| Literature DB >> 34130366 |
Dibbendhu Khanra1, Anindya Mukherjee2, Saurabh Deshpande3, Hassan Khan4, Sanjeev Kathuria5, Danesh Kella6, Deepak Padmanabhan3.
Abstract
BACKGROUND: There are limited studies comparing the risk of osteoporosis and fractures between different direct oral anticoagulants (DOACs) and vitamin K antagonists (VKA) in non-valvular atrial fibrillation (AF). Using a network meta-analysis (NMA), we compared osteoporotic fractures among 5 different treatment arms, viz. dabigatran, rivaroxaban, apixaban, edoxaban, and VKA.Entities:
Keywords: Atrial fibrillation; Factor Xa inhibitors; Network meta-analysis; Osteoporotic fractures; Vitamin K
Year: 2021 PMID: 34130366 PMCID: PMC8206613 DOI: 10.11005/jbm.2021.28.2.139
Source DB: PubMed Journal: J Bone Metab ISSN: 2287-6375
Fig. 1Preferred Reporting Items for Systematic Review and Meta-Analysis flow diagram of patient selection. DOAC, direct oral anticoagulant.
Baseline parameters across the studies
| References | Year | Comparison | Study design | Country | Median follow-up (yr) | Sample size | Age (yr) | Female (%) | CHADS2 | CKD (%) | Steroids (%) | Osteoporosis (%) | Drugs for osteoporosis (%) | ||||||||
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| DOAC | VKA | DOAC | VKA | DOAC | VKA | DOAC | VKA | DOAC | VKA | DOAC | VKA | DOAC | VKA | DOAC | VKA | ||||||
| Lau et al. [ | 2020 | DOAC vs. VKA | Population-based study | Hong Kong | 2.2 | 13,974 | 9,541 | D: 74.4±10 | 73±11.4 | 49.9 | 45.2 | - | - | 3.0 | 8.8 | 7.9 | 9.5 | 1.3 | 1.1 | 1.2 | 0.8 |
| R: 75±10.3 | |||||||||||||||||||||
| A: 77.9±10.3 | |||||||||||||||||||||
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| Binding et al. [ | 2019 | DOAC vs. VKA[ | Population-based study | Denmark | 2 | 25,182 | 12,168 | 73 (67–81) | 72 (65–79) | 44.1 | 38.2 | - | - | - | - | 6.0 | 6.3 | 4.1 | 2.9 | 7 | 6.1 |
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| Huang et al. [ | 2020 | DOAC vs. VKA | Population-based study | Taiwan | 2.4 | 9,707 | 9,707 | 72.4±10.7 | 71.3±11.5 | 40.8 | 41.1 | 2.8±1.6[ | 2.7±1.8[ | 6.7 | 7.9 | 5.9 | 6.0 | 0.5 | 0.7 | 0.9 | 1 |
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| Lutsey et al. [ | 2020 | DOAC vs. VKA | Population-based study | USA | 2.1 | 84,650 | 82,625 | D: 67.0±12.4 | 70.2±12.3 | 37.3 | 38.8 | D: 3.0±1.9[ | 3.6±2.0[ | 8.5 | 14.6 | - | - | 28.1 | 29.9 | 4.4 | 5.1 |
| R: 67.7±12.3 | R: 3.1±1.9[ | ||||||||||||||||||||
| A: 69.1±12.6 | A: 3.4±2.0[ | ||||||||||||||||||||
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| Lau et al. [ | 2017 | DOAC (D) vs. VKA | Population-based study | Hong Kong | 1.5 | 3,268 | 4,884 | 74.2±10.1 | 73.3±11.0 | 50.7 | 49.0 | 3.4±2.2 | 3.4±2.3 | 2.9 | 3.7 | 6.5 | 7.5 | 1.2 | 1.1 | 1.0 | 0.9 |
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| Connolly et al. [ | 2009 | DOAC (D) vs. VKA | Randomized-open-label trial | 44 countries | 2 | 6,011 (110 mg) | 6,021 | 71.4±8.6 (110 mg) | 71.6±8.6 | 35.7 (110 mg) | 36.7 | - | - | - | - | - | - | - | - | - | - |
| 6,075 (150 mg) | 71.5±8.8 (150 mg) | 36.8 (150 mg) | |||||||||||||||||||
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| Patel et al. [ | 2011 | DOAC (R) vs. VKA | Randomized-double-blind trial | 45 countries | 2.1 | 7,131 | 7,133 | 73 (65–78) | 73 (65–78) | 39.7 | 39.7 | 3.48±0.94 | 3.46±0.95 | - | - | - | - | - | - | - | - |
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| Hori et al. [ | 2012 | DOAC (R) vs. VKA | Randomized-double-blind trial | Japan | 0.8 | 639 | 639 | 71.0 (34–89) | 71.2 (43–90) | 17.1 | 21.8 | 3.22 | 3.27 | - | - | - | - | - | - | - | - |
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| Granger et al. [ | 2011 | DOAC (A) vs. VKA | Randomized-double-blind trial | 40 countries | 1.8 | 9,120 | 9,081 | 70 (63–76) | 70 (63–76) | 35.5 | 35.0 | 2.1±1.1 | 2.1±1.1 | 58.8 | 58.6 | - | - | - | - | - | - |
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| Giugliano et al. [ | 2013 | DOAC (E) vs. VKA | Randomized-double-blind trial | 46 countries | 2.8 | 7,035 | 7,036 | 72 (64–78) | 72 (64–78) | 37.9 (60 mg) | 37.5 | 2.8±1.0 | 2.8±1.0 | 19.6 (60 mg) | 19.3 | - | - | - | - | - | - |
| 38.8 (30 mg) | 19.0 (30 mg) | ||||||||||||||||||||
The data is presented as mean±standard deviation or median (range) and categorical variables expressed as number (%).
No individual DOAC data.
CHADS2 scores are CHA2DS2-VASc score (congestive heart failure, hypertension, age, diabetes mellitus, stroke or transient ischemic attack, vascular disease, age 65 to 74 years, sex category).
DOAC, direct oral anticoagulant; D, dabigatran; R, rivaroxaban; A, apixaban; E, edoxaban; VKA, vitamin K antagonists; CHADS2, congestive heart failure, hypertension, age, diabetes mellitus, stroke or transient ischemic attack; CKD, chronic kidney disease.
Fig. 2(A) Forest plot depicting the comparison of total fractures with vitamin K antagonists (VKA) and direct oral anticoagulant (DOAC) among different studies in random effect and inverse variance method. Estimates were expressed in odds ratio (OR) with 95% confidence interval (CI). Heterogeneity was expressed in I2 and tau2. P<0.05 was set as level of significance. Sub-group analysis showing comparison of fractures between individual (B) dabigatran and VKA, (C) rivaroxaban and VKA, (D) apixaban and VKA, (E) edoxaban and VKA. Binding et al. [35], 2019 was excluded from sub-group analysis as it did not report DOAC-specific fracture data.
Fig. 3Network meta-analysis comparing fracture events among 5 treatment arms. (A) Network plot where each node on the plot represents an individual intervention (dabigatran, rivaroxaban, apixaban, edoxaban, and vitamin K antagonists [VKA]) with connecting lines between nodes indicating number of trials making each comparison. (B) League table showing Bayesian comparison of all treatment pairs: the table displays the results for all treatment pairs in both the upper triangle and lower triangle, but with the comparison switched over. For both above and below the leading diagonal, the results are for the treatment at the top of the same column vs. treatment at the left hand side of the same row. (C) Bayesian random effect consistency model forest plot of the pooled effect estimates of fractures expressed in odds ratio and 95% credible interval (CrI) for individual direct oral anticoagulants (DOACs) compared to VKA. (D) Ranking probability table for all studies showing probability for each treatment at each rank expressed in percentage. (E) Rankogram showing median rank chart of intervention arms with all studies included in the network meta-analysis model. For treatment rankings, smaller outcome values were set as desirable.
Fig. 4Deviance report: (A) residual deviance from primary network meta-analysis (NMA) model are plotted against the residual deviance from the unrelated mean effect (UME) inconsistency model for each study arm separately in the analysis. For both models, the larger the residual deviance, the poorer the fit of that study arm data to the respective model. The values of residual deviances for each trial arm from NMA and UME model are mentioned in Supplementary Appendix 8; (B) plot derived from primary NMA model showing contribution for each study arm to the residual deviance; arms from the same study are ordered from left to right; (C) the contour plot looking at residual deviance and leverage (which is a statistical measure of influence of a data point on model estimation) simultaneously.