Publications by authors named "Robert J Tibshirani"

42 Publications

An approach to explore for a sweet spot in randomized trials.

J Clin Epidemiol 2020 04 23;120:59-66. Epub 2019 Dec 23.

Department of Biomedical Data Sciences, Stanford University, Stanford, CA, USA; Department of Statistics, Stanford University, Stanford, CA, USA.

Objective: The objective of the study was to demonstrate how a conventional randomized trial can be analyzed through a stratified or a matched approach to identify a potential sweet spot where observed differences might be accentuated in the mid range of disease severity.

Design And Setting: We review a landmark randomized trial of heart failure patients that tested whether implantable defibrillators reduce mortality (n = 2,521).

Results: Overall, 22% (182/829) of the patients in the defibrillator group died compared with 29% (484/1,692) of patients in the control group. Proportional hazards analysis yielded a modest 25% survival benefit (hazard ratio = 0.75, 95% confidence interval: 0.63 to 0.89). Stratified analysis of the trial yielded a larger 52% survival benefit for those in the middle quintile of disease severity (hazard ratio = 0.48, 95% confidence interval: 0.29 to 0.79). In contrast, little of the survival benefit was explained by patients with the greatest disease severity (hazard ratio = 0.89, 95% confidence interval: 0.69 to 1.15). The discrepancy between crude and stratified analyses could be visualized by graphical displays and replicated with matched comparisons.

Conclusion: Our approach for analyzing a randomized trial could help identify a potential sweet spot of an accentuated treatment effect.
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http://dx.doi.org/10.1016/j.jclinepi.2019.12.012DOI Listing
April 2020

Increased T Cell Differentiation and Cytolytic Function in Bangladeshi Compared to American Children.

Front Immunol 2019 20;10:2239. Epub 2019 Sep 20.

Department of Microbiology and Immunology, Stanford University, Stanford, CA, United States.

During the first 5 years of life, children are especially vulnerable to infection-related morbidity and mortality. Conversely, the Hygiene Hypothesis suggests that a lack of exposure to infectious agents early in life could explain the increasing incidence of allergies and autoimmunity in high-income countries. Understanding these phenomena, however, is hampered by a lack of comprehensive, direct immune monitoring in children with differing degrees of microbial exposure. Using mass cytometry, we provide an in-depth profile of the peripheral blood mononuclear cells (PBMCs) of children in regions at the extremes of exposure: the San Francisco Bay Area, USA and an economically poor district of Dhaka, Bangladesh. Despite variability in clinical health, functional characteristics of PBMCs were similar in Bangladeshi and American children at 1 year of age. However, by 2-3 years of age, Bangladeshi children's immune cells often demonstrated altered activation and cytokine production profiles upon stimulation with PMA-ionomycin, with an overall immune trajectory more in line with American adults. Conversely, immune responses in children from the US remained steady. Using principal component analysis, donor location, ethnic background, and cytomegalovirus infection status were found to account for some of the variation identified among samples. Within Bangladeshi 1-year-olds, stunting (as measured by height-for-age z-scores) was found to be associated with IL-8 and TGFβ expression in PMA-ionomycin stimulated samples. Combined, these findings provide important insights into the immune systems of children in high vs. low microbial exposure environments and suggest an important role for IL-8 and TGFβ in mitigating the microbial challenges faced by the Bangladeshi children.
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http://dx.doi.org/10.3389/fimmu.2019.02239DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6763580PMC
October 2020

Early detection of unilateral ureteral obstruction by desorption electrospray ionization mass spectrometry.

Sci Rep 2019 07 29;9(1):11007. Epub 2019 Jul 29.

Department of Urology, Stanford University School of Medicine, Stanford, CA, 94305, USA.

Desorption electrospray ionization mass spectrometry (DESI-MS) is an emerging analytical tool for rapid in situ assessment of metabolomic profiles on tissue sections without tissue pretreatment or labeling. We applied DESI-MS to identify candidate metabolic biomarkers associated with kidney injury at the early stage. DESI-MS was performed on sections of kidneys from 80 mice over a time course following unilateral ureteral obstruction (UUO) and compared to sham controls. A predictive model of renal damage was constructed using the LASSO (least absolute shrinkage and selection operator) method. Levels of lipid and small metabolites were significantly altered and glycerophospholipids comprised a significant fraction of altered species. These changes correlate with altered expression of lipid metabolic genes, with most genes showing decreased expression. However, rapid upregulation of PG(22:6/22:6) level appeared to be a hitherto unknown feature of the metabolic shift observed in UUO. Using LASSO and SAM (significance analysis of microarrays), we identified a set of well-measured metabolites that accurately predicted UUO-induced renal damage that was detectable by 12 h after UUO, prior to apparent histological changes. Thus, DESI-MS could serve as a useful adjunct to histology in identifying renal damage and demonstrates early and broad changes in membrane associated lipids.
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http://dx.doi.org/10.1038/s41598-019-47396-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6662848PMC
July 2019

Found In Translation: a machine learning model for mouse-to-human inference.

Nat Methods 2018 12 26;15(12):1067-1073. Epub 2018 Nov 26.

Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel.

Cross-species differences form barriers to translational research that ultimately hinder the success of clinical trials, yet knowledge of species differences has yet to be systematically incorporated in the interpretation of animal models. Here we present Found In Translation (FIT; http://www.mouse2man.org ), a statistical methodology that leverages public gene expression data to extrapolate the results of a new mouse experiment to expression changes in the equivalent human condition. We applied FIT to data from mouse models of 28 different human diseases and identified experimental conditions in which FIT predictions outperformed direct cross-species extrapolation from mouse results, increasing the overlap of differentially expressed genes by 20-50%. FIT predicted novel disease-associated genes, an example of which we validated experimentally. FIT highlights signals that may otherwise be missed and reduces false leads, with no experimental cost.
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http://dx.doi.org/10.1038/s41592-018-0214-9DOI Listing
December 2018

Analyzing excess risk from matched designs with double controls: author's response.

J Clin Epidemiol 2019 03 16;107:127-128. Epub 2018 Nov 16.

Department of Statistics, Stanford University, Stanford, CA, USA.

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http://dx.doi.org/10.1016/j.jclinepi.2018.11.009DOI Listing
March 2019

Reply to Vickers: Pharmacogenetics and progression to neovascular age-related macular degeneration-Evidence supporting practice change.

Proc Natl Acad Sci U S A 2018 06 7;115(25):E5640-E5641. Epub 2018 Jun 7.

Dalla Lana School of Public Health, University of Toronto, Toronto, ON M5T 3M7, Canada.

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http://dx.doi.org/10.1073/pnas.1804781115DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6016766PMC
June 2018

Distinguishing malignant from benign microscopic skin lesions using desorption electrospray ionization mass spectrometry imaging.

Proc Natl Acad Sci U S A 2018 06 4;115(25):6347-6352. Epub 2018 Jun 4.

Department of Chemistry, Stanford University, Stanford, CA 94305;

Detection of microscopic skin lesions presents a considerable challenge in diagnosing early-stage malignancies as well as in residual tumor interrogation after surgical intervention. In this study, we established the capability of desorption electrospray ionization mass spectrometry imaging (DESI-MSI) to distinguish between micrometer-sized tumor aggregates of basal cell carcinoma (BCC), a common skin cancer, and normal human skin. We analyzed 86 human specimens collected during Mohs micrographic surgery for BCC to cross-examine spatial distributions of numerous lipids and metabolites in BCC aggregates versus adjacent skin. Statistical analysis using the least absolute shrinkage and selection operation (Lasso) was employed to categorize each 200-µm-diameter picture element (pixel) of investigated skin tissue map as BCC or normal. Lasso identified 24 molecular ion signals, which are significant for pixel classification. These ion signals included lipids observed at / 200-1,200 and Krebs cycle metabolites observed at / < 200. Based on these features, Lasso yielded an overall 94.1% diagnostic accuracy pixel by pixel of the skin map compared with histopathological evaluation. We suggest that DESI-MSI/Lasso analysis can be employed as a complementary technique for delineation of microscopic skin tumors.
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http://dx.doi.org/10.1073/pnas.1803733115DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6016785PMC
June 2018

Methods for analyzing matched designs with double controls: excess risk is easily estimated and misinterpreted when evaluating traffic deaths.

J Clin Epidemiol 2018 06 13;98:117-122. Epub 2018 Feb 13.

Department of Biomedical Data Sciences, Stanford University, 450 Serra Mall, Stanford, CA 94305, USA; Department of Statistics, Stanford University, 450 Serra Mall, Stanford, CA 94305, USA.

Objectives: To demonstrate analytic approaches for matched studies where two controls are linked to each case and events are accumulating counts rather than binary outcomes. A secondary intent is to clarify the distinction between total risk and excess risk (unmatched vs. matched perspectives).

Study Design And Setting: We review past research testing whether elections can lead to increased traffic risks. The results are reinterpreted by analyzing both the total count of individuals in fatal crashes and the excess count of individuals in fatal crashes, each time accounting for the matched double controls.

Results: Overall, 1,546 individuals were in fatal crashes on the 10 election days (average = 155/d), and 2,593 individuals were in fatal crashes on the 20 control days (average = 130/d). Poisson regression of total counts yielded a relative risk of 1.19 (95% confidence interval: 1.12-1.27). Poisson regression of excess counts yielded a relative risk of 3.22 (95% confidence interval: 2.72-3.80). The discrepancy between analyses of total counts and excess counts replicated with alternative statistical models and was visualized in graphical displays.

Conclusion: Available approaches provide methods for analyzing count data in matched designs with double controls and help clarify the distinction between increases in total risk and increases in excess risk.
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http://dx.doi.org/10.1016/j.jclinepi.2018.02.005DOI Listing
June 2018

and genetic risk determines progression to neovascular age-related macular degeneration after antioxidant and zinc supplementation.

Proc Natl Acad Sci U S A 2018 01 8;115(4):E696-E704. Epub 2018 Jan 8.

Dalla Lana School of Public Health, University of Toronto, Toronto, ON M5T 3M7, Canada.

We evaluated the influence of an antioxidant and zinc nutritional supplement [the Age-Related Eye Disease Study (AREDS) formulation] on delaying or preventing progression to neovascular AMD (NV) in persons with age-related macular degeneration (AMD). AREDS subjects ( = 802) with category 3 or 4 AMD at baseline who had been treated with placebo or the AREDS formulation were evaluated for differences in the risk of progression to NV as a function of () and () genotype groups. We used published genetic grouping: a two-SNP haplotype risk-calling algorithm to assess , and either the single SNP rs10490924 or 372_815del443ins54 to mark risk. Progression risk was determined using the Cox proportional hazard model. Genetics-treatment interaction on NV risk was assessed using a multiiterative bootstrap validation analysis. We identified strong interaction of genetics with AREDS formulation treatment on the development of NV. Individuals with high and no risk alleles and taking the AREDS formulation had increased progression to NV compared with placebo. Those with low risk and high risk had decreased progression risk. Analysis of and genotype groups from a validation dataset reinforces this conclusion. Bootstrapping analysis confirms the presence of a genetics-treatment interaction and suggests that individual treatment response to the AREDS formulation is largely determined by genetics. The AREDS formulation modifies the risk of progression to NV based on individual genetics. Its use should be based on patient-specific genotype.
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http://dx.doi.org/10.1073/pnas.1718059115DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5789949PMC
January 2018

Big data modeling to predict platelet usage and minimize wastage in a tertiary care system.

Proc Natl Acad Sci U S A 2017 10 9;114(43):11368-11373. Epub 2017 Oct 9.

Department of Pathology, Stanford University, Stanford, CA 94305;

Maintaining a robust blood product supply is an essential requirement to guarantee optimal patient care in modern health care systems. However, daily blood product use is difficult to anticipate. Platelet products are the most variable in daily usage, have short shelf lives, and are also the most expensive to produce, test, and store. Due to the combination of absolute need, uncertain daily demand, and short shelf life, platelet products are frequently wasted due to expiration. Our aim is to build and validate a statistical model to forecast future platelet demand and thereby reduce wastage. We have investigated platelet usage patterns at our institution, and specifically interrogated the relationship between platelet usage and aggregated hospital-wide patient data over a recent consecutive 29-mo period. Using a convex statistical formulation, we have found that platelet usage is highly dependent on weekday/weekend pattern, number of patients with various abnormal complete blood count measurements, and location-specific hospital census data. We incorporated these relationships in a mathematical model to guide collection and ordering strategy. This model minimizes waste due to expiration while avoiding shortages; the number of remaining platelet units at the end of any day stays above 10 in our model during the same period. Compared with historical expiration rates during the same period, our model reduces the expiration rate from 10.5 to 3.2%. Extrapolating our results to the ∼2 million units of platelets transfused annually within the United States, if implemented successfully, our model can potentially save ∼80 million dollars in health care costs.
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http://dx.doi.org/10.1073/pnas.1714097114DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5664553PMC
October 2017

Diagnosis of prostate cancer by desorption electrospray ionization mass spectrometric imaging of small metabolites and lipids.

Proc Natl Acad Sci U S A 2017 03 14;114(13):3334-3339. Epub 2017 Mar 14.

Department of Urology, Stanford University School of Medicine, Stanford, CA 94305.

Accurate identification of prostate cancer in frozen sections at the time of surgery can be challenging, limiting the surgeon's ability to best determine resection margins during prostatectomy. We performed desorption electrospray ionization mass spectrometry imaging (DESI-MSI) on 54 banked human cancerous and normal prostate tissue specimens to investigate the spatial distribution of a wide variety of small metabolites, carbohydrates, and lipids. In contrast to several previous studies, our method included Krebs cycle intermediates ( <200), which we found to be highly informative in distinguishing cancer from benign tissue. Malignant prostate cells showed marked metabolic derangements compared with their benign counterparts. Using the "Least absolute shrinkage and selection operator" (Lasso), we analyzed all metabolites from the DESI-MS data and identified parsimonious sets of metabolic profiles for distinguishing between cancer and normal tissue. In an independent set of samples, we could use these models to classify prostate cancer from benign specimens with nearly 90% accuracy per patient. Based on previous work in prostate cancer showing that glucose levels are high while citrate is low, we found that measurement of the glucose/citrate ion signal ratio accurately predicted cancer when this ratio exceeds 1.0 and normal prostate when the ratio is less than 0.5. After brief tissue preparation, the glucose/citrate ratio can be recorded on a tissue sample in 1 min or less, which is in sharp contrast to the 20 min or more required by histopathological examination of frozen tissue specimens.
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http://dx.doi.org/10.1073/pnas.1700677114DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5380053PMC
March 2017

High-dimensional regression adjustments in randomized experiments.

Proc Natl Acad Sci U S A 2016 Nov 25;113(45):12673-12678. Epub 2016 Oct 25.

Department of Statistics, Stanford University, Stanford, CA 94305;

We study the problem of treatment effect estimation in randomized experiments with high-dimensional covariate information and show that essentially any risk-consistent regression adjustment can be used to obtain efficient estimates of the average treatment effect. Our results considerably extend the range of settings where high-dimensional regression adjustments are guaranteed to provide valid inference about the population average treatment effect. We then propose cross-estimation, a simple method for obtaining finite-sample-unbiased treatment effect estimates that leverages high-dimensional regression adjustments. Our method can be used when the regression model is estimated using the lasso, the elastic net, subset selection, etc. Finally, we extend our analysis to allow for adaptive specification search via cross-validation and flexible nonparametric regression adjustments with machine-learning methods such as random forests or neural networks.
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http://dx.doi.org/10.1073/pnas.1614732113DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5111650PMC
November 2016

A simple method for analyzing matched designs with double controls: McNemar's test can be extended.

J Clin Epidemiol 2017 01 24;81:51-55.e2. Epub 2016 Aug 24.

Department of Statistics, Stanford University, Stanford, CA, USA.

Objectives: To introduce a new analytic approach for matched studies, where exactly two controls are linked to each case (double controls rather than solitary controls). The intent is to extend McNemar's test for one-to-two matching (instead of one-to-one matching) when evaluating binary predictors and outcomes.

Study Design And Setting: We review McNemar's approach for analyzing matched data, demonstrate the Mantel-Haenszel approach for integrating two overlapping McNemar's estimates, review conditional logistic regression as an alternative analytic approach, and introduce a new method that yields a visual display and easy verification.

Results: We illustrate the new approach with real data testing the association between overcast weather and the risk of a life-threatening traffic crash (n = 6,962). We show that results from the new approach agree closely with conditional logistic regression and are sufficiently simple as to be computed on a handheld calculator. We further validate the approach by conducting simulations when a positive association was predefined and when a null association was predefined.

Conclusion: The new approach provides a feasible, simple, and efficient method for analyzing matched designs with double controls.
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http://dx.doi.org/10.1016/j.jclinepi.2016.08.006DOI Listing
January 2017

Successful immunotherapy induces previously unidentified allergen-specific CD4+ T-cell subsets.

Proc Natl Acad Sci U S A 2016 Mar 25;113(9):E1286-95. Epub 2016 Jan 25.

Sean N. Parker Center for Allergy and Asthma Research at Stanford University, Pulmonary and Critical Care Medicine, Institute of Immunity, Transplantation, and Infectious Diseases, Stanford University, Stanford, CA 94305;

Allergen immunotherapy can desensitize even subjects with potentially lethal allergies, but the changes induced in T cells that underpin successful immunotherapy remain poorly understood. In a cohort of peanut-allergic participants, we used allergen-specific T-cell sorting and single-cell gene expression to trace the transcriptional "roadmap" of individual CD4+ T cells throughout immunotherapy. We found that successful immunotherapy induces allergen-specific CD4+ T cells to expand and shift toward an "anergic" Th2 T-cell phenotype largely absent in both pretreatment participants and healthy controls. These findings show that sustained success, even after immunotherapy is withdrawn, is associated with the induction, expansion, and maintenance of immunotherapy-specific memory and naive T-cell phenotypes as early as 3 mo into immunotherapy. These results suggest an approach for immune monitoring participants undergoing immunotherapy to predict the success of future treatment and could have implications for immunotherapy targets in other diseases like cancer, autoimmune disease, and transplantation.
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http://dx.doi.org/10.1073/pnas.1520180113DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4780622PMC
March 2016

The Radiogenomic Risk Score: Construction of a Prognostic Quantitative, Noninvasive Image-based Molecular Assay for Renal Cell Carcinoma.

Radiology 2015 Oct 19;277(1):114-23. Epub 2015 Aug 19.

From the Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Box 951721, CHS 17-135, 10833 LeConte Ave, Los Angeles, CA 90095-1721 (N.J., M.Z., S.B., M.D.K.); Department of Genitourinary Medical Oncology, The University of Texas M.D. Anderson Cancer Center, Houston, Tex (E.J.); Department of Radiology, Hospital of Veterans Affairs, University of California-San Diego, San Diego, Calif (M.Z., L.A.); Scottsdale Medical Imaging, Scottsdale, Ariz (R.K.); Department of Urology, Stanford University School of Medicine, Stanford, Calif (H.Z., J.D.B.); Department of Surgical and Perioperative Sciences, Urology and Andrology, Umea Hospital, Umea, Sweden (R.T.S., B.L.); and Department of Statistics, Stanford University, Stanford, Calif (R.J.T.).

Purpose: To evaluate the feasibility of constructing radiogenomic-based surrogates of molecular assays (SOMAs) in patients with clear-cell renal cell carcinoma (CCRCC) by using data extracted from a single computed tomographic (CT) image.

Materials And Methods: In this institutional review board approved study, gene expression profile data and contrast material-enhanced CT images from 70 patients with CCRCC in a training set were independently assessed by two radiologists for a set of predefined imaging features. A SOMA for a previously validated CCRCC-specific supervised principal component (SPC) risk score prognostic gene signature was constructed and termed the radiogenomic risk score (RRS). It uses the microarray data and a 28-trait image array to evaluate each CT image with multiple regression of gene expression analysis. The predictive power of the RRS SOMA was then prospectively validated in an independent dataset to confirm its relationship to the SPC gene signature (n = 70) and determination of patient outcome (n = 77). Data were analyzed by using multivariate linear regression-based methods and Cox regression modeling, and significance was assessed with receiver operator characteristic curves and Kaplan-Meier survival analysis.

Results: Our SOMA faithfully represents the tissue-based molecular assay it models. The RRS scaled with the SPC gene signature (R = 0.57, P < .001, classification accuracy 70.1%, P < .001) and predicted disease-specific survival (log rank P < .001). Independent validation confirmed the relationship between the RRS and the SPC gene signature (R = 0.45, P < .001, classification accuracy 68.6%, P < .001) and disease-specific survival (log-rank P < .001) and that it was independent of stage, grade, and performance status (multivariate Cox model P < .05, log-rank P < .001).

Conclusion: A SOMA for the CCRCC-specific SPC prognostic gene signature that is predictive of disease-specific survival and independent of stage was constructed and validated, confirming that SOMA construction is feasible.
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http://dx.doi.org/10.1148/radiol.2015150800DOI Listing
October 2015

Statistical learning and selective inference.

Proc Natl Acad Sci U S A 2015 Jun;112(25):7629-34

Department of Health Research & Policy and Department of Statistics, Stanford University, Stanford, CA 94305

We describe the problem of "selective inference." This addresses the following challenge: Having mined a set of data to find potential associations, how do we properly assess the strength of these associations? The fact that we have "cherry-picked"--searched for the strongest associations--means that we must set a higher bar for declaring significant the associations that we see. This challenge becomes more important in the era of big data and complex statistical modeling. The cherry tree (dataset) can be very large and the tools for cherry picking (statistical learning methods) are now very sophisticated. We describe some recent new developments in selective inference and illustrate their use in forward stepwise regression, the lasso, and principal components analysis.
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http://dx.doi.org/10.1073/pnas.1507583112DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4485109PMC
June 2015

Fibromyalgia and the Risk of a Subsequent Motor Vehicle Crash.

J Rheumatol 2015 Aug 15;42(8):1502-10. Epub 2015 May 15.

From the Department of Medicine, University of Toronto; Evaluative Clinical Sciences Platform, Sunnybrook Research Institute; Institute for Clinical Evaluative Sciences in Ontario; Division of General Internal Medicine, Sunnybrook Health Sciences Centre; Center for Leading Injury Prevention Practice Education and Research, Toronto, Ontario, Canada; Department of Statistics, Stanford University, Stanford, California, USA.D.A. Redelmeier, MD, FRCPC, MSHSR, FACP, Department of Medicine, University of Toronto, and the Evaluative Clinical Sciences Platform, Sunnybrook Research Institute, and the Institute for Clinical Evaluative Sciences in Ontario, and Division of General Internal Medicine, Sunnybrook Health Sciences Centre, and the Center for Leading Injury Prevention Practice Education and Research; J.D. Zung, BSc, Department of Medicine, University of Toronto, and the Evaluative Clinical Sciences Platform, Sunnybrook Research Institute, and the Institute for Clinical Evaluative Sciences in Ontario; D. Thiruchelvam, MSc, Evaluative Clinical Sciences Platform, Sunnybrook Research Institute, and the Institute for Clinical Evaluative Sciences in Ontario; R.J. Tibshirani, PhD, Department of Statistics, Stanford University.

Objective: Motor vehicle crashes are a widespread contributor to mortality and morbidity, sometimes related to medically unfit motorists. We tested whether patients diagnosed with fibromyalgia (FM) have an increased risk of a subsequent serious motor vehicle crash.

Methods: We conducted a population-based self-matched longitudinal cohort analysis to estimate the incidence rate ratio of crashes among patients diagnosed with FM relative to the population norm in Ontario, Canada. We included adults diagnosed from April 1, 2006, to March 31, 2012, excluding individuals younger than 18 years, living outside Ontario, lacking valid identifiers, or having only a single visit for the diagnosis. The primary outcome was an emergency department visit as a driver involved in a motor vehicle crash.

Results: The patients (n = 137,631) accounted for 738 crashes during the first year of followup after diagnosis, equal to an incidence rate ratio of 2.44 compared with the population norm (95% CI 2.27-2.63, p < 0.001). The crash rate was more than twice the population norm for those with a new or a persistent diagnosis. The increased risk included patients with diverse characteristics, approached the rate observed among other patients diagnosed with alcoholism, and was mitigated among those who received dedicated FM care or a physician warning for driving safety.

Conclusion: A diagnosis of FM is associated with an increased risk of a subsequent motor vehicle crash that might justify medical interventions for traffic safety.
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http://dx.doi.org/10.3899/jrheum.141315DOI Listing
August 2015

Alteration of the lipid profile in lymphomas induced by MYC overexpression.

Proc Natl Acad Sci U S A 2014 Jul 3;111(29):10450-5. Epub 2014 Jul 3.

Department of Chemistry, Stanford University, Stanford, CA 94305-5080;

Overexpression of the v-myc avian myelocytomatosis viral oncogene homolog (MYC) oncogene is one of the most commonly implicated causes of human tumorigenesis. MYC is known to regulate many aspects of cellular biology including glucose and glutamine metabolism. Little is known about the relationship between MYC and the appearance and disappearance of specific lipid species. We use desorption electrospray ionization mass spectrometry imaging (DESI-MSI), statistical analysis, and conditional transgenic animal models and cell samples to investigate changes in lipid profiles in MYC-induced lymphoma. We have detected a lipid signature distinct from that observed in normal tissue and in rat sarcoma-induced lymphoma cells. We found 104 distinct molecular ions that have an altered abundance in MYC lymphoma compared with normal control tissue by statistical analysis with a false discovery rate of less than 5%. Of these, 86 molecular ions were specifically identified as complex phospholipids. To evaluate whether the lipid signature could also be observed in human tissue, we examined 15 human lymphoma samples with varying expression levels of MYC oncoprotein. Distinct lipid profiles in lymphomas with high and low MYC expression were observed, including many of the lipid species identified as significant for MYC-induced animal lymphoma tissue. Our results suggest a relationship between the appearance of specific lipid species and the overexpression of MYC in lymphomas.
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http://dx.doi.org/10.1073/pnas.1409778111DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4115527PMC
July 2014

Automated identification of stratifying signatures in cellular subpopulations.

Proc Natl Acad Sci U S A 2014 Jul 16;111(26):E2770-7. Epub 2014 Jun 16.

Baxter Laboratory for Stem Cell Biology, Department of Microbiology and Immunology, and

Elucidation and examination of cellular subpopulations that display condition-specific behavior can play a critical contributory role in understanding disease mechanism, as well as provide a focal point for development of diagnostic criteria linking such a mechanism to clinical prognosis. Despite recent advancements in single-cell measurement technologies, the identification of relevant cell subsets through manual efforts remains standard practice. As new technologies such as mass cytometry increase the parameterization of single-cell measurements, the scalability and subjectivity inherent in manual analyses slows both analysis and progress. We therefore developed Citrus (cluster identification, characterization, and regression), a data-driven approach for the identification of stratifying subpopulations in multidimensional cytometry datasets. The methodology of Citrus is demonstrated through the identification of known and unexpected pathway responses in a dataset of stimulated peripheral blood mononuclear cells measured by mass cytometry. Additionally, the performance of Citrus is compared with that of existing methods through the analysis of several publicly available datasets. As the complexity of flow cytometry datasets continues to increase, methods such as Citrus will be needed to aid investigators in the performance of unbiased--and potentially more thorough--correlation-based mining and inspection of cell subsets nested within high-dimensional datasets.
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http://dx.doi.org/10.1073/pnas.1408792111DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4084463PMC
July 2014

LMO2 and BCL6 are associated with improved survival in primary central nervous system lymphoma.

Br J Haematol 2014 Jun 26;165(5):640-8. Epub 2014 Feb 26.

Division of Hematology-Oncology, Department of Medicine, Sylvester Comprehensive Cancer Center, University of Miami, Miami, FL, USA.

Primary central nervous system lymphoma (PCNSL) is an aggressive sub-variant of non-Hodgkin lymphoma (NHL) with morphological similarities to diffuse large B-cell lymphoma (DLBCL). While methotrexate (MTX)-based therapies have improved patient survival, the disease remains incurable in most cases and its pathogenesis is poorly understood. We evaluated 69 cases of PCNSL for the expression of HGAL (also known as GCSAM), LMO2 and BCL6 - genes associated with DLBCL prognosis and pathobiology, and analysed their correlation to survival in 49 PCNSL patients receiving MTX-based therapy. We demonstrate that PCNSL expresses LMO2, HGAL(also known as GCSAM) and BCL6 proteins in 52%, 65% and 56% of tumours, respectively. BCL6 protein expression was associated with longer progression-free survival (P = 0·006) and overall survival (OS, P = 0·05), while expression of LMO2 protein was associated with longer OS (P = 0·027). Further research is needed to elucidate the function of BCL6 and LMO2 in PCNSL.
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http://dx.doi.org/10.1111/bjh.12801DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4123533PMC
June 2014

Molecular assessment of surgical-resection margins of gastric cancer by mass-spectrometric imaging.

Proc Natl Acad Sci U S A 2014 Feb 3;111(7):2436-41. Epub 2014 Feb 3.

Department of Chemistry, Stanford University, Stanford, CA 94305-5080.

Surgical resection is the main curative option for gastrointestinal cancers. The extent of cancer resection is commonly assessed during surgery by pathologic evaluation of (frozen sections of) the tissue at the resected specimen margin(s) to verify whether cancer is present. We compare this method to an alternative procedure, desorption electrospray ionization mass spectrometric imaging (DESI-MSI), for 62 banked human cancerous and normal gastric-tissue samples. In DESI-MSI, microdroplets strike the tissue sample, the resulting splash enters a mass spectrometer, and a statistical analysis, here, the Lasso method (which stands for least absolute shrinkage and selection operator and which is a multiclass logistic regression with L1 penalty), is applied to classify tissues based on the molecular information obtained directly from DESI-MSI. The methodology developed with 28 frozen training samples of clear histopathologic diagnosis showed an overall accuracy value of 98% for the 12,480 pixels evaluated in cross-validation (CV), and 97% when a completely independent set of samples was tested. By applying an additional spatial smoothing technique, the accuracy for both CV and the independent set of samples was 99% compared with histological diagnoses. To test our method for clinical use, we applied it to a total of 21 tissue-margin samples prospectively obtained from nine gastric-cancer patients. The results obtained suggest that DESI-MSI/Lasso may be valuable for routine intraoperative assessment of the specimen margins during gastric-cancer surgery.
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http://dx.doi.org/10.1073/pnas.1400274111DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3932851PMC
February 2014

Systems analysis of sex differences reveals an immunosuppressive role for testosterone in the response to influenza vaccination.

Proc Natl Acad Sci U S A 2014 Jan 23;111(2):869-74. Epub 2013 Dec 23.

Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94305-5323.

Females have generally more robust immune responses than males for reasons that are not well-understood. Here we used a systems analysis to investigate these differences by analyzing the neutralizing antibody response to a trivalent inactivated seasonal influenza vaccine (TIV) and a large number of immune system components, including serum cytokines and chemokines, blood cell subset frequencies, genome-wide gene expression, and cellular responses to diverse in vitro stimuli, in 53 females and 34 males of different ages. We found elevated antibody responses to TIV and expression of inflammatory cytokines in the serum of females compared with males regardless of age. This inflammatory profile correlated with the levels of phosphorylated STAT3 proteins in monocytes but not with the serological response to the vaccine. In contrast, using a machine learning approach, we identified a cluster of genes involved in lipid biosynthesis and previously shown to be up-regulated by testosterone that correlated with poor virus-neutralizing activity in men. Moreover, men with elevated serum testosterone levels and associated gene signatures exhibited the lowest antibody responses to TIV. These results demonstrate a strong association between androgens and genes involved in lipid metabolism, suggesting that these could be important drivers of the differences in immune responses between males and females.
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http://dx.doi.org/10.1073/pnas.1321060111DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3896147PMC
January 2014

Identification of gene microarray expression profiles in patients with chronic graft-versus-host disease following allogeneic hematopoietic cell transplantation.

Clin Immunol 2013 Jul 1;148(1):124-35. Epub 2013 May 1.

Department of Medicine Stanford University School of Medicine, 300 Pasteur Drive, Stanford, CA 94305 USA.

Chronic graft-versus-host disease (GVHD) results in significant morbidity and mortality, limiting the benefit of allogeneic hematopoietic cell transplantation (HCT). Peripheral blood gene expression profiling of the donor immune repertoire following HCT may provide associated genes and pathways thereby improving the pathophysiologic understanding of chronic GVHD. We profiled 70 patients and identified candidate genes that provided mechanistic insight in the biologic pathways that underlie chronic GVHD. Our data revealed that the dominant gene signature in patients with chronic GVHD represented compensatory responses that control inflammation and included the interleukin-1 decoy receptor, IL-1 receptor type II, and genes that were profibrotic and associated with the IL-4, IL-6 and IL-10 signaling pathways. In addition, we identified three genes that were important regulators of extracellular matrix. Validation of this discovery phase study will determine if the identified genes have diagnostic, prognostic or therapeutic implications.
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http://dx.doi.org/10.1016/j.clim.2013.04.013DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8166221PMC
July 2013

Sparse estimation of a covariance matrix.

Biometrika 2011 Dec;98(4):807-820

Departments of Statistics and Health, Research & Policy, Stanford University, Sequoia Hall, 390 Serra Mall, Stanford, California 94305-4065, U.S.A.

We suggest a method for estimating a covariance matrix on the basis of a sample of vectors drawn from a multivariate normal distribution. In particular, we penalize the likelihood with a lasso penalty on the entries of the covariance matrix. This penalty plays two important roles: it reduces the effective number of parameters, which is important even when the dimension of the vectors is smaller than the sample size since the number of parameters grows quadratically in the number of variables, and it produces an estimate which is sparse. In contrast to sparse inverse covariance estimation, our method's close relative, the sparsity attained here is in the covariance matrix itself rather than in the inverse matrix. Zeros in the covariance matrix correspond to marginal independencies; thus, our method performs model selection while providing a positive definite estimate of the covariance. The proposed penalized maximum likelihood problem is not convex, so we use a majorize-minimize approach in which we iteratively solve convex approximations to the original nonconvex problem. We discuss tuning parameter selection and demonstrate on a flow-cytometry dataset how our method produces an interpretable graphical display of the relationship between variables. We perform simulations that suggest that simple elementwise thresholding of the empirical covariance matrix is competitive with our method for identifying the sparsity structure. Additionally, we show how our method can be used to solve a previously studied special case in which a desired sparsity pattern is prespecified.
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http://dx.doi.org/10.1093/biomet/asr054DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3413177PMC
December 2011

Physicians' warnings for unfit drivers and the risk of trauma from road crashes.

N Engl J Med 2012 Sep;367(13):1228-36

Department of Medicine, University of Toronto, Toronto, ON, Canada.

Background: Physicians' warnings to patients who are potentially unfit to drive are a medical intervention intended to prevent trauma from motor vehicle crashes. We assessed the association between medical warnings and the risk of subsequent road crashes.

Methods: We identified consecutive patients who received a medical warning in Ontario, Canada, between April 1, 2006, and December 31, 2009, from a physician who judged them to be potentially unfit to drive. We excluded patients who were younger than 18 years of age, who were not residents of Ontario, or who lacked valid health-card numbers under universal health insurance. We analyzed emergency department visits for road crashes during a baseline interval before the warning and a subsequent interval after the warning.

Results: A total of 100,075 patients received a medical warning from a total of 6098 physicians. During the 3-year baseline interval, there were 1430 road crashes in which the patient was a driver and presented to the emergency department, as compared with 273 road crashes during the 1-year subsequent interval, representing a reduction of approximately 45% in the annual rate of crashes per 1000 patients after the warning (4.76 vs. 2.73, P<0.001). The lower rate was observed across patients with diverse characteristics. No significant change was observed in subsequent crashes in which patients were pedestrians or passengers. Medical warnings were associated with an increase in subsequent emergency department visits for depression and a decrease in return visits to the responsible physician.

Conclusions: Physicians' warnings to patients who are potentially unfit to drive may contribute to a decrease in subsequent trauma from road crashes, yet they may also exacerbate mood disorders and compromise the doctor-patient relationship. (Funded by the Canada Research Chairs program and others.).
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http://dx.doi.org/10.1056/NEJMsa1114310DOI Listing
September 2012

Autoantibody epitope spreading in the pre-clinical phase predicts progression to rheumatoid arthritis.

PLoS One 2012 25;7(5):e35296. Epub 2012 May 25.

Division of Rheumatology, Department of Medicine, Stanford University School of Medicine, Stanford, California, United States of America.

Rheumatoid arthritis (RA) is a prototypical autoimmune arthritis affecting nearly 1% of the world population and is a significant cause of worldwide disability. Though prior studies have demonstrated the appearance of RA-related autoantibodies years before the onset of clinical RA, the pattern of immunologic events preceding the development of RA remains unclear. To characterize the evolution of the autoantibody response in the preclinical phase of RA, we used a novel multiplex autoantigen array to evaluate development of the anti-citrullinated protein antibodies (ACPA) and to determine if epitope spread correlates with rise in serum cytokines and imminent onset of clinical RA. To do so, we utilized a cohort of 81 patients with clinical RA for whom stored serum was available from 1-12 years prior to disease onset. We evaluated the accumulation of ACPA subtypes over time and correlated this accumulation with elevations in serum cytokines. We then used logistic regression to identify a profile of biomarkers which predicts the imminent onset of clinical RA (defined as within 2 years of testing). We observed a time-dependent expansion of ACPA specificity with the number of ACPA subtypes. At the earliest timepoints, we found autoantibodies targeting several innate immune ligands including citrullinated histones, fibrinogen, and biglycan, thus providing insights into the earliest autoantigen targets and potential mechanisms underlying the onset and development of autoimmunity in RA. Additionally, expansion of the ACPA response strongly predicted elevations in many inflammatory cytokines including TNF-α, IL-6, IL-12p70, and IFN-γ. Thus, we observe that the preclinical phase of RA is characterized by an accumulation of multiple autoantibody specificities reflecting the process of epitope spread. Epitope expansion is closely correlated with the appearance of preclinical inflammation, and we identify a biomarker profile including autoantibodies and cytokines which predicts the imminent onset of clinical arthritis.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0035296PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3360701PMC
December 2012

In situ vaccination against mycosis fungoides by intratumoral injection of a TLR9 agonist combined with radiation: a phase 1/2 study.

Blood 2012 Jan 1;119(2):355-63. Epub 2011 Nov 1.

Department of Dermatology, Stanford University School of Medicine, CA, USA.

We have developed and previously reported on a therapeutic vaccination strategy for indolent B-cell lymphoma that combines local radiation to enhance tumor immunogenicity with the injection into the tumor of a TLR9 agonist. As a result, antitumor CD8(+) T cells are induced, and systemic tumor regression was documented. Because the vaccination occurs in situ, there is no need to manufacture a vaccine product. We have now explored this strategy in a second disease: mycosis fungoides (MF). We treated 15 patients. Clinical responses were assessed at the distant, untreated sites as a measure of systemic antitumor activity. Five clinically meaningful responses were observed. The procedure was well tolerated and adverse effects consisted mostly of mild and transient injection site or flu-like symptoms. The immunized sites showed a significant reduction of CD25(+), Foxp3(+) T cells that could be either MF cells or tissue regulatory T cells and a similar reduction in S100(+), CD1a(+) dendritic cells. There was a trend toward greater reduction of CD25(+) T cells and skin dendritic cells in clinical responders versus nonresponders. Our in situ vaccination strategy is feasible also in MF and the clinical responses that occurred in a subset of patients warrant further study with modifications to augment these therapeutic effects. This study is registered at www.clinicaltrials.gov as NCT00226993.
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http://dx.doi.org/10.1182/blood-2011-05-355222DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3257006PMC
January 2012

Prediction of survival in diffuse large B-cell lymphoma based on the expression of 2 genes reflecting tumor and microenvironment.

Blood 2011 Aug 13;118(5):1350-8. Epub 2011 Jun 13.

Department of Medicine, Division of Oncology, Stanford University, Stanford, CA, USA.

Several gene-expression signatures predict survival in diffuse large B-cell lymphoma (DLBCL), but the lack of practical methods for genome-scale analysis has limited translation to clinical practice. We built and validated a simple model using one gene expressed by tumor cells and another expressed by host immune cells, assessing added prognostic value to the clinical International Prognostic Index (IPI). LIM domain only 2 (LMO2) was validated as an independent predictor of survival and the "germinal center B cell-like" subtype. Expression of tumor necrosis factor receptor superfamily member 9 (TNFRSF9) from the DLBCL microenvironment was the best gene in bivariate combination with LMO2. Study of TNFRSF9 tissue expression in 95 patients with DLBCL showed expression limited to infiltrating T cells. A model integrating these 2 genes was independent of "cell-of-origin" classification, "stromal signatures," IPI, and added to the predictive power of the IPI. A composite score integrating these genes with IPI performed well in 3 independent cohorts of 545 DLBCL patients, as well as in a simple assay of routine formalin-fixed specimens from a new validation cohort of 147 patients with DLBCL. We conclude that the measurement of a single gene expressed by tumor cells (LMO2) and a single gene expressed by the immune microenvironment (TNFRSF9) powerfully predicts overall survival in patients with DLBCL.
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http://dx.doi.org/10.1182/blood-2011-03-345272DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3152499PMC
August 2011

Predicting patient survival from longitudinal gene expression.

Stat Appl Genet Mol Biol 2010 22;9:Article41. Epub 2010 Nov 22.

Stanford University, USA.

Characterizing dynamic gene expression pattern and predicting patient outcome is now significant and will be of more interest in the future with large scale clinical investigation of microarrays. However, there is currently no method that has been developed for prediction of patient outcome using longitudinal gene expression, where gene expression of patients is being monitored across time. Here, we propose a novel prediction approach for patient survival time that makes use of time course structure of gene expression. This method is applied to a burn study. The genes involved in the final predictors are enriched in the inflammatory response and immune system related pathways. Moreover, our method is consistently better than prediction methods using individual time point gene expression or simply pooling gene expression from each time point.
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http://dx.doi.org/10.2202/1544-6115.1617DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3004784PMC
March 2011