Clases de interventoría

4.3.1

Literature Search

A systematic search on literature from January 1992 to December 2012 was performed on electronic databases including MEDLINE, EMBASE and CINAHL. MeSH terms “os- teoarthritis”, “inflammation”, “c-reactive protein”and related free text terms were used for the search. Search filters designed by Scottish Intercollegiate Guidelines Network (SIGN) for observational studies were incorporated into the electronic database search strategies [249]. Results were then limited to human epidemiological and clinical studies in English. The search strategy for each electronic database is detailed in the Appendix A. We tried to

identify ongoing clinical trials by electronically searching ClinicalTrials.gov, WHO Interna- tional Clinical Trial Registration Platform Search Portal, and Australian and New Zealand Clinical Trial Registry. The reference lists of obtained studies from the initial electronic search were scanned for further unidentified relevant studies. Conference abstracts from the American College of Rheumatology (ACR) and the European League Against Rheumatism (EULAR) were also searched.

4.3.2

Selection of Studies

Two independent investigators (XJ and JRB) were assigned for the selection of studies. Titles, abstracts, keywords and information of identified studies were entered in an Inclu- sion/Exclusion form (Appendix A). The initial screening was set to be relatively open-ended to retain as many relevant studies as possible. Full-text was then further examined if the col- lected information of a primary study suggested that it might meet the inclusion criteria for this review. When information from the published article was not sufficient to make a judg- ment, correspondent authors were contacted to obtain further information. Discrepancies between two investigators were addressed by consensus after discussion.

Inclusion Criteria

Studies that fulfilled the following criteria were included in this systematic review.

1. Studies included patients with OA;

2. Serum CRP levels were measured using high-sensitivity methodology;

3. Study compared OA patient with healthy subjects, or associated serum hs-CRP levels with phenotypes of OA (e.g. radiological grading, joint space narrowing, pain score and dysfunction score);

4. The article represented original data; 5. Human study;

6. Studies published in English.

4.3.3

Exclusion Criteria

1. Studies included patients with inflammatory joint diseases and other acute inflamma- tory conditions;

2. Review article;

3. In vitro, animal or ex vivo study.

4.3.4

Data Extraction

One investigator (XJ) extracted the data from included studies using a pre-designed data extraction form (Appendix A). The accuracy of the data was verified by a second investigator (JRB). Study characteristics were recorded including publication information, study design, origin of study, study setting, time frame of study, age, gender split, BMI, definition of OA, affected joints, hs-CRP measuring method, serum hs-CRP levels, relative measures and correlational data with OA.

4.3.5

Quality Assessment

Two investigators (XJ and JRB) independently evaluated the methodological quality of all included studies. The assessment was based on the Newcastle-Ottawa Quality Assessment Scale (NOS) for Case-Control Studies [250] with modifications to accommodate the topic of this review (Appendix A). The NOS was identified to be one of the two useful tools to assess

the quality of non-randomized studies in a systematic review of 182 tools [251]. The total quality score was not utilized in the meta-analyses, as we believed it was more appropriate to assess different aspects of methodological quality of a study in a separate manner.

4.3.6

Assessment of Heterogeneity

Heterogeneity across included studies was examined using Cochran Q test and I2test. A re- sult of Chi2>25% and p<0.10 was defined as evidence of significant heterogeneity across studies. To further analyze heterogeneity, the I2test was used to estimate the extent of hetero- geneity, for example, the percentage of variation across studies that is not caused by chance. A I2 value higher than 30% would indicate moderate heterogeneity and a value higher than 50% would represent substantial heterogeneity [252]. Possible sources of heterogeneity and their effects on the results were explored by subgroup analyses and sensitivity analyses.

4.3.7

Assessment of Publication Bias

Publication bias and ”small-study effects” were evaluated using a funnel plot. Asymmetry identified on the funnel plot would imply possible publication bias. A modified Eggers regression test was performed to detect the publication bias. When p-value equaled or was less than 0.10, significant publication bias was considered [253].

4.3.8

Data Synthesis and Analysis

For dichotomous data, a pooled odd ratio (OR) and a 95% confidence interval (95% CI) were computed by the Mantel-Haenszel method. For studies that reported relative risks (RR), we made an attempt to reconstruct a 2 × 2 table with information provided in the text and calculated the OR.

Because crude hs-CRP levels are frequently skewed, some individual studies had normalized the hs-CRP by logarithmic transformation in the statistical analysis while others reported the results on the original scale. In order to allow meta-analysis to be conducted on a common scale, we adopted the methods proposed by Higgins et al to transform data from a logarith- mic scale to a raw scale [254]. The unit of hs-CRP measurement was uniformly converted to mg/l in the meta-analysis. The difference in means and its 95% CI were calculated to estimate the difference in hs-CRP levels between OA patients and healthy controls. Generic inverse variance method on the random-effects model was used for the statistical pooling as we expected the true effects would vary across individual studies.

For correlational data, we obtained correlation coefficients (r) and calculated the correspond- ing standard error by computing the square root of sample variance as below.

SE =

s

1−r2

n−2 (4.1)

Correlation coefficients were combined using generic inverse variance method and the random- effects model.

When data were sufficient and appropriate, pre-specified subgroup analyses stratified by age, BMI, joints of OA, definition of OA, hs-CRP measuring methods and study designs were performed to assess the influence of the above parameters. Meta-regression analysis was performed to assess the influence of age, BMI and female sex using the random-effects model.

Statistical analyses were performed using Revman version 5.2 (The Nordic Cochrane Centre, The Cochrane Collaboration, 2012) and STATA (Release 12. College Station, TX. StataCorp LP). All reported p-values were two-sided and p<0.05 was considered to be statistically significant.