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Objective.To identify how patients perceive the broad effect of active rheumatoid arthritis (RA) on their daily lives and indicate how RA disease management could benefit from the inclusion of individual goal-setting strategies.Methods.Two multinational surveys were completed by patients with RA. The “Good Days Fast” survey was conducted to explore the effect of disease on the daily lives and relationships of women with RA. The “Getting to Your Destination Faster” survey examined RA patients’ treatment expectations and goal-setting practices.Results.Respondents from all countries agreed that RA had a substantial negative effect on many aspects of their lives (work productivity, daily routines, participation in social and leisure activities) and emotional well-being (loss of self-confidence, feelings of detachment, isolation). Daily pain was a paramount issue, and being pain- and fatigue-free was considered the main indicator of a “good day.” Setting personal, social, and treatment goals, as well as monitoring disease progress to achieve these, was considered very beneficial by patients with RA, but discussion of treatment goals seldom appeared to be a part of medical appointments.Conclusion.Many patients with RA feel unable to communicate their disease burden and treatment goals, which are critically important to them, to their healthcare provider (HCP). Insights gained from these 2 surveys should help to guide patients and HCP to better focus upon mutually defined goals for continued improvement of management and achievement of optimal care in RA.

IntroductionEscherichia coli ingested by PMN are promptly growth arrested but undergo limited destruction. We have studied bacterial phospholipid hydrolysis as a possible limiting factor in the disassembly of ingested E. coli, comparing the fates, during phagocytosis by rabbit peritoneal exudate PMN, of three isogenic strains, differing in their content of the pldA gene encoding the principal E. coli phospholipase A (PLA), i.e., pldA-, pldA+, pldA+++ (the latter strain bearing the pldA gene in a multicopy plasmid resulting in a 20-fold increase in PLA content). Ingestion and growth inhibition (> 99% within 15 min) were the same for the three strains, but phospholipid degradation differed according to bacterial PLA content: pldA+++ up to 60%, pldA+ up to 30%, and pidA-up to 20%. Since the pidA-strain has no activatable PLA, phospholipid degradation in this strain demonstrates the action of a PMN PLA. Added PLA2-rich ascitic fluid (AF) or purified AF PLA2 increased the rate and extent of degradation of the pldA-strain, provided the enzyme was added before ingestion was complete.125I-AF-PLA2 binds to both E. coli and PMN and thus can enter the vacuole during phagocytosis. Although up to 50-fold more AF-PLA2 than the PLA2 content of the PMN could be loaded into the PMN in this way, degradation of pldA-E. coli did not exceed 30%. Increased phospholipid degradation had no effect on the degradation of bacterial macromolecules. In contrast, bacterial disassembly manifest as structural disorganization, release of bacterial protein derived material, and inhibition of protein synthesis were markedly enhanced when > 50% of prelabelled bacterial phospholipids were degraded. These findings reveal a link between envelope phospholipid degradation and overall bacterial destruction, suggesting therefore that factors limiting PLA action limit the destruction of E. coli ingested by PMN. (J.

Objective To use unbiased, data‐driven, principal component (PC) and cluster analysis to identify patient phenotypes of rheumatoid arthritis (RA) that might exhibit distinct trajectories of disease progression, response to treatment, and risk for adverse events. Methods Patient demographic, socioeconomic, health, and disease characteristics recorded at entry into a large, single‐center, prospective observational registry cohort, the Brigham and Women’s Rheumatoid Arthritis Sequential Study (BRASS), were harmonized using PC analysis to reduce dimensionality and collinearity. The number of PCs was established by eigenvalue >1, cumulative variance, and interpretability. The resulting PCs were used to cluster patients using a K‐means approach. Longitudinal clinical outcomes were compared between the clusters over 2 years. Results Analysis of 142 variables from 1,443 patients identified 41 PCs that accounted for 77% of the cumulative variance in the data set. Cluster analysis distinguished 5 patient clusters: 1) less RA disease activity/multimorbidity, shorter RA duration, lower incidence of comorbidities; 2) less RA disease activity/multimorbidity, longer RA duration, more infections, psychiatric comorbidities, health care utilization; 3) moderate RA disease activity/multimorbidity, more neurologic comorbidity; 4) more RA disease activity/multimorbidity, shorter RA duration, more metabolic comorbidity, higher body mass index; 5) more RA disease activity/multimorbidity, longer RA duration, more hepatic, orthopedic comorbidity and RA‐related surgeries. The clusters exhibited differences in clinical outcomes over 2 years of follow‐up. Conclusion Data‐driven analysis of the BRASS registry identified 5 distinct phenotypes of RA. These results illustrate the potential of data‐driven patient profiling as a tool to support personalized medicine in RA. Validation in an independent data set is ongoing.

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