European Journal of Cancer (2014) 50, 2119– 2125
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Current Perspective
Diabetes and cancer: 5 years into the recent controversy Ellena Badrick a, Andrew G. Renehan b,⇑ a b
Institute of Population Health, University of Manchester, Manchester, UK Institute of Cancer Sciences, University of Manchester, Manchester, UK
Received 3 March 2014; received in revised form 10 April 2014; accepted 12 April 2014 Available online 11 June 2014
KEYWORDS Diabetes Cancer Insulin Metformin Immortal time bias Incidence risk
Abstract Diabetes and cancer are common chronic disorders. The literature has long recognised that type 2 diabetes (T2D) is associated with an increased incident risk of several cancer types, independent of the mutual risk factor, obesity. However, in June 2009, four papers were published simultaneously in Diabetologia, the official journal of the European Association for the Study of Diabetes, raising questions of a link between diabetes therapies, notably the long-acting insulin analogue, glargine, and increased cancer risk. These papers awakened an unprecedented debate in the diabetes community, drawing in cancer experts and bringing together representatives from these two large, traditionally non-intersecting, biomedical communities. This Current Perspective summarises the events that followed the ‘breaking news’ from summer 2009: the pitfalls encountered; the increased mutual understanding between diabetes and cancer researchers; and the direction of current research. Much of the debate on the clinical impact of this controversy has been played out in the diabetes literature: here, we update the oncology readership. Ó 2014 Published by Elsevier Ltd.
1. Background Diabetes and cancer are common chronic disorders. In Europe, there are 55.4 million individuals living with ⇑ Corresponding author: Address: Department of Surgery, University of Manchester, Manchester Academic Health Science Centre, The Christie NHS Foundation Trust, Wilmslow Road, Manchester M20 4BX, UK. Tel.: +44 161 446 3157. E-mail address: [email protected] (A.G. Renehan).
http://dx.doi.org/10.1016/j.ejca.2014.04.032 0959-8049/Ó 2014 Published by Elsevier Ltd.
diabetes, mainly type 2 diabetes (T2D) [1]; while there are an estimated 3.5 million new cancer cases per year [2]. Estimates of co-occurrence of prevalent diabetes and cancer are likely to be age-, sex-, population and cancer-type specific but, for example, in a study from the Eindhoven Cancer Registry, the prevalence of diabetes was highest among patients with cancer of the pancreas (19%), uterus (14%) and among young men with kidney cancer (8%) [3].
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A link between these two common diseases has been noted for at least 100 years [4], but diabetes-cancer associations were only glimpsed at as secondary findings over that century, and the topic seldom reached mainstream interest. However, in June 2009, a controversy erupted after four epidemiological studies [5–8] evaluating links between diabetes therapies and cancer were published simultaneously in Diabetologia, the official journal of the European Association for the Study of Diabetes (EASD). The controversy started when the lead paper, from Hemkens and colleagues [7], raised concerns that the long-acting insulin analogue, glargine, was associated with increased risk of subsequent cancer, particularly breast cancer, in a dose–response manner. This epidemiological observation was supported by well-established laboratory evidence showing that, as a result of molecular engineering, insulin glargine takes on structural characteristics similar to those for insulin-like growth factor (IGF)-I, and is more mitogenic than human (natural) insulin in in vitro assays [9]. The journal faced a difficult editorial challenge in that the Hemken paper [7] had evident methodological limitations but addressed an important clinical topic for the first time. The editor thus commissioned three other research groups to analyse their respective cohorts. The net result was that three [5,7,8] of the four synchronously published papers speculated links between glargine and increased cancer risk, in at least some of their analyses. In retrospect, all four studies had design limitations and it was not possible to draw firm conclusions [10]. Nonetheless, the studies initially left the diabetes community bewildered and confused [11], but positive outcomes subsequently emerged. This Current Perspective summarises the events that followed the ‘breaking news’ from summer 2009.
2. Drawing together experts from cancer and diabetes One of the first constructive consequences was the coming together of experts from diabetes and cancer. This was most visible in the form of a consensus document written under the joint auspices of the American Diabetes Association and American Cancer Society, and with representations from other US endocrine organisations, the EASD, and the European Cancer Organisation (ECCO) [12]. The meeting reached broad consensus and set research directions, but also accepted that there were several complexities ahead – for example, the methodological challenges of disentangling the relative importance of diabetes treatments, other (confounding) risk factors and cancer risk [13]. A parallel development was the formation of the Diabetes and Cancer Research Consortium (DCRC), an international group mainly focusing on pharmaco-epidemiological queries in the complex relationships between diabetes, anti-diabetes therapies and cancer, but with a key aim to develop and optimise methodological
approaches required to address these complexities. The group published two framework papers: one on cancer incidence [14], the other on cancer mortality [15]. Two important methodological features were emphasised: (i) accounting for detection time bias; and (ii) setting-up data to account for time-varying exposures. Detection time bias results in exaggerated risk associations due to increased surveillance around the time of diagnosis of diabetes or cancer, or occasionally due to reverse causality (for example, pancreatic cancer presenting as diabetes). Time-varying exposures refer to real-life variation in prescription of medications with time, and may result in false risk associations in either positive or inverse directions. Further methodological work from DCRC members came when Walker and colleagues [16] summarised the problems of capturing drug exposure from observational datasets and described optimal methodology to reduce bias. For instance, they illustrated that different drugs are administered to control glucose as T2D progresses, making direct ‘trial-like’ comparisons between drug classes uninterpretable – in this setting, the use of ever/never drug exposure categories only should be avoided, and cumulative exposure handled statistically as a time-varying covariate.
3. Insulin analogues and cancer risk Following 2009, several observational studies evaluated the putative link between insulin glargine and cancer risk. Meta-analyses of these observational studies followed: six of these reviews are summarised in Table 1 [17–22]. In general, there are many inconsistencies in the findings of these meta-analyses. In turn, these reflect important design differences in the included studies. For example, some studies evaluated any insulin use versus non-insulin therapies in patients with diabetes; while others evaluated glargine versus non-glargine insulin use. As insulins are generally prescribed late in the course of diabetes, patients are older and ‘sicker’ and not surprisingly these biases result in an apparent increased cancer risk. None of the meta-analyses directly addressed the problem of time-related biases (detailed below in relation to metformin and cancer risk). For similar reasons, lumping data from case-controls with cohorts is particularly problematic; although, it is possible to take account of time-varying exposure in case-control studies, this is seldom done. The publication of the ORIGIN trial in 2012 potentially brought a clearer picture. This trial randomly assigned 12,537 patients with impaired glucose tolerance or type 2 diabetes to receive insulin glargine versus standard care [23]; the largest trial of its type. Although the protocol end-points were cardiovascular non-fatal events or deaths, following the concerns raised by the 2009 papers, the investigators additionally detailed risk per cancer type by treatment allocation. There were no differences between treatment arms for all cancer
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Table 1 Summary of systematic reviews and meta-analyses of observational studies of the effect of insulin therapies on cancer risk. Author (year)
Specific question
No. of studies
No. of cancers
Summary estimates Overall cancers (RR: 95% CIs)
Specific cancers (RR: 95% CIs)
Janghorbani et al. (2012) [20] Isfahan, Iran
Any insulin versus no insulin.
Fifteen studies (five case-control and ten cohort studies)
14,085
RR: 1.39, 95%CI: 1.14, 1.70
Pancreatic: (RR: 4.78, 95%CI: 3.12, 7.32) Colorectal: (RR: 1.50, 95%CI: 1.08, 2.08) No association with breast, prostate and hepatocellular cancers. Breast: (RR: 1.14, 95%CI: 0.65–2.02) Prostate: (RR: 1.00, 95%CI: 0.79–1.26) Pancreatic: (RR: 0.57, 95%CI: 0.14–2.35) Breast: (OR: 0.99, 95%CI: 0.68–1.46) No association between insulin glargine and prostate, pancreatic and respiratory tract cancers. Pancreatic: (RR: 1.63, 95%CI: 1.05–2.51); Prostate: (RR: 2.68, 95%CI: 1.50–4.79); Colorectal: (RR: 0.78, 95%CI: 0.64–0.94) 27 cancer sites. Increased risk for pancreatic and colorectal cancer; no increase for breast and prostate. For glargine versus nonglargine: decreased risk for colon cancer. Versus other glucoselowering agents (RR = 0.89, 95% CI: 0.72– 1.09). Glargine versus nonglargine: (RR = 1.26, 95% CI: 0.86–1.84).
Du et al. (2012) [19] Nanjing, China
Insulin glargine versus non-glargine
Seven cohorts
Tang et al. (2012) [22] Gansu, China
Insulin glargine versus non-glargine
10 cohorts: 1 c.c.
19,128
Colmers et al. (2012) [18] Alberta, Canada Karlstad et al. (2013) [21] Olso, Norway
Any insulin versus no insulin. Reported by new users
19 cohorts and nested c.c.
41,947
Any insulin versus no insulin. Also examined glargine versus non-glargine
34 analysable studies: 27 cohorts; 15 c.c.
Chen et al. (2013) [17] Shanghai, China
Limited to prostate (PCa) cancer risk
10 cohorts: 1 c.c.
RR: 0.86, 95%CI: 0.69–1.07
OR: 0.81, 95%CI: 0.68–0.98
Increased overall cancer incidence
7,053
Concluding remarks
‘Association between insulin use and increased risk of overall, pancreatic, and colorectal cancers’
‘No support of an increased cancer risk in patients treated with insulin glargine’
‘No support of a link between insulin glargine and an increased risk of cancer’
‘Interpretation with caution’
‘Study design has profound effect on estimated cancer risk’
‘No association between insulin use and risk of PCa’
RR, risk ratio; OR, odds ratio; CI, confidence interval; c.c.: case-control studies.
incidence or deaths, and no differences between treatment arms for specific reported cancer types. These data seemed definitive, leading some commentators to suggest ‘closure’ on this topic [24]. However, there are caveats to the interpretation of the ORIGIN trial and cancer risk. First, although median follow-up was 6.2 years, there is a rapid drop-off thereafter such that only 14% of recruited patients were followed to the seventh year (Fig. 1). Many cancer epidemiologists would consider this lag period too short to assess associations between an exposure and cancer incidence. Second, there was considerable contamination across the arms – 16.7% of patients in the experimental arm discontinued glargine;
while 11.5% of patients in the standard arm commenced some insulin by the end of the study follow-up. 4. Metformin and cancer risk Almost as an incidental ‘by-product’ of the pharmaco-epidemiological analyses of insulin analogues and cancer risk, attention was directed to the observation that metformin may be associated with a reduced risk of cancer. In an era when oncologists are encouraged to repurpose inexpensive licensed drugs, metformin seemed a strong candidate, and led one UK mainstream newspaper to headline ‘A diabetes pill that costs just 2p
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E. Badrick, A.G. Renehan / European Journal of Cancer 50 (2014) 2119–2125 7000
Median FU
6000
No. of patients
5000 4000 3000 2000
Exposed to glargine
1000
Non-glargine exposure (standard care)
0 0
1
2
3 Years
4
5
6
7
Fig. 1. Follow-up ‘drop-off’ by treatment allocation in the ORIGIN trial. The numbers per arm have taken account of the numbers followed after randomisation minus those cases that discontinued glargine in the intervention arm, and commenced insulin in the standard care arm. FU: follow-up. Drawn from data in Table 2, Ref. [13].
a day could prevent thousands dying from Britain’s biggest cancer killers’ [25]. However, we now understand that many of the earlier epidemiological studies contained time-related biases that artificially made metformin look ‘protective’. Most important of these is immortal time bias. This statistical pitfall is conceptually difficult and perhaps not well appreciated by many researchers. The bias occurs when the analysis mismatches exposure in two comparison groups. Individuals have to survive to the start of exposure – hence, the name of ‘immortal’. The result is an advantage to the users of the drug of interest when the analysis is simply categorised by ever/never use. This was well illustrated by Suissa and colleagues [26] – they found that immortal time bias was prevalent among many studies that reported a reduced cancer risk associated with metformin use. By contrast, those studies that used methods to avoid these biases reported no effect of metformin use on cancer incidence. A further pitfall to interpretation is treatment allocation bias. For example, metformin is first line treatment for diabetes, and is therefore used earlier in the disease course than other medications. Those who achieve control with metformin alone differ in disease severity from those who require additional medication. Differential allocation of drugs based on such confounding factors tends to exaggerate the benefits of metformin. Differential allocation is an inevitable bias in observational studies and has to be addressed within a randomised trial framework. Primary cancer prevention trials are currently impractically huge and thus investigators have selected to test the hypothesis that metformin is cancer protective in the secondary prevention setting. An example is an adjuvant trial in early breast cancer, NCIC MA.32, with a primary end-points of 5-year invasive cancer-free survival [27]. The recruitment target (3582
women without diabetes) was completed in early 2013 – the results of this trial are eagerly awaited. The third key lesson from the story of metformin and cancer lies in the pharmacokinetics. There are now many laboratories across the globe exploring the role of metformin in cancer, and several novel anti-cancer mechanisms have been demonstrated. However, it has become clear that many preclinical studies use concentrations of metformin considerably higher than those safely obtained in the clinical setting (Fig. 2) [28]. The doses of metformin currently used in many oncology trials are those shown to be effective for glucose control; there is a need to establish the appropriate dose of metformin for its proposed anti-cancer effects. 5. Other anti-diabetes therapies and cancer As investigators examined their databases, they stumbled upon the observation that use of pioglitazone, a thiazolidinedione (used as 2nd or 3rd line therapy in T2D), might be associated with increased risk of bladder cancer. This drug causes bladder cancer in dogs, but by mechanisms which may not apply to humans. The initial epidemiological studies were based on relatively crude analyses of health insurance system databases with small numbers of bladder cancer cases – nonetheless the drug regulation authorities in France and Germany withdrew this agent in June 2011. Since then, there have been at least three large published analyses from – the General Practice Research Database, UK [29], Systeme National d’Information Inter-regimes de l’Assurance Maladie, France [30] and the Kaiser Permanente Northern California (KPNC) diabetes registry [31] – with large numbers of bladder cancer cases, and all suggesting an increased risk. However, here again, there may be biases clouding the interpretation. Recent updated analyses [32] of the KPNC cohort study of pioglitazone and Metformin concentrations
Standard clinical use
In vivo preclinical studies
In vitro laboratrory studies
Dose
250 to 2250 mg/day
750 mg/kg per day
2 to 50 mM
Relative Dose*
0.15 to 1.0
2 to 45
25 to 1000
Fig. 2. Concentrations of metformin used in laboratory studies. Clinical and epidemiological studies utilise metformin doses of up to 2250 mg/day. Conversely, in vivo preclinical and in vitro studies often involve extremely high, non-physiological concentrations of metformin that are in excess of the therapeutic levels safely achieved in human patients. Adopted from Ref. [18]. *Relative to standard clinical use.
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bladder cancer show that when there is adjustment for albuminuria (as a surrogate for subsequent cystoscopic investigation), the increased risk essentially disappears. These new analyses suggest that the bladder cancer association might be due to ascertainment (heightened investigations) bias [33]. Further confirmatory studies are required to this question. Incretin-based glucose-lowering medications were introduced to the US in 2005 and have proven to be effective glucose-lowering agents – both as glucagon-like peptide 1 (GLP-1) receptor agonists and as dipeptidyl peptidase 4 (DPP-4) inhibitors. Here again, over recent years, there have been cancer safety concerns. In animal models, both classes may promote acute pancreatitis, and initiate histological changes suggestive of subclinical chronic pancreatitis with associated pre-neoplastic lesions (for example, ductal proliferation), and potentially, in the long run, induce pancreatic cancer [34]. There may be additional risks for thyroid cancer. These data are challenging to interpret for several reasons: long-term use of incretin-based glucose-lowering is limited; it is unclear whether or not pre-clinical animal model data translate directly to human cancer development; and whether there had been adequate modelling to take account of the biases and confounding outlined in the early paragraphs. 6. What is the role of obesity in the controversy? One final area for consideration is the role played by change in body mass index (BMI), and other adiposity indicators, during the course of diabetes development
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and progression, as excess BMI is an established risk factor for several cancer types [35]. There is a continuing need to disentangle the effects of obesity versus diabetes and disease end-points, and this is equally true for cancer end-points. A relatively new dimension to this relationship is that several studies have observed that BMI at the time of diabetes diagnosis has a U-shaped relationship with mortality [36,37] – the ‘obesity paradox’ – and in turn, this relationship may be modified by smoking status [38]. It is well recognised clinically that weight among patients with diabetes varies considerably over years – thus, there is a need to develop more sophisticated time-varying, yet clinically-relevant, models to account for these ‘real-world’ relationships. 7. Future directions It is evident that, over the last 5 years, the interrogation of epidemiological databases to assess the relations between diabetes, anti-diabetes therapies and cancer has produced a large number of studies, and that these have in general shown regression towards the null: i.e. that both positive and inverse drug effects have tended to diminish as methodologies improve and further studies are undertaken. The coming together of experts from different fields and the linking together of databases has been very positive, and networks and platforms are now in place to address some of the major gaps for future research, as outlined in Box 1. So what do these wide ranging observations mean for day-to-day clinical oncology practice? Oncologists should be aware that T2D patients are at increased risk
Box 1 Diabetes and cancer: research gaps. 1
2
3
4
5
There are broadly five domains to consider. The examples are illustrative – these are not an exhaustive list. Translational science 1.1. There is a need to establish animal models that mimic human diabetes and facilitate evaluation of treatments and pathological states (hyperinsulinaemia and hyperglycaemia) that may affect cancer predisposition and progression. 1.2. In vitro models are needed to consider effects of glucose-lowering agents in early, as well as late, transformed neoplastic cells. 1.3. There is a need to distinguish the pharmacodynamic and pharmacokinetic parameters required for cancer-modifying versus glucoselowering effects of anti-diabetes therapies. Epidemiology of cancer risk 2.1. There is a continued need to disentangle the effects of adiposity versus T2D per se on cancer risk. Mendelian randomisation may offer one methodological approach. 2.2. There is a continued need to perform ‘good’ pharmacoepidemiology, with appropriate capture of cumulative exposure, long follow-up and use of time-varying statistical approaches. Clinical study in patients with cancer and diabetes 3.1. For some cancers, there is evidence that patients with T2D present with more advanced disease, receive sub-optimal treatment, and have poorer oncological outcomes. 3.2. There is a need to test the hypothesis that patients with T2D have reduced quality of life after cancer treatment. 3.3. There is a need to better quantify the relationships in 3.1 and 3.2; link these to lifestyle influences (e.g. physical activity), treatment morbidity and patient-related outcomes (PROMs). Interventional trials 4.1. Within new and on-going trials of glucose-lowering agents, and other interventions (for example, weight reduction programmes) in patients with impaired glucose tolerance or type 2 diabetes, there is a need to include long-term cancer end-points. 4.2. Key findings derived from (1) to (3) above should be considered for validation within the setting of randomised prospective trials. Global burden and cost 5.1. There is a need to develop methods to appropriately assign attribution of T2D to cancer risk to derive country-level burden of disease (cancer attributed to diabetes). In turn, this will allow monitoring of the effect of population-level interventions. 5.2. There is a need to establish the economic burden of cancer attributed to diabetes.
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of several common cancer types compared with the general population. This does not translate into a need for more intensive cancer screening. Rather, there is evidence that patients with T2D under-utilise national screening programmes [39] – oncologists should enquire after these activities. Additionally, among patients with diabetes who develop cancer, treatment and outcomes may be sub-optimal [40] – this needs to be better quantified and reversed. The continued exploration of metformin as an anti-cancer agent in the laboratory should be encouraged. From the diabetes point of view, there is no call for changes in clinical practice in terms of glucose-lowering drugs. Cancer risk can be considered negligibly small or absent with long-acting insulin analogues. When prescribing pioglitazone, the clinician needs to be mindful of patients with a history or predisposition to bladder cancer. For incretin-based medications, the evidence currently is too immature to impact on clinical practice, but further studies are needed. Researchers across diabetes and cancer communities must continue to collaborate, design trials, and explore new and existing databases, especially where outcomes are rare. Finally, journal editors in the diabetes and cancer fields must be aware of methodological pitfalls and support the pursuit of unbiased interpretations. Competing interests A.G. Renehan has received lecture honoraria and independent research funding from Novo Nordisk. Conflict of interest statement None declared. Acknowledgements We would like to acknowledge the critical appraisal of this manuscript by Professor E.A.M. Gale, former editor-in-chief of Diabetologia. He also contributed to the exactness of the narration of events around the ‘breaking news’ in June 2009. References [1] IDF. International Diabetes Federation, Diabetes Atlas, 6th ed. http://www.idf.org/diabetesatlas/europe [accessed 17 Feb 2014]. [2] Ferlay J, Steliarova-Foucher E, Lortet-Tieulent J, Rosso S, Coebergh JW, Comber H, et al. Cancer incidence and mortality patterns in Europe: estimates for 40 countries in 2012. Eur J Cancer 2013;49(6):1374–403. [3] van de Poll-Franse LV, Houterman S, Janssen-Heijnen ML, Dercksen MW, Coebergh JW, Haak HR. Less aggressive treatment and worse overall survival in cancer patients with diabetes: a large population based analysis. Int J Cancer 2007;120(9):1986–92. [4] Greenwood M, Wood F. The Relation between the Cancer and Diabetes Death-rates. J Hyg (Lond) 1914;14(1): 83–118.
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Current Perspective
Diabetes and cancer: 5 years into the recent controversy Ellena Badrick a, Andrew G. Renehan b,⇑ a b
Institute of Population Health, University of Manchester, Manchester, UK Institute of Cancer Sciences, University of Manchester, Manchester, UK
Received 3 March 2014; received in revised form 10 April 2014; accepted 12 April 2014 Available online 11 June 2014
KEYWORDS Diabetes Cancer Insulin Metformin Immortal time bias Incidence risk
Abstract Diabetes and cancer are common chronic disorders. The literature has long recognised that type 2 diabetes (T2D) is associated with an increased incident risk of several cancer types, independent of the mutual risk factor, obesity. However, in June 2009, four papers were published simultaneously in Diabetologia, the official journal of the European Association for the Study of Diabetes, raising questions of a link between diabetes therapies, notably the long-acting insulin analogue, glargine, and increased cancer risk. These papers awakened an unprecedented debate in the diabetes community, drawing in cancer experts and bringing together representatives from these two large, traditionally non-intersecting, biomedical communities. This Current Perspective summarises the events that followed the ‘breaking news’ from summer 2009: the pitfalls encountered; the increased mutual understanding between diabetes and cancer researchers; and the direction of current research. Much of the debate on the clinical impact of this controversy has been played out in the diabetes literature: here, we update the oncology readership. Ó 2014 Published by Elsevier Ltd.
1. Background Diabetes and cancer are common chronic disorders. In Europe, there are 55.4 million individuals living with ⇑ Corresponding author: Address: Department of Surgery, University of Manchester, Manchester Academic Health Science Centre, The Christie NHS Foundation Trust, Wilmslow Road, Manchester M20 4BX, UK. Tel.: +44 161 446 3157. E-mail address: [email protected] (A.G. Renehan).
http://dx.doi.org/10.1016/j.ejca.2014.04.032 0959-8049/Ó 2014 Published by Elsevier Ltd.
diabetes, mainly type 2 diabetes (T2D) [1]; while there are an estimated 3.5 million new cancer cases per year [2]. Estimates of co-occurrence of prevalent diabetes and cancer are likely to be age-, sex-, population and cancer-type specific but, for example, in a study from the Eindhoven Cancer Registry, the prevalence of diabetes was highest among patients with cancer of the pancreas (19%), uterus (14%) and among young men with kidney cancer (8%) [3].
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A link between these two common diseases has been noted for at least 100 years [4], but diabetes-cancer associations were only glimpsed at as secondary findings over that century, and the topic seldom reached mainstream interest. However, in June 2009, a controversy erupted after four epidemiological studies [5–8] evaluating links between diabetes therapies and cancer were published simultaneously in Diabetologia, the official journal of the European Association for the Study of Diabetes (EASD). The controversy started when the lead paper, from Hemkens and colleagues [7], raised concerns that the long-acting insulin analogue, glargine, was associated with increased risk of subsequent cancer, particularly breast cancer, in a dose–response manner. This epidemiological observation was supported by well-established laboratory evidence showing that, as a result of molecular engineering, insulin glargine takes on structural characteristics similar to those for insulin-like growth factor (IGF)-I, and is more mitogenic than human (natural) insulin in in vitro assays [9]. The journal faced a difficult editorial challenge in that the Hemken paper [7] had evident methodological limitations but addressed an important clinical topic for the first time. The editor thus commissioned three other research groups to analyse their respective cohorts. The net result was that three [5,7,8] of the four synchronously published papers speculated links between glargine and increased cancer risk, in at least some of their analyses. In retrospect, all four studies had design limitations and it was not possible to draw firm conclusions [10]. Nonetheless, the studies initially left the diabetes community bewildered and confused [11], but positive outcomes subsequently emerged. This Current Perspective summarises the events that followed the ‘breaking news’ from summer 2009.
2. Drawing together experts from cancer and diabetes One of the first constructive consequences was the coming together of experts from diabetes and cancer. This was most visible in the form of a consensus document written under the joint auspices of the American Diabetes Association and American Cancer Society, and with representations from other US endocrine organisations, the EASD, and the European Cancer Organisation (ECCO) [12]. The meeting reached broad consensus and set research directions, but also accepted that there were several complexities ahead – for example, the methodological challenges of disentangling the relative importance of diabetes treatments, other (confounding) risk factors and cancer risk [13]. A parallel development was the formation of the Diabetes and Cancer Research Consortium (DCRC), an international group mainly focusing on pharmaco-epidemiological queries in the complex relationships between diabetes, anti-diabetes therapies and cancer, but with a key aim to develop and optimise methodological
approaches required to address these complexities. The group published two framework papers: one on cancer incidence [14], the other on cancer mortality [15]. Two important methodological features were emphasised: (i) accounting for detection time bias; and (ii) setting-up data to account for time-varying exposures. Detection time bias results in exaggerated risk associations due to increased surveillance around the time of diagnosis of diabetes or cancer, or occasionally due to reverse causality (for example, pancreatic cancer presenting as diabetes). Time-varying exposures refer to real-life variation in prescription of medications with time, and may result in false risk associations in either positive or inverse directions. Further methodological work from DCRC members came when Walker and colleagues [16] summarised the problems of capturing drug exposure from observational datasets and described optimal methodology to reduce bias. For instance, they illustrated that different drugs are administered to control glucose as T2D progresses, making direct ‘trial-like’ comparisons between drug classes uninterpretable – in this setting, the use of ever/never drug exposure categories only should be avoided, and cumulative exposure handled statistically as a time-varying covariate.
3. Insulin analogues and cancer risk Following 2009, several observational studies evaluated the putative link between insulin glargine and cancer risk. Meta-analyses of these observational studies followed: six of these reviews are summarised in Table 1 [17–22]. In general, there are many inconsistencies in the findings of these meta-analyses. In turn, these reflect important design differences in the included studies. For example, some studies evaluated any insulin use versus non-insulin therapies in patients with diabetes; while others evaluated glargine versus non-glargine insulin use. As insulins are generally prescribed late in the course of diabetes, patients are older and ‘sicker’ and not surprisingly these biases result in an apparent increased cancer risk. None of the meta-analyses directly addressed the problem of time-related biases (detailed below in relation to metformin and cancer risk). For similar reasons, lumping data from case-controls with cohorts is particularly problematic; although, it is possible to take account of time-varying exposure in case-control studies, this is seldom done. The publication of the ORIGIN trial in 2012 potentially brought a clearer picture. This trial randomly assigned 12,537 patients with impaired glucose tolerance or type 2 diabetes to receive insulin glargine versus standard care [23]; the largest trial of its type. Although the protocol end-points were cardiovascular non-fatal events or deaths, following the concerns raised by the 2009 papers, the investigators additionally detailed risk per cancer type by treatment allocation. There were no differences between treatment arms for all cancer
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Table 1 Summary of systematic reviews and meta-analyses of observational studies of the effect of insulin therapies on cancer risk. Author (year)
Specific question
No. of studies
No. of cancers
Summary estimates Overall cancers (RR: 95% CIs)
Specific cancers (RR: 95% CIs)
Janghorbani et al. (2012) [20] Isfahan, Iran
Any insulin versus no insulin.
Fifteen studies (five case-control and ten cohort studies)
14,085
RR: 1.39, 95%CI: 1.14, 1.70
Pancreatic: (RR: 4.78, 95%CI: 3.12, 7.32) Colorectal: (RR: 1.50, 95%CI: 1.08, 2.08) No association with breast, prostate and hepatocellular cancers. Breast: (RR: 1.14, 95%CI: 0.65–2.02) Prostate: (RR: 1.00, 95%CI: 0.79–1.26) Pancreatic: (RR: 0.57, 95%CI: 0.14–2.35) Breast: (OR: 0.99, 95%CI: 0.68–1.46) No association between insulin glargine and prostate, pancreatic and respiratory tract cancers. Pancreatic: (RR: 1.63, 95%CI: 1.05–2.51); Prostate: (RR: 2.68, 95%CI: 1.50–4.79); Colorectal: (RR: 0.78, 95%CI: 0.64–0.94) 27 cancer sites. Increased risk for pancreatic and colorectal cancer; no increase for breast and prostate. For glargine versus nonglargine: decreased risk for colon cancer. Versus other glucoselowering agents (RR = 0.89, 95% CI: 0.72– 1.09). Glargine versus nonglargine: (RR = 1.26, 95% CI: 0.86–1.84).
Du et al. (2012) [19] Nanjing, China
Insulin glargine versus non-glargine
Seven cohorts
Tang et al. (2012) [22] Gansu, China
Insulin glargine versus non-glargine
10 cohorts: 1 c.c.
19,128
Colmers et al. (2012) [18] Alberta, Canada Karlstad et al. (2013) [21] Olso, Norway
Any insulin versus no insulin. Reported by new users
19 cohorts and nested c.c.
41,947
Any insulin versus no insulin. Also examined glargine versus non-glargine
34 analysable studies: 27 cohorts; 15 c.c.
Chen et al. (2013) [17] Shanghai, China
Limited to prostate (PCa) cancer risk
10 cohorts: 1 c.c.
RR: 0.86, 95%CI: 0.69–1.07
OR: 0.81, 95%CI: 0.68–0.98
Increased overall cancer incidence
7,053
Concluding remarks
‘Association between insulin use and increased risk of overall, pancreatic, and colorectal cancers’
‘No support of an increased cancer risk in patients treated with insulin glargine’
‘No support of a link between insulin glargine and an increased risk of cancer’
‘Interpretation with caution’
‘Study design has profound effect on estimated cancer risk’
‘No association between insulin use and risk of PCa’
RR, risk ratio; OR, odds ratio; CI, confidence interval; c.c.: case-control studies.
incidence or deaths, and no differences between treatment arms for specific reported cancer types. These data seemed definitive, leading some commentators to suggest ‘closure’ on this topic [24]. However, there are caveats to the interpretation of the ORIGIN trial and cancer risk. First, although median follow-up was 6.2 years, there is a rapid drop-off thereafter such that only 14% of recruited patients were followed to the seventh year (Fig. 1). Many cancer epidemiologists would consider this lag period too short to assess associations between an exposure and cancer incidence. Second, there was considerable contamination across the arms – 16.7% of patients in the experimental arm discontinued glargine;
while 11.5% of patients in the standard arm commenced some insulin by the end of the study follow-up. 4. Metformin and cancer risk Almost as an incidental ‘by-product’ of the pharmaco-epidemiological analyses of insulin analogues and cancer risk, attention was directed to the observation that metformin may be associated with a reduced risk of cancer. In an era when oncologists are encouraged to repurpose inexpensive licensed drugs, metformin seemed a strong candidate, and led one UK mainstream newspaper to headline ‘A diabetes pill that costs just 2p
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Median FU
6000
No. of patients
5000 4000 3000 2000
Exposed to glargine
1000
Non-glargine exposure (standard care)
0 0
1
2
3 Years
4
5
6
7
Fig. 1. Follow-up ‘drop-off’ by treatment allocation in the ORIGIN trial. The numbers per arm have taken account of the numbers followed after randomisation minus those cases that discontinued glargine in the intervention arm, and commenced insulin in the standard care arm. FU: follow-up. Drawn from data in Table 2, Ref. [13].
a day could prevent thousands dying from Britain’s biggest cancer killers’ [25]. However, we now understand that many of the earlier epidemiological studies contained time-related biases that artificially made metformin look ‘protective’. Most important of these is immortal time bias. This statistical pitfall is conceptually difficult and perhaps not well appreciated by many researchers. The bias occurs when the analysis mismatches exposure in two comparison groups. Individuals have to survive to the start of exposure – hence, the name of ‘immortal’. The result is an advantage to the users of the drug of interest when the analysis is simply categorised by ever/never use. This was well illustrated by Suissa and colleagues [26] – they found that immortal time bias was prevalent among many studies that reported a reduced cancer risk associated with metformin use. By contrast, those studies that used methods to avoid these biases reported no effect of metformin use on cancer incidence. A further pitfall to interpretation is treatment allocation bias. For example, metformin is first line treatment for diabetes, and is therefore used earlier in the disease course than other medications. Those who achieve control with metformin alone differ in disease severity from those who require additional medication. Differential allocation of drugs based on such confounding factors tends to exaggerate the benefits of metformin. Differential allocation is an inevitable bias in observational studies and has to be addressed within a randomised trial framework. Primary cancer prevention trials are currently impractically huge and thus investigators have selected to test the hypothesis that metformin is cancer protective in the secondary prevention setting. An example is an adjuvant trial in early breast cancer, NCIC MA.32, with a primary end-points of 5-year invasive cancer-free survival [27]. The recruitment target (3582
women without diabetes) was completed in early 2013 – the results of this trial are eagerly awaited. The third key lesson from the story of metformin and cancer lies in the pharmacokinetics. There are now many laboratories across the globe exploring the role of metformin in cancer, and several novel anti-cancer mechanisms have been demonstrated. However, it has become clear that many preclinical studies use concentrations of metformin considerably higher than those safely obtained in the clinical setting (Fig. 2) [28]. The doses of metformin currently used in many oncology trials are those shown to be effective for glucose control; there is a need to establish the appropriate dose of metformin for its proposed anti-cancer effects. 5. Other anti-diabetes therapies and cancer As investigators examined their databases, they stumbled upon the observation that use of pioglitazone, a thiazolidinedione (used as 2nd or 3rd line therapy in T2D), might be associated with increased risk of bladder cancer. This drug causes bladder cancer in dogs, but by mechanisms which may not apply to humans. The initial epidemiological studies were based on relatively crude analyses of health insurance system databases with small numbers of bladder cancer cases – nonetheless the drug regulation authorities in France and Germany withdrew this agent in June 2011. Since then, there have been at least three large published analyses from – the General Practice Research Database, UK [29], Systeme National d’Information Inter-regimes de l’Assurance Maladie, France [30] and the Kaiser Permanente Northern California (KPNC) diabetes registry [31] – with large numbers of bladder cancer cases, and all suggesting an increased risk. However, here again, there may be biases clouding the interpretation. Recent updated analyses [32] of the KPNC cohort study of pioglitazone and Metformin concentrations
Standard clinical use
In vivo preclinical studies
In vitro laboratrory studies
Dose
250 to 2250 mg/day
750 mg/kg per day
2 to 50 mM
Relative Dose*
0.15 to 1.0
2 to 45
25 to 1000
Fig. 2. Concentrations of metformin used in laboratory studies. Clinical and epidemiological studies utilise metformin doses of up to 2250 mg/day. Conversely, in vivo preclinical and in vitro studies often involve extremely high, non-physiological concentrations of metformin that are in excess of the therapeutic levels safely achieved in human patients. Adopted from Ref. [18]. *Relative to standard clinical use.
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bladder cancer show that when there is adjustment for albuminuria (as a surrogate for subsequent cystoscopic investigation), the increased risk essentially disappears. These new analyses suggest that the bladder cancer association might be due to ascertainment (heightened investigations) bias [33]. Further confirmatory studies are required to this question. Incretin-based glucose-lowering medications were introduced to the US in 2005 and have proven to be effective glucose-lowering agents – both as glucagon-like peptide 1 (GLP-1) receptor agonists and as dipeptidyl peptidase 4 (DPP-4) inhibitors. Here again, over recent years, there have been cancer safety concerns. In animal models, both classes may promote acute pancreatitis, and initiate histological changes suggestive of subclinical chronic pancreatitis with associated pre-neoplastic lesions (for example, ductal proliferation), and potentially, in the long run, induce pancreatic cancer [34]. There may be additional risks for thyroid cancer. These data are challenging to interpret for several reasons: long-term use of incretin-based glucose-lowering is limited; it is unclear whether or not pre-clinical animal model data translate directly to human cancer development; and whether there had been adequate modelling to take account of the biases and confounding outlined in the early paragraphs. 6. What is the role of obesity in the controversy? One final area for consideration is the role played by change in body mass index (BMI), and other adiposity indicators, during the course of diabetes development
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and progression, as excess BMI is an established risk factor for several cancer types [35]. There is a continuing need to disentangle the effects of obesity versus diabetes and disease end-points, and this is equally true for cancer end-points. A relatively new dimension to this relationship is that several studies have observed that BMI at the time of diabetes diagnosis has a U-shaped relationship with mortality [36,37] – the ‘obesity paradox’ – and in turn, this relationship may be modified by smoking status [38]. It is well recognised clinically that weight among patients with diabetes varies considerably over years – thus, there is a need to develop more sophisticated time-varying, yet clinically-relevant, models to account for these ‘real-world’ relationships. 7. Future directions It is evident that, over the last 5 years, the interrogation of epidemiological databases to assess the relations between diabetes, anti-diabetes therapies and cancer has produced a large number of studies, and that these have in general shown regression towards the null: i.e. that both positive and inverse drug effects have tended to diminish as methodologies improve and further studies are undertaken. The coming together of experts from different fields and the linking together of databases has been very positive, and networks and platforms are now in place to address some of the major gaps for future research, as outlined in Box 1. So what do these wide ranging observations mean for day-to-day clinical oncology practice? Oncologists should be aware that T2D patients are at increased risk
Box 1 Diabetes and cancer: research gaps. 1
2
3
4
5
There are broadly five domains to consider. The examples are illustrative – these are not an exhaustive list. Translational science 1.1. There is a need to establish animal models that mimic human diabetes and facilitate evaluation of treatments and pathological states (hyperinsulinaemia and hyperglycaemia) that may affect cancer predisposition and progression. 1.2. In vitro models are needed to consider effects of glucose-lowering agents in early, as well as late, transformed neoplastic cells. 1.3. There is a need to distinguish the pharmacodynamic and pharmacokinetic parameters required for cancer-modifying versus glucoselowering effects of anti-diabetes therapies. Epidemiology of cancer risk 2.1. There is a continued need to disentangle the effects of adiposity versus T2D per se on cancer risk. Mendelian randomisation may offer one methodological approach. 2.2. There is a continued need to perform ‘good’ pharmacoepidemiology, with appropriate capture of cumulative exposure, long follow-up and use of time-varying statistical approaches. Clinical study in patients with cancer and diabetes 3.1. For some cancers, there is evidence that patients with T2D present with more advanced disease, receive sub-optimal treatment, and have poorer oncological outcomes. 3.2. There is a need to test the hypothesis that patients with T2D have reduced quality of life after cancer treatment. 3.3. There is a need to better quantify the relationships in 3.1 and 3.2; link these to lifestyle influences (e.g. physical activity), treatment morbidity and patient-related outcomes (PROMs). Interventional trials 4.1. Within new and on-going trials of glucose-lowering agents, and other interventions (for example, weight reduction programmes) in patients with impaired glucose tolerance or type 2 diabetes, there is a need to include long-term cancer end-points. 4.2. Key findings derived from (1) to (3) above should be considered for validation within the setting of randomised prospective trials. Global burden and cost 5.1. There is a need to develop methods to appropriately assign attribution of T2D to cancer risk to derive country-level burden of disease (cancer attributed to diabetes). In turn, this will allow monitoring of the effect of population-level interventions. 5.2. There is a need to establish the economic burden of cancer attributed to diabetes.
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of several common cancer types compared with the general population. This does not translate into a need for more intensive cancer screening. Rather, there is evidence that patients with T2D under-utilise national screening programmes [39] – oncologists should enquire after these activities. Additionally, among patients with diabetes who develop cancer, treatment and outcomes may be sub-optimal [40] – this needs to be better quantified and reversed. The continued exploration of metformin as an anti-cancer agent in the laboratory should be encouraged. From the diabetes point of view, there is no call for changes in clinical practice in terms of glucose-lowering drugs. Cancer risk can be considered negligibly small or absent with long-acting insulin analogues. When prescribing pioglitazone, the clinician needs to be mindful of patients with a history or predisposition to bladder cancer. For incretin-based medications, the evidence currently is too immature to impact on clinical practice, but further studies are needed. Researchers across diabetes and cancer communities must continue to collaborate, design trials, and explore new and existing databases, especially where outcomes are rare. Finally, journal editors in the diabetes and cancer fields must be aware of methodological pitfalls and support the pursuit of unbiased interpretations. Competing interests A.G. Renehan has received lecture honoraria and independent research funding from Novo Nordisk. Conflict of interest statement None declared. Acknowledgements We would like to acknowledge the critical appraisal of this manuscript by Professor E.A.M. Gale, former editor-in-chief of Diabetologia. He also contributed to the exactness of the narration of events around the ‘breaking news’ in June 2009. References [1] IDF. International Diabetes Federation, Diabetes Atlas, 6th ed. http://www.idf.org/diabetesatlas/europe [accessed 17 Feb 2014]. [2] Ferlay J, Steliarova-Foucher E, Lortet-Tieulent J, Rosso S, Coebergh JW, Comber H, et al. Cancer incidence and mortality patterns in Europe: estimates for 40 countries in 2012. Eur J Cancer 2013;49(6):1374–403. [3] van de Poll-Franse LV, Houterman S, Janssen-Heijnen ML, Dercksen MW, Coebergh JW, Haak HR. Less aggressive treatment and worse overall survival in cancer patients with diabetes: a large population based analysis. Int J Cancer 2007;120(9):1986–92. [4] Greenwood M, Wood F. The Relation between the Cancer and Diabetes Death-rates. J Hyg (Lond) 1914;14(1): 83–118.
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