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Epidemiology
Protocol
Concordance of shoulder symptoms and imaging findings: a protocol for the Finnish Imaging of Shoulder (FIMAGE) study
  1. Thomas Ibounig1,2,
  2. Rachelle Buchbinder3,
  3. Niko Sillanpää2,4,
  4. Lasse Rämö1,2,
  5. Pirjo Toivonen2,
  6. Saara Raatikainen1,2,
  7. Seppo Koskinen5,
  8. Tommi Härkänen5,
  9. Harri Rissanen5,
  10. Tomasz Czuba6,
  11. Mika Paavola1,
  12. Teppo Jarvinen1,2,
  13. Simo Taimela1,2
  14. for the FIMAGE investigators
    1. 1Department of Orthopaedics and Traumatology, Helsinki University Central Hospital, Helsinki, Finland
    2. 2Finnish Centre for Evidence-Based Orthopaedics, University of Helsinki, Helsinki, Finland
    3. 3Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
    4. 4Tampere University Hospital, Tampere, Finland
    5. 5Population Health, National Institute for Health and Welfare, Helsinki, Finland
    6. 6Department of Molecular and Clinical Medicine, University of Gothenburg, Goteborg, Sweden
    1. Correspondence to Dr Thomas Ibounig; thomas.ibounig{at}helsinki.fi

    Abstract

    Introduction Shoulder pain is a substantial medical and socioeconomic problem in most societies, affecting the ability to work or carry out leisure time activities as well as subsequently influencing physical and psychological well-being. According to a nationwide survey in Finland, 27% of the population reported shoulder pain within the last 30 days. In clinical practice, imaging findings of structural abnormalities are typically thought to explain symptoms, even though such findings are also prevalent in asymptomatic individuals, particularly with increasing age. Overall, there is a paucity of high-quality evidence on the prevalence, clinical relevance and prognosis of ‘abnormal’ imaging findings of the shoulder.

    The aim of the Finnish Imaging of Shoulder (FIMAGE) study is fourfold: to assess (1) the prevalence of shoulder symptoms and the most common anatomical variants and imaging abnormalities of the shoulder; (2) the concordance between shoulder symptoms, function and imaging abnormalities; (3) the most important determinants of symptoms, function and imaging abnormalities; and (4) the course of shoulder complaints over 5 years.

    Methods The FIMAGE target population of 600 participants, aged 40–75 years, will be randomly selected from a nationally representative general population sample of 9922 individuals originally recruited for the Finnish Health 2000 Survey. On giving informed consent, the participants will be invited to a clinical visit that includes assessment of general health, shoulder symptoms, bilateral shoulder examination and imaging of both shoulders with plain radiography and MRI.

    Ethics and dissemination The study has been approved by the Institutional Review Board of the Helsinki and Uusimaa Hospital District. The findings will be published according to the Strengthening the Reporting of Observational Studies in Epidemiology criteria.

    Trial registration number NCT05641415.

    • Shoulder
    • RADIOLOGY & IMAGING
    • EPIDEMIOLOGIC STUDIES
    http://creativecommons.org/licenses/by-nc/4.0/

    This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

    https://doi.org/10.1136/bmjopen-2023-074457

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      STRENGTHS AND LIMITATIONS OF THIS STUDY

      • A large general population sample to assess the prevalence of abnormal shoulder imaging findings and their concordance with shoulder symptoms.

      • Data on background variables from the year 2000 will enable a prospective analysis of possible determinants of shoulder symptoms and imaging findings.

      • Use of state-of-the-art shoulder imaging technology (plain radiography and 3.0T MRI).

      • Our study population is limited to individuals aged 40–75 years and the study results may not be generalisable to other age groups.

      Introduction

      Background and rationale

      Musculoskeletal disorders are the leading cause of chronic impairment and permanent working disability in adults, putting an enormous burden on our health and social security systems.1 2 The shoulder is the third most commonly affected site with 27% of the Finnish population reporting pain in the previous month.3 Shoulder complaints are also the third most common musculoskeletal presentation in general practice after back and neck complaints,4 5 and are among the most common musculoskeletal causes of work absence.6 While the natural history of shoulder complaints varies and is often self-limiting, up to 50% of people presenting for care, particularly the elderly, might have persisting symptoms after 12 months of follow-up.7–9

      The origin of pain in degenerative musculoskeletal conditions is commonly attributed to imaging abnormalities. However, recent evidence has cast doubt on this reasoning, as imaging studies in other sites such as the lumbar spine and knee show a high prevalence of structural abnormalities even in asymptomatic individuals.10–14 The prevalence of full-thickness rotator cuff tears and radiographic signs of shoulder osteoarthritis (OA) in middle-aged and elderly populations has been reported to range from 17% to 22%.15–18 However, the validity of these estimates is open to question due to the imaging modalities used in these studies as well as the representativeness of their study participants to the general population. As well, mental health has been found to have a stronger association with symptoms than structural abnormalities.19

      Precise valid age-specific prevalence estimates of shoulder imaging abnormalities in the general population, and an understanding of their connection with symptoms, are needed to optimally interpret shoulder imaging findings in patients who present for care with shoulder pain.20

      Aims and objectives

      Finnish Imaging of Shoulder (FIMAGE) is a population-based, longitudinal, observational study aiming to improve our understanding of the aetiology, epidemiology and diagnostic utility of imaging of shoulder complaints (table 1).

      View this table:
      Table 1

      Overview of the FIMAGE study and its most important subprojects

      The four main objectives of the FIMAGE study are to:

      1. Determine the prevalence of shoulder symptoms, anatomical variants and imaging abnormalities of the shoulder in the general population aged 40–75 years.

      2. Determine the concordance between shoulder symptoms, function and imaging abnormalities.

      3. Explore the determinants of shoulder symptoms, function and imaging abnormalities.

      4. Investigate the course of shoulder complaints at a 5-year follow-up.

      Methods and analysis

      Overview of study design

      Participants for this observational study will be drawn from the sample of a nationwide, population-based health survey performed in Finland from August 2000 to June 2001 (Health 2000 Survey).21 The Health 2000 Survey is one of the most comprehensive nationwide health surveys with well-refined study protocols and a high participation rate. The survey consisted of several questionnaires, an extensive interview, laboratory and functional capacity tests and a clinical examination. A nationally representative two-stage stratified cluster sample was drawn by stratifying Finland into 20 strata consisting of the 15 biggest cities and five university hospital districts. A total of 9922 persons aged 18 years or older were sampled from these clusters.3 Most of them took part in the follow-up survey 11 years later (Health 2011 Survey).

      This protocol has been written according to the ‘Strengthening The Reporting of OBservational Studies in Epidemiology’ guidelines22 where applicable; the checklist is available as online supplemental table 1.

      Study settings and participant selection

      For the FIMAGE study, we will recruit a random, population-based subsample of Health 2000 Survey participants. To be included in the study, participants have to be ambulatory, aged between 40 and 75 years, capable of communicating in Finnish or Swedish and be participants in the Health 2000 Survey. In total, 2368 participants fulfilled these criteria on 1 December 2022, and will serve as the baseline for our random subsample of 600 participants. Participants with dementia, terminal cancer, previous shoulder replacement surgery and contraindications to MRI will be excluded.

      The random sampling process will be performed using the SAS/STAT software v9.4 M7 (SAS Institute, Cary, North Carolina, USA) developed for statistical analysis of variance and predictive modelling. For feasibility reasons, that is, availability of 3T MRI, we will only recruit participants living within a reasonable travelling distance of the five university hospitals and not the whole of Finland. The distribution of the Finnish population can be seen in figure 1, showing that most of the Finnish population lives in the proximity of the five university hospitals. The recruitment areas do include rural areas in addition to metropolitan areas.

      Figure 1
      Figure 1

      Map showing the distribution of the Finnish population and the location of our recruitment centres. We will recruit participants living within a reasonable travelling distance of the five university hospitals. The marked areas represent where one-fourth of the population lives in Finland with the majority living in the southern part.

      Informed consent

      At the research visit, we will provide participants with detailed written and oral information about the study and ask them to sign a written consent form. Withdrawal from the study is possible at any time, in accordance with the latest version of the Declaration of Helsinki.23

      Data collection and case definitions

      Our data collection is based on methods developed and validated for the Health 2000 and Health 2011 Surveys, as it ensures reliable data and provides a unique opportunity to implement a prospective design for investigating possible determinants of shoulder symptoms and imaging findings, including general health parameters and work-related exposures. We would then have detailed background data from two to three different time points (2000, 2011 (some of the participants) and 2023–2024).

      Recruitment

      The first contact with potential participants will be established by the Finnish Institute for Health and Welfare, which was responsible for the planning and execution of the Health 2000 and Health 2011 Surveys. The contact letter will include an information leaflet explaining the study protocol. Individuals who fail to respond will be contacted via phone by Statistics Finland to increase participation rates and minimise selection bias. We will attempt to minimise potential recruitment bias by not specifically emphasising the presence of shoulder symptoms and stressing the fact that participation is important regardless of symptom status. Study participants will be invited to a research visit, where they will undergo an extensive health interview and clinical shoulder examination. Shoulder imaging (plain radiography and MRI) of both shoulders will be taken during the same visit or scheduled for a second visit depending on the participant’s preference (figure 2).

      Figure 2
      Figure 2

      Recruitment flow chart. FIMAGE, Finnish Imaging of Shoulder Study; THL, Finnish Institute for Health and Welfare.

      Medical history

      A detailed medical history will be obtained in a face-to-face health interview. A standardised questionnaire will collect data on social background, medical history and demographic variables (figure 3). The interview will determine presence of past and present shoulder symptoms, history of shoulder trauma and general health status, including smoking, alcohol consumption, comorbidities, physical and psychosocial work exposures, overhead activities and pain elsewhere (pain at multiple body sites). General health-related quality of life will be assessed using the EuroQoL 5-Dimension 5-Level questionnaire24 and psychological well-being will be assessed using the Hospital Anxiety and Depression Scale.25

      Figure 3
      Figure 3

      Data collection and outcomes. Constant Score indicates functional shoulder assessment. Work exposures characterise physical and psychosocial. 3T MRI, 3 Tesla MRI; AC, acromioclavicular; GH, glenohumeral; PCS, Pain Catastrophizing Scale; SPADI, Shoulder Pain and Disability Index.

      Worry about shoulder pain will be assessed using a single-item question that has been used previously26: how worried have you felt about your shoulder pain in the past week? (possible responses: not this week, often, sometimes, every day). Self-reported health literacy will also be assessed using a single-item question used previously26: how often do you need to have someone help you read written instructions, pamphlets or other written material from your doctor or pharmacy? (response options: never, rarely, sometimes, often, always). Fear avoidance beliefs will be assessed using two single-item questions previously published by Wynne-Jones et al.26 Pain self-efficacy and catastrophising will be measured using short forms of the Pain Self-Efficacy Questionnaire27 and Pain Catastrophizing Scale,28 respectively.

      Shoulder-specific questionnaires

      At the clinical visit, subjects will complete several questionnaires concerning shoulder symptoms. Shoulder-specific questionnaires will include the Shoulder Pain and Disability Index (SPADI),29 30 the Constant Score (CS)31 and Subjective Shoulder Value (SSV).32 The SPADI is a self-administered questionnaire designed to measure shoulder pain and disability associated with shoulder pathology. The means of the pain and disability subscales are averaged to produce a total score ranging from 0 (best) to 100 (worst). It has been validated for different clinical settings and populations and has been widely used.33 The CS is a combined self-based and examiner-based tool divided into four subscales (pain, activities of daily living, range of motion (ROM) and strength). The higher the score, the higher is the quality of function (minimum 0, maximum 100). The SSV is a participant’s subjective shoulder assessment scored as a percentage from 0% to 100%, with 100% representing a completely normal shoulder.

      Clinical examination

      Active and passive ROM of both shoulders will be measured using an inclinometer using a standardised protocol,34 35 and isometric muscle strength of shoulder abduction, internal and external rotation will be measured using a handheld dynamometer. In addition, we will perform special shoulder tests (online supplemental table 2) following a structured assessment protocol. Similar to a previous study,36 investigators will attend a prestudy training course that includes quality control measures such as observation, feedback on examination technique and repeated and parallel measurements.

      Imaging

      Plain radiography

      Radiographic examination of both shoulders by plain radiography (three views: anterior posterior in internal and external rotations and a lateral view of the scapula) will be carried out to evaluate scapular anatomy and degenerative changes of the glenohumeral and acromioclavicular joints (online supplemental table 3). OA of the glenohumeral joint will be graded according to the Allain modification of the Samilson-Prieto classification37 and the acromioclavicular joint as described by de Abreu et al.38 The radiographs will be read independently using structured assessment forms by two musculoskeletal radiologists who will be blinded to the information gathered by history, clinical examination and MRI.

      MRI and grading of structural changes

      Bilateral MRI scans of the shoulders will be obtained with the use of a 3 Tesla scanner with a phased-array shoulder coil. The MRI scans will be read independently using structured assessment forms by two musculoskeletal radiologists who will be blinded to the information gathered by history, clinical examination and radiography findings. For cases in which the findings are not consistent, consensus will be obtained. Structures that will be evaluated will include the glenohumeral and acromioclavicular joints, subacromial-subdeltoid bursa, rotator cuff tendons and muscles, biceps tendon, scapular morphology and nerves (online supplemental table 4). Grading of imaging findings will be performed according to the procedure by Gill et al.39

      Sample size

      Given the wide range of prevalence estimates of imaging abnormalities in the published literature, we have focused instead on what precision we can achieve for such a sample size for a range of potential true prevalence values. With 600 participants, 95% CI widths would range from 2.4% units (for a prevalence of 2%) to a maximum of 8%-units (for a prevalence of 50%).

      Our recruitment target is 600 participants, which is divided into an initial sample of 200 participants and a secondary sample of 400 participants. After the first 200 participants have completed their baseline assessment, we will perform an interim analysis to assess the need to adjust the sampling probabilities of the secondary sample to sample more individuals in those subgroups where the participation rates are low. This way, the coefficient of variation of the sample weights and therefore the inefficiency will be smaller.40 We will use age, sex and other variables, which are associated with the non-response, for the comparison of the participants of the initial sample and the Health 2000 participants. If needed, we will modify the number of participants to achieve higher precision of the estimates for our main outcomes of interest, if the preliminary CIs appear to be considerably wider (accounting for the smaller number of participants in the initial sample) than those anticipated in our power analyses above. This adaptive study design will ensure that our results regarding our key study questions are sufficiently precise and valid, and it will guarantee the most economic use of our resources.41 42

      Statistical analyses

      To ensure that our sample will be representative of the Finnish population, in interim analyses, we will compare both the demographic variables and the symptom and risk factor variables collected in the Health 2000 and Health 2011 Surveys of study participants to the general Finnish population, and the Health 2000 and Health 2011 Surveys, respectively, aged 40–75 years to assess the representativeness of our participants. Important comparisons will be, for example, with respect to the non-participants, who participated in the Health 2000 or Health 2011 Survey, and with respect to the rural population, which will be under-represented in our data. If deemed necessary, we will adjust the weights of our random sampling for certain subgroups, especially age, to improve representativeness to the general population. We will also assess for potential recruitment bias by comparing shoulder symptom prevalence in study participants with people who decline participation.

      We will employ standard epidemiological statistical analysis methods applicable to each study question.43 44 These methods are presented in table 2. For bilateral data outcomes we will used mixed-effects regression models.

      View this table:
      Table 2

      Outcome measures, variable types and statistical analysis methods in the FIMAGE study

      Quality assurance

      Prior to study launch, we will create a written standard operating procedures file and perform a pilot study training and standardising shoulder measurements and the clinical examination protocol. The radiologists will read both separately and together a 10-patient random sample cohort to calibrate their scoring practices and delineation of anatomical regions before the definite readings. Study data will be collected and managed using REDCap electronic data capture tools hosted at the University of Helsinki.45 46

      Patient and public involvement

      To achieve a participant-friendly design for our study,26 we recruited patient experts from the patient research panel of the Helsinki University Hospital. They reviewed and provided feedback on the following documents: (a) the clarity and comprehensibility of the Finnish version of the study protocol, the patient consent form and the General Data Protection Regulation form, (b) the burden (time amount needed) related to filling out the numerous questionnaires (to assess if the amount of questionnaires is feasible and finalise the time schedule for the research visit) and (c) the clarity and understandability of our questionnaires. After the study is completed, we will contemplate together with patient experts on how to best share the study results to the public.

      Time schedule

      Recruitment of our study started in February 2023 in Helsinki and gradually expanded to first Tampere (April 2023), Turku (August 2023), Kuopio (September 2023) and Oulu (September 2023). Our scheduled average enrolment rate per week is 14 and at the current pace we aim to have completed the baseline data collection in early 2024. Thus, the 5-year follow-up should be completed in 2029.

      Ethics and dissemination

      This study will be conducted according to the Helsinki Declaration. The protocol has been approved by the Institutional Review Board of the Helsinki and Uusimaa Hospital District (HUS/13564/2022), and the study is registered at www.ClinicalTrials.gov (NCT05641415). All modifications to the study protocol will be communicated by updating the study registry. Before recruitment, oral and written explanations will be provided to all eligible patients, and informed consent will be obtained at the participating centre.

      All participating centres will obtain local institutional research approvals before start of recruitment. Information about the study participants will be kept confidential and will be managed in accordance with the following rules: (1) all study-related information is stored securely at the research sites, (2) all possible study participant information in paper form is stored in locked file cabinets and is accessible only to study personnel, (3) all case report forms are identified only by a coded participant number, (4) all records that contain participant names or other identifying information are stored separately from the study records that are identified only by the coded participant number and (5) all local databases are password protected.

      The findings of this study will be published through peer-reviewed journals and conference presentations and disseminated to the public through newspapers and social media. Study participants will be provided with a summary of the results after the research visit is completed.

      Ethics statements

      Patient consent for publication

      Acknowledgments

      We thank the patient research panel of the Helsinki University Hospital for their valuable comments on improving the material we will send to the participants. We also thank the research personnel at all study sites for their invaluable contributions. We express our gratitude to Drs Juha Paloneva, Jaakko Niinimäki and Martin Englund for their initial comments on the study protocol.

      References

      1. ↵
        1. Kansaneläkelaitos
        . Kelan Tilastollinen Vuosikirja 2016; 2017.
      2. ↵
        1. GBD 2016 Disease and Injury Incidence and Prevalence Collaborators
        . Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990-2016: a systematic analysis for the global burden of disease study 2016. Lancet 2017;390:1211–59. doi:10.1016/S0140-6736(17)32154-2
        OpenUrlCrossRefPubMed
      3. ↵
        1. Koskinen S,
        2. Lundqvist A,
        3. Ristiluoma N
        . Health, functional capacity and welfare in Finland in 2011, Report 68/2012. National Institute for Health and Welfare (THL); 2012.
      4. ↵
        1. Urwin M,
        2. Symmons D,
        3. Allison T, et al
        . Estimating the burden of musculoskeletal disorders in the community: the comparative prevalence of symptoms at different anatomical sites, and the relation to social deprivation. Ann Rheum Dis 1998;57:649–55. doi:10.1136/ard.57.11.649
        OpenUrlAbstract/FREE Full Text
      5. ↵
        1. Adamson J,
        2. Ebrahim S,
        3. Dieppe P, et al
        . Prevalence and risk factors for joint pain among men and women in the west of Scotland Twenty-07 study. Ann Rheum Dis 2006;65:520–4. doi:10.1136/ard.2005.037317
        OpenUrlAbstract/FREE Full Text
      6. ↵
        1. US Department of Labor, Bureau of Labor Statistics
        . Lost-worktime injuries and illnesses: characteristics and resulting time away from work. Washington, DC: US Department of Labor, Bureau of Labor Statistics, 2005.
      7. ↵
        1. van der Heijden GJ
        . Shoulder disorders: a state-of-the-art review. Baillieres Best Pract Res Clin Rheumatol 1999;13:287–309. doi:10.1053/berh.1999.0021
        OpenUrlCrossRefPubMed
      8. ↵
        1. Linsell L,
        2. Dawson J,
        3. Zondervan K, et al
        . Prevalence and incidence of adults consulting for shoulder conditions in UK primary care; patterns of diagnosis and referral. Rheumatology (Oxford) 2006;45:215–21. doi:10.1093/rheumatology/kei139
        OpenUrlCrossRefPubMedWeb of Science
      9. ↵
        1. Whittle S,
        2. Buchbinder R
        . In the clinic. rotator cuff disease. Ann Intern Med 2015;162:ITC1–15. doi:10.7326/AITC201501060
        OpenUrlCrossRefPubMed
      10. ↵
        1. Englund M,
        2. Guermazi A,
        3. Gale D, et al
        . Incidental meniscal findings on knee MRI in middle-aged and elderly persons. N Engl J Med 2008;359:1108–15. doi:10.1056/NEJMoa0800777
        OpenUrlCrossRefPubMedWeb of Science
      11. ↵
        1. Brinjikji W,
        2. Luetmer PH,
        3. Comstock B, et al
        . Systematic literature review of imaging features of spinal degeneration in asymptomatic populations. AJNR Am J Neuroradiol 2015;36:811–6. doi:10.3174/ajnr.A4173
        OpenUrlAbstract/FREE Full Text
      12. ↵
        1. Kasch R,
        2. Truthmann J,
        3. Hancock MJ, et al
        . Association of lumbar MRI findings with current and future back pain in a population-based cohort study. Spine 2022;47:201–11. doi:10.1097/BRS.0000000000004198
        OpenUrl
      13. ↵
        1. Chen L,
        2. Perera RS,
        3. Radojcic MR, et al
        . Association of lumbar spine radiographic changes with severity of back pain-related disability among middle-aged, community-dwelling women. JAMA Netw Open 2021;4:e2110715. doi:10.1001/jamanetworkopen.2021.10715
      14. ↵
        1. Culvenor AG,
        2. Øiestad BE,
        3. Hart HF, et al
        . Prevalence of knee osteoarthritis features on magnetic resonance imaging in asymptomatic uninjured adults: a systematic review and meta-analysis. Br J Sports Med 2019;53:1268–78. doi:10.1136/bjsports-2018-099257
        OpenUrlAbstract/FREE Full Text
      15. ↵
        1. Minagawa H,
        2. Yamamoto N,
        3. Abe H, et al
        . Prevalence of symptomatic and asymptomatic rotator cuff tears in the general population: from mass-screening in one village. J Orthop 2013;10:8–12. doi:10.1016/j.jor.2013.01.008
        OpenUrlCrossRefPubMed
      16. ↵
        1. Yamamoto A,
        2. Takagishi K,
        3. Osawa T, et al
        . Prevalence and risk factors of a rotator cuff tear in the general population. J Shoulder Elbow Surg 2010;19:116–20. doi:10.1016/j.jse.2009.04.006
        OpenUrlCrossRefPubMedWeb of Science
      17. ↵
        1. Kobayashi T,
        2. Takagishi K,
        3. Shitara H, et al
        . Prevalence of and risk factors for shoulder osteoarthritis in Japanese middle-aged and elderly populations. J Shoulder Elbow Surg 2014;23:613–9. doi:10.1016/j.jse.2013.11.031
        OpenUrl
      18. ↵
        1. Oh JH,
        2. Chung SW,
        3. Oh CH, et al
        . The prevalence of shoulder osteoarthritis in the elderly Korean population: association with risk factors and function. J Shoulder Elbow Surg 2011;20:756–63. doi:10.1016/j.jse.2011.01.021
        OpenUrlCrossRefPubMed
      19. ↵
        1. Wylie JD,
        2. Suter T,
        3. Potter MQ, et al
        . Mental health has a stronger association with patient-reported shoulder pain and function than tear size in patients with full-thickness rotator cuff tears. J Bone Joint Surg Am 2016;98:251–6. doi:10.2106/JBJS.O.00444
        OpenUrlAbstract/FREE Full Text
      20. ↵
        1. Jaeschke R,
        2. Guyatt GH,
        3. Sackett DL
        . Users' guides to the medical literature. III. how to use an article about a diagnostic test. B. what are the results and will they help me in caring for my patients? The evidence-based medicine working group. JAMA 1994;271:703–7. doi:10.1001/jama.271.9.703
        OpenUrlCrossRefPubMedWeb of Science
      21. ↵
        1. Kaila-Kangas L
        . Musculoskeletal disorders and diseases in Finland - results of the health 2000 survey, (KTL B25/2007). Publications of the National Public Health Institute; 2007.
      22. ↵
        1. von Elm E,
        2. Altman DG,
        3. Egger M, et al
        . The strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies. Ann Intern Med 2007;147:573. doi:10.7326/0003-4819-147-8-200710160-00010
        OpenUrlCrossRefPubMedWeb of Science
      23. ↵
        1. World Medical Association
        . World Medical Association declaration of Helsinki: ethical principles for medical research involving human subjects. JAMA 2013;310:2191–4. doi:10.1001/jama.2013.281053
        OpenUrlCrossRefPubMedWeb of Science
      24. ↵
        1. EuroQol G
        . Euroqol--a new facility for the measurement of health-related quality of life. Health Policy 1990;16:199–208. doi:10.1016/0168-8510(90)90421-9
        OpenUrlCrossRefPubMedWeb of Science
      25. ↵
        1. Zigmond AS,
        2. Snaith RP
        . The hospital anxiety and depression scale. Acta Psychiatr Scand 1983;67:361–70. doi:10.1111/j.1600-0447.1983.tb09716.x
        OpenUrlCrossRefPubMedWeb of Science
      26. ↵
        1. Wynne-Jones G,
        2. Myers H,
        3. Hall A, et al
        . Predicting pain and function outcomes in people consulting with shoulder pain: the PANDA-S clinical cohort and qualitative study protocol. BMJ Open 2021;11:e052758. doi:10.1136/bmjopen-2021-052758
      27. ↵
        1. Nicholas MK
        . The pain self-efficacy questionnaire: taking pain into account. Eur J Pain 2007;11:153–63. doi:10.1016/j.ejpain.2005.12.008
        OpenUrlCrossRefPubMedWeb of Science
      28. ↵
        1. Walton DM,
        2. Wideman TH,
        3. Sullivan MJL
        . A Rasch analysis of the pain catastrophizing scale supports its use as an interval-level measure. Clin J Pain 2013;29:499–506. doi:10.1097/AJP.0b013e318269569c
        OpenUrlCrossRefPubMedWeb of Science
      29. ↵
        1. Roach KE,
        2. Budiman-Mak E,
        3. Songsiridej N, et al
        . Development of a shoulder pain and disability index. Arthritis Care Res 1991;4:143–9.
        OpenUrlCrossRefPubMed
      30. ↵
        1. Williams JW,
        2. Holleman DR,
        3. Simel DL
        . Measuring shoulder function with the shoulder pain and disability index. J Rheumatol 1995;22:727–32.
        OpenUrlPubMedWeb of Science
      31. ↵
        1. Constant CR,
        2. Murley AH
        . A clinical method of functional assessment of the shoulder. Clin Orthop Relat Res 1987;1987:160–4.
        OpenUrlPubMed
      32. ↵
        1. Gilbart MK,
        2. Gerber C
        . Comparison of the subjective shoulder value and the constant score. J Shoulder Elbow Surg 2007;16:717–21. doi:10.1016/j.jse.2007.02.123
        OpenUrlCrossRefPubMedWeb of Science
      33. ↵
        1. Angst F,
        2. Schwyzer HK,
        3. Aeschlimann A, et al
        . Measures of adult shoulder function: disabilities of the arm, shoulder, and hand questionnaire (DASH) and its short version (QuickDASH), shoulder pain and disability index (SPADI), American shoulder and elbow Surgeons (ASES) society standardized shoulder assessment form, constant (Murley) score (CS), simple shoulder test (SST), Oxford shoulder score (OSS), shoulder disability questionnaire (SDQ), and Western Ontario shoulder instability index (WOSI). Arthritis Care Res (Hoboken) 2011;63 Suppl 11:S174–88. doi:10.1002/acr.20630
        OpenUrl
      34. ↵
        1. Green S,
        2. Buchbinder R,
        3. Forbes A, et al
        . A standardized protocol for measurement of range of movement of the shoulder using the Plurimeter-V inclinometer and assessment of its intrarater and interrater reliability. Arthritis Care Res 1998;11:43–52. doi:10.1002/art.1790110108
        OpenUrlCrossRefPubMedWeb of Science
      35. ↵
        1. Hoving JL,
        2. Buchbinder R,
        3. Green S, et al
        . How reliably do rheumatologists measure shoulder movement? Ann Rheum Dis 2002;61:612–6. doi:10.1136/ard.61.7.612
        OpenUrlAbstract/FREE Full Text
      36. ↵
        1. Miranda H,
        2. Punnett L,
        3. Viikari-Juntura E, et al
        . Physical work and chronic shoulder disorder. Results of a prospective population-based study. Ann Rheum Dis 2008;67:218–23. doi:10.1136/ard.2007.069419
        OpenUrlAbstract/FREE Full Text
      37. ↵
        1. Allain J,
        2. Goutallier D,
        3. Glorion C
        . Long-term results of the Latarjet procedure for the treatment of anterior instability of the shoulder. J Bone Joint Surg Am 1998;80:841–52. doi:10.2106/00004623-199806000-00008
        OpenUrlAbstract/FREE Full Text
      38. ↵
        1. de Abreu MR,
        2. Chung CB,
        3. Wesselly M, et al
        . Acromioclavicular joint osteoarthritis: comparison of findings derived from MR imaging and conventional radiography. Clin Imaging 2005;29:273–7. doi:10.1016/j.clinimag.2004.11.021
        OpenUrlCrossRefPubMed
      39. ↵
        1. Gill TK,
        2. Shanahan EM,
        3. Allison D, et al
        . Prevalence of abnormalities on shoulder MRI in symptomatic and asymptomatic older adults. Int J Rheum Dis 2014;17:863–71. doi:10.1111/1756-185X.12476
        OpenUrlCrossRefPubMed
      40. ↵
        1. Korn EL,
        2. Graubard BI
        . Analysis of Health Surveys, 1st ed. Wiley, 2011.
      41. ↵
        1. Bhatt DL,
        2. Mehta C
        . Adaptive designs for clinical trials. N Engl J Med 2016;375:65–74. doi:10.1056/NEJMra1510061
        OpenUrlCrossRefPubMed
      42. ↵
        1. Pallmann P,
        2. Bedding AW,
        3. Choodari-Oskooei B, et al
        . Adaptive designs in clinical trials: why use them, and how to run and report them. BMC Med 2018;16:29. doi:10.1186/s12916-018-1017-7
      43. ↵
        1. Clayton D,
        2. Hills M
        . Statistical models in epidemiology. Oxford: Oxford University Press, 1996.
      44. ↵
        1. Rothman KJ,
        2. Greenland S
        . Modern epidemiology. Philadelphia: Lippincott Williams & Wilkins, 1998.
      45. ↵
        1. Harris PA,
        2. Taylor R,
        3. Thielke R, et al
        . Research electronic data capture (REDCap)--A metadata-driven methodology and workflow process for providing translational research Informatics support. J Biomed Inform 2009;42:377–81. doi:10.1016/j.jbi.2008.08.010
        OpenUrlCrossRefPubMedWeb of Science
      46. ↵
        1. Harris PA,
        2. Taylor R,
        3. Minor BL, et al
        . The REDCap consortium: building an international community of software platform partners. J Biomed Inform 2019;95:103208. doi:10.1016/j.jbi.2019.103208
        OpenUrlCrossRefPubMed

      Supplementary materials

      Footnotes

      • Correction notice This article has been corrected since it was published. Incorrect ORCID of Tomasz Czuba has been corrected.

      • Collaborators FIMAGE investigators: Robert Björkenheim, Markku Heliövaara, Roope Kalske, Kari Kanto, Eira Viikari-Juntura, Danielle van der Windt.

      • Contributors TI, ST, TJ and RB conceptualised the study idea and contributed to the overall design of the study. TI, ST, TJ, PT and SR will implement the study at all study sites. ST, TJ, TI and TC planned the statistical analyses. All authors (TI, RB, NS, LR, PT, SR, SK, TH, HR, TC, MP, TJ, ST) contributed to the design of the study and revised and approved the final manuscript. All collaborators (FIMAGE investigators: RB, MH, RK, KK, EV-J, DvdW) provided feedback on drafts and approved the final manuscript.

      • Funding This work is supported by the Academy of Finland (316061), the Social Insurance Institution of Finland (KELA, 63/26/2018), the state funding for university-level health research in Finland (TYH2020213) and the Helsinki University Research Fund (WBS47087321). RB is supported by an Australian National Health and Medical Research Council (NHMRC) Leadership Fellowship (GNT1194483).

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      • Competing interests None declared.

      • Patient and public involvement Patients and/or the public were involved in the design, or conduct, or reporting, or dissemination plans of this research. Refer to the Methods section for further details.

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