiabetic therapies, such as insulin. This is in line with the 46% risk reduction of hepatocellular carcinoma for users of sulfonylurea with respect to insulin users reported by the only study investigating the issue [31]. This possible association, however, should be further investigated.

As with all meta-analyses of observational studies, our results have some limitations. First, they are vulnerable to confounding inherent in the original studies. We investigated the heterogeneity resulting from adjustment of original estimates for confounders. Studies reporting unadjusted estimates found a higher protective effect for metformin than those reporting adjusted estimates. However, the clinical characteristics of diabetic patients treated with metformin are different from those of patients treated with other medications, and particularly those treated with insulin. Thus, even correcting for a large number of covariates, it is not possible to entirely eliminate the potential of residual confounding and, in particular, confounding by indication [54, 55]. Patients treated with metformin are likely to have less severe diabetes and/or shorter disease duration compared to patients treated with other antidiabetic drugs [56]. Consequently, we cannot exclude that part of the protective effect of metformin can be explained by confounding by indication. In the sulfonylurea studies, adjustment of estimates did not substantially modify the cancer risk, supporting the conclusion that there is no increased risk of cancer. Second, in the metformin studies, the comparator group consisted of diabetics treated with no metformin, insulin, or insulin secretagogues (sulfonylurea): the similarity of the results irrespective of the nature of the comparator suggests that this did not importantly affect our estimates. Third, the study populations included were heterogeneous, particularly with regard to their ethnicity. No evidence of heterogeneity was however noticed when we investigated the geographic area where the study was conducted (data not shown). Finally, we found evidence for selective inclusion of studies reporting higher protective effect of metformin on the cancer risk. The publication bias could be related to the use of MEDLINE as the only source for literature research, as well as to the exclusion of “grey literature” (for example, Ph.D. theses and conference abstracts) and of studies published in a language different from English.

Conclusion

The present meta-analysis offers quantitative evidence that oral antidiabetic drugs have different effects on cancer risk in patients with type 2 diabetes. In particular, important risk reductions for users of metformin, mainly for pancreatic and colorectal cancer, contrasted by a substantial independence from use of sulfonylurea, were noticed. Our findings, on the protective effect of metformin, confirm the findings reported in a previous meta-analysis based on 11 studies, reporting a total of 4,042 cancer events and 529 cancer deaths [16]. In light of the exploding global epidemic of diabetes, there is a pressing need for implementing diabetes treatment with potentially protective effect against cancer. Better-designed studies on the complex interactions between diabetes, diabetes therapies, and cancer are also urgently required.

Acknowledgments

This study was funded by grants from the Italian Ministry for University and Research (“Fondo d'Ateneo per la Ricerca”, 2010). The work of C.B. and C.L.V. was supported by the Italian Association for Research on Cancer (AIRC, grant n. 10068).

Footnotes

(C/A)
Consulting/advisory relationship
(RF)
Research funding
(E)
Employment
(H)
Honoraria received
(OI)
Ownership interests
(IP)
Intellectual property rights/inventor/patent holder
(SAB)
Scientific advisory board

Author Contributions

Conception/Design: Antonella Zambon, Giovanni Corrao

Collection and/or assembly of data: Davide Soranna, Lorenza Scotti

Data analysis and interpretation: Davide Soranna, Carlo La Vecchia, Lorenza Scotti, Antonella Zambon, Giuseppe Mancia, Giovanni Corrao

Data checking and editing: Carlo La Vecchia

Manuscript writing: Davide Soranna, Giovanni Corrao

Final approval of manuscript: Davide Soranna, Carlo La Vecchia, Lorenza Scotti, Antonella Zambon, Cristina Bosetti, Guido Grassi, Alberico Catapano, Giuseppe Mancia, Giovanni Corrao

References

  • 1.King H, Aubert RE, Herman WH. Global burden of diabetes, 1995–2025: prevalence, numerical estimates, and projections. Diabetes Care. 1998;21:1414–1431. doi: 10.2337/diacare.21.9.1414. [DOI] [PubMed] [Google Scholar]
  • 2.Noto H, Tsuijmoto T, Takehiko S, et al. Significantly increased risk of cancer in patients with diabetes mellitus: a systematic review and meta-analysis. Endocr Pract. 2011;17:616–628. doi: 10.4158/EP10357.RA. [DOI] [PubMed] [Google Scholar]
  • 3.Hernandez-Diaz S, Adami H-O. Diabetes and cancer risk: causal effects and other possible explanations. Diabetologia. 2010;53:802–808. doi: 10.1007/s00125-010-1675-2. [DOI] [PubMed] [Google Scholar]
  • 4.Stolar MW, Hoogwerf BJ, Gorshow SM, et al. Managing type 2 diabetes: going beyond glycaemic control. J Manag Care Pharm. 2008;14(5 suppl B):S2–S19. [PubMed] [Google Scholar]
  • 5.Krentz AJ, Bailey CJ. Oral antidiabetic agents: current role in type 2 diabetes mellitus. Drugs. 2005;65:385–411. doi: 10.2165/00003495-200565030-00005. [DOI] [PubMed] [Google Scholar]
  • 6.Barclay AW, Petocz P, McMillan-Price J, et al. Glycemic index, glycemic load, and chronic disease risk—a meta-analysis of observational studies. Am J Clin Nutr. 2008;87:627–637. doi: 10.1093/ajcn/87.3.627. [DOI] [PubMed] [Google Scholar]
  • 7.Belfiore A, Malaguarnera R. Insulin receptor and cancer. Endocr Relat Cancer. 2011;18:R125–R147. doi: 10.1530/ERC-11-0074. [DOI] [PubMed] [Google Scholar]
  • 8.Holly JMP, Gunnell DJ, Davey Smith G. Growth hormone, IGF-I and cancer. Less intervention to avoid cancer? More intervention to prevent cancer? J Endocrinol. 1999;162:321–330. doi: 10.1677/joe.0.1620321. [DOI] [PubMed] [Google Scholar]
  • 9.Dowling RJ, Goodwin PJ, Stambolic V. Understanding the benefit of metformin use in cancer treatment. BMC Med. 2011;9:33. doi: 10.1186/1741-7015-9-33. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Anisimov VN, Egormin PA, Berstein LM. Metformin decelerates aging and development of mammary tumors in HER-2/neu transgenic mice. Bull Exp Biol Med. 2005;139:721–723. doi: 10.1007/s10517-005-0389-9. [DOI] [PubMed] [Google Scholar]
  • 11.Berstein LM. Clinical usage of hypolipidemic and antidiabetic drugs in the prevention and treatment of cancer. Cancer Lett. 2005;224:203–212. doi: 10.1016/j.canlet.2004.11.011. [DOI] [PubMed] [Google Scholar]
  • 12.Zakikhani M, Dowling R, Fantus IG, et al. Metformin is an AMP kinase-dependent growth inhibitor for breast cancer cells. Cancer Res. 2006;66:10269–10273. doi: 10.1158/0008-5472.CAN-06-1500. [DOI] [PubMed] [Google Scholar]
  • 13.Stolzenberg-Solomon RZ, Graubard BI, Chari S, et al. Insulin, glucose, insulin resistance, and pancreatic cancer in male smokers. JAMA. 2005;294:2872–2878. doi: 10.1001/jama.294.22.2872. [DOI] [PubMed] [Google Scholar]
  • 14.Buzzai M, Jones RG, Amaravadi RK, et al. Systematic treatment with the antidiabetic drug metformin selectively impairs p53-deficient tumour cell growth. Cancer Res. 2007;67:6745–6752. doi: 10.1158/0008-5472.CAN-06-4447. [DOI] [PubMed] [Google Scholar]
  • 15.Wong AK, Howie J, Petrie JR, et al. AMP-activated protein kinase pathway: potential therapeutic target in cardiometabolic disease. Clin Sci (Lond) 2009;116:607–620. doi: 10.1042/CS20080066. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Decensi A, Puntoni M, Goodwin P, et al. Metformin and cancer risk in diabetic patients: a systematic review and meta-analysis. Cancer Prev Res (Phila) 2010;3:1451–1461. doi: 10.1158/1940-6207.CAPR-10-0157. [DOI] [PubMed] [Google Scholar]
  • 17.Johnson JA, Bowker SL. Intensive glycaemic control and cancer risk in type 2 diabetes: a meta-analysis of major trials. Diabetologia. 2011;54:25–31. doi: 10.1007/s00125-010-1933-3. [DOI] [PubMed] [Google Scholar]
  • 18.Jalving M, Gietema JA, Lefrandt JD, et al. Metformin: taking away the candy for cancer? Eur J Cancer. 2010;46:2369–2380. doi: 10.1016/j.ejca.2010.06.012. [DOI] [PubMed] [Google Scholar]
  • 19.DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials. 1986;7:177–188. doi: 10.1016/0197-2456(86)90046-2. [DOI] [PubMed] [Google Scholar]
  • 20.Cochran WG. The combination of estimates from different experiments. Biometrics. 1954;10:101–129. [Google Scholar]
  • 21.Higgins JPT, Thompson SG, Deeks JJ, et al. Measuring inconsistency in meta-analyses. BMJ. 2003;327:557–560. doi: 10.1136/bmj.327.7414.557. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Egger M, Smith DG, Schneider M, et al. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997;315:629–634. doi: 10.1136/bmj.315.7109.629. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Yang YX, Hennessy S, Lewis JD. Insulin therapy and colorectal cancer risk among type 2 diabetes mellitus patients. Gastroenterology. 2004;127:1044–1050. doi: 10.1053/j.gastro.2004.07.011. [DOI] [PubMed] [Google Scholar]
  • 24.Oliveria SA, Koro CE, Yood MU, et al. Cancer incidence among patients treated with antidiabetic pharmacotherapy. Diabetes Metab Syndrome: Clin Res Rev. 2007;2:47–57. [Google Scholar]
  • 25.Murtola TJ, Tammela TL, Lahtela J, et al. Antidiabetic medication and prostate cancer risk: a population-based case-control study. Am J Epidemiol. 2008;168:925–931. doi: 10.1093/aje/kwn190. [DOI] [PubMed] [Google Scholar]
  • 26.Currie CJ, Poole CD, Gale EA. The influence of glucose-lowering therapies on cancer risk in type 2 diabetes. Diabetologia. 2009;52:1766–1777. doi: 10.1007/s00125-009-1440-6. [DOI] [PubMed] [Google Scholar]
  • 27.Li D, Yeung SC, Hassan MM, et al. Antidiabetic therapies affect risk of pancreatic cancer. Gastroenterology. 2009;137:482–488. doi: 10.1053/j.gastro.2009.04.013. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Libby G, Donnelly LA, Donnan PT, et al. New users of metformin are at low risk of incident cancer: a cohort study among people with type 2 diabetes. Diabetes Care. 2009;32:1620–1625. doi: 10.2337/dc08-2175. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Bodmer M, Meier C, Krähenbühl S, et al. Long-term metformin use is associated with decreased risk of breast cancer. Diabetes Care. 2010;33:1304–1308. doi: 10.2337/dc09-1791. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Bowker SL, Yasui Y, Veugelers P, et al. Glucose-lowering agents and cancer mortality rates in type 2 diabetes: assessing effects of time-varying exposure. Diabetologia. 2010;53:1631–1637. doi: 10.1007/s00125-010-1750-8. [DOI] [PubMed] [Google Scholar]
  • 31.Donadon V, Balbi M, Mas MD, et al. Metformin and reduced risk of hepatocellular carcinoma in diabetic patients with chronic liver disease. Liver Int. 2010;30:750–758. doi: 10.1111/j.1478-3231.2010.02223.x. [DOI] [PubMed] [Google Scholar]
  • 32.Hassan MM, Curley SA, Li D, et al. Association of diabetes duration and diabetes treatment with the risk of hepatocellular carcinoma. Cancer. 2010;116:1938–1946. doi: 10.1002/cncr.24982. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Landman GW, Kleefstra N, van Hateren KJ, et al. Metformin associated with lower cancer mortality in type 2 diabetes: ZODIAC-16. Diabetes Care. 2010;33:322–326. doi: 10.2337/dc09-1380. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Azoulay L, Dell'Aniello S, Gagnon B, et al. Metformin and the incidence of prostate cancer in patients with type 2 diabetes. Cancer Epidemiol Biomarkers Prev. 2011;20:337–344. doi: 10.1158/1055-9965.EPI-10-0940. [DOI] [PubMed] [Google Scholar]
  • 35.Bosco JL, Antonsen S, Sørensen HT, et al. Metformin and incident breast cancer among diabetic women: a population-based case-control study in Denmark. Cancer Epidemiol Biomarkers Prev. 2011;20:101–111. doi: 10.1158/1055-9965.EPI-10-0817. [DOI] [PubMed] [Google Scholar]
  • 36.Lee MS, Hsu CC, Wahlqvist ML, et al. Type 2 diabetes increases and metformin reduces total, colorectal, liver and pancreatic cancer incidences in Taiwanese: a representative population prospective cohort study of 800,000 individuals. BMC Cancer. 2011;11:20. doi: 10.1186/1471-2407-11-20. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Monami M, Colombi C, Balzi D, et al. Metformin and cancer occurrence in insulin-treated type 2 diabetic patients. Diabetes Care. 2011;34:129–131. doi: 10.2337/dc10-1287. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Tseng CH. Diabetes and risk of prostate cancer: a study using the National Health Insurance. Diabetes Care. 2011;34:616–621. doi: 10.2337/dc10-1640. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Yang X, So WY, Ma RC, et al. Low HDL cholesterol, metformin use, and cancer risk in type 2 diabetes: the Hong Kong Diabetes Registry. Diabetes Care. 2011;34:375–380. doi: 10.2337/dc10-1509. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Giovannucci E. Metabolic syndrome, hyperinsulinemia, and colon cancer: a review. Am J Clin Nutr. 2007;86:836s–842s. doi: 10.1093/ajcn/86.3.836S. [DOI] [PubMed] [Google Scholar]
  • 41.Hsu IR, Kim SP, Kabir M, et al. Metabolic syndrome, hyperinsulinemia, and cancer. Am J Clin Nutr. 2007;86:s867–s871. doi: 10.1093/ajcn/86.3.867S. [DOI] [PubMed] [Google Scholar]
  • 42.Giovannucci E, Michaud D. The role of obesity and related metabolic disturbances in cancers of the colon, prostate, and pancreas. Gastroenterology. 2007;132:2208–2225. doi: 10.1053/j.gastro.2007.03.050. [DOI] [PubMed] [Google Scholar]
  • 43.Garmendia ML, Pereira A, Alvarado ME, et al. Relation between insulin resistance and breast cancer among Chilean women. Ann Epidemiol. 2007;17:403–409. doi: 10.1016/j.annepidem.2007.01.037. [DOI] [PubMed] [Google Scholar]
  • 44.Grote VA, Becker S, Kaaks R. Diabetes mellitus type 2–an independent risk factor for cancer? Exp Clin Endocrinol Diabetes. 2010;118:4–8. doi: 10.1055/s-0029-1243193. [DOI] [PubMed] [Google Scholar]
  • 45.Pisani P. Hyper-insulinaemia and cancer, meta-analyses of epidemiological studies. Arch Physiol Biochem. 2008;114:63–70. doi: 10.1080/13813450801954451. [DOI] [PubMed] [Google Scholar]
  • 46.Alessi DR, Sakamoto K, Bayascas JR. LKB1-dependent signaling pathways. Annu Rev Biochem. 2006;75:137–163. doi: 10.1146/annurev.biochem.75.103004.142702. [DOI] [PubMed] [Google Scholar]
  • 47.Towler MC, Hardie DG. AMP-activated protein kinase in metabolic control and insulin signaling. Circ Res. 2007;100:328–341. doi: 10.1161/01.RES.0000256090.42690.05. [DOI] [PubMed] [Google Scholar]
  • 48.Steinberg GR, Macaulay SL, Febbraio MA, et al. AMP-activated protein kinase–the fat controller of the energy railroad. Can J Physiol Pharmacol. 2006;84:655–665. doi: 10.1139/y06-005. [DOI] [PubMed] [Google Scholar]
  • 49.Palacios OM, Carmona JJ, Michan S, et al. Diet and exercise signals regulate SIRT3 and activate AMPK and PGC-1alpha in skeletal muscle. Aging (Albany NY) 2009;1:771–783. doi: 10.18632/aging.100075. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Inoki K, Zhu T, Guan KL. TSC2 mediates cellular energy response to control cell growth and survival. Cell. 2003;115:577–590. doi: 10.1016/s0092-8674(03)00929-2. [DOI] [PubMed] [Google Scholar]
  • 51.Bowker SL, Majumdar SR, Veugelers P, et al. Increased cancer-related mortality for patients with type 2 diabetes who use sulfonylureas or insulin. Diabetes Care. 2006;29:254–258. doi: 10.2337/diacare.29.02.06.dc05-1558. [DOI] [PubMed] [Google Scholar]
  • 52.Monami M, Luzzi C, Lamanna C, et al. Three-year mortality in diabetic patients treated with different combinations of insulin secretagogues and metformin. Diabetes Metab Res Rev. 2006;22:477–482. doi: 10.1002/dmrr.642. [DOI] [PubMed] [Google Scholar]
  • 53.Monami M, Balzi D, Lamanna C, et al. Are sulfonylureas all the same? A cohort study on cardiovascular and cancer-related mortality. Diabetes Metab Res Rev. 2007;23:479–484. doi: 10.1002/dmrr.736. [DOI] [PubMed] [Google Scholar]
  • 54.Pocock SJ, Smeeth L. Insulin glargine and malignancy: an unwarranted alarm. Lancet. 2009;374:511–513. doi: 10.1016/S0140-6736(09)61307-6. [DOI] [PubMed] [Google Scholar]
  • 55.La Vecchia C. Diabetes mellitus, medications for type 2 diabetes mellitus, and cancer risk. Metabolism. 2011;60:1357–1358. doi: 10.1016/j.metabol.2011.03.011. [DOI] [PubMed] [Google Scholar]
  • 56.Aguilar D, Chan W, Bozkurt B, et al. Metformin use and mortality in ambulatory patients with diabetes and heart failure. Circ Heart Fail. 2011;4:53–58. doi: 10.1161/CIRCHEARTFAILURE.110.952556. [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from The Oncologist are provided here courtesy of Oxford University Press

RESOURCES