LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

SAT0680 The development and validation of interstitial lung disease prediction models in three international mixed connective tissue disease cohorts: the norwegian mctd cohort, the hungarian mctd cohort and the mctd cohort from minnesota, us

Photo by celtic57 from unsplash

Background Mixed Connective Tissue Disease (MCTD) is characterised by the presence of anti-RNP antibodies with clinical features also found in SSc, SLE and IIM. There is an ongoing debate of… Click to show full abstract

Background Mixed Connective Tissue Disease (MCTD) is characterised by the presence of anti-RNP antibodies with clinical features also found in SSc, SLE and IIM. There is an ongoing debate of MCTD’s position as a CTD. A substancial proportion of MCTD patients develop Interstitial Lung Disease (ILD). Objectives This study was conducted with the aims to explore the value of MCTD diagnosis and risk assessment by developing and validating ILD prediction models. Methods Multivariable logistic regression analyses were performed in 3 international MCTD cohorts. ILD prediction model development from clinical and laboratory parameters was performed in the Norwegian MCTD cohort (n=119). External validation of the models were performed in the Hungarian MCTD cohort (n=196) and the MCTD cohort from Minnesota, US (n=50). ILD was diagnosed by chest CT examination. Results The cohort characteristics are presented in table 1. An ILD prediction model including Pulmonary Function Test (PFT) results (table 2) and excluding PFT results was developed. The Hosmer-Lemeshow goodness of fit test (HL test) was. 31 and. 71 and the ROC was. 83 and. 78 respectively. The ILD prediction model including DLCO <60% was validated in the Hungarian MCTD cohort and showed good calibration and discrimination (HL test=0.95 and ROC=0.82). The ILD prediction model excluding PFT results showed good calibration and discrimination in both the Hungarian MCTD cohort (HL test=0.72 and ROC=0.80) and the MCTD cohort from Minnesota (HL test=0.96 and ROC=0.67).Abstract SAT0680 – Table 1 Characteristics of the three MCTD cohorts Characteristics Norwegian MCTD cohort (n=119) Hungarian MCTD cohort (n=196) Minnesota MCTD cohort (n=50) P- value Male sex, N (%) 32(24 10 (5) 8 (16) p<0.001 Age at diagnosis, yrs 34 (10) 36 (9) 48 (16) p<0.001 Age at CT, yrs 44 (14) 41 (11) 48 (14) p=0.001 ILD, N(%) 52(39 116(59) 14(28 p<0.001 DLCO<60% pred 28 (23) 67 (35) NA p=0.025 FVC<75% pred 18 (14) 97 (49) NA p<0.001Abstract SAT0680 – Table 2 ILD prediction model including PFT results Univariable Multivariable HR 95% CI P value HR 95% CI P value Sclerodactily 2.0 0.94–4.0 0.071 RNP>200 3.0 1.5–7.1 0.003 4.4 1.7–11.1 0.002 SR>30 2.3 1.0–5.0 0.043 Male sex 1.6 0.71–3.5 0.268 Never arthritis 5.4 2.1–13.6 <0.001 4.1 1.4–11.6 0.008 Pericarditis 2.2 0.8–6.1 0.117 Agegroup at CT <25 years 26–35 years36–45 years46–55 years56–65 years>65 years 1.02.61.72.36.0 0.2–4.50.6–11.7.4–7.4.5–10.81.0–35.4 0.9530.2130.5130.2890.048 1.84.82.93.713.0 0.3–9.80.9–25.50.5–14.70.6–23.91.6–107.3 0.5040.0650.2100.1670.017 Conclusions The cohorts have different characteristics. Despite these differences the ILD prediction models developed in the Norwegian MCTD cohort have shown external validity when assessed in the Hungarian MCTD cohort and the MCTD cohort from Minnesota. Risk factors of ILD in MCTD patients are high levels of anti-U1 RNP antibodies, absence of arthritis and increasing age. The successive ILD prediction across different MCTD cohorts strengthens the value of MCTD diagnosis and anti-RNP antibody detection in clinical practice. Disclosure of Interest None declared

Keywords: mctd cohort; hungarian mctd; ild prediction; mctd

Journal Title: Annals of the Rheumatic Diseases
Year Published: 2018

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.