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. 2024 Jul 1;21(7):e1004400. doi: 10.1371/journal.pmed.1004400

Direct factor Xa inhibitors and the risk of cancer and cancer mortality: A Danish population-based cohort study

Floris Bosch 1,2,3,*, Erzsébet Horváth-Puhó 4, Suzanne C Cannegieter 5,6, Nick van Es 2,3, Henrik T Sørensen 4
Editor: Aadel A Chaudhuri7
PMCID: PMC11251598  PMID: 38950074

Abstract

Background

Preclinical animal studies have suggested that myeloid cell–synthesized coagulation factor X dampens antitumor immunity and that rivaroxaban, a direct factor Xa inhibitor, can be used to promote tumor immunity. This study was aimed at assessing whether patients with atrial fibrillation taking direct factor Xa inhibitors have lower risk of cancer and cancer-related mortality than patients taking the direct thrombin inhibitor dabigatran.

Methods and findings

This nationwide population-based cohort study in Denmark included adult patients with atrial fibrillation and without a history of cancer, who started taking a factor Xa inhibitor or dabigatran between 2011 and 2015. Data on medical history, outcomes, and drug use were acquired through Danish healthcare registries. The primary outcome was any cancer. Secondary outcomes were cancer-related mortality and all-cause mortality. Outcome events were assessed during 5 years of follow-up in an intention-to-treat analysis. The propensity score-based inverse probability of treatment weighting was used to compute cumulative incidence and subdistribution hazard ratios (SHRs) and corresponding 95% confidence intervals (CIs), with death as a competing event. Propensity scores were estimated using logistic regression and including in the model sex, age group at index date, comorbidities, and use of comedications. A total of 11,742 patients with atrial fibrillation starting a factor Xa inhibitor and 11,970 patients starting dabigatran were included. Mean age was 75.2 years (standard deviation [SD] 11.2) in the factor Xa cohort and 71.7 years (SD 11.1) in the dabigatran cohort. On the basis of the propensity score-weighted models, after 5 years of follow-up, no substantial difference in the cumulative incidence of cancer was observed between the factor Xa inhibitor (2,157/23,711; 9.11%, 95% CI [8.61%,9.63%]) and dabigatran (2,294/23,715; 9.68%, 95% CI [9.14%,10.25%]) groups (SHR 0.94, 95% CI [0.89,1.00], P value 0.0357). We observed no difference in cancer-related mortality (factor Xa inhibitors cohort 1,028/23,711; 4.33%, 95% CI [4.02%,4.68%]. Dabigatran cohort 1,001/23,715; 4.22%, 95% CI [3.83%,4.66%]; SHR 1.03, 95% CI [0.94,1.12]), but all-cause mortality was higher in the factor Xa inhibitor cohort (factor Xa inhibitors cohort 7,416/23,711; 31.31%, 95% CI [30.37%,32.29%]. Dabigatran cohort 6,531/23,715; 27.56%, 95% CI [26.69%,28.45%]; HR 1.17, 95% CI [1.13,1.21]). The main limitations of the study were the possibility of residual confounding and the short follow-up period.

Conclusions

In this population based cohort study, factor Xa inhibitor use was not associated with an overall lower incidence of cancer or cancer-related mortality when compared to dabigatran. We did observe an increase in all-cause mortality in the factor Xa inhibitor cohort.


Floris Bosch and colleagues investigate whether patients with atrial fibrillation taking direct Factor Xa inhibitors have a lower risk of cancer and cancer-related mortality than patients taking dabigatran.

Author summary

Why was this study done?

  • A preclinical study in mice with breast cancer and fibrosarcoma showed that factor X dampens antitumor immunity and that factor Xa inhibitor promote tumor immunity.

  • Whether factor Xa inhibition is associated with decreased cancer incidence and cancer-related mortality in humans is unknown.

What did the researchers do and find?

  • We assessed cancer incidence during 5 years of follow-up in patients with atrial fibrillation in Denmark using a factor Xa inhibitor (n = 11,742) or a thrombin inhibitor (dabigatran) (n = 11,970) for stroke prevention.

  • No substantial difference in the cumulative incidence of cancer was observed between the factor Xa inhibitor (9.11%, 95% CI [8.61%,9.63%]) and dabigatran (9.68%, 95% CI [9.14%,10.25%]) groups (SHR 0.94, 95% CI [0.89,1.00].

  • No difference in cancer-related mortality (SHR 1.03, 95% CI [0.94,1.12]) was observed, but all-cause mortality was higher in the factor Xa inhibitor cohort (HR 1.17, 95% CI [1.13,1.21]).

What do these findings mean?

  • Factor Xa inhibitor use for atrial fibrillation did not appear to significantly reduce cancer risk compared to dabigatran use.

  • The main limitations of the study were the possibility of residual confounding and the short follow-up period.

Introduction

Cancer activates the hemostatic system, thereby promoting tumor growth and metastasis [1]. Components of the coagulation cascade have been suggested to play important roles in tumor spread and cancer progression [2,3]. For example, tissue factor promotes tumor progression in breast cancer, fibrosarcoma, colon carcinoma, melanoma, and pancreatic cancer [46], possibly by binding factor VIIa and subsequently cleaving protease activated receptor 2 (PAR2), thereby inducing the release of proangiogenic factors, and promoting cell migration and metastasis [5]. Whether anticoagulants confer a benefit in patients with cancer by slowing tumor growth and metastasis has long been debated and different randomized controlled trials on low-molecular-weight heparin (LMWH) in patients with cancer showed both a beneficial as well as no effect on survival [711]. Finally, a systematic review and meta-analysis on 9 randomized controlled trials (RCTs) showed no effect on survival [12].

A recent study on breast cancer and fibrosarcoma in mice has indicated that monocytes and macrophages produce factor X in the tumor microenvironment, where it dampens antitumor immunity by signaling through PAR2 [13]. Specifically, factor X promotes tumor immune evasion by recruiting immune-suppressive neutrophils and regulatory T cells. Pharmacological blockade of this factor Xa-PAR2 axis by the factor Xa inhibitor rivaroxaban has been found to decrease the risk of cancer progression in breast cancer and fibrosarcoma by promoting antitumor immunity, with efficacy comparable to that of immune checkpoint inhibition [13].

We performed a nationwide cohort study of patients with newly diagnosed atrial fibrillation initiating treatment with direct oral anticoagulants (DOACs) for stroke prevention. Using an active comparator, new user design, we compared patients prescribed factor Xa inhibitors (rivaroxaban, apixaban, or edoxaban) with those receiving the direct thrombin inhibitor dabigatran. Given the factor X–specific cancer effects, we hypothesized that incident cancer, cancer progression, and death from cancer would be lower in patients taking direct factor Xa inhibitors rather than dabigatran.

Methods

Setting, design, and data sources

This study was executed according to a prospective protocol, which can be found in the Supporting information (S1 Appendix). In Denmark, all residents have free access to a universal tax-supported healthcare system [14]. Healthcare data from Danish residents are collected in national medical and administrative registries. Data on demographics, medical history, medication use, and death are recorded in different registries, and their records are linked through the unique civil register numbers that are given to each resident in Denmark at the time of birth or immigration, and recorded in the Danish Civil Registration System.

This study used several Danish registries as data sources. The Danish National Patient Registry (DNPR) has collected data on all hospitalizations in Denmark since 1977 [15] and on outpatient clinic and emergency department visits since 1995. Diagnoses have been coded via the 10th revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-10) system since January 1994 and were coded according to the ICD-8 classification system before January 1994 [15]. The Danish National Prescription Registry records data on dispensed medications and dates of prescription from 1995 onward, by using the Anatomical Therapeutic Chemical (ATC) coding system [16]. The Danish Cancer Registry contains records of all incidences of malignant neoplasms in the Danish population, according to the ICD-10 coding system, from 1978 onward [17]. Causes of death are recorded in the Danish Register of Causes of Death. Since 1994, causes of death have been recorded with ICD-10 codes [18]. Information on date of birth, sex, date of death, and migration status was obtained from the Danish Civil Registration System [19].

Study population

The DNPR was used to identify all patients ≥18 years of age with a first-time primary or secondary hospital inpatient or outpatient clinic discharge diagnosis of atrial fibrillation or flutter, for which DOAC treatment was started between September 2011 and December 2015. Diagnoses of atrial fibrillation or flutter were obtained according to the ICD-10 coding system (S1 Table). The positive predictive value of atrial fibrillation or flutter in the DNPR is 93% [20].

Patients with atrial fibrillation or flutter were linked to the Danish National Prescription Registry to construct a cohort of patients who initiated DOAC treatment (S2 Table). September 2011 was chosen as the start of the study period, because rivaroxaban and dabigatran were then approved for stroke prevention in patients with atrial fibrillation by the European Medicines Agency [2123]. Patients were included only if DOAC treatment was started within 3 months before or after the first atrial fibrillation diagnosis. This 3-month window is used since the atrial fibrillation diagnosis in outpatients is registered somewhere between the first and last visit date. Therefore, DOAC treatment could have been started before the diagnosis was registered.

The index date of the study and the start of follow-up was the date of DOAC treatment initiation. Outpatients with a secondary diagnosis of atrial fibrillation and more than 1 year between the admission and discharge dates were excluded, because the exact date of atrial fibrillation diagnosis within this period could not be assessed in the DNPR. Patients with a history of cancer other than nonmelanoma skin cancer before the index date were also excluded. Patients with prior short-term DOAC use for other indications, e.g., deep vein thrombosis, were not excluded. Two cohorts were compared: patients initiating factor Xa inhibitor (rivaroxaban, apixaban, or edoxaban) treatment and those initiating treatment with the direct thrombin inhibitor dabigatran.

Study outcomes and follow-up

The primary outcome was a first diagnosis of any type of cancer other than nonmelanoma skin cancer. Secondary outcomes included individual cancer types and groups of cancer, including obesity-related cancers, smoking- and alcohol-related cancers, hematological cancers, immune-related cancers, neurological cancers, hormone-related cancers, and other cancers (S3 Table) [2426]. Other secondary outcomes were metastatic disease at diagnosis, overall mortality, and cancer-specific mortality. Gastrointestinal bleeding was also included as a secondary outcome because bleeding from the gastrointestinal tract after DOAC initiation may prompt suspicion of gastrointestinal cancer and frequently leads to additional testing (e.g., endoscopy). Therefore, differences in cancer outcomes might result from diagnosis suspicion bias if a substantial difference in gastrointestinal bleeding risk exists between DOAC cohorts [27].

Cancer diagnoses were collected from the Danish Cancer Registry according to ICD-10 codes. All cancers were defined except for nonmelanoma skin cancer (ICD-10 code C44). Cancer mortality was collected from the Danish Register of Causes of Death according to ICD-10 codes. Gastrointestinal bleeding was assessed according to ICD-10 codes in the DNPR (S1 Table).

Patients were followed from the date of the DOAC initiation until the analyzed outcome event, death, emigration, loss to follow-up, end of study (December 31, 2020), or 5 years of follow-up, whichever came first. There was virtually complete follow-up in all patients; however, in very few cases (<10), we cannot follow the patients until death, emigration, or study end. An intention-to-treat approach was used in the main analyses, in which crossover or DOAC discontinuation was not taken into account. Additionally, in several sensitivity analyses, we assessed different outcomes in an on-treatment analysis and a time-varying analysis.

Covariates

Data on the following comorbidities and comedications at baseline were collected: myocardial infarction, congestive heart failure, ischemic stroke, chronic obstructive pulmonary disease, liver disease, renal disease, inflammatory bowel disease, pancreatitis, gallstones, diabetes mellitus (including use of diabetes medication), hypertension (including use of antihypertensive agents), anemia, rheumatoid arthritis, alcohol dependency (including drugs for alcohol dependency), obesity and obesity-related disorders, platelet aggregation inhibitors, antihypertensive agents, lipid-lowering drugs, glucocorticoids, nonsteroidal anti-inflammatory drugs (NSAIDs), strong analgesics, and antidepressants (S1 and S2 Tables). Use of comedication was recorded if patients had a prescription in the Danish National Prescription Registry within 3 months before the index date.

Statistical analysis

We characterized the study cohorts according to sex, age group at index date, calendar period of index date, comorbidities, and use of comedications. We performed propensity score weighting, using average treatment effect in the population weights, to compare the clinical outcomes of patients receiving factor Xa inhibitors with those receiving dabigatran. Propensity scores were computed with a multivariable logistic regression model with DOAC type as the dependent variable (factor Xa inhibitors versus dabigatran), including the following covariates: age; sex; myocardial infarction; congestive heart failure; ischemic stroke; chronic obstructive pulmonary disease; liver disease; renal disease; inflammatory bowel disease; pancreatitis; gallstones; diabetes mellitus (including use of diabetes medication); hypertension; anemia; rheumatoid arthritis; alcohol dependency (including drugs for alcohol dependency); obesity and obesity-related disorders; and use of platelet aggregation inhibitors, antihypertensive agents, lipid-lowering drugs, glucocorticoids, NSAIDs, strong analgesics, and antidepressants (S1 and S2 Tables). The positivity assumption (i.e., that any patient must have a nonzero probability of receiving either treatment) was supported by the observation that none of the individual weights were considered extreme (across all analyses: minimum weight 1.1; maximum weight 5.8; median weight 1.9, interquartile range [IQR] 1.7,2.2). Covariate balance after weighting was assessed according to standardized differences (S1 Fig).

Using the propensity score weighted cohorts, we constructed cumulative incidence curves for the outcomes of cancer, all-cause mortality, and gastrointestinal bleeding, by calculating the 5-year cumulative incidences, comparing the factor Xa inhibitor cohort with patients treated with dabigatran, using the Aalen–Johansen estimator, which accounts for the competing risk of death. For the primary and secondary outcomes, we used inverse probability of treatment weighted (IPTW) Fine and Gray competing risk regression models to calculate subdistribution hazard ratios (SHRs), with overall death as a competing event, by using a robust sandwich estimator to calculate the 95% confidence intervals (CIs). We assessed the proportional hazards assumption through visual inspection of log-minus-log plots in the populations, weighted by their propensity scores, and found no major violations of the assumption. A visual distribution of propensity scores in both groups is presented in S2 Fig.

To evaluate the robustness of our estimates, we performed several sensitivity analyses. First, we assessed the association between DOAC treatments and different outcomes in the intention-to-treat analysis, adjusted for calendar year, because the proportion of patients with atrial fibrillation or flutter prescribed a factor Xa inhibitor increased each year during the study period. Next, we assessed outcomes in both cohorts in an on-treatment analysis and by using a time-varying exposure approach. In the on-treatment analysis, the patients were censored on the date at which the initial DOAC had not been prescribed for >200 days. In the time-varying analysis, DOAC use was assessed as a time-varying exposure. The exposure period was defined as the time from the index date until a switch from the factor Xa inhibitor cohort to the dabigatran cohort, or vice versa. In this analysis, exposure was not stopped after the DOAC had not been prescribed for >200 days. Additionally, we assessed the association between DOAC treatment initiation and outcomes in cause-specific Cox proportional hazards regression models.

After peer review of the manuscript, we added 2 sensitivity analysis. We performed an additional sensitivity analysis with follow-up time extended to 9 years to increase exposure time to the study drug. Of note, in this analysis, the mean follow-up time can differ between both cohorts since patients included in 2015 can only reach a maximum of 5 years of follow-up since we collected data up until 2020. We also performed a sensitivity analysis in which the inclusion period was stopped at the end of 2014 and all patients were followed for 5 years. In this analysis, the last included patient was followed until the end of 2019, excluding 2020 from the analysis, during which the Coronavirus Disease 2019 (COVID-19) pandemic started, resulting in less cancer diagnosis and higher mortality risks than previous years [28].

All analyses were performed in SAS version 9.4 (SAS Institute, Cary, NC, USA).

According to Danish legislation, registry-based research does not require ethical approval and informed consent but only permission from the Danish Data Protection Board. This study was approved by the Danish Data Protection Agency through registration at Aarhus University (Record Number 2016-051-000001/812). This study is reported as per the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline (S1 STROBE Checklist).

Results

A total of 23,712 patients who started DOAC treatment for newly diagnosed atrial fibrillation or flutter between 2011 and 2015 were included. Of these patients, 11,742 (49.5%) received a factor Xa inhibitor, and 11,970 received dabigatran (50.5%; Table 1). Before IPTW, patients in the factor Xa inhibitor cohort were older. The mean age was 75.2 years (standard deviation [SD] 11.2) in the factor Xa cohort and 71.7 years (SD 11.1) in the dabigatran cohort. Patients on factor Xa inhibitors were more often female (5,613/11,742 [47.8%] versus 4,953/11,970 [41.4%]), were less often included in the period between 2011 and 2013 (1,836/11,742, 15.6% versus 7,340/11,970; 61.3%), and had more comorbidities than those in the dabigatran cohort (Table 1).

Table 1. Baseline characteristics.

Overall cohorts Propensity score-weighted cohorts
Factor Xa inhibitors
N (%)
Thrombin inhibitors
N (%)
Factor Xa inhibitors
N (%)
Thrombin inhibitors
N (%)
Total 11,742 (100.0) 11,970 (100.0) 23,711 (100.0) 23,715 (100.0)
Sex (female) 5,613 (47.8) 4,953 (41.4) 10,576 (44.6) 10,578 (44.6)
Age, years
 <60 996 (8.5) 1,560 (13.0) 2,547 (10.7) 2,552 (10.8)
 60–69 2,434 (20.7) 3,365 (28.1) 5,811 (24.5) 5,805 (24.5)
 70–79 3,960 (33.7) 3,987 (33.3) 7,946 (33.5) 7,952 (33.5)
 80+ 4,352 (37.1) 3,058 (25.5) 7,406 (31.2) 7,406 (31.2)
Years of index date
 2011–2013 1,836 (15.6) 7,340 (61.3) 3,634 (15.3) 14,592 (61.5)
 2014–2015 9,906 (84.4) 4,630 (38.7) 20,077 (84.7) 9,123 (38.5)
Myocardial infarction 1,138 (9.7) 1,025 (8.6) 2,156 (9.1) 2,164 (9.1)
Heart failure 1,509 (12.9) 1,267 (10.6) 2,780 (11.7) 2,783 (11.7)
Ischemic stroke 1,626 (13.8) 1,100 (9.2) 2,733 (11.5) 2,742 (11.6)
Hypertension 9,846 (83.9) 9,615 (80.3) 19,473 (82.1) 19,475 (82.1)
Anemia 822 (7.0) 522 (4.4) 1,344 (5.7) 1,344 (5.7)
COPD 1,448 (12.3) 1,104 (9.2) 2,558 (10.8) 2,571 (10.8)
Diabetes 1,971 (16.8) 1,754 (14.7) 3,726 (15.7) 3,723 (15.7)
Liver disease 162 (1.4) 147 (1.2) 310 (1.3) 311 (1.3)
Renal insufficiency 427 (3.6) 220 (1.8) 647 (2.7) 648 (2.7)
Inflammatory bowel disease 403 (3.4) 282 (2.4) 684 (2.9) 678 (2.9)
Pancreatitis 158 (1.3) 122 (1.0) 282 (1.2) 284 (1.2)
Gallstones 853 (7.3) 750 (6.3) 1,615 (6.8) 1,611 (6.8)
Rheumatoid arthritis 291 (2.5) 231 (1.9) 523 (2.2) 520 (2.2)
Alcohol dependency 766 (6.5) 739 (6.2) 1,504 (6.3) 1,502 (6.3)
Obesity 887 (7.6) 798 (6.7) 1,687 (7.1) 1,685 (7.1)
Drugs used within 3 months before index date
 Antiplatelet therapy 3,582 (30.5) 3,298 (27.6) 6,863 (28.9) 6,858 (28.9)
 Lipid-lowering therapy 3,171 (27.0) 3,208 (26.8) 6,399 (27.0) 6,391 (27.0)
 NSAIDs 1,217 (10.4) 1,328 (11.1) 2,560 (10.8) 2,553 (10.8)
 Corticosteroids 756 (6.4) 663 (5.5) 1,429 (6.0) 1,429 (6.0)
 Strong analgesics 1,629 (13.9) 1,375 (11.5) 2,998 (12.6) 2,999 (12.7)
 Antidepressants 1,236 (10.5) 1,059 (8.8) 2,292 (9.7) 2,294 (9.7)

COPD, chronic obstructive pulmonary disease; NSAIDs, nonsteroidal anti-inflammatory drugs.

The median duration of treatment was 2.95 (IQR 0.69,5.00) years for a factor Xa inhibitor, as compared with 2.13 (IQR 0.49,5.00) years for dabigatran. During the 5-year follow-up period, 1,058/11,742 (9.0%) patients in the factor Xa inhibitor cohort and 1,145/11,970 (9.6%) patients in the dabigatran cohort were diagnosed with cancer. After IPTW, the propensity score-weighted cumulative incidence of cancer was not substantially lower in the factor Xa inhibitor cohort (2,157/23,711; 9.11%, 95% CI [8.61%,9.63%]) than in the dabigatran cohort (2,294/23,715; 9.68%, 95% CI [9.14%,10.25%]; SHR 0.94, 95% CI 0.89 to 1.00; Fig 1). In sensitivity analyses, we found no difference in cancer incidence in the intention-to-treat analysis adjusted for calendar year (SHR 0.94, 95% CI 0.88 to 1.00), the on-treatment analysis (SHR 0.99; 95% CI 0.92 to 1.06), or the time-varying analysis (HR 1.05; 95% CI 0.95 to 1.15) (S4 and S5 Tables).

Fig 1. IPT-weighted cumulative cancer incidence in patients treated with factor Xa inhibitors versus thrombin inhibitors.

Fig 1

The following variables were used to compute propensity scores and construct propensity score weighted cohorts: age; sex; myocardial infarction; congestive heart failure; ischemic stroke; chronic obstructive pulmonary disease; liver disease; renal disease; inflammatory bowel disease; pancreatitis; gallstones; diabetes mellitus (including use of diabetes medication); hypertension; anemia; rheumatoid arthritis; alcohol dependency (including drugs for alcohol dependency); obesity and obesity-related disorders; and use of platelet aggregation inhibitors, antihypertensive agents, lipid-lowering drugs, glucocorticoids, NSAIDs, strong analgesics, and antidepressants. IPT, inverse probability of treatment; NSAID, nonsteroidal anti-inflammatory drug.

Cancer stage was recorded in 1,302/2,203 (59.1%) of all patients with a cancer diagnosis during follow-up. In these patients, no difference in IPT-weighted cumulative incidence was observed in metastatic disease at diagnosis in the factor Xa inhibitor group (432/23,711; 1.86%, 95% CI [1.61%,2.16%]) and the dabigatran group (414/23,715; 1.79%, 95% CI [1.56%,2.05%]; SHR 1.04, 95% CI [0.91,1.19]). Moreover, no difference was observed in the incidence of grouped cancers, except for smoking- and alcohol-related cancers, whose incidence was lower in the factor Xa inhibitor cohort (519/23,711; 2.24%, 95% CI [1.97%,2.53%]) than the dabigatran cohort (624/23,715; 2.69%, 95% CI [2.41%,3.00%]; SHR 0.83, 95% CI [0.74,0.93]; Table 2) For individual tumor types, the cumulative incidence was lower in the factor Xa inhibitor cohort than the dabigatran cohort for lung cancer (307/23,711; 1.32%, 95% CI [1.12,1.56] versus 364/23,715; 1.57%, 95% CI [1.36,1.82]; SHR 0.84, 95% CI [0.72,0.98]), hematological cancer (181/23,711; 0.78%, 95% CI [0.64,0.97] versus 276/23,715; 1.19%, 95% CI [1.01,1.41]; SHR 0.66, 95% CI [0.55,0.79]), and gastroesophageal cancer (64/23,711; 0.28%, 95% CI [0.19,0.40] versus 103/23,715; 0.45%, 95% CI [0.33,0.61]; SHR 0.63, 95% CI [0.46,0.85]), but not the other cancer types (Table 2). These findings were also observed in the sensitivity analysis of IPT-weighted SHR adjusted for calendar year, but in the on-treatment analysis, factor Xa inhibitors were only associated with lower incidence of smoking- and alcohol-related cancers and hematological cancers (S4 and S5 Tables). In the time-varying analysis, factor Xa inhibitor initiation was not associated with a lower risk of these outcomes.

Table 2. IPT-weighted cumulative incidence and SHRs in the intention-to-treat analysis for factor Xa inhibitor cohort versus the dabigatran cohort during 5 years of follow-up.

Outcome Factor Xa inhibitor cohort Dabigatran cohort IPT-weighted SHR (95% CI)
P value*
N = 23,711 N = 23,715
Total % (95% CI) Total % (95% CI)
Cancer total 2,157 9.11 (8.61,9.63) 2,294 9.68 (9.14,10.25) 0.94 (0.89,1.00) 0.0357
Metastatic disease at diagnosis 432 1.86 (1.61,2.16) 414 1.79 (1.56,2.05) 1.04 (0.91,1.19) 0.5538
Cancer-specific mortality 1,028 4.34 (4.02,4.68) 1,001 4.23 (3.83,4.66) 1.03 (0.94,1.12) 0.5389
All-cause mortality 7,416 31.31 (30.37,32.29) 6,531 27.56 (26.69,28.45) 1.17 (1.13,1.21) < .0001
Gastrointestinal bleeding 1,245 5.26 (4.90,5.64) 1,540 6.50 (6.05,6.98) 0.80 (0.75,0.87) < .0001
Cancer groups
 Obesity-related cancer 642 2.75 (2.45,3.09) 616 2.64 (2.38,2.93) 1.04 (0.93,1.17) 0.4537
 Hormone-related cancer 528 2.27 (2.02,2.54) 516 2.22 (1.96,2.51) 1.02 (0.91,1.15) 0.7235
 Smoking- and alcohol-related cancers 519 2.24 (1.97,2.53) 624 2.69 (2.41,3.00) 0.83 (0.74,0.93) 0.0019
 Immune-related cancer 140 0.61 (0.49,0.74) 119 0.52 (0.40,0.67) 1.18 (0.92,1.50) 0.1932
 Neurological cancer 87 0.38 (0.28,0.50) 85 0.37 (0.28,0.48) 1.03 (0.76,1.38) 0.8628
 Other cancers 60 0.26 (0.17,0.38) 58 0.25 (0.17,0.37) 1.01 (0.70,1.45) 0.9583
Cancer types
 Colorectal 362 1.56 (1.37,1.77) 376 1.61 (1.40,1.85) 0.96 (0.83,1.11) 0.5854
 Lung 307 1.32 (1.12,1.56) 364 1.57 (1.36,1.82) 0.84 (0.72,0.98) 0.0276
 Prostate 296 1.28 (1.06,1.53) 293 1.26 (1.06,1.50) 1.01 (0.86,1.19) 0.8963
 Breast 202 0.87 (0.73,1.05) 200 0.86 (0.72,1.04) 1.01 (0.83,1.23) 0.9171
 Hematological 181 0.78 (0.64,0.97) 276 1.19 (1.01,1.41) 0.66 (0.55,0.79) < .0001
 Urogenital 145 0.63 (0.51,0.77) 134 0.58 (0.45,0.75) 1.09 (0.86,1.38) 0.4827
 Gynecological 89 0.38 (0.29,0.50) 70 0.30 (0.21,0.43) 1.26 (0.92,1.73) 0.1463
 Gastroesophageal 64 0.28 (0.19,0.40) 103 0.45 (0.33,0.61) 0.63 (0.46,0.85) 0.0031
 Hepatobiliary 29 0.13 (0.08,0.21) 38 0.17 (0.11,0.25) 0.77 (0.47,1.24) 0.2771
 Brain 17 0.07 (0.04,0.14) 26 0.11 (0.06,0.19) 0.66 (0.36,1.22) 0.1869

CI, confidence interval; HR, hazard ratio; IPT, inverse probability of treatment; SHR, subdistribution hazard ratio.

*Chi-squared tests have been used to determine P values.

Disease stage was recorded in 59.1% of patients with cancer during follow-up.

During the 5-year follow-up period, 4,133/11,742 (35.2%) patients in the factor Xa inhibitor cohort and 2,881/11,970 (24.1%) patients in the dabigatran cohort died. After IPTW, the all-cause mortality was higher in the factor Xa inhibitor cohort than the dabigatran cohort (SHR 1.17, 95% CI [1.13,1.21]; Table 2 and Fig 2). No difference in cancer-specific mortality was observed between factor Xa inhibitors (1,028/23,711; 4.34%, 95% CI [4.02%,4.68%]) and dabigatran (1,001/23,715; 4.23%, 95% CI [3.83%,4.66%]; SHR 1.03, 95% CI [0.94,1.12]) treatments. Gastrointestinal bleeding occurred less frequently in the factor Xa inhibitor cohort (1,245/23,711; 5.26%, 95% CI [4.90%,5.64%]) than the dabigatran cohort (1,540/23,715; 6.50%, 95% CI [6.05%,6.98%]; SHR 0.80; 95% CI, 0.75,0.87; Table 2 and Fig 3).

Fig 2. IPT-weighted cumulative incidence curves for mortality in patients treated with factor Xa inhibitors versus thrombin inhibitors.

Fig 2

The following variables were used to compute propensity scores and construct propensity score weighted cohorts: age; sex; myocardial infarction; congestive heart failure; ischemic stroke; chronic obstructive pulmonary disease; liver disease; renal disease; inflammatory bowel disease; pancreatitis; gallstones; diabetes mellitus (including use of diabetes medication); hypertension; anemia; rheumatoid arthritis; alcohol dependency (including drugs for alcohol dependency); obesity and obesity-related disorders; and use of platelet aggregation inhibitors, antihypertensive agents, lipid-lowering drugs, glucocorticoids, NSAIDs, strong analgesics, and antidepressants. IPT, inverse probability of treatment; NSAID, nonsteroidal anti-inflammatory drug.

Fig 3. IPT-weighted cumulative gastrointestinal bleeding incidence in patients treated with factor Xa inhibitors versus thrombin inhibitors.

Fig 3

The following variables were used to compute propensity scores and construct propensity score weighted cohorts: age; sex; myocardial infarction; congestive heart failure; ischemic stroke; chronic obstructive pulmonary disease; liver disease; renal disease; inflammatory bowel disease; pancreatitis; gallstones; diabetes mellitus (including use of diabetes medication); hypertension; anemia; rheumatoid arthritis; alcohol dependency (including drugs for alcohol dependency); obesity and obesity-related disorders; and use of platelet aggregation inhibitors, antihypertensive agents, lipid-lowering drugs, glucocorticoids, NSAIDs, strong analgesics, and antidepressants. IPT, inverse probability of treatment; NSAID, nonsteroidal anti-inflammatory drug.

In the sensitivity analysis with 9 years of follow-up, cancer incidence was significantly lower in the factor Xa inhibitor group than in the dabigatran group (2,277/23,711 (9.60%) versus 2,706/23,715 (11.41%); SHR 0.88, 95% CI [0.83,0.93]) (S6 Table). Importantly, in contrast to the other analyses, the mean follow-up time was higher in the dabigatran group (5.98 years (SD 2.40)) than in the factor Xa inhibitor group (4.60 years (SD 2.14)). In the sensitivity analysis excluding the follow-up during the COVID-19 pandemic, there was no difference in cancer between the 2 cohorts (1,547/15,772 (9.81%) versus 1,516/15,801 (9.59%); SHR 1.02, 95% CI [0.95,1.10]) (S7 Table).

Results for all sensitivity analyses are presented in S6 and S7 Tables.

Discussion

In this cohort study of patients with atrial fibrillation or flutter initiating DOAC treatment, we sought to investigate whether the use of factor Xa inhibitor had an effect on cancer incidence and cancer-related mortality. After propensity score weighting, we found no substantial difference in incidence of cancer or cancer-related mortality between patients taking factor Xa inhibitors and those taking dabigatran. Although the upper bound of the 95% CI of the primary analysis was 1.00, suggesting a possible effect, no difference was found in any of the sensitivity analysis, including an analysis in which we excluded the first year of COVID-19 during which fewer cancer diagnosis were made, possibly resulting in fewer cancer incidences in the factor Xa inhibitor group.

A preclinical study in mice by Graf and colleagues has shown that factor X is a crucial driver of important innate immune signaling pathways [13]. The authors assessed the effects of factor X and rivaroxaban on tumor burden and metastasis in breast cancer and fibrosarcoma. Whether inhibition of factor X also works in humans or in other cancer types is unclear. Mechanisms of innate immune evasion are different across tumor types and tumors respond differently to immunotherapy [29]. Therefore, based on this hypothesis, differences in response to factor Xa inhibition across tumor types are expected. In the present cohort, we found no evidence for an effect of factor Xa inhibitors on overall cancer occurrence. We did find an association with factor Xa inhibitor use and lower incidence of alcohol- and smoking-related cancers, lung cancer, hematological cancer, and gastroesophageal cancer, suggesting that factor Xa may play a role in cancer progression in specific cancer types. However, these findings on secondary outcomes should be interpreted with caution. Precision in certain cancer-specific estimates was low due to low event numbers. As for the main analysis, potential residual confounding precludes strong conclusions about causality. Yet, as patients with factor Xa inhibitors more often had comorbidities, the incidence of alcohol- and smoking-related cancers and lung cancer would likely have been higher in this group instead of lower. Finally, differences in subgroup outcomes might have been mediated by differences in bleeding risk between the cohorts. For example, gastrointestinal bleeding occurs more frequently in patients using dabigatran, thus potentially leading to an earlier diagnosis of gastrointestinal cancer [30]. Not all subgroup analysis showed the same results in sensitivity analysis. The time-varying results might differ from the intention-to-treat and on-treatment analyses, given that in time-varying analyses, we have not used the IPTW approach as they were directly adjusted for confounding variables, resulting in a decrease in the precision of the estimates. In the on-treatment analysis, patients were followed for 200 days after last subscription, resulting in a shorter overall follow-up time. Although the intention-to-treat and on-treatment analyses show largely the same results, shorter follow-up time could have an effect on outcomes.

Several limitations of the present study merit consideration. First, we chose dabigatran as the comparator, assuming no preference for a particular type of DOAC, because all DOACs are usually considered equally efficacious and safe in patients with atrial fibrillation [21,31]. However, considerable differences in baseline characteristics and all-cause mortality risk were observed between the cohorts. Whereas dabigatran use was more prevalent at the beginning of the study period, because this drug was licensed first, factor Xa inhibitors were increasingly prescribed later, after clinicians had been assured of their efficacy and safety profiles. Factor Xa inhibitors also seemed to be prescribed preferentially in older and frail patients [32]. Although we used IPTW to decrease confounding, the all-cause mortality risk was still higher in the factor Xa cohort than in the dabigatran cohort, which may be the result of residual confounding. Guidelines suggest to be cautious when prescribing dabigatran to elderly patients because of concerns of bleeding and myocardial infarction [3335]. Factor Xa inhibitors are also preferred over dabigatran in patients with chronic kidney disease [34]. Nonetheless, previous observational studies suggest that factor Xa inhibitors do not increase mortality compared to dabigatran [36]. The sensitivity analysis excluding the time period of COVID-19, during which factor Xa use was more prevalent, suggests that this pandemic may also have led to a higher mortality risk in the factor Xa group [28]. Therefore, we performed a sensitivity analysis with 5 years follow-up and the inclusion period ending at the end of 2019, excluding overlap with the first year of the COVID-19 pandemic. In this analysis, the point estimate of SHR for cancer was slightly higher compared to the primary analysis, suggesting a small potential effect of COVID-19, although estimates were largely comparable between both analyses. Second, a recent study has suggested that dabigatran prevents cancer spread in mice with colon cancer by obliterating transforming growth factor-β1 (TGF-β1), an immunosuppressive cytokine with important roles in oncogenesis; therefore, we could not rule out competing effects on cancer progression [37]. Third, the timeframe in which a positive effect of factor Xa inhibitors on cancer occurrence or progression could be expected is unknown. Because most cancers develop over many years, our relatively short follow-up period might not have been sufficiently long to detect differences in cancer incidence and mortality [38]. Nonetheless, the preclinical study in mice by Graf and colleagues on which the hypothesis is based [13] suggests that factor Xa inhibitors should prevent progression of cancer and cancer growth with a mechanism similar to PD-L1 inhibition, which suggests it could also have an effect when a tumor has not yet been diagnosed but already has had several years since inception, possibly resulting in postponement of a tumor becoming clinically apparent. We therefore hypothesized that 5 years would be sufficient to observe a potential effect. To increase exposure time to the study drug, we performed a sensitivity analysis with follow-up time increased to 9 years. In this analysis, we did find a lower risk of cancer in the factor Xa inhibitor group, but since the majority of patients on dabigatran were included in the beginning of the study period, important differences in follow-up time were observed. Therefore, no clear conclusions can be drawn based on this analysis. Together, these potential biases might have led to an underestimation of the relationship between factor Xa inhibitors and cancer, and we therefore cannot rule out a potential causal link.

Transferability from animal models to humans could also be a problem when testing this hypothesis. While the importance of factor X in cancer progression was proved in preclinical mice studies, it is unknown whether factor X and factor Xa inhibition plays a similar role in humans and different cancer types. Previous studies evaluating the association between DOACs and cancer either have combined thrombin inhibitors with factor Xa inhibitors [39] or have assessed only cancer mortality in patients who were already diagnosed with cancer or had a relatively short follow-up [40]. Therefore, large studies are necessary to corroborate these findings in various cancer types. Because RCTs to address this question are not feasible, given the large number of patients and long-term follow-up required, large cohort studies can serve as an alternative, because they provide detailed healthcare data on medication prescription, medical history, comedication, and causes of death. In this study, we assessed the incidence of onset of many cancer types in patients with atrial fibrillation treated with factor Xa inhibitors or thrombin inhibitors, with 5 years’ follow-up. Alternatively, long-term follow-up data from Phase III trials comparing DOACs to vitamin K antagonists for atrial fibrillation could be used to assess cancer incidence in different treatment arms [22,23,41].

In conclusion, we did not observe lower cancer incidence in patients with atrial fibrillation taking a factor Xa inhibitor rather than dabigatran during a 5-year follow-up. Our data do not support the hypothesis that factor Xa inhibition strongly limits cancer growth overall or reduces cancer-related mortality.

Supporting information

S1 STROBE Checklist. Statement Checklist of items that should be included in reports of cohort studies.

*Give information separately for exposed and unexposed groups. Note: An Explanation and Elaboration article discusses each checklist item and gives methodological background and published examples of transparent reporting. The STROBE checklist is best used in conjunction with this article (freely available on the websites of PLoS Medicine at http://www.plosmedicine.org/, Annals of Internal Medicine at http://www.annals.org/, and Epidemiology at http://www.epidem.com/). Information on the STROBE Initiative is available at http://www.strobe-statement.org.

(DOCX)

pmed.1004400.s001.docx (29.9KB, docx)
S1 Table. Index variable, covariates, and noncancer-related outcomes from the DNPR.

ICD-8, 8th revision of the International Statistical Classification of Diseases and Related Health Problems; ICD-10, 10th revision of the International Statistical Classification of Diseases and Related Health Problems.

(DOCX)

pmed.1004400.s002.docx (14.2KB, docx)
S2 Table. Drugs and ATC codes.

*Used to define diagnosis. ATC, Anatomical Therapeutic Chemical; NSAIDs, nonsteroidal anti-inflammatory drugs.

(DOCX)

pmed.1004400.s003.docx (13KB, docx)
S3 Table. Table of cancer diagnosis and cancer groups.

ICD-10, 10th revision of the International Statistical Classification of Diseases and Related Health Problems.

(DOCX)

pmed.1004400.s004.docx (15.3KB, docx)
S4 Table. SHRs adjusted for calendar year (intention-to-treat), cause-specific HR (intention-to-treat analysis), and adjusted HRs (time-varying analysis) for different outcomes in the factor Xa inhibitor versus dabigatran cohorts.

CI, confidence interval; HR, hazard ratio; IPT, inverse probability of treatment; SHR, subdistribution hazard ratio. *Disease stage was recorded in 59.1% of patients with cancer during follow-up.

(DOCX)

pmed.1004400.s005.docx (14.4KB, docx)
S5 Table. SHRs in the on-treatment analysis for different outcomes in the factor Xa inhibitor versus dabigatran cohorts.

CI, confidence interval; HR, hazard ratio; IPT, inverse probability of treatment; SHR, subdistribution hazard ratio. *Disease stage was recorded in 59.1% of patients with cancer during follow-up.

(DOCX)

pmed.1004400.s006.docx (14.2KB, docx)
S6 Table. Sensitivity analysis with IPT-weighted cumulative incidence and SHRs for different outcomes in the factor Xa inhibitor cohort versus the dabigatran cohort during 9 years of follow-up.

CI, confidence interval; HR, hazard ratio; IPT, inverse probability of treatment; SHR, subdistribution hazard ratio.

(DOCX)

pmed.1004400.s007.docx (14.8KB, docx)
S7 Table. Sensitivity analysis with IPT-weighted cumulative incidence and SHRs for different outcomes in the factor Xa inhibitor cohort versus the dabigatran cohort during 5 years of follow-up with inclusion period between 2011 and 2014.

CI, confidence interval; HR, hazard ratio; IPT, inverse probability of treatment; SHR, subdistribution hazard ratio.

(DOCX)

pmed.1004400.s008.docx (14.8KB, docx)
S1 Fig. Standardized differences for covariates included in the propensity score model.

CHF, congestive heart failure; COPD, chronic obstructive pulmonary disease; IBD, inflammatory bowel disease; Istroke, ischemic stroke; MI, myocardial infarction; NSAIDs, nonsteroidal anti-inflammatory drugs; prop score, propensity score; obs, observations; w3m, within 3 months.

(DOCX)

pmed.1004400.s009.docx (76KB, docx)
S2 Fig. Propensity score distribution in the factor Xa inhibitor and dabigatran cohorts.

Bars represent histogram of propensity scores in the 2 cohorts (expressed as percentages per 100) and lines represent kernel density plots of propensity scores prior to inverse probability of treatment weighting.

(DOCX)

pmed.1004400.s010.docx (50.1KB, docx)
S1 Appendix. Supporting information.

(DOCX)

pmed.1004400.s011.docx (101.5KB, docx)

Abbreviations

ATC

Anatomical Therapeutic Chemical

CI

confidence interval

COVID-19

Coronavirus Disease 2019

DNPR

Danish National Patient Registry

DOAC

direct oral anticoagulant

IPTW

inverse probability of treatment weighted

IQR

interquartile range

LMWH

low-molecular-weight heparin

NSAID

nonsteroidal anti-inflammatory drug

PAR2

protease activated receptor 2

RCT

randomized controlled trial

SD

standard deviation

SHR

subdistribution hazard ratio

TGF-β1

transforming growth factor-β1

Data Availability

All relevant data are within the manuscript and its Supporting Information files.

Funding Statement

The author(s) received no specific funding for this work.

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Decision Letter 0

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22 Nov 2023

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Decision Letter 1

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5 Jan 2024

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We ask every co-author listed on the manuscript to fill in a contributing author statement, making sure to declare all competing interests. If any of the co-authors have not filled in the statement, we will remind them to do so when the paper is revised. If all statements are not completed in a timely fashion this could hold up the re-review process. If new competing interests are declared later in the revision process, this may also hold up the submission. Should there be a problem getting one of your co-authors to fill in a statement we will be in contact. YOU MUST NOT ADD OR REMOVE AUTHORS UNLESS YOU HAVE ALERTED THE EDITOR HANDLING THE MANUSCRIPT TO THE CHANGE AND THEY SPECIFICALLY HAVE AGREED TO IT. You can see our competing interests policy here: http://journals.plos.org/plosmedicine/s/competing-interests.

Please use the following link to submit the revised manuscript:

https://www.editorialmanager.com/pmedicine/

Your article can be found in the "Submissions Needing Revision" folder.

To enhance the reproducibility of your results, we recommend that you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. Additionally, PLOS ONE offers an option to publish peer-reviewed clinical study protocols. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols

Please ensure that the paper adheres to the PLOS Data Availability Policy (see http://journals.plos.org/plosmedicine/s/data-availability), which requires that all data underlying the study's findings be provided in a repository or as Supporting Information. For data residing with a third party, authors are required to provide instructions with contact information for obtaining the data. PLOS journals do not allow statements supported by "data not shown" or "unpublished results." For such statements, authors must provide supporting data or cite public sources that include it.

We look forward to receiving your revised manuscript.

Sincerely,

Alexandra Schaefer, PhD

PLOS Medicine

plosmedicine.org

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Requests from the editors:

ACADEMIC EDITOR COMMENTS

My review of this paper aligns most closely with Reviewer 1. This is a well-designed, well-executed negative study. The sentence in the abstract, discussion, and cover letter "subgroup analyses suggested that it might decrease the risk of several cancer types" is somewhat exaggerated -- there were three cancer types (out of 10) where cancer incidence was lower in the Factor Xa inhibitor group (Table 2), but these data did not consistently hold up in the Table S4 analysis.

EDITORIAL COMMENTS

The editors concur with the reviewers that the follow-up is rather short for the outcome of interest. Therefore, we suggest extending the follow-up period to provide a more robust assessment and agree with the statistical reviewer that a sensitivity analysis adjusting for age is merited. In addition, we ask that you report absolute numbers throughout the entire manuscript and revise your discussion to include a more formal discussion of limitations.

GENERAL COMMENTS

1) Please include page numbers and line numbers in the manuscript file. Use continuous line numbers (do not restart the numbering on each page). For review purposes, we started counting the Abstract as page 1.

2) Please cite the reference numbers in square brackets (e.g., “We used the techniques developed by our colleagues [19] to analyze the data”). Citations should be preceding punctuation.

3) Please cite your Supporting Information as outlined here: https://journals.plos.org/plosmedicine/s/supporting-information

FINANCIAL DISCLOSURE

Please enter a financial disclosure statement that describes the sources of funding for the work included in this submission. If the study received no specific funding, please enter “The author(s) received no specific funding for this work.”

COMPETING INTEREST

All authors must declare their relevant competing interests per the PLOS policy, which can be seen here: https://journals.plos.org/plosmedicine/s/competing-interests

Please add this statement to the manuscript's Competing Interests: "SC is an Academic Editor on PLOS Medicine's editorial board."

TITLE

Please include the study setting, i.e. Denmark, in the title.

ABSTRACT

1) PLOS Medicine requests that main results are quantified with 95% CIs as well as p values. When reporting p values please report as p<0.001 and where higher as the exact p value p=0.002, for example. For the purposes of transparent data reporting, if not including the aforementioned please clearly state the reasons why not.

2) Throughout, suggest reporting statistical information as follows to improve clarity for the reader “22% (95% CI [13%,28%]; p</=)”. Please amend throughout the abstract and main manuscript. Please note the use of commas to separate upper and lower bounds, as opposed to hyphens as these can be confused with reporting of negative values.

3) When a p value is given, please specify the statistical test used to determine it.

4) Please structure your abstract using the PLOS Medicine headings (Background, Methods and Findings, Conclusions). Please combine the Methods and Findings sections into one section, “Methods and findings”.

5) Please explain what rivaroxaban is, e.g. “…rivaroxaban, a direct anticoagulant and factor Xa inhibitor,..” or similar.

6) Please ensure that all numbers presented in the abstract are present and identical to numbers presented in the main manuscript text.

7) Please include the age of the study population and the main outcome measures.

8) Please include the important dependent variables that are adjusted for in the analyses.

9) In the last sentence of the Abstract Methods and Findings section, please describe the main limitation(s) of the study's methodology.

AUTHOR SUMMARY

At this stage, we ask that you include a short, non-technical Author Summary of your research to make findings accessible to a wide audience that includes both scientists and non-scientists. The Author Summary should immediately follow the Abstract in your revised manuscript. This text is subject to editorial change and should be distinct from the scientific abstract. Please see our author guidelines for more information: https://journals.plos.org/plosmedicine/s/revising-your-manuscript#loc-author-summary.

The summary should include 2-3 single sentence, individual bullet points under each of the questions. The last bullet under ‘What Do These Findings Mean?’ point should describe the main limitation of the study's methodology.

It may be helpful to review currently published articles for examples which can be found on our website here https://journals.plos.org/plosmedicine/

INTRODUCTION

1) p.2: Please introduce the abbreviation “RCT” before its first use.

2) “Pharmacological blockade…immune checkpoint inhibition.” – please provide reference.

METHODS AND RESULTS

General points:

1) For all observational studies, in the manuscript text, please indicate: (1) the specific hypotheses you intended to test, (2) the analytical methods by which you planned to test them, (3) the analyses you actually performed, and (4) when reported analyses differ from those that were planned, transparent explanations for differences that affect the reliability of the study's results. If a reported analysis was performed based on an interesting but unanticipated pattern in the data, please be clear that the analysis was data-driven.

2) Did your study have a prospective protocol or analysis plan? Please state this (either way) early in the Methods section.

a) If a prospective analysis plan (from your funding proposal, IRB or other ethics committee submission, study protocol, or other planning document written before analyzing the data) was used in designing the study, please include the relevant prospectively written document with your revised manuscript as a Supporting Information file to be published alongside your study, and cite it in the Methods section. A legend for this file should be included at the end of your manuscript.

b) If no such document exists, please make sure that the Methods section transparently describes when analyses were planned, and when/why any data-driven changes to analyses took place.

c) In either case, changes in the analysis-- including those made in response to peer review comments-- should be identified as such in the Methods section of the paper, with rationale.

3) Please ensure that the study is reported according to the STROBE guideline and include the completed STROBE checklist as Supporting Information. When completing the checklist, please use section and paragraph numbers, rather than page numbers. Please add the following statement, or similar, to the Methods: ""This study is reported as per the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline (S1 Checklist).""

4) PLOS Medicine requests that main results are quantified with 95% CIs as well as p values. When reporting p values please report as p<0.001 and where higher as the exact p value p=0.002, for example. For the purposes of transparent data reporting, if not including the aforementioned please clearly state the reasons why not. Please include any important dependent variables that are adjusted for in the analyses. We suggest reporting statistical information as detailed above – see under ABSTRACT.

5) Please present numerators and denominators for percentages, at least in the Tables [not necessarily each time they're mentioned].

6) Please define "lost to follow-up" as used in this study. Other reasons for exclusion should be defined.

7) p.6: Please define ‘NSAID’.

8) p.7: “The study was reported to the Danish Data Protection Board by Aarhus University” - Please confirm that this specific study was reviewed and approved by an institutional review board (ethics committee) before the study began and provide additional details regarding consent. Please provide the specific name of the ethics committee/IRB that approved your study. Once you have amended this/these statement(s) in the Methods section of the manuscript, please add the same text to the “Ethics Statement” field of the submission form.

9) p.7: “Of these patients, 11,742 (50%) received a factor Xa inhibitor, and 11,970 received dabigatran (50%; Table 1).” – To make the values closer to the actual distribution (49.5% and 50.5%), we suggest adding a decimal point to the percentages.

10) p.7: Please define ‘SD’ at first use.

11) p.7: “were more often female (47.8% vs 41.4%), were less often included in the period between 2011 and 2013 (15.6% vs 61.3%), and had more comorbidities than those in the dabigatran cohort (Table 1).” – please revise.

12) p.8: “After IPTW, the all-cause mortality was higher in the factor Xa inhibitor cohort than the dabigatran cohort (HR 1.17, 95% CI 1.13–1.21; Table 2 and Figure 2).” – Should HR be SHR here?

DISCUSSION

1) p.9 “A pre-clinical study in mice by Graf et al. has shown that factor Xa is a crucial driver of the innate immune signaling pathway.” – please provide the reference number.

2) p.10: Please define ‘FX’ or write in full.

3) p.10: Please define ‘VKA’ or write in full.

TABLES

1) Please define abbreviations used in each table (including those in Supporting Information files).

2) Please note the use of commas to separate upper and lower bounds, as opposed to hyphens as these can be confused with reporting of negative values.

3) Table 2: Please define ‘IPTW’, ‘CI’, ‘HR’.

FIGURES

1) For all Figures, please ensure that you have complied with our figures requirements http://journals.plos.org/plosmedicine/s/figures.

2) Please consider avoiding the use of red and green in order to make your figure more accessible to those with colour blindness.

3) Please in the figure legend/description, define abbreviations used in each figure (e.g. ‘IPTW’; including those in Supporting Information files).

4) Please provide titles, legends and descriptions for all figures (including those in Supporting Information files).

SUPPLEMENTARY MATERIAL

1) For supplementary figures and tables, please see the general comments under TABLES and FIGURES (color, abbreviations, titles, descriptions, etc.) and amend accordingly.

2) We suggest reporting statistical information as detailed above – see under ABSTRACT. Please define all numerical values (e.g. Supplemental Table 4 does not specify the numerical value of the numbers in brackets).

3) Supplemental Figure 1: Please ensure that all covariates and their abbreviations are properly defined as well as the abbreviations used in the figure legend.

4) Supplemental Figure 2: Please ensure to reference Supplemental Figure 2 in the main manuscript. Please describe the meaning of the lines and bars and add a unit for ‘Percent’.

REFERENCES

1) PLOS uses the numbered citation (citation-sequence) method and first six authors, et al.

2) Please ensure that journal name abbreviations match those found in the National Center for Biotechnology Infor

Decision Letter 2

Alexandra Tosun

18 Mar 2024

Dear Dr. Bosch,

Thank you very much for re-submitting your manuscript "Direct factor Xa inhibitors and the risk of cancer and cancer mortality: a population-based cohort study" (PMEDICINE-D-23-03433R2) for review by PLOS Medicine.

Thank you for your detailed response to the editors' and reviewers' comments. I have discussed the paper with my colleagues and the academic editor, and it has also been seen again by two of the original reviewers. The changes made to the paper were satisfactory to the reviewers. As such, we intend to accept the paper for publication, pending your attention to the editorial comments below in a further revision. When submitting your revised paper, please once again include a detailed point-by-point response to the editorial comments.

The remaining issues that need to be addressed are listed at the end of this email. Any accompanying reviewer attachments can be seen via the link below. Please take these into account before resubmitting your manuscript:

[LINK]

In revising the manuscript for further consideration here, please ensure you address the specific points made by each reviewer and the editors. In your rebuttal letter you should indicate your response to the reviewers' and editors' comments and the changes you have made in the manuscript. Please submit a clean version of the paper as the main article file. A version with changes marked must also be uploaded as a marked up manuscript file. Please also check the guidelines for revised papers at http://journals.plos.org/plosmedicine/s/revising-your-manuscript for any that apply to your paper.

Please note, when your manuscript is accepted, an uncorrected proof of your manuscript will be published online ahead of the final version, unless you've already opted out via the online submission form. If, for any reason, you do not want an earlier version of your manuscript published online or are unsure if you have already indicated as such, please let the journal staff know immediately at plosmedicine@plos.org.   

We ask that you submit your revision within 1 week (Mar 25 2024). However, if this deadline is not feasible, please contact me by email, and we can discuss a suitable alternative.

Please do not hesitate to contact me directly with any questions (aschaefer@plos.org). If you reply directly to this message, please be sure to 'Reply All' so your message comes directly to my inbox.

We look forward to receiving the revised manuscript.

Sincerely,

Alexandra Schaefer, PhD

Associate Editor

PLOS Medicine

plosmedicine.org

***Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.***

------------------------------------------------------------

Requests from Editors:

ACADEMIC EDITOR COMMENTS

I think the authors have done a reasonable job of responding to the reviewers' comments.

I would like to note that this is a completely negative study, and furthermore, the Factor Xa inhibitors increased all-cause mortality compared to standard thrombin inhibitors.

I think the authors need to highlight the increase in all-cause mortality with factor Xa inhibitors in the conclusion of their abstract and in the "What did the researchers do and find?" and "What do these findings mean?" sections of the Author Summary. It is important that this important (and adverse) finding be clearly stated and obvious even to the quick reader.

EDITORIAL COMMENTS

Please be sure to include absolute numbers of events when reporting results, including in the sensitivity analyses, (e.g., #s of all-cause deaths, cancer-specific deaths, cancer subtypes) for the matched group analysis. In the text, it appears that you are reporting the total N for incident cancers (and deaths), but only for the overall group, not after matching, so the absolute numbers of events used for IPT-weighted cumulative incidence/SHR are not available in the text. Please also include the absolute numbers of events in the relevant tables, such as Table 2 (i.e., add two columns in table 2 to report numbers of events in each treatment group for each outcome listed) as well as Tables S4 and S5.

ABSTRACT

1) l.41: Please define ‘SD’ at first use.

2) ll.46-47: Please include absolute numbers of events and denominators before percentages: e.g., (n/N; 9.11%, 95%CI [8.61%,9.63%]). Please do the same for lines 48-50 and when you report these data in the Results section (e.g., lines 252-253; 259-260, etc.).

3) Please state the main limitation at the end of the “Methods and Findings” section. Please also consider modifying this sentence as follows, “The main limitations of the study were the possibility of residual confounding and the short follow up period.”

AUTHOR SUMMARY

Thank for providing the Author Summary. We feel that the Author Summary in its current form does not provide sufficient detail (please also see the comments provided by the Academic Editor). The Author Summary should consist of 2-3 succinct bullet points under each of the following headings:

• Why Was This Study Done? Authors should reflect on what was known about the topic before the research was published and why the research was needed.

• What Did the Researchers Do and Find? Authors should briefly describe the study design that was used and the study’s major findings. Do include the headline numbers from the study, such as the sample size and key findings.

• What Do These Findings Mean? Authors should reflect on the new knowledge generated by the research and the implications for practice, research, policy, or public health. Authors should also consider how the interpretation of the study’s findings may be affected by the study limitations. In the final bullet point of ‘What Do These Findings Mean?’, please describe the main limitations of the study in non-technical language.

INTRODUCTION

1) Please note that references should be preceding punctuation. Also, in some instances, e.g. line 80, the references are still in uppercase format. Please revise throughout the main manuscript.

2) ll.90-94: For clarity, we suggest adding “in mice” after “fibrosarcoma”.

METHODS AND RESULTS

1) Please note that changes in the analysis-- including those made in response to peer review comments-- should be identified as such in the Methods section of the paper, with rationale.

2) Please add the following statement, or similar, to the Methods: "This study is reported as per the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline (S1 Checklist)."

3) l.247: Please add “IQR” in the parentheses when reporting the interquartile range. Please revise throughout the main manuscript.

4) l.278: “0.75–0.87” – Please replace the hyphen with a comma.

DISCUSSION

1) ll.298-299: “Whether inhibition of factor X also works in other cancer types is unclear.” – We suggest adding here that it is also unclear whether the inhibition of factor X also works in humans given the study was done in mice.

2) ll.306-307: Please mention that these results should also be interpreted with caution due to low event numbers (if correct); perhaps at the end of the sentence on precision?

3) l.347: Please include the reference to Graf et al. Also, please reiterate that the study was a preclinical study in mice.

4) We suggest briefly discussing the transferability from animal models to humans given your study hypothesis is based on data stemming from animal studies.

SUPPLEMENTARY MATERIAL

Thank you for providing the STROBE checklist. Please replace the page numbers with paragraph numbers per section (e.g. "Methods, paragraph 1"), since the page numbers of the final published paper may be different from the page numbers in the current manuscript.

SOCIAL MEDIA

To help us extend the reach of your research, please provide any X (formerly known as Twitter) handle(s) that would be appropriate to tag, including your own, your coauthors’, your institution, funder, or lab. Please respond to this email with any handles you wish to be included when we tweet this paper.

Comments from Reviewers:

Reviewer #2: Thank you to the authors for addressing my previous comments well. I have no further issues to raise.

Reviewer #3: The authors have addressed my previous comments.

Any attachments provided with reviews can be seen via the following link:

[LINK]

------------------------------------------------------------

General Editorial Requests

1) We ask every co-author listed on the manuscript to fill in a contributing author statement. If any of the co-authors have not filled in the statement, we will remind them to do so when the paper is revised. If all statements are not completed in a timely fashion this could hold up the re-review process. Should there be a problem getting one of your co-authors to fill in a statement we will be in contact. YOU MUST NOT ADD OR REMOVE AUTHORS UNLESS YOU HAVE ALERTED THE EDITOR HANDLING THE MANUSCRIPT TO THE CHANGE AND THEY SPECIFICALLY HAVE AGREED TO IT.

2) Please ensure that the paper adheres to the PLOS Data Availability Policy (see http://journals.plos.org/plosmedicine/s/data-availability), which requires that all data underlying the study's findings be provided in a repository or as Supporting Information. For data residing with a third party, authors are required to provide instructions with contact information for obtaining the data. PLOS journals do not allow statements supported by "data not shown" or "unpublished results." For such statements, authors must provide supporting data or cite public sources that include it.

3) Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript.

Decision Letter 3

Alexandra Tosun

5 Apr 2024

Dear Dr Bosch, 

On behalf of my colleagues and the Academic Editor, Aadel A Chaudhuri, I am pleased to inform you that we have agreed to publish your manuscript "Direct factor Xa inhibitors and the risk of cancer and cancer mortality: a population-based cohort study" (PMEDICINE-D-23-03433R3) in PLOS Medicine.

I appreciate your thorough responses to the reviewers' and editors' comments throughout the editorial process. We look forward to publishing your manuscript, and editorially there are only a few remaining minor stylistic/presentation points that should be addressed prior to publication. We will carefully check whether the changes have been made. If you have any questions or concerns regarding these final requests, please feel free to contact me at aschaefer@plos.org.

Please see below the minor points that we request you respond to:

1) l.48/l.51: Please change the period to a comma or semicolon after reporting the values of the factor Xa inhibitors cohort.

2) l.52: Please check whether “HR” should be “SHR” here.

3) ll.55-56: Please change to “However, we observed an increase in all-cause mortality in the factor Xa inhibitor cohort.”.

4) Author Summary: Under ‘Why Was This Study Done?’, please change “promote” to “promotes”. Also, under ‘What Did the Researchers Do and Find?’, please remove any values mentioned.

5) In the figure descriptions of Figures 1, 2, and 3, please include the factors that are included in the IPTW. In the figures, please include the numbers at risk and the event numbers for the different cohorts, as well as the subdistribution hazard ratios (you may want to use Figure 1 from https://doi.org/10.1007/s00392-023-02308-y as a template). In the figure description, please include all abbreviations used.

Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow up email. Please be aware that it may take several days for you to receive this email; during this time no action is required by you. Once you have received these formatting requests, please note that your manuscript will not be scheduled for publication until you have made the required changes.

In the meantime, please log into Editorial Manager at http://www.editorialmanager.com/pmedicine/, click the "Update My Information" link at the top of the page, and update your user information to ensure an efficient production process. 

PRESS

We frequently collaborate with press offices. If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximise its impact. If the press office is planning to promote your findings, we would be grateful if they could coordinate with medicinepress@plos.org. If you have not yet opted out of the early version process, we ask that you notify us immediately of any press plans so that we may do so on your behalf.

We also ask that you take this opportunity to read our Embargo Policy regarding the discussion, promotion and media coverage of work that is yet to be published by PLOS. As your manuscript is not yet published, it is bound by the conditions of our Embargo Policy. Please be aware that this policy is in place both to ensure that any press coverage of your article is fully substantiated and to provide a direct link between such coverage and the published work. For full details of our Embargo Policy, please visit http://www.plos.org/about/media-inquiries/embargo-policy/.

Thank you again for submitting to PLOS Medicine. We look forward to publishing your paper. 

Sincerely, 

Alexandra Schaefer, PhD 

Associate Editor 

PLOS Medicine

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 STROBE Checklist. Statement Checklist of items that should be included in reports of cohort studies.

    *Give information separately for exposed and unexposed groups. Note: An Explanation and Elaboration article discusses each checklist item and gives methodological background and published examples of transparent reporting. The STROBE checklist is best used in conjunction with this article (freely available on the websites of PLoS Medicine at http://www.plosmedicine.org/, Annals of Internal Medicine at http://www.annals.org/, and Epidemiology at http://www.epidem.com/). Information on the STROBE Initiative is available at http://www.strobe-statement.org.

    (DOCX)

    pmed.1004400.s001.docx (29.9KB, docx)
    S1 Table. Index variable, covariates, and noncancer-related outcomes from the DNPR.

    ICD-8, 8th revision of the International Statistical Classification of Diseases and Related Health Problems; ICD-10, 10th revision of the International Statistical Classification of Diseases and Related Health Problems.

    (DOCX)

    pmed.1004400.s002.docx (14.2KB, docx)
    S2 Table. Drugs and ATC codes.

    *Used to define diagnosis. ATC, Anatomical Therapeutic Chemical; NSAIDs, nonsteroidal anti-inflammatory drugs.

    (DOCX)

    pmed.1004400.s003.docx (13KB, docx)
    S3 Table. Table of cancer diagnosis and cancer groups.

    ICD-10, 10th revision of the International Statistical Classification of Diseases and Related Health Problems.

    (DOCX)

    pmed.1004400.s004.docx (15.3KB, docx)
    S4 Table. SHRs adjusted for calendar year (intention-to-treat), cause-specific HR (intention-to-treat analysis), and adjusted HRs (time-varying analysis) for different outcomes in the factor Xa inhibitor versus dabigatran cohorts.

    CI, confidence interval; HR, hazard ratio; IPT, inverse probability of treatment; SHR, subdistribution hazard ratio. *Disease stage was recorded in 59.1% of patients with cancer during follow-up.

    (DOCX)

    pmed.1004400.s005.docx (14.4KB, docx)
    S5 Table. SHRs in the on-treatment analysis for different outcomes in the factor Xa inhibitor versus dabigatran cohorts.

    CI, confidence interval; HR, hazard ratio; IPT, inverse probability of treatment; SHR, subdistribution hazard ratio. *Disease stage was recorded in 59.1% of patients with cancer during follow-up.

    (DOCX)

    pmed.1004400.s006.docx (14.2KB, docx)
    S6 Table. Sensitivity analysis with IPT-weighted cumulative incidence and SHRs for different outcomes in the factor Xa inhibitor cohort versus the dabigatran cohort during 9 years of follow-up.

    CI, confidence interval; HR, hazard ratio; IPT, inverse probability of treatment; SHR, subdistribution hazard ratio.

    (DOCX)

    pmed.1004400.s007.docx (14.8KB, docx)
    S7 Table. Sensitivity analysis with IPT-weighted cumulative incidence and SHRs for different outcomes in the factor Xa inhibitor cohort versus the dabigatran cohort during 5 years of follow-up with inclusion period between 2011 and 2014.

    CI, confidence interval; HR, hazard ratio; IPT, inverse probability of treatment; SHR, subdistribution hazard ratio.

    (DOCX)

    pmed.1004400.s008.docx (14.8KB, docx)
    S1 Fig. Standardized differences for covariates included in the propensity score model.

    CHF, congestive heart failure; COPD, chronic obstructive pulmonary disease; IBD, inflammatory bowel disease; Istroke, ischemic stroke; MI, myocardial infarction; NSAIDs, nonsteroidal anti-inflammatory drugs; prop score, propensity score; obs, observations; w3m, within 3 months.

    (DOCX)

    pmed.1004400.s009.docx (76KB, docx)
    S2 Fig. Propensity score distribution in the factor Xa inhibitor and dabigatran cohorts.

    Bars represent histogram of propensity scores in the 2 cohorts (expressed as percentages per 100) and lines represent kernel density plots of propensity scores prior to inverse probability of treatment weighting.

    (DOCX)

    pmed.1004400.s010.docx (50.1KB, docx)
    S1 Appendix. Supporting information.

    (DOCX)

    pmed.1004400.s011.docx (101.5KB, docx)
    Attachment

    Submitted filename: Response to the Reviewers - PMEDICINE-D-23-03433R1.docx

    pmed.1004400.s012.docx (45.6KB, docx)
    Attachment

    Submitted filename: Response to the Editor and Reviewers.docx

    pmed.1004400.s013.docx (19.8KB, docx)

    Data Availability Statement

    All relevant data are within the manuscript and its Supporting Information files.


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