Dear Editor in Chief
Please find enclosed the revised version of our manuscript titled "Quality of care
of peptic ulcer disease worldwide: a systematic analysis for the global burden of
disease study 1990-2019", which we would like to submit for publication in PLOS ONE.
Please find enclosed our reply to the editors and reviewer's comments. We have appreciated
the encouraging, fair and constructive comments of the editors and reviewers. We revised
the manuscript according to the suggestions and enclosed a highlighted version of
the revised manuscript.
We feel that the changes made according to the comments have improved the quality
of the manuscript, and we would be happy if it now meets the criteria for publication
in the journal.
Best regards;
Farshad Farzadfar
(On behalf of myself and my co-authors)
Editor comments
Editor
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Authors
Amended.
Editor
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Kindly be informed that the maps were generated using free, open-source map data of
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This was also included in the methods section of the manuscript. It now reads:
The maps were generated using free open-source map data of Natural Earth public domain
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We will update your Data Availability statement on your behalf to reflect the information
you provide.
Authors
Thank you for your meticulous comment. Regarding the data availability, we have previously
published the study protocol to enable other researchers to reproduce this work. Moreover,
the data used in this study are available from the Global Burden of Disease Results
Tool, made public by Institute for Health Metrics and Evaluation. The authors confirm
they had no special access or privileges to the data that other researchers would
not have. We revised the data source sub-heading in the methods section, which now
reads:
The study data were derived from GBD 2019, conducted by IHME. GBD 2019 included 204
countries and territories from 1990 to 2019 and a systematic analysis of 286 causes
of death, 369 diseases and injuries, and 87 risk factors in 204 countries and territories
[1,2]. GBD classified countries and territories into 21 regions based on epidemiological
homogeneity and geographical contiguity [3]. The regions were also grouped into seven
super-regions based on the cause of death patterns [4]. The seven super-regions are
High income; Latin America & Caribbean; Sub-Saharan Africa; North Africa & Middle
East; Southeast Asia, East Asia & Oceania; South Asia; Central Europe, Eastern Europe
& Central Asia.
The study protocol and codes used in this study are available from (https://dx.doi.org/10.17504/protocols.io.bprjmm4n) [5]. The data used in this work are available from Global Burden of Disease Results
Tool (http://ghdx.healthdata.org/gbd-results-tool) [6], made public by Institute for Health Metrics and Evaluation. The data of PUD
were extracted from GBD 2019: GBD code: B.4.2.1, International Statistical Classification
of Diseases and Related Health Problems 10th Revision, World Health Organization version
10 (ICD-10) code: K-25 to K28.9 [7]. Data sources used to provide estimates in GBD
2019 are presented in Supplementary Table 1. In terms of the development status, countries
were categorized using the GBD Socio-Demographic Index (SDI) [8].
Reviewer 1
Reviewer
Reviewer #1: The paper tackles a public health issue using measures such as the socio
demographical index, in addition to using a proxy for quality of care, as well as
the gender disparity ratio to assess the levels of inequities and quality of care
for peptic ulcer disease worldwide among different demographical aspects.
The paper is simple and its writing style is comprehensible for the non specialized
of readers. It uses easy to understand figures and graphs. The conclusion is supported
by valid data.
This kind of analysis is useful in aiding policy makers in deciding on interventions
to combat peptic ulcer disease at the root cause, because the study takes into consideration
sociodemographic determinants of health, which in turn affect health outcomes and
quality of care.
Authors
The authors appreciate the encouraging comments of the reviewer.
Reviewer 2
Reviewer
1. All acronyms should be defined at the first mention of each of the acronyms in
the manuscript.
Authors
The authors appreciate the fair and constructive comment of the reviewer. Amended.
Reviewer
2. What is NSAIDs?
Authors
Thank you for your comment. We double-checked the manuscript and realized that the
abbreviation "NSAID" (non-steroidal anti-inflammatory drugs) was not defined in the
text, which was then included in the text.
Reviewer
3. What are the criteria for the classifications of GBD super regions?
Authors
GBD 2019 included 204 countries and territories from 1990 to 2019 and a systematic
analysis of 286 causes of death, 369 diseases and injuries, and 87 risk factors in
204 countries and territories [1,2]. GBD classified countries and territories into
21 regions based on epidemiological homogeneity and geographical contiguity [3]. The
regions were also grouped into seven super-regions based on the cause of death patterns
[4]. The seven super-regions are High income; Latin America & Caribbean; Sub-Saharan
Africa; North Africa & Middle East; Southeast Asia, East Asia & Oceania; South Asia;
Central Europe, Eastern Europe & Central Asia.
The data source section of the methods was revised and now reads:
The study data were derived from GBD 2019, conducted by IHME. GBD 2019 included 204
countries and territories from 1990 to 2019 and a systematic analysis of 286 causes
of death, 369 diseases and injuries, and 87 risk factors in 204 countries and territories
[1,2]. GBD classified countries and territories into 21 regions based on epidemiological
homogeneity and geographical contiguity [3]. The regions were also grouped into seven
super-regions based on the cause of death patterns [4]. The seven super-regions are
High income; Latin America & Caribbean; Sub-Saharan Africa; North Africa & Middle
East; Southeast Asia, East Asia & Oceania; South Asia; Central Europe, Eastern Europe
& Central Asia. The data of PUD was extracted from GBD 2019: GBD code: B.4.2.1, International
Statistical Classification of Diseases and Related Health Problems 10th Revision,
World Health Organization version 10 (ICD-10) code: K-25 to K28.9 [7]. Data sources
used to provide estimates in GBD 2019 are presented in Supplementary Table 1. In terms
of the development status, countries were categorized using the GBD Socio-Demographic
Index (SDI) [8].
Reviewer
4. Please remove the list of abbreviations at the end of the manuscript.
Authors
Thank you for your comment. Amended.
Reviewer 3
Reviewer
This study has been conducted using the data derived from the Global Burden of Disease
study 19990 – 2019. The objective of this study was to compare the health-system quality-of-care
and inequities for Peptic Ulcer Disease (PUD) among age groups and sexes worldwide.
The authors have concluded that the Quality of Care Index of PUD improved dramatically
during 1990-2019 worldwide. There are still significant heterogeneities among countries
both on different and on similar SDI-levels.
The rationale for the study is clear and valid. The authors have used a technically
suitable protocol and a feasible methodology to effectively achieve the study's aims.
However, I have the following concerns about their methodology.
Authors
The authors would like to thank the reviewer for the encouraging opinion. They also
appreciate the fair and constructive comments of the reviewer.
Reviewer
1.) QCI is a relatively new index attempting to estimate the health care quality at
the population level. The index was developed using a linear combination of mortality
to incidence, DALY to prevalence, prevalence to incidence, and YLL to YLD ratios estimated
using an acceptable statistical method. However, the authors should elaborate on interpreting
the QCI relevant to the subject matter under consideration. To me, the QCI is too
composite.
Authors
The authors appreciate the fair and constructive comment of the reviewer. We reviewed
the methods section and agree that further details need to be included. The quality
of care index section in the methods now reads:
To determine QCI for PUD, the following indices were defined as follows:
Mortality to incidence ratio of PUD=(# Age-standardizaed PUD mortality)/(# Age-standardizaed
PUD Incidence)
The mortality to incidence ratio of PUD indicates that with a stable PUD incidence
in regions, higher mortality values could represent worse care provided to these patients.
DALY to prevalence ratio of PUD=(# Age-standardizaed DALY of PUD )/(# Age-standardizaed
PUD prevalence )
DALY to prevalence ratio of PUD indicates that with a similar prevalence of PUD in
regions, higher DALY could represent worse care quality.
Prevalence to incidence ratio of PUD=(# Age-standardizaed PUD prevalence )/(# Age-standardizaed
PUD incidence)
The prevalence to incidence ratio of PUD indicates that in regions with similar PUD
incidence, higher prevalence could represent better PUD management to avert mortality.
YLL to YLD ratio of PUD=(# Age-standardizaed YLL of PUD )/(# Age-standardizaed YLD
of PUD)
YLL to YLD ratio of PUD could reflect the quality of healthcare in a region, as poor
health quality provided for PUD in a region would result in higher YLLs and fewer
YLDs. In other words, patients would live less than the life expectancy of the region).
Moreover, the section describing the Principal Components Analysis was revised, which
now reads:
PCA would allow us to reduce the number of variables in a large set of correlated
variables to a smaller number of variables that collectively explain most of the variance
in the original set [9]. The first component of PCA was made up of a linear combination
of the four abovementioned ratios, including mortality to incidence, DALY to prevalence,
prevalence to incidence, and YLL to YLD, containing the most significant amount of
information about these variables and is referred to as QCI in this study. QCI ranged
from 0 to 100, with 100 indicating the best quality of care [10–14].
Reviewer
2.) The rationale of selecting or dividing the QCI into different levels (Level 1
to 5) is not clearly explained in terms of their relative importance. For example,
the difference between levels 1 and 5 when considering the service delivery outcomes
at the operational level is challenging to comprehend. How a country should move from
level 1 to 5 is not clear.
Authors
Thank you for your meticulous comment. For enhanced interpretation and comparison
of countries, QCI was categorized as five levels in 2019 based on quintiles, where
Level 1 (the first quintile) indicated the highest index and Level 5 (the fifth quintile)
the lowest: Level 5 included QCI ≤69.14, Level 4 QCI>69.14 to 75.23, Level 3 QCI>75.23
to 81.33, Level 2 QCI>81.33 to 86.35, and Level 1 QCI≥86.35.
We revised the corresponding section in the methods, which now reads:
PCA was performed using R software version 3.5.2. For enhanced interpretation and
comparison of countries, QCI was categorized as five levels in 2019 based on quintiles,
where Level 1 (the first quintile) indicated the highest index and Level 5 (the fifth
quintile) the lowest: Level 5 included QCI ≤69.14, Level 4 QCI>69.14 to 75.23, Level
3 QCI>75.23 to 81.33, Level 2 QCI>81.33 to 86.35, and Level 1 QCI≥86.35
We also revised the last paragraph of the discussion on the witnessed heterogeneities
across countries in terms of PUD:
This study also highlights the considerable existing heterogeneity across the globe
regarding the changes in prevalence, incidence, and mortality of PUD. While the age-standardized
mortality rate due to PUD has decreased by 69% in high-SDI countries, low and low-middle
SDI countries remain to have the highest age-standardized PUD mortality rate despite
previous endeavors. The reasons for the witnessed heterogeneity could be larger family
size, low socioeconomic status, overcrowding, poor sanitation, having an infected
sibling, growth retardation, and nutritional deficiencies, particularly iron-deficiency
anemia in low SDI countries [15,16]. The witnessed gaps and inequities call for concerted
efforts to lessen the burden of PUD in areas with limited resources. Given the level
of technology, expenses, and the expertise required for complications management of
PUD, its early detection and prevention seem feasible and cost-effective [17]. However,
further research is required to determine the most suitable strategies for early detection,
treatment, and follow-up based on available resources.
Reviewer
3.) The major drawback was that the estimates lacked the confidence intervals to compare
the different levels defined. The study's authors have highlighted this drawback,
but it is better to get expert statistical advice to overcome this fundamental limitation.
Authors
Thank you for your meticulous comment. Kindly note that in this study, PCA was used
to generate QCI, which is a mathematical method [18]. GBD utilizes statistical methods
to estimate the burden measures, i.e. DALYs, YLLs, YLDs, death, incidences, and prevalence.
Nevertheless, PCA did not allow us to present any uncertainty values; thus, the study
does not report confidence or uncertainty intervals.
We revised the strengths and limitations section of the manuscript accordingly, which
now reads:
QCI combined mortality to incidence ratio [19], DALYs to prevalence ratio [20], prevalence
to incidence ratio [21], and YLLs to YLDs ratio [22] into a single index, aiming to
demonstrate the quality of care among countries [11–13,22–25]. Although QCI does not
reflect all the aspects of the quality of services among healthcare systems, it could
be used as a proxy for comparing various countries. The review of the existing literature
also confirmed that the current situation of PUD on a global scale and its time trends
during 1990-2019 mainly were consistent with the picture, as shown via QCI [26–29].
In addition, it showed an acceptable correlation with the HAQ Index for PUD. The advantage
of QCI is that, unlike HAQ Index, it could be used to present inequities among both
sexes, age groups, and in all the seven GBD super-regions and 21 regions.
Moreover, we used the estimates of GBD 2019, while the latest published HAQ Index
used the data of GBD 2016 [23]. However, QCI does not currently capture subnational
inequalities, and future efforts with a better geospatial resolution on sub-national
levels need to be prioritized. Despite using as many data sources as possible, the
GBD study includes estimations based on the predictive covariates in locations with
scarce data sources. Since the data of this study were derived from the GBD study,
the limitations experienced in GBD estimations also apply to this study [30]. Among
risk factors of PUD, smoking was the only risk factor with sufficient data to be modeled
in the GBD study 2019. In this study, PCA was used to generate QCI, which is a mathematical
method [18]. GBD utilizes statistical methods to estimate the burden measures, i.e.
DALYs, YLLs, YLDs, death, incidences, and prevalence. Nevertheless, PCA did not allow
us to present any uncertainty values; thus, the study does not report confidence or
uncertainty intervals. Despite its limitations, the current study could show the big
picture of the current inequities regarding PUD management based on geographical distribution,
sex, and age groups to empower policymakers in making well-informed decisions.
Reviewer
4) Few spelling mistakes were noted.
Authors
The authors appreciate the reviewer's opinion. We asked a bilingual native English
professor at our institution to thoroughly review and revise the manuscript regarding
possible grammar and syntax errors to ensure enhanced readability. In addition, we
used "Grammarly", a cross-platform cloud-based writing assistant that reviews spelling,
grammar, punctuation, clarity, engagement, and delivery mistakes.
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