Metformin use and risk of myeloproliferative neoplasms: a Danish population-based case-control study.

Introduction

The classic Philadelphia chromosome–negative myeloproliferative neoplasms (MPN) are clonal neoplastic disorders that include the disease entities essential thrombocythemia (ET), polycythemia vera (PV), myelofibrosis (MF), and MPN unclassifiable (MPN-U). MPN are characterized by acquired somatic mutations, most commonly in the genes JAK2, CALR, or MPL, resulting in excessive proliferation of myeloid progenitors producing abnormal peripheral blood counts. 1 , 2 , 3 Many patients experience constitutional symptoms due to a hyperinflammatory and hypermetabolic state affecting quality of life and well-being. Additionally, excessive formation of bone marrow (BM) fibrosis ultimately leads to disruption of normal BM function, with ineffective hematopoiesis leading to severe cytopenia and increased risk of leukemic transformation. 4 The compensatory extramedullary hematopoiesis, mainly in the spleen, exacerbates constitutional symptoms and causes symptomatic organomegaly.

Metformin, an oral biguanide derivative used in the treatment of type 2 diabetes mellitus or metabolic syndrome, has become so widely used over the past decades that the drug is now among the most prescribed drugs in Denmark. 5 The use of metformin has been associated with reduced solid tumor risk and mortality in meta-analyses, 6 but results are inconsistent across studies and solid tumor subtypes. The cancer-preventive and clinical effects of metformin for hematological neoplasms, in particular MPN, are not well-investigated. However, preclinical studies have shown antileukemic activity of metformin in myeloid neoplasms by activating the AMP-activated protein kinase (AMPK)-mTOR pathway, downregulating JAK2/STAT signaling, and influencing mitochondrial activity, suggesting possible antineoplastic effects in myeloid neoplasms. 7 , 8 , 9 Knowledge regarding potential pleiotropic and cancer-preventive effects of metformin is of great clinical and public health interest in a time with increased focus on drug repurposing for cancer treatment and prevention. The present study investigated the association between metformin use and the risk of MPN in the Danish population.

Materials and methods

Study design and Danish nationwide health registers

This Danish population–based case-control study compared metformin use between patients diagnosed with MPN (cases) and a matched population from the Danish general population (controls) in the period between 2010 and 2018. Associations between MPN and metformin use, including duration of use, was estimated using odds ratios (ORs).

The following 5 nationwide health registers were merged by using the unique 10-digit personal identification number (CPR number) given to Danish citizens at birth or immigration 10 , 11 : the Danish Civil Registration System, 10 , 11 the National Patient Register, 12 , 13 the Danish National Chronic Myeloid Neoplasia Registry (DCMR), 14 the Danish National Prescription Registry (DNPR), 15 , 16 and the Danish Education Registers 17 (the supplemental Material includes more detailed information).

Case and control selection

Cases with MPN were identified using the DCMR covering over 90% of MPN cases in Denmark since 2010. 14 Cases had to be Danish residents with an MPN (ET, PV, MF, or MPN-U) diagnosis according to the World Health Organization (WHO) criteria from 2008 or later 18 , 19 between 1 January 2010 and 31 December 2018. The index date was defined as the first registered date of the MPN diagnosis from the DCMR. Moreover, to ensure a medical history spanning a minimum of 10 years, all cases and controls were required to have been continuous residents for at least 10 consecutive years before the index date. Controls were selected by incidence density sampling in a 5:1 control-to-case ratio from the Danish general population matched on age, sex, and index date. 20 Cases and controls were excluded if MPN or other cancers had been diagnosed before the index date (supplemental Material includes more detailed information, with the exception of nonmelanoma skin cancer and carcinomas in situ). The exclusion of previous cancers was aimed at preventing the inclusion of therapy-related MPN.

Metformin exposure assessment

Information on metformin exposure was retrieved from the DNPR (ATC code: A10BA02). Ever-use of metformin was defined as having redeemed at least 1 prescription of metformin before the index date, and never-use was defined as no filled prescription of metformin before the index date. Long-term use was defined as ≥5 years of cumulative treatment with metformin before the MPN diagnosis. The DNPR does not contain information on prescribed doses or indication for the treatment. Therefore, cumulative treatment duration was determined on the basis of the WHO-defined daily dose of metformin at 2000 mg, with an additional 25% of days to accommodate variations in prescription filling patterns and minor instances of noncompliance. The use of metformin in the 12 months before the index date was disregarded in the primary analyses to avoid reverse causation.

Covariates and confounders

Data from the National Patient Register (diagnoses to assess comorbidity), the DNPR (prescriptions related to conditions or use of drug with suggested cancer-protective properties), and the Danish Education Registers (demographics and education) were used to adjust for the following prespecified potential confounders: (1) highest achieved educational level (primary school; high school; short/middle long education; long education) as a measure of socioeconomic status; (2) Charlson Comorbidity Index 21 (CCI: 0; 1; ≥2); 3) use of drugs with suggested cancer-preventive effects 22 including aspirin, nonsteroidal anti-inflammatory drugs, alendronate, immunosuppressants, and statins (≥2 previous prescriptions for all); and (4) markers of smoking (diagnosis of chronic obstructive pulmonary disease or use of bronchodilating inhalation agents containing an antimuscarinic component), markers of autoimmune diseases (AD) (diagnosis codes or prescription of immunomodulating drugs), and diagnoses related to excessive alcohol consumption (diagnose codes and prescription of disulfiram). Information to compute CCI was collected from the National Patient Register, using ICD-10 codes associated with the diagnoses of 19 chronic conditions. Detailed information regarding included ICD- 10 codes and definitions is provided in supplemental Table 1 . In the primary analysis, data used for assessing confounding were excluded for the 12-months period leading up to the index date to avoid misclassification.

Statistical analysis

Categorical variables were reported as counts and percentages, and continuous variables were reported as medians with interquartile range ([IQR]; 25th to 75th percentile). For our primary analysis, we assessed the association between metformin use (exposure) and MPN (outcome) using conditional logistic regression to obtain sex- and age-adjusted ORs and a fully-adjusted model (aORs, adjusted for sex, age, calendar time, educational level, CCI, previous use of drugs with suggested cancer-preventive effects, history of alcohol-related diagnoses, overweight/obesity, chronic obstructive pulmonary disease, and AD) provided with 95% confidence intervals (CIs). Analyses stratified by subtype of MPN (MF, PV, ET, and MPN-U), sex (male and female), age group (<60 years; 60-75 years; >75 years), molecular subtype ( JAK2- or CALR -mutated [see supplemental Table 2 for additional information]), and absence of AD were performed to investigate subgroup associations between long-term metformin use and MPN risk. Furthermore, for long-term use, analyses were repeated with single potential confounders to show the effects of single confounder adjustments and to analyze the contribution of each suggested confounder. Conducting a sensitivity analysis, we varied the lag time (ie, the disregarded time before index date when assessing exposure and confounders) for the analysis of long-term use by 6-month increments.

Statistical analyses were conducted using SAS version 9.4 (SAS Institute Inc), Rstudio version 1.1.447 (Rstudio, Inc), and R version 3.6.1 (R Foundation for Statistical Computing). The study was approved by the institution responsible for the data (North Denmark Region, approval number: 2021-034) in accordance with the General Data Protection Regulation.

Results

A total of 3816 cases and 19 080 matched controls were included ( Table 1 ). The case cohort comprised 1306 (34.2%) patients with PV, 1307 (34.3%) with ET, 574 (15.0%) with MF, and 629 (16.5%) with MPN-U. Most cases had available information on molecular testing (96%), 2871 (78.4%) had a JAK2- V617F mutation, and 184 (5.0%) had a CALR mutation. Aspirin use was more common among cases (34.4% vs 26.4%), and cases had a higher CCI. Otherwise, baseline characteristics were balanced between groups ( Table 1 ).

For the primary analysis, a total of 268 (7.0%) cases were categorized as ever-users of metformin as opposed to 1573 (8.2%) of controls, yielding an age- and sex-adjusted OR for MPN of 0.84 (95% CI, 0.73-0.96). Long-term use (≥5 years) was observed in 1.1% of cases and 2.0% of controls, resulting in an OR of 0.57 (95% CI, 0.42-0.79) ( Table 2 ). When adjusting for potential confounders in the fully-adjusted model, the aORs for MPN were 0.70 (95% CI, 0.61-0.81) and 0.45 (95% CI, 0.33-0.63) for ever-users and long-term users, respectively ( Table 2 ). When assessing the effect of cumulative duration of treatment, no clear relationship was found for the sex- and age-adjusted estimates. However, a dose-response relationship was present in the fully-adjusted model with aORs of 0.79 (95% CI, 0.62-1.00) for <1 year, 0.78 (95% CI, 0.64-0.95) for 1 to 4.99 years, 0.42 (95% CI, 0.29-0.61) for 5 to 9.99 years, and 0.56 (95% CI, 0.30-1.03) for >10 years ( Table 2 ).

In stratified analyses including long-term users (≥5 years of cumulative treatment), the magnitude of the effect was observed across all age groups, with aORs of 0.47 (95% CI, 0.15-1.50) for <60 years, 0.45 (95% CI, 0.28-0.71) for 60 to 75 years, and 0.46 (95% CI, 0.27-0.78) for >75 years ( Table 3 ). Furthermore, the protective effect of long-term metformin use was consistent according to sex, but stronger in male patients, with an aOR of 0.37 (95% CI, 0.23-0.60) compared with 0.56 (95% CI, 0.36-0.89) among female patients ( Table 3 ). The protective effect of metformin was observed in all subtypes of MPN (PV: aOR, 0.45; [95% CI, 0.26-0.77]; ET: aOR, 0.33; [95% CI, 0.16-0.67]; MF: aOR, 0.65; [95% CI, 0.32-1.33]; MPN-U: aOR, 0.46; [95% CI, 0.20-1.06]) ( Table 3 ). Additionally, when restricting the analysis to molecular subtypes, similar magnitude of protective effect was observed, with aORs of 0.47 (95% CI, 0.32-0.68) and 0.53 (95% CI, 0.11-2.50) for JAK2- V617F- and CALR -mutated MPN, respectively. Finally, when restricting the analysis to cases and controls without markers of AD, the effect was of the same magnitude as observed in the primary analysis, with an aOR of 0.46 (95% CI, 0.32-0.64) ( Table 3 ).

As a supplemental analysis, the effects of adjustment for single potential confounders were investigated, and estimates are given in supplemental Table 2 . With the exception of adjustments for the previous use of aspirin and CCI, adjustment for each confounder had limited influence on the estimate. As a sensitivity analysis to assess the potential of reverse causation, we varied the lag time in 6-month increments, and no large differences were observed for our estimate ( supplemental Table 3 ).

Discussion

In this large Danish population–based case-control study, we showed an association between metformin use and decreased risk of MPN. The magnitude of this association showed a clear dose-response relationship with increasing cumulative treatment duration. Furthermore, this effect was numerically consistent in stratified analyses, implying effect in both male and female patients, different age strata, and MPN subtypes including molecular subtypes, although not all estimates reached statistical significance because of small numbers. Collectively, the results indicate that metformin may reduce the risk of MPN.

To our knowledge, this study is the first to investigate this association specifically for MPN. However, a recent study collectively investigated hematological cancers including multiple myeloma, leukemia, and lymphoma among US veterans with diabetes. 23 In this large retrospective cohort study using inverse probability of treatment weighting, metformin users aged 55 to 75 years had significantly lower risk for both incident solid and hematological cancers than sulfonylurea users with diabetes. 23 The estimated hazard ratio (HR) for hematological malignancy was similar to that of solid cancers, with inverse probability of treatment weighting-adjusted HRs for hematological cancer of 0.68 (95% CI, 0.54-0.87) and 0.79 (95% CI, 0.63-0.98) for age of 55 to 64 and 65 to 75 years, respectively. 23 In comparison with our study (and taking into account different age strata, control groups, and study designs), which found the most pronounced effect in older individuals aged >59 years (including those aged >75 years), Abdallah et al 23 recorded the most pronounced effect in younger individuals and no effect in individuals aged ≥75 years.

Similarly, an observational study using the US veteran cohort investigated the effect of metformin use (≥4 years of treatment) on the progression to multiple myeloma from monoclonal gammopathy of undetermined significance. This study showed a significantly reduced risk of progression associated with metformin treatment, with an adjusted HR of 0.47 (95% CI, 0.25-0.87). 24 Like multiple myeloma preceded by the premalignant disorder monoclonal gammopathy of undetermined significance, MPN develops from a stage characterized by clonal hematopoiesis of indeterminate potential (CHIP), and strong evidence suggests that CHIP-MPN are extremely underdiagnosed. 25 A previous Danish study investigating the population prevalence of JAK2 -V617F- and CALR -mutated clones surprisingly found a prevalence of 3.2%, with most being small clones with variant allele frequency <1%. 25 Notably, only a minor fraction of these individuals had an MPN diagnosis, but ∼50% had abnormal laboratory findings. A CHIP stage of MPN with vague symptoms and chronic inflammation may also explain an observed increase in the utilization of health care resources before the diagnosis of an overt MPN. 26

Because the present study is merely observational and registry-based, we cannot assess the mechanism by which metformin might protect against the development of MPN. However, additionally supportive of a CHIP-MPN hypothesis, a recent phase 2 study failed to demonstrate an effect of metformin in reversing bone marrow fibrosis in patients with MF. Yet, the study showed significant downregulation of the JAK-STAT pathway and reduced levels of the proinflammatory cytokine interleukin-5. 27 These results indicate that metformin does inhibit the central pathway in MPN in addition to dampening the chronic inflammation, which is considered a key factor for clonal expansion and evolution toward overt MPN. 28 , 29 Consistent with this, we have previously shown that the use of statins, another agent assumed to possess antineoplastic and anti-inflammatory properties, also reduced the risk of developing MPN. 30 Furthermore, a more recent study showed that statin treatment after the MPN diagnosis was associated with prolonged survival and reduced incidence of thrombosis. 31

Many other studies have investigated the association between metformin use and risk of solid cancers, and meta-analyses suggest a relative risk reduction at a magnitude of 30% to 55% for specific cancer sites including colorectal, liver, pancreatic, stomach, and esophageal cancer in addition to reduced risk of cancer-related death. 6 , 32 , 33 Although observational studies provide a strong rationale for a cancer-protective effect of metformin, the efforts to explore this potential effect prospectively have been very limited. One reason may be the need for large numbers of study participants and long follow-up time to obtain adequate power to detect differences in cancer incidence. However, several clinical trials have been undertaken in populations at higher risk of developing malignancies. A phase 3 randomized study investigated the effect of metformin treatment on prevalence and number of colorectal adenoma or polyps among nondiabetic patients with recent polypectomy. 34 This study showed that treatment with metformin resulted in a significantly lower risk of polyps and adenomas at the 1-year follow-up colonoscopy compared with placebo. 34 Furthermore, among breast cancer patients treated with tamoxifen and at high risk of developing endometrial polyps, hyperplasia, and cancer, metformin appeared to inhibit and prevent tamoxifen-induced endometrial changes in a randomized clinical trial. 35 Again, these studies suggest that metformin may excel in inhibiting premalignant states and hinder progression to overt disease.

Metformin either as a single agent or combined with cytotoxic, endocrine, or targeted therapy has also been investigated in a handful of solid cancers, but most of these studies have failed to demonstrate the clinical benefit of metformin. 36 Latest, and most notably, the phase 3 randomized MA.32 trial, randomized over 3600 nondiabetic patients with high-risk nonmetastatic breast cancer to 850-mg metformin twice daily vs placebo for 5 years. 37 The study did not meet the primary end point of improved invasive disease-free survival, and the investigators concluded that the addition of metformin for 5 years to standard-of-care treatment in this population did not show any beneficial clinical effects. 37 Interestingly, in an explorative analysis of patients with human epidermal growth factor receptor 2–positive disease, the addition of metformin to standard-of-care was associated with longer invasive disease–free survival and overall survival for the C allele of the rs11212617 single-nucleotide variant. However, this should be interpreted with caution and is yet to be confirmed independently. 37

The present study has several strengths and limitations. Using the Danish registers ensures individual-level high-quality data and complete follow-up of every individual living in Denmark in the study period, allowing for detailed exposure and covariate measurements. Furthermore, using the DCMR to identify MPN cases ensures a high degree of diagnostic certainty, and the good coverage of the register of 90% in earlier periods and exceeding 90% in later periods entails limiting selection bias and high generalizability. 14 Although the virtually similar proportions of patients with ET and PV in our cohort are surprising, this might reflect the well-known misclassification of JAK2 -V617F–positive ET. 38 Even if some patients may have been misclassified as having ET instead of PV, we still see a similar protective effect of metformin for both subtypes. Therefore, this potential misclassification has limited impact on our results. Furthermore, 16.5% of patients were classified as MPN-U, representing a clinically and molecularly heterogeneous group of patients including overlapping myelodysplastic and myeloproliferative syndromes. However, for these patients, the magnitude and direction of the association were similar to those observed in more established MPN entities.

For the present study, we also recognize limitations related to the registry-based retrospective design. Firstly, patients receiving metformin may differ substantially from patients who did not, leading to potential unmeasured bias in our estimates. Studies on drug–cancer relationships have the potential to suffer from healthy user bias. Namely, patients using metformin may be more aware about their health and thus improving their health habits, leading to a lower risk of developing cancer, including MPN. 39 These factors and habits are extremely difficult to measure and adjust for, and despite efforts to adjust for several conditions known to influence metformin prescription (exposure) and the development of MPN (outcome), the data quality for confounder assessment remains a limitation in the present study. We cannot exclude the presence of residual confounding related to lifestyle, including smoking, overweight, and dietary habits. Particularly, obesity is an important confounding factor due to the association between obesity-related inflammation and clonal expansion of CHIP-related clones. 40 To adjust for overweight and obesity, we used diagnostic codes from the National Patient Register and classified 4.1% and 4.4% as overweight or obese among cases and controls, respectively. We acknowledge that this proportion is much lower than expected from a recent Danish study with data from 2021 showing that 18.4% of adults were considered obese. 41 This discrepancy may originate in the registration procedure of primary and secondary diagnostic codes in our health care system, where the primary cause of contact is prioritized. A previous study evaluating ICD-10 codes for overweight and obesity found a coverage of only ∼11%, but with a very satisfactory positive predictive value for registered patients. 42 Furthermore, increased medical surveillance and attention around the prescription of a new drug could also affect our results given that more regular laboratory tests could detect abnormal blood counts, leading to further investigations. To assess this bias, we conducted a sensitivity analysis by varying the lag time for exposure and confounder assessment around the diagnosis, which did not alter our findings significantly.

Moreover, metformin users could also differ in other risk factors associated with decreased or increased risk of cancer (eg, socioeconomic factors or lifestyle) compared with individuals using other types of antidiabetic medications or no antidiabetic medication. The presence of type 2 diabetes mellitus has been associated with increased risk of subtypes of MPN in 1 study, 43 whereas another found no association 44 ; however, for this study, if an association exists, it would bias the estimate against no association between metformin use and risk of MPN.

In summary, this study showed significant reduction in risk of MPN among metformin users and a dose-response relationship, with long-term use of metformin having more protective effects. However, overall, given the rarity of MPN, the absolute risk reduction is small and primary prophylaxis is not feasible. Given the retrospective design, causality cannot be established from the present study, and further studies are needed. We believe that our findings merit future well-designed prospective studies on a high-risk population, that is, patients with low level JAK2 -V617F positive clones not meeting the current WHO criteria for MPN.

Conflict-of-interest disclosure: D.T.K. serves as a member on consulting/advisory boards for AbbVie, Atheneum, and Astellas Pharma. H.C.H. is the chairman of the scientific committee for the INCA 33989-101 study (mCALR-101), Incyte; is a member on the advisory boards of AOP Orphan and Incyte; and is part of the scientific committee of Incyte. A.S.R. received consulting fees from AbbVie and Pfizer and a travel grant from Jazz Pharmaceuticals. The remaining authors declare no competing financial interests.

The current affiliation for L.H.K.J. is Novo Nordisk.

Acknowledgments

The authors express profound gratitude to everyone who has participated in forming and collecting data for the National Chronic Myeloid Neoplasia Registry, the Danish Clinical Quality Program, and the National Clinical Registries for providing and governing the data.

This study was supported by a grant from the Danish Cancer Society to D.T.K. and A.S.R. (grant number R327-A18949) and to T.C.E.-G. (grant number R274-A17146).

Authorship

Contribution: D.T.K., A.K.Ø., L.H.K.J., M.T.S., T.C.E.-G., and A.S.R. conceived and designed the study; D.T.K., A.K.Ø., M.T.S., L.H.H., J.S., M.H.H., A.P.V., M.B., H.C.H., and A.S.R. provided the study materials or patients; D.T.K., A.K.Ø., and A.S.R. collected and assembled the data; D.T.K., A.K.Ø., L.H.K.J., M.T.S., T.C.E.-G., and A.S.R. analyzed and interpreted the data; and all authors wrote the manuscript, approved the final version of the manuscript, and are accountable for all aspects of the work.

Footnotes

D.T.K. and A.K.Ø. contributed equally to this study.

Per Danish law, the data cannot be shared directly; however, they can be accessed through application.

Additional information is available on request from the corresponding author, Anne Stidsholt Roug ( annrou@rm.dk ) or at www.rkkp.dk/in-english/ and www.dst.dk/en/TilSalg/Forskningsservice/Data .

The full-text version of this article contains a data supplement.

Supplementary Material

Supplemental Methods, Tables, and References

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Supplementary Materials

Supplemental Methods, Tables, and References