Predicting outcomes in rheumatoid arthritis related interstitial lung disease.

The aim of this study was to compare radiology-based prediction models in rheumatoid arthritis-related interstitial lung disease (RAILD) to identify patients with a progressive fibrosis phenotype.RAILD patients had computed tomography (CT) scans scored visually and using CALIPER and forced vital capacity (FVC) measurements. Outcomes were evaluated using three techniques, as follows. 1) Scleroderma system evaluating visual interstitial lung disease extent and FVC values; 2) Fleischner Society idiopathic pulmonary fibrosis (IPF) diagnostic guidelines applied to RAILD; and 3) CALIPER scores of vessel-related structures (VRS). Outcomes were compared to IPF patients.On univariable Cox analysis, all three staging systems strongly predicted outcome (scleroderma system hazard ratio (HR) 3.78, p=9×10-5; Fleischner system HR 1.98, p=2×10-3; and 4.4% VRS threshold HR 3.10, p=4×10-4). When the scleroderma and Fleischner systems were combined, termed the progressive fibrotic system (C-statistic 0.71), they identified a patient subset (n=36) with a progressive fibrotic phenotype and similar 4-year survival to IPF. On multivariable analysis, with adjustment for patient age, sex and smoking status, when analysed alongside the progressive fibrotic system, the VRS threshold of 4.4% independently predicted outcome (model C-statistic 0.77).The combination of two visual CT-based staging systems identified 23% of an RAILD cohort with an IPF-like progressive fibrotic phenotype. The addition of a computer-derived VRS threshold further improved outcome prediction and model fit, beyond that encompassed by RAILD measures of disease severity and extent.

Predicting Outcomes in Idiopathic Pulmonary Fibrosis Using Automated Computed Tomographic Analysis.

RATIONALE: Quantitative computed tomographic (CT) measures of baseline disease severity might identify patients with idiopathic pulmonary fibrosis (IPF) with an increased mortality risk. We evaluated whether quantitative CT variables could act as a cohort enrichment tool in future IPF drug trials. OBJECTIVES: To determine whether computer-derived CT measures, specifically measures of pulmonary vessel-related structures (VRSs), can better predict functional decline and survival in IPF and reduce requisite sample sizes in drug trial populations. METHODS: Patients with IPF undergoing volumetric noncontrast CT imaging at the Royal Brompton Hospital, London, and St. Antonius Hospital, Utrecht, were examined to identify pulmonary function measures (including FVC) and visual and computer-derived (CALIPER [Computer-Aided Lung Informatics for Pathology Evaluation and Rating] software) CT features predictive of mortality and FVC decline. The discovery cohort comprised 247 consecutive patients, with validation of results conducted in a separate cohort of 284 patients, all fulfilling drug trial entry criteria. MEASUREMENTS AND MAIN RESULTS: In the discovery and validation cohorts, CALIPER-derived features, particularly VRS scores, were among the strongest predictors of survival and FVC decline. CALIPER results were accentuated in patients with less extensive disease, outperforming pulmonary function measures. When used as a cohort enrichment tool, a CALIPER VRS score greater than 4.4% of the lung was able to reduce the requisite sample size of an IPF drug trial by 26%. CONCLUSIONS: Our study has validated a new quantitative CT measure in patients with IPF fulfilling drug trial entry criteria-the VRS score-that outperformed current gold standard measures of outcome. When used for cohort enrichment in an IPF drug trial setting, VRS threshold scores can reduce a required IPF drug trial population size by 25%, thereby limiting prohibitive trial costs. Importantly, VRS scores identify patients in whom antifibrotic medication prolongs life and reduces FVC decline.

The preferences of users of electronic medical records in hospitals: quantifying the relative importance of barriers and facilitators of an innovation.

BACKGROUND: Currently electronic medical records (EMRs) are implemented in hospitals, because of expected benefits for quality and safety of care. However the implementation processes are not unproblematic and are slower than needed. Many of the barriers and facilitators of the adoption of EMRs are identified, but the relative importance of these factors is still undetermined. This paper quantifies the relative importance of known barriers and facilitators of EMR, experienced by the users (i.e., nurses and physicians in hospitals). METHODS: A discrete choice experiment (DCE) was conducted among physicians and nurses. Participants answered ten choice sets containing two scenarios. Each scenario included attributes that were based on previously identified barriers in the literature: data entry hardware, technical support, attitude head of department, performance feedback, flexibility of interface, and decision support. Mixed Multinomial Logit analysis was used to determine the relative importance of the attributes. RESULTS: Data on 148 nurses and 150 physicians showed that high flexibility of the interface was the factor with highest relative importance in their preference to use an EMR. For nurses this attribute was followed by support from the head of department, presence of performance feedback from the EMR and presence of decisions support. While for physicians this ordering was different: presence of decision support was relatively more important than performance feedback and support from the head of department. CONCLUSION: Considering the prominent wish of all the intended users for a flexible interface, currently used EMRs only partially comply with the needs of the users, indicating the need for closer incorporation of user needs during development stages of EMRs. The differences in priorities amongst nurses and physicians show that different users have different needs during the implementation of innovations. Hospital management may use this information to design implementation trajectories to fit the needs of various user groups.