Effects on Liver Cirrhotic Patient's Health Related Quality of Life by a Nurse-led Clinic: A Multicenter Randomized Controlled Trial
Phase: NA
Conditions: Liver Cirrhosis
Sponsor: Uppsala University

 
Nurse-led clinic for 
patients with liver 
cirrhosis – effects on 
health-related quality 
of life 
NCT02957253 
Date: 08/08/2018 

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Hjorth M, et al. BMJ Open 2018;8:e023064. doi:10.1136/bmjopen-2018-023064
Open access
Nurse-led clinic for patients with liver 
cirrhosis—effects on health-related 
quality of life: study protocol of a 
pragmatic multicentre randomised 
controlled trial
Maria Hjorth,1,2 Daniel Sjöberg,1 Anncarin Svanberg,2,3,4 Elenor Kaminsky,3 
Sophie Langenskiöld,3 Fredrik Rorsman2
To cite: Hjorth M, Sjöberg D, 
Svanberg A, et al.  Nurse-
led clinic for patients with 
liver cirrhosis—effects on 
health-related quality of life: 
study protocol of a pragmatic 
multicentre randomised 
controlled trial. BMJ Open 
2018;8:e023064. doi:10.1136/
bmjopen-2018-023064
►
►Prepublication history for 
this paper is available online. 
To view these files, please visit 
the journal online (http://​dx.​doi.​
org/​10.​1136/​bmjopen-​2018-​
023064).
Received 19 March 2018
Revised 21 June 2018
Accepted 8 August 2018
1Center of Clinical Reaerch in 
Dalarna, Falun, Sweden
2Department of Medical 
Sciences, Uppsala Universitet 
Medicinska fakulteten, Uppsala, 
Sweden
3Department of Public Health 
and Caring Sciences, Uppsala 
University, Falun, Sweden
4Dalarna University, Falun, 
Sweden
Correspondence to
Mrs Maria Hjorth;  
​maria.​hjorth@​medsci.​uu.​se
Protocol
© Author(s) (or their 
employer(s)) 2018. Re-use 
permitted under CC BY-NC. No 
commercial re-use. See rights 
and permissions. Published by 
BMJ.
Abstract
Introduction  Liver cirrhosis affects health-related 
quality of life (HRQoL) even in its early stages. Morbidity 
is especially high when the disease decompensates and 
self-care actions become essential. Nurse involvement 
in secondary prevention in other chronic diseases has 
contributed to better symptom control, less need of 
inpatient care and improved HRQoL. In order to evaluate 
the impact of nurse involvement in the follow-up of 
patients with liver cirrhosis, we decided to compare 
structured nurse-led clinics, inspired by Dorothea Orem’s 
nursing theory and motivational strategies, with a group 
of patients receiving standard care. The primary outcome 
is HRQoL and the secondary outcomes are quality of care, 
visits to outpatient clinics or hospitals, disease progress 
and health literacy.
Methods and analysis  This is a pragmatic, multicentre 
randomised controlled study conducted at six Swedish 
hepatology departments. Eligible patients are adults with 
diagnosed cirrhosis of the liver (n=500). Participants 
are randomised into either an intervention with nurse-
led follow-up group or into a standard of care group. 
Recruitment started in November 2016 and is expected 
to proceed until 2020. Primary outcomes are physical and 
mental HRQoL measured by RAND-36 at enrolment, after 
1 and 2 years.
Ethics and dissemination  The study is ethically approved 
by the Regional Ethical Review Board in Uppsala. The 
results shall be disseminated in international conferences 
and peer-reviewed articles. 
Trial registration number  NCT02957253; Pre-results.
Introduction 
The incidence of liver cirrhosis in Sweden is 
approximately 14 per 100 000 citizens each 
year.1 It is a disease with high mortality as 
well as high morbidity, affecting patient’s 
health-related quality of life (HRQoL). 
Fatigue and depression are already frequent 
during the early, compensated, phase of liver 
cirrhosis and are believed to impair HRQoL 
by affecting the patient’s social life.2 HRQoL 
is further impaired in the decompensated 
patients, when symptoms of ascites, hepatic 
encephalopathy (HE) or variceal haemor-
rhage occur.3 4 
In the compensated stages, lifestyle changes 
are important to prevent or delay disease 
progression. While in the decompensated 
phase, customised lifestyle changes and self-
care become essential in the management of 
the disease.5 Unstructured follow-up in outpa-
tient settings causes frequent readmissions 
due to the reappearance of complications 
of cirrhosis. The reason may be drug-related 
side effects, for example, diuretics, non-ad-
herence to self-care or medical treatment. 
One-third of these episodes are said to be 
preventable with closer follow-up in an outpa-
tient setting.6 7
Motivating patients for self-care activities 
is essential in nursing care. For this, Orem’s 
theory of nursing,8 consisting of the three 
theories: self-care, self-care deficit and the 
nursing system may be applied. This theory 
Strengths and limitations of this study
►
►This pragmatic multicentre randomised controlled 
study design enables evaluation of a nurse-led clin-
ic intervention in patients with liver cirrhosis in the 
real-life context.
►
►All nurses involved in the study are proficient in the 
field of liver diseases, having a holistic understand-
ing of the situation of liver cirrhosis.
►
►The generic health-related quality of life instrument 
RAND-36 is used as a Swedish version of a liv-
er-specific instrument is currently unavailable.
►
►There is a risk of unwittingly transferring the inter-
vention to the control group. This is counteracted by 
the multicentre design and will shorten the time for 
recruitment of participants.
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guides nurses to identify and support patients to enter self-
care for better symptom control and improved health.8–10 
In liver cirrhosis, management of patients with liver 
cirrhosis is traditionally taken care of by physicians, while 
nurse-led clinics are still rare. However, previous studies 
on liver cirrhosis, nurse-led clinics have suggested that 
nurse-led clinics will contribute to better patient concor-
dance with physician recommendations11–13 and medical 
treatment,11 12 with positive effects on patients HRQoL.12 
Furthermore, there are indications that nurse-led clinics 
increase the quality of care by increasing the number 
of patients treated according to medical healthcare 
guidelines.12 Finally, the patients have reported a high 
degree of satisfaction by nursing care in such outpatient 
settings.12 14 Despite these reports, the significance of 
adjunctive nurse-led clinic to standard care by physician 
in liver cirrhosis is unclear. Conversely, in chronic heart 
failure, nurse-led care is established and proved equally 
effective as traditional care by the physician within 
outpatient settings.15 The holistic and person-centred 
approaches by the nurse, including motivational strat-
egies, have been shown to be crucial in the secondary 
prevention of chronic heart disease, reducing the need 
for inpatient care and to increase HRQoL.16 17 Hence, 
the experience from nurse-led clinics in chronic heart 
disease is likely to provide guidance regarding content, 
methods and necessary skills in the set-up of nurse-led 
clinics within the field of liver cirrhosis.
The aim with the present study is to compare HRQoL 
in patients with liver cirrhosis receiving either adjunctive 
nursing care based on Orem’s nursing theory or standard 
care only in outpatient settings.
Methods and analysis
The protocol follows the statement of Standard Protocol 
Items: Recommendations for Interventional Trials 2013,18 
for study protocol and Template for Intervention Dscrip-
tion and Replication (TIDieR).19 .
Study design
The study has a pragmatic, multicentre randomised 
controlled comparative design.
Study arms
Patients in the intervention group obtain structured 
visits to nurse-led clinics depending on the severity of 
the disease. The intervention is adjunctive, that is, the 
intervention is added to standard care. Patients in the 
control group get standard inpatient and outpatient care 
according to clinical routines.
Study sites
The study settings consist of six outpatient clinics at hepa-
tology departments in Sweden, two county hospitals and 
four university hospitals. None of the clinics had struc-
tured nursing care for patients with liver cirrhosis at the 
beginning of the study. The six outpatient clinics serve 
a population of approximately 2 000 000 individuals, 
comprising about 20% of Sweden’s population.
Eligibility criteria
Diagnosis of liver cirrhosis is based on clinical investi-
gation, laboratory findings, histology, MRI, computer 
tomography, ultrasound or elastography. Factors likely to 
strongly affect the primary variable due to other reasons 
than liver cirrhosis, that is, severe comorbidities and those 
unable to adhere to the study protocol, that is, persistent, 
overt HE, are excluded. Inclusion and exclusion criteria 
are presented in table 1.
Screening and recruitment of participants
Invitation letters are sent by intervention nurses (INs), 
offering oral information. Patients are invited to a 
screening visit to IN for baseline measurements. Those 
who meet inclusion criteria are registered. Patients, who 
agree to participate, hereafter denoted as participants, 
are randomised after giving informed consent. Newly 
diagnosed patients are recruited consecutively (figure 1). 
INs are responsible facilitators and consecutively follow 
participants.
Randomisation
Computerised randomisation (Randomize.Net, Inter-
rand, Ottawa, Canada) is performed at the screening visit 
with randomly mixed block sizes of 4, 6 and 8, stratified 
by study site and disease severity in terms of compen-
sated or decompensated state (figure  1). Blinding of 
the randomisation sequence is applicable to all involved 
personnel; allocation will be 1:1. Baseline measurements 
are completed before randomisation. Further blinding is 
not possible in this study.
Table 1  Inclusion and exclusion criteria 
Inclusion criteria 
Exclusion criteria 
Diagnosed liver 
cirrhosis within the past 
24 months
Insufficient knowledge of the 
Swedish language
Follow-up at the 
hepatology department
Persistent hepatic encephalopathy 
grades 2–4
Age 18–85 years
Comorbidity 
Chronic obstructive pulmonary 
disease grades 3–4
Coronary heart disease New York 
Heart Association Functional 
Classification (NYHA) classes 3–4
Dementia
Actual advanced cancer
Stroke with sequelae
Severe psychiatric disease
Renal failure requiring dialysis
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Description of the intervention
Participants in the intervention group offer scheduled 
individual visits to INs at the nurse-led clinic, in addi-
tion to visits to a physician according to clinical prac-
tice. Intervals between visits to the nurse-led clinic are 
varying from once yearly in compensated stable disease, 
up to two visit per month in decompensated disease 
(figure 2). The tailored frequency and content of visits 
are individualised to promote person-centred care 
(table 2).
Participants in the control group will receive standard 
care by physicians within hepatology inpatient or outpa-
tient clinics as required and a yearly follow-up for data 
collection by IN within the study (figure 2).
Figure 1  Recruitment and randomisation of participants. CC, compensated control group; CI, compensated intervention 
group; DC, decompensated control group; DI, decompensated intervention group; LC, liver cirrhosis. 
Figure 2  Study measurements and intervention nurse visit interval. CRT, continuous reaction time; IN, intervention nurse; 
MELD, Model for End-Stage Liver Disease; NVS, Newest Vital Sign; PHES-test, psychometric HE score; QPP, quality of care 
from the patient’s perspective; RFH-NPT, Royal Free Hospital-Nutritional Prioritising Tool. 
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Each visit to INs contains assessment of disease severity 
to enable early action against disease progression and 
malnutrition (table 2). The intervention includes treat-
ment and nursing care inspired by Dorothea Orem’s 
nursing theory.10 Further, motivational interviewing 
(MI),20 communication strategies will be used. Both 
Orem’s theory and MI implies that individuals have an 
intrinsic motivation to make appropriate choices, to 
promote health and prevent disease or to perform actions 
to counteract disease.10 20 The task of the IN is to assess the 
participants’ self-care needs and their ability to perform 
essential self-care in order to discover self-care deficits. 
To evoke participants’ motivation, INs listen and reflect 
on preparatory and mobilising change talk. In addition, 
INs give information adherent to MI techniques to facil-
itate participants understanding of actual self-care and 
medical treatment (figure 3). When applicable, INs offer 
next of kin instructions to help the participant achieve 
self-care.
The areas of the intervention are: (1) monitoring risk 
factors for deterioration of the liver disease, (2) informa-
tion and motivation to perform self-care and adhere to 
medical treatment, (3) nutrition assessment and support, 
(4) motivation of lifestyle changes essential for preventing 
or delaying disease progress and (5) psychosocial care. 
A booklet written by MH is handed to all INs describing 
these five areas converted into terms of Orem’s nursing 
theory.
One objective of INs’ use of MI is to promote engage-
ment and increased collaboration between IN and partic-
ipant via the MI spirit concepts: partnership, evocation, 
compassion and acceptance. Another objective is that INs 
evoke participants’ own motivation and explore patients’ 
own thoughts about a target behaviour when there is 
need for behavioural change. When participants express 
mobilising ‘change talk’,20 they are ready for the plan-
ning phase (figure  3). The intervention is individually 
tailored and INs’ activities depend on actual needs. An 
Table 2  Description of the intervention
Disease severity
Frequency of visits Content of visits
Compensated disease
Once yearly
Child Pugh score
Model for End-Sage Liver Disease (MELD)-score
The Royal Free Hospital-Nutritional Prioritising Tool
Assessment of: ascites, encephalopathy
Motivation to lifestyle changes
Psychosocial issues
Decompensated disease 
within 12 months or
1–2 visits/month
Child Pugh score
MELD score
The Royal Free Hospital-Nutritional Prioritising Tool
Assessment of: ascites, encephalopathy, side effects of medical treatment
Motivation to self-care and/or lifestyle changes
Psychosocial issues
Previously decompensated 
disease
Every third month
Figure 3  The four processes of motivational interviewing techniques. IN, intervention nurse; MI, motivational interviewing.
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information booklet about liver cirrhosis is available to 
participants as a complement to oral information.
Standard care includes flexible visits or telephone 
follow-up by physicians, gastroscopies, ascites drainage, 
registered nurse telephone counselling by a nurse not 
participating in the study and inpatient care.
Intervention nurses
At each of the six clinics, 1–2 INs are involved in the 
intervention. All of these are registered nurses with a 
minimum of 2 years experience from hepatology inpa-
tient or outpatient care. Implementation of the interven-
tion and training of INs include a 6-hour seminar with a 
short description of MI and Orem theories followed by 
a 3-day training to perform MI. INs are also educated in 
pathophysiology of liver cirrhosis, nursing care according 
to presenting symptoms, study bias and study instruments. 
Scheduled tutorial group sessions to follow the interven-
tion and MI practice will be due every 6 months for all INs 
during the study period.
Study piloting
A pilot of the intervention and patient questionnaire was 
performed in Falun from 2014 to 2015 with 26 partici-
pating patients. The aim was to define the actual size of 
the population available for the study and to assess the 
time and budget for the INs’ assignment.
Baseline sociodemographic data collection
Sociodemographic data collected at enrolment are 
presented in figure 2.
Primary outcome
Physical and mental HRQoL are the two main outcomes 
in the present study measured by RAND-36.21 RAND-36 
consists of 36 category scale questions: the answer to each 
question ranges from 0 to 100, a higher value predicts 
better health. From the RAND-36 questionnaire, eight 
subscales are derived: (1) physical functioning, (2) role 
limitations caused by physical health problems, (3) pain, 
(4) energy/fatigue, (5) social functioning, (6) role limita-
tions caused by emotional problems, (7) emotional well-
being and (8) general health perception. Out of the eight 
subscales, two summary components are derived: Phys-
ical Component Summary (PCS) and Mental Compo-
nent Summary (MCS).21 22 HRQoL measurements by 
the RAND-36 has high validity and reliability to identify 
differences in HRQoL over time within and compared 
with patient populations with different chronic diseases.22
Secondary outcomes
►
►Patient’s perspective of quality of care due to a change 
in follow-up strategy: The questionnaire quality of care 
from the patient’s perspective (QPP)23 includes four 
dimensions: (1) medical-technical competence, (2) 
physical-technical conditions, (3) identity-orientated 
approach and (4) sociocultural atmosphere. Within 
each dimension, the participants first value their expe-
rience of the specific care aspects they have received 
((1) totally agree, (2) agree in large part, (3) partly 
agree or (4) do not agree) and second, the impor-
tance of these aspects ((1) of greatest importance, (2) 
of great importance, (3) of some importance or (4) of 
little or no importance). The difference between the 
experienced care and the importance of each ques-
tion is categorised as: excess of, balanced or lack of 
quality of care. A short form of QOP has been found 
valid and reliable.24 In the present study, partici-
pants receive a modified QPP 38-item questionnaire 
adjusted for patients with liver cirrhosis in outpatient 
care. The modification has been approved by the 
instrument developer. The questionnaire includes a 
variation of yes/no questions, category scales from 1 
to 4 and open-ended questions.
►
►Visits at outpatient clinics and admissions to hospital: 
Visits at outpatient clinics, number of admissions to 
hospitals and days of inpatient care at medical wards 
or intensive care units will be recorded as measures of 
healthcare consumption. In case of significant clinical 
outcomes, these data will later be used to perform a 
separate health economic analysis.
►
►Disease progress
1.	 Child Pugh score25 includes five variables: serum 
albumin, serum bilirubin, prothrombin time, 
ascites and encephalopathy. Each variable grading 
from 1 to 3 and the total range is 5–15. A higher 
value means a more advanced disease. Three risk 
classes are derived: A=score 5–6, B=score 7–9 and 
C=score 10–15.26
2.	 The Model for End-Stage Liver Disease (MELD)27 
predicts the 3-month mortality of patients with 
chronic end-stage liver disease. Based on labora-
tory findings, MELD is a valid and reliable instru-
ment. The formula for MELD is constant for 
disease aetiology, the calculation score is: 9.57 x log 
e (creatinine mg/dL)+3.78 x log e (bilirubin mg/
dL)+11.20 x log e (INR) +6.4. The score is contin-
uous, ranging from 6 to 40, a high score predicts an 
increased risk of mortality within 3 months.28
3.	 The Royal Free Hospital-Nutritional Prioritising 
Tool (RFH-NPT)29 assesses the risk of malnutrition 
in liver cirrhosis as a predictor of disease deteriora-
tion and transplant-free survival. RFH-NPT corre-
lates with deterioration of the liver disease and 
divides participants into low (0 points), medium 
(1 point) or high (2–7 points) risk groups for 
malnutrition. Parameters taken into account are 
nutritional history (unplanned weight loss, dietary 
intake body mass index) and current complications 
of liver cirrhosis (acute alcoholic hepatitis, ascites, 
general fluid overload). The instrument used in the 
study is a translation into Swedish from the English 
version. Validation of the translation is made in a 
research seminar within the research group.
4.	 Appearance of decompensation episodes (eg, 
ascites, overt HE and variceal bleed) is assessed at 
screening, after 12 months and after 24 months 
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through medical records. HE is common in liver 
cirrhosis with a cumulative risk of 30%–40%.30 
According to the West-Haven criteria,31 HE ranges 
from 0 to 4. Grades 0–1 mean subclinical or minimal 
symptoms (covert HE) and grades 2–4 mean 
severe neuropsychiatric symptoms (overt HE).30 
Even milder grades of HE affect HRQoL.30 31 In 
the majority of cases, HE is treatable. Two psycho-
metric tests in combination are recommended to 
detect covert HE.30 In this study, the psychometric 
HE score (PHES) and continuous reaction time 
(CRT) are used:
a.	 PHES consists of five-step paper and pencil 
tests,32 and includes a line drawing test, a serial 
dotting test and a digit symbol test to examine 
motor speed and accuracy, visual perception, 
visuospatial orientation, visual construction, 
concentration and attention. The test ends up 
with a score ranging from +6 to −18; −4 or less is 
the cut-off for a pathological result.
b.	CRT33 is a 10 min test with auditory stimuli in 
headphones in intervals of every 2–6 s. It tests 
the reaction time and endurance by pushing a 
trigger button after a signal. Using the software 
EKHO reaction-time analysis tool, an index <1, 
9 with 150 repetitions separate HE from other 
brain dysfunctions with a specificity of 0.92 and 
sensitivity of 0.93.
►
►Health literacy (HL): involves a person’s ability 
to receive, process and understand basic medical 
information in making decisions and taking actions 
to promote health.34 The grade of HL may influ-
ence the intervention as it impacts the participants’ 
ability to understand and translate information into 
practice. The instrument Newest Vital Sign,35 which 
consists of six standardised questions about nutrition 
label information, is used. The questions is asked by 
INs, the correct answer scores 1 point, a score of 4 
or above indicates no limits of HL and scores below 
4 indicate limited HL. The instrument is translated 
from English to Swedish within another study (Health 
literacy among Swedish lung transplant recipients 1–5 
years after transplantation, A Lennerling, A Kisch and 
A Forsberg, personal communication, 2018). Valida-
tion of the translation has been made in a research 
seminar within our research group and the risk of 
translation errors was judged to be low.
Participant flow through the study
Study time for each participant is 24 months (figure 2), 
after which participants in the intervention group 
may continue their follow-up at the nurse-led clinic if 
they want to. Participants in the control group may be 
offered follow-up at the nurse-led clinic after the end of 
study. Data collection and frequency of visits to INs are 
presented in figure 2. Reasons for withdrawal from the 
study are liver transplantation, move out of follow-up area 
or mortality. In case of two consecutive cancelled visits 
to an IN, a reminder will be sent, asking participants to 
contact INs for further participation in the study.
Data analysis and sample size calculation
Analysis includes the two primary variables in RAND-36: 
the PCS and the MCS. These components will be calcu-
lated based on weights from the oblique method,36 to 
avoid potential problems in interpretation due to nega-
tive weights. A repeated measurements model will be used 
for analysis of baseline, 12 and 24 months values of the 
component summary score. Treatment group, time (base-
line, 12, 24 months) with interaction, and decompen-
sated/compensated state will be fixed effects, while site 
will be a random effect in the model. The main contrast 
of interest to be estimated with this model is change from 
baseline to month 24 for both treatment groups. For the 
treatment group comparison, Bonferroni-Holm method 
using a corrected alpha=2.5% will be used to compensate 
for multiple testing of both PCS and MCS.
All tests will be two sided. For analyses of secondary vari-
ables, p values<0.05 are considered significant. Multiple 
imputation will be used for missing values.
For the power calculation, a SD of 9 points was used 
based on back-calculated residual variances from CIs for 
MCS.37 A change of 3–5 points is estimated to be a mini-
mally clinically important difference and corresponds to 
an effect size of 0.09–0.28.22 It is argued that even smaller 
changes are important,38 and a change of 2.5 points is 
therefore considered to be potentially relevant for the 
power calculation. To ensure a power of 0.80 for the 
effect size of 2.5 points and a Bonferroni-corrected alpha 
level of 2.5%, the recommended sample size is 250 partic-
ipants per treatment group, that is, 500 in total.39 With a 
calculated 33% non-inclusion rate, enrolment time is esti-
mated from November 2016 to December 2020 or until 
500 participants are included.
Patient involvement
Five patients contributed with comments on the question-
naire that resulted in changes in tree of the 78 questions. 
No patients were involved in study design, research ques-
tion or recruitment. The results will be disseminated to 
the study participants in a short summary after the publi-
cation of the study.
Strengths and limitations
This randomised controlled trial in the field of nursing is 
a complex intervention with a pragmatic design and has a 
high risk of confounding factors. In a pragmatic design,40 
the research aim is to reflect the clinical practice. Partici-
pant heterogeneity and a minimum of exclusion criteria 
are therefore allowed to a larger extent. The researcher 
must be aware of factors that may bias study results. In this 
study, participants may have other chronic diseases that 
may affect HRQoL. Patients with severe comorbidity are 
not included in this trial as it would have required a larger 
sample than available. A prolonged study of 5 years raises 
the risk of unwitting transfer of the intervention on to 
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the control group when other personnel than INs start to 
develop skills included in the study protocol.17 To reduce 
this risk and preserve the ability to identify changes in 
HRQoL, study time is set to 4 years. Furthermore, six 
study sites are included in the study that aims to shorten 
the time for the study as well as reduce time for contam-
ination of the control group. Six study sites, however, 
imply a risk of performance differences regarding the 
intervention and control group. In a forthcoming study, 
the context and mechanisms that may affect the results 
will be assessed in a process evaluation as described by 
Moore et al.41 To reduce bias in inclusion, participants 
in the control group offer a nurse-led clinic when study 
participation ends.
Although RAND-36 has proved sensitivity to changes in 
liver cirrhosis, a disease-specific instrument may be more 
nuanced. However, available disease-specific HRQoL 
instruments for liver cirrhosis are unfortunately not 
translated into Swedish. The former comparable generic 
instrument SF-3622 has been shown to be sensible for 
differences in HRQoL in populations of liver cirrhosis,.4 42
The MI experience may affect INs’ ability to use MI 
skills in conversations with participants. However, all INs 
in the present study are proficient or experts in nursing in 
the field of liver cirrhosis, having a holistic understanding 
of the situation of the disease. During the study, the INs 
will attend tutorial sessions twice a year to develop their 
skills in MI.
The occurrence of overt HE limits the enrolment of 
participants. Overt HE may have an impact on the ability 
to answer questionnaires used in the study. At enrolment, 
patients with covert HE are accepted. Before measure-
ments at 12 and 24 months, HE tests will be repeated 
before the participants answer the questionnaires. Partic-
ipants with overt HE will not be asked to answer the ques-
tionnaires, including RAND-36 and QPP, due to the risk 
of unreliable answers.
To our knowledge, this is the largest randomised 
controlled study evaluating nurse-led intervention in liver 
cirrhosis. The pragmatic design enables us to evaluate the 
effect of the intervention in the real-life context under 
which the study is performed. The results will hope-
fully contribute with important knowledge about nurse 
involvement in the care of patients with liver cirrhosis that 
can be applied in the routine clinical setting.
Dissemination
The study result will be published in peer-reviewed jour-
nals and presented at international conferences. The 
result will be used for education and competence devel-
opment within the field. Study results are reported on the 
group level.
Acknowledgements  To Frank Miller for statistical support and to patient advisers 
for comments in development of the patient questionnaire. 
Contributors  MH has contributed to the design, implementation of the study and 
responsible for drafting the manuscript. DS has taken part in the design of the 
study and supervised MH in drafting the Manuscript, and has approved the final 
manuscript. AS has taken part in the design of the study and supervised MH in 
drafting the manuscript, and has approved the final manuscript. EK has taken part 
in the design of the study and supervised MH in drafting the Manuscript, and has 
approved the final manuscript. SL has taken part in the design of the study and 
supervised MH in drafting the manuscript, and has approved the final manuscript. 
FR has taken part in the design of the study and supervised MH in drafting the 
manuscript, and has approved the final manuscript.
Funding  This work was supported by Ester Åsberg Lindberg foundation and Centre 
for Clinical Research in Dalarna. The CRT equipment was funded by Norgine. 
Competing interests  None declared.
Patient consent  Obtained.
Ethics approval  The study has been approved by the Regional Ethical Review 
Board in Uppsala (Dnr: 2016/146) and is performed according to the Declaration of 
Helsinki and to the Swedish Ethical Review Act.
Provenance and peer review  Not commissioned; externally peer reviewed.
Open access This is an open access article distributed in accordance with the 
Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which 
permits others to distribute, remix, adapt, build upon this work non-commercially, 
and license their derivative works on different terms, provided the original work is 
properly cited, appropriate credit is given, any changes made indicated, and the use 
is non-commercial. See: http://​creativecommons.​org/​licenses/​by-​nc/​4.​0/.
References
	 1.	 Nilsson E, Anderson H, Sargenti K, et al. Incidence, clinical 
presentation and mortality of liver cirrhosis in Southern Sweden: 
a 10-year population-based study. Aliment Pharmacol Ther 
2016;43:1330–9.
	 2.	 Nardelli S, Pentassuglio I, Pasquale C, et al. Depression, anxiety 
and alexithymia symptoms are major determinants of health 
related quality of life (HRQoL) in cirrhotic patients. Metab Brain Dis 
2013;28:239–43.
	 3.	 Arguedas MR, DeLawrence TG, McGuire BM. Influence of hepatic 
encephalopathy on health-related quality of life in patients with 
cirrhosis. Dig Dis Sci 2003;48:1622–6.
	 4.	 Younossi ZM, Boparai N, Price LL, et al. Health-related quality of life 
in chronic liver disease: the impact of type and severity of disease. 
Am J Gastroenterol 2001;96:2199–205.
	 5.	 Tsochatzis EA, Bosch J, Burroughs AK. New therapeutic paradigm 
for patients with cirrhosis. Hepatology 2012;56:1983–92.
	 6.	 Agrawal K, Kumar P, Markert R, et al. Risk factors for 30-day 
readmissions of individuals with decompensated cirrhosis. South 
Med J 2015;108:682–7.
	 7.	 Volk ML, Tocco RS, Bazick J, et al. Hospital readmissions among 
patients with decompensated cirrhosis. Am J Gastroenterol 
2012;107:247–52.
	 8.	 Orem D. Nursing: concepts of practice. United States of America: 
McGraw-Hill Book Company, 1980:225.
	 9.	 Aish AE, Isenberg M. Effects of Orem-based nursing intervention on 
nutritional self-care of myocardial infarction patients. Int J Nurs Stud 
1996;33:259–70.
	10.	 Orem DE, Renpenning KM, Taylor SG. Self care theory in nursing: 
selected papers of Dorothea Orem. New York: Springer Pub, 
2000:400.
	11.	 Shutt JD, Robathan J, Vyas SK. Impact of a clinical nurse specialist 
on the treatment of chronic hepatitis C. Br J Nurs 2008;17:572–5.
	12.	 Wigg AJ, McCormick R, Wundke R, et al. Efficacy of a chronic 
disease management model for patients with chronic liver failure. 
Clin Gastroenterol Hepatol 2013;11:850–8.
	13.	 Biddle ML, Adler NR, Heath M, et al. Nurse-led clinic: effective and 
efficient delivery of assessment and review of patients with hepatitis 
B and C. Intern Med J 2014;44:581–5.
	14.	 Grogan A, Timmins F. Side effects of treatment in patients with 
hepatitis C - implications for nurse specialist practice. Aust J Adv 
Nurs 2009;27:8.
	15.	 Schadewaldt V, Schultz T. Nurse-led clinics as an effective service for 
cardiac patients: results from a systematic review. Int J Evid Based 
Healthc 2011;9:199–214.
	16.	 Campbell NC, Thain J, Deans HG, et al. Secondary prevention clinics 
for coronary heart disease: randomised trial of effect on health. BMJ 
1998;316:1434–7.
	17.	 Murchie P, Campbell NC, Ritchie LD, et al. Effects of secondary 
prevention clinics on health status in patients with coronary heart 
disease: 4 year follow-up of a randomized trial in primary care. Fam 
Pract 2004;21:567–74.
 on 8 January 2019 by guest. Protected by copyright.
http://bmjopen.bmj.com/
BMJ Open: first published as 10.1136/bmjopen-2018-023064 on 17 October 2018. Downloaded from 

8
Hjorth M, et al. BMJ Open 2018;8:e023064. doi:10.1136/bmjopen-2018-023064
Open access
	18.	 Chan AW, Tetzlaff JM, Altman DG, et al. SPIRIT 2013 statement: 
defining standard protocol items for clinical trials. Ann Intern Med 
2013;158:200–7.
	19.	 Hoffmann TC, Glasziou PP, Boutron I, et al. Better reporting of 
interventions: template for intervention description and replication 
(TIDieR) checklist and guide. BMJ 2014;348:g1687.
	20.	 Miller W, Rollnick S, Interviewing M. Helping People Change. 3rd 
Edition. United states of America: The Guilford Press, 2013:482.
	21.	 Hays RD, Sherbourne CD, Mazel RM. The RAND 36-Item Health 
Survey 1.0. Health Econ 1993;2:217–27.
	22.	 Hays RD, Morales LS. The RAND-36 measure of health-related 
quality of life. Ann Med 2001;33:350–7.
	23.	 Wilde B, Starrin B, Larsson G, et al. Quality of care from a 
patient perspective-a grounded theory studyScand. J Caring Sci 
1993;7:113–20.
	24.	 Wilde Larsson B, Larsson G. Development of a short form of the 
quality from the patient's perspective (qpp) questionnaire. J Clin Nurs 
2002;11:681–7.
	25.	 Pugh RN, Murray-Lyon IM, Dawson JL, et al. Transection of 
the oesophagus for bleeding oesophageal varices. Br J Surg 
1973;60:646–9.
	26.	 Durand F, Valla D. Assessment of prognosis of cirrhosis. Semin Liver 
Dis 2008;28:110–22.
	27.	 Kamath PS, Wiesner RH, Malinchoc M, et al. A model to predict 
survival in patients with end-stage liver disease. Hepatology 
2001;33:464–70.
	28.	 Wiesner R, Edwards E, Freeman R, et al. Model for end-stage liver 
disease (MELD) and allocation of donor livers. Gastroenterology 
2003;124:91–6.
	29.	 Borhofen SM, Gerner C, Lehmann J, et al. The royal free 
hospital-nutritional prioritizing tool is an independent predictor of 
deterioration of liver function and survival in cirrhosis. Dig Dis Sci 
2016;61:1735–43.
	30.	 American Association for the Study of Liver DiseasesEuropean 
Association for the Study of the Liver. Hepatic encephalopathy 
in chronic liver disease: 2014 practice guideline by the 
European Association for the Study of the Liver and the 
American Association for the study of liver diseases. J Hepatol 
2014;61:642–59.
	31.	 Bleibel W, Al-Osaimi AM. Hepatic encephalopathy. Saudi J 
Gastroenterol 2012;18:301–9.
	32.	 Weissenborn K, Ennen JC, Schomerus H, et al. Neuropsychological 
characterization of hepatic encephalopathy. J Hepatol 
2001;34:768–73.
	33.	 Elsass P, Christensen SE, Mortensen EL, et al. Discrimination 
between organic and hepatic encephalopathy by means of 
continuous reaction times. Liver 1985;5:29–34.
	34.	 Sheridan SL, Halpern DJ, Viera AJ, et al. Interventions for individuals 
with low health literacy: a systematic review. J Health Commun 
2011;16 Suppl 3:30–54.
	35.	 Weiss BD, Mays MZ, Martz W, et al. Quick assessment of literacy in 
primary care: the newest vital sign. Ann Fam Med 2005;3:514–22.
	36.	 Laucis NC, Hays RD, Bhattacharyya T. Scoring the SF-36 in 
Orthopaedics: a brief guide. J Bone Joint Surg Am 2015;97:1628–34.
	37.	 Team UR. UKATT Research Team. Effectiveness of treatment for 
alcohol problems: findings of the randomised UK alcohol treatment 
trial (UKATT). BMJ 2005;331:541.
	38.	 Samsa G, Edelman D, Rothman ML, et al. Determining 
clinically important differences in health status measures. 
Pharmacoeconomics 1999;15:141–55.
	39.	 Julious SA. Sample sizes for clinical trials. United States of America: 
Chapman & Hall/CRC, 2009:268.
	40.	 Hotopf M. The pragmatic randomised controlled trial. Advances in 
Psychiatric Treatment 2002;8:326–33.
	41.	 Moore GF, Audrey S, Barker M, et al. Process evaluation of 
complex interventions: medical research council guidance. BMJ 
2015;350:h1258–7.
	42.	 Les I, Doval E, Flavià M, et al. Quality of life in cirrhosis is related 
to potentially treatable factors. Eur J Gastroenterol Hepatol 
2010;22:221–7.
 on 8 January 2019 by guest. Protected by copyright.
http://bmjopen.bmj.com/
BMJ Open: first published as 10.1136/bmjopen-2018-023064 on 17 October 2018. Downloaded from 

Statistical Analysis Plan NCT02957253 
 
 
TABLE OF CONTENTS 
1 
Abbreviations .................................................................................................................................. 1 
2 
Introduction and study aim ............................................................................................................. 1 
3 
Study endpoints ............................................................................................................................... 1 
3.1 
Primary outcome ..................................................................................................................... 1 
3.2 
Secondary outcomes ............................................................................................................... 2 
3.2.1 
Patient’s perspective of quality of care (QPP) ................................................................. 2 
3.2.2 
Visits at outpatient clinics and admissions to hospital .................................................... 2 
3.2.3 
Child Pugh score .............................................................................................................. 2 
3.2.4 
Model of end stage liver disease (MELD) ........................................................................ 3 
3.2.5 
Royal free hospital-nutritional prioritising tool (RFH-NPT) ............................................. 3 
3.2.6 
Appearance of decompensation episodes ...................................................................... 3 
3.2.7 
Hepatic encephalopathy (HE) .......................................................................................... 3 
3.2.8 
Health literacy (HL) .......................................................................................................... 3 
4 
Sample size determination .............................................................................................................. 3 
4.1 
Assumption for variability ....................................................................................................... 3 
4.2 
Assumption for effect .............................................................................................................. 4 
4.3 
Sample size calculation ............................................................................................................ 4 
5 
Analysis Populations ........................................................................................................................ 4 
6 
General analysis methods ............................................................................................................... 5 
6.1 
Multiplicity aspects .................................................................................................................. 5 
6.2 
Visit windows ........................................................................................................................... 5 
6.3 
Handling of missing data ......................................................................................................... 5 
7 
Primary and secondary analyses ..................................................................................................... 5 
7.1 
Primary analysis ....................................................................................................................... 5 
7.2 
Secondary analyses ................................................................................................................. 6 
7.2.1 
Patient’s perspective of quality of care (QPP) ................................................................. 6 
7.2.2 
Visits at outpatient clinics and admissions to hospital .................................................... 6 
7.2.3 
Child Pugh score .............................................................................................................. 7 
7.2.4 
Model of end stage liver disease (MELD) ........................................................................ 7 
7.2.5 
Royal free hospital-nutritional prioritising tool (RFH-NPT) ............................................. 7 
7.2.6 
Appearance of decompensation episodes ...................................................................... 7 
7.2.7 
Hepatic encephalopathy (HE) .......................................................................................... 7 
7.2.8 
Health literacy (HL) .......................................................................................................... 7 
References ............................................................................................................................................... 7 

 
1 
 
 
1 ABBREVIATIONS 
CI 
 
Confidence interval 
CRT 
 
Continuous reaction time 
HE 
 
Hepatic encephalopathy 
HL 
 
Health literacy 
HRQoL  
Health-related quality of life 
ITT 
 
Intention-to-treat (population) 
MELD  
Model of end stage liver disease 
MCID  
Minimum clinically important difference 
MCS 
 
Mental component summary (of RAND-36) 
NVS 
 
Newest Vital Sign (questionnaire) 
PCS 
 
Physical component summary (of RAND-36) 
PHES 
 
Psychometric hepatic encephalopathy score 
QPP 
 
Quality of care from the patient’s perspective (questionnaire)  
RAND-36 
Health survey by the RAND (Research and Development) group 
RFH-NPT 
Royal free hospital-nutritional prioritising tool  
2 INTRODUCTION AND STUDY AIM 
The study protocol is described by Hjorth et al. (2018). The Clinical Trial registration number is: 
NCT02957253. 
The aim with the present study is to compare Health-related quality of life (HRQoL) in patients with 
liver cirrhosis receiving either adjunctive nursing care based on Orem’s nursing theory (intervention 
group) or standard care only (control group) in outpatient settings. 
The study has a pragmatic, multicentre randomised controlled comparative design. Computerised 
randomisation (allocation 1:1) is performed at the screening visit after completion of baseline 
measurements. Randomly mixed block sizes of 4, 6 and 8 are used, stratified by study site and 
disease severity in terms of compensated or decompensated state. It is not possible to blind 
interventions in this study. 
Study time for each participant is 24 months and main timepoints for data collection are: baseline, 
Month 12, Month 24.  
3 STUDY ENDPOINTS 
3.1 PRIMARY OUTCOME 
Physical and mental HRQoL are the two main outcomes in the present study measured by RAND-36 
(Hays et al., 1993). RAND-36 consists of 36 category scale questions: the answer to each question 
ranges from 0-100, a higher value predicts better health. From the RAND-36 questionnaire, eight 
subscales are derived: (I) physical functioning, (II) role limitations caused by physical health problems, 
(III) pain, (IV) energy/fatigue, (V) social functioning, (VI) role limitations caused by emotional 
problems, (VII) emotional wellbeing and (VIII) general health perception. Out of the eight subscales, 

 
2 
 
two summary components are derived: physical component summary (PCS) and mental component 
summary (MCS), see Hays et al. (1993), Hays and Morales (2001). These components will be 
calculated based on weights from the oblique method (Laucis et al., 2015) to avoid potential 
problems in interpretation due to negative weights. 
3.2 SECONDARY OUTCOMES 
3.2.1 
Patient’s perspective of quality of care (QPP) 
Patients received at baseline, at Month 12, and at Month 24 a 38-item version of the questionnaire 
Quality of care from the patient’s perspective (QPP). For Item 5 to 26, the participants both value 
their experience of the specific care aspects they have received and their importance. These answers 
were classified according to the QPP manual Wilde-Larsson et al. (2001) into “lacking quality”, 
“balance” and “excess quality”. The items are grouped into 4 dimensions: (I) Medical-technical 
competence, (II) physical-technical conditions, (III) identity-orientated approach and (IV) socio-
cultural atmosphere. The other items are items with multiple choice answers (usually, only one of 
the provided answers can be given, except for Item 1 where multiple responses can be given) and 
some open-ended questions.  
3.2.2 
Visits at outpatient clinics and admissions to hospital 
The following variables will describe the number of visits at outpatient clinics: 
 
Number of outpatient visits to physicians 
 
number of outpatient visits to nurse-led clinics  
 
number of visits to dietitian 
 
number of visits to physiotherapist 
 
number of visits to social counsellor 
 
number of telephone contacts to physicians 
 
number of telephone contacts to nurses  
 
number of gastroscopies 
 
number of paracentesis  
The following variables will describe admissions to hospitals: 
 
Number of admissions to hospitals, 
 
days of inpatient care at medical wards, 
 
days of inpatient care at intensive care units. 
If a health economic analysis is conducted (see Section 7.2.2), the following measures will be 
considered to calculate costs: TIPS, paracentesis, liver surgery, ablation, TACE, Sirtex and medical 
treatment with Hepa-Mertz and Glypressin.  
The above variables will be recorded for the interval between baseline and Month 12 and for the 
interval between Month 12 and Month 24. 
3.2.3 
Child Pugh score  
The Child Pugh score include five variables: serum albumin, serum bilirubin, prothrombin time, 
ascites and encephalopathy. Each variable grading from 1-3 and the total range is 5-15. A higher 
value means a more advanced disease. Three risk classes are derived: A= score 5-6, B= score 7-9 and 
C= score 10-15.   

 
3 
 
3.2.4 
Model of end stage liver disease (MELD) 
The model of end stage liver disease (MELD) predicts the three-month mortality of patients with 
chronic end-stage liver disease. The score used (defined in Hjorth et al., 2018) is continuous, ranging 
from 6 to 40 with higher values for a worse disease state.  
3.2.5 
Royal free hospital-nutritional prioritising tool (RFH-NPT) 
The Royal free hospital-nutritional prioritising tool (RFH-NPT) correlates with deterioration of the 
liver disease and divides participants into low (0 points), medium (1 point) or high (2 to 7 points) risk 
groups for malnutrition.  
3.2.6 
Appearance of decompensation episodes 
Appearance of decompensation episodes (e.g., ascites, overt HE and variceal bleed) is assessed at 
baseline, at Month 12, and at Month 24 through medical records. The event is recorded as yes or no. 
3.2.7 
Hepatic encephalopathy (HE) 
Two psychometric tests for HE are used in this study: the psychometric HE score (PHES) and 
continuous reaction time (CRT). 
The PHES test ends up with a score ranging from +6 to -18; -4 or less is the cut-off for a pathological 
result (Weissborn et al., 2001).   
The CRT results will be analysed using the software EKHO reaction-time analysis tool. An index is 
computed and the cut-off value of 1.9 separates a normal and pathological test result (Elsass et al., 
1985). 
Minimal or Grade 1 HE is diagnosed if and only if both tests show a pathological result (according to 
clinical guidelines). 
3.2.8 
Health literacy (HL) 
Health literacy (HL) is measured with the instrument Newest Vital Sign (NVS) which consists of six 
standardised questions about nutrition label information; a correct answer scores 1 point. A score of 
4 or above indicates adequate literacy, 2 or 3 indicate possible limited literacy, 0 or 1 indicate likely 
limited literacy (Shah et al., 2010). In the case that less than expected data is obtained, it might be 
considered to pool the two classes for scores 0-3.  
4 SAMPLE SIZE DETERMINATION 
4.1 ASSUMPTION FOR VARIABILITY 
Change from baseline in summary components were analysed in UKATT (2005). Based on the 
reported confidence intervals in their Table 3, the residual standard deviation for change from 
baseline was back-calculated to be 5.5 for PCS and 9 for MCS. Note that in this study, PCS values at 
baseline were not far from healthy population while MCS values were worse than healthy 
population; therefore, it could not be expected that PCS change much during treatment and 
variability for change from baseline might be lower than in situations where the potential for change 
is larger. Hence, a standard deviation of 9 is judged as reasonable even for PCS in a population which 
is worse than healthy population. We note that this is also roughly in line with the sd for change from 
baseline in Ward et al. (2014) (PCS-sd=9.0, MCS-sd=11.2), however there a Rheumatoid Arthritis 
population is studied and follow up is some months after baseline. 

 
4 
 
4.2 ASSUMPTION FOR EFFECT 
Samsa et al. (1999) mention a recommendation of a Minimum Clinically Important Difference (MCID) 
= 3-5 points for the 8 subscales. Since these are non-standardized, this corresponds roughly to 1.5-
2.5 points for standardized subscales. Ward et al. (2014) justify a MCID of 7.2 for the standardized 
PCS but this in patients with rheumatoid arthritis; Strand et al. (2012) have in the same population 
argued for a MCID of 2.5. In general, it is argued that even small changes are judged important (e.g. 
by Samsa et al., 1999) and a change of 2.5 points is therefore considered to be potentially relevant.  
We judge now which effect can be expected from the proposed treatment. Younossi et al. (2001) 
identified that the average PCS in patients with chronic liver diseases was 41, 39, and 31 for viral, 
cholestatic, and hepatocellular disease, respectively, compared with 50 in the healthy population, i.e. 
9, 11, and 19 points difference to normal population, respectively. This suggests a larger potential for 
improvement. However, the results of Murchie et al. (2004) who investigated similar treatment 
suggest that the potential might be limited. They have not analysed summary components but 
averaging their results for the subscales roughly according to oblique-weights from Farivar et al. 
(2007), we obtain around 4.5 points improvement for PCS and around 2.5 for MCS. These numbers 
are based on non-standardized scores. The improvement in standardized scores would roughly be 2-
2.5 for PCS after one year. We recommend therefore to target an effect of 2.5 points for the 
standardized summary components. 
4.3 SAMPLE SIZE CALCULATION 
Assuming a residual standard deviation of 9 for change from baseline in PCS and MCS based on 
calculations from reported confidence intervals in UKATT (2005) and requiring 80% power for a two-
sided test with significance level 5% between the treatment groups, the required sample size is in the 
following table depending on the assumed treatment difference.  
Treatment difference 
2 
2.5 
3 
3.5 
4 
4.5 
Sample size per group (both PCS 
and MCS primary variables;  
Bonferroni correction) 
390 
250 
175 
125 
100 
80 
  
The effects seen in the study by Murchie et al. (2004) correspond approximately to 2.5 points on PCS. 
This change has been considered relevant in other diseases (see e.g. Strand et al., 2012). To ensure 
the 80% power when the treatment difference is 2.5 points and when both PCS and MCS are primary 
variables with Bonferroni-corrected tests, the sample size of 250 patients per treatment-group, i.e. 
500 in total, was chosen (Julious, 2009). With a calculated 33% non-inclusion rate, enrolment time is 
estimated from November 2016 to December 2020 or until 500 participants are included. 
5 ANALYSIS POPULATIONS 
The analyses will be based on the intention-to-treat (ITT) principle. All randomized patients will be 
included in the analysis as belonging to the randomized treatment group, irrespectively of their 
actual treatment. 
Some of the secondary analyses will be based on complete cases which means that patients who 
drop out prior to the analysis timepoint (Month 12 or Month 24) are excluded from the analysis. The 
analysis populations for these analyses are therefore restricted to patients following the study 
procedures (protocol) until a certain timepoint.  

 
5 
 
6 GENERAL ANALYSIS METHODS 
6.1 MULTIPLICITY ASPECTS 
All tests will be two-sided. Generally, a significance level of 5% will be used. The analyses for the two 
primary variables will be multiplicity adjusted. For analyses of secondary variables, no formal 
adjustment for multiplicity will be done. Single significances must therefore not be overinterpreted. 
Only if several analyses show results which together give a clear picture, a discussion of a potential 
effect of the intervention is justified. 
6.2 VISIT WINDOWS 
Most of the analysis variables are recorded at baseline, Month 12, and Month 24. The actual date of 
collection might deviate from the ideal time point 12 or 24 months after the randomization date. The 
measurement is considered valid if it is collected between 10 months and 14 months after 
randomisation, or between 22 months and 26 months after randomisation, respectively. Otherwise 
the measurement is not considered in the analysis. If two or more measurements fall in one of the 
above windows, the measurement closest to the ideal time point (12 or 24 months after 
randomisation date) will be used and the other measurements is not considered. 
6.3 HANDLING OF MISSING DATA 
Missing values are expected in this study in most analysis variables. We assume however that the 
variables “disease severity in terms of compensated or decompensated state” and “study site” used 
as independent variables do not suffer from missingness; the former is required for randomisation. 
The primary analysis uses a model-based method to deal with missing values: the repeated 
measurements model analyses data of every patient even if one or two observations of baseline, 
Month 12, and Month 24 are missing.  
Secondary analyses will be performed first as complete case analysis. A sensitivity analysis using 
multiple imputation (see e.g. Van Buuren, 2018) will be used to handle impact of missing values. If 
the analysis model for a specific analysis is a linear or logistic regression model, then the imputation 
model will be based on this model adding the independent variables age and gender. If the Mann-
Whitney U test is used for treatment comparison, then an imputation model which is appropriate for 
the distribution of the variable will be searched using following independent variables: group 
(intervention or control), baseline value (if relevant for this variable), disease severity in terms of 
compensated or decompensated state, study site, age, and gender.  
Reasons for dropout (patients prematurely terminating the study) will be compared between groups 
(intervention or control) by reporting percentage dropout by reason and group. Implications of 
differences between groups will be discussed. 
7 PRIMARY AND SECONDARY ANALYSES 
7.1 PRIMARY ANALYSIS 
The two primary variables are the physical component summary (PCS) and the mental component 
summary (MCS) from RAND-36. A repeated measurements model will be used for analysis of 
baseline, Month 12, and Month 24 values of the component summary score. Treatment group 

 
6 
 
(intervention or control), time (baseline, Month 12, Month 24) with interaction, and 
decompensated/compensated state will be fixed effects, while site will be a random effect in the 
model. The dependence of the observations over time will be modelled using an unstructured 
covariance matrix. The main contrast of interest to be estimated with this model is change from 
baseline to Month 24 for both treatment groups.  
For the treatment group comparison, Bonferroni-Holm-method using a corrected alpha=2.5% will be 
used to compensate for multiple testing of both PCS and MCS.  
The contrast “change from baseline to Month 12” for both treatment groups will also be estimated 
with this model for both PCS and MCS. The treatments will be compared but the p-values for this 
Month 12 analysis will not be multiplicity adjusted. 
7.2 SECONDARY ANALYSES 
7.2.1 
Patient’s perspective of quality of care (QPP) 
The probability of having “lacking quality” in each of the Items 5-26 will be analysed with a logistic 
regression model; in accordance with the QPP manual (Wilde-Larsson et al., 2001, page 37) we focus 
on this category since it reflects the least favourable and most demanding situation. We distinguish 
not between the categories “balance” and “excess quality” in this model.  
Independent variables in the logistic model will be group (intervention or control), if the patient had 
“lacking quality” at baseline, disease severity in terms of compensated or decompensated state, and 
study site. The effect of group will be summarized using odds ratio with 95% CI, and a p-value for the 
null hypothesis of no group effect. The analysis will be done separately for Month 12 and Month 24 
data.  
Based on the recommendation in the QPP manual (Wilde-Larsson et al., 2001, page 37), items are 
analysed separately. Single significances must not be overinterpreted since no adjustment for these 
multiple analyses is done. Only if several items within a dimension show similar differences this 
points to a potential effect of the intervention. 
Items with multiple choice answers are summarized descriptively showing percentage patients by 
group (intervention, control) and by time (baseline, Month 12, Month 24). Answers to open-ended 
items are summarized if deemed to be relevant. 
7.2.2 
Visits at outpatient clinics and admissions to hospital 
Mean values for number of visits/days in each analysis variable will be summarized by group 
(intervention, control) and by time interval (baseline-to-Month-12, Month-12-to-Month-24). Further, 
the ratio of number of visits/days for the intervention group relative to the control group will be 
reported. 
The number of visits/days in each analysis variable will be compared between groups with the Mann-
Whitney U test; the analysis will be done for the baseline-to-Month-12 and Month-12-to-Month-24 
interval separately. 
These summaries and analyses will be done separately for the patients in compensated and 
decompensated state. 
If significant clinical outcomes are identified in the study, a health economic analysis will be 
conducted. 

 
7 
 
7.2.3 
Child Pugh score  
The risk classes (A, B, C) will be summarized descriptively showing percentage patients in each class 
by group (intervention, control) and by time (baseline, Month 12, Month 24). 
The change from baseline in Child Pugh score (5-15) will be compared between groups with the 
Mann-Whitney U test; the analysis will be done for Month 12 and Month 24 separately. 
7.2.4 
Model of end stage liver disease (MELD) 
The change from baseline in MELD score will be compared between groups using a linear regression 
model with MELD-change as dependent variable. Independent variables will be group (intervention 
or control), baseline MELD score, disease severity in terms of compensated or decompensated state, 
and study site. The effect of group will be summarized using estimated group difference with 95% CI, 
and a p-value from the t-test. The analysis will be done separately for Month 12 and Month 24 data. 
7.2.5 
Royal free hospital-nutritional prioritising tool (RFH-NPT) 
The risk classes (low, medium, high) will be summarized descriptively showing percentage patients in 
each class by group (intervention, control) and by time (baseline, Month 12, Month 24). 
The change from baseline in RFH-NPT score (0-7) will be compared between groups with the Mann-
Whitney U test; the analysis will be done for Month 12 and Month 24 separately. 
7.2.6 
Appearance of decompensation episodes 
The probability of appearance will be analysed with a logistic regression model. Independent 
variables in the logistic model will be group (intervention or control), if the patient had these 
episodes at baseline, disease severity in terms of compensated or decompensated state, and study 
site. The effect of group will be summarized using odds ratio with 95% CI, and a p-value for the null 
hypothesis of no group effect. The analysis will be done separately for Month 12 and Month 24 data.  
7.2.7 
Hepatic encephalopathy (HE) 
The probability of having a Grade 1 HE diagnosis (pathological result in both PHES and CRT, i.e PHES-
score -4 or lower and CRT-index < 1.9) will be analysed with a logistic regression model. Independent 
variables in the logistic model will be group (intervention or control), if the patient had a Grade 1 HE 
diagnosis at baseline, disease severity in terms of compensated or decompensated state, and study 
site. The effect of group will be summarized using odds ratio with 95% CI, and a p-value for the null 
hypothesis of no group effect. The analysis will be done separately for Month 12 and Month 24 data. 
7.2.8 
Health literacy (HL) 
The classes (likely limited literacy, possible limited literacy, adequate literacy) will be summarized 
descriptively showing percentage patients in each class by group (intervention, control) and by time 
(baseline, Month 12, Month 24). 
The change from baseline in NVS score (0-6) will be compared between groups with the Mann-
Whitney U test; the analysis will be done for Month 12 and Month 24 separately. 
REFERENCES 
Elsass P, Christensen SE, Mortensen EL, et al (1985). Discrimination between organic and hepatic 
encephalopathy by means of continuous reaction times. Liver, 5, 29-34. 
 
Farivar SS, Cunningham WE, Hays RD (2007). Correlated physical and mental health summary scores 
for the SF-36 and SF-12 Health Survey, V.1. Health and Quality of Life Outcomes, 5, 54. 

 
8 
 
Hays RD, Sherbourne CD, Mazel RM (1993). The RAND 36-Item Health Survey 1.0. Healthecon, 2, 217-
27. 
 
Hays RD, Morales LS (2001). The RAND-36 measure of health-related quality of life. Ann Med, 33, 
350-7. 
 
Hjorth, M, Sjöberg, D, Svanberg, A, Kaminsky, E, Langenskiöld, S, Rorsman F (2018). Nurse-led Clinic 
for Liver Cirrhotic Patients – Effects on Health-Related Quality of Life: Study Protocol of a Pragmatic 
Multicentre Randomised Controlled Trial. Submitted manuscript. 
 
Jenkinson C (1999). Comparison of UK and US methods for weighting and scoring the SF-36 summary 
measures. Journal of Public Health Medicine, 21, 372-376. 
 
Julious SA (2009). Sample Sizes for Clinical Trials. Chapman & Hall/CRC. 
Laucis NC, Hays RD, Bhattacharyya T (2015). Scoring the SF-36 in Orthopaedics: A Brief Guide. J Bone 
Joint Surg Am., 97, 1628-1634. 
Rannou F et al. (2007). Should aggregate scores of the Medical Outcomes Study 36-item Short Form 
Health Survey be used to assess quality of life in knee and hip osteoarthritis? A national survey in 
primary care. OsteoArthritis and Cartilage, 15, 1013-1018.  
Shah LC, West P, Bremmeyr K, Savoy-Moore RT (2010). Health Literacy Instrument in Family 
Medicine: The “Newest Vital Sign” Ease of Use and Correlates. J Am Board Fam Med, 23, 195-203. 
Strand V, Burmester GR, Ogale S, Devenport J, John A, Emery P (2012). Improvements in health-
related quality of life after treatment with tocilizumab in patients with rheumatoid arthritis 
refractory to tumour necrosis factor inhibitors: results from the 24-week randomized controlled 
RADIATE study. Rheumatology, 51, 1860-1869. 
UKATT Research Team (2005).  Effectiveness of treatment for alcohol problems: findings of the 
randomised UK alcohol treatment trial (UKATT). BMJ, 331, 541-545. 
Van Buuren S (2018). Flexible Imputation of Missing Data. Second Edition. Boca Raton, FL.: Chapman 
& Hall/CRC Press. 
Ward MM, Guthrie LC, Alba MI (2014). Clinically Important Changes in Short Form 36 Health Survey 
Scales for Use in Rheumatoid Arthritis Clinical Trials: The Impact of Low Responsiveness. Arthritis 
Care & Research, 66, 1783-1789. 
Weissenborn K, Ennen JC, Schomerus H, et al (2001). Neuropsychological characterization of hepatic 
encephalopathy. J Hepatol, 34, 768-73. 
Wilde-Larsson B, Larsson G, Larsson M, Starrin B (2001). KUPP-boken. Vägledning till frågeformuläret 
KUPP, Kvalitet ur patientens perspektiv (in Swedish). Vårdförbundet, Stockholm. 
 

Nurse-led clinic for patients with liver cirrhosis  
– effects on health-related quality of life  
 
 
Date 17-11-2016 
 
 
 
Consent Form 
 
Patient ID:____________________ 
 
I hereby confirm that I have read and understood the written information concerning 
participation in the research project: Liver Nurse-led Clinic I have been given verbal 
information and my questions have been answered. I have had sufficient time in which to 
consider my participation. 
I consent to: 
 Participate and that my participation is wholly voluntarily. 
 
 I can at any time and without needing to state the reason why, terminate my 
participation without it affecting my present and future care and healthcare needs. 
 
 My personal data is handled and processed in compliance with the stipulations under 
the header Handling of data and confidentiality, in the written information about the 
research project. 
 
Patient: 
Signature of the patient 
 
 
 
Date (dated by the patient) 
Name, block letters 
 
 
 
 
 
Nurse Practitioner: 
I have provided the patient with complete information concerning every aspect of this study. 
Signature of nurse providing information 
 
 
 
Date (dated by the nurse 
providing information) 
Name, block letters 
 
 
 
 
 
One copy of the patient information and the signed consent form is given to the patient.