Literature DB >> 19714587

Polymyalgia rheumatica prevalence in a population-based sample.

S Bernatsky1, L Joseph, C A Pineau, P Belisle, L Lix, D Banerjee, A E Clarke.   

Abstract

OBJECTIVE: To determine polymyalgia rheumatica (PMR) prevalence using population-based administrative data, and to estimate the error associated with case ascertainment approaches when using these databases.
METHODS: Cases were ascertained using physician billing and hospitalization data from the province of Manitoba (population 1.1 million). Focusing on the population age >/=45 years, we compared 3 different case definition algorithms and also used statistical methods that accounted for imperfect case ascertainment to estimate the prevalence and the properties of the ascertainment algorithms. A hierarchical Bayesian latent class regression model was developed that also allowed us to assess differences across patient demographics (sex and region of residence).
RESULTS: Using methods that account for the imperfect nature of both billing and hospitalization databases, we estimated the prevalence of PMR in women age >/=45 years to be lower in urban areas (754.5 cases/100,000; 95% credible interval [95% CrI] 674.1-850.3) compared with rural areas (1,004 cases/100,000; 95% CrI 886.3-1,143). This regional trend was also seen in men age >/=45 years, where the prevalence was estimated at 273.6 cases/100,000 (95% CrI 219.8-347.6) in urban areas and 380.7 cases/100,000 (95% CrI 311.3-468.1) in rural areas. Billing data appeared more sensitive in ascertaining cases than hospitalization data, and a large proportion of diagnoses was made by physicians other than rheumatologists.
CONCLUSION: These data suggest a higher prevalence of PMR in rural versus urban regions. Our approach demonstrates the usefulness of methods that adjust for the imperfect nature of multiple information sources, which also allow for estimation of the sensitivity of different case ascertainment approaches.

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Year:  2009        PMID: 19714587     DOI: 10.1002/art.24793

Source DB:  PubMed          Journal:  Arthritis Rheum        ISSN: 0004-3591


  7 in total

1.  Prevalence of polymyalgia rheumatica in Colombia: data from the national health registry 2012-2016.

Authors:  Daniel G Fernández-Ávila; Santiago Bernal-Macías; Diana N Rincón-Riaño; Juan M Gutiérrez; Diego Rosselli
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Review 2.  Advances and challenges in the diagnosis and treatment of polymyalgia rheumatica.

Authors:  Tanaz A Kermani; Kenneth J Warrington
Journal:  Ther Adv Musculoskelet Dis       Date:  2014-02       Impact factor: 5.346

3.  Contemporary prevalence estimates for giant cell arteritis and polymyalgia rheumatica, 2015.

Authors:  Cynthia S Crowson; Eric L Matteson
Journal:  Semin Arthritis Rheum       Date:  2017-04-07       Impact factor: 5.532

Review 4.  Polymyalgia Rheumatica.

Authors:  Miriam Giovanna Colombo; Anna-Jasmin Wetzel; Hannah Haumann; Simon Dally; Gudula Kirtschig; Stefanie Joos
Journal:  Dtsch Arztebl Int       Date:  2022-06-17       Impact factor: 8.251

5.  [Polymyalgia rheumatica].

Authors:  W A Schmidt
Journal:  Z Rheumatol       Date:  2013-02       Impact factor: 1.372

6.  The rate of polymyalgia rheumatica (PMR) and remitting seronegative symmetrical synovitis with pitting edema (RS3PE) syndrome in a clinic where primary care physicians are working in Japan.

Authors:  Toshikatsu Okumura; Satoshi Tanno; Masumi Ohhira; Tsukasa Nozu
Journal:  Rheumatol Int       Date:  2011-03-24       Impact factor: 2.631

7.  The prevalence of giant cell arteritis and polymyalgia rheumatica in a UK primary care population.

Authors:  Max Yates; Karly Graham; Richard Arthur Watts; Alexander James MacGregor
Journal:  BMC Musculoskelet Disord       Date:  2016-07-15       Impact factor: 2.362

  7 in total

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