Bio

Bio


Statistician and Pain Physician

Academic Appointments


Honors & Awards


  • Howard Hughes Pre-Doctoral Fellowship, Howard Hughes Medical Institute (2000)
  • NIH Training Grant, National Institute of Mental Health (1999)

Professional Education


  • Board Certification, American Board of Physical Medicine and Rehabilitation (2013)
  • Fellowship, Stanford University, Pain Medicine (2013)
  • Residency, Stanford University, Physical Medicine & Rehabilitation (2012)
  • Internship, Yale-New Haven Hospital (2008)
  • MD, University of Michigan (2007)
  • PhD, Harvard University, Biostatistics & Computational Biology (2005)
  • BA, UC Berkeley (1999)

Research & Scholarship

Current Research and Scholarly Interests


1. Patient-reported outcomes. Efficient, multi-feature item-response theory (IRT) based computerized adaptive testing (CAT) algorithm using item banks from PROMIS and NIH Toolbox

2. Activity monitoring. Novel analytic framework for physical activity monitoring in the context of pain.

3. Operations research. Multi-variable discrete and continuous optimization for Lean Hospital Management

4. National trends in pain medication prescription

Publications

Journal Articles


  • Assessment and management of back pain. JAMA internal medicine Kao, M., Zheng, P., Smuck, M. 2014; 174 (3): 479-?

    View details for DOI 10.1001/jamainternmed.2013.13695

    View details for PubMedID 24590093

  • Does physical activity influence the relationship between low back pain and obesity? SPINE JOURNAL Smuck, M., Kao, M. J., Brar, N., Martinez-Ith, A., Choi, J., Tomkins-Lane, C. C. 2014; 14 (2): 209-216

    Abstract

    Evidence supporting an association between obesity and low back pain (LBP) continues to grow; yet little is known about the cause and effect of this relationship. Even less is known about the mechanisms linking the two. Physical activity is a logical suspect, but no study has demonstrated its role.This study was designed to examine the interrelationship between physical activity, obesity, and LBP. The specific aims were to determine if obesity is a risk factor for LBP in the U.S. population, measure the strength of any observed association, and evaluate the role of physical activity in modulating this association.A cross-sectional U.S. population-based study.A cohort of 6,796 adults from the 2003-2004 National Health and Nutrition Examination Survey.Demographic information, an in-depth health questionnaire, physical examination details, and 7-day free-living physical activity monitoring using accelerometry (ActiGraph AM-7164; ActiGraph, Pensacola, FL, USA).LBP status was determined by questionnaire response. Body mass index (BMI) was calculated during physical examination and divided here into four groups (normal weight <25, overweight 25-30, obese 31-35, and ultraobese 36+). Summary measures of physical activity were computed based on intensity cutoffs, percentile intensities, and bout. Demographics, social history, and comorbid health conditions were used to build adjusted weighted logistic regression models constructed using Akaike Information Criterion. All displayed estimates are significant at level <.05. No external funding was received to support this study. None of the authors report conflicts of interest directly related to the specific subject matter of this manuscript.In the U.S. population, the risk of low LBP increases in step with BMI from 2.9% for normal BMI (20-25) to 5.2% for overweight (26-30), 7.7% for obese (31-35), and 11.6% for ultraobese (36+). Smoking is consistently the strongest predictor of LBP across the BMI spectrum (odds ratio 1.6-2.9). Physical activity also modulates these risks. In the overall model, the best physical activity predictors of LBP are in the moderate and high intensity ranges with small effects (odds ratio 0.98 and 0.996 per standard deviation increase, respectively). When broken down by BMI, time spent in sedentary and moderate activity ranges demonstrate more robust influences on LBP status in the overweight, obese, and ultraobese groups.Increased BMI is a risk factor for back pain in Americans. More important, the role of physical activity in mitigating back pain risk is shown to be of greater consequence in the overweight and obese populations.

    View details for DOI 10.1016/j.spinee.2013.11.010

    View details for Web of Science ID 000329971900004

    View details for PubMedID 24239800

  • Duration of fluoroscopic-guided spine interventions and radiation exposure is increased in overweight patients. PM & R : the journal of injury, function, and rehabilitation Smuck, M., Zheng, P., Chong, T., Kao, M., Geisser, M. E. 2013; 5 (4): 291-296

    Abstract

    The impact of patient body mass index (BMI) on image-guided spine interventions remains unknown. Higher BMI is known to complicate the acquisition of radiographic images. Therefore it can be hypothesized that the patient's body habitus can influence the delivery of a spinal injection.To quantify the impact of patient BMI on the length of fluoroscopy and procedure times during spine interventions.Secondary analysis of 2 prospective observational studies.All injections were performed in an outpatient university setting.A total of 209 patients in whom spine injections were performed (99 women), with a mean age of 54.6 years.The fluoroscopy times for 202 participants and total procedure times for 137 participants were recorded. Additional participant characteristics, including age, gender, BMI, and actual procedures performed, also were collected. Analysis of covariance and linear and nonlinear model analysis were performed to assess the effect of BMI on fluoroscopy and procedure times.Fluoroscopy time and procedure duration times.Participants had a mean age of 54.6 years, 51% were men, and 77% (n = 155) were overweight (BMI ?25). Participants received the following interventions: 40 zygapophyseal joint injections, 33 medial branch nerve blocks, 113 transforaminal epidural injections, and 16 combined zygapophyseal joint injections and epidural injections. Gender, procedure number, and procedure type did not differ between groups. The overweight group demonstrated a 30% increase in mean fluoroscopy time and a 35% increase in mean procedure time. Controlling for other variables, we found that differences in fluoroscopy time and procedure time were significant (P = .032 and P = .031, respectively) between the 2 groups.Significantly prolonged procedure time and fluoroscopy time in overweight patients increase the risks associated with spine interventions, not only to the patients but also to the operating room staff exposed to ionizing radiation.

    View details for DOI 10.1016/j.pmrj.2013.01.015

    View details for PubMedID 23435199

  • The value of physical examination in the diagnosis of hip osteoarthritis. Journal of back and musculoskeletal rehabilitation Chong, T., Don, D. W., Kao, M., Wong, D., Mitra, R. 2013; 26 (4): 397-400

    Abstract

    To compare the sensitivity of physical examination (internal rotation of the hip) with radiographs (using the Kellgren-Lawrence grading scale) in the diagnosis of clinically significant hip osteoarthritis.Case Series, Retrospective chart review of hip pain patients that underwent fluoroscopically guided hip steroid and anesthetic injections.10 patients with hip pain patients seen at an academic outpatient center over a 2 year period were analyzed.Fluoroscopically guided hip steroid and anesthetic injection.Pain relief and change in VAS pain score after intra-articular hip steroid and lidocaine injection was the main outcome measure.Based on Fisher's exact test, there was no association between severity of radiographic hip arthritis and pain relief with intra-articular anesthetic/steroid injection (p=0.45). Physical examination (provocative hip internal rotation) however was associated with a significant decrease in VAS pain score after intra-articular lidocaine and corticosteroid hip injection (p=0.022).Simple hip radiographs alone are not sufficient to diagnose clinically significant hip osteoarthritis. Physical examination (hip internal rotation) was found to be more accurate than simple radiographs in the diagnosis of clinically significant hip osteoarthritis. Radiographs seem to best utilized when they are an extension of the physical examination and patient history.

    View details for DOI 10.3233/BMR-130398

    View details for PubMedID 23948824

  • Diagnostic Accuracy of Bedside Swallow Evaluation Versus Videofluoroscopy to Assess Dysphagia in Individuals With Tetraplegia PM&R Shem, K. L., Castillo, K., Wong, S. L., Chang, J., Kao, M., Kolakowsky-Hayner, S. A. 2012; 4 (4): 283-289

    Abstract

    To assess the accuracy of bedside swallow evaluation (BSE) compared with videofluorosopic swallow study (VFSS) in diagnosing dysphagia in individuals with tetraplegia due to spinal cord injury (SCI).A prospective diagnostic accuracy study according to STAndards for the Reporting of Diagnostic accuracy studies (STARD) criteria.A county hospital with acute inpatient SCI unit.Thirty-nine subjects with SCI and tetraplegia were enrolled. All of the subjects underwent BSE, and 26 subjects completed the VFSS.Individuals with SCI underwent a BSE followed by a VFSS within 72 hours of the BSE. The subjects were diagnosed as having dysphagia if they had positive findings in either BSE or VFSS.Sensitivity, specificity, and positive and negative predictive values were calculated by using VFSS as the criterion standard.Fifteen subjects (38%) were diagnosed as having dysphagia based on the BSE results. Among the subjects who completed the VFSS, 11 were diagnosed with dysphagia (42%) and 4 were diagnosed with aspiration (10%). Of the 26 subjects who completed both BSE and VFSS, only 1 subject was diagnosed differently compared with BSE (3.8%). Different diet recommendations were made in 4 cases after VFSS versus BSE. Different liquid recommendations were made in 8 cases after VFSS versus BSE. Sensitivity of BSE was 100% (95% confidence interval [CI], 71.5%-100%), specificity was 93.3% (95% CI, 68.1%-99.8%). A positive predictive value of BSE was 91.7% (95% CI, 61.5%-100%), and the negative predictive value was 100% (95% CI, 76.8%-100%).Dysphagia is present in approximately 38% of individuals with acute tetraplegia. Because only one of the 21 subjects was diagnosed differently based on VFSS, we believe that BSE is an appropriate screening tool for dysphagia for individuals with cervical SCI. However, VFSS provided additional information on diet and liquid recommendations, so there appears to be an important clinical role for the VFSS.

    View details for DOI 10.1016/j.pmrj.2012.01.002

    View details for Web of Science ID 000305438600006

    View details for PubMedID 22541374

  • An integrative approach to characterize disease-specific pathways and their coordination: a case study in cancer BMC GENOMICS Xu, M., Kao, M. J., Nunez-Iglesias, J., Nevins, J. R., West, M., Zhou, X. J. 2008; 9
  • HumanUpstream and MouseUpstream: Databases of promoter sequences in the human and mouse genomes OMICS-A JOURNAL OF INTEGRATIVE BIOLOGY Leykin, I., Kao, M. C., Wong, W. H. 2005; 9 (3): 220-224

    Abstract

    Large-scale genome annotations, based largely on gene prediction programs, may be inaccurate in their predictions of transcription start sites, so that the identification of promoter regions remains unreliable. Here we focus on the identification of reliable gene promoter regions, critical to the understanding of transcriptional regulation. We report the construction of databases of upstream sequences Human Upstream and Mouse Upstream based on information from both the human and mouse genomes and the database of expressed sequence tags (dbEST). Using the ENSEMBL generic genome annotation system, our approach allows more reliable identification of transcript start sites, and therefore extraction of more reliable promoters regions. The Human Upstream and Human Upstream databases are available free of charge.

    View details for Web of Science ID 000232649500002

    View details for PubMedID 16209636

  • Functional annotation and network reconstruction through cross-platform integration of microarray data NATURE BIOTECHNOLOGY Zhou, X. H., Kao, M. C., Huang, H. Y., Wong, A., Nunez-Iglesias, J., Primig, M., Aparicio, O. M., Finch, C. E., Morgan, T. E., Wong, W. H. 2005; 23 (2): 238-243

    Abstract

    The rapid accumulation of microarray data translates into a need for methods to effectively integrate data generated with different platforms. Here we introduce an approach, 2(nd)-order expression analysis, that addresses this challenge by first extracting expression patterns as meta-information from each data set (1(st)-order expression analysis) and then analyzing them across multiple data sets. Using yeast as a model system, we demonstrate two distinct advantages of our approach: we can identify genes of the same function yet without coexpression patterns and we can elucidate the cooperativities between transcription factors for regulatory network reconstruction by overcoming a key obstacle, namely the quantification of activities of transcription factors. Experiments reported in the literature and performed in our lab support a significant number of our predictions.

    View details for DOI 10.1038/nbt1058

    View details for Web of Science ID 000226797600032

    View details for PubMedID 15654329

  • GoSurfer: a graphical interactive tool for comparative analysis of large gene sets in Gene Ontology space. Applied bioinformatics Zhong, S., Storch, K., Lipan, O., Kao, M. J., Weitz, C. J., Wong, W. H. 2004; 3 (4): 261-264

    Abstract

    The analysis of complex patterns of gene regulation is central to understanding the biology of cells, tissues and organisms. Patterns of gene regulation pertaining to specific biological processes can be revealed by a variety of experimental strategies, particularly microarrays and other highly parallel methods, which generate large datasets linking many genes. Although methods for detecting gene expression have improved substantially in recent years, understanding the physiological implications of complex patterns in gene expression data is a major challenge. This article presents GoSurfer, an easy-to-use graphical exploration tool with built-in statistical features that allow a rapid assessment of the biological functions represented in large gene sets. GoSurfer takes one or two list(s) of gene identifiers (Affymetrix probe set ID) as input and retrieves all the Gene Ontology (GO) terms associated with the input genes. GoSurfer visualises these GO terms in a hierarchical tree format. With GoSurfer, users can perform statistical tests to search for the GO terms that are enriched in the annotations of the input genes. These GO terms can be highlighted on the GO tree. Users can manipulate the GO tree in various ways and interactively query the genes associated with any GO term. The user-generated graphics can be saved as graphics files, and all the GO information related to the input genes can be exported as text files.GoSurfer is a Windows-based program freely available for noncommercial use and can be downloaded at http://www.gosurfer.org. Datasets used to construct the trees shown in the figures in this article are available at http://www.gosurfer.org/download/GoSurfer.zip.

    View details for PubMedID 15702958

  • Determination of local statistical significance of patterns in Markov sequences with application to promoter element identification JOURNAL OF COMPUTATIONAL BIOLOGY Huang, H. Y., Kao, M. C., Zhou, X. H., Liu, J. S., Wong, W. H. 2004; 11 (1): 1-14

    Abstract

    High-level eukaryotic genomes present a particular challenge to the computational identification of transcription factor binding sites (TFBSs) because of their long noncoding regions and large numbers of repeat elements. This is evidenced by the noisy results generated by most current methods. In this paper, we present a p-value-based scoring scheme using probability generating functions to evaluate the statistical significance of potential TFBSs. Furthermore, we introduce the local genomic context into the model so that candidate sites are evaluated based both on their similarities to known binding sites and on their contrasts against their respective local genomic contexts. We demonstrate that our approach is advantageous in the prediction of myogenin and MEF2 binding sites in the human genome. We also apply LMM to large-scale human binding site sequences in situ and found that, compared to current popular methods, LMM analysis can reduce false positive errors by more than 50% without compromising sensitivity. This improvement will be of importance to any subsequent algorithm that aims to detect regulatory modules based on known PSSMs.

    View details for Web of Science ID 000220234300001

    View details for PubMedID 15072685

  • Chemical genetic modifier screens: Small molecule trichostatin suppressors as probes of intracellular histone and tubulin acetylation CHEMISTRY & BIOLOGY Koeller, K. M., Haggarty, S. J., Perkins, B. D., Leykin, I., Wong, J. C., Kao, M. C., Schreiber, S. L. 2003; 10 (5): 397-410

    Abstract

    Histone deacetylase (HDAC) inhibitors are being developed as new clinical agents in cancer therapy, in part because they interrupt cell cycle progression in transformed cell lines. To examine cell cycle arrest induced by HDAC inhibitor trichostatin A (TSA), a cytoblot cell-based screen was used to identify small molecule suppressors of this process. TSA suppressors (ITSAs) counteract TSA-induced cell cycle arrest, histone acetylation, and transcriptional activation. Hydroxamic acid-based HDAC inhibitors like TSA and suberoylanilide hydroxamic acid (SAHA) promote acetylation of cytoplasmic alpha-tubulin as well as histones, a modification also suppressed by ITSAs. Although tubulin acetylation appears irrelevant to cell cycle progression and transcription, it may play a role in other cellular processes. Small molecule suppressors such as the ITSAs, available from chemical genetic suppressor screens, may prove to be valuable probes of many biological processes.

    View details for DOI 10.1016/S1074-5521(03)00093-0

    View details for Web of Science ID 000183647400003

    View details for PubMedID 12770822

  • Novel mechanisms of T-cell and dendritic cell activation revealed by profiling of psoriasis on the 63,100-element oligonucleotide array PHYSIOLOGICAL GENOMICS Zhou, X. H., Krueger, J. G., Kao, M. C., Lee, E., Du, F. H., Menter, A., Wong, W. H., Bowcock, A. M. 2003; 13 (1): 69-78

    Abstract

    A global picture of gene expression in the common immune-mediated skin disease, psoriasis, was obtained by interrogating the full set of Affymetrix GeneChips with psoriatic and control skin samples. We identified 1,338 genes with potential roles in psoriasis pathogenesis/maintenance and revealed many perturbed biological processes. A novel method for identifying transcription factor binding sites was also developed and applied to this dataset. Many of the identified sites are known to be involved in immune response and proliferation. An in-depth study of immune system genes revealed the presence of many regulating cytokines and chemokines within involved skin, and markers of dendritic cell (DC) activation in uninvolved skin. The combination of many CCR7+ T cells, DCs, and regulating chemokines in psoriatic lesions, together with the detection of DC activation markers in nonlesional skin, strongly suggests that the spatial organization of T cells and DCs could sustain chronic T-cell activation and persistence within focal skin regions.

    View details for DOI 10.1152/physiolgenomics.00157.2002

    View details for Web of Science ID 000181684400009

    View details for PubMedID 12644634

  • Transitive functional annotation by shortest-path analysis of gene expression data PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA Zhou, X. H., Kao, M. C., Wong, W. H. 2002; 99 (20): 12783-12788

    Abstract

    Current methods for the functional analysis of microarray gene expression data make the implicit assumption that genes with similar expression profiles have similar functions in cells. However, among genes involved in the same biological pathway, not all gene pairs show high expression similarity. Here, we propose that transitive expression similarity among genes can be used as an important attribute to link genes of the same biological pathway. Based on large-scale yeast microarray expression data, we use the shortest-path analysis to identify transitive genes between two given genes from the same biological process. We find that not only functionally related genes with correlated expression profiles are identified but also those without. In the latter case, we compare our method to hierarchical clustering, and show that our method can reveal functional relationships among genes in a more precise manner. Finally, we show that our method can be used to reliably predict the function of unknown genes from known genes lying on the same shortest path. We assigned functions for 146 yeast genes that are considered as unknown by the Saccharomyces Genome Database and by the Yeast Proteome Database. These genes constitute around 5% of the unknown yeast ORFome.

    View details for DOI 10.1073/pnas.192159399

    View details for Web of Science ID 000178391700053

    View details for PubMedID 12196633

Stanford Medicine Resources: