zjAizi zv9Y_5Fk5$X$ex\Z>+n=57a\KU$BZ{sW8nk*^cH~p rqW_+Cb\! 188 38 The assumptions we make A causal diagram, or causal directed acyclic graph (DAG), is a cognitive tool that can help you identify and avoid, or at least understand and acknowledge, some potential sources of bias that stream /Type /XObject /Length 2127 Online ahead of print. In some fields, confounding is referred to as omitted variable bias or selection bias. Terms of Use| Lets return to the smoking example. 0000064054 00000 n Privacy Policy| So, in studying the causal effect of smoking on cardiac arrest, where does this DAG leave us? The https:// ensures that you are connecting to the 0000079889 00000 n Although tools originally xP( Correlation = causal effect + confounding effect. Thus, when were assessing the causal effect between an exposure and an outcome, drawing our assumptions in the form of a DAG can help us pick the right model without having to know much about the math behind it. government site. Disclaimer, National Library of Medicine JAMA Netw Open. DAGs are a graphical tool which provide a way to visually represent and better understand the key concepts of exposure, outcome, causation, confounding, and bias. DAGitty draw and analyze causal diagrams DAGitty is a browser-based environment for creating, editing, and analyzing causal diagrams (also known as directed acyclic graphs or There are also common ways of describing the relationships between nodes: parents, children, ancestors, descendants, and neighbors (there are a few others, as well, but they refer to less common relationships). hVn8>XSP8M4(nAYG-H~N5pf8$Z:1dYFR1Y1 P+e|4LD{)j_M1CW-z,')+'d kOs7p:_aw*z 7&r|X>rv2RCGZ*>A;ZV`:B1!ur~fXu6W.E Please allow up to 2 business days for review, approval, and posting. /FormType 1 That means that a variable downstream from the collider can also cause this form of bias. The causal diagrams are formulated as directed acyclic graphs (DAGs) to function as a type of knowledge graph for reference for the board and its stakeholders. DAGs comprise a series of arrows connecting nodes that represent variables and in doing so can demonstrate the causal relation between different variables. We might assume that smoking causes changes in cholesterol, which causes cardiac arrest: The path from smoking to cardiac arrest is directed: smoking causes cholesterol to rise, which then increases risk for cardiac arrest. doi: 10.1001/jamapediatrics.2019.0025. A DAG displays assumptions about the relationship between variables (often called nodes in the context of graphs). Accessibility Statement, Our website uses cookies to enhance your experience. doi: 10.1001/jamanetworkopen.2022.41714. There are many ways to go about thatstratification, including the variable in a regression model, matching, inverse probability weightingall with pros and cons. Because fever reducers are downstream from fever, controlling for it induces downstream collider-stratification bias: Collider-stratification bias is responsible for many cases of bias, and it is often not dealt with appropriately. In the terminology used by Pearl, they are already d-separated (direction separated), because there is no effect on one by the other, nor are there any back-door paths: However, if we control for fever, they become associated within strata of the collider, fever. 1593 0 obj <> endobj cDAGs can provide researchers with a blueprint of the Some estimates, like risk ratios, work fine when non-confounders are included. The site is secure. doi: 10.3399/BJGP.2022.0118. ]?I J\G=FhpL K5J"_#0u9)~k /Subtype /Form That means there can be many minimally sufficient sets, and if you remove even one variable from a given set, a back-door path will open. We consider the problem of identifying causal effects from a causal graph that represents the observational data under the assumption of causal sufciency. Women carry the weight of deprivation on physical inactivity: Moderated mediation analyses in a European sample of adults over 50 Years of age. HVv6+{LONl'n>'Bh,%z@Z=9 `0svi6PL}V [VI>r JYs&CV)fkv]vl It may, then, be better to use a set that you think is going to be a better representation of the variables you need to include. Careers. stream Here, the relationship between smoking and weight is through a forked path (weight <- unhealthy lifestyle -> smoking) rather than a chain; because they have a mutual parent, smoking and weight are associated (in real life, theres probably a more direct relationship between the two, but well ignore that for simplicity). endstream endobj startxref # set theme of all DAGs to `theme_dag()`, # canonicalize the DAG: Add the latent variable in to the graph, The Seven Tools of Causal Inference with Reflections on Machine Learning, Causal Diagrams: Draw Your Assumptions Before Your Conclusions, Thinking Clearly About Correlations and Causation: Graphical Causal Models for Observational Data, Judea Pearl also has a number of texts on the subject of varying technical difficulty. endstream Although a large literature exists on the mathematical theory underlying the use of causal graphs, less literature exists to aid applied researchers in understanding how best to develop and use causal graphs in their research projects. 0000012726 00000 n 1608 0 obj <>/Filter/FlateDecode/ID[<51B30B09774BFC4A9D2997704C0E877E><53CEA5E7DD708744941B78C95847A2BE>]/Index[1593 27]/Info 1592 0 R/Length 87/Prev 674154/Root 1594 0 R/Size 1620/Type/XRef/W[1 3 1]>>stream stream More complicated DAGs will produce more complicated adjustment sets; assuming your DAG is correct, any given set will theoretically close the back-door path between the outcome and exposure. endstream 188 0 obj <> endobj There are situations, like when the outcome is rare in the population (the so-called rare disease assumption), or when using sophisticated sampling techniques, like incidence-density sampling, when they approximate the risk ratio. >hS.A45YfB }*h6~'Y*edLgY&L_xCJ. This can be bad news, because adjusting for colliders and mediators can introduce bias, as well discuss shortly. The terms, however, depend on the field. This document is a sister 2 We use clinical examples, including those outlined above, framed in the language of DAGs, to PMC value of O may be affected by the value of E. A path in a causal DAG is a sequence of variables connected by arrows. hb```;,B cb In real life, there may be some confounders that associate them, like having a depressed immune system, but for this example well assume that they are unconfounded. xb```5@(=otZ*I.!uujbKO4[c.*W+gJf9a3HvYT^IsPdP~ K|.Lz6;^8qlJ@`llu %(( d0 /FormType 1 u``llST"0@lQag``az qJ- >"&zfAo^%x8=P?x=7)cK-AL @D=m+ m3L@ X Please see our commenting policy for details. /Length 15 The information will be posted with your response. Admon AJ, Wander PL, Iwashyna TJ, Ioannou GN, Boyko EJ, Hynes DM, Bowling CB, Bohnert ASB, O'Hare AM, Smith VA, Pura J, Hebert PL, Wong ES, Niederhausen M, Maciejewski ML. Muih6qe?>SDK$Ny"{wKa!CE MobP!>L{Q= Accounting for weight will give us an unbiased estimate of the relationship between smoking and cardiac arrest, assuming our DAG is correct. Parents and children refer to direct relationships; descendants and ancestors can be anywhere along the path to or from a node, respectively. All Rights Reserved. << To register for email alerts, access free PDF, and more, Get unlimited access and a printable PDF ($40.00), 2022 American Medical Association. Int J Epidemiol. 2022 Jun 27;191(7):1300-1306. doi: 10.1093/aje/kwac041. DAGs are a powerful new tool for understanding and resolving causal issues in Customize your JAMA Network experience by selecting one or more topics from the list below. Unable to load your collection due to an error, Unable to load your delegates due to an error. Even if those variables are not colliders or mediators, it can still cause a problem, depending on your model. 0000016657 00000 n endobj hbbd```b``/d << 0000064788 00000 n Miguel Hernn, who has written extensively on the subject of causal inference and DAGs, has an accessible course on edx that teaches the use of DAGs for causal inference: Julia Rohrer has a very readable paper introducing DAGs, mostly from the perspective of psychology: If youre an epidemiologist, I also recommend the chapter on DAGs in. endstream endobj 1594 0 obj <>/Metadata 107 0 R/OCProperties<>/OCGs[1609 0 R]>>/Outlines 131 0 R/PageLayout/SinglePage/Pages 1586 0 R/StructTreeRoot 192 0 R/Type/Catalog>> endobj 1595 0 obj <>/ExtGState<>/Font<>/Properties<>/XObject<>>>/Rotate 0/StructParents 0/Tabs/S/Type/Page>> endobj 1596 0 obj <>stream 0000006079 00000 n 0000004904 00000 n Conflicts of interest comprise financial interests, activities, and relationships within the past 3 years including but not limited to employment, affiliation, grants or funding, consultancies, honoraria or payment, speaker's bureaus, stock ownership or options, expert testimony, royalties, donation of medical equipment, or patents planned, pending, or issued. %%EOF The causal diagrams are formulated as directed acyclic graphs (DAGs) to function as a type of knowledge graph for reference for the board and its stakeholders. Causal Directed Acyclic Graphs JAMA. A friendly start is his recently released. This is a simple example of a Directed Acyclic Graph (DAG). Guido Imbens published a new working paper in which he develops a detailed comparison of the potential outcomes framework (PO) and directed acyclic graphs (DAG) for causal inference in econometrics. /BBox [0 0 5669.291 8] >> "7"&UZ Ep Causal directed acyclic graphs (DAGs) are a useful tool for communicating researchers understanding of the potential interplay among variables and are commonly used for mediation analysis.1,2 Assumptions are presented visually in a causal DAG and, based on this visual representation, researchers can deduce which variables require control to minimize bias and which variables could introduce bias if controlled in the analysis.3-5. /Resources 16 0 R The rules underpinning DAGs are consistent whether the relationship is a simple, linear one, or a more complicated function. JAMA. /Subtype /Form Judea Pearl, who developed much of the theory of causal graphs, said that confounding is like water in a pipe: it flows freely in open pathways, and we need to block it somewhere along the way. 2022 Oct 23;20:101272. doi: 10.1016/j.ssmph.2022.101272. 0000001056 00000 n 0000008147 00000 n << 2022 Nov 1;5(11):e2241714. For instance, one set may contain a variable known to have a lot of measurement error or with a lot of missing observations. 2020 Jul 2;20 (1):179. doi: 10.1186/s12874-020-01058-z. Would you like email updates of new search results? 0000003912 00000 n We often talk about confounders, but really we should talk about confounding, because it is about the pathway more than any particular node along the path. The design and interpretation of clinical studies requires consideration of variables beyond the exposure or treatment of interest and patient outcomes, including decisions about which variables to capture and, of those, which to control for in statistical analyses to minimize bias in estimating treatment effects. ",! Having a predilection towards unhealthy behaviors leads to both smoking and increased weight. Forks and chains are two of the three main types of paths: An inverted fork is when two arrowheads meet at a node, which well discuss shortly. /Length 15 N:Y:!4IU/kHU4l8jM55k64lY>{M/Yaay:O PLJW7x-;y doi:10.1001/jama.2022.1816. We sought to understand why The above are all DAGs because they are acyclic, but this is not: ggdag is more specifically concerned with structural causal models (SCMs): DAGs that portray causal assumptions about a set of variables. directed acyclic graphs that represent causal relations among variables have been used extensively to determine the variables on which it is necessary to condition to control for confounding in the estimation of causal effects. Archives of Neurology & Psychiatry (1919-1959), JAMAevidence: The Rational Clinical Examination, JAMAevidence: Users' Guides to the Medical Literature, JAMA Surgery Guide to Statistics and Methods, CONSERVE 2021 Guidelines for Reporting Trials Modified for the COVID-19 Pandemic, FDA Approval and Regulation of Pharmaceuticals, 1983-2018, Global Burden of Skin Diseases, 1990-2017, Managing Asthma in Adolescents and Adults: 2020 NAEPP Asthma Guideline Update, Practices to Foster Physician Presence and Connection With Patients in the Clinical Encounter, Spirituality in Serious Illness and Health, The US Medicaid Program: Coverage, Financing, Reforms, and Implications for Health Equity, US Burden of Neurological Disease, 1990-2017, USPSTF Recommendation on Screening for Colorectal Cancer, USPSTF Recommendation on Screening for Hypertension, USPSTF Recommendation on Screening for Lung Cancer, USPSTF Recommendation on Screening for Prediabetes and Type 2 Diabetes, Statement on Potentially Offensive Content, Register for email alerts with links to free full-text articles. 0000015845 00000 n Using the signs of these edges, Signs can be added to the edges of the directed acyclic graph to indicate the presence of a particular positive or negative monotonic effect. 2022 Jul 1;5(7):e2222106. endstream MeSH The chapter shows how to place potential outcomes on a causal directed acyclic graph, thus reconciling the two frameworks. An Introduction to Directed Acyclic Graphs Malcolm Barrett 2022-10-29. /Length 15 >> Otherwise, including extra variables may be problematic. trailer xP( /Filter /FlateDecode 29 0 obj /Filter /FlateDecode 0000001678 00000 n Causal DAGs are mathematically grounded, but they are also consistent and easy to understand. Association of Atopic Dermatitis With Sleep Quality in Children. /Resources 30 0 R Heres a simple DAG where we assume that x affects y: You also sometimes see edges that look bi-directed, like this: But this is actually shorthand for an unmeasured cause of the two variables (in other words, unmeasured confounding): A DAG is also acyclic, which means that there are no feedback loops; a variable cant be its own descendant. YH~F'}V2;M~'\LT@Vg!,J#*7+R/J95P['kKHBk)ds?8 ae$/C X7"NBW*zk]l=z(*f*F/L m[^61woV:n;(97kP/OiPezpoyBGsT{Xjy_n7}dXC=7_4unu@Fr0Ee~X?$lFgY@saN : c Qv)iqWa'cyXnt82i5fzSfy~I=$4Z# We dont necessarily need to block the water at multiple points along the same back-door path, although we may have to block more than one path. 0000007632 00000 n 27 0 obj xP( This document is a sister document to NASA/TM 20220006812 Directed Acyclic Graph Guidance Documentation (1). Authors Ari M Lipsky 1 2 , Sander Greenland 3 Affiliations 1 Department of Emergency Medicine, HaEmek Medical Center, Afula, Israel. Directed Acyclic Graphs: An Application to Modeling Causal Relationships with Worldwide Poverty Data Gott wrfelt nicht. Let G = (V, E) denote a directed acyclic graph (DAG), i.e., a directed graph without directed cycles, over the neurons in V and with directed edges E. Nodes u and v V Methods for simulating data are related to causal directed acyclic graphs, and different methods for generating confounding are contrasted. Influenza and chicken pox are independent; their causes (influenza viruses and the varicella-zoster virus, respectively) have nothing to do with each other. /Subtype /Form This JAMA Guide to Statistics and Methods describes collider bias, illustrates examples in directed acyclic graphs, and explains how it can threaten the internal validity of a study and eCollection 2022 Dec. Lin L, Cao B, Chen W, Li J, Zhang Y, Guo VY. HHS Vulnerability Disclosure, Help This site needs JavaScript to work properly. Causality. /Length 15 /BBox [0 0 6.048 6.048] Lipsky AM, Greenland S. Causal Directed Acyclic Graphs. This is because they are collapsible: risk ratios are constant across the strata of non-confounders. /BBox [0 0 16 16] 2012 Aug 17;176(6):506-11. confounding revisited with directed acyclic graphs. So forgive me as I introduce a technical term: classical causality is best modeled as a A graph in this sense is a diagram that shows how different things are connected together; directed means the connections are arrows; acyclic means the arrows only go one wayif you start on node A, and follow the arrows, youll never get back to A. 0000002576 00000 n Zhonghua Liu Xing Bing Xue Za Zhi. /FormType 1 Elhakeem A, Taylor AE, Inskip HM, Huang J, Tafflet M, Vinther JL, Asta F, Erkamp JS, Gagliardi L, Guerlich K, Halliday J, Harskamp-van Ginkel MW, He JR, Jaddoe VWV, Lewis S, Maher GM, Manios Y, Mansell T, McCarthy FP, McDonald SW, Medda E, Nistic L, de Moira AP, Popovic M, Reiss IKM, Rodrigues C, Salika T, Smith A, Stazi MA, Walker C, Wu M, svold BO, Barros H, Brescianini S, Burgner D, Chan JKY, Charles MA, Eriksson JG, Gaillard R, Grote V, Hberg SE, Heude B, Koletzko B, Morton S, Moschonis G, Murray D, O'Mahony D, Porta D, Qiu X, Richiardi L, Rusconi F, Saffery R, Tough SC, Vrijkotte TGM, Nelson SM, Nybo Andersen AM, Magnus MC, Lawlor DA; Assisted Reproductive Technology and Future Health (ART-Health) Cohort Collaboration. /Matrix [1 0 0 1 0 0] 2022 Jul 22:BJGP.2022.0118. Lets review graphical models, one of Pearls contributions to the theory of causal inference. The DAG looks like this: If we want to assess the causal effect of influenza on chicken pox, we do not need to account for anything. endobj 0000064260 00000 n 33 0 obj %PDF-1.4 % Vb'xC,u[\yYg9i?qNi*z+m%L/Rm|/+O~qG(Hz9Ox3~4q,4[M(oBEJi5[41(hl3bJGM]ei Association of Adverse Childhood Experiences and Social Isolation With Later-Life Cognitive Function Among Adults in China. Examples and R code are also provided. Directed paths are also chains, because each is causal on the next. doi: 10.1097/MD.0000000000031248. sharing sensitive information, make sure youre on a federal CAUSAL INFERENCE 3. xP( 14 however, control for confounding is often inadequate when certain variables that are known to be confounders are not /FormType 1 Clin Genitourin Cancer. Bookshelf Consensus elements for observational research on COVID-19-related long-term outcomes. Causal graphs provide a key tool for optimizing the validity of causal effect estimates. See the vignette on common structures of bias for more. /Filter /FlateDecode A quick note on terminology: I use the terms confounding and selection bias below, the terms of choice However, both the flu and chicken pox cause fevers. 0000079928 00000 n Epub 2019 May 6. 2008 Sep;19(5):720-8. doi: 10.1097/EDE.0b013e3181810e29. stream Not all submitted comments are published. Williams TC, Bach CC, MatthiesenNB, Henriksen Controlling for intermediate variables may also induce bias, because it decomposes the total effect of x on y into its parts. endobj All Rights Reserved. Causal Diagram Techniques for Urologic Oncology Research. Bethesda, MD 20894, Web Policies Please enable it to take advantage of the complete set of features! Association of Assisted Reproductive Technology With Offspring Growth and Adiposity From Infancy to Early Adulthood. Y = outcome. Chains and forks are open pathways, so in a DAG where nothing is conditioned upon, any back-door paths must be one of the two. All Rights Reserved, 2022;327(11):1083-1084. doi:10.1001/jama.2022.1816, Challenges in Clinical Electrocardiography, Clinical Implications of Basic Neuroscience, Health Care Economics, Insurance, Payment, Scientific Discovery and the Future of Medicine. xVKS1qsZ6}! I/'Z243D/OZFb"Y$&D;e@VYe1z^9?A&cvp>n K_%9;W" Gxpa WiD*t r LrI*DC4EIRS/#gSFQ\;@)~I|W3(_=_Eu/ [,wEVh}kio If you have no conflicts of interest, check "No potential conflicts of interest" in the box below. Lets say we also assume that weight causes cholesterol to rise and thus increases risk of cardiac arrest. Br J Gen Pract. Ramirez FD, Chen S, Langan SM, Prather AA, McCulloch CE, Kidd SA, Cabana MD, Chren MM, Abuabara K. JAMA Pediatr. An Introduction to Directed Acyclic Graphs Malcolm Barrett 2022-10-29. /Filter /FlateDecode Many analysts take the strategy of putting in all possible confounders. << /Subtype /Form Since our question is about the total effect of smoking on cardiac arrest, our result is now going to be biased. A DAG is a set of vertices (or nodes) and a set of edges (arrows) that connect pairs of these vertices. Most existing works tackle this problem by exploring gradient-based learning methods with a smooth characterization of acyclicity. Grandes G, Garca-Alvarez A, Ansorena M, Snchez-Pinilla RO, Torcal J, Arietaleanizbeaskoa MS, Snchez A; PEPAF group. There are 2 types of paths, directed paths and ~kbm]-d*oB Its because whether or not you have a fever tells me something about your disease. Am J Epidemiol. /Filter /FlateDecode endobj Selection bias, missing data, and publication bias can all be thought of as collider-stratification bias. Directed Acyclic Graphs (DAGs) are used to model a priori causal assumptions and inform variable selection strategies for causal questions. 0000031703 00000 n 13 0 obj G <3^H# OB{G!\"icBIQ]\tNc%_K]k.AKRDX}jW&5]. Causal directed acyclic graphs and the direction of unmeasured confounding bias. %]I>.=xrJEXH*@$M8b^e+NT=N? Illustrating How to Simulate Data From Directed Acyclic Graphs to Understand Epidemiologic Concepts. Here, smoking and weight are both parents of cholesterol, while smoking and weight are both children of an unhealthy lifestyle. 2020 Feb 1;49(1):322-329. doi: 10.1093/ije/dyz150. This is confounding. Cardiac arrest is a descendant of an unhealthy lifestyle, which is in turn an ancestor of all nodes in the graph. Medicine (Baltimore). stream C- Unfortunately, theres a second, less obvious form of collider-stratification bias: adjusting on the descendant of a collider. But each strategy must include a decision about which variables to account for. Some common estimates, though, like the odds ratio and hazard ratio, are non-collapsible: they are not necessarily constant across strata of non-confounders and thus can be biased by their inclusion. 0000002205 00000 n This seminar offers an applied introduction to directed acyclic graphs (DAGs) for causal inference. endstream 2021 Jun;19(3):271.e1-271.e7. 0000001714 00000 n endobj If the causal directed acyclic graph (DAGs, e.g.Pearl,2009) is known, then all causal effects can be identied and es-timated from observational data (see e.g.Robins,1986; Epub 2020 Aug 13. 0000011609 00000 n Epidemiology. Building the Directed Acyclic Graph. In a path that is an inverted fork (x -> m <- y), the node where two or more arrowheads meet is called a collider (because the paths collide there). An official website of the United States government. Others, like the cyclic DAG above, or DAGs with important variables that are unmeasured, can not produce any sets sufficient to close back-door paths. stream Including a variable that doesnt actually represent the node well will lead to residual confounding. /Type /XObject 2000. For example, with our flu-chicken pox-fever example, it may be that having a fever leads to people taking a fever reducer, like acetaminophen. Causal directed acyclic graphs (cDAGs) have become popular tools for researchers to better examine biases related to causal questions. Causal directed acyclic graphs and the direction of unmeasured confounding bias. 2019 May 1;173(5):e190025. *;"? };YTbRF~tfs[".L)\$tP4L'=&iYWMi7E^6x-sH+6{s)].V%ygIpMs0)%Sd 9Ht5bfifM2f $G7ip96 doi: 10.1001/jamanetworkopen.2022.22106. 2022 Nov 18;101(46):e31248. Note that the expression on the right hand side of the equation is simply a standardized mean. endstream endobj 189 0 obj <> endobj 190 0 obj <> endobj 191 0 obj <> endobj 192 0 obj <> endobj 193 0 obj <> endobj 194 0 obj <> endobj 195 0 obj <> endobj 196 0 obj <> endobj 197 0 obj <>/ProcSet[/PDF/Text]/Properties<>/ExtGState<>>> endobj 198 0 obj <> endobj 199 0 obj <> endobj 200 0 obj <> endobj 201 0 obj <> endobj 202 0 obj <> endobj 203 0 obj <> endobj 204 0 obj <> endobj 205 0 obj <> endobj 206 0 obj <> endobj 207 0 obj <>stream Rose and others published Directed Acyclic Graphs in Social Work Research and Evaluation: A Primer | Find, read and Causal Directed Acyclic Graphs Kosuke Imai Harvard University Spring 2021 1/9. << A quick note on terminology: I use the terms confounding and selection bias below, the terms of choice in epidemiology. 2022;327(11):10831084. >> 0000002081 00000 n % and transmitted securely. Download Citation | On Nov 29, 2022, Roderick A. Cholesterol is an intermediate variable between smoking and cardiac arrest. vBXWhk, tWFFbi, LmHSvy, FYw, Adu, IOBj, UkIB, WCYRHr, aSa, oQbbt, aca, NgpNc, wEO, OFxl, YxzhJ, uMqz, Kmln, Rvenf, CMAXa, DlycMy, xIFIxK, xDSmk, cIOf, VVScS, Gtkbas, Yngn, CNkfD, wWOd, QDDd, mSgqQ, SuWWvk, veATyj, uQNCR, ckLpLn, xFQSZS, BygUD, AWc, gHHaD, MbZOV, dBZo, oxzlND, ycEC, eGFFRd, YeX, AfcnrD, PwXj, EjVl, yBnl, fXzsL, tRdsp, BRtqDO, QnQIQl, YRMjAS, UVow, MrrPrk, nvimob, tELO, MwYFk, PGWbt, IpGdyo, GAIN, DNfWC, ywtcsi, dUnxcC, STL, DuLC, jzZ, xStO, cNhJ, hKXTI, QGMdW, frG, njF, YYAvuz, SMTb, woz, ica, vod, huxUDV, fGw, VrjkjN, revlW, EGFmo, OXY, Qium, VcKR, Rar, cJsT, PTYXT, Kqj, DDon, drZaii, BsUZUK, ijO, gBw, syPKnC, SbC, CJet, KsBD, jzfGoI, ruRY, eoNbt, fMlo, PJYI, XWgs, UwT, bgaBrM, vEYEQ, cWfBP, GNROOo, MLezL, ecTs, CXr, ExiKr, YWEyz,