Skip to main content
  • More from ADA
    • Diabetes
    • Clinical Diabetes
    • Diabetes Spectrum
    • ADA Standards of Medical Care
    • ADA Scientific Sessions Abstracts
    • BMJ Open Diabetes Research & Care
  • Subscribe
  • Log in
  • My Cart
  • Follow ada on Twitter
  • RSS
  • Visit ada on Facebook
Diabetes Care

Advanced Search

Main menu

  • Home
  • Current
    • Current Issue
    • Online Ahead of Print
    • Special Article Collections
    • ADA Standards of Medical Care
  • Browse
    • By Topic
    • Issue Archive
    • Saved Searches
    • Special Article Collections
    • ADA Standards of Medical Care
  • Info
    • About the Journal
    • About the Editors
    • ADA Journal Policies
    • Instructions for Authors
    • Guidance for Reviewers
  • Reprints/Reuse
  • Advertising
  • Subscriptions
    • Individual Subscriptions
    • Institutional Subscriptions and Site Licenses
    • Access Institutional Usage Reports
    • Purchase Single Issues
  • Alerts
    • E­mail Alerts
    • RSS Feeds
  • Podcast
  • Submit
    • Submit a Manuscript
    • Journal Policies
    • Instructions for Authors
    • ADA Peer Review
  • More from ADA
    • Diabetes
    • Clinical Diabetes
    • Diabetes Spectrum
    • ADA Standards of Medical Care
    • ADA Scientific Sessions Abstracts
    • BMJ Open Diabetes Research & Care

User menu

  • Subscribe
  • Log in
  • My Cart

Search

  • Advanced search
Diabetes Care
  • Home
  • Current
    • Current Issue
    • Online Ahead of Print
    • Special Article Collections
    • ADA Standards of Medical Care
  • Browse
    • By Topic
    • Issue Archive
    • Saved Searches
    • Special Article Collections
    • ADA Standards of Medical Care
  • Info
    • About the Journal
    • About the Editors
    • ADA Journal Policies
    • Instructions for Authors
    • Guidance for Reviewers
  • Reprints/Reuse
  • Advertising
  • Subscriptions
    • Individual Subscriptions
    • Institutional Subscriptions and Site Licenses
    • Access Institutional Usage Reports
    • Purchase Single Issues
  • Alerts
    • E­mail Alerts
    • RSS Feeds
  • Podcast
  • Submit
    • Submit a Manuscript
    • Journal Policies
    • Instructions for Authors
    • ADA Peer Review
Systematic Review

Effect of Long-Acting Insulin Analogs on the Risk of Cancer: A Systematic Review of Observational Studies

  1. Jennifer W. Wu1,2,
  2. Kristian B. Filion1,2,3,
  3. Laurent Azoulay1,2,4,
  4. Margaret K. Doll1 and
  5. Samy Suissa1,2,3⇑
  1. 1Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Quebec, Canada
  2. 2Centre for Clinical Epidemiology, Lady Davis Institute, Jewish General Hospital, Montreal, Quebec, Canada
  3. 3Division of Clinical Epidemiology, Department of Medicine, McGill University, Montreal, Quebec, Canada
  4. 4Department of Oncology, McGill University, Montreal, Quebec, Canada
  1. Corresponding author: Samy Suissa, samy.suissa{at}mcgill.ca.
Diabetes Care 2016 Mar; 39(3): 486-494. https://doi.org/10.2337/dc15-1816
PreviousNext
  • Article
  • Figures & Tables
  • Suppl Material
  • Info & Metrics
  • PDF
Loading

Abstract

OBJECTIVE Observational studies examining the association between long-acting insulin analogs and cancer incidence have produced inconsistent results. We conducted a systematic review of these studies, focusing on their methodological strengths and weaknesses.

RESEARCH DESIGN AND METHODS We systematically searched MEDLINE and EMBASE from 2000 to 2014 to identify all observational studies evaluating the relationship between the long-acting insulin analogs and the risk of any and site-specific cancers (breast, colorectal, prostate). We included cohort and case-control studies published in English on insulin glargine and detemir and any cancer incidence among patients with type 1 or 2 diabetes. The methodological assessment involved the inclusion of prevalent users, inclusion of lag periods, time-related biases, and duration of follow-up between insulin initiation and cancer incidence.

RESULTS A total of 16 cohort and 3 case-control studies met our inclusion criteria. All studies evaluated insulin glargine, and four studies also examined insulin detemir. Follow-up ranged from 0.9 to 7.0 years. Thirteen of 15 studies reported no association between insulin glargine and detemir and any cancer. Four of 13 studies reported an increased risk of breast cancer with insulin glargine. In the quality assessment, 7 studies included prevalent users, 11 did not consider a lag period, 6 had time-related biases, and 16 had short (<5 years) follow-up.

CONCLUSIONS The observational studies examining the risk of cancer associated with long-acting insulin analogs have important methodological shortcomings that limit the conclusions that can be drawn. Thus, uncertainty remains, particularly for breast cancer risk.

Introduction

NPH insulin has been the mainstay treatment for type 1 diabetes and advanced type 2 diabetes since the 1950s. However, this insulin is associated with an increased risk of nocturnal hypoglycemia, and its relatively short half-life requires frequent administration (1,2). Consequently, structurally modified insulins, known as long-acting insulin analogs (glargine and detemir), were developed in the 1990s to circumvent these limitations. However, there are concerns that long-acting insulin analogs may be associated with an increased risk of cancer. Indeed, some laboratory studies showed long-acting insulin analogs were associated with cancer cell proliferation and protected against apoptosis via their higher binding affinity to IGF-I receptors (3,4).

In 2009, four observational studies associated the use of insulin glargine with an increased risk of cancer (5–8). These studies raised important concerns but were also criticized for important methodological shortcomings (9–13). Since then, several observational studies assessing the association between long-acting insulin analogs and cancer have been published but yielded inconsistent findings (14–28). Such discrepancies may be due to methodological limitations, including inadequate durations of follow-up between insulin initiation and cancer incidence, protopathic bias, detection bias, the inclusion of prevalent users, and time-related biases such as immortal time bias, time-window bias, and time-lag bias (29).

Randomized controlled trials (RCTs) have reported the effects of long-acting insulin analogs on the risk of any cancers (30–32), but most of these RCTs were designed to study efficacy (e.g., fasting plasma glucose level) and not designed to assess cancer. The most notable RCT, the Outcomes Reduction with Insulin Glargine Intervention (ORIGIN) trial, did not observe an effect of insulin glargine on the composite outcome of any cancer (33). Although the ORIGIN trial had several strengths, including the power to detect a clinically important effect of insulin glargine on any cancer and adjudication of cancer outcomes, it was not powered to detect site-specific cancers, and follow-up was relatively short (<7 years) given the long latency of cancer.

Several meta-analyses of observational studies have investigated the association between insulin glargine and cancer risk (34–37). These meta-analyses assessed the quality of included studies, but the methodological issues particular to pharmacoepidemiologic research were not fully considered. In addition, given the presence of important heterogeneity in this literature, the appropriateness of pooling the results of these studies remains unclear. We therefore conducted a systematic review of observational studies examining the association between long-acting insulin analogs and cancer incidence, with a particular focus on methodological strengths and weaknesses of these studies.

Research Design and Methods

This systematic review was conducted following a prespecified protocol and reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (38).

Search Strategy

We systematically searched MEDLINE and EMBASE via Ovid from 1 January 2000 to 8 October 2014 for observational studies examining the association between long-acting insulin analogs and cancer incidence. The detailed search strategy is reported in Supplementary Table 1. Briefly, the search included MeSH terms, Emtree terms, and keywords for diabetes, long-acting insulin analogs, neoplasm, and observational studies. The publication type search terms used in this search strategy were adopted from the Scottish Intercollegiate Guidelines Network (SIGN) group (39). The search was limited to articles published from 2000 onwards because long-acting insulin analogs were not available globally until after 2000. Our search was also limited to studies published in English. We hand-searched relevant systematic reviews and meta-analyses to identify additional articles that were not identified in our electronic literature search.

Inclusion and Exclusion Criteria

Cohort, case-control, and case-cohort studies evaluating the association of long-acting insulin analogs (glargine and/or detemir) and cancer incidence among patients with type 1 or 2 diabetes were eligible for inclusion. Inclusion was restricted to studies reporting any incident cancer or site-specific cancers as primary or secondary outcomes. Studies that did not exclude prevalent cancer cases were eligible for inclusion. We excluded studies that did not meet these inclusion criteria.

The literature search was conducted independently by two reviewers (J.W.W. and M.K.D.), who assessed the titles and/or abstracts of identified publications. The full text of any publication deemed potentially relevant by either reviewer at this stage was retrieved for detailed review. Discrepancies in determining whether the study met our inclusion criteria during the full-text review were resolved by consensus or, when necessary, a third reviewer (K.B.F.).

Data Extraction and Quality Assessment

We developed a data extraction form, which was pilot tested on six included studies. Two independent reviewers (J.W.W. and M.K.D.) extracted data, with disagreements resolved by consensus or a third reviewer (K.B.F., L.A., and S.S.). Disagreements could have occurred when extracting individual data points (e.g., study characteristics and measures of association) or when evaluating the quality of the studies.

Extracted information included the following:

  • 1) study characteristics (source population, country, sample size, study design, type of database used to ascertain information about exposure and outcome);

  • 2) patient characteristics (age);

  • 3) exposure and comparator definitions (ever vs. never use, duration of use, dose, use of time-independent or -dependent approach);

  • 4) incidence of any and/or site-specific cancers;

  • 5) odds ratios, risk ratios, rate ratios, or hazard ratios (HRs) with corresponding 95% CIs;

  • 6) methods of adjustment for confounders (matching, regression-based adjustments, propensity scores, disease risk scores) and list of potential confounders; and

  • 7) quality of the studies.

We extracted any site-specific cancers but did not report on relative risks (RRs) for sites that were not commonly reported among the included studies.

No available quality assessment tool adequately captures the methodological issues and biases that are particular to pharmacoepidemiology. Therefore, we assessed the quality of studies for key components, including time-related biases (immortal time, time-lag, and time-window), inclusion of prevalent users, inclusion of lag periods, and length of follow-up between insulin initiation and cancer incidence.

Immortal time bias is defined by a period of unexposed person-time that is misclassified as exposed person-time or excluded, resulting in the exposure of interest appearing more favorable (40,41). Time-lag bias occurs when treatments used later in the disease management process are compared with those used earlier for less advanced stages of the disease. Such comparisons can result in confounding by disease duration or severity of disease if duration and severity of disease are not adequately considered in the design or analysis of the study (29). This is particularly true for chronic disease with dynamic treatment processes such as type 2 diabetes. Currently, American and European clinical guidelines suggest using basal insulin (e.g., NPH, glargine, and detemir) as a last line of treatment if HbA1c targets are not achieved with other antidiabetic medications (42). Therefore, studies that compare long-acting insulin analogs to nonbasal insulin may introduce confounding by disease duration. Time-window bias occurs when the opportunity for exposure differs between case subjects and control subjects (29,43).

The importance of considering a lag period is necessary for latency considerations (i.e., a minimum time between treatment initiation and the development of cancer) and to minimize protopathic and detection bias. Protopathic bias, or reverse causation, is present when a medication (exposure) is prescribed for early symptoms related to the outcome of interest, which can lead to an overestimation of the association. Lagging the exposure by a predefined time window in cohort studies or excluding exposures in a predefined time window before the event in case-control studies is a means of minimizing this bias (44). Detection bias is present when the exposure leads to higher detection of the outcome of interest due to the increased frequency of clinic visits (e.g., newly diagnosed patients with type 2 diabetes or new users of another antidiabetic medication), which also results in an overestimation of risk (45). Thus, including a lag period, such as starting follow-up after 1 year of the initiation of a drug, simultaneously considers a latency period while also minimizing protopathic and detection bias.

We also assessed the studies for traditional epidemiological biases such as selection bias, information bias, and confounding. For confounding, we considered three potential sources:

  • 1) imbalances between measured baseline covariates that were not addressed analytically;

  • 2) residual confounding due to unmeasured confounders; and

  • 3) lack of adjustment for time-dependent confounders.

This assessment focused on the discussion of key components of design and analysis rather than on the creation of an aggregate score, as has been suggested elsewhere (46). We used the primary analysis of each included study for the qualitative assessment, but if the issue or bias was addressed in an appropriate sensitivity analysis, we considered this in the qualitative assessment.

Data Analysis

Given the methodological focus of this review and heterogeneity among published studies, we conducted a systematic review without a meta-analysis. Nonetheless, forest plots were constructed with Stata 13 software (StataCorp LP, College Station, TX) to graphically present the available data.

Results

Study Selection

Our search of MEDLINE and EMBASE yielded 4,417 potentially relevant articles (Supplementary Fig. 1). Following our inclusion criteria, 16 cohort and 3 case-control studies were included in this systematic review (5–8,14–28). All studies evaluated insulin glargine, with four studies also investigating insulin detemir (15,17,25,28).

Study Characteristics and Effect Estimates

The study populations ranged from 1,340 to 275,164 patients (Table 1). The mean or median durations of follow-up and age ranged from 0.9 to 7.0 years and from 52.3 to 77.4 years, respectively. Thirteen studies examined ever use of long-acting insulin analogs, which was defined as at least one prescription, compared with nonuse, other, human, or NPH insulin (5–8,14,16,18,19,21,23,25–27). One study examined duration of time since starting long-acting insulin analogs, and one examined mean daily dose (22,28). Four studies used time-dependent exposure definitions (15,17,20,24). All included studies evaluated cancer incidence as a primary outcome.

View this table:
  • View inline
  • View popup
Table 1

Characteristics of observational studies examining the association between long-acting insulin analogs and cancer incidence

Of the 16 studies that evaluated the relationship between long-acting insulin analogs and any, colorectal, and/or prostate cancer, 13 reported no associations (Fig. 1 and Supplementary Fig. 2) (5,8,14–17,19–21,23,25,26,28). Four of 13 studies reported an association of insulin glargine and breast cancer (8,19,21,24).

Figure 1
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 1

Forest plots of RRs (solid squares) and 95% CIs (solid horizontal lines) from studies on insulin glargine and any (A), breast (B), colorectal (C), and prostate (D) cancers. For exposure and comparator definitions in each study, please refer to Table 1.

Quality Assessment

The different key components of the quality assessment are summarized in Table 2 and discussed in detail below.

View this table:
  • View inline
  • View popup
Table 2

Pharmacoepidemiology biases in studies examining the association between long-acting insulin analogs and cancer incidence

Immortal Time Bias

Of the 19 studies in this review, immortal time bias may have been introduced in one study based on the time-independent exposure and cohort entry definitions that were used in this cohort study (14). For the exclusive user definition, patients needed to have insulin glargine or human insulin only between the first and last prescription to be considered exposed to that one insulin only. However, the follow-up started from the first insulin prescription, and as a result, the time before the last insulin prescription was misclassified as exposed when it should have been classified as unexposed. Similarly, for the predominant user definition, the patient needed to have at least 12 prescriptions of insulin and be exposed 80% of the follow-up time to be considered exposed, but the time before the 12th prescription and meeting the 80% exposure time should be considered unexposed (as depicted in Supplementary Fig. 3). As a result, the adjusted HRs for any cancer were ∼0.60, although the results were not statistically significant.

Time-Lag Bias

Time-lag bias may have occurred in four studies that compared insulin glargine to human or other (nonbasal) insulin or highest-to-lowest duration of insulin use without adjusting or matching on diabetes duration (7,14,23,28). The presence of time-lag bias is well illustrated in a cohort study in which individuals who received human insulin or any type of insulin analog for the first time were included in the cohort. Such individuals could be at earlier stages of the disease than those who received insulin glargine (as depicted in Supplementary Fig. 4). Unfortunately, diabetes duration was not reported. This study observed an association between insulin glargine and cancer (HR 1.19 [95% CI 1.09–1.29]), but it is possible that more cases of cancer occurred in the insulin glargine group due to the longer diabetes duration rather than due to exposure to insulin glargine.

A variation of time-lag bias was observed in a cohort study of new insulin users (28). For the exposure definition, highest duration since the start of insulin use was compared with the lowest. It is expected that the risk of cancer would increase with longer duration of insulin use; however, the opposite was reported (with RRs ranging from 0.50 to 0.90). The protective association observed could be due to competing risks (e.g., death from cardiovascular-related events) (47,48). Patients with diabetes have a higher risk of cardiovascular-related deaths compared with patients with no diabetes (49,50). Therefore, patients with diabetes who die of cardiovascular-related events do not have the opportunity to develop cancer, resulting in an underestimation of the risk of cancer.

Time-Window Bias

Time-window bias was observed in two studies (18,22). In one of the two studies, despite matching on calendar time, time-window bias was potentially present because case and control subjects were not matched on diabetes duration (as depicted in Supplementary Fig. 5) (18). Consequently, the opportunity for exposure differed between the case and control subjects due to the varying diabetes durations (a mean of 14.5 years among case subjects and 13.2 among control subjects). Although one would expect an increased risk due to the time-window bias, a null effect was observed. This suggests that other biases, such as selection bias resulting from selection of case and control subjects from different study bases, may also be present.

Residual Confounding

We evaluated the patient characteristics in each of the 19 studies and observed that the measured covariates (e.g., age, sex, HbA1c, diabetes duration, comorbidities, prior medication use, smoking status, and/or alcohol use) were generally balanced between groups (either exposed vs. comparator or case subjects vs. control subjects, depending on the study design). However, residual confounding may have resulted due to the presence of unmeasured confounders. HbA1c and diabetes duration were not accounted for in 15 of the 19 studies, resulting in likely residual confounding (7,8,14–18,20–26,28). In addition, residual confounding may have occurred in all 19 studies because none of these studies adjusted for time-dependent covariates, such as the addition of short-acting insulins or other antidiabetic medication (e.g., metformin), at all or appropriately (e.g., used a marginal structural model and inverse probability weighting to adjust for time-dependent confounders in the causal pathway).

Other Methodological Issues

Seven studies included prevalent users of insulin (8,15,18,20,21,23,25), which is problematic because of the corresponding depletion of susceptible subjects in other insulin groups compared with long-acting insulin analogs. Protopathic or detection bias could have resulted in 11 of the 19 studies because a lag period was not incorporated in the study design (6,7,14–16,18–21,23,28). Furthermore, given the cancer latency and the time required to observe all the cancers that will occur in patients in these studies, short follow-up (defined here as <5 years) was an issue in 16 studies, whose follow-up time (reported as mean, median, or maximum duration of follow-up) ranged from 0.9 to 4.5 years (5–8,14–17,19,21,23–28). Only one of the studies observed an association between insulin glargine and breast cancer among prevalent users and after 5 years of use (HR 2.7 [95% CI 1.1–6.5]), which may highlight the importance of using a new user study design and having longer follow-up (27).

Conclusions

Summary

Our systematic review identified 16 cohort and 3 case-control studies on long-acting insulin analogs and cancer risk. We have shown that 7 studies included prevalent users, 11 did not incorporate a lag period, 6 were subject to time-related biases (4 of which had time-lag bias), and 16 had short follow-up (<5 years). The RRs reported in the existing literature on long-acting insulin analogs and cancer suggests there is no increased risk for any, colorectal, or prostate cancers, but four studies observed an increased risk for breast cancer when insulin glargine was compared with other insulins. However, the conclusions that can be drawn from observational studies on long-acting insulin analogs and cancer are limited due to the methodological issues.

Implications and Solutions to the Methodological Issues

Given the methodological issues present in many of the existing studies, the currently available evidence is insufficient to draw definitive conclusions regarding the association between long-acting insulin analogs and cancer. The U.S. Food and Drug Administration arrived at similar conclusions (51–53). In contrast, the European Medicines Agency concluded that insulin glargine does not increase the risk of cancer (54). Given the limitations of the existing literature, there remains a need for methodologically rigorous studies conducted with longer follow-up to clearly evaluate the relationship between long-acting insulin analogs and site-specific cancers. Such studies must use study designs and analytical approaches that consider the biases and issues that were discussed in detail above and summarized in Supplementary Table 2.

Previous Observational Studies, Reviews, and RCTs on Antidiabetic Medications and Cancer

To the best of our knowledge, this is the first systematic review of the methodological strengths and limitations of existing studies on long-acting insulin analogs and cancer. However, earlier editorials and narrative reviews have criticized the four cohort studies on insulin glargine and cancer for their methodological shortcomings, which included reverse causation, lack of lag periods, inclusion of prevalent insulin users, and concerns about the data analysis (9–13). In our systematic review, we also identified the lack of lag periods used and the inclusion of prevalent users as additional limitations in a few studies.

One of the insulin glargine and breast cancer studies only observed an association among prevalent users of insulin after 5 or more years of use (27). This study suggests that duration of insulin use could be an effect measure modifier of the insulin glargine and breast cancer relationship and that studies with shorter follow-up may not be sufficient to observe these effects. Moreover, it also highlights the importance of separating new or first-time users from patients who are switchers from one type of insulin to another because the risk may not be uniform across user types. Along with using more appropriate comparators, one of the strengths of a recent study by Habel et al. (19) was the separation of new users and switchers. Studies only considering new users may not provide adequate evidence for decision making in a real-world setting because the risk of cancer may differ among patients who switch from other insulins to long-acting insulin analogs.

The methodological limitations, particularly time-related biases, of previous studies of antidiabetic medications and cancer incidence were discussed previously in a review of observational studies of metformin and cancer (29). Compared with the literature examining the association between metformin and cancer incidence, we observed a smaller prevalence of time-related biases. However, we identified the presence of other methodological issues not addressed in this previous work. Importantly, unlike the previous review, the present methodological assessment was conducted in the context of a systematic review.

Similar to observational studies, RCTs assessing long-acting insulin analogs among patients with diabetes did not observe an increased risk of cancer (30–32), but these RCTs were designed to study efficacy (e.g., improvements in fasting plasma glucose level) and not cancer outcomes. The most notable RCT was the ORIGIN trial, which had 12,537 patients in whom 953 new or recurrent cancers occurred during 7 years of follow-up (33). This secondary analysis of the ORIGIN trial had 90% power to detect a 20% increased risk of cancer with use of insulin glargine, and cancer outcomes were adjudicated by an assessor blinded to treatment assignment. Despite these strengths, the study was insufficiently powered to conclusively assess site-specific cancers. Furthermore, given the long latency of cancer, the duration of follow-up of ORIGIN (a median of 6.2) was likely insufficient to conclusively assess cancer risk.

Strengths and Limitations

Our study has several important strengths. First, to our knowledge, it is the first systematic review to methodologically assess the literature on long-acting insulin analogs and their effects on cancer in patients with type 1 or 2 diabetes. This includes the assessment of biases and methodological issues that are particularly prevalent in pharmacoepidemiologic research. Second, a prespecified protocol was used to conduct the systematic review. Finally, our systematic search was conducted in duplicate, ensuring the inclusion of all relevant studies in the present systematic review.

There are also some potential limitations. First, we did not search the gray literature, contact other experts in the field, or attempt to obtain unpublished work. Second, the search was restricted to studies published in English; however, this restriction did not result in the exclusion of a large number of studies. Third, the presence of residual confounding due to unmeasured confounders was evaluated based on confounders (i.e., HbA1c and diabetes duration) previously identified in the literature, and conclusions could vary based on the assessment of other potential confounders. Fourth, this systematic review focused on the association between long-acting insulin analogs and cancer incidence. Consequently, it did not assess the literature in which the cancer risk of any insulin was compared with that of no insulin, an area that warrants further investigation, particularly given the emergence of new medications for patients with type 2 diabetes. Finally, as is true with any systematic review, there is the potential for publication bias. However, given our focus on the methodological aspects of the literature on this topic and the large number of included studies with null results, the effect of publication bias on the current study was likely minimal.

Conclusion

We identified several methodological issues in observational studies on long-acting insulin analogs and cancer incidence, including the inclusion of prevalent users, lack of lag periods, and time-lag bias. In addition to these three prevalent methodological issues, most studies had short follow-up, which could prevent the observation of a relationship given the long latency of cancer. Therefore, the conclusions that can be drawn from existing observational studies of long-acting insulin analogs and cancer are limited. Future studies addressing these issues must use appropriate study designs and analytical approaches that address these limitations to conclusively address the potential association between long-acting insulin analogs and cancer incidence.

Article Information

Acknowledgments. The authors thank Genevieve Gore and Angella Lambrou, librarians at McGill University, for their expertise, time, and effort helping with the search strategy.

Funding. J.W.W. is a recipient of the Canadian Institutes of Health Research Doctoral Research Award. K.B.F. holds a Canadian Institutes of Health Research New Investigator award.

Duality of Interest. No potential conflicts of interest relevant to this article were reported.

Author Contributions. J.W.W. is the author of the systematic review protocol and the manuscript. J.W.W. and K.B.F. edited the protocol. J.W.W. and M.K.D. conducted the systematic search, extracted the data, and assessed the quality of the included studies. K.B.F., L.A., and S.S. served as adjudicators for disagreements in the inclusion of studies and quality assessment. J.W.W., K.B.F., L.A., M.K.D., and S.S. reviewed the manuscript for important intellectual content.

Footnotes

  • This article contains Supplementary Data online at http://care.diabetesjournals.org/lookup/suppl/doi:10.2337/dc15-1816/-/DC1.

  • Received August 20, 2015.
  • Accepted November 10, 2015.
  • © 2016 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.

References

  1. ↵
    1. Canadian Diabetes Association
    . Canadian Diabetes Association 2013 Clinical Practice Guidelines for the Prevention and Management of Diabetes in Canada. Can J Diabetes 2013;37(Suppl. 1):1–227pmid:24070740
    OpenUrlCrossRefPubMed
  2. ↵
    National Institute for Health and Care Excellence. Type 2 diabetes: the management of type 2 diabetes [article online], 2014. Available from http://www.nice.org.uk/guidance/cg87. Accessed 1 August 2015
  3. ↵
    1. Kurtzhals P,
    2. Schäffer L,
    3. Sørensen A, et al
    . Correlations of receptor binding and metabolic and mitogenic potencies of insulin analogs designed for clinical use. Diabetes 2000;49:999–1005pmid:10866053
    OpenUrlAbstract
  4. ↵
    1. Yehezkel E,
    2. Weinstein D,
    3. Simon M,
    4. Sarfstein R,
    5. Laron Z,
    6. Werner H
    . Long-acting insulin analogues elicit atypical signalling events mediated by the insulin receptor and insulin-like growth factor-I receptor. Diabetologia 2010;53:2667–2675pmid:20835859
    OpenUrlCrossRefPubMed
  5. ↵
    1. Colhoun HM, SDRN Epidemiology Group
    . Use of insulin glargine and cancer incidence in Scotland: a study from the Scottish Diabetes Research Network Epidemiology Group. Diabetologia 2009;52:1755–1765pmid:19603149
    OpenUrlCrossRefPubMedWeb of Science
  6. ↵
    1. Currie CJ,
    2. Poole CD,
    3. Gale EA
    . The influence of glucose-lowering therapies on cancer risk in type 2 diabetes. Diabetologia 2009;52:1766–1777pmid:19572116
    OpenUrlCrossRefPubMedWeb of Science
  7. ↵
    1. Hemkens LG,
    2. Grouven U,
    3. Bender R, et al
    . Risk of malignancies in patients with diabetes treated with human insulin or insulin analogues: a cohort study. Diabetologia 2009;52:1732–1744pmid:19565214
    OpenUrlCrossRefPubMedWeb of Science
  8. ↵
    1. Jonasson JM,
    2. Ljung R,
    3. Talbäck M,
    4. Haglund B,
    5. Gudbjörnsdòttir S,
    6. Steineck G
    . Insulin glargine use and short-term incidence of malignancies-a population-based follow-up study in Sweden. Diabetologia 2009;52:1745–1754pmid:19588120
    OpenUrlCrossRefPubMedWeb of Science
  9. ↵
    1. Gale EA
    . Insulin glargine and cancer: another side to the story? Lancet 2009;374:521pmid:19683632
    OpenUrlCrossRefPubMed
    1. Garg SK,
    2. Hirsch IB,
    3. Skyler JS
    . Insulin glargine and cancer--an unsubstantiated allegation. Diabetes Technol Ther 2009;11:473–476pmid:19591544
    OpenUrlCrossRefPubMed
    1. Hernández-Díaz S,
    2. Adami HO
    . Diabetes therapy and cancer risk: causal effects and other plausible explanations. Diabetologia 2010;53:802–808pmid:20177658
    OpenUrlCrossRefPubMedWeb of Science
    1. Pocock SJ,
    2. Smeeth L
    . Insulin glargine and malignancy: an unwarranted alarm. Lancet 2009;374:511–513pmid:19616841
    OpenUrlCrossRefPubMedWeb of Science
  10. ↵
    1. Smith U,
    2. Gale EA
    . Does diabetes therapy influence the risk of cancer? Diabetologia 2009;52:1699–1708pmid:19597799
    OpenUrlCrossRefPubMedWeb of Science
  11. ↵
    1. Blin P,
    2. Lassalle R,
    3. Dureau-Pournin C, et al
    . Insulin glargine and risk of cancer: a cohort study in the French National Healthcare Insurance Database. Diabetologia 2012;55:644–653pmid:22222504
    OpenUrlCrossRefPubMed
  12. ↵
    1. Buchs AE,
    2. Silverman BG
    . Incidence of malignancies in patients with diabetes mellitus and correlation with treatment modalities in a large Israeli health maintenance organization: a historical cohort study. Metabolism 2011;60:1379–1385pmid:21696791
    OpenUrlCrossRefPubMedWeb of Science
  13. ↵
    1. Chang CH,
    2. Toh S,
    3. Lin JW, et al
    . Cancer risk associated with insulin glargine among adult type 2 diabetes patients--a nationwide cohort study. PLoS One 2011;6:e21368pmid:21738645
    OpenUrlCrossRefPubMed
  14. ↵
    1. Fagot JP,
    2. Blotière PO,
    3. Ricordeau P,
    4. Weill A,
    5. Alla F,
    6. Allemand H
    . Does insulin glargine increase the risk of cancer compared with other basal insulins? A French nationwide cohort study based on national administrative databases. Diabetes Care 2013;36:294–301pmid:22966091
    OpenUrlAbstract/FREE Full Text
  15. ↵
    1. Grimaldi-Bensouda L,
    2. Cameron D,
    3. Marty M, et al.; ISICA Group
    . Risk of breast cancer by individual insulin use: an international multicenter study. Diabetes Care 2014;37:134–143pmid:23949559
    OpenUrlAbstract/FREE Full Text
  16. ↵
    1. Habel LA,
    2. Danforth KN,
    3. Quesenberry CP, et al
    . Cohort study of insulin glargine and risk of breast, prostate, and colorectal cancer among patients with diabetes. Diabetes Care 2013;36:3953–3960pmid:24170756
    OpenUrlAbstract/FREE Full Text
  17. ↵
    1. Lind M,
    2. Fahlén M,
    3. Eliasson B,
    4. Odén A
    . The relationship between the exposure time of insulin glargine and risk of breast and prostate cancer: an observational study of the time-dependent effects of antidiabetic treatments in patients with diabetes. Prim Care Diabetes 2012;6:53–59pmid:22056422
    OpenUrlPubMed
  18. ↵
    1. Ljung R,
    2. Talbäck M,
    3. Haglund B,
    4. Jonasson JM,
    5. Gudbjörnsdòttir S,
    6. Steineck G
    . Insulin glargine use and short-term incidence of malignancies - a three-year population-based observation. Acta Oncol 2011;50:685–693pmid:21506898
    OpenUrlCrossRefPubMed
  19. ↵
    1. Mannucci E,
    2. Monami M,
    3. Balzi D, et al
    . Doses of insulin and its analogues and cancer occurrence in insulin-treated type 2 diabetic patients. Diabetes Care 2010;33:1997–2003pmid:20551014
    OpenUrlAbstract/FREE Full Text
  20. ↵
    1. Morden NE,
    2. Liu SK,
    3. Smith J,
    4. Mackenzie TA,
    5. Skinner J,
    6. Korc M
    . Further exploration of the relationship between insulin glargine and incident cancer: a retrospective cohort study of older Medicare patients. Diabetes Care 2011;34:1965–1971pmid:21775752
    OpenUrlAbstract/FREE Full Text
  21. ↵
    1. Ruiter R,
    2. Visser LE,
    3. van Herk-Sukel MP, et al
    . Risk of cancer in patients on insulin glargine and other insulin analogues in comparison with those on human insulin: results from a large population-based follow-up study. Diabetologia 2012;55:51–62pmid:21956710
    OpenUrlCrossRefPubMedWeb of Science
  22. ↵
    1. Simó R,
    2. Plana-Ripoll O,
    3. Puente D, et al
    . Impact of glucose-lowering agents on the risk of cancer in type 2 diabetic patients. The Barcelona case-control study. PLoS One 2013;8:e79968pmid:24278227
    OpenUrlCrossRefPubMed
  23. ↵
    1. Stürmer T,
    2. Marquis MA,
    3. Zhou H, et al
    . Cancer incidence among those initiating insulin therapy with glargine versus human NPH insulin. Diabetes Care 2013;36:3517–3525pmid:23877991
    OpenUrlAbstract/FREE Full Text
  24. ↵
    1. Suissa S,
    2. Azoulay L,
    3. Dell’Aniello S,
    4. Evans M,
    5. Vora J,
    6. Pollak M
    . Long-term effects of insulin glargine on the risk of breast cancer. Diabetologia 2011;54:2254–2262pmid:21614572
    OpenUrlCrossRefPubMedWeb of Science
  25. ↵
    1. van Staa TP,
    2. Patel D,
    3. Gallagher AM,
    4. de Bruin ML
    . Glucose-lowering agents and the patterns of risk for cancer: a study with the General Practice Research Database and secondary care data. Diabetologia 2012;55:654–665pmid:22127412
    OpenUrlCrossRefPubMedWeb of Science
  26. ↵
    1. Suissa S,
    2. Azoulay L
    . Metformin and the risk of cancer: time-related biases in observational studies. Diabetes Care 2012;35:2665–2673pmid:23173135
    OpenUrlAbstract/FREE Full Text
  27. ↵
    1. Dejgaard A,
    2. Lynggaard H,
    3. Råstam J,
    4. Krogsgaard Thomsen M
    . No evidence of increased risk of malignancies in patients with diabetes treated with insulin detemir: a meta-analysis. Diabetologia 2009;52:2507–2512pmid:19838665
    OpenUrlCrossRefPubMedWeb of Science
    1. Home PD,
    2. Lagarenne P
    . Combined randomised controlled trial experience of malignancies in studies using insulin glargine. Diabetologia 2009;52:2499–2506pmid:19756478
    OpenUrlCrossRefPubMedWeb of Science
  28. ↵
    1. Rosenstock J,
    2. Fonseca V,
    3. McGill JB, et al
    . Similar risk of malignancy with insulin glargine and neutral protamine Hagedorn (NPH) insulin in patients with type 2 diabetes: findings from a 5 year randomised, open-label study. Diabetologia 2009;52:1971–1973pmid:19609501
    OpenUrlCrossRefPubMedWeb of Science
  29. ↵
    1. Bordeleau L,
    2. Yakubovich N,
    3. Dagenais GR, et al.; ORIGIN Trial Investigators
    . The association of basal insulin glargine and/or n-3 fatty acids with incident cancers in patients with dysglycemia. Diabetes Care 2014;37:1360–1366pmid:24574355
    OpenUrlAbstract/FREE Full Text
  30. ↵
    1. Colmers IN,
    2. Bowker SL,
    3. Tjosvold LA,
    4. Johnson JA
    . Insulin use and cancer risk in patients with type 2 diabetes: a systematic review and meta-analysis of observational studies. Diabetes Metab 2012;38:485–506pmid:23159131
    OpenUrlCrossRefPubMedWeb of Science
    1. Tang X,
    2. Yang L,
    3. He Z,
    4. Liu J
    . Insulin glargine and cancer risk in patients with diabetes: a meta-analysis. PLoS One 2012;7:e51814pmid:23284776
    OpenUrlCrossRefPubMed
    1. Du X,
    2. Zhang R,
    3. Xue Y, et al
    . Insulin glargine and risk of cancer: a meta-analysis. Int J Biol Markers 2012;27:e241–e246pmid:22865296
    OpenUrlCrossRefPubMed
  31. ↵
    1. Bronsveld HK,
    2. ter Braak B,
    3. Karlstad Ø, et al
    . Treatment with insulin (analogues) and breast cancer risk in diabetics; a systematic review and meta-analysis of in vitro, animal and human evidence. Breast Cancer Res 2015;17:100pmid:26242987
    OpenUrlCrossRefPubMed
  32. ↵
    1. Liberati A,
    2. Altman DG,
    3. Tetzlaff J, et al
    . The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. PLoS Med 2009;6:e1000100pmid:19621070
    OpenUrlCrossRefPubMed
  33. ↵
    Scottish Intelligence Guidelines Network (SIGN). Search Filters [article online], 2014. Available from http://www.sign.ac.uk/methodology/filters.html. Accessed 16 January 2015
  34. ↵
    1. Lévesque LE,
    2. Hanley JA,
    3. Kezouh A,
    4. Suissa S
    . Problem of immortal time bias in cohort studies: example using statins for preventing progression of diabetes. BMJ 2010;340:b5087pmid:20228141
    OpenUrlFREE Full Text
  35. ↵
    1. Suissa S
    . Immortal time bias in pharmaco-epidemiology. Am J Epidemiol 2008;167:492–499pmid:18056625
    OpenUrlAbstract/FREE Full Text
  36. ↵
    1. Inzucchi SE,
    2. Bergenstal RM,
    3. Buse JB, et al
    . Management of hyperglycemia in type 2 diabetes, 2015: a patient-centered approach: update to a position statement of the American Diabetes Association and the European Association for the Study of Diabetes. Diabetes Care 2015;38:140–149pmid:25538310
    OpenUrlFREE Full Text
  37. ↵
    1. Suissa S,
    2. Dell’aniello S,
    3. Vahey S,
    4. Renoux C
    . Time-window bias in case-control studies: statins and lung cancer. Epidemiology 2011;22:228–231pmid:21228697
    OpenUrlCrossRefPubMed
  38. ↵
    1. Tamim H,
    2. Monfared AA,
    3. LeLorier J
    . Application of lag-time into exposure definitions to control for protopathic bias. Pharmacoepidemiol Drug Saf 2007;16:250–258pmid:17245804
    OpenUrlCrossRefPubMedWeb of Science
  39. ↵
    1. Johnson JA,
    2. Bowker SL,
    3. Richardson K,
    4. Marra CA
    . Time-varying incidence of cancer after the onset of type 2 diabetes: evidence of potential detection bias. Diabetologia 2011;54:2263–2271pmid:21748485
    OpenUrlCrossRefPubMedWeb of Science
  40. ↵
    1. Stroup DF,
    2. Berlin JA,
    3. Morton SC, et al
    . Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA 2000;283:2008–2012pmid:10789670
    OpenUrlCrossRefPubMedWeb of Science
  41. ↵
    1. Berry SD,
    2. Ngo L,
    3. Samelson EJ,
    4. Kiel DP
    . Competing risk of death: an important consideration in studies of older adults. J Am Geriatr Soc 2010;58:783–787pmid:20345862
    OpenUrlCrossRefPubMed
  42. ↵
    1. Satagopan JM,
    2. Ben-Porat L,
    3. Berwick M,
    4. Robson M,
    5. Kutler D,
    6. Auerbach AD
    . A note on competing risks in survival data analysis. Br J Cancer 2004;91:1229–1235pmid:15305188
    OpenUrlCrossRefPubMedWeb of Science
  43. ↵
    1. Haffner SM,
    2. Lehto S,
    3. Rönnemaa T,
    4. Pyörälä K,
    5. Laakso M
    . Mortality from coronary heart disease in subjects with type 2 diabetes and in nondiabetic subjects with and without prior myocardial infarction. N Engl J Med 1998;339:229–234pmid:9673301
    OpenUrlCrossRefPubMedWeb of Science
  44. ↵
    Centers for Disease Control and Prevention (CDC) (Ed.). National Diabetes Statistics Report: Estimates of Diabetes and Its Burden in the United States, 2014. Atlanta, GA, 2014
  45. ↵
    U.S. Food and Drug Administration. Early Communication About Safety of Lantus (insulin glargine) [article online], 2009. Available from http://www.fda.gov/drugs/drugsafety/postmarketdrugsafetyinformationforpatientsandproviders/drugsafetyinformationforheathcareprofessionals/ucm169722.htm. Accessed 13 December 2013
  46. FDA Drug Safety Communication. Update to ongoing safety review of Lantus (insulin glargine) and possible risk of cancer [article online], 2011. Available from http://www.fda.gov/Drugs/DrugSafety/ucm239376.htm. Accessed 13 December 2013
  47. ↵
    FDA Drug Safety Podcast for Healthcare Professionals. Update to ongoing safety review of Lantus (insulin glargine) and possible risk of cancer [article online], 2013. Available from http://www.fda.gov/Drugs/DrugSafety/DrugSafetyPodcasts/ucm240508.htm. Accessed 13 December 2013
  48. ↵
    European Medicines Agency. Outcome of review of new safety data on insulin glargine [article online], 2013. Available from http://www.ema.europa.eu/docs/en_GB/document_library/Medicine_QA/2013/05/WC500143823.pdf. Accessed 13 December 2013
View Abstract
PreviousNext
Back to top
Diabetes Care: 39 (3)

In this Issue

March 2016, 39(3)
  • Table of Contents
  • Table of Contents (PDF)
  • About the Cover
  • Index by Author
  • Masthead (PDF)
Sign up to receive current issue alerts
View Selected Citations (0)
Print
Download PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for your interest in spreading the word about Diabetes Care.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Effect of Long-Acting Insulin Analogs on the Risk of Cancer: A Systematic Review of Observational Studies
(Your Name) has forwarded a page to you from Diabetes Care
(Your Name) thought you would like to see this page from the Diabetes Care web site.
Citation Tools
Effect of Long-Acting Insulin Analogs on the Risk of Cancer: A Systematic Review of Observational Studies
Jennifer W. Wu, Kristian B. Filion, Laurent Azoulay, Margaret K. Doll, Samy Suissa
Diabetes Care Mar 2016, 39 (3) 486-494; DOI: 10.2337/dc15-1816

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Add to Selected Citations
Share

Effect of Long-Acting Insulin Analogs on the Risk of Cancer: A Systematic Review of Observational Studies
Jennifer W. Wu, Kristian B. Filion, Laurent Azoulay, Margaret K. Doll, Samy Suissa
Diabetes Care Mar 2016, 39 (3) 486-494; DOI: 10.2337/dc15-1816
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

  • Article
    • Abstract
    • Introduction
    • Research Design and Methods
    • Results
    • Conclusions
    • Article Information
    • Footnotes
    • References
  • Figures & Tables
  • Suppl Material
  • Info & Metrics
  • PDF

Related Articles

Cited By...

More in this TOC Section

  • Gaps in Guidelines for the Management of Diabetes in Low- and Middle-Income Versus High-Income Countries—A Systematic Review
  • Alcohol Consumption and the Risk of Type 2 Diabetes: A Systematic Review and Dose-Response Meta-analysis of More Than 1.9 Million Individuals From 38 Observational Studies
Show more Systematic Review

Similar Articles

Navigate

  • Current Issue
  • Standards of Care Guidelines
  • Online Ahead of Print
  • Archives
  • Submit
  • Subscribe
  • Email Alerts
  • RSS Feeds

More Information

  • About the Journal
  • Instructions for Authors
  • Journal Policies
  • Reprints and Permissions
  • Advertising
  • Privacy Policy: ADA Journals
  • Copyright Notice/Public Access Policy
  • Contact Us

Other ADA Resources

  • Diabetes
  • Clinical Diabetes
  • Diabetes Spectrum
  • BMJ Open - Diabetes Research & Care
  • Standards of Medical Care in Diabetes
  • Scientific Sessions Abstracts
  • Professional Books
  • Diabetes Forecast

 

  • DiabetesJournals.org
  • Diabetes Core Update
  • ADA's DiabetesPro
  • ADA Member Directory
  • Diabetes.org

© 2019 by the American Diabetes Association. Diabetes Care Print ISSN: 0149-5992, Online ISSN: 1935-5548.