School Inner-City Asthma Intervention Study
Phase: NA
Conditions: Asthma
Sponsor: Boston Children's Hospital

 
Confidential 
Page 1 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
 
PROTOCOL NUMBER U01-BCH-01 
School Inner-City Asthma Intervention Study: 
 
VERSION 3.0 / VERSION DATE: 03/27/2015 
IND# [n/a] 
Study Sponsor(s): 
 
The National Institute of Allergy and Infectious Diseases (NIAID) 
 
 
 
 
NIAID Funding Mechanism: U01 AI110397 NCT 02291302  
Study Drug Manufacturer/Provider: 
 
[n/a] 
PROTOCOL CHAIR- WANDA 
PHIPATANAKUL, MD, MS 
 
Professor of Pediatrics 
Boston Children’s Hospital 
300 Longwood Avenue 
Boston, MA 02115 
Phone: 857-218-5336 
Fax: 617-730-4709 
Email:  
wanda.phipatanakul@childrens. 
harvard.edu 
 
NIAID MEDICAL OFFICER/MONITOR-  
PETER GERGEN, MD, MPH 
Division of Allergy, Immunology, and 
Transplantation – NIAID/NIH 
5601 Fishers Lane 
Bethesda, MD 20892-9828, USA 
Phone:  240-627-3545 
Fax:  301-480-4258 
E-mail:  pgergen@niaid.nih.gov 
 BIOSTATISTICIAN- BRENT COULL, PHD 
Professor of Biostatistics 
Harvard School of Public Health 
655 Huntington Ave 
Boston, MA 02115 
Phone: 617-432-0156 
Fax: 617-432-1659 
E-mail: bacoull@hsph.harvard.edu 
 
  
NIAID  NURSE CONSULTANT/PROJECT 
MANAGER-KATHERINE THOMPSON 
Division of Allergy, Immunology, and 
Transplantation – NIAID/NIH 
PO Box 7 
Lecanto, FL 34460, USA 
Phone:  301-706-1177 
E-mail:  thompsonkath@niaid.gov 
REGULATORY OFFICER – Ling Li Ph.D 
OFFICE OF  REGULATORY AFFAIRS 
Division of Allergy, Immunology, 
and Transplantation – NIAID/NIH 
5601 Fishers Lane 
Bethesda, MD 20892-9828, USA 
Phone: (240) 627-3765 
Fax: (301) 480-1537  
E-mail: lil16@niaid.nih.gov 
 
 

 
Confidential 
Page 2 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
 
 
Protocol Synopsis 
Title 
School Inner-City Asthma Intervention Study 
Short Title 
SICAS-2 
Clinical Phase 
II 
Number of Sites 
1 
IND Sponsor/Number   
n/a 
Intervention(s) 
A. Classroom Air Filter Purifier, School Integrated Pest 
Management 
 B. Endpoints:  Asthma Symptoms, health care utilization, rescue 
medication use,  lung function 
Study Objectives 
The primary objective is to determine the efficacy of this 
environmental intervention to improve asthma outcomes.  
Study Design 
The study is a randomized, double-blind, placebo controlled, 
parallel Classroom Air Filter Intervention and a single-blind, 
controlled parallel trial of a school-wide (with targeting of 
participant classrooms) mouse-targeted integrated pest 
management (IPM) intervention. 
Primary Endpoint(s) 
The primary outcome measure is maximum days of symptoms/ 2 
weeks. Maximum days of asthma symptoms will be assessed by 
questionnaire as done previously in NIAID funded in NCICAS, ICAS, 
and ICAC consortiums and studies1-4. The primary endpoint is the 
longitudinal vector of symptom-days at each of the five visits 
(baseline and follow up)  for each subject.   
Secondary Endpoint(s)  
Secondary outcomes  include: (1) school absences, (2) health care 
utilization, 3) Composite Asthma Severity Index adapted from the 
Inner-City Asthma Consortium5, and incorporates day symptoms, 
short-acting beta agonist use,  nights symptoms, and exacerbations 
(defined as systemic steroids for asthma) and lung function.  Core 
outcomes come from the recent Asthma Outcomes Workshop6 
These data will be obtained from questionnaires, and lung function 

 
Confidential 
Page 3 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
(i.e. FEV1/FVC, FEV1 percent predicted, percent change in FEV1 
after short-acting beta agonist, FEF 25%-75%)with  Koko spirometer 
Degree of Exposure Reduction and  Health Outcomes (Primary and 
Secondary) 
Accrual Objective 
250 
Study Duration 
52 months total duration (accrual 40 months + follow-up period 12 
months 
Treatment Description  
There will be four parallel groups randomized in a multi-level, 
factorial fashion:  The student’s primary CLASSROOM will be 
randomized to Air Filters versus Sham Control.  Simultaneously, 
the student’s SCHOOL will be randomized to receive intense IPM 
INTERVENTION (extermination and sealing of sealing of holes and 
cracks surrounding the classroom/cafeteria), education, reservoir 
cleaning versus control.   
Inclusion Criteria 
Subject and/or parent guardian must be able to understand and 
provide informed consent 
Males and females who will be in grades K-8 (age 4-15 at 
randomization) during the subsequent academic school year after 
spring screening  
 
Attend one of the schools that study team have permission to 
obtain classroom/school environmental samples for the 
subsequent academic school year.  
 
Have no plans to move schools within the upcoming 12 months 
 
Have health care insurance and asthma provider  
Have physician-diagnosed asthma at least 1 year prior to the 
screening visit 
  
Have evidence of active asthma  disease as defined by at least one of 
the following: 
 
One asthma-related unscheduled visit to an emergency 
department (ED), clinic or urgent care facility in the 
previous 12 months 
 
One asthma-related overnight hospitalization in the 
previous 12 months 
 
One or more bursts of oral or injectable corticosteroids in 
the previous 12 months  
 
Wheezing symptoms in the past 12 months 
 
On Daily controller medications for asthma 
 

 
Confidential 
Page 4 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
Inclusion/exclusion criteria modeled from the NIAID funded Inner-
City Asthma Studies)1-4 
Exclusion Criteria for Individual 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Exclusion Criteria for School 
Individuals who meet any of these criteria are not eligible 
for enrollment as study participants:  
Inability or unwillingness of a participant to give written informed 
consent or comply with study protocol in the judgment of the PI 
 
Inability to perform spirometry 
 
Lung disease, other than asthma, that requires daily medication 
 
Cardiovascular disease that requires daily medication, excluding 
hypertension 
 
Taking a beta-blocker 
 
Currently receiving escalation (has not reached maintenance) of 
Immunotherapy (allergy shots) 
 
Switching to a school where staff are not doing environmental 
sampling for that year. 
 
Past or current medical problems or findings from physical 
examination or laboratory testing that are not listed above, which, 
in the opinion of the investigator, may pose additional risks from 
participation in the study, may interfere with the participant’s 
ability to comply with study requirements or that may impact the 
quality or interpretation of the data obtained from the study. 
 
 
Unable to access areas of school necessary to conduct extermination 
 
School in extensive state of disrepair/damage as determined by 
Study Coordinator/PI judgment 
 
Centralized Air Filtration or Purifying System  
 
 
Study Stopping Rules 
The intervention will be ended if found disruptive to the classroom  
 

 
Confidential 
Page 5 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
 
 
Table of Contents 
Glossary of Abbreviations ....................................................................................................................................................... 9 
1. 
Background and Rationale ............................................................................................................................................ 10 
1.1. 
Background and Scientific Rationale ..................................................................................................................... 10 
1.2. 
Preclinical Experience: n/a This is an environmental intervention....................................................................... 14 
1.3. 
Clinical Studies for Intervention ............................................................................................................................ 14 
Summary of Other Relevant School-Based Intervention Studies: ................................................................................ 15 
2. 
Study Hypotheses/Objectives ....................................................................................................................................... 16 
2.1. 
Hypotheses............................................................................................................................................................ 16 
2.2. 
Primary Objective(s) .............................................................................................................................................. 16 
To determine whether a school/classroom-based environmental intervention (classroom High Efficiency Particulate Air 
(HEPA) filter/purifying units and school integrated pest management) will: ...................................................................... 16 
2.3. 
Secondary Objective(s) ......................................................................................................................................... 16 
To explore whether sensitization or other asthma phenotypes defined at baseline modify which pathways or networks 
of genes undergo intervention-related changes in methylation or gene expression that, in turn, are associated with 
improvement in asthma outcomes. .................................................................................................................................. 16 
3. 
Study Design .................................................................................................................................................................. 17 
3.1. 
Description of Study Design .................................................................................................................................. 17 
3.2. 
Primary Endpoint .................................................................................................................................................. 18 
3.3. 
Secondary Endpoint .............................................................................................................................................. 20 
3.4. 
Exploratory Enpoint(s) .......................................................................................................................................... 21 
3.5. 
Stratification, Randomization, and Blinding/Masking .......................................................................................... 22 
4. 
Selection of Participants and Clinical Sites/Laboratories.............................................................................................. 23 
4.1. 
Rationale for Study Population ............................................................................................................................. 23 
4.2. 
Inclusion Criteria ................................................................................................................................................... 23 
4.3. 
Exclusion Criteria for Participant .......................................................................................................................... 24 
4.4. 
Selection of Clinical Sites/Labs .............................................................................................................................. 25 
5. 
Known and Potential Risks and Benefits to Participants .............................................................................................. 25 

 
Confidential 
Page 6 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
5.1. 
Risks of Investigational Product or Intervention as cited in Investigator Brochure or Package Insert................. 25 
5.2. 
Risks of Investigational Product or Intervention cited in Medical Literature and/or those based on the 
Investigators’ experience .................................................................................................................................................. 25 
5.3. 
Risks of Other Protocol Specified Medications ..................................................................................................... 25 
5.4. 
Risks of Study Procedures ..................................................................................................................................... 26 
5.5. 
Potential Benefits .................................................................................................................................................. 27 
6. 
Intervention .................................................................................................................................................................. 27 
6.1.1. 
Intervention #1.............................................................................................................................................. 27 
6.1.1.1. 
Formulation, Packaging, and Labeling ...................................................................................................... 28 
6.1.1.2. 
Dosage, Preparation, and Administration ................................................................................................. 28 
6.1.2. 
Intervention #2.................................................................................................................................................. 28 
6.1.2.1. 
Formulation, Packaging, and Labeling ...................................................................................................... 28 
6.2. 
Assessment of Participant Compliance with Investigational Agent ..................................................................... 28 
6.3. 
Toxicity Prevention and Management .................................................................................................................. 28 
6.4. 
Premature Discontinuation of Investigational Agent ........................................................................................... 29 
7. 
Other Medications ........................................................................................................................................................ 29 
7.1. 
Concomitant Medications ..................................................................................................................................... 29 
7.2. 
Prophylactic Medications ...................................................................................................................................... 29 
7.3. 
Prohibited Medications ......................................................................................................................................... 29 
7.4. 
Rescue Medications .............................................................................................................................................. 29 
8. 
Study Procedures .......................................................................................................................................................... 29 
8.1. 
Enrollment ............................................................................................................................................................. 29 
Screening Visit ................................................................................................................................................................... 29 
8.2 
HEPA Air Filter Accountability ............................................................................................................................... 34 
9. 
Mechanistic Assays ....................................................................................................................................................... 37 
10. 
Biospecimen Storage................................................................................................................................................. 38 
11. 
Criteria for Participant and Study Completion and Premature Study Termination.................................................. 38 
11.1. 
Participant Completion ..................................................................................................................................... 38 
11.2. 
Participant Stopping Rules and Withdrawal Criteria ........................................................................................ 39 
11.3. 
Participant Replacement ................................................................................................................................... 39 
11.4. 
Follow-up after Early Study Withdrawal ........................................................................................................... 39 

 
Confidential 
Page 7 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
12. 
Overview ................................................................................................................................................................... 39 
12.1 Definitions ................................................................................................................................................................. 40 
12.1.2 Adverse Event (AE) ............................................................................................................................................. 40 
N/A ................................................................................................................................................................................ 41 
12.2.2 Unexpected Adverse Event ................................................................................................................................ 41 
12.2.3 Serious Adverse Event (SAE) ................................................................................. Error! Bookmark not defined. 
12.2 Grading and Attribution of Adverse Events ................................................................. Error! Bookmark not defined. 
12.2.1 Grading Criteria .................................................................................................................................................. 41 
12.2.2 Attribution Definitions ....................................................................................................................................... 42 
12.4 Collection and Recording of Adverse Events ............................................................................................................ 42 
12.4.1 Collection Period ................................................................................................................................................ 42 
12.4.2 Collecting Adverse Events .................................................................................................................................. 43 
12.4.3 Recording Adverse Events .................................................................................................................................. 43 
12.5 Reporting of Serious Adverse Events and Adverse Events ....................................................................................... 43 
12.5.1 Reporting of Serious Adverse Events to Sponsor (DAIT/NIAID) ......................................................................... 43 
12.5.2 Reporting to Health Authority ........................................................................................................................... 44 
Not Applicable ............................................................................................................................................................... 44 
12.5.3 Reporting of Adverse Events to IRBs .................................................................................................................. 44 
12.7 Reporting of Unanticipated Safety Information ....................................................................................................... 44 
12.8 Review of Safety Information ................................................................................................................................... 44 
12.8.1 Medical Monitor Review .................................................................................................................................... 44 
12.8.2  Data and Safety Monitoring Board(DDSMB) Review ........................................................................................ 44 
13. 
Statistical Considerations and Analytical Plan .......................................................................................................... 45 
13.1 
Overview ............................................................................................................................................................... 45 
13.2 
Outcomes (Described in 1.1-1.3) .......................................................................................................................... 45 
Primary Outcome(s) .......................................................................................................................................................... 45 
Maintenance of Trial Treatment Randomization Codes ................................................................................................... 45 
13.4 
Analysis Plan .......................................................................................................................................................... 46 
13.4.1 
Analysis Populations. .................................................................................................................................... 46 
13.4.2 
Primary Analysis of Primary Endpoint(s) ....................................................................................................... 46 

 
Confidential 
Page 8 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
13.4.3 
Supportive Analyses of the Primary Outcome .............................................................................................. 48 
13.4.4 
Analyses of Secondary and Other Endpoint(s)/Outcome(s) ......................................................................... 48 
13.4.5 
Analyses of Exploratory Endpoint(s) ............................................................................................................. 51 
13.4.6 
Descriptive Analyses ..................................................................................................................................... 52 
Descriptive Analyses ..................................................................................................................................................... 52 
13.5 
Interim Analyses  (Not Applicable: Environmental Intervention- NOT a medication, high risk intervention) ..... 52 
13.6 
Statistical Hypotheses ........................................................................................................................................... 52 
Aim 1: To determine the effectiveness of a school/classroom based environmental intervention [Classroom particle air 
filter/purifying units and school-wide integrated pest management (IPM)] to: .................................................................. 52 
13.7 
Sample Size Considerations Sample Size Estimates: ............................................................................................. 53 
14. 
Identification and Access to Source Data ................................................................................................................. 54 
14.1. 
Source Data ....................................................................................................................................................... 54 
14.2. 
Access to Source Data ....................................................................................................................................... 55 
15. 
Protocol Deviations ................................................................................................................................................... 55 
15.1. 
Protocol Deviation Definitions .......................................................................................................................... 56 
15.2. 
Reporting and Managing Protocol Deviations .................................................................................................. 56 
16. 
Ethical Considerations and Compliance with Good Clinical Practice ........................................................................ 56 
16.1. 
Statement of Compliance ................................................................................................................................. 56 
16.2. 
Informed Consent Process ................................................................................................................................ 56 
16.3. 
Privacy and Confidentiality ............................................................................................................................... 57 
17. 
Quality Control and Quality Assurance ................................................................................................................. 57 
18. 
Publication Policy ...................................................................................................................................................... 58 
19. 
References ................................................................................................................................................................ 58 
 

 
Confidential 
Page 9 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
Glossary of Abbreviations 
ACT 
Asthma Control Test 
CASI 
Composite Asthma Severity Index 
CFR 
Code of Federal Regulations 
CRF 
Case Report Form 
CTCAE 
Common Terminology Criteria for Adverse Events 
DAIT 
Division of Allergy, Immunology, and Transplantation 
DBPC 
Double-Blind, Placebo Controlled 
DCC 
Data Coordinating Center 
DSMB 
 Data Safety Monitoring Board 
FDA 
Food and Drug Administration 
FeNO 
Fractional Exhaled Nitric Oxide 
FEF 25-75% 
Forced expiratory flow between 25-75% of vital capacity 
FEV1 
Forced expiratory volume in 1 second 
FVC 
Forced Vital Capacity 
GCP 
Good Clinical Practice 
HEPA 
High Efficiency Particulate Air 
ICAC 
Inner-City Asthma Consortium 
ICAS 
Inner-City Asthma Study 
ICH 
International Conference on Harmonization 
IEC 
Institutional Ethics Committee 
IMM 
Independent Medical Monitor 
IND 
Investigational New Drug 
IPM 
Integrated Pest Management 
IRB 
Institutional Review Board 
ISM 
Independent Safety Monitor 
MAAIT 
Mouse Allergen Asthma Intervention Trial 
MOP 
Manual of Procedures 
n/a 
Not Applicable 
NHLBI 
National Heart Lung Blood Institute 
NIH 
National Institutes of Health 
NIAID 
National Institute of Allergy and Infectious Diseases 
NO2 
Nitrogen Dioxide 
PC 
Protocol Chair 
PEF 
Peak Expiratory Flow 
PFT 
Pulmonary Function Test 
PI 
[Site] Principal Investigator 
PM 
Particulate Matter 
PM 
Project Manager 
SACCC 
Statistical and Clinical Coordinating Center 
SAE 
Serious Adverse Event 
SAP 
Statistical Analysis Plan 
SAR 
Suspected Adverse Reaction 
SICAS 
School Inner-City Asthma Study- observational study 

 
Confidential 
Page 10 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
SICAS-1 
School Inner-City Asthma Study-observational study 
SICAS-2 
School Inner-City Asthma Intervention Study – proposed clinical trial 
SOP 
Standard Operating Procedure 
1. Background and Rationale  
1.1. Background and Scientific Rationale 
A) Impact and Significance  Asthma affects 12-15% of children in urban United States, accounts for over 14 million 
missed school days per year7, and costs billions of dollars in health care utilization despite aggressive measures to 
identify remediable causes8. 
  
B) Scientific Background and Rationale  
Elementary school children spend 7 to 12 hours a day in school, (primarily in one classroom), and school is nearly every 
child’s “required occupation” and source of multiple environmental exposures.  The School Inner-City Asthma Study-1 
(SICAS-1) (RO1 AI 073964, Phipatanakul) is the first obsetrvational American study to comprehensively evaluate the role 
of urban exposures in school, classroom and home environments and asthma morbidity9, 10.  SICAS-1 showed that 
classroom-specific mouse allergen, mold, and particulate pollutant exposures are independently associated with 
symptom worsening11-13.  Until SICAS-1, most studies have focused on home exposures to allergenic and pollutant 
exposures and their associations with asthma morbidity14. A number of home-based trials have demonstrated that 
targeted interventions (including air filter units) are effective in decreasing asthma morbidity1, 15-17.  Using established 
integrated pest management measures, we are currently conducting an NIAID-funded home intervention clinical trial (AI 
083238) to evaluate mouse-targeted IPM effects on asthma morbidity18. SICAS 1 provided the rationale for SICAS 2, 
which is a school based environmental intervention clinical trial targeted towards  school-specific exposures identified in 
SICAS 1 as important. 
 
In schools, we have demonstrated that we can effectively decrease classroom-specific toxic exposures during the 
academic school year by 75% to 90% utilizing cleverly engineered, effective, and quiet classroom-suitable High Efficiency 
Particulate Air (HEPA) air filters.   
 
C) Innovation and Advancement of the Field: Our next step is to apply successful school/community-based strategies to 
determine whether a school/classroom intervention will efficiently and effectively improve asthma morbidity by 
reducing harmful exposures.  This is an unprecedented, high impact opportunity to test whether we can efficiently 
benefit a community of children in the school environment as opposed to individuals in single homes. Our goal is to 
determine the efficacy of a two-pronged intervention using classroom particle air filter units and school-wide targeted 
IPM/cleaning in reducing asthma morbidity in urban school children. Furthermore, we aim to link molecular mechanisms 
induced by our clinical intervention and ascertain whether environmental control can induce disease-modifying effects on 
the epigenome/transcriptome. 
 
D) Knowledge and Unmet Need Fulfilled from this Study to Reduce the Impact of this Public Health Concern and 
Sustainability 
 
Our study is the first ever comprehensive school-based environment intervention trial of HEPA filtration and IPM to 
improve asthma. Our engineers have unique skills and experience which they applied to development, tailoring and 
successful piloting of unique quiet high efficiency air cleaner technology (and matched sham filter controls) which we 
have demonstrated to be effective in reducing exposures and acceptable in the classrooms setting. Our established, 

 
Confidential 
Page 11 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
successful community relationships over the past decade make us uniquely positioned to give back to the community 
who, after participation in SICAS-1, 4 want this trial. Our study has potential for huge impact.  Rather than just 
intervening for one asthmatic child in one home at a time, we aim to effectively and efficiently improve the school 
environment, and by so doing, improve control of asthma, one of the most prevalent and costly chronic diseases of 
childhood, in a large community of vulnerable symptomatic urban children. 
 
Our school-based IPM and air cleaner trial will have particular relevance to long-term public policy and planning for 
disadvantaged urban U.S. schools with similar indoor environments, where, as we found in 17% of elementary school 
children wake up at night because of asthma and 15% have missed school or medical care for asthma in the past year.  
Our proposed interventions will likely result in net savings, where implementation costs are offset by fewer symptom-
days and improved quality of life for children, less health care utilization and less loss of work-days (greater economic 
productivity) for caregivers. Previous indoor environment intervention trials focused on individuals in single homes.  If 
we demonstrate that reduction of classroom-specific exposures leads to improved asthma outcomes, then our findings 
can be translated into efficient and cost-effective strategies to benefit communities of children through improving the 
school environment, where children in America spend the majority of their day. 
Rationale for Selection of Intervention  
A) Nature of Intervention to be Tested: 
 Classroom Environmental Intervention:  After randomization, active or sham (placebo) HEPA air filters will be 
placed in the primary home classroom, where elementary students spend the majority of their day.  The students, 
staff, and investigators will be blinded to active versus sham. The Air Filters: AP103A model(Woongjin Coway Co., 
Ltd; Oreck Air Instinct™ 200, Oreck Direct, LLC) captures particles down to 0.1 micron in size and has a maximum 
clean air delivery rate (CADR) of 160 ft3/min (CFM) for dust. The filter is designed for rooms up to 400 sq. ft., 4 filters 
worked well in our Pilot and well-received in classroom/school setting.   School Intervention: The Integrated Pest 
Management (IPM) School will receive an IPM strategy (extermination with rodenticide, traps, and sealing of holes 
and cracks), air filters, cleaning reservoirs, and education regarding pest control measures. The intervention 
procedures will be those that were used in a pilot intervention study,18 and the ICAS Pongracic Study15, and the 
current NIAID funded MAAIT Study (AI 083238). The school-specific IPM will focus on surrounding areas that feed 
into the classroom and harbor infestation by food and water sources (i.e. cafeteria).  This is modeled after the home 
interventions that work by focusing on the child’s bedroom, surrounding areas, and the kitchen.  The home-based 
strategies have been proven as effective and cost-effective strategies for reducing pertinent allergen exposure and 
improving health outcomes in homes1.   Our school-based strategies will focus on the child’s primary classroom, 
surrounding areas, and the cafeteria.   Unlike home intervention strategies, where it is impossible to blind, the 
School IPM strategies may also be single blinded, because the students attend school during the day, and the IPM 
will be conducted after hours when the students are home.  Therefore, staff will know which school is randomized 
to IPM but the students will be blinded.  
B) Stage of Intervention Phase III Environmental Intervention with Extensive Home-based Clinical experience that will be 
described in section 1.4   
C) Mechanism of action of the Intervention Reducing classroom/school environmental exposure to particulate matter 
and its associated allergen and mold particles. Targeted integrated pest management to further reduce mouse allergen.  

 
Confidential 
Page 12 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
 D) Rationale for the Intervention Targets to Address the Overall Study Objective (Described in Section 2)  
RATIONALE FOR CLINICAL TRIAL INTERVENTION TARGETS: Mouse, Mold and Particle Pollution  
 
1.1.  Supporting Data (Clinical Aim 1):Overview of SICAS-1:  SICAS-1, our school-based inner-city observational study, 
was designed to assess the relation of classroom/school environment allergen and mold exposure to asthma morbidity, 
adjusting for home exposure. It is the most comprehensive study of its kind ever performed in the United States4, 9, 19-24. 
Every spring, screening surveys in English or Spanish were distributed to all students at 8-10 elementary schools. Of 
7032 school children screened, 22% had a history of asthma, which for most children was active and involved health care 
utilization: 15% of the 7032 had asthma-related missed school days or medical care in the past 12 months, and 17% had 
night time asthma symptoms. 
From the 700-1000 surveys collected each spring, children with asthma were recruited for extensive summer 
baseline phenotypic assessments, including allergy and lung function testing. Every year approximately 75-100 students 
were enrolled from 8-10 unique schools. School/classroom visits were conducted twice during the academic school year, 
approximately 6 months apart, to perform week-long school floor dust, air, airborne mold sampling, and inspections 
using standardized methods4, 25. Home dust samples and inspection were also obtained. Standard measures1 (Table 1) of 
maximum number of symptoms per 2 week period, school absences for asthma, caregiver and health care utilization 
data were collected 3, 6, 9, and 12 months after summer baseline assessments. During the academic school year we also 
measured follow up lung function and fractional exhaled NO (FeNO). We assessed associations of school, classroom and 
home specific exposure data to child health outcomes obtained during the academic school year. Seventy-percent of 
enrolled children had at least one positive skin test. While specific sensitization to mouse was associated with slightly 
higher symptom counts (Fig. 2), the association of mouse allergen level with maximum symptom counts /2 weeks did not 
differ for those with any sensitization vs no sensitization. Our findings reported below (Sections 1.1.a, b, and c) support 
our hypothesis that our interventions will benefit all the asthmatic children. 
1.1.a. SICAS-1 Mouse Allergen, Mold Allergen and Particle Pollution Classroom/School Exposures:  We measured 
exposures in all 36 schools and 241 classrooms of participating students (N=351). All schools and 99% of classrooms had 
detectable mouse allergen. Compared to participants’ home levels9, 10, their classroom levels of mouse allergen were 
consistently higher20. Levels were markedly above levels shown to increase asthma morbidity in other studies14 and 
comparable to those seen in occupational research facilities that house/breed mice26.  School cat and dog allergen levels 
were variable9 and not at levels previously shown to worsen symptoms27.  While there was very little dust mite or 
cockroach allergen, we measured significant dust and airborne mold levels in the schools21.  As well as reducing mouse 
exposures, our SICAS-2 intervention (IPM/cleaning and HEPA air filters) will decrease molds and other allergen or irritant 
components of particles (see Sections 1.2 and 1.3 for preliminary data demonstrating intervention efficacy). 
1.1.b. Classroom MOUSE Exposure and Asthma Symptoms: SICAS-1 enabled us to identify the independent role of 
classroom mouse allergen exposure in exacerbation of asthma symptoms, adjusting for potential confounders: home 
environmental tobacco smoke, endotoxin, household income, gender, age, race, body mass index28, perceived stress29 
cockroach and home mouse exposure. Upon updating analyses since the last submission to include our full asthma 
cohort, we observe that higher mouse allergen levels in classrooms were associated with higher asthma symptoms in the 
school year for all study participants, and these associations were not modified by specific or any sensitization. Overall a 
10-fold increase in mouse allergen levels was associated with 45% more symptom days (95% CI: 9% to 91%, p=0.01) per 2 
week period.  Given that classroom mouse allergen levels were as high as in animal labs30, we are not surprised to find 
associations of mouse allergen with increased asthma symptoms in non-sensitized as well as sensitized children. In 
occupational lab animal settings, twice as many lab techs have symptoms than are specifically sensitized, suggesting 
non-allergic effects of mouse allergen or mouse-associated particle exposures31.   
 

 
Confidential 
Page 13 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
Classroom MOLD Exposure and Multiple Asthma Outcomes:  For clinically relevant taxa (e.g., Penicillium/ Aspergillus, 
Alternaria)32, our classroom mold levels were also higher than those identified in home-based inner-city studies linking 
mold to increased asthma symptoms in children33.  Previously we reported associations of mold with symptoms only for 
mold-sensitized students.12 Subsequent preliminary analyses for the full SICAS-1 cohort show that regardless of 
sensitization status, higher classroom air Alternaria was linked to more missed sleep due to asthma, changed caregiver 
plans [OR=1.96(1.27, 3.02); p=0.002 for a SD increase in Alternaria level], and a higher composite outcome score (more 
dyspnea, nocturnal wheeze, limited activity, rescue medication) [OR=1.73(1.19, 2.52)]. There is ample evidence that 
molds in home/school environments can worsen symptoms via not only allergic, but also non-allergic, irritant 
mechanisms.33-35 
 
Classroom Pollution Exposure and Asthma Symptoms:  Pollution has been shown to worsen asthma in urban children36.  
SICAS-1 was not funded for air pollution assessment but outside funds enabled us to measure classroom-specific air 
pollutants over 1 week periods [integrated NO2, black carbon (BC), PM2.5; continuous PM2.5] in a subset of classrooms.  In 
SICAS-1 students, we demonstrated a exposure-response relationship between increasing concentrations of indoor NO2 
(ppb) and more asthma symptom-days, (adjusted relative rate (RRadj)=1.05 per unit increase in NO2 levels (95% CI= 
1.02, 1.08), p=0.002)13.   NO2 is likely a marker for local traffic and regional pollution infiltrating indoors,37 given the 
absence of indoor school sources for this pollutant. We found similar exposure-response relationships of BC and PM2.5 
with increased symptoms;power was limited by the fact that we had fewer indoor measurements for these two 
pollutants.  
 
1.2. Pilot HEPA Filter Intervention: We acknowledge that there is a paucity of data relating school-specific interventions 
and asthma/allergic symptoms.  We conducted a pilot evaluation of HEPA filters (AP1008BH and AP1008CH model, 
Woongjin Coway Co., Ltd; Oreck Air Instinct™ 200, Oreck Direct, LLC) in two neighboring classrooms of approximately 
1000 ft2 in the normal classroom setting (control and intervention).  Environmental sampling was conducted at baseline, 
during a two-week intervention and immediately after the intervention to compare exposure levels between the control 
and intervention classrooms at baseline, during, and post intervention.  Particle Reduction: Our pilot study 
demonstrated a 75% reduction in PM2.5 from the HEPA particle filter/purifiers after adjusting for natural ambient 
particles in control classrooms. Using the same study design, in another busy building, when windows were closed or 
minimally opened we demonstrated an 87-97% reduction in particles and a 74% reduction when windows were opened 
2.2 cm.   
 
 
Allergen/Mold Reduction: Classroom HEPA air filters alone reduced airborne mouse allergen by 75% compared to 
control classrooms but did not reduce settled dust levels (which we plan to reduce with IPM).   We found similar effects 
of HEPA filters in reducing classroom cat and dog allergen levels, which were, as previously documented, low to begin 
with, and therefore, likely of limited clinical significance38.  We also demonstrated that classroom HEPA filters reduced 
mold levels (measured by Burkhart Mold Samplers as in SICAS-1) by 79% in one day. Mold levels rose back up to baseline 
when the air filter/purifiers were turned off.  
 
1.3. Pilot IPM Intervention: With donated resources, we conducted Integrated Pest Management (IPM) targeting mouse 
allergen in the school, utilizing similar methods conducted in homes18 and the NIAID home IPM study (AI 083238).  IPM 
included inspection, trapping with glue and snap traps, and exclusion (door sweeps and filled heating pipe holes with 
school maintenance).  Within a couple months of school-wide IPM (focused on cafeteria/classroom, targeting 
surrounding reservoirs), we were able to effectively reduce classroom mouse allergen levels in settled dust by 75%.  
 

 
Confidential 
Page 14 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
Summary.Our observational SICAS-1 study provides the rationale for our Clinical Trial Intervention Targets in SICAS-2.  
We have demonstrated that classroom mouse allergen, mold, and air pollution exposures are highly prevalent and are 
important influences on childhood asthma morbidity. Moreover we have shown that we can reduce these exposures in 
our real world urban school settings. Addressing reviewer concerns that only children with specific sensitization to mouse 
or mold would benefit from SICAS-2 interventions --reduction of classroom airborne particles (including particle-
associated mouse and mold allergens as well as pollution) and pest management of mouse and other associated 
exposures-- our data suggest that all symptomatic asthmatic school children will benefit.   
 
E) Advantages of Intervention to be Tested:  SICAS-2 will be a factorial design with the classroom randomized double-
blind, placebo controlled to Air Filter/purifier and school being randomized in a parallel fashion to an intervention of 
IPM/Education/Cleaning versus Control School.  This allows the advantage of understanding the classroom specific 
benefits of the air filter/purifier and school wide(focused on classroom/cafeteria, and surrounding supporting areas) 
effects of the IPM intervention. Factorial designs have been validated and established39, 40 as an efficient use of 
resources by answering the effects of two interventions.  The classroom intervention with the parallel school wide 
intervention allows us to maximize impact and efficiency of answering two questions in one trial.    
Advantages and Impact: Schools are equivalent to occupational settings: we have shown that exposures (especially to 
mouse) can be at occupational levels. Approaches to reduce exposure in the work place are relevant for improvement of 
asthma in large populations of school children. Our study is the first ever comprehensive school-based environment 
intervention trial of HEPA filtration and IPM to improve asthma. Our engineers have unique skills and experience which 
they applied to development, tailoring and successful piloting of unique quiet high efficiency air cleaner technology (and 
matched sham filter controls) which we have demonstrated to be effective in reducing exposures and acceptable in the 
classrooms setting. Our established, successful community relationships over the past decade  make us uniquely 
positioned to give back to the community who, after participation in SICAS-1, 4 want this trial. Our study has potential for 
huge impact.  Rather than just intervening for one asthmatic child in one home at a time, we aim to effectively and 
efficiently improve the school environment, and by so doing, improve control of asthma, one of the most prevalent and 
costly chronic diseases of childhood, in a large community of vulnerable symptomatic urban children. 
 
1.2. Preclinical Experience: n/a This is an environmental intervention 
1.3. Clinical Studies for Intervention  
Home Allergen Exposure, Sensitization, and Asthma Morbidity: Allergen exposure in home environments is an 
important trigger in 80% to 90% of children with asthma41, 42.  It is well established from multiple cohorts, particularly 
NIAID funded National Cooperative Inner- City Asthma Study (NCICAS) and Inner-City Asthma Study/Consortium 
(ICAS/ICAC) that certain unique inner-city allergenic exposures in home environments such as cockroach43-45 and rodent 
allergen18, 46-53 14  are highly prevalent.  These and other previous studies have shown that children who are sensitized to 
cockroach, mouse, and rat allergen have increased asthma symptoms and morbidity when exposed to that specific 
allergen in the home.   Mold, such as Alternaria, Aspergillus, Cladosporium, and Penicillium, may be an important 
respiratory irritant or allergen in home environments and increase asthma morbidity even in asthmatic children not 
sensitized to mold33, 54-56 .   The Inner-City Asthma Study showed that particulate matter from outdoor pollution was 

 
Confidential 
Page 15 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
highly prevalent in homes57, and that higher outdoor concentrations of NO2 (from auto emissions) and indoor particulate 
pollutants were associated with asthma morbidity in urban children with asthma36.  High indoor particulate-matter was 
associated with decreased lung function, greater respiratory symptoms, more frequent use of rescue medications 58, 59, 
and evidence of inflammation as measured by elevated exhaled nitric oxide levels in asthmatic children59. 
Home Based Allergen/Mold Abatement Intervention Studies: There has been significant attention to the potential role 
of intervention measures in inner-city homes to reduce allergen exposure (particularly mouse, dust mite, and cockroach) 
and asthma morbidity in sensitized individuals60-64.  Review of these data concluded that interventions to reduce these 
allergen levels should be routine in the management of allergic asthma and have shown benefit in reducing asthma 
symptoms and morbidity, particularly in those sensitized to the specific allergen60, 65-67,68-71.  In the Inner-City Asthma 
Study (ICAS), a recent comprehensive home intervention targeted at allergens to which the child was sensitized was 
found to be cost-effective72 and helpful in decreasing asthma symptoms1.  ICAS also demonstrated children sensitized to 
mouse allergen who had targeted mouse allergen intervention resulting in 50% reduction in home exposure 
demonstrated reduced asthma morbidity15.  
In the ICAS, a substudy in 40 children that decreased mouse allergen by 50% regardless of baseline levels, were 
associated with decreased morbidity15.    In only 18  homes (12 intervention 6 controls), decreasing mouse allergen by 
75% reduced symptom days by 1/week, but was just not powered for significant effects18.   
Recent publications from this work did determine that mold exposure was associated with symptoms and that simple 
home-based interventions that have worked in NCICAS and ICAS were beneficial for these children.    In a Hurricane 
Katrina study, simple intervention of education and providing caretakers with HEPA filters showed reductions of mold 
counts by 50% and reduction of symptoms73.    
We are currently conducting an NIAID funded intervention trial in Boston and Baltimore (AI 083238) using an established 
targeted method to decrease mouse allergen in homes of children with asthma18.  While not a randomized controlled 
trial, we have evidence from our partners in the Children’s Hospital  Community Asthma Initiative that home based 
education and Integrated Pest Management (IPM) referrals improved health outcomes and was highly cost-effective in 
reducing hospital and health care utilization costs74, suggesting interventions to reduce exposures are important in 
reducing asthma morbidity. 
Air Pollution Intervention in Homes: Regardless of baseline levels, a New Zealand home intervention by using gas 
flues to reduce NO2 from gas stoves (geometric mean 7.3 mcg/m3 versus 10.9 mcg/m3 in controls, P<0.01), resulted in 
significant reduction in asthma symptoms75. 
Summary of Other Relevant School-Based Intervention Studies: 
There is a paucity of comprehensive data on school/classroom based environmental intervention studies and its effects 
on asthma morbidity.  One Swedish study showed that levels of airborne cat allergen can be reduced by allergen 
avoidance measures in 2 classrooms, using special school clothing or pet ownership ban76, while another Swedish study 
found that a term of curtain, upholstery, bookshelves and cupboard replacement along with increased regular cleaning 
did not alter cat allergen levels77.  The same group found that increased cleaning measures to decrease allergen levels 
may have decreased self-reported asthma symptoms, but these studies did not influence actual cat allergen levels 78. 

 
Confidential 
Page 16 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
Mold Intervention in Schools: Pilot health benefits were demonstrated in a mold intervention in only two  (one 
intervention one control) Finnish schools34 with 50% reduction in mold levels.  In a comparison of only two schools (one 
with intervention and one without), there were significant differences in symptoms by reducing mold spore levels 
50%34.    
NO2 air pollution Intervention in Schools: In one Australian school study an intervention replacing unflued gas heaters 
with electric heaters among 199 students (45 intervention and 73 controls) attending 18 schools effectively reduced NO2 
(Intervention mean (standard deviation) 15 ppb (6.6) and Control 47 ppb (26.8) and improved asthma symptoms as 
measured by difficulty breathing during the day (Relative Risk [RR] = 0.41; 95% CI: 0.07, 0.98) and night (RR = 0.32; 95% 
CI: 0.14, 0.69), chest tightness during the day (RR = 0.45; 95% CI: 0.25, 0.81), and daytime asthma attacks (RR = 0.39; 
95% CI: 0.17, 0.93)79.  Most schools in the United States no longer have active kitchens with stoves so the indoor source 
of NO2 as seen in the Australian study is not applicable in America.   
2. Study Hypotheses/Objectives  
2.1. Hypotheses  
Our central hypothesis is that reducing classroom/school exposure to particles and their associated allergens 
(particularly mouse/mold) will decrease asthma morbidity in students with asthma.   In School Inner-City Asthma 
Intervention Study-2 (SICAS-2) we plan to test our central hypothesis in an intervention study of 300 elementary school-
aged children with asthma from multiple classrooms in 40  inner-city elementary schools.  
2.2. Primary Objective(s) 
To determine whether a school/classroom-based environmental intervention (classroom High Efficiency Particulate Air 
(HEPA) filter/purifying units and school integrated pest management) will:  
(a)  Reduce asthma symptoms (primary outcome as used in other NIAID inner-city asthma studies1, 3); and 
(b)  Reduce medication use, health care utilization, and improve lung function (secondary outcomes). 
 
 
2.3. Secondary Objective(s) 
 To explore whether sensitization or other asthma phenotypes defined at baseline modify which pathways or networks 
of genes undergo intervention-related changes in methylation or gene expression that, in turn, are associated with 
improvement in asthma outcomes. 
 
Mechanistic Objective: 
Hypothesis -  Growing evidence suggests that asthma phenotypes are sustained by gene expression alterations 
programmed through modifiable epigenetic mechanisms80  . 
To test the hypothesis that effects of school/classroom-based environmental interventions on symptoms/other 
measures of asthma control occur through changes in gene methylation or expression in pathways (and secondarily, in 
genes) relevant to airway function and asthma.  Within pathways or networks of genes (pre-specified or discovered in 

 
Confidential 
Page 17 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
unsupervised analyses) we will (a) determine how our interventions influence changes in airway cell methylation or gene 
expression and (b) evaluate how our intervention-associated changes in methylation and gene expression influence 
asthma outcomes. Finally, using mediation analysis, we will (c) estimate how much of the intervention effects on asthma 
symptoms occur through methylation/expression changes86, 87. 
3. Study Design 
3.1. Description of Study Design  
SICAS-2 is a factorial, randomized, placebo controlled, parallel group phase II clinical trial designed to assess the efficacy 
of a classroom (Air Filter) and , randomized, controlled, parallel group school (IPM) environmental intervention in 
improving asthma control in children with asthma.  SICAS-2 is a single-center environmental intervention study. Three 
hundred children attending one of the Schools in the metropolitan area (SBMA) (total of 40 schools) from September 
thru June in grades K to 8th (generally ages 4-15) will be randomized to one of the four groups (75 per group) : 
 (1) IPM School/Classroom Air Filter 
 (2) IPM School/Classroom Sham (Placebo) Air Filter 
(3) Control School/ Classroom Air Filter and 
 (4) Control School/Classroom Sham (Placebo) Air Filter.  
Each randomized participant will be followed for a total of about 12 months, approximately 6-12 weeks prior to 
randomization and 10 months following randomization. 
   
 
 
 
 
 
 
 
 
 
 

 
Confidential 
Page 18 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
Figure 1 SICAS-2 Annual Schema 
fall
winter
spring
Season
Clinical 
Trial
*Classroom HEPA filter vs Sham Control
School-wide IPM vs school-wide Control
Randomization*
Mechanistic
Core
Nasal cell collection
for methylation &
expression analysis
Nasal cell collection
for methylation &
expression analysis
PFT/FeNO
School/Home 
Exposure
PFT/FeNO
School/Home 
Exposure
Intervention* 
Ends
summer
spring
Baseline 
Survey
PFTs/FeNO
Intervention
Starts
Screening
Recruitment
75 students/year, 10 schools
300 students, 40 schools, 4 years
Baseline 
School
Exposure
School 
ends
Follow-up surveys every 2 months
School
starts
summer
 
 
 
 
 
 
 
 
 
 
*Arms of SICAS-2 Study 
Cohort  A - ARM 1 
75 
SCHOOL: IPM INTERVENTION 
CLASSROOM: AIR FILTER 
Cohort  B  - ARM 2 
75 
SCHOOL: IPM INTERVENTION 
CLASSROOM:  SHAM (PLACEBO) AIR FILTER 
Cohort C  - ARM 3 
75 
SCHOOL: CONTROL 
CLASSROOM: AIR FILTER 
Cohort D  - ARM 4 
75 
SCHOOL: CONTROL 
CLASSROOM: SHAM (PLACEBO) AIR FILTER 
 
3.2. Primary Endpoint   
 Annual recruitment schema depicted.  Schools randomized to IPM/Targeted Cleaning Reservoirs Parallel Design.  Within 
schools, classrooms randomized to air purifiers or sham purifiers in double blind, placebo controlled fashion.  Target annual 
recruitment is 75 students enrolled per year from 8-10 unique schools. Target study enrollment Year 1-4  is 300 students 
from 40 unique schools.     Year 5, complete follow-up, data analysis. * Primary efficacy is ascertained at baseline  and the 
follow-up phone surveys conducted every 2 months post randomization (Schedule of events/procedures, Table 2, page 34) 

 
Confidential 
Page 19 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
See Table 1. The primary endpoint is the rate of maximal number of days with asthma symptoms in the previous two 
weeks before the clinical outcome interview, defined as the largest value among the following three variables: number 
of days with wheezing, tightness in the chest, or cough; number of nights with disturbed sleep as a result of asthma; and 
number of days on which the child had to slow down or discontinue play activities because of asthma. The primary 
endpoint is the longitudinal vector of symptom-days at each of the visits for each subject ascertained at baseline and 
every two months follow up during the school year after randomization.  We have proposed to include visit number, 
which will does not serve as a confounder but will remove any seasonal variation in symptoms exhibited independent of 
intervention groups.  This is the main advantage of using the vector of multiple visit-specific symptom outcomes as the 
outcome, rather than the average of the values over the post-randomization period and allows us to control for 
covariates.   Maximum asthma symptom days over two weeks will be compared between the 4 groups: (1) IPM 
School/Classroom Air Filter (2) IPM School/Classroom Sham (Placebo) Air Filter, (3) Control School/ Classroom Air Filter 
and (4) Control School/Classroom Sham (Placebo) Air Filter.  This is the same primary outcome used in the other NIAID 
funded Inner-City Asthma Consortium Studies1, 3. 
 
The disease pattern that we anticipate (and have seen in SICAS-1) will be representative of that of most inner-city urban 
asthmatic children. Many have frequent nighttime awakenings with asthma symptoms, disrupted activities, and 
frequent use of rescue medication. Their disease takes its economic toll through loss of caregiver work days, and child 
absences or increased health care utilization that does not necessarily involve hospitalization or systemic steroid 
bursts.  Our primary composite outcome “maximum symptom days” was used and validated as the primary outcome in 
the Inner-City Asthma3, 14, 33, 36  trial and other home-based clinical environmental intervention trials1, 15. Symptom-days 
and health care utilization were both demonstrated to have economic relevance in cost-benefit analyses by the Inner-
City Asthma trial1, 72, 88.  
 
Table 1: Primary and Secondary Clinical Outcomes1, 5, 72, 88  
Primary  Clinical Outcomes  
Primary Indices  
Maximum asthma symptom days 
in past two weeks 
Maximum number  of 
1.  Days with wheezing, tightness in 
the chest, or cough  and/or 
2. Nights with disturbed sleep as a 
result of asthma and/or  
3. Days on which the child had to 
slow down or discontinue play 
activities because of asthma 
Secondary  Clinical Outcomes 
Primary Indices 
School Absences 
Number of school days missed 
because of asthma/ 2 weeks 
 
 
 
 
Health Care Utilization 
Total asthma-related unscheduled 
visits (UVs) defined as sum of 
unscheduled clinic visits and 
emergency department visits, and 
asthma-related overnight 
hospitalizations /school year* 
Composite Asthma Severity 
Index5  
Day symptoms and albuterol use, 
night symptoms and albuterol use, 
controller treatment, lung function, 

 
Confidential 
Page 20 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
 
 
 
 
 
3.3. Secondary Endpoint 
Secondary outcomes specified in Table 1 will be standardized according to the recent Asthma Outcomes Workshop 
guidelines5, 6. They include school absences, Health Care Utilization; the Composite Asthma Severity Index PFT’s and 
degree of exposure reduction. As demonstrated in our Cost Effectiveness Analysis Plan, a number of these outcomes can 
be used in estimating costs of the asthma morbidity and cost savings of the intervention. 
 
 
Pulmonary function: 
FEV1, 
FEV1/FVC 
FEF 25%-75% 
percent change in FEV1 after short-acting bronchodilator 
 
 
Mechanistic Endpoints:  
To explore whether sensitization or other asthma phenotypes defined at baseline modify which pathways or networks 
of genes undergo intervention-related changes in methylation or gene expression that, in turn, are associated with 
improvement in asthma outcomes. 
DNA/RNA Methylation/Transcriptomic Biomarkers. DNA methylation and RNA gene expression will be measured as 
described below. Within pathways or networks of genes (pre-specified or discovered in unsupervised analyses) we will 
(a) determine how our interventions influence changes in airway cell methylation or gene expression and (b) evaluate 
how our intervention-associated changes in methylation and gene expression influence asthma outcomes. Finally, using 
mediation analysis, we will (c) estimate how much of the intervention effects on asthma symptoms occurs through 
methylation/expression changes86, 87 
Thus these measures can be considered to be intermediate outcomes, but the changes in these measures between 
baseline and near the end of the intervention are being considered both as outcomes of the interventions, as predictors 
of the clinical outcomes (e.g., symptoms/2-week period) and finally, as mediators of the relationship of the interventions 
to the clinical responses. 
and exacerbations (defined as 
systemic steroids for asthma )* 
Pulmonary Function (PFT) 
FEV1; FEV1/FVC* 
[Secondary indices : (a) FEF25-75.  
(b) Bronchodllator responsiveness 
(% change in FEV1 post albuterol)] 
Degree of Exposure Reduction 
Health Outcomes (Primary and 
Secondary)  
* Standardized  core asthma outcomes from  Asthma Outcomes Workshop5, 6  
**Health care use post randomization 

 
Confidential 
Page 21 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
Precious specimens beyond our scope to analyze with funding from this proposal will be saved to provide opportunities 
for future testing of follow-up hypotheses. 
Mechanistic endpoint is magnitude of changes in cell gene methylation or expression in pathways (and secondarily, in 
genes) relevant to airway function and asthma to determine if the effects of school/classroom-based environmental 
interventions on symptoms/other measures of asthma control occur through these changes. This will be done by 
evaluating within pathways or networks of genes (pre-specified or discovered in unsupervised analyses) we will (a) 
determine how our interventions influence changes in  airway cell methylation or gene expression and (b) evaluate how 
our intervention-associated changes in methylation and gene expression influence asthma outcomes. Finally, using 
mediation analysis, we will (c) estimate how much of the intervention effects on asthma symptoms occur through 
methylation/expression changes 
3.4. Exploratory Enpoint(s) 
1. Days of rescue medication use/2 weeks; 
2. Days of cough without a cold/2 weeks; 
3. Days of exercise-induced asthma symptoms/2 weeks; 
4. Nocturnal symptoms/2 weeks. 
5. Days of slowed activity/2 weeks. 
7. Asthma control, assessed by the Asthma Control Test 
8. Pulmonary inflammation, assessed by exhaled nitric oxide (FeNO) 
The following exploratory research questions will also be addressed: 
(1) In the Intervention Group, does the degree of exposure reduction modify the effect of the intervention on asthma 
outcomes? 
 
(2) Is there a multi-level effect in relation to School, Home, Class Effect on outcomes? 
 
(3) In the Intervention group, does the presence of other indoor allergen sensitivities and exposures modify the effect of 
the intervention on asthma outcomes? 
 
4) Does the degree of sensitization to mouse or mold (skin test size of allergen specific IgE level)  modify the effect of the 
intervention? 
Any of the above sensitization and exposure criteria 
Other cut points will also be determined a priori and interactions will also be tested using exposure as a continuous 
variable based on the literature of clinically relevant exposure and sensitization levels. 
 
5) Does obesity defined as Body Mass Index for age/percentiles modify these outcomes? This variable will be analyzed 
and adjusted for in models.  
 
6) Does perceived stress defined as standardized perceived stress score29 modify these outcomes? This variable will be 
analyzed and adjusted for in models. 
7) Does sleep (habits,quality)  affect any of these outcomes?   
Validated comprehensive sleep questions and sleep diary will be collected. 
 Sleep quality assessed with  wrist actigraphs (sleep monitors)  which are worn for 5-7 days while sleeping.  
Sleep quality assessed with sound level meter which will be placed in the home for 5-7 days. 

 
Confidential 
Page 22 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
Sleep Disordered Breathing  will be assessed with the nasal oxygen cannula monitor and pulse oximeter.  
These variable will be analyzed and adjusted for in models 
 
8) Does pulse oximetry/ CO-Oximetry affect any of these outcomes? This variable will be analyzed and adjusted for in 
models 
 
9) Are there any urinary biomarkers that predict outcomes? (i.e. metabolomics, proteomics, pesticides, urinary 
chemicals ( BP-3, BPA, Butylparaben, Ethylparaben, Methylparaben, Propylparaben, Triclosan, 2,4-dichlorophenol and 
2,5-dichlorophenol, ispoprotenes, pesticides, benzenes, leukotrienes, and creatinine), that could effect outcomes 
 
10) Are there any environmental metagenome, microbiome markers that could affect outcomes? 
 
11) Are there any fungal, microbiome, bacterial markers that could affect or predict outcomes? (shot gun sequencing, 
ergosterol) 
 
12) Would any food allergen exposures in the environment effect outcomes (i.e. peanut, milk, egg proteins)? 
 
13) Does the intervention improve symptoms of other students in the classroom (i.e. non-allergic, nasal, irritant, other)? 
 
14) Are there any other immune biomarkers which could further our understanding of mechanisms behind the response 
to our intervention such as pro-inflammatory cytokines such as IL-6, IL-33, leptin, basophils, TNF α, IFN-γ and other 
cytokines,  
 
15) Are there gender differences that could modify our outcomes including  serum gender specific hormones (i.e. 
E2,DHEAS,testosterone, SHBG, Progesterone)  
 
16) Could certain nasal viruses, microbial organisms, and bacteria affect these outcomes? 
 
17)  Do Patient Reported Outcomes Measurement Information System (PROMIS) variables that measure patient–
reported health status for physical, mental, and social well–being.affect our outcomes and are they reproducible in 
other cohorts of asthma and other chronic diseases? 
 
18.  Does the intervention prove to be cost-effective? (i.e. if it decreases missed school days and parent/caregiver 
missed days of work and improve quality of life in comparison to the cost of the intervention is it cost-effective?)? 
 
19.  Could any markers of ventilation, CO2, temperature and humidity affect outcomes? 
 
3.5. Stratification, Randomization, and Blinding/Masking 
Randomization: Participants will be randomized within three weeks of the screening school visit in a 1:1 ratio using a 
statistical software package to generate random numbers. The randomization scheme will be developed by the DMAC. 
Participants at each site will be randomized independently of the other sites, and random blocks of 4 to 6 will be used to 
maintain similar enrollment into the two study groups at each site. There will be no stratification.  

 
Confidential 
Page 23 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
Masking:  Although it may be possible to attempt to mask some study staff by increasing the number of research 
assistants at each site so that 1-2 RAs could be dedicated to collection of clinical outcome data, this would substantially 
increase the budget, so double-blind is not practical or feasible, even in a school-based study.  Double-blinding in 
environmental home-based studies are also not feasible.  There are also several aspects of the study that will guard 
against bias that could result from having unmasked study staff. First, all laboratory assays will be conducted by 
laboratory technicians who will be masked to group assignments.  Second, some of the clinical data that are collected, 
including exhaled nitric oxide and pre- and post- bronchodilator spirometry, are objective measurements that are less 
subject to influence by the study staff or study participants. Third, analyses will be conducted to determine if any 
improvements in clinical outcomes are associated specifically with decreases in school allergen, mold pollutant levels, not 
just to group assignment. 
The Air Filter Classroom Intervention, however, will be double-blind, placebo controlled randomization.  Staff from the 
HSPH Environmental Assessment and Intervention Core who do not have contact with the study participants will service 
and change the air filters every 3 months at the school after school hours, maintaining participants, PI, and study staff 
blinding. 
All laboratory studies (allergen ELISAs, allergen-specific IgE levels , endotoxin levels, PM 2.5, Black Carbon levels, NO2 
levels, and mold) will be performed in centralized laboratories in batches to minimize variability of the assay. 
4. Selection of Participants and Clinical Sites/Laboratories 
4.1. Rationale for Study Population 
Health disparities urban school aged children is particularly high in regards to asthma and its associated morbidity, 
costing billions of dollars in health care utilization.  Recent NIH/NIAID efforts have put significant resources in identifying 
remediable causes, particularly in the home environment.8  Nearly all elementary school children spend 7 to 12 hours a 
day in school, and most of that time is spent in one classroom. It is nearly every child’s required occupational 
environment.  Our observational School Inner-City Asthma Study (SICAS-1) demonstrated the importance of the school 
environment in inner-city environments among elementary students.  Therefore, focusing our population in elementary 
school age inner-city children makes this an ideal population for this study.  Our proposed age/grade levels are a time 
where children spend the majority of their day in a primary classroom, and prior to further effect modifying changes 
that may change during puberty.   
 
We are simply building on our established protocol and infrastructure developed during SICAS-1 and adding an 
established environmental school-based intervention to test our hypothesis. This is an unprecedented, high impact 
opportunity to test whether we can efficiently benefit a community of children in the school environment as opposed 
to individuals in single homes.  
4.2. Inclusion Criteria 
Individuals who meet all of the following criteria are eligible for enrollment as study participants:  
1. Subject and/or parent guardian must be able to understand and provide informed consent 
2. Males and females who are grades K-8 (age 4-15) during the subsequent academic school year after spring 
screening.  

 
Confidential 
Page 24 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
3. Attend one of the schools that study team have permission to obtain classroom/school environmental samples for 
the subsequent academic school year.  
4. Have no plans to move schools within the upcoming 12 months 
5. Have physician-diagnosed asthma at least 1 year prior to the screening visit 
 
6. Have  evidence of active,  asthma  as defined by at least one of the following: 
 
Wheezing symptoms in the past 12 months 
 
On Daily controller medications for asthma 
 
One asthma-related unscheduled visit to an emergency department (ED), clinic or urgent care facility in the 
previous 12 months  
 
One asthma-related overnight hospitalization in the previous 12 months  
 
One or more bursts of oral or injectable corticosteroids in the previous 12 months 
 (criteria modeled from the NIAID funded Inner-City Asthma Consortium inclusion/exclusion criteria and SICAS) 1-4 
4.3. Exclusion Criteria for Participant 
Individuals who meet any of these criteria are not eligible for enrollment as study participants:  
1. Inability or unwillingness of a participant to give written informed consent or comply with study protocol 
Coordinator/PI judgment  
2. Lung disease, other than asthma, that requires daily medication 
3. Inability to do lung function testing 
4. Cardiovascular disease that requires daily medication, excluding hypertension 
5. Taking a beta-blocker 
6. Currently receiving escalation (has not reached maintenance) of Immunotherapy (allergy shots) 
7. Switching to a school where staff are not doing environmental sampling for that year. 
 
8.  Current, diagnosed, mental illness or current, diagnosed or self-reported drug or alcohol abuse that, in the opinion 
of the investigator, would interfere with the participant’s ability to comply with study requirements 
Past or current medical problems or findings from physical examination or laboratory testing that are not listed above, 
which, in the opinion of the investigator, may pose additional risks from participation in the study, may interfere with 
the participant’s ability to comply with study requirements or that may impact the quality or interpretation of the data 
obtained from the study. 
Exclusion Criteria for School 
1. Unable to access areas of school necessary to conduct extermination 
2. School in extensive state of disrepair/damage  as determined by Study PI 
3. Centralized  Air Filtration or Purifying System ( although feasible to account for this, rare in  schools) 
 

 
Confidential 
Page 25 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
4.4. Selection of Clinical Sites/Labs  
The Children’s Hospital Asthma Clinical Research Center (ACRC) is run by Dr. Wanda Phipatanakul and was the single 
site that conducted all the clinical visits and recruitment for SICAS-1, and successfully recruited 400 elementary school 
children with the identical inclusion/exclusion criteria for SICAS-2.  SICAS-1 entailed identical clinical procedures and a 
more aggressive milestone target than proposed for SICAS-2, ensuring the success of this Intervention protocol.   
 
The CTSU laboratory is experienced in molecular biology procedures, immunological assays, radioimmunoassays, and 
specialized sample processing of various body fluids. Genetic testing and evaluation is also available as part of the 
Children’s Hospital Program for Genomics.  As part of Harvard Catalyst, the study has access to all the CLIA approved 
laboratory facilities of Children’s Hospital Clinical Laboratory and of the entire Harvard Community including the 
Harvard School of Public Health (HSPH) Laboratory of Human Epigenetics and Genetics, the Program in Genomics,  the 
Integrated Health Science Facility,  the Harvard Partners Microarry Core and Columbia University for the nasal 
epigenetic/expression mechanistic studies, and the HSPH Environmental Chemistry Laboratory for the analysis of 
environmental particulate matter and pollutants. University of Iowa will provide the analysis of the mold spore sampling 
and allergen/endotoxin analysis of the environmental dust and air samples.  This entire infrastructure and set up has 
already been running in place successfully for SICAS-1.  
5. Known and Potential Risks and Benefits to Participants 
5.1. Risks of Investigational Product or Intervention as cited in Investigator Brochure or Package Insert 
Not Applicable: Environmental Intervention  
5.2. Risks of Investigational Product or Intervention cited in Medical Literature and/or those based on the 
Investigators’ experience 
Portable Room High Efficiency Particulate Air (HEPA) Air Purifier Filters are commercially available and provide no risk to 
the children as they are used to improve environmental air quality.  
Integrated Pest Management may involve using caulking agents, traps, sealing plugging of  holes and keep pests out of 
buildings as directed by manufacturer instructions. 
Cleaning will be standard practices that are to improve the environment and as routinely done by janitors in a school 
setting.  We plan to use non-bleach agents.      Commercially available, non-bleach cleaning agents (e.g. 409®, Fantastik®) 
will be used. The risk of any irritation or symptoms is very small. The cleaning agents will be used as directed by the 
manufacturers as routinely done. 
Commercially available, non-bleach cleaning agents (e.g. 409®, Fantastik®) will be used during the cleaning that occurs 
during the first IPM visit.  Commercially available foam caulking agents (Pur-fill®) will be used to seal holes and cracks 
during the IPM visits.  Both of these agents contain potential irritants that could cause asthma symptoms.  The risk of 
developing asthma symptoms serious enough to require emergency medical attention is very small. The cleaning agents 
will be used as directed by the manufacturers.   
5.3. Risks of Other Protocol Specified Medications 

 
Confidential 
Page 26 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
Risks of Albuterol: Albuterol is a medicine used routinely to help diagnose asthma and to treat asthma, and 
serious reactions are rare. The more common side effects are  
 
fast heart beat 
 
shakiness 
 
upset stomach 
 
heartburn  
 
nervousness 
5.4. Risks of Study Procedures  
 
Skin Testing: 
There is a risk of  
 
Feeling of itching where the skin test was done,  
 
Red raised bump, like an insect bite, where the skin test was done 
 
Rarely wheezing or shortness of breath 
 
1 in 10,000 tests results in a reaction such as sneezing, itchy eyes or hives 
 
Even more rarely, a reaction may occur that may be life-threatening, and in extremely rare cases may 
cause death 
Stopping Antihistamines: If  child is taking antihistamine medication, and stops taking it before skin testing,  
child may have more allergy symptoms such as sneezing, runny nose or stuffy nose.  
 
Blood Draw: Taking blood may cause pain, bleeding, or bruising where the needle is placed.  
 
In rare cases, it may result in fainting.  
 
There is a small risk of infection. 
 
Spirometry 
• Light-headedness during the breathing out period. 
• Occasionally minor chest soreness for several days after the testing. 
 
 
Exhaled Nitric Oxide 
• Your child may become lightheaded or dizzy but this is unlikely 
 
Pulse Oximetrry/ 
 
There are no known risks  
 
Pulse CO Oximetry 
 
There are no known risks 
 
Sleep Monitor  
 
The nasal sensor may cause slight discomfort i.e.tickling sensation in the nose). 
 
The actigraph worn on the wrist overnight may cause slight discomfort. 
 
Saliva 
 
There is no known risk associated with spitting into a cup.  

 
Confidential 
Page 27 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
 
Buccal brush Collection 
 
There is no known risk associated with the collection of buccal cells using small, soft brush 
 
Urine Collection 
 
There is no known risk associated with providing a urine sample 
 
Nasal swab/blow 
 
There is no known risk with providing a nasal sample in this manner. 
 
              Skin swab  
• 
 There is no known risk with providing a skin swab 
 
Nasorption 
• 
There is no known risk with providing a nasal fluid sample in this manner 
 
 
Nasal Epithelial Cell Collection 
  
 
Epistaxis  
 
Nose may feel a bit of tickling in the area or mild irritation. 
 
5.5. Potential Benefits 
Individual participant benefits : The potential benefits for the study participant includes receiving an assessment of 
allergic sensitivities, assessment of school environmental exposures, classroom air filters, extermination and cleaning, as 
well as education regarding environmental control practices. The study participants may also benefit from improved 
asthma control. 
 Benefits to Society : The potential benefits to others include the identification of a method to reduce asthma morbidity 
in students. This knowledge could impact policy decisions regarding environmental interventions to reduce 
school/classroom exposures that may trigger asthma symptoms. This information will directly impact the medical care 
provided to this patient population and could confirm the role of a school/classroom based environmental interventions 
that could effectively and efficiently benefit a community of children. If we demonstrate that reduction of classroom-
specific exposures leads to improved asthma outcomes, then our findings can be translated into efficient and cost-
effective strategies to benefit communities of children through improving the school environment, where children in 
America spend the majority of their day. 
6. Intervention  
6.1.1. Intervention #1 
COWAY  AP1013Amodel High Efficiency Particulate Air (HEPA) Air Purifier Filtration Unit- commercially available 
for use of air filtration in homes, buildings, and classrooms 

 
Confidential 
Page 28 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
6.1.1.1. Formulation, Packaging, and Labeling 
Four COWAY AP1013A model, room Air Filters will be deployed in each school randomized to the IPM Group (appropriate 
for rooms up to 170 square feet). Units will be deployed in the enrolled SICAS-2 student’s primary classroom. Number of 
Units will be determined by the size of classroom.  The units are available in commercial packaging that includes an 
instruction manual. The HSPH Intervention Core will do the masking and blinding of the Sham (Placebo) Air Filters and 
the Active Air Filters with a coded randomization for deployment. The study staff and investigators will be blinded to 
whether the Air Filters are Active or Sham.  For details on commercially available air filters, used commercially in rooms 
for air filtration, company website (Ransport,New Jersey or Los Angeles, CA) 
http://coway-usa.com/product/03_airpurifier.html  
 
6.1.1.2. Dosage, Preparation, and Administration 
Air filter units will be stored at each site according to the manufacturer’s recommendations and product label.   Air filter 
units will be checked for functionality prior to deploying in a school. 
6.1.2. Intervention #2 
 Integrated Pest Management/Cleaning 
6.1.2.1. Formulation, Packaging, and Labeling 
We are modeling methods off of published methods that work in homes , which led to  our NIAID funded Home based 
study (Mouse Allergen Asthma Intervention Trial U01AI083238), and which utilizes successful strategies reducing mouse 
allergen in homes. 
In order to ensure the provision of high quality IPM services according to the study protocol, IPM company (Buono Pest) 
that have been trained for the NIAID AI 083238 will work with the study teams.  Buono Pest is licensed and insured and have 
been successfully working with us in the NIAID funded Mouse Allergen Asthma Intervention Trial.  Buono Pest will 
provide approximately 3-4 IPM technicians who will undergo training for the SICAS-2 IPM protocol along with the IPM 
Company President/CEO and/or operations manager, whichever is most appropriate. 
Overview: Each IPM Module will include two school visits. The first visit of each module will be conducted by a Research 
Assistant (RA) and an IPM technician (IT) from Buono Pest. The two IPM visits will be 4±3 weeks apart for the initial 
module that is delivered after randomization. Subsequent IPM modules will occur if there is evidence of infestation or 
report of infestation at the follow up school assessment visits, and will consist of two IPM visits that will be 4±3 weeks 
apart.  The control group will receive one IPM intervention visit.  IPM is further described in the study procedures section 
8 after completion of the study. 
6.2. Assessment of Participant Compliance with Investigational Agent 
Not Applicable (Environmental Intervention)  
6.3. Toxicity Prevention and Management 
Not Applicable (Environmental Intervention)  

 
Confidential 
Page 29 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
6.4. Premature Discontinuation of Investigational Agent 
Not Applicable (Environmental Intervention)  
7. Other Medications 
7.1. Concomitant Medications 
7.1.1. Protocol-mandated 
Not Applicable(Environmental Intervention) 
7.1.2.  Other permitted concomitant medications 
Medications and/or procedures prescribed by the participant’s health care provider or initiated and obtained by the 
participant’s parent/guardian are permitted. 
7.2. Prophylactic Medications 
Not Applicable 
7.3. Prohibited Medications 
Taking a beta-blocker 
Currently receiving escalation (has not reached maintenance) of Immunotherapy (allergy shots) 
Antihistamines will be discontinued for 3-5 days prior to the screening clinic visit for skin testing. 
7.4. Rescue Medications  
 Not Applicable.  
8. Study Procedures 
Clinical and Environmental Evaluations will occur during five types of study events: clinic visits, telephone 
questionnaires, school/home assessment visits, home assessment visits, and school subject follow-up visit.  
8.1. Enrollment 
We will utilize the same successful recruitment/enrollment strategy that we have been implementing in SICAS 1. 
We will use, as we have done successfully in SICAS-1, validated screening surveys89( collected under a screening survey 
protocol) that were  distributed to 8-10 elementary schools to be filled out by students and teachers. From SICAS-1, we 
have averaged 1000 to 1500 surveys returned each spring.  
Potential study participants will be screened over the telephone and those who meet study criteria and fulfill 
inclusion/exclusion criteria by an eligibility screening form will be explained about the study and invited to be scheduled 
for a baseline enrollment study visit in the clinic. 
  
8.2 Screening Visit 

 
Confidential 
Page 30 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
This visit will take place at the  Children’s Hospital Asthma Clinical Research Center (ACRC) in order to confirm eligibility 
and phenotypically characterized participants’ asthma before randomization at the start of the school year. The 
procedures performed will be:  
 
Informed Consent: The research study will be explained in lay terms to each potential research participant. The 
participant’s parent/guardian will sign an informed consent form and the participant will sign an assent form 
before undergoing any study procedures. Once the informed consent and assent have been signed, the 
participant is considered enrolled in the study and will be assigned a unique participant number. 
 
Questionnaires - assess clinical characteristics (asthma symptoms, health care utilization, home characteristics); 
 
Anthropometric Measurements: Height, weight and waist will be taken.  
 
Oximetry: The saturation of oxygen will be obtained by placing an electric device in the finger. 
 
CO oximetry : The percentage carbon monoxide in the blood will be assessed by placing a small device in one of 
the fingers. 
 
Skin testing: Allergy skin testing will be performed to 14 allergens, using the MultiTest II device (Lincoln 
Diagnostics, Decatur, IL). The allergen extracts to be used are: Timothy grass, Penicillium, German Roach, Oak 
tree pollen, Dog, Cat, Mouse epithelia, Rat epithelia, Dermatophagoides farinae, Dermatophagoides 
pteronyssinus Der p, Aspergillus mix, Alternaria tenuis, Cladosporium, Ragweed pollen mix . Skin tests will be 
performed according to standard procedures90 
 
Fractional Exhaled NO (FeNO): F eNO is a known marker of pulmonary inflammation and will provide a non-
invasive means of assessing pulmonary inflammation.. Measurement of exhaled nitric oxide will be obtained prior 
to lung function testing, and will be obtained according to the American Thoracic Society Guidelines91. Exhaled 
nitric oxide concentrations will be measured using an FDA-approved (for clinical use in asthma management) 
handheld device that uses electrochemical technology to quantify FeNO levels (NIOX Mino/NIOX Vero System, 
Aerocrine, Sweden). . 
 Spirometry and Bronchodilator reversibility: Pre- and post-bronchodilator spirometry will be performed 
according to ATS guidelines92. At least three reproducible flow-volume loops will be obtained using the portable 
Koko spirometer, after which albuterol will be administered via nebulizer. Approximately 10-15 minutes after 
completing the nebulized albuterol, spirometry will be repeated to obtain post-bronchodilator FVC, FEV1, FEF25-
75, and PEF.  
 Nasal swab/blow: This will be obtained by swabbing the nares to clean and blowing into a nasal sample kit to be 
frozen and saved for future analysis of viral and microbial organisms that could affect clinical response to the 
intervention. 
 Skin swab:  This will be obtained by swabbing the crease behind the ear with a damp swab. This sample will be 
frozen and saved for future analysis of viral and microbial organisms that could affect clinical response to the 
intervention. 
 Nasorption: This will be obtained by placing a small piece of absorbent paper in one of the nares of the child’s 
nose and staff will hold that side close for a few seconds. These samples will be stored and may be used for 
future understanding of inflammatory markers linked with asthma or environmental changes 

 
Confidential 
Page 31 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
 
Nasal brushing (optional):  Only children who have agreed to this procedure We will collect nasal epithelial cells 
from behind the inferior turbinate. The procedure will be done in kids 10 and older using a cytology brush under 
direct visualization with  a nasal illuminator. This procedure will be done one time before the start of school and 
one time before the child finishes the school year. The procedure will only be done in the hospital clinic.  The 
collected brush will be submerged in RLT Plus lysis buffer plus b-mercaptoethanol and frozen at -80 degrees C 
until extraction. Samples will be stored at Baccarelli’s Laboratory. 
 
Venipuncture A 35 ml venous blood sample will be obtained so that the serum can be used to measure total IgE 
and allergen-specific IgE levels. Cell count with differential to obtain eosinophils will also be obtained. The 
leftover serum and plasma will be frozen at Biocore (BCH)for future research use. 
Urine Collection: A sample of 25 ml of urine will be collected and Nic-Alert/cotinine and specific gravity measure 
done.  An aliquot of urine from the screening visit will be saved for measurement of F-isoprostane, pesticides and 
other inflammatory markers.  Additional aliquots will be saved and frozen  in the biorepository for future use. 
 
Saliva: This sample will be used to measure cortisol levels as a marker for stress. Children will chew on parafilm 
paper for up to 15 minutes or until 6-10ml of saliva are collected. The sample will be aliquoted. They will be sent 
to be frozen and stored  in the biorepository for future use should funding become available. 
 
Buccal Swabs(optional): This sample will be collected to look into DNA/RNA epigenetic changes due to 
environmental exposure. We will use a cytology brush (6 brushes) to get the sample from the inside of the 
cheeks and lips. This sample will be frozen and saved in the biorepository for future use should funding become 
available.   
 
Sleep monitor (optional):  There are 3 parts of this evaluation. 
a)  Evaluation of sleep disordered breathing: The subject will wear a home sleep testing device that is  
FDA approved to safely monitor sleep in children down to age 2. There are three sensors 1) a pneumatic 
sensor attached to a Velcro belt measures respiratory effort. 2) a nasal cannula records airflow and 
snoring and 3) a pulse oximeter measures pulse and  oxygen saturation. The device will be worn for 2 
nights, only while subject is asleep.  
b) Evaluation of sleep habits and quality:  The wrist actigraph is worn like a wrist watch and records 
movements during day and night.  The wrist actigraph will be worn for a total of 7 days (+/-2). A 
sleep diary will be completed while the subject wears the actigraph. 
c) Home noise evaluation: To measure the noise inside and outside the home, we will ask the 
participant to place a sound meter. This is a machine that will be placed in the child’s bedroom and 
will record the amount of noise in this space 
 
If a subject cannot complete all activities at one screening visit, he/she may return within a week to complete the 
remainder of study activities. 
 8.3 Home Environmental Assessment: This assessment will done once at any point throughout the subject’s 
participation in the study.  Dust sampling collection from the participant’s bedroom and kitchen.   Home samples will be 
linked to school/class sampling as a surrogate measure for home exposure and for adjusted analyses. Home 

 
Confidential 
Page 32 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
environmental assessments will also be done to differentiate the effect of home exposure in adjusted analyses with the 
primary focus of this study on the school/classroom specific exposure and clinical outcomes. 
8.4 Randomization.   The DCC Data Management System will randomize the classroom to receive active versus sham 
(placebo) air purifiers and the school to receive the IPM intervention.  Randomization will occur by site and with random 
blocks. The randomization scheme will be developed by the Data Coordinating Center (DCC) and embedded into the data 
management system so that schools and classrooms can be randomized, linked to enrolled SICAS-2 students. Study staff 
will not have access to the randomization codes. 
 
8.5 Integrated Pest Management (IPM)  
Intervention includes IPM Module of two IPM visits, conducted 4 ±3 weeks apart. 
IPM Intervention Visit 1: If the School has been randomized to the IPM School, the study coordinator will schedule an 
IPM visit in the fall after the baseline school sampling.  The IPM intervention team will include the Research Assistants (RA) 
and IPM Technicians (IT). The Classroom/School Inspection Form(s) will be used to document a walk through the school in 
order to sketch a layout and document visual evidence of infestation and holes/cracks in the structure. IPM procedures 
will include placement of traps,  sealing of holes and cracks as specified in the MOP. 
Our school-based work will focus on the primary exposure school room of interest, the child’s primary home classroom , 
which is where we focused in our observational findings that provided supporting data for this study.  We 1) inspect 
conditions, record observations, 2) Identify pests, 3) continue follow up and adjust as needed, 4) record observations 
and activities, 5) educate staff.  Focusing on the classroom/cafeteria will also allow us to isolate and control conditions 
focused where the child spends the majority of his/her time.  We will also clean and target IPM on the heating system of 
the classroom, and evaluate nearby surrounding areas, including cafeteria, and any nearby support areas if they directly 
feed into the classroom such as storage rooms, boiler rooms, janitor/storage closets if they have evidence of mouse 
infestation.     
IPM Intervention Visit 2: The second visit of the IPM module will serve as a booster visit and will include an assessment 
of the status of the mouse infestation and repeat setting of traps, , and sealing of holes and cracks. 
Additional IPM Intervention Visits: Subsequent IPM modules will be delivered only if there is persistent or recurrent 
mouse infestation so that IPM will be tailored to the infestation status of the school.  Mouse infestation will be assessed 
at the follow up school visits and a school will be considered to have ongoing or recurrent mouse infestation if there is 
evidence of mouse infestation during inspection or if staff reports seeing mice, or evidence of mice, during subsequent 
sampling.   
IPM Accountability: Several procedures will be in place to ensure adherence to the protocol, including timely and 
appropriate delivery of IPM services. These procedures include: 
1. IPM technicians will undergo training and certification prior to enrollment. The training and certification will be led by 
Certified Pest Management QI . 
2.  IPM technicians will be required to complete all study forms and document procedures; forms will be reviewed by the 
Study Coordinator and 10% will be reviewed by Pest Management Specialist annually 
4.  Annual site visits will be conducted by Pest Management Quality Control Specialist to observe at least 1 IPM visit to 
the schools. 

 
Confidential 
Page 33 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
5.  IPM Company President or Operations Manager will participate in regular conference calls to ensure timely 
communication of any protocol deviations or issues that need to be addressed. 
6. For IPM visits, the visits and dates of the visits will be documented. In addition, the IPM Technician(s) will document 
the number of traps placed. 
 
8.6 School Environmental Assessment: Participating schools for the Academic Year will be scheduled for a baseline 
school visit to determine allergen/mold/particulate exposure status in the fall prior to deploying the randomized 
intervention. At the school visit, a school environmental assessment will be conducted, and settled dust and table wipes 
will be collected from SICAS-2 student’s home classroom, cafeteria , and gym,  The air samples will be collected from the 
student’s home classroom to have a baseline determination of airborne dust. School environmental assessment includes 
the following procedures:  
Completion of School Assessment/Inspection Form 
 
Collection of settled dust from cafeteria, primary home classroom and gym. 
 
Air pollution, air and mold samples will be collected from the primary home classroom. 
 
The dust and air samples from home and school will be shipped to Indoor Biotechnologies for allergen (dust mite, mouse, 
rat, cockroach, cat, dog, alternaria, milk, peanut, egg)/endotoxin analysis. The mold samples will be analyzed at the 
University of Massachusetts, Amherst. Particulate Pollutant monitoring samples will be done at HSPH . 
 
A return school visit will occur approximately one week after the first school visit to collect the air sampling equipment and 
samples. Follow-up school environmental assessments will take place once during the fall school semester and one 
during the spring school semester. 
 
8.7 Phone call surveys: These will be performed in order to collect health outcomes (e.g., symptoms, health care use; 
time-activity) and home environmental information. They will be conducted  after the start of the school year 
(baseline), and every 2 months after  the intervention is deployed, yielding 4 follow-up measures during the school 
year, including  1 at the end of the school year.  
8.8 School Subject Follow-up visit:  By the same standard procedures performed at the screening visit, we will obtain 
anthropometric measurements (height and weight), Co-oximetry measurement, spirometry, FeNO,  at the fall and 
spring follow-up visits.  Nasal swab/blow, skin swab, nasorption and buccal swabs will only be performed during the 
spring follow-up visit.  Follow-up clinical assessments will be linked in timing to the environmental sampling done 
during the academic year, post randomization. Not only will the timing of the assessments enable us to evaluate the 
effects of the interventions on these outcomes (lung function, FeNO,) partway through and near the end of the 
intervention periods.  This timing will also enable us to do secondary analyses on the relation of these outcomes to 
short-term measured school exposures in the different treatment arms. 
These school environmental and clinical measures will enable us to: (1) estimate the efficacy of the interventions in 
opposite seasons and (2) conduct secondary analyses linking season-specific health outcomes with exposure 
measures rather than treatment group. 
8.9 Focused Cleaning: 

 
Confidential 
Page 34 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
At the firs visit of the first IPM module, the research assistant will complete a focused cleaning aimed at (1) removing 
allergen reservoirs; and (2) removing clutter to aid the IPM technician. Procedures will include removal of dead mice 
from traps, removal of trash and clutter, removal of mouse droppings, wet mopping of floors with hard surfaces and 
vacuuming carpeted floors with HEPA filtered vacuum cleaner. Our methods are modeled off of successful  intervention 
work in homes18  which led to  our NIAID funded Home based study (Mouse Allergen Asthma Intervention Trial 
U01AI083238), and which utilizes successful strategies targeted to the bedroom, inspection targeted in surrounding 
areas, and kitchen.  Our school-based study will focus on the primary exposure school room of interest, the child’s 
classroom, surrounding support areas, and the cafeteria.   
8.10 Education: 
An educational module will be delivered to IPM Schools. The Education SOP which can be found in the MOP details the 
information to be covered and the Education Form will serve as documentation of delivery of the Education Module.  
The module will review the approaches to reducing mouse allergen levels – source removal, prevention of re-entry, and 
cleaning of allergen reservoirs with school staff. 
8.11 HEPA Air Filter Accountability 
According to the manufacturer, the portable air filter units have a particle collection efficiency of 99.9% for particles as 
small as 0.3 microns. All filters will be replaced at each school visit, every 3 months, as recommended by the 
manufacturer’s instructions. 
 
For the Classroom Air Filters, a research assistant will assess the units at the school visits to document functionality and 
whether the unit is on and plugged in at the time of the school visit. Reminders are taped on the units to encourage 
compliance.  If the units are turned off or plugged in , staff will communicate with the school contacts to encourage 
compliance. 
8 . 1 2 Unscheduled Visits  
There will not be unscheduled visits since the study will not be managing the study participant’s asthma. Instead, 
documentation of the study participant’s primary care provider will occur at the screening clinic visit and participants who 
do not identify a primary care provider will be referred to one. A participant who contacts study staff with acute health 
concerns will be referred to his/her primary care provider or the Emergency Department, depending on nursing or 
physician judgment. 
8.13 Laboratory Reference Ranges: We will use age and sex specific published standard reference ranges for all clinical 
labs to define out of range safety lab values in the clinical database. Laboratory results will also be reviewed by the PI or 
her physician investigator designee as they become available to follow-up promptly with the family regarding any 
abnormal results that require medical intervention. The original lab results reports for each participant will be signed 
and data to verify they have been reviewed and action taken where appropriate. 
Schedule of Events:   

 
Confidential 
Page 35 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
Table 2 Surveys
 
      
 
Table 3 Clinical Procedures 
Screening 
(Jun-Sep) 
Randomizat
ion 
School 
Follow-Up 1 
(Dec-Feb) 
School 
Follow-Up 2 
(Mar-Jun) 
Participant Baseline Visit Data and Sample Collection 
 
CBC/Allergen specific IgE 
 
Serum, plasma, urine and saliva for storage 
 
Nasal swab and blow 
 
Skin swab 
 
nasoprtion 
 
Buccal Swab (optional) 
 
Height, Weight, Heart rate, Pulse Oximetry 
 
Skin Allergy Test 
X 
 
 
 

 
Confidential 
Page 36 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
 
Pre/Post Albuterol Spirometry 
 
Nasal Brush (optional) 
Participant Follow-up Visit Data Collection 
 
Spirometry 
 
FeNO 
 
CO-oximetry 
X 
 
X 
X 
Participant Follow-up Visit Sample Collection at School 
 
Nasal Swab and Blow 
 
Buccal Swab 
 
Skin swab 
 
nasorption 
 
 
 
X 
Participant Follow-up Clinic Visit Sample Collection 
 
Nasal Brush (optional) done in clinic  only 
 
 
<---------- 
----------- > 
  
 
 
 
 

 
Confidential 
Page 37 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
      Table 4: Environmental Measures and Forms (School, Classroom, and Home) 
Measure 
Baseline  
(Oct-Nov) 
Randomiza
tion
Follow-Up 1 
(Dec-Feb)  
Follow-Up 2 
(Mar-Jun) 
School Contact and Demographics Form 
X 
 
 
 
School/Classroom Evaluation  
X 
 
X 
X 
School Environmental Samples 
X 
 
X 
X 
Home Environmental Samples- Vacuum Dust** 
<----------- 
 
-------------- 
----------- > 
**One home dust sample is taken at any time during the year as a surrogate measure for home exposure 
 
9. Mechanistic Assays 
Rationale: 
 Mechanistic Background Data Methylation and gene expression to environmental responses Epithelial cells (ECs)93, 94 
provide the front-line physical, immune, and chemical barrier to the allergen and irritant exposures that we will reduce82, 
89. Pattern recognition receptors (PRRs: TLRs, NOD-like receptors, C-type lectins; protease-activated receptors) on ECs 
recognize proteolytic allergens and allergen-associated microbial contaminants, with EC release of innate cytokines (e.g., 
TSLP,CM-CSF, IL-25, IL-33) that can activate dendritic cells and increase Th2 cytokine expression, or activate basophils, 
mast cells and eosinophils involved in allergic/asthmatic responses. Altered EC barrier function with tight-junction 
disruption is linked to poor ciliary clearance or increased mucous production in asthma. EC innate96,97, barrier, and repair 
function may be dysregulated by particle pollution components as well as cigarette smoke98. 
 
Gene expression is regulated in part by upstream epigenetic programming (e.g., by DNA methylation, as well as 
by a coordinated suite of less accessible epigenetic marks acting in synergy with DNA methylation). Both can be 
influenced by environmental exposures,99-103 as well as by genetics.  We have shown that within-person methylation of 
PRRs (TLR4) is decreased with particle pollution exposure104. We found higher airway inflammation (FENO) was 
associated with methylation of the innate pro-inflammatory cytokine IL-6 (29.0%; p=0.004) and iNOS in asthmatic 
children79. While epigenetic silencing of some genes may be established in utero, we have demonstrated plasticity in 
methylation of other genes, with changes that begin with short-term exposures and become greater with cumulative 
exposure over months105-113. 
 
  
 
I Mechanistic Assays: This would be the first trial assessing how school-based interventions (integrated pest 
management and/or reduction in classroom particles levels) influence changes in methylation and downstream gene 
expression pathways or networks of genes that, in turn, have relevance to reduction of asthma morbidity and 
improvement in the natural course of the disease. Application of bioinformatic techniques will enable us to discover pre-
specified as well as novel pathways of genes that respond to our intervention with changes in methylation and/or 

 
Confidential 
Page 38 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
changes in gene expression relevant to prevention of asthma morbidity. Thus ascertainment of the benefits of our 
environmental intervention at the molecular level will help to identify novel pathways to target in pharmacologic therapy 
for children with asthma, and to explore whether pathway responses vary by asthma phenotype or by baseline gene 
expression and methylation.  Furthermore, our study has clinical applicability, yielding measures with direct relation to 
airway biomarkers83, 114, utilizing samples that can be obtained from children non-invasively, rather than by more 
invasive procedures like lung biopsy. 
 
Health Outcomes from Students in Entire Classrooms (Exploratory):  
Secondarily, depending on scheduling with the school, we will redistribute  surveys to entire classrooms of the same 
classrooms/schools that we are collecting environmental dust/air sampling data during the academic year. This will 
allow us to have a one follow up measure of health outcomes form the entire classrooms, linked to the environmental 
sampling.  This will provide us with symptoms (including nasal) from the students without asthma that are enrolled in 
the study.  
This allows to efficiently obtain health outcome data of our intervention in entire classrooms of these students.  In 
SICAS-1, most of classrooms of students in our study had at most 2-3 students in a classroom of 20 students. Although 
these outcomes are not the primary specific aims of SICAS-2, this will allow us to assess preliminary respiratory and nasal 
symptoms from entire schools, linked to our intervention and preliminarily determine the intervention on 10-20 times 
the number of enrolled SICAS-2 students with asthma or 3000-6000 students, and greatly leverage the wealth of 
information on determining the effectiveness of our intervention in a community of students.  
10. Biospecimen Storage 
Serum, plasma, saliva, urine and buccal brushes, nasal swab and blow samples will be stored using unique identifiers. 
These samples will be stored at BIOCORE part of Children’s Hospital for possible future use.  Samples will be saved for 
future analyses such as immune markers such as pro-inflammatory cytokines such as IL-6, IL-33, leptin, basophils, TNF α, 
IFN-γ and other cytokines, stress markers such as salivary cortisol and  α-amylase, serum gender specific hormones (i.e. 
E2,DHEAS,testosterone, SHBG, Progesterone) urinary metabolomics, proteomics, urinary chemicals ( BP-3, BPA, 
Butylparaben, Ethylparaben, Methylparaben, Propylparaben, Triclosan, 2,4-dichlorophenol and 2,5-dichlorophenol, 
ispoprotenes, pesticides, benzenes, leukotrienes, and creatinine), and buccal brushes saved for epigenetics/RNA gene 
expression, and nasal swab/blow samples saved for viral, microbial, and bacterial organism analysis, which may help us 
further our understanding of mechanisms behind the interventions, pending future funding 
 
11. Criteria for Participant and Study Completion and Premature Study Termination 
11.1. Participant Completion 
Subject who has completed summer baseline clinical and clinical follow up through the entire subsequent academic 
school year has completed the study as long as they remain in the school classroom where the intervention and 

 
Confidential 
Page 39 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
environmental sampling is also done subsequently. Required milestones include minimum clinical baseline evaluation 
and clinical outcomes post randomization of intervention linked to classroom exposure sampling.  
11.2. Participant Stopping Rules and Withdrawal Criteria 
Participants may be prematurely terminated from the study for the following reasons: 
1. Voluntary withdrawal by the study participant may occur at any point during the course of the study. Every effort 
will be made to collect clinical and AE data via telephone. 
2. The participant is “lost to follow-up” (i.e., no further follow-up is possible because attempts to reestablish 
contact with the participant have failed).  After up to 10 attempts at follow-up by through varying methods, 
phone, email, letters139, which is the commonly required for follow up in this population to maintain retentions, 
we will assume patient is lost to follow up.    
3. The participant dies.  
4. A study participant will be discontinued from further study intervention if any clinical adverse event, other 
medical condition or situation occurs such that continued participation in the study would not be in the best 
interest of the participant. This includes an asthma hospitalization that results in intubation. 
5. The intervention is determined to be too disruptive in the classroom or school and the school or classroom staff 
request withdrawal from the study. 
11.3. Participant Replacement 
Study participants who have completed one follow up clinical visit after the school/classroom has been randomized to 
the environmental intervention will not be replaced. Participants who withdraw or are withdrawn will not be replaced. 
11.4. Follow-up after Early Study Withdrawal 
Voluntary withdrawal by the study participant may occur at any point during the course of the study. Every effort will be 
made to collect clinical and AE data via telephone. 
 
11.5.  Study Stopping Rules 
Given the nature of this intervention and the enrollment schedule, we will not have a priori study stopping rules for 
early efficacy or futility.  If we learn of new information that would make the intervention unsafe (unlikely in an 
environmental intervention study, but i.e. a severe adverse event directly related to the intervention), that could also 
warrant stopping the study if determined necessary by the DSMB.   
12. Overview 
 
This section defines the types of safety data that will be collected under this protocol and outlines the procedures for 
appropriately collecting, grading, recording, and reporting those data. Adverse events that are classified as serious 
according to the definition of health authorities must be reported promptly (per Section 12.5, Reporting of Serious 
Adverse Events and Adverse Events) to the sponsor DAIT/NIAID.  Appropriate notifications will also be made to site PI, 
Institutional Review Boards (IRBs), and health authorities.  
Information in this section complies with ICH Guideline E2A: Clinical Safety Data Management: Definitions and Standards 
for Expedited Reporting, ICH Guideline E-6: Guideline for Good Clinical Practice, 21CFR Parts 312 and 320, and applies 

 
Confidential 
Page 40 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
the standards set forth in the National Cancer Institute (NCI), Common Terminology Criteria for Adverse Events (CTCAE), 
Version [enter 4.0 or correct version applicable to trial] : http://ctep.cancer.gov/reporting/ctc.html. 
12.1 Definitions 
12.1.1 Serious Adverse Event (SAE) 
An adverse event or suspected adverse reaction is considered “serious” if, in the view of either the investigator 
or Sponsor( DAIT/NIAID), it results in any of the following outcomes (21 CFR 312.32(a)): 
1. Death. 
2. A life-threatening event: An AE or SAR is considered “life-threatening” if, in the view of either the 
investigator or Sponsor( DAIT/NIAID), its occurrence places the subject at immediate risk of death. It does 
not include an AE or SAR that, had it occurred in a more severe form, might have caused death.  
3. Inpatient hospitalization or prolongation of existing hospitalization. 
4. Persistent or significant incapacity or substantial disruption of the ability to conduct normal life functions. 
5. Congenital anomaly or birth defect.  
6. Important medical events that may not result in death, be life threatening, or require hospitalization may be 
considered serious when, based upon appropriate medical judgment, they may jeopardize the subject and 
may require medical or surgical intervention to prevent one of the outcomes listed above. 
Asthma hospitalizations not related to study procedures will not be considered SAEs and will be entered on the 
appropriate Case Report Forms. 
 
12.1.2 Adverse Event (AE) 
Any untoward or unfavorable medical occurrence associated with the subject’s participation in the research, whether or 
not considered related to the subject’s participation in the research (modified from the definition of adverse events in 
the 1996 International Conference on Harmonization E-6 Guidelines for Good Clinical Practice) (from OHRP "Guidance 
on Reviewing and Reporting Unanticipated Problems Involving Risks to Subjects or Others and Adverse Events 
(1/15/07)" http://www.hhs.gov/ohrp/policy/advevntguid.html#Q2 )  
For this study, recorded and reported as an adverse events are limited to 1.) any occurrence or worsening of an 
undesirable or unintended sign (including an abnormal laboratory finding), symptom, or disease in a study subject that is 
specifically associated (possible, or definite – defined in section 10.2.2.) with a study procedure; 2) Asthma 
exacerbations that require hospitalization and are determined to be related to study procedures will be considered a 
SAE and 3) SAEs which are not asthma exacerbations..  
Study therapy regimen:  Environmental Intervention, generally not applicable. No treatment given as part of this study.  
 
Study mandated procedures:  blood draw, nasal sample, skin swab, nasorption and lung function test.  
For the procedures below, clinical situations are listed that are considered to be outside the 
normal range of outcomes and will be recorded as Adverse Events.  These situations do not 
limit an investigator from recording and reporting any other events, associated or not with 
these procedures as AEs.    

 
Confidential 
Page 41 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
Allergen Skin Testing 
 
Prolonged (>24 hours) itching at test site 
 
Swelling (> 10 cm ) at site of test lasting more than 24 hours 
 
Nasal allergic symptoms within 30 minutes from the procedure 
 
Fainting /Vasovagal event within 30 minutes from the procedure 
 
Blood Draw 
 
Fainting/Vasovagal events 
 
Bruising at puncture site larger than 2 cm diameter 
 
Bleeding from puncture site lasting more than 30 minutes 
 
Swelling at puncture site larger than 2 cm 
 
Pulmonary Function Testing  
 
Wheezing or bronchoconstriction requiring treatment with bronchodilators within 30 minutes from 
the procedure 
 
Coughing requiring treatment with bronchodilators within 30 minutes from the procedure 
 
Nasal Epithelial Cell Collection 
• Epistaxis within 24 hours after the procedure 
 
 
12.2.1.1 Suspected Adverse Reaction (SAR)  
N/A 
12.2.2 Unexpected Adverse Event  
Not Applicable.  
12.2.1 Grading Criteria 
The study site will grade the severity of adverse events experienced by the study subjects according to the 
criteria set forth in the National Cancer Institute’s Common Terminology Criteria for Adverse Events (CTCAE) 
version 4.0.  This document (referred to herein as the NCI-CTCAE manual) provides a common language to 
describe levels of severity, to analyze and interpret data, and to articulate the clinical significance of all adverse 
events. The NCI-CTCAE has been reviewed by the Principal Investigator and has been deemed appropriate for 
the subject population to be studied in this protocol.  
Adverse events will be graded on a scale from 1 to 5 according to the following standards in the NCI-CTCAE 
manual: 
Grade 1 = mild adverse event. 

 
Confidential 
Page 42 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
Grade 2 = moderate adverse event. 
Grade 3 = severe and undesirable adverse event. 
Grade 4 = life-threatening or disabling adverse event. 
Grade 5 = death. 
All AE’s related to study procedures will be recorded on the appropriate AE case report form  for this study. 
For grading an abnormal value or result of a clinical or laboratory evaluation (including, but not limited to, a 
radiograph, an ultrasound, an electrocardiogram etc.), a treatment-emergent adverse event is defined as an 
increase in grade from baseline or from the last post-baseline value that doesn’t meet grading criteria. Changes 
in grade from screening to baseline will also be recorded as adverse events, but are not treatment-emergent. If 
a specific event or result from a given clinical or laboratory evaluation is not included in the NCI-CTCAE manual, 
then an abnormal result would be considered an adverse event if changes in therapy or monitoring are 
implemented as a result of the event/result. 
12.2.2 Attribution Definitions 
The relationship, or attribution, of an adverse event to the  study procedure(s) will initially be determined by the 
site investigator and recorded on the appropriate AE case report form AE/SAE paper CRF.  Final determination of 
attribution for safety reporting will be determined by DAIT/NIAID Medical Monitor (MM).  The relationship of an 
adverse event to study therapy regimen or procedures will be determined using the descriptors and definitions 
provided in Table 12.2.2.  
For additional information and a printable version of the NCI-CTCAE manual, consult the NCI-CTCAE web site: 
http://ctep.cancer.gov/reporting/ctc.html 
 
       
Table 12.2.2 Attribution of Adverse Events 
Code 
Descriptor 
Relationship (to study procedure) 
UNRELATED CATEGORY 
1 
Unrelated 
There is insufficient evidence to suggest a causal 
relationship 
 RELATED CATEGORIES 
2 
Possible 
The adverse event has a reasonable possibility to be 
related; there is evidence to suggest a causal 
relationship. 
3 
Definite 
The adverse event is clearly related. 
 
12.4 Collection and Recording of Adverse Events 
12.4.1 Collection Period 

 
Confidential 
Page 43 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
Adverse events will be collected from the time of enrollment until a subject completes study participation or 
until 30 days after he/she prematurely withdraws (without withdrawing consent) or is withdrawn from the 
study. 
12.4.2 Collecting Adverse Events 
Adverse events (including SAEs) may be discovered through any of these methods: 
• 
Observing the subject. 
• 
Interviewing the subject [e.g., using a checklist, structured questioning, diary, etc.]  . 
• 
Receiving an unsolicited complaint from the subject. 
• 
In addition, an abnormal value or result from a clinical or laboratory evaluation can also indicate an adverse 
event, as defined in Section 12.2, Grading and Attribution of Adverse Events. 
12.4.3 Recording Adverse Events 
Throughout the study, the investigator will record adverse events and serious adverse events as described 
previously (Section 12.2, Definitions) on the appropriate case report form AE/SAE paper CRF regardless of the 
relationship to study therapy regimen or study procedure. 
Once recorded, an AE/SAE will be followed until it resolves with or without sequelae, or until the end of study 
participation, or until 30 days after the subject prematurely withdraws (without withdrawing consent)/or is 
withdrawn from the study, whichever occurs first. 
12.5 Reporting of Serious Adverse Events and Adverse Events 
12.5.1 Reporting of Serious Adverse Events to Sponsor (DAIT/NIAID) 
This section describes the responsibilities of the site investigator to report serious adverse events to the sponsor 
(DAIT/NIAID) via (Case Report Form, facsimile,  hotline-mail).   Timely reporting of adverse events is required by 
21 CFR and ICH E6 guidelines.  
Site investigators will report to the NIAID Medical Monitor  all serious adverse events (see Section 12.1.3, 
Serious Adverse Event), regardless of relationship or expectedness within 24 hours of discovering the event.  
Contact information for NIAID Medical Monitor: 
PETER GERGEN, MD, MPH 
Division of Allergy, Immunology, and Transplantation – NIAID/NIH 
5601 Fishers Lane 
Bethesda, MD 20892-9828, USA 
Phone:  240-627-3545 
Fax:  301-480-4258 
E-mail:  pgergen@niaid.nih.gov] 
For serious adverse events, all requested information on the AE/SAE Case Report Form will be provided.  
However, unavailable details of the event will not delay submission of the known information.  As additional 
details become available, the AE/SAE case report form will be updated and submitted. 

 
Confidential 
Page 44 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
12.5.1.1 Reporting of Unexpected Non-Serious Adverse Events 
Any non-serious adverse event that is of Grade 2 severity or higher and study related will be recorded 
and reported to the NIAID Medical Monitor under the serious adverse event reporting procedure above 
(i.e. within 24 hours).     
12.5.2 Reporting to Health Authority 
Not Applicable 
12.5.3 Reporting of Adverse Events to IRBs 
All investigators shall report adverse events, including expedited reports, in a timely fashion to their 
respective IRBs/IECs in accordance with applicable regulations and guidelines.  
12.7 Reporting of Unanticipated Safety Information 
An investigator shall promptly notify the site  IRB as well as the DAIT/Medical Monitor and Data Management 
and Analysis Core when an “unanticipated problem involving risks to subjects or others” is identified, which is 
not otherwise reportable as an adverse event. 
12.8 Review of Safety Information 
12.8.1 Medical Monitor Review 
The NIAID Medical Monitor shall receive quarterly reports from the PI/Protocol Chair compiling new and 
accumulating information on AEs and , SAEsrecorded by the study site on appropriate case report forms. 
In addition, the NIAID Medical Monitor shall review and make decisions on the disposition of the SAE received 
by the PI and Data Management and Analysis Core (See Sections 12.5.1, Reporting of Serious Adverse Events to 
Sponsor (DAIT/NIAID)).   
12.8.2  Data and Safety Monitoring Board(DDSMB) Review  
12.8.2.1 Planned Data and Safety Monitoring Reviews  
The Data and Safety Monitoring Board (DSMB) shall review safety data at least yearly during planned 
DSMB Data Review Meetings. Data for the planned safety reviews will include, at a minimum, a listing of 
all reported AEs and SAEs.   
12.8.2.2 Ad hoc DSMB Reviews  
In addition to the pre-scheduled data reviews and planned safety monitoring, the DSMB may be called 
upon for ad hoc reviews. The DSMB will review any event that potentially impacts safety at the request 
of the Protocol Chair or the NIAID Medical Monitor. In addition, the following events will trigger an ad 
hoc comprehensive DSMB Safety Review:  
o 
Any death that occurs in the study, which is possibly or definitely related to study treatment 
regimen. 
o 
The occurrence of a Grade 3 or higher related and unexpected SAE in 3or more of the study 
participants who have received a study treatment. 

 
Confidential 
Page 45 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
o 
After review of the data, the DSMB will make recommendations regarding study conduct and/or 
continuation. 
12.8.2.2.1 Temporary Suspension of enrollment for ad hoc DSMB Safety Review  
A temporary halt in enrollment will be implemented if an ad hoc DSMB safety review is 
required.   This is very unlikely in an environmental intervention, and study will proceed unless it 
is determined by DSMB that study must stop due to safety reasons. 
13. Statistical Considerations and Analytical Plan 
13.1 
Overview  
Note: SICAS-1 (School Inner-City Asthma Study) refers to observational R01 (AI 0739654, Phipatanakul), and SICAS-2 
(School Inner-City Asthma  Intervention Study) is the proposed clinical trial. 
The primary objective of SICAS-2 is to test the efficacy of School Integrated Pest Management (IPM) and Classroom Air 
Filters in reducing asthma morbidity in school children with asthma. Reducing school/classroom mouse, mold allergen and 
particulate pollutant exposure will be associated with improvement in asthma outcomes.   
Our mechanistic objective is to test the hypothesis that effects of school/classroom-based environmental interventions 
on symptoms/other measures of asthma control occur through changes in gene methylation or expression in pathways 
(and secondarily, in genes) relevant to airway function (Research Strategy Section 1.4) and asthma. 
13.2 
Outcomes (Described in 3.2-3.4) 
Primary Outcome(s) 
 
13.3 
Measures to Minimize Bias  
Randomization: Schools will be randomized to IPM vs no IPM, and within schools, participant classrooms will be randomized to HEPA filter vs 
Sham Air Cleaner within three weeks of the baseline school visit in a 1:1 ratio using a statistical software package to 
generate random numbers. The randomization scheme will be developed by the Data Management and Analysis Core 
(DMAC). Dr.   Stravoula Osganian, MD, MPH, DrPH and her team  will lead the DMAC  and assistance from Dr. Jonathan 
Bickel’s team from the Clinical Research Information Technology Team will provide support for database programming 
for the trial and program the forms for data capture using REDCap. Carter Perry, MA will provide the statistical 
programming.      
Maintenance of Trial Treatment Randomization Codes 
The randomization scheme will be embedded in the data tracking system and access to the scheme will be restricted to 
the DMAC database programmer. In addition, once a school or participant classroom has been randomized, the group 
assignment will be locked. The randomization codes may only be broken at the request of the Data Safety Monitoring 
Board (DSMB) and the minimum number of DMAC staff necessary will be unmasked in order to provide requested 
analyses to the DSMB. 

 
Confidential 
Page 46 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
 
Masking : The Air Filter Classroom Intervention involves double-blinding, with placebo controlled randomization. The 
Sham Air Cleaner is designed to emit the same quiet background sound as the HEPA filter Air Cleaner. Staff from the HSPH 
Environmental Assessment and Intervention Core who do not have contact with the study participants will service and 
change the air filters every 3 months at the school after school hours, ensuring participants, PI, and study staff are 
blinded to classroom intervention assignment.  
For IPM, the benefit of SICAS-2, compared to home-based interventions in which masking is impossible, is that it will be possible 
to single blind  and mask the School IPM procedures. Students will not know whether or not IPM is being applied at the 
school---IPM procedures are done after hours when the students are not in school. Although it may be possible to 
attempt to mask some study staff from knowledge of IPM treatment by increasing the number of research assistants at 
each site (so that 1-2 RAs who ascertained clinical outcomes would not be involved in tasks related to IPM) this would 
substantially increase the budget. Thus double-blinding for IPM is not feasible or practical even in a school based study.  
There are also several aspects of the study that will guard against bias that could result from having unmasked study staff. 
First, all laboratory assays will be conducted by laboratory technicians who will be masked to group assignments. Second, 
some of the clinical data that are collected, including exhaled nitric oxide and pre- and post- bronchodilator spirometry 
are objective measurements that are less subject to influence by the study staff or study participants. Third, secondary 
analyses will be conducted to determine if any improvements in clinical outcomes are associated specifically with 
decreases in school allergen, mold or other pollutant levels, not just with group assignment. 
While randomization should result in minimal differences between treatment groups in home allergen levels, we will 
measure home allergens levels and these measures will enable us to control for any residual confounding by home 
allergen level in analyses.  Home samples will be linked to participants as a surrogate measure for home exposure and 
for adjusted analyses. Home environmental assessments will also be done to differentiate the effect of home exposure 
in adjusted analyses with the primary focus of this study on the school/classroom specific exposure and clinical 
outcomes.   
All laboratory studies (allergen ELISAs, allergen-specific IgE levels, endotoxin levels, PM 2.5, Black Carbon levels, trace 
elements, NO2 levels, and mold) will be performed in centralized laboratories in batches to minimize variability of the 
assay. 
13.4 
Analysis Plan 
13.4.1 Analysis Populations. 
Analyses will be performed using an intent-to-treat (ITT) dataset which will include all participants who are randomized. 
Analyses will be performed using a per-protocol (PP) dataset and an intent-to-treat (ITT) dataset. The primary analysis 
will be an ITT analysis. After ensuring that any dropout is missing completely at random (see Missing Data Considerations below). 
The ITT dataset will include all participants who are randomized, and the per-protocol dataset will include only 
participants who have completed at least one intervention visit (one IPM/ Air Purifier visit) and one follow up clinical 
outcome visit. 
13.4.2 Primary Analysis of Primary Endpoint(s)   

 
Confidential 
Page 47 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
 
Multi-Level Modelling: 
We will employ multi-level models140 to quantify the effects of interventions (both class-specific filters and school-wide 
IPM) on the clinical outcomes, while accounting for the multiple levels (school, classroom, student, time point) of data.  
Specifically, we will employ non-linear mixed effects models, which intrinsically handle unbalanced data (unequal 
number of classrooms within schools and unequal number of children with asthma within classrooms) while accounting 
for child, class, and school-level variability (clustering) in the outcome by treating these factors as random effects.  
SICAS-1 generally had no more than one to two SICAS asthma students per classroom, so that clustering by classroom 
will be minimal and classroom random effects are likely not necessary. Count data (such as our primary symptom 
outcome) will be analyzed by negative binomial regression and continuous outcomes by linear mixed models.  Our 
primary analysis will contrast outcome levels in the intervention and control arms. For symptom-days, we will use the 
negative binomial regression:  
(Model 1): log E[Yijcs] = b0 + b1schs + b2clsc + b3schs * postj + b4clsc * postj + aTzij+ us + wics 
 
where Yijcs  is the number of symptom days for subject i in class c and school s on visit j, schsj is the indicator of IPM 
treatment for school s, clsc is the class-specific filter treatment for class c at visit j, postj is an indicator variable for post-
(versus pre-) randomization for a given visit, and zij is a vector of potential confounders, including seasonal influences 
captured by visit number (1-5), and, in the unlikely event that home exposures are not balanced across treatment arms, 
home exposures.Visit number is the visit (0,1,2,3,4) on which a given measurement was recorded (reflecting time of year 
at which measurement was taken), as opposed to post which is 0/1 representing pre/post.  In this model the main 
intervention effects (schs, clsc) represent differences at baseline and allow us to check for imbalance in the 
randomization. Post is 0/1 for pre/post regardless of the timing of the post visit. We include visit number as a covariate 
into the analysis to account for the timing of each observation. The terms us and  wics  represent school-specific and 
subject-specific random effects, respectively, to account for longitudinal correlation among measurements taken on the 
same subjects (wics) and among measurements taken on different subjects within the same school (us). As is traditional 
in non-linear mixed effects models, we will assume each set of random effects are normally distributed with unknown 
variance estimated from the data. We will use standard diagnostic methods to check this normality assumption, with 
some of these having been developed by our group.   In the likely event that there is balance in symptoms at baseline 
and the effects are absent, we can re-fit the model removing these main effects. The sch*post and cls*post terms are 
the terms of scientific interest and represent how post vs pre randomization changes in symptoms rates differ between 
intervention and control arms.   Because we include visit number as a main effect we do not need to include the main 
effect of post-randomization. We note that this model is standard for longitudinal pre-post randomization designs141. 
Again, we will add class-specific random effects if subjects are clustered significantly within classrooms within a school. 
For continuous outcomes such as lung function, we will fit analogous linear mixed effect models, which takes the form  
 
         (Model 2): Yijcs = b0 + b1schs + b2clsc + b3schs * postj + b4clsc * postj + aTzij+ us + wics+ eijcs, 
where the covariates are defined as above for the negative binomial model and eijcs are normally distributed errors.  
Extensions for secondary analyses (a)-(d) will be handled analogously to those for model (1) (Please see secondary 
analyses section). Standard diagnostics will be applied to detect non-normality of the errors, but experience suggests 
that this distributional assumption will be appropriate for lung function outcomes. Our primary analyses will entail fitting 
the models (1) and (2), with Zi  terms including visit number (as a categorical variable) and home exposures that 

 
Confidential 
Page 48 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
correspond with the same exposure in school (ie. classroom/school mouse exposure adjusting for home mouse 
exposure).  As written, these models will include the cls and sch intervention terms.  Secondary analyses will include (a) 
the effect of intervention varies by time of year(visit/survey 1-5) (b) exposure concentrations as predictors,(c) whether 
the effect of intervention or exposure concentration is modified by sensitization or other asthma phenotype at baseline, 
and (d) assess whether there is a synergistic effect of the classroom and school-wide interventions.  The terms  Zij will 
not include any post-baseline patient measurements that can be influenced by treatment assignment.  The terms to be 
include in this vector will include visit number as a categorical variable, and home exposures.  We will test b3 and b4 in 
separate hypothesis tests. 
 
Missing Data Considerations: 
Missing Data: Missed study visits and drop-outs will occur, and if these events occur completely at random or at random, 
then the use of multi-level models in the primary analyses will produce consistent estimates of the treatment effects and 
tests of these effects.   It will be extremely rare, if it happens at all, that we will have symptom data for a subject just at 
baseline with no post-baseline measures. The only time this would happen is if a subject moves to a non-participating 
school for that academic school year.  If this does occur we will first investigate whether dropout is associated with any 
covariates.  If it is, then to obtain valid inferences for the intervention, we will have to control for those covariates 
explaining the missingness (see Fitzmaurice, Laird, Ware, Chapter 17-18).  If it is completely at random (MCAR dropout), 
then it is acceptable to remove that subject from the analysis and only patients with some post-baseline symptom data 
will contribute to the primary analysis. As sensitivity analyses, we will conduct analyses using inverse probability 
weights, which effectively up-weights subjects that are more likely to dropout142.  We may also have missing covariates, 
as opposed to dropout.  The main tool for adjusting for missing covariate data will be multiple imputation methods, 
which can now be easily implemented in SAS (PROC MI and PROC MIANALYZE).  
Multiple Comparisons:  For symptoms, we have defined a single primary endpoint for analysis and no multiple 
comparisons adjustment will be made.  For the mechanistic component, we will run the analysis separately 
for each endpoint and each DNA methylation mediator and will adjust for multiple comparisons using False 
Discovery Rates148  
13.4.3 Supportive Analyses of the Primary Outcome  
The primary clinical outcome measure, maximum number of days of symptoms in the preceding two weeks, will be 
assessed in relation to classroom/school allergen/mold/particulate levels.  The primary analysis will be conducted using the 
values of the primary outcome at the 2, 4, 6, and 8 month follow-up surveys. The 10 month survey can be used in tertiary 
analyses to assess for carry-over effects.  
13.4.4 Analyses of Secondary and Other Endpoint(s)/Outcome(s) 
Secondary analyses will include (a) the effect of intervention varies by time of year (visit 1-5) (b) exposure 
concentrations as predictors, (c) whether the effect of intervention or exposure concentration is modified by 
sensitization or other asthma phenotype at baseline, (d) assess whether there is a synergistic effect of the classroom and 
school-wide interventions.  In (b), exposure concentrations will be matched to health outcomes according to the season 
in which a particular visit falls. Our preliminary data from SICAS-1 shows that any potential error induced by aligning 

 
Confidential 
Page 49 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
health and exposure data in this way will not materially diminish our ability to detect intervention effects, as SICAS-1 
analyses showed significant effects using this same design/plan.  Also, our preliminary intervention study demonstrated 
exposure reductions of ≥ 75%. This is greater than any seasonal variability demonstrated in classroom exposures in 
SICAS-19, 22, and will allow us to detect the effects of our intervention, regardless. For (c), we will add sensitization, 
sensitization*visit number, sensitization*clsc, and sensitization*schs   terms to the model. For (d), to models (1) and (2) 
we will add clsc * schs  and  clsc * schs * postj   interaction terms.  
Other factors that may modify the effect of the intervention on outcomes include level of mouse allergen exposure, 
number of other allergic sensitivities, ( i . e .  the combination of cat exposure+sensitization, and/or the combination of 
cockroach exposure+sensitization). Additional clinical characteristics that might affect responsiveness to the intervention 
include severity of asthma, lung function, and FeNO concentrations. Analyses will again include interaction terms in 
models to determine of any of these factors predict responsiveness to the intervention.  
In secondary analyses, we will adjust for factors that may affect responses to treatment such as the degree of exposure at 
baseline, the degree of sensitivity to mouse, number of other allergies, and asthma severity. Because hospitalizations, ED 
visits, unscheduled visits, and corticosteroid bursts are relatively infrequent events, we will assess the distribution of 
these variables and may decide to dichotomize the outcome as any vs. none and use logistic models. 
Other secondary clinical outcome variables that will be examined will include those listed above in Table 1. 
Other potential confounders will be explored by examining differences between the intervention and control groups and 
also assessing the association between the potential confounders at screening and at each study visit. In addition, 
potential confounders will be included in the models to determine the impact the variables have on the relationship 
between group assignment and the outcome. Some specific confounders that will be carefully examined include, 
cockroach sensitization and exposure (SICAS-1 had minimal to no cockroach exposure in schools and homes9), 
medication use, upper and lower respiratory infections, changes in exposure to other pollutants  and other allergens (note 
that cat and dogs as pets in schools are not allowed but exposure levels from home and school will be available), 
environmental tobacco smoke exposure (smoking in schools is banned), home exposures, and endotoxin levels, age, 
gender, race, household income, perceived stress29, body mass index144, and season. Effect modifiers, including the 
degree of allergen/pollutant reduction, will also be examined by creating an interaction term to include in the final 
models. 
 
Mechanistic Outcome Analysis: 
Mechanistic Analytical Plan: 
Pathway analysis: Analysis of the data from the mechanistic portion of the study will focus on pathway-specific effects 
of the intervention on genome-wide methylation and expression, and their downstream effects on asthma symptoms. 
Because we will have genome-wide methylation and mRNA expression data collected before and after the intervention, 
analyses will apply to post-pre differences in site-specific methylation and expression, and assess whether these 
differences relate to intervention group and asthma symptom. Within this design, in order to uncover pathways or 

 
Confidential 
Page 50 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
methylation/expression signatures associated with the intervention and asthma symptom reduction, we will perform (1) 
a semi-supervised pathway analysis and (2) an unsupervised methylation/expression signature analysis. These analyses 
will use all available genes on the chip but can also be used to examine association with candidate pathways. DNA 
methylation and mRNA expression will be analyzed separately and their results will be cross referenced to interpret the 
function of genes identified.  
Pathway perturbed by intervention and affects asthma symptom and related outcomes 
Separately for methylation and expression results, we will first cross reference association results with intervention and 
asthma symptom to identify pathways and gene networks that are perturbed by intervention and subsequently affect 
asthma symptoms and related outcomes. In addition to estimating the association of methylation and expression with 
each intervention and with asthma symptoms, we will also estimate how much the intervention effect on asthma 
symptoms is through methylation/expression changes using causal mediation analysis. Based on the theory of 
counterfactuals (e.g. what a subject’s methylation/expression and symptoms would have been if that person had been 
instead randomized to the opposite treatment arm), we will apply the VanderWeele and Vansteelandt80 approach, 
which is very general in that it allows for the possibility of intervention-mediator (methylation/expression in this case) 
interactions on symptom outcomes, to estimate the direct and indirect (through a methylation/expression mechanism) 
effect of intervention on asthma symptoms (or other clinical endpoint).  These models will include both interventions 
(classroom air filter and school-wide IPM).  In the absence of intervention and methylation/expression interaction, this 
approach reduces to the well-known approach of Baron and Kenney79.  This class of models, which can be easily 
extended to count outcomes via Poisson or negative binomial regression and also to include random effects to account 
for the longitudinal design of the study, is one with which our investigative team has extensive prior experience104, 155 
. 
To interpret downstream functional role of the identified methylation loci, we will cross reference pathways and 
networks identified from methylation data and expression data and test for association between methylation changes 
and expression changes of the corresponding genes.  
Effect modification due to sensitization and related phenotypes 
We will repeat the above association analyses by including interaction terms with sensitization and related phenotypes. 
In model assessing the association of intervention with methylation and gene expression, the interaction term in the 
model will be each intervention indicator by sensitization or related phenotypes. For association of asthma symptom 
and methylation and expression, the interaction term in the model will be methylation/expression and sensitization and 
related phenotypes. We will also characterize subjects based on their methylation/expression patterns at baseline 
before intervention. We expect that part of these patterns might reflect epithelial and downstream mast cell, TH2 or 
other functions measurable in nasal samples. We will examine whether molecular characteristics before intervention 
modifies the size of effect and influences which gene pathways are changed by intervention and lead to downstream 
reduction of asthma symptoms.     
Correction of potential confounding due to cell counts and batch effects 

 
Confidential 
Page 51 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
Although we will completely randomized the samples in methylation/expression batches (run, plate, chip, etc) so that 
batches would not be correlated with intervention and asthma symptoms, thus not likely to be confounding factors. We 
will examine the sensitivity of our result to potential confounding due to cell counts and batch effects. We will use the 
experimentally obtained cell counts and the batch effects estimated by surrogate variable analysis (SVA)156 as covariates 
in the association analysis. Before computing the post-pre difference in methylation/expression, we will regress out the 
cell count effect and batch effect first and then calculate the difference in residual methylation/expression.   
We will repeat the above association analyses by including interaction terms with sensitization and related phenotypes. 
In the association of intervention with methylation and gene expression, the interaction term in the model will be 
intervention indicator and sensitization and related phenotypes. For association of asthma symptom and methylation 
and expression, the interaction term in the model will be methylation/expression and sensitization and related 
phenotypes. We will also characterize subjects based on their methylation/expression patterns at baseline before 
intervention. We expect that part of these patterns might reflect epithelial and downstream mast cell,  TH2 or other 
functions measurable in nasal samples. We will examine whether molecular characteristic before intervention modifies 
the size of effect and influences which gene pathways will be changed by intervention and lead to downstream 
reduction of asthma symptom.     
Selection of CpGs and genes for technical validation using pyrosequencing and realtime PCR 
We will select representative genes and CpGs in expression/methylation pathway and network. The representative 
genes/CpGs are defined as those that show the most significant individual association with intervention and asthma 
symptom. We will also select the hub genes/CpGs that show the strongest connection with other genes/CpGs in the 
same pathway and network.  
Relation of mechanistic study design to clinical trial 
Analysis of the data from the mechanistic portion of the study will focus on pathway-specific effects of the intervention 
on genome-wide methylation and expression, and on the downstream effects of changes in these intermediate 
outcomes on asthma symptoms and other relevant clinical outcomes. In evaluating whether school environment 
exposure abatement results in molecular changes that modify the course of asthma, we will not only expand our 
understanding of asthma immunopathogenesis, but will also create opportunities to identify potential novel targets for 
asthma phenotype-specific therapy.  
 
13.4.5 Analyses of Exploratory Endpoint(s) 
Exploratory data analysis will include compilation of descriptive statistics to detect any outliers or discrepancies in data 
and to compare baseline characteristics and demographics between IPM and Control, as well as between Filter and 
Control, Groups. Continuous variables will be summarized using means, medians, standard deviations, ranges, and 
interquartile ranges. Continuous variables will be analyzed using non-parametric approaches or will be transformed to 
meet assumptions of normality required for parametric statistics. Categorical variables will be tabulated. The percent of 
participants who complete the study, losses to follow-up, missed visits, and reasons for discontinuation will be presented. 

 
Confidential 
Page 52 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
13.4.6 Descriptive Analyses  
Descriptive Analyses  
The change in settled dust allergen levels will be compared between the 4 Groups to assess efficacy of allergen reduction. 
Asthma symptoms, rescue medication use, and health care utilization will be compared between IPM/Air Filter and 
Control Groups to assess efficacy of the intervention in reducing asthma symptoms and morbidity. 
Descriptive statistics to detect any outliers or discrepancies in data and to compare baseline characteristics and 
demographics between IPM and Education Groups. Continuous variables will be summarized using means, medians, 
standard deviations, ranges, and interquartile ranges. Continuous variables will be analyzed using non-parametric 
approaches or will be transformed to meet assumptions of normality required for parametric statistics. Categorical 
variables will be tabulated. The percent of participants who complete the study, losses to follow-up, missed visits, and 
reasons for discontinuation will be presented. 
13.5 
Interim Analyses  (Not Applicable: Environmental Intervention- NOT a medication, high risk 
intervention) 
13.6 
Statistical Hypotheses  
Clinical Trial Hypothesis and Aims: Our central hypothesis is that reducing classroom/school exposure to particles and 
their associated allergens (particularly mouse/mold) will decrease asthma morbidity in students with asthma.  In School 
Inner-City Asthma Intervention Study-2 (SICAS-2) we plan to test our central hypothesis in an intervention study of 300 
elementary school-aged children with asthma from multiple classrooms in 40 inner-city elementary schools.  
Aim 1: To determine the effectiveness of a school/classroom based environmental intervention [Classroom particle air 
filter/purifying units and school-wide integrated pest management (IPM)] to:  
 (a)  Reduce asthma symptoms (primary outcome) as used in other NIAID inner-city asthma studies1, 3; 
 (b)  Reduce medication use, health care utilization, and improve lung function (secondary outcomes). 
 
Mechanistic Aims: 
Aim 2: To test the hypothesis that effects of school/classroom-based environmental interventions on symptoms/other 
measures of asthma control occur through changes in gene methylation or expression in pathways (and secondarily, in 
genes) relevant to airway function and asthma.  Within pathways or networks of genes (pre-specified or discovered in 
unsupervised analyses) we will (a) determine how our interventions influence changes in nasal airway cell methylation 
or gene expression and (b) evaluate how our intervention-associated changes in methylation and gene expression 
influence asthma outcomes. Finally, using mediation analysis, we will (c) estimate how much of the intervention effects 
on asthma symptoms occurs through methylation/expression changes1115, 1116. 
Secondary Aim 3:  To explore whether sensitization or other asthma phenotypes defined at baseline modify which 
pathways or networks of genes undergo intervention-related changes in methylation or gene expression that, in turn, 
are associated with improvement in asthma outcomes. 

 
Confidential 
Page 53 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
 
13.7 
Sample Size Considerations Sample Size Estimates: 
 
Power and Sample Size Calculations: (a) Primary Clinical Outcome: We include the Annual Study Schema Figure 1 
(labeled Figure 5 in the Research Strategy) to aid in understanding both the statistical analysis plan and the power 
calculations. For the primary clinical outcome, assumptions for the sample size estimate for the symptom outcome are 
based on classroom/exposure and symptom data from SICAS-1. The proposed primary statistical analysis assessing the 
impact of the interventions (school- and classroom-based) is based on a multilevel negative binomial regression model, 
which simultaneously accounts for correlation among clustered observations while accounting for over-dispersion in the 
symptom counts We calculated power using a simulation-based approach that repeatedly generated data under this 
model, and calculating the proportion of time we reject the null hypothesis of no school-wide IPM effect (H0: b3=0) and 
no classroom filter effect (H0: b4=0). We assumed θ = 3.  The intercept b0 = log(3) was chosen to correspond to a rate of 
three symptom days at baseline prior to the intervention.  The amount of overdispersion in the negative binomial 
distribution was set equal to that estimated in SICAS-1. Specifically, this set was using the overdispersion parameter 
“theta” in the rnegbin function in the MASS package in R.  The random effects standard deviations were set equal to 0.5 
and 0.2 for the subject and school random effects, respectively.  All power calculations were run assuming a two-sided 
alpha=0.05 level test, and all power estimates are based on 1,000 simulated datasets.  Power calc table 2 shows that 
with a total n = 240, we have >80% power to detect a difference of at least 0.6 days of symptoms and >90% power to 
detect a difference of 0.75 days between the two groups.  Taking into account a conservative projected 20% dropout 
rate (SICAS-1 > 90% retention), we will enroll 300 participants to ensure that 240 will complete the study. To check our 
power to detect associations among quintiles of the exposure distribution (as a continuous variable, ), we used the same 
simulation strategy based on a multilevel negative binomial regression model but with exposure quintile as a covariate. 
 
Using this approach, we estimate that we will have 90% power to detect the slope estimated in SICAS-1 of 0.173 (the 
effect size in Figure 2), which represents the log relative rate per increase in exposure quintile, in as little of 40 subjects. 
This result demonstrates the increase in power that results in using the continuous exposure concentrations, when such 
an effect in fact exists, and suggests that we will be able to detect such associations even if this effect exists only in 
subjects sensitized to mouse and mold (our SICAS-1 data supports that we will have more than 40 sensitized subjects). 
 
Our power calculations for our primary outcome were determined by the SICAS-1 data on exposure, sensitization and 
symptoms for mouse and mold, and the pollutant exposures for the entire population and supports that the SICAS-2 
population will have adequate power to test our primary hypotheses. 
We also estimated our power to detect intervention effects on secondary outcomes, specifically FEV1 reflecting 
pulmonary function.  We used the same simulation approach outlined above for symptoms, but simulating from a linear  
Sample Size Estimates: 
Table 2 
Δ sx 
days/2 
Total 
N 
Power: 
IPM 
Power: 
Class 

 
Confidential 
Page 54 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
mixed effects model for a continuous outcome instead of a negative binomial 
regression model for counts. We used as variance component estimates values 
taken from unpublished analyses of the association between FEV1 and air 
pollution exposure our group (Gold, Coull, Koutrakis) has just recently 
completed on data from the Childhood Asthma Management Program (CAMP) 
study.  Specifically, from our CAMP analyses using outcome measures taken 
quarterly, we assumed values of 10 and 6 for the subject-specific and residual 
error terms, yielding a subject-specific intraclass  correlation of approximately 
0.6.  We assumed a value of 6 for the school-specific error term, yielding a school-specific intraclass correlation of 0.2.  
For ease of interpretability, following the convention of Cohen157we express the minimal detectable effect size as a 
percentage of the residual standard deviation of the outcome, with 0.2 representing a “small” effect size, 0.5 
representing a medium effect size, and 0.8 representing a large effect size.  Under these assumptions, we estimated that 
we will have 80% (90% in parentheses) power to detect an Cohen’s effect size (for either class or school-wide 
intervention) of 0.3 (0.4), suggesting we will have the power to detect relatively modest effects of intervention based on 
n=240 after a conservative estimate of 20% dropout (again, we observed <10% dropout in SICAS-1).  Existing published 
results suggest the effect of particle exposures may be at least moderate, with an reported correlation between PM2.5 
and FEV1 of -0.72 (p<0.01) in Southern California public schoolchildren from the Children’s Health Study158.  Therefore 
we are likely to have sufficient power to detect plausible effect sizes of the intervention.  
Analysis will compare IPM versus Control Schools and Air Filter Versus Sham Classrooms, and efficiently testing the 
effectiveness of the intervention in real life, translatable practicality to all schools, since likely IPM affects school wide 
exposures, while air filters will affect classroom specific exposures.  The power calculations are based on a two-sided 
0.05 alpha level test  
 
 
14. Identification and Access to Source Data 
14.1. Source Data 
Source documents and source data are considered to be the original documentation where subject information, visits 
consultations, examinations and other information are recorded.   Documentation of source data is necessary for the 
reconstruction, evaluation and validation of clinical findings, observations and other activities during a clinical trial.  The 
Data Coordinating Center (DCC) lead will manage the data repository for the clinical and safety database. She will 
generate reports for review by the Protocol Chair on at least a monthly basis or more frequently as dictated by the rate 
of participant enrollment and availability of results. 
The investigator or designee will to the best of his/her ability encourage compliance in completing case report forms for 
every participant entered into the trial without being coercive. In addition, the investigator or designee is responsible for 
the reliability of the data  collected and recorded in the database and will review and sign the pertinent case report 
weeks 
School 
0.60 
240 
84 
89 
280 
91 
92 
0.75 
240 
96 
98 
280 
99 
99 
0.90 
240 
99 
100 
280 
100 
100 

 
Confidential 
Page 55 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
forms, namely adverse events, severe adverse events, and protocol deviations when completed.  Lung function tests will 
be reviewed and signed by PI or qualified designee (i.e. certified pulmonology specialist, asthma/allergy specialist). 
Data collected on hard copy forms will be entered into a REDCAP database, which is a web- based data entry system 
located on the BCH network. It provides audit trails for tracking data changes and user activity as well as automated 
export procedures for seamless downloads to Excel and common statistical packages. The database has range and valid 
value checks to ensure integrity at the time of data entry. Out of range values must be confirmed by the staff person 
conducting data entry at the time of entry. Missing values will be flagged at the time of data entry and reported to the 
project manager for follow-up and resolution. Hard copy source documents will be used to verify missing data or 
discrepancies whenever available. 
 
The study staff will complete data entry into REDCap as data are collected and at the latest by the last day of the month 
during which data was collected so data the manager may generate accurate and timely reports. Data will also be 
reviewed on an ongoing basis and in real time by the by the Data Manager.  If the Data Manager finds discrepancies or 
missing data, she will assign data queries to the project manager.  It will be the data manager’s  responsibility to check 
the data field against the source documentation.  S/he will then respond to the query either by verifying the entered 
value or correcting the value.  If the Data Manager finds the response acceptable, she will make the appropriate 
correction to the database and close the query.  Data queries will be therefore be resolved promptly after identification 
at the time of data entry as well as at monthly intervals during data monitoring and cleaning activities throughout the 
year. 
 
Several procedures will be in place to confirm the completeness, consistency, and accuracy of all documented data 
within the database(s) for this trial. These include computerized edit checks at the time of data entry and data query 
resolution procedures as described above. In addition, double data entry will be performed on a randomly selected 
sample of study forms, with the percentage depending on relevance to primary and secondary outcomes. Double data 
entry will be conducted by a second study staff member to evaluate the degree of keying errors and on an ongoing basis 
during data collection. The data manager will run monthly reports comparing the double entry for discrepancies. If any 
errors are found, a query will be opened and directed to the project manager, who will need to return to the source 
documentation to resolve the issue. The project manager will reply with the correct data that should be captured, make 
the appropriate change, and save the form. The data manager will review changes and close query. Finally, various study 
status and quality reports will also be programmed and generated by the DCC to monitor study progress, data integrity, 
and safety. These will include reports that monitor form expectation and completion rates, visit window compliance, 
missing data and out of range values, recruitment and enrollment rates, and withdrawal or loss to follow-up 
rates.  Adverse event reports and Protocol Deviation Reports will also be generated routinely by the DMAC. Adverse 
events, protocol deviations study status and data quality reports will be reviewed on an ongoing basis by the PI. In 
addition, these reports will be generated periodically for DSMB review.  
  
14.2. Access to Source Data 
The site investigators and site staff will make all source data available to the DAIT/NIAID, as well as to relevant health 
authorities.  Authorized representatives as noted above are bound to maintain the strict confidentiality of medical and 
research information that may be linked to identified individuals. 
15. Protocol Deviations 

 
Confidential 
Page 56 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
15.1. Protocol Deviation Definitions 
Protocol Deviation – The investigators and site staff will conduct the study in accordance to the protocol; no deviations 
from the protocol are permitted.  Any change, divergence, or departure from the study design or procedures constitutes 
a protocol deviation.  As a result of any deviation, corrective actions will be developed by the site and implemented 
promptly. 
 
Major Protocol Deviation (Protocol Violation) - A Protocol Violation is a deviation from the IRB approved protocol that 
may affect the subject's rights, safety, or well-being and/or the completeness, accuracy and reliability of the study data.  
In addition, protocol violations include willful or knowing breaches of human subject protection regulations, or policies, 
any action that is inconsistent with the NIH Human Research Protection Program’s research, medical, and ethical 
principles, and a serious or continuing noncompliance with federal, state, local or institutional human subject protection 
regulations, policies, or procedures.  
 
Non-Major Protocol Deviation - A non-major protocol deviation is any change, divergence, or departure from the study 
design or procedures of a research protocol that does not have a major impact on the subject's rights, safety or well-
being, or the completeness, accuracy and reliability of the study data. 
 
15.2. Reporting and Managing Protocol Deviations 
The study site principal investigator has the responsibility to identify, document and report protocol deviations as 
directed by the study Sponsor (DAIT/NIAID) .  However, protocol deviations may also be identified during site monitoring 
visits or during other forms of study conduct review.  
Upon determination that a protocol deviation has occurred, the study staff will a) notify the site Principal Investigator, b) 
notify the NIAID Project Manager, the DMAC,  and c) will complete a Protocol Deviation form.  The DAIT/NIAID Project 
Manager will make the decision as to whether the Deviation is major or not and what the impact of the Deviation on the 
study participant or the entire study may be.  PI will submit  the Protocol Deviation reports to the appropriate review 
bodies (IRB, DAIT/NIAID.) and who will review and approve the action plan that will be implemented as a result of the 
Protocol Deviation.  
16. Ethical Considerations and Compliance with Good Clinical Practice 
16.1. Statement of Compliance 
This clinical study will be conducted using good clinical practice (GCP), as delineated in Guidance for Industry: E6 Good 
Clinical Practice Consolidated Guidance, and according to the criteria specified in this study protocol.  Before study 
initiation, the protocol and the informed consent documents will be reviewed and approved by the IRB.  Any 
amendments to the protocol or to the consent materials will also be approved by the IRB before they are implemented. 
The Sponsor (DAIT/NIAID) will review and approve the Protocol and consent documents, and all changes in addition to 
IRB. 
16.2. Informed Consent Process 

 
Confidential 
Page 57 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
The consent process will provide information about the study to a prospective participant and will allow adequate time 
for review and discussion prior to his/her decision.  The principal investigator or designee listed on the IRB approved 
Protocol will review the consent and answer questions.  The designees will all be trained in human subjects’ protection 
and conflict of interest and able to provide informed consent per Institution guidelines. The prospective participant will 
be told that being in the trial is voluntary and that he or she may withdraw from the study at any time, for any reason.  
All participants (or their legally acceptable representative) will read, sign, and date a consent form before undergoing 
any study procedures.  Consent materials will be presented in participants’ primary language. Spanish-speaking 
participants will be provided with consent documents in Spanish and the consent discussion will be facilitated or 
conducted by a translator.  A copy of the signed consent form will be given to the participant. 
The consent process will be ongoing.  The consent form will be revised when important new safety information is 
available, the protocol is amended, and/or new information becomes available that may affect participation in the 
study.  
16.3. Privacy and Confidentiality 
A participant’s privacy and confidentiality will be respected throughout the study.  Each participant will be assigned a 
unique identification number and these numbers rather than names will be used to collect, store, and report participant 
information.  Site personnel will not transmit documents containing personal health identifiers (PHI) to the study 
sponsor (DAIT/NIAID) or their representatives.    
17.  Quality Control and Quality Assurance  
The investigator is required to keep accurate records to ensure that the conduct of the study is fully documented.  The 
investigator is required to ensure that all CRFs are completed for every participant entered in the trial.  Quality Control 
and Quality Assurance processes for data handling are discussed in Section 12.1 above. 
The sponsor is responsible for regular inspection of the conduct of the trial, for verifying adherence to the protocol, and 
for confirming the completeness, consistency, and accuracy of all documented data. 
In accordance with applicable regulations, GCP, and procedures, PPD will contact the site prior to the start of the study 
to review with the site staff the protocol, study requirements, and their responsibilities to satisfy regulatory, ethical, and 
protocol requirements.  When reviewing data collection procedures, the discussion will include identification, 
agreement and documentation of data items for which the CRF will serve as the source document. 
PPD contracted by DAIT/NIAID will monitor the study to ensure that the: 
 
Data are authentic, accurate, and complete. 
 
Safety and rights of subjects are being protected. 
 
Study is conducted in accordance with the currently approved protocol and any other study 
agreements, GCP, and all applicable regulatory requirements. 
The investigator agrees to allow the monitor direct access to all relevant documents. 

 
Confidential 
Page 58 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
To ensure compliance with GCP and all applicable regulatory requirements, PPD may conduct a quality assurance 
assessment and/or audit of the site records, and the regulatory agencies may conduct a regulatory inspection at any 
time during or after completion of the study. In the event of an assessment, audit or inspection, the investigator (and 
institution) must agree to grant the advisor(s), auditor(s) and inspector(s) direct access to all relevant documents and to 
allocate their time and the time of their staff to discuss the conduct of the study, any findings/relevant issues and to 
implement any corrective and/or preventative actions to address any findings/issues identified. 
17.1   
Data Handling 
The investigator is required to ensure that all CRFs are completed for every participant entered in the trial.  All elements 
of data entry (i.e., time, date, verbatim text, and the name of the person performing the data entry) will be recorded 
with an audit trail to allow all data changes in the database to be monitored and maintained in accordance with federal 
regulations.  
 
18. Publication Policy 
Every possible effort will be made for the primary outcome of the trial to be published in a peer-reviewed journal within 
12 months after the database is locked, that DAIT/NIAID will review and comment on any manuscript derived from this 
trial prior to submission and that, if the trial is funded by a NIAID grant of > $500,000 direct costs/year, the NIH data 
sharing policy applies (http://grants.nih.gov/grants/policy/data_sharing/data_sharing_guidance.htm#goals) and that 
data from this trial will be shared in accordance to the specific plan that was included in the grant application.    
 
19. References 
1. 
Morgan WJ, Crain EF, Gruchalla RS, O'Connor GT, Kattan M, Evans R, 3rd, Stout J, Malindzak G, Smartt E, Plaut 
M, Walter M, Vaughn B, Mitchell H. Results of a home-based environmental intervention among urban children with 
asthma. N Engl J Med. 2004;351(11):1068-80. 
2. 
Mitchell H, Senturia Y, Gergen P, Baker D, Joseph C, McNiff-Mortimer K, Wedner HJ, Crain E, Eggleston P, Evans 
R, 3rd, Kattan M, Kercsmar C, Leickly F, Malveaux F, Smartt E, Weiss K. Design and methods of the National Cooperative 
Inner-City Asthma Study. Pediatric pulmonology. 1997;24(4):237-52. 
3. 
Rosenstreich DL, Eggleston P, Kattan M, Baker D, Slavin RG, Gergen P, Mitchell H, McNiff-Mortimer K, Lynn H, 
Ownby D, Malveaux F. The role of cockroach allergy and exposure to cockroach allergen in causing morbidity among 
inner-city children with asthma. N Engl J Med. 1997;336(19):1356-63. 
4. 
Phipatanakul W, Bailey A, Hoffman EB, Sheehan WJ, Lane JP, Baxi S, Rao D, Permaul P, Gaffin JM, Rogers CA, 
Muilenberg ML, Gold DR. The school inner-city asthma study: design, methods, and lessons learned. J Asthma. 
2011;48(10):1007-14. PMCID: 3220801. 
5. 
Wildfire JJ, Gergen PJ, Sorkness CA, Mitchell HE, Calatroni A, Kattan M, Szefler SJ, Teach SJ, Bloomberg GR, Wood 
RA, Liu AH, Pongracic JA, Chmiel JF, Conroy K, Rivera-Sanchez Y, Busse WW, Morgan WJ. Development and validation of 
the Composite Asthma Severity Index--an outcome measure for use in children and adolescents. The Journal of allergy 
and clinical immunology. 2012;129(3):694-701. PMCID: 3294274. 

 
Confidential 
Page 59 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
6. 
Krishnan JA, Lemanske RF, Jr., Canino GJ, Elward KS, Kattan M, Matsui EC, Mitchell H, Sutherland ER, Minnicozzi 
M. Asthma outcomes: symptoms. The Journal of allergy and clinical immunology. 2012;129(3 Suppl):S124-35. 
7. 
Vital signs: asthma prevalence, disease characteristics, and self-management education: United States, 2001--
2009. MMWR Morb Mortal Wkly Rep. 2011;60(17):547-52. 
8. 
Joseph CL, Foxman B, Leickly FE, Peterson E, Ownby D. Prevalence of possible undiagnosed asthma and 
associated morbidity among urban schoolchildren. J Pediatr. 1996;129(5):735-42. 
9. 
Permaul P, Hoffman E, Fu C, Sheehan W, Baxi S, Gaffin J, Lane J, Bailey A, King E, Chapman M, Gold D, 
Phipatanakul W. Allergens in urban schools and homes of children with asthma. Pediatr Allergy Immunol. 
2012;23(6):543-9. PMCID: 3424376. 
10. 
Sheehan WJ, Rangsithienchai PA, Muilenberg ML, Rogers CA, Lane JP, Ghaemghami J, Rivard DV, Otsu K, 
Hoffman EB, Israel E, Gold DR, Phipatanakul W. Mouse allergens in urban elementary schools and homes of children 
with asthma. Ann Allergy Asthma Immunol. 2009;102(2):125-30. PMCID: 2658645. 
11. 
Permaul P, Petty C, Sheehan W, Baxi S, Gaffin J, Kopel L, Kanchongkittiphan W, Bailey A, Fu C, DR G, Phipatanakul 
W. Mouse Allergen Exposure in Urban Schools and its Effect on Childhood Asthma Morbidity. J Allergy and Clin Immunol. 
2013;131:AB 141. 
12. 
Baxi S, Petty C, Fu C, Sheehan W, Permaul P, Rogers C, Muilenberg M, DR G, Phipatanakul W. Classroom Fungal 
Spore Exposure and Asthma Morbidity in Inner-City School Children. J Aller Clin Immunol. 2013;131:AB 54. 
13. 
Gaffin J, Petty C, Sheehan WJ, Baxi S, Permaul P, Kopel L, Fu C, Kanchongkittiphan W, Gold DR, Phipatanakul W. 
Classroom-Based Air Pollution Effects on Asthma Morbidity in Inner City School Children. Amer J Respir Crit Care Med. 
2013;187:A2521. 
14. 
Matsui EC, Eggleston PA, Buckley TJ, Krishnan JA, Breysse PN, Rand CS, Diette GB. Household mouse allergen 
exposure and asthma morbidity in inner-city preschool children. Ann Allergy Asthma Immunol. 2006;97(4):514-20. 
15. 
Pongracic JA, Visness CM, Gruchalla RS, Evans R, 3rd, Mitchell HE. Effect of mouse allergen and rodent 
environmental intervention on asthma in inner-city children. Ann Allergy Asthma Immunol. 2008;101(1):35-41. 
16. 
Butz AM, Matsui EC, Breysse P, Curtin-Brosnan J, Eggleston P, Diette G, Williams D, Yuan J, Bernert JT, Rand C. A 
randomized trial of air cleaners and a health coach to improve indoor air quality for inner-city children with asthma and 
secondhand smoke exposure. Arch Pediatr Adolesc Med. 2011;165(8):741-8. 
17. 
Lanphear BP, Hornung RW, Khoury J, Yolton K, Lierl M, Kalkbrenner A. Effects of HEPA air cleaners on 
unscheduled asthma visits and asthma symptoms for children exposed to secondhand tobacco smoke. Pediatrics. 
2011;127(1):93-101. PMCID: 3010094. 
18. 
Phipatanakul W, Cronin B, Wood RA, Eggleston PA, Shih MC, Song L, Tachdjian R, Oettgen HC. Effect of 
environmental intervention on mouse allergen levels in homes of inner-city Boston children with asthma. Ann Allergy 
Asthma Immunol. 2004;92(4):420-5. 
19. 
Gaffin JM, Raby BA, Petty CR, Hoffman EB, Baccarelli AA, Gold DR, Phipatanakul W. beta-2 Adrenergic receptor 
gene methylation is associated with decreased asthma severity in inner-city Schoolchildren: Asthma and Rhinitis. Clin 
Exp Allergy. 2014;44(5):681-9. 
20. 
Permaul P, Sheehan WJ, Baxi SN, Gaffin JM, Fu C, Petty CR, Gold DR, Phipatanakul W. Predictors of indoor 
exposure to mouse allergen in inner-city elementary schools. Ann Allergy Asthma Immunol. 2013;111(4):299-301 e1. 
21. 
Baxi SN, Muilenberg ML, Rogers CA, Sheehan WJ, Gaffin J, Permaul P, Kopel LS, Lai PS, Lane JP, Bailey A, Petty 
CR, Fu C, Gold DR, Phipatanakul W. Exposures to molds in school classrooms of children with asthma. Pediatr Allergy 
Immunol. 2013;24(7):697-703. 
22. 
Sheehan WJ, Hoffman EB, Fu C, Baxi SN, Bailey A, King EM, Chapman MD, Lane JP, Gaffin JM, Permaul P, Gold 
DR, Phipatanakul W. Endotoxin exposure in inner-city schools and homes of children with asthma. Ann Allergy Asthma 
Immunol. 2012;108(6):418-22. PMCID: 3367391. 

 
Confidential 
Page 60 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
23. 
Kanchongkittiphon W, Sheehan WJ, Friedlander J, Chapman MD, King EM, Martirosyan K, Baxi SN, Permaul P, 
Gaffin JM, Kopel L, Bailey A, Fu C, Petty CR, Gold DR, Phipatanakul W. Allergens on desktop surfaces in preschools and 
elementary schools of urban children with asthma. Allergy. 2014;Epub ahead of print. 
24. 
Baxi SN, Sheehan WJ, Gaffin JM, Yodying J, Panupattanapong S, Lane JP, Fu C, Hoffman EB, Gold DR, 
Phipatanakul W. Agreement between parent and student responses to an asthma and allergy questionnaire in a diverse, 
inner-city elementary school population. Ann Allergy Asthma Immunol. 2011;107(4):371-3. PMCID: 3187549. 
25. 
Arbes SJ, Jr., Sever M, Vaughn B, Mehta J, Lynch JT, Mitchell H, Hoppin JA, Spencer HL, Sandler DP, Zeldin DC. 
Feasibility of using subject-collected dust samples in epidemiologic and clinical studies of indoor allergens. 
Environmental health perspectives. 2005;113(6):665-9. 
26. 
Curtin-Brosnan J, Paigen B, Hagberg KA, Langley S, O'Neil EA, Krevans M, Eggleston PA, Matsui EC. Occupational 
mouse allergen exposure among non-mouse handlers. J Occup Environ Hyg. 2010;7(12):726-34. PMCID: PMC3143460. 
27. 
Platts-Mills TA. Allergen avoidance in the treatment of asthma: problems with the meta-analyses. The Journal of 
allergy and clinical immunology. 2008;122(4):694-6. 
28. 
Ogden CL, Carroll MD, Curtin LR, Lamb MM, Flegal KM. Prevalence of high body mass index in US children and 
adolescents, 2007-2008. Jama. 2010;303(3):242-9. 
29. 
Islam T, Urman R, Gauderman WJ, Milam J, Lurmann F, Shankardass K, Avol E, Gilliland F, McConnell R. Parental 
stress increases the detrimental effect of traffic exposure on children's lung function. American journal of respiratory 
and critical care medicine. 2011;184(7):822-7. PMCID: 3208647. 
30. 
Curtin-Brosnan J, Paigen B, Hagberg KA, Langley S, O'Neil EA, Krevans M, Eggleston PA, Matsui EC. Occupational 
mouse allergen exposure among non-mouse handlers. J Occup Environ Hyg. 2010;7(12):726-34. 
31. 
Pacheco KA. New insights into laboratory animal exposures and allergic responses. Curr Opin Allergy Clin 
Immunol. 2007;7(2):156-61. 
32. 
Baxi S, Sheehan WJ, Permaul P, Gaffin JM, Rao D, Fu C, Rogers C, Muilenberg M, Hoffman EB, Gold DR, 
Phipatanakul W. Airborne Fungus Diversity and Concentrations in Inner City Elementary Schools Ped Aller Immunol. 
2013;24(7):697-703. 
33. 
Pongracic JA, O'Connor GT, Muilenberg ML, Vaughn B, Gold DR, Kattan M, Morgan WJ, Gruchalla RS, Smartt E, 
Mitchell HE. Differential effects of outdoor versus indoor fungal spores on asthma morbidity in inner-city children. The 
Journal of allergy and clinical immunology. 2010;125(3):593-9. 
34. 
Lignell U, Meklin T, Putus T, Rintala H, Vepsalainen A, Kalliokoski P, Nevalainen A. Effects of moisture damage 
and renovation on microbial conditions and pupils' health in two schools--a longitudinal analysis of five years. J Environ 
Monit. 2007;9(3):225-33. 
35. 
Kioumourtzoglou MA, Coull BA, Dominici F, Koutrakis P, Schwartz J, Suh H. The impact of source contribution 
uncertainty on the effects of source-specific PM on hospital admissions: A case study in Boston, MA. Journal of exposure 
science & environmental epidemiology. 2014. 
36. 
O'Connor GT, Neas L, Vaughn B, Kattan M, Mitchell H, Crain EF, Evans R, 3rd, Gruchalla R, Morgan W, Stout J, 
Adams GK, Lippmann M. Acute respiratory health effects of air pollution on children with asthma in US inner cities. The 
Journal of allergy and clinical immunology. 2008;121(5):1133-9 e1. 
37. 
Brunekreef B, Beelen R, Hoek G, Schouten L, Bausch-Goldbohm S, Fischer P, Armstrong B, Hughes E, Jerrett M, 
van den Brandt P. Effects of long-term exposure to traffic-related air pollution on respiratory and cardiovascular 
mortality in the Netherlands: the NLCS-AIR study. Res Rep Health Eff Inst. 2009(139):5-71; discussion 3-89. 
38. 
Permaul P, Hoffman E, Fu C, Sheehan W, Baxi S, Gaffin J, Lane J, Bailey A, King E, Chapman M, Gold D, 
Phipatanakul W. Allergens in urban schools and homes of children with asthma. Pediatr Allergy Immunol. 2012. 
39. 
Fletcher DJ, Lewis SM, Matthews JN. Factorial designs for crossover clinical trials. Statistics in medicine. 
1990;9(10):1121-9. 
40. 
Simon R. Designs for efficient clinical trials. Oncology (Williston Park). 1989;3(7):43-9; discussion 51-3. 

 
Confidential 
Page 61 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
41. 
Niemeijer NR, de Monchy JG. Age-dependency of sensitization to aero-allergens in asthmatics. Allergy. 
1992;47(4 Pt 2):431-5. 
42. 
Schwartz J, Weiss ST. Relationship of skin test reactivity to decrements in pulmonary function in children with 
asthma or frequent wheezing. American journal of respiratory and critical care medicine. 1995;152(6 Pt 1):2176-80. 
43. 
Liccardi G, Cazzola M, D'Amato M, D'Amato G. Pets and cockroaches: two increasing causes of respiratory allergy 
in indoor environments. Characteristics of airways sensitization and prevention strategies. Respiratory medicine. 
2000;94(11):1109-18. 
44. 
Arruda LK, Ferriani VP, Vailes LD, Pomes A, Chapman MD. Cockroach allergens: environmental distribution and 
relationship to disease. Current Allergy and Asthma Reports. 2001;1(5):466-73. 
45. 
Arshad SH. Indoor allergen exposure in the development of allergy and asthma. Current Allergy and Asthma 
Reports. 2003;3(2):115-20. 
46. 
Chew GL, Perzanowski MS, Miller RL, Correa JC, Hoepner LA, Jusino CM, Becker MG, Kinney PL. Distribution and 
determinants of mouse allergen exposure in low-income New York City apartments. Environmental health perspectives. 
2003;111(10):1348-51. 
47. 
Chew GL, Correa JC, Perzanowski MS. Mouse and cockroach allergens in the dust and air in northeastern United 
States inner-city public high schools. Indoor Air. 2005;15(4):228-34. 
48. 
Matsui EC, Simons E, Rand C, Butz A, Buckley TJ, Breysse P, Eggleston PA. Airborne mouse allergen in the homes 
of inner-city children with asthma. Journal of Allergy & Clinical Immunology. 2005;115(2):358-63. 
49. 
Perry T, Matsui E, Merriman B, Duong T, Eggleston P. The prevalence of rat allergen in inner-city homes and its 
relationship to sensitization and asthma morbidity. Journal of Allergy & Clinical Immunology. 2003;112(2):346-52. 
50. 
Phipatanakul W, Eggleston PA, Wright EC, Wood RA, The National Coooperative Inner-City Asthma S. Mouse 
allergen. II. The relationship of mouse allergen exposure to mouse sensitization and asthma morbidity in inner-city 
children with asthma. Journal of Allergy & Clinical Immunology. 2000;106(6):1075-80. 
51. 
Phipatanakul W, Eggleston PA, Wright EC, Wood RA. Mouse allergen. I. The prevalence of mouse allergen in 
inner-city homes. The National Cooperative Inner-City Asthma Study. The Journal of allergy and clinical immunology. 
2000;106(6):1070-4. 
52. 
Phipatanakul W. Rodent allergens. Current Allergy and Asthma Reports. 2002;2(5):412-6. 
53. 
Findley S, Lawler K, Bindra M, Maggio L, Penachio MM, Maylahn C. Elevated asthma and indoor environmental 
exposures among Puerto Rican children of East Harlem. Journal of Asthma. 2003;40(5):557-69. 
54. 
Simoni M, Lombardi E, Berti G, Rusconi F, La Grutta S, Piffer S, Petronio MG, Galassi C, Forastiere F, Viegi G. 
Mould/dampness exposure at home is associated with respiratory disorders in Italian children and adolescents: the 
SIDRIA-2 Study. Occupational and environmental medicine. 2005;62(9):616-22. 
55. 
Matheson MC, Abramson MJ, Dharmage SC, Forbes AB, Raven JM, Thien FC, Walters EH. Changes in indoor 
allergen and fungal levels predict changes in asthma activity among young adults. Clin Exp Allergy. 2005;35(7):907-13. 
56. 
Targonski PV, Persky VW, Ramekrishnan V. Effect of environmental molds on risk of death from asthma during 
the pollen season. The Journal of allergy and clinical immunology. 1995;95(5 Pt 1):955-61. 
57. 
Wallace LA, Mitchell H, O'Connor GT, Neas L, Lippmann M, Kattan M, Koenig J, Stout JW, Vaughn BJ, Wallace D, 
Walter M, Adams K, Liu LJ. Particle concentrations in inner-city homes of children with asthma: the effect of smoking, 
cooking, and outdoor pollution. Environmental health perspectives. 2003;111(9):1265-72. PMCID: 1241585. 
58. 
Delfino RJ, Quintana PJ, Floro J, Gastanaga VM, Samimi BS, Kleinman MT, Liu LJ, Bufalino C, Wu CF, McLaren CE. 
Association of FEV1 in asthmatic children with personal and microenvironmental exposure to airborne particulate 
matter. Environmental health perspectives. 2004;112(8):932-41. PMCID: 1242025. 
59. 
Koenig JQ, Mar TF, Allen RW, Jansen K, Lumley T, Sullivan JH, Trenga CA, Larson T, Liu LJ. Pulmonary effects of 
indoor- and outdoor-generated particles in children with asthma. Environmental health perspectives. 2005;113(4):499-
503. PMCID: 1278493. 

 
Confidential 
Page 62 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
60. 
Platts-Mills TA, Vaughan JW, Carter MC, Woodfolk JA. The role of intervention in established allergy: avoidance 
of indoor allergens in the treatment of chronic allergic disease. Journal of Allergy and Clinical Immunology. 
2000;106(5):787-804. 
61. 
Shapiro GG, Wighton TG, Chinn T, Zuckrman J, Eliassen AH, Picciano JF, Platts-Mills TA. House dust mite 
avoidance for children with asthma in homes of low-income families. Journal of Allergy and Clinical Immunology. 
1999;103(6):1069-74. 
62. 
Vojta PJ, Randels SP, Stout J, Muilenberg M, Burge HA, Lynn H, Mitchell H, O'Connor GT, Zeldin DC. Effects of 
physical interventions on house dust mite allergen levels in carpet, bed, and upholstery dust in low-income, urban 
homes. Environmental health perspectives. 2001;109(8):815-9. 
63. 
Gergen PJ, Mortimer KM, Eggleston PA, Rosenstreich D, Mitchell H, Ownby D, Kattan M, Baker D, Wright EC, 
Slavin R, Malveaux F. Results of the National Cooperative Inner-City Asthma Study (NCICAS) environmental intervention 
to reduce cockroach allergen exposure in inner-city homes. Journal of Allergy and Clinical Immunology. 1999;103(3 Pt 
1):501-6. 
64. 
Wood RA. Environmental control in the prevention and treatment of pediatric allergic disease. Current opinion 
in pediatrics. 1993;5(6):692-5. 
65. 
Custovic A, Taggart SC, Francis HC, Chapman MD, Woodcock A. Exposure to house dust mite allergens and the 
clinical activity of asthma. Journal of Allergy & Clinical Immunology. 1996;98(1):64-72. 
66. 
Platts-Mills TA, Ward GW, Jr., Sporik R, Gelber LE, Chapman MD, Heymann PW. Epidemiology of the relationship 
between exposure to indoor allergens and asthma. International Archives of Allergy and Applied Immunology. 
1991;94(1-4):339-45. 
67. 
Htut T, Higenbottam TW, Gill GW, Darwin R, Anderson PB, Syed N. Eradication of house dust mite from homes of 
atopic asthmatic subjects: a double-blind trial. Journal of Allergy and Clinical Immunology. 2001;107(1):55-60. 
68. 
Phipatanakul W. Animal allergens and their control. Current Allergy and Asthma Reports. 2001;1(5):461-5. 
69. 
Phipatanakul W. Environmental indoor allergens. Pediatric Annals. 2003;32(1):40-8. 
70. 
Bollinger ME, Eggleston PA, Flanagan E, Wood RA. Cat antigen in homes with and without cats may induce 
allergic symptoms. Journal of Allergy and Clinical Immunology. 1996;97(4):907-14. 
71. 
Wood RA, Chapman MD, Adkinson NF, Jr., Eggleston PA. The effect of cat removal on allergen content in 
household-dust samples. Journal of Allergy and Clinical Immunology. 1989;83(4):730-4. 
72. 
Kattan M, Stearns SC, Crain EF, Stout JW, Gergen PJ, Evans R, 3rd, Visness CM, Gruchalla RS, Morgan WJ, 
O'Connor GT, Mastin JP, Mitchell HE. Cost-effectiveness of a home-based environmental intervention for inner-city 
children with asthma. The Journal of allergy and clinical immunology. 2005;116(5):1058-63. 
73. 
Mitchell H, Cohn RD, Wildfire J, Thornton E, Kennedy S, El-Dahr JM, Chulada PC, Mvula MM, Grimsley LF, 
Lichtveld MY, White LE, Sterling YM, Stephens KU, Martin WJ. Implementation of Evidence-based Asthma Interventions 
in Post-Katrina New Orleans: The Head-off Environmental Asthma in Louisiana (HEAL) Study. Environmental health 
perspectives. 2012;120(11):1607-12. 
74. 
Woods ER, Bhaumik U, Sommer SJ, Ziniel SI, Kessler AJ, Chan E, Wilkinson RB, Sesma MN, Burack AB, Klements 
EM, Queenin LM, Dickerson DU, Nethersole S. Community asthma initiative: evaluation of a quality improvement 
program for comprehensive asthma care. Pediatrics. 2012;129(3):465-72. 
75. 
Howden-Chapman P, Pierse N, Nicholls S, Gillespie-Bennett J, Viggers H, Cunningham M, Phipps R, Boulic M, 
Fjallstrom P, Free S, Chapman R, Lloyd B, Wickens K, Shields D, Baker M, Cunningham C, Woodward A, Bullen C, Crane J. 
Effects of improved home heating on asthma in community dwelling children: randomised controlled trial. BMJ. 
2008;337:a1411. PMCID: 2658826. 
76. 
Karlsson AS, Renstrom A, Hedren M, Larsson K. Allergen avoidance does not alter airborne cat allergen levels in 
classrooms. Allergy. 2004;59(6):661-7. 

 
Confidential 
Page 63 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
77. 
Karlsson AS, Andersson B, Renstrom A, Svedmyr J, Larsson K, Borres MP. Airborne cat allergen reduction in 
classrooms that use special school clothing or ban pet ownership. The Journal of allergy and clinical immunology. 
2004;113(6):1172-7. 
78. 
Karlsson AS, Renstrom A, Hedren M, Larsson K. Comparison of four allergen-sampling methods in conventional 
and allergy prevention classrooms. Clin Exp Allergy. 2002;32(12):1776-81. 
79. 
Pilotto LS, Nitschke M, Smith BJ, Pisaniello D, Ruffin RE, McElroy HJ, Martin J, Hiller JE. Randomized controlled 
trial of unflued gas heater replacement on respiratory health of asthmatic schoolchildren. International journal of 
epidemiology. 2004;33(1):208-14. 
80. 
Morales E, Bustamante M, Vilahur N, Escaramis G, Montfort M, de Cid R, Garcia-Esteban R, Torrent M, Estivill X, 
Grimalt JO, Sunyer J. DNA hypomethylation at ALOX12 is associated with persistent wheezing in childhood. American 
journal of respiratory and critical care medicine. 2012;185(9):937-43. 
81. 
Baccarelli A, Rusconi F, Bollati V, Catelan D, Accetta G, Hou L, Barbone F, Bertazzi PA, Biggeri A. Nasal cell DNA 
methylation, inflammation, lung function and wheezing in children with asthma. Epigenomics. 2012;4(1):91-100. PMCID: 
3297414. 
82. 
Woodruff PG, Modrek B, Choy DF, Jia G, Abbas AR, Ellwanger A, Koth LL, Arron JR, Fahy JV. T-helper type 2-
driven inflammation defines major subphenotypes of asthma. American journal of respiratory and critical care medicine. 
2009;180(5):388-95. PMCID: 2742757. 
83. 
Woodruff PG, Boushey HA, Dolganov GM, Barker CS, Yang YH, Donnelly S, Ellwanger A, Sidhu SS, Dao-Pick TP, 
Pantoja C, Erle DJ, Yamamoto KR, Fahy JV. Genome-wide profiling identifies epithelial cell genes associated with asthma 
and with treatment response to corticosteroids. Proc Natl Acad Sci U S A. 2007;104(40):15858-63. PMCID: 2000427. 
84. 
Lambrecht BN, Hammad H. The airway epithelium in asthma. Nat Med. 2012;18(5):684-92. 
85. 
Poole A, Urbanek C, Eng C, Schageman J, Jacobson S, O'Connor BP, Galanter JM, Gignoux CR, Roth LA, Kumar R, 
Lutz S, Liu AH, Fingerlin TE, Setterquist RA, Burchard EG, Rodriguez-Santana J, Seibold MA. Dissecting childhood asthma 
with nasal transcriptomics distinguishes subphenotypes of disease. The Journal of allergy and clinical immunology. 
2014;133(3):670-8 e12. 
86. 
Baron RM, Kenny DA. The moderator-mediator variable distinction in social psychological research: conceptual, 
strategic, and statistical considerations. Journal of personality and social psychology. 1986;51(6):1173-82. 
87. 
Vanderweele TJ, Vansteelandt S. Odds ratios for mediation analysis for a dichotomous outcome. Am J Epidemiol. 
2010;172(12):1339-48. PMCID: 2998205. 
88. 
Kattan M, Crain EF, Steinbach S, Visness CM, Walter M, Stout JW, Evans R, 3rd, Smartt E, Gruchalla RS, Morgan 
WJ, O'Connor GT, Mitchell HE. A randomized clinical trial of clinician feedback to improve quality of care for inner-city 
children with asthma. Pediatrics. 2006;117(6):e1095-103. 
89. 
Kanabar D, Volans G. Accidental superwarfarin poisoning in children--less treatment is better. Lancet. 
2002;360(9338):963. 
90. 
Ingels M, Lai C, Tai W, Manning BH, Rangan C, Williams SR, Manoguerra AS, Albertson T, Clark RF. A prospective 
study of acute, unintentional, pediatric superwarfarin ingestions managed without decontamination. Ann Emerg Med. 
2002;40(1):73-8. 
91. 
Position Statement: Allergen Skin Testing. Journal of Allergy and Clinical Immunology. 1993;92:636-7. 
92. 
Dweik R, Boggs P, Erzurum S, Irvin C, Leigh M, Lundberg J, Olin A, Plummer A, Taylor D. An official ATS clinical 
practice guideline: Interpretation of exhaled nitric oxide levels (FENO) for clinical applications. Am J Respir Crit Care 
Med. 2011;184(5):602-15. 
93. 
NIH.NHLBI. Guidelines for Diagnosis and Management of Asthma: Expert Panel Report 2. 2002:45-6. 
94. 
Redline S, Gruchalla RS, Wolf RL, Yawn BP, Cartar L, Gan V, Nelson P, Wollan P. Development and validation of 
school-based asthma and allergy screening questionnaires in a 4-city study. Ann Allergy Asthma Immunol. 
2004;93(1):36-48. 

 
Confidential 
Page 64 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
95. 
Pipkorn U, Karlsson G. Methods for obtaining specimens from the nasal mucosa for morphological and 
biochemical analysis. Eur Respir J. 1988;1(9):856-62. 
96. 
Stokes A, Kieninger E, Künzi L, Kopf BS, Geiser M, Casaulta C, Regamey N. Comparison of different brushing 
techniques to obtain nasal epithelial cells from human subjects. Freitag. 2011. 
97. 
Lambrecht BN, Hammad H. Asthma: The importance of dysregulated barrier immunity. Eur J Immunol. 
2013;43(12):3125-37. 
98. 
Luttmann-Gibson H, Sarnat SE, Suh HH, Coull BA, Schwartz J, Zanobetti A, Gold DR. Short-term effects of air 
pollution on oxygen saturation in a cohort of senior adults in Steubenville, Ohio. Journal of occupational and 
environmental medicine / American College of Occupational and Environmental Medicine. 2014;56(2):149-54. PMCID: 
3987810. 
99. 
Wylie BJ, Coull BA, Hamer DH, Singh MP, Jack D, Yeboah-Antwi K, Sabin L, Singh N, MacLeod WB. Impact of 
biomass fuels on pregnancy outcomes in central East India. Environmental health : a global access science source. 
2014;13(1):1. PMCID: 3922846. 
100. 
Higgins TS, Reh DD. Environmental pollutants and allergic rhinitis. Curr Opin Otolaryngol Head Neck Surg. 
2012;20(3):209-14. 
101. 
Zhang X, Sebastiani P, Liu G, Schembri F, Dumas YM, Langer EM, Alekseyev Y, O'Connor GT, Brooks DR, Lenburg 
ME, Spira A. Similarities and differences between smoking-related gene expression in nasal and bronchial epithelium. 
Physiol Genomics. 2009;41(1):1-8. 
102. 
Feng CH, Miller MD, Simon RA. The united allergic airway: connections between allergic rhinitis, asthma, and 
chronic sinusitis. Am J Rhinol Allergy. 2012;26(3):187-90. 
103. 
Anway MD, Cupp AS, Uzumcu M, Skinner MK. Epigenetic transgenerational actions of endocrine disruptors and 
male fertility. Science. 2005;308(5727):1466-9. 
104. 
Richards E. Inherited epigenetic variation — revisiting soft inheritance. Nat Rev Genet. 2006;7:395-401. 
105. 
Dolinoy DC, Weidman JR, Jirtle RL. Epigenetic gene regulation: Linking early developmental environment to adult 
disease. . Reprod Toxicol. 2006. 
106. 
Rager JE, Bauer RN, Muller LL, Smeester L, Carson JL, Brighton LE, Fry RC, Jaspers I. DNA methylation in nasal 
epithelial cells from smokers: identification of ULBP3-related effects. Am J Physiol Lung Cell Mol Physiol. 
2013;305(6):L432-8. PMCID: 3763036. 
107. 
Beane J, Sebastiani P, Liu G, Brody JS, Lenburg ME, Spira A. Reversible and permanent effects of tobacco smoke 
exposure on airway epithelial gene expression. Genome Biol. 2007;8(9):R201. PMCID: 2375039. 
108. 
Baccarelli A, Wright RO, Bollati V, Tarantini L, Litonjua AA, Suh HH, Zanobetti A, Sparrow D, Vokonas PS, 
Schwartz J. Rapid DNA methylation changes after exposure to traffic particles. American journal of respiratory and 
critical care medicine. 2009;179(7):572-8. PMCID: 2720123. 
109. 
Bellavia A, Urch B, Speck M, Brook RD, Scott JA, Albetti B, Behbod B, North M, Valeri L, Bertazzi PA, Silverman F, 
Gold D, Baccarelli AA. DNA hypomethylation, ambient particulate matter, and increased blood pressure: findings from 
controlled human exposure experiments. Journal of the American Heart Association. 2013;2(3):e000212. 
110. 
Madrigano J, Baccarelli A, Mittleman MA, Sparrow D, Spiro A, 3rd, Vokonas PS, Cantone L, Kubzansky L, Schwartz 
J. Air pollution and DNA methylation: interaction by psychological factors in the VA Normative Aging Study. Am J 
Epidemiol. 2012;176(3):224-32. PMCID: 3491965. 
111. 
Guo L, Byun HM, Zhong J, Motta V, Barupal J, Zheng Y, Dou C, Zhang F, McCracken JP, Diaz A, Marco SG, Colicino 
S, Schwartz J, Wang S, Hou L, Baccarelli AA. Effects of short-term exposure to inhalable particulate matter on DNA 
methylation of tandem repeats. Environmental and molecular mutagenesis. 2014;55(4):322-35. 
112. 
Hou L, Zhang X, Zheng Y, Wang S, Dou C, Guo L, Byun HM, Motta V, McCracken J, Diaz A, Kang CM, Koutrakis P, 
Bertazzi PA, Li J, Schwartz J, Baccarelli AA. Altered methylation in tandem repeat element and elemental component 
levels in inhalable air particles. Environmental and molecular mutagenesis. 2014;55(3):256-65. 

 
Confidential 
Page 65 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
113. 
Tarantini L, Bonzini M, Apostoli P, Pegoraro V, Bollati V, Marinelli B, Cantone L, Rizzo G, Hou L, Schwartz J, 
Bertazzi PA, Baccarelli A. Effects of particulate matter on genomic DNA methylation content and iNOS promoter 
methylation. Environmental health perspectives. 2009;117(2):217-22. 
114. 
Sofer T, Baccarelli A, Cantone L, Coull B, Maity A, Lin X, Schwartz J. Exposure to airborne particulate matter is 
associated with methylation pattern in the asthma pathway. Epigenomics. 2013;5(2):147-54. 
115. 
Byun HM, Motta V, Panni T, Bertazzi PA, Apostoli P, Hou L, Baccarelli AA. Evolutionary age of repetitive element 
subfamilies and sensitivity of DNA methylation to airborne pollutants. Particle and fibre toxicology. 2013;10:28. 
116. 
Tarantini L, Bonzini M, Tripodi A, Angelici L, Nordio F, Cantone L, Apostoli P, Bertazzi PA, Baccarelli AA. Blood 
hypomethylation of inflammatory genes mediates the effects of metal-rich airborne pollutants on blood coagulation. 
Occupational and environmental medicine. 2013;70(6):418-25. 
117. 
Peluso M, Bollati V, Munnia A, Srivatanakul P, Jedpiyawongse A, Sangrajrang S, Piro S, Ceppi M, Bertazzi PA, 
Boffetta P, Baccarelli AA. DNA methylation differences in exposed workers and nearby residents of the Ma Ta Phut 
industrial estate, Rayong, Thailand. International journal of epidemiology. 2012;41(6):1753-60; discussion 61-3. 
118. 
Breton CV, Byun HM, Wang X, Salam MT, Siegmund K, Gilliland FD. DNA methylation in the arginase-nitric oxide 
synthase pathway is associated with exhaled nitric oxide in children with asthma. American journal of respiratory and 
critical care medicine. 2011;184(2):191-7. PMCID: 3172885. 
119. 
Verdugo RA, Deschepper CF, Munoz G, Pomp D, Churchill GA. Importance of randomization in microarray 
experimental designs with Illumina platforms. Nucleic Acids Res. 2009;37(17):5610-8. PMCID: 2761262. 
120. 
Zhang X, Mu W, Zhang W. On the analysis of the illumina 450k array data: probes ambiguously mapped to the 
human genome. Frontiers in genetics. 2012;3:73. 
121. 
Moen EL, Zhang X, Mu W, Delaney SM, Wing C, McQuade J, Myers J, Godley LA, Dolan ME, Zhang W. Genome-
wide variation of cytosine modifications between European and African populations and the implications for complex 
traits. Genetics. 2013;194(4):987-96. PMCID: 3730924. 
122. 
Du P, Zhang X, Huang CC, Jafari N, Kibbe WA, Hou L, Lin SM. Comparison of Beta-value and M-value methods for 
quantifying methylation levels by microarray analysis. BMC Bioinformatics. 2010;11:587. PMCID: 3012676. 
123. 
Pidsley R, CC YW, Volta M, Lunnon K, Mill J, Schalkwyk LC. A data-driven approach to preprocessing Illumina 
450K methylation array data. BMC Genomics. 2013;14:293. PMCID: 3769145. 
124. 
Hansel NN, Cheadle C, Diette GB, Wright J, Thompson KM, Barnes KC, Georas SN. Analysis of CD4+ T-cell gene 
expression in allergic subjects using two different microarray platforms. Allergy. 2008;63(3):366-9. 
125. 
Wright RO, Schwartz J, Wright RJ, Bollati V, Tarantini L, Park SK, Hu H, Sparrow D, Vokonas P, Baccarelli A. 
Biomarkers of lead exposure and DNA methylation within retrotransposons. Environmental health perspectives. 
2010;118(6):790-5. PMCID: 2898855. 
126. 
Hou L, Wang H, Sartori S, Gawron A, Lissowska J, Bollati V, Tarantini L, Zhang FF, Zatonski W, Chow WH, 
Baccarelli A. Blood leukocyte DNA hypomethylation and gastric cancer risk in a high-risk Polish population. Int J Cancer. 
2010;127(8):1866-74. PMCID: 3009461. 
127. 
Bollati V, Baccarelli A, Hou L, Bonzini M, Fustinoni S, Cavallo D, Byun HM, Jiang J, Marinelli B, Pesatori AC, 
Bertazzi PA, Yang AS. Changes in DNA methylation patterns in subjects exposed to low-dose benzene. Cancer Res. 
2007;67(3):876-80. PMCID: N.A. 
128. 
Bollati V, Schwartz J, Wright R, Litonjua A, Tarantini L, Suh H, Sparrow D, Vokonas P, Baccarelli A. Decline in 
genomic DNA methylation through aging in a cohort of elderly subjects. Mech Ageing Dev. 2009;130(4):234-9. PMCID: 
2956267. 
129. 
Pavanello S, Bollati V, Pesatori AC, Kapka L, Bolognesi C, Bertazzi PA, Baccarelli A. Global and gene-specific 
promoter methylation changes are related to anti-B[a]PDE-DNA adduct levels and influence micronuclei levels in 
polycyclic aromatic hydrocarbon-exposed individuals. Int J Cancer. 2009;125(7):1692-7. PMCID: In Process. 

 
Confidential 
Page 66 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
130. 
Rusiecki JA, Baccarelli A, Bollati V, Tarantini L, Moore LE, Bonefeld-Jorgensen EC. Global DNA hypomethylation is 
associated with high serum-persistent organic pollutants in Greenlandic Inuit. Environmental health perspectives. 
2008;116(11):1547-52. PMCID: 2592276. 
131. 
Baccarelli A, Wright R, Bollati V, Litonjua A, Zanobetti A, Tarantini L, Sparrow D, Vokonas P, Schwartz J. Ischemic 
heart disease and stroke in relation to blood DNA methylation. Epidemiology. 2010;21(6):819-28. PMCID: In Process. 
132. 
Baccarelli A, Tarantini L, Wright RO, Bollati V, Litonjua AA, Zanobetti A, Sparrow D, Vokonas P, Schwartz J. 
Repetitive element DNA methylation and circulating endothelial and inflammation markers in the VA normative aging 
study. Epigenetics : official journal of the DNA Methylation Society. 2010;5(3). PMCID: 3155741. 
133. 
Pavanello S, Pesatori AC, Dioni L, Hoxha M, Bollati V, Siwinska E, Mielzynska D, Bolognesi C, Bertazzi PA, 
Baccarelli A. Shorter telomere length in peripheral blood lymphocytes of workers exposed to polycyclic aromatic 
hydrocarbons. Carcinogenesis. 2010;31(2):216-21. 
134. 
Bind MA, Baccarelli A, Zanobetti A, Tarantini L, Suh H, Vokonas P, Schwartz J. Air Pollution and Markers of 
Coagulation, Inflammation, and Endothelial Function: Associations and Epigene-environment Interactions in an Elderly 
Cohort. Epidemiology. 2012. 
135. 
Madrigano J, Baccarelli A, Mittleman MA, Sparrow D, Vokonas PS, Tarantini L, Schwartz J. Aging and epigenetics: 
Longitudinal changes in gene-specific DNA methylation. Epigenetics : official journal of the DNA Methylation Society. 
2012;7(1). 
136. 
Gao Y, Baccarelli A, Shu XO, Ji BT, Yu K, Tarantini L, Yang G, Li HL, Hou L, Rothman N, Zheng W, Gao YT, Chow 
WH. Blood leukocyte Alu and LINE-1 methylation and gastric cancer risk in the Shanghai Women's Health Study. Br J 
Cancer. 2011. 
137. 
Rusiecki JA, Al-Nabhani M, Tarantini L, Chen L, Baccarelli A, Al-Moundhri MS. Global DNA methylation and tumor 
suppressor gene promoter methylation and gastric cancer risk in an Omani Arab population. Epigenomics. 
2011;3(4):417-29. 
138. 
Wernimont SM, Clark AG, Stover PJ, Wells MT, Litonjua AA, Weiss ST, Gaziano JM, Tucker KL, Baccarelli A, 
Schwartz J, Bollati V, Cassano PA. Folate network genetic variation, plasma homocysteine, and global genomic 
methylation content: a genetic association study. BMC Med Genet. 2011;12(1):150. 
139. 
Carugno M, Pesatori AC, Dioni L, Hoxha M, Bollati V, Albetti B, Byun HM, Bonzini M, Fustinoni S, Cocco P, Satta 
G, Zucca M, Merlo DF, Cipolla M, Bertazzi PA, Baccarelli A. Increased Mitochondrial DNA Copy Number in Occupations 
Associated with Low-Dose Benzene Exposure. Environmental health perspectives. 2011. 
140. 
Bollati V, Galimberti D, Pergoli L, Dalla Valle E, Barretta F, Cortini F, Scarpini E, Bertazzi PA, Baccarelli A. DNA 
methylation in repetitive elements and Alzheimer's disease. Brain Behav Immun. 2011;25(6):1078-83. PMCID: In 
Progress. 
141. 
Ursini G, Bollati V, Fazio L, Porcelli A, Iacovelli L, Catalani A, Sinibaldi L, Gelao B, Romano R, Rampino A, Taurisano 
P, Mancini M, Di Giorgio A, Popolizio T, Baccarelli A, De Blasi A, Blasi G, Bertolino A. Stress-Related Methylation of the 
Catechol-O-Methyltransferase Val158 Allele Predicts Human Prefrontal Cognition and Activity. J Neurosci. 
2011;31(18):6692-8. PMCID: In Process. 
142. 
Dioni L, Hoxha M, Nordio F, Bonzini M, Tarantini L, Albetti B, Savarese A, Schwartz J, Bertazzi PA, Apostoli P, Hou 
L, Baccarelli A. Effects of Short-Term Exposure to Inhalable Particulate Matter on Telomere Length, Telomerase 
Expression and Telomerase Methylation in Steel Workers. Environmental health perspectives. 2011;119(5):622-7. 
PMCID: 3094411. 
143. 
Fabris S, Bollati V, Agnelli L, Morabito F, Motta V, Cutrona G, Matis S, Grazia Recchia A, Gigliotti V, Gentile M, 
Deliliers GL, Bertazzi PA, Ferrarini M, Neri A, Baccarelli A. Biological and clinical relevance of quantitative global 
methylation of repetitive DNA sequences in chronic lymphocytic leukemia. Epigenetics : official journal of the DNA 
Methylation Society. 2011;6(2):188-94. PMCID: In Process. 
144. 
Zook PM, Jordan C, Adams B, Visness CM, Walter M, Pollenz K, Logan J, Tesson E, Smartt E, Chen A, D'Agostino J, 
Gern JE. Retention strategies and predictors of attrition in an urban pediatric asthma study. Clin Trials. 2010;7(4):400-10. 

 
Confidential 
Page 67 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
145. 
Goldstein H. Multilevel statistical models. 3rd ed. London: Arnold; 2003. 
146. 
Fitzmaurice GM LN, Ware JH. Applied Longitudinal Analysis, 2nd Edition. New York: Wiley; 2011. 
147. 
G.M. F, Laird NM, Ware JH, editors. Applied Longitudinal Analysis: Wiley & Sons; 2011. 
148. 
Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple 
testing. Journal of the Royal Statistical Society, Series B. 1995;57(1):289-300. 
149. 
Hedley AA, Ogden CL, Johnson CL, Carroll MD, Curtin LR, Flegal KM. Prevalence of Overweight and Obesity 
Among US Children, Adolescents, and Adults, 1999-2002. JAMA: The Journal of the American Medical Association. 
2004;291(23):2847-50. 
150. 
Kanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic acids research. 2000;28(1):27-30. 
151. 
Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, Harris 
MA, Hill DP, Issel-Tarver L, Kasarskis A, Lewis S, Matese JC, Richardson JE, Ringwald M, Rubin GM, Sherlock G. Gene 
ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet. 2000;25(1):25-9. 
152. 
Harris MA, Clark J, Ireland A, Lomax J, Ashburner M, Foulger R, Eilbeck K, Lewis S, Marshall B, Mungall C, Richter 
J, Rubin GM, Blake JA, Bult C, Dolan M, Drabkin H, Eppig JT, Hill DP, Ni L, Ringwald M, Balakrishnan R, Cherry JM, Christie 
KR, Costanzo MC, Dwight SS, Engel S, Fisk DG, Hirschman JE, Hong EL, Nash RS, Sethuraman A, Theesfeld CL, Botstein D, 
Dolinski K, Feierbach B, Berardini T, Mundodi S, Rhee SY, Apweiler R, Barrell D, Camon E, Dimmer E, Lee V, Chisholm R, 
Gaudet P, Kibbe W, Kishore R, Schwarz EM, Sternberg P, Gwinn M, Hannick L, Wortman J, Berriman M, Wood V, de la 
Cruz N, Tonellato P, Jaiswal P, Seigfried T, White R. The Gene Ontology (GO) database and informatics resource. Nucleic 
Acids Res. 2004;32(Database issue):D258-61. 
153. 
Langfelder P, Horvath S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics. 
2008;9(1):559. 
154. 
Poole A, Urbanek C, Eng C, Schageman J, Jacobson S, O'Connor BP, Galanter JM, Gignoux CR, Roth LA, Kumar R, 
Lutz S, Liu AH, Fingerlin TE, Setterquist RA, Burchard EG, Rodriguez-Santana J, Seibold MA. Dissecting childhood asthma 
with nasal transcriptomics distinguishes subphenotypes of disease. The Journal of allergy and clinical immunology. 2014. 
155. 
Gehlenborg N, O'Donoghue SI, Baliga NS, Goesmann A, Hibbs MA, Kitano H, Kohlbacher O, Neuweger H, 
Schneider R, Tenenbaum D, Gavin AC. Visualization of omics data for systems biology. Nat Methods. 2010;7(3 
Suppl):S56-68. 
156. 
Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, Paulovich A, Pomeroy SL, Golub TR, 
Lander ES, Mesirov JP. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide 
expression profiles. Proceedings of the National Academy of Sciences USA. 2005;102(43):15545-50. 
157. 
Wu MC, Lee S, Cai T, Li Y, Boehnke M, Lin X. Rare-variant association testing for sequencing data with the 
sequence kernel association test. Am J Hum Genet. 2011;89(1):82-93. PMCID: 3135811. 
158. 
Liu D, Ghosh D, Lin X. Estimation and testing for the effect of a genetic pathway on a disease outcome using 
logistic kernel machine regression via logistic mixed models. BMC Bioinformatics. 2008;9:292. PMCID: 2483287. 
159. 
Dittrich MT, Klau GW, Rosenwald A, Dandekar T, Muller T. Identifying functional modules in protein-protein 
interaction networks: an integrated exact approach. Bioinformatics. 2008;24(13):i223-31. PMCID: 2718639. 
160. 
Bind M-A, Vanderweele T, Coull B, Schwartz J. Mixed effects causal mediation analysis for longitudinal data. 
Submitted to Biostatistics. 2014. 
161. 
Liu Y, Aryee MJ, Padyukov L, Fallin MD, Hesselberg E, Runarsson A, Reinius L, Acevedo N, Taub M, Ronninger M, 
Shchetynsky K, Scheynius A, Kere J, Alfredsson L, Klareskog L, Ekstrom TJ, Feinberg AP. Epigenome-wide association data 
implicate DNA methylation as an intermediary of genetic risk in rheumatoid arthritis. Nature biotechnology. 
2013;31(2):142-7. PMCID: 3598632. 
162. 
Cohen J. Statistical Power Analysis for the Behavioral Sciences. second ed: Lawrence Erlbaum Associates; 1988. 
163. 
McConnell R, Islam T, Shankardass K, Jerrett M, Lurmann F, Gilliland F, Gauderman J, Avol E, Kunzli N, Yao L, 
Peters J, Berhane K. Childhood incident asthma and traffic-related air pollution at home and school. Environmental 
health perspectives. 2010;118(7):1021-6. PMCID: 2920902. 

 
Confidential 
Page 68 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15 
164. 
Diggle P, Heagerty P, Liang KY, Zeger SL. Analysis of Longitudinal Data. 2nd ed. Oxford: Oxford University; 2002. 
165. 
Benson M, Svensson PA, Carlsson B, Jernas M, Reinholdt J, Cardell LO, Carlsson L. DNA microarrays to study gene 
expression in allergic airways. Clin Exp Allergy. 2002;32(2):301-8. 
166. 
Janssen BG, Godderis L, Pieters N, Poels K, Kici Ski M, Cuypers A, Fierens F, Penders J, Plusquin M, Gyselaers W, 
Nawrot TS. Placental DNA hypomethylation in association with particulate air pollution in early life. Particle and fibre 
toxicology. 2013;10(1):22. PMCID: 3686623. 
167. 
Lilly CM, Tateno H, Oguma T, Israel E, Sonna LA. Effects of allergen challenge on airway epithelial cell gene 
expression. American journal of respiratory and critical care medicine. 2005;171(6):579-86. 
168. 
Vittinghoff E, Sen S, McCulloch CE. Sample size calculations for evaluating mediation. Statistics in medicine. 
2009;28(4):541-57. 
169. 
CAMP. Long-term effects of budesonide or nedocromil in children with asthma. The Childhood Asthma 
Management Program Research Group. N Engl J Med. 2000;343(15):1054-63. 
170. 
Asthma prevalence, disease characteristics, and self-management education — United States, 2001–2009. 
Morbidity and Mortality Weekly Report. 2011;60. 
171. 
Gottlieb DJ, Beiser AS, O'Connor GT. Poverty, race, and medication use are correlates of asthma hospitalization 
rates. A small area analysis in Boston. Chest. 1995;108(1):28-35. 
172. 
Ungar WJ, editor. Economic Evaluation in Child Health. New York: Oxford University Press Inc; 2010. 
173. 
Akinbami LJ, Sullivan SD, Campbell JD, Grundmeier RW, Hartert TV, Lee TA, Smith RA. Asthma outcomes: 
healthcare utilization and costs. The Journal of allergy and clinical immunology. 2012;129(3 Suppl):S49-64. 
174. 
Paltiel AD, Fuhlbrigge AL, Kitch BT, Liljas B, Weiss ST, Neumann PJ, Kuntz KM. Cost-effectiveness of inhaled 
corticosteroids in adults with mild-to-moderate asthma: results from the asthma policy model. The Journal of allergy and 
clinical immunology. 2001;108(1):39-46. 
175. 
Braithwaite RS, Meltzer DO, King JT, Jr., Leslie D, Roberts MS. What does the value of modern medicine say 
about the $50,000 per quality-adjusted life-year decision rule? Med Care. 2008;46(4):349-56. 

 
Confidential 
Page 69 of 69 
 
 
 
SICAS-2  
Version 3.0 
Date 03.27.15