Palliative Care Interventions for Outpatients Newly Diagnosed With Lung Cancer: Phase II
Phase: NA
Conditions: Lung Cancer
Sponsor: VA Office of Research and Development

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Project Number: NRI 15-456-1 
Project Title: Palliative Care Interventions for Outpatients Newly Diagnosed with Lung 
Cancer: Phase II 
Principal Investigator: Lynn F. Reinke, PhD, ARNP; VA Puget Sound Health Care 
System 
Primary Site: VA Puget Sound Health Care System 
Secondary Sites: Birmingham VA Medical Center, Portland VA Medical Center 
DATA ANALYSIS PLAN (DAP) 
A. Study sample size rationale
Power Calculation 
Sample size calculations for the study were calculated in order to be well-powered to evaluate 
the main primary outcome in Aim 1, the Functional Assessment of Cancer Therapy - Lung 
Scale Trial Outcome Index (FACT-L TOI) assessed at baseline and completion of the study 
post-randomization. This measure assesses functional and physical well-being and lung 
cancer specific symptoms, and is the most well described measurement of quality of life in 
lung cancer patients and has been used extensively in clinical trials. We calculated sample 
sizes assuming a minimum clinically meaningful difference of 5 points in the intervention arm 
as compared to the usual care arm, corresponding to an effect size of 0.45, considered a 
moderate effect size in the Cella study [1]. We assume a maximum standard deviation of 11 in 
both arms, an estimate taken from a study done in a similar population of patients and 
matching our pilot study data [2].  We use a conservative estimate 15% attrition rate based on 
our previous recruitment experience with patients with lung cancer. Correlation within subject 
between baseline and outcome measures is estimated to be between .4 and .6.  We base our 
study on a correlation of 0.5.  To have 80% power (with a two-tailed alpha of 0.05), we require 
69 patients per group for a total of 138 patients*. 
Correlation (ρ)
ρ=0.4
ρ=0.5
ρ=0.6
Required Total Sample 
Size* 
154 
138 
118 
Further details of our sample size calculation can be found below: 
For a randomized control trial, the hypothesis that will be tested is Ho: δ = μc −μI = 0 vs. 
Ha: δ = μc −μI ≠0.  According to Friedman et al [3], the sample size needed for each group for 
conducting a two-tailed test of size α with power of 1-β is  
𝑛=
2 𝜎2 (𝑍𝛼/2 + 𝑍𝛽)
2
𝛿2
Where δ/σ is equivalent to Cohen’s d and Zα/2 and Zβ are critical values for the standard normal 
distribution at α/2 and β respectively. 
The final n required for each group to adequately power the study is then: 
September 30, 2017

2 
 
𝑛𝑓𝑖𝑛𝑎𝑙=
𝑛(1 −𝜌2)
1 −𝑎𝑡𝑡𝑟𝑖𝑡𝑖𝑜𝑛 
 
Where (1 − 𝜌2) is the design factor for an ANCOVA design [4] and 
1
1−𝑎𝑡𝑡𝑟𝑖𝑡𝑖𝑜𝑛 accounts for the 
highest expected attrition in the study. 
 
 
B. Data collection 
Setting 
The study will be performed at the three VA Medical Centers, Puget Sound Health Care System 
(VAPSHCS), Birmingham VA HCS, and Portland VA Medical Center, all university-affiliated 
tertiary medical centers.  VAPSHCS receives approximately 100 new diagnoses of lung cancer 
annually and provides care to patients with lung cancer for the northern alliance of VISN 20 that 
includes all of Washington State, Alaska, and Idaho. VAPSHCS provides full diagnostic and 
treatment services for lung cancer including pulmonary medicine, oncology medicine, 
cardiothoracic surgery, and radiation oncology. VAPSHCS has only in-patient palliative care 
consult service and no outpatient palliative care clinic. The Birmingham VA receives 
approximately 150 new diagnoses of lung cancer annually and provides care to patients with 
lung cancer within VISN 7. The Birmingham VA offers in-patient palliative care consult services 
and no outpatient palliative care services. The Portland VA receives approximately 150 new 
diagnoses of lung cancer annually and provides care to patients with lung cancer within VISN 
20. The Portland VA offers in-patient palliative care consult services and no outpatient palliative 
care services. Ancillary care services for all centers include social service, Chaplain service, 
nutrition, home care, and referrals for hospice.   
Subjects 
Our study population includes Veterans diagnosed with non-small and small cell lung cancer 
receiving care at the VAPSHCS, Birmingham VA HCS and Portland VA HCS.   
 
Identification and recruitment process 
We will recruit individuals (n=138) with lung cancer over a 2.5 year period using a similar 
approach that we used for our NRI pilot study. We will target recruitment activities to identify all 
patients at both VA PSHCS and Alabama VA with lung cancer who will receive therapy other 
than solely surgical resection. Virtually all patients undergoing evaluation for lung cancer at the 
both VAs are presented at the Tumor Board, or are evaluated in the chest (thoracic surgery and 
pulmonary), oncology and radiation oncology clinics. As members who regularly attend the 
tumor board, we are well acquainted with other Tumor Board attendees, including physicians, 
social workers, and other support staff. Each week, we will review patients who are to be 
presented at Tumor Board, or seen in the Chest (includes pulmonary and thoracic surgery) and 
Oncology Clinics for patients with new diagnoses of lung cancer.  
 
We will mail potential candidates invitation letters and include pre-paid postcards providing an 
opportunity for patients to opt out of the study or to be contacted if they are interested in 
learning more about the study. We will contact patients initially by telephone to introduce the 
study. Among interested patients, we will take two approaches to obtain informed consent and 
conduct the initial study visit based on patient preference. First, if the patient has an upcoming 
clinical appointment, we will coordinate the initial study visit with that clinic visit. Second, 

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because of the travel and clinical burden, we will also offer to perform the informed consent 
process and initial interviews by telephone. For several of our pilot studies we have conducted 
informed consent over the telephone and have not experienced any unforeseen challenges. 
Given the frequency at which patients are seen in clinics, we anticipate that the majority of these 
initial interviews will be performed in person. If a patient elects to participate in this study, we will 
document this in the medical record to inform all medical providers of their patients’ 
involvement.  
Patients will receive $50 following randomization into the study, $25 after completing 8 weeks in 
the study and $25 after completion of the final assessment for a possible total of $100.  
Measures 
Outcome measures will be collected on all enrolled participants by a research coordinator at 
baseline and the final visit. Outcome measures will be collected through surveys over the 
telephone. Prior to data collection, we will mail the surveys to the patient so they can visually 
follow while the research coordinator asks the questions and records their response. The 
estimated time for completion of the six surveys is approximately 30-45 minutes based on our 
pilot study. Subjects did not commonly report being overly burdened by the surveys.   
 
C. Method of randomization  
The unit of randomization will be the patient, performed at a ratio of 1:1 within strata using the 
permuted-block method with block sizes of 4 [3]. Given three stratifying variables of cancer 
stage (early and late), site (Seattle, Birmingham, Portland) and COPD (yes or no), there will be 
eight strata. Patients from each strata will be assigned to the intervention (I) or the control (C) in 
randomly generated sequences ICIC, IICC, CIIC, and so forth as they enter the trial.   
 
Randomization will be conducted by a statistician on our study team.  Providers will not be 
specifically informed of patients’ treatment allocation. However, providers cannot be masked 
in this intervention trial and will have access to the research notes entered into CPRS by the 
study nurse. The research coordinator collecting baseline and final visit outcome measures 
will be blinded to the subject’s treatment allocation. 
 
D. Interim analysis of the data 
Stopping rules 
 
There are no formal stopping rules for safety, efficacy, and futility for the study. This 
determination was made based on previous studies incorporating palliative care interventions 
into routine care finding improvements in quality of life and depression for patients with 
advanced cancers. ER visits, hospitalizations, and death are expected for patients with 
advanced cancers. These events are due to the underlying disease or side effects from cancer 
treatments, not from a palliative care intervention. This study does not involve investigational 
medications or devices. Patients will continue to receive standard of clinical care for their lung 
cancer during the study.  
During our pilot study, no complaints were received from study participants regarding the study 
procedures and there were no reported unanticipated serious adverse events due to study 
participation. Therefore, the study’s sample size should not be impacted.    
The data safety monitoring board will assess and respond to complaints and monitor all deaths, 

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hospitalizations, and ER visits.  In the unlikely event that any unanticipated adverse events are 
identified, they will be reported appropriately to the facility’s IRB. As stated in the consent forms, 
a provider may also withdraw specific patients without their consent for medical or other 
reasons.  
 
 
If at any time during the course of the study, the DSMB judges that risk to subjects may 
significantly outweigh the potential benefit, the DSMB shall have the discretion and 
responsibility to request all necessary information for detailed analyses, and if warranted, 
recommend that the study be terminated. Reason to stop the trial may include a significant 
number of adverse events that can reasonably be attributed to participation in the study, inability 
to recruit and measure the required number of participants to conduct the primary outcome 
analyses, serious deviation from study protocols, or other circumstances that would render the 
study unlikely to produce scientifically valid findings. The DSMB will carefully weigh the risk of 
completing the trial as planned against the risk of prematurely stopping the trial for safety or 
futility. 
 
E. Missing data 
 
We will make every effort to obtain complete data on each study participant at all data 
collection points. Collecting survey data via telephone with the study coordinator documenting 
responses will facilitate complete data. However, some missing data is inevitable and creates 
a risk for selection bias that can skew results.  Prior to evaluating our primary and secondary 
aims, we will perform multiple imputation (MI) which relies on the assumption that the outcome 
measure is missing at random (MAR) [5].  Datasets resulting from the multiple imputation 
procedure will be analyzed separately and the results from each data set will be summarized 
into one summary set of findings the ease of which is facilitated by statistical software. 
 
F. Definition of covariates included in adjustment models 
Prior to the analysis of the specific study aims, descriptive statistics, means and standard 
deviations for the quantitative variables, and frequencies and percentages for the categorical 
variables, will be calculated. All surveys will be scored according to the instructions. 
Differences between the intervention and control groups in baseline characteristics and 
clinical outcomes will be assessed using chi-squared tests for categorical variables and t-tests 
for continuous variables. The primary hypotheses we will test the effect of the intervention on 
improving quality of life scores (includes symptoms).  
Analysis of Aim 1 
H1: Among patients newly diagnosed with lung cancer, provision of a telephone-based 
palliative care intervention will be associated with a change in FACT-L TOI. 
 
The outcome measure for this hypothesis is quality of life as measured by the FACT-L TOI.  
FACT-L TOI includes functional and physical well-being and lung cancer specific symptoms.  
We will assess the difference in FACT-L TOI between the intervention and control subjects. 
Patient will be the unit of analysis and we will use a multiple linear regression model to 
estimate the effect of the treatment group on patient outcome, adjusting baseline FACT-L TOI 
as well as for randomization grouping variables (site, cancer stage and diagnosis of COPD). 
This approach is referred to as analysis of covariance (ANCOVA).  A multiple linear regression 
model will be constructed using FACT-L TOI as the outcome variable and include treatment 

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group as a covariate. The intervention will be considered a success if the indicator variable for 
the intervention group is significantly associated with an increase in the FACT-L TOI score. The 
linear model for this analysis takes the following form: 
𝑌1 = 𝑎 + 𝑏(treatment group)+ 𝑐(𝑌0) + 𝒅(Xi-j) + 𝜀 
Where 𝑌1 = FACT-L TOI at the end of the study period, treatment group = intervention or 
control group, 𝑌0 = baseline FACT-L TOI, and Xi-j randomization grouping variables (cancer 
stage, site, and COPD).   
 
We will conduct sensitivity analyses to evaluate if a difference exists between inference drawn 
using the multiple imputed datasets and complete case analyses.  Additionally, we will conduct 
sensitivity analysis by including patient level covariates (race and FEV 1) in the model both 
together and individually to complement and elucidate primary results. 
 
Secondary Aims 
 
For secondary aim 1, we will evaluate if the intervention is associated with higher satisfaction of 
care as measured by FAMCARE-P.  The evaluation of this aim will take the same form as that 
described for FACT-L TOI above including multiple imputation and sensitivity analyses. 
 
For secondary aim 2, we will assess if the intervention makes a difference in patient activation 
to discuss their treatment preferences with their provider from baseline to the final visit. Item 
responses on the Health Care Communication Questionnaire are ordinal. We will use Wilcoxon 
rank sum test [6] to analyze the change in the score from baseline to the final visit. 
 
For secondary aim 3, we will assess if the intervention will make a difference in improving the 
level of concordance between the clinicians’ knowledge of the patients’ life-sustaining 
treatment. Item responses for these questions are ordinal. We will use Wilcoxon rank sum test 
to analyze the difference between the subjects’ and providers’ responses. 
 
For secondary aim 4, we will determine if the provision of palliative care integrated at the time 
of lung cancer diagnosis improves appropriate resource utilization (pharmacy, social work, 
dietician, spiritual care, psychology, and PT/OT) as compared to the usual care group. We will 
collect data on health care utilization from CDW at the end of the study period (3 years). 
Measures include: 1) number of hospital admissions (for any reason); 2) number of intensive 
care admissions; 3) use of mechanical ventilation or no use of mechanical ventilation; 4) the 
number of Emergency Department visits (for any reason); 5) number of cancer treatments 
(chemotherapy); 6) number of radiation treatments– definitive or curative; 7) fee service for 
hospice care; and 8) survival status. Referrals to system interdisciplinary resources (pharmacy, 
social work, dietician, spiritual care, psychology, and PT/OT) will be monitored on a monthly 
basis for all enrolled subjects. 
 
G. Prospective tracking of serious adverse events 
Data and Safety Monitoring Board 
An external and independent data safety monitoring board (DSMB) will be established to 
examine interim study results on a periodic, scheduled basis and to recommend early 
termination due to the burden of participation if warranted. The issues that are raised in these 
interviews bring up sensitive subjects among a terminally ill group of patients and it is 

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reasonable to expect that the surveys may cause some patients distress. If patients have any 
questions or do not feel comfortable responding to specific survey questions, they have the right 
to refuse and will be informed of their right to opt out of any questions.   
Specifically, we propose that the data safety monitoring board to assess and respond to 
complaints and monitor all deaths and hospitalizations.  
If depression or suicidal ideation or intention is detected during the phone conversations, study 
staff will adhere to the VA suicide protocol.  
During the administration of the study questionnaires and during the intervention telephone 
calls, study staff may detect symptoms of depression.  If this situation occurs, we will inform the 
Primary Care Physician and refer the patient to Mental Health services for further evaluation.  
In the unlikely but possible detection of suicidal ideation, the following protocol will be followed: 
 
The interviewer will ask, “You mentioned that you have had thoughts that you would be better 
off dead or hurting yourself in some way.  Do you have a plan for how you would hurt yourself?”  
If the subject says: “I would not actually hurt myself”, the interviewer may continue with the 
interview.  If the subject endorses a plan, the interviewer would proceed as follows: “Our 
highest priority is keeping Veterans safe.  I would like to have one of our study doctors call you 
to make sure you are safe.” 
 
If the Veteran indicates he/she is safe, but does not want to be evaluated by a study doctor or 
mental health provider, let him/her know you will need to contact the mental health provider to 
ensure his/her safety.  In the case of possible suicidal intention or ideation, the Veteran will be 
provided with the VA Suicide Hotline number. 
 
If the Veteran indicates he/she will wait for an evaluation from the study doctor or mental health 
provider, thank him/her and let him/her know that a doctor will be seeing him/her soon.  Then 
call the mental health provider/study doctor to see the Veteran and assess his/her suicidality. 
 
 
DSMB Role 
The DSMB will provide the investigators and the IRBs with objective, scientific monitoring of the 
conduct of the study from the standpoint of ensuring the protection of human subjects and the 
integrity of the trial. It will do so by regularly monitoring adverse events (AEs) and serious 
adverse events (SAEs) and the quality of data, as well as reviewing and assessing the 
performance of the study’s operations. The DSMB will convene with the investigators at least 
semi-annually to review study progress and provide objective recommendations, as appropriate, 
with respect to: 
•       Determination of any actions to be taken in response to AEs and SAEs reported during 
the study; 
•       Reports related to study operations and the quality of the data; 
•       Consideration of early termination of the study because of treatment safety concerns 
or inadequate performance; 
•       Modifications in the study protocol concerning recruitment, participant retention, data 
quality, outcome assessment, statistical analysis, or general trial operations. 
At the end of each meeting, DSMB members will make a recommendation regarding the 
continuation of the trial and the date and format of the next meeting. The DSMB's findings and 
recommendations will be documented in the meeting minutes and transmitted to the 

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Investigators for their information and action, and will be incorporated into the annual Status 
Reports to the IRB. 
 
 
 
Safety monitoring 
Project staff will be trained to identify and report all potential AEs. To ensure unbiased 
determination across treatment arms, we will systematically identify AEs by query of the EHR 
and/or patients at each scheduled data collection time-point. AEs discovered will be investigated 
and reported to the IRB and DSMB according to required timelines. The DSMB may request 
additional information if it deems additional deliberation is warranted. The project director and/or 
analyst will prepare a statistical summary of the numbers and types of all AEs (serious or not), 
by unidentified treatment arms, for the investigators and the DSMB on a quarterly basis. At the 
discretion of the DSMB, the Chair may request unblinded results in order to determine the 
nature and extent of effect of the experimental intervention. Should the DSMB make this 
request, it will be fulfilled following a procedure that will maintain blinding of the investigators 
and the staff involved in follow-up data collection and analysis. If, at any time, the investigators 
believe they are seeing an unexpected increase in AEs that is a cause of concern, this will be 
specifically brought to the attention of the DSMB and their advice will be sought. This 
systematic, non-biased monitoring process will ensure that any group disparities will be 
effectively addressed. 
 
 
References 
 
1. 
Cella, D., et al., What is a clinically meaningful change on the Functional Assessment of 
Cancer Therapy–Lung (FACT-L) Questionnaire?: Results from Eastern Cooperative 
Oncology Group (ECOG) Study 5592. Journal of clinical epidemiology, 2002. 55(3): p. 
285-295. 
2. 
Temel, J.S., et al., Early palliative care for patients with metastatic non–small-cell lung 
cancer. New England Journal of Medicine, 2010. 363(8): p. 733-742. 
3. 
Friedman, L.M., et al., Fundamentals of clinical trials. Vol. 4. 2010: Springer. 
4. 
Borm, G.F., J. Fransen, and W.A. Lemmens, A simple sample size formula for analysis 
of covariance in randomized clinical trials. Journal of clinical epidemiology, 2007. 60(12): 
p. 1234-1238. 
5. 
Schafer, J.L., Multiple imputation: a primer. Statistical methods in medical research, 
1999. 8(1): p. 3-15. 
6. 
Hollander, M., D.A. Wolfe, and E. Chicken, Nonparametric statistical methods. 2013: 
John Wiley & Sons.