Failure of a systemic lupus erythematosus response index developed from clinical trial data: lessons examined and learned.

Background Our primary goal was to create an outcome change score index similar to a standard rheumatoid arthritis (RA) model utilizing real-world data in systemic lupus erythematosus (SLE) patients that occurred during their phase 3 trials with a Food and Drug Administration-approved drug. Methods We utilized raw data from trials of belimumab for the treatment of SLE. Data were split 80/20 into training/validation sets. Index variables present in a majority of patients and with face validity were selected. Variables were scored for each patient as percentage improvement from baseline after one year. The percentage of placebo- and drug-treated patients considered improved after the application of various criteria was ascertained. Logistic regression was employed to determine the ability of the new index to predict treatment assignment. Results A total of 1693 subjects had data for analyses. Eight variables were chosen: arthritis, rash, physician global assessment, fatigue, anti-double stranded DNA antibodies, C3, C4 and C-reactive protein. In the training dataset, ≥20% improvement in ≥4 of eight variables produced the largest difference between placebo- and drug-treated patients (22.1%) with an acceptable rate of improved placebo-treated patients (25%). This resulted in an odds ratio for belimumab (10 mg/kg) vs placebo of 2.7 (95% CI: 2.0-3.6; p < 0.001). However, in the validate dataset the odds ratio was not significant at 1.3 (95% CI: 0.8-2.2; p = 0.863). Conclusions The index created from training data did not achieve statistical significance when tested in the validation set. We have speculated why this happened. Is the lack of success of therapeutics for SLE caused by ineffective medications, study design and outcome instruments that fail to inform us, or is the heterogeneity of the disease too daunting? The lessons learned here can help direct future endeavors intended to improve SLE outcome instruments.

Abdominal Colpopexy: Comparison of Endoscopic Surgical Strategies (ACCESS).

INTRODUCTION: Robotic assistance during laparoscopic surgery for pelvic organ prolapse rapidly disseminated across the United States without level I data to support its benefit over traditional open and laparoscopic approaches [1]. This manuscript describes design and methodology of the Abdominal Colpopexy: Comparison of Endoscopic Surgical Strategies (ACCESS) Trial. METHODS: ACCESS is a randomized comparative effectiveness trial enrolling patients at two academic teaching facilities, UCLA (Los Angeles, CA) and Loyola University (Chicago, IL). The primary aim is to compare costs of robotic assisted versus pure laparoscopic abdominal sacrocolpopexy (RASC vs LASC). Following a clinical decision for minimally-invasive abdominal sacrocolpopexy (ASC) and research consent, participants with symptomatic stage≥II pelvic organ prolapse are randomized to LASC or RASC on the day of surgery. Costs of care are based on each patient's billing record and equipment costs at each hospital. All costs associated with surgical procedure including costs for robot and initial hospitalization and any re-hospitalization in the first 6weeks are compared between groups. Secondary outcomes include post-operative pain, anatomic outcomes, symptom severity and quality of life, and adverse events. Power calculation determined that 32 women in each arm would provide 95% power to detect a $2500 difference in total charges, using a two-sided two sample t-test with a significance level of 0.05. RESULTS: Enrollment was completed in May 2011. The 12-month follow-up was completed in May 2012. CONCLUSIONS: This is a multi-center study to assess cost as a primary outcome in a comparative effectiveness trial of LASC versus RASC.

Ergonomic analysis of New York apple harvest work using a Posture-Activities-Tools-Handling (PATH) work sampling approach.

Although back, neck, and shoulder strains are common among migrant and seasonal orchard workers, little data currently exist regarding the ergonomic factors contributing to this problem. We adapted Posture-Activities-Tools-Handling (PATH) instruments and methods for ergonomic job analysis of apple harvest work in three New York orchards, and used the resulting protocol to quantify hazardous activities, loads, and postures. Using a prototype developed previously, we trained twelve contract orchard observers with classroom training and supervised orchard practice. The PATH data were then collected on 14 orchard workers over four days (2,900 observations). Mean coefficients of variation ranged from a low of 0.212 (standing leg neutral) to a high of 0.603 (trunk moderate flexion). Most frequently observed activities were: picking (62.9%), placing and moving apples in the bag (8. 7%), and walking (8.1%). Weight bearing (>10 lb, >4.54 kg) was observed 78.5% of the time throughout a range of activities. Apple harvest work is comparable with other ergonomically high-risk occupations. Future research should focus on low-cost interventions that reduce load and awkward postures.