AB1252 CAN THE HUPI BE MORE USEFUL THAN OTHER INDICES IN THE SEARCH OF BIOMARKERS FOR RA?
Authors: S. C. Rodriguez-García, N. Montes, J. Ivorra, A. Triguero-Martinez, L. Rodriguez Rodriguez, I. Castrejon, L. Carmona, I. González-Álvaro
Journal: Annals of the Rheumatic Diseases (2020)

Background: The Hospital Universitario La Princesa Index (HUPI) was developed to tackle metric shortcomings of DAS28 and SDAI, and has shown better accuracy and responsiveness than these widespread indices. 1 Objectives: To compare the performance of HUPI, DAS28, and SDAI in explaining the variability of radiographic progression, HAQ and the distribution of a biomarker of damage such as IL6. Methods: Two cohorts were assembled with data from a clinical trial (ACT-RAY) and an early arthritis register (PEARL). Radiographic progression, measured as the change (Δ) of Genant or Sharp/Van der Heijde indices at week 52 in ACT-RAY and PEARL respectively, Δ HAQ and serum IL6 (ELISA; R&amp;D Systems) levels, the latter only available in PEARL, were the outcome variables. HUPI, DAS28, SDAI, sex and age were the independent variables. For each index, linear regression models adjusted for sex and age were developed using standardized variables. The overall performance of the model, as well as that of the specific index it included, were evaluated using the adjusted R2. Differences between models were assessed with the likelihood ratio test. Also, The fpfitci command (Stata v14) was used to estimate the predicted distribution of the described variables using fractional polynomials and plotting the resulting curves. Results: The performance of the models and indices are shown in table 1. The variability of radiographic progression was better explained by the SDAI model in ACT-RAY whereas HUPI did it so in PEARL. The latter also performed better for explaining HAQ in ACT-RAY (figure 1) and IL6. Sex modified the performance of DAS28 and SDAI in their respective models. The relation between all the described outcomes predicted using fractional polynomials and each index was also more linear for HUPI than its comparators. (see an example in figure 2). Table 1. Adjusted R 2 of the models and indices. R 2 m: adjusted R 2 of the models; R 2 I: adjusted R 2 of the index included in the model; LR: Likelihood-Ratio test comparing HUPI models vs other indices’. OUTCOME INDEX ACT-RAY LR PEARL LR R 2 m R 2 I R 2 m R 2 I RADIOGRAPHIC PROGRESSION HUPI 0.025 0.024 ref 0.110 0.020 ref DAS28 0.031 0.030 &lt;0.000 0.102 0.011 &lt;0.000 SDAI 0.051 0.050 &lt;0.000 0.109 0.019 &lt;0.000 HAQ HUPI 0.353 0.323 ref 0.477 0.448 ref DAS28 0.329 0.298 &lt;0.000 0.472 0.442 &lt;0.000 SDAI 0.334 0.303 &lt;0.000 0.486 0.457 &lt;0.000 IL6 HUPI - - - 0.212 0.184 ref DAS28 - - - 0.204 0.176 &lt;0.000 SDAI - - - 0.201 0.172 &lt;0.000 Figure 1. Box plots comparing the adjusted R 2 of each index estimated in models for HAQ in ACT-RAY. Figure 2. Curves for comparison of predicted serum IL6 using fractional polynomials for HUPI and DAS28. Conclusion: Although all indices explained the outcomes’ variability similarly, HUPI did it better than DAS28 and SDAI for almost all outcomes except for Δ Genant and HAQ in PEARL. References: [1]Gonzalez-Alvaro I, et al. PLoS ONE 14(4): e0214717 Disclosure of Interests: Sebastian C Rodriguez-García Speakers bureau: Novartis Farmaceutica, S.A., Merck Sharp &amp; Dohme España, S.A., Sanofi Aventis, UCB Pharma, Nuria Montes: None declared, José Ivorra: None declared, Ana Triguero-Martinez: None declared, Luis Rodriguez Rodriguez: None declared, Isabel Castrejon: None declared, Loreto Carmona Grant/research support from: Novartis Farmaceutica, SA, Pfizer, S.L.U., Merck Sharp &amp; Dohme España, S.A., Roche Farma, S.A, Sanofi Aventis, AbbVie Spain, S.L.U., and Laboratorios Gebro Pharma, SA (All trhough institution), Isidoro González-Álvaro Grant/research support from: Roche Laboratories, Consultant of: Lilly, Sanofi, Paid instructor for: Lilly, Speakers bureau: Abbvie, MSD, Roche, Lilly