Study Highlights WHAT IS THE CURRENT KNOWLEDGE ON THE TOPIC?

☑ Observational evidence with regard to the potential chemoprotective effect of vitamin K antagonists (VKAs) is unclear and may be affected by several confounding biases.

WHAT QUESTION DID THIS STUDY ADDRESS?

☑ Whether patients with atrial fibrillation (AF) treated with VKA are protected against cancer when compared with patients treated with non-VKA (direct oral anticoagulant (DOAC)) agents.

WHAT DOES THIS STUDY ADD TO OUR KNOWLEDGE?

☑ In this population-based, propensity-weighted cohort study comprising 39,989 patients with AF that initiated oral anticoagulant treatment followed for up to 5 years, we found no risk reduction of cancer incidence in patients using VKA compared with DOAC users. Several sensitivity and subgroup analyses produced comparable results.

HOW MIGHT THIS CHANGE CLINICAL PHARMACOLOGY OR TRANSLATIONAL SCIENCE?

☑ Our findings do not confirm a chemoprotective effect of VKA as a protective factor against cancer when compared with DOAC in patients with AF.

Vitamin K antagonists (VKAs), such as warfarin, phenprocoumon, or acenocoumarin (the most prescribed VKA in Spain), are traditionally used as oral anticoagulant (OAC) agents and are widely prescribed worldwide, mainly for atrial fibrillation (AF), valvular heart disease, and venous thromboembolism. In the last decade, non-VKA oral anticoagulants, namely dabigatran, rivaroxaban, apixaban, and edoxaban, that directly inhibit thrombin or factor-X have been commercialized (direct oral anticoagulants (DOACs)). In several clinical trials and observational studies, DOAC appears to be at least as effective and safe to VKA,1-3 with some advantages and disadvantages.4 They have rapidly replaced VKA in their approved indications and, currently, DOAC is the treatment of choice for patients with nonvalvular AF (NVAF) in most developed countries.

Different in vitro and animal experimental models have proposed the antitumorigenic potential of VKA.5-7 A clear molecular mechanism by which VKA would affect cancer development has not been identified yet, but it has been postulated that VKA inhibits the AXL receptor signaling (a vitamin K-dependent receptor of the tyrosine-kinase family associated with immunity and cancer), consequently enhancing natural killer cell antitumor activity.7 In humans, the evidence of VKA antitumorigenic effect remains inconclusive. Some studies suggest the existence of a generalized antitumor effect8, 9 others find limited effects in some types of tumors (essentially prostate cancer),10-12 whereas others do not find a relationship between VKA exposure cancer risk reduction13-15 (including prostate cancer16-18), or even suggest an increased risk of some cancer types.19 Clinical trials and observational studies are heterogeneous regarding study populations or time of VKA exposure, or are affected by insufficient sample sizes or common biases present in causal observational studies, such as confounding by selection, immortal-time bias, lack of active comparators, and inadequate adjustment of potential confounding. Two recent meta-analyses provide an accurate picture of this heterogeneity and of the reported opposite conclusions about VKA effectiveness, notably regarding prostate cancer risk reduction.17, 20

In this context, and given that OAC therapy can entail severe risks, the clinical use of VKA as a cancer preventive therapy cannot be recommended, until well-designed and adequately powered randomized clinical trials confirm its efficacy and its risk-benefit balance. Nevertheless, well-designed real-world data studies can provide relevant information about the antitumorigenic effect of VKA when compared with other OAC agents, and this evidence may be useful for guidance on treatment choice (VKA vs. DOAC) in patients requiring oral anticoagulation.

Our aim was to examine the association between VKA or DOAC use and cancer incidence, overall and for some specific cancers, in a large, population-based cohort of patients with NVAF that initiate OAC treatment.

METHODS Study design

This population-based retrospective cohort included all patients aged 40 years and over with NVAF or atrial flutter who initiated oral anticoagulant therapy (with either a VKA or a DOAC) from November 1, 2011, to December 31, 2015. Patients were followed up to December 31, 2016.

Data sources

Data were obtained from the VHS Integrated Databases (VID). The VID is the result of the linkage, by means of a single personal identification number, of a set of publicly owned, population-based healthcare, clinical and administrative electronic databases in Valencia, which has provided comprehensive information for the region’s 5 million inhabitants since 2008. It includes sociodemographic and administrative data (sex, age, and nationality) as well as healthcare information, such as diagnoses, procedures, laboratory data, pharmaceutical prescriptions, and dispensing (including brand and generic name, formulation, strength, and dosing schedule/regimen), hospitalizations, mortality, healthcare utilization, and public health data. Additionally, the VID includes a set of specific associated databases with population-wide information on significant care areas, such as rare diseases, vaccines, imaging data, or the regional Cancer Information System, from which information on cancer incidence was retrieved.21, 22

Setting

The study was conducted in the region of Valencia, namely in the Valencia Health System (VHS), an extensive network of public hospitals and primary healthcare centers, which is part of the Spanish National Health System,23 funded and mostly provided by the Valencia Regional Government, free at the point of care (except for some co-payments for out-of-hospital medication), and almost universal, covering about 97% of the region’s population (~ 5 million inhabitants, equivalent to 10% of the Spanish population or 1% of the European population).

Population and inclusion/exclusion criteria

All patients aged 40 years and over with a diagnosis of NVAF or atrial flutter, according to the diagnosis code of the corresponding version of the International Classification of Diseases Clinical Modification (ICD-9-CM: 427.31; ICD-10-ES: I48) who initiated therapy for stroke prevention in NVAF with an OAC medication (warfarin, acenocoumarin, dabigatran, rivaroxaban, or apixaban) from November 1, 2011 (date of market launch of the first DOAC for NVAF in Spain) to December 31, 2015, were initially included, and follow-up was available up to the date of data extraction (December 31, 2016). Patients without anticoagulant treatment for stroke prevention in NVAF in the 12 months preceding the index prescription (index date) were defined as therapy initiators (naïve patients), and thus were included in the study; non-naïve patients were excluded. People without pharmaceutical/health coverage by the VHS (mainly some Spanish central government employees whose prescriptions are reimbursed by civil service insurance mutualities, and thus not included in the pharmacy databases of the VHS), and patients not registered in the municipal census (non-residents or temporary residents) were excluded due to limitations on follow-up. Other exclusion criteria were age under 40 years old, presence of valvular disease (in Spain, DOACs are not licensed to treat valvular heart disease) or presence of a cancer diagnosis in the 24 months before the index date (see Table S1 for codes used). Finally, patients were divided into two groups according to the choice of initial prescription, resulting in the VKA and DOAC cohorts (see Figure 1 Flowchart).

Study population. DOAC, direct oral anticoagulant; NVAF, nonvalvular atrial fibrillation; OAC, oral anticoagulant; VKA, vitamin K antagonist; VTE, venous thromboembolism.

Main end point

A combined end point of diagnosis of any incident malignant neoplasm during the follow-up period, except nonmelanoma skin malignancy. See Table S2 for codes used.

Secondary end points

Diagnosis of the types of cancers with a higher observed incidence during that follow-up period in the region include: lung, colon, prostate, bladder, and breast cancer.24 See Table S2 for codes used.

Follow-up

Follow-up of the cohorts for the identification of end points started at the index date and lasted until censoring or the end of the follow-up period. In the main intention-to-treat analyses, follow-up was censored in the occurrence of any incident cancer diagnosis included in our primary and secondary end points, death or loss of coverage (individuals leaving the region, mainly). In secondary per-protocol analysis, we included all patients with at least 150 days covered with medication over a period of 180 days or less since therapy initiation. Patients who discontinued or switched were followed up (in their original group in the case of switching) for up to 12 months from the date of discontinuation or switching. Discontinuation was defined as having at least 60 days consecutive days without medication; switching was defined as discontinuation of VKA treatment and initiation of DOAC treatment lasting for at least 2 months, or vice versa. Covariates

We used a 12-month look-back period since the index date to define the baseline sociodemographic, clinical, and lifestyle characteristics of the population. Sociodemographic data included age, sex, country of origin, vulnerability status, and income. Cancer risk factors included chronic obstructive pulmonary disease, inflammatory bowel disease, rheumatologic diseases, previous organ transplantation, gastritis, polyps, and lifestyle factors, such as tobacco and alcohol use. Other clinical conditions included were congestive heart failure, hypertension, diabetes, liver and renal disease, previous ischemic stroke or transient ischemic attack, coronary artery disease, gastrointestinal bleeding, venous thromboembolism or pulmonary embolism (VTE-PE), dementia, and depression (see Table S3 for codes used).

Ethics

The study protocol was classified by the Spanish Drugs and Medical Devices Agency as a “Post-authorization study with designs other than prospective follow-up” (Ref. FIS-ACO-2018-01) and received ethics approval by the Research Ethics Committee of the “Hospital Clínico-Universitario de Valencia” (Ref. F-CE-GEva −14 v1.2; October 26, 2018). As usual in anonymized real-world data studies, patient consent was waived. According to the EU General Data Protection Regulation and Spanish law, data accessed by researchers rely on pseudo-anonymized, non-traceable codes that do not allow the identification of individual patients.

Statistical analysis

We used an intention-to-treat approach for our main analyses. First, we described the characteristics of the cohorts (means for continuous variables and frequencies for categorical variables). Second, we performed a time-to-event analysis from the data of therapy initiation to the first incident cancer or censoring event. Third, we used a stepwise Cox proportional hazards regression with an entry and removal alpha significance level of 0.2 and 0.1, respectively, using DOAC as the primary reference, to assess the risk of cancer in the VKA cohort compared with the DOAC cohort. To deal with potential confounding by indication, we used an inverse probability treatment-weighting estimation (IPTW). Stabilized weights were derived to obtain estimates representing population average treatment effects.25, 26 The underlying propensity models were estimated using a logistic regression analysis and including all available covariates (see Table S3) to minimize confounding. Covariate balance between the weighted exposure cohorts was assessed using standardized mean differences, with standardized differences < 0.10 suggesting adequate balance.27 Incidence rates by 1,000 person-years in both cohorts as well as crude and adjusted hazard ratios (HRs) for risk of cancer in VKA patients when compared with DOAC patients were presented as main results. We also plotted Kaplan–Meier survival curves for the primary and secondary end points over the observation window of 5 years. We then carried on several secondary, sensitivity analyses. Fourth, we performed an additional IPTW analysis after weight truncation (all weights with value below the 2.5th percentile and above the 97.5th percentile were set equal to the values of the 2.5th and 97.5th percentiles). Fifth, we conducted a competing risk regression analysis (using the Fine and Gray method) with mortality handled as a competing event. Sixth, we performed per-protocol analyses, using IPTW and IPTW with truncation. Finally, we analyzed associations stratified by gender and for specific subgroups, such as patients with AF (excluding patients with flutter), patients 65 years and over, and patients initiating from August 1, 2013 (date of market launch of apixaban for NVAF in Spain; date from which all drugs under assessment in this study were available for prescription).

RESULTS

After exclusion criteria, we identified a study population of 39,989 patients, 31,200 (78.0%) in the VKA cohort and 8,789 in the DOAC cohort. Patients starting treatment with VKA were older than DOAC initiators (75.4 years old vs. 74.4, P < 0.001), with a higher proportion of women (48.3% vs. 46.8%, P < 0.001), of those born in Spain (91.3% vs. 88.2%, P < 0.001) and of people with low income (76.9% vs. 71.6% of patients earning < 18,000 euros/year, P < 0.001). They showed a higher prevalence of heart failure (18.5% vs. 15.7%, P < 0.05), hypertension (80.4% vs. 77.1%, P < 0.05), diabetes (35.9% vs. 31.4%, P < 0.001), renal failure (13.8% vs. 9.6%, P < 0.001), VTE-PE (7.5% vs. 5.2%, P < 0.001), and previous organ transplantation (0.6% vs. 0.2%, P < 0.001), but less inflammatory bowel disease (0.6% in the VKA cohort vs. 0.9% in the DOAC cohort, P = 0.005), coronary disease (18.1% vs. 18.5%, P < 0.001), previous stroke or transient ischemic attack (20% vs. 21.8%, P < 0.001), and dementia (6.8% vs. 8.2%, P < 0.001). After inverse probability weighting, the standardized differences were < 0.2 for all covariates, resulting in a cohort with a comparable distribution of baseline covariates between groups (see Table 1). Propensity score weight distribution is available at Supplementary Material Figure S4. The median follow-up time was 2.94 years and was similar although slightly longer in the VKA cohort than in the DOAC cohort (VKA: 3.05 years, interquartile range: 1.96–4.10, DOAC: 2.62 years, interquartile range: 1.68–3.65).

Table 1. Patients’ characteristics at baseline and weighted characteristics after IPTW Patients’ characteristics n = 39,992 Weighted populations

DOAC

n = 8,789

VKA

n = 31,200

DOAC VKA Standardized diff. Mean SE Mean SE Mean Mean Before After Age (age when first started treatment) 74.42 0.12 75.36 0.05 75.33 75.17 0.09 −0.015 N % N % % % Sex (female) 4,112 46.8 15,054 48.3 48.3 48.0 0.029 −0.007 Country Africa 60 07 160 0.5 0.6 0.5 −0.022 −0.015 America 75 0.8 213 0.7 0.8 0.7 −0.020 −0.017 Spain 7,755 88.2 28,488 91.3 88.5 91.2 0.102 0.089 Europe 739 8.4 1,699 5.4 8.2 5.5 −0.117 −0.107 Other 160 1.8 640 2.1 1.8 2.1 0.017 0.020 Vulnerability No risk 8,087 92.0 28,655 91.8 92 91.8 −0.006 −0.005 Unemployed 169 1.9 560 1.8 1.7 1.9 −0.009 0.014 Irregular foreigner 2 0,02 14 0.04 0 0 0.012 0.013 Without resources 218 2,5 772 2.5 2.5 2.5 0.000 −0.004 Undefined 4 0,1 11 0.04 0 0 −0.005 −0.006 Missing 309 3,5 1,188 3.8 3.7 3.7 0.016 0.000 Income < 18,000 6,294 71,6 23,996 76.9 70.5 76.8 0.121 0.098 18,000–100,000 1,836 20,9 4,722 15.1 20 15.3 −0.150 −0.122 > 100,000 75 0,9 63 0.2 0.8 0.2 −0.090 −0.078 Without resources 309 3,5 1,211 3.9 3.6 3.9 0.019 0.016 Unknown 275 3,1 1,208 3.9 3.2 3.9 0.040 0.036 Cancer risk factors Smoking 899 10,2 3,395 10.9 10.7 10.7 0.021 0.003 Gastritis 530 6,0 1,867 6.0 6.1 6 −0.002 −0.002 Intestinal polyps 146 1,7 500 1.6 1.6 1.6 −0.005 −0.002 COPD 439 5,0 1,715 5.5 5.4 5.4 0.023 0.000 Inflammatory bowel disease 79 0,9 191 0.6 0.7 0.7 −0.032 0.002 Alcohol use 178 2,0 678 2.2 2.2 2.1 0.004 −0.003 Comorbidities Rheumatologic diseases 193 2.2 729 2.3 2.3 2.3 0.009 −0.002 Previous organ transplant 18 0.2 175 0.6 0.5 0.5 0.058 0.004 Coronary heart disease 1,471 18.5 5,781 18.1 18.2 17.9 0.047 −0.007 VTE-PE 458 5.2 2,330 7.5 7.0 7.0 0.093 −0.002 Gastrointestinal bleeding 355 4.0 1,284 4.1 4.1 4.1 0.004 −0.005 Heart failure 1,382 15.7 5,756 18.5 18.2 17.9 0.072 −0.009 Hypertension 6,775 77.1 25,090 80.4 79.9 79.7 0.082 −0.005 Diabetes 2,756 31.4 11,188 35.9 35.1 34.9 0.095 −0.004 Liver disease 615 7.0 2,274 7.3 7.2 7.2 0.011 0.000 Renal disease 839 9.7 4,315 13.8 12.9 12.9 0.134 0.001 Previous stroke or TIA 1,912 21.7 6,255 20.1 20.7 20.5 −0.042 −0.006 Dementia 717 8.2 2,129 6.8 7.2 7.1 0.031 −0.005 Depression 1,194 13.6 4,285 13.7 13.8 13.7 −0.051 −0.002 COPD, chronic obstructive pulmonary disease; DOAC, direct oral anticoagulant; IPTW, inverse probability treatment-weighting; TIA, transient ischemic attack; VKA, vitamin K antagonist; VTE-PE, venous thromboembolism or pulmonary embolism.

In the main analysis and for the primary end point, the incidence rate for any cancer was 12.45 per 1,000 person-years in the DOAC cohort, vs. 14.55 in the VKA cohort (crude HR: 1.19; adjusted HR: 1.16, 95% confidence interval (CI): 1.02–1.32). For secondary end points, no differences were found for specific types of cancer, such as lung (HR: 1.28, CI: 0.89–1.83), colon (HR: 0.84, CI: 0.62–1.13), prostate (HR: 1.40, CI: 0.94–2.10), bladder (HR: 1.07, CI: 0.76–1.52), and breast (HR: 1.05, CI: 0.66–1.69; see Table 2 and Figure 2). Kaplan–Meier survival curves for the main and secondary end points show the trends in the occurrence of events in both groups over time (see Figure 3). Secondary sensitivity analyses, including weight truncation, the per protocol approach, and the competing risks analysis yielded similar results (see Table 3). In subgroup analyses, men showed a significant reduction in the risk of colon cancer (HR: 0.68; 95% CI: 0.48–0.96). All other differences were nonsignificant for both primary and secondary outcomes (see Table S5).

Table 2. Incidence rates by 1,000 person-years in both cohorts as well as crude and adjusted HRs and 95% CI) for risk of cancer in VKA patients compared to DOAC patients Cancer Group Person-time Failures Rate 95% CI Crude HR 95% CI Adj. HR 95% CI Any DOAC 23,051.44 287 12.45 11.09 13.98 1.19 1.05 1.35 1.16 1.02 1.32 VKA 91,751.50 1335 14.55 13.79 15.35