\documentclass[10pt]{article}

\usepackage{fullpage}
\usepackage{setspace}
\usepackage{parskip}
\usepackage{titlesec}
\usepackage[section]{placeins}
\usepackage{xcolor}
\usepackage{breakcites}
\usepackage{lineno}
\usepackage{hyphenat}





\PassOptionsToPackage{hyphens}{url}
\usepackage[colorlinks = true,
            linkcolor = blue,
            urlcolor  = blue,
            citecolor = blue,
            anchorcolor = blue]{hyperref}
\usepackage{etoolbox}
\makeatletter
\patchcmd\@combinedblfloats{\box\@outputbox}{\unvbox\@outputbox}{}{%
  \errmessage{\noexpand\@combinedblfloats could not be patched}%
}%
\makeatother


\usepackage{natbib}




\renewenvironment{abstract}
  {{\bfseries\noindent{\abstractname}\par\nobreak}\footnotesize}
  {\bigskip}

\titlespacing{\section}{0pt}{*3}{*1}
\titlespacing{\subsection}{0pt}{*2}{*0.5}
\titlespacing{\subsubsection}{0pt}{*1.5}{0pt}


\usepackage{authblk}


\usepackage{graphicx}
\usepackage[space]{grffile}
\usepackage{latexsym}
\usepackage{textcomp}
\usepackage{longtable}
\usepackage{tabulary}
\usepackage{booktabs,array,multirow}
\usepackage{amsfonts,amsmath,amssymb}
\providecommand\citet{\cite}
\providecommand\citep{\cite}
\providecommand\citealt{\cite}
% You can conditionalize code for latexml or normal latex using this.
\newif\iflatexml\latexmlfalse
\providecommand{\tightlist}{\setlength{\itemsep}{0pt}\setlength{\parskip}{0pt}}%

\AtBeginDocument{\DeclareGraphicsExtensions{.pdf,.PDF,.eps,.EPS,.png,.PNG,.tif,.TIF,.jpg,.JPG,.jpeg,.JPEG}}

\usepackage[utf8]{inputenc}
\usepackage[english]{babel}



\usepackage{float}








\begin{document}

\title{Exploring financial relationships between board-certified cardiologists
and pharmaceutical industry in Japan between 2016 and 2019}



\author[1]{Anju Murayama}%
\author[1]{Kenichi Higuchi}%
\author[1]{Yuki Senoo}%
\affil[1]{Affiliation not available}%


\vspace{-1em}



  
  \date{June 18, 2024}


\begingroup
\let\center\flushleft
\let\endcenter\endflushleft
\maketitle
\endgroup








\sloppy


Anju Murayama\textsuperscript{1,2*}; Kenichi Higuchi\textsuperscript{1};
Yuki Senoo, MD, MUDr\textsuperscript{3}

\textbf{Affiliations:}

\textsuperscript{1} School of Medicine, Tohoku University, Sendai City,
Miyagi, Japan

\textsuperscript{2} Department of Population Health Science and Policy,
Icahn School of Medicine at Mount Sinai, New York City, NY, USA

\textsuperscript{3} Department of Internal Medicine, Higashitotsuka
Memorial Hospital, Yokohama, Kanagawa, Japan

*Corresponding author

\textbf{Correspondence}

Anju Murayama

School of Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba ward,
Sendai City, Miyagi, 980-0872, Japan

Telephone: 81-22-717-8006

Email address:\emph{anju.murayama.s8@dc.tohoku.ac.jp}

\textbf{Introduction}

Collaborations between physicians and pharmaceutical companies play a
crucial role in advancing healthcare innovation and improving patient
care through joint research efforts. However, such collaborations can
also lead to financial conflicts of interest (COIs) for physicians.
Furthermore, physicians may engage in promotional activities or be
targeted for marketing by the companies,\textsuperscript{1-3}potentially
biasing their decision-making, including prescribing patterns and
guideline recommendations.\textsuperscript{4-9} These COIs could bias
physicians' decision-making including prescribing patterns and guideline
recommendations.

To improve transparency in these financial relationships, the Japan
Pharmaceutical Manufacturers Association (JPMA), the largest
pharmaceutical trade organization in Japan, implemented a policy in 2013
requiring its member companies to disclose payments to physicians on
their websites. This data is then collected by an independent research
organization and journalists and has been voluntarily available on a
comprehensive searchable database since
2016.\textsuperscript{10}Previous research using this database has
revealed prevalent financial relationships between physicians and
pharmaceutical companies in Japan.\textsuperscript{11-17}

Among several specialists, cardiologists are among the most heavily
targeted specialists for marketing by pharmaceutical companies. Murayama
et al. previously reported that society executive board members of the
Japanese Circulation Society received the second highest mean payments
of \$311,653, with the fourth highest median payments of \$207,888 in
personal payments for lecturing, consulting, and writing among 15
internal medicine subspecialty societies in
Japan.\textsuperscript{12}Another study found that authors of the
Japanese Society of Hypertension clinical guidelines received a mean of
\$21,447 in personal payments in 2016.\textsuperscript{18} Additionally,
Tringale et al. reported that cardiologists received the highest median
payments of \$862 from healthcare companies of 26 specialties in the
United States (US).\textsuperscript{2} Similarly, Murayama et al.
reported that cardiologists received \$725 in personal payments in the
US in 2019.\textsuperscript{1} Despite the likely presence of prevalent
and substantial financial relationships between cardiologists and
pharmaceutical companies in Japan, no studies have been conducted to
evaluate the whole size and extent of financial relationships between
cardiologists and pharmaceutical companies. Utilizing a publicly
accessible database, this study investigated the extent and trends of
personal payments from pharmaceutical companies to all cardiologists in
Japan.

\textbf{Methods}

Utilizing the publicly available payment
database,\textsuperscript{10}this analysis examined all personal
payments to cardiologists from JPMA-affiliated pharmaceutical companies
from 2016 to 2019. We included all cardiologists board-certified by the
Japanese Circulation Society (JCS) as of September 2021. The JCS,
established in 1935, is the sole professional body board-certifying
cardiologists since 1989. As of the specified date, we identified 15,048
board-certified cardiologists from the JCS webpage. The JPMA only
requires its member companies to disclose personal payments to
individual physicians for lecturing, consulting, and writing services at
individual physician level. More common payment categories such as
meals, travel, accommodations, and other gifts are reported in
aggregate, precluding individual-level
analysis.\textsuperscript{19}Therefore, we searched for the names of
cardiologists and collected from the payment database only payments to
cardiologists for lectures, consulting, and writing for this study. As
payments in 2019 were the latest analyzable data at the time of data
collection, we collected payments from 2016 to 2019.

We conducted descriptive analyses including mean and median payments per
cardiologist and the proportion of cardiologists receiving payments. The
concentration of payments among cardiologists was assessed using the
Gini index, as in previous studies.\textsuperscript{20-22} Furthermore,
we examined trends in the number of cardiologists receiving payments and
the payment amounts from 2016 to 2019 using generalized estimating
equation (GEE) models. To adjust for highly skewed distribution of
payments, we used a log-linked GEE model with a Poisson distribution for
the number of cardiologists receiving payments and a negative binomial
GEE model for payments per cardiologist, as conducted in previous
studies.\textsuperscript{11,13,16,19,23} For trend analysis, we adjusted
for inflation, converting all payment values to 2019 Japanese yen value.
Given that all data used in this study were publicly available and met
the definition of non-human subjects research, institutional review
board approval was not required in Japan.

\textbf{Results}

Of the 15,048 eligible cardiologists board-certified by the JCS, 9,858
(65.5\%) received at least one personal payment from pharmaceutical
companies between 2016 and 2019 (Table 1). The total amount of these
payments was \$112,934,503, entailing 164,978 payment transactions. For
cardiologists who received at least one payment, the median amount per
cardiologist was \$2,947 (interquartile range {[}IQR{]}:
\$1,022--\$8,787), with a mean of \$11,456 (standard deviation {[}SD{]}:
\$35,876) over the four-year period. The Gini index was 0.840 for
personal payments per cardiologist, indicating that only a small
proportion of cardiologists received the vast majority of these
payments. Specifically, the top 1\% (150 cardiologists), 5\% (752
cardiologists), and 10\% (1505 cardiologists) received 31.6\%, 59.4\%,
and 73.5\% of all personal payments, respectively. Only 0.5\% (67
cardiologists) received more than \$200,000 payments and one
cardiologist received 565 payments totaling \$782,015 over the four
years.

Lecturing payments accounted for 88.6\% of the total payments
(\$100,067,695) in monetary value and 89.7\% in the number of payments
over the four years, with 64.5\% (9,710) of cardiologists receiving at
least one lecturing payment. Consulting and writing payments accounted
for 8.0\% (\$9.1 million) and 3.3\% (\$3.8 million) in monetary value.
The mean values per payment were \$1,243 for lecturing, \$1,236 for
consulting, and \$915 for drafting services.

Of 83 pharmaceutical companies making payments to the cardiologists,
Daichi Sankyo made the largest amounts of personal payments totaling
\$26.4 million (23.4\% of all payments), followed by Bayer (\$11.8
million; 10.4\% of all payments), Boehringer Ingelheim Japan (\$8.8
million; 7.8\% of all payments), Otsuka Pharmaceutical (\$8.3 million;
7.5\% of all payments), Bristol Myers Squibb (\$5.7 million; 5.0\% of
all payments), and Takeda Pharmaceutical (\$5.2 million; 4.6\%\% of all
payments). The top 5 and 10 companies with the largest payment amounts
were responsible for 54.2\% (\$61.2 million) and 71.3\% (\$80.5 million)
of all payments over the four years.

The total annual payments to cardiologists were from \$27.4 million in
2016 to \$28.8 million in 2017 (Table 2). Of all cardiologists, 46.4\%
to 47.4\% of cardiologists received at least one personal payment each
year. Median annual payments slightly increased from \$1,226 (IQR:
\$511--\$3,247) in 2016 to \$1,354 (IQR: \$613--\$3,335) in 2019. The
GEE models showed that there were no significant trends in the number of
cardiologists receiving personal payments (relative annual average
percentage change {[}RAAPC{]}: 0.3\% {[}95\% confidence interval: -0.2\%
to 0.8\%{]}, p=0.23) and payments per cardiologist (RAAPC: 0.6\% {[}95\%
confidence interval: -0.7\% to 1.8\%{]}, p=0.39) between 2016 and 2019.

\textbf{Discussion}

Our study revealed that 65.5\% of all board-certified cardiologists in
Japan received personal payments for activities such as lecturing,
consulting, and writing from pharmaceutical companies between 2016 and
2019. The total amount of these payments exceeded \$112.9 million,
equivalent to approximately 12.3 billion Japanese yen over this
four-year period. Although the level of these payments remained stable
throughout the study period, a disproportionately small group of
cardiologists received the majority of these payments. To the best of
our knowledge, this is the first study to explore the comprehensive
financial interactions between pharmaceutical companies and
cardiologists in a country other than the US.\textsuperscript{1,2,20}

Contrary to findings in the US, where approximately three-quarters of
cardiologists reportedly received various personal payments, including
compensation, honoraria, travel fees, royalties, and food and beverage
payments from pharmaceutical and medical device
corporations,\textsuperscript{1,2} our research in Japan indicates that
a mere half of the board-certified cardiologists annually received
financial recompense for lecturing and consulting from the
pharmaceutical companies. Although the study findings were consistent
with previous studies in Japan,\textsuperscript{11,13-17,19,23-25} this
lower percentage of cardiologists in Japan receiving such payments than
those in the US would substantially underrepresent the actual degree of
their financial engagements with the healthcare companies, given that
our study was limited to compensation payments to individual
cardiologists and did not encompass other prevalent payment categories
or payments from medical device companies, despite that cardiologists
frequently utilized medical equipment and devices such as implantable
cardioverter-defibrillators, cardiac catheters, and stents.

Although the majority of cardiologists received only modest amounts of
payments relative to their overall income as cardiologists, the impact
of these payments should not be underestimated. Previous studies in the
United States have demonstrated that even small payments to
cardiologists from medical device and pharmaceutical companies are
significantly associated with increased usage of implantable
cardioverter-defibrillators,\textsuperscript{8} percutaneous coronary
interventions,\textsuperscript{26} stent
placements,\textsuperscript{9}and prescriptions for oral
anticoagulants\textsuperscript{27} and antiplatelet
drugs.\textsuperscript{9} Nonetheless, given the absence of studies
exploring the associations between payments to cardiologists and their
clinical practices, future research is warranted to investigate the
impact of industry payments on the clinical practices of cardiologists
in Japan.

Additionally, we found that only a small number of cardiologists
received the vast majority of personal payments. As we elucidated, the
average payments to JCS executive board members\textsuperscript{12} and
cardiology guideline authors\textsuperscript{18} were substantially
larger than those received by the board-certified cardiologists on
average. These physicians, often referred to as key opinion leaders, are
frequently targeted by pharmaceutical and medical device
companies,\textsuperscript{28-37} due to their authoritative and
influential positions.

Given their significant influence on other cardiologists, it is crucial
to properly manage COIs among these influential cardiologists. However,
previous studies have indicated significant undeclared and underreported
COIs between these physicians and pharmaceutical companies in
Japan.\textsuperscript{12,18,28-30,37} Additionally, the policies for
managing COIs in Japan are less rigorous and transparent compared to
those in other developed countries.\textsuperscript{28,30,36,37} The
study findings further underscore the critical need for effective
management of financial COIs among influential cardiologists in Japan.

This study has several limitations. Potential inaccuracies in the
payment data reported by companies and in the database may exist.
Moreover, the omission of certain types of payments, including meals,
travel expenses, and gifts, which are not readily available in Japan,
likely leads to a substantial underestimation of the magnitude and
proportion of financial relationships between cardiologists and
pharmaceutical companies in Japan. Furthermore, as the study encompassed
only payments from JPMA-affiliated companies, it may not fully represent
the entire range of financial interactions between cardiologists and
pharmaceutical companies not affiliated with the JPMA and medical device
companies.

Despite these limitations, our study demonstrates that more than 65\% of
cardiologists certified by the Japanese Circulation Society received
personal payments related to lecturing, consulting, and writing from
pharmaceutical companies between 2016 and 2019. These payments were
concentrated among a small group of cardiologists. Future studies should
explore the influence of these payments to cardiologists on their
clinical practice in Japan.

\textbf{Declarations}

\textbf{Data availability statement}

All data used in this study is available from Yen For Docs database run
by Medical Governance Research Institute (\emph{https://yenfordocs.jp/})
and each pharmaceutical companies belonging to the Japan Pharmaceutical
Manufacturers Association. The datasets generated during and/or analyzed
during the current study are available from the corresponding author on
reasonable request.

\textbf{Conflicts of interest:}

The authors have no conflicts of interest for this study.

\textbf{Funding statement:}

The authors declare that there were no funding sources for this study.

\textbf{Ethics approval statement:}

As this study was a retrospective analysis of publicly available data
and met the definition of non-human subjects research, no institutional
board review and approval were required. This study followed the
Strengthening the Reporting of Observational Studies in Epidemiology
(STROBE) guideline.

\textbf{Patient consent statement}

Not applicable

\textbf{Permission to reproduce material from other sources}

Not applicable

\textbf{Clinical trial registration}

Not applicable

\textbf{Declaration of generative AI in scientific writing}

During the preparation of this work, the authors used ChatGPT version
4.0 to check and correct grammatical and spelling errors. After using
this tool, the authors carefully reviewed and edited the content as
needed and takes full responsibility for the content of the publication.

\textbf{Author contribution:}

A.M.: conceptualization; methodology; resource; software; formal
analysis; investigation; writing - original draft; writing - review \&
editing; visualization; study administration

K.H.: conceptualization; methodology; resource; software; formal
analysis; investigation; writing - review \& editing

Y.S.: conceptualization; methodology; resource; formal analysis;
investigation; writing - original draft; writing - review \& editing

\textbf{Acknowledgments}

We would like to thank Ms. Megumi Aizawa for her dedicated support of
our research project. For proofreading parts of the presented text, we
used the freely available pre-trained ChatGPT (version 4.0) model
developed by OpenAI in order to check and proofread the manuscript for
language, spelling and grammatical errors. We checked and edited the
text for unintended plagiarism and verified all facts and values that I
used from the ChatGPT outputs before the manuscript submission. The
version of ChatGPT accessed was the latest as of April 2023.

\textbf{References}

1. Murayama A, Kamamoto S, Shigeta H, Ozaki A. Industry Payments During
the COVID-19 Pandemic to Cardiologists in the United States. CJC Open
2023;5(3):253-255.

2. Tringale KR, Marshall D, Mackey TK, Connor M, Murphy JD,
Hattangadi-Gluth JA. Types and Distribution of Payments From Industry to
Physicians in 2015. JAMA 2017;317(17):1774-1784.

3. Marshall DC, Jackson ME, Hattangadi-Gluth JA. Disclosure of Industry
Payments to Physicians: An Epidemiologic Analysis of Early Data From the
Open Payments Program. Mayo Clin Proc 2016;91(1):84-96.

4. Murayama A. Industry-sponsored meal payments are associated with
prescriptions and Medicare expenditures on brand-name colchicine in the
United States. International Journal of Rheumatic Diseases
2023;n/a(n/a).

5. Murayama A. Pharmaceutical industry-sponsored meals and prescriptions
of biologics for asthma. J Allergy Clin Immunol Pract
2023;11(9):2916-2918.

6. Mitchell AP, Dusetzina SB, Mishra Meza A, Trivedi NU, Bach PB, Winn
AN. Pharmaceutical industry payments and delivery of non-recommended and
low value cancer drugs: population based cohort study. Bmj
2023;383:e075512.

7. Mitchell AP, Trivedi NU, Gennarelli RL, et al. Are Financial Payments
From the Pharmaceutical Industry Associated With Physician Prescribing?
: A Systematic Review. Ann Intern Med 2021;174(3):353-361.

8. Annapureddy AR, Henien S, Wang Y, et al. Association Between Industry
Payments to Physicians and Device Selection in ICD Implantation. Jama
2020;324(17):1755-1764.

9. Yanagisawa M, Blumenthal DM, Kato H, Inoue K, Tsugawa Y. Associations
Between Industry Payments to Physicians for Antiplatelet Drugs and
Utilization of Cardiac Procedures and Stents. J Gen Intern Med
2022;37(7):1626-1633.

10. Medical Governance Research Institute, Tansa. Yen For Docs. Medical
Governance Research Institute; 2023.

11. Murayama A, Saito H, Kamamoto S, Shigeta H, Yamashita E, Tanimoto T,
Ozaki A. Evaluation of non-research payments from pharmaceutical
companies to urologists in Japan between 2016 and 2019. Int Urogynecol J
2023;34(6):1285-1292.

12. Murayama A, Saito H, Tanimoto T, Ozaki A. Financial conflicts of
interest between pharmaceutical companies and executive board members of
internal medicine subspecialty societies in Japan between 2016 and 2020.
J Eval Clin Pract 2023;29(6):883-886.

13. Murayama A, Mamada H, Shigeta H, et al. Financial Relationships
Between Pharmaceutical Companies and Rheumatologists in Japan Between
2016 and 2019. J Clin Rheumatol 2023;29(3):118-125.

14. Murayama A, Hoshi M, Saito H, et al. Nature and Trends in Personal
Payments Made to the Respiratory Physicians by Pharmaceutical Companies
in Japan between 2016 and 2019. Respiration 2022;101(12):1088-1098.

15. Kamamoto S, Ozaki A, Murayama A. Assessment of Financial
Relationships Between Otorhinolaryngologists and Pharmaceutical
Companies in Japan Between 2016 and 2019. Cureus 2023;15(8):e43633.

16. Murayama A, Kamamoto S, Saito H, Ozaki A. Pharmaceutical payments to
Japanese board-certified dermatologists: a 4-year retrospective analysis
of personal payments from pharmaceutical companies between 2016 and
2019. Sci Rep 2023;13(1):7425.

17. Kusumi E, Murayama A, Kamamoto S, et al. Pharmaceutical payments to
Japanese certified hematologists: a retrospective analysis of personal
payments from pharmaceutical companies between 2016 and 2019. Blood
Cancer J 2022;12(4):54.

18. Senoo Y, Saito H, Ozaki A, et al. Pharmaceutical company payments to
authors of the Japanese guidelines for the management of hypertension.
Medicine (Baltimore) 2021;100(12):e24816.

19. Murayama A, Kamamoto S, Kawashima M, Saito H, Yamashita E, Tanimoto
T, Ozaki A. Cross-sectional analysis of pharmaceutical payments to
Japanese board-certified gastroenterologists between 2016 and 2019. BMJ
Open 2023;13(4):e068237.

20. Annapureddy A, Murugiah K, Minges KE, Chui PW, Desai N, Curtis JP.
Industry Payments to Cardiologists. Circ Cardiovasc Qual Outcomes
2018;11(12):e005016.

21. Murayama A, Kamamoto S, Kugo H, Saito H, Ozaki A. Research and
Nonresearch Industry Payments to Nephrologists in the United States
between 2014 and 2021. J Am Soc Nephrol 2023;34(10):1709-1720.

22. Murayama A, Kugo H, Saito Y, Saito H, Tanimoto T, Ozaki A. A 9-Year
Investigation of Healthcare Industry Payments to Pulmonologists in the
United States. Ann Am Thorac Soc 2023;20(9):1283-1292.

23. Kamamoto S, Murayama A, Kusumi E, et al. Evaluation of financial
relationships between Japanese certified pediatric
hematologist/oncologists and pharmaceutical companies: a cross-sectional
analysis of personal payments from pharmaceutical companies between 2016
and 2019. Pediatr Blood Cancer 2022;69(10):e29891.

24. Murayama A, Shigeta H, Kamamoto S, et al. Pharmaceutical Payments to
Japanese Board-Certified Head and Neck Surgeons Between 2016 and 2019.
OTO Open 2023;7(1):e31.

25. Murayama A, Kamamoto S, Saito H, et al. Pharmaceutical Payments to
Japanese Board-Certified Infectious Disease Specialists: A Four-Year
Retrospective Analysis of Payments from 92 Pharmaceutical Companies
between 2016 and 2019. Int J Environ Res Public Health 2022;19(12):7417.

26. Muluk SL, Lin GA, Anderson TS. Association of Device Industry
Payments, Physician Supply, and Regional Utilization of Orthopedic and
Cardiac Procedures. Journal of General Internal Medicine
2023;38(11):2501-2510.

27. Fleischman W, Agrawal S, King M, et al. Association between payments
from manufacturers of pharmaceuticals to physicians and regional
prescribing: cross sectional ecological study. BMJ 2016;354:i4189.

28. Murayama A, Kamamoto S, Murata N, et al. Evaluation of financial
conflicts of interest and quality of evidence in Japanese
gastroenterology clinical practice guidelines. J Gastroenterol Hepatol
2023;38(4):565-573.

29. Mamada H, Murayama A, Ozaki A, et al. Observational study of
financial and non-financial conflicts of interest among the Japanese
government advisory board members concerning coronavirus disease 2019.
Medicine (Baltimore) 2023;102(4):e32776.

30. Murayama A, Yamada K, Yoshida M, et al. Evaluation of Conflicts of
Interest among Participants of the Japanese Nephrology Clinical Practice
Guideline. Clin J Am Soc Nephrol 2022;17(6):819-826.

31. Murayama A, Kamamoto S, Shigeta H, Saito H, Yamashita E, Tanimoto T,
Akihiko O. Undisclosed financial conflicts of interest with
pharmaceutical companies among the authors of the Esophageal Cancer
Practice Guidelines 2017 by the Japan Esophageal Society. Dis Esophagus
2022;35(10).

32. Harada K, Ozaki A, Saito H, et al. Financial payments made by
pharmaceutical companies to the authors of Japanese hematology clinical
practice guidelines between 2016 and 2017. Health Policy
2021;125(3):320-326.

33. Kida F, Murayama A, Saito H, Ozaki A, Shimada Y, Tanimoto T.
Pharmaceutical company payments to authors of the Japanese Clinical
Practice Guidelines for Hepatitis C treatment. Liver Int
2021;41(3):464-469.

34. Hashimoto T, Murayama A, Mamada H, Saito H, Tanimoto T, Ozaki A.
Evaluation of financial conflicts of interest and drug statements in the
coronavirus disease 2019 clinical practice guideline in Japan. Clin
Microbiol Infect 2022;28(3):460-462.

35. Murayama A, Ozaki A, Saito H, Sawano T, Sah R, Tanimoto T.
Coronavirus disease 2019 experts appearing on Japanese television: their
characteristics and financial conflicts of interest with pharmaceutical
companies. Clin Microbiol Infect 2020;27(5):805-807.

36. Murayama A. Financial Conflicts of Interest Among the Authors of the
Clinical Practice Guidelines for Rheumatoid Arthritis in Japan. Cureus
2023;15(10):e46650.

37. Mamada H, Murayama A, Kamamoto S, et al. Evaluation of Financial and
Nonfinancial Conflicts of Interest and Quality of Evidence Underlying
Psoriatic Arthritis Clinical Practice Guidelines: Analysis of Personal
Payments From Pharmaceutical Companies and Authors' Self-Citation Rate
in Japan and the United States. Arthritis Care Res (Hoboken)
2023;75(6):1278-1286.

Table 1. Summary of personal payments to board-certified cardiologists\selectlanguage{english}
\begin{longtable}[]{@{}ll@{}}
\toprule
\begin{minipage}[b]{0.47\columnwidth}\raggedright\strut
Variables\strut
\end{minipage} & \begin{minipage}[b]{0.47\columnwidth}\raggedright\strut
Value\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
Total amounts of payments\strut
\end{minipage} & \begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
Payment values, \$\strut
\end{minipage} & \begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
112,934,503\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
Number of payments, No.\strut
\end{minipage} & \begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
164,978\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
Payments per cardiologist\strut
\end{minipage} & \begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
Mean (standard deviation) \textsuperscript{a}\strut
\end{minipage} & \begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
Payment values, \$\strut
\end{minipage} & \begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
12,649 (35,012)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
Number of payments, No.\strut
\end{minipage} & \begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
16.7 (33.9)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
Median (interquartile range) \textsuperscript{a}\strut
\end{minipage} & \begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
Payment values, \$\strut
\end{minipage} & \begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
2,947 (1,022 -- 8,787)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
Number of payments, No.\strut
\end{minipage} & \begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
7.0 (2.0 -- 17.0)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
Maximum\textsuperscript{a}\strut
\end{minipage} & \begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
Payment values, \$\strut
\end{minipage} & \begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
782,015\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
Number of payments, No.\strut
\end{minipage} & \begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
575.0\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
Gini index\strut
\end{minipage} & \begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
0.840\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
Cardiologists with specific amounts of payments (N=15,048), n (\%)\strut
\end{minipage} & \begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
No payment\strut
\end{minipage} & \begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
5,190 (34.5)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
Any payments\strut
\end{minipage} & \begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
9,858 (65.5)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
\$1-\$1,000\strut
\end{minipage} & \begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
2,318 (15.4)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
\$1,001-\$10,000\strut
\end{minipage} & \begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
5,314 (35.3)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
\$10,001-\$50,000\strut
\end{minipage} & \begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
1,825 (12.1)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
\$50,001-\$100,000\strut
\end{minipage} & \begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
225 (1.5)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
\$100,001-\$200,000\strut
\end{minipage} & \begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
109 (0.7)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
\$200,001 or more\strut
\end{minipage} & \begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
67 (0.5)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
Payment categories\strut
\end{minipage} & \begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
Lecturing payments\strut
\end{minipage} & \begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
Monetary value (\%), \$\strut
\end{minipage} & \begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
100,067,695 (88.6)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
Number of payments (\%), No.\strut
\end{minipage} & \begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
148,012 (8.0)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
Number of cardiologists receiving payments (\%), n\strut
\end{minipage} & \begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
9,710 (64.5)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
Consulting payments\strut
\end{minipage} & \begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
Monetary value (\%), \$\strut
\end{minipage} & \begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
9,084,765 (89.7)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
Number of payments (\%), No.\strut
\end{minipage} & \begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
11,814 (8.0)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
Number of cardiologists receiving payments (\%), n\strut
\end{minipage} & \begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
3,561 (23.7)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
Writing payments\strut
\end{minipage} & \begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
Monetary value (\%), \$\strut
\end{minipage} & \begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
3,782,044 (3.3)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
Number of payments (\%), No.\strut
\end{minipage} & \begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
5,152 (3.1)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
Number of cardiologists receiving payments (\%), n\strut
\end{minipage} & \begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
2,300 (15.3)\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

Legends: \textsuperscript{a} Payments per cardiologist were calculated
among cardiologists who received one or more payments, as 34.5\% of
cardiologists did not receive any payments over the five years.

Table 2. Trend in personal payments from pharmaceutical companies to
board-certified cardiologists between 2016 and 2019.\selectlanguage{english}
\begin{longtable}[]{@{}llllll@{}}
\toprule
\begin{minipage}[b]{0.14\columnwidth}\raggedright\strut
Variables\strut
\end{minipage} & \begin{minipage}[b]{0.14\columnwidth}\raggedright\strut
2016\strut
\end{minipage} & \begin{minipage}[b]{0.14\columnwidth}\raggedright\strut
2017\strut
\end{minipage} & \begin{minipage}[b]{0.14\columnwidth}\raggedright\strut
2018\strut
\end{minipage} & \begin{minipage}[b]{0.14\columnwidth}\raggedright\strut
2019\strut
\end{minipage} & \begin{minipage}[b]{0.14\columnwidth}\raggedright\strut
Average relative yearly change between 2016 and 2019 (95\% CI), \%\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Total payments\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
Monetary value, \$\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
27,358,539\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
28,757,456\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
28,090,504\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
28,728,005\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
--\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
Number of payments, No.\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
40,527\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
41,822\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
40,572\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
42,057\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
--\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Payments per cardiologist\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Monetary value, \$\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
Mean (standard deviation)\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
3,917 (10,883)\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
4,068 (11,314)\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
3,938 (10,416)\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
4,082 (10,764)\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
0.6 (-0.7 to 1.8)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
Median (interquartile range)\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
1,226 (511--3,247)\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
1,328 (511--3,372)\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
1,320 (511--3,270)\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
1,354 (613--3,335)\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
Maximum\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
248,198\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
221,104\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
173,339\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
211,955\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
Gini index\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
0.865\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
0.862\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
0.858\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
0.858\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Number of payments, No.\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
Mean (standard deviation)\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
5.8 (10.1)\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
5.9 (10.4)\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
5.7 (9.7)\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
6.0 (10.0)\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
0.8 (-0.1 to 1.7)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
Median (interquartile range)\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
3.0 (1.0--6.0)\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
3.0 (1.0--6.0)\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
3.0 (1.0--6.0)\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
3.0 (1.0--6.0)\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
Maximum\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
189.0\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
160.0\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
155.0\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
162.0\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
Gini index\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
0.810\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
0.808\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
0.802\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
0.805\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Physicians with payments (\%) (N=15,048), n\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
6,984 (46.4)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
7,070 (47.0)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
7,133 (47.4)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
7,038 (46.8)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
0.3 (-0.2 to 0.8)\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

Abbreviation: 95\% confidence interval (95\% CI). *p\textless{}0.01.
**p\textless{}0.001.

\selectlanguage{english}
\FloatBarrier
\end{document}

