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Background This study aimed to assess the accuracy of the Short-Form Health Survey (SF-36) mental health subscale (MH) and mental component summary (MCS) scores in identifying the presence of probable major depressive or anxiety disorder in patients with rheumatoid arthritis. Methods SF-36 data were collected in 100 hospital outpatients with rheumatoid arthritis. MH and MCS scores were compared against depression and anxiety data collected using validated measures as part of routine clinical practice. Sensitivity and specificity of the SF-36 were established using receiver operating characteristic (ROC) curve analysis, and area under the curve (AUC) compared the performance of the SF-36 components with the 9-item Patient Health Questionnaire (PHQ9) for depression and the 7-item Generalised Anxiety Disorder (GAD7) questionnaire for anxiety. Results The MH with a threshold of ≤52 had sensitivity and specificity of 81.0 and 71.4 % respectively to detect anxiety, correctly classifying 73.5 % of patients with probable anxiety disorder. A threshold of ≤56 had sensitivity and specificity of 92.6 and 73.2 % respectively to detect depression, correctly classifying 78.6 % of patients, and the same threshold could also be used to detect either depression or anxiety with a sensitivity of 87.9 %, specificity of 76.9 % and accuracy of 80.6 %. The MCS with a threshold of ≤35 had sensitivity and specificity of 85.7 and 81.9 % respectively to detect anxiety, correctly classifying 82.8 % of patients with probable anxiety disorder. A threshold of ≤40 had sensitivity and specificity of 92.3 and 70.2 % respectively to detect depression, correctly classifying 76.3 % of patients. A threshold of ≤38 could be used to detect either depression or anxiety with a sensitivity of 87.5 %, specificity of 80.3 % and accuracy of 82.8 %. Conclusion This analysis may increase the utility of a widely-used questionnaire. Overall, optimal use of the SF-36 for screening for mental disorder may be through using the MCS with a threshold of ≤38 to identify the presence of either depression or anxiety. Electronic supplementary material The online version of this article (doi:10.1186/s12891-016-1083-y) contains supplementary material, which is available to authorized users.

A pragmatic approach that balances the benefit of a whole-genome association (WGA) experiment against the cost of individual genotyping is to use pooled genomic DNA samples. We aimed to determine the feasibility of this approach in a WGA scan in rheumatoid arthritis (RA) using the validated human leucocyte antigen (HLA) and PTPN22 associations as test loci. A total of 203 269 single-nucleotide polymorphisms (SNPs) on the Affymetrix 100K GeneChip and Illumina Infinium microarrays were examined. A new approach to the estimation of allele frequencies from Affymetrix hybridization intensities was developed involving weighting for quality signals from the probe quartets. SNPs were ranked by z-scores, combined from United Kingdom and New Zealand case-control cohorts. Within a 1.7 Mb HLA region, 33 of the 257 SNPs and at PTPN22, 21 of the 45 SNPs, were ranked within the top 100 associated SNPs genome wide. Within PTPN22, individual genotyping of SNP rs1343125 within MAGI3 confirmed association and provided some evidence for association independent of the PTPN22 620W variant (P=0.03). Our results emphasize the feasibility of using genomic DNA pooling for the detection of association with complex disease susceptibility alleles. The results also underscore the importance of the HLA and PTPN22 loci in RA aetiology.