Clinical trial NCT04768569
Conditions: Hearing Loss, Noise-Induced
Sponsor: Washington University School of Medicine
Start date: 2021-10-04; Completion date: 2023-09-29
Enrollment: 24 participants; Allocation: RANDOMIZED; Intervention model: PARALLEL

Brief summary:
The purpose of this study is to assess the safety and efficacy of zonisamide for the treatment of noise-induced hearing loss in adults.

Detailed description:
This study is a randomized, double-blinded placebo-control trial with three parallel groups, to make use of a common control group. After being informed about the study expectations and potential risks, all individuals providing written informed consent will undergo screening to determine eligibility for study entry.

Participants who meet the eligibility requirements will be randomized in a balanced fashion into one of 3 arms:

Group 1) Zonisamide 100 milligrams (mg) pre-op + Placebo post-op; Group 2) Placebo pre- + placebo post-op; and Group 3) Zonisamide 100 mg post-op + placebo post-op

Arms: arm 1: For subjects randomized to zonisamide pre-op, the pre-op package will contain one zonisamide capsule (100 mg PO) and the post-op package will contain one placebo capsule that looks, smells, and tastes the same as zonisamide capsules. arm 2: For the subjects randomized to placebo, both pre- and post-op packages will contain placebo capsules that looks, smells, and taste the same as zonisamide capsules. arm 3: For subjects randomized to zonisamide post-op, the pre-op package will contain one placebo capsule and the post-op package will contain one zonisamide capsule (100 mg PO).
Interventions: intervention 1: Zonisamide 100Mg Cap intervention 2: Placebo
Intervention descriptions: intervention 1: ZONEGRAN® is commercially available for oral administration as capsules containing 100 mg of Zonisamide. intervention 2: The placebo will contain microcrystalline cellulose which is the predominant filler in the generic capsule.

Protocol documents:
Prot_002.pdf: 
1 | P a g e  
 
Pharmaceutical Interventions for Noise-Induced Hearing Loss–Acute Exposure Treatment 
(PINIHL-AET) 
 
 
 
 
Washington University School of Medicine 
Department of Otolaryngology – Head & Neck Surgery 
660 South Euclid Avenue, Campus Box 8115 
St. Louis, MO  63110 
 
Protocol#: PINIHL-WU  
Version #: 9.0 
  Version Date: 03 MARCH 2023 
 
 
Sponsor : 
 
 
Washington University School of Medicine 
 
ClinicalTrials.gov #: 
 
NCT04768569 
IND: 
 
147812 
 
 
 
 
 
 
 
 
 
 
 
CONFIDENTIAL 
The information contained in this document is regarded as confidential and, except to the extent necessary to 
obtain informed consent, may not be disclosed to another party unless law or regulations require such 
disclosure.  Persons to whom the information is disclosed must be informed that the information is 
confidential and may not be further disclosed by them 
 
 
 


2 | P a g e  
 
 
Signature Page: 
 
Clinical Study Protocol No. PINIHL-WU v9.0 
 
 
Title: Pharmaceutical Interventions for Noise-Induced Hearing Loss–Acute Exposure Treatment 
(PINIHL-AET) 
 
 
I have read this protocol and agree to conduct this study in accordance with all stipulations of the 
protocol. 
 
 
 
 
Craig Buchman, MD  
 
 
  
 
03/03/2023 
Principal Investigator Name:  
 
Signature 
 
 
 
Date 
(Printed) 
 


3 | P a g e  
 
 
Pharmaceutical Interventions for Noise-Induced Hearing Loss–Acute Exposure Treatment 
(PINIHL-AET) 
 
Protocol Revision History 
 
Version Date 
Revision Summary 
19 January 2021 
Initial Version 
19 February 2021 
• Clarification of baseline and follow-up 
blood draws that include an electrolyte 
panel, BUN, Cr, ALT, and AST; serum 
pregnancy at baseline 
• Addition of effective birth control 
instruction 
10 June 2021 
• Addition of NIOSH red flag guideline 
(an increase in hearing threshold level of 
15 dB or more at any frequency (2, 3, 4, 
6 kHz) in either ear for permanent 
threshold shift as a secondary endpoint 
• Addition of LENS-Q Adapted for 
Surgical Noise Study and stratification 
language 
• Surgery drilling time reduced to 45 
minutes for inclusion criteria 
• Change in sample size 
• Corrected section 5.5 Follow-up 
Assessments to include “Hearing History 
and Occupation Exposure” questionnaire 
as listed in study calendar and appendix 
E 
• Study calendar clarifications including 
baseline testing adjusted from 1 week to 
1-2 weeks 
• Numbering correction in “Hearing 
History and Occupation Exposure—Visit 
1” questionnaire 
• Edited inclusion criteria for DPOAE as 
the number of data points (denominator) 
was incorrect 
• Removed urine sample; Added blood 
sample for PGx collection at baseline 
visit. 


4 | P a g e  
 
• Range of 2-8 degree Celsius (C) 
refrigerator at WUSM replaces 4 degree 
C for blood sample 
• Removed PI and Sub-Investigator 
information 
• List protocol version as a separate line. 
• Statistical considerations section updated 
to match SAP 
21 October 2021 
• Inclusion of stratification table for noise 
exposure 
• Randomization language updated 
09 November 2021 
• Clarification of language for secondary 
outcomes analysis criteria 
21 January 2022 
• Change time between baseline visit (#1) 
and surgical visit (#2) from 1-2 weeks to 
within 1 month (+/- 3 days). 
23 March 2022 
• Clarification of post-op DPOAE timing 
from within 4-8 hours to within 8 hours. 
• Clarification of baseline visit timing to 
within 30 days (+3 days). 
• Update timing of pre- and post-op 
dosing. 
• Correct efficacy analysis timing. 
• Addition of audiometry language in 
situations of an absence of a threshold. 
04 October 2022 
• WIN conducted once rather than 3 times.  
• ECG removed from study calendar and 
pre-op data collection as it is not 
standard of care 
18 November 2022 
• Update audiometric inclusion criteria 
03 March 2023 
• Correct air-bone gap inclusion criteria 
• Minor edits for consistency with 
previous modifications 
 
 
 


5 | P a g e  
 
TABLE OF CONTENTS 
 
1.0 
BACKGROUND AND SIGNIFICANCE ................................................................................... 6 
1.1 
Noise-induced hearing loss (NIHL) .................................................................................... 6 
1.2 
NIHL and its Pathogenesis ................................................................................................... 6 
1.3 
Molecular Pathways Underlying NIHL .............................................................................. 7 
1.4 
NIHL and Pharmacogenetics ............................................................................................... 8 
1.5 
NIHL and Drilling Noise During Skull-based Surgery .............................................. 10 
2.0 
STUDY OBJECTIVES ............................................................................................................... 10 
2.1 
Primary Objective .................................................................................................................. 10 
2.2 
Secondary Objectives ........................................................................................................... 11 
3.0 
ELIGIBILITY CRITERIA............................................................................................................ 11 
3.1 
Inclusion Criteria .................................................................................................................. 11 
3.2 
Exclusion Criteria ................................................................................................................. 11 
3.3 
Inclusion of Women and Minorities ................................................................................ 12 
4.0 
STUDY DESIGN ......................................................................................................................... 12 
5.0 
SCHEDULED ASSESSMENTS .............................................................................................. 13 
5.1 
Screening/Baseline/Preoperative Assessment ............................................................ 13 
5.2 
Randomization ....................................................................................................................... 15 
5.3 
Standard of Care Surgery ................................................................................................... 17 
5.4 
Intra-operative Testing ........................................................................................................ 17 
5.5 
Follow-Up Assessments ...................................................................................................... 17 
5.6 
Blood collection, transportation, and storage .............................................................. 18 
6.0 
EVALUABILITY ........................................................................................................................... 18 
7.0 
PHARMACEUTICAL INFORMATION .................................................................................... 19 
7.1 
Zonisamide (ZONEGRAN®) ................................................................................................ 19 
7.2 
Placebo ...................................................................................................................................... 20 
8.0 
REGULATORY AND REPORTING REQUIREMENTS ...................................................... 20 
8.1 
Sponsor-Investigator Reporting Requirements............................................................ 21 
8.2 
Secondary Site Reporting Requirements ....................................................................... 22 
8.3 
Exceptions to Expedited Reporting ................................................................................. 23 
9.0 
STUDY CALENDAR ................................................................................................................... 24 
10.0 DATA SUBMISSION SCHEDULE ......................................................................................... 24 
11.0 DATA AND SAFETY MONITORING ...................................................................................... 25 
11.1 Adverse Event Collection in the Case Report Forms ................................................. 26 
12.0 STATISTICAL CONSIDERATIONS ........................................................................................ 26 
12.1 Data Analysis .......................................................................................................................... 26 
12.2 Efficacy analysis .................................................................................................................... 26 
12.3 Sample Size Estimation ...................................................................................................... 30 
12.4  Interim Analysis ..................................................................................................................... 31 
12.5  Pharmacogenetics analysis plan ...................................................................................... 32 
13.0 REFERENCES ............................................................................................................................ 33 
APPENDIX A: Definitions for Adverse Event Reporting ............................................................ 44 
APPENDIX B: Reporting Timelines .................................................................................................. 46 
APPENDIX C: Washington University Unanticipated Problem Reporting Cover Sheet .. 48 
APPENDIX D: Questionnaire 1a: Hearing History and Occupation Exposure – Visit 1 . 49 
APPENDIX E: Questionnaire 1b: Hearing History and Occupation Exposure – Visit 3 . 51 
APPENDIX F: LENS-Q Adapted for Surgical Noise Study –Visit 1 ........................................ 53 
 


6 | P a g e  
 
1.0 
BACKGROUND AND SIGNIFICANCE 
 
1.1 
Noise-induced hearing loss (NIHL) 
 
Noise-induced hearing loss (NIHL) is a serious problem. When a service member 
leaves the military, hearing loss can impact his or her quality of life and 
employability (Pfannenstiel, 2014). Service members are vulnerable to two types 
of NIHL: occupational NIHL due to continuous or intermittent noise exposure and 
acoustic trauma due to a sudden burst of sound. Because no form of hearing 
protection offers complete protection against noise of that intensity, repeated firing 
of weapons even with ear protection devices can subsequently lead to occupational 
NIHL (Chen and Brueck, 2011). Almost every member of the armed forces will be 
exposed to hazardous noise at some point in his or her career (McIlwain et al., 2008; 
Kirchner et al., 2012; Yankaskas, 2013), highlighting the urgent need for 
pharmaceutical intervention. Despite positive outcomes in preclinical studies, to 
date, no drugs have been approved by the U.S. Food and Drug Administration 
(FDA) for use in the amelioration of NIHL (Le Prell and Bao, 2012; Mukherjea et 
al., 2015). 
 
1.2 
NIHL and its Pathogenesis 
 
After noise exposure, two phases of hearing loss can be measured. The first is a 
temporary threshold shift (TTS), which is greatest immediately after noise 
exposure, and gradually lessens within the first 24 hours. The second phase is a 
permanent threshold shift (PTS), which is measured two to three weeks after noise 
exposure (for recent review, Ryan et al., 2016; Liberman, 2016). These changes are 
typically monitored using behavioral pure-tone thresholds, distortion product 
otoacoustic emissions (DPOAE), or the auditory brainstem response (ABR) to 
generate an audiogram (a plot of threshold as a function of test frequency). The 
noise-induced damage is dependent on the noise pattern, intensity, and duration, 
with longer and louder noises being more hazardous than shorter or quieter sound 
exposures (Wang et al., 2002; Harding and Bohne, 2007; Chen et al., 2015). In 
addition, NIHL susceptibility differs markedly among individuals, resulting from 
the interaction of genetic and environmental factors (Clifford et al., 2016; Groth et 
al., 2016; Lavinsky et al., 2016). For example, in animals, the C57BL/6J mouse 
strain is more susceptible to noise than other mouse strains (Davis et al., 2001). In 
humans, individuals with specific single nucleotide polymorphisms (SNPs) in 
genes for certain antioxidant enzymes may be more susceptible to NIHL (Lin et al., 
2009). 
 
NIHL is caused by sensorineural damage, primarily to the sensory hair cells and 
primary auditory neurons of the cochlea (Liberman, 2017). Outer hair cells (OHCs) 
are particularly sensitive to noise. When OHCs are damaged, hearing thresholds 
increase due to a loss in amplification of the cochlear signal. Recently, Kujawa and 
Liberman (2006, 2009) have expanded on these classic findings with the 
observation that certain noise exposures at “benign” levels to rodents can result in 


7 | P a g e  
 
only TTS, but no PTS. Nevertheless, the animals show selective synaptic loss 
between inner hair cells (IHCs) and spiral ganglion neurons (SGNs) with high 
thresholds, ultimately accelerating hearing loss over time. Because this cochlear 
synaptopathy does not change the hearing threshold immediately, the term “hidden 
hearing loss” has been used to label the hidden synaptopathic injury, and this term 
has also been used to describe corresponding functional deficits that are assumed 
to be hidden behind the normal hearing threshold. 
 
Clinically, difficulties with understanding speech in noise have long been observed 
in older adults with normal audiometric thresholds (e.g. Frisina and Frisina, 1997). 
Loss of fidelity in the encoding of suprathreshold signals may provide one 
explanation for this deficit (Sergeyenko et al., 2013; Tremblay et al., 2015). Thus, 
there is the potential for profound functional consequences after a so-called benign 
noise exposure that led to only TTS. Of particular concern for military personnel 
with the potential for repeat exposure (Davis, 2016; Bramhall et al., 2017), further 
studies have found that benign noise exposures resulting in only TTS can also 
contribute to PTS after repeated exposure (Wang and Ren, 2012), underpinning the 
importance of developing pharmaceutical interventions to prevent noise-induced 
cochlear synaptopathy for military service members. 
 
1.3 
Molecular Pathways Underlying NIHL 
 
Although mechanical destruction and decreased blood flow contribute to NIHL 
(Quirk et al., 1991; Mulroy et al., 1998), several key molecular mechanisms such 
as signaling mediated by an ATP receptor have been identified to contribute to TTS 
(for recent review, see Kurabi et al., 2017). Common mechanisms underlying both 
TTS and PTS have also been identified. One is the increase of mitochondrial free 
radical formation such as reactive oxygen species (ROS) due to noise-induced 
intense metabolic activity in the cochlea (e.g., Yamane et al., 1995; Ohlemiller et 
al., 1999; Ohinata et al., 2000; Henderson et al., 2006; Campbell et al., 2007; Darrat 
et al., 2007). Thus, it is not surprising that attempts to prevent NIHL with 
antioxidant agents have become the focus of much research in this field (Seidman 
et al., 1993; Hight et al., 2003; McFadden et al., 2005; Yamashita et al., 2005; for 
review, see Le Prell and Lobarinas, 2015). However, most of these interventions 
have been only partially effective or ineffective in preventing NIHL (Lynch and 
Kil, 2005; Campbell et al., 2007; Kopke et al., 2007; Le Prell et al., 2007). The 
largely disappointing outcomes may be due to a narrow therapeutic window. As 
ROS signaling is also important for normal cellular function (for recent review, 
Sbodio et al., 2018), high doses of antioxidants may have less therapeutic benefit 
(for example, Kil et al., 2017). Recently, new signaling pathways underlying NIHL 
have been identified, including deregulation of calcium homeostasis (Guitton et al., 
2004; Zine and Van De Water, 2004; Chen et al., 2012; Han et al., 2015; Chen et 
al., 2015). Deregulation of calcium signaling may contribute to development of 
both TTS and PTS. In addition, calcium signaling is upstream of many other 
cellular survival signaling pathways. For example, it can control ROS signaling by 
regulating the release of ROS from the mitochondrion (Estergerg et al., 2013, 


8 | P a g e  
 
2014). Calcium homeostasis in the cochlea can be regulated by several types of 
calcium channels, which include voltage-gated calcium channels (VGCCs) 
(Rodrigues Contreraz and Yamoah, 2001; Adamson et al., 2002; Fuchs, 2002; 
Schnee and Ricci, 2003). VGCCs can be divided into two groups: high-voltage-
activated calcium channels and low-voltage-activated calcium channels (Igelmund 
et al., 1996; Lacinova et al., 2000; Perez-Reyes, 2003; Yunker and McEnery, 2003). 
The family of low-voltage-activated, or T-type, calcium channels (Cav3) is 
composed of three members (Cav3.1, Cav3.2, and Cav3.3) based on their respective 
main pore-forming alpha subunits: α 1G, α 1H, and α1I (Perez-Reyes, 2003; 
Yunker and McEnery, 2003). Our studies on drug repurposing have shown that a 
family of antiepileptic drugs blocking T-type calcium channels can prevent and 
treat NIHL (Shen et al., 2007; Bao et al., 2013). We have also determined the 
expression pattern of these calcium channels in the cochlea. All subtypes are 
present in SGNs, and α 1G and α 1I are expressed in the hair cells and supporting 
cells (Shen et al., 2007). Thus, it is not surprising that an antiepileptic drug (AED), 
zonisamide (ZNS), which blocks T-type calcium channels, has both prophylactic 
and therapeutic functions against NIHL (Bao et al., 2013). In addition, 
epidemiological studies show that ZNS is well-tolerated even for long-term 
treatment (Hashimoto et al., 1994; Leppik, 2006, White et al., 2010). These findings 
have led us to this project, which is the repurposing ZNS against NIHL for military 
service members. 
 
1.4 
NIHL and Pharmacogenetics 
 
Preliminary results. Pharmacogenetics (PGx) is the study of how a person’s genetic 
makeup determines his or her response to a therapeutic intervention. It offers the 
promise of utilizing genetic fingerprints to predict an individual’s responses to 
drugs in terms of safety, efficacy, and pharmacokinetics. It can revolutionize the 
practice of medicine by individualizing treatment through the use of novel 
diagnostic tools. To date over 100 loci have been associated with syndromic and 
non-syndromic hearing loss providing excellent biomarkers for PGx studies.  These 
markers are easily surveyed through both SNP-based or whole exome sequencing 
using DNA samples taken from patients (Pawelczyk et al. 2009; Konings et al. 
2009; Grondin et al. 2015).  In a recent study, a genetic risk score for the likelihood 
of NIHL was developed based on SNP markers in 10 genes (Zhang et al. 2019).  
Thus, we will test the applicability of this index to predicting both TTS and PTS in 
patients undergoing skull-base surgery. In addition to examining associations of 
candidate genes for NIHL, we will also screen patients for known genetic variation 
associated with the metabolism of ZNS (Saruwatari et al. 2010).  Ultimately, we 
envision incorporating SNPs associated with high risk for NIHL with drug 
metabolism SNPs to develop predictive models for drug efficacy.  These data would 
be used in dialogue with FDA and subsequent studies to develop personalized drug 
treatment regimens for patients. 
 


9 | P a g e  
 
Here, we provide three types of data from our PGx study of age-related hearing loss 
(ARHL). They are highly pertinent because the same approaches will be applied to 
this project. First, we describe our recent clinical findings on the delay of ARHL in 
human subjects taking calcium channel blockers (CCBs). Second, we present our 
preliminary human genetic studies of ARHL in the same population based on the 
continuous extreme phenotypes (CEP) and sequence kernel association test 
(SKAT) approaches. Third, we present an estimate of patient populations using the 
CEP-SKAT method. 
 
Delay of ARHL in patients taking 
CCBs. In our preliminary study, a 
total of 35 white female patients have 
completed their first visit, with 26 of 
them using amlodipine (74%) for 
more than one year. We 
compared 
this 
CCB 
group with two control 
cohorts, also of white 
females: control 1 group 
(Con 1) from the Rochester, NY, area (447 participants) and control 2 group (Con 
2) from the St. Louis, MO, area (55 participants) (Fig. 1).  
 
Since ARHL starts at higher frequencies in the cochlea, we divided audiograms into 
three pure tone averages (PTA): averages of 0.25, 0.5, and 1 kHz (PTAL); averages 
of 
2 
and 
4 
kHz 
(PTAH24); and averages 
of 2, 4, and 8 kHz 
(PTAH248). The means 
for the CCB group were: 
PTAL (15.1 dB HL), 
PTAH24 (20.7 dB HL), 
and PTAH248 (24.0 dB 
HL), and the means for the 
control 1 group were: 
PTAL (20.1 dB HL), 
PTAH24 (30.7 dB HL), and PTAH248 (35.2 dB HL). Since there were no data for 
8 kHz for the control 2 group, the means for this group were PTAL (20.7, dB HL) 
and PTAH24 (29.3 dB HL). The two-tailed unequal variance t-test showed a 
significant difference between the CCB and the control 1 group for PTAL (p = 
0.00067), PTAH24 (p = 0.00001), and PTAH248 (p = 0.00021), and a significant 
difference between the CCB and control 2 groups for PTAL (p = 0.02777) and 
PTAH24 (p = 0.00959). To correct for possible influences from both age and the 
three cohort sites, we used multivariate regression models with the Bonferroni 
correction method (Table 1, 2 and 3 for PTAL, PTAH24 and PTAH248, 
respectively). No significant difference was observed for PTAL between the CCB 
and control 1 or 2 groups (Table 1), or PTAH24 (Table 2) between the CCB and 
Fig. 1. CCB protection against ARHL. 
Participants taking CCBs show better hearing 
thresholds than participants taking no CCBs 
even at low frequency regions (0.25 to 1 kHz). 


10 | P a g e  
 
control 2 group. However, statistically significant differences were found for both 
PTAH24 and PTAH248 between the CCB and control 1 group (Table 2 and 3). 
These data indicate CCB had beneficial effects against peripheral ARHL.  
 
1.5 
NIHL and Drilling Noise During Skull-based Surgery 
 
Patients undergoing skull-based surgery are unavoidably exposed to noise from 
operative drills. High-speed drills that are capable of producing elevated levels are 
used during skull based surgeries (Hilmi et al., 2011; Yu et al., 2014). Hilmi et al. 
(2011) used accelerometers with cadaver temporal bones to measure the bone-
transmitted drill noise. The authors found that the while the highest overall bone-
conducted noise levels occurred while drilling on the mastoid process with a sound 
level of 110.2 dBA, other drilling locations such as the cranial base produce 
excessive amounts of drill noise primarily in the 2-4 Hz bandwidth. If bone-
transmitted surgical drilling noise exposure was regulated by occupational safety 
organizations such as the National Institute of Occupational Safety and Health 
(NIOSH), the exposure time duration would be limited to between 1.5 to 12 minutes 
depending on drill location.  
 
The drilling noise transmitted to the unoperated ear through the skull is difficult to 
prevent. Thus, noise-induced damage cannot be avoided by mechanical protection 
such as ear plug. Many patients who undergo a skull-based surgery for treatment to 
an affected ear, have normal or near-normal hearing in the contralateral ear. 
Therefore, the unoperated, normal-hearing ear is subjected to a similar drill-noise 
intensity compared to the operated side (Tos et al., 1984; Hickey and O’Connor, 
1991). It is not surprising that temporary cochlear changes are commonly observed 
in unoperated ears. It has been shown that surgical drilling may have a temporary 
effect on the amplitude of the otoacoustic emissions of the ear contralateral to the 
surgical site (Baradaranfar et al., 2015; Shenoy et al., 2015). Furthermore, it has 
been reported that the incidence of a permanent SNHL (PTS) following 
tympanomastoid surgery is between 1.2% and 4.5% (Tos et al., 1984). PTS is also 
observed in some studies (Palva and Sorri, 1979; Lustig et al., 1995; Hallmo and 
Mair, 1996; Goyal et al., 2013; Abtahi et al., 2016).  
 
The overarching goal of this study is to test whether ZNS can prevent temporary 
cochlear changes and PTS in patients undergoing skull-based surgery.  Participants 
will be randomized to receive either active treatment (ZNS) or placebo.     
 
2.0 
STUDY OBJECTIVES 
 
2.1 
Primary Objective 
 
To determine if preoperative and/or postoperative ZNS is more effective than 
placebo at preventing PTS in the contralateral ear of patients undergoing drilling 
during skull base surgery. 
 


11 | P a g e  
 
 
2.2 
Secondary Objectives 
 
To determine if preoperative ZNS is more effective than placebo at preventing 
temporary changes in cochlear health, synaptopathy, and degraded speech 
perception in the contralateral ear of patients undergoing drilling during skull base 
surgery. 
 
To identify a genetic risk profile associated with drilling-induced hearing loss we 
will survey known genetic markers associated with NIHL including markers in 
CDH23, PCDH15, EYA4, MYO1A, KCNMA1 and OTOG (Zhang et al., (2019) 
and zonisamide (ZNS) metabolism, CYP2C9 and CYP2C19 (Saruwatari et al., 
2010). If significant associations are observed and validated in a subsequent clinical 
study, we will optimize drug dosages based on a subject’s genetic profile. 
 
 
 
3.0 
ELIGIBILITY CRITERIA 
 
3.1 
Inclusion Criteria 
 
1. Patients who are scheduled to undergo a skull-based surgery that requires 
at least 45 minutes of surgical-drilling. 
 
2. At least 18 years of age. 
 
3. Air conduction thresholds in the non-operated ears are to be no worse than 
25 dB HL for pure tone average 0.5, 1, and 2 kHz with no individual 
threshold greater than 30 dB HL, and no worse than 45 dB HL at 4 kHz at 
screening. 
 
4. Observed air-bone gap ≤ 10 dB HL at 0.5, 1, 2, and 4 kHz, with normal 
tympanometry. 
 
5. Ability to understand and willingness to sign an IRB approved written 
informed consent document. 
 
 
3.2 
Exclusion Criteria 
 
1. History of known sulfa allergy or hypersensitivity to carbonic anhydrase 
inhibitors. 
 
2. History of moderate-to-severe kidney or liver disease. 
 
3. Acute viral, bacterial, fungal or parasitic infection. 


12 | P a g e  
 
 
4. History of seizures. 
 
5. Currently pregnant or breast-feeding.  
 
6. Any current or history of ear disorder and/or central auditory dysfunction in 
the non-operated ear. 
 
7. History of ototoxic drug use. 
 
8. Current use of strong/moderate 3A4 inhibitor/inducer and grapefruit juice. 
 
Note:  For secondary outcomes analysis only, exclusion criteria is as 
 
follows:  
a) DPOAE data will be used as a secondary outcome measure, and 
participants will be excluded if their DPOAE is absent at more than 
4/10 frequencies. Criteria for a present response is any response that 
is > 5 dB SPL above the noise floor and replicable within ±5 dB 
SPL. 
b) ECochG: Participants will be excluded if the ECochG/ABR wave I 
response is absent. 
c) WIN test: Participants with WIN scores greater than moderate 
difficulty or 14.9 dB SNR will be excluded. 
  
Participants will not be excluded from the study for not meeting secondary 
  
outcome criteria. 
 
3.3 
Inclusion of Women and Minorities 
 
Both men and women and members of all races and ethnic groups are eligible for 
this trial. 
 
4.0 
STUDY DESIGN  
 
This study is a randomized, double-blinded placebo-control trial with three parallel 
groups, to make use of a common control group. Subjects will be randomized in a 
balanced fashion into one of 3 arms: ZNS 100 mg pre-op, Placebo, or ZNS 100 mg 
post-op. 
 
The primary efficacy endpoint will be the proportion of PTS-positive subjects defined 
as the ratio of PTS-positive subjects to total number of subjects within each study 
arm/group. Subjects defined as PTS-positive will demonstrate an increase in threshold 
that is ≥10 dB HL at any frequency from 2-6 kHz post-surgery as compared to baseline 
audiogram.  
 
The secondary efficacy outcome measures will be: (1) the proportion of PTS-positive 
subjects as defined above, but the definition of PTS will also include the NIOSH red 


13 | P a g e  
 
flag guideline for permanent threshold shift: an increase in hearing threshold level of 
15 dB or more at any frequency (2, 3, 4, 6 kHz). (2) The rate of temporary cochlear 
change as measured by a DPOAE amplitude shift at any frequency that is significantly 
greater than the stability of each measurement (i.e., 95% confidence interval of each 
measurement do not overlap). The rate of DPOAE shift is the ratio of DPOAE shift-
positive subjects to total subjects within each arm.  
 
To ensure double-blinding of the trial, each subject will be randomized to one of three 
treatment arms via an interactive randomization tool (IRT) and assigned to study 
group. Once randomized, each subject will be provided a kit on the day of surgery that 
contains two bottles, with one package labeled to be taken prior to surgery and another 
package designated to be taken within 12 hours after surgery or when the patient is 
released clinically to oral medication. For subjects randomized to “ZNS pre-op”, the 
pre-op package will contain one ZNS capsule (100 mg PO) and the post-op package 
will contain one placebo capsule that looks, smells, and tastes the same as ZNS 
capsules. For subjects randomized to “ZNS post-op”, the pre-op package will contain 
one placebo capsule and the post-op package will contain one ZNS capsule (100 mg 
PO). For the subjects randomized to “placebo”, both pre- and post-op packages will 
contain placebo.  
 
The study will be “masked” or “blinded” in the sense that all the study participants 
and the study team members will be blinded to the assignment in the study groups. 
Only the pharmacist who will prepare the study drug kits and the unblinded Statistician 
will have access to the kit assignments. A copy of the randomization kit list with study 
ID assignments will be saved in a limited access folder on a secure network server at 
Pharm-Olam. The Medical Monitor will be contacted in emergent medical cases when 
knowing the treatments assignment is mandatory for clinical care of the patient. 
 
At the time when we will need to “freeze” the data sets for purposes of developing the 
DSMB report, a series of SAS programs will be run from an independent programmer 
to produce data for each pairwise comparison into two subsets of data from the total 
cohort. Each subset will be de-identified. A previously prepared SAS code will be run 
in each subset and the output will be used to complete the table shells where the groups 
will not be identified.  The programmer preparing subsets will not be involved in the 
handling of data forms or the analysis of data. 
 
Study participants will be recruited from the Washington University Otology clinics. 
Patients will be offered participation if they are being offered skull-based surgery as 
part of their standard treatment. These are patients that would be recommended skull-
based surgery despite this investigation and this investigation will have no influence 
on treatment recommendations.  Consenting and eligible participants will be 
scheduled for standard of care surgery. 
 
5.0 SCHEDULED ASSESSMENTS 
 
5.1 
Screening/Baseline/Preoperative Assessment 


14 | P a g e  
 
 
The screening and baseline assessments will occur within 30 days (+3 days) of 
surgery and include the following tests or procedures: 
 
1. Documentation of demographic information, including gender, age, 
allergies, current medications, imaging related to surgery, and planned 
surgical approach.  
 
2. Clinical examination of the ears. 
 
3. Documentation of key clinical data such as confirmation of air conduction 
thresholds in the non-operated ears to be no worse than 25 dB HL for pure 
tone average 0.5, 1, and 2 kHz with no individual threshold greater than 30 
dB HL, and no worse than 45 dB HL at 4 kHz and absence of ear disorder 
in the ear contralateral to surgery.  
 
4. Collection of laboratory test results that include a pregnancy test*, 
electrolyte panel, BUN, Cr, ALT, and AST.   
If these tests are not performed as part of pre-operative workup, we will 
obtain them for research purposes. 
*Women capable of becoming pregnant will be asked to have a pregnancy 
test before beginning this study.  If a pregnancy test (urine or serum) is 
performed as part of pre-operative testing we will collect the results from 
the medical record for research purposes. Women capable of becoming 
pregnant will be instructed to use effective birth control methods and not to 
become pregnant while participating in this study as there may be unknown 
risks to the unborn child.  There may be long-term effects of the treatment 
being studied that could increase the risk of harm to an unborn child.  The 
study team must be notified if the birth control method fails while on the 
study and/or if the participant becomes pregnant while participating in this 
research study. 
 
5. Blood sample will be collected for PGx surveys. 
 
6. DPOAE, Audiogram, electrocochleography (ECochG), and WIN testing to 
document the measurements of the non-operated ear.  
 
Distortion Product Otoacoustic Emissions (DPOAE): DPOAEs are a 
measure of outer hair cell function and will be used as an indicator of 
changes in cochlear health and possible PTS in the early period following 
noise exposure. A soft earphone will be inserted into the participant’s ear 
and a series of tones at a comfortable volume will be played at varying 
frequencies. No participation is required of the participant as DPOAE are 
an objective assessment of cochlear health. The measurement system will 
record the level of the emissions evoked by two primary tones, f1 and f2 
(f2/f1 = 1.22) at levels 65 and 55 dB SPL respectively. The f2 primary tone 


15 | P a g e  
 
will be swept from 1-6 kHz, and will be repeated at least five times per 
session in order to calculate the stability of the emission at each session. All 
data will be identified and stored on a password protected computer. 
DPOAE recording will take about 20 minutes to complete. 
 
Audiometry: Audiogram will be performed to look for PTS. Earphones 
will be placed over the participant’s ear and a series of tones at a soft volume 
will be played at varying frequencies, and the participants have to indicate 
that they hear the tones by pressing a button. Thresholds will be measured 
from 250 Hz to 16 kHz. If there is an absence of a threshold at the limits of 
the equipment, the threshold will be reported as equipment limits (in dB 
HL) + 10 dB HL. As with the DPOAE, all equipment and procedures are 
based on a clinically approved protocol. 
 
Electrocochleography (ECochG): An ECochG is an electrophysiological 
measurement of the cochlea in response to sound and it will be used to 
identify synaptopathy. It is a clinically-approved auditory evoked potential 
that is used to evaluate the status of the both the cochlear and the auditory 
nerve fiber. This measurement is obtained by inserting a soft gold-foiled 
earphone into the participant’s ear. This earphone serves to deliver a series 
of clicks, as well as an electrode to measure the electrophysiological 
response of the cochlea to the sound. The electrode montage is completed 
with a ground electrode on the forehead at midline and a gold-foil electrode 
in the contralateral to serve as the inverting electrode. The impedance 
between electrodes will be < 3 kΩ for all participants. The click stimuli at 
90 dB nHL used for the study will be repeated 2000 times so that the 
recording signal can be averaged with artifact rejection. The measurement 
will be repeated three times. Testing time 45 min to 1 hour. 
 
Words in Noise Test (WIN): Earphones will be placed over the 
participant’s test ear and the WIN test will presented to the test ear. The 
WIN test battery consists of 35 words that are presented with varying 
degrees of signal-to-noise ratios (SNR) from 24 dB HL to 0 dB HL. The 
SNR at 24 dB HL is the easiest, with words presented at 24 dB above the 
babble background, whereas the SNR of 0 dB is the most difficult due to 
the target words being presented at the same level as the background noise 
(Wilson and Burks, 2005; Wilson and Watts, 2012). The WIN list will be 
presented to the test ear one time. The total number of words correctly 
identified will be used to calculate a dB HL S/N threshold by the Spearman-
Karber equation at the mean of 50% correct points. All of speech testing 
will take 5-10 minutes to complete. 
 
7. Completion of the Hearing History and Occupation Exposure questionnaire 
and LENS-Q Adapted for Surgical Noise Study. 
 
5.2 
Randomization  


16 | P a g e  
 
 
Participants will be randomized into one of three groups as shown below: 
 
 
Pre-op Package 
Post-op Package 
Pre-op group 
ZNS 100 mg PO 
Placebo 
Placebo group 
Placebo 
Placebo 
Post-op group 
Placebo 
ZNS 100 mg PO 
 
 
Randomization will be based on a randomization list generated by unblinded 
statistician using a computer algorithm written in SAS using randomly selected 
blocks of sizes 3. Within each block of 3, there will be 1 subject assigned to each 
study group. To balance noise-exposure history across study arms we will employ 
stratified randomization. The subjects will be stratified based on noise exposure 
survey responses (see table below), and will then be randomized to study groups. 
The random assignment of subjects to the different study groups will be associated 
with consecutively assigned random numbers which will be unique for each study 
participant. The stratified kit list will be provided to Advanced Rx who will package 
and label the drug for shipment to the pharmacist. Each kit will contain two bottles 
and will be labeled with the same kit number. The bottle will not contain any 
information of the treatment allocation. One interim analysis is planned, once 33% 
(n=78) of the subjects have completed participation in the study.  
 
Study medication will be dispensed to the participants with instruction to take their 
first assigned dose prior to surgery.  Participants will take their second assigned 
dose within 12 hours after surgery or when the patient is released clinically to oral 
medication. Participants will be instructed to take zonisamide without food. We 
will recommend that capsules be swallowed whole per the current approved 
labeling. 
 
 
Name 
Description 
1: High Noise 
Screening: 
   LENS-Q Adapted for Surgical 
Noise Study – 


17 | P a g e  
 
Name 
Description 
1A Or 2A Or 4A =   
a.Daily, Or 
b.Less than 
daily/more than 
weekly, Or 
c.Weekly, Or 
d.Less than 
weekly/more than 
monthly Or 
e.Monthly 
OR 
1C Or 2C Or 3C >= 5 Years 
 
2: Low Noise 
Screening: 
   LENS-Q Adapted for Surgical 
Noise Study – 
1A AND 2A AND 4A =   
f.Less than 
monthly/more than 
yearly, 
g.Yearly, 
h.Less than yearly Or 
i.Never 
OR 
1C AND 2C AND 3C < 5 
Years 
 
 
 
 
5.3 
Standard of Care Surgery 
 
Patients will undergo a typical preoperative workup in preparation for surgery, 
including routine lab work, pregnancy testing (females only), and a preoperative 
assessment by anesthesiology. Patients will undergo their procedure per surgical 
protocol. 
 
5.4 
Intra-operative Testing 
 
Documentation of drilling noise, as recorded by a probe mic in the contralateral ear 
to capture only ambient OR noise intensity level and duration from the non-
operated ear during surgery. Documentation will also include duration of 
anesthesia. 
 
5.5 
Follow-Up Assessments  


18 | P a g e  
 
 
 
 
The follow-up assessments will occur after surgery and include the following tests 
or procedures: 
 
1. DPOAE testing in recovery, within 8 hours after surgery. 
 
2. Blood samples taken within 12 hours following the first pill for PGx 
surveys.  
 
3. Collection of laboratory test results for research purposes that include an 
electrolyte panel, BUN, Cr, ALT, and AST.  If these tests are not performed 
as part of clinical care post-operatively, we will obtain them for research 
purposes at the time of the PGx blood draw. 
 
4. DPOAE, Audiogram, ECochG, and WIN testing 30 days (+/-3 days) after 
surgery. 
 
5. Completion of the Hearing History and Occupation Exposure questionnaire 
30 days (+/- 3 days) after surgery. 
 
6. Documentation of adverse events. 
 
Follow-up assessments will be planned at the stated time points; actual follow up 
times may vary due to patient logistics and compliance. 
 
5.6 
Blood collection, transportation, and storage  
 
 
Blood samples will be collected from each participant during the baseline visit and 
the post-surgery visit within 12 hours after the pre-operative drug dose.  A post-
operative nurse will draw blood into a red-top tube (EDTA or citrate) using an IV 
line.  Samples will be labeled with a study identification number.  They will be 
stored in a 2-8oC degree refrigerator at WUSM.  Samples will then be transported 
weekly by a study team member for extraction and stored in a -80oC freezer at 
Gateway Biotechnology’s lab. 
 
 
 
6.0 EVALUABILITY 
 
All participants are evaluable for the primary outcome – the proportion of patients who are 
PTS positive as defined by the ratio of the number of participants with > 10 dB increase in 
PTS to the total number of participants tested 30 days (+/- 3 days) post-surgery – provided 
they have had the assigned study dose and undergone the post-op study assessments. 
 
Participants who receive the study medication are evaluable for toxicity related to the drug.  
Participants are evaluated from the time of dose administration through two weeks post 
dose for drug related adverse events. 


19 | P a g e  
 
 
The participant will be withdrawn from the study if: 
• Participant withdraws consent 
• Investigator removes the participant from study 
• The Sponsor decides to close the study 
 
 
7.0 
PHARMACEUTICAL INFORMATION 
 
7.1 
Zonisamide (ZONEGRAN®) 
 
7.1.1 Zonisamide Description 
 
 
 
 
 
Molecular formula: C8H8N2O3S 
 
Molecular weight: 212.23 
 
 
 
7.1.2 Clinical Pharmacology 
 
The precise mechanism(s) by which ZNS exerts its antiseizure effect is 
unknown. ZNS may produce these effects through action at sodium and 
calcium channels. In vitro pharmacological studies suggest that ZNS blocks 
sodium channels and reduces voltage-dependent, transient inward currents (T-
type Ca2+ currents), consequently stabilizing neuronal membranes and 
suppressing neuronal hypersynchronization.  Additional information can be 
found in the package insert. 
 
7.1.3 Supplier 
 
 
 
 
ZNS will be supplied through Advanced Rx (Fort Washington, PA). 
 
7.1.4 Dosage Form and Preparation 
 
ZONEGRAN® is commercially available for oral administration as 
capsules containing 25 mg, 50 mg, or 100 mg of ZNS. 
 
Each 100 mg capsule contains the labeled amount of ZNS plus the following 
inactive ingredients: microcrystalline cellulose, hydrogenated vegetable oil, 
gelatin, and titanium dioxide. 
 
7.1.5 Storage and Stability 
 
Store at 25◦C (77◦F), excursions permitted to 15–30◦C (59–86◦F), in a dry 
place and protected from light. 
 
7.1.6 Administration 
 


20 | P a g e  
 
For subjects randomized to “ZNS pre-op”, the pre-op package will contain 
ZNS capsules (100 mg) and the post-op package will contain placebo 
capsules that look and taste the same as ZNS capsules. For subjects 
randomized to “ZNS post-op”, the pre-op package will contain placebo and 
the post-op package will contain ZNS (100 mg). For the subjects 
randomized to “placebo”, both pre- and post-op packages will contain 
placebo. Participants will be instructed to take zonisamide without food. We 
will recommend that capsules be swallowed whole per the current approved 
labeling. 
  
 
7.1.7 Side Effects 
 
Potential side effects from the administration of ZNS: 
• Somnolence 
• Anorexia 
• Dizziness 
• Ataxia 
• Agitation/irritability 
• Difficulty with memory and/or concentration   
 
ZNS may cause serious side effects, including: 
• Serious skin rash that can cause death. 
• Serious allergic reactions that may affect different parts of the body. 
• Less sweating and increase in body temperature (fever). 
• Suicidal thoughts or actions in some people. 
• Increased level of acid in blood (metabolic acidosis). 
• Problems with concentration, attention, memory, thinking, speech, 
or language. 
• Blood cell changes such as reduced red and white blood cell counts. 
 
7.2 
Placebo 
 
The placebo will contain microcrystalline cellulose which is the predominant 
filler in the generic capsule.  
 
 
8.0 
REGULATORY AND REPORTING REQUIREMENTS 
 
The entities providing oversight of safety and compliance with the protocol require 
reporting as outline below.  Please refer to Appendix A for definitions and Appendix B for 
a grid of reporting timelines. 
 
Adverse events will be tracked for the WU site from the time of dose administration through 
two weeks post dose and at the follow up 30 day visit for drug-related adverse events.  All 
adverse events will be documented and assessed for relatedness to the study medication. 


21 | P a g e  
 
 
The study team will monitor for adverse events on an ongoing basis. Once the team becomes 
aware of an adverse event, the AE will be reported according to institutional guidelines. 
Reporting requirements for Washington University study team may be found in Section 8.1.  
Reporting requirements for secondary site study teams participating in Washington 
University-coordinated research may be found in Section 8.2. 
 
In the event of a Serious Adverse Event determined by the PI to necessitate the breaking 
of the blind, the intervention assignment will be revealed by the independent programmer 
to the medical staff doctor caring for the patient. In the event the statistician is unable to 
be reached in a time needed, to assure the safety of the subject, the blind can be broken by 
Sara Kukuljan, RN and information will be shared with the medical staff assuming care 
for the research subject. 
 
 
8.1 Sponsor-Investigator Reporting Requirements 
 
8.1.1 Reporting to the Human Research Protection Office (HRPO) 
at Washington University 
 
Reporting will be conducted in accordance with Washington University 
IRB Policies. 
 
Pre-approval of all protocol exceptions must be obtained prior to 
implementing the change 
 
8.1.2 Reporting to the FDA 
 
The conduct of the study will comply with all FDA safety reporting 
requirements.  It is the responsibility of the Washington University principal 
investigator to report to the FDA as follows: 
 
• Report any unexpected fatal or life-threatening suspected adverse 
reaction (refer to Appendix A for definitions) no later than 7 
calendar days after initial receipt of the information.   
• Report a suspected adverse reaction that is both serious and 
unexpected (SUSAR, refer to Appendix A) no later than 15 
calendar days after it is determined that the information qualifies 
for reporting.  Report an adverse event (refer to Appendix A) as a 
suspected adverse reaction only if there is evidence to suggest a 
causal relationship between the drug and the adverse event, such as: 
o A single occurrence of an event that is uncommon and known 
to be strongly associated with drug exposure 
o One or more occurrences of an event that is not commonly 
associated with drug exposure but is otherwise uncommon in 
the population exposed to the drug 


22 | P a g e  
 
o An aggregate analysis of specific events observed in a clinical 
trial that indicates those events occur more frequently in the 
drug treatment group than in a concurrent or historical control 
group 
• Report any findings from epidemiological studies, pooled analysis 
of multiple studies, or clinical studies that suggest a significant risk 
in humans exposed to the drug no later than 15 calendar days after 
it is determined that the information qualifies for reporting. 
• Report any findings from animal or in vitro testing that suggest 
significant risk in humans exposed to the drug no later than 15 
calendar days after it is determined that the information qualifies 
for reporting.  
• Report any clinically important increase in the rate of a serious 
suspected adverse reaction of that listed in the protocol or IB within 
15 calendar days after it is determined that the information qualifies 
for reporting. 
 
Submit each report as an IND safety report in a narrative format or on FDA 
Form 3500A or in an electronic format that FDA can process, review, and 
archive.   
 
Each notification to FDA must bear prominent identification of its contents 
(“IND Safety Report”) and must be transmitted to the review division in the 
Center for Drug Evaluation and Research (CDER) or in the Center for 
Biologics Evaluation and Research (CBER) that has responsibility for 
review of the IND.  Relevant follow-up information to an IND safety report 
must be submitted as soon as the information is available and must be 
identified as such (“Follow-up IND Safety Report”). 
 
 
 
 
8.1.3 Reporting to Secondary Sites 
 
The Washington University Sponsor-Investigator will notify the research 
team at the secondary site of all unanticipated problems involving risks to 
participants or others that have occurred at other sites within 10 working 
days of the occurrence of the event or notification of the Sponsor-
Investigator of the event.  This includes events that take place both at 
Washington University and at other site, if applicable. 
 
 
8.2 
Secondary Site Reporting Requirements  
 
The research team at each secondary site is required to promptly notify the 
Washington University Sponsor-Investigator of all serious adverse events (refer to 
Appendix A, Section D) within 1 working day of the occurrence of the event or 
notification of the secondary site’s PI of the event.  This notification may take place 


23 | P a g e  
 
via email if there is not yet enough information for a formal written report (using 
FDA Form 3500a (MedWatch) and Washington University’s cover sheet 
(Appendix C).  A formal written report must be sent to the Washington University 
Sponsor-Investigator and designee within 4 calendar days (for fatal or life-
threatening suspected adverse reactions) or 11 calendar days (for serious 
unexpected suspected adverse reactions) of the occurrence of the event or 
notification of the secondary site’s PI of the event. 
 
The research team at the secondary site is responsible for following its site’s 
guidelines for reporting applicable events to its site’s IRB according to its own 
institutional guidelines.  The research team at Washington University is responsible 
for reporting all applicable events to the FDA as needed. 
 
Washington University pre-approval of all protocol exceptions must be obtained 
prior to implementing the change.  Local IRB approval must be obtained as per local 
guidelines.  Washington University IRB approval is not required for protocol 
exceptions occurring at secondary sites. 
 
8.3 
Exceptions to Expedited Reporting  
 
Events that do not require expedited reporting as described in Section 1.1 include: 
• planned hospitalizations 
• hospitalizations < 24 hours 
• respite care 
• events related to disease progression 
 
Events that do not require expedited reporting must still be captured in the EDC. 
 
 
 


24 | P a g e  
 
 
9.0 
STUDY CALENDAR 
 
 
Screening / 
Baseline 
Surgery 
Post-op 
 
 
Within 30 days 
(+3 days) prior to 
surgery  
 
Within 12 
Hours 
30 days  
(+/- 3 days) 
Informed consent 
X 
 
 
 
Clinical Exam 
X 
 
 
 
Demographic Info 
X 
 
 
 
Pre-Op Data 
(pregnancy test, lab 
results (electrolyte 
panel, BUN, Cr, 
ALT, and AST)) 
X 
 
 
 
Current Meds 
X 
 
 
 
Questionnaire 
X 
 
 
X 
Audiogram 
X 
 
 
X 
ECochG 
X 
 
 
X 
DPOAE 
X 
 
X* 
X 
WIN 
X 
 
 
X 
Randomization 
X 
 
 
 
Oral Dose** 
 
X 
X 
 
Blood draw*** 
X 
 
X 
 
AE assessment 
 
X 
X 
X 
* Within 8 hours 
** Dispensed on the day of surgery with instruction to take first dose prior to surgery and second 
dose after surgery.  
*** Plasma sample for PGx will be collected at baseline visit. Plasma sample for ZNS level, PGx, 
electrolyte panel, BUN, Cr, ALT, and AST will be collected within 12 hours after first dose. 
 
 
10.0 
DATA SUBMISSION SCHEDULE 
 
Case report forms with appropriate source documentation will be completed according to 
the schedule listed in this section. 
 
Case Report Form 
Submission Schedule 
Original Consent Form 
Prior to study activities 
Eligibility Form 
At time of consent; Prior to surgery 
Screening/Baseline 
Prior to surgery 
Surgery/Post-Op Form 
Post-Op (within 12 hours) 
Post-Op 
Post-Op (30 days (+/- 3 days) 
Adverse Event Form 
Continuous 
 


25 | P a g e  
 
 
11.0 
DATA AND SAFETY MONITORING 
 
In compliance with the Washington University Institutional Data and Safety Monitoring 
Plan, an independent Data and Safety Monitoring Board (DSMB) will be specifically 
convened for this trial to review toxicity data.  A DSMB will consist of no fewer than 3 
members including 2 clinical investigators and a biostatistician.  Individuals invited to serve 
on the DSMB will disclose any potential conflicts of interest to the trial principal 
investigator and/or appropriate university officials, in accordance with institution policies.  
Potential conflicts that develop during a trial or a member’s tenure on a DSMB must also 
be disclosed.  
 
The DSM report for the DSMB will be prepared by the study team with assistance from the 
study statistician, will be reviewed by the DSMB, and will be submitted to the PI. The DSM 
report will be prepared for the DSMB semi-annually and at other times at the discretion of 
the DSMB. The DSMB must meet at least every six months beginning six months after 
enrollment of the first participant at the secondary site, no more than one month prior to the 
due date of the DSM report to the PI.  This report will include: 
 
• HRPO protocol number, protocol title, Principal Investigator name, data coordinator 
name, regulatory coordinator name, and statistician 
• Date of initial HRPO approval, date of most recent consent HRPO 
approval/revision, date of HRPO expiration, date of most recent QA audit, study 
status, and phase of study 
• History of study including summary of substantive amendments; summary of 
accrual suspensions including start/stop dates and reason; and summary of protocol 
exceptions, error, or breach of confidentiality including start/stop dates and reason 
• Study-wide target accrual and study-wide actual accrual  
• Protocol activation date at each participating site 
• Average rate of accrual observed in year 1, year 2, and subsequent years at each 
participating site 
• Expected accrual end date, accrual by site, and accrual by cohort 
• Objectives of protocol with supporting data and list the number of participants who 
have met each objective 
• Measures of efficacy  
• Early stopping rules with supporting data and list the number of participants who 
have met the early stopping rules 
• Power analysis and/or interim analysis (if described in the protocol) 
• Summary of toxicities  
• Abstract submissions/publications 
• Summary of any recent literature that may affect the safety or ethics of the study 
 
The study principal investigator and coordinator will monitor for serious toxicities on an 
ongoing basis. Once the principal investigator or coordinator becomes aware of an adverse 
event, the AE will be reported to the HRPO according to institutional guidelines (please 
refer to Section 1.0). 


26 | P a g e  
 
 
11.1 
Adverse Event Collection in the Case Report Forms 
 
All adverse events that occur beginning with start of treatment must be captured in the AE 
Form.   
 
 
 
 
12.0 
STATISTICAL CONSIDERATIONS 
 
12.1 
Data Analysis 
 
Data will be analyzed using an intention-to-treat principle with patients analyzed in 
the groups they were randomized to. The primary outcome measure for assessing 
effectiveness of ZNS (100 mg PO) pre-op will be the proportion of subjects in the 
pre-op arm experiencing PTS as compared to the control group. The primary 
outcome measure for assessing effectiveness of post-op ZNS (100 mg PO) will be 
the proportion of subjects in the “post-op” arm experiencing PTS as compared to 
the control group. The secondary outcome measures are key audiological and 
clinical assessments of hearing loss. OAE shift will be a secondary outcome 
measure and an early indicator of changes in cochlear health and PTS. 
 
Standard descriptive statistics will be used to describe distribution of demographic, 
clinical and audiometric characteristics as well as outcome measures for each study 
group. For continuous level characteristics Q-Q plots and Shapiro-Wilk test will be 
used to test assumption of normality. For normally distributed data, mean and 
standard deviation will be used as descriptive stats of continuous level variables, 
and if the assumption of normality is violated we will report median and range for 
description of variables. Frequency and relative frequency will be used for 
description of categorical level variables.  
 
12.2 
Efficacy analysis 
 
12.2.1 Analysis of primary outcome variable 
 
 
Efficacy analysis at the end of the study 
 
The primary outcome measure for assessing effectiveness of ZNS (100 mg 
PO) either pre-op or post-op compared to the placebo group will be the 
proportion of subjects defined as PTS positive 30 days (+/-3 days) after 
surgery.  
  
Audiogram will be performed to look for PTS. Patients for whom the 
difference at any frequency from 2-6 kHz in hearing thresholds (30 days 
(+/-3 days) post-surgery - Baseline) is ≥10 dB HL will be defined as PTS 


27 | P a g e  
 
positive. Primary analysis and sensitivity analyses will be carried out on the 
primary endpoint. 
 
 
Primary analysis. 
 
Frequency and relative frequency will be used to describe the distribution 
of the primary outcome measure in each study group. To assess efficacy, 
Fisher’s exact test will be used to compare the proportion of subjects with 
PTS positive in ZNS group with the proportion of patients with PTS positive 
in the placebo group.  
 
To provide an estimate of treatment effect a supportive logistic regression 
analysis will be done with covariates: age, pre-op hearing dichotomized to 
normal to minimal hearing loss and slight to mild loss, noise exposure 
history dichotomized to high risk and low risk, exposure categorized as low 
(8-hour equivalent A-weighted sound level in decibel (LAeq8hr) < 80 
dBA), moderate (LAeq8hr > 80 dBA but < 90 dBA), or high (LAeq8hr > 
90 dBA). 
  
 
Sensitivity analysis of the primary endpoint 
 
The potential impact of missing primary endpoint data will be explored in 
sensitivity analyses using multiple imputation.  Two sensitivity analyses 
performed: 
 
Sensitivity 1: MI analysis under the missing not at random assumption 
(MNAR) 
Sensitivity 2: Logistic regression tipping point analysis under the 
assumption of data missing at random. 
 
 
 
Sensitivity 1. 
Proc MI procedure in SAS will be used to impute missing data for study 
treatment groups using the distribution implied by the non-missing patient 
data within the placebo group. The SAS code to impute data for Sensitivity 
analysis 1 under the MNAR assumption will be of the form: 
 
PROC MI DATA=X SEED=<value> NIMPUTE=10  OUT=MI_OUT1 NOPRINT; 
CLASS  GROUP; 
VAR AGE PTA LSurg………; 
FCS LOGISTIC(PTS);  
RUN; 
 
Post imputation each of the imputed 10 datasets will be analyzed using the 
same approach as for the primary outcome measure. The estimates of the 
analysis of the 10 imputed datasets will be then combined following 
Rubin’s rules using PROC MIANALYZE procedure in SAS which will be 
of the form:  


28 | P a g e  
 
 
PROC MIANALYZE PARMS=GMPARMS COVB=GMCOVB PARMINFO=GMPINFO WCOV 
BCOV 
TCOV; / *dataset "gmparms" contains the estimates and 
associated standard errors for the mean parameters from each of 
the M=10 imputed data sets. 
dataset "gmcovb" contains the asymptotic covariance matrics 
dataset "gmpinfo" contains parameter info*/ 
 
    MODELEFFECTS INTERCEPT AGE PTA LSurg………; 
RUN; 
 
 
Sensitivity 2. 
 
Multiple imputation will be used to impute data in each of the study groups. 
A progressive penalty of 𝛿𝛿𝑖𝑖= 𝑘𝑘𝑖𝑖× log (𝑂𝑂𝑂𝑂) will be added to imputed 
values in ZNS arm where (i) 𝑂𝑂𝑂𝑂 is the Odds ratio estimate for ZNS as 
compared to Placebo from the primary logistic regression analysis and (ii)  
𝑘𝑘𝑖𝑖= 1, 0.95, 0.90, … 0.05, 0, 1.05, 1.10,… thus k ranges from 1 (equivalent 
to MI approach based on MAR) to 0 (or higher), until the conclusion of the 
primary analysis is overturned (i.e., p<0.05 is lost at, this value of 𝑘𝑘𝑖𝑖 being 
the ‘tipping point’). Rubin’s method will be used to combine the primary 
endpoint treatment effects across imputations for each value, 𝑘𝑘𝑖𝑖, of the 
penalty.  Forest plots will be used to graphically display the penalty value 
that results in loss of statistical significance.  
 
 
SAS code sample for Sensitivity analysis is provided below: 
**Step 1: Generate 10  datasets by imputing the missing data**; 
 
PROC MI DATA=X SEED=<value> NIMPUTE=10  OUT=MI_OUT1 NOPRINT; 
CLASS  GROUP; 
VAR AGE PTA LSurg………; 
FCS LOGISTIC(PTS);  
RUN; 
 
**Step 2: Generate 10 complete datasets from the 10 monotonized 
datasetsin Step 1 for missing values in the drug arm,  
subtract DELTA derived above from their imputed data.**; 
proc mi data=YYY NIMPUTE=1 SEED=<value> OUT=YYY_shift; 
by group; 
class group; 
var AGE PTA LSurg………; 
monotone method=logistic; 
mnar adjust(PTS / shift=DELTA adjustobs=(group=’1’)); 
run; 
 
**Step 3: Apply the primary MMRM to the 10 complete datasets in S
 
tep 2**; 
proc genmod data=YYY_shift descending; 
by _imputation_; 
class group; 
model PTS = group AGE PTA LSurg………; 
ods output GEEModPEst=gmparms; 
run; 
 
 
 


29 | P a g e  
 
 
**Step 4: Obtain the pooled inference from 10 sets of estimates 
from Step 3**; 
 
 
 
 
PROC MIANALYZE PARMS=GMPARMS COVB=GMCOVB PARMINFO=GMPINFO WCOV 
BCOV 
    TCOV;  
    MODELEFFECTS group; 
RUN; 
 
12.2.2 Analysis for secondary outcome measures. 
 
The focus of the study is to determine efficacy of ZNS for treatment of acute 
hearing loss based on the testing of hypothesis for primary outcome. In 
addition, we will also conduct analysis to evaluate other important 
audiologic measures. The secondary outcome measures are key 
audiological and clinical assessments of change in cochlear function and 
hearing loss: DPOAEs, ECochG, WIN testing. They will be measured as 
continuous level variables.  We do not plan any adjustment of alpha error 
for multiple comparisons. 
  
Analysis of variance (ANCOVA) will be used for comparison of outcome 
measures between each of the ZNS groups and placebo study group after 
controlling for baseline value and age, age, pre-op hearing dichotomized to 
normal to minimal hearing loss and slight to mild loss, noise exposure 
history dichotomized to high risk and low risk, exposure categorized as low 
(LAeq8hr < 80 dBA), moderate (LAeq8hr > 80 dBA but < 90 dBA), or high 
(LAeq8hr > 90 dBA). 
 
Statistical analyses will be conducted using the SAS software (SAS Institute Inc., 
Cary, N.C., USA). 
 
Missing Data 
Every attempt will be made to ensure data completeness. We do not anticipate 
much loss to follow-up because of the relatively short time follow-up interval. 
Conservatively, we would estimate that fewer than 5% of subjects will drop 
out/withdraw from the study. The participant will be withdrawn from the study 
follow-up procedures if the participant withdraws consent, or the sponsor decides 
to close the study. 
 
If any, the loss of data would almost certainly be due to the fact that the subjects 
refused to complete or did not show up for the assessment of PTS 30 days (+/- 3 
days) after the surgery. If the participants reschedules the post-surgery 
appointment for a later date for any reason, and if this delay is within 30 days of 
the scheduled date, the data will be considered valid and used in the efficacy 
analysis. Any measure outside this time window of +30 days will be defined and 
considered missing data. 
 


30 | P a g e  
 
Missing PTS at 30 days will be imputed using SAS PROC MI procedure within 
each treatment group using the distribution implied by the non-missing data for 
the specific treatment group.  
 
The SAS code below using MICE via the Fully Conditional Specification (FCS) 
statement will be used to impute the missing data under the missing at random 
(MAR) assumption.  
 
PROC MI DATA=X SEED=<value> NIMPUTE=10  OUT=MI_OUT1 NOPRINT; 
CLASS  GROUP; 
VAR AGE PTA LSurg………; 
FCS LOGISTIC(PTS);  
RUN; 
 
The estimates of the analysis of the 10 imputed datasets will be then combined 
following Rubin’s rules using PROC MIANALYZE procedure in SAS which will 
be of the form:  
PROC MIANALYZE PARMS=GMPARMS COVB=GMCOVB PARMINFO=GMPINFO WCOV BCOV 
TCOV; / *dataset "gmparms" contains the estimates and associated 
standard errors for the mean parameters from each of the M=10 imputed 
data sets. 
dataset "gmcovb" contains the asymptotic covariance matrics 
dataset "gmpinfo" contains parameter info*/ 
 
    MODELEFFECTS group; 
RUN; 
 
 
12.3 
Sample Size Estimation 
 
 
 
Sample size estimation for primary outcome measure. 
 
The primary efficacy outcome will be the proportion of PTS positive subjects 
defined as the ratio of PTS-positive subjects to total number of subjects in each 
study arm/group. Using pilot data from a retrospective chart review of 75 similar 
patients undergoing >1-hour drill noise exposure, we estimate the proportion of 
PTS positive subjects in the placebo group will be 50%. We hypothesize that the 
expected effect of ZNS either pre-op or post-op will be a 50% reduction of the 
proportion of subjects with PTS positive as compared to placebo group. This is the 
desired clinically import effect for treating hearing loss for single dose of 100 mg 
ZNS. 
 
The sample size for this study was calculated for the planned comparisons of each 
of the ZNS groups with the placebo group using a balanced design and a one-
sided alpha level of 0.0125.  
 
Based on the data from our retrospective study, using Fisher’s exact test, we 
estimated that 78 subjects in the ZNS group and 78 subjects in the placebo group 
will be needed to provide us with 80.4 % power to detect a 50% reduction in the 
proportion of PTS positive subjects (from 50% to 25% corresponding to an 


31 | P a g e  
 
absolute proportion difference of 25%) at the 1-sided alpha level of 0.0125 for 
each ZNS-Placebo group comparison.  Our one-sided hypothesis is supported by 
animal studies, and lack of any evidence of hearing loss as a side effect of ZNS in 
human studies. A total of 234 subjects will be enrolled to be randomized in this 
study. We will make all the needed effort to minimize and eliminate drop outs, 
and due to short term-follow-up of the study subjects in a period where they are 
under medical care, we do not expect any drop-outs or lost to follow-up.  
 
All sample size calculations were carried out using PROC POWER procedure in 
SAS 9.4. 
 
 
 
 
12.4  Interim Analysis 
 
A sponsor blinded interim analysis focused on the primary endpoint after 33% of 
the patients have completed participation in the study (26 in each group).  The 
independent programmer will prepare the datasets for each pairwise comparison 
(subsets of data) using a pre-prepared SAS code and will freeze them for the 
interim analysis. To ensure the double blinding of the study the subjects will not 
be presented in the assigned groups. The blinded statistician will estimate the 
overall proportion of PTS positive subjects in each group.  
 
 
For each pair-wise comparison, with 33% information, the trial would be stopped 
for futility if the interim z-value <= 0.6850 (p=0.49 2-sided) for either or both 
comparisons, corresponding to a conditional power of ≤10% for each comparison. 
This design would provide 79.6% overall power (i.e. the probability of passing 
futility and reaching p<0.0125 for one or both comparisons in the final analysis 
would be 79.6%). 
 
 
 
Based on interim analysis the following actions may be taken: 
• Stop only one of the ZNS groups for futility 
• Stop the trial (both ZNS groups) for futility 
• Continue the trial as planned. 
 
Early stopping rules related to serious adverse events: In the event of a serious 
adverse event, DSMB will evaluate the association of the serious adverse events 
with the study arm, break the blind if needed, and if found to be associated with 
treatment, DSMB will consider the study for revision or stopping.  
Serious feasibility or design difficulties: If one year after the start of the trial, 
<50% of the planned accrual goals are met, DSM and the study team will discuss 
difficulties in recruitment. Patient remuneration will be revised, if needed. If there 
are not enough patients meeting inclusion/exclusion criteria, then the criteria will 
be revised without impacting study objectives. If there are not enough patients 
that undergo more than 1-hr drilling time during surgery, we will explore 


32 | P a g e  
 
including into the study, patients with drilling time at least 45 minutes, expanding 
audiometric criteria, or expanding to different institutions. 
The overall timing associated with the study is based on our previous clinical study 
experience.  Approximately 50 patients per year receive skull surgery that requires 
1 hour or more of drilling time at WUSM.  Accounting for participant attrition, we 
plan to finish the study within 4 years.  If participant enrollment numbers are 
consistently below expectations as determined by the study team and DSMC, plans 
will be made to add additional sites or adjust study inclusion criteria (e.g. including 
head/skull surgeries requiring less than 1 hour of drilling time). 
 
 
12.5  Pharmacogenetics analysis plan 
 
This analysis will be performed at the end of the trial by Gateway Biotechnology.  
To identify genetic variants with ZNS protection against hearing loss, we will first 
use univariate logistic regression analyses to identify potential confounding 
variables: sex, age, Z-scores of drug concentration, Z-scores of noise intensity and 
duration, and Z-scores of hearing functions measure immediately following 
surgery. Single-marker allelic association analyses will be conducted on the two 
imputed data sets in PLINK v1.07. The data will be analyzed with a logistic 
regression model on the additive continuous dosage of minor alleles from 0 to 2 to 
account for uncertainty of imputation. We will combine association results in the 
two cohorts by performing a genome-wide inverse-variance weighting meta-
analysis using PLINK v1.07, and assuming a fixed-effect model. Functional 
annotation of top-associated markers will be performed with R package NCBI2R 
1.4.6 (http://CRAN.Rproject. org/package=NCBI2R), and key regional association 
plots of meta-analyzed results will be generated. To confirm whether these variants 
are specific to ZNS response, we will apply CEP SKAT to analyze genetic 
associations based on Z-scores of audiogram average threshold shifts and DPOAE 
amplitudes. All genetic variants, including both common and rare variants, will be 
included in this association study. Age, gender, and noise duration and intensity 
will be adjusted for the analysis. The analysis will also be performed using hearing 
data collected two weeks following surgery. The only differences will be a) using 
the Z scores of ECochG AP amplitude, latency, and width as well as WIN score, 
and b) using average audiogram threshold shifts and DPOAE amplitudes at 30 days 
post-treatment. We will also include metabolite profiling data to support potential 
genotypic responses to drug treatments. To control for confounding effects, these 
models will be adjusted for age, gender, and noise duration and intensity. Finally, 
the control and ZNS-treated comparisons will be performed using post-hoc 
comparisons with a Bonferroni adjustment for multiple comparisons of any ZNS 
versus none. Statistical analyses will be performed using the CEP-SKAT method 
in R language, and the statistical software SAS version 9.4 for Windows will be 
used for additional analysis. 
 


33 | P a g e  
 
 
13.0 
REFERENCES 
 
1. 
Abtahi SH, Fazel A, Rogha M, Nilforoush M, Solooki R. Effect of drill-induced 
noise on hearing in nonoperated ear. Adv Biomed Res. 2016. 11;5:87. 
2. 
Adamson CL, Reid MA, Davis RL. Opposite actions of brain-derived neurotrophic 
factor and neurotrophin-3 on firing features and ion channel composition of murine 
spiral ganglion neurons. J Neurosci. 2002.22(4):1385-96. 
3. 
Ahn H, Fehlings MG. Prevention, identification, and treatment of perioperative 
spinal cord injury. Neurosurg Focus. 2008. 25(5):E15. 
4. 
Bao J, Hungerford M, Luxmore R, Ding D, Qiu Z, Lei D, Yang A, Liang R, 
Ohlemiller KK. Prophylactic and therapeutic functions of drug combinations 
against noise-induced hearing loss. Hear Res. 2013. 304:33-40. 
5. 
Bielefeld EC, Kopke RD, Jackson RL, Coleman JK, Liu J, Henderson D. Noise 
protection with N-acetyll-cysteine (NAC) using a variety of noise exposures, NAC 
doses, and routes of administration. Acta Otolaryngol. 2007. 127(9):914-9. 
6. 
Bohne BA. In: Henderson D, Hamernik RP, Mills JH, Dosanjh DS Eds. Mechanisms 
of noise damage in the inner ear. In Effects of Noise on Hearing. NY, Raven Press, 
1976. 41-68. 
7. 
Bramhall NF, Konrad-Martin D, McMillan GP, Griest, SE. Auditory brainstem 
response altered in humans with noise exposure despite normal outer hair cell 
function. Ear Hear. 2017. 
8. 
Brodie MJ, Ben-Menachem E, Chouette I, Giorgi L. Zonisamide: its pharmacology, 
efficacy and safety in clinical trials. Acta Neurol Scand Suppl. 2012. 194:19-28. 
9. 
Cacace AT, Silver SM, Farber M. Rapid recovery from acoustic trauma: chicken 
soup, potato knish, or drug interaction? Am J Otolaryngol. 2003 24(3):198-203. 
10. 
Campbell KC, Meech RP, Klemens JJ, Gerberi MT, Dyrstad SS, Larsen DL, 
Mitchell DL, El-Azizi M, Verhulst SJ, Hughes LF. Prevention of noise- and drug-
induced hearing loss with D-methionine. Hear Res. 2007. 226(1-2):92-103. 
11. 
Canlon B, Meltser I, Johansson P, Tahera Y. Glucocorticoid receptors modulate 
auditory sensitivity to acoustic trauma. Hear Res. 2007. 226(1-2):61-9. 
12. 
Casto KL, Casali JG. Effects of headset, flight workload, hearing ability, and 
communications message quality on pilot performance. Hum Factors. 2013 
Jun;55(3):486-98.13. Hinni ML, Zarka MA, Hoxworth JM. Margin mapping in 
transoral surgery for head and neck cancer. Laryngoscope. May 2013;123(5):1190-
1198. 
14. 
Chen, L. Brueck, S. Noise and Lead Exposures at an Outdoor Firing Range 
California. Health Hazard Evaluation Report. 2011. HETA 2011-0069-3140. 
15. 
Chen FQ, Zheng HW, Hill K, Sha SH. Traumatic noise activates Rho-family 
GTPases through transient cellular energy depletion. J Neurosci. 2012. 
32(36):12421-30. 
16. 
Chen J, Yuan H, Talaska AE, Hill K, Sha SH. Increased Sensitivity to Noise-Induced 
Hearing Loss by Blockade of Endogenous PI3K/Akt Signaling. J Assoc Res 
Otolaryngol. 2015. 16(3):347-56. 


34 | P a g e  
 
17. 
Clifford, R E, Hoffer, M, Rogers, R. The Genomic Basis of Noise-induced Hearing 
Loss: A Literature Review Organized by Cellular Pathways. Otology & 
Neurotology. 2016. Volume 37 - Issue 8 - p e309–e316 
18. 
Davis RR, Kozel P, Erway LC. Genetic influences in individual susceptibility to 
noise: a review. Noise Health. 2003. 5(20):19-28. 
19. 
Darrat I, Ahmad N, Seidman K, Seidman MD. Auditory research involving 
antioxidants. Curr Opin Otolaryngol Head Neck Surg. 2007. 15(5):358-63. 
20. 
Dodson, K.M., Sismanis, A. Intratympanic perfusion for the treatment of tinnitus. 
Otolaryngol Clin North Am. 2004. 37:991-1000. 
21. 
Dodson, K.M., Woodson, E., Sismanis, A. Intratympanic steroid perfusion for the 
treatment of Meniere's disease: a retrospective study. Ear Nose Throat J. 2004. 
83:394-8. 
22. 
Du X, Chen K, Choi CH, Li W, Cheng W, Stewart C, Hu N, Floyd RA, Kopke RD. 
Selective degeneration of synapses in the dorsal cochlear nucleus of chinchilla 
following acoustic trauma and effects of antioxidant treatment. Hear Res. 2012. 
283(1-2):1-13. 
23. 
Earl BR, Chertoff ME. Mapping auditory nerve firing density using high-level 
compound action potentials and high-pass noise masking. J Acoust Soc Am. 2012. 
131(1):337-52. 
24. 
Esterberg R, Hailey DW, Coffin AB, Raible DW, Rubel EW. Disruption of 
Intracellular Calcium Regulation Is Integral to Aminoglycoside-Induced Hair Cell 
Death. 2013. Journal of Neuroscience. 33 (17) 7513-25. 
25. 
Fausti SA, Wilmington DJ, Gallun FJ, Myers PJ, Henry JA. Auditory and vestibular 
dysfunction associated with blast-related traumatic brain injury. J Rehabil Res Dev. 
2009;46(6):797-810. 
26. 
Fernandez KA, Jeffers PW, Lall K, Liberman MC, Kujawa SG. Aging after noise 
exposure: acceleration of cochlear synaptopathy in "recovered" ears. J Neurosci. 
2015. 35(19):7509-20. 
27. 
Frisina DR, Frisina RD. Speech recognition in noise and presbycusis: relations to 
possible neural mechanisms. Hear Res. 1997. 106(1-2):95-104. 
28. 
Fuchs P. The synaptic physiology of cochlear hair cells. Audiol Neurootol. 2002. 
7(1):40-4.  
29. 
Gould AL. Interim analyses for monitoring clinical trials that do not materially 
affect the type I error rate. Statistics in medicine. 1992;11(1):55-66. 
30. 
Gould AL. Sample size re‐estimation: recent developments and practical 
considerations. Statistics in Medicine. 2001 Sep 15;20(17‐18):2625-43. 
31. 
Gould AL, Shih WJ. Modifying the design of ongoing trials without unblinding. 
Statistics in Medicine. 1998 Jan 15;17(1):89-100. 
32. 
Griffith SG, Dai Y. Effect of zonisamide on the pharmacokinetics and 
pharmacodynamics of a combination ethinyl estradiol-norethindrone oral 
contraceptive in healthy women. Clin Ther. 2004. 26(12):2056-65. 
33. 
Groth JB, Kao SY, Briët MC, Stankovic KM. Hepatocyte nuclear factor-4 alpha in 
noise-induced cochlear neuropathy. 2016. Dev Neurobiol. 2016 Dec;76(12):1374-
1386. 


35 | P a g e  
 
34. 
Gubata ME, Packnett ER, Feng X, Cowan DN, Niebuhr DW. Pre-enlistment hearing 
loss and hearing loss disability among US soldiers and marines. Noise Health. 2013. 
15(66):289-95. 
35. 
Guitton MJ, Wang J, Puel JL. New pharmacological strategies to restore hearing 
and treat tinnitus. Acta Otolaryngol. 2004.124(4):411-5. 
36. 
Gupta D, Gulati A, Gupta U. Impact of socio-economic status on ear health and 
behaviour in children: A cross-sectional study in the capital of India. Int J Pediatr 
Otorhinolaryngol. 2015. 79(11):1842-50. 
37. 
Goyal, A., Singh, P., & Vashishth, A. Effect of mastoid drilling on hearing of the 
contralateral ear. 2013. The Journal of Laryngology & Otology. 127(10), 952-956. 
38. 
Hallmo P1, Mair IW. Drilling in ear surgery. A comparison of pre- and postoperative 
bone-conduction thresholds in both the conventional and extended high-frequency 
ranges. Scand Audiol. 1996. 25(1):35-8. 
39. 
Han Y, Wang X, Chen J, Sha SH. Noise-induced cochlear F-actin depolymerization 
is mediated via ROCK2/p-ERM signaling. J Neurochem. 2015. 133(5):617-28. 
40. 
Harding GW, Bohne BA. Distribution of focal lesions in the chinchilla organ of 
Corti following exposure to a 4-kHz or a 0.5-kHz octave band of noise. Hear Res. 
2007 254(1-2):54-63. 
41. 
Hashimoto Y, Odani A, Tanigawara Y, Yasuhara M, Okuno T, Hori R. Population 
analysis of the dosedependent pharmacokinetics of zonisamide in epileptic patients. 
Biol Pharm Bull. 1994. 17(2):323-6. 
42. 
Hayball PJ, Cosh DG, Ahern MJ, Schultz DW, Roberts-Thomson PJ. High dose oral 
methylprednisolone in patients with rheumatoid arthritis: pharmacokinetics and 
clinical response. Eur J Clin Pharmacol. 1992. 42(1):85-8. 
43. 
Helfer TM, Jordan NN, Lee RB, Pietrusiak P, Cave K, Schairer K. Noise-induced 
hearing injury and comorbidities among postdeployment U.S. Army soldiers: April 
2003-June 2009. Am J Audiol. 2011. Jun;20(1):33-41. 
44. 
Henderson D, Bielefeld EC, Harris KC, Hu BH. The role of oxidative stress in noise-
induced hearing loss. Ear Hear. 2006. 27(1):1-19. 
45. 
Henry, K.R. Noise-induced auditory loss: influence of genotype, naloxone and 
methyl-prednisolone. Acta Otolaryngol. 1992. 112:599-603. 
46. 
Hickey SA, O'Connor AF. Measurement of drill-generated noise levels during ear 
surgery. J Laryngol Otol. 1991. 105(9):732-5. 
47. 
Hickox AE, Liberman MC. Is noise-induced cochlear neuropathy key to the 
generation of hyperacusis or tinnitus? J Neurophysiol. 2014. 111(3):552-64. 
48. 
Hight NG, McFadden SL, Henderson D, Burkard RF, Nicotera T. Noise-induced 
hearing loss in chinchillas pre-treated with glutathione monoethylester and R-PIA. 
Hear Res. 2003.179:21-32. 
49. 
Hilmi OJ, Mckee RH, Abel EW, Spielmann PM, Hussain SS. Do high-speed drills 
generate high-frequency noise in mastoid surgery?. Otol Neurotol. 2012. 33(1):2-5. 
50. 
Hope AJ, Luxon LM, Bamiou DE. Effects of chronic noise exposure on speech-in-
noise perception in the presence of normal audiometry. J Laryngol Otol. 2013 
127(3):233-8. 
51. 
Humes LE, Lee JH, Coughlin MP. Auditory measures of selective and divided 
attention in young and older adults using single-talker competition. J Acoust Soc 
Am. 2006 120(5 Pt 1):2926-37. 


36 | P a g e  
 
52. 
Igelmund P, Zhao YQ, Heinemann U. Effects of T-type, L-type, N-type, P-type, and 
Q-type calcium channel blockers on stimulus-induced pre- and postsynaptic calcium 
fluxes in rat hippocampal slices. Exp. Brain Res. 1996.109(1):22-32. 
53. 
Jensen JB, Lysaght AC, Liberman MC, Qvortrup K, Stankovic KM. Immediate and 
delayed cochlear neuropathy after noise exposure in pubescent mice. PLoS One. 
2015. 10(5):e0125160. 
54. 
Jin DX, Lin Z, Lei D, Bao J. The role of glucocorticoids for spiral ganglion neuron 
survival. Brain Res.  2009. 24;1277:3-11. 
55. 
Khimich D, Nouvian R, Pujol R, Tom Dieck S, Egner A, Gundelfinger ED, Moser 
T. Hair cell synaptic ribbons are essential for synchronous auditory signalling. 
Nature. 2005. 434(7035):889-94. 
56. 
Kieser M, Friede T. Simple procedures for blinded sample size adjustment that do 
not affect the type I error rate. Statistics in medicine. 2003 Dec 15;22(23):3571-81. 
57. 
Kil J, Lynch ED, Griffiths S, Lobarinas E, Spankovich C, Antonelli PJ, Le Prell CG. 
Efficacy of SPI-1005 for prevention of noise-induced hearing loss: phase 2 clinical 
trial results. Otolaryngol Head Neck Surg 2014. 151:83–84. 
58. 
Kil J, Lobarinas E, Spankovich C, Griffiths SK, Antonelli PJ, Lynch ED, Le Prell 
CG. Safety and efficacy of ebselen for the prevention of noise-induced hearing loss: 
a randomised, double-blind, placebocontrolled, phase 2 trial. The Lancet. 2017. 
390(10098):969-79. 
59. 
Kirchner DB, Evenson E, Dobie RA, Rabinowitz P, Crawford J, Kopke R, Hudson 
TW. Occupational noise-induced hearing loss: ACOEM Task Force on 
Occupational Hearing Loss. J Occup Environ Med. 2012. 54(1):106-8. 
60. 
Kochak GM, Page JG, Buchanan RA, Peters R, Padgett CS. Steady-state 
pharmacokinetics of zonisamide, an antiepileptic agent for treatment of refractory 
complex partial seizures. J Clin Pharmacol. 1998. 38(2):166-71. 
61. 
Kopke RD, Jackson RL, Coleman JK, Liu J, Bielefeld EC, Balough BJ. NAC for 
noise: from the bench top to the clinic. Hear Res. 2007. 226(1-2):114-25. 
62. 
Kopke R, Slade MD, Jackson R, Hammill T, Fausti S, Lonsbury-Martin B, 
Sanderson A, Dreisbach L, Rabinowitz P, Torre P 3rd, Balough B. Efficacy and 
safety of n-acetylcysteine in prevention of noise induced hearing loss: a randomized 
clinical trial. Hear Res 2015. 323:40–50. 
63. 
Kothare SV, Kaleyias J. Zonisamide: review of pharmacology, clinical efficacy, 
tolerability, and safety. Expert Opin. Drug Metab. Toxicol. 2008. 4:4.493. 
64. 
Kujawa SG, Liberman MC. Acceleration of age-related hearing loss by early noise 
exposure: evidence of a misspent youth. J Neurosci. 2006. 26(7):2115-23. 
65. 
Kujawa SG, Liberman MC. Adding insult to injury: cochlear nerve degeneration 
after "temporary" noiseinduced hearing loss. J Neurosci. 2009. 29(45):14077-85. 
66. 
Kujawa SG, Liberman MC. Synaptopathy in the noise-exposed and aging cochlea: 
Primary neural degeneration in acquired sensorineural hearing loss. Hear Res. 
2015. 330(Pt B):191-9. 
67. 
Kumar UA, Ameenudin S, Sangamanatha AV. Temporal and speech processing 
skills in normal hearing individuals exposed to occupational noise. Noise Health 
2012. 14:100-5. 
68. 
Kurabi A, Keithley EM, Housely GD, Ryan AF, Wong A. Cellular mechanisms of 
noise-induced hearing loss. Hearing Res. 2017. 349:129-37. 


37 | P a g e  
 
69. 
Lacinova L, Klugbauer N, Hofmann F. Low voltage activated calcium channels: 
from genes to function. Gen. Physiol. Biophys. 2000. 19(2):121-36. 
70. 
Lavinsky J, Ge M, Crow AL, Pan C, Wang J, Salehi P, Myint A, Eskin E, Allayee 
H, Lusis AJ, Friedman RA. The Genetic Architecture of Noise-Induced Hearing 
Loss: Evidence for a Gene-by-EnvironmentInteraction. G3 (Bethesda). 2016. 
6(10):3219-3228. 
71. 
Lamm, K., Arnold, W. The effect of prednisolone and non-steroidal anti-
inflammatory agents on the normal and noise-damaged guinea pig inner ear. Hear 
Res. 1998. 115:149-61. 
72. 
Leppik IE. Practical prescribing and long-term efficacy and safety of zonisamide. 
Epilepsy Res. 2006. 68 Suppl 2:S17-24. 
73. 
Lei D1, Gao X, Perez P, Ohlemiller KK, Chen CC, Campbell KP, Hood AY, Bao J. 
Anti-epileptic drugs delay age-related loss of spiral ganglion neurons via T-type 
calcium channel. Hear Res. 2011. 278(1-2):106-12. 
74. 
Le Prell CG, Bao, J. Prevention of noise-induced hearing loss: potential therapeutic 
agents. Noise-Induced Hearing Loss-Scientific Advances. 2011. Ed by Le Prell CG, 
Henderson D, Fay RR and Popper AN. Springer, ISSN 0947-2657. 
75. 
Le Prell CG, Brungart DS. Speech-in-Noise Tests and Supra-threshold Auditory 
Evoked Potentials as Metrics for Noise Damage and Clinical Trial Outcome 
Measures. Otol Neurotol. 2016. 37(8):e295-302. 
76. 
Le Prell CG, Clavier O. Effects of noise on speech recognition: Challenges for 
communication by service members. Hear Res. 2016. Jun;349:76-89 
77. 
Le Prell CG, Fulbright A, Spankovich C, Griffiths S, Lobarinas E, Campbell KCM, 
Antonelli PJ, Green GE, Guire K, Miller JM. Dietary supplement comprised of β-
carotene, vitamin C, vitamin E, and magnesium: failure to prevent music-induced 
temporary threshold shift. 2016. Audiol Neurotol. 6: 20-39. 
78. 
Le Prell CG, Hughes LF, Miller JM. Free radical scavengers vitamins A, C, and E 
plus magnesium reduce noise trauma. Free Radic Biol Med. 2007. 42(9):1454-63. 
79. 
Le Prell CG, Johnson AC, Lindblad AC, Skjönsberg A, Ulfendahl M, Guire K, 
Green GE, Campbell KC, Miller JM. Increased vitamin plasma levels in Swedish 
military personnel treated with nutrients prior to automatic weapon training. Noise 
Health. 2011. 13(55):432-43. 
80. 
Le Prell CG, Dell S, Hensley B, Hall JW 3rd, Campbell KC, Antonelli PJ, Green 
GE, Miller JM, Guire K. Digital music exposure reliably induces temporary 
threshold shift in normal-hearing human subjects. Ear Hear. 2012. 33(6):e44-58. 
81. 
Le Prell CG, Lobarinas E. Strategies for assessing antioxidant efficacy in clinical 
trials. In: Miller, J.M., Le Prell, C.G., Rybak, L.P., (Eds.), Oxidative Stress in 
Applied Basic Research and Clinical Practice: Free Radicals in ENT Pathology. 
Humana Press, New York. 2015. pp.163-192. 
82. 
Levy RH, Ragueneau-Majlessi I, Garnett WR, Schmerler M, Rosenfeld W, Shah J, 
Pan WJ. Lack of clinically significant pharmacokinetic interactions between 
zonisamide and lamotrigine at steady state in patients with epilepsy. Ther Drug 
Monit. 2005. 27(2):193-8. 
83. 
Lesage FX, Jovenin N, Deschamps F, Vincent S. Noise-induced hearing loss in 
French police officers. Occup Med (Lond). 2009. 59(7):483-6. 


38 | P a g e  
 
84. 
Liberman MC. Noise-Induced Hearing Loss: Permanent Versus Temporary 
Threshold Shifts and the Effects of Hair Cell Versus Neuronal Degeneration. Adv 
Exp Med Biol. 2016 
85. 
Liberman MC. Noise-induced and age-related hearing loss: new perspectives and 
potential therapies. F1000Res. 2017. 6:927 
86. 
Lim DJ, Melnick W. Acoustic damage of the cochlea. A scanning and transmission 
electron microscopic observation. Arch Otolaryngol. 1971. 94(4):294-305. 
87. 
Lin CY, Wu JL, Shih TS, Tsai PJ, Sun YM, Guo YL. Glutathione S-transferase M1, 
T1, and P1 polymorphisms as susceptibility factors for noise-induced temporary 
threshold shift. Hear Res. 2009. 257(1-2):8-15. 
88. 
Lin HW, Furman AC, Kujawa SG, Liberman MC. Primary neural degeneration in 
the Guinea pig cochlea after reversible noise-induced threshold shift. J Assoc Res 
Otolaryngol. 2011. 12(5):605-16. 
89. 
Lobarinas E, Scott R, Spankovich C, Le Prell CG. Differential effects of suppressors 
on hazardous sound pressure levels generated by AR-15 rifles: Considerations for 
recreational shooters, law enforcement, and the military. Int J Audiol. 2016. 55 
Suppl 1:S59-71. 
90. 
Lustig LR, Jackler RK, Chen DA. Contralateral hearing loss after neurotologic 
surgery. Otolaryngol Head Neck Surg. 1995. 113(3):276-82. 
91. 
Lynch ED, Kil J. Compounds for the prevention and treatment of noise-induced 
hearing loss. Drug Discov Today. 2005.10(19):1291-8. 
92. 
Lynch ED, Gu R, Pierce C, Kil J. Ebselen-mediated protection from single and 
repeated noise exposure 
 in rat. Laryngoscope. 2004. 114(2):333-7. 
93. 
MacArthur CJ, Kempton JB, DeGagne J, Trune DR. Control of chronic otitis media 
and sensorineural hearing loss in C3H/HeJ mice: glucocorticoids vs 
mineralocorticoids. Otolaryngol Head Neck Surg. 2008. 139(5):646-53. 
94. 
MacDonald RL. Zonisamide: mechanism of action. 2002. Ed by Levy R, Mattson 
R, Meldrum B, Perucca E. Antiepileptic drugs. (5th ed). Philadelpia, PA: Lippincott, 
Williams & Witkins Healthcare; p. 867-72. 
95. 
Pfannenstiel TJ. Noise-induced hearing loss: a military perspective. Curr Opin 
Otolaryngol Head Neck Surg. 2014. 22(5):384-7. 
96. 
Matsubara A, Laake JH, Davanger S, Usami S, Ottersen OP. Organization of AMPA 
receptor subunits at a glutamate synapse: a quantitative immunogold analysis of 
hair cell synapses in the rat organ of Corti. J Neurosci. 1996. 16(14):4457-67. 
97. 
Mager DE, Lin SX, Blum RA, Lates CD, Jusko WJ. Dose equivalency evaluation of 
major corticosteroids: pharmacokinetics and cell trafficking and cortisol dynamics. 
J Clin Pharmacol. 2003. 43(11):1216-27.  
98. 
Mattson MP. Excitatory amino acids, growth factors, and calcium: a teeter-totter 
model for neural plasticity and degeneration. Adv. Exp. Med. Biol. 1990. 268:211-
20. 
99. 
Maison SF, Rauch SD. Ethical considerations in noise-induced hearing loss 
research. 2017. The Lancet. 
100. 
McBride DI, Williams S. Audiometric notch as a sign of noise induced hearing loss. 
Occup Environ Med. 2001. 58(1):46-51. 
101. 
McCabe, B.F. Autoimmune sensorineural hearing loss. Ann Otol Rhinol Laryngol. 
1979. 88, 585-9. 


39 | P a g e  
 
102. 
McFadden SL, Ohlemiller KK, Ding D, Shero M, Salvi RJ. The Influence of 
Superoxide Dismutase and Glutathione Peroxidase Deficiencies on Noise-Induced 
Hearing Loss in Mice. Noise Health. 2001. 3(11):49-64. 
103. 
McFadden SL, Woo JM, Michalak N, Ding D. Dietary vitamin C supplementation 
reduces noise-induced hearing loss in guinea pigs. Hear Res. 2005. 202(1-2):200-8. 
104. 
McIlwain DS, Gates K, Ciliax D. Heritage of army audiology and the road ahead: 
the Army Hearing Program. Am J Public Health. 2008. 98(12):2167-72. 
105. 
Mehraei G, Hickox AE, Bharadwaj HM, Goldberg H, Verhulst S, Liberman MC, 
Shinn-Cunningham BG. Auditory Brainstem Response Latency in Noise as a 
Marker of Cochlear Synaptopathy. J Neurosci. 2016. 36(13):3755-64. 
106. 
Mukherjea D, Ghosh S, Bhatta P, Sheth S, Tupal S, Borse V, Brozoski T, Sheehan 
KE, Rybak LP, Ramkumar V. Early investigational drugs for hearing loss. Expert 
Opin Investig Drugs. 2015. 24(2):201-17. 
107. 
Mulroy MJ, Henry WR, McNeil PL. Noise-induced transient microlesions in the 
cell membranes of auditory hair cells. Hear Res. 1998. 115(1-2):93-100. 
108. 
Nikonenko I, Bancila M, Bloc A, Muller D, Bijlenga P. Inhibition of T-type calcium 
channels protects neurons from delayed ischemia-induced damage. Mol Pharmacol. 
2005. 68(1):84-9. NIOSH (National Institute for Occupational Safety and Health). 
Work-Related Hearing Loss. Pub 2001-103. 
109. 
Nordmann AS, Bohne BA, Harding GW. Histopathological differences between 
temporary and permanent threshold shift. Hear Res. 2000. 139(1-2):13-30. 
110. 
Ohlemiller KK. Recent findings and emerging questions in cochlear noise injury. 
Hear Res. 2008 245(1-2):5-17. 
111. 
Ohlemiller KK, McFadden SL, Ding DL, Flood DG, Reaume AG, Hoffman EK, 
Scott RW, Wright JS, Putcha GV, Salvi RJ. Targeted deletion of the cytosolic 
Cu/Zn-superoxide dismutase gene (Sod1) increases susceptibility to noise-induced 
hearing loss. Audiol Neurootol. 1999. 4(5):237-46. 
112. 
Ohlemiller KK, McFadden SL, Ding DL, Lear PM, Ho YS. Targeted mutation of 
the gene for cellular glutathione peroxidase (Gpx1) increases noise-induced hearing 
loss in mice. J Assoc Res Otolaryngol. 2000. 1(3):243-54. 
113. 
Ohinata Y, Miller JM, Altschuler RA, Schacht J. Intense noise induces formation of 
vasoactive lipid peroxidation products in the cochlea. Brain Res. 2000. 878(1-
2):163-73. 
114. 
Ohinata Y, Miller JM, Schacht J. Protection from noise-induced lipid peroxidation 
and hair cell loss in the cochlea. Brain Res. 2003. 966(2):265-73. 
115. 
Palva A, Sorri M. Can an operation of deaf ear be dangerous for hearing?. Acta 
Otolaryngol Suppl. 1979. 360:155-7. 
116. 
Panusa A, Regazzoni L, Aldini G, Orioli M, Giombini A, Minghetti P, Tranquilli C, 
Carini M. Urinary profile of methylprednisolone acetate metabolites in patients 
following intra-articular and intramuscular administration. Anal Bioanal Chem. 
2011. 400:255-67. 
117. 
Park E, Bell JD, Baker AJ. Traumatic brain injury: can the consequences be 
stopped? CMAJ. 2008. 178(9):1163-70. 
118. 
Paz, Z., Freeman, S., Horowitz, M., Sohmer, H. Prior heat acclimation confers 
protection against noiseinduced hearing loss. Audiol Neurootol. 2004. 9:363-9. 


40 | P a g e  
 
119. 
Perez-Reyes E. Molecular physiology of low-voltage-activated t-type calcium 
channels. Physiol. Rev. 2003. 83(1):117-61. 
120. 
Puel JL, Ruel J, Guitton M, Pujol R. The inner hair cell afferent/efferent synapses 
revisited: a basis for new therapeutic strategies. Adv. Otorhinolaryngol. 2002. 
59:124-30. 
121. 
Quaranta A, Portalatini P, Henderson D. Temporary and permanent threshold shift: 
an overview. Scand Audiol Suppl. 1998. 48:75-86. 
122. 
Quirk WS, Shapiro BD, Miller JM, Nuttall AL. Noise-induced changes in red blood 
cell velocity in lateral wall vessels of the rat cochlea. Hear Res. 1991. 52(1):217-23. 
123. 
Rodriguez-Contreras A, Yamoah EN. Direct measurement of single-channel 
Ca(2+) currents in bullfrog hair cells reveals two distinct channel subtypes. J 
Physiol. 2001. 534(Pt 3):669-89. 
124. 
Rogawski MA, Löscher W. The neurobiology of antiepileptic drugs. Nat Rev 
Neurosci. 2004. 5(7):553-64. 
125. 
Rohde NN, Baca CB, Van Cott AC, Parko KL, Amuan ME, Pugh MJ. Antiepileptic 
drug prescribing patterns in Iraq and Afghanistan war veterans with epilepsy. 
Epilepsy Behav. 2015. 46:133-9. 
126. 
Ryan AF, Kujawa SG, Hammill T, Le Prell C, Kil J. Temporary and Permanent 
Noise-induced Threshold Shifts: A Review of Basic and Clinical Observations. Otol 
Neurotol. 2016. 37(8):e271-5. 
127. 
Saruwatari  J,  Ishitsu  T,  Nakagawa  K.  Update  on  the  Genetic Polymorphisms  
of  Drug-Metabolizing   Enzymes   in   Antiepileptic   Drug   Therapy. 
Pharmaceuticals (Basel). 2010;3(8):2709-2732. 
128. 
Saunders JC, Cohen YE, Szymko YM. The structural and functional consequences 
of acoustic injury in the cochlea and peripheral auditory system: a five year update. 
J Acoust Soc Am. 1991. 90:136-46. 
129. 
Sbodio JI, Snyder SH, Paul BD. Redox Mechanisms in Neurodegeneration: From 
Disease Outcomes to Therapeutic Opportunities. Antioxidants & Redox Signaling. 
2019. 20(11):1450-1499. 
130. 
Schnee ME, Ricci AJ. Biophysical and pharmacological characterization of 
voltage-gated calcium currents in turtle auditory hair cells. J Physiol. 2003. 549(Pt 
3):697-717. 
131. 
Seidman MD, Shivapuja BG, Quirk WS. The protective effects of allopurinol and 
superoxide dismutase on noise-induced cochlear damage. Otolaryngol Head Neck 
Surg. 1993. 109:1052-6. 
132. 
Sendowski, I., Abaamrane, L., Raffin, F., Cros, A., Clarencon, D. Therapeutic 
efficacy of intra-cochlear administration of methylprednisolone after acoustic 
trauma caused by gunshot noise in guinea pigs. Hear Res. 2006. 221, 119-27. 
133. 
Sergeyenko Y, Lall K, Liberman MC, Kujawa SG. Age-related cochlear 
synaptopathy: an early-onset contributor to auditory functional decline. J Neurosci. 
2013. 33(34):13686-94. 
134. 
Shen H, Zhang B, Shin JH, Lei D, Du Y, Gao X, Wang Q, Ohlemiller KK, Piccirillo 
J, Bao J. Prophylactic and therapeutic functions of T-type calcium blockers against 
noise-induced hearing loss. Hear Res. 2007. 226(1-2):52-60. 


41 | P a g e  
 
135. 
Shimazaki T, Ichimiya I, Suzuki M, Mogi G. Localization of glucocorticoid 
receptors in the murine inner ear. Ann Otol Rhinol Laryngol. 2002. 111(12 Pt 
1):1133-8. 
136. 
Slepecky N. Overview of mechanical damage to the inner ear: noise as a tool to 
probe cochlear function. Hear Res. 1986. 22:307-21. 
137. 
Spoendlin H. Primary structural changes in the organ of Corti after acoustic 
overstimulation. Acta Otolaryngol. 1971. 71(2):166-76. 
138. 
Stamper GC, Johnson TA. Auditory function in normal-hearing, noise-exposed 
human ears. Ear Hear. 2015.36(2):172-84 
139. 
Shrestha I, Shrestha BL, Pokharel M, Amatya RC, Karki DR. Prevalence of noise 
induced hearing loss among traffic police personnel of Kathmandu Metropolitan 
City. Kathmandu Univ Med J (KUMJ). 2011. 9(36):274-8. 
140. 
Tabuchi, K., Murashita, H., Sakai, S., Hoshino, T., Uemaetomari, I., Hara, A. 
Therapeutic time window of methylprednisolone in acoustic injury. Otol Neurotol. 
2006. 27:1176-9. 
141. 
Tahera, Y., Meltser, I., Johansson, P., Bian, Z., Stierna, P., Hansson, A.C., Canlon, 
B. NF-kappaB mediated glucocorticoid response in the inner ear after acoustic 
trauma. J Neurosci Res. 2006a. 83:1066-76. 
142. 
Tahera, Y., Meltser, I., Johansson, P., Canlon, B. Restraint stress modulates 
glucocorticoid receptors and nuclear factor kappa B in the cochlea. Neuroreport. 
2006b. 17:879-82. 
143. 
Tahera, Y., Meltser, I., Johansson, P., Hansson, A.C., Canlon, B. Glucocorticoid 
receptor and nuclear factor-kappa B interactions in restraint stress-mediated 
protection against acoustic trauma. Endocrinology. 2006c. 147:4430-7. 
144. 
ten Cate, W.J., Curtis, L.M., Small, G.M., Rarey, K.E. Localization of 
glucocorticoid receptors and glucocorticoid receptor mRNAs in the rat cochlea. 
Laryngoscope. 1993.103:865-71. 
145. 
Tos M, Lau T, Plate S. Sensorineural hearing loss following chronic ear surgery. 
1984. Ann Otol Rhinol Laryngol. 93:1984 The American Journal of Otology: 
October 1984 - Volume 5 - Issue 6 - ppg 459-462 
146. 
Tremblay KL, Pinto A, Fischer ME, Klein BE, Klein R, Levy S, Tweed TS, 
Cruickshanks KJ. Self-Reported Hearing Difficulties Among Adults With Normal 
Audiograms: The Beaver Dam Offspring Study. Ear Hear. 2015. 36(6):e290-9. 
147. 
Trune DR, Canlon B. Corticosteroid therapy for hearing and balance disorders. 
Anat Rec (Hoboken). 2012. 295(11):1928-43. 
148. 
Viana LM, O'Malley JT, Burgess BJ, Jones DD, Oliveira CA, Santos F, Merchant 
SN, Liberman LD, Liberman MC. Cochlear neuropathy in human presbycusis: 
Confocal analysis of hidden hearing loss in post-mortem tissue. Hear Res. 2015. 
327:78-88. 
149. 
Wan G, Corfas G. Transient auditory nerve demyelination as a new mechanism for 
hidden hearing loss. Nat Commun. 2017. 17;8:14487. 
150. 
Wang, Y., Hirose, K., Liberman, MC. Dynamics of noise-induced cellular injury 
and repair in the mouse cochlea. JARO. 2002. 3:248-68. 
151. 
Y Wang, C Ren. Effects of repeated “benign” noise exposures in young CBA mice: 
shedding light on agerelated hearing loss. JARO. 2012. 


42 | P a g e  
 
152. 
Werling LL, Lauterbach EC, Calef U. Dextromethorphan as a potential 
neuroprotective agent with unique mechanisms of action. Neurologist. 2007. 
13(5):272-93. 
153. 
Wilson RH, Burks CA. Use of 35 words for evaluation of hearing loss in signal-to-
babble ratio: A clinic protocol. J. Rehabil. Res. Dev. 2005. 42:839-52. 
154. 
Wilson RH, McArdle R. Intra- and inter-session test, retest reliability of the Words-
in-Noise (WIN) test. J. Am. Acad. Audiol. 2007.18:813-25. 
155. 
Wilson RH, Cates WB. A comparison of two word-recognition tasks in multitalker 
babble: Speech Recognition in Noise Test (SPRINT) and Words-in-Noise Test 
(WIN). J. Am. Acad. Audiol. 2008.19:548-56. 
156. 
Wilson RH, Watts KL. The Words-in-Noise Test (WIN), list 3: a practice list. J. Am. 
Acad. Audiol. 2012. 23:92-6. 
157. 
Wilson RH, Abrams HB, Pillion AL. A word-recognition task in multitalker babble 
using a descending presentation mode from 24 dB to 0 dB signal to babble. J. 
Rehabil. Res. Dev. 2003. 40:321-7. 
158. 
Wilson RH, Burks CA, Weakley DG. Word recognition in multitalker babble 
measured with two psychophysical methods. J. Am. Acad. Audiol. 2005.16:622-30. 
159. 
Wilson, R.H., McArdle, R.A., Smith, S.L. An Evaluation of the BKB-SIN, HINT, 
QuickSIN, and WIN Materials on Listeners with Normal Hearing and Listeners With 
Hearing Loss. J. Speech. Lang. Hear. Res. 2007. 50:844-56. 
160. 
Wilson RH, McArdle R, Betancourt MB, Herring K, Lipton T, Chisolm TH. Word-
recognition performance in interrupted noise by young listeners with normal 
hearing and older listeners with hearing loss. J. Am. Acad. Audiol. 2010. 21:90-
109. 
161. 
Xu J, Chen S, Chen H, Xiao Q, Hsu CY, Michael D, Bao J. STAT5 mediates 
antiapoptotic effects of methylprednisolone on oligodendrocytes. J Neurosci. 2009. 
29(7):2022-6. 
162. 
Yankaskas K. Prelude: noise-induced tinnitus and hearing loss in the military. Hear 
Res. 2013. 295:3-8 
163. 
Yamane H, Nakai Y, Takayama M, Iguchi H, Nakagawa T, Kojima A. Appearance 
of free radicals in the guinea pig inner ear after noise-induced acoustic trauma. Eur 
Arch Otorhinolaryngol. 1995. 252(8):504-8. 
164. 
Yamashita D, Jiang HY, Schacht J, Miller JM. Delayed production of free radicals 
following noise exposure. Brain Res. 2004. 1019(1-2):201-9. 
165. 
Yamashita D, Jiang HY, Le Prell CG, Schacht J, Miller JM. Post-exposure treatment 
attenuates noiseinduced hearing loss. Neuroscience. 2005. 134(2):633-42. 
166. 
Yamasoba T, Schacht J, Shoji F, Miller JM. Attenuation of cochlear damage from 
noise trauma by an iron chelator, a free radical scavenger and glial cell line-derived 
neurotrophic factor in vivo. Brain Res. 1999. ;815(2):317-25. 
167. 
Yoshida, N., Kristiansen, A., Liberman, M.C., 1999. Heat stress and protection from 
permanent acoustic injury in mice. J Neurosci. 19, 10116-24. 
168. 
Yu M, Liu T, Chen Y, Li Y, Li W. Combination therapy with protein kinase 
inhibitor H89 and Tetrandrine elicits enhanced synergistic antitumor efficacy. J Exp 
Clin Cancer Res. 2018. 37(1):114. 
169. 
Yunker AM, McEnery MW. Low-voltage-activated ("T-Type") calcium channels in 
review. J. Bioenerg. Biomembr. 2003. 35(6):533-75. 


43 | P a g e  
 
170. 
Zhang  X,  Ni  Y,  Liu  Y,  et  al.  Screening  of  noise-induced  hearing  loss  (NIHL)-
associated SNPs and the assessment of its genetic susceptibility. Environ Health. 
2019;18(1):30. 
171. 
Zecker SG1, Hoffman HJ, Frisina R, Dubno JR, Dhar S, Wallhagen M, Kraus N, 
Griffith JW, Walton JP, Eddins DA, Newman C, Victorson D, Warrier CM, Wilson 
RH. Audition assessment using the NIH Toolbox. Neurology. 2013. 80(11 Suppl 
3):S45-8. 
172. 
Zine A, van de Water TR. The MAPK/JNK signalling pathway offers potential 
therapeutic targets for the prevention of acquired deafness. Curr Drug Targets CNS 
Neurol Disord. 2004. 3(4):325-32. 
173. 
Zipfel GJ, Babcock DJ, Lee JM, Choi DW. Neuronal apoptosis after CNS injury: 
the roles of glutamate and calcium. J Neurotrauma. 2000. 17(10):857-69. 
174. 
Zhou Y, Zheng G, Zheng H, Zhou R, Zhu X, Zhang Q. Primary observation of early 
transtympanic steroid injection in patients with delayed treatment of noise-induced 
hearing loss. Audiol Neurootol. 2013. 18(2):89-94. 
175. 
Zuo J, Curtis LM, Yao X, ten Cate WJ, Bagger-Sjöbäck D, Hultcrantz M, Rarey KE. 
Glucocorticoid receptor expression in the postnatal rat cochlea. Hear Res. 1995. 
87(1-2):220-7. 
  
 
 


44 | P a g e  
 
APPENDIX A: Definitions for Adverse Event Reporting 
 
A. Adverse Events (AEs) 
 
As defined in 21 CFR 312.32: 
 
Definition: any untoward medical occurrence associated with the use of a drug in humans, 
whether or not considered drug-related. 
 
Grading: the descriptions and grading scales that should be used are those provided by the 
Department of Health and Human Services’ Office for Human Research Protections (OHRP).  
A copy of this guidance can be found on OHRP’s website: 
http://www.hhs.gov/ohrp/policy/advevntguid.html 
 
Attribution (relatedness), Expectedness, and Seriousness: the definitions for the terms 
listed that should be used are those provided by the Department of Health and Human Services’ 
Office for Human Research Protections (OHRP).  A copy of this guidance can be found on 
OHRP’s website: 
http://www.hhs.gov/ohrp/policy/advevntguid.html 
 
B. Suspected Adverse Reaction (SAR) 
 
As defined in 21 CFR 312.32: 
 
Definition: any adverse event for which there is a reasonable possibility that the drug caused 
the adverse event.  “Reasonable possibility” means there is evidence to suggest a causal 
relationship between the drug and the adverse event.  “Suspected adverse reaction” implies a 
lesser degree of certainty about causality than adverse reaction, which means any adverse event 
caused by a drug. 
 
C. Life-Threatening Adverse Event / Life Threatening Suspected Adverse Reaction  
 
As defined in 21 CFR 312.32: 
 
Definition: any adverse drug event or suspected adverse reaction is considered “life-
threatening” if, in the view of the investigator, its occurrence places the patient at immediate 
risk of death. It does not include an adverse event or suspected adverse reaction that, had it 
occurred in a more severe form, might have caused death. 
 
D.  Serious Adverse Event (SAE) or Serious Suspected Adverse Reaction 
 
As defined in 21 CFR 312.32: 
 
Definition:  an adverse event or suspected adverse reaction is considered “serious” if, in the 
view of the investigator, it results in any of the following outcomes: 
o Death 


45 | P a g e  
 
o A life-threatening adverse event 
o Inpatient hospitalization or prolongation of existing hospitalization 
o A persistent or significant incapacity or substantial disruption of the ability to conduct 
normal life functions 
o A congenital anomaly/birth defect 
o Any other important medical event that does not fit the criteria above but, based upon 
appropriate medical judgment, may jeopardize the subject and may require medical or 
surgical intervention to prevent one of the outcomes listed above 
 
E. Protocol Exceptions 
 
Definition: A planned change in the conduct of the research for one participant. 
 
F. Deviation 
 
Definition: Any alteration or modification to the IRB-approved research without prospective 
IRB approval.  The term “research” encompasses all IRB-approved materials and documents 
including the detailed protocol, IRB application, consent form, recruitment materials, 
questionnaires/data collection forms, and any other information relating to the research study. 
 
A minor or administrative deviation is one that does not have the potential to negatively impact 
the rights, safety, or welfare of participants or others or the scientific validity of the study. 
 
A major deviation is one that does have the potential to negatively impact the rights, safety, or 
welfare of participants or others or the scientific validity of the study. 
 


46 | P a g e  
 
APPENDIX B: Reporting Timelines 
 
Event 
HRPO 
FDA 
Serious AND unexpected suspected adverse 
reaction 
 
Report no later than 15 calendar days after it is 
determined that the information qualifies for reporting 
Unexpected fatal or life-threatening 
suspected adverse reaction 
 
Report no later than 7 calendar days after initial 
receipt of the information 
Unanticipated problem involving risk to 
participants or others 
Report within 10 working days.  If the event results in 
the death of a participant enrolled at WU/BJH/SLCH, 
report within 1 working day. 
 
Major deviation 
Report within 10 working days.  If the event results in 
the death of a participant enrolled at WU/BJH/SLCH, 
report within 1 working day. 
 
A series of minor deviations that are being 
reported as a continuing noncompliance 
Report within 10 working days.   
 
Protocol exception 
Approval must be obtained prior to implementing the 
change 
 
Clinically important increase in the rate of a 
serious suspected adverse reaction of that list 
in the protocol or IB 
 
Report no later than 15 calendar days after it is 
determined that the information qualifies for reporting 
Complaints 
If the complaint reveals an unanticipated problem 
involving risks to participants or others OR 
noncompliance, report within 10 working days.  If the 
event results in the death of a participant enrolled at 
WU/BJH/SLCH, report within 1 working day.  
Otherwise, report at the time of continuing review. 
 
Breach of confidentiality 
Within 10 working days. 
 
Incarceration 
If withdrawing the participant poses a safety issue, 
report within 10 working days.   
 
If withdrawing the participant does not represent a 
safety issue and the patient will be withdrawn, report at 
continuing review. 
 
 
 
 


47 | P a g e  
 
Event 
HRPO 
FDA 
Adverse event or SAE that does not require 
expedited reporting 
If they do not meet the definition of an unanticipated 
problem involving risks to participants or others, report 
summary information at the time of continuing review 
The most current toxicity table from the DSM report 
is provided to the FDA with the IND’s annual report. 
Minor deviation 
Report summary information at the time of continuing 
review. 
 
Complaints 
If the complaint reveals an unanticipated problem 
involving risks to participants or others OR 
noncompliance, report within 10 working days.  If the 
event results in the death of a participant enrolled at 
WU/BJH/SLCH, report within 1 working day.  
Otherwise, report at the time of continuing review. 
 
Incarceration 
If withdrawing the participant poses a safety issue, 
report within 10 working days.   
 
If withdrawing the participant does not represent a 
safety issue and the patient will be withdrawn, report at 
continuing review. 
 
 
Event 
WU (Coordinating Center) 
Local IRB 
FDA 
Serious AND unexpected suspected 
adverse reaction 
Report no later than 11 calendar days after it is 
determined that the information qualifies for 
reporting. 
Report all applicable 
events to local IRB 
according to local 
institutional 
guidelines. 
The research team at Washington 
University is responsible for reporting all 
applicable events to the FDA as needed. 
Unexpected fatal or life-threatening 
suspected adverse reaction 
Report no later than 4 calendar days after initial 
receipt of the information. 
Unanticipated problem involving 
risk to participants or others 
Report no later than 4 calendar days after initial 
receipt of the information. 
Adverse event or SAE that does not 
require expedited reporting 
As per routine data entry expectations 
Protocol exception 
Approval must be obtained prior to implementing the 
change. 
 
 
 


Pharmaceutical Interventions for Noise-Induced Hearing Loss–Acute Exposure Treatment 
(PINIHL-AET) 
Version: 03 March 2023 
 
Page 48 of 55 
 
 
 
 
 
APPENDIX C: Washington University Unanticipated Problem Reporting Cover Sheet 
 
SAE COVER SHEET- Secondary Site Assessment 
 
Washington University HRPO#:  
Sponsor-Investigator:  
Subject Initials:   
Subject ID:  
Treating MD:  
Treating Site:  
EVENT TERM:  
Admission Date:  
EVENT GRADE: 
Date of site’s first notification: 
 
Treating MD Event Assessment:  
 
 
Is this event possibly, probably, or definitely related study treatment? 
 
 yes  
 
 no 
 
If yes, please list which drug (if more than one)______________________________ 
 
       
Explain ______________________________________________________________________ 
 
______________________________________________________________________________ 
 
 
 
_________________________           ___________________________      _________________  
Physician’s Name 
 
 
Physician’s Signature 
 
Date 
 
 
 
 
 
 


Pharmaceutical Interventions for Noise-Induced Hearing Loss–Acute Exposure Treatment 
(PINIHL-AET) 
Version: 03 March 2023 
 
Page 49 of 55 
 
 
 
 
 
APPENDIX D: Questionnaire 1a: Hearing History and Occupation Exposure – Visit 1 
 
Hearing History and Occupation Exposure 
Visit 1 
 
1. In the ear opposite of surgery, do you have any difficulties hearing speech?    
 
  
□ No    
 
□ Yes, sometimes    
 □ Yes, often      
 
2. In the ear opposite of surgery, do you have any difficulties hearing other types of 
sounds?     
 
 
□ No     
 
 Yes, sometimes          
□ Yes, often      
 
3. Do you have tinnitus, ringing in your ears? □ Yes           □ No      
 
If yes,  
A. Which ear?     □ Right           □ Left   
B. When did the tinnitus start? ________________________________________ 
1. Suddenly or gradually? ______________________________________ 
 
4.  Have you worked in any of the following types of loud-noise occupations?  
 
□ Yes    
□ No       
 
Circle all that apply, even if very brief:      
 
 
Logging/lumber industry     Mining 
Farming   
 
Factory   
 
Landscape 
(lawnmower/weedeater/chainsaw)  
Printing 
 
Truck Driver    
Pilot   
Police 
 
Construction        
Military      
Hunting (gun powder)    
 
Fire Department       
Musician/Theatrical 
performer             
 
 
Current Occupation: ______________________________________________ 
 


Pharmaceutical Interventions for Noise-Induced Hearing Loss–Acute Exposure Treatment 
(PINIHL-AET) 
Version: 03 March 2023 
 
Page 50 of 55 
 
 
 
 
 
5. Have you been exposed to loud noise during recreational or leisure-time activities 
(e.g., gunfire, power tools, boat engines, auto engines, motorcycle, ski-mobile, or loud 
music)?  
  
 □ Yes           □ No     
 
If yes, describe: ____________________________________________________________ 
 
 
6. Have you undergone any accidental exposure to sudden, intense noise?       
 
 □ Yes           □ No  
 
 If yes,  
 
6a. Please explain:  type of noise 
___________________________________________________________________________       
 
 
 
6b. Which ear or side of your head was exposed? 
____________________________________________________________________________ 
 
 
6c. Your age at the time of noise exposure ______________________________           
 
7. Do you have any blood relatives who have, or have had, any problems with their 
hearing?   
 □ Yes           □ No    
 
 
If yes, please indicate the nature of their problem(s), and their relationship to you.  
___________________________________________________________________________ 
8. Do you have any blood relatives who have, or have had, tinnitus?  
 
 □ Yes           □ No   
 
        If yes, please indicate the nature of their problem(s), and their relationship to you. 
_____________________________________________________________________________ 
 
REVIEWED BY  
 
CRC signature ____________________________________________ Date _____________ 
 
PI Signature _______________________________________________ Date ____________ 
 
 


Pharmaceutical Interventions for Noise-Induced Hearing Loss–Acute Exposure Treatment 
(PINIHL-AET) 
Version: 03 March 2023 
 
Page 51 of 55 
 
 
 
 
 
 
 
APPENDIX E: Questionnaire 1b: Hearing History and Occupation Exposure – Visit 3 
 
Hearing History and Occupation Exposure 
Visit 3 
 
1. In the ear opposite of surgery, do you have any difficulties hearing speech?    
 
  
□ No    
 
□ Yes, sometimes    
 □ Yes, often      
 
2. In the ear opposite of surgery, do you have any difficulties hearing other types of 
sounds?  
    
 
□ No     
 
 Yes, sometimes          
□ Yes, often      
 
3. Do you have tinnitus, ringing in your ears? □ Yes           □ No      
 
If yes,  
C. Which ear?     □ Right           □ Left   
D. When did the tinnitus start? ________________________________________ 
2. Suddenly or gradually? ______________________________________ 
 
4.  Since your surgery, have you been in any of the following types of loud-noise 
situations?  
 
□ Yes    
□ No       
 
Circle all that apply, even if very brief:      
 
 
Logging/lumber industry     Mining 
Farming   
 
Factory   
 
Landscape 
(lawnmower/weedeater/chainsaw)  
Printing 
 
Truck Driver    
Pilot   
Police 
 
Construction        
Military      
Hunting (gun powder)    
 
Fire Department       
Musician/Theatrical 
performer             
Rock Concerts 


Pharmaceutical Interventions for Noise-Induced Hearing Loss–Acute Exposure Treatment 
(PINIHL-AET) 
Version: 03 March 2023 
 
Page 52 of 55 
 
 
 
 
 
Woodworking 
Listening to music on 
   MP3 players 
 
 
 
 
 
 
 
 
   
 
 
 
5. Since your surgery, have you been exposed to loud noise during recreational or 
leisure-time activities (e.g., gunfire, power tools, boat engines, auto engines, 
motorcycle, ski-mobile, or loud music)?  
  
 □ Yes           □ No     
If yes, describe: ____________________________________________________________ 
 
6. Since your surgery, have you undergone any accidental exposure to sudden, 
intense noise?       
 
 □ Yes           □ No  
 
 If yes, Please explain:  type of noise 
___________________________________________________________________________       
 
 
 
Which ear or side of your head was exposed? 
____________________________________________________________________________ 
 
 
 
REVIEWED BY  
 
CRC signature ____________________________________________ Date _____________ 
 
PI Signature _______________________________________________ Date ____________ 
 
 
 
 
 
 
 
 
 


Pharmaceutical Interventions for Noise-Induced Hearing Loss–Acute Exposure Treatment 
(PINIHL-AET) 
Version: 03 March 2023 
 
Page 53 of 55 
 
 
 
 
 
APPENDIX F: LENS-Q Adapted for Surgical Noise Study –Visit 1 
LENS-Q Adapted for Surgical Noise Study: The point of this modified survey is to stratify participants 
into relatively higher and relatively lower exposure groups. 
Noise Exposure History Interview Questions  
1.  
 
A. In your occupation, how often are you exposed to loud noise(s) where you have to shout to 
be heard? (For example, loud equipment or trucks, loud ship or jet engines, exposure from the 
rifle range, sirens, K-9 noise, loud crowds, loud music (e.g. concert/band events), loud noise from 
construction sites)  
a. Daily 
b. Less than daily/more than weekly 
c. Weekly 
d. Less than weekly/more than monthly 
e. Monthly 
f. Less than monthly/more than yearly 
g. Yearly 
h. Less than yearly 
i. 
Never 
 
B. How likely are you to be wearing hearing protection when this occurs (circle one)? 
 
Never          Rarely          Sometimes          Usually          Always 
 
C. How many years have you worked in your occupation? _________________ 
 
2.  
Have you served in the military? If yes: 
A. How often did your military service cause you to be exposed to loud noise(s) where you had 
to shout to be heard? (For example, loud equipment or trucks, loud ship or jet engines, loud 
aircraft)  
a. Daily 
b. Less than daily/more than weekly 
c. Weekly 
d. Less than weekly/more than monthly 
e. Monthly 
f. Less than monthly/more than yearly 
g. Yearly 
h. Less than yearly 
i. 
Never 
 


Pharmaceutical Interventions for Noise-Induced Hearing Loss–Acute Exposure Treatment 
(PINIHL-AET) 
Version: 03 March 2023 
 
Page 54 of 55 
 
 
 
 
 
B. How likely were you to be wearing hearing protection when this occurred (circle one)? 
 
Never          Rarely          Sometimes          Usually          Always 
 
C. How many years did you serve in the military? _________________ 
 
3. 
A. How often did or do recreational activities cause you to be exposed to loud noise(s) where 
you would have to shout to be heard?  
a. Daily 
b. Less than daily/more than weekly 
c. Weekly 
d. Less than weekly/more than monthly 
e. Monthly 
f. Less than monthly/more than yearly 
g. Yearly 
h. Less than yearly 
i. 
Never 
 
B. Were you wearing hearing protection when this occurred?  
 
Never          Rarely          Sometimes          Usually          Always 
 
C. How many years were you involved with a recreational activity where you had to shout to be 
heard? ____________________________________ 
 
4.  
In either your occupation, your military service, or your recreational activities:   
A. How often have you been exposed to sudden intense noise? (For example, shooting range, 
target practice, hunting, explosions, cannon fire, gun shot, music (e.g. drums), etc.)  
a. Daily 
b. Less than daily/more than weekly 
c. Weekly 
d. Less than weekly/more than monthly 
e. Monthly 
f. Less than monthly/more than yearly 
g. Yearly 
h. Less than yearly 
i. 
Never 
 
B. Were you wearing hearing protection when this occurred (circle one)?  


Pharmaceutical Interventions for Noise-Induced Hearing Loss–Acute Exposure Treatment 
(PINIHL-AET) 
Version: 03 March 2023 
 
Page 55 of 55 
 
 
 
 
 
 
Never          Rarely          Sometimes          Usually          Always 
 
 
Noise Exposure Group Assignment Based on Interview Questions  
• 
Participants with a response to 1.A., 2.A., or 4.A. of monthly or more frequent exposure are 
assigned to the higher noise group. Participants with less than monthly exposure are assigned to 
the lower noise group. 
• 
Participants with a response to 1.C., 2.C, or 3.C. of 5 years or more are assigned to the Higher 
Noise group. 
 

SAP_001.pdf: 
Statistical Analysis Plan V6.0 
Washington University 
PINIHL-WU Protocol V9.0 
21 Jun 2023 
Confidential 
Page 1 of 36 
STATISTICAL ANALYSIS PLAN 
 
 
 
PROTOCOL TITLE: 
 
Pharmaceutical Interventions for Noise-Induced Hearing 
Loss - Acute Exposure Treatment (PINIHL-AET) 
PROTOCOL  
(Short Name, Version, 
Date):  
 
PINIHL-WU, Version 9.0 03 March 2023  
STUDY TREATMENT:    
Zonisamide (ZNS) 
STUDY PHASE: 
 
Phase 2 
SPONSOR: 
 
 
Washington University School of Medicine 
AUTHORS: 
 
Dorina Kallogjeri, MD, MPH, Raviprakash Nagaraj, PhD 
SAP Version: 
 
Final 6.0 
SAP Version Date: 
 
21 June 2023 
 
 
Version 
 
Date 
Comments 
Final 1.0 
 
03 February 2021 
Initial Version 
Final 2.0 
 
10 June 2021 
• 
Increase in total subjects at WU 
and UA and sample size section 
updated. 
• 
Null hypothesis statements 
reworded. 
• 
Inclusion of stratification 
language at WU. 
• 
Missing data sections revised at 
WU and UA. 
• 
Efficacy Analysis section revised 
and covariates clarified at WU 
and UA. Sensitivity analysis 
added 
• 
Interim Analysis section updated. 
• 
Secondary efficacy outcome 
timepoint clarified at UA. 
Final 3.0 
 
21 October 2021 
• 
Alternate hypothesis written as 
HA: pZNS < pplacebo 


Statistical Analysis Plan V6.0 
Washington University 
PINIHL-WU Protocol V9.0 
21 Jun 2023 
Confidential 
Page 2 of 36 
Version 
 
Date 
Comments 
• 
Randomization language updated 
to match protocols 
Draft 3.1 
 
12 January 2022 
• 
Developed separate SAP for 
Washington University Study 
based combined WU and UA 
SAP v3.0. 
Draft 3.2 
 
25 February 2022 
• Updated based on sponsor 
comments 
• Updated based on FDA 
comments 
Draft 3.3 
 
22 March 2022 
• Updated based on sponsor 
comments 
Draft 3.4 
 
28 March 2022 
• Updated to match protocol 
Final 4.0 
 
18 April 2022 
• Final Version 
Draft 4.1 
 
12 January 2023 
• Updated section 2.6 by removing 
ECG to match protocol v8.0 
Final 5.0 
 
19 January 2023 
• Final Version 
Draft 5.1 
 
02 June 2023 
• Updated based on FDA 
comments 
Draft 5.2 
 
19 June 2023 
• Updated the SAS procedure for 
Rubin’s rule in missing data 
analysis (Section 5.2) 
Final 6.0 
 
21 June 2023 
• Final Version 
 
 
 


Statistical Analysis Plan V6.0 
Washington University 
PINIHL-WU Protocol V9.0 
21 Jun 2023 
Confidential 
Page 3 of 36 
Signature Page 
I confirm that I have reviewed this document and agree with the content. 
 
APPROVALS: 
 
 
Prepared by: Pharm-Olam 
 
  
Name: 
Raviprakash Nagaraj 
 Date: (dd/mmm/yyyy) 
Title: 
Biostatistician 
  
 
 
 
 
Approved by: Pharm-Olam 
 
  
Name: 
Kaushik Maity 
 Date: (dd/mmm/yyyy) 
Title: 
Senior Reviewer, Biostatistician 
    
 
 
 
Approved by: Washington 
University 
 
  
Name: 
Dorina Kallogjeri 
 Date: (dd/mmm/yyyy) 
Title: 
Statistician 
    
 
 
 
 
Approved by: Washington 
University 
 
  
Name: 
Banan Ead 
 Date: (dd/mmm/yyyy) 
Title: 
Clinical Research Coordinator 
    


Statistical Analysis Plan V6.0 
Washington University 
PINIHL-WU Protocol V9.0 
21 Jun 2023 
Confidential 
Page 4 of 36 
TABLE of CONTENTS 
LIST OF ABBREVIATIONS .................................................................................................................... 6 
1 
PURPOSE ........................................................................................................................................... 7 
1.1 
RESPONSIBLITIES ....................................................................................................... 7 
2 
INTRODUCTION .............................................................................................................................. 8 
2.1 
STUDY DESIGN ............................................................................................................ 8 
2.2 
STUDY OBJECTIVES ................................................................................................... 8 
2.2.1 Primary Objective ....................................................................................................... 8 
2.2.2 Secondary Objectives .................................................................................................. 8 
2.2.3 Exploratory Analysis ................................................................................................... 9 
2.3 
STUDY POPULATION ........................................................................................................ 9 
2.4 
RANDOMISATION ............................................................................................................. 9 
2.5 
TREATMENT ASSIGNMENT AND BLINDING ..................................................................... 10 
2.6 
SCHEDULE OF ASSESSMENTS AND PROCEDURES ............................................................ 11 
2.7 
SAMPLE SIZE DETERMINATION FOR THE PRIMARY EFFICACY OUTCOME MEASURE ...... 11 
3 
STUDY OUTCOMES ...................................................................................................................... 13 
3.1 
PRIMARY ESTIMAND ...................................................................................................... 13 
3.2 
PRIMARY EFFICACY OUTCOME ...................................................................................... 13 
3.2.1 Comparison of the proportion of PTS-positive patients between ZNS pre-op and 
Placebo ................................................................................................................................. 13 
3.2.2 Comparison of the proportion of PTS-positive patients between ZNS post-op and 
Placebo ................................................................................................................................. 13 
3.3 
SECONDARY EFFICACY OUTCOMES ................................................................................ 14 
3.4 
SAFETY MEASURES ........................................................................................................ 14 
4 
ANALYSIS POPULATIONS .......................................................................................................... 15 
4.1 
TARGET POPULATION ..................................................................................................... 15 
4.2 
INTENT-TO-TREAT (ITT) SAMPLE ................................................................................... 15 
4.3 
THE SAFETY SAMPLE ...................................................................................................... 15 
4.4 
PER-PROTOCOL SAMPLE ................................................................................................. 15 
5 
GENERAL ASPECTS FOR STATISTICAL ANALYSES .......................................................... 16 
5.1 
GENERAL METHODS ...................................................................................................... 16 
5.2 
MISSING DATA ............................................................................................................... 16 
6 
STUDY SUBJECTS ......................................................................................................................... 18 
6.1 
DISPOSITION OF SUBJECTS ............................................................................................. 18 
6.2 
DEMOGRAPHICS CHARACTERISTICS ............................................................................... 18 
6.3 
MEDICAL HISTORY AND SURGICAL HISTORY ................................................................ 18 
6.4 
CONCOMITANT MEDICATIONS ....................................................................................... 18 
6.5 
TREATMENT ADMINISTRATION ...................................................................................... 19 
6.6 
PROTOCOL DEVIATIONS ................................................................................................. 19 
7 
EFFICACY ANALYSES ................................................................................................................. 20 
7.1.1 Analysis of primary outcome variable ...................................................................... 20 


Statistical Analysis Plan V6.0 
Washington University 
PINIHL-WU Protocol V9.0 
21 Jun 2023 
Confidential 
Page 5 of 36 
7.1.2 Analysis for secondary outcome measures. .............................................................. 23 
7.1.3 Pharmacogenetics analysis plan............................................................................... 23 
8 
SAFETY ANALYSES ...................................................................................................................... 25 
8.1.1 Safety monitoring ...................................................................................................... 25 
8.2 
CLINICAL LABORATORY TESTS ...................................................................................... 25 
8.3 
CLINICAL EXAMINATION OF THE EARS .......................................................................... 25 
8.4 
ELECTROCARDIOGRAM (ECG) ....................................................................................... 26 
8.5 
PREGNANCY TEST .......................................................................................................... 26 
9 
INTERIM ANALYSIS ..................................................................................................................... 27 
10 
SOFTWARE AND PROGRAMMING SPECIFICATIONS ....................................................... 28 
10.1 
GENERAL PROGRAMMING SPECIFICATIONS ................................................................... 28 
10.1.1 
General ................................................................................................................. 28 
10.1.2 
Headers ................................................................................................................. 28 
10.1.3 
Display Titles ........................................................................................................ 29 
10.1.4 
Column Headers ................................................................................................... 29 
10.1.5 
Body of the Data Display ...................................................................................... 29 
10.1.6 
Footnotes............................................................................................................... 31 
11 
QUALITY CONTROL .................................................................................................................... 33 
11.1 
SPECIFICATIONS ............................................................................................................. 33 
11.2 
OUTPUTS ........................................................................................................................ 33 
12 
APPENDICES .................................................................................................................................. 34 
12.1 
INDEX OF PROPOSED TABLES ......................................................................................... 34 
12.2 
INDEX OF PROPOSED LISTINGS ....................................................................................... 35 
12.3 
INDEX OF PROPOSED FIGURES ........................................................................................ 36 
 
 
 


Statistical Analysis Plan V6.0 
Washington University 
PINIHL-WU Protocol V9.0 
21 Jun 2023 
Confidential 
Page 6 of 36 
LIST OF ABBREVIATIONS 
 
Abbreviation 
Description 
AE 
Adverse Event(s) 
dB 
Decibels 
DPOAE 
Distortion Product Otoacoustic Emissions 
DSMB 
Data Safety Monitoring Board 
ECochG 
electrocochleography 
FDA 
United States Food and Drug Administration 
HL 
Hearing Loss 
hr 
Hour 
ITT 
Intent-to-treat  
kHz 
Kilohertz 
LAeq8hr 
8 hour equivalent A-weighted sound level in 
decibel 
mg 
Milligram 
NIHL 
Noise Induced Hearing Loss 
PGx 
Pharmacogenetics 
PI 
Principal Investigator 
PO 
Per os (orally) 
Post-op 
Postoperative 
Pre-op 
Preoperative 
PTS 
Permanent Threshold Shift 
SAE 
Serious Adverse Event(s) 
TTS 
Temporary Threshold Shift 
UA 
University of Akron 
WIN 
Word in noise 
WU 
Washington University School of Medicine 
ZNS 
Zonisamide 
 
 
 


Statistical Analysis Plan V6.0 
Washington University 
PINIHL-WU Protocol V9.0 
21 Jun 2023 
Confidential 
Page 7 of 36 
1 
PURPOSE 
This document describes the planned statistical strategies for the analysis of data for the 
“Pharmaceutical Interventions for Noise-Induced Hearing Loss–Acute Exposure Treatment 
(PINIHL-AET)” Study.  The document will be shared with the members of the Data Safety 
Monitoring Board (DSMB) and will be modified based on their feedback and requests.  
 
Data reports will be prepared for the DSMB and will be part of the DSM report that will be 
prepared by the study team with assistance from the study statistician. The DSM report will be 
prepared for the DSMB semi-annually and at other times at the discretion of the DSMB.  The 
DSM report will be reviewed by the DSMB, and will be submitted to the PI.  The DSMB must 
meet at least every six months beginning six months after study activation at Washington 
University beginning six months after enrollment of the first patient at the secondary site, or due 
to Adverse Events (AE) or Serious Adverse Events (SAEs) to ensure subject safety through data, 
process or conduct of study and recommend to the sponsor on continuation, modification, or 
termination of the study, and no more than one month prior to the due date of the DSM report to 
the PI.   
In the event of future amendments to the protocol, this SAP will be modified as necessary to 
account for changes relevant to the statistical analysis. 
1.1 
RESPONSIBLITIES 
Pharm-Olam will perform the statistical analyses and is responsible for the production and 
quality control of all derived datasets and tables, listings, and figures. 
 
 


Statistical Analysis Plan V6.0 
Washington University 
PINIHL-WU Protocol V9.0 
21 Jun 2023 
Confidential 
Page 8 of 36 
2 
INTRODUCTION 
2.1 
STUDY DESIGN 
This study is a randomized, double-blinded, placebo-controlled trial with three parallel groups, 
to make use of a common control group between the experimental groups. Subjects will be 
randomized in a balanced fashion into one of 3 arms: Zonisamide (ZNS) pre-op, Placebo, or ZNS 
post-op.  
 
Study Subjects will be recruited from the Washington University Otology clinics. Patients will 
be offered participation if they are undergoing skull-based surgery as part of their standard 
treatment. These are patients that would be recommended skull-based surgery despite this 
investigation and this investigation will have no influence on treatment recommendations.   
 
Figure 1  Overall Study Design  
 
 
2.2 
STUDY OBJECTIVES  
2.2.1 Primary Objective 
 
To determine if preoperative and/or postoperative ZNS is more effective than placebo at 
preventing a permanent threshold shift (PTS) in the contralateral ear of patients undergoing 
drilling during skull base surgery. 
 
The primary efficacy outcome will be the proportion of PTS-positive subjects defined as the ratio 
of PTS-positive subjects to total number of subjects in each study arm/group. PTS positive will be 
defined as all subjects who in audiogram are identified as having a PTS of > 10 dB HL increase at 
any frequency between 2-6 kHz post-surgery as compared to baseline audiogram. 
 
2.2.2 Secondary Objectives 
To determine if preoperative and/or postoperative ZNS is more effective than placebo at 
preventing a temporary threshold shift (TTS), synaptopathy, and degraded speech perception in 
the contralateral ear of patients undergoing drilling during skull base surgery. 
 


Statistical Analysis Plan V6.0 
Washington University 
PINIHL-WU Protocol V9.0 
21 Jun 2023 
Confidential 
Page 9 of 36 
2.2.3 Exploratory Analysis 
 
To identify a genetic risk profile associated with drilling-induced hearing loss we will survey 
known genetic markers associated with NIHL including markers in CDH23, PCDH15, EYA4, 
MYO1A, KCNMA1 and OTOG1 and zonisamide (ZNS) metabolism, CYP2C9 and CYP2C192. 
If significant associations are observed and validated in a subsequent clinical study, we will 
optimize drug dosages based on a subject’s genetic profile. 
2.3 
Study Population 
We plan to enroll approximately 234 subjects over approximately 4 years. Subjects will be 
randomized in a balanced fashion into one of the 3 arms: ZNS 100 mg pre-op, Placebo, or ZNS 
100 mg post-op. We proposed the three-group design in order to establish a common control group 
between the experimental groups. Enrolled study subjects will be randomized into three equal 
groups. The placebo group is the common group for comparison to each active group 
independently. Alpha error will be adjusted for multiple comparison. 
 
2.4 
Randomisation 
Eligible subjects will be randomized in a balanced fashion into one of the 3 arms: ZNS 100 mg 
pre-op, Placebo, or ZNS 100 mg post-op. To balance noise-exposure history across study arms 
we will employ stratified randomization. The subjects will be stratified based on noise exposure 
survey responses (see table below), and will then be randomized to study groups. Randomization 
will be based on the randomization list generated by unblinded statistician using a computer 
algorithm written in SAS® using randomly selected blocks of sizes 3. Within each block of 3, 
there will be 1 subject assigned to each study group.  The random assignment of subjects to the 
different study groups will be associated with consecutively assigned random numbers which 
will be unique for each study subject. The stratified kit list will be provided to Advanced Rx who 
will package and label the drug for shipment to the pharmacist. Each kit will contain two bottles 
and will be labeled with the same kit number. The bottle will not contain any information of the 
treatment allocation. One interim analysis is planned, once 33% (n=78) of the subjects have 
completed participation in the study.  
 
 
Name 
Description 
1: High Noise 
Screening: 
   LENS-Q Adapted for Surgical Noise Study – 
1A Or 2A Or 4A =   
a.Daily, Or 
b.Less than daily/more than weekly, Or 
c.Weekly, Or 
d.Less than weekly/more than monthly Or 
e.Monthly 
OR 
1C Or 2C Or 3C >= 5 Years 
 


Statistical Analysis Plan V6.0 
Washington University 
PINIHL-WU Protocol V9.0 
21 Jun 2023 
Confidential 
Page 10 of 36 
Name 
Description 
2: Low Noise 
Screening: 
   LENS-Q Adapted for Surgical Noise Study – 
1A AND 2A AND 4A =   
f.Less than monthly/more than yearly, 
g.Yearly, 
h.Less than yearly Or 
i.Never 
OR 
1C AND 2C AND 3C < 5 Years 
 
 
 
2.5 
Treatment Assignment and Blinding 
 
To ensure double-blinding of the trial, each subject will be randomized to one of three treatment 
arms via an interactive randomization tool (IRT) and assigned to a study group. Once randomized, 
each subject will be provided a kit on the day of surgery that contains two bottles, with one package 
labeled to be taken prior to surgery, and another package designated to be taken within 12 hours 
after surgery or when patient is released clinically to oral medication. For subjects randomized to 
“ZNS pre-op”, the pre-op package will contain one ZNS capsule of 100 mg, and the post-op 
package will contain one placebo capsule that looks and tastes the same as ZNS capsules. For 
subjects randomized to “ZNS post-op”, the pre-op package will contain one placebo capsule and 
the post-op package will contain one ZNS capsule of 100 mg. For the subjects randomized to 
“placebo”, both pre- and post-op packages will contain capsules of placebo. 
 
The study will be “masked” or “blinded” in the sense that all the study subjects and the study 
team members will be blinded to the assignment in the study groups. Only the pharmacist who 
will prepare the study drug kits and the unblinded Statistician will have access to the kit 
assignments. A copy of the randomization kit list with study ID assignments will be saved in a 
limited access folder on a secure network server at Pharm-Olam. The Medical Monitor will be 
contacted in emergent medical cases when knowing the treatments assignment is mandatory for 
clinical care of the patient. 
 
At the time when we will need to “freeze” the data sets for purposes of developing the DSMB 
report, a series of SAS programs will be run from an independent programmer to produce data 
for each pairwise comparison into two subsets of data from the total cohort. Each subset will be 
de-identified. A previously prepared SAS code will be run in each subset and the output will be 
used to complete the table shells. Table shells will be blinded. If DSMB members find any safety 
issues, they may request specific unblinded data. The programmer preparing subsets will not be 
involved in the handling of data forms or the analysis of data. Table shells for DSMB (content 
and formats) will be agreed upon prior to start of study. 


Statistical Analysis Plan V6.0 
Washington University 
PINIHL-WU Protocol V9.0 
21 Jun 2023 
Confidential 
Page 11 of 36 
2.6 
Schedule of Assessments and Procedures 
Table below summarizes the calendar of study activities and assessments 
 
Screening / 
Baseline 
Surgery 
Post-op 
 
 
Within 30 days 
(+3 days) prior to 
surgery  
 
Within 12 
Hours 
Within 30 
days (+/- 3 
days) 
Informed 
consent 
X 
 
 
 
Clinical Exam 
X 
 
 
 
Demographic Info 
X 
 
 
 
Pre-Op Data 
(pregnancy test, lab 
results (electrolyte 
panel, BUN, Cr, 
ALT, and AST) 
X 
 
 
 
Current Meds 
X 
 
 
 
Questionnaire 
X 
 
 
X 
Audiogram 
X 
 
 
X 
ECochG 
X 
 
 
X 
DPOAE 
X 
 
X* 
X 
WIN 
X 
 
 
X 
Randomization 
X 
 
 
 
Oral Dose** 
 
X 
X 
 
Blood draw*** 
 
 
X 
 
AE assessment 
 
X 
X 
X 
* Within 8 hours 
**Dispensed on the day of surgery with instruction to take first dose prior to surgery and second 
dose after surgery.  
*** Plasma sample for PGx will be collected at baseline visit. Plasma sample for ZNS level and 
PGx, electrolyte panel, BUN, Cr, ALT, and AST will be collected 12 hours after first dose. 
 
2.7 
Sample Size Determination for The Primary Efficacy Outcome Measure 
The primary efficacy outcome will be the proportion of PTS positive subjects defined as the ratio 
of PTS-positive subjects to total number of subjects in each study arm/group. Using pilot data from 
a retrospective chart review of 75 similar patients undergoing >1-hour drill noise exposure, we 
estimate the proportion of PTS positive subjects in the placebo group will be 50%. We hypothesize 
that the expected effect of ZNS either pre-op or post-op will be a 50% reduction of the proportion 
of subjects with PTS positive as compared to placebo group. This is the desired clinically 
significant effect for treating hearing loss for single dose of 100 mg ZNS. 
 
The sample size for this study was calculated for the planned comparisons of each of the ZNS 
groups with the placebo group using a balanced design and a one-sided alpha level of 0.0125  
Based on the data from our retrospective study, using Fisher’s exact test we estimated that 78 
subjects in the ZNS group and 78 subjects in the placebo group will be needed to provide us with 
80.4 % power to detect a 50% reduction in the proportion of PTS positive subjects (from 50% to 


Statistical Analysis Plan V6.0 
Washington University 
PINIHL-WU Protocol V9.0 
21 Jun 2023 
Confidential 
Page 12 of 36 
25% corresponding to an absolute proportion difference of 25%) at the 1-sided alpha level of 
0.0125 for each ZNS-Placebo group comparison.  A total of 234 subjects will be enrolled to be 
randomized in this study. All efforts will be made minimize and eliminate drop outs.  Given the 
short term-follow-up of study subjects in a period where they are under medical care, few, if any, 
drop-outs or lost to follow-up are expected.  
 
Sample size calculations were carried out using PROC POWER procedure in SAS 9.4. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 


Statistical Analysis Plan V6.0 
Washington University 
PINIHL-WU Protocol V9.0 
21 Jun 2023 
Confidential 
Page 13 of 36 
3 
Study Outcomes 
3.1 
Primary estimand 
The primary estimand for the study is: In adults with no more than a mild to moderate high-
frequency hearing loss and who undergo drilling during skull-based surgery, what is the difference 
in the proportion of patients experiencing PTS in the contralateral ear (the proportion of PTS-
positive subjects defined as the ratio of PTS-positive subjects (defined as all subjects who in 
audiogram are identified as having a PTS of > 10 dB HL increase at any frequency between 2-6 
kHz post-surgery as compared to baseline audiogram) to total number of subjects in each study 
arm/group) between ZNS treatment compared to Placebo, 30 days (+/- 3 days) after randomization 
or death (whichever occurs first). 
 
3.2 
Primary Efficacy Outcome 
The study is designed to test the null hypothesis associated with the primary efficacy measure. The 
primary efficacy outcome will be the proportion of PTS-positive subjects defined as the ratio of 
PTS-positive subjects to total number of subjects in each study arm/group. PTS positive will be 
defined as all subjects who in audiogram are identified as having a permanent threshold shift (PTS) 
of >10db HL increase at any frequency between 2-6 kHz post-surgery as compared to baseline 
audiogram. A SAS code will be written to code all the patients for whom the difference at any 
frequency from 2-6 kHz in hearing thresholds (30 days (+/-3 days) post-surgery - Baseline) is ≥10 
dB HL as PTS-positive. If this difference will be less than 10dB then the patients will be coded as 
non-PTS positive.  
 
For the primary outcome measure, the null and alternative hypotheses for each pairwise 
comparison are provided below.  
 
3.2.1 Comparison of the proportion of PTS-positive patients between ZNS pre-op and 
Placebo  
H0 : 𝑝𝑝𝑍𝑍𝑍𝑍𝑍𝑍𝑝𝑝𝑝𝑝𝑝𝑝−𝑜𝑜𝑜𝑜−𝑝𝑝𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃= 0 
 
  HA : 𝑝𝑝𝑍𝑍𝑍𝑍𝑍𝑍𝑝𝑝𝑝𝑝𝑝𝑝−𝑜𝑜𝑜𝑜< 𝑝𝑝𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 
We hypothesize that ZNS pre-op will reduce the proportion of PTS-positive patients by 
an absolute difference of 25% as compared to placebo  
 
3.2.2 Comparison of the proportion of PTS-positive patients between ZNS post-op and 
Placebo  
H0 : 𝑝𝑝𝑍𝑍𝑍𝑍𝑍𝑍𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝−𝑜𝑜𝑜𝑜−𝑝𝑝𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃= 0 
 
  HA : 𝑝𝑝𝑍𝑍𝑍𝑍𝑍𝑍𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝−𝑜𝑜𝑜𝑜< 𝑝𝑝𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 
 
We hypothesize that ZNS post-op will reduce the proportion of PTS-positive patients by an 
absolute difference of 25% as compared to placebo. Our one-sided hypothesis is supported by 
animal studies, and lack of any evidence of hearing loss as a side effect of ZNS in human studies. 
The statistical testing will be performed using Bonferroni method to control for type I error rate 
at one-sided alpha level of 0.0125.  
 


Statistical Analysis Plan V6.0 
Washington University 
PINIHL-WU Protocol V9.0 
21 Jun 2023 
Confidential 
Page 14 of 36 
3.3 
Secondary efficacy outcomes 
The secondary outcome measures are key audiological and clinical assessments of hearing loss 
as listed below as continuous level variables.   
• DPOAE: Distortion product otoacoustic emissions will be measured at baseline (before 
surgery), as well as within 8 hours and at 30 days (+/- 3 days) post-surgery to measure 
both temporary and permanent change in DPOAE amplitude relative to baseline. A 
change is noted in DPOAE amplitude at any frequency that is significantly greater than 
the stability of each measurement (i.e., 95% confidence interval of each measurement do 
not overlap). 
• ECochG: Electrocochleography will be measured at baseline (before surgery) and at 30 
days (+/- 3 days) post-surgery to measure change in ECochG AP amplitude, latency, and 
width.  
• WIN testing: The Words in Noise Test will be administered at baseline (before surgery) 
and at 30 days (+/- 3 days) after surgery. The respective scores will be converted to Z-
scores to evaluate any change in scores relative to baseline.  
 
The study will also include an exploratory analysis aiming to identify biomarkers of response to 
ZNS.  
 
3.4 
Safety measures 
AE and SAE that are temporally related to the intervention (beginning at time of dose through 
post-dose) will be evaluated for regulatory reportability as per FDA and IRB requirements. The PI 
and study team will review data in real time for safety. We will closely monitor and report all AE 
and SAE in the study per requirement. 
 
Potential known side effects from the administration of ZNS: 
• Somnolence 
• Anorexia 
• Dizziness 
• Ataxia 
• Agitation/irritability 
• Difficulty with memory and/or concentration   
 
ZNS may cause serious side effects including: 
• Serious skin rash that can cause death. 
• Serious allergic reactions that may affect different parts of the body. 
• Less sweating and increase in body temperature (fever). 
• Suicidal thoughts or actions in some people. 
• Increased level of acid in blood (metabolic acidosis). 
• Problems with concentration, attention, memory, thinking, speech, or language. 
 
 


Statistical Analysis Plan V6.0 
Washington University 
PINIHL-WU Protocol V9.0 
21 Jun 2023 
Confidential 
Page 15 of 36 
4 
Analysis Populations 
 
4.1 
Target population 
Target population includes all patients that meet the inclusion/exclusion criteria as defined in the 
study protocol. 
 
4.2 
Intent-to-treat (ITT) sample 
ITT sample will include all subjects who are randomized. Following principles of intent-to-treat 
analysis all subjects will be analyzed in the treatment group they were randomized to when they 
were enrolled in the study. 
 
4.3 
The safety sample 
The safety sample will include subjects from the full analysis population who will be enrolled and 
will receive active or placebo ZNS. Adherence to protocol does not affect inclusion in safety 
population.  subjects are evaluated from the time of dose administration through two weeks post 
dose for drug related adverse events. 
 
4.4 
Per-protocol sample 
The per-protocol sample will be limited to subjects who will be randomized and treated in 
compliance with the protocol. Only observations or specimens collected according to the protocol 
will be included in the analyses using the per-protocol population. If a subject will receive one or 
more treatments out of compliance with the protocol schedule, any observations or specimens 
collected after the out-of-compliance treatment will be excluded from the analyses using the per-
protocol population.   
 
The overall timing associated with the study is based on our previous clinical study experience.  
Approximately 50 patients per year receive skull surgery that requires 1 hour or more of drilling 
time at Washington University School of Medicine (WU).  We estimate to finish the study within 
4 years.  If subject enrollment numbers are consistently below expectations as determined by the 
study team and DSMB, plans will be made to add additional sites or adjust study inclusion criteria 
(e.g. including head/skull surgeries requiring less than 1 hour of drilling time). 
 
Serious feasibility or design difficulties: If one year after the start of the trial, < 50% of the planned 
accrual goals are met, DSMB and the study team will discuss difficulties in recruitment. Patient 
remuneration will be revised, if needed. If there are not enough patients meeting 
inclusion/exclusion criteria, then the criteria will be revised without impacting study objectives. If 
there are not enough patients that undergo more than 1-hr drilling time during surgery, we will 
explore including into the study, patients with drilling time at least 45 minutes, expanding 
audiometric criteria, or expanding to different institutions. 
 
 


Statistical Analysis Plan V6.0 
Washington University 
PINIHL-WU Protocol V9.0 
21 Jun 2023 
Confidential 
Page 16 of 36 
5 
GENERAL ASPECTS FOR STATISTICAL ANALYSES 
5.1 
General Methods 
• All analyses and summaries will be produced using SAS® version 9.4 (or higher). 
• Standard descriptive statistics will be used to describe distribution of demographic, clinical, 
and audiometric characteristics as well as outcome measures for all the study samples listed 
in section 4. For continuous level characteristics Q-Q plots and Shapiro-Wilk test will be 
used to test assumption of normality. If continuous level data is found to be normally 
distributed data, mean and standard deviation will be used as descriptive statistics, and if the 
assumption of normality is violated, we will report median and range for description of these 
variables. Frequency and relative frequency will be used for description of categorical level 
variables. 
• The same number of decimal places as in the raw data will be presented when reporting 
range, 1 more decimal place than in the raw data will be presented when reporting the mean 
and median, and 2 more decimal places than in the raw data will be presented when reporting 
the standard deviation.  
• Unless stated otherwise, tabular summaries will present columns for the active treatment arm 
(“ZNS pre-op” and “ZNS post-op”), placebo arm, and overall. 
• Unless stated otherwise, the relative frequency will be based on the number of non-missing 
observations. The column header will still contain the number of subjects in the treatment 
group.  There will be a row for the number of non-missing observations in the table (at each 
time point, if required) for each variable being summarized.  
• Any calculated p-values will be presented to 3 decimal places; p-values less than 0.001 will 
be presented as ‘p<0.001’ and p-values greater than 0.999 will be presented as ‘p>0.999’. 
• All relevant subjects data will be included in listings and sorted by treatment group, subject 
ID, and visit, as applicable, for all randomized subjects.  
• Unscheduled or repeat assessments will not be included in summary tables unless specified. 
All assessments will be included in the subject listings. 
• All tables, listings and figures will include footers that identify the name of the program that 
created the output, together with the date and time on which it was created. Headers will 
include the total number of pages that the presentation contains and, for each page, the 
number of the page within the presentation. 
5.2 
Missing Data 
 
Every attempt will be made to ensure data completeness. We do not anticipate much loss to follow-
up because of the relatively short time follow-up interval. Conservatively, we would estimate that 
fewer than 5% of subjects will drop out/withdraw from the study. The subject will be withdrawn 
from the study follow-up and procedures if the subject withdraws consent, or the sponsor decides 
to close the study. 
 
Data loss, if any, would almost likely be due to subjects refusing to complete or not returning at 
all for the post-surgery assessment of PTS 30 days (+/- 3 days). If the subject reschedules the 
post-surgery appointment for a later date for any reason, and if this delay is within 30 days of the 


Statistical Analysis Plan V6.0 
Washington University 
PINIHL-WU Protocol V9.0 
21 Jun 2023 
Confidential 
Page 17 of 36 
scheduled date, the data will be considered valid and used in the efficacy analysis. Any measure 
outside this time window of +30 days will be defined and considered as missing data. 
 
Missing PTS at 30 days will be imputed using SAS PROC MI procedure within each treatment 
group using the distribution implied by the non-missing data for the specific treatment group.  
The SAS code below using Multiple Imputation by Chained Equations (MICE) via  the Fully 
Conditional Specification (FCS) statement will be used to impute the missing data under the 
missing at random (MAR) assumption.  
 
PROC MI DATA=X SEED=<value> NIMPUTE=10  OUT=MI_OUT1 NOPRINT; 
CLASS  GROUP; 
VAR AGE PTA LSurg………; 
FCS LOGISTIC(PTS);  
RUN; 
 
Each of the 10 complete data sets will be then analyzed using Fisher’s exact test. One-sided p-
value (p_i) from Fisher’s exact test will be converted to a z-value using the inverse Normal 
transformation [1,2], i.e. z_i=Φ^(-1) (1-p_i), where Φ^(-1) (∙) represents the inverse standard 
Normal cumulative distribution function. 
 
SAS funtion to convert Fisher’s exact P-value to Z-value is as follows: 
 
Z_i= QUANTILE('NORMAL', p_i, 0, 1); 
 
The estimated z-vales from  the 10 imputed datasets will be then combined following Rubin’s 
rules using PROC MIANALYZE procedure in SAS which will be of the form:  
 
 
PROC MIANALYZE DATA=Y; 
   MODELEFFECTS Z_i; 
   STDERR Z_i; 
   ODS OUTPUT ParameterEstimates=XX; 
RUN; 
 
The pooled estimate of z-vales from PROC MIANALYZE procedure will be then converted to 
probability value using the following SAS function: 
 
P_value=PROBNORM(estimate);  
 


Statistical Analysis Plan V6.0 
Washington University 
PINIHL-WU Protocol V9.0 
21 Jun 2023 
Confidential 
Page 18 of 36 
6 
STUDY SUBJECTS 
6.1 
Disposition of Subjects 
Subject disposition data will be summarized by treatment group and overall for the ITT Sample 
Set. The number randomised, treated, completed or discontinued from the study, including 
reasons for discontinuation as well as the number of subjects in each sample set and subject 
treatment status will be summarized descriptively.   
All disposition data will be listed. Inclusion and exclusion criteria will also be listed. 
6.2 
Demographics Characteristics 
Demographic characteristics will be summarized descriptively by treatment group for the Safety 
Sample Set, including: 
 
• Age (years) at time of consent    
• Sex 
• Ethnicity  
• Race  
 
Demographics characteristics will be listed.  
6.3 
Medical History and Surgical History 
Medical and surgical history will be coded with Medical Dictionary for Regulatory Activities 
(MedDRA) version 24.0 and summarized by System Organ Class (SOC), Preferred Term (PT), 
and by treatment group with counts and relative frequency based on the Safety Sample Set. A 
subject will only be counted once in an SOC and an SOC/PT combination. 
All medical history data will be listed. 
6.4 
Concomitant Medications  
Concomitant medications are defined as all medications (excluding study dose) taken on or after 
the date of first dose administration up to and including the date of the post operative Day 30 
visit.  
Medications that started before the date of first dose and are ongoing after the date of first dose 
will be considered as concomitant medications. 
Medications will be coded using the Anatomical Therapeutic Chemical (ATC) classification 
codes and preferred drug name according to the World Health Organization (WHO) Drug Global 
B3, (March 2021). Summary table will be provided for concomitant medications for the Safety 
Sample Set, presenting the number and relative frequency of subjects by treatment group, and 
will be sorted in alphabetical order of ATC Level 2 and then PT in the overall column. For each 
subject, the medication will be counted only once within a given ATC level 2 and only once 
within a given preferred drug name level. A subject may appear more than once if she has more 
than one concomitant medication coded under different ATC categories. 
Concomitant medications will be presented in a listing..  


Statistical Analysis Plan V6.0 
Washington University 
PINIHL-WU Protocol V9.0 
21 Jun 2023 
Confidential 
Page 19 of 36 
6.5 
Treatment Administration 
The number of doses taken will be summarized by treatment group and overall for the Safety 
Sample Set and include 
 
• Number and percentage of subjects who received dose 1 
• Number and percentage of subjects who received dose 2 
• Number and percentage of subjects who received both doses 
 
Dose administration information will be listed for all safety subjects. 
6.6 
Protocol Deviations 
Protocol deviations will be summarized for the Safety Sample Set by type of deviation. Protocol 
deviations for all subjects who signed an informed consent will be entered into Pharm-Olam’s 
Clinical Trial Management System. Examples of deviation types may include but are not limited 
to: 
• Inclusion/exclusion criteria not met 
• Informed consent 
• Randomization  
• Essential/Study Documents 
• Investigational product administration and handling 
• CRF/source data 
• Sample/tests handling 
• Equipment/Facilities 
• Visit procedures 
• Other 
Protocol deviations will be reviewed by Washington University and Pharm-Olam medical and 
clinical (including statistical) personnel and classified as major or minor deviations at a blinded 
data review meeting prior to database lock.  
Major protocol deviations are defined as those that may significantly impact the quality (i.e., 
completeness, accuracy, and reliability) or integrity of key trial data; or indicates systemic 
problem within the study or its conduct; or that might significantly impact the rights, safety or 
welfare or trial subjects. 
Protocol deviations will be presented in each deviation category as a major or minor deviation by 
treatment group. The total count of protocol deviations within each treatment group will be used 
as the denominator for relative frequency in this table. All protocol deviations will be presented 
in a data listing. 
 


Statistical Analysis Plan V6.0 
Washington University 
PINIHL-WU Protocol V9.0 
21 Jun 2023 
Confidential 
Page 20 of 36 
7 
EFFICACY ANALYSES 
All efficacy analyses will be carried out using the Intent-to-treat Sample and Per-Protocol 
Sample. 
7.1.1 Analysis of primary outcome variable 
 
Efficacy analysis at the end of the study 
 
The primary outcome measure for assessing effectiveness of ZNS (100 mg PO) either pre-op or 
post-op compared to the placebo group will be the proportion of subjects defined as PTS positive 
30 days (+/-3 days) after surgery.  
  
Audiogram will be performed to look for PTS. Patients for whom the difference at any frequency 
from 2-6 kHz in hearing thresholds (30 days (+/-3 days) post-surgery - Baseline) is ≥10 dB HL 
will be defined as PTS positive. Primary analysis and sensitivity analyses will be carried out on 
the primary endpoint. 
 
Primary analysis 
 
Frequency and relative frequency will be used to describe the distribution of the primary 
outcome measure in each study group. To assess efficacy, Fisher’s exact test will be used to 
compare the proportion of subjects with PTS positive in ZNS group with the proportion of 
patients with PTS positive in the placebo group.  
 
The confidence intervals will be calculated using method 10 described by Newcombe RG, 1998 
and also described by Altman et al.  
1. Altman, Douglas, et al., eds. Statistics with confidence: confidence intervals and 
statistical guidelines. https://www.amazon.com/Statistics-Confidence-Intervals-
Statistical-Guidelines/dp/0727913751 
 
Let n1 be the number of participants in placebo group, and r1 the number of participants with PTS 
in the placebo group.  p1=r1/n1 be the proportion of PTS in the placebo group, and q1=r2/n2the 
proportion of participants that do not have PTS in placebo group. 
l1 and u1 are the lower and upper limits of the 100(1-α)% confidence interval for p1 
Using Wilson method we calculate: 
 
 
 
 
 


Statistical Analysis Plan V6.0 
Washington University 
PINIHL-WU Protocol V9.0 
21 Jun 2023 
Confidential 
Page 21 of 36 
               
 
𝑧𝑧𝑎𝑎= the 100(1 −𝛼𝛼)𝑡𝑡ℎ percentile of the standard Normal distribution. 
Let n2 be the number of participants in ZNS group, and r2 the number of participants with PTS in 
the ZNS group.  p2=r2/n2 be the proportion of PTS in the ZNS group, and q2 the proportion of 
participants that do not have PTS in ZNS group.  
l2 and u2 are the lower and upper limits of the 100(1-α)% confidence interval for p2 
 
 
 
 
 
               
 
𝑧𝑧𝑎𝑎= the 100(1 −𝛼𝛼)𝑡𝑡ℎ percentile of the standard Normal distribution. 
 
The proportion difference between groups is: 
 
The lower (lD) and the upper limits (uD)of 100 (1-α)% confidence interval for D will be 
calculated as: 
 
 
 
 A supportive logistic regression analysis will be done with covariates: age, pre-op hearing 
dichotomized to normal to minimal hearing loss and slight to mild loss, noise exposure history 
dichotomized to high risk and low risk, exposure categorized as low (8-hour equivalent A-
weighted sound level in decibel (LAeq8hr) < 80 dBA), moderate (LAeq8hr > 80 dBA but < 90 
dBA), or high (LAeq8hr > 90 dBA). 
 
PROC LOGISTIC DATA=X; 
CLASS  GROUP; 
  MODEL PTS = COVARIATE1 COVARIATE2.. ;/*Covariates are as mentioned above*/ 
RUN; 
 
  
Sensitivity analysis of the primary endpoint 
 
The potential impact of missing primary endpoint data will be explored in sensitivity analyses 
using multiple imputation. Two sensitivity analyses performed: 


Statistical Analysis Plan V6.0 
Washington University 
PINIHL-WU Protocol V9.0 
21 Jun 2023 
Confidential 
Page 22 of 36 
 
Sensitivity 1: MI analysis under the missing not at random assumption (MNAR) 
Sensitivity 2: Logistic regression tipping point analysis under the assumption of data missing at 
random. 
 
Sensitivity 1 
Proc MI procedure in SAS will be used to impute missing data for study treatment groups using 
the distribution implied by the non-missing patient data within the placebo group. The SAS code 
to impute data for Sensitivity analysis 1 under the MNAR assumption will be of the form: 
 
PROC MI DATA=X SEED=<value> NIMPUTE=10  OUT=MI_OUT1 NOPRINT; 
CLASS  GROUP; 
VAR AGE PTA LSurg………; 
FCS LOGISTIC(PTS);  
RUN; 
Post imputation each of the imputed 10 datasets will be analyzed using the same approach as for 
the primary outcome measure. The estimates of the analysis of the 10 imputed datasets will be 
then combined following Rubin’s rules using PROC MIANALYZE procedure in SAS which will 
be of the form:  
 
PROC MIANALYZE PARMS=GMPARMS COVB=GMCOVB PARMINFO=GMPINFO WCOV BCOV 
    TCOV; / *dataset "gmparms" contains the estimates and associated standard errors 
for the mean parameters from each of the M=10 imputed data sets. 
dataset "gmcovb" contains the asymptotic covariance matrics 
dataset "gmpinfo" contains parameter info*/ 
 
    MODELEFFECTS INTERCEPT AGE PTA LSurg………; 
RUN; 
 
Sensitivity 2 
 
Multiple imputation will be used to impute data in each of the study groups. A progressive 
penalty of 𝛿𝛿𝑖𝑖= 𝑘𝑘𝑖𝑖× log (𝑂𝑂𝑂𝑂) will be added to imputed values in ZNS arm where (i) 𝑂𝑂𝑂𝑂 is the 
Odds ratio estimate for ZNS as compared to Placebo from the primary logistic regression 
analysis and (ii)  𝑘𝑘𝑖𝑖= 1, 0.95, 0.90, … 0.05, 0, 1.05, 1.10,… thus k ranges from 1 (equivalent to 
MI approach based on MAR) to 0 (or higher), until the conclusion of the primary analysis is 
overturned (i.e., p<0.05 is lost at, this value of 𝑘𝑘𝑖𝑖 being the ‘tipping point’). Rubin’s method will 
be used to combine the primary endpoint treatment effects across imputations for each value, 𝑘𝑘𝑖𝑖, 
of the penalty.  Forest plots will be used to graphically display the penalty value that results in 
loss of statistical significance.  
 
SAS code sample for Sensitivity analysis is provided below: 
**Step 1: Generate 10  datasets by imputing the missing data**; 
 
PROC MI DATA=X SEED=<value> NIMPUTE=10  OUT=MI_OUT1 NOPRINT; 
CLASS  GROUP; 
VAR AGE PTA LSurg………; 
FCS LOGISTIC(PTS);  
RUN; 
 
**Step 2: Generate 10 complete datasets from the 10 monotonized datasetsin Step 1 for 
missing values in the drug arm,  


Statistical Analysis Plan V6.0 
Washington University 
PINIHL-WU Protocol V9.0 
21 Jun 2023 
Confidential 
Page 23 of 36 
subtract DELTA derived above from their imputed data.**; 
proc mi data=YYY NIMPUTE=1 SEED=<value> OUT=YYY_shift; 
by group; 
class group; 
var AGE PTA LSurg………; 
monotone method=logistic; 
mnar adjust(PTS / shift=DELTA adjustobs=(group=’1’)); 
run; 
 
**Step 3: Apply the primary MMRM to the 10 complete datasets in Step 2**; 
proc genmod data=YYY_shift descending; 
by _imputation_; 
class group; 
model PTS = group AGE PTA LSurg………; 
ods output GEEModPEst=gmparms; 
run; 
 
 
**Step 4: Obtain the pooled inference from 10 sets of estimates from Step 3**; 
 
PROC MIANALYZE PARMS=GMPARMS COVB=GMCOVB PARMINFO=GMPINFO WCOV BCOV 
    TCOV;  
    MODELEFFECTS group; 
RUN; 
 
7.1.2 Analysis for secondary outcome measures. 
 
The focus of the study is to determine efficacy of ZNS for treatment of acute hearing loss based 
on the testing of hypothesis for primary outcome. In addition, we will also conduct analysis to 
evaluate other important audiologic measures. The secondary outcome measures are key 
audiological and clinical assessments of change in cochlear function and hearing loss: DPOAEs, 
ECochG, WIN testing. They will be measured as continuous level variables.  We do not plan any 
adjustment of alpha error for multiple comparisons. 
  
Analysis of variance (ANCOVA) will be used for comparison of outcome measures between 
each of the ZNS groups and placebo study group after controlling for baseline value and age,  
pre-op hearing dichotomized to normal to minimal hearing loss and slight to mild loss, noise 
exposure history dichotomized to high risk and low risk, exposure categorized as low (LAeq8hr 
< 80 dBA), moderate (LAeq8hr > 80 dBA but < 90 dBA), or high (LAeq8hr > 90 dBA). 
 
7.1.3 Pharmacogenetics analysis plan  
 
This analysis will be performed at the end of the trial by Gateway Biotechnology.  To identify 
genetic variants associated with ZNS protection against hearing loss, we will utilize genetic and 
metabolic data collected from patients in a genetic association study. Variables including sex, 
age, normalized values (Z-scores) of drug plasma concentration, Z-scores of noise intensity and 
duration, and Z-scores of hearing functions measured immediately following surgery will be 
included in the analysis of variance. Single-marker allelic association analyses will be conducted 
on the two imputed data sets using PLINK v1.07. The data will be analyzed with a logistic 
regression model on the additive continuous dosage of minor alleles from 0 to 2 to account for 
uncertainty of imputation. We will combine association results in the two cohorts by performing 


Statistical Analysis Plan V6.0 
Washington University 
PINIHL-WU Protocol V9.0 
21 Jun 2023 
Confidential 
Page 24 of 36 
a genome-wide inverse-variance weighting meta-analysis using PLINK v1.07, and assuming a 
fixed-effect model. Functional annotation of top-associated markers will be performed with R 
package NCBI2R 1.4.6 (http://CRAN.Rproject. org/package=NCBI2R), and key regional 
association plots of meta-analyzed results will be generated. To confirm whether these variants 
are specific to ZNS response, we will apply CEP SKAT to analyze genetic associations based on 
Z-scores of audiogram average threshold shifts and DPOAE amplitudes. All genetic variants, 
including both common and rare variants, will be included in this association study. Age, gender, 
drug concentration, and noise duration and intensity will be adjusted for the analysis. The 
analysis will also be performed using hearing data collected two weeks following surgery. The 
only differences will be a) using the Z scores of ECochG AP amplitude, latency, and width as 
well as WIN score, and b) using average audiogram threshold shifts and DPOAE amplitudes at 
30 days (+/- 3 days) post-treatment. We will also include metabolite profiling data to support 
potential genotypic responses to drug treatments. To control for confounding effects, these 
models will be adjusted for age, gender, and noise duration and intensity. Finally, the control and 
ZNS-treated comparisons will be performed using post-hoc comparisons with a Bonferroni 
adjustment for multiple comparison testing. Statistical analyses will be performed using the 
CEP-SKAT method in R language, and the statistical software SAS version 9.4 for Windows 
will be used for additional analysis.  
 
 
 


Statistical Analysis Plan V6.0 
Washington University 
PINIHL-WU Protocol V9.0 
21 Jun 2023 
Confidential 
Page 25 of 36 
8 
SAFETY ANALYSES 
All safety analyses will be carried out using the Safety Sample Set. 
Descriptive statistics will be used to summarize all AEs and SAEs. Frequency and relative 
frequency will be used to present the number of subjects with AEs, SAEs, and with each specific 
event. We will explore the expected and unexpected adverse events. 
8.1.1 Safety monitoring 
 
Adverse events will be tracked for the WU site from the time of dose administration through two 
weeks post dose for drug related adverse events Laboratory testing (electrolyte panel, BUN, Cr, 
ALT, and AST) done as part of the study conducted at WU site, will be collected post dose 
within 12 hours. In the event the lab values are not within normal limits post dose, the PI will be 
notified and recommend that the subjects be evaluated by his/her treating physician. Study 
subjects will remain in the study and lab tests repeated until within normal limits. All adverse 
events will be documented and assessed for relatedness to the study medication.  
 
The study team will monitor for adverse events on an ongoing basis. Once the team becomes 
aware of an adverse event, the AE will be reported according to institutional guidelines. 
Reporting requirements for Washington University study team may be found in Section 1.1 of 
protocol.  Reporting requirements for secondary site study teams participating in Washington 
University-coordinated research may be found in Section 1.2 of protocol. 
 
Early stopping rule related to serious adverse events: In the event of a serious adverse event, 
DSMB will evaluate the association of the serious adverse events with the study arm, break the 
blind if needed, and if found to be associated with treatment, DSMB will consider the study for 
revision or stopping.  
8.2 
Clinical Laboratory Tests 
 
Biochemistry blood tests will be performed at screening for all subjects.  
 
The following biochemistry laboratory parameters will be measured: Chloride, sodium, 
potassium, Carbon dioxide, Blood urea Nitrogen (BUN), creatinine, Alanine aminotransferase 
(ALT), Aspartate aminotransferase (AST). 
Laboratory test results will be summarized descriptively by treatment group using Safety 
Analysis Sample. 
 
All clinical laboratory results will be listed. Laboratory values that are outside the normal range 
will be flagged. 
8.3 
Clinical Examination of the Ears 
 
A clinical examination of ears will be performed at screening. Overall results will be recorded as 
Normal, Abnormal Not Clinically Significant, or Abnormal Clinically Significant. 
 


Statistical Analysis Plan V6.0 
Washington University 
PINIHL-WU Protocol V9.0 
21 Jun 2023 
Confidential 
Page 26 of 36 
The frequency and relative frequency of the overall assessment of the clinical examination will 
be summarized for screening visit by treatment group.  
 
Clinical examination results will be listed. 
 
8.4 
Electrocardiogram (ECG) 
 
A ECG was to be performed at screening for all subjects prior to protocol version 7.0, and no 
longer performed with changes in protocol 7.0. EGC parameters include heart rate, PR Interval, 
RR Interval, QRS Duration, QT Interval, and QTcF. Actual values of each ECG parameter at the 
screening visit will be summarized using descriptive statistics if requested upon final analysis. 
 
All ECG results will be listed if requested upon final analysis. 
 
8.5 
Pregnancy Test 
A pregnancy test (serum/urine) will be performed in female subjects of childbearing potential at 
screening. Pregnancy test results will be listed. 
 
 


Statistical Analysis Plan V6.0 
Washington University 
PINIHL-WU Protocol V9.0 
21 Jun 2023 
Confidential 
Page 27 of 36 
9 
INTERIM ANALYSIS  
A sponsor blinded interim analysis focused on the primary endpoint after 33% of the patients have 
completed participation in the study (26 in each group).  The independent programmer will prepare 
the datasets for each pairwise comparison (subsets of data) using a pre-prepared SAS code and 
will freeze them for the interim analysis. To ensure the double blinding of the study the subjects 
will not be presented in the assigned groups. The blinded statistician will estimate the overall 
proportion of PTS positive subjects in each group. Then one-sided Fisher’s exact test will be used 
to compare the proportion of subjects with PTS positive in ZNS group with the proportion of 
patients with PTS positive in the placebo group. one-sided p-value (𝑝𝑝𝑖𝑖) from Fisher’s Exact Test 
will be converted to a z-value using the inverse Normal transformation [1,2], i.e. 𝑧𝑧𝑖𝑖= Φ−1(1 −
𝑝𝑝𝑖𝑖), where Φ−1(∙) represents the inverse standard Normal cumulative distribution function.   
 
For each pair-wise comparison, with 33% information, the trial would be stopped for futility if the 
interim z-value <= 0.6850  for either or both comparisons, corresponding to a conditional power 
of ≤10% for each comparison. This design would provide 79.6% overall power (i.e. the probability 
of passing futility and reaching p<0.0125 for one or both comparisons in the final analysis would 
be 79.6%). 
 
Based on interim analysis the following actions may be taken: 
• Stop only one of the ZNS groups for futility 
• Stop the trial (both ZNS groups) for futility 
• Continue the trial as planned.  
 
 
 


Statistical Analysis Plan V6.0 
Washington University 
PINIHL-WU Protocol V9.0 
21 Jun 2023 
Confidential 
Page 28 of 36 
10 SOFTWARE AND PROGRAMMING SPECIFICATIONS 
All datasets, TLFs, and statistical analyses will be generated using SAS, Release 9.4 or higher 
(SAS Institute Inc., Cary, NC, USA). Computer-generated datasets, table, listing and figure 
output will adhere to the following specifications: 
10.1 General Programming Specifications 
• One SAS program can create several outputs or a separate SAS program can be created for 
each output at statistical programmer’s discretion. 
• Each output will be stored in a separate file. 
• Dataset files will be delivered in SAS7BDAT format. 
• TLF output files will be delivered in Word format / rtf format (or in pdf format if sponsor 
requests). 
 
10.1.1 
General 
• All TLFs will be produced in landscape format, unless otherwise specified. 
• All TLFs will be produced using the Courier New font, size 8, in sentence case. 
• The data displays for all TLFs will have a 1.5-inch binding margin on top of a landscape 
oriented page and a minimum 1-inch margin on the other 3 sides. 
• Headers and footers for figures will be in Courier New font, size 8, in sentence case. 
• Legends will be used for all figures with more than 1 variable, group, or item displayed. 
• TLFs will be in black and white (no color), unless otherwise specified. 
• Specialized text styles, such as bolding, italics, borders, shading, and superscripted and 
subscripted text, will not be used in the TLFs, unless otherwise specified. On some 
occasions, superscripts 1, 2, or 3 may be used (see below). 
• Only standard keyboard characters will be used in the TLFs. Special characters, such as non-
printable control characters, printer-specific, or font-specific characters, will not be used. 
Hexadecimal-derived characters will be used, where possible, if they are appropriate to help 
display math symbols (e.g., μ). Certain subscripts and superscripts (e.g., cm2, Cmax) will be 
employed on a case-by-case basis. 
• 
Mixed case will be used for all titles, footnotes, column headers, and programmer-supplied 
formats, as appropriate. 
 
10.1.2 
Headers 
• All output should have the following header at the top left of each page: 
 
Washington University School of Medicine  
Protocol: PINIHL-WU 
Data Cutoff Date: ddMonyyyy  


Statistical Analysis Plan V6.0 
Washington University 
PINIHL-WU Protocol V9.0 
21 Jun 2023 
Confidential 
Page 29 of 36 
• All output should have Page n of N at the top or bottom right corner of each page. TLFs 
should be internally paginated in relation to the total length (i.e., the page number should 
appear sequentially as page n of N, where N is the total number of pages in the table). 
• The date (date output was generated) should appear along with program name and location as 
the last footer on each page. 
 
10.1.3 
Display Titles 
Each TLF should be identified by the designation and a numeral. (i.e., Table 14.1.1). ICH E3 
numbering is strongly recommended but sponsor preferences should be obtained prior to final 
determination. A decimal system (x.y and x.y.z) should be used to identify TLFs with related 
contents. The title is centered. The sample set should be identified on the line immediately 
following the title. The title and table designation are single spaced. A solid line spanning the 
margins will separate the display titles from the column headers. There will be 1 blank line 
between the last title and the solid line. 
Table x.y.z 
First Line of Title 
Second Line of Title (if needed) 
Sample Set 
 
10.1.4 
Column Headers 
• Column headings should be displayed immediately below the solid line described above in 
initial upper-case characters.  
• For numeric variables, include “unit” in column or row heading when appropriate. 
• Sample set sizes will be presented for each treatment group in the column heading as (N=xx) 
(or in the row headings if applicable). This is distinct from the ‘n’ used for the descriptive 
statistics representing the number of subjects in the sample set. 
 
10.1.5 
Body of the Data Display 
10.1.5.1 
General Conventions 
Data in columns of a table or listing should be formatted as follows: 
• 
alphanumeric values are left-justified; 
• 
whole numbers (e.g., counts) are right-justified; and 
• 
numbers containing fractional portions are decimal aligned. 
 
10.1.5.2 
Table Conventions 
• Units will be included where available. 
• If the categories of a parameter are ordered, then all categories between the maximum and 
minimum category should be presented in the table, even if n=0 for all treatment groups in a 


Statistical Analysis Plan V6.0 
Washington University 
PINIHL-WU Protocol V9.0 
21 Jun 2023 
Confidential 
Page 30 of 36 
given category that is between the minimum and maximum level for that parameter. For 
example, the frequency distribution for symptom severity would appear as: 
Severity Rating 
N 
severe 
0 
moderate 
8 
mild 
3 
Where relative frequencies are presented in these tables, zero relative frequencies will not be 
presented and so any counts of 0 will be presented as 0 and not as 0 (0%). 
• If the categories are not ordered (e.g., Medical History, Reasons for Discontinuation from the 
Study, etc.), then only those categories for which there is at least 1 subject represented in 1 or 
more groups should be included. 
• An Unknown or Missing category should be added to any parameter for which information is 
not available for 1 or more subjects.  
• Unless otherwise specified, the estimated mean and median for a set of values should be 
printed out to 1 more significant digit than the original values, and standard deviations should 
be printed out to 2 more significant digits than the original values. The minimum and 
maximum (range) should report the same significant digits as the original values. For 
example, for systolic blood pressure: 
N 
  XX 
Mean 
XXX.X 
Std Dev 
 X.XX 
Median 
XXX.X 
Range 
XXX - XXX 
• P-values should be output in the format: “0.xxx”, where xxx is the value rounded to 3 
decimal places. Any p-value less than 0.001 will be presented as <0.001. If the p-value 
should be less than 0.0001 then present as <0.0001. If the p-value is returned as >0.999 then 
present as >0.999 
• Relative frequency values should be printed to one decimal place, in parentheses with no 
spaces, one space after the count (e.g., 7 (12.8%), 13 (5.4%)). Values that round down to 0.0 
will be displayed as ‘<0.1’. Unless otherwise noted, for all relative frequencies, the number 
of subjects in the sample set for the treatment group who have an observation will be the 
denominator. Relative frequency after zero counts should not be displayed and Relative 
frequency percentages equating to 100% should be presented as 100%.  
• Unless otherwise specified, tabular displays of data for medical history, concomitant 
medications, and all tabular displays of adverse event data should be presented by the body 
system, drug class, or SOC by decreasing frequency, assuming all terms are coded. Within 
the body system, drug class and SOC, medical history (by preferred term), drugs (by ATC 
code), and adverse events (by preferred term) should be displayed in order of decreasing 
frequency. If incidence for more than 1 term is identical, they should then be sorted 
alphabetically. Missing descriptive statistics or p-values which cannot be estimated should be 
reported as “-”. 
• The relative frequency of subjects is normally calculated as a proportion of the number of 
subjects assessed in the relevant treatment group (or overall) for the sample set presented. 
However, careful consideration is required in many instances due to the complicated nature 


Statistical Analysis Plan V6.0 
Washington University 
PINIHL-WU Protocol V9.0 
21 Jun 2023 
Confidential 
Page 31 of 36 
of selecting the denominator, usually the appropriate number of subjects exposed. Describe 
details of this in footnotes or programming notes. 
• For categorical summaries (number and relative frequency of subjects) where a subject can 
be included in more than one category, describe in a footnote or programming note if the 
subject should be included in the summary statistics for all relevant categories or just 1 
category and the criteria for selecting the criteria.  
• 
Where a category with a subheading (such as system organ class) has to be split over more 
than one page, output the subheading followed by “(cont)” at the top of each subsequent 
page.  The overall summary statistics for the subheading should only be output on the first 
relevant page. 
 
10.1.5.3 
Listing Conventions 
• Listings will be sorted for presentation in order of treatment groups as above, subject 
number, visit/collection day, and visit/collection time. 
• Missing data should be represented on subject listings as either a hyphen (“-”) with a 
corresponding footnote (“- = unknown or not evaluated”), or as “N/A”, with the footnote 
“N/A = not applicable”, whichever is appropriate. 
• Dates should be printed in SAS® DATE9.format (“DDMMMYYYY”: 01JUL2000). Missing 
portions of dates should be represented on subject listings as dashes (--JUL2000). Dates that 
are missing because they are not applicable for the subject are output as “N/A”, unless 
otherwise specified. 
• All observed time values must be presented using a 24-hour clock HH:MM or HH:MM:SS 
format (e.g., 11:26 or 11:26:45). Time will only be reported if it was measured as part of the 
study. 
• Units will be included where available. 
 
10.1.6 
Footnotes 
• A solid line spanning the margins will separate the body of the data display from the 
footnotes.  
• All footnotes will be left justified with single-line spacing immediately below the solid line 
underneath the data display. 
• Footnotes should always begin with “Note:” if an informational footnote, or 1, 2, 3, etc. if a 
reference footnote. Each new footnote should start on a new line where possible. 
• Footnotes will be present on the page where they are first referenced and thereafter on each 
page of the table, unless the footnote is specific only to certain pages. subject specific 
footnotes should be avoided. 
• Footnotes will be used sparingly and must add value to the table, figure, or data listing. If 
more than six lines of footnotes are planned, then a cover page may be used to display 


Statistical Analysis Plan V6.0 
Washington University 
PINIHL-WU Protocol V9.0 
21 Jun 2023 
Confidential 
Page 32 of 36 
footnotes, and only those essential to comprehension of the data will be repeated on each 
page.  
• The last 2 lines of the footnote section will be a standard source that indicates the name of the 
program used to produce the data display, date and time the program was run, and the listing 
source (or data source for a listing) (i.e., ‘Program: myprogram.sas    Listing source: 
16.x.y.z’). 
 


Statistical Analysis Plan V6.0 
Washington University 
PINIHL-WU Protocol V9.0 
21 Jun 2023 
Confidential 
Page 33 of 36 
11 
QUALITY CONTROL 
11.1 Specifications 
Once the SAP is finalized, dataset and TLF specifications will be developed and reviewed by the 
study team. An internal round table review of draft specifications will be conducted by the Lead 
Programmer, Lead Validator, Lead Statistician and Senior Reviewer (or member of Statistics 
Management).  
The client will have the opportunity to review, comment and approve (via signature) all dataset 
and TLF specifications. 
11.2 Outputs 
Validation of analysis datasets and tables are conducted through independent parallel 
programming of the statistical output according to the agreed upon specifications defined in the 
protocol, SAP, table shells, and dataset specifications. In this process, two programmers working 
independently (i.e., without input from one another), program the same output and compare 
results (via SAS PROC COMPARE). Any discrepancies are discussed and resolved, and the 
validation cycle is repeated until no further differences are noted between the two outputs.   
All programs are submitted in batch mode to document the results of the PROC COMPARE 
indicating no unequal observations. Additionally, tracking logs are maintained which document 
all QC and validation findings and their resolution.  
For CDISC datasets the Pinnacle 21 report will be used to validate the datasets for CDISC 
compliance. 
Once the validation cycle is complete, the output (dataset or TLF) is provided for the lead 
statistician’s review as well as an internal round table review including the Lead Programmer, 
Lead Validator, Lead Statistician and Senior Reviewer (or member of Statistics Management).  
For the delivery of the outputs for the Blinded Data Review Meeting (BDRM) the following 
team members from Pharm-Olam may join the output review round table as well: Medical Writer 
(if applicable), Data Manager (if applicable), Medical Monitor (if applicable) and Project 
Manager (if applicable).  
The client will have the opportunity to review, comment and approve (via signature) all final 
datasets and TLFs as well.  
 
 
 
 
 


Statistical Analysis Plan V6.0 
Washington University 
PINIHL-WU Protocol V9.0 
21 Jun 2023 
Confidential 
Page 34 of 36 
12 APPENDICES 
12.1 Index of Proposed Tables  
 
Table Number 
Table Title 
Sample Set 
Table 14.1.1 
Subject Disposition 
ITT Sample Set 
Table 14.1.2 
Protocol Deviation 
Safety Sample Set 
Table 14.1.3 
Demographic and Baseline Characteristics 
Safety Sample Set 
Table 14.1.4 
Medical and Surgical History 
Safety Sample Set 
Table 14.1.5 
Concomitant Medications 
Safety Sample Set 
Table 14.1.6 
Study Dose Administration 
Safety Sample Set 
Table 14.2.1.1 
Primary Efficacy Analysis: Permanent Threshold Shift 
(PTS) in the Contralateral Ear Using Audiogram 
ITT Sample Set 
Table 14.2.1.2 
Primary Efficacy Analysis: Permanent Threshold Shift 
(PTS) in the Contralateral Ear Using Audiogram 
PP Sample Set 
Table 14.2.1.3 
Sensitivity Analysis 1: Permanent Threshold Shift 
(PTS) in the Contralateral Ear Using Audiogram 
ITT Sample Set 
Table 14.2.1.4 
Sensitivity Analysis 1: Permanent Threshold Shift 
(PTS) in the Contralateral Ear Using Audiogram 
PP Sample Set 
Table 14.2.1.5 
Sensitivity Analysis 2: Permanent Threshold Shift 
(PTS) in the Contralateral Ear Using Audiogram 
ITT Sample Set 
Table 14.2.1.6 
Sensitivity Analysis 2: Permanent Threshold Shift 
(PTS) in the Contralateral Ear Using Audiogram 
PP Sample Set 
Table 14.2.1.7 
Audiogram Results on Hearing Thresholds: Actual and 
Change from Baseline 
ITT Sample Set 
Table 14.2.1.8 
Audiogram Results on Hearing Thresholds: Actual and 
Change from Baseline 
PP Sample Set 
Table 14.2.2.1 
DPOAE OAE Amplitude: Actual and Change from 
Baseline 
ITT Sample Set 
Table 14.2.2.2 
DPOAE OAE Amplitude: Actual and Change from 
Baseline 
PP Sample Set 
Table 14.2.2.3 
DPOAE Noise Floor: Actual and Change from 
Baseline 
ITT Sample Set 
Table 14.2.2.4 
DPOAE Noise Floor: Actual and Change from 
Baseline 
PP Sample Set 
Table 14.2.3.1 
ECochG Results: Actual and Change from Baseline 
ITT Sample Set 
Table 14.2.3.2 
ECochG Results: Actual and Change from Baseline 
PP Sample Set 
Table 14.2.4.1 
WIN Test: Actual and Change from Baseline 
ITT Sample Set 
Table 14.2.4.2 
WIN Test: Actual and Change from Baseline 
PP Sample Set 
Table 14.3.1.1 
Overall Summary Adverse Events 
Safety Sample Set 
Table 14.3.1.2 
Summary of Treatment-Emergent Adverse Events by 
System Organ Class and Preferred Term 
Safety Sample Set 


Statistical Analysis Plan V6.0 
Washington University 
PINIHL-WU Protocol V9.0 
21 Jun 2023 
Confidential 
Page 35 of 36 
Table Number 
Table Title 
Sample Set 
Table 14.3.1.3 
Summary of Serious Treatment Emergent Adverse 
Events 
Safety Sample Set 
Table 14.3.1.4 
Summary of TEAEs by severity using the Common 
Terminology Criteria for Adverse Events (CTCAE 
grades) by Maximum-reported Severity 
Safety Sample Set 
Table 14.3.1.5 
Summary of Related Treatment Emergent Adverse 
Events 
Safety Sample Set 
Table 14.3.1.6 
Summary of TEAEs Leading to Study Drug 
Interruption 
Safety Sample Set 
Table 14.3.1.7 
Summary of TEAEs Leading to Study Drug 
Withdrawn 
Safety Sample Set 
Table 14.3.2 
Summary of Biochemistry Lab Results at Screening  
Safety Sample Set 
Table 14.3.3.1 
Overall Summary of Physical Examination of Ears 
Results at Screening 
Safety Sample Set 
 
12.2 Index of Proposed Listings 
 
Listing Number 
Listing Title 
Sample Set 
Listing 16.1.1 
Subject Enrollment and Disposition All Subjects 
All Subjects 
Listing 16.1.2.1  
Subject Inclusion and Exclusion Criteria  
All Subjects 
Listing 16.1.2.2  
Protocol Deviations  
All Subjects 
Listing 16.1.3 
Demographic Characteristics 
All Subjects 
Listing 16.1.4 
Medical and Surgical History 
Safety Sample Set 
Listing 16.1.5 
Hearing History and Occupation Exposure 
Safety Sample Set 
Listing 16.1.6 
Concomitant Medications 
Safety Sample Set 
Listing 16.1.7 
Study Drug Administration 
Safety Sample Set 
Listing 16.2.1 
Audiogram Results on Hearing Thresholds 
ITT Sample Set 
Listing 16.2.2 
Distortion Product Otoacoustic Emissions (DPOAE) 
Results 
ITT Sample Set 
Listing 16.2.3 
Electrocochleography (ECochG) Results ITT Analysis 
Set 
ITT Sample Set 
Listing 16.2.4 
Word in Noise (WIN) Test Results ITT Analysis Set 
ITT Sample Set 
Listing 16.2.5 
LENS-Q Adapted for Surgical Noise Study Results at 
Screening ITT Analysis Set 
ITT Sample Set 
Listing 16.3.1.1 
Serious Adverse Events 
Safety Sample Set 
Listing 16.3.1.2 
Adverse Events Resulting in Death 
Safety Sample Set 
Listing 16.3.1.3 
Treatment-emergent Adverse Events 
Safety Sample Set 
Listing 16.3.1.4 
Treatment-emergent Adverse Events leading to Study 
Drug Interruption 
Safety Sample Set 
Listing 16.3.1.5 
Treatment-emergent Adverse Events leading to Study 
Drug Withdrawn 
Safety Sample Set 


Statistical Analysis Plan V6.0 
Washington University 
PINIHL-WU Protocol V9.0 
21 Jun 2023 
Confidential 
Page 36 of 36 
Listing Number 
Listing Title 
Sample Set 
Listing 16.3.2.1 
Clinical Laboratory Results at Screening: Biochemistry Safety Sample Set 
Listing 16.3.2.2 
Pregnancy Test at Screening 
Safety Sample Set 
Listing 16.3.3 
Physical Examination of Ears at Screening 
Safety Sample Set 
 
12.3 Index of Proposed Figures  
 
Figure Number 
Figure Title 
Sample Set 
Figure 14.1.1 
QQ Plot for Age 
Safety Sample Set 
Figure 14.1.2 
QQ Plot for Biochemistry Lab Parameters 
Safety Sample Set 
Figure 14.2.1 
QQ Plot for Distortion Product Otoacoustic Emissions 
(DPOAE) OAE Amplitude 
ITT Sample Set 
Figure 14.2.2 
QQ Plot for Distortion Product Otoacoustic Emissions 
(DPOAE) Noise Floor Amplitude 
ITT Sample Set 
Figure 14.2.3 
QQ Plot for Electrocochleography 
(ECochG)Parameters 
ITT Sample Set 
Figure 14.2.4 
QQ Plot for Word in Noise (WIN) Test Parameters 
ITT Sample Set