Symptom Screening Linked to Care Pathways for Children With Cancer: a Cluster Randomized Trial
Phase: NA
Conditions: Pediatric Cancer, Quality of Life
Sponsor: The Hospital for Sick Children

Symptom Screening Linked to Care Pathways for Pediatric Patients with Cancer: a 
Cluster Randomized Trial 
This supplement contains the following items: 
1. Final Protocol (version date: 21Nov2023) with document history and summary of 
amendments table p. 2
2. Original Protocol (version date: 26Feb2020) p. 19
3. Original and Final Statistical Analysis Plan (version date: 21Nov2023 ) (no amendments 
made) p. 32 

 
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Protocol Title: Symptom Screening Linked to Care Pathways for Children with Cancer: a 
Cluster Randomized Trial 
 
Date: November 21, 2023 
 
Sponsor/Coordinating Center:  
The Hospital for Sick Children  
555 University Avenue  
Toronto, Ontario 
M5G 1X8 
 
Principal Investigators: 
 
Lillian Sung, MD PhD 
The Hospital for Sick Children  
555 University Avenue  
Toronto, Ontario 
M5G 1X8 
416-813-7654 x 305287 
 
Lee Dupuis, RPh, ACPR, FCSHP, PhD 
The Hospital for Sick Children  
555 University Avenue  
Toronto, Ontario  
M5G 1X8 
416-813-7654 x 309355 
 
Allison Grimes, MD 
University of Texas Health Science Center at San Antonio  
7703 Floyd Curl Dr, MC7810 
San Antonio, Texas 
78229 
210-567-7477 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
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BACKGROUND 
 
 
Over the last few decades, impressive gains in survival for children and adolescents with 
cancer have been made and now, more than 82% of children with cancer will be cured.1 These 
survival gains have been, in part, attributable to the provision of intensive therapies. However, 
as a result, most children suffer and experience severe and distressing treatment-related 
symptoms such as pain, fatigue and nausea.2 In our cross-sectional study of 302 inpatients 8-18 
years of age, when asked about yesterday or today, 99% of children experienced at least one 
bothersome symptom and 60% experienced at least one severely bothersome symptom, 
including severe pain in 22% and severe fatigue in 33%.3 Symptoms are important; we 
previously demonstrated a strong correlation between increasing symptom burden and worse 
quality of life (QoL) in children receiving cancer treatments.3 Given excellent survival outcomes, 
we now need to focus more attention on symptom control.   
 
To gain insight into why symptoms are uncontrolled, we evaluated 168 children and 
described the extent to which symptoms self-reported as severely bothersome were 
documented in the health record and for which any interventions were provided.4 We created a 
standard operating procedure and a list of synonyms that met criteria for documentation of 
symptoms. For example, “tired”, “feel weak”, “low energy”, and “sluggish” were all considered 
adequate documentation for fatigue. We also created a list of possible interventions for each 
symptom. For most of the symptoms measured (12/15), severely bothersome symptoms were 
documented in the health record less than 60% of the time. The most infrequently documented 
severely bothersome symptoms were problems with thinking or remembering things (0%), 
changes in how your body or face look (4.8%), changes in taste (7.7%) and tingly or numb 
hands or feet (11.1%). Only two severely bothersome symptoms were documented at least 80% 
of the time, namely hurt or pain (92.6%) and throwing up or feeling like you might throw up 
(92.6%). 
 
Provision of an intervention to address severely bothersome symptoms occurred less than 
60% of the time for 10 of 15 symptoms. The most infrequently treated severely bothersome 
symptoms were thinking or remembering things (0%), changes in how your body or face look 
(0%), tingly or numb hands or feet (0%), changes in taste (0%), diarrhea (0%) and feeling tired 
(1.6%). Intervention provision was most common for hurt or pain (96.3%), headache (89.5%), 
throwing up or feeling like you might throw up (88.9%) and constipation (84.2%). However, even 
when interventions were provided, they were often not prescribed specifically for that symptom 
(for example, acetaminophen for fever rather than pain). 
 
Within the adult oncology setting, screening and assessment of symptoms through patient 
self-report has been identified as an important priority.5-8 In adult cancer patients, routine 
collection of patient-reported outcomes (PROs) improves patient-clinician communication9, 
reduces distress10 and improves QoL.11,12 Furthermore, a recent randomized trial showed that 
routine PRO assessment may improve survival in adult patients with metastatic solid tumors.13 
Among participants that were randomized to symptom screening vs. standard of care, median 
overall survival was 31.2 months (95% confidence interval (CI) 24.5 to 39.6) in the symptom 
screening group vs. 26.0 months (95% CI 22.1 to 30.9) in the standard of care group (P=0.03). 
Consequently, routine assessment of PROs is now considered essential to high quality care.11 It 
is also known that delivery of care consistent with clinical practice guidelines (CPGs) can 
improve patient outcomes. For example, timely administration of CPG-consistent antibiotics to 
adult patients with fever and neutropenia resulted in significantly lower mortality compared to 
patients who did not receive CPG-consistent antibiotics.14 However, adherence to CPGs is 
generally poor.15,16  
 
In contrast to these accomplishments in adults, efforts in children are limited.17 To help 
address this gap, we developed SSPedi (Symptom Screening in Pediatrics Tool; Appendix 
1)18,19 and SPARK (Supportive care Prioritization, Assessment and Recommendations for Kids; 
Appendix 2). SSPedi is a self-reported 15-item symptom screening tool for children receiving 
cancer treatments. SSPedi consists of the following 15 items: disappointed or sad, scared or 
worried, cranky or angry, problems thinking, body or face changes, tiredness, mouth sores, 

 
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headache, other pain, tingling or numbness, throwing up, hunger changes, taste changes, 
constipation and diarrhea. We developed SSPedi because our previous work concluded that 
then-available pediatric cancer symptom assessment tools were not appropriate for clinical use 
due to length or content.20 Items were generated using a nominal group technique among 
pediatric cancer clinicians and a patient advocate.20 Next, based upon input from 50 children 
receiving cancer treatments and 20 parents of pediatric oncology patients, we refined the paper 
and electronic versions of SSPedi and confirmed content validity, understandability and ease of 
use.20-22 The electronic version of SSPedi has an audio feature that allows specific questions or 
the entire instrument to be read aloud. A help feature provides synonyms for each symptom; 
these were derived from children themselves during cognitive interviews. 
 
Next, we conducted a multi-center study in the US and Canada to evaluate the 
psychometric properties of SSPedi. SSPedi was shown to be reliable (internal consistency and 
test re-test and inter-rater reliability), valid (construct validity) and responsive to change in 502 
English-speaking children 8-18 years of age receiving cancer therapies.3 More specifically, the 
intraclass correlation coefficients (ICC) were 0.88 (95% CI 0.82 to 0.92) for test re-test reliability, 
and 0.76 (95% CI 0.71 to 0.80) for inter-rater reliability between children and parents. Mean 
difference in SSPedi scores between groups hypothesized to be more and less symptomatic 
was 7.8 (95% CI 6.4 to 9.2; P<0.001).3 Construct validity was demonstrated as all hypothesized 
relationships among measures were observed. SSPedi was responsive to change; those who 
reported they were much better or worse on a global symptom change scale had significantly 
changed from their baseline score (mean absolute difference 5.6, 95% CI 3.8 to 7.5; P<0.001). 
This instrument has been translated into Spanish; the translated version is satisfactory to use in 
the US and Canada based on understandability and cultural relevance. 
 
Building upon SSPedi, SPARK is a web-based application that consists of two components: 
(1) a symptom screening component centered on SSPedi; and (2) a supportive care CPG 
component. While SSPedi asks children about symptoms, SPARK facilitates access to SSPedi, 
encourages symptom screening, generates reports and allows children to track their symptoms. 
In addition, when used by healthcare providers, SPARK links the symptoms identified using 
SSPedi with CPGs to manage them. CPGs contained within SPARK are those endorsed by the 
Children’s Oncology Group (COG) and thereby meet minimum specific criteria with respect to 
methodological rigor and relevance to pediatric oncology.23 
 
 
AIMS 
 
Aims 1 and 2: Among children with newly diagnosed cancer, to determine if symptom screening 
and feedback to healthcare providers at least three times weekly and locally-adapted symptom 
management care pathways, when compared to usual care: 
Aim 1. Improves overall self-reported symptom scores (total SSPedi score), fatigue 
(PROMIS–Fatigue) and cancer-specific QoL (PedsQL 3.0 Acute Cancer Module) over 8 
weeks 
Hypothesis: Symptom screening and care pathways will improve symptoms, fatigue and 
QoL 
Aim 2. Improves symptom documentation, increases provision of interventions for 
symptoms, and reduces emergency department visits and unplanned clinic visits and 
hospitalizations over 8 weeks 
Hypotheses: Symptom screening and care pathways will increase symptom 
documentation and provision of interventions for symptoms, and will reduce healthcare 
utilization. 
Aim 3: As an exploratory aim, we will evaluate key elements of the intervention related to the 
external validity and generalizability of the intervention effects using the RE-AIM framework.  

 
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METHODS 
 
Overall Strategy 
 
This is a cluster randomized trial including 20 pediatric oncology sites. The coordinating 
center is The Hospital for Sick Children in Toronto, Canada. Sites will be randomized to either 
systematic symptom screening via SPARK with provision of symptom reports to healthcare 
providers containing links to care pathways for symptom management (intervention) or usual 
care (control).  
 
Research Methods 
Eligibility: We will include children with cancer who: (1) are 8-18 years of age at enrollment 
(SSPedi is validated in this age range); (2) are English or Spanish-speaking (all PROs are 
validated in these languages in this age range); (3) have any newly diagnosed cancer; (4) have 
a plan for any chemotherapy, radiotherapy or surgery; (5) have a plan to be followed by or 
receive care from the study institution for ≥ 50% of the 8-week study period and expected to be 
available on site or virtually for the week 8 assessment and (6) enroll within 28 days after 
diagnosis or treatment initiation, whichever occurs later. Exclusion criteria will be cognitive 
disability (attending lower than second grade or equivalent) or visual impairment (cannot see 
SPARK even with corrective lens).   
 
 
Procedures: In this cluster randomized trial, we will randomize sites to either intervention or 
control groups. At both intervention and control sites, we will enroll participants within 28 days 
after diagnosis or treatment initiation, whichever occurs later. Eligible participants will be 
identified by site personnel and the study will be explained to them by trained research team 
members. Participant capacity to consent will be assessed by the clinical or research team 
according to institutional standards. After the study has been explained and sufficient time has 
been provided to ensure all questions have been answered, informed consent and assent will 
be obtained from participants and guardians as appropriate. For those who decline to contribute 
PROs, they will be given the option to only participate in a retrospective chart review to evaluate 
symptom documentation, intervention provision and healthcare utilization. Careful tracking of all 
newly diagnosed patients by site research personnel will occur to determine how many patients 
are approached and consented, and where possible, reasons for declining participation.  
 
For all enrolled participants who will be contributing PROs (excluding those only involved in 
the retrospective chart review), a personal SPARK account will be created to allow SSPedi to be 
completed and symptom results to be recorded. At the 10 intervention sites, site-specific 
symptom management care pathways will be adapted from template care pathways for each of 
the 15 symptoms included in SSPedi. Enrolled participants will be prompted by text or email to 
complete symptom screening three times weekly via SPARK with corresponding feedback sent 
to their healthcare providers. Participants may be contacted in person, by email, text, or over the 
phone to ensure there are no technical barriers to completing SSPedi. Symptom reports will 
contain links to care pathways for symptom management. Active intervention will last for eight 
weeks starting from the date of enrollment. At the 10 control sites, participants will complete 
SSPedi to obtain the primary outcome at weeks 0, 4 and 8 but the scores will not be revealed to 
providers and will not be linked to care pathways. Usual care will be provided to participants at 
control sites and thus, there will be no study-requested routine, systematic symptom screening, 
symptom feedback to providers, or linkage to care pathways. If sites already routinely perform 
systematic symptom screening or use care pathways for symptom management, these may be 
continued but their use will be recorded.  
 
At both intervention and control sites, demographic information including age, sex, race, 
ethnicity, diagnosis, cancer stage, family socioeconomic information and treatment plan will be 
collected at enrollment. The following PROs will be obtained by trained research staff at 
baseline, week 4 and week 8 for all participants: SSPedi, PROMIS Fatigue and the PedsQL 3.0 
Acute Cancer Module (Aim 1). We will contact participants ahead of time to coordinate the week 

 
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4 and 8 PROs so that they can be completed in person during hospitalizations or clinic visits. If 
unable to arrange completion of these PROs in person, we will use their contact information to 
complete the questionnaires by email, text or over the phone.  Data from health records (Aim 2) 
will be abstracted for all enrolled participants. Relapse and cancer treatment received 
information will be collected at the end of the study. 
 
  
 
Procedures at Intervention and Control Sites: 
 
Procedures at Intervention Sites: Participants enrolled at intervention sites will be prompted 
to complete symptom screening three times weekly via SPARK with corresponding feedback 
and links to symptom management care pathways sent to their healthcare providers.  
 
a) Symptom Screening using SPARK: Symptom screening using SPARK can be performed at 
any time and as often as desired, but screening will be prompted three times weekly for eight 
weeks. In our pilot studies, the mean time for SSPedi completion using the identical SPARK 
platform was 1.0 (SD=1.5) minutes and in over 1,000 children who have completed SSPedi, no 
child has ever stated that SSPedi completion was distressing. The ideal frequency of symptom 
screening is not known; the need to identify change in symptoms as soon as possible must be 
balanced against the burden of frequent screening to children and healthcare providers. In order 
to identify the ideal frequency of symptom screening reminders, we surveyed site investigators 
at participating sites. The most commonly suggested frequency was three times weekly (n=15, 
range 2-5 times weekly). However, it is important to stress that three times weekly is the 
frequency in which we will remind participants to complete SSPedi; participants can complete 
SSPedi as often as they wish including daily or more often.  
 
Participants will be set up to use their own smart phone, tablet or computer to perform 
symptom screening. If participants do not have a device, one will be loaned to them for the 
study duration. Text message reminders will be sent from SPARK using a HIPPA-compliant 
third party vendor to route the text messages. Email reminders will be sent from SPARK using 
the institutional email domain or other institutionally-approved approaches where required.  
 
b) Symptom Reports to Healthcare Providers: Each day the participant completes symptom 
screening (whether prompted or unprompted) and has at least one severely bothersome 
symptom, the primary healthcare team will receive an email summarizing the symptom report 
and highlighting symptoms that are “a lot” or “extremely” bothersome. Emails will include links to 
the site-specific care pathways for symptom management. Patient name and date of SSPedi 
completion are included in the email to ensure correct identification of the patient. Thus, patient 
name will exist within the SPARK database but the system is configured such that no other site 
including The Hospital for Sick Children can access it. These approaches have been approved 
by The Hospital for Sick Children’s Privacy Office and IRB, and all IRBs of institutions that have 
participated in other SPARK studies. In terms of email communication, each hospital’s policies 
will be followed. At some hospitals, emails sent internally within the hospital are considered 
secure. In this case, SPARK emails will be generated from that hospital’s email domain if 
possible. Some hospitals may require encrypted emails; these will be used where required. 
Other approaches will be instituted where required. 
 
Qualitative feedback from providers receiving these reports in our pilot study has been 
positive. When specifically asked, receiving these reports was not considered burdensome. In 
fact, providers found reports helpful to communicate symptom experience and to initiate or 
escalate symptom management interventions. 
 
c) Creation of Local Care Pathways for Symptom Management: Care pathway templates for 
symptom management have been drafted for each of the 15 items included in SSPedi. These 
are primarily based on COG-endorsed CPGs and other CPGs that were developed using 
appropriate methodology. To supplement SSPedi symptom care pathway templates for which 

 
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CPGs exist and to address SSPedi symptoms for which CPGs do not exist, templates are also 
based on “good practice statements”24. In brief, “good practice statements” are guidance 
statements regarding the provision of care where to provide care in any other way would be 
considered unethical or absurd. Guideline experts have explicitly acknowledged their necessity 
and have published guidance for how and when to use such statements.24 Upon study 
activation, we will work with each of the 10 intervention sites to develop site-specific, adapted 
care pathways that consider relevant work flows, institutional culture and available resources 
(laboratory tests, medications and personnel); this process will require three months to 
complete. The finalized local care pathways will contain explicit direction for how to prevent and 
manage symptoms at each site. The process for creating local care pathways will be based 
upon a procedure we developed for CPG adaptation, will require local inter-professional input 
and will be finalized at an in-person or video-conference meeting at the site.25 This process 
incorporates activities known to promote practice change and enhance implementation. 
Activities include appreciation of local resources and values, identification of local barriers and 
facilitators, stakeholder participation in decision making, education of healthcare professionals 
and creation of implementation tools. It is expected that across the 10 sites, the care pathways 
could differ substantially in some areas, such as which profession or specialty should be 
consulted and choice of specific medications to treat a symptom, but that there should be 
similarities across all 10 local care pathways since they have a common evidence base. 
Annually, we will assess how the initial adaptations have changed to gain insight into the 
adaptation process over the course of the study and to evaluate how the process might inform 
future implementation of care pathways. Adaptations will be summarized and will be made 
available to all intervention sites during the study, and will be widely available to all sites 
following study completion as part of knowledge translation, and as a component of the RE-AIM 
implementation evaluation. 
 
d) Training: From a patient participant perspective, training on how to use SPARK and how to 
interpret SPARK symptom reports will be provided at enrollment. From a healthcare provider 
perspective, training on how to interpret SPARK symptom reports, CPGs and care pathways will 
be provided to each site during the in-person or video-conference meeting to adapt symptom 
management care pathways and via a webinar at study activation and regularly throughout the 
study to educate new staff and to re-enforce knowledge for existing staff. Different aspects of 
training also will be highlighted during the site calls every two weeks. Stories of successful 
implementation at a particular site will be shared so that all sites can benefit. Technical 
assistance and support will be available to providers throughout the study from The Hospital for 
Sick Children where SPARK is located.  
 
Procedures at Control Sites: At control sites, usual care will be provided, which may or may 
not include symptom screening, access to CPGs or care pathways. Participants will complete 
SSPedi to obtain the primary outcome at weeks 0, 4 and 8 but the scores will not be revealed to 
providers and will not be linked to care pathways. 
 
Describing Site Characteristics (both Intervention and Control Sites): In order to describe 
supportive care practices that could impact on intervention effectiveness and to gain insight into 
future implementation (adoption), the site PIs will complete a short questionnaire at study 
activation (baseline prior to randomization) and annually while participants are being enrolled. 
Questions will include demographic characteristics of patients and providers (only at baseline), 
psychosocial resources available for pediatric cancer patients and current approaches to 
systematic symptom screening, symptom management CPG availability and care pathway 
existence for SSPedi symptoms. CPG availability will be defined as either the posting of CPGs 
themselves or links to CPGs on an institutional website or drive that is available to all oncology 
providers (not an individual clinician’s computer only). Care pathway use will be defined as a 
written set of instructions for the management of a symptom that is available to all oncology 
providers at that site. Site characteristics were also measured using the inner setting measures 

 
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from the Consolidated Framework for Implementation Research (CFIR).26,27  
 
Site Monitoring, Quality Control and Intervention Site Auditing: Quality control will be maintained 
with calls every two weeks among participating site PIs and clinical research personnel. 
Separate calls will be held with intervention and control sites to reduce the risk of contamination. 
On those calls, we will summarize enrollments at each site and review the proportion of eligible 
patients enrolled. We will also review identified issues with respect to missing data and data 
quality identified during routine data checks.  
 
For intervention sites, fidelity to the symptom screening approach will also be monitored. 
Each intervention site will be audited at least once (4-6 months after site activation) to assess 
adherence to the process of symptom screening, namely documentation of participant training 
in the health records, completion of SSPedi at least three times weekly, and delivery of 
symptom reports to providers. Accessibility of local care pathways will also be examined. These 
will be evaluated as part of the implementation dimension of RE-AIM.28 Audits may be 
conducted in person or remotely. 
 
Proposed Practical Arrangements for Allocating Sites: The allocation sequence will be 
computer generated. Sites will be randomized 1:1 and will be stratified by two site 
characteristics ≥ or < median: (1) anticipated number of cancer patients 8-18 years of age who 
speak English or Spanish per year, and (2) percentage of patients with private insurance vs. 
other payment types. Block size is not disclosed in this protocol. Assignment will be 
communicated by email to the site PI and clinical research personnel following randomization.  
  
Proposed Methods for Protecting against Sources of Bias: Given the cluster randomized 
nature of the study, a potential source of bias is that allocation will be known, which could lead 
to selection bias during participant enrollment. To address this potential, efforts will be made to 
both identify all potentially eligible participants and maximize enrollment. We will describe those 
not approached and those who decline to participate in the intervention and control sites. We 
will describe these groups by sex, age, race, ethnicity, cancer type and institution.  
 
Primary, Secondary and Exploratory Outcome Measures: Endpoints for Aim 1 are PROs; all 
PROs are self-report. The primary endpoint is the total SSPedi symptom score, which is the 
sum of each of the 15 SSPedi item’s Likert scores, resulting in a total score that ranges from 0 
(no bothersome symptoms) to 60 (worst bothersome symptoms). The recall period is yesterday 
or today. The total SSPedi score is reliable, valid and responsive to change in children with 
cancer 8-18 years of age.3 Secondary endpoints include fatigue and QoL. Fatigue will be 
measured using PROMIS. The recall period is the last 7 days. It is reliable and valid in children 
8-18 years of age with cancer.29 QoL will be measured using the PedsQL 3.0 Acute Cancer 
Module.30 The 7 day recall version will be used. This measure is a multidimensional instrument 
that is reliable and valid in children with cancer.30 It assesses pain and hurt, nausea, procedural 
anxiety, treatment anxiety, worry, cognitive problems, perceived physical appearance and 
communication. All PROs are validated for use in English and Spanish for children 8-18 years of 
age. 
 
For both groups, all questionnaires including SSPedi will be administered at baseline, week 
4 (±1 week) and week 8 (±1 week) at an in-person visit during a hospitalization or clinic visit 
(preferred), or will be obtained remotely. The approach will be identical for intervention and 
control sites.   
 
Endpoints for Aim 2 will be abstracted from the health record and are: documentation of 
symptoms, provision of interventions for symptoms and emergency department visits and 
unplanned clinic visits and hospitalizations. Guardians will also be asked about healthcare visits 
to ensure encounters outside the primary institution are captured. Documentation of symptoms 
and intervention provision for symptom control will be abstracted from the patients’ health 
records using the procedures our team previously developed.4 The number of interventions for 
each symptom at each reporting period will be recorded and categorized as any intervention 

 
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provided vs. no intervention provided. Interventions included in the local care pathway will be 
noted. Both documentation of symptoms and interventions for these symptoms will be described 
for each specific symptom at each time point. These outcomes will be obtained on each day that 
a week 4 or 8 SSPedi assessment was obtained (as measured in conjunction with the other 
PROs) with a one day window before and after these assessments. For example, if the 
participant completed SSPedi on a Tuesday, we would accept documentation of that symptom 
(or provision of an intervention for that symptom) if it were recorded in the health records on 
Monday, Tuesday or Wednesday. A comprehensive and field-tested list of synonyms for 
symptoms and interventions is available for each of the 15 symptoms in SSPedi.4 We found 
study data could be abstracted with minimal training and effort. De-identified source 
documentation will be sent to the coordinating center for quality assurance. 
 
 
Exploratory endpoints for Aim 3 will be RE-AIM characteristics to measure reach, 
effectiveness, adoption and implementation. For reach, we propose to describe the baseline 
demographic characteristics of eligible patients who participate and who do not participate. We 
will describe site attributes using the inner setting measures from the CFIR as measured at 
baseline.26,27 These attributes include culture, culture stress, culture effort, implementation 
climate, learning climate, leadership engagement and available resources. Effectiveness will be 
evaluated through primary and secondary outcomes and also by comparisons of the 
percentages of patients with severely bothersome symptoms within intervention and control 
sites. We will characterize adoption at intervention sites by describing characteristics of sites 
and providers at those sites.  Site characteristics will include pediatric vs. mixed adult and 
pediatric, number of pediatric cancer patients diagnosed annually, and percentage of patients 
anticipated to have private, public or no insurance. Healthcare provider characteristics will 
include number of physician and nurse practitioner full-time equivalents and median years in 
practice.  Adoption will be assessed through the number of SSPedi per participant completed at 
intervention institutions; this analysis will use duration of time on protocol therapy as an offset. 
Further, we will dichotomize each participant as a high or low SSPedi completer, with a high 
completer being defined as one who completed 15 or more SSPedi. This analysis will use those 
who complete protocol therapy as planned as the denominator. In addition, we will count the 
number of times the institutional care pathways were clicked at intervention sites. We will 
describe the total number of clicks overall and by specific care pathway, access route (email link 
or QR code) and device (iPad, iPhone, Mac, Windows or unknown). Implementation outcomes 
will capture the percentages of intervention patients who came off protocol therapy early and the 
number of all participants who came off study early, both overall and stratified by intervention or 
control group.  
 
Off Protocol and Off Study Criteria 
Off protocol criteria only apply to intervention sites. When off protocol criteria are met, the 
reminders to complete symptom screening via SPARK will be discontinued but the collection of 
PROs will continue until off study criteria are met.  
 
Off protocol criteria: 
a) Refusal to continue with study intervention 
b) Physician determines it is in the patient’s best interest 
c) Death 
d) Completion of planned study intervention 
e) Other, describe  
 
Off study criteria: 
a) Withdrawal of consent for further data submission 
b) Physician determines it is in the patient’s best interest 
c) Death 
d) Completion of planned study observations (Up to 10 weeks after enrollment to allow 
window around week 8 assessment and to allow ability to abstract health records 

 
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outcomes accurately) 
e) Other, describe 
 
ANALYTIC PLAN 
 
Power Calculations  
The primary endpoint is the total self-reported SSPedi score at eight weeks. We used 
data from our SSPedi validation study for power calculation.3 In that study, we recruited 302 
children across nine sites who were hospitalized and expected to be in hospital or in clinic three 
days later. Children completed SSPedi on days 1 and 4 and a 5-point global symptom change 
scale on day 4. The average absolute change in total SSPedi scores for those who reported 
they were a little better or a little worse (1-point change) was 2.7 while the average absolute 
change in total SSPedi scores for those who reported they were much better or much worse (2-
point change) was 5.6. Thus, the minimum plausible clinically important difference is likely 
approximately 3.0 but may be higher. The intracluster correlation coefficient (ICC), a measure of 
the degree of clustering, was 0.021 (95% CI 0 to 0.123). In power calculations for the proposed 
study, we used ICC=0.021 but show sensitivity analyses to ICCs at the extremes of the 95% CI 
(which are unlikely). Among the 20 sites in the proposed trial, we anticipate that four will each 
contribute eight patients, four will each contribute 32 patients, and the remaining 12 will each 
contribute 20 patients, for a total of 400 patients. With these cluster sizes, Table 1 shows power 
for combinations of these ICCs and clinically important differences, at a 2-sided alpha of 0.05 
and assuming a within-cluster standard deviation of 8.8 (derived from the SSPedi validation 
study3). Power for each combination in the table was calculated through simulation of 4000 
trials; each one was analyzed with a linear mixed effects model clustering by site and the 
percentage with a significant P value was taken as the estimate of power. If there is a baseline 
characteristic, such as age, that explains 20% of the variance in 8-week scores, including that 
variable in analyses increases power to the value shown in the far right column. Table 1 shows 
that assuming a minimal clinically important difference of 3.0 and with inclusion of age as a 
covariate in the analysis, there is 85% power with ICC=0.021. Assuming that 10% of patients 
have missing final scores, we will inflate the sample size to 444. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Baseline Characteristics: Summary statistics on baseline characteristics will be calculated 
within each study arm and presented in a table – means and standard deviations (SDs) for 
variables treated as continuous, counts and percentages for categorical variables, along with 
total numbers with missing data.   
 
 
Table 1: Power Assuming 400 Patients, Alpha=0.05 and Standard Deviation=8.8 
ICC 
Difference 
Power 
Without baseline predictor 
With age as baseline predictor 
0.000 
2.5 
71.0 
81.4 
 
3.0 
86.7 
94.2 
 
3.5 
95.9 
98.9 
0.021 
2.5 
59.5 
70.1 
 
3.0 
75.7 
85.2 
 
3.5 
86.5 
94.2 
0.123 
2.5 
26.6 
32.6 
 
3.0 
38.2 
45.3 
 
3.5 
47.7 
57.0 

 
Page 10 of 17 
 
Outcomes: Similar tables will be created for all study outcomes.  Individual SSPedi symptom 
scores will be summarized by the percentages of participants with scores of 3 or 4, the two most 
bothersome categories. 
 
Comparative Analyses: The primary analysis will use the patient-level 8-week total SSPedi 
score as the outcome in a mixed linear regression model with a random effect for cluster, fixed 
effects for treatment assignment, child age and diagnosis group (leukemia/lymphoma, solid 
tumor and central nervous system tumor), and two binary fixed effects at the cluster level for 
stratification variables (above or below the average anticipated yearly number of English or 
Spanish-speaking cancer patients 8-18 years of age, and above or below the average 
anticipated percentage of patients with private insurance vs. other payment types). Child age 
and diagnosis group will be included as they are known to be associated with total SSPedi 
scores; this will reduce residual variance in scores. We do not plan to adjust the model for 
baseline SSPedi score because some of the care pathway interventions (that are prophylactic) 
will affect symptoms prior to enrollment and the baseline score may already reflect some benefit 
of the cluster’s treatment assignment. The treatment effect will be the covariate-adjusted mean 
difference between study groups in 8-week SSPedi, presented with a 95% CI and a two-sided 
p-value for a test of no treatment effect. If we find the residuals from the mixed model fitted to 
the 8-week total SSPedi score deviate substantially from normality, we will conduct sensitivity 
analyses, one using normalizing transformations of the outcome and another using an ordinal 
regression model. To account for potential differential enrollment of surgery only patients (who 
might not be cared for by oncology teams) between intervention vs. control sites, we will also 
conduct a sensitivity analysis restricted to patients that received systemic chemotherapy.  
 
 
Secondary outcomes will be analyzed as follows: 
1. Self-reported individual symptoms at weeks 4 and 8 on the SSPedi instrument: For 
each of the 15 ordinal outcomes representing symptoms (scored 0-4), a mixed effects 
proportional odds model will be fitted using treatment assignment and stratification factors 
as fixed effects covariates and with a random effect for site.  As some individual symptoms 
may be uncommon, to avoid specifying models that may be overfitted for those symptoms, 
these models will use only this minimal set of three covariates. The estimated odds ratio for 
the intervention (representing the odds of having a higher vs. lower score in the intervention 
group) will be estimated and presented along with a 95% CI.  
2. PROMIS Fatigue Scale: This scale will be treated as a continuous variable and analyzed 
using a linear mixed effects model in the same way as the primary SSPedi outcome.   
3. PedsQL 3.0 Acute Cancer Module domain scores:  Each of these 8 scores will be treated 
as continuous variables and analyzed using a linear mixed effects model in the same way 
as the primary SSPedi outcome.   
4. Documentation of symptoms on weeks 4 and 8 (± 1 day): Analyses will involve three 
analyses for each symptom class. Each analysis will fit a mixed effects logistic regression 
model to estimate the odds ratio for documentation (on weeks 4 and 8) comparing 
intervention groups, adjusting for stratification factors. It is possible that there will be too few 
documentation events to reliably fit this mixed model to all 15 symptoms. If this model 
cannot be fitted to some symptoms (likely because the random effects variance cannot be 
estimated), we will fit a fixed effects logistic regression model to just those symptoms. Three 
cohorts will be defined: 
a. Each participant will be classed as having the symptom documented or not. All 
participants are included in the analytic sample for each symptom. 
b. The analytic sample will be limited to those participants who self-report the symptom 
on weeks 4 and 8 (symptom score > 0).  

 
Page 11 of 17 
 
c. The analytic sample will be limited to those participants who have the most 
bothersome self-report of the symptom on the weeks 4 and 8 SSPedi (symptom 
score ≥ 3). 
5. Interventions for symptoms: Analyses will follow a similar flow to the analyses of 
documentation of symptoms. For each of the 15 symptoms, each participant will be 
classified as having an intervention at weeks 4 and 8 (±1 days).  Also collected is whether 
interventions were administered specifically for the specific symptoms. For example, 
acetaminophen may be administered for fever or pain. As interventions are expected to be 
more uncommon than symptoms, all treatment effects will be estimated by simple 
differences in the proportions with interventions (i.e., ignoring clustering), p-values will be 
computed from the Fisher exact test, and 95% CI for differences in proportions will use the 
Newcombe method. Three cohorts will be defined: 
a. Each participant will be classed as having an intervention for the symptom or not. All 
participants are included in the analytic sample for each intervention-symptom pair. 
b. The analytic sample will be limited to those participants who self-report the symptom 
on the weeks 4 and 8 SSPedi (symptom score > 0).  
c. The analytic sample will be limited to those participants who have the most 
bothersome self-report of the symptom on the weeks 4 and 8 SSPedi (symptom 
score ≥ 3). 
6. Unplanned encounters: For each of the secondary endpoints of unplanned health services 
utilization (emergency, clinic visits, hospitalizations, and the total across categories), the 
number of events per child will be counted over the 8-week period and compared between 
randomized groups using a mixed-effects Poisson or negative binomial regression analysis 
(with zero-inflation if necessary), with a random effect for site and fixed effects for the two 
stratification factors. If a child has less than 8 weeks of follow-up, the model will include an 
offset equal to the logarithm of each child’s follow-up time. 
 
 
Exploratory outcomes will be analyzed as follows: 
1. Reach: we will describe the baseline demographic characteristics (sex, age or age group 
and diagnosis group) of eligible patients who participate and who do not participate using 
means and standard deviations for continuous variables and counts and percentages for 
categorical variables. We will also summarize CFIR inner setting attributes as counts and 
percentages. 
2. Effectiveness: In addition to the analyses of primary and secondary outcomes detailed 
above, we will also carry out analyses that dichotomize each of the 15 SSPedi symptoms as 
being severely bothersome (3 or 4) or not.  Percentages for each symptom will be tabulated 
and compared between intervention groups using mixed effects binary logistic regression. 
We will also assess between-site variation in the odds of having a severely bothersome 
symptom (after adjusting for intervention and stratification factors) by plotting the random 
effects associated with each site and by calculating the median odds ratio (MOR). This is an 
alternative measure of clustering (or between-cluster variability); it is the estimated median 
of the ratio of the odds of a bothersome symptom for a participant at one site to the odds of 
a bothersome symptom for an otherwise identical participant at another site. The MOR is 
always defined with the higher odds in the numerator. One appealing aspect of the MOR is 
that it is on the same scale as the odds ratio for treatment, aiding interpretation of both the 
OR for intervention and the MOR for variation in the outcome. 
3. Adoption: We will characterize adoption at intervention sites by summarizing the following:  
a. characteristics of sites and their providers 
b. number of SSPedis completed per enrolled participant 
c. proportion of participants that are high or low SSPedi completers 
d. number of times the institutional care pathways were clicked.  

 
Page 12 of 17 
 
 
Site and provider attributes will be described by using means and standard deviations for 
continuous variables and counts and percentages for categorical variables. Site 
characteristics will include pediatric vs. mixed adult and pediatric, number of pediatric cancer 
patients diagnosed annually, and percentage of patients anticipated to have private, public 
or no insurance. Healthcare provider characteristics will include number of physician and 
nurse practitioner full-time equivalents and median years in practice.  CFIR attributes will 
also be described.  
 
The dependence of the number of SSPedi completed by a participant on participant, 
guardian and site characteristics will be assessed using a mixed effects Poisson or negative 
binomial regression model, with a random effect for site. Participant characteristics will 
include sex, age/age group, race, ethnicity, preferred language, and cancer diagnosis group. 
Guardian characteristics will include marital status, guardian employment and highest 
education, and high annual household income. Site characteristics will be those included 
above. The dependence of the odds of being a high responder on these same 
characteristics will be assessed using mixed effects logistic regression adjusting for 
stratification factors.   
 
The number of recorded clicks is available on aggregate for each site, so we will 
summarize this as a set of 10 rates, clicks per enrolled participant, and assess whether 
there is site-to-site variability by fitting a random effects Poisson or negative binomial model 
with clicks as the outcome and the logarithm of the number of patients as an offset.  A 
summary rate will be estimated from this model and the median rate ratio (analogous to the 
MOR above) will be calculated. 
4. Implementation will calculate the percentage of patients who enrolled but came off protocol 
therapy early (intervention only) or off study early (all participants), overall and stratified by 
intervention or control group.  Counts and percentages will be shown, with no inferential 
statistics. 
 
Missing Data: The PedsQL will be scored according to its scoring guide, which includes rules 
for scoring in the presence of missing elements on each domain modules.  No other 
deterministic rule-based method will be used to deal with missing data.   
 
If more than 10% of participants are missing the primary outcome or secondary patient-
reported outcomes, the analysis will use multiple imputation based on previous SSPedi 
assessments (weeks 0 and 4), group and site. In addition, we will conduct sensitivity analysis 
assuming that missing scores are from children with high total SSPedi scores and from children 
with low total SSPedi scores (randomly drawn from the highest and lowest quartile). A set of 20 
complete datasets will be generated using separate within-treatment-group imputation models. 
These models will include all the study outcomes listed just above, and the key covariates that 
appear in our adjusted models (age, diagnosis group and stratification factors). The models will 
be fitted in each imputed dataset and the pooled estimate of the treatment effect and its 
standard error will be computed using Rubin’s rules.  
 
Analyses of documentation and interventions will not use any imputation. There can be 
no missing data for these outcomes: if a symptom is not documented in the health record and 
there is no record of an intervention being used, then this constitutes a ‘no’ for the outcome. 
While it is possible that the SSPedi symptom score needed for the identification of the analytic 
datasets in analyses (4b, 4c, 5b, and 5c) is missing for some participants, the more exploratory 
nature of these analyses led us to the decision to use only observed data for these outcomes.  
 
FEASIBILITY AND POTENTIAL BENEFITS/RISKS 
 
Feasibility and Recruitment Rate 
 
Among the 20 sites that have agreed to participate, there are expected to be 60 patients/ 

 
Page 13 of 17 
 
month who are newly diagnosed with cancer 8-18 years of age and who speak English or 
Spanish. Assuming that 60% meet eligibility criteria (for example, some patients will not receive 
treatment for cancer such as those with low grade brain tumors and some centers provide 
consultation only services for newly diagnosed patients), and 75% agree to participate 
(conservative estimate based upon other SPARK studies), we anticipate enrollment of 27 
patients/month. Thus, to reach the target sample size of 444 patients, enrollment is anticipated 
to be complete within 2 to 2.5 years (this allows for periods of slow enrollment such as holidays 
or when research personnel have limited availability). In terms of timelines, start-up activities will 
require 12 months, enrollment and follow-up of the last patient will require 24 to 36 months, data 
analysis will require nine months and knowledge dissemination will be completed within three 
months. Thus, the entire study will require five years to complete.  
 
The time commitment of participants, providers and research staff is expected to be similar 
to other supportive care and SPARK trials and we do not anticipate barriers with respect to 
effort required. Abstraction of symptom documentation and intervention provision will be done 
over a short time frame (3 days for each of two time points (weeks 4 and 8)); pilot work at The 
Hospital for Sick Children has shown this workload to be modest. The PROs at weeks 4 and 8 
will require <5-10 minutes to complete and can be completed electronically.  
 
Potential Benefits and Risks to Study Participation 
 
For participants at intervention sites, potential benefits include increased awareness of 
experienced symptoms and increased guideline-concordant care to prevent and manage 
symptoms. Consequently, participants may have better symptom control and QoL by 
participating in this study. Even for those who decline participation in the study, establishment of 
care pathways for symptom management may improve symptom control for all patients at that 
site. For participants at control sites, participants may gain increased self-awareness of 
symptoms by completion of PROs at weeks 0, 4 and 8.  
 
Risks include the potential for inadvertent disclosure of personal health information although 
risks should be low given the precautions instituted. Although there is a risk of distress with 
symptom assessment, such an occurrence has not been observed in SSPedi studies to date. 
Study participation also entails time commitment and some inconvenience to schedule the 
weeks 4 and 8 PRO assessments.  
 
 
 
  
 
 

 
Page 14 of 17 
 
REFERENCES 
 
 
1. 
Canadian Cancer Society's Steering Committee on Cancer Statistics: Canadian Cancer 
Statistics. Toronto, ON, Canadian Cancer Society, 2011 
 
2. 
Baggott C, Dodd M, Kennedy C, et al: Changes in children's reports of symptom 
occurrence and severity during a course of myelosuppressive chemotherapy. J Pediatr Oncol Nurs 
27:307-15, 2010 
 
3. 
Dupuis LL, Johnston DL, Baggott C, et al: Validation of the Symptom Screening in 
Pediatrics Tool in Children Receiving Cancer Treatments. J Natl Cancer Inst, 2017 
 
4. 
Hyslop S, Davis H, Duong N, et al: Symptom Documentation and Intervention Provision 
for Symptom Control in Children Receiving Cancer Treatments. Submitted 2018 
 
5. 
Carelle N, Piotto E, Bellanger A, et al: Changing patient perceptions of the side effects of 
cancer chemotherapy. Cancer 95:155-63, 2002 
 
6. 
Coates A, Abraham S, Kaye SB, et al: On the receiving end--patient perception of the 
side-effects of cancer chemotherapy. Eur J Cancer 19:203-8, 1983 
 
7. 
de Boer-Dennert M, de Wit R, Schmitz PI, et al: Patient perceptions of the side-effects of 
chemotherapy: the influence of 5HT3 antagonists. Br J Cancer 76:1055-61, 1997 
 
8. 
Griffin AM, Butow PN, Coates AS, et al: On the receiving end. V: Patient perceptions of 
the side effects of cancer chemotherapy in 1993. Ann Oncol 7:189-95, 1996 
 
9. 
Yang LY, Manhas DS, Howard AF, et al: Patient-reported outcome use in oncology: a 
systematic review of the impact on patient-clinician communication. Support Care Cancer 26:41-60, 
2018 
 
10. 
Berry DL, Hong F, Halpenny B, et al: Electronic self-report assessment for cancer and 
self-care support: results of a multicenter randomized trial. J Clin Oncol 32:199-205, 2014 
 
11. 
Mooney K, Berry DL, Whisenant M, et al: Improving Cancer Care Through the Patient 
Experience: How to Use Patient-Reported Outcomes in Clinical Practice. Am Soc Clin Oncol Educ Book 
37:695-704, 2017 
 
12. 
Basch E, Deal AM, Kris MG, et al: Symptom Monitoring With Patient-Reported Outcomes 
During Routine Cancer Treatment: A Randomized Controlled Trial. J Clin Oncol 34:557-65, 2016 
 
13. 
Basch E, Deal AM, Dueck AC, et al: Overall Survival Results of a Trial Assessing Patient-
Reported Outcomes for Symptom Monitoring During Routine Cancer Treatment. JAMA, 2017 
 
14. 
Wright JD, Neugut AI, Ananth CV, et al: Deviations from guideline-based therapy for 
febrile neutropenia in cancer patients and their effect on outcomes. JAMA Intern Med 173:559-68, 2013 
 
15. 
FitzGerald JM, Boulet LP, McIvor RA, et al: Asthma control in Canada remains 
suboptimal: the Reality of Asthma Control (TRAC) study. Can Respir J 13:253-9, 2006 
 
16. 
Grimshaw J, Eccles M, Thomas R, et al: Toward evidence-based quality improvement. 
Evidence (and its limitations) of the effectiveness of guideline dissemination and implementation 
strategies 1966-1998. J Gen Intern Med 21 Suppl 2:S14-20, 2006 
 
17. 
Wolfe J, Orellana L, Cook EF, et al: Improving the care of children with advanced cancer 
by using an electronic patient-reported feedback intervention: results from the PediQUEST randomized 
controlled trial. J Clin Oncol 32:1119-26, 2014 
 
18. 
O'Sullivan C, Dupuis LL, Gibson P, et al: Refinement of the symptom screening in 
pediatrics tool (SSPedi). Br J Cancer 111:1262-8, 2014 
 
19. 
O'Sullivan C, Dupuis LL, Gibson P, et al: Evaluation of the electronic self-report Symptom 
Screening in Pediatrics Tool (SSPedi). BMJ Support Palliat Care, 2016 
 
20. 
Tomlinson D, Dupuis LL, Gibson P, et al: Initial development of the Symptom Screening 
in Pediatrics Tool (SSPedi). Support Care Cancer 22:71-5, 2014 

 
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21. 
Soman D: The Last Mile: Creating Social and Economic Value from Behavioural Insights, 
University of Toronto Press, 2015  
 
22. 
O'Sullivan C, Dupuis LL, Gibson P, et al: Refinement of the symptom screening in 
pediatrics tool (SSPedi). British Journal of Cancer 111:1262-8, 2014 
 
23. 
National Guideline Clearinghouse: Inclusion Criteria. 
http://www.guideline.gov/about/inclusion-criteria.aspx, 2014 
 
24. 
Guyatt GH, Schunemann HJ, Djulbegovic B, et al: Guideline panels should not GRADE 
good practice statements. J Clin Epidemiol 68:597-600, 2015 
 
25. 
Koo A, Li C, Liu LL, et al: Successful adaptation of fever and neutropenia clinical practice 
guideline in China. . Applied Cancer Research, In Press, 2018 
 
26. 
Damschroder LJ, Aron DC, Keith RE, et al: Fostering implementation of health services 
research findings into practice: a consolidated framework for advancing implementation science. 
Implement Sci 4:50, 2009 
 
27. 
Fernandez ME, Walker TJ, Weiner BJ, et al: Developing measures to assess constructs 
from the Inner Setting domain of the Consolidated Framework for Implementation Research. Implement 
Sci 13:52, 2018 
 
28. 
Glasgow RE, Harden SM, Gaglio B, et al: RE-AIM Planning and Evaluation Framework: 
Adapting to New Science and Practice With a 20-Year Review. Front Public Health 7:64, 2019 
 
29. 
Hinds PS, Nuss SL, Ruccione KS, et al: PROMIS pediatric measures in pediatric oncology: 
valid and clinically feasible indicators of patient-reported outcomes. Pediatr Blood Cancer 60:402-8, 
2013 
 
30. 
Varni JW, Burwinkle TM, Katz ER, et al: The PedsQL in pediatric cancer: reliability and 
validity of the Pediatric Quality of Life Inventory Generic Core Scales, Multidimensional Fatigue Scale, 
and Cancer Module. Cancer 94:2090-2106, 2002 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
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Appendix 1: Symptom Screening in Pediatrics Tool (SSPedi)  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
Page 17 of 17 
 
Appendix 2: SPARK Landing Page  
 
 

Symptom Screening Linked to Care Pathways for Children with Cancer: a Cluster Randomized Trial 
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BACKGROUND 
 
 
Over the last few decades, impressive gains in survival for children and adolescents with cancer have 
been made and now, more than 82% of children with cancer will be cured.1 These survival gains have been, in 
part, attributable to the provision of intensive therapies. However, as a result, most children suffer and 
experience severe and distressing treatment-related symptoms such as pain, fatigue and nausea.2 In our 
cross-sectional study of 302 inpatients 8-18 years of age, when asked about yesterday or today, 99% of 
children experienced at least one bothersome symptom and 60% experienced at least one severely 
bothersome symptom, including severe pain in 22% and severe fatigue in 33%.3 Symptoms are important; we 
previously demonstrated a strong correlation between increasing symptom burden and worse quality of life 
(QoL) in children receiving cancer treatments.3 Given excellent survival outcomes, we now need to focus more 
attention on symptom control.   
 
To gain insight into why symptoms are uncontrolled, we evaluated 168 children and described the extent 
to which symptoms self-reported as severely bothersome were documented in the health record and for which 
any interventions were provided.4 We created a standard operating procedure and a list of synonyms that met 
criteria for documentation of symptoms. For example, “tired”, “feel weak”, “low energy”, and “sluggish” were all 
considered adequate documentation for fatigue. We also created a list of possible interventions for each 
symptom. For most of the symptoms measured (12/15), severely bothersome symptoms were documented in 
the health record less than 60% of the time. The most infrequently documented severely bothersome 
symptoms were problems with thinking or remembering things (0%), changes in how your body or face look 
(4.8%), changes in taste (7.7%) and tingly or numb hands or feet (11.1%). Only two severely bothersome 
symptoms were documented at least 80% of the time, namely hurt or pain (92.6%) and throwing up or feeling 
like you might throw up (92.6%). 
 
Provision of an intervention to address severely bothersome symptoms occurred less than 60% of the time 
for 10 of 15 symptoms. The most infrequently treated severely bothersome symptoms were thinking or 
remembering things (0%), changes in how your body or face look (0%), tingly or numb hands or feet (0%), 
changes in taste (0%), diarrhea (0%) and feeling tired (1.6%). Intervention provision was most common for hurt 
or pain (96.3%), headache (89.5%), throwing up or feeling like you might throw up (88.9%) and constipation 
(84.2%). However, even when interventions were provided, they were often not prescribed specifically for that 
symptom (for example, acetaminophen for fever rather than pain). 
 
Within the adult oncology setting, screening and assessment of symptoms through patient self-report has 
been identified as an important priority.5-8 In adult cancer patients, routine collection of patient-reported 
outcomes (PROs) improves patient-clinician communication9, reduces distress10 and improves QoL.11,12 
Furthermore, a recent randomized trial showed that routine PRO assessment may improve survival in adult 
patients with metastatic solid tumors.13 Among participants that were randomized to symptom screening vs. 
standard of care, median overall survival was 31.2 months (95% confidence interval (CI) 24.5 to 39.6) in the 
symptom screening group vs. 26.0 months (95% CI 22.1 to 30.9) in the standard of care group (P=0.03). 
Consequently, routine assessment of PROs is now considered essential to high quality care.11 It is also known 
that delivery of care consistent with CPGs can improve patient outcomes. For example, timely administration of 
CPG-consistent antibiotics to adult patients with fever and neutropenia resulted in significantly lower mortality 
compared to patients who did not receive CPG-consistent antibiotics.14 However, adherence to CPGs is 
generally poor.15,16  
 
In contrast to these accomplishments in adults, efforts in children are limited.17 To help address this gap, 
we developed SSPedi (Symptom Screening in Pediatrics Tool; Appendix 1)18,19 and SPARK (Supportive care 
Prioritization, Assessment and Recommendations for Kids; Appendix 2). SSPedi is a self-reported 15-item 
symptom screening tool for children receiving cancer treatments. SSPedi consists of the following 15 items: 
disappointed or sad, scared or worried, cranky or angry, problems thinking, body or face changes, tiredness, 
mouth sores, headache, other pain, tingling or numbness, throwing up, hunger changes, taste changes, 
constipation and diarrhea. We developed SSPedi because our previous work concluded that then-available 
pediatric cancer symptom assessment tools were not appropriate for clinical use due to length or content.20 
Items were generated using a nominal group technique among pediatric cancer clinicians and a patient 
advocate.20 Next, based upon input from 50 children receiving cancer treatments and 20 parents of pediatric 
oncology patients, we refined the paper and electronic versions of SSPedi and confirmed content validity, 
understandability and ease of use.20-22 The electronic version of SSPedi has an audio feature that allows 
specific questions or the entire instrument to be read aloud. A help feature provides synonyms for each 
symptom; these were derived from children themselves during cognitive interviews. 

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Next, we conducted a multi-center study in the US and Canada to evaluate the psychometric properties of 
SSPedi. SSPedi was shown to be reliable (internal consistency and test re-test and inter-rater reliability), valid 
(construct validity) and responsive to change in 502 English-speaking children 8-18 years of age receiving 
cancer therapies.3 More specifically, the intraclass correlation coefficients (ICC) were 0.88 (95% CI 0.82 to 
0.92) for test re-test reliability, and 0.76 (95% CI 0.71 to 0.80) for inter-rater reliability between children and 
parents. Mean difference in SSPedi scores between groups hypothesized to be more and less symptomatic 
was 7.8 (95% CI 6.4 to 9.2; P<0.001).3 Construct validity was demonstrated as all hypothesized relationships 
among measures were observed. SSPedi was responsive to change; those who reported they were much 
better or worse on a global symptom change scale had significantly changed from their baseline score (mean 
absolute difference 5.6, 95% CI 3.8 to 7.5; P<0.001). This instrument has been translated into Spanish; the 
translated version is satisfactory to use in the US and Canada based on understandability and cultural 
relevance. 
 
Building upon SSPedi, SPARK is a web-based application that consists of two components: (1) a 
symptom screening component centered on SSPedi; and (2) a supportive care CPG component. While SSPedi 
asks children about symptoms, SPARK facilitates access to SSPedi, encourages symptom screening, 
generates reports and allows children to track their symptoms. In addition, when used by healthcare providers, 
SPARK links the symptoms identified using SSPedi with CPGs to manage them. CPGs contained within 
SPARK are those endorsed by the Children’s Oncology Group (COG) and thereby meet minimum specific 
criteria with respect to methodological rigor and relevance to pediatric oncology.23 
 
 
AIMS 
 
Aims 1 and 2: Among children with newly diagnosed cancer, determine if symptom feedback to healthcare 
providers given at least three times weekly using SPARK and locally-adapted symptom management care 
pathways based on CPGs, when compared with usual care: 
Aim 1. Improves overall self-reported symptom scores (total SSPedi score), fatigue (PROMIS–Fatigue) and 
cancer-specific QoL (PedsQL 3.0 Acute Cancer Module) over 8 weeks 
Hypothesis: Symptom screening and care pathways will improve symptoms, fatigue and QoL 
Aim 2. Improves symptom documentation, increases provision of interventions for symptoms, and reduces 
emergency department visits and unplanned clinic visits and hospitalizations over 8 weeks 
Hypotheses: Symptom screening and care pathways will increase symptom documentation and 
provision of interventions for symptoms, and will reduce healthcare utilization. 
Aim 3: As an exploratory aim, we will evaluate key elements of the intervention related to the external validity 
and generalizability of the intervention effects using the RE-AIM framework.  
 
METHODS 
 
Overall Strategy 
 
This is a cluster randomized trial including 20 pediatric oncology sites, each with a history of excellent 
accrual to supportive care trials, with geographic variation and representativeness among ethnic minority 
groups. Sites will be randomized to either systematic symptom screening via SPARK with provision of 
symptom reports to healthcare providers containing links to care pathways for symptom management 
(intervention) vs. usual care (control).  
 
Research Methods 
Eligibility: We will include children with cancer who: (1) are 8-18 years of age at enrollment (SSPedi is 
validated in this age range); (2) are English or Spanish-speaking (all PROs are validated in these languages in 
this age range); (3) have any newly diagnosed cancer; (4) have a plan for any chemotherapy, radiotherapy or 
surgery; and (5) enroll within 28 days after treatment initiation. Exclusion criteria will be cognitive disability 
(attending minimum second grade or equivalent) or visual impairment (cannot see SPARK even with corrective 
lens).   
 
Procedures: In this cluster randomized trial, we will randomize participating sites to either intervention or 

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control groups.  We will enroll participants within 28 days after treatment initiation. Potential participants will be 
identified by the clinical staff and recruited from the inpatient ward and outpatient clinics. Informed consent and 
assent will be obtained from each participant/guardian as appropriate. Careful tracking of all newly diagnosed 
patients by site clinical research associates will occur to determine how many patients are approached and 
consented, and where possible, reasons for declining participation.  
 
At the 10 intervention sites, site-specific symptom management care pathways will be adapted from 
template care pathways based upon COG-endorsed CPGs for each of the 15 symptoms included in SSPedi. 
Enrolled participants will be prompted to complete symptom screening three times weekly via SPARK with 
corresponding feedback sent to healthcare providers. Symptom reports will contain links to care pathways for 
symptom management. Active intervention will last for eight weeks starting from the date of enrollment. At the 
10 control sites, participants will complete SSPedi to obtain the primary outcome at weeks 0, 4 and 8 but the 
scores will not be revealed to providers and will not be linked to care pathways. Usual care will be provided to 
participants at control sites and thus, there will be no study-requested routine, systematic symptom screening, 
symptom feedback to providers, or linkage to care pathways. If sites already routinely perform systematic 
symptom screening or use care pathways for symptom management, these may be continued but their use will 
be recorded. We will contact participants to time the week 4 and 8 PROs with hospital or clinic visits. If unable 
to arrange, we will use their contact information to complete the questionnaires by email, text or over the 
phone. 
 
Demographic information including age, sex, race, ethnicity, diagnosis, cancer stage, family 
socioeconomic information and treatment plan will be collected at enrollment. For all participants, the following 
PROs will be obtained by trained research staff at baseline, week 4 and week 8: SSPedi, PROMIS Fatigue and 
the PedsQL 3.0 Acute Cancer Module (Aim 1). Data from health records (Aim 2) will be abstracted for all 
enrolled participants.   
 
Procedures at Intervention and Control Sites: 
 
Procedures at Intervention Sites: Participants enrolled at intervention sites will be prompted to complete 
symptom screening three times weekly via SPARK with corresponding feedback and links to symptom 
management care pathways sent to their healthcare providers.  
 
a) Symptom Screening using SPARK and Timing Justifications: Symptom screening using SPARK can be 
performed at any time and as often as desired, but screening will be prompted three times weekly for eight 
weeks. In our pilot studies, the mean time for SSPedi completion using the identical SPARK platform was 1.0 
(SD=1.5) minutes and in over 1,000 children who have completed SSPedi, no child has ever stated that 
SSPedi completion was distressing. The ideal frequency of symptom screening is not known; the need to 
identify change in symptoms as soon as possible must be balanced against the burden of frequent screening 
to children and healthcare providers. In a trial of adult oncology patients demonstrating that routine symptom 
screening improved QoL, weekly email reminders were sent.17 In order to identify the ideal frequency of 
symptom screening reminders, we surveyed site investigators at participating sites. The most commonly 
suggested frequency was three times weekly (n=15, range 2-5 times weekly). However, it is important to stress 
that three times weekly is the frequency in which we will remind participants to complete SSPedi; participants 
can complete SSPedi as often as they wish including daily or more often.  
 
Participants will be set up to use their own smart phone, tablet or computer to perform symptom 
screening. If participants do not have a device, one will be loaned to them for the study duration.  
 
b) Symptom Reports to Healthcare Providers: Each day the participant completes symptom screening 
(whether prompted or unprompted), the primary healthcare team will receive an email summarizing the 
symptom report and highlighting of symptoms that are “a lot” or “extremely” bothersome. Emails will include 
links to the site-specific care pathways for symptom management. Patient name and date of SSPedi 
completion are included in the email to ensure correct identification of the patient. Thus, patient name will exist 
within the SPARK database but the system is configured such that no other site including SickKids can access 
it. These approaches have been approved by the SickKids Privacy Office and IRB, and all IRBs outside of 
SickKids that have participated in other SPARK studies. In terms of email communication, each hospital’s 
policies will be followed. For example, at all institutions currently participating in other SPARK studies, emails 
sent within that hospital’s system are considered secure and that approach is being used to transmit symptom 
reports with these emails being generated from the hospital’s email domain. Some hospitals may require 

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encrypted emails; these will be used where required.  
 
Qualitative feedback from providers receiving these reports in our pilot study has been positive. When 
specifically asked, receiving these reports was not considered burdensome. In fact, providers found reports 
helpful to communicate symptom experience and to initiate or escalate symptom management interventions. 
 
c) Creation of Local Care Pathways for Symptom Management: Care pathway templates for symptom 
management have been drafted for each of the 15 items included in SSPedi. These are primarily based on 
COG-endorsed CPGs. To supplement SSPedi symptom care pathway templates for which COG-endorsed 
CPGs exist and to address SSPedi symptoms for which COG-endorsed CPGs do not exist, templates are also 
based on “good practice statements”35. In brief, “good practice statements” are guidance statements regarding 
the provision of care where to provide care in any other way would be considered unethical or absurd. 
Guideline experts have explicitly acknowledged their necessity and have published guidance for how and when 
to use such statements.35 Upon study activation, we will work with each of the 10 intervention sites to develop 
site-specific, adapted care pathways that consider relevant work flows, institutional culture and available 
resources (laboratory tests, medications and personnel); this process will require three months to complete. 
The finalized local care pathways will contain explicit direction for how to prevent and manage symptoms at 
each site. The process for creating local care pathways will be based upon a procedure we developed for CPG 
adaptation, will require local inter-professional input and will be finalized at an in-person meeting at the site.26 
This process incorporates activities known to promote practice change and enhance implementation. Activities 
include appreciation of local resources and values, identification of local barriers and facilitators, stakeholder 
participation in decision making, education of healthcare professionals and creation of implementation tools. It 
is expected that across the 10 sites, the care pathways could differ substantially in some areas, such as which 
profession or specialty should be consulted and choice of specific medications to treat a symptom, but that 
there should be similarities across all 10 local care pathways since they have a common evidence base. Each 
care pathway will contain links to the healthcare provider SPARK portal so that providers can view the source 
CPG summary or full guideline document upon which the care pathway was based. Annually, we will assess 
how the initial adaptations have changed to gain insight into the adaptation process over the course of the 
study and to evaluate how the process might inform future implementation of care pathways. Adaptations will 
be summarized and will be made available to all intervention sites during the study, and will be widely available 
to all sites following study completion as part of knowledge translation, and as a component of the RE-AIM 
implementation evaluation. 
 
d) Training: From a patient participant perspective, training on how to use SPARK and how to interpret SPARK 
symptom reports will be provided at enrollment. From a healthcare provider perspective, training on how to 
interpret SPARK symptom reports, CPGs and care pathways will be provided to each site during the in-person 
meeting to adapt symptom management care pathways and via a webinar at study activation and regularly 
throughout the study to educate new staff and to re-enforce knowledge for existing staff. Different aspects of 
training also will be highlighted during the site calls every two weeks. Stories of successful implementation at a 
particular site will be shared so that all sites can benefit. Technical assistance and support will be available to 
providers throughout the study from SickKids where SPARK is located.  
 
Procedures at Control Sites: At control sites, usual care will be provided, which may or may not include 
symptom screening, access to CPGs or care pathways. Participants will complete SSPedi to obtain the primary 
outcome at weeks 0, 4 and 8 but the scores will not be revealed to providers and will not be linked to care 
pathways. 
 
Describing Site Characteristics (both Intervention and Control Sites): In order to describe supportive care 
practices that could impact on intervention effectiveness and to gain insight into future implementation 
(adoption), the site PIs will complete a short questionnaire at study activation (baseline prior to randomization) 
and annually while participants are being enrolled. Questions will include demographic characteristics of 
patients and providers (only at baseline), psychosocial resources available for pediatric cancer patients and 
current approaches to systematic symptom screening, symptom management CPG availability and care 
pathway existence for SSPedi symptoms. CPG availability will be defined as either the posting of CPGs 
themselves or links to CPGs on an institutional website or drive that is available to all oncology providers (not 
an individual clinician’s computer only). Care pathway use will be defined as a written set of instructions for the 
management of a symptom that is available to all oncology providers at that site. At intervention sites, 

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questions will pertain to patients not enrolled. 
 
Site Monitoring, Quality Control and Intervention Site Auditing: Quality control will be maintained with calls 
every two weeks among participating site PIs and clinical research associates. Separate calls will be held with 
intervention and control sites to reduce the risk of contamination. On those calls, we will summarize 
enrollments at each site and review the proportion of eligible patients enrolled. We will also review identified 
issues with respect to missing data and data quality identified during routine data checks.  
 
For intervention sites, fidelity to the symptom screening approach will also be monitored. Each intervention 
site will be audited at least once (4-6 months after site activation) to assess adherence to the process of 
symptom screening, namely documentation of participant training in the health records, completion of SSPedi 
at least three times weekly, and delivery of symptom reports to providers. Accessibility of local care pathways 
will also be examined. These will be evaluated as part of the implementation dimension of RE-AIM.36  
 
Proposed Practical Arrangements for Allocating Sites: The allocation sequence will be computer 
generated. Sites will be randomized 1:1 and will be stratified by two site characteristics ≥ or < median: (1) 
anticipated number of cancer patients 8-18 years of age who speak English or Spanish per year, and (2) 
percentage of patients with private insurance vs. other payment types. Block size is not disclosed in this 
protocol. Randomization will be performed using an internet-based randomization service. Assignment will be 
communicated by email to the site PI and clinical research associate following randomization.  
  
Proposed Methods for Protecting against Sources of Bias: Given the cluster randomized nature of the 
study, a potential source of bias is that allocation will be known, which could lead to selection bias during 
participant enrollment. To address this potential, efforts will be made to both identify all potentially eligible 
participants and maximize enrollment. We will describe those not approached and those who decline to 
participate in the intervention and control sites. We will describe these groups by sex, age, race, ethnicity, 
cancer type and institution.  
 
Primary, Secondary and Exploratory Outcome Measures: Endpoints for Aim 1 are PROs; all PROs are 
self-report. The primary endpoint is the total SSPedi symptom score, which is the sum of each of the 15 
SSPedi item’s Likert scores, resulting in a total score that ranges from 0 (no bothersome symptoms) to 60 
(worst bothersome symptoms). The recall period is yesterday or today. The total SSPedi score is reliable, valid 
and responsive to change in children with cancer 8-18 years of age.3 Secondary endpoints include fatigue and 
QoL. Fatigue will be measured using PROMIS. The recall period is the last 7 days. It is reliable and valid in 
children 8-18 years of age with cancer.37 QoL will be measured using the PedsQL 3.0 Acute Cancer Module.38 
The 7 day recall version will be used. This measure is a multidimensional instrument that is reliable and valid in 
children with cancer.38 It assesses pain and hurt, nausea, procedural anxiety, treatment anxiety, worry, 
cognitive problems, perceived physical appearance and communication. All PROs are validated for use in 
English and Spanish for children 8-18 years of age. 
 
For both groups, all questionnaires including SSPedi will be administered at baseline, week 4 (±1 week) 
and week 8 (±1 week) at an in-person visit during a hospitalization or clinic visit (preferred), or will be obtained 
remotely. The approach will be identical for intervention and control sites.   
 
Endpoints for Aim 2 will be abstracted from the health record and are: documentation of symptoms, 
provision of interventions for symptoms and emergency department visits and unplanned clinic visits and 
hospitalizations. Guardians will also be asked about healthcare visits to ensure encounters outside the primary 
institution are captured. Documentation of symptoms and intervention provision for symptom control will be 
abstracted from the patients’ health records using the procedures our team previously developed.4 The number 
of interventions for each symptom at each reporting period will be recorded and categorized as any 
intervention provided vs. no intervention provided. Interventions included in the local care pathway will be 
noted. Both documentation of symptoms and interventions for these symptoms will be described for each 
specific symptom at each time point. These outcomes will be obtained on each day that a week 4 or 8 SSPedi 
assessment was obtained (as measured in conjunction with the other PROs) with a one day window before 
and after these assessments. For example, if the participant completed SSPedi on a Tuesday, we would 
accept documentation of that symptom (or provision of an intervention for that symptom) if it were recorded in 
the health records on Monday, Tuesday or Wednesday. A comprehensive and field-tested list of synonyms for 
symptoms and interventions is available for each of the 15 symptoms in SSPedi.4 We found study data could 
be abstracted with minimal training and effort. De-identified source documentation will be sent to the 

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coordinating center for quality assurance. 
 
Exploratory endpoints for Aim 3 will be RE-AIM characteristics to measure reach, effectiveness, adoption 
and implementation. Sufficient understanding of the contextual factors in SPARK implementation is critical to 
ensuring future scale-up of the intervention. An important aspect of dissemination is estimating the reach and 
representativeness of participants. Therefore, we propose to describe the baseline sociodemographic 
characteristics of eligible patients who participate and who do not participate (where possible). Effectiveness 
will be evaluated through primary and secondary outcomes. In addition, we will describe the percentage of 
patients without any severely bothersome symptoms within intervention and control sites. We will estimate 
adoption of the intervention by describing characteristics of sites that participate and providers at those sites. 
We will describe adherence with symptom screening and care pathways at intervention sites. Adoption can 
also be assessed through metrics that the SPARK website itself tracks such as the number of clicks within the 
symptom screening and CPG components and specific sections clicked. Implementation will focus on care 
pathway adaptations and number of patients who use SPARK as intended.  
 
Statistical Analyses, Power Calculations and Data Management 
 
The primary endpoint is the total self-reported SSPedi score at eight weeks. We used data from our 
SSPedi validation study for power calculation.3 In that study, we recruited 302 children across nine sites who 
were hospitalized and expected to be in hospital or in clinic three days later. Children completed SSPedi on 
days 1 and 4 and a 5-point global symptom change scale on day 4. The average absolute change in total 
SSPedi scores for those who reported they were a little better or a little worse (1-point change) was 2.7 while 
the average absolute change in total SSPedi scores for those who reported they were much better or much 
worse (2-point change) was 5.6. Thus, the minimum plausible clinically important difference is likely 
approximately 3.0 but may be higher. The intracluster correlation coefficient (ICC), a measure of the degree of 
clustering, was 0.021 (95% CI 0 to 0.123). In power calculations for the proposed study, we used ICC=0.021 
but show sensitivity analyses to ICCs at the extremes of the 95% CI (which are unlikely). Among the 20 sites in 
the proposed trial, we anticipate that four will each contribute eight patients, four will each contribute 32 
patients, and the remaining 12 will each contribute 20 patients, for a total of 400 patients. With these cluster 
sizes, Table 1 shows power for combinations of these ICCs and clinically important differences, at a 2-sided 
alpha of 0.05 and assuming a within-cluster standard deviation of 8.8 (derived from the SSPedi validation 
study3). Power for each combination in the table was calculated through simulation of 4000 trials; each one 
was analyzed with a linear mixed effects model clustering by site and the percentage with a significant P value 
was taken as the estimate of power. If there is a baseline characteristic, such as age, that explains 20% of the 
variance in 8-week scores, including that variable in analyses increases power to the value shown in the far 
right column. Table 1 shows that assuming a minimal clinically important difference of 3.0 and with inclusion of 
age as a covariate in the analysis, there is 85% power with ICC=0.021. Assuming that 10% of patients have 
missing final scores, we will inflate the sample size to 444. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
The primary analysis will use the patient-level 8-week total SSPedi score as the outcome in a mixed linear 
regression model with a random effect for cluster, a fixed effect for child age, and fixed effects at the cluster 
level for stratification variables and treatment assignment. Child age will be included as it is known to be 
associated with higher total SSPedi scores39; this will reduce residual variance in scores. We do not plan to 
adjust the model for baseline SSPedi score because some of the care pathway interventions (that are 
Table 1: Power Assuming 400 Patients, Alpha=0.05 and Standard Deviation=8.8 
ICC 
Difference 
Power 
Without baseline predictor 
With age as baseline predictor 
0.000 
2.5 
71.0 
81.4 
 
3.0 
86.7 
94.2 
 
3.5 
95.9 
98.9 
0.021 
2.5 
59.5 
70.1 
 
3.0 
75.7 
85.2 
 
3.5 
86.5 
94.2 
0.123 
2.5 
26.6 
32.6 
 
3.0 
38.2 
45.3 
 
3.5 
47.7 
57.0 

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prophylactic) will affect symptoms prior to enrollment and this baseline score may already reflect some benefit 
of the cluster’s treatment assignment. All attempts to avoid missing data will be made and, given the short 
duration of this study, we anticipate a low dropout rate by week 8. However, if more than 10% of participants 
are missing the primary outcome, the primary analysis will use multiple imputation based on previous SSPedi 
assessments (weeks 0 and 4), group and site. In addition, we will conduct sensitivity analysis assuming that 
missing scores are from children with high total SSPedi scores and from children with low total SSPedi scores 
(randomly drawn from the highest and lowest quartile).  
The secondary endpoints of self-reported fatigue and QoL will be compared between randomized groups 
using the methods for the primary analysis (with inclusion of child age in the model). Presence of documented 
severely bothersome symptoms (SSPedi score of 3 or 4) and any intervention for severely bothersome 
symptoms at weeks 4 and 8 will be compared between groups for each symptom using mixed-effects logistic 
regression analysis that takes cluster effects into account. For the secondary endpoint of unplanned health 
services utilization (emergency and clinic visits and hospitalizations), the number of visits or unplanned 
admissions per child will be counted over the 8-week period and compared between randomized groups using 
a mixed-effects Poisson or negative binomial regression analysis (with zero-inflation if necessary), accounting 
for site.  
 
Child sex, race, ethnicity, diagnosis (leukemia/lymphoma, solid tumor vs brain tumor), cancer stage, 
socioeconomic status and guardian education will be described. If a covariate is found, blinded to group 
treatment assignment, to be associated with the 8-week total SSPedi scores, it will be included in each of the 
regression analyses described above for primary and secondary outcomes. In addition, psychosocial 
resources and characteristics of the usual care provided by each site (e.g. routine systematic symptom 
screening, availability of CPGs and care pathways for symptom management) will be described and accounted 
for in exploratory regression and stratified analysis. For sex in particular, we also will determine if the impact of 
the intervention is moderated by sex by including an interaction term in the model and we will explore stratified 
analysis by sex. 
 
For the exploratory aim, we propose to describe key elements related to the external validity and 
generalizability of the intervention effects using the RE-AIM framework. These analyses will be descriptive. 
 
In terms of data management, SPARK data are stored on the SickKids server each time SSPedi is 
completed. This process was used in SSPedi and other SPARK multi-institutional trials; processes met 
institutional privacy and IRB requirements to maintain personal health information. Data outside of SSPedi 
scores including demographics, non-SSPedi outcomes and covariates will be maintained in a REDCap 
database. The database will have data validation checks to maximize data quality at data entry. Data will be 
downloaded and evaluated quarterly to identify missing data and perform additional data validation checks.  
 
Feasibility and Recruitment Rate 
 
Among the 20 sites that have agreed to participate, there are expected to be 60 patients/ month who are 
newly diagnosed with cancer 8-18 years of age and who speak English or Spanish. Assuming that 60% meet 
eligibility criteria (for example, some patients will not receive treatment for cancer such as those with low grade 
brain tumors and some centers provide consultation only services for newly diagnosed patients), and 75% 
agree to participate (conservative estimate based upon other SPARK studies), we anticipate enrollment of 27 
patients/month. Thus, to reach the target sample size of 444 patients, enrollment is anticipated to be complete 
within 2 to 2.5 years (this allows for periods of slow enrollment such as holidays or when research personnel 
have limited availability). In terms of timelines, start-up activities will require 12 months, enrollment and follow-
up of the last patient will require 24 to 36 months, data analysis will require nine months and knowledge 
dissemination will be completed within three months. Thus, the entire study will require five years to complete.  
 
The time commitment of participants, providers and research staff is expected to be similar to other 
supportive care and SPARK trials and we do not anticipate barriers with respect to effort required. Abstraction 
of symptom documentation and intervention provision will be done over a short time frame (3 days for each of 
two time points (weeks 4 and 8)); pilot work at SickKids has shown this workload to be modest. The PROs at 
weeks 4 and 8 will require <5-10 minutes to complete and can be completed electronically.  
 
Knowledge Translation and Exchange 
 
The targets of our KTE efforts are patients, families, healthcare providers and decision makers including 
hospital and governmental administrators. 
Integrated KTE: To increase awareness and to engage with a variety of stakeholders, we will create an 
Advisory Panel. The Panel will include two childhood cancer survivors, one parent of a child with cancer, 

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healthcare providers and hospital administrators. We will meet face-to-face or by teleconference at least 
annually to discuss progress and identify opportunities for KTE. 
End of Grant KTE: We will publish the results of this study in peer-reviewed journals (minimum of 3 mid to high 
impact journals) and support attendance at national and international conferences. We plan to distribute plain 
language summaries throughout the COG, the C17 Research Network (represents the 17 centers in Canada) 
and the Pediatric Oncology Group of Ontario (represents the 5 centers in Ontario). We also plan to hold regular 
webinars and podcasts. The SickKids Industry, Partnerships and Commercialization office will help promote 
SPARK as a no cost web-portal for hospital use. In order to further enhance KTE, we will create an end-of-
grant report that summarizes the processes refined to achieve symptom screening and feedback, and to adapt 
local care pathways for symptom management. This report will include the steps taken, challenges 
encountered and solutions to those challenges. This report will help other institutions to implement the 
approach expeditiously. 
 
 
 
  
 
 
 
 

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Adapting to New Science and Practice With a 20-Year Review. Front Public Health 7:64, 2019 
 
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38. 
Varni JW, Burwinkle TM, Katz ER, et al: The PedsQL in pediatric cancer: reliability and validity 
of the Pediatric Quality of Life Inventory Generic Core Scales, Multidimensional Fatigue Scale, and Cancer 
Module. Cancer 94:2090-2106, 2002 
 
39. 
Johnston DL, Hyslop S, Tomlinson D, et al: Describing symptoms using the Symptom Screening 
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40. 
Wild D, Grove A, Martin M, et al: Principles of Good Practice for the Translation and Cultural 
Adaptation Process for Patient-Reported Outcomes (PRO) Measures: report of the ISPOR Task Force for 
Translation and Cultural Adaptation. Value Health 8:94-104, 2005 
 
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Prioritization and Recommendations for Kids (SPARK), a symptom screening and management application. 
Submitted 2018 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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Appendix 1: Symptom Screening in Pediatrics Tool (SSPedi)  
 
 

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Appendix 2: SPARK Landing Page  
 
 
 
 
 

PROTOCOL AMENDMENT SUMMARY OF CHANGES TABLE 
Document History of Initial Approvals, Amendments and Statistical Plan 
Version Date 
Timeline 
Date 
N/A 
Data sent to biostiatistician 
15Dec2023 
21Nov2023 
Statistical Analysis Plan Uploaded to 
ClinicalTrials.gov 
13Dec2023 
21Nov2023 
Amendment #2-4 – statistical edits 
Nov 23, 2023 
July 19, 2023 
April 18, 2023 
21Dec2021 
Amendment #1 – modified eligibility criteria and 
ability to contact 
March 2, 2022 
26Feb2020 
Initial protocol approved by SickKids Research 
Ethics Board 
April 15, 2020 
 
Amendment #2-4 (version date 21Nov2023) 
Protocol Section Major Modifications 
Reason for Amendment 
Statistical 
Analysis, Power 
Calculations and 
Data 
Management 
Modifications to match the final statistical 
analytical plan uploaded to 
clinicaltrials.gov 
To match the final statistical 
analytical plan uploaded to 
clinicaltrials.gov 
 
Amendment #1 (version date 21Dec2021) 
Protocol Section Major Modifications 
Reason for Amendment 
Eligibility Criteria 
Added: 
(5) have a plan to be followed by or 
receive care from the study institution for 
≥ 50% of the 8-week study period and 
expected to be available on site or 
virtually for the week 8 assessment and 
(6) enroll within 28 days after diagnosis or 
treatment initiation, whichever occurs 
later. 
Changes made to study 
eligibility to ensure there is a 
healthcare team at the 
participating site to receive 
the reports and have the 
ability to act on them if 
required for the on-study 
period, and to account for 
patients that receive initial 
treatment prior to a 
confirmed cancer diagnosis. 
Procedures 
Added that participants may be contacted 
in person, by email, text, or over the 
phone to ensure there are no technical 
barriers to completing SSPedi. 
Changes made to 
procedures since we have 
identified technical issues 
preventing receipt of 
reminders to complete 
SSPedi. This allows us to 
identify and address those 
issues if needed. 
 

Version Date: November 21, 2023 
 
1 
 
Statistical Analytic Plan for Symptom Screening Linked to Care Pathways  
for Children with Cancer: A Cluster Randomized Trial 
 
Study Title: Symptom Screening Linked to Care Pathways for Children with Cancer: A Cluster 
Randomized Trial 
 
NCT Number: NCT04614662 
 
Document Date: November 21, 2023 
 
Objectives ___________________________________________________________________ 2 
Sample Size Justification _______________________________________________________ 2 
Analytic datasets _____________________________________________________________ 2 
Study Outcomes ______________________________________________________________ 3 
Descriptive Statistics __________________________________________________________ 5 
Comparative Analyses _________________________________________________________ 5 
Primary outcome __________________________________________________________________ 5 
Secondary outcomes _______________________________________________________________ 5 
Missing data _________________________________________________________________ 7 
Software ____________________________________________________________________ 9 
 
 
 

Version Date: November 21, 2023 
 
2 
 
Objectives 
Aims 1 and 2: Among children with newly diagnosed cancer, to determine if symptom screening 
and feedback to healthcare providers at least three times weekly and locally-adapted symptom 
management care pathways, when compared to usual care: 
Aim 1. Improves overall self-reported symptom scores (total SSPedi score), fatigue 
(PROMIS–Fatigue) and cancer-specific quality of life (QoL) (PedsQL 3.0 Acute Cancer 
Module) over 8 weeks. 
Hypothesis: Symptom screening and care pathways will improve symptoms, fatigue and 
QoL 
Aim 2. Improves symptom documentation, increases provision of interventions for 
symptoms, and reduces emergency department visits and unplanned clinic visits and 
hospitalizations over 8 weeks. 
Hypotheses: Symptom screening and care pathways will increase symptom 
documentation and provision of interventions for symptoms, and will reduce healthcare 
utilization. 
Aim 3: As an exploratory aim, we will evaluate key elements of the intervention related to the 
external validity and generalizability of the intervention effects using the RE-AIM framework.  
 
Sample Size Justification 
 
The primary endpoint is the total self-reported SSPedi score at eight weeks. We used 
data from our SSPedi validation study for power calculation. In that study, we recruited 302 
children across nine sites who were hospitalized and expected to be in hospital or in clinic three 
days later. Children completed SSPedi on days 1 and 4 and a 5-point global symptom change 
scale on day 4. The average absolute change in total SSPedi scores for those who reported they 
were a little better or a little worse on this global change scale (a 1-point change) was 2.7 while 
the average absolute change in total SSPedi scores for those who reported they were much 
better or much worse (a 2-point change) was 5.6. Thus, the minimum plausible clinically 
important difference is likely approximately 3.0 but may be higher. The intracluster correlation 
coefficient (ICC), a measure of the degree of clustering, was 0.021 (95% confidence interval (CI) 
0 to 0.123). In power calculations for the proposed study, we used ICC=0.021 but show 
sensitivity analyses to ICCs at the extremes of the 95% CI (which are unlikely). Among the 20 
sites in the proposed trial, we anticipate that four will each contribute eight patients, four will 
each contribute 32 patients, and the remaining 12 will each contribute 20 patients, for a total of 
400 patients. With these cluster sizes, Table 1 shows power for combinations of these ICCs and 
clinically important differences, at a 2-sided alpha of 0.05 and assuming a within-cluster 
standard deviation of 8.8 (derived from the SSPedi validation study). Power for each 
combination in the table was calculated through simulation of 4000 trials. Each one was 
analyzed with a linear mixed effects model clustering by site and the percentage with a 
significant P value was taken as the estimate of power. If there is a baseline characteristic, such 
as age, that explains 20% of the variance in 8-week scores, including that variable in analyses 
increases power to the value shown in the far right column. Table 1 shows that assuming a 
minimal clinically important difference of 3.0 and with inclusion of age as a covariate in the 
analysis, there is 85% power with ICC=0.021. Assuming that 10% of patients have missing final 

Version Date: November 21, 2023 
 
3 
 
scores, we inflated the sample size to 444. 
 
 
Analytic Datasets  
 
All analyses will follow the intention-to-treat principle. See below (Missing Data) for details 
on how those with missing data will be included in the analysis. 
 
Study Outcomes 
Questionnaires including the primary outcome and secondary patient-reported outcomes are 
obtained at weeks 4 and 8 from enrollment. 
1. Primary outcome: The primary outcome is the total SSPedi symptom score, which is the 
sum of each of the 15 SSPedi item’s Likert scores, resulting in a total score that ranges 
from 0 (no bothersome symptoms) to 60 (worst bothersome symptoms).  The 
designated week 4 or 8 SSPedi score will be taken on the day the other patient-reported 
outcomes were obtained or were planned to be obtained. This assures that the SSPedi 
score was collected as an outcome rather than as an intervention.  
2. Secondary outcomes: 
a. Individual SSPedi symptom scores, which consist of each of the 15 symptoms 
scored as 0, 1, 2, 3 or 4. 
b. Fatigue will be measured using PROMIS. The raw score is translated to a T-score 
for each participant, where in the general population, the average T-score is 50 
and the standard deviation is 10.  The recall period is the last seven days. A 
higher T-score represents more fatigue, or worse health. 
c. PedsQL 3.0 Acute Cancer Module (scored according to 
https://www.pedsql.org/PedsQL-Scoring.pdf), which produces 8 domain scores 
on a 0-100 scale. The domains are (1) pain and hurt; (2) nausea; (3) procedural 
anxiety; (4) treatment anxiety; (5) worry; (6) cognitive problems; (7) perceived 
physical appearance; and (8) communication. The recall period is the last seven 
days. Higher scores indicate better QoL. 
Table 1: Power With 400 Patients, Alpha=0.05 and Standard Deviation=8.8 
ICC 
Difference 
Power (%) 
Without baseline predictor 
With age as baseline predictor 
0.000 
2.5 
71.0 
81.4 
3.0 
86.7 
94.2 
3.5 
95.9 
98.9 
0.021 
2.5 
59.5 
70.1 
3.0 
75.7 
85.2 
3.5 
86.5 
94.2 
0.123 
2.5 
26.6 
32.6 
3.0 
38.2 
45.3 
3.5 
47.7 
57.0 

Version Date: November 21, 2023 
 
4 
 
d. Documentation of symptoms (mapped onto the 15 SSPedi symptoms) in the 
participant’s heath record; these are a set of 15 binary outcomes (assessed at 
weeks 4 and 8). For each, the window is a 3-day period extending from one day 
before to one day after the week 4 and 8 SSPedi time point. 
e. SSPedi symptom-specific intervention performed; these are a set of 15 binary 
outcomes (assessed at weeks 4 and 8). For each, the window is a 3-day period 
extending from one day before to one day after the week 4 and 8 SSPedi time 
point. 
f. Healthcare encounters including emergency department visits, unplanned clinic 
visits and unplanned hospitalizations over the 8-week period.  The number of 
encounters in each category and the total across categories will each be a 
separate secondary outcome. 
3. Exploratory outcomes: These are RE-AIM characteristics to measure reach, 
effectiveness, adoption and implementation.  
a. For reach, we propose to describe the baseline demographic characteristics of 
eligible patients who participate and who do not participate. We will also 
describe site attributes using the inner setting measures from the Consolidated 
Framework for Implementation Research (CFIR) as measured at baseline.(18, 19)  
This conceptual framework includes factors that may impact on intervention 
implementation. These attributes include culture, culture stress, culture effort, 
implementation climate, learning climate, leadership engagement and available 
resources.  
b. Effectiveness will be evaluated through primary and secondary outcomes as 
described in list items 1 and 2 above and also by comparisons of the percentages 
of patients with severely bothersome symptoms within intervention and control 
sites. We will characterize adoption at intervention sites by describing 
characteristics of sites and providers at those sites.  Site characteristics will 
include pediatric vs. mixed adult and pediatric, number of pediatric cancer 
patients diagnosed annually, and percentage of patients anticipated to have 
private, public or no insurance. Healthcare professional characteristics will 
include number of physician and nurse practitioner full-time equivalents and 
median years in practice.   
c. Adoption will be assessed through the number of SSPedis per participant 
completed at intervention institutions; this analysis will use duration of time on 
protocol therapy as an offset. Further, we will dichotomize each participant as a 
high or low SSPedi completer, with a high completer being defined as one who 
completed 15 or more SSPedis. This analysis will use those who complete 
protocol therapy as planned as the denominator. In addition, we will count the 
number of times the institutional care pathways were clicked at intervention 
sites. We will describe the total number of clicks overall and by specific care 
pathway, access route (email link or QR code) and device (iPad, iPhone, Mac, 
Windows or unknown). 
d.  Implementation outcomes will capture the percentages of intervention patients 
who came off protocol therapy early and the number of all participants  who 

Version Date: November 21, 2023 
 
5 
 
came off study early, both overall and stratified by intervention or control group.  
 
Descriptive Statistics 
Baseline characteristics: Summary statistics on baseline characteristics will be calculated within 
each study arm and presented in a table – means and standard deviations (SDs) for variables 
treated as continuous, counts and percentages for categorical variables, along with total 
numbers with missing data.   
Outcomes: Similar tables will be created for all study outcomes.  Individual SSPedi symptom 
scores will be summarized by the percentages of participants with scores of 3 or 4, the two 
most bothersome categories. 
 
Comparative Analyses 
Primary Outcome 
 
The primary analysis will use the patient-level 8-week total SSPedi score as the outcome in 
a mixed linear regression model with a random effect for cluster, fixed effects for treatment 
assignment, child age and diagnosis group (leukemia/lymphoma, solid tumor and central 
nervous system tumor), and two binary fixed effects at the cluster level for stratification 
variables (above or below the average anticipated yearly number of English or Spanish-speaking 
cancer patients 8-18 years of age, and above or below the average anticipated percentage of 
patients with private insurance vs. other payment types). Child age and diagnosis group will be 
included as they are known to be associated with total SSPedi scores; this will reduce residual 
variance in scores. We do not plan to adjust the model for baseline SSPedi score because some 
of the care pathway interventions (that are prophylactic) will affect symptoms prior to 
enrollment and the baseline score may already reflect some benefit of the cluster’s treatment 
assignment. The treatment effect will be the covariate-adjusted mean difference between 
study groups in 8-week SSPedi, presented with a 95% CI and a two-sided p-value for a test of no 
treatment effect. If we find the residuals from the mixed model fitted to the 8-week total 
SSPedi score deviate substantially from normality, we will conduct sensitivity analyses, one 
using normalizing transformations of the outcome and another using an ordinal regression 
model.  
 
To account for potential differential enrollment of surgery only patients (who might not be 
cared for by oncology teams) between intervention vs. control sites, we will also conduct a 
sensitivity analysis restricted to patients that received systemic chemotherapy.  
 
  
Secondary Outcomes  
1. Self-reported individual symptoms at weeks 4 and 8 on the SSPedi instrument: For 
each of the 15 ordinal outcomes representing symptoms (scored 0-4), a mixed effects 
proportional odds model will be fitted using treatment assignment and stratification 
factors as fixed effects covariates and with a random effect for site.  As some individual 
symptoms may be uncommon, to avoid specifying models that may be overfitted for 
those symptoms, these models will use only this minimal set of three covariates. The 
estimated odds ratio for the intervention (representing the odds of having a higher vs. 
lower score in the intervention group) will be estimated and presented along with a 95% 

Version Date: November 21, 2023 
 
6 
 
CI. Two figures will be generated to present these results graphically: (a) to display the 
raw outcome data, a set of 15 pairs of stacked barplots will be created; within each pair, 
the stacked barplot will show the percentages of participants with scores of 0-4 in the 
control and intervention groups; (b) a forest-plot type figure will be created showing the 
estimated odds ratios with 95% CIs for each of the 15 symptoms. 
2. PROMIS Fatigue Scale: This scale will be treated as a continuous variable and analyzed 
using a linear mixed effects model in the same way as the primary SSPedi outcome.   
3. PedsQL 3.0 Acute Cancer Module domain scores:  Each of these 8 scores will be treated 
as continuous variables and analyzed using a linear mixed effects model in the same way 
as the primary SSPedi outcome.  A forest-plot type figure will be created showing the 
estimated treatment effects with 95% CIs for each of the 8 domains. 
4. Documentation of symptoms on weeks 4 and 8 (± 1 day): Analyses will involve three 
analyses for each symptom class. Each analysis will fit a mixed effects logistic regression 
model to estimate the odds ratio for documentation (on weeks 4 and 8) comparing 
intervention groups, adjusting for stratification factors. It is possible that there will be 
too few documentation events to reliably fit this mixed model to all 15 symptoms. If this 
model cannot be fitted to some symptoms (likely because the random effects variance 
cannot be estimated), we will fit a fixed effects logistic regression model to just those 
symptoms. Three cohorts will be defined: 
a. Each participant will be classed as having the symptom documented or not. All 
participants are included in the analytic sample for each symptom. 
b. The analytic sample will be limited to those participants who self-report the 
symptom on weeks 4 and 8 (symptom score > 0).  
c. The analytic sample will be limited to those participants who have the most 
bothersome self-report of the symptom on the weeks 4 and 8 SSPedi (symptom 
score ≥ 3). 
5. Interventions for symptoms: Analyses will follow a similar flow to the analyses of 
documentation of symptoms. For each of the 15 symptoms, each participant will be 
classified as having an intervention at weeks 4 and 8 (±1 days).  Also collected is 
whether interventions were administered specifically for the specific symptoms. For 
example, acetaminophen may be administered for fever or pain. As interventions are 
expected to be more uncommon than symptoms, all treatment effects will be estimated 
by simple differences in the proportions with interventions (i.e., ignoring clustering), p-
values will be computed from the Fisher exact test, and 95% CI for differences in 
proportions will use the Newcombe method. Three cohorts will be defined: 
a. Each participant will be classed as having an intervention for the symptom or 
not. All participants are included in the analytic sample for each intervention-
symptom pair. 
b. The analytic sample will be limited to those participants who self-report the 
symptom on the weeks 4 and 8 SSPedi (symptom score > 0).  
c. The analytic sample will be limited to those participants who have the most 
bothersome self-report of the symptom on the weeks 4 and 8 SSPedi (symptom 
score ≥ 3). 

Version Date: November 21, 2023 
 
7 
 
6. Unplanned encounters: For each of the secondary endpoints of unplanned health 
services utilization (emergency, clinic visits, hospitalizations, and the total across 
categories), the number of events per child will be counted over the 8-week period and 
compared between randomized groups using a mixed-effects Poisson or negative 
binomial regression analysis (with zero-inflation if necessary), with a random effect for 
site and fixed effects for the two stratification factors. If a child has less than 8 weeks of 
follow-up, the model will include an offset equal to the logarithm of each child’s follow-
up time. 
 
Exploratory Outcomes 
1. Reach: we will describe the baseline demographic characteristics (sex, age or age group 
and diagnosis group) of eligible patients who participate and who do not participate 
using means and standard deviations for continuous variables and counts and 
percentages for categorical variables. The difference between participants and non-
participants will be summarized two ways: numerically by the standardized mean 
difference and graphically by side-by-side barplots for categorical variables and by side-
by side beeswarm plots for continuous variables. We will also summarize CFIR inner 
setting attributes as counts and percentages. 
2. Effectiveness: In addition to the analyses of primary and secondary outcomes detailed 
above, we will also carry out analyses that dichotomize each of the 15 SSPedi symptoms 
as being severely bothersome (3 or 4) or not.  Percentages for each symptom will be 
tabulated and compared between intervention groups using mixed effects binary 
logistic regression. We will also assess between-site variation in the odds of having a 
severely bothersome symptom (after adjusting for intervention and stratification 
factors) by plotting the random effects associated with each site and by calculating the 
median odds ratio (MOR). This is an alternative measure of clustering (or between-
cluster variability); it is the estimated median of the ratio of the odds of a bothersome 
symptom for a participant at one site to the odds of a bothersome symptom for an 
otherwise identical participant at another site. The MOR is always defined with the 
higher odds in the numerator. One appealing aspect of the MOR is that it is on the same 
scale as the odds ratio for treatment, aiding interpretation of both the OR for 
intervention and the MOR for variation in the outcome. 
3. Adoption: We will characterize adoption at intervention sites by summarizing the 
following:  
a. characteristics of sites and their providers 
b. number of SSPedis completed per enrolled participant 
c. proportion of participants that are high or low SSPedi completers 
d. number of times the institutional care pathways were clicked.  
 
Site and provider attributes will be described by using means and standard 
deviations for continuous variables and counts and percentages for categorical 
variables. Site characteristics will include pediatric vs. mixed adult and pediatric, number 
of pediatric cancer patients diagnosed annually, and percentage of patients anticipated 
to have private, public or no insurance. Healthcare professional characteristics will 

Version Date: November 21, 2023 
 
8 
 
include number of physician and nurse practitioner full-time equivalents and median 
years in practice.  CFIR attributes will also be described.  
 
The dependence of the number of SSPedis completed by a participant on 
participant, guardian and site characteristics will be assessed using a mixed effects 
Poisson or negative binomial regression model, with a random effect for site.  
Participant characteristics will include sex, age/age group, race, ethnicity, preferred 
language, and cancer diagnosis group. Guardian characteristics will include marital 
status, guardian employment and highest education, and high annual household 
income. Site characteristics will be those included above. The dependence of the odds 
of being a high responders on these same characteristics will be assessed using mixed 
effects logistic regression adjusting for stratification factors.   
 
The number of recorded clicks is available on aggregate for each site, so we will 
summarize this as a set of 10 rates, clicks per enrolled participant, and assess whether 
there is site-to-site variability by fitting a random effects Poisson or negative binomial 
model with clicks as the outcome and the logarithm of the number of patients as an 
offset.  A summary rate will be estimated from this model and the median rate ratio 
(analogous to the MOR above) will be calculated. 
4. Implementation will calculate the percentage of patients who enrolled but came off 
protocol therapy early (intervention only) or off study early (all participants), overall and 
stratified by intervention or control group.  Counts and percentages will be shown, with 
no inferential statistics. 
 
Missing Data 
Rule-based methods: The PedsQL will be scored according to its scoring guide, which includes 
rules for scoring in the presence of missing elements on each domain modules.  No other 
deterministic rule-based method will be used to deal with missing data.   
 
Multiple imputation: If more than 10% of participants are missing the primary outcome or 
secondary patient-reported outcomes, the analysis will use multiple imputation based on 
previous SSPedi assessments (weeks 0 and 4), group and site. In addition, we will conduct 
sensitivity analysis assuming that missing scores are from children with high total SSPedi scores 
and from children with low total SSPedi scores (randomly drawn from the highest and lowest 
quartile). A set of 20 complete datasets will be generated using separate within-treatment-
group imputation models. These models will include all the study outcomes listed just above, 
and the key covariates that appear in our adjusted models (age, diagnosis group and 
stratification factors). The models will be fitted in each imputed dataset and the pooled 
estimate of the treatment effect and its standard error will be computed using Rubin’s rules.  
 
Analyses of documentation and interventions will not use any imputation. There can be no 
missing data for these outcomes: if a symptom is not documented in the health record and 
there is no record of an intervention being used, then this constitutes a ‘no’ for the outcome. 
While it is possible that the SSPedi symptom score needed for the identification of the analytic 
datasets in analyses (4b, 4c, 5b, and 5c) is missing for some participants, the more exploratory 
nature of these analyses led us to the decision to use only observed data for these outcomes.  

Version Date: November 21, 2023 
 
9 
 
 
Software 
All analyses will use R 4.3.0 with these specific packages: 
- base R for general programming and fitting linear and logistic regression models. 
- the tidyverse and lubridate packages for data “wrangling”. 
- the rms package for the proportional odds model. 
- the mice package for multiple imputation. 
- the ggplot2 package for graphs. 
- the tableone package for summary descriptive tables. 
- glmer for linear and logistic mixed effects regression models 
- ordinal for proportional odds mixed effects regression models 
 
Planned Tables 
Planned tables are below. 
 
 
 

Version Date: November 21, 2023 
 
10 
 
Table 1: Participant Demographic Characteristics 
Characteristics 
All Patients  
 
Symptom 
Screening 
 
Usual Care 
 
 
 
 
 
Male 
 
 
 
Median Age in Years (range) 
 
 
 
Age Group in Years 
 
 
 
8-10 
 
 
 
11-14 
 
 
 
15-18 
 
 
 
Race 
 
 
 
American Indian or Alaska Native 
 
 
 
Asian 
 
 
 
Black or African American 
 
 
 
Native Hawaiian or Other Pacific 
Islander 
 
 
 
White 
 
 
 
Unknown 
 
 
 
Ethnicity 
 
 
 
Hispanic or Latino 
 
 
 
Not Hispanic or Latino 
 
 
 
Unknown 
 
 
 
Diagnosis 
 
 
 
Leukemia 
 
 
 
Lymphoma 
 
 
 
Solid tumor 
 
 
 
Brain tumor 
 
 
 
Other 
 
 
 
Metastatic Disease 
 
 
 
Median Days from Diagnosis (range) 
 
 
 
Planned or Received Treatment 
 
 
 
Chemotherapy 
 
 
 
Radiotherapy 
 
 
 
Surgery 
 
 
 
Median Days from Treatment Start 
(range) 
 
 
 
Inpatient at Enrollment 
 
 
 
First language English or Spanish 
 
 
 
Preferred Language for Patient 
Reported Outcomes 
 
 
 
English 
 
 
 
Spanish 
 
 
 
Not applicable (chart review only) 
 
 
 
Family Composition - Married 
 
 
 
Guardian Employment Full or Part Time 
 
 
 
Guardian Education College or Higher 
 
 
 
Annual Household Income ≥ $60,000 
 
 
 
 

Version Date: November 21, 2023 
 
11 
 
 
 
Table 2: SSPedi Outcomes by Assessment Timepoint and Group 
 
Baseline 
Week 4 
Week 8 
Treatment Effect 
Estimate;  
 95% CI; p-value 
 
Symptom 
Screening  
Usual 
Care  
Symptom 
Screening  
Usual 
Care  
Symptom 
Screening  
Usual 
Care  
Unadjusted Adjusted 
Primary Outcome 
 
 
 
 
 
 
Mean Difference 
SSPedi Score 
(mean, SD) 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Odds Ratio 
Secondary 
Outcomes 
 
 
 
 
 
 
 
 
Severely 
Bothersome, n (%)* 
 
 
 
 
 
 
 
 
Feeling 
disappointed or 
sad 
 
 
 
 
 
 
 
 
Feeling scared 
or worried 
 
 
 
 
 
 
 
 
Feeling cranky 
or angry 
 
 
 
 
 
 
 
 
Problems with 
thinking or 
remembering 
things 
 
 
 
 
 
 
 
 
Changes in how 
your body or 
face look 
 
 
 
 
 
 
 
 
Feeling tired 
 
 
 
 
 
 
 
 
Mouth sores 
 
 
 
 
 
 
 
 
Headache 
 
 
 
 
 
 
 
 
Hurt or pain 
(other than 
headache) 
 
 
 
 
 
 
 
 
Tingly or numb 
hands or feet 
 
 
 
 
 
 
 
 
Throwing up or 
feeling like you 
may throw up 
 
 
 
 
 
 
 
 
Feeling more or 
less hungry than 
you usually do 
 
 
 
 
 
 
 
 
Changes in 
taste 
 
 
 
 
 
 
 
 
Constipation 
(hard to poop) 
 
 
 
 
 
 
 
 
Diarrhea 
(watery, runny 
poop) 
 
 
 
 
 
 
 
 

Version Date: November 3, 2023 
 
 
12 
Table 3: Non-SSPedi Patient-reported Outcomes by Assessment Timepoint and Group 
 
 
 
 
 
Baseline 
 
 
Week 8 
Treatment Effect 
Estimate;  
 95% CI; p-value 
 
Symptom 
Screening 
(n=175) 
Usual 
Care 
(n=169) 
 
 
Symptom 
Screening 
(n=168) 
Usual 
Care 
(n=164) 
Unadjusted 
 
Adjusted 
 
PROMIS Fatigue 
(Mean, SD) 
 
 
 
 
 
 
Mean Difference 
 
 
 
 
 
 
 
 
 
Total PedsQL 3.0 
Acute Cancer 
Module Score 
(Mean, SD) 
 
 
 
 
 
 
Mean Difference 
Pain and hurt 
 
 
 
 
 
 
 
 
Nausea 
 
 
 
 
 
 
 
 
Procedural 
anxiety 
 
 
 
 
 
 
 
 
Treatment 
anxiety 
 
 
 
 
 
 
 
 
Worry 
 
 
 
 
 
 
 
 
Cognitive 
problems 
 
 
 
 
 
 
 
 
Perceived 
physical 
appearance  
 
 
 
 
 
 
 
 
Communication 
 
 
 
 
 
 
 
 

Version Date: November 3, 2023 
 
 
13 
Table 4: Symptom Documentation and Intervention by Group for All Participants 
 
Symptom 
Screening 
Usual Care 
 P value 
 
 
 
 
Symptom Documentation (%) 
 
 
 
Feeling disappointed or sad 
 
 
 
Feeling scared or worried 
 
 
 
Feeling cranky or angry 
 
 
 
Problems with thinking or 
remembering things 
 
 
 
Changes in how your body or 
face look 
 
 
 
Feeling tired 
 
 
 
Mouth sores 
 
 
 
Headache 
 
 
 
Hurt or pain (other than 
headache) 
 
 
 
Tingly or numb hands or feet 
 
 
 
Throwing up or feeling like you 
may throw up 
 
 
 
Feeling more or less hungry 
than you usually do 
 
 
 
Changes in taste 
 
 
 
Constipation (hard to poop) 
 
 
 
Diarrhea (watery, runny poop) 
 
 
 
 
 
 
 
Any Symptom Intervention (%) 
 
 
 
Feeling disappointed or sad 
 
 
 
Feeling scared or worried 
 
 
 
Feeling cranky or angry 
 
 
 
Problems with thinking or 
remembering things 
 
 
 
Changes in how your body or 
face look 
 
 
 
Feeling tired 
 
 
 
Mouth sores 
 
 
 
Headache 
 
 
 
Hurt or pain (other than 
headache) 
 
 
 
Tingly or numb hands or feet 
 
 
 
Throwing up or feeling like you 
may throw up 
 
 
 
Feeling more or less hungry 
than you usually do 
 
 
 
Changes in taste 
 
 
 
Constipation (hard to poop) 
 
 
 
Diarrhea (watery, runny poop) 
 
 
 
 
 
 
 
Symptom Intervention Clearly 
 
 
 

Version Date: November 3, 2023 
 
 
14 
for Symptom (%) 
Feeling disappointed or sad 
 
 
 
Feeling scared or worried 
 
 
 
Feeling cranky or angry 
 
 
 
Problems with thinking or 
remembering things 
 
 
 
Changes in how your body or 
face look 
 
 
 
Feeling tired 
 
 
 
Mouth sores 
 
 
 
Headache 
 
 
 
Hurt or pain (other than 
headache) 
 
 
 
Tingly or numb hands or feet 
 
 
 
Throwing up or feeling like you 
may throw up 
 
 
 
Feeling more or less hungry 
than you usually do 
 
 
 
Changes in taste 
 
 
 
Constipation (hard to poop) 
 
 
 
Diarrhea (watery, runny poop) 
 
 
 
 
 
 

Version Date: November 3, 2023 
 
 
15 
Table 5: Number of Unplanned Healthcare Encounters by Group  
 
Unplanned Encounter Type 
Total  
 
Symptom Screening 
 
Control  
 
 
 
(n=xx) 
(n=xx) 
All unplanned encounters 
 
 
 
    Rate per 100 patient-weeks 
 
 
 
Number of encounters (n, %) 
 
 
 
0 
 
 
 
1 
 
 
 
2 
 
 
 
3 
 
 
 
4 
 
 
 
5 
 
 
 
6 or more 
 
 
 
Emergency department visits 
 
 
 
     Rate per 100 patient-weeks 
 
 
 
Number of encounters (n, %) 
 
 
 
0 
 
 
 
1 
 
 
 
2 
 
 
 
3 
 
 
 
4 
 
 
 
5 
 
 
 
6 or more 
 
 
 
Unplanned clinic visits  
 
 
 
    Rate per 100 patient-weeks 
 
 
 
Number of encounters (n, %) 
 
 
 
0 
 
 
 
1 
 
 
 
2 
 
 
 
3 
 
 
 
4 
 
 
 
5 
 
 
 
6 or more 
 
 
 
Unplanned hospital admissions  
 
 
 
    Rate per 100 patient-weeks 
 
 
 
Number of encounters (n, %) 
 
 
 
0 
 
 
 
1 
 
 
 
2 
 
 
 
3 
 
 
 
4 
 
 
 
5 
 
 
 
6 or more