PHILUCA: The Development of Muscle Mass, Muscle Strength, and Muscle Function in Patients With Lung Cancer During Cancer Treatment
Conditions: Non-small Cell Lung Cancer (NSCLC), Small Cell Lung Cancer (SCLC)
Sponsor: Zealand University Hospital

Changes on 05.02.2026 
NCT Number NCT06730685  
Unique Protocol Id PHILUCA 
 
PHILUCA: The Development of Muscle Mass, Muscle Strength, and Muscle Function in Patients 
With Lung Cancer During Cancer Treatment 
Updated power considerations and sample size 
The sample size calculation was originally based on a pooled estimate from prospective cohorts of 
patients with advanced-stage lung cancer, assuming a hazard ratio for mortality of 2.38 and a 
sarcopenia prevalence of 50%. With power set at 90% and a two-sided alpha of 0.05, a final 
sample of 130 patients with advanced-stage lung cancer was required for the primary analysis. 
Initially, an expected study withdrawal rate of 28% was assumed, corresponding to a required 
baseline inclusion of 180 patients with advanced-stage lung cancer to ensure 130 patients 
available at 3-months follow-up. 
However, based on observed study retention during recruitment, the actual withdrawal rate has 
been lower than anticipated. As of 05 February 2026, among the first 153 included patients, the 
observed dropout rate was 19%. Under this empirically observed retention rate, inclusion of 160 
patients with advanced-stage lung cancer is sufficient to ensure the required final sample size of 
130 patients. 
Accordingly, the target sample size for patients with advanced-stage lung cancer has been revised 
from 180 to 160 patients, without compromising the statistical power of the study. 
Update to data collection timepoints 
The study protocol was amended with respect to the timing of follow-up assessments.  
Due to logistical and time constraints in the clinical setting, it was not possible to assess changes in 
muscle parameters or health-related quality of life beyond three months after inclusion. 
Furthermore, repeated assessments of muscle parameters at each chemotherapy cycle during 
first-line treatment could not be performed, as these timepoints coincided with treatment 
administration and clinical workflows that did not allow for additional study procedures. 
As a result, follow-up assessments were limited to a single post-baseline timepoint. Assessments 
are intended to be performed approximately three months after inclusion, which in routine 
clinical practice usually corresponds to the timepoint immediately prior to the first control 
imaging scan. This timing ensures clinical relevance while maintaining feasibility and minimizing 
participant burden. 
These changes do not affect the primary study objectives but define the scope of longitudinal 
analyses accordingly. 

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Study Protocol 
 
 
 
 
 
Original English 4tle: 
PHILUCA: The development of muscle mass, muscle strength, and 
muscle func=on in pa=ents with lung cancer during cancer treat-
ment 
 
Original Danish 4tle: 
PHILUCA: Udviklingen af muskelmasse, muskelstyrke og muskel-
funk=on hos pa=enter med lungekræD under kræDbehandlingen 
 
 
 
 
Version: 1.3 
 
Date of last revision: 20.12.2024 
 
Edited by:  
Lukas Svendsen, Susanne Oksbjerg Dalton, Gunn Ammitzbøll, CharloIe SueIa, Morten 
Quist, Pernille Bidstrup and Rikke Langballe 
 
 
 
 

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Contents 
1.0 INVESTIGATORS AND COLLABORATORS 
3 
2.0 INTRODUCTION 
4 
3.0 BACKGROUND 
5 
4.0 AIMS 
6 
4.1 RESEARCH QUESTION AND HYPOTHESIS 
7 
5.0 METHODS 
7 
5.1 PATIENT AND PUBLIC INVOLVEMENT 
7 
5.2 STUDY DESIGN AND SETTING 
7 
5.3 POPULATION 
8 
5.3.1 Inclusion criteria 
8 
5.3.2 Exclusion criteria 
8 
5.4 STUDY PROCEDURE 
8 
5.4.1 Recruitment procedure 
8 
5.4.2 Par<cipants’ informa<on and wri@en informed consent 
9 
5.4.3 Adherence, reten<on and dropouts 
10 
5.4.4 Withdrawal of study par<cipants 
10 
5.5 STUDY MEASUREMENTS 
10 
5.5.1 Measurements and clinical data 
14 
5.5.2 Ques<onaries 
15 
5.6 DATA COLLECTION TIMELINE 
18 
6.0 STATISTICS 
18 
6.1 POWER CONSIDERATIONS AND STATISTICAL ANALYSIS 
18 
7.0 DATA MANAGEMENT AND STORAGE 
19 
7.1 DATA FROM MEDICAL RECORDS 
19 
7.2 DATA STORAGE AND SAFETY 
20 
8.0 ETHICAL CONSIDERATIONS 
21 
9.0 ORGANIZATION 
22 
10.0 DISSEMINATION 
23 
11.0 FINANCES 
23 
12.0 INSURANCE 
23 
13.0 PUBLICATION OF RESULTS 
24 
14.0 PERSPECTIVES 
24 
15.0 REFERENCES 
24 
 
 
 
 
 
 
 

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1.0 Inves;gators and collaborators 
 
Principal inves;gator  
Susanne Oksbjerg Dalton, Professor, MD, PhD 
Danish Research Center for Equality in Cancer (COMPAS) 
Department of Clinical Oncology and Pallia@ve Care, Zealand University Hospital 
Rådmandsengen 5, 4700 Næstved, Denmark & Group Leader at Survivorship & Inequality in Can-
cer, Danish Cancer Ins@tute, Strandboulevarden 49, 2100 Copenhagen, Denmark 
 
Primary project site: 
Department of Clinical Oncology and Pallia@ve Care, Zealand University Hospital 
Rådmandsengen 5,  4700 Næstved, Denmark 
 
Secondary project site: 
Department of Pulmonary Medicine, Zealand University Hospital 
Ringstedgade 61, 4700 Næstved, Denmark 
Inves@gator: Uﬀe Bødtger, Professor, MD, PhD 
 
Project manager 
Pa;ent iden;ﬁca;on, pa;ent contact and data collec;on  
Lukas Svendsen, PhD student, MSc in exercise physiology 
Department of Clinical Oncology and Pallia@ve Care, Zealand University Hospital 
 
Collaborators  
CharloLe SueLa, Clinical Professor, MD, PhD 
Geriatric Department, Copenhagen University Hospital, Bispebjerg and Frederiksberg Ins@tute of 
Clinical Medicine, University of Copenhagen 
 
Gunn Ammitzbøll, Postdoc, Physiotherapist, PhD 
Department of Clinical Oncology and Pallia@ve Care, Zealand University Hospital & Danish Cancer 
Ins@tute 
 
Morten Quist, Associate Professor, Physiotherapist, PhD 
UCSF – Center for Health Research, Rigshospitalet & Department of Clinical Medicine, University of 
Copenhagen 
 
Malene Støckel Frank, PhD, Consultant   
Department of Clinical Oncology and Pallia@ve Care, Zealand University Hospital 
Rådmandsengen 5, 4700 Næstved, Denmark   
 

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Casper Simonsen, PhD, Group Leader   
TrygFonden’s Center for Physical Ac@vity Research (CFAS) 
Rigshospitalet, Ole Maaløes Vej 26, 2200 Copenhagen N, Denmark   
 
Pernille Bidstrup, Senior Researcher, Head of Research Team & Rikke Langballe, Postdoc   
Danish Cancer Ins@tute   
Strandboulevarden 49, 2100 Copenhagen Ø, Denmark   
 
GiLe Alstrup, research project nurse, Lungemedicinsk Forskningsenhed (PLUZ) 
Department of Pulmonary Medicine, Zealand University Hospital 
Ringstedgade 61, 4700 Næstved, Denmark 
 
Declara;on from inves;gators and collaborators 
The inves;gators and collaborators of this trial declare no conﬂicts of interest and that the trial will 
be conducted in accordance with the Declara;on of Helsinki, and the respec;ve rules and regula-
;ons in Denmark.  
 
Authorships 
This protocol was authored by abovemen;oned study group. First- and co-authorships of the sci-
en;ﬁc publica;ons with experiences and ﬁndings from the project will follow the Vancouver guide-
lines.  
 
2.0 Introduc-on 
Low socioeconomic posi;on (SEP) is strongly associated with lung cancer incidence and survival. 
Barriers related to receiving recommended treatment among lung cancer pa;ents with low SEP may 
include adverse health behavior, long distances to the hospital, and limited physical and psychosocial 
resources. Other biological barriers related to treatment receipt include the development of sarco-
penia, which is the natural degenera;on of the body with a gradual reduc;on in muscle mass and 
physical performance. A cancer disease and treatment can further accelerate sarcopenia substan-
;ally, thus enhancing the risk of cancer cachexia, which involves sarcopenia along with weight loss. 
Sarcopenia and cachexia are highly prevalent among pa;ents with lung cancer, and emerging evi-
dence suggests an associa;on between these factors and worse treatment outcomes. Progressive 
cancer-related sarcopenia and cachexia is mul;factorial and self-enhancing and with current 
knowledge incompletely explaining underlying mechanisms, an eﬃcient management strategy is 
lacking. Exploring these factors as well as pa;ent-related barriers to treatment may provide an 

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opportunity to improve lung cancer treatment receipt and tolerance and thus prognosis by inform-
ing the treatment plan and intervening ;mely and appropriately to prevent or improve sarcopenia 
and cachexia.  
 
3.0 Background 
Lung cancer has one of the worst prognoses among cancers, especially for pa;ents with low SEP and 
advanced disease 1-3. Diﬀerences in received treatment, stage, and comorbidity may explain a large 
propor;on of the social inequality in lung cancer prognosis both among early-stage and advanced-
stage pa;ents 2. Thus, both disease-related factors as well as social and behavioral factors may in-
crease the risk of not adhering to lung cancer treatment. Pa;ents with lung cancer oden have poor 
Eastern Coopera;ve Oncology Group performance status (PS) 4 at the ;me of diagnosis resul;ng in 
a high burden of side eﬀects, treatment delays, dose-reduc;ons and treatment failure 5. Chemother-
apy is primarily oﬀered to pa;ents with a PS of 0-2. Yet, this measure is not an ideal parameter, and 
in par;cularly in older pa;ents with cancer, determina;on of PS is oden inaccurate 6. The dose of 
chemotherapy is rou;nely calculated based on pa;ent’s body surface area. This method might be 
problema;c i.e. in pa;ents with sarcopenic obesity, as the combina;on of a large body surface area 
and low muscle mass may lead to a lower tolerance for chemotherapy and a worse prognosis 7,8. 
Further, ini;al dose downregula;on is based on the pa;ent’s age, comorbidity and/or PS. Taken to-
gether, it appears that the tools available for physicians to precisely judge if downregula;on is ap-
propriate may be insuﬃcient. Even pa;ents with a good PS at ;me of diagnosis are at risk of devel-
oping sarcopenia or cachexia through the course of systemic treatment 9. This receives liLle focus in 
the clinic, although it could provide a poten;al pa;ent beneﬁt in terms of intervening prior to a loss 
in physical func;on and reduced Quality of Life (QoL) 10,11. If an interven;on could be successful in 
preven;ng or reversing sarcopenia or cachexia, it can poten;ally increase pa;ents’ chance of com-
ple;ng the scheduled treatment regime. Emerging evidence suggests that resistance training and 
protein rich diet may have this eﬀect 12, but studies in pa;ents with lung cancer during systemic 
treatment are lacking 13.  
There is marked diversity in current clinical prac;ce in assessing the degree of muscle loss in pa;ents 
with cancer and in quan;fying its func;onal implica;ons 14. If the loss of muscle mass and strength 
have signiﬁcant clinical implica;ons for pa;ents with cancer, then standardized, validated diagnos;c 

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thresholds are clearly needed 14. Furthermore, while the eﬀects of sarcopenia have been extensively 
studied in the elderly pa;ents, factors associated with loss of muscle mass and strength in cancer 
remain unclear 14. 
The prevalence of sarcopenia in lung cancer is higher than in other cancers, ranging from 22-71% 
depending on the popula;on and deﬁni;on of sarcopenia 8,15-18, however, no studies have described 
the prevalence in a Danish lung cancer popula;on. Among associated clinical factors iden;ﬁed in 
previous studies are older age, smoking, comorbidity, low BMI, low caloric intake, physical inac;vity, 
cancer treatment and progression 19,20. The knowledge about underlying mechanisms of sarcopenia 
in cancer is, however, fragmented, and it remains to be uncovered what happens in real life pa;ents 
and if it can be inﬂuenced by an interven;on. Further, with the rela;vely poor prognosis in lung 
cancer, it is important not only to explore if survival ;me may be improved, but also if QoL during 
treatment and survival ;me can be improved.  
Taken together, with the lack of knowledge about pa;ent-related factors and sarcopenia and ca-
chexia prevalence and development, there is a need to explore what inﬂuences the individual pa-
;ent’s treatment tolerance, QoL and prognosis. Further, this may provide an opportunity to explore 
if clinical tools covering social vulnerability, as well as muscle mass and physical func;on tests,  can 
add valuable and precise informa;on that may be used to beLer judge the op;mal systemic treat-
ment dose and to beLer iden;fy pa;ents in need of support and symptom management during 
treatment. Finally, due to the high risk of losing physical func;on and developing sarcopenia and 
cachexia in pa;ents with lung cancer, there is a serious need for developing eﬀec;ve interven;ons 
that can prevent or restore physical func;on and muscle mass throughout treatment and into survi-
vorship. 
4.0 Aims  
The overall aims of the PHILUCA study are in a longitudinal study to examine sarcopenia and cachexia 
risk factors, the development over ;me, and the associa;ons with lung cancer treatment tolerance, 
QoL and prognosis. In addi;on, the aim is to test whether a vulnerability screening tool can iden;fy 
pa;ents at high risk of not comple;ng the planned treatment.  
 
 

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4.1 Research QuesQon and hypothesis 
What is the prevalence and paLern of development of sarcopenia and cachexia and what are the 
associated factors, prognosis, treatment tolerance and QoL throughout treatment? 
 
We hypothesize that if the Danish stage distribu;on of sarcopenia and cachexia is worse than that 
of other countries - and health is worse than that of other countries, then the risk of sarcopenia and 
cachexia might also be higher and could explain why we have a rela;vely larger subgroup of pa;ents 
with lung cancer who have low 1-year survival rates. 
 
Which pa;ent-related and disease-related factors from can best predict treatment adherence as part 
of a vulnerability screening instrument? 
 
We hypothesize that selected pa;ent-related and disease-related factors can contribute to a vulner-
ability scale and that this scale is able to predict treatment adherence.  
 
5.0 Methods 
5.1 PaQent and public involvement 
The design of PHILUCA has been developed and reﬁned by the pa;ent panel of Zealand University 
Hospital, consis;ng of former or current cancer pa;ents and their rela;ves. The pa;ent panel has 
by the 13th of May 2024 recognized the project's relevance and approved the quan;ty and type of 
data collec;on methods. 
 
5.2 Study design and se0ng 
The PHILUCA study will be a prospec;ve cohort involving 180 par;cipants and will be conducted at 
the Department of Oncology and Pallia;ve Care at Zealand University Hospital (ZUH) in Næstved. 
This allows us to inves;gate the prevalence, paLerns of development, and impact of sarcopenia and 
cachexia throughout the pa;ent’s treatment as well as pa;ent and disease-related factors associ-
ated with treatment adherence. This approach allows for the iden;ﬁca;on of associated factors and 
provides real-;me data, ensuring accuracy and reliability. 

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5.3 Popula6on 
5.3.1 Inclusion criteria 
- 
Pa;ents newly diagnosed with histologically veriﬁed lung cancer and scheduled for oncolog-
ical treatment   
- 
Age > 18 years 
- 
Expected survival > 3 months 
 
5.3.2 Exclusion criteria  
- 
Compe;ng cancer 
- 
Pregnancy 
- 
Physical or cogni;ve disabili;es preven;ng par;cipa;on  
- 
Not able to understand wriLen and verbal Danish 
 
5.4 Study Procedure 
5.4.1 Recruitment procedure  
Pa;ents with suspected lung cancer will be recruited from the Department of Pulmonary Medicine, 
Zealand University Hospital (ZUH), Næstved. According to reports from the Department of Pulmo-
nary Medicine, > 70% of cases pa;ents will be diagnosed with lung cancer, but in the approximately 
30% of pa;ents where a lung cancer diagnosis is not conﬁrmed we omit follow-up assessments. This 
will thoroughly be explained to the pa;ent verbally and in the wriLen informa;on leaﬂet during 
invita;on.  
Moreover, eligible candidates not already iden;ﬁed from Department of Pulmonary Medicine, will 
be iden;ﬁed during the mul;disciplinary team (MDT) lung cancer conference within the Department 
of Clinical Oncology and Pallia;ve Care. Subsequently, following a comprehensive medical examina-
;on during their ini;al outpa;ent visit, pa;ents mee;ng the speciﬁed inclusion criteria will be ap-
proached by the aLending physician regarding poten;al par;cipa;on in the study. 
It is important to emphasize that pa;ent recruitment may occur at two dis;nct ;me points: ﬁrst, 
during the diagnos;c phase when suspicion of lung cancer arises, and second, during the ini;al out-
pa;ent visit at the Department of Clinical Oncology and Pallia;ve Care ader further evalua;on and 
conﬁrma;on of eligibility criteria. This dual approach ensures a comprehensive recruitment strategy, 

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capturing pa;ents at various stages of the diagnos;c phase thus facilita;ng robust data collec;on 
for the study. 
 
5.4.2 Par)cipants’ informa)on and wri6en informed consent 
The trea;ng physician, nurse or inves;gator will inform eligible pa;ents about the op;on to bring 
rela;ves to be informed and invited into the study by one of the inves;gators, which will take place 
in a private room within the Department of Clinical Oncology and Pallia;ve Care, ZUH, Næstved. All 
pa;ents eligible for par;cipa;on will receive a verbal explana;on in clear Danish regarding the 
study's purpose and procedures, the voluntary nature of par;cipa;on, the guarantee of anonymity, 
the conﬁden;al handling of data, and the implica;ons of their involvement, as detailed in Appendix 
4c (Retningslinjer for afgivelse af mundtlig deltagerinforma@on). Pa;ents will be assured that par-
;cipa;ng in the study will not aﬀect their standard medical treatment and that they can withdraw 
their consent at any ;me without any impact on their future care. The following wriLen materials 
about the PHILUCA study will be distributed: the 1) par;cipant informa;on sheet, 2) the wriLen 
consent form, 3) the latest version of the brochure "Before You Make Up Your Mind: The Rights of a 
Trial Subject in a Clinical Research Project," and 4) a document outlining our management of per-
sonal data according to Region Zealand guidelines (Appendiks 6 Oplysningspligt). 
Pa;ents will be oﬀered a minimum of 24-hour for considera;on, with the opportunity to discuss 
par;cipa;on with rela;ves. Ader mutual agreement about a contact ;mepoint, an inves;gator will 
contact the pa;ent to determine par;cipa;on. If par;cipa;on is agreed and the consent form is 
signed, the pa;ent will receive a copy, and the baseline test will be scheduled and performed. Pa-
;ents who decline to par;cipate in the full PHILUCA study will be asked if they would be willing to 
par;cipate in a minor part of the study by comple;ng the baseline ques;onnaire and allow that 
clinical and treatment data is obtained from their medical journal (see Appendix 5, Samtykkeerk-
læring). This aims to examine the characteris;cs of these par;al decliners and determine if they 
diﬀer from full par;cipants. Informed consent will be obtained for this purpose before any data 
about them is collected and stored. The same data from medical records and the baseline ques;on-
naire will be collected from par;al par;cipants as from full par;cipants (see part 7.1). 
 

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5.4.3 Adherence, reten)on and dropouts 
Physical tes;ng days will be scheduled in coordina;on with par;cipants’ individual hospital sched-
ules to the best extent possible. However, aLending physical tes;ng sessions may pose challenges 
for some pa;ents, par;cularly those experiencing chemotherapy-related side eﬀects, live alone, 
have scarce resources, or have func;onal limita;ons. Thus, some ﬂexibility in the scheduling of phys-
ical tes;ng sessions may be necessary. Any devia;ons from the tes;ng manual will be communicated 
with an inves;gator for discussion and considera;on of pragma;c solu;ons with regards to ;ming. 
Adherence to the physical tes;ng protocol, adherence to prescribed intensity, modiﬁca;ons made 
during tes;ng, interrup;ons, and reasons for dropouts, will be me;culously recorded throughout 
the study period. Addi;onally, any adverse events will be documented electronically by inves;gators 
following thorough instruc;on. 
 
5.4.4 Withdrawal of study par)cipants 
Par;cipants will be withdrawn from the study if the par;cipant withdraws consent or if the inves;-
gators deem that it is in the best interest of the pa;ent due to e.g. unexpected sudden events such 
as bone fractures, psychological distress or newly diagnosed severe comorbidi;es during the study 
period.  
 
5.5 Study measurements 
Par;cipa;on in the study involves measurements of muscle mass (body composi;on), muscle 
strength, muscle func;on, and pa;ent-reported outcomes on lifestyle and social vulnerability factors 
(only at ;me of diagnosis) and QoL and frailty. All physical measurements are performed while the 
pa;ent is at the hospital for treatment or examina;on. For pa;ents undergoing chemotherapy, phys-
ical tests are - in addi;on to the planned assessments at the ;me of diagnosis, ader 3 months, and 
ader 6 months - also performed before each treatment cycle, but no later than 6 months ader the 
diagnosis. A ;meline of data collec;on is presented in part 5.6. 
 
Sarcopenia 
A cri;cal challenge for using sarcopenia as a risk factor based on current evidence is the diﬀerences 
in the assessment methods applied in diﬀerent research ﬁelds and clinical sesngs 21. In aging and 

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clinical popula;ons outside the oncological ﬁeld, the sarcopenia diagnosis is based on an assessment 
of appendicular lean sod ;ssue by dual-energy x-ray absorp;ometry (DXA), bioelectrical impedance 
analysis (BIA) and rarely magne;c resonance 22,23. In contrast, sarcopenia is commonly assessed by 
computed tomography (CT) scans in pa;ents with cancer. CT scans are readily available for many 
pa;ents with cancer, given their role in diagnosing and monitoring the disease 14,24. To account for 
diverging muscle mass measurements within current literature, muscle mass will be measured by 
both BIA and CT scans. 
 
The European Working Group on Sarcopenia in Older People (EWGSOP2) updated their 2010 sarco-
penia deﬁni;on in 2018, emphasizing muscle strength as a primary indicator, streamlining diagnosis 
methods, and advoca;ng for early detec;on, treatment and increased research 23.  
Muscle strength will be measured by maximal isometric handgrip strength. The cut-oﬀ points for 
handgrip strength (HGS) will be < 27 kg for males and < 16 kg for females.  
Muscle mass measured by BIA will be expressed as appendicular lean mass (ALM) with cut-oﬀ points 
for males < 20 kg and females < 15 kg, and ALM/height2 with cut-oﬀ points for males < 7.0 kg/m2 
and females < 5.5 kg/m2. 
Muscle mass measured by CT scans by the third lumbar vertebra (L3), since muscle mass and adipose 
;ssue at the L3 are highly correlated with the whole-body measurements 25,26, and are a common 
muscle mass measurement within the context of lung cancer 14. This cross-sec;onal area contains 
visceral and subcutaneous adipose ;ssue, psoas, and posterior paravertebral muscles, as well as 
abdominal wall muscles. These images will be analyzed by using the Slice-O-Ma;c (Tomovision, 
Montreal, Canada) sodware which will allow the speciﬁca;on and segmenta;on of speciﬁc ;ssue. 
Segmenta;on describes the process of separa;ng pixels based on their aLenua;on in Hounsﬁeld 
units (HU). Structures are labeled on an image by combining aLenua;on (oden using a range of Hus) 
and anatomic informa;on. When a range of HU values is used, the process is called threshold-based 
segmenta;on. The speciﬁc HU range selected varies depending on the ;ssue of interest27. By using 
the HU limits of 29 to þ150 for skeletal muscles (psoas, erector spinae, quadratus lumborum, trans-
versus abdominis, obliquus externus, obliquus internus, and rectus abdominis), 150 to 50 for visceral 
adipose ;ssue, and 190 to 30 for subcutaneous and intramuscular adipose ;ssue27,28. The cross-
sec;onal areas (cm2) will be calculated for each ;ssue by the sum of pixels mul;plied by the surface 

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area. Lumbar Vertebrae 3 Skeletal Muscle Index (L3SMI) will be calculated by dividing muscle mass 
in cm2 by the pa;ent’s height in m2 (cm2/m2)27. Low muscle mass by L3SMI determined by CT imag-
ing will be deﬁned by (men <55 cm2/m2; women <39 cm2/m2)29. 
Sarcopenia will be present if both HGS and muscle mass are below the cut-oﬀ points23. Gait speed 
will be used to dis;nguish between sarcopenia and severe sarcopenia. Figure 1 presents the algo-
rithm of diagnosing sarcopenia by the EWGOSP2: 
 
Figure 1: As presented in Meza-Valderrama et. al. (2021) 30.  
 
In addi;on, through L3 cross-sec;onal area, a quan;ﬁca;on of body composi;on; muscle mass area, 
adipose ;ssue area (visceral, subcutaneous and intramuscular), and muscle aLenua;on will be ob-
tained. This method presents high sensi;vity and speciﬁcity for the detec;on of changes in body 
composi;on 28. Segmenta;on will be performed by trained researchers; with further evalua;on and 
approval by a board-cer;ﬁed clinical radiologist 31.  
 
Cachexia 
Cachexia is a mul;factorial syndrome with involuntary progressive weight loss as a result of reduc-
;on of skeletal muscle mass with or without deple;on of adipose ;ssue. Cancer cachexia is charac-
terized by systemic inﬂamma;on and metabolic changes leading to progressive func;onal impair-
ment. Sarcopenia as an index for cancer cachexia is a maLer of debate. There is a lack of consensus 
on a deﬁni;on, diagnos;c criteria and classiﬁca;on of cancer cachexia 32. Therefore, two separate 
deﬁni;ons will be accounted for in the PHILUCA study, to ensure possible comparison with exis;ng 
literature: 
The Interna;onal consensus of the deﬁni;on of cancer cachexia from Fearon et. al. from 2011 will 
be used in deﬁning cancer cachexia as >5% self-reported unintended weight loss within the past six 
months, or a 2–5 % weight loss with either a BMI <20 kg/m2, or reduced muscle mass (males, <7.3 
kg/ m2; females, <5.5 kg/m2) 29,33. Further, cachexia can be stra;ﬁed into following stages. 

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Figure 2: Fearon (2011) 29 deﬁni;on as presented in Meza-Valderrama et. al. (2021)30.  
 
To supplement abovemen;oned, the deﬁni;on by Evans et. al. from 2008 will be used (Figure 3). 
Rou;ne blood samples collected during each hospital visit will provide insight into any abnormal 
biochemistry. Plasma C-reac;ve protein and serum albumin levels will be used to calculate the mod-
iﬁed Glasgow Prognos;c Score (mGPS) 34. 
 
Figure 3: Evans (2008) 35 deﬁni;on as presented in Meza-Valderrama et. al. (2021)30.  
 
 
 
 

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Frailty 
Frailty is a mul;dimensional clinical condi;on characterized by a decrease in biological reserve ca-
pacity leading to increased vulnerability and reduced ability to resist stressors such as illness, falls, 
or any circumstances that aﬀect mental and physical well-being36-40.  Frailty will be assessed by an 
inves;gator using the 9-point Clinical Frailty Scale (CFS), according to the deﬁni;on by Rockwood41. 
A frailty score ≥ 5 indicated the presence of frailty. 
 
5.5.1 Measurements and clinical data 
Table 1 shows the outcomes, measurements and sources that will be used in the study period. 
Endpoints 
Description 
Test/sample/source 
Primary outcome 
Survival  
o 
1-year overall survival  
o 
5-year overall survival 
Medical records 
Medical records 
Exploratory outcomes  
Sarcopenia 
 
o 
Muscle strength and mass and 
change over time  
Routine CT-scan (baseline CT to last performed 
CT within 12-months after diagnosis) & bioim-
pedance analysis 
Cachexia 
o 
Stages of cachexia and change over 
time 
Muscle mass (by routine CT-scan and bioim-
pedance analysis), abnormal biochemistry by 
routine blood samples and weight loss 
Chemotherapy  
completion rate 
o 
Mean RDI in % 
o 
Number of patients with an RDI  
< and ≥ 85 % 
o 
Dose-limiting toxicity (DLT) 
DLT defined as ‘switching treatment’ 
, ‘treatment delay’ (≥3 days from ini-
tially planned), ‘treatment de-escala-
tion’ (dose reduction ≥15% of plati-
num agent), early treatment termi-
nation, and hospitalization ≥1 day, all 
due to chemotherapy-induced side 
effects.  
Medical records 
Treatment com-
plications 
o 
Complications related to surgery, ra-
diotherapy, immunotherapy and tar-
geted therapy. 
Medical records 
 
Biomarkers 
o 
Routine blood tests of plasma CRP 
and serum-albumin to diagnose ca-
chexia and haematological toxicities  
Medical records  
Changes in 
body composi-
tion 
o 
Total muscle and fat mass 
Routine CT-scans 
Bioimpedance analysis 

Appendiks 2 
Studyprotocol, v.1.3 20.12.2024 
 
 
15 
Changes in  
muscle strength 
 
o 
Isometric muscle strength 
Dynamometry for handgrip strength (HGS) 
Changes in  
muscle function 
o 
Muscle power 
 
o 
Gait speed 
30sSTS 
5 x STS 
10 m. walking test (maximal and habitual) 
Geriatric treat-
ment- 
related  
vulnerability 
o 
Geriatric-8 screening tool  
 
Filling in of the G8 will be partly self-reported 
by the patient and from medical records. 
Frailty 
o 
Clinical Frailty Scale (CFS) 
Assessed at visit at hospital by physician or in-
vestigator 
Vulnerability in-
dex 
o 
Items for new scale to predict treat-
ment adherence 
Self-reported items on social vulnerability and 
obtained from medical records 
 
A comprehensive health/capacity assessment will be completed by an inves;gator (physiotherapist 
or exercise physiologist) before every test session and include the following: (a) exercise prepar;ci-
pa;on health screening, and pre-exercise evalua;on; (b) measurement of body composi;on by bi-
oimpedance analysis; (c) measurement of maximal muscle strength by HGS 42 using a hand dyna-
mometer (Jamar); (d) muscular func;on; ﬁrstly, lower-extremity muscular func;on by 30-second sit 
to stand test (30sSTS). Concurrently, ﬁve ;mes stand up within the 30sSTS test will be measured 
using an addi;onal stopwatch. Secondly, maximal and habitual gait speed will be measured over a 
10-meter straight walking course. In-depth descrip;ons of the tes;ng procedures can be found in 
(Appendiks 2a testmanual på dansk).  
 
5.5.2 Ques)onaries  
Treatment-related vulnerability 
A tool commonly used to iden;fy prognos;c vulnerability among older pa;ents with cancer is the 
Geriatric-8 screening tool (G8) 43 originally developed from the Mini Nutri;onal Assessment ques-
;onnaire44. The G8 is recommended by the Interna;onal Society of Geriatric Oncology (SIOG) 45 and 
was originally designed to iden;fy older pa;ents who would beneﬁt from geriatric assessment and 
interven;on in the trajectory of cancer treatment. Studies have found that the G8 has high sensi;v-
ity and nega;ve predic;ve value in iden;fying older pa;ents at risk of nega;ve outcomes when un-
dergoing surgery for cancer33,43,46,47. Pa;ents with a score of ≤ 14 will be regarded vulnerable regard-
ing treatment, while pa;ents with a score of ≥15 will be regarded “ﬁt”. Filling in of the G8 will be 
partly self-reported by pa;ent and from medical records.  

Appendiks 2 
Studyprotocol, v.1.3 20.12.2024 
 
 
16 
 
Self-reported physical ac?vity levels 
Par;cipants will be asked about their self-reported weekly physical ac;vity, moderate-to-vigorous 
physical ac;vity and daily sedentary ;me using single-item ques;ons. 
 
Health-Related Quality of Life 
HRQOL, evaluated by self-reported ques;onnaires, is a valid and strong measure. It correlates with 
various crucial aspects such as longevity, health habits, mental and physical well-being, social con-
nec;ons, and produc;vity among cancer pa;ents48. The European Organiza;on for Research and 
Treatment of Cancer Quality of Life Ques;onnaire (EORTC QLQ-C30) is an integrated system for as-
sessing the HRQoL of cancer pa;ents par;cipa;ng in clinical studies and other types of research in 
which pa;ent-reported outcomes are collected49. The EORTC QLQ-C30 is designed for use in a wide 
range of cancer popula;ons and is intended to be supplemented by tumour-speciﬁc ques;onnaire 
modules such as those for lung cancer (QLQ-LC13)49. 
HRQoL will be evaluated by EORTC QLQ-C30 and EORTC QLQ LC1349. Items from EORTC-QLQ-C30 
contain a global scale covering global Quality of Life (QoL), ﬁve func;oning scales and 9 symptoms 
scales. Items from the EORTC QLQ LC13 contain ten disease-speciﬁc symptom scales.   
All the scales and single-item measures range in score from 0 to 100. Thus, a high score for the global 
health status / QoL represents a high QoL, a high score for a func;onal scale represents a high / 
healthy level of func;oning, but a high score for a symptom scale / item represents a high level of 
symptomatology / problems49.  
 
Social vulnerability index 
We have based on knowledge from previous studies and feedback from clinical experts and pa;ents 
on factors impac;ng treatment adherence among lung cancer pa;ents, developed and pilot tested 
a vulnerability instrument to predict adherence to treatment 50.  The instrument include nine clinical 
and pa;ent-reported vulnerability criteria: (1) stage (from medical journal), (2) comorbidity (soma;c 
or psychiatric) (from medical journal), (3) age (from medical journal), (4) performance status (from 
medical journal), (5) ac;vi;es of daily living (three pa;ent-reported items regarding diﬃcul;es with 
personal hygiene, taking a walk and climbing stairs), (6) social support (three pa;ent-reported items 

Appendiks 2 
Studyprotocol, v.1.3 20.12.2024 
 
 
17 
regarding emo;onal support as well as support with prac;cali;es at home and transporta;on), (7) 
health literacy (three pa;ent-reported items regarding diﬃcul;es in understanding healthcare infor-
ma;on, instruc;ons from healthcare professionals and ﬁlling in forms), (8) transporta;on related 
barriers for treatment (three pa;ent-reported items regarding diﬃcul;es in reaching the hospital 
due to lack of transporta;on, long distance to the hospital or limited energy) or (9) alcohol abuse 
(three pa;ent-reported items regarding alcohol consump;on) 50  
 
Table 2 – Self-reported ques?onaries 
Patient characteristics 
and 
Exploratory outcomes 
Scale, Reference 
Abbreviation 
Details 
Sociodemographic  
factors 
Education, work market affilia-
tion, civil status, cohabitation 
status 
Self-constructed 
Items: 4 
(only at baseline) 
Weight, clinical char-
acteristics and smok-
ing 
Current weight and 12+6 
month(s) ago 
Self-constructed and 
3 self-reported G8 
items 
Items: 9 
(only at baseline) 
Vulnerability index 
Items for new scale to predict 
treatment adherence 
New scale that will 
be validated in this 
study 
Items: 15 
(only at baseline) 
Physical activity levels 
Physical activity levels  
Self-constructed 
Items: 3 
(only at baseline) 
Health-Related 
Quality of Life  
(Functioning and 
symptoms) 
The European Organization for 
Research and Treatment of Can-
cer Quality of Life Questionnaire 
EORTC QLQ-C30 
Items: 30 
Domains: 15 
 
Health-Related 
Quality of Life  
(Disease-specific 
symptoms) 
The European Organization for 
Research and Treatment of Can-
cer Quality of Life Questionnaire 
Lung cancer module: QLQ-LC13  
EORTC QLQ-LC13 
 
 
Items: 13 
Domains: 10 
 
 
Par;cipants will be asked to ﬁll out a ques;onnaire comprising diﬀerent scales and self-con-
structed ques;ons addressing exploratory outcomes and addi;onal informa;on, possible media-
tors and confounders (Table 2) at diagnosis, ader 3 months and ader 6 months. The ques;ons will 
be gathered to comprise one extended ques;onnaire. Weight and clinical characteris;cs and socio-
demographic factors will only be collected at baseline.  
Pa;ents can complete the ques;onnaire on paper on the ﬁrst test day if there is enough ;me and a 
quiet space available. Further, pa;ents can complete it at home, where they will receive the 

Appendiks 2 
Studyprotocol, v.1.3 20.12.2024 
 
 
18 
ques;onnaire electronically. If the pa;ent prefers to ﬁll out the ques;onnaire at home, and lack 
necessary electronic skills, it can be done over a phone call, where a project staﬀ member assists 
the pa;ent through the ques;ons verbally. It will be agreed with the pa;ent when and how it would 
be most convenient for them, but the ﬁrst ques;onnaire must be completed before the treatment 
ini;a;on or as soon as possible thereader (at the latest, one week ader the start of treatment). Data 
collec;ons will be managed through REDCap.  
 
5.6 Data collec6on 6meline  
Table 3 
*Up to 12-months. 
Rou1ne CT scans are generally performed at deﬁned intervals during the diagnos1c and treatment course, typically at diag-
nosis, around 3 months, and at 6 months. For our analysis, we aim to u1lize the most recent CT scan conducted within 12 
months as the post-treatment measure to evaluate changes in muscle mass before and aGer treatment. If the ﬁnal CT scan 
post-treatment occurs earlier, for instance, at 4.5 or 9 months, this scan will be used as the endpoint measure. It is important 
to note that no addi1onal CT scans beyond rou1ne scans and the established 12-month 1meline will be scheduled. 
**3 muscle func1on tests as presented in Table 1 
Abbrevia1ons; Computed Tomography (CT); The European Organiza1on for Research and Treatment of Cancer Quality of Life 
Ques1onnaire (EORTC-QLQC30), and lung cancer module (EORTC-QLQLC13). 
 
 
6.0 Sta-s-cs 
6.1 Power consideraQons and staQsQcal analysis 
The popula;on size (n=180) is calculated based on a pooled es;mate from prospec;ve cohorts, in-
cluding pa;ents with advanced stage lung cancer, with a hazard ra;o for mortality risk of 2.38 and a 
prevalence of sarcopenia for the popula;on of 50% 8. With power set to 90% and alpha=0,05, we 
Months (number) 
1 
2 
3 
4 
5 
6 
12 
Test/Examination 
 
Muscle mass by routine CT-
scans* 
• 
 
• 
 
 
• 
• 
Muscle mass by bioimpedance 
analysis 
• 
 
• 
 
 
• 
 
Muscle strength tests 
• 
• 
• 
• 
• 
• 
 
Muscle function tests** 
• 
• 
• 
• 
• 
• 
 
Frailty 
• 
 
• 
 
 
• 
 
Questionnaires 
 
Self-constructed G8 items 
• 
 
 
 
 
 
 
Social vulnerability instrument  
• 
 
 
 
 
 
 
Lifestyle 
• 
 
 
 
 
 
 
EORTC-QLQC30, EORTC-QLQLC13 
• 
 
• 
 
 
• 
 

Appendiks 2 
Studyprotocol, v.1.3 20.12.2024 
 
 
19 
have to include 130 pa;ents with advanced stage lung cancer. To account for an expected study 
withdrawal rate of approximately 28%, we need to ensure that we have 130 pa;ents remaining by 
the end of the study. To ﬁnd the ini;al number of par;cipants required, we divide the ﬁnal required 
sample size (n=130) by the reten;on rate (0.72). Rounded up to the nearest whole number, we need 
to include 180 pa;ents with advanced stage lung cancer. Our recruitment method (at ;me of referral 
for suspicion of lung cancer) will include non-cancer pa;ents, pa;ents at low stage who undergo 
surgery, which means the total cohort will include n=500 par;cipants, to ensure 180 pa;ents with 
advanced stage lung cancer. This total cohort will enable subgroup analyses comparing cancer and 
non-cancer par;cipants, as well as analyses within diﬀerent treatment subgroups. 
We will stra;fy analyses according to relevant categories in uni- and mul;variate regression analyses 
examine associa;ons between exposures and outcomes, presen;ng es;mates of regression coeﬃ-
cients and odds ra;os with 95% conﬁdence intervals and p-values and use mixed eﬀect models for 
repeated measurements. 
For the social vulnerability screening instrument, we will describe the distribu;on of each factor 
included in the vulnerability screening tool. Next, we will use sta;s;cal analysis ('predic;on mod-
els') to select the vulnerability factor that best predicts treatment adherence (measured in Rela;ve 
Dose Intensity). Furthermore, we will examine the sensi;vity and speciﬁcity of the screening tool 
using diﬀerent cut-oﬀ scores to assess the op;mal cut-oﬀ for iden;fying pa;ents who did not com-
pleted treatment op;mally.  
7.0 Data management and storage  
7.1 Data from medical records 
Before the study recruitment, relevant clinical informa;on will be passed to the inves;gators in order 
to iden;fy poten;al pa;ents for inclusion at the Department of Pulmonary Medicine, ZUH.  Based 
on pa;ent lists these will include: personal and contact informa;on (name, address, phone number, 
email), date of next visit to clinic, and sensi;ve personal informa;on (CPR number, suspected cancer 
type). During the invita;on session, the exclusion criteria of severe physical or cogni;ve comorbidi-
;es will be assessed by asking the pa;ent. We expect up to 10 % of approached pa;ents will decline 
par;cipa;on. We therefore need to screen approximately 1550 pa;ents within the period of 

Appendiks 2 
Studyprotocol, v.1.3 20.12.2024 
 
 
20 
01.09.2024 to 01.09.2027. If pa;ents decline par;cipa;on, all informa;on stored will be deleted 
immediately.  
 
Ader wriLen informed consent has been obtained from par;cipants at baseline the medical records 
will be reviewed by an inves;gator at regular intervals during lung cancer treatment to collect data 
on sociodemographic characteris;cs, anthropometrics, health status, func;onal status, and clinical 
informa;on on cancer type and cancer treatment. These include:  
• Ordinary personal informa;on; name, address, phone number, email, cohabita;on status, 
employment status, age and sex.  
• Sensi;ve personal informa;on; CPR number, cancer type, cancer treatment, body mass in-
dex, body surface area, informa;on on the degree of treatment comple;on and complica-
;ons, physical or cogni;ve comorbidi;es, CT scan images, PS, ;me since cancer diagnosis, 
results from standard blood tests.  
The pa;ent's consent gives the inves;gator and their representa;ve direct access to this informa;on 
to conduct, monitor, and audit the study. The informa;on from medical records is collected with the 
aim of inves;ga;ng whether muscle mass, strength, and func;on are related to treatment tolerance. 
The medical records will be reviewed at the end of the study by one of the inves;gators to extract 
data on recurrence and survival for a period of up to 1 year and 5-years ader lung cancer diagnosis. 
The data will be handled with conﬁden;ality according to Part 7.2 and used for descrip;ve sta;s;cs 
of par;cipants and in mul;variate analyses of outcomes in a pseudonymised form. Par;cipants who 
ini;ally provided informed consent and had performed baseline measurements, but were later 
found not to  have lung cancer will contribute with data for comparison analysis between people 
with and without lung cancer on variables such as sociodemographics, clinical characteris;cs, base-
line physical func;on and body composi;on, and survival. No addi;onal measurements beyond 
baseline tes;ng will be conducted for this cohort. All data will be securely handled in compliance 
with ethical and conﬁden;ality standards. 
 
7.2 Data storage and safety 
We will no;fy and obtain permission from Region Zealand and Research Ethics CommiLee Region 
Zealand before study ini;a;on. Handling of all personal data will comply with the General Data 

Appendiks 2 
Studyprotocol, v.1.3 20.12.2024 
 
 
21 
Protec;on Regula;on and the Data Protec;on Act. Data will be stored electronically according to 
Region Zealand’s guidelines on data safety. The Clinical Study Management sodware, Research Elec-
tronic Data Capture (REDCap) with oﬀ-site backup systems will be used for data management and 
storage un;l the end of the study period (and 5 years ader the end of the study). REDCap automat-
ically pseudonymises data by giving a unique study number to par;cipants by inclusion. Data in pa-
per form may be stored temporarily behind three locks in a locked cabin at a locked oﬃce at a locked 
hallway in the oﬃce located at the Department of Clinical Oncology and Pallia;ve Care, Zealand 
University Hospital, Rådmandsengen 5, DK-4700 Næstved, room number 50.02.15 before being 
scanned and uploaded electronically and aderwards destroyed. In addi;on, pseudonymised docu-
ments that may not be suitable for storage in REDCap will be stored in a secured project folder at 
the O-drive (ONK_DATA (\\regsj.intern\ﬁles) (0:), which is protected by passwords. Only the inves;-
gators will have data access. For sta;s;cal analyses data will be transferred to the Danish Cancer 
Society (see Appendix 6, Oplysningspligt). 
 
8.0 Ethical considera-ons 
This study is conducted based on the Danish Code of Integrity in Research complying with the prin-
ciples of integrity and responsibility in research. Par;cipants in the studies will be included upon 
informed wriLen consent, allowing withdrawal of consent without any consequences for their treat-
ment and without explana;on. 
 
The study will be conducted in accordance with the Declara;on of Helsinki, and the study procedure 
will comply with the ethical standards of the par;cipa;ng clinical department. Inves;gators will be 
trained in (online course) and comply with guidelines from the Good Clinical Prac;ce unit through-
out the study period.  
Informed consent will be obtained from all par;cipants prior to ini;a;on of any study procedures. 
Informed consent will only be obtained ader thorough verbal informa;on, discussions, and answers 
to any ques;ons the pa;ents may have about the wriLen informa;on or other thoughts during the 
process of deciding to par;cipate or not. Pa;ents will be informed that they may withdraw their 
consent at any ;me. We ensure that all obtained data during the study period will be treated 

Appendiks 2 
Studyprotocol, v.1.3 20.12.2024 
 
 
22 
conﬁden;ally. All sta;s;cal analyses will be conducted on grouped data only, and no results are dis-
closed revealing individual pa;ent data.  
 
The considera;ons for the safety, and well-being of research par;cipants, as well as the rights, in-
tegrity, and privacy of research par;cipants, take precedence over scien;ﬁc and societal interests. 
Since the risk of pa;ents experiencing side eﬀects or harms does not exceed the risks in everyday 
life, and the societal beneﬁt of the project is signiﬁcant and beneﬁcial for the treatment of future 
pa;ents, this is considered fulﬁlled. In addi;on to receiving informa;on about muscle mass, muscle 
strength, and muscle func;on, no therapeu;c beneﬁt is considered for the par;cipants. However, 
the study par;cipants will contribute to research that may have a signiﬁcant impact on the develop-
ment of future treatments for pa;ents with lung cancer. 
9.0 Organiza-on 
The study will take place in the Department of Pulmonary Medicine and Department of Clinical On-
cology and Pallia;ve Care, ZUH. We have formed a unique collabora;on between clinical experts in 
lung cancer treatment, physiotherapists and nutri;onal specialists, ensuring clinical and scien;ﬁc 
relevance and full transla;onal poten;al to clinical prac;ce. The project will be conducted as a PhD 
project by Lukas Svendsen who will ensure high quality data collec;on and the appropriate conduc-
;on and scien;ﬁc documenta;on. The transla;onal poten;al of the project will be maximized by 
the involvement of clinicians and pragma;c solu;ons in all elements of the study. 
PI and primary supervisor is Professor, Director of Danish Research Center for Equality in Cancer 
(COMPAS), Department of Clinical Oncology and Pallia;ve Care, ZUH, Susanne Dalton and the study 
will be included as one of the research ac;vi;es in COMPAS aiming to reduce inequality in outcomes 
ader cancer through targeted interven;ons to vulnerable/high-risk pa;ents. Primary co-supervisor 
is Clinical Professor CharloLe SueLa, Department of Clinical Medicine, University of Copenhagen. 
Co-supervisors will be physiotherapist, postdoc, Gunn Ammitzbøll and Morten Quist, Associate Pro-
fessor, Department of Clinical Medicine, University of Copenhagen. 
The project team further include highly experienced clinicians and researchers; Consultant, Malene 
Støckel Frank and Professor, Consultant in Pulmonary Medicine Uﬀe Bødtger, and project nurse GiLe 
Alstrup all aﬃliated at ZUH, and Casper Simonsen, PhD, group leader at Centre for Physical Ac;vity 
Research (CFAS). The work regarding sta;s;cal valida;on of the vulnerability screening instrument 

Appendiks 2 
Studyprotocol, v.1.3 20.12.2024 
 
 
23 
is done in collabora;on with Pernille Bidstrup and Rikke Langballe at the Danish Cancer Ins;tute at 
the Danish Cancer Society.  
10.0 Dissemina-on 
Results will be published as at least 2 peer-reviewed papers, presented at na;onal/interna;onal 
conferences, press releases and homepage news (compas.dk, cancer.dk, dccc.dk, dlcg.dk), as well as 
social media (linkedin and X) and popular science talks to i.e., pa;ent and professional organiza;ons. 
11.0 Finances  
There is no ﬁnancial compensa;on for par;cipa;on in the project. Par;cipa;on will not entail addi-
;onal hospital visits or ﬁnancial expenses from the par;cipants' side. The ini;a;ve of conduc;ng 
the study was taken by the Clinical Professors Susanne Oksbjerg Dalton and Gunn Ammitzbøll from 
Department of Clinical Oncology and Pallia;ve Care, Zealand University Hospital. The study is ﬁ-
nanced through funding from the Danish Cancer Society (A20717, 1.250.000 DKK); the Department 
of Clinical Oncology and Pallia;ve Care, Zealand University Hospital (342.001 DKK); The Danish Re-
search Center for Inequality in Cancer (COMPAS) (223-A13094-18-S68, 102.500 DKK); Region Zea-
land's Health Science Research Fund (150.000 DKK). The majority of expenses will be for salary of 
the PhD student. External funds, such as sodware, will be applied through independent founda;ons 
and government grants during the study period. The ﬁnancial support and study expenses will be 
administered from accounts in Region Zealand. None of the inves;gators or collaborators have ﬁ-
nancial interests in the study or other conﬂicts of interest.  
 
12.0 Insurance 
Par;cipants will be covered by the regular insurance for pa;ents treated at hospitals in Region Zea-
land under current legisla;on as the principal inves;gator Susanne Oksbjerg Dalton is employed as 
a Professor at the Department of Clinical Oncology and Pallia;ve Care. In case of severe injuries, 
compensa;on for injury will be provided through Pa@enterstatningsordningen for pa;ents included 
in the study. If any requests occur, the inves;gators and clinical staﬀ will be obligated to guide the 
par;cipants in the applica;on process.  
 

Appendiks 2 
Studyprotocol, v.1.3 20.12.2024 
 
 
24 
13.0 Publica-on of results  
The study will be conducted as part of Lukas Svendsen’s PhD project. The study will be registered at 
www.clinicaltrials.gov. The repor;ng will follow “The Strengthening the Repor@ng of Observa@onal 
Studies in Epidemiology (STROBE) Statement: guidelines for repor@ng observa@onal studies.” The 
Vancouver criteria will be met for all authors. Posi;ve, nega;ve and inconclusive study ﬁndings will 
be reported to the public. Furthermore, results will be disseminated to the staﬀ of the involved clin-
ical department and presented at both na;onal scien;ﬁc mee;ngs such as the Danish Cancer Days 
held by the Danish Comprehensive Cancer Center and at interna;onal conferences.  
14.0 Perspec-ves 
Results from this study may poten;ally inform clinical prac;ce and indicate the poten;al for improv-
ing physical func;on, quality of life and prognosis through treatment. The ﬁndings from this pro-
spec;ve cohort study will elucidate which pa;ents are at risk for sarcopenia and cachexia, thereby 
informing the development of a forthcoming RCT feasibility study incorpora;ng a combined exercise 
and nutri;onal interven;on. 
 
 
 
 
 
 
15.0 References 
 
 
1. 
Dalton SO, Steding-Jessen M, Engholm G, et al. Social inequality and incidence of and 
survival from lung cancer in a popula;on-based study in Denmark, 1994-2003. Eur J Cancer 
2008;44(14):1989-1995, doi:10.1016/j.ejca.2008.06.023 
2. 
Dalton SO, Steding-Jessen M, Jakobsen E, et al. Socioeconomic posi;on and survival 
ader lung cancer: Inﬂuence of stage, treatment and comorbidity among Danish pa;ents with lung 
cancer 
diagnosed 
in 
2004-2010. 
Acta 
Oncol 
2015;54(5):797-804, 
doi:10.3109/0284186x.2014.1001037 

Appendiks 2 
Studyprotocol, v.1.3 20.12.2024 
 
 
25 
3. 
Sidorchuk A, Agardh EE, Aremu O, et al. Socioeconomic diﬀerences in lung cancer 
incidence: a systema;c review and meta-analysis. Cancer Causes & Control 2009;20(4):459-471, 
doi:10.1007/s10552-009-9300-8 
4. 
Neeman E, Gresham G, Ovasapians N, et al. Comparing Physician and Nurse Eastern 
Coopera;ve Oncology Group Performance Status (ECOG-PS) Ra;ngs as Predictors of Clinical 
Outcomes 
in 
Pa;ents 
with 
Cancer. 
Oncologist 
2019;24(12):e1460-e1466, 
doi:10.1634/theoncologist.2018-0882 
5. 
Goussault H, Gendarme S, Assié JB, et al. Factors associated with early lung cancer 
mortality: 
a 
systema;c 
review. 
Expert 
Rev 
An;cancer 
Ther 
2021;21(10):1125-1133, 
doi:10.1080/14737140.2021.1941888 
6. 
Friedlaender A, Banna GL, Buﬀoni L, et al. Poor-Performance Status Assessment of 
Pa;ents with Non-small Cell Lung Cancer Remains Vague and Blurred in the Immunotherapy Era. 
Curr Oncol Rep 2019;21(12):107, doi:10.1007/s11912-019-0852-9 
7. 
Kidd AC, Skrzypski M, Jamal-Hanjani M, et al. Cancer cachexia in thoracic malignancy: 
a 
narra;ve 
review. 
Curr 
Opin 
Support 
Palliat 
Care 
2019;13(4):316-322, 
doi:10.1097/spc.0000000000000465 
8. 
Buentzel J, Heinz J, Bleckmann A, et al. Sarcopenia as Prognos;c Factor in Lung Cancer 
Pa;ents: A Systema;c Review and Meta-analysis. An;cancer Res 2019;39(9):4603-4612, 
doi:10.21873/an;canres.13640 
9. 
Davis MP, Panikkar R. Sarcopenia associated with chemotherapy and targeted agents 
for cancer therapy. Ann Palliat Med 2019;8(1):86-101, doi:10.21037/apm.2018.08.02 
10. 
Fearon K, Strasser F, Anker SD, et al. Deﬁni;on and classiﬁca;on of cancer cachexia: an 
interna;onal consensus. Lancet Oncol 2011;12(5):489-95, doi:10.1016/s1470-2045(10)70218-7 
11. 
Nipp RD, Fuchs G, El-Jawahri A, et al. Sarcopenia Is Associated with Quality of Life and 
Depression 
in 
Pa;ents 
with 
Advanced 
Cancer. 
Oncologist 
2018;23(1):97-104, 
doi:10.1634/theoncologist.2017-0255 
12. 
Negm AM, Lee J, Hamidian R, et al. Management of Sarcopenia: A Network Meta-
Analysis of Randomized Controlled Trials. J Am Med Dir Assoc 2022;23(5):707-714, 
doi:10.1016/j.jamda.2022.01.057 
13. 
Brown JC, Cespedes Feliciano EM, Caan BJ. The evolu;on of body composi;on in 
oncology-epidemiology, clinical trials, and the future of pa;ent care: facts and numbers. J Cachexia 
Sarcopenia Muscle 2018;9(7):1200-1208, doi:10.1002/jcsm.12379 
14. 
Collins J, Noble S, Chester J, et al. The assessment and impact of sarcopenia in lung 
cancer: a systema;c literature review. BMJ Open 2014;4(1):e003697, doi:10.1136/bmjopen-2013-
003697 

Appendiks 2 
Studyprotocol, v.1.3 20.12.2024 
 
 
26 
15. 
Yang M, Shen Y, Tan L, et al. Prognos;c Value of Sarcopenia in Lung Cancer: A Systema;c 
Review and Meta-analysis. Chest 2019;156(1):101-111, doi:10.1016/j.chest.2019.04.115 
16. 
Baracos VE, Reiman T, Mourtzakis M, et al. Body composi;on in pa;ents with non-
small cell lung cancer: a contemporary view of cancer cachexia with the use of computed 
tomography image analysis. Am J Clin Nutr 2010;91(4):1133s-1137s, doi:10.3945/ajcn.2010.28608C 
17. 
Kim EY, Lee HY, Kim KW, et al. Preopera;ve Computed Tomography-Determined 
Sarcopenia and Postopera;ve Outcome Ader Surgery for Non-Small Cell Lung Cancer. Scand J Surg 
2018;107(3):244-251, doi:10.1177/1457496917748221 
18. 
Srdic D, Ples;na S, Sverko-Peternac A, et al. Cancer cachexia, sarcopenia and 
biochemical markers in pa;ents with advanced non-small cell lung cancer-chemotherapy toxicity 
and prognos;c value. Support Care Cancer 2016;24(11):4495-502, doi:10.1007/s00520-016-3287-y 
19. 
Kim CR, Kim EY, Kim YS, et al. Histologic subtypes are not associated with the presence 
of sarcopenia in lung cancer. PLoS One 2018;13(3):e0194626, doi:10.1371/journal.pone.0194626 
20. 
Schneider SM, Correia M. Epidemiology of weight loss, malnutri;on and sarcopenia: A 
transatlan;c view. Nutri;on 2020;69(110581, doi:10.1016/j.nut.2019.110581 
21. 
Buckinx F, Landi F, Cesari M, et al. Pi‚alls in the measurement of muscle mass: a need 
for a reference standard. J Cachexia Sarcopenia Muscle 2018;9(2):269-278, doi:10.1002/jcsm.12268 
22. 
Christensen JF, Jones LW, Andersen JL, et al. Muscle dysfunc;on in cancer pa;ents. Ann 
Oncol 2014;25(5):947-958, doi:10.1093/annonc/mdt551 
23. 
Cruz-Jentod AJ, Bahat G, Bauer J, et al. Sarcopenia: revised European consensus on 
deﬁni;on and diagnosis. Age Ageing 2019;48(1):16-31, doi:10.1093/ageing/afy169 
24. 
Simonsen C, Kristensen TS, Sundberg A, et al. Assessment of sarcopenia in pa;ents 
with upper gastrointes;nal tumors: Prevalence and agreement between computed tomography and 
dual-energy x-ray absorp;ometry. Clin Nutr 2021;40(5):2809-2816, doi:10.1016/j.clnu.2021.03.022 
25. 
Mourtzakis M, Prado CM, Lieﬀers JR, et al. A prac;cal and precise approach to 
quan;ﬁca;on of body composi;on in cancer pa;ents using computed tomography images acquired 
during rou;ne care. Appl Physiol Nutr Metab 2008;33(5):997-1006, doi:10.1139/h08-075 
26. 
Shen W, Punyanitya M, Wang Z, et al. Visceral adipose ;ssue: rela;ons between single-
slice areas and total volume. Am J Clin Nutr 2004;80(2):271-8, doi:10.1093/ajcn/80.2.271 
27. 
Troschel AS, Troschel FM, Best TD, et al. Computed Tomography-based Body 
Composi;on Analysis and Its Role in Lung Cancer Care. J Thorac Imaging 2020;35(2):91-100, 
doi:10.1097/r;.0000000000000428 
28. 
Toledo DO, Carvalho AM, Oliveira A, et al. The use of computed tomography images as 
a prognos;c marker in cri;cally ill cancer pa;ents. Clin Nutr ESPEN 2018;25(114-120, 
doi:10.1016/j.clnesp.2018.03.122 

Appendiks 2 
Studyprotocol, v.1.3 20.12.2024 
 
 
27 
29. 
Fearon K, Strasser F, Anker SD, et al. Deﬁni;on and classiﬁca;on of cancer cachexia: an 
interna;onal consensus. Lancet Oncol 2011;12(5):489-495, doi:10.1016/s1470-2045(10)70218-7 
30. 
Meza-Valderrama D, Marco E, Dávalos-Yerovi V, et al. Sarcopenia, Malnutri;on, and 
Cachexia: Adap;ng Deﬁni;ons and Terminology of Nutri;onal Disorders in Older People with Cancer. 
Nutrients 2021;13(3), doi:10.3390/nu13030761 
31. 
Recio-Boiles A, Galeas JN, Goldwasser B, et al. Enhancing evalua;on of sarcopenia in 
pa;ents with non-small cell lung cancer (NSCLC) by assessing skeletal muscle index (SMI) at the ﬁrst 
lumbar (L1) level on rou;ne chest computed tomography (CT). Support Care Cancer 
2018;26(7):2353-2359, doi:10.1007/s00520-018-4051-2 
32. 
VanhouLe G, van de Wiel M, Wouters K, et al. Cachexia in cancer: what is in the 
deﬁni;on? BMJ Open Gastroenterol 2016;3(1):e000097, doi:10.1136/bmjgast-2016-000097 
33. 
Dolin TG, Mikkelsen MK, Jakobsen HL, et al. The prevalence of sarcopenia and cachexia 
in older pa;ents with localized colorectal cancer. J Geriatr Oncol 2023;14(1):101402-101402, 
doi:10.1016/j.jgo.2022.11.001 
34. 
Proctor MJ, Morrison DS, Talwar D, et al. An inﬂamma;on-based prognos;c score 
(mGPS) predicts cancer survival independent of tumour site: a Glasgow Inﬂamma;on Outcome 
Study. Br J Cancer 2011;104(4):726-34, doi:10.1038/sj.bjc.6606087 
35. 
Evans WJ, Morley JE, Argilés J, et al. Cachexia: a new deﬁni;on. Clin Nutr 
2008;27(6):793-9, doi:10.1016/j.clnu.2008.06.013 
36. 
Clegg A, Young J, Iliﬀe S, et al. Frailty in elderly people. Lancet 2013;381(9868):752-62, 
doi:10.1016/s0140-6736(12)62167-9 
37. 
Chen X, Mao G, Leng SX. Frailty syndrome: an overview. Clin Interv Aging 2014;9(433-
41, doi:10.2147/cia.S45300 
38. 
Morley JE, Vellas B, van Kan GA, et al. Frailty consensus: a call to ac;on. J Am Med Dir 
Assoc 2013;14(6):392-7, doi:10.1016/j.jamda.2013.03.022 
39. 
HowleL SE, Rockwood K. New horizons in frailty: ageing and the deﬁcit-scaling 
problem. Age Ageing 2013;42(4):416-23, doi:10.1093/ageing/ad059 
40. 
Nygaard H, Kamper RS, Ekmann A, et al. Co-Occurrence of Sarcopenia and Frailty in 
Acutely AdmiLed Older Medical Pa;ents: Results from the Copenhagen PROTECT Study. J Frailty 
Aging 2024;13(2):91-97, doi:10.14283/jfa.2024.23 
41. 
Rockwood K, Song X, MacKnight C, et al. A global clinical measure of ﬁtness and frailty 
in elderly people. Cmaj 2005;173(5):489-95, doi:10.1503/cmaj.050051 
42. 
Yorke AM, Cur;s AB, Shoemaker M, et al. Grip strength values stra;ﬁed by age, gender, 
and chronic disease status in adults aged 50 years and older. J Geriatr Phys Ther 2015;38(3):115-21, 
doi:10.1519/jpt.0000000000000037 

Appendiks 2 
Studyprotocol, v.1.3 20.12.2024 
 
 
28 
43. 
Bellera CA, Rainfray M, Mathoulin-Pélissier S, et al. Screening older cancer pa;ents: 
ﬁrst evalua;on of the G-8 geriatric screening tool. Ann Oncol 2012;23(8):2166-2172, 
doi:10.1093/annonc/mdr587 
44. 
Vellas B, Guigoz Y, Garry PJ, et al. The Mini Nutri;onal Assessment (MNA) and its use in 
grading the nutri;onal state of elderly pa;ents. Nutri;on 1999;15(2):116-22, doi:10.1016/s0899-
9007(98)00171-3 
45. 
Wildiers H, Heeren P, Puts M, et al. Interna;onal Society of Geriatric Oncology 
consensus on geriatric assessment in older pa;ents with cancer. J Clin Oncol 2014;32(24):2595-603, 
doi:10.1200/jco.2013.54.8347 
46. 
Kenig J, Zychiewicz B, Olszewska U, et al. Screening for frailty among older pa;ents with 
cancer 
that 
qualify 
for 
abdominal 
surgery. 
J 
Geriatr 
Oncol 
2015;6(1):52-9, 
doi:10.1016/j.jgo.2014.09.179 
47. 
Kenig J, Szabat K, Mituś J, et al. Usefulness of eight screening tools for predic;ng frailty 
and postopera;ve short- and long-term outcomes among older pa;ents with cancer who qualify for 
abdominal surgery. Eur J Surg Oncol 2020;46(11):2091-2098, doi:10.1016/j.ejso.2020.07.040 
48. 
Christensen JF, Simonsen C, Hojman P. Exercise Training in Cancer Control and 
Treatment. Compr Physiol 2018;9(1):165-205, doi:10.1002/cphy.c180016 
49. 
European Organisa;on for Research and Treatment of Cancer. EORTC QLQ-C30 Scoring 
Manual. 2001; 
50. 
Langballe R, Dalton SO, Jakobsen E, et al. NAVIGATE: improving survival in vulnerable 
pa;ents with lung cancer through nurse naviga;on, symptom monitoring and exercise - study 
protocol for a mul;centre randomised controlled trial. BMJ Open 2022;12(10):e060242, 
doi:10.1136/bmjopen-2021-060242