Rheumatoid arthritis response to treatment across IgG1 allotype - anti-TNF incompatibility: a case-only study.

INTRODUCTION We have hypothesized that incompatibility between the G1m genotype of the patient and the G1m1 and G1m17 allotypes carried by infliximab (INX) and adalimumab (ADM) could decrease the efficacy of these anti-tumor necrosis factor (anti-TNF) antibodies in the treatment of rheumatoid arthritis (RA). METHODS The G1m genotypes were analyzed in three collections of patients with RA totaling 1037 subjects. The first, used for discovery, comprised 215 Spanish patients. The second and third were successively used for replication. They included 429 British and Greek patients and 393 Spanish and British patients, respectively. Two outcomes were considered: change in the Disease Activity Score in 28 joint (ΔDAS28) and the European League Against Rheumatism (EULAR) response criteria. RESULTS An association between less response to INX and incompatibility of the G1m1,17 allotype was found in the discovery collection at 6 months of treatment (P = 0.03). This association was confirmed in the replications (P = 0.02 and 0.08, respectively) leading to a global association (P = 0.001) that involved a mean difference in ΔDAS28 of 0.4 units between compatible and incompatible patients (2.3 ± 1.5 in compatible patients vs. 1.9 ± 1.5 in incompatible patients) and an increase in responders and decrease in non-responders according to the EULAR criteria (P = 0.03). A similar association was suggested for patients treated with ADM in the discovery collection, but it was not supported by replication. CONCLUSIONS Our results suggest that G1m1,17 allotypes are associated with response to INX and could aid improved therapeutic targeting in RA.

Development and validation of a risk score predicting substantial weight gain over 5 years in middle-aged European men and women.

BACKGROUND Identifying individuals at high risk of excess weight gain may help targeting prevention efforts at those at risk of various metabolic diseases associated with weight gain. Our aim was to develop a risk score to identify these individuals and validate it in an external population. METHODS We used lifestyle and nutritional data from 53°758 individuals followed for a median of 5.4 years from six centers of the European Prospective Investigation into Cancer and Nutrition (EPIC) to develop a risk score to predict substantial weight gain (SWG) for the next 5 years (derivation sample). Assuming linear weight gain, SWG was defined as gaining ≥ 10% of baseline weight during follow-up. Proportional hazards models were used to identify significant predictors of SWG separately by EPIC center. Regression coefficients of predictors were pooled using random-effects meta-analysis. Pooled coefficients were used to assign weights to each predictor. The risk score was calculated as a linear combination of the predictors. External validity of the score was evaluated in nine other centers of the EPIC study (validation sample). RESULTS Our final model included age, sex, baseline weight, level of education, baseline smoking, sports activity, alcohol use, and intake of six food groups. The model's discriminatory ability measured by the area under a receiver operating characteristic curve was 0.64 (95% CI = 0.63-0.65) in the derivation sample and 0.57 (95% CI = 0.56-0.58) in the validation sample, with variation between centers. Positive and negative predictive values for the optimal cut-off value of ≥ 200 points were 9% and 96%, respectively. CONCLUSION The present risk score confidently excluded a large proportion of individuals from being at any appreciable risk to develop SWG within the next 5 years. Future studies, however, may attempt to further refine the positive prediction of the score.