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• v.5(1); Jan-Feb 2015

A comprehensive comparative analysis of articles retracted in 2012 and 2013 from the scholarly literature

Ravi sankar damineni.

Department of Conservative Dentistry, Albadar Rural Dental College and Hospital, Gulbarga, Karnataka, India

Kapil Kumar Sardiwal

1 Department of Quantitative Methods, School of Public Health, Rutgers University, New Jersey, USA

Sita Ram Waghle

2 Department of Prosthodontics, Mithala Minority Dental College and Hospital, Darbhanga, Bihar, India

M.B Dakshyani

3 Department of Pedodontics, Mithala Minority Dental College and Hospital, Darbhanga, Bihar, India

Background:

Science is a dynamic subject with ever-changing concepts and is said to be self-correcting. One of the major mechanisms of self-correction is retraction of flawed work.

To study the various parameters associated with retraction of scientific articles in 2012 and 2013 and discuss the current trends in article retraction over the period of 2 years.

Materials and Methods:

Data were retrieved from MEDLINE (via PubMed) using the keywords retraction of articles, retraction notice, and withdrawal of article in January 2014, and analysis of articles published in 2012 and 2013 was carried out.

A total of 155 articles in 2012 and 182 in 2013 were retracted, and original articles followed by case reports constituted major part of it. The most cited reasons for retraction were mistakes, plagiarism, and duplicate submission, and the time interval between submission and retraction had reduced in 2013.

Conclusion:

Although retracted articles constitute the tip of an iceberg, they are still a matter of major concern in the scientific world. So, editors should follow the Committee on Publication Ethics (COPE) guidelines and make an effective strategy in order to reduce such misconduct, as it reflects very adversely not only in the scientific community but also in the general public.

INTRODUCTION

Science is an ever-changing subject that changes with the wind of changing time and is said to be self-correcting as scientific literature is never flawless.[ 1 ] One of the major mechanisms of self-correction is retraction of flawed work and retraction rate of scholarly articles has sharply risen in recent years.[ 2 ]

Retraction is a public statement made about an earlier statement that withdraws, cancels, refutes, diametrically reverses the original statement, or ceases and desists from publishing the original statement. It may be initiated by the editors of a journal or by the author (s) of the papers (or their institution).[ 3 ] Committee on Publication Ethics (COPE) described retraction as a mechanism for correcting the literature and alerting readers to publications that contain such seriously flawed or erroneous data that their findings and conclusions cannot be relied upon.

The number of articles retracted each year has increased precipitously in recent years.[ 4 , 5 , 6 ] Furthermore, fraud was found to be involved in 94% of the 228 cases of misconduct identified by the US Office of Research Integrity from 1994 to 2012.[ 7 ] The number of retractions in journals covered by the Science Citation Index Expanded has increased 20 times, i.e. a 10-fold increase, since there was a twofold increase in article production between 1990 and 2008.[ 8 ] A similar 10-fold increase was found when focusing on MEDLINE only (1999–2009), although retraction remains a rare event since it represents only 0.02% of publications.[ 9 ] So, we aimed to study the various factors governing retraction of scientific articles by analyzing all the retracted articles in 2012 and 2013.

MATERIALS AND METHODS

To obtain data regarding retraction of articles in the years 2012 and 2013, we retrieved MEDLINE (via PubMed), a bibliographic database of biomedical literature produced by the National Library of Medicine, using the keywords: Retraction of articles, retraction notice, and withdrawal of article in January 2014. We noted the number of articles retracted in the years 2012 and 2013. We assessed all the characteristics of retractions where the text was available in English. (Retractions are identified in MEDLINE as a specific category and we used this tag for searching.) For each retraction, we recorded the article type (e.g. original research, review article, case report, letter), number of authors, who issued the retraction (e.g. authors, editor, publisher), and the reason for the retraction [e.g. data fabrication or falsification, suspected fraud, scientific error, unethical, plagiarism, duplicate publication, other causes (e.g. publisher error, authorship disputes, copyright infringement), or unknown]. We also noted the time interval between publication and retraction of the particular article. We also performed the comparative analysis of the years 2012 and 2013.

Overall, 135 retraction notices in 2012 and 158 in 2013 were retrieved. Of these, 135 retraction notices presented 155 retractions and 158 notices presented a total of 182 retractions. Retraction notices represent a notice issued by a journal, which comprise notification of retraction of one or more articles by the journal at that particular time. Overall, 155 retractions in 2012 and 182 in 2013 were considered for evaluation [ Table 1 ].

Reasons for retraction of articles in the years 2012 and 2013

Of the 155 retractions available in 2012, the reason was not given for 32 articles (20.65%), and 182 retractions revealed no reasoning for 46 articles. For example, the only information given by some journals is that the article is being retracted.

In Table 1 is given the various reasons for the retraction of articles such as Mistakes (honest errors), Plagiarism, Duplicate publication, Fabricated data, Author dispute, Ethical issues and it showed that the most cited reasons were mistakes, plagiarism, and duplicate submission both in 2012 and 2013 [ Table 1 ].

Table 2 shows that in both 2012 and 2013, original articles followed by case reports and reviews constituted the maximum percentage of total retracted articles [ Figure 1 ]. Time interval between submission and retraction reduced to a mean of 2.2 years in 2013 as compared to 2.8 years in 2012.

Various characteristics of the retracted articles

Representing the incidence of retraction of various types of articles

A retraction notice is issued to alert readers when a published study is no longer scientifically valid or trustworthy.

The present study showed that the incidence of retraction of articles increased from 155 in the year 2012 to 182 in 2013. Corbyn et al .[ 8 ] and Wagner et al .,[ 9 ] in their study of retraction of articles between 1990 and 2008 and between 1999 and 2009, respectively, observed nearly 10-fold increase in the incidence of retraction.

In our analysis, mistakes or honest errors constituted the commonest reason for article retractions than any other reason, as given in Table 1 . However, plagiarism represents the second most common reason and this had increased significantly in 2013 as compared to 2012. Wager et al .[ 9 ] observed that the most common reasons for retraction were honest errors (28%), redundant publication (17%), and plagiarism (16%). The present study also revealed similar findings showing honest errors as the most common cause of retraction. Nath et al .[ 10 ] also examined the retractions listed in MEDLINE between 1982 and 2002 and found that 27% of articles were retracted because of misconduct and 62% because of errors, but they failed to provide more descriptive categorization for reasons of retraction. Decullier et al .[ 11 ] in their cross-sectional study in the year 2008 also observed similar results that the most cited reasons were mistakes (28%), plagiarism (20%), fraud (14%), and overlap (11%).

This is an alarming situation since it is a disgraceful act in a scientific writing and represents one of the biggest challenges faced by the scholarly world and andby far a grim form of delinquency in academics.

So, in the author's opinion, such forms of academic misconduct must be recognized and significant reduction of it can be brought about by awareness, objective check methods, and stringent punishment.

It is unfortunate that retractions may be due to genuine mistakes or misconduct. So, it is imperative to indicate the reason for the retraction, so that the authors who have acted responsibly and honestly are alerted by the journal about the flaws of their work and should not be stigmatized along with those who have committed gross misconduct. This is even emphasized in the retraction guidelines of COPE.[ 12 , 13 ]

If we take into account the number of publications worldwide, the first and second rankings are bagged by the US and the UK with 22,969 and 8069 publications, respectively, and India represents 2296 publications. However, retractions, as a whole, are quite rare and represent just a tip of an iceberg, i.e. mere upsurge in the quantity of publications does not indicate increased quality of research work in the country.[ 14 ] This goes in accordance to one very famous saying, “You can put millions of farmers to cultivate, but you need some real scientists to make green revolution.”

Most of the articles retracted in biomedical literature are related to original articles, followed by case reports and review articles. Table 1 shows that retraction of original articles and case reports had increased in 2013 because of mistakes (honest errors), plagiarism, duplicate publication, and fabricated data. So, we can say that there is more potential of providing fraudulent data in experimental studies than in other types of articles. Fraudulent data are not new in science. Gregor Mendel, the Father of Genetics, may have selectively modified his data to support his conclusions, and statistical analysis suggests that Mendel's data are biased strongly in the direction of agreement with expectation.[ 15 ]

In 12 cases (12.2%) of 2012 and 8 (7.7%) of 2013, no reason for retraction was stated, or the language was so unclear that the reason could not be determined. Journal editors may be reluctant to print retractions with sufficient information either because others may doubt on the expertise of the editorial team or due to the fear of legal actions by discredited authors. This shows some discomfort on the part of authors and journals in admitting mistakes. However, the impact of published retractions is, in part, determined by the researchers seeking them out.[ 15 ] Wager et al .,[ 9 ] in their study of retractions between 1988 and 2008, found that 5% of the retracted articles did not state the reason for retraction.

According to COPE, authors usually would not have grounds for taking legal action against a journal over the act of retraction if it follows a suitable investigation and proper procedures. COPE also states that journal editors should consider at least issuing an expression of concern if an investigation is underway, but a judgment will not be available for a considerable period of time.[ 16 ] National Library of Medicine (NLM)implemented a policy for identifying and indexing published retractions. They chose to link the notice of retraction to the original article rather than delete the citation to the retracted article, because they felt that removal might affect the historical perspective.[ 17 ]

Unfortunately, retraction notices take a long time to reach the target readers after the article is published and this remains a chronic problem. In the present study, we observed that publication of notice for retraction of articles took a long mean time of 2.8 years in 2012 which reduced to 2.2 years in 2012. Steen et al .[ 2 ] in their study observed that for the 714 retracted articles published between 1973 and 2002, retraction required an average of 49.82 months. But for the 1333 retracted articles published after 2002, retraction took 23.82 months, and thus, the author concludes that retraction may be occurring more quickly now than in the past.

Present study revealed an ast-onishing observation that an article published in Nature by Bezouska et al . in 1994, was retracted after a long time of 19 years in 2013 as they failed to reproduce the results, and it has been cited 255 times, according to Thomson Scientific's Web of Knowledge.[ 18 ]

There is no sufficient evidence available that retraction notices make much difference to the citation behavior of authors. Retracted articles still continue to be cited as valid studies for years after retraction notices have been issued.[ 19 , 20 , 21 ]

Evidence shows that articles receive fewer citations after retraction compared to a control group and that highly cited articles continue to be frequently cited after retraction.[ 17 ] Steen in his study also observed that since 2000, there has been a progressive decline in the time-to-retraction, when analyzed by the year of publication. This substantial rapid increase in retraction can be because infractions have become more common or are more quickly detected. An apparent glut of retractions might be because editors began to reach further back in time to retract articles.[ 22 ]

The final, and the most important, lesson to be learned from the human error literature is that strategies for reducing error are very different from those used to detect and handle scientific misconduct. Whereas “naming, shaming, and blaming” may be appropriate for dealing with scientific misconduct, these approaches are not effective, and may even be counterproductive, in reducing unintentional errors. Reducing errors requires a commitment to building systems that can prevent, detect, and mitigate the effects of errors when they occur. Ultimately, research mistakes, like all human errors, must be seen not as sources of embarrassment or failure, but rather as opportunities for learning and improvement. It is very imperative that approach in handling unintentional errors should be different from that of intentional errors. “Naming, shaming, and blaming” does not seem to be appropriate for handling unintentional or honest errors, but rather it should be an opportunity for learning and improvement. At the same time, authors favor that misconduct should not be tolerated at all and there is need to build an effective system that can prevent, detect, and mitigate the effects of errors when they occur. The prime objective of retractions is to rectify the literature and to ensure its academic and research integrity, rather than punishing any authors.[ 10 , 15 , 22 ] This study has a limitation that it is restricted to retracted articles indexed in the MEDLINE database only.

CONCLUSIONS

We conclude that although retractions represent a small fraction of a percent of all publications in any given field in a year, this misconduct has been rising sharply in recent years. So, we suggest that editors should make some effective strategy by following the COPE guidelines to reduce such gross misconduct as it besmirches the image of scholarly research not only in scientific community but also in general public and sullies the ethical standards of scientific publications.

Source of Support: Nil

Conflict of Interest: None declared.

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• Comparative Analysis

What It Is and Why It's Useful

Comparative analysis asks writers to make an argument about the relationship between two or more texts. Beyond that, there's a lot of variation, but three overarching kinds of comparative analysis stand out:

• Coordinate (A ↔ B): In this kind of analysis, two (or more) texts are being read against each other in terms of a shared element, e.g., a memoir and a novel, both by Jesmyn Ward; two sets of data for the same experiment; a few op-ed responses to the same event; two YA books written in Chicago in the 2000s; a film adaption of a play; etc. 
• Subordinate (A  → B) or (B → A ): Using a theoretical text (as a "lens") to explain a case study or work of art (e.g., how Anthony Jack's The Privileged Poor can help explain divergent experiences among students at elite four-year private colleges who are coming from similar socio-economic backgrounds) or using a work of art or case study (i.e., as a "test" of) a theory's usefulness or limitations (e.g., using coverage of recent incidents of gun violence or legislation un the U.S. to confirm or question the currency of Carol Anderson's The Second ).
• Hybrid [A  → (B ↔ C)] or [(B ↔ C) → A] , i.e., using coordinate and subordinate analysis together. For example, using Jack to compare or contrast the experiences of students at elite four-year institutions with students at state universities and/or community colleges; or looking at gun culture in other countries and/or other timeframes to contextualize or generalize Anderson's main points about the role of the Second Amendment in U.S. history.

"In the wild," these three kinds of comparative analysis represent increasingly complex—and scholarly—modes of comparison. Students can of course compare two poems in terms of imagery or two data sets in terms of methods, but in each case the analysis will eventually be richer if the students have had a chance to encounter other people's ideas about how imagery or methods work. At that point, we're getting into a hybrid kind of reading (or even into research essays), especially if we start introducing different approaches to imagery or methods that are themselves being compared along with a couple (or few) poems or data sets.

Why It's Useful

In the context of a particular course, each kind of comparative analysis has its place and can be a useful step up from single-source analysis. Intellectually, comparative analysis helps overcome the "n of 1" problem that can face single-source analysis. That is, a writer drawing broad conclusions about the influence of the Iranian New Wave based on one film is relying entirely—and almost certainly too much—on that film to support those findings. In the context of even just one more film, though, the analysis is suddenly more likely to arrive at one of the best features of any comparative approach: both films will be more richly experienced than they would have been in isolation, and the themes or questions in terms of which they're being explored (here the general question of the influence of the Iranian New Wave) will arrive at conclusions that are less at-risk of oversimplification.

For scholars working in comparative fields or through comparative approaches, these features of comparative analysis animate their work. To borrow from a stock example in Western epistemology, our concept of "green" isn't based on a single encounter with something we intuit or are told is "green." Not at all. Our concept of "green" is derived from a complex set of experiences of what others say is green or what's labeled green or what seems to be something that's neither blue nor yellow but kind of both, etc. Comparative analysis essays offer us the chance to engage with that process—even if only enough to help us see where a more in-depth exploration with a higher and/or more diverse "n" might lead—and in that sense, from the standpoint of the subject matter students are exploring through writing as well the complexity of the genre of writing they're using to explore it—comparative analysis forms a bridge of sorts between single-source analysis and research essays.

Typical learning objectives for single-sources essays: formulate analytical questions and an arguable thesis, establish stakes of an argument, summarize sources accurately, choose evidence effectively, analyze evidence effectively, define key terms, organize argument logically, acknowledge and respond to counterargument, cite sources properly, and present ideas in clear prose.

Common types of comparative analysis essays and related types: two works in the same genre, two works from the same period (but in different places or in different cultures), a work adapted into a different genre or medium, two theories treating the same topic; a theory and a case study or other object, etc.

How to Teach It: Framing + Practice

Framing multi-source writing assignments (comparative analysis, research essays, multi-modal projects) is likely to overlap a great deal with "Why It's Useful" (see above), because the range of reasons why we might use these kinds of writing in academic or non-academic settings is itself the reason why they so often appear later in courses. In many courses, they're the best vehicles for exploring the complex questions that arise once we've been introduced to the course's main themes, core content, leading protagonists, and central debates.

For comparative analysis in particular, it's helpful to frame assignment's process and how it will help students successfully navigate the challenges and pitfalls presented by the genre. Ideally, this will mean students have time to identify what each text seems to be doing, take note of apparent points of connection between different texts, and start to imagine how those points of connection (or the absence thereof)

• complicates or upends their own expectations or assumptions about the texts
• complicates or refutes the expectations or assumptions about the texts presented by a scholar
• confirms and/or nuances expectations and assumptions they themselves hold or scholars have presented
• presents entirely unforeseen ways of understanding the texts

—and all with implications for the texts themselves or for the axes along which the comparative analysis took place. If students know that this is where their ideas will be heading, they'll be ready to develop those ideas and engage with the challenges that comparative analysis presents in terms of structure (See "Tips" and "Common Pitfalls" below for more on these elements of framing).

Like single-source analyses, comparative essays have several moving parts, and giving students practice here means adapting the sample sequence laid out at the " Formative Writing Assignments " page. Three areas that have already been mentioned above are worth noting:

• Gathering evidence : Depending on what your assignment is asking students to compare (or in terms of what), students will benefit greatly from structured opportunities to create inventories or data sets of the motifs, examples, trajectories, etc., shared (or not shared) by the texts they'll be comparing. See the sample exercises below for a basic example of what this might look like.
• Why it Matters: Moving beyond "x is like y but also different" or even "x is more like y than we might think at first" is what moves an essay from being "compare/contrast" to being a comparative analysis . It's also a move that can be hard to make and that will often evolve over the course of an assignment. A great way to get feedback from students about where they're at on this front? Ask them to start considering early on why their argument "matters" to different kinds of imagined audiences (while they're just gathering evidence) and again as they develop their thesis and again as they're drafting their essays. ( Cover letters , for example, are a great place to ask writers to imagine how a reader might be affected by reading an their argument.)
• Structure: Having two texts on stage at the same time can suddenly feel a lot more complicated for any writer who's used to having just one at a time. Giving students a sense of what the most common patterns (AAA / BBB, ABABAB, etc.) are likely to be can help them imagine, even if provisionally, how their argument might unfold over a series of pages. See "Tips" and "Common Pitfalls" below for more information on this front.

Sample Exercises and Links to Other Resources

• Common Pitfalls
• Advice on Timing
• Try to keep students from thinking of a proposed thesis as a commitment. Instead, help them see it as more of a hypothesis that has emerged out of readings and discussion and analytical questions and that they'll now test through an experiment, namely, writing their essay. When students see writing as part of the process of inquiry—rather than just the result—and when that process is committed to acknowledging and adapting itself to evidence, it makes writing assignments more scientific, more ethical, and more authentic. 
• Have students create an inventory of touch points between the two texts early in the process.
• Ask students to make the case—early on and at points throughout the process—for the significance of the claim they're making about the relationship between the texts they're comparing.
• For coordinate kinds of comparative analysis, a common pitfall is tied to thesis and evidence. Basically, it's a thesis that tells the reader that there are "similarities and differences" between two texts, without telling the reader why it matters that these two texts have or don't have these particular features in common. This kind of thesis is stuck at the level of description or positivism, and it's not uncommon when a writer is grappling with the complexity that can in fact accompany the "taking inventory" stage of comparative analysis. The solution is to make the "taking inventory" stage part of the process of the assignment. When this stage comes before students have formulated a thesis, that formulation is then able to emerge out of a comparative data set, rather than the data set emerging in terms of their thesis (which can lead to confirmation bias, or frequency illusion, or—just for the sake of streamlining the process of gathering evidence—cherry picking). 
• For subordinate kinds of comparative analysis , a common pitfall is tied to how much weight is given to each source. Having students apply a theory (in a "lens" essay) or weigh the pros and cons of a theory against case studies (in a "test a theory") essay can be a great way to help them explore the assumptions, implications, and real-world usefulness of theoretical approaches. The pitfall of these approaches is that they can quickly lead to the same biases we saw here above. Making sure that students know they should engage with counterevidence and counterargument, and that "lens" / "test a theory" approaches often balance each other out in any real-world application of theory is a good way to get out in front of this pitfall.
• For any kind of comparative analysis, a common pitfall is structure. Every comparative analysis asks writers to move back and forth between texts, and that can pose a number of challenges, including: what pattern the back and forth should follow and how to use transitions and other signposting to make sure readers can follow the overarching argument as the back and forth is taking place. Here's some advice from an experienced writing instructor to students about how to think about these considerations:

a quick note on STRUCTURE

     Most of us have encountered the question of whether to adopt what we might term the “A→A→A→B→B→B” structure or the “A→B→A→B→A→B” structure.  Do we make all of our points about text A before moving on to text B?  Or do we go back and forth between A and B as the essay proceeds?  As always, the answers to our questions about structure depend on our goals in the essay as a whole.  In a “similarities in spite of differences” essay, for instance, readers will need to encounter the differences between A and B before we offer them the similarities (A d →B d →A s →B s ).  If, rather than subordinating differences to similarities you are subordinating text A to text B (using A as a point of comparison that reveals B’s originality, say), you may be well served by the “A→A→A→B→B→B” structure.  

     Ultimately, you need to ask yourself how many “A→B” moves you have in you.  Is each one identical?  If so, you may wish to make the transition from A to B only once (“A→A→A→B→B→B”), because if each “A→B” move is identical, the “A→B→A→B→A→B” structure will appear to involve nothing more than directionless oscillation and repetition.  If each is increasingly complex, however—if each AB pair yields a new and progressively more complex idea about your subject—you may be well served by the “A→B→A→B→A→B” structure, because in this case it will be visible to readers as a progressively developing argument.

As we discussed in "Advice on Timing" at the page on single-source analysis, that timeline itself roughly follows the "Sample Sequence of Formative Assignments for a 'Typical' Essay" outlined under " Formative Writing Assignments, " and it spans about 5–6 steps or 2–4 weeks. 

Comparative analysis assignments have a lot of the same DNA as single-source essays, but they potentially bring more reading into play and ask students to engage in more complicated acts of analysis and synthesis during the drafting stages. With that in mind, closer to 4 weeks is probably a good baseline for many single-source analysis assignments. For sections that meet once per week, the timeline will either probably need to expand—ideally—a little past the 4-week side of things, or some of the steps will need to be combined or done asynchronously.

What It Can Build Up To

Comparative analyses can build up to other kinds of writing in a number of ways. For example:

• They can build toward other kinds of comparative analysis, e.g., student can be asked to choose an additional source to complicate their conclusions from a previous analysis, or they can be asked to revisit an analysis using a different axis of comparison, such as race instead of class. (These approaches are akin to moving from a coordinate or subordinate analysis to more of a hybrid approach.)
• They can scaffold up to research essays, which in many instances are an extension of a "hybrid comparative analysis."
• Like single-source analysis, in a course where students will take a "deep dive" into a source or topic for their capstone, they can allow students to "try on" a theoretical approach or genre or time period to see if it's indeed something they want to research more fully.
• DIY Guides for Analytical Writing Assignments

• Types of Assignments
• Unpacking the Elements of Writing Prompts
• Formative Writing Assignments
• Single-Source Analysis
• Research Essays
• Multi-Modal or Creative Projects
• Giving Feedback to Students

Assignment Decoder

• Published: 26 March 2021

The journal coverage of Web of Science, Scopus and Dimensions: A comparative analysis

• Vivek Kumar Singh   ORCID: orcid.org/0000-0002-7348-6545 1 ,
• Prashasti Singh 1 ,
• Mousumi Karmakar 1 ,
• Jacqueline Leta 2 &
• Philipp Mayr 3  

Scientometrics volume  126 ,  pages 5113–5142 ( 2021 ) Cite this article

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Traditionally, Web of Science and Scopus have been the two most widely used databases for bibliometric analyses. However, during the last few years some new scholarly databases, such as Dimensions, have come up. Several previous studies have compared different databases, either through a direct comparison of article coverage or by comparing the citations across the databases. This article aims to present a comparative analysis of the journal coverage of the three databases (Web of Science, Scopus and Dimensions), with the objective to describe, understand and visualize the differences in them. The most recent master journal lists of the three databases is used for analysis. The results indicate that the databases have significantly different journal coverage, with the Web of Science being most selective and Dimensions being the most exhaustive. About 99.11% and 96.61% of the journals indexed in Web of Science are also indexed in Scopus and Dimensions, respectively. Scopus has 96.42% of its indexed journals also covered by Dimensions. Dimensions database has the most exhaustive journal coverage, with 82.22% more journals than Web of Science and 48.17% more journals than Scopus. This article also analysed the research outputs for 20 selected countries for the 2010–2018 period, as indexed in the three databases, and identified database-induced variations in research output volume, rank, global share and subject area composition for different countries. It is found that there are clearly visible variations in the research output from different countries in the three databases, along with differential coverage of different subject areas by the three databases. The analytical study provides an informative and practically useful picture of the journal coverage of Web of Science, Scopus and Dimensions databases.

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Vivek Kumar Singh, Prashasti Singh & Mousumi Karmakar

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This appendix describes the detailed steps of pre-processing and matching applied to the master journal lists from the three databases.

Pre-processing

On a detailed inspection, the three master journal lists were found to have some duplicate and incomplete entries. Further, since the Dimensions database also includes preprints and conferences, its comprehensive journal list contained some entries that referred to preprint servers or conference proceedings. Therefore, the journal lists were pre-processed to remove duplicate and incomplete entries and entries for preprint servers and conference proceedings. The pre-processing steps applied are as follows:

Pre-processing step 1 : In the first pre-processing step, we analysed journal entries on two keys: ISSN and e-ISSN. In each of the journal lists, entries that had both these fields null were removed first. Thereafter, entries that had both ISSN and e-ISSN fields duplicated were removed. Thus, at the end of pre-processing step 1, we were left with 13,610 entries in Web of Science journal list (out of total 14,737 entries), 39,851 entries in Scopus journal list (out of total 40,385 entries), and 74,705 entries in Dimensions journal list (out of total 77,471 entries).

Pre-processing step 2 : In the second step, we analysed inconsistent entries where same ISSN or e-ISSN values occurred in different journal entries. Such entries (with repeated ISSN or e-ISSN values) were identified and removed. The Web of Science journal list had no such entry. In Scopus, 93 such duplicate occurrences were found and removed, leaving the remaining list to comprise of 39,758 entries. In Dimensions, 112 such entries were found and removed, and the remaining list comprised of 74,593 entries.

Pre-processing step 3 : In the third step, the entries in the journal lists have been checked to see if they contain any entry for a non-journal publication source. It was found that the Dimensions journal list included some entries for preprints and conference proceedings as well. Accordingly, the journal list entries were scanned to see occurrence of certain keywords, such as preprint, preprints, preprint-server, symposium, conference, congress etc. A total of 7 entries were found for preprint sources in Dimensions list and were removed. A total of 617 entries were found for conferences in Dimensions list and were removed. The resulting journal list of Dimensions database contained 73,966 journal entries.

Thus, the pre-processed journal list of Web of Science contained 13,610 journal entries; Scopus pre-processed list had 39,758 journal entries, and Dimensions pre-processed list contained 73,966 journal entries.

After the pre-processing steps, a systematic matching process was used to identify overlapping and unique journal records in different databases. We used a step-by-step matching process which used simple matching in the initial steps and a more restrictive matching strategy in later steps when the remaining journal lists became smaller. In the beginning, we did an ISSN/ e-ISSN based record matching and then later on used title-based and title text similarity-based matching. The matching steps along with the intermediate number of matching journal entries at each stage are illustrated below. The matching steps used criteria of exclusion through which records that yielded in match in one step were excluded from rest of the computations for matching.

Matching step 1 : The first matching step involved computing matches based on ISSN and e-ISSN fields. First the records were matched on ISSN and thereafter the remaining ones on e-ISSN. For doing this, the journal lists were partitioned in two sets- those having non-null ISSN value (hereafter referred to as ISSN set) and those with non-null e-ISSN values (hereafter referred to as e-ISSN set). The ISSN set comprised of 13,584 journal entries in Web of Science, 37,780 journal entries in Scopus, and 60,538 journal entries in Dimensions. The e-ISSN set comprised of 12,827 journal entries in Web of Science, 14,203 journal entries in Scopus, and 53,505 journal entries in Dimensions. Both these lists had common journal entries too. To avoid duplicate processing of matching, we removed from e-ISSN set all those records that were already included in the ISSN set. This way, the modified e-ISSN set comprised of 17 records in Web of Science, 1978 records in Scopus, and 13,428 records in Dimensions.

The subsequent matching on ISSN followed by e-ISSN is done as follows:

The entries in the ISSN sets are matched by their ISSN field across all database pairs. This resulted in 12,744 matching records in Web of Science and Scopus, 11,305 matching records in Web of Science and Dimensions, and 23,579 matching records in Scopus and Dimensions.

The next step involved matching journal entries in the modified e-ISSN sets of the three databases. Here the entries in the three sets are matched by their e-ISSN values. This resulted in 12 matching records in Web of Science and Scopus, 1084 matching records in Web of Science and Dimensions, and 8 matching records in Scopus and Dimensions.

In the next step, the remaining unmatched records in the ISSN sets after step (a) are matched to modified e-ISSN set with respect to the e-ISSN values. This results in 413 matching records in Web of Science and Scopus, 648 matches in Web of Science and Dimensions, and 43 matching records in Scopus and Dimensions.

The remaining ISSN sets are then compared to find any matches on e-ISSN. The ISSN of Web of Science and Scopus have 164 matching e-ISSNs, Web of Science and Dimensions have 763 matching e-ISSNs, and Scopus and Dimensions have 12,246 matching e-ISSNs.

Similarly, the modified e-ISSN sets are compared with remaining ISSN set. Web of Science and Scopus have 1 matching e-ISSNs, Web of Science and Dimensions have 3 matching e-ISSNs, and Scopus and Dimensions have 239 matching e-ISSNs.

In the last step we did cross matches for the remaining journal entries in both ISSN and e-ISSN sets taken together. The ISSN field in the entries was matched with e-ISSN and vice versa. This was done to address the manual observations that in some records the ISSN and e-ISSN numbers were interchanged in different database lists. This cross matching in the ISSN and e-ISSN sets resulted in 120 matching records in Web of Science and Scopus, 259 matching records in Web of Science and Dimensions, and 999 matching records in Scopus and Dimensions.

Matching Step 2 : After the matching of records based on ISSN and e-ISSN fields, we tried to match the remaining records on the journal title field. First an exact title match is done on title fields of records. Thereafter, an inexact match involving cosine similarity is done to process records that have the same journal, spelled or written differently in the three lists. Such cases included journals which are written with ‘&’ in one list and ‘and’ in the other list, as well as records where one database lists three parts (say part A, B, C) of a journal as a separate entry whereas the other has a single entry for all the three parts taken together. The matching was done as follows:

The remaining records (after first step of matching) in the Web of Science and Scopus databases are matched on the title field of record. First an exact match is done. This resulted in 42 matching records in Web of Science and Scopus. However, 12 records with title match have different publisher information in the two databases. Therefore, they were discarded and we were left with 30 matching records by title field. For Web of Science and Dimensions 180 records matched on title, from which only 144 records have same publisher. In case of Scopus and Dimensions we got 188 title matches out of which 120 records have same publisher.

In the second step of title matching, an inexact match was performed between title fields of the remaining records by computing cosine similarity between them. We considered cosine similarity of 0.9 or higher as an indication of match between two titles. This step resulted in 5 matching records in Web of Science and Scopus, with same publisher name. Therefore, only 5 matching records were considered. Web of Science and Dimensions have 19 records with same publishers out of 22 matches. Similarly, Scopus and Dimensions have 26 records with same publishers out of 56 matches.

The pre-processing and matching steps were executed as above to identify overlapping and unique journal entries across the three databases.

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Singh, V.K., Singh, P., Karmakar, M. et al. The journal coverage of Web of Science, Scopus and Dimensions: A comparative analysis. Scientometrics 126 , 5113–5142 (2021). https://doi.org/10.1007/s11192-021-03948-5

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Received : 26 September 2020

Accepted : 09 March 2021

Published : 26 March 2021

Issue Date : June 2021

DOI : https://doi.org/10.1007/s11192-021-03948-5

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Study drug discontinuation was defined as not refilling a medication after 30 days of the end of last treatment episode, which was calculated based on fill date and supply. The 1-month drop observed here is likely due to the allowed 30-day gap. DOAC indicates direct oral anticoagulant; LMWH, low-molecular-weight heparin.

DOAC indicates direct oral anticoagulant; LMWH, low-molecular-weight heparin.

eMethods. Detailed Methodology

eFigure 1. Patient Selection Flowchart

eFigure 2. Cumulative Incidence Curves for (A) Major Bleeding; (B) GI Bleeding; (C) Intracranial Bleeding

eFigure 3. Reconciliation of Study Characteristics and Results With Previous Clinical Evidence

eTable 1. VTE Risk Stratification According to CCS Cancer Categories

eTable 2.  ICD Codes for Major Bleeding and Different Sites of Bleeding

eTable 3. Additional Baseline Sociodemographic and Clinical Characteristics of Patients Included in the Study

eTable 4. Factors Without Significant Associations With Utilization of Anticoagulants in Cancer-Associated Thrombosis

eTable 5. Sociodemographic and Clinical Characteristics of Patients After Propensity Score Weighting

eTable 6. Factors Associated With Utilization of Anticoagulants in Sensitivity Cohort of Patients (Index Date: January 1, 2018, to September 30, 2019) With Cancer-Associated Thrombosis

eTable 7. Post Hoc Sensitivity Analysis for Gastrointestinal (GI) Bleeding in Patients Upper GI Malignant Neoplasm

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Riaz IB , Fuentes H , Deng Y, et al. Comparative Effectiveness of Anticoagulants in Patients With Cancer-Associated Thrombosis. JAMA Netw Open. 2023;6(7):e2325283. doi:10.1001/jamanetworkopen.2023.25283

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Comparative Effectiveness of Anticoagulants in Patients With Cancer-Associated Thrombosis

• 1 Department of Hematology and Oncology, Mayo Clinic, Phoenix, Arizona
• 2 Department of Hematology and Oncology, Mayo Clinic, Rochester, Minnesota
• 3 Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota
• 4 Division of Health Care Delivery Research, Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota
• 5 Gonda Vascular Center, Mayo Clinic, Rochester, Minnesota
• 6 Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota
• 7 Department of Cardiovascular Medicine, Mayo Clinic, Phoenix, Arizona

Question   What are the patterns of anticoagulant utilization and the anticoagulants associated with the lowest risk for venous thromboembolism (VTE) recurrence in patients with cancer in a clinical setting?

Findings   In this comparative effectiveness study with 5100 adult patients, twice as many patients were prescribed direct oral anticoagulants (DOACs) as other classes, and cancer type was associated with the choice of anticoagulant prescription. Use of DOACs was associated with a 50% risk reduction in VTE recurrence compared with low-molecular-weight heparin (LMWH) and warfarin and a 60% risk reduction in all-cause mortality compared with LMWH; DOACs were also associated with reduced risk of major bleeding and gastrointestinal tract bleeding compared with LMWH.

Meaning   In this study, DOACs were associated with a higher persistence rate, lower risk of VTE recurrence, lower risk of major bleeding, and improved mortality.

Importance   Patterns of clinical utilization and comparative effectiveness of anticoagulants for cancer-associated thrombosis (CAT) remain largely unexplored.

Objectives   To assess patterns of and factors associated with anticoagulant use and to evaluate the comparative effectiveness of contemporary anticoagulants in patients with active cancer in a clinical setting.

Design, Setting, and Participants   This retrospective cohort study obtained deidentified OptumLabs electronic health record claims data from January 1, 2012, to September 30, 2019. Adult patients (≥18 years of age) with a primary cancer diagnosis (except skin cancer) during at least 1 inpatient or 2 outpatient visits within 6 months before the venous thromboembolism (VTE) date were included. Data were analyzed from April 2020 to September 2021.

Exposures   The patients were grouped according to the anticoagulant prescribed: (1) direct oral anticoagulants (DOACs), (2) low-molecular-weight heparin (LMWH), and (3) warfarin.

Main Outcomes and Measures   Odds ratios (ORs) were used to present the association between factors of interest and utilization of anticoagulants. Main efficacy outcomes included risk of VTE recurrence and all-cause mortality. Main safety outcomes included the risk of hospitalization due to major bleeding. Relative treatment effect estimates were expressed as hazard ratios (HRs) with 95% CIs.

Results   This study included 5100 patients (mean [SD] age, 66.3 [12.3] years; 2670 [52.4%] women; 799 [15.7%] Black, 389 [7.6%] Hispanic, and 3559 [69.8%] White individuals). Overall, 2512 (49.3%), 1488 (29.2%), and 1460 (28.6%) filled prescriptions for DOACs, LMWH, and warfarin, respectively. The median (IQR) treatment duration was 3.2 (1.0-6.5) months for DOACs, 3.1 (1.0-6.8) months for warfarin, and 1.8 (0.9-3.8) months for LWMH. Patients with lung (OR, 2.07; 95% CI, 1.12-3.65), urological (OR, 1.94; 95% CI,1.08-3.49), gynecological (OR, 4.25; 95% CI, 2.31-7.82), and colorectal (OR, 2.26; 95% CI, 1.20-4.32) cancer were associated with increased prescriptions for LMWH compared with DOACs. LMWH (HR, 1.47; 95% CI, 1.14-1.90) and warfarin (HR, 1.46; 95% CI, 1.13-1.87) were associated with an increased risk of VTE recurrences compared with DOACs. LMWH was associated with an increased risk of major bleeding (HR, 2.27; 95% CI, 1.62-3.20) and higher all-cause mortality (HR, 1.61; 95% CI, 1.15-2.25) compared with DOACs.

Conclusions and Relevance   In this comparative effectiveness study of claims-based data, patients with CAT received anticoagulation for a remarkably short duration in clinical settings. DOACs was associated with a lower risk of VTE recurrence, major bleeding, and mortality. Warfarin may still be considered for patients with contraindications to DOACs and those with poor persistence on LMWH.

Management of cancer-associated thrombosis (CAT) is complicated owing to several variables, including cancer-specific thrombotic and bleeding risk, cancer treatment–associated complications, frequent invasive procedures, and constitutional adverse effects such as nausea, vomiting, and anorexia, which may impact medication absorption and adherence. These add to the risk of venous thromboembolism (VTE) recurrence and major bleeding, which both carry high case fatality rates. Treating patients with cancer-associated VTE is therefore challenging due to the delicate balance between these extremes. 1

For nearly 20 years, guideline recommendations for patients with cancer-associated VTE was low-molecular-weight heparin (LMWH) 2 - 6 based on the results of the CLOT trial. 7 Trials of other LMWH preparations, however, were not able to duplicate these results. 8 - 11 More recently, 4 randomized clinical trials (RCTs) have found that direct oral anticoagulants (DOACs) offer a reasonable alternative to parenteral dalteparin for the acute treatment of cancer-associated VTE with acceptable efficacy and safety outcomes. 12 - 15 As such, DOACs have received guideline endorsement for treating acute VTE in this setting. 16 , 17 Despite these findings and guideline statements, warfarin has remained a common treatment strategy for community-based oncology practices for various reasons, including cost and patient preference for oral over parenteral medications. 18 , 19 The comparative utilization of these 3 classes of anticoagulant in clinical oncology practices has not been thoroughly explored.

DOACs decrease VTE recurrence and major bleeding as compared with LMWH in clinical trial settings. 13 Whether DOACs are more effective and safer than LMWH and how they compare with warfarin in a clinical oncology context is not established. Thus, we used claims-based data from OptumLabs to assess the utilization patterns and the comparative efficacy and safety of these available anticoagulant classes.

This comparative effectiveness study was reported in accordance with the Professional Society for Health Economics and Outcomes Research ( ISPOR ) reporting guideline for comparative effectiveness research. 20 Deidentified administrative claims data from OptumLabs Data Warehouse (OLDW) 21 were queried to identify patients with active cancer and acute VTE from January 1, 2012, to September 30, 2019. The Mayo Clinic institutional review board exempted this study from review and the requirement for informed consent due to the analysis of preexisting, deidentified data.

Adult patients (≥18 years of age) with a primary cancer diagnosis (except skin cancer) with at least 1 inpatient or 2 outpatient visits within 6 months before the VTE date were included. Patients with hematological malignant neoplasms and solid tumors, including those with lung, urologic or genitourinary [GU], breast, colorectal, gynecological, pancreaticobiliary, upper gastrointestinal [GI], brain, head and neck, and musculoskeletal cancers, were included. Incident VTE was identified using International Classification Disease ( ICD ) billing codes between January 1, 2012, and September 30, 2019 (eFigure 1 in Supplement 1 ). The first diagnosis date of VTE was defined as the date of incident diagnosis. The study cohort was limited to patients who filled an anticoagulant prescription within 30 days after the VTE date. Patients were then categorized into 1 of 3 groups ([1] DOAC, [2] LMWH, or [3] warfarin) based on the initial prescription filled. The first fill date of a specific anticoagulant was defined as the index therapy and treatment date. Study drug discontinuation was defined as not refilling a medication after 30 days of the end of last treatment episode, which is calculated based on fill date and supply.

Patients who crossed over to a different anticoagulant within the first year were excluded from the analysis. Patients were also excluded from the analysis for any of the following reasons: (1) crossed over to a different anticoagulant within the first year; (2) prior history of VTE; (3) filled prescription for an oral anticoagulant (warfarin and DOAC) less than 1 year prior to the VTE index date; or (4) less than 1 year of continuous insurance coverage prior to the VTE index date. Eligible individuals with missing data were removed and were not included in statistical analyses. Detailed inclusion and exclusion criteria are outlined in the eMethods in Supplement 1 .

Follow-up originated at the VTE index date and continued until the end of treatment. This was defined as (1) date of index anticoagulant discontinuation; (2) end of enrollment in health insurance plan; (3) 1 year after VTE index date; (4) end of the study period (September 30, 2019); or (5) date of patient death.

The main efficacy end points included any VTE recurrence and all-cause mortality. The main safety end points included any episode of major bleeding and sites of bleeding (GI, GU, intracranial bleeding) (eTable 2 in Supplement 1 ). 22

Analyses were performed between April 2020 and September 2021. Baseline characteristics (including but not limited to cancer type, presence of metastatic disease, baseline intervention [chemotherapy and surgery], baseline comorbidities, and Charlson Comorbidity Index) of the treatment cohorts were reported. Multinomial logistic regression was used to assess factors associated with use of DOAC relative to other anticoagulants (LMWH and warfarin) and presented as odds ratios (ORs) and 95% CIs. Kaplan-Meier curves were plotted to assess the differences in time to medication discontinuation among the 3 groups.

Propensity score (PS) with inverse probability of treatment weighting was used to balance differences in baseline characteristics among the 3 treatment groups. 23 All baseline characteristics listed were included in the PS models to derive the PS and the average treatment effect weights ( Table 1 ; eTable 3 in Supplement 1 ). The standardized mean difference was used to assess the balance of covariates, and a standardized mean difference less than 0.1 was considered acceptable.

Weighted Cox proportional hazards regression with a robust variance estimator was used to assess outcomes. The event rates per 100 person-years and hazard ratios (HRs) were calculated, and the cumulative incidence curves were plotted. P  < .05 was considered statistically significant for all 2-sided tests. Sensitivity analyses were also conducted on the cohort with index dates between January 1, 2018, and September 30, 2019, to account for selection bias in the use of different anticoagulant medications.

All analyses were conducted using SAS 9.4 (SAS Institute Inc), R version 4.0.2 (R Foundation for Statistical Computing), and Stata version 14.1 (StataCorp). Detailed methods are available in eMethods in Supplement 1 .

A total of 5100 patients were included (mean [SD] age, 66.3 [12.3] years; 2670 [52.4%] women) as shown in Table 1 . Most of the population was represented by White individuals (3559 [69.8%]), with 799 (15.7%) Black and 389 (7.6%) Hispanic participants, from the Southern United States (2218 [43.5%]). Among the different cancer types, the 5 most prevalent were lung (913 [17.9%]), urological (830 [16.3%]), breast (699 [13.7%]), colorectal (580 [11.4%]), and hematologic (536 [10.5%]) cancer. Just over 60% of patients had metastatic disease (3063 [60.1%]) at the time of incident VTE, and 2787 (54.6%) received chemotherapy within the antecedent 6 months. More than one-third of patients (1972 [38.7%]) had also undergone cancer-related surgery within this time interval.

Of the total population, 2512 patients (49.3%) were administered DOACs; 1488 (29.2%), LMWH; and 1460 (28.6%), warfarin. VTE was nearly equally divided into deep vein thrombosis (DVT) (2405 [47.2%]) and pulmonary embolism (PE) (2254 [44.2%]) while 441 (8.6%) had evidence of both DVT and PE at the time of diagnosis. Most cases were diagnosed during hospitalization (3365 [65.8%]) or in the emergency department (ED) (1357 [26.6%]) while a paucity was found during a clinic visit (387 [7.6%]). Additional details of baseline characteristics are provided in eTable 3 in Supplement 1 .

By multinomial regression analysis, younger patients were more likely to be prescribed LMWH (OR per 1-year, 0.97; 95% CI, 0.97-0.98; P  < .001) ( Table 2 ). Both LMWH and warfarin were more likely to be prescribed for patients with lung, urological, gynecological, and colorectal cancer. LMWH was more likely to be prescribed for patients with musculoskeletal and brain cancer, while warfarin was more likely to be prescribed in patients with breast cancer compared with DOACs.

Warfarin was more likely to be prescribed for patients with DVT alone (OR, 1.31; 95% CI, 1.12-1.52; P  < .001). In contrast, for patients with either combined DVT plus PE or isolated PE, prescribing patterns were similar for LMWH (OR, 1.22; 95% CI, 0.94-1.58; P  = .13) and warfarin (OR, 1.06; 95% CI, 0.82-1.37; P  = .66) compared with DOACs.

Patients were more likely to be given DOACs relative to LMWH when treated in the ED (OR, 1.59; 95% CI, 1.33-1.89; P  < .001) or as an outpatient in the clinics (OR, 1.49; 95% CI, 1.11-2.00; P  = .01) compared with in-hospital setting. Likewise, DOACs, when compared with warfarin, were more frequently prescribed from either the ED (OR, 2.56; 95% CI, 2.17-3.13; P  < .001) or outpatient office setting (OR, 1.67; 95% CI, 1.28-2.22; P  < .001) relative to an in-hospital stay. If patients had a prior history of cardiac arrhythmia as a baseline comorbid condition, they were more likely to be prescribed DOACs compared with warfarin (OR, 1.28; 95% CI, 1.09-1.52; P  = .005). No statistically significant differences were observed among patients with other baseline comorbidities in terms of being prescribed a medication. The detailed results of multinominal regression are outlined in Table 2 and eTable 4 in Supplement 1 . The results of sensitivity analyses were consistent and are provided in eTable 6 in Supplement 1 .

The median (IQR) treatment duration was 3.2 (1.0-6.5) months for DOACs, 3.1 (1.0-6.8) months for warfarin, and 1.8 (0.9-3.8) months for LWMH ( P  < .001). ( Figure 1 ). At 6 months, a greater percentage of patients continued taking either a DOAC (620 of 2152 [28.8%]) or warfarin (439 of 1460 [30.0%]) compared with LMWH (208 of 1488 [13.9%]).

The results for comparative effectiveness in the weighted cohort are highlighted in Table 3 . The 3 groups were balanced after propensity score weighting with SMDs less than 0.1 in all covariates (eTable 5 in Supplement 1 ). In the weighted cohort, patients receiving LMWH or warfarin were associated with an increased risk of VTE recurrence compared with those prescribed DOACs (LMWH: 39.76 per 100 person-years; warfarin: 29.89 per 100 person-years; DOACs: 20.62 per 100 person-years; LMWH vs DOAC: HR, 1.47; 95% CI, 1.14-1.90; warfarin vs DOAC: HR, 1.46; 95% CI, 1.13-1.87), as shown in Figure 2 A. Patients receiving LMWH were associated with an increased risk of all-cause mortality compared with those prescribed DOACs (LMWH: 21.18 per 100 person-years; DOACs: 11.36 per 100 person-years; LMWH vs DOACs: HR, 1.61; 95% CI, 1.15-2.25). In contrast, mortality rates with warfarin did not differ significantly from DOACs (HR, 1.19; 95% CI, 0.85-1.68), as shown in Figure 2 B.

Patients receiving LMWH were associated with an increased risk of hospitalizations for major bleeding compared with those prescribed DOACs (LMWH: 26.73 per 100 person-years; DOACs: 9.88 per 100 person-years; LMWH vs DOAC: HR, 2.27; 95% CI, 1.62-3.20) as shown in eFigure 2A in Supplement 1 . Many of these events were accounted for by GI bleeding with LMWH compared with DOACs (LMWH: 14.64 per 100 person-years; DOACs: 7.17 per 100 person years; LMWH vs DOAC: HR, 1.72; 95% CI, 1.12-2.62) as shown in eFigure 2B in Supplement 1 . The total number of major GU bleeding events was low (<20), which precluded formal statistical testing. Patients receiving LMWH were associated with an increased risk of intracranial bleeding compared with those prescribed DOACs (LMWH: 5.88 per 100 person-years; DOACs: 1.84 per 100 person-years; LMWH vs DOAC: HR, 2.72; 95% CI, 1.24-5.97) as shown in eFigure 2C in Supplement 1 . The risks of hospitalization for major bleeding, GI bleeding, and intracranial bleeding in patients receiving warfarin (major bleeding: 11.10 per 100 person-years; GI bleeding: 7.38 per 100 person-years; intracranial bleeding: 1.93 per 100 person-years) were similar to DOACs (major bleeding: HR, 1.12; 95% CI, 0.78-1.61; GI bleeding: HR, 1.03; 95% CI, 0.67-1.59; intracranial bleeding: HR, 1.04; 95% CI, 0.45-2.45).

Sample size in the sensitivity cohort (with index date January 1, 2018, to September 30, 2019) was small and precluded any meaningful statistics. Additionally, post hoc sensitivity analysis for GI bleeding in upper GI malignant neoplasms showed no significant differences among anticoagulants (eTable 7 in Supplement 1 ).

A literature search was conducted to identify similar studies and to reconcile the findings of our study with the results of those studies. Findings are shown in eFigure 3 in Supplement 1 .

Consistent with the general theme of recent RCTs, results from this claims-based cohort of more than 5000 patients include a general preference for DOAC therapy use, with nearly twice as many patients receiving this class of medication compared with other classes. Furthermore, these data reinforce the general efficacy and safety of DOACs in this patient population; they were associated with a nearly 50% reduction in VTE recurrence rates and a more than 2-fold reduction in hospitalization for major bleeding compared with LMWH therapy. The odds of GI and intracranial bleeding were likewise reduced among patients receiving DOACs. Not seen in clinical trials, these data showed an association between DOAC therapy and a significant 60% reduction in all-cause mortality rates relative to LMWH. As such, it is anticipated that these data will help facilitate shared decision-making and inform clinical guidelines for the treatment of such patients.

DOACs have emerged as the most prescribed anticoagulant choice for management of cancer-associated VTE. 24 Half of patients in this cohort were treated with a DOAC and less than one-third received LMWH (29.1%) despite contemporary guideline recommendations. 2 , 5 , 6 The timeframe of this study (2012-2019) antedated guideline changes endorsing DOAC use in this context. 2 , 3 However, DOAC popularity might be attributed to pharmacologic benefits including rapid onset of action, convenient oral administration and dosing, short half-life, lack of monitoring, few drug or food interactions, and good bioavailability. 25 , 26 Compared with LMWH, patient preference for oral apixaban, for example, resulted in fewer discontinuations in a recent RCT of cancer-associated acute VTE treatment. 13 By comparison, warfarin was the least frequently prescribed anticoagulant in this cohort (28.6%). While some studies have shown a decreasing use of warfarin, others have not. In some community oncology practices, nearly half of patients with cancer and acute VTE are still treated with warfarin. 18 , 19 , 24 Guideline recommendations preferring LMWH, specifically dalteparin, over warfarin are based on a single trial. 7 Trials of other LMWH preparations have not shown an advantage over warfarin. 8 - 11 Warfarin was associated with improved overall survival compared with LMWH in a recent study assessing 9706 propensity score–matched patients with cancer and VTE. 27 Despite a clear benefit for DOACs over LMWH in the current study, neither major bleeding nor survival outcomes favored DOACs over warfarin; VTE recurrence rates were lower with DOACs.

This study revealed low persistence rates of patients with cancer receiving anticoagulant therapy, with a minority continuing treatment beyond 3 months, similar to findings in another analysis of Medicare data. 27 Conversely, Guo et al 28 observed that 87.8% of patients continued to receive DOAC therapy at 3 months. Papakotoulas et al 29 observed that, on average, patients continued DOAC therapy for 6.8 months. Cohen et al 30 reported persistence rates at 6 months of 60.6% for DOACs, 38.9% for LMWH, and 51.0% for warfarin. However, lack of crossover between the medications (except for 30-day bridging period of LMWH for warfarin, dabigatran, and edoxaban) could plausibly explain the shorter follow-up period for LMWH in our study. Moreover, different data sources and choice of anticoagulant agents may explain higher adherence rates observed in these studies.

Reasons for treatment discontinuation are complex. It may occur due to tumor-related bleeding complications, GI issues, drug interactions, contraindications due to comorbidities, financial barriers, and concerns about the lack of proven survival benefits. 31 - 33 These factors contribute to a reduced likelihood of treatment continuation in this patient population.

Anticoagulant utilization patterns appear to vary by regional, sociodemographic, and clinical factors. Younger patients were more likely to receive LMWH. Similarly, for patients being evaluated in the office or ED, DOACs were more frequently prescribed. By comparison, if the clinical interaction was in a hospital setting, DOACs were less likely to be prescribed. These findings are consistent with those of Guo et al, 28 who found that DOACs were preferred in 40% of outpatients discharged from the hospital, while LMWH was preferred in the inpatient setting. Similarly, DOACs were more frequently prescribed to patients from the South compared with the Midwest, while LMWH use was greater in the Northeast. While we observed no statistically significant differences in prescription patterns by different racial categories, other studies have suggested relatively lower use of DOACs for incident VTE in Black patients, which highlights potential inequity in access to this novel pharmacotherapy. 34 - 36 The reasons for these different prescribing patterns are not clear, and further exploration of factors associated with anticoagulant choice is required to better understand these differences.

Prescribing patterns also appear to vary by cancer type. DOACs were less likely to be prescribed in patients with lung, urological, colorectal, and breast cancer in our study. Contrasting results were reported with DOACs more likely to be prescribed in patients with prostate and breast cancer. 18 Varying patient-physician preferences may be responsible for the inconsistency observed between the results, as currently we are lacking evidence to facilitate anticoagulant choice in different cancers. Similarly, in our study, DOACs were more likely to be preferred in patients with concomitant cardiac arrhythmias compared with warfarin, similar to another study. 18 These preferences are most likely derived from the results of multiple cardiovascular clinical trials that showed superiority of DOACs over warfarin. 37 - 39 Whether these preferences translate into actual benefit in patients with arrhythmia and cancer is still unknown.

VTE recurrence rates favored DOAC therapy over other anticoagulant choices. DOACs were associated with a 32% risk reduction in VTE recurrence compared with LMWH, consistent with RCTs comparing DOACs with LMWH. 13 - 15 Cohen et al 30 found a similar 39% reduction in VTE risk with apixaban compared with LMWH. An important distinction between RCTs and clinical practice is the nearly universal employment of enoxaparin as opposed to dalteparin, which may impact outcomes. Additionally, DOAC trials recruited a low proportion of patients with primary brain tumors and known intracerebral metastases. VTE recurrence rates were also significantly higher for patients receiving warfarin compared with DOACs. While data from RCTs are limited, these findings complement the results of several network meta-analyses that have reported efficacy benefit with DOACs compared with warfarin. 40 , 41 Several unanswered questions regarding anticoagulant choice include VTE risk by tumor type, VTE presentation (symptomatic or incidental), and various patient and clinical characteristics. 42 , 43

Similarly, patients with cancer receiving anticoagulant therapy are at an increased risk of bleeding, which further hinders anticoagulation delivery and complicates anticoagulant choices. Contrary to guidelines and RCTs (SELECT-D, HOKUSAI-VTE, and CARAVAGGIO), this study found lower rates of major bleeding and GI bleeding with DOACs compared with LMWH in patients with cancer. 12 , 14 , 15 Variable study design, randomization, patient selection, and a relatively higher proportion of patients with upper GI malignant neoplasms included in the trials as opposed to our study could explain the differences. Cohen et al 30 found a 37% risk reduction in major bleeding with apixaban compared with LMWH but observed no difference for GI bleeding. Furthermore, lower rates of intracranial bleeding likewise favored DOAC use, similar to the results of Cohen et al. 30 Contrarily, several meta-analyses have suggested increased risk of major bleeding with DOACs compared with LMWH; however, these results are based on limited data and have wide confidence intervals. 40 , 41 , 44 , 45

Recurrent VTE also presents with an increased risk of mortality, especially in patients with prior history of PE. No anticoagulants to date have been able to achieve overall survival benefit. 7 - 15 , 44 , 45 However, contrary to RCTs, which included near-equal proportion of patients with metastatic disease as our study, we observed lower all-cause mortality with DOACs and an increased risk with LMWH compared with DOACs. These findings indicate that most of these RCTs might have been underpowered to detect such differences. Consistently, another study showed a significant reduction in mortality with rivaroxaban when compared with enoxaparin. 46 Taken together, these findings reassure and reinforce prior evidence in terms of VTE risk reduction and may be suggestive of lower risk of mortality with DOACs.

The current study has several strengths. We relied on claims data from OLDW, which contain longitudinal health information on enrollees and patients, representing a diverse mixture of ages, races and ethnicities, and geographical regions across the US; conducted multinominal regression analysis to assess factors associated with treatment patterns of utilization; applied propensity score matching for adjustment of differences across baseline sociodemographic and clinical characteristics; assessed comparative effectiveness of DOACs, LMWH, and warfarin using weighted Cox proportional hazard models; and reconciled our design and findings with previous clinical studies to compare differences and consistency between results (eFigure 3 in Supplement 1 ).

This study has limitations, including information bias (billing inaccuracies and data omissions), the use of ICD codes to identify patients with VTE, and the lack of radiological evidence of VTE in the database, which can potentially lead to classification bias for assessment of VTE. The analyses were conducted using US claim-based data so the results could not be extrapolated to other populations. We lacked information on uninsured patients or patients receiving insurance from other federal- or state-regulated insurances; hence, the results may not be representative of such populations. Only observable uncontrolled covariates were accounted for in adjusted multivariate analyses; hence, there is a risk of residual confounding bias. Likewise, this analysis predates the pivotal RCTs; therefore, selection bias in the use of different drugs is likely. The proportion of patients still receiving treatment was used to reflect patient adherence to different medications and assumed that medications supplied were being used, which may not be reflective of true patient adherence. Clinically relevant nonmajor bleeding, which has competing risks among different anticoagulant treatments, was not assessed and may alter the choice of anticoagulant therapy. We assessed all-cause mortality and not VTE or bleeding-specific mortality, which might be more informative to guide the choice of anticoagulant therapy in patients with CAT. We used propensity score matching to address differences in baseline characteristics among the 3 treatment groups. However, it is important to note that there may be additional confounding variables that were not accounted for in outcome assessment. Therefore, careful consideration is warranted when interpreting the results of this study.

In this study, patients with cancer-associated VTE received anticoagulation therapy for a short duration in clinical practice. The findings suggest that DOACs and warfarin may offer better treatment persistence than LMWH in clinical practice. Warfarin may still be considered for patients with contraindications to DOACs and for those who have poor persistence on LMWH.

Accepted for Publication: June 12, 2023.

Published: July 24, 2023. doi:10.1001/jamanetworkopen.2023.25283

Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2023 Riaz IB et al. JAMA Network Open .

Corresponding Author: Irbaz Bin Riaz, MD, PhD, Department of Hematology and Oncology, Mayo Clinic, 5881 E Mayo Blvd, Phoenix, AZ 85054 ( [email protected] ).

Author Contributions: Drs Riaz and Fuentes had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Drs Riaz and Fuentes have equally contributed as first authors.

Concept and design: Riaz, Fuentes, Yao, Sangaralingham, Shamoun, Wysokinski, McBane.

Acquisition, analysis, or interpretation of data: Fuentes, Deng, Naqvi, Yao, Sangaralingham, Houghton, Padrnos, McBane.

Drafting of the manuscript: Riaz, Fuentes, Naqvi, McBane.

Critical revision of the manuscript for important intellectual content: Fuentes, Deng, Naqvi, Yao, Sangaralingham, Houghton, Padrnos, Shamoun, Wysokinski, McBane.

Statistical analysis: Deng, Naqvi, Yao, Sangaralingham.

Obtained funding: McBane.

Administrative, technical, or material support: Sangaralingham, Padrnos, Wysokinski.

Supervision: Houghton, Shamoun, McBane.

Conflict of Interest Disclosures: None reported.

Data Sharing Statement: See Supplement 2 .

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What is Comparative Analysis?

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Comparative Analysis Essay Writing Guide

This kind of academic assignment is quite widespread in colleges or universities. It aims to show students how to review different types of materials, divide them into separate parts, and analyze each element in turn. Every comparative analysis essay requires in-depth research on the subject, the author's ability for critical thinking, and support for the position indicated in the material analyzed. Preparing the academic paperwork, you should make it fascinating and intelligent for your readers. Any comparative analysis paper may be a complicated task, but if you follow all the steps mentioned in our guidelines, the writing process will become much easier!

What Is a Comparative Analysis Paper?

In order to know what you can expect from the task, fully understanding the comparative analysis concept is vital. A comparative analysis is one of the most popular types of assignments that are often given in colleges or universities. In such paperwork for college or university, you should compare and oppose two different things. Those can be two texts, historical figures, scientific processes, theories, etc. These papers are very popular as college assignments because they are pretty universal: no matter what subject you study or what field you are working in - there are always things that can be compared. A "classic" version of a comparative analysis essay is when you select two similar things with a few critical differences. Or, it can be vice versa: two entirely different things have some similarities which may not even be noticed. Comparative analysis essays help students gain useful expertise, develop analytical thinking, improve their writing skills, the ability to highlight essential information, and, in the end, compare things and support your opinion with relevant facts and actual examples.

Every student should have some skills to write a quality comparative analysis paper. It's challenging and requires a lot of additional elaboration of the materials, but the result you get in the end is worth it. With the help of the comparative analysis approach, you can see how different some similar things might be and vice versa. It takes much time and a lot of effort to prepare an excellent academic assignment, but following the guide below will assist you in achieving the best results!

How To Do a Comparative Analysis

As we mentioned earlier, the comparative analysis paper is a bit tricky when discussing its primary concept. If you have to convince your audience, you should find real similarities and differences based on a specific comparison type. Here comes the challenge - you should analyze both principles you compare. In order to highlight those main commonalities and differences, your task is to learn the subject. Therefore, our advice for everyone who faces creating a comparative analysis paper is to study, explore and read a lot. The best thing is to expand the expertise in the chosen topic. It will serve you to prepare the assignment without any difficulties because everything you need to do after the analysis follows the basic structure guideline and sums up everything you've found on your topic. Those who do everything haphazardly, without any preparation whatsoever, might face problems during the actual writing. Let's take a closer look at some structural aspects of such essays.

The Structure Outlines

Apart from general standard parts like an introduction, primary part, results, discussion and conclusions, which you should include in your paperwork, some other structural characteristics are specific for a comparative analysis assignment.

You can choose among the two ways to build the textual structure:

• Point-by-point method. Choosing this type, you need to compare two subjects (let's name them A and B) using the ABABAB structure. Thus, after selecting the criteria for comparing these two concepts, you first discuss this criterion regarding subject A and then use the same approach for subject B. For example, if comparing the World War I and World War II, the essay's body structure might look like this:
• A Paragraph 1 - military strategies used in World War I
• B Paragraph 2 - military strategies used in World War II
• A Paragraph 3 - weapons and new technologies in World War I
• B Paragraph 4 - weapons and new technologies in World War II
• A Paragraph 5 - scale and duration of World War I
• B Paragraph 6 - scale and duration of World War II
• Block method: Subject-by-subject pattern. Here, you should discuss all aspects of subject A and then move to subject B. This method has the following structure of the body part:
• A Paragraphs 1-3 - The discussion of particular aspects of World War I
• B Paragraphs 4-6 - Discussing the same categories but reviewing the World War II events

In addition to those methods, we recommend building a comparative analysis assignment outline as we did with the essay's body. Outlining the whole paperwork will assist you in organizing your views and opinions and planning out the paper's structure beforehand. Write down all paragraph headings, the key questions you have decided to review and provide all necessary details you want to mention in the academic task.

Good Examples for Comparative Analysis Paper Topics

Everything begins with a subject, so it's one of the most critical aspects of a comparative analysis assignment. Do not be hasty when considering different topics and choose the best one that will be fascinating for your audience. Let's look at some examples:

• Fascism and Nazism: Different or the Same?
• World War I and World War II: The Difference in Events
• Coffee and Tea: The Effects of Both
• Working in the Office or Being a Freelancer?
• Education or Professional Career: What Is Easier and What Is More Difficult?
• Online Dating vs. Real-Life Relations
• Anorexia Nervosa and Obesity: What Is More Dangerous?
• Life and Death: Philosophical Views

Choose a good topic, follow the guideline and try to enjoy the writing process as much as you wish! Great results won't keep you waiting if you like what you're doing. We hope that our guidelines will come in handy to build top-notch paper!

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Main Article Content

Comparative analysis of abrasive wear between aluminium alloy and mild steel in a pin-on-disc tribological test, b.n.g. aliemeke, a.e. akhigbe, h.a. okwudibe.

A comparative analysis of the abrasive wear of aluminium alloy and mild steel on the pin-on-disc wear test machine has been  successfully  carried out. An investigation on the effects of wear, stress and strain on the aluminium alloy and the mild steel was  conducted. The wear test carried out determined the difference between rate of wear of the aluminium alloy and the mild steel. The input parameters applied in determining the wear rate were time of wear, sliding distance, track diameter of the disc and mass difference  before and after the experiment. The finite element analysis developed the stress and elastic strain distribution obtained on the  application of 2 kg load (20 N) on the aluminium alloy and mild steel specimen. The equivalent (Von Mises) stress distribution in mild steel  had a maximum stress value of 0.023625 Mpa and minimum stress of 1.444×10 -5 Mpa while that of the aluminium alloy yielded a  maximum and minimum stress of 0.0365 Mpa and 8.5×10 -5 Mpa respectively. It was evident that the aluminium alloy recorded a higher  magnitude of stress than the mild steel. This showed that the aluminium alloy being relatively light was more stressed than the mild  steel. It was discovered that the rate of wear was higher in the aluminium alloy than in the mild steel.  

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