Khalatbari, Shokoufeh

Abstract Context Lipodystrophy syndromes are rare disorders characterized by deficient adipose tissue, leading to insulin resistance, dyslipidemia, and organ system abnormalities. Objective Our goal was to develop a lipodystrophy severity score (LDS) to holistically capture the diverse manifestations of lipodystrophy into a numerical score to aid in prediction of clinical outcomes and/or treatment impact. Design An 8-domain LDS was developed by 8 disease experts in consultation with patient organizations. The LDS was rated for feasibility and content validity by 28 additional clinicians and 9 patient representatives. LDS was compared to the Clinical Global Impression (CGI) of severity for 20 putative patient profiles, each at 2 different time points, and by comparing change in LDS to global impression of change. For external validation, LDS was calculated in 2 cohorts of patients with lipodystrophy treated with metreleptin. Results LDS domains include Diabetes/Insulin Resistance, Microvascular Complications of Diabetes, Lipids, Cardiovascular, Liver, Kidney, Reproductive, and Other. Each domain is assessed by 1 or more questions assessing both lifetime and recent complications of lipodystrophy. The LDS had high content validity and feasibility and high reliability by intraclass correlation coefficients (>0.95). Global and domain-specific LDS were strongly correlated with CGI, as were changes in scores across visits (R = 0.79-0.99, P < .001 for all). In generalized lipodystrophy, metreleptin significantly reduced LDS (from 46 to 26 at 12 months, P < .001). The reductions were smaller in partial lipodystrophy (from 65 to 61 at 12 months, P = .04). Conclusion The LDS can reflect the severity of diverse manifestations of lipodystrophy and monitor changes following interventions.

Collaborative quantitative scientists, including biostatisticians, epidemiologists, bioinformaticists, and data‐related professionals, play vital roles in research, from study design to data analysis and dissemination. It is imperative that academic health care centers (AHCs) establish an environment that provides opportunities for the quantitative scientists who are hired as staff to develop and advance their careers. With the rapid growth of clinical and translational research, AHCs are charged with establishing organizational methods, training tools, best practices, and guidelines to accelerate and support hiring, training, and retaining this staff workforce. This paper describes three essential elements for building and maintaining a successful unit of collaborative staff quantitative scientists in academic health care centers: (1) organizational infrastructure and management, (2) recruitment, and (3) career development and retention. Specific strategies are provided as examples of how AHCs can excel in these areas.