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Epidemiology of Dupuytren disease unraveled

Broekstra, Dieuwke

IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document version below.

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Publication date: 2017

Link to publication in University of Groningen/UMCG research database

Citation for published version (APA):

Broekstra, D. (2017). Epidemiology of Dupuytren disease unraveled: Prevalence, risk factors and disease course. Rijksuniversiteit Groningen.

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Dupuytren disease unraveled

Prevalence, risk factors and disease course

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Financial support for printing of this thesis was kindly provided by the University Medical Center Groningen - Graduate School of Medical Sciences, BAPmedical and Pfizer.

ISBN: 978-90-367-9986-7

ISBN (electronic version): 978-90-367-9985-0 © Copyright 2017 Dieuwke Broekstra

All rights are reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means without written permission of the author or the publisher holding the copyright of the published articles.

Cover: Dieuwke Broekstra Layout: Dieuwke Broekstra

Printed by: Ridderprint BV, Ridderkerk

The cover represents a nodule in a Dupuytren cord. The word ‘nodule’ is derived from the Latin word ‘nodus’, which means ‘knot’. In a progressed stage, Dupuytren cells align and form a cord, which is represented by the strings that are placed in one line.

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Dupuytren disease unraveled

Prevalence, risk factors and disease course

Proefschrift

ter verkrijging van de graad doctor aan de Rijksuniversiteit Groningen

op gezag van de

rector magnificus prof. dr. E. Sterken en volgens besluit van het College voor Promoties.

De openbare verdediging zal plaatsvinden op woensdag 27 september om 14:30 uur

door

Dieuwke Christina Broekstra Geboren op 14 februari 1987

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Prof. dr. E.R. van den Heuvel

Beoordelingscommissie

Prof. dr. G.H. de Bock

Prof. D. Furniss, DM, FRCS(Plast) Prof. dr. I. Degreef

Paranimfen

S.F. Broekstra, BSc R. Lanting, MD, PhD

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Zij die nieuwsgierigheid hebben aangemoedigd,

doorzettingsvermogen hebben aangeleerd,

zij die altijd in mij hebben geloofd,

die nog altijd in mij geloven

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Chapter 1. General introduction 8

Part I. Prevalence and risk factors

Chapter 2. A systematic review and meta-analysis on the prevalence 22

of Dupuytren disease in the general population of

Western countries

Chapter 3. A systematic review and meta-analysis on the strength and 46

consistency of the associations between Dupuytren disease, diabetes mellitus, liver disease and epilepsy

Chapter 4. Dupuytren disease is highly prevalent in field hockey 76

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Chapter 5. Intra- and inter-observer agreement on diagnosis of 96 Dupuytren disease, measurements of severity of contracture,

and disease extent

Chapter 6. Clinimetric properties of the Dutch URAM and its 116

ability to detect Dupuytren disease progression compared

to the MHQ

Part III. Natural course of Dupuytren disease

Chapter 7. 4.5-year results of a prospective cohort study on disease 136

course of primary Dupuytren disease

Chapter 8. General discussion 162

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Dupuytren disease: etiology and epidemiology

Dupuytren disease is a connective tissue disease affecting the palmar fascias of the hand. It has been named after the French surgeon and anatomist Guillaume Dupuytren. Early signs of this disease are skin pitting, and the presence of nodules (Figure 1A). Usually, a nodule is a firm lump, commonly located in the palm of

the hand, that mainly consists of collagen and (myo)fibroblasts.1,2 Myofibroblasts

are fibroblasts that contain a contractile element. Mostly, nodules are painless and do not lead to functional complaints. Therefore, they are not always recognized by

the patient, as indicated by a previous study of our research group on prevalence,3

in which many of the participants having mild disease reported that they did not notice the small nodules. The nodules can progress into cords, in which the cellular density is decreased and the myofibroblasts are aligned along the lines of

mechanical stress.4 Contraction of myofibroblasts in combination with synthesis

and degradation of extra-cellular matrix, results in connective tissue remodeling. This interplay eventually gives rise to the characteristic flexion contracture of the fingers (Figure 1B). The flexion contractures can cause functional complaints, or

even lead to psychosocial complaints, as it may impede the patients’ self-esteem.5

Even though Dupuytren disease is considered as a benign disease, underlying

mechanisms as abnormal Wnt signaling6 or molecular alterations,4 and features

such as a high likelihood of recurrence after treatment, with lower recurrence rates

after rigorous treatment, have similarities with neoplastic diseases.7 Previously, it

has been suggested that Dupuytren disease is associated with a higher mortality,8-10

and this has recently been supported by results of a large cohort study.11

It is unknown what exactly triggers the transformation of fibroblasts in the palmar fascia into myofibroblasts, but there is evidence that it is associated with cell stress and several molecular changes. These include an increased level of

growth factors,12-14 cytokines,12 extra-cellular related proteins,15,16 and altered levels

of matrix-metalloproteinases,17,18 combined with altered levels of tumor necrosis

factor.19 These alterations are also present in inflammation and scar formation.20,21

The reported prevalence of Dupuytren disease varies largely, from 0.6 to 56.0%.22

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studies only included patient groups, while others studied general populations), differences in genetic predisposition between populations of different countries, or suboptimal study design of the prevalence studies. Research performed in the general elderly population of Groningen (the Netherlands), has shown that the prevalence

is 22.1% in people over 50 years of age.3 Men are more frequently affected than

women.3,23 As the prevalence tends to rise with increasing age,3,23 Dupuytren disease

can be seen as a chronic disease of the elderly. This may, in the coming decades, lead to increased health care costs related to the treatment of this disease. Because of this, a reliable estimation of the prevalence of Dupuytren disease in the general population worldwide, is important.

Although the influence of many suspected risk factors has not yet been elucidated, genome wide association studies (GWAS) and twin studies have shown that Figure 1. A) Mild stage of Dupuytren disease, in which a nodule is present in the ring finger ray in the palm of the hand. B) Severe stage of Dupuytren disease, in which a contracture of the little finger ray is present, and multiple nodules and cords in the first web space, palm and fingers have been encircled.

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genetics play an important role.6,24,25 Beside this, several other intrinsic and extrinsic

risk factors are frequently linked to Dupuytren disease in the literature. Examples of intrinsic risk factors are diabetes mellitus, epilepsy and liver disease. These conditions are often studied in relation with Dupuytren disease, but a statistically

significant association has not always been confirmed.26-29 Examples of extrinsic risk

factors that are often suggested to be related with Dupuytren disease, are exposure

to manual work and hand-arm vibrations.30-33 Several studies have been done on

this topic, but again, a statistically significant association was not always found. Almost all studies that investigated the association between Dupuytren disease and

vibration, focused on occupational exposure to vibration.29,31,33 However, vibration

exposure can also occur during leisure or sports activities.34,35 To date, this has never

been subject of study. Treatment options

Dupuytren disease cannot be cured, so treatment is aimed at preventing disease progression or reducing the flexion contractures of the fingers. Some claim that the former can be achieved by radiation therapy that prevents the proliferation of

fibroblasts,36,37 by anti-inflammatory drugs,38,39 or by the estrogen receptor antagonist

tamoxifen,40 although the evidence for the effectiveness of these methods is limited.

Recently, a possible new therapeutic target has been identified, i.e. tumor necrosis

factor, that might prevent disease progression.19

Flexion contractures can be corrected using different treatment options, such as surgery, in which the cord is transsected or resected, or collagenase injections that lead to local breakdown of the Dupuytren cord. Although collagenase injections

replaced part of the surgical procedures in the United States,41,42 most patients in

the Netherlands are still treated surgically with percutaneous needle fasciotomy or limited fasciectomy, because collagenase treatment is not being reimbursed by the

insurance companies.43 In percutaneous needle fasciotomy, the Dupuytren cord

is divided with a needle, whereafter the finger (in most cases) can be extended. The dissected cord is not removed using this technique. In limited fasciectomy, the diseased tissue is removed, sometimes combined with removal of the overlying skin (dermofasciectomy). A skin graft is used to close the defect that occurs as consequence of the dermofasciectomy.

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Unfortunately, recurrences are common and many patients require treatment

again.7 This is a challenge in surgical treatment of Dupuytren disease, since the

scar tissue itself (that remains after surgical treatment) may form a source for the

formation of new Dupuytren nodules and cords.20,21 In extreme cases, amputation

of the affected ray is the only treatment option that is left to regain functional ability. With this in mind, it is evident that timing of surgical treatment is essential. Treating

too early might result in multiple recurrences or earlier recurrences.44 However,

treating too late can make the treatment less successful, because of larger contracture deformities involving multiple joints, an increased chance of natural arthrodesis due to flexion contractures, and because of increased surgical complexity.

Disease course

Despite the fact that this disease has been described as early as in the 17th century

by Felix Platter, literature on the course of Dupuytren disease is scarce. One study describes the results of fasciectomy and fasciotomy with a follow-up time of 5 years, and the results are compared to a control group of Dupuytren patients who received

no treatment.45 Unfortunately, the sample size in this study is small (47 untreated

hands, and the number of participants is not reported) and no statistical analyses have been done, which hampers the interpretation of the results.

The prevailing thought from a clinical point of view is that Dupuytren disease is progressive. However, experience shows there are also cases in which the disease is

stable, or even in regression.46 This difference might be explained by the sampling

method. In the vast majority of studies, participants are recruited from a hospital population. As a consequence, only patients with a more severe form of Dupuytren disease are included. The mild cases, in which only nodules are present, may not seek medical advice. So, they are less likely to be included in a study. Additionally, the few other studies that were done to determine the disease course, only used two

measurement times.28,46 In this way, only a linear disease course profile could be

estimated. Precise knowledge about the disease course is important to gain insight in the development of the disease, but more importantly, to identify factors that may trigger disease progression, and to facilitate the clinicians’ decision about when to treat best.

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of Dupuytren disease were followed-up every 6 months, to evaluate the course of primary Dupuytren disease. After 1.5 years, interim-analyses were done. Three clinically different disease courses were identified, namely progression, stability and regression. In the majority of the participants, the disease was stable. Disease extent (surface area of the nodules and cords in a ray) at the start of the study

was associated with disease course.47 So, the larger the disease extent, the larger

the chance to have progressive disease. There were no other risk factors that could explain why some experienced progression, and others did not. An explanation might be that the change due to progression was too small to be discriminated from variability in measurements. Therefore, a description of long-term (more than 1.5 years) disease course of Dupuytren disease may be needed to identify risk factors for progression.

Outcome measures in research on Dupuytren disease

The most commonly used outcome measure in Dupuytren research is range of motion, and especially extension deficit, which is the inability to straighten the

fingers.48 It can be measured either active or passive, and both types are used in

the literature.7,49,50 The extension deficit is measured in each finger joint separately,

but it can be summed to form a total passive or active extension deficit per finger. Although this variable is considered as the most suitable objective outcome measure for quantifying severity and treatment effects, the reliability of this outcome is unclear. Furthermore, it has some disadvantages in statistical analysis, that will be explained later. Another disadvantage is that it cannot be measured in patients who only have mild Dupuytren disease without flexion contractures. Therefore, we searched for an alternative measure. In such patients, we used the surface area of nodules and cords, measured with a tumorimeter. This is a planimeter that is used

in oncology to measure the surface area of tumors on X-rays.51 The surface area was

used as alternative measure for quantifying disease extent.

As mentioned before, previous studies have mainly focused on extension deficit as outcome measure in Dupuytren research. The patient’s perspective has long been neglected. Lately, a few studies have appeared studying hand function and quality

of life in patients with Dupuytren disease.52,53 Despite the increasing attention to

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is universally used. Additionally, all the available PROMs are designed to detect

change after treatment. It is unclear whether the PROMs are able to detect change over time due to disease progression. This needs to be elucidated before the PROM can be used in clinical practice to determine the functional consequences of disease progression.

Data-analysis of outcome measures

As stated in the previous section, measuring extension deficits has some important consequences for the statistical data-analysis.

First, extension deficit is often measured in all finger joints, and in multiple fingers per participant. This results in multiple observations within one participant. Clearly, these observations cannot be considered independent, which is an assumption of many statistical tests. The data contain a multilevel structure, as is shown in Figure 2. This multilevel structure of the data poses some challenges when it comes

to analyzing the data, and ignoring it can lead to wrong conclusions.54

There are several methods to manage multilevel data statistically. First of all, commonly used statistical software packages contain techniques such as generalized linear mixed-effects models that are designed to analyze multilevel data. If the use of these models is not possible, another solution is to reduce the number of levels in the dataset by processing parameters: for example, passive extension deficits that are measured in the three different finger joints can be added together to form a total passive extension deficit. By doing this, one level has been eliminated (joint). Further reduction of the number of levels can be done by randomly selecting one finger per participant which is included in the analysis, instead of including multiple fingers per participant in the analysis. It is important to note that as a consequence, data are lost after data reduction, so this is not always a preferable option.

Secondly, extension deficit (regardless of whether it is active, passive, or total) is often a zero-inflated continuous parameter, which means that the parameter shows clustering at zero, since most patients do not have contractures anymore once they have been treated. It is also possible that there are Dupuytren disease patients in the study who do not have contractures at all, resulting in an extension deficit of zero. Therefore, the distribution of this outcome measure is not normal. Data transformation to obtain normality is also not possible, since no calculations

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can handle large numbers of zero. A possibility to analyze this type of outcome measure is to use a mixture distribution. A mixture distribution can be considered as a combination of only parametric distributions, or as combination of a parametric and a non-parametric distribution (or distribution free). The zero-inflated data can be analyzed with the parametric model, while the positive values would be modeled with the non-parametric component. This way, the parametric and non-parametric components that frequently characterize extension deficit measurements, can be analyzed together. However, in practice the non-parametric part is often replaced by a normal or lognormal distribution.

Thirdly, measuring outcomes at multiple moments in time yields an additional level in the multilevel structure of the data (Figure 2). Although paired t-tests and repeated measures analysis of variance (RM ANOVA) can be used for two or more measurements, these techniques are often not applicable due to non-normality of the data. In some cases, the difference score between two measurements might be normally distributed, and can be used as outcome. Another limitation of t-tests, RM Figure 2. An example of the data structure of a Dupuytren dataset containing multiple levels. Note that the different levels are only presented for the MCP of the left fifth digit, to limit the size of the figure. Dig: digit; MCP: metacarpophalangeal joint; PIP: proximal interphalangeal joint; DIP: distal interpha-langeal joint.

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ANOVA, and non-parametric equivalents, is that they can only handle two levels

in the data. Generalized linear mixed-effects models provide much a more flexible statistical technique, that, at this moment, is the most suitable technique that is available to analyze data in Dupuytren research.

Aim of this thesis

It is clear that Dupuytren disease is a developing field of study, according to the increase of papers that have been published on Dupuytren disease in the last

decades.55 Despite this, there are many epidemiological and methodological aspects

left to unravel. Therefore, the general aim of this thesis is to gain more insight into prevalence, risk factors and disease course of Dupuytren disease. In addition, some considerations on the methodology are addressed.

Outline of this thesis

Part I. Prevalence and risk factors

To narrow the prevalence range of Dupuytren disease reported in the literature, a systematic review and meta-analysis on the prevalence of Dupuytren disease in the general population was done. The results are presented in Chapter 2, in which prevalence rates including prediction intervals are presented as function of age and sex. In an attempt to end the ongoing debate about the association between Dupuytren disease and diabetes mellitus, liver disease, and epilepsy, the strength and consistency of previously reported associations was studied in a systematic review and meta-analysis (Chapter 3). Furthermore, we studied the influence of sports activities with hand-held devices on the presence of Dupuytren disease, which was examined in Chapter 4. In this chapter, the results of a large cross-sectional study are reported in which the association between field-hockey playing and Dupuytren disease was determined.

Part II. Considerations on the measurement methods

As the reliability of the most frequently used outcome measure in Dupuytren research is unknown, Chapter 5 covers the inter- and intra-observer reliability of diagnosis and finger goniometry in patients with Dupuytren disease. A new measurement method is introduced as well, to determine disease progression in

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participants with mild disease: a tumorimeter. Furthermore, various PROMs are used in Dupuytren research, but it has never been investigated whether the PROMs are able to detect change in hand function as result of Dupuytren disease progression. This was determined in Chapter 6, in which the Dutch language version of the Unité Rhumatologique des Affection de la Main (URAM) was validated and its ability to assess change in hand function due to disease progression was compared to the Michigan Hand Questionnaire (MHQ).

Part III. Natural disease course of Dupuytren disease

To provide a detailed description of the long-term natural disease course of primary Dupuytren disease as function over time, the 4.5 year results of the previously described cohort study are presented in Chapter 7. In this chapter, prospectively gathered data of 258 participants with Dupuytren disease was examined to describe the natural disease course of untreated Dupuytren disease. Additionally, we tried to find risk factors for disease progression.

Chapter 8 provides a critical discussion of the findings in this thesis, and places

the results in a wider context. Next to that, future perspectives are also presented in this chapter.

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Tumor Pharmacother. 1988; 5(4): 249-251.

52. Engstrand C, Krevers B, Nylander G, Kvist J. Hand function and quality of life before and after fasciectomy for Dupuytren contracture. J Hand Surg Am. 2014; 39(7): 1333-1343.

53. Dias JJ, Braybrooke J. Dupuytren’s contracture: An audit of the outcomes of surgery. J Hand Surg Br. 2006; 31(5): 514-521.

54. Sauerland S, Lefering R, Bayer-Sandow T, Bruser P, Neugebauer EA. Fingers, hands or patients? The concept of independent observations. J Hand Surg Br. 2003; 28(2): 102-105.

55. National Center for Biotechnology Information (NCBI)[Internet]. Bethesda (MD): National Library of Medicine (US), National Center for Biotechnology Information; [1988] - [cited 2017 May 16]. Available from: https:// www.ncbi.nlm.nih.gov/pubmed?term=%22Dupuytren+Contracture%22[Mesh]

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Part I

Prevalence

and risk factors

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population of Western countries

Rosanne Lanting, MD, PhD * Dieuwke C. Broekstra, MSc * Paul M.N. Werker, MD, PhD Edwin R. van den Heuvel, PhD * These authors contributed equally to this article. Plastic and Reconstructive Surgery, 2014; 133(3), 593-603

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2

ABSTRACT Background

Dupuytren disease is a fibroproliferative disease of the palmar fascia of the hand. Its prevalence has been the subject of several reviews; however an accurate description of the prevalence range in the general population - and of the relation between age and Dupuytren disease - is lacking.

Methods

Embase and PubMed were searched using database-specific Medical Subject Headings; titles and abstracts were searched for the words “Dupuytren”, “incidence”, and “prevalence”. Two reviewers independently assessed the articles using inclusion and exclusion criteria, and rated the included studies with a quality assessment instrument. In a meta-analysis the median prevalence, as function of age by sex, was estimated, accompanied with 95% prediction intervals. The observed heterogeneity in prevalence was investigated with respect to the quality of the study.

Results

Twenty-three of 199 unique identified papers were included. The number of participants ranged from 37 to 97,537, aging 18 – 100 years. Prevalence varied from 0.6 – 31.6%. The quality of studies differed, but could not explain the heterogeneity between studies. The median prevalence was estimated at 12%, 21%, and 29% at ages 55, 65, and 75 respectively, based on the relationship between age and prevalence determined from 10 studies.

Conclusions

We describe a prevalence range of Dupuytren disease in the general population of Western countries. The relationship between age and prevalence of Dupuytren disease is given according to sex, including 95% prediction intervals. Hereby, it is possible to determine the prevalence at a certain age for the total general population, and for men and women separately.

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INTRODUCTION

Dupuytren disease is a fibroproliferative disease that affects the palmar fascia of the hand. This results in the development of nodules and cords, which eventually may contract and give rise to flexion contractures of the affected fingers.

The origin of Dupuytren disease has been attributed to both genetic and environmental factors. The results of several family studies – and, more specific,

twin studies – suggested that Dupuytren disease has a strong genetic component.1-3 In

2011, Dolmans et al.4 performed a genome-wide association study in which 9 genes

that are associated with Dupuytren disease were identified. Some environmental risk factors include excessive alcohol consumption, smoking, manual work and

hand trauma.5,6 In addition, several diseases, such as diabetes mellitus and epilepsy,

are thought to play a role in the etiology of Dupuytren disease.7-9 However, the role

of these risk factors and diseases is not fully elucidated, and the results of different studies are occasionally conflicting.

Many articles about the prevalence of Dupuytren disease have been published.10-15

In these articles there is a wide range of prevalence rates, varying from 0.2% to 56%,16,17as reported in a previous literature review.18 This wide range, in our opinion,

may at least partly be caused by the great heterogeneity between study populations, such as healthy populations, participants with certain risk factors as well as patients with specific diseases. Suboptimal design of the included studies may also be a reason for the wide range.

Until now, no systematic review was conducted to scrutinize the prevalence rates specifically in the general population, i.e. a healthy non-hospital population. It is

assumed that life expectancy will increase considerably in the coming decades,19

and from our clinical experience we know that Dupuytren disease is a chronic disease of the elderly. Therefore, it will be important to enhance our knowledge about prevalence rates in the general population, and to be aware of changes in the prevalence across age. Furthermore, new treatment options have emerged, such as radiotherapy, percutaneous needle fasciotomy, and collagenase injection, and prevalence rates may be used to evaluate their cost effectiveness.

The aim of this study was to specify the prevalence range of Dupuytren disease in the general population, i.e. a healthy nonhospital population. This was done by reviewing the literature on prevalence of Dupuytren disease systematically,

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2

combined with a quality assessment of the included studies. A secondary goal was

to perform a meta-analysis on the relation between age and prevalence of Dupuytren disease.

METHODS

Literature search

Our final literature search was performed on May 9, 2012, in the bibliographical databases PubMed and Embase, because earlier searches also in the Web of Science and Cochrane Library databases had not retrieved any additional results. PubMed was searched with the search strategy: (“Dupuytren Contracture”[Mesh] OR dupuytren*[TIAB]) AND (“Prevalence”[Mesh] OR prevalen*[TIAB] OR “Incidence”[Mesh] OR “incidence”[TIAB]). In Embase, the following search strategy was imputed: dupuytren*:ab,ti AND (‘prevalence’/exp OR prevalen*:ab,ti OR ‘incidence’/exp OR ‘incidence’:ab,ti) NOT [medline]/lim AND [embase]/lim. The search was updated on January 24, 2013, and was supplemented by automatically weekly derived updates from PubMed until August 4, 2013. No limits were implemented in our search queries.

Assessment of relevant studies

Two authors independently assessed the studies in three rounds, based on predefined criteria (Table 1), and Cohen’s kappa was calculated for each round. If in the first round the inclusion or exclusion criteria could not be assessed from the title and abstract, a full-text analysis was performed. After each round, discrepancies were discussed to reach consensus. The third author was consulted if no consensus could be reached.

Quality assessment of included studies

We used the scoring instrument of Cho and Bero20 to assess the quality of the

studies, based on a review article on quality assessment tools for epidemiologic

studies.21 The instrument consists of 24 questions about study design, participants,

methods to control bias, statistical analyses, reporting of results, and the conclusions drawn from the results.

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Table 1. Criteria for inclusion and exclusion. Round 1. Title and abstract

Inclusion criteria:

- DD as research theme - General population as sample

Exclusion criteria:

- Case report - Case series - Review article - Subjects aged <18 years Round 2. First full-text assessment

Inclusion criteria:

- Prevalence of DD as research theme

Exclusion criteria:

- Age is not reported

- Physical examination to diagnose DD was not performed or not reported - Full text is not available

Round 3. Second full-text assessment

Inclusion criteria:

- Prevalence is calculated

- Data is provided to calculate prevalence

Exclusion criteria:

- Unclear how DD is diagnosed

- Outcome is ‘Dupuytren Contracture’, not further specified - Incidence was reported instead of prevalence

DD: Dupuytren disease.

“Yes”, “Partial”, “No”, and “Not applicable”, in order to obtain an overall quality score for each article. This was done for each question except for the question on study design; in that case 1 to 5 points were given (1 for case reports, 2 for time series or uncontrolled experiments, 3 for cohort or case-control studies, 4 for

non-randomized controlled trials, and 5 for non-randomized controlled trials).20 Total points

awarded for the 24 questions were divided by the total possible points (the sum of the maximum points for each item, excluding “Not applicable” items) to generate a

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2

All papers that were included after the second full text round were scored with

this instrument by the two authors independently. The article by Lanting et al.22 was

evaluated by DCB and an independent clinical epidemiologist to avoid a conflict of interest.

Data extraction and statistical analysis

In a statistical analysis, we combined studies that provided information on prevalence and sample sizes for different age categories in a total population, or in men and women separately. The aim of this meta-analysis was to determine a population-averaged relationship between age and Dupuytren disease, and to study possible heterogeneity in this relationship between studies. The midpoints of the age categories were used in a generalized linear mixed model. The form of the age-prevalence relationship was selected equal to an asymmetric logistic function with a random intercept for study to address possible heterogeneity. This model was applied to the data of men and women simultaneously with a random intercept for men and women that was correlated. A simpler model with only one random intercept was applied to the totals of men and women, since some studies did not provide data separately by sex. From the estimated models and the random effects, a range of age based predicted prevalences were estimated (i.e. 95% prediction intervals). Additionally, in case heterogeneity was present, it was investigated whether the overall quality score, the quality of study design or geographical location affects the heterogeneity.

In some of the studies, the prevalence was determined in patients with a specific disease, and in a control group. If that was the case, only the data from the control group were used. The calculation of the exact 95% confidence intervals for the

overall proportion of Dupuytren disease was calculated using the F-distribution.23

RESULTS

Results of literature search and assessment of relevant studies

The search resulted in 212 papers. After excluding duplicates and critical appraisal of the studies by predefined criteria (Table 1), 23 studies were included (Figure 1). Two main reasons led to exclusion: first, the prevalence of Dupuytren disease was not determined, and second, the study population was not a general population.

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As a consequence also all non-English papers were excluded. To quantify the decisions in the selection process, we calculated a Cohen’s kappa for each round of assessment; title and abstract (κ = 0.623, p < 0.001); full text round 1 (κ = 0.449, p = 0.001); and full text round 2 (κ = 0.528, p = 0.001).

As shown in Table 2, papers were published between 1972 and 2013. In some

studies, only data from the control group were used (noted as CG in Table 2).13,24-33

Several times, these control groups were chosen from a population that sustained

hand pathology.25,29,30 In two studies, it was explicitly noted that the control group

did not suffer from hand pathology.31,34

The total number of participants in the included studies ranged from 37 to 97,537,

and in seven of these studies only men participated.28,33,35-39 Age ranged from 18 to

100 years, with an average above 50 years in 12 studies. In six studies age was only reported in categories, without absolute number of participants in each category, so

it was not possible to calculate a mean age (CAT in Table 2).24,29,34,39-41

The lowest prevalence found was 0.6% compared with 31.6% as highest prevalence

over all age groups.12,32 In two studies, Dupuytren disease was diagnosed in a

different fashion compared with the other studies. Descatha et al. did not include palmar thickening as sign of Dupuytren disease, and Lucas et al. excluded the

thumb from examination.37,38 The quality score is depicted in the last column of

Table 2, this score ranged from 0.23 to 0.80. Results of quality assessment

Table 3 shows in detail the results of the quality assessment per question, and Table 4 shows the score on the different questions per study. Question 2 is an open question which does not contribute to the final score.

The majority of studies reported the study question only partially. In 13% of the papers, the inclusion and exclusion criteria were completely explained, while in 61% these criteria were not depicted at all. In almost 80% of the studies, the subjects were not randomly selected from the target population, or this was not reported.

Only one of the 23 studies reported a sample size justification.22 Regarding the

statistical analyses, almost a quarter of the papers did not report which analyses were performed, and in only 52%, the performed analyses were fully appropriate to answer the research question. The effect of confounders was most frequently corrected in the statistical analyses, and not beforehand in the study design.

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2

Figure 1. Flow-chart of the study selection procedure.

In 70%, the conclusion of the study was fully supported by the findings. However,

in one study the results point to a contrary conclusion than that reported.29

Explorative analysis

The generalized linear mixed model indicated substantial heterogeneity between studies, meaning that prevalence varies between studies. It was explored whether the overall quality score and the subscore on methodology (questions 1, 4, 7-9,

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T able 2. Details of included studies . Stud y P opulation N Sex A ge Pre valence Quality Mean SD Rang e [95%CI] Arafa (1984) 24 P atients of fracture clinic (CG) 555 F+M C AT 16.0 [13.1 ; 19.4] 0.46 Ardic (2003) 25 Non-diabetic patients of de

pt. medicine and rehabilitation

(di vision rheumatolog y) (CG) 37 F+M 55.7 11.5 30-79 2.7 [1.0 ; 14.2] 0.44 Attali (1987) 26 P atients of gastroenterolog

y unit without alcoholism or

chronic li ver disease (CG) 174 F+M 58.9 22.7 12.5 [8.1 ; 18.5] 0.49 A ydeniz (2008) 27 Non-diabetic patients of

public health clinic (CG)

101 F+M 60.1 7.6 4.0 [1.1 ; 9.8] 0.51 Bennett (1982) 28 W orkers PV C man

ufacturing plant not in

volv ed with bagging or packing (CG) 84 M 40.1 1.19 [0.0 ; 6.5] 0.46 Burke (2007) 35

Miners seeking compensation for Hand-Ar

m V ibration Syndrome 97537 M 53.5 8.13 [8.0 ; 8.30] 0.62 Carson (1993) 36 Ex-militar y ser

vice pensioners in the R

oy al Hospital Chelsea 400 M 75.9 65-99 13.8 [10.5 ; 17.5] 0.38 Deg reef (2010) 12 V isitors of markets in Flanders , Belgium 500 F+M 70.4 50-100 31.6 [27.5 ; 35.9] 0.46 Descatha (2012) 37 Emplo yees in pri vate sector in P ays de la Loire , F rance 2161 M 38.5 20-59 1.25 [0.8 ; 1.8] 0.66 Eadington (1989) 13 Nor motensi ve , non-diabetic subjects

, selected from

in-patients

, outpatients and hospital staff

members (CG) 150 F+M 51.2 17.4 18.0 [12.2 ; 25.1] 0.64 Finsen (2002) 40 R esidents of r ural m unicipalities in Norw ay 456 F+M C AT 50-80+ 7.5 [5.05 ; 9.87] 0.51 Gudm undsson (2000) 15 R esidents of R eykja

vik and adjacent comm

unes , Iceland 2165 F+M 57.5 45-94 13.3 [11.9 ; 14. 8] 0.56

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2

T able 2 (continued). Details of included studies . Stud y P opulation N Sex A ge Pre valence Quality Mean SD Rang e [95% CI] Lanting (2013) 22 R esidents of Groning

en, The Netherlands

763 F+M 62 * 56-69 (IQR) 22.1 [19.3 ; 25.3] 0.80 Lenno x (1993) 34 P atients on g eriatric w

ard, not admitted for hand

patholog y 200 F+M C AT 30.0 [23.7 ; 36.9] 0.37 Lucas (2008) 38 Ci vil ser vants of P

ays de la Loire and Brittany

, F rance 2406 M 45.3 7.6 8.8 [7.7 ; 10.0] 0.64 Mikkelsen (1972) 42 R esidents of Haug esund, Norw ay 15950 F+M 45.0 16-99 5.6 [5.3 ; 6.0] 0.46 Noble (1992) 9 P atients of fracture clinic (CG) 100 F+M C AT 8.0 [3.5 ; 15.2] 0.36 Noble (1984) 30 P atients of fracture clinic (CG) 150 F+M 57.4 18.0 [12.2 ; 25.1] 0.28 P al (1987) 31

Non-diabetic subjects without m

usculoskeletal complaints (CG) 75 F+M 44.0 * 18-76 9.0 [3.8 ; 18.3] 0.49 Rafter (1980) 39

Inpatients in acute medical and surgical w

ards 403 M C AT 17.1 [13.6 ; 21.2] 0.23 Ra vid (1977) 32 Non-diabetic patients of different de par tments of medicine (CG) 1396 F+M 52.0 19-86 0.6 [0.3 ; 1.2] 0.49 Thomas (1992) 33 P atients admitted to g eneral surgical w ard (CG) 150 M 64.1 50-85 10.7 [6.2 ; 16.7] 0.46 Zerajic (2004) 41 V isitors of

public places in both urban and r

ural areas of Bosnia Herzego vina 1207 F+M C AT 25.4 [23.0 ; 28.0] 0.59 N: n umber of par ticipants; SD: standard de

viation; CI: confidence inter

val; F: female; M: male; IQR: inter

quar tile rang e; CG: Control g roup; CA T : ag e re por

ted in categories; * medians

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Table 3. Quality assessment of included studies per question.

Question n Yes (%) n Partial (%) n No (%) n NA (%)

1 Study design †

2 What was the study question? ‡ 3 Was the study question sufficiently

described?

5 (22%) 15 (65%) 3 (13%) 0 (0%)

4 Was the study design appropriate to answer the study question?

21 (91%) 2 (9%) 0 (0%) 0 (0%)

5 Were both inclusion and exclusion criteria specified?

3 (13%) 6 (26%) 14 (61%) 0 (0%)

6 For case studies only: Were patient characteristics adequately reported?*

0 (0%) 0 (0%) 0 (0%) 23 (100%)

7 Were subjects appropriate to the study question?

19 (83%) 4 (17%) 0 (0%) 0 (0%)

8 Were control subjects appropriate? 12 (52%) 6 (26%) 5 (22%) 0 (0%)

9 Were subjects randomly selected from the target population?

5 (22%) 0 (0%) 18 (78%) 0 (0%)

10 If subjects were randomly selected, was the method of random selection sufficiently well described?

1 (4%) 1 (4%) 3 (13%) 18 (78%)

11 If subjects were randomly allocated to treatment groups, was method of random allocation sufficiently described?**

0 (0%) 0 (0%) 0 (0%) 23 (100%)

12 If blinding of investigators was possible, was it reported?**

0 (0%) 0 (0%) 0 (0%) 23 (100%)

13 If blinding of subjects to intervention was possible, was it reported?**

(0%) 0 (0%) 0 (0%) 23 (100%)

14 Was measurement bias accounted for by other methods than blinding?

6 (26%) 11 (48%) 6 (26%) 0 (0%)

15 Were known confounders accounted for by study design?

5 (22%) 3 (13%) 13 (57%) 2 (9%)

16 Were known confounders accounted for by analysis?

9 (39%) 5 (22%) 7 (30%) 2 (9%)

17 Was there a sample size justification before the study?

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2

Table 3 (continued). Quality assessment of included studies per question.

Question n Yes (%) n Partial (%) n No (%) n NA (%)

18 Were post hoc power calculations or confidence intervals reported for statistical non significant results?

4 (17%) 4 (17%) 15 (65%) 0 (0%)

19 Were statistical analyses appropriate? 12 (52%) 5 (22%) 6 (26%) 0 (0%)

20 Were the statistical tests stated? 6 (26%) 12 (52%) 5 (22%) 0 (0%)

21 Were exact values or confidence intervals reported for each test?

5 (22%) 13 (57%) 5 (22%) 0 (0%)

22 Were attrition of subjects and reason for attrition recorded?

4 (17%) 3 (13%) 16 (70%) 0 (0%)

23 For those subjects who completed the study; were results completely reported?

15 (65%) 7 (30%) 1 (4%) 0 (0%)

24 Do the findings support the conclusions?

16 (70%) 6 (26%) 1 (4%) 0 (0%)

n: number of studies, NA: not applicable, † See Table 4, ‡ Open question which does not contribute to final score, * Case studies were not included, so question 6 was not applicable for each of the included articles, ** Questions were not applicable, because this concerns intervention studies.

14-17, 19 in Table 4) were related to the heterogeneity. The goal of this analysis was to check whether selecting studies on quality would narrow the prevalence range substantially. The distance of each study to the median profile in Figure 2 was plotted against the variables of interest. No clear pattern was observed for the quality scores or the subscores; both low- and high-quality studies appear on both sides of the median prevalence for all levels. This indicates that the quality of a study did not explain the variation in prevalence, so no studies were excluded for further analyses based on quality score. Furthermore, we investigated whether the heterogeneity was explained by the geographical location (i.e. whether the relative difference of a study to the median age-related prevalence fits with an order in geographical location), but no clear trend was visible. For example, the prevalence found by both

Bennett28 and Burke et al.35 was below the median age-related prevalence curve and

the prevalence found by Arafa et al.24 was above this median, whereas they all came

from the same geographical location: England. On the other hand, prevalences in the Nordic countries all seem to be below the median curve. Instead of trying to understand the influence of geographic location, we calculated, based on our

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T

able 4.

Quality assessment of

included studies per stud

y. A uthor Questions *† 1 3 4 5 7 8 9 10 14 15 16 17 18 19 20 21 22 23 24 T otal Max. points Score Arafa 24 2 0 1 0 2 1 2 0 2 2 1 0 0 0 1 1 0 2 2 19 41 0.46 Ardic 25 2 1 2 0 2 0 2 0 1 0 2 0 0 1 1 0 0 2 2 18 41 0.44 Attali 26 2 1 2 0 2 2 0 NA 0 0 2 0 0 2 1 1 0 2 2 19 39 0.49 A ydeniz 27 2 1 2 1 2 2 0 NA 2 2 0 0 0 1 1 1 0 2 1 20 39 0.51 Bennett 28 2 1 2 0 2 2 0 NA 1 0 2 0 0 1 1 0 0 2 2 18 39 0.46 Burke 35 2 2 2 0 2 2 0 NA 1 0 2 0 2 2 2 2 0 1 2 24 39 0.62 Carson 36 2 0 2 0 2 2 0 NA 1 0 1 0 0 0 0 1 0 2 2 15 39 0.38 Deg reef 12 2 1 2 2 2 2 0 NA 2 0 0 0 0 0 0 1 0 2 2 18 39 0.46 Descatha 37 2 1 2 2 2 2 2 0 1 0 2 0 2 2 1 1 1 2 2 27 41 0.66 Eadington 13 2 2 2 2 2 1 0 NA 1 1 2 0 1 2 2 1 1 2 1 25 39 0.64 Finsen 40 2 1 2 1 2 0 0 NA 0 0 1 0 1 2 2 2 2 1 1 20 39 0.51 Gudm undsson 15 3 1 2 0 2 2 2 1 1 0 2 0 1 2 1 1 0 1 1 23 41 0.56 Lanting 22 2 2 2 0 2 2 2 2 1 2 2 2 2 2 2 2 0 2 2 33 41 0.80 Lenno x 34 2 1 2 0 1 0 0 NA 1 NA NA 0 0 1 1 1 0 1 2 13 37 0.37 Lucas 38 2 1 2 1 1 2 0 NA 1 0 2 0 2 2 2 2 1 2 2 25 39 0.64 Mikkelsen 42 2 1 2 1 2 0 0 NA 2 NA NA 0 0 0 0 0 2 2 2 16 35 0.46 Noble 9 2 0 2 0 2 1 0 NA 0 2 0 0 0 0 0 1 0 0 1 11 39 0.28 Noble 30 2 1 2 0 1 1 0 NA 0 1 0 0 0 2 1 1 0 2 0 14 39 0.36 Pa l 31 2 2 2 1 2 2 0 NA 2 0 0 0 0 1 1 1 2 1 0 19 39 0.49 Rafter 39 2 1 1 0 1 2 0 NA 0 0 0 0 0 0 0 0 0 1 1 9 39 0.23 Ra vid 32 2 2 2 0 2 1 0 NA 0 2 1 0 0 2 1 0 0 0 0 19 39 0.49

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2

T

able 4 (continued).

Quality assessment of

included studies per stud

y. A uthor Questions *† 1 2 4 5 7 8 9 10 14 15 16 17 18 19 20 21 22 23 24 T otal Max. points Score Thomas 33 2 1 2 0 2 1 0 NA 1 0 1 0 0 2 1 2 0 1 2 18 39 0.46 Zerajic 41 2 1 2 1 2 0 0 NA 2 1 0 0 1 2 2 1 2 2 2 23 39 0.59 * Questio n 2 is not presented in this table , since it w as an open question. Questions 6, 11, 12, and 13 are not presented, since these questions w ere

not applicable for the included studies (applicable for case studies or inter

vention studies). † Questions: 1: Stud y design, 2: R esearch question, 3: Stud y question sufficientl y described, 4: Stud

y design appropriate to ans

w er stud y question, 5: Inclusio n and e xclusion criteria spe cified, 6: Case studies: patient charac teristics adequatel y re por ted, 7: Subjects appropriate to stud y ques -tion, 8: Control subjects appropriate , 9: Random selection of subjects , 10 : Method of random selection sufficientl y w ell described, 11 : Random allocation to treatment group sufficientl y described, 12 : Blinding of in vestigators to inter vention re por ted, 13 : Blinding of subjects to inter vention re por ted, 14

: Measurement bias accounted

for by methods other than blindin g, 15 : Kno wn confounders accounted for by stud y design, 16 : Kno wn confounders accounted for by anal ysis , 17 : Sample size justification, 18 : P ost hoc po w er calculations or confidence inter vals re por ted for statisti -call y non significan t results , 19 : Appro priate statistical anal yses , 20 : Statement of statistical tests , 21 : Exact v alues of confidence inter vals re por ted

for each test,

22

: R

epor

ting of

attrition of

subject and reason for attrition,

23

: R

esults completel

y re

por

ted for subjects who completed the stud

y, 24 : Findings suppor t the conclusion. Question 1 w as scored 3 (cohor

t design) or 2 (cross-sectional design), other questions w

ere scored 2 (y es), 1 (par tial), 0 (no), N A (not applicable). The score w as calculated by di

viding the total points by the maxim

um possible points

. A higher score re

presents a higher quality

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model, 95% prediction limits (the outer limits in Figure 2). These limits indicate the range of expected true age-related prevalence of Dupuytren disease in observed and unobserved geographical locations in Western countries.

Relation between age and prevalence of Dupuytren disease

A combined analysis of 10 studies12,15,22,24,29,30,34,40-42 representing information on

prevalences in different age groups showed an overall relationship that is visualized in the upper graph of Figure 2. In the center and lower graphs of Figure 2, this

relationship is shown respectively for women (8 studies12,15,22,24,34,40-42) and men (11

studies.12,15,22,24,28,34,35,37,40-42 The prevalence is shown, as well as the 95% confidence

intervals (inner dotted lines), taking into account the heterogeneity between studies. Furthermore, a 95% prediction interval is presented (outer dashed lines), which makes it possible to predict the prevalence at a certain age in a healthy nonhospital population. For instance, the overall prevalence of Dupuytren disease is estimated 12% at 55 years, and 29% at an age of 75 years. The prediction band can be used to estimate the a priori prevalence in a random sample at different ages and geographical locations. Clearly, the prevalence increases with rising age. Furthermore, the graphs show that the prevalence of Dupuytren disease is higher in men than in women. In addition, the age of onset is lower in men compared with the age of onset in women.

Investigating the goodness of fit of the estimated models, the R2 was calculated

between the observed numbers of Dupuytren disease, and the predicted numbers

of Dupuytren disease from the model. For men, the R2 was estimated at 99.5%,

for women the R2 was equal to 93.0% and for men and women together the R2 was

97.5%, which demonstrates a good fit of the generalized linear mixed model. This indicates that the models in Figure 2 are able to predict new observations with high

certainty.The high goodness of fit may not seem in line with the observed outliers

outside the prediction limits in Figure 2. However, several of these outliers were based on small number of subjects (Table 5). For instance, when only one subject is observed in an age category, the prevalence can only be estimated at either 100% or 0% depending on the outcome of Dupuytren disease. The prediction intervals hold true for relative large sample sizes.

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2

Figure 2. Relationship between age and Dupuytren prevalence, presented for totals, and men and women separately. Dotted lines: 95% confidence interval. Dashed lines: 95% prediction interval.

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DISCUSSION

Dupuytren disease is a hand disorder that is often progressive and eventually can cause contractures of the affected fingers. The reported prevalence rates of Dupuytren disease vary widely in the literature. Therefore, the primary goal of this systematic review was to come to a more accurate distribution of the prevalence of Dupuytren disease in the general population. A secondary goal was to perform a meta-analysis on the relation between prevalence of Dupuytren disease and age.

To our knowledge, this systematic review is the first of its kind. First, it focuses on prevalence rates specifically in the general population of Western countries (i.e. a healthy nonhospital population), excluding specific patient groups. Second, the quality of the studies was critically assessed. Previous reviews about prevalence of

Dupuytren disease concern different kinds of populations, such as manual workers,43

rock climbers,44,45 and a mixture of healthy participants and patients with a specific

disease.18 Furthermore, geographical location was studied and we performed a

thorough meta-analysis on the relationship between age and Dupuytren disease. Our English search strategy was performed in English databases, so we might have missed relevant papers in foreign languages. However, despite this limitation, several papers in foreign languages, such as German, French and Italian, entered the full text analysis. The Cohen’s kappa for each round of assessment was moderate, emphasizing the necessity of discussing the assessment with multiple authors.

After the full text analysis, 23 studies were included, with the number of participants ranging from 37 to 97,537 in the age of 18 to 100 years. Prevalence in these studies

varied from 0.6% to 31.6%, which is a smaller range than previously published.18

During the quality assessment we came across a number of noteworthy points. First, only few studies reported that they applied sampling to select their

participants.15,22,24,25,37 However, three of these studies did not describe the method

of sampling.24,25,37 If participants are not randomly selected the risk of selection

bias increases, which makes it difficult to extrapolate data from these studies.

Second, only one study reported a sample size justification.22 In an observational

study, the accuracy of the estimates (i.e. the prevalence) depends on sample size.46

If a sample size is not calculated beforehand, the results of the study might be less precise than intended. Finally, in only a quarter of the studies the statistical tests were fully stated, and in 52% the analyses were completely appropriate. To enlarge

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2

Table 5. Studies outside prediction intervals.

Population Age Author n DD/n Total % DD 95% PI

Totals <30 Arafa24 1/34 2.94 0.02 – 0.61 30-34 Mikkelsen42 1/1043 0.10 0.12 – 2.89 30-39 Arafa24 4/47 8.51 0.18 – 4.38 30-39 Noble30 1/5 20 0.18 – 4.38 50-59 Finsen40 2/103 1.94 2.53 – 27.46 61-65 Degreef12 32/86 37.21 5.25 – 37.20 75-79 Zerajic41 43/72 59.72 12.26 – 49.43 76-80 Lanting22 30/57 52.63 12.84 – 50.15 >80 Finsen40 0/24 0 16.76 – 54.41 95-99 Mikkelsen42 0/3 0 24.32 – 60.98 Men <30 Descatha37 0/491 0 0.06 – 4.22 55-64 Bennett28 0/9 0 2.84 – 42.03 75-79 Zerajic41 30/40 75 7.60 – 53.80 76-80 Lanting22 18/24 75 7.95 – 54.34 >80 Finsen40 0/7 0 10.38 – 57.52 80+ Zerajic41 24/40 60 9.41 – 56.35 81-85 Lanting22 8/14 57.14 9.80 – 56.83 >90 Lennox34 4/6 66.67 14.52 – 61.62 90-94 Mikkelsen42 1/1 100† 13.45 – 60.68 95-99 Burke35 0/1 0 15.60 – 62.53 95-99 Mikkelsen42 0/1 0 15.60 – 62.53 Women 81-85 Lanting22 8/17 47.06 0.25 – 46.83

n DD: participants with Dupuytren disease; n total: total participants; % DD: percentage of participants with Dupuytren disease; 95% PI: 95% prediction interval.

† Outlier not visible in Figure 2 (Y-axis ranges from 0 - 80%).

the reproducibility of the results, it is essential that such information is properly documented. More importantly, to ensure that correct conclusions will be drawn, it is crucial that appropriate analyses are performed.

To narrow the prevalence range, we intended to select studies for further analysis, based on their quality. The final overall quality score differed from 0.23 to 0.80. However, in the explorative analysis, no relation was found between this quality score and the reported prevalence. This is in accordance with the findings in a meta-analysis in which the meta-odds ratio for manual work and vibration exposure of all

(41)

studies was similar to the meta-odds ratio of only high quality studies.43

Several papers have been published about the difficulties using an overall score to

assess the quality of a study.47-49 With an overall quality score it is hard to discriminate

between poor reporting and poor methodology of the study. Thus, it is advised

to evaluate papers based on key components rather than an overall score.21,48,50

Therefore, we analyzed the relation between a high score on methodology and the prevalence of Dupuytren disease. Still, no link was found, so we assumed that the current spread in prevalence was not based on a difference in quality of the studies, but on heterogeneity of the study populations.

We aimed to include studies with participants from a general population. However, we ended with studies that did not provide information about race and that originated mainly from Europe. Nonetheless, the biogeographic regions in Europe differ from Arctic to Mediterranean. Based on our model, we suppose that the prevalence in different geographical locations lies within the prediction interval of Figure 2, but more thorough analyses with additional variables are necessary to clarify and understand the geographic influence on the prevalence of Dupuytren disease.

As mentioned in the results, two studies diagnosed Dupuytren disease differently

than other studies.37,38 Although this did not change our prevalence range substantially,

differences in diagnosing Dupuytren disease complicate the comparison of results. Preferably, all stages of Dupuytren disease in all rays are taken into account, for

example by using the classification of Iselin51 or Tubiana.52 Furthermore, there were

differences in reporting age; 6 studies reported age in categories, without giving the

actual range.24,29,34,39-41 The discrepancies in reporting age also impede comparison

of prevalence rates of different studies. Fortunately, we have been able to use data of different age categories in our meta-analysis.

It is well recognized that prevalence of Dupuytren disease increases with rising age. However, until now, a thorough analysis on this relationship was lacking. In our meta-analysis, we investigated this relationship by using all studies that provided information on prevalence in different age categories. We presented the relationship between age and Dupuytren disease, including 95% confidence intervals and 95% prediction intervals. The graphs can be used to determine a common estimate for the prevalence of Dupuytren disease at different ages, both for the total population

(42)

2

as well as for men and women separately. Nowadays, still little is known about the

prevalence of Dupuytren disease in younger people, since in most studies an age over 50 years was one of the inclusion criteria. However, the relationship between age and prevalence presented in this paper already provides a first indication for prevalence at younger age.

CONCLUSION

The prevalence of Dupuytren disease in the general population of Western countries ranges from 0.6 to 31.6%. With the results of our meta-analysis, we have been able to present the relationship between prevalence of Dupuytren disease and age, including confidence intervals and prediction intervals. With the presented graphs it is possible to determine the prevalence at a certain age for the total general population of western countries, and for men and women separately.

ACKNOWLEDGEMENT

The authors would like to thank Professor P.U. Dijkstra, PhD for performing the quality assessment of the study in which some of the authors participated.

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