DOES POLLEN TRIGGER UROLOGIC CHRONIC PELVIC PAIN SYNDROME FLARES? A CASE-CROSSOVER ANALYSIS IN THE MULTIDISCIPLINARY APPROACH TO THE STUDY OF CHRONIC PELVIC PAIN RESEARCH NETWORK

Abstract

Purpose:

To determine whether pollen triggers urologic chronic pelvic pain syndrome (UCPPS) flares.

Materials and methods:

We assessed flare status every two weeks for one year as part of the Multidisciplinary Approach to the study of Chronic Pelvic Pain (MAPP) case-crossover study of flare triggers. Flare symptoms, flare start date, and exposures in the three days before a flare were queried for the first three flares and at three randomly selected non-flare times. These data were linked to daily pollen count by date and the first three digits of participants’ zip codes. Pollen count in the 3 days before and day of a flare, as well as pollen rises past established thresholds, were compared to non-flare values by conditional logistic regression. Poisson regression was used to estimate flare rates in the three weeks following pollen rises past established thresholds in the full longitudinal study. Analyses were performed in all participants and separately in those who reported allergies or respiratory tract disorders.

Results:

Although no associations were observed for daily pollen count and flare onset, positive associations were observed for pollen count rises past medium or higher thresholds in participants with allergies or respiratory tract disorders in the case-crossover (odds ratio=1.31, 95% confidence interval [CI]: 1.04-1.66) and full longitudinal (relative rate=1.23, 95% CI: 1.03-1.46) samples.

Conclusions:

We found some evidence to suggest that rising pollen count may trigger UCPPS flares. If confirmed in future studies, these findings may help to inform flare pathophysiology, prevention, treatment, and control over the unpredictability of flares.

INTRODUCTION

Urologic chronic pelvic pain syndrome (UCPPS) comprises two conditions, interstitial cystitis/bladder pain syndrome (IC/BPS) and chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS). These two idiopathic conditions are characterized by chronic pelvic or bladder pain, and urinary symptoms such as urinary urgency and frequency. Both conditions are difficult to diagnose and treat,^1,2 and contribute to a large physical, mental, and economic burden for patients.^3-5 Adding further to this burden is the wide and often unpredictable variability of UCPPS symptoms. Symptom exacerbations (or “flares”) range in frequency and manifestation, but can occur as often as multiple times per day, can last up to several weeks to months, and can be severely debilitating (e.g., requiring hospitalization).^6,7

Despite their common occurrence and debilitating nature, little is known about the etiology of flares. Anecdotally, some UCPPS patients report that allergens, such as pollen or animal dander, trigger their flares.^7-9 Although this hypothesis has not been tested empirically, it is consistent with the higher observed prevalence of self-reported allergies and asthma in UCPPS cases than controls in previous studies.^10-14 It is also consistent with anecdotal and observed improvement in IC/BPS symptoms following administration of asthma or allergy therapies,^7,15-18 and UCPPS medications with anti-histamine (amitriptyline and hydroxyzine²) and Mast cell inhibitory properties (pentosan polysulfate sodium^2,19). However, it is seemingly inconsistent with observed improvement following administration of therapeutic pollen extract preparations in randomized controlled trials of CP/CPPS patients.²⁰ Therefore, to address this discrepancy and evaluate whether pollen does in fact trigger UCPPS flares, we took advantage of data collected in our case-crossover study of flare triggers in the Multidisciplinary Approach to the Study of Chronic Pelvic Pain (MAPP) one-year longitudinal study.

METHODS

Study design and population

The MAPP Epidemiology and Phenotyping longitudinal study was designed to better understand the “usual-care” natural history of UCPPS, and to identify sub-groups of patients with possibly differing pathophysiology, clinical course, and, ultimately, response to therapy. Participants were recruited from 11/2009-12/2012 at six main clinical sites (Los Angeles, Seattle, Ann Arbor, Chicago, Iowa City, and St. Louis [with one participant residing in Atlanta]) and two sub-sites (San Francisco and Miami). Participation involved: 1) attending three in-person visits (baseline, 6-months, and 12-months) during which participants completed an extensive series of questionnaires (including current medication use) and provided biologic specimens; and 2) completing a shorter series of bi-weekly online questionnaires.²¹ The MAPP study was approved by the institutional review boards at each participating clinical site and the data coordinating center. All participants provided written informed consent.

To investigate flare triggers, we nested a case-crossover study into the MAPP longitudinal study. Specifically, at each in-person visit and biweekly assessment, we asked participants to report their current flare status (“Are you currently experiencing a flare of your urologic or pelvic pain symptoms. By this we mean, […] symptoms that are much worse than usual”) to identify flare (“case”) and non-flare (“control”) time points. Participants who responded affirmatively were also asked to report their flare start date, current flare symptoms, and exposures in the three days preceding their flare. These questions were asked for the first three flares post-baseline, as well as at three randomly-selected non-flare times (one each per study third).^21,22

Ascertainment and definition of pollen count variables

Daily pollen count data were obtained from IQVIA (Durham, NC; formerly IMS Health) and linked to participants’ flare information by date (date of flare onset for flares and questionnaire completion for non-flares) and the first three digits of participants’ zip code. Missing pollen count data (1.5%) were imputed using values collected on the same day from the nearest zip code within the same geographic region. As the time from flare trigger exposure to flare onset is unknown, we explored several pollen count values in relation to flare onset. These included values on the day of a flare or non-flare assessment (Day 0), and those in the three days before each assessment (Day −1, Day −2, and Day −3). Pollen count values were categorized as: low (0–2.4), low/medium (2.5-4.8), medium (4.9-7.2), medium/high (7.3-9.6), and high (9.7-12) based on a national forecasting scale developed by IQVIA.

To account for the fact that participants might be more sensitive to an initial rise in pollen rather than sustained high levels, we investigated pollen rises past pollen thresholds in the three days before flare and non-flare assessments (i.e., between Days −1 and 0, −2 and −1, and −3 and −2). Initially, thresholds included rises past low/medium, medium, medium/high, and high pollen levels in the spring of each year in each geographic region, and second rises past medium/high or high pollen levels in the fall. However, because of small numbers, we collapsed categories to rises past a low/medium threshold and rises past medium or higher thresholds in the spring or fall.

Finally, to explore the influence of pollen rises further, we identified the first three weeks following initial rises to low/medium and medium or higher pollen levels in the full longitudinal sample. We selected a time frame of three weeks to account for the unknown time between flare trigger exposure and flare onset, and the fact that participants may not have completed their biweekly study assessments exactly every two weeks.

Statistical analysis

All participants who provided information on at least one flare and one non-flare assessment from visit 3 onwards were included in the case-crossover analysis. Daily pollen count values and changes in these values were investigated in relation to flare onset by conditional logistic regression²³ to allow us to compare flare and non-flare assessments from the same participant in the model. Associations were explored first using indicator variables for each exposure category and then summarized by a linear trend. For the analysis of pollen rises and flare frequency, all participants who provided information on flare status at least once from visit 3 onwards were included. Associations between pollen rises and flare rates were analyzed by Poisson regression with robust variance estimation.

We performed analyses among all participants and separately among those with self-reported allergies or respiratory tract disorders (drug, food, skin, latex, and other allergies, sinusitis, hayfever/allergic rhinitis, and asthma) because we suspected that participants with allergies/respiratory tract disorders might be more susceptible to pollen. Additional stratified/restricted analyses were those restricted to participants not taking UCPPS medications with antihistamine or Mast cell inhibitory properties (amitriptyline, hydroxyzine, and pentosan polysulfate sodium) during follow-up, and analyses stratified by sex, IC/BPS versus CP/CPPS diagnosis, condition duration, baseline pain limited to the pelvis versus beyond, presence of self-reported chronic overlapping pain conditions, bladder hypersensitivity, and sensory hypersensitivity. These additional analyses were performed to identify sub-groups of patients who might be more susceptible to pollen, as UCPPS is believed to comprise a heterogeneous group of conditions/clinical phenotypes with varying etiology.²²

Additional analyses performed for the case-crossover sample only were those restricted to: 1) more bothersome flares (those with worse pain, longer duration, or occurring close in time to when participants sought care for their symptoms); and 2) flare and non-flare assessments without preceding sexual activity, as we previously observed that sexual activity was associated with flares in this study population.²² These additional analyses were possible only for the case-crossover sample because detail on flare symptoms and exposures preceding flare and non-flare assessments was collected only for the three flare and non-flare assessments included in the case-crossover study. To address the possible concern that bias may have been introduced by differences in the way in which flare and non-flare assessments were selected for the case-crossover study (i.e., first three during follow-up for flare assessments versus randomly selected within study follow-up third for non-flare assessments), we performed analyses restricted to participants with ≤2 flares (and thus whose flares were not constrained to occur earlier in follow-up). We also adjusted for study follow-up third. Finally, as pollen may be correlated with meteorological factors, such as temperature, we adjusted for temperature and differences in temperature in the analyses. However, as no differences were observed, we presented unadjusted values only. All analyses were performed in SAS version 9.4 (SAS Institute, Inc; Cary, NC).

RESULTS

Of the 424 participants who completed the MAPP study, 290 participants (791 non-flare and 574 flare observations) were included in the case-crossover analysis, after excluding those with negative responses to all flare questions (n=79), and those who reported a flare at baseline but none later during follow-up (n=28), did not complete both flare and non-flare assessments (n=25), and did not provide a start date for any of their flares (n=2). For the longitudinal analysis, 409 participants (5,387 non-flare and 966 flare observations) were included, after excluding those who did not complete flare and non-flare assessments from visit 3 onwards (n=15). Approximately two fifths of participants were male and most were Caucasian, with a median age of 41.6-43.4 years, a median condition duration of 3.6-3.9 years, and median baseline pain and urologic symptom intensities of 5-6 out of 10. Approximately two thirds of participants reported a history of allergies, with the most common being drug allergies (32.8-37.8%) and allergic rhinitis (32.4-34.3%). Just over one third reported a chronic overlapping pain condition (Table 1).

Table 1:

Baseline demographic and clinical characteristics of urologic chronic pelvic pain syndrome participants in the Multidisciplinary Approach to the Study of Chronic Pelvic Pain Epidemiology and Phenotyping Study, 2009-2013.

	Case-crossover sample (n=290)	Longitudinal sample (n=409)
Male (%)	37.8	44.5
Age (years, median (range))	41.6 (19.4-81.5)	43.4 (18.9-81.6)
Caucasian (%)	91.8	91.4
Duration of symptoms (years, median (range))	3.6 (0.2-47.6)	3.9 (0.0-54.1)
Baseline symptoms (median (range))
Pelvic pain, pressure, or discomfort in the past 2 weeks (on a scale of 0-10)	5.0 (1.0-10.0)	5.0 (1.0-10.0)
Urgency in the past 2 weeks (on a scale of 0-10)	6.0 (0.0-10.0)	5.0 (0.0-10.0)
Frequency in the past 2 weeks (on a scale of 0-10)	5.0 (0.0-10.0)	5.0 (0.0-10.0)
Pain severity score (on a scale of 0-28)1	15.6 (0.0-28.0)	15.0 (0.0-28.0)
Urinary severity score (on a scale of 0-25) 2	14.0 (0.0-25.0)	13.0 (0.0-25.0)
Bladder-associated symptoms (painful urgency, painful filling, %)
None	12.0	16.0
Either	29.5	31.3
Both	58.5	52.7
Self-reported history of allergies and respiratory tract disorders (%)
Drug allergies	37.8	32.8
Food allergies	15.9	15.0
Skin allergies	11.5	10.5
Latex allergies	7.1	N/A
Other allergies	11.0	11.5
Hay fever/allergic rhinitis	34.3	32.4
Asthma	16.9	15.7
Any allergies or respiratory tract disorders	67.4	65.2
Presence of self-reported chronic overlapping pain conditions (%)
Irritable bowel syndrome	23.0	23.1
Fibromyalgia	3.8	3.2
Chronic fatigue syndrome	2.6	2.8
Any chronic overlapping pain condition	40.4	37.3

¹Defined as the sum of the Genitourinary Pain Index pain sub-score and question 4 of the Interstitial Cystitis Symptom Index.

²Defined as the sum of the Genitourinary Pain Index urinary sub-score and questions 1 to 3 of the Interstitial Cystitis Symptom Index

Although absolute pollen counts varied across the six main clinical and two sub-sites, most experienced a bimodal, annual pollen distribution (Appendix figure 1). The lowest pollen values tended to be observed in November and December (range of mean monthly values: 0.10-3.29), followed by a peak in the spring (7.50-9.29), a drop mid-summer (2.93-4.22), and then a second peak in late summer to fall (5.29-8.44). This pattern was observed for all sites except for the University of Washington catchment area, which experienced one longer peak from spring through summer.

In analyses examining the influence of daily pollen count on flare onset, no associations were observed for higher pollen levels on the day of a flare or any of the three preceding days in all participants and those who reported a history of allergies/respiratory tract disorders (p-trends: 0.58-0.91; Table 2). In contrast, positive associations were observed for initial pollen rises past medium or higher thresholds, but not past a low/medium threshold, in the 1-2 days before a flare among all participants (odds ratio [OR]=1.22, 95% confidence interval [CI]: 0.99-1.50) and those with allergies (OR=1.31, 95% CI: 1.04-1.66). Increased flare rates were also observed in the three weeks following initial pollen rises past medium or higher thresholds in the full longitudinal analysis among all participants (RR=1.14, 95% CI: 0.98-1.33) and those with allergies (RR=1.23, 95% CI: 1.03-1.46; Table 3). The results did not strengthen further in sensitivity analyses excluding participants taking UCPPS medications with anti-histamine or Mast cell inhibitory properties (case-crossover sample: OR=1.20, 95% CI: 0.88-1.63 among participants unselected for allergies and OR=1.29, 95% CI: 0.90-1.83 among those with allergies; longitudinal sample: RR=1.08, 95% CI: 0.88-1.32 among participants unselected for allergies and RR=1.10, 95% CI: 0.86-1.41 among those with allergies). No notable patterns of associations were observed in additional sensitivity analyses.

Table 2:

Associations between daily pollen count level and changes in level in the past three days and urologic chronic pelvic pain syndrome flare onset in a case-crossover study in the Multidisciplinary Approach to the study of chronic Pelvic Pain Epidemiology and Phenotyping Study, 2009-2013.

	Case pollen values (n=574 flare assessments)					Control pollen values (n=791 non-flare assessments)					All participants		Participants with a history of allergies or respiratory tract disorders
Daily pollen count level (%)
	Low	Low/ medium	Medium	Medium/ high	High	Low	Low/ medium	Medium	Medium/ high	High	Matched OR (95% CI)2	P- trend	Matched OR (95% CI)2	P- trend
Day 0	32.8	28.6	19.3	14.1	5.2	36.4	23.1	19.5	16.3	4.7	1.01 (0.92-1.10)	0.91	1.02 (0.91-1.14)	0.74
Day −1	34.0	27.9	17.8	13.8	6.6	34.9	24.2	17.1	18.7	5.2	0.98 (0.90-1.08)	0.72	0.98 (0.88-1.09)	0.69
Day −2	33.5	27.9	18.5	14.5	5.8	33.9	25.9	19.7	16.1	4.4	1.01 (0.92-1.11)	0.82	1.01 (0.91-1.13)	0.83
Day −3	32.9	26.8	19.5	15.7	5.1	35.4	23.5	20.2	16.1	4.8	1.02 (0.93-1.12)	0.67	1.03 (0.92-1.15)	0.58
Rise in daily pollen count level across pollen thresholds (%)
		Rise across threshold				Rise across threshold					Matched OR (95% CI)3	P- value	Matched OR (95% CI)3	P -value
Day −1 to 0
Low/medium		3.1				5.8					0.66 (0.44-1.00)	0.048	0.58 (0.34-0.99)	0.044
Medium or greater		6.4				7.1					0.94 (0.73-1.22)	0.66	0.80 (0.56-1.14)	0.21
Day −2 to −1
Low/medium		4.0				5.2					0.85 (0.61-1.17)	0.32	0.88 (0.62-1.24)	0.46
Medium or greater		9.4				6.7					1.22 (0.99-1.50)	0.06	1.31 (1.04-1.66)	0.025
Day −3 to −2
Low/medium		4.2				3.7					1.08 (0.81-1.44)	0.60	1.05 (0.73-1.51)	0.81
Medium or greater		11.1				9.9					1.08 (0.89-1.31)	0.43	1.09 (0.87-1.38)	0.45

CI=confidence interval; OR=odds ratio

¹All values were calculated by conditional logistic regression, clustering by participant. The full analysis included 290 participants and the analysis restricted to participants with a history of allergies or respiratory tract disorders included 194 participants.

²OR for increasing pollen count level.

³OR for a rise across a specific threshold.

Table 3:

Relative rates (RRs) and 95% confidence intervals (CIs)¹ of urologic chronic pelvic pain syndrome flares by initial annual rise in pollen count level in the Multidisciplinary Approach to the Study of Chronic Pelvic Pain Epidemiology and Phenotyping Study, 2009-2013.

	All participants (n=409)		Participants with a history of allergies or respiratory tract disorders (n=263)
No. of flare assessments	966		674
No. of total assessments	6,353		4,126
Initial rise in pollen count to levels of:	RR (95% CI)	P-value	RR (95% CI)	P-trend/value
Low/medium	1.07 (0.84-1.35)	0.58	0.98 (0.74-1.31)	0.91
Medium or higher level	1.14 (0.98-1.33)	0.10	1.23 (1.03-1.46)	0.02

¹Calculated by Poisson regression with robust variance estimation.

DISCUSSION

Overall, we found some evidence to suggest that pollen triggers UCPPS flares in our large, longitudinal study. Although we are not aware of previous empirical studies to which to compare our findings, our results are consistent with patient reports that pollen triggers their flares^7-9 and with case series/report data suggesting that asthma and allergy medications relieve UCPPS symptoms.^15-18 Our results are also supported biologically by at least one common pathway known or suspected to underlie the pathophysiology of allergic disorders (allergic rhinitis and asthma) and UCPPS – i.e., Mast cell activation and histamine release. Mast cell activation is well-known to contribute to allergic rhinitis,²⁴ and suspected to contribute to IC/BPS based on the greater numbers of Mast cells (overall and activated) and Mast cell mediators observed in IC/BPS animal models and patients than in controls.²⁵ Interestingly, Mast cells are also suspected to contribute to other chronic overlapping pain conditions, such as fibromyalgia²⁶ and irritable bowel syndrome.²⁷

Mast cell activation leads to degranulation and release of chemotactic factors, such as cytokines, proteolytic enzymes, and histamine.²⁸ Once released, histamine diffuses rapidly into the surrounding tissues, appearing in blood within 2.5 minutes, peaking at 5 minutes, and returning to baseline by 30 minutes. However, urinary histamine remains elevated for much longer²⁹ and has been shown to contribute to bladder afferent neuronal sensitization, a possible mediator of UCPPS symptoms, in animal models.³⁰ Therefore, pollen may potentially trigger UCPPS flares by first raising circulating histamine levels in susceptible individuals (e.g., those with allergies), and then by raising urinary levels as they are excreted from the body. In addition, given the long lifespan of Mast cells, this reaction may potentially be protracted.²⁸ Finally, although the proposed mechanism is seemingly inconsistent with the observed therapeutic benefit of flower pollen extract preparations in CP/CPPS clinical trials,²⁰ refined pollen extract may potentially have different properties (e.g., anti-inflammatory²⁰) than crude pollen.

Although our findings provide some support for a role of pollen in triggering UCPPS flares, they are not all statistically significant. Multiple sources of misclassification may have contributed to this lack of statistical significance, including: 1) use of participants’ baseline residential address to assign pollen levels, which precluded taking into account periods of time when participants moved outside of their residential 3 digit zip codes; 2) investigation of all sources of plant pollen combined (the only data available from IQVIA), which precluded exploring differential susceptibility to pollen by pollen type; and 3) lack of information on non-environmental plant pollens (e.g., a bouquet of flowers), which may have also contributed to flares. Additional limitations included: 4) minimal information on participants’ likelihood of susceptibility to pollen beyond a history of allergies and respiratory disorders, which precluded restricting the analyses to susceptible individuals in an optimal manner; 5) lack of information on anti-histamine use, which precluded excluding periods of time when flares induced by pollen may have been prevented by anti-histamine use; 6) minimal information on UCPPS therapy (collected at only three time points), which limited our ability to test the influence of UCPPS medications with anti-histamine and Mast cell inhibitory properties on observed associations; and 7) lack of information about flare start date in our longitudinal analysis, which precluded linking pollen data to flare onset accurately. More detailed, real-time data collection, such as through an app, and biomarkers of susceptibility may help to address these limitations. Finally, it is also possible that our findings may have been confounded by other unstudied factors that trigger flares and coincide with pollen rises (besides temperature, for which we controlled in the analyses).

Further investigation of this research question is warranted because of its potential to inform multiple aspects of UCPPS flare pathophysiology, prevention, and care. If pollen does indeed trigger flares for some patients, these findings could be used to motivate research and provide clues into the pathophysiology of flares, which is currently poorly-understood. They could also be used to: 1) inform flare prevention by avoiding pollen, if possible; taking prophylactic anti-histamines during pollen blooms; or undergoing allergy testing and allergen immunotherapy; 2) inform flare treatment by taking anti-histamines; and 3) provide some degree of control for participants over the unpredictability of flares by planning their activities around pollen rises.

Glossary

UCPPS

Urologic Chronic Pelvic Pain Syndrome

MAPP

Multidisciplinary Approach to the study of Chronic Pelvic Pain

IC/BPS

Interstitial Cystitis/Bladder Pain Syndrome

CP/CPPS:

Chronic Prostatitis/Chronic Pelvic Pain Syndrome

OR

Odds Ratio

RR

Relative Risk

CI

Confidence Interval

MAPP II Research Network Study Group

MAPP Network Executive Committee

J. Quentin Clemens, MD, FACS, MSci, Network Chair, 2013-

Philip Hanno, MD

Ziya Kirkali, MD

John W. Kusek, PhD

J. Richard Landis, PhD

M. Scott Lucia, MD

Robert M. Moldwin, MD

Chris Mullins, PhD

Michel A. Pontari, MD

University of Colorado Denver Tissue Analysis & Technology Core

M. Scott Lucia, MD, Core Dir.

Adrie van Bokhoven, PhD, Co-Dir.

Andrea A. Osypuk, BS

Robert Dayton, Jr

Chelsea S. Triolo, BS

Karen R. Jonscher, PhD

Holly T. Sullivan, BS

R. Storey Wilson, MS

Zachary D. Grasmick, BS

National Institutes of Diabetes & Digestive and Kidney Diseases

Chris Mullins, PhD

John W. Kusek, PhD

Ziya Kirkali, MD

Tamara G. Bavendam, MD

University of Pennsylvania Data Coordinating Core

J. Richard Landis, PhD, Core Dir.

Dina Appleby, MS

Ted Barrell, BA

Ro-Pauline Doe, BA

John T. Farrar, MD, MSCE, PhD

Melissa Fernando, MPH

Laura Gallagher, MPH, CCRP

Philip Hanno, MD

Xiaoling Hou, MS

Tamara Howard, MPH

Thomas Jemielita, MS

Natalie Kuzla, MA

Robert M. Moldwin, MD

Craig Newcomb, MS

Michel A. Pontari, MD

Nancy Robinson-Garvin, PhD

Sandra Smith, AS

Alisa Stephens-Shields, PhD

Yanli Wang, MS

Xingmei Wang, MS

DISCOVERY SITES

Northwestern University

David J. Klumpp, PhD, Co-Dir.

Anthony J. Schaeffer, MD, Co-Dir.

Apkar (Vania) Apkarian, PhD

Christina Arroyo

Michael Bass, PhD

David Cella, PhD

Melissa A. Farmer, PhD

Colleen Fitzgerald, MD

Richard Gershon, PhD

James W. Griffith, PhD

Charles J. Heckman II, PhD

Mingchen Jiang, PhD

Laurie Keefer, PhD

Robert Lloyd, PhD

Darlene S. Marko, RN, BSN, CCRC

Jean Michniewicz

Richard Miller, PhD

Todd Parrish, PhD

Frank Tu, MD, MPH

Ryan Yaggie

University of California, LA PAIN Neuroimaging Core

Emeran A. Mayer, MD, Co-Dir.

Larissa V. Rodríguez, MD, Co-Dir.

Jeffry Alger, PhD

Cody P. Ashe-McNalley

Ben Ellingson, PhD

Nuwanthi Heendeniya

Lisa Kilpatrick, PhD

Cara, Kulbacki

Jason Kutch, PhD

Jennifer S. Labus, PhD

Bruce D. Naliboff, PhD

Fornessa Randal

Suzanne R. Smith, RN, NP

University of Iowa

Karl J. Kreder, MD, MBA, Dir.

Catherine S. Bradley, MD, MSCE

Mary Eno, RN, RA

Kris Greiner, BA

Yi Luo, PhD, MD

Susan K. Lutgendorf, PhD

Michael A. O’Donnell, MD

Barbara Ziegler, BA

Andrew Schrepf, PhD

Isabelle Hardy, MBA

Vince Magnotta, PhD

Brad Erickson, MD

University of Michigan

Daniel J. Clauw, MD, Co-Dir.; Network Chair, 2008-2013

J. Quentin Clemens, MD, FACS, MSci, Co-Dir.; Network Chair, 2013-

Suzie As-Sanie, MD

Sandra Berry, MA

Clara Grayhack,

Megan E. Halvorson, BS, CCRP

Richard Harris, PhD

Steve Harte, PhD

Eric Ichesco, BS

Ann Oldendorf, MD

Katherine A. Scott, RN, BSN

David A. Williams, PhD

University of Washington, Seattle

Dedra Buchwald, MD, Dir.

Niloofar Afari, PhD, UCSD

Tamara Bacus, BS

Todd Edwards, PhD

John Krieger, MD

Kenneth Maravilla, MD

Jane Miller, MD

Donald Patrick, PhD

Xiaoyan Qin, PhD

Stephanie Richey, BS

Rosana Risques, PhD

Kelly Robertson, BS

Susan O. Ross, RN, MN

Roberta Spiro, MS

Eric Strachan, PhD

TJ Sundsvold, MPH

Suzette Sutherland, MD

Claire C. Yang, MD

Washington University, St. Louis

Gerald L. Andriole, MD, Co-Dir., PI

H. Henry Lai, MD, Co-Dir., PI

Rebecca L. Bristol, BA, BS

Robert W. Gereau IV, PhD,

Barry A. Hong, PhD, FAACP

Aleksandra P. Klim, RN, MHS, CCRC

Siobhan Sutcliffe, PhD, ScM, MHS

Joel Vetter

David G. Song

Melissa Milbrandt

Simon Haroutounian, PhD

Pooja Vijairania

Kaveri Parker (Chaturvedi)

Tran Hung

Graham Colditz, MD, PH

Vivien C. Gardner, RN, BSN

Jeffrey P Henderson, MD, PhD

Theresa M. Spitznagle, PT, DPT, WCS

Ratna Pakpahan, MHA

Aimee James PhD, MPH

Yan Yan

Marvin Epolian Langston

Barry Hong, PhD

Susan Mueller

Jan Crowley

Sherri Vogt

Scott Hultgren, PhD

Nang Nguyen, PhD

Gabriel Blasche

Chang Shen Qiu, PhD

Lori Cupps

Song Bok

NON-RECRUITING DISCOVERY SITES

Cedars-Sinai Medical Center

Jennifer Anger, MD, MPH

James Ackerman, MA

A. Lenore Ackerman, MD, PhD

Jeena Cha, BS, CCRP

Karyn Eilber, MD

Michael Freeman, PhD

Vincent Funari, PhD

Jayoung Kim, PhD

Jennifer Van Eyk, PhD

Wei Yang, PhD

Queens University

J. Curtis Nickel, MD, FRCSC, Dir.

Garth D. Ehrlich, PhD [Drexel COM]

Harvard Medical School/Boston Children’s Hospital

Marsha A. Moses, PhD, Dir.

Andrew C. Briscoe

David Briscoe, MD

Adam Curatolo, BA

John Froehlich, PhD

Richard S. Lee, MD

Monisha Sachdev, BS

Keith R. Solomon, PhD

Hanno Steen, PhD

Stanford University

Sean Mackey, MD, PhD, Dir.

Epifanio Bagarinao, PhD

Lauren C. Foster, BA

Emily Hubbard, BA

Kevin A. Johnson, PhD, RN

Katherine T. Martucci, PhD

Rebecca L. McCue, BA

Rachel R. Moericke, MA

Aneesha Nilakantan, BA

Noorulain Noor, BS