Dean Billheimer

Dean Billheimer

Professor, Public Health
Director, Statistical Consulting
Professor, Statistics-GIDP
Professor, BIO5 Institute
Member of the General Faculty
Member of the Graduate Faculty
Primary Department
Contact
(520) 626-9902

Work Summary

My research develops new clinical trial and experimental study designs to allow 'learning from data' more efficiently. My research also develops new analysis methods to understand latent structure in data. This allows better understanding of disease processes, better targeting of existing treatments, and development of more effective new treatments. Finally, I am developing new statistical methods based on prediction of future events.

Research Interest

Dean Billheimer, PhD, works with the Arizona Statistics Consulting Laboratory (StatLab) to partner with scientists and physicians to advance discovery and understanding. The 'Stat Lab' provides statistical expertise, personnel and computing resources to facilitate study design and conduct, data acquisition protocols, data analysis, and the preparation of grants and manuscripts. Dr. Billheimer also works to adapt and develop new statistical methods to address emerging problems in science and medicine. Dr. Billheimer facilitates discovery translation and economic development by consulting with public and private organizations external to the University of Arizona. Keywords: Biostatistics, Bioinformatics, Study Design, Bayesian Analysis

Publications

Chisholm-Burns, M. A., Spivey, C. A., Billheimer, D., Schlesselman, L. S., Flowers, S. K., Hammer, D., Engle, J. P., Nappi, J. M., Pasko, M. T., Ross, L. A., Sorofman, B., Rodrigues, H. A., & Vaillancourt, A. M. (2012). Multi-institutional study of women and underrepresented minority faculty members in academic pharmacy.. American journal of pharmaceutical education, 76(1), 7-.

PMID: 22412206;PMCID: PMC3298405;Abstract:

To examine trends in the numbers of women and underrepresented minority (URM) pharmacy faculty members over the last 20 years, and determine factors influencing women faculty members' pursuit and retention of an academic pharmacy career. Twenty-year trends in women and URM pharmacy faculty representation were examined. Women faculty members from 9 public colleges and schools of pharmacy were surveyed regarding demographics, job satisfaction, and their academic pharmacy career, and relationships between demographics and satisfaction were analyzed. The number of women faculty members more than doubled between 1989 and 2009 (from 20.7% to 45.5%), while the number of URM pharmacy faculty members increased only slightly over the same time period. One hundred fifteen women faculty members completed the survey instrument and indicated they were generally satisfied with their jobs. The academic rank of professor, being a nonpharmacy practice faculty member, being tenured/tenure track, and having children were associated with significantly lower satisfaction with fringe benefits. Women faculty members who were tempted to leave academia for other pharmacy sectors had significantly lower salary satisfaction and overall job satisfaction, and were more likely to indicate their expectations of academia did not match their experiences (p0.05). The significant increase in the number of women pharmacy faculty members over the last 20 years may be due to the increased number of female pharmacy graduates and to women faculty members' satisfaction with their careers. Lessons learned through this multi-institutional study and review may be applicable to initiatives to improve recruitment and retention of URM pharmacy faculty members.

Yassine, H. N., Jackson, A. M., Borges, C. R., Billheimer, D., Koh, H., Smith, D., Reaven, P., Lau, S. S., & Borchers, C. H. (2013). The application of multiple reaction monitoring and multi-analyte profiling to HDL proteins. Lipids in health and disease, 13.

HDL carries a rich protein cargo and examining HDL protein composition promises to improve our understanding of its functions. Conventional mass spectrometry methods can be lengthy and difficult to extend to large populations. In addition, without prior enrichment of the sample, the ability of these methods to detect low abundance proteins is limited. Our objective was to develop a high-throughput approach to examine HDL protein composition applicable to diabetes and cardiovascular disease (CVD).

Lieber, C. A., Majumder, S. K., Ellis, D. L., Billheimer, D. D., & Mahadevan-Jansen, A. (2008). In vivo nonmelanoma skin cancer diagnosis using Raman microspectroscopy. Lasers in surgery and medicine, 40(7), 461-7.

Nonmelanoma skin cancers, including basal cell carcinoma (BCC) and squamous cell carcinoma (SCC), are the most common skin cancers, presenting nearly as many cases as all other cancers combined. The current gold-standard for clinical diagnosis of these lesions is histopathologic examination, an invasive, time-consuming procedure. There is thus considerable interest in developing a real-time, automated, noninvasive tool for nonmelanoma skin cancer diagnosis. In this study, we explored the capability of Raman microspectroscopy to provide differential diagnosis of BCC, SCC, inflamed scar tissue, and normal tissue in vivo.

Gibbens, R. P., Havstad, K. M., Billheimer, D. D., & Herbel, C. H. (1993). Creosotebush vegetation after 50 years of lagomorph exclusion. Oecologia, 94(2), 210-217.

Abstract:

In 1939, an experiment was established on the Jornada Experimental Range to evaluate the effects of shrub removal, rabbit exclusion, furrowing, and seeding in creosotebush [Larrea tridentata (DC.) Cov] vegetation. Sixteen plots (21.3×21.3 m) were laid out in four rows of four plots per row with a buffer zone of 7.6 m between plots and rows. A barbed wire fence excluded cattle and poultry wire fencing excluded lagomorphs. Treatments were factorially applied at two levels. Plant cover in the plots was sampled in 1938 (before treatment), 1947, 1956, 1960, 1967 and 1989 with randomly located, line-intercept transects. Data from all sampling dates were analyzed as a split plot in time and main effects for 1989 tested by analysis of variance for a 2×4 factorial experiment. There were significant (P0.10) year x treatment interactions. Seeding and furrowing treatments were ineffective but lagomorph exclusion and shrub clearing treatments resulted in significant treatment differences for several species. In 1989, basal area of spike dropseed (Sporobolus contractus A.S. Hitchc.) was 30-fold greater on the lagomorph excluded than on the lagomorph unexcluded treatment. Canopy cover of honey mesquite (Prosopis glandulosa Torr. var. glandulosa), tarbush (Flourensia cernua DC.) and mariola (Parthenium incanum H.B.K.) were affected by lagomorph exclusion. None of the responses were viewed as successional in nature. They principally represented individual species sensitivities to either absence of a primary herbivore or removal of aboveground shrub biomass. Though the physical treatments could be regarded as relatively severe disturbances of the system, the impacts on community vegetation dynamics were relatively insignificant. © 1993 Springer-Verlag.

Rudnick, P. A., Clauser, K. R., Kilpatrick, L. E., Tchekhovskoi, D. V., Neta, P., Blonder, N., Billheimer, D. D., Blackman, R. K., Bunk, D. M., Cardasis, H. L., Ham, A. L., Jaffe, J. D., Kinsinger, C. R., Mesri, M., Neubert, T. A., Schilling, B., Tabb, D. L., Tegeler, T. J., Vega-Montoto, L., , Variyath, A. M., et al. (2010). Performance metrics for liquid chromatography-tandem mass spectrometry systems in proteomics analyses. Molecular and Cellular Proteomics, 9(2), 225-241.

PMID: 19837981;PMCID: PMC2830836;Abstract:

A major unmet need in LC-MS/MS-based proteomics analyses is a set of tools for quantitative assessment of system performance and evaluation of technical variability. Here we describe 46 system performance metrics for monitoring chromatographic performance, electrospray source stability, MS1 and MS2 signals, dynamic sampling of ions for MS/MS, and peptide identification. Applied to data sets from replicate LC-MS/MS analyses, these metrics displayed consistent, reasonable responses to controlled perturbations. The metrics typically displayed variations less than 10% and thus can reveal even subtle differences in performance of system components. Analyses of data from interlaboratory studies conducted under a common standard operating procedure identified outlier data and provided clues to specific causes. Moreover, interlaboratory variation reflected by the metrics indicates which system components vary the most between laboratories. Application of these metrics enables rational, quantitative quality assessment for proteomics and other LC-MS/MS analytical applications.