HANSE - Holistic Implementation Study Assessing a Northern German Interdisciplinary Lung Cancer Screening Effort, Population-based Screening Study -Prospective, Randomized Comparator Controlled
Phase: NA
Conditions: Lung Cancer
Sponsor: Hannover Medical School

 
Study Protocol 
 
Study ESR Code ESR-20-20770 
 
Version 
final 2.1 
 
Date 
09-Feb-2021 
 
 
 
 
 
 
 
 
 
HANSE - Holistic implementation study Assessing a Northern German 
interdisciplinary lung cancer Screening Effort
 
Population-based Screening Study -Prospective, randomized comparator 
controlled 
 
 

Study Protocol 
Study ESR Code ESR-20-20770  
Version: final 2.1 
Date 09-Feb-2021 
2 
TABLE OF CONTENTS 
PAGE
 
TITLE PAGE ............................................................................................................................ 1 
TABLE OF CONTENTS ......................................................................................................... 2 
LIST OF ABBREVIATIONS .................................................................................................. 4 
RESPONSIBLE PARTIES ...................................................................................................... 5 
PROTOCOL SYNOPSIS ......................................................................................................... 6 
AMENDMENT HISTORY .................................................................................................... 15 
MILESTONES ....................................................................................................................... 16 
1. 
BACKGROUND AND RATIONALE .................................................................. 17 
1.1 
Background ............................................................................................................ 17 
1.2 
Rationale ................................................................................................................ 17 
2. 
OBJECTIVES AND HYPOTHESES .................................................................... 20 
2.1 
Primary Objective(s) & Hypothesis(es) ................................................................. 20 
2.2 
Secondary Objective(s) & Hypothesis(es) (Optional) ........................................... 20 
3. 
METHODOLOGY ................................................................................................ 21 
3.1 
Study Design – General Aspects ............................................................................ 21 
3.1.1 
Data Source(s) ........................................................................................................ 21 
3.2 
Study Population .................................................................................................... 21 
3.3 
Inclusion Criteria ................................................................................................... 22 
3.4 
Exclusion Criteria .................................................................................................. 22 
4. 
VARIABLES AND EPIDEMIOLOGICAL MEASUREMENTS ........................ 23 
4.1 
Exposures ............................................................................................................... 23 
4.1.1 
Definition of Primary Exposure ............................................................................. 23 
4.1.2 
Definition of Comparison Drug Exposure (Optional) ........................................... 23 
4.2 
Outcomes ............................................................................................................... 23 
4.3 
Other Variables and Covariates ............................................................................. 25 
5. 
STATISTICAL ANALYSIS PLAN ...................................................................... 26 
5.1 
Statistical Methods – General Aspects................................................................... 26 
5.1.1 
Primary and key-secondary Objective(s): .............................................................. 26 

Study Protocol 
Study ESR Code ESR-20-20770  
Version: final 2.1 
Date 09-Feb-2021 
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The primary and key-secondary endpoints of this study will be calculated from the 
following two fourfold tables summarizing the distribution of included 
patients and patients with detected lung cancer: .................................................... 26 
5.1.2 
Secondary Objective(s):  Calculation of Epidemiological Measure(s) of 
Interest (e.g. hazard ratios, incidence rates, test/retest reliability) ......................... 28 
5.1.3 
Exploratory Objective(s):  Calculation of Epidemiological Measure(s) of 
Interest (e.g. hazard ratios, incidence rates, test/retest reliability) ......................... 29 
5.2 
Bias ........................................................................................................................ 30 
5.2.1 
Methods to Minimize Bias ..................................................................................... 30 
5.2.2 
Adjustment for Multiple Comparisons .................................................................. 30 
5.2.3 
Strengths and Limitations ...................................................................................... 30 
5.3 
Sample Size and Power Calculations ..................................................................... 31 
6. 
STUDY CONDUCT AND REGULATORY DETAILS....................................... 36 
6.1 
Data Management .................................................................................................. 36 
6.1.1 
Study Flow Chart and Plan .................................................................................... 36 
6.1.2 
Procedures .............................................................................................................. 37 
6.1.3 
Quality Control ...................................................................................................... 45 
6.1.4 
Storage and Retention ............................................................................................ 46 
6.2 
Protection of Human Subjects................................................................................ 47 
6.2.1 
Subject Informed Consent ...................................................................................... 47 
6.2.2 
Confidentiality of Study/Subject Data ................................................................... 48 
6.3 
Management and Report of Adverse Events/Adverse Drug Reactions ................. 48 
6.3.1 
Definition of Adverse Events (AE) ........................................................................ 48 
6.3.2 
Definition of Serious Adverse Events (SAE) ........................................................ 48 
6.3.3 
Definition of Adverse Drug Reactions (ADR) ...................................................... 49 
6.3.4 
Collection of Adverse Events ................................................................................ 49 
 
Causality collection ................................................................................................ 49 
 
Time period for collection of adverse events ......................................................... 49 
6.3.5 
Reporting of Adverse Events ................................................................................. 50 
6.4 
Communication Plan .............................................................................................. 50 
6.4.1 
Publication Plan ..................................................................................................... 51 
6.4.2 
Compliance with Study Registration and Results Posting Requirements ............. 51 
6.4.3 
Compliance with Financial Disclosure Requirements ........................................... 51 
7. 
LIST OF REFERENCES ....................................................................................... 52 
8. 
APPENDICES ....................................................................................................... 54 
9. 
ATTACHMENTS .................................................................................................. 54 
10. 
SIGNATURES ....................................................................................................... 55 
 
 
 

Study Protocol 
Study ESR Code ESR-20-20770  
Version: final 2.1 
Date 09-Feb-2021 
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LIST OF ABBREVIATIONS 
Abbreviation or 
special term 
Explanation 
ARCN 
ADR 
AE 
AI 
BMI 
BREATH 
CAD 
CHERH 
CT 
DSGVO 
DRG 
ECG 
eCRF 
gGmbH 
IEC 
IQWiG 
LDCT 
LungRADS 
MDT 
PanCan 
PLCO 
SAE 
VDT 
Airway Research Center North 
Adverse drug reaction 
Adverse event 
Artificial Intelligence 
Body mass index 
Biomedical Research in End-stage and Obstructive Lung Disease Hannover 
computer-assisted detection/ computer-aided diagnosis 
Center for Health Economics Research Hannover  
Computed tomography 
Datenschutz-Grundverordnung 
Deutsche Röntgengesellschaft 
electrocardiogram 
Electronic case report form 
gemeinnützige Gesellschaft mit beschränkter Haftung 
Independent Ethics Committee 
Institut für Qualität und Wirtschaftlichkeit im Gesundheitswesen 
Low-dose computed tomography 
Lung CT Screening Reporting & Data System 
Multidisciplinary tumor board 
Pan-Canadian Early Detection of Lung Cancer 
Prostate, lung, colorectal, and ovarian cancer screening 
Serious adverse events 
Volume doubling time 
 
 
 
 
 

Study Protocol 
Study ESR Code ESR-20-20770  
Version: final 2.1 
Date 09-Feb-2021 
5 
RESPONSIBLE PARTIES 
Name 
Professional 
Title 
Role in Study 
Affiliation 
Email Address 
Jens Vogel-
Claussen 
Prof. Dr. 
Principal 
Investigator 
Institute for Diagnostic and 
Interventional Radiology 
Biomedical Research in 
End-stage and Obstructive 
Lung Disease Hannover 
(BREATH),  
German Center for Lung 
Research (DZL) 
vogel-
claussen.jens@mh-
hannover.de 
Sabine 
Bohnet 
Dr. 
Co-
Investigator 
Universitätsklinikum 
Schleswig-Holstein - 
Campus Lübeck 
Airway Research Center 
North (ARCN) 
German Center for Lung 
Research (DZL) 
Sabine.Bohnet@uksh.de 
Martin Reck 
Prof. Dr. 
Co-
Investigator 
LungenClinic 
Grosshansdorf gGmbH 
Airway Research Center 
North (ARCN) 
German Center for Lung 
Research (DZL) 
m.reck@lungenclinic.de 
 

Study Protocol 
Study ESR Code ESR-20-20770  
Version: final 2.1 
Date 09-Feb-2021 
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PROTOCOL SYNOPSIS 
 
APPLICANT/ 
COORDINATING 
INVESTIGATOR 
Prof. Dr. Jens Vogel-Claussen (Principal Investigator) 
Dr. Sabine Bohnet 
Prof. Dr. Martin Reck 
TITLE OF STUDY 
HANSE - Holistic implementation study Assessing a Northern German 
interdisciplinary lung cancer Screening Effort
BACKGROUND 
/RATIONALE: 
Germany has a long history of offering screening programs for cancers, such as 
breast, colorectal, and, more recently, cervical and skin cancer. Screening for lung 
cancer, however, which causes more deaths than any other cancer in men and is the 
second leading cancer death in women (not far behind breast cancer), has not been 
implemented to date.  
 
Only very recently, IQWiG in a preliminary assessment of low-dose CT screening, 
concluded that the benefits from screening outweigh potential risks. However, an 
implementation of a national lung cancer screening program, which would be 
covered by the general health insurance, will likely not be implemented before 2022. 
Nonetheless, the IQWiG report also comments on important criteria for 
implementing lung cancer screening in Germany using low-dose CT: 
 
1. 
It would be necessary to determine criteria that define a high-risk population. 
Various risk forecasting models are currently being propagated to enable a 
more precise selection of high-risk individuals. Their reliability and 
repeatability needs to be checked. 
2. 
Integration of access to a smoking cessation program. 
3. 
Quality assurance measures must be taken into account, including 
standardized protocols for the evaluation of the CT images and the 
subsequent follow-up checks as well as the invasive diagnostic tissue 
sampling procedures. 
 
The HANSE study is primarily intended as a pilot to provide evidence that a holistic 
and effective lung cancer screening program can be implemented in Germany and 
that such a screening program can be integrated in the current infrastructure of 
certified lung cancer centers.  
OBJECTIVE(S) 
Primary Objectives: 
The primary goal of this study is to compare the efficiency of the PLCOM2012 
>1.58% (6 year risk) risk score and the NELSON inclusion criteria in identifying 
patients with lung cancer in the age group 55-79 years. 
To that end, the PLCOM2012 model and the NELSON inclusion criteria will be 
compared  
(i) primarily regarding the positive predictive value of the two inclusion methods for 
lung cancers detected after 2 screening rounds in the study population and  
 
Secondary Objectives: 
(ii) secondarily regarding the following hierarchically ordered key-secondary 
endpoints: 
1. Proportion of individuals selected for screening 

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Study ESR Code ESR-20-20770  
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2. Proportion of lung cancers detected after 5 years  
3. Proportion of lung cancers detected after 5 years in the high-risk population 
4. Sensitivity of the two inclusion methods in lung cancer detection after 5 years 
5. Specificity of the two inclusion methods in lung cancer detection after 5 years 
 
The main secondary objective of this trial is to document that: 
1. 
Reporting of the coronary artery calcium score from low dose computed 
tomography (LDCT) data will lead to an increase in the rate of preventive 
cardiovascular treatments and reduced cardiovascular mortality. 
 
Additional objectives are to show that: 
1. 
Effective smoking cessation counselling is implemented as part of the 
screening program (urine cotinine check in quitters). 
2. 
CT derived information on tobacco related lung destruction, such as 
emphysema, may influence the smoking cessation rate. 
3. 
Structured reporting of clinically relevant non-cardiac incidental findings, 
e.g., emphysema or lung fibrosis, will lead to early detection and improved 
management of diseases. 
4. 
Adding the PanCan algorithm to the LungRads1.1 algorithm for nodule 
management increases the efficiency.  
5. 
Assessment of various blood-based or exhalation-based biomarkers may 
provide additional translational information in positive LDCT cases with subsequent 
biopsy, which may have an impact on the effectiveness of the LDCT test. 
6. 
Cost effectiveness analysis on recruiting strategies, risk models used, 
effectiveness on smoking cessation and cardiovascular mortality is implemented. 
 
INTERVENTION(S) 
Experimental intervention: 
Low-dose computed tomography with lung nodule evaluation (LungRADS1.1, high-
risk score group), randomized reporting of coronary artery calcium score, 
%emphysema 
Control intervention: 
No CT (low risk score group) No coronary artery calcium score and no % emphysema 
report, 
Follow-up per patient: 
1 year (10 years, follow-up study) 
Duration of intervention per patient: 
1 year (10 years, follow-up study) 
KEY INCLUSION AND 
EXCLUSION CRITERIA 
Key inclusion criteria: 
1. 
Male and female subjects aged 55-79 years 
2. 
Current or former smokers 
3. 
Subjects with calculated risk score PLCOM2012 1.58% (6 yrs.) or NELSON 
inclusion criteria (current or former smokers [those who had quit 10 years 
ago] who had smoked >15 cigarettes a day for >25 years or >10 cigarettes a 
day for >30 years). 
4. 
Able and willing to give written informed consent 
 
In addition, non-qualifying subjects fulfilling inclusion criteria 1 (age), 2 (smoking 
history) and 4 (consent), but do not meet the inclusion criterion 3 (risk too low) will 
be asked to volunteer by contributing long-term outcome data informing of the 

Study Protocol 
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development of lung cancer or death from lung cancer (about n=7100 randomly 
selected from all 3 centers, low-risk group).  These subjects will be contacted via mail 
after a minimum of 5 year follow up to inquire if they developed lung cancer in the 
time between their recruitment and present. Non-responders will be followed by local 
registries and by phone.  New lung cancer cases will be verified using official hospital 
or cancer registry documents. 
 
Key exclusion criteria:  
1. 
Comorbidity, which would unequivocally contraindicate either screening or 
treatment if lung cancer is detected.  
2. 
History of chest CT within the past year preceding the invitation. 
3. 
Inability to undergo non-contrast CT (e.g.  200 kg body weight, inability to 
lie flat). 
4. 
Pregnancy 
5. 
Risk of non-compliance with study procedures. 
- 
Unable to give written consent 
- 
Patient`s inability to fill in the questionnaire self-dependent 
- 
Limited knowledge of the German language 
- 
Inability to travel, residents of care facilities, etc. 
 
OUTCOME(S) 
Primary endpoint: 
Positive predictive value (PPV) for lung cancer detection with different inclusion methods 
(NELSON vs. PLCO) after 2 screening rounds. 
 
Secondary endpoints: 
 
Key secondary endpoint(s): 
1.  
Proportion of individuals selected for screening within the high-risk            
population 
2.  
Proportion of lung cancers detected with different inclusion methods 
(NELSON vs. PLCO) within the overall study population after 5 years  
3.  
Proportion of lung cancers detected with in the high-risk population after 5 
years 
4.       Specificity within the overall population after 5-year follow-up  
5.  
Sensitivity within the overall population after 5-year follow-up 
 
Secondary endpoints: 
1. Rate of initiation of cardiovascular treatments (in particular lipid-lowering) 
in the calcium score reporting group vs. the non-reporting group after year 1 of 
study. 
2. Efficiency of nodule management algorithms (LungRads1.1 + PanCan) will 
be evaluated according to  
 
The number of patients sorted in the category (a) “Next 
surveillance scan” AND  
 
The number of patients with lung cancer sorted into category (b) 
“early recall scan”, or (c) “diagnostic evaluation”.  
3. Success of screening program. Based on all individuals enrolled. Definition of 
success is calculated using: 

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Study ESR Code ESR-20-20770  
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a. Response rate (1. Respondents to questionnaire / invitation: those who send 
their smoking history & other relevant data; 2. among the above 
respondents, those who are eligible by one of the two criteria, or both; 3. 
those who are eligible, and actually take part in the screening), number of 
drop-outs, effectiveness of patient recruitment via mailings vs. GPs 
referrals (individual response rates) 
b. Reliability of PLCO risk scoring (self-reported vs. on site assessment) 
c. Percentage of subjects receiving an adequate low-dose CT scan and report 
according to DRG guidelines (number of diagnostic CTs/number of all CTs) 
d. Percentage of subjects receiving adequate follow-up procedures 
5. Quality of screening program  
a. CT reading performance (2nd reader vs. CAD vs. AI) 
b. Quality of lung nodule management 
c. Frequency of detection and management of incidental findings from low dose 
chest CT (emphysema, coronary heart disease, etc.) 
d. LDCT dose management 
6. Smoking cessation 
a. 
Success of smoking cessation counseling based on number of participants 
quitting with or without revealing additional health risks (emphysema 
score, coronary calcium score or both). 
7.  
Blood-based and exhalation- based biomarkers 
a. Evaluation of various blood-based or exhalation- based biomarkers in positive 
LDCT cases with subsequent biopsy on the positive predictive value of the LDCT test.
 
8. 
Cost-effectiveness analysis 
a. Main objectives of the modelling study are to investigate the impact of different 
components of LDCT lung cancer screening on the long-term all-cause mortality and 
cost-effectiveness. Key components include risk score-based selection criteria, nodule 
management protocols, threshold values of imaging biomarkers for cardio-vascular 
diseases and COPD, and inclusion of smoking cessation programs. (performed by 
Center for Health Economics Research Hannover (CHERH) 
b. Comparison of patient recruitment strategies: Cost-effectiveness of register-based 
mailing campaign vs. GP referrals in terms of recruitment of qualified screening 
subjects (CHERH). 
 
STUDY TYPE 
Population-based Screening Study - 
Prospective, randomized comparator controlled 
 
STATISTICAL   
ANALYSIS 
Primary analysis 
The primary and key-secondary endpoints of this study will be calculated from the 
following two fourfold tables summarizing the distribution of included patients and 
patients with detected lung cancer: 
 
 
 
 
 
 

Study Protocol 
Study ESR Code ESR-20-20770  
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Table 1 
Number of Participants by Screening Eligibility 
 
 
NELSON 
 
 
+ 
- 
PLCOm2012 
+ 
A 
B 
- 
C 
D* 
 
 
 
Table 2 
Number of detected lung cancers by Screening Eligibility 
 
 
NELSON 
 
 
+ 
- 
PLCOm2012 
+ 
a 
b 
- 
c 
d* 
Please note that * indicates volunteers with a low risk score, which are both PLCO 
and NELSON negative at inclusion. 
 
PPV NELSON = (a+c) / (A+C); PPV PLCO = (a+b) / (A+B). For testing the null-
hypothesis of equal PPVs for lung cancer detected in PLCOm2012-selected versus 
NELSON-selected individuals the weighted generalized score statistic developed by 
Kosinski will be used (20).  
 
Secondarily, the proportion of lung cancers detected will be calculated as 
prop_lung(PLCO) = (a+b) / (a+b+c+d*) and prop_lung(NELSON) = (a+c) / 
(a+b+c+d*) after a follow up period of 5 years. 
The proportion of individuals selected for screening will be calculated as 
prop_screening(PLCO) = (A+B) / (A+B+C) and prop_screening(NELSON) = (A+C) 
/ (A+B+C). 
 
Additionally, also the proportion of lung cancers detected in the identified high-risk 
population (PLCO or NELSON positive) will be calculated, using (a+b+c) as 
denominator and the proportion of individuals selected for screening within the low-
risk population will also be calculated using (A+B+C+D*) as a denominator. 
 
Specificities of the risk scores will be calculated after 5 years as spec(PLCO)=(C+D* 
– c-d)/(A+B+C+D* – a –b-c-d*) and spec(NELSON)=(B+D* – b-d)/(A+B+C+D* – 
a –b-c-d*). 
 
The primary and key-secondary endpoints will be compared between PLCO and 
NELSON in a hierarchical at a two-sided type-I-error of 5% to control the overall 
type-I-error at 5% (according to the hierarchy of endpoints outlined above). For testing 
the null-hypothesis of no difference between the risk scores regarding the proportion 
of lung cancers detected, McNemar’s Test will be used.  
 
 

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Description of the primary analysis and population: 
The primary analysis will be conducted of all volunteers within the overall study 
population including the low-risk population and the high-risk population. 
 
(i) 
Power calculation for the primary endpoint 
Sample size calculation is based on data from the German Health Update study 
(GEDA; “Gesundheit in Deutschland aktuell”) - a health monitoring program 
consisting of cross-sectional surveys conducted by the Robert Koch Institute to 
provide data on health and disease, health determinants and health behaviors from 
nationally representative samples of adults in Germany (20). Between 2008 and 2013, 
three GEDA studies were carried out, in 2008–2009, 2009–2010 and 2012–2013, 
involving a total of 62,606 computer assisted telephone interviews (23, 24). Based on 
this dataset the PLCO risk score was adjusted to a level (5-year risk of 1.314%, or 6-
year risk of 1.58% [rounded]) were the NELSON inclusion criteria and the PCLO risk 
score are equally weighted in the German population aged 55-79 to include the same 
amount of volunteers in each group  (table 3) 
 
Table 3: 
 
Number of ever smokers (predicted cancers) GEDA dataset (23, 24). 
Between parentheses are the 5-year case numbers predicted by the PLCO model.  
In a study by Hüsing & Kaaks (24) this model was found to accurately predict 
absolute lung cancer incidence compared to incidence actually observed (cancer 
registry data). 
However, for power calculations one cannot directly assume that predicted 5-year 
incidence corresponds to the number of LC cases that will be detected by two CT 
screenings over a 1-year interval. 
To estimate the number of expected CT-detected cases (two screens, 1-year interval) 
we extrapolated from observations in the LUSI trial. LUSI included participants 50-
69 years of age who met the smoking criteria of NELSON. In a total of 2029 
participants in the screening arm, 34 LC cases were detected in the first two 
screening rounds (22 at prevalence screen, and 12 at the first incidence screen).  
From GEDA data, using the PLCO model, we estimated that, compared to 
individuals who meet the inclusion criteria of LUSI (age 50-69, and smoking criteria 
identical as in NELSON) the (5-year) LC incidence is 1.72 times higher for 
individuals in the higher age range (55-79, + NELSON smoking criteria) chosen for 
the present study. 

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Study Protocol 
Study ESR Code ESR-20-20770  
Version: final 2.1 
Date 09-Feb-2021 
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For the present study, we thus estimated an expected overall number of CT-detected 
cases of 144:34 x 5000/2029 x 1.72 = 144 
We assume that these 144 CT-detected cases will be proportionally distributed as 
those in Table 3 (i.e., as with predicted 5-year incidence without screening). 
The numbers in Table 3 suggest that the PPV of the PLCO (risk-based, with 6-year 
risk threshold of 1.58%) will be 14% higher than the PPV of NELSON. 
For comparing positive predictive values from a paired diagnostic study, the weighted 
generalized score statistic proposed by Kosinski (20) will be used to test the Null-
hypothesis of the PPVs being equal for Nelson and PLCO.  
Using a two-sided type-I error rate of 5%, the power of the primary comparison was 
estimated with a simulation study based on the above described proportions. 
Assuming an overall number of 5000 patients who are selected by the Nelson or the 
PCLO criterion, and number of patients which are positive by Nelson or PLCO only 
are simulated as a realization of a multivariate variable with n=5000 and proportions 
(2857/5000, 1070/5000 and 1072/5000 respectively) as n_both, n_Nelson and 
n_PLCO. Subsequently, the number of cancers detected was calculated from 
independent Binominal variables for each of the following conditions.   
 
Number of cancers in the group of patients who are Nelson and PLCO positive: 
Bin(n_both, (144/149)*(112/2857)) 
Number of cancers in the group of patients who are Nelson positive and PLCO 
negative: Bin(n_Nelson, (144/149)* (10/1070)) 
Number of cancers in the group of patients who are Nelson negative and PLCO 
positive: Bin(n_PLCO, (144/149)* (27/1072)) 
 
The empirical power was estimated as the proportion of 10,000 simulation runs, where 
the weighted generalized score statistic (20) applied to the simulated data showed a p-
value smaller than 5%.  
 
Based on the above procedure, the estimated power to reject the null-hypothesis of 
equal PPVs between the NELSON and the PLCO score is 80,3%. 
 
For the HANSE study the calibrated  threshold for the PLCO 5 year risk score of 
1,314% was converted to a 6year threshold of 1,58% , because the original PLCO risk 
score calculates the 6year risk and thus the original calculators by Tammemägi et al. 
can be used for the HANSE study (13). For this conversion linearity between year 5 
and 6 was assumed. 
 
(ii) Sample size for the evaluation of initiation of cardiovascular therapy within 1 
year after randomization has been calculated using Chi-Square Test and two-sided 
type-I-error rate of 5% based on the results of the ITALUNG study (15,16), where for 
44% of all patients coronary artery calcification (CAC) was detected. In the 
ITALUNG study, 63% of patients with CAC were on cardiovascular treatment 
without receiving results of their low dose CT screening. For this study, where the 
patients are randomized to either reporting or non-reporting of CT screening results, 
we conservatively assume that the non-reporting group shows a rate of cardiovascular 
treatment of 68%. In contrast, as an effect of reporting the screening results, we 
assume that in the reporting group 73% of patients receive cardiovascular treatment, 
so the effect of reporting the CT results is assumed to be an increase of 5 percentage 

Study Protocol 
Study ESR Code ESR-20-20770  
Version: final 2.1 
Date 09-Feb-2021 
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points in the cardiovascular treatment rate. Acknowledging that only 44% of all 
patients are assumed to show CAC on low dose CT, the expected difference between 
the reporting and non-reporting group is (73%-68%) * 44% = 2.2%. Equivalently, the 
assumed rate ratio between the reporting and non-reporting group is (73% * 44*) / 
(68% *44%) = 1.07. With 2500 patients randomized to each arm and using a Chi-
Square Test with a two-sided type-I-error rate of 5% for testing the null-hypothesis of 
no difference between the groups, the statistical power is 97%.  
 
(iii) To evaluate the power of potential longitudinal follow-up studies based on this 
screening trial, the power for the 10 year mortality endpoint has been calculated based 
on the results of the NELSON study using a Chi-Square Test with a two-sided type-I-
error rate of 5% for testing the null-hypothesis of no difference in 10-year mortality 
rates between the reporting and non-reporting groups. In line with the results of the 
NELSON study, we assume a 10 year cardiovascular mortality rate in the non-
reporting group of 2.7%. 
Assuming a rate ratio of 0.6 between the reporting and non-reporting group (or 
equivalently, a 10-year mortality rate of 1.6%), the difference between the reporting 
and non-reporting group can be shown with a power of 75%.  
 
In order to include 5000 volunteers in the high-risk group in the HANSE study 5500 
need to be recruited to account for drop outs (10%). 
 
Conclusion: With an overall sample size of 5,000 subjects (and 2500 volunteers 
randomized to the reporting and non-reporting group) the study is well-powered 
to investigate the primary hypothesis, evaluate potential cardiovascular benefit 
and provide the basis to investigate mortality in a follow-up study. 
 
 
SAMPLE SIZE 
To be assessed for eligibility: n = 350 000 
To be allocated to trial:           n = 5500 + all recruited volunteers with low risk 
scores/low NELSON criteria (low risk group) 
To be analysed:                      n = 5000 + 7100 low risk group 
TRIAL DURATION 
First patient in to last patient out (months): 30 
Duration of the entire trial (months): 36 (longitudinal extension up to 10 years) 
Recruitment period (months): 12 
PARTICIPATING 
CENTERS 
n = 3 
Hannover Medical School (BREATH) 
Universitätsklinikum Schleswig-Holstein - Campus Lübeck (ARCN) 
LungenClinic Grosshansdorf gGmbH (ARCN) 
In the 1st and 2nd screening round CT imaging will be performed in a mobile CT 
scanner in a truck serving all 3 sites. 
RELEVANCE TO DZL 
With this flagship trial, the DZL is a key driver for implementation of a structured 
and cost-effective lung cancer screening program in northern Germany defining the 
high-risk population and including comorbidity assessment, a biomarker program 
and smoking cessation.  

Study Protocol 
Study ESR Code ESR-20-20770  
Version: final 2.1 
Date 09-Feb-2021 
14 
 
STUDY FLOW CHART 
 
 
 
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Study Protocol 
Study ESR Code ESR-20-20770  
Version: final 2.1 
Date 09-Feb-2021 
15 
AMENDMENT HISTORY 
Date 
Brief description of change 
Administrative Change / Amendment / 
New Protocol Version. 
15.09.2020
N/A 
Initial Protocol Version 1.0 
23.11.2020
Adjustment of study objectives after 
epidemiological review and related 
power calculation of primary endpoint 
Amendment Protocol Version 2.0 
09.02.2021
Administrative changes only: 
Additional clarifications for recruitment 
methods, potential sampling bias and 
biomarkers 
Amendment Protocol Version 2.1 
 

Study Protocol 
Study ESR Code ESR-20-20770  
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Date 09-Feb-2021 
16 
MILESTONES 
Date 
Milestone 
August 2020 
August 2020 
August 2020 
August 2020 
August 2020 
September 2020 
September 2020 
March 2021 
April 2021 
August 2023  
September 2023  
December 2023 
 
Final study protocol 
Contract Astra Zeneca 
Contract CRO  
Contract Coreline 
 
Contract truck/CT 
Ethics approval  
BfS application  
 
Study fully set-up   
 
 
Start of enrollment: First patient in 
Date of last data entry in database 
Date of Database Lock (Clean Database) 
Publication and Final report 
 
 
 

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Study ESR Code ESR-20-20770  
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Date 09-Feb-2021 
17 
1. 
BACKGROUND AND RATIONALE 
1.1 
Background 
Lung cancer caused more than 45,000 deaths in Germany in 2016, with 57,000 newly diagnosed 
cases. The death toll from lung cancer corresponds to 19.9% of deaths from all cancer combined, 
whereas the incidence of lung cancer is only 11.5% of all cancer cases (1).  Smoking (or a 
history of smoking) is the main risk factor, accounting for approx. 9/10 cases in men and 6/10 
cases in women. Although tobacco usage has declined in recent years in Germany, rates are still 
higher than in many other European countries (2).  
Consequently, lung cancer will continue to be one of the most important health issues in 
Germany with a massive impact on the health system in the years to come. When compared to 
other cancers, lung cancer has a particularly poor prognosis. Approx. 70% of patients are 
diagnosed at late stages - stage III or IV of the disease, when their 5-year survival is 16% and 
4% (3).  
At earlier stages, lung cancer is more amenable for curative treatment, thus prompting efforts 
to identify cancer at early stages by screening programs. However, initial screening trials using 
chest radiography have not led to a reduction in lung cancer mortality.  
More recently, a US landmark study (NLST) has shown that low-dose CT (LDCT) of the chest 
detected more nodules and cancers, including early-stage cancers than chest radiography, and, 
in particular, reduced mortality from lung cancer among the high-risk population (4).  
Since the first landmark study, however, several smaller European trials have provided 
inconclusive results in evidence that LDCT will lead to a reduced cancer or all-cause mortality 
(5, 6). Only recently, the LUSI study (5), and, in particular, the NELSON trial with more than 
15,000 participants (6) have shown convincingly that low-dose computed tomography (LDCT) 
screening may reduce lung-cancer mortality in a high-risk population.  
However, despite the high prevalence and associated high mortality, a national screening 
program for lung cancer has not been implemented in Germany. 
1.2 
Rationale 
Germany has a long history of offering screening programs for cancers, such as breast, 
colorectal, and, more recently, cervical and skin cancer. Screening for lung cancer, however, 
which causes more deaths than any other cancer in men and is the second leading cancer death 
in women (not far behind breast cancer), has not been implemented to date.  
Only very recently, IQWiG in a preliminary assessment of low-dose CT screening, concluded 
that the benefits from screening outweigh potential risks (7). However, an implementation of a 
national lung cancer screening program, which would be covered by the general health 
insurance, will likely not be implemented before 2022. Nonetheless, the IQWiG report also 
comments on important criteria for implementing lung cancer screening in Germany using low-
dose CT: 

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1. 
It would be necessary to determine criteria that define a high-risk population. Various 
risk forecasting models are currently being propagated to enable a more precise selection of 
high-risk individuals. Their reliability and repeatability needs to be checked. 
2. 
Integration of access to a smoking cessation program. 
3. 
Quality assurance measures must be taken into account, including standardized 
protocols for the evaluation of the CT images and the subsequent follow-up checks as well as 
the invasive diagnostic tissue sampling procedures. 
The HANSE study is primarily intended as a pilot to provide evidence that a holistic and 
effective lung cancer screening program can be implemented in Germany and that such a 
screening program can be integrated in the current infrastructure of certified lung cancer centers.  
The design of the HANSE study closely follows German and European recommendations for 
using risk scores to identify the population at greatest risk for lung cancer (8, 9, 10, 21). 
Moreover, HANSE will address one of the key questions concerning the most appropriate 
approach for recruiting and identifying the ‘true’ high-risk target population, which is crucial 
for the implementation of a cost-effective screening program (11, 12). To that end, HANSE is 
laid out specifically to address, whether NELSON inclusion criteria, or the PLCOM2012 risk 
model will prove more reliable in selecting the true high-risk patients for the screening program 
in the age group 55-79y (13). 
For the HANSE trial, 5,000 participants aged 55-79y who meet the NELSON and/or PLCOM2012 
6 year risk >1.58% selection criteria will be included. Participants will undergo baseline and 1-
year screening under defined conditions using low-dose computed tomography in three 
specialized lung cancer centers in northern Germany.  
Standardized and quality-assured image analysis will be conducted using state-of-the-art 
artificial intelligence (AI)-based detection and nodule measurement software (AVIEW, 
Coreline Soft Company Ltd., South Korea) to support the radiologist. CT assessment of lung 
nodules will be done according to LungRADS 1.1 criteria, as well as volume doubling time 
according to the European position statement on lung cancer screening (14). Additionally, this 
trial integrates different recruiting strategies, a smoking cessation counselling program, includes 
a cost-effectiveness modelling, cardiovascular and lung comorbidity assessment, different lung 
nodule management strategies (Lung RADS 1.1. vs. PanCan vs. AI) and explores blood-based 
biomarkers in positive LDCT cases. 
An additional objective of the HANSE study is to provide evidence for the potential of low dose 
CT in the diagnosis of diseases other than lung cancer, such as emphysema, but also cardio-
vascular diseases, which to date has only been suggested by retrospective analyses of LDCT 
studies (15, 16). Low dose CT does allow to examine the coronary calcium score (Agatston 
score (17)), indicative of the coronary plaque status which has shown to correlate with the rate 
of future myocardial infarction, stroke and death due to cardiovascular disease (18). The trial 
will assess whether reporting of the score may have consequences in individuals with a positive 

Study Protocol 
Study ESR Code ESR-20-20770  
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19 
coronary calcium score seeking specialist consultation and initiating preventive cardio-vascular 
therapy.  
The trial will further encompass a smoking cessation program and smoking cessation rate under 
the different experimental settings will be determined at 1-year follow-up. Specifically, the 
consequences on smoking status will be compared between the non-reporting group, the 
calcium score reporting group, the emphysema score reporting group vs. the non-reporting 
group in order to document a potential impact of reporting.  
Additionally, this design feature allows to analyse long-term smoking cessation rates and 
mortality in a follow-up study at year 5 and 10 (not part of this funding period). 
Besides that an extensive translational biomarker program with the assessment of potential 
predictive epigenetic signatures from blood samples and exhalation markers from exhalation 
samples in patients with positive findings on their LDCT scans will provide further insights 
about the potential predictivity of circulating and exhalatory markers for the early detection of 
lung cancer. In addition, blood samples will be collected optionally from the high-risk group at 
the 1st and 2nd screening round visit and stored in the DZL biobank for future research. 
Furthermore, the Center for Health Economics Research Hannover (CHERH) develops a 
comprehensive microsimulation platform for the assessment of long-term performance and 
cost-effectiveness of nationwide lung cancer screening with LDCT based on the HANSE study 
data. Main objectives of the modelling study are to investigate the impact of different 
components of LDCT lung cancer screening on the log-term all-cause mortality and cost-
effectiveness. Key components include risk score-based selection criteria, nodule management 
protocols, threshold values of imaging biomarkers for cardio-vascular diseases and COPD, and 
inclusion of smoking cessation programs.       
In order to be successful with the aim to implement a holistic structured lung cancer screening 
program in northern Germany an interdisciplinary team of expert physicians from pneumology, 
radiology, cardiology, thoracic surgery, oncology, pathology and epidemiology works together 
in three certified lung cancer centers. To succeed with the aim of recruiting 5,000 high risk 
persons for LDCT screening within 12 months the interdisciplinary team works together with 
an experienced CRO and call center to create an efficient workflow and infrastructure using 
state of the art information technology. To achieve a structured cutting edge radiologist reading 
workflow for LDCT reporting, specialized LDCT screening software is used including AI based 
automated coronary artery calcium scoring and emphysema quantification in addition to the 
lung nodule management tools. 
Taken together, HANSE is designed to address critical open issues concerning lung cancer 
screening programs, such as targeting and cost—effectiveness. In addition, inclusion of 
additional disease-related markers, such as the emphysema and coronary calcium scores will 
greatly enhance benefits of the screening program beyond lung cancer.   

Study Protocol 
Study ESR Code ESR-20-20770  
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2. 
OBJECTIVES AND HYPOTHESES 
2.1 
Primary Objective(s) & Hypothesis(es) 
Primary Objectives: 
 The primary goal of this study is to compare the efficiency of the PLCOM2012 >1.58% (6 year 
risk) risk score and the NELSON inclusion criteria in identifying patients with lung cancer in 
the age group 55-79 years. To that end, the PLCOM2012 model and the NELSON inclusion 
criteria will be compared  
(i) primarily regarding the positive predictive value of lung cancers detected using the two 
inclusion methods.  
 
2.2 
Secondary Objective(s) & Hypothesis(es)  
Key-Secondary Objectives: 
The PLCOM2012 model and the NELSON inclusion method will be compared 
(ii) secondarily to the primary objective regarding the following hierarchically ordered key-
secondary endpoints: 
1. Proportion of individuals selected for screening 
2. Proportion of lung cancers detected 
3. Sensitivity and specificity of the scores in cancer detection 
 
Secondary Objectives: 
The main secondary objectives of this trial is to document that: 
1. 
Reporting of the coronary artery calcium score from low dose computed tomography 
(LDCT) data will lead to an increase in the rate of preventive cardiovascular treatments and 
reduced cardiovascular mortality. 
 
Additional objectives are to show that: 
1. 
Effective smoking cessation counselling is implemented as part of the screening program 
(urine cotinine check in quitters). 
2. 
CT derived information on tobacco related lung destruction, such as emphysema, may 
influence the smoking cessation rate. 
3. 
Structured reporting of clinically relevant non-cardiac incidental findings, e.g., 
emphysema or lung fibrosis, will lead to early detection and improved management of diseases. 
4. 
Adding the PanCan algorithm/AI to the LungRads1.1 algorithm for nodule management 
increases the efficiency.  
5. 
Assessment of various blood-based or exhalation-based biomarkers may provide 
additional translational information in positive LDCT cases with subsequent biopsy, which may 
have an impact on the effectiveness of the LDCT test. 
6. 
Cost effectiveness analysis on recruiting strategies, risk models used, effectiveness on 
smoking cessation and cardiovascular mortality is implemented. 

Study Protocol 
Study ESR Code ESR-20-20770  
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3. 
METHODOLOGY 
3.1 
Study Design – General Aspects 
The HANSE study is a prospective, randomized comparator controlled population-based 
screening study. 
3.1.1 
Data Source(s) 
 
Low-dose CT: Presence and grade of lung nodules according to LungRADS 1.1 criteria; 
Coronary calcium scores (Agatston score); Percent lung emphysema (Coreline Software), 
clinically relevant incidental findings. 
 
Patient questionnaire.  
 
Results of blood sample and exhalation sample analysis in LDCT positive patients. 
 
Lung function test (bodyplethysmography and diffusing capacity of the lungs for carbon 
monoxide) 
 
BMI, blood pressure 
 
Urine cotinine test 
 
healthcare costs for the HANSE study 
 
All data will be collected in the HANSE electronic case report form (eCRF) 
3.2 
Study Population 
Male and female subjects age 55-79 years AND history of smoking. Population will be 
identified via local general population-based registries (“Einwohnermeldeämter”) and informed 
about the screening study by mail. The registries are general population based local registries 
(“Einwohnermeldeamt”), where all inhabitants in a region are registered by law. We requested 
Name, birthdate and address from the 3 participating cites (Hannover, Lübeck and Hamburg) 
in the age group 55-79. Additional recruitment efforts via local physicians (GPs, specialists) 
and campaigns targeting the general public. 
Mailed information package will contain a response element (paper) with questions concerning 
their smoking habits and history and link to study website. Interested individuals might either 
reply using the response element or input their data on the study website. Self-reported health 
data will be used to pre-qualify subjects based on PLCO / NELSON criteria.  
Subjects with preliminary PLCO risk-score 1.58% (6 years) or NELSON inclusion criteria 
will be invited to one of the study centers (high-risk group). On site, all subjects will undergo 
validation of their risk scores, additional examination of their medical condition, medical history 
and current medication by qualified personnel. Data will be stored in specially designed 
database (Clinical Research Organisation – CRO).  
Subjects, who did not meet the NELSON or PLCO criteria, will be asked to volunteer by 
contributing long-term outcome data, from regional and national cancer registries informing of 
the development of lung cancer or death from lung cancer (low-risk group).  
Subjects included will be randomized prior to the initial LDCT scan. Randomization will not 
affect the procedure of the lung cancer screening protocol but only determine the participants 

Study Protocol 
Study ESR Code ESR-20-20770  
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Date 09-Feb-2021 
22 
of the coronary calcium score and emphysema score reporting vs. non-reporting group. 
Randomization ratio of 1:1 and a 2-factorial design (¼ calc score only; ¼ emphysema score 
only, ¼ both; ¼ none) will provide equally sized groups of patients in the reporting and non-
reporting group. 
Randomization will be upheld for the one year CT screening round. Coronary calcium and 
emphysema scores of the subjects in the non-reporting group will remain confidential during 
the entire study duration (10 years). 
3.3 
Inclusion Criteria 
	 
Male and female subjects aged 55-79 years 

	 
Current or former smokers 
	 
Subjects with calculated risk score PLCO2012 1.58% (6 yrs.) or NELSON inclusion 
criteria (current or former smokers [those who had quit 10 years ago] who had smoked 
>15 cigarettes a day for >25 years or >10 cigarettes a day for >30 years). 
	 
Able and willing to give written informed consent 
Volunteers fulfilling all inclusion criteria are undergoing two low dose CT screening rounds 
(high-risk group). 
In addition, non-qualifying subjects fulfilling inclusion criteria 1 (age), 2 (smoking history) 
and 4 (consent), but do not meet the inclusion criterion 3 (risk too low) will be asked to 
volunteer by contributing long-term outcome data informing of the development of lung 
cancer or death from lung cancer (n=7100 randomly selected, low-risk group).  These 
subjects will be contacted via mail after a minimum of 5 year follow up to inquire if they 
developed lung cancer in the time between their recruitment and present. Non-responders 
will be followed by local registries and by phone. New lung cancer cases will be verified 
using official hospital or cancer registry documents. The 5 year follow up period was chosen 
to account for the lead-time bias between tumor and symptoms occurrence and cancer 
diagnosis in the low-risk group.  
 
3.4 
Exclusion Criteria 
	 
Comorbidity, which would unequivocally contraindicate either screening or treatment 
if lung cancer were detected.  

	 
History of chest CT within the past year preceding the invitation. 
	 
Inability to undergo non-contrast CT (e.g.  200 kg body weight, inability to lie flat). 
	 
Pregnancy 
	 
Risk of non-compliance with study procedures. 
 
Unable to give written consent 

Study Protocol 
Study ESR Code ESR-20-20770  
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Date 09-Feb-2021 
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Patient`s inability to fill in the questionnaire self-dependent 
 
Limited knowledge of the German language 
 
Inability to travel, residents of care facilities, etc. 
 
4. 
VARIABLES AND EPIDEMIOLOGICAL MEASUREMENTS 
4.1 
Exposures  
4.1.1 
Definition of Primary Exposure  
Recruited volunteers in the high-risk group undergo 2 low-dose CT screening rounds (baseline 
and 1 year follow up). 
4.1.2 
Definition of Comparison Exposure  
The low-risk group will not receive low-dose CT screening. They will be contacted after 5 years 
to inquire if they developed lung cancer in the time between their recruitment and present. Non-
responders will be followed by local registries and by phone. 
4.2 
Outcomes 
Primary endpoints: 
1. Proportion of lung cancers detected with different risk models 
To address the suitability of different inclusion methods for identifying the high-risk population 
for screening, the PLCOM2012 model and the NELSON inclusion criteria will be compared 
primarily for the positive predictive value of lung cancers detected within the study population 
after 2 screening rounds. 
 
Key-Secondary endpoints: 
Additionally, the PLCOM2012 model and the NELSON inclusion criteria will be compared in a 
hierarchical order regarding the key secondary endpoints: 
1.  
Proportion of individuals selected for screening within the high-risk study population 
2.  
Proportion of lung cancers detected with different inclusion methods (NELSON vs. 
 
PLCO) within the overall study population after 5 years 
3.  
Proportion of lung cancers detected within the high-risk population 
4.  
Sensitivity within the overall population after 5 years. 

Study Protocol 
Study ESR Code ESR-20-20770  
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5.  
Specificity within the overall population after 5 years. 
 
 
 
Secondary endpoints: 
6. Rate of initiation of cardiovascular treatments (in particular lipid-lowering) in the 
calcium score reporting group vs. the non-reporting group after year 1 of study. 
7. Efficiency of nodule management algorithms: Based on the two alternative management 
algorithms (LungRads1.1 alone or LungRads1.1 + PanCan/AI) participants are sorted into 
three management groups: (a) next surveillance scan, (b) early recall scan, or (c) diagnostic 
evaluation recommended. For one algorithm to be more efficient, the following criteria 
must both be fulfilled 
i. The number of participants without cancer sorted in the category (a) is higher AND 
ii. The number of participants with lung cancer sorted into category (b) or (c) is higher. 
8. Success of screening program. Based on all individuals enrolled. Definition of success is 
calculated using: 
a. Response rate (1. Respondents to questionnaire / invitation: those who send their smoking 
history & other relevant data; 2.among the above respondents, those who are eligible by  one of 
the two criteria, or both; 3. those who are eligible, and actually take part in the screening), 
number of drop-outs, effectiveness of patient recruitment via mailings vs. GPs referrals 
(individual response rates) 
b. Reliability of PLCO risk scoring (self-reported vs. on site assessment) 
c. Percentage of subjects receiving an adequate low-dose CT scan and report according to DRG 
guidelines (number of diagnostic CTs/number of all CTs) 
d. Percentage of subjects receiving adequate follow-up procedures 
9. Quality of screening program.  
a. CT reading performance (2nd reader vs. CAD vs. AI, positive predictive value) 
b. Quality of lung nodule management 
c. Frequency of detection and management of incidental findings from low dose chest CT 
(emphysema, coronary heart disease, etc.) 
d. LDCT dose management 

Study Protocol 
Study ESR Code ESR-20-20770  
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Date 09-Feb-2021 
25 
10. Smoking cessation 
a. Success of smoking cessation counseling based on number of participants quitting with or 
without revealing additional health risks (emphysema score, coronary calcium score or both). 
11. Blood-based and exhalation-based biomarkers 
a. Evaluation of various blood-based or exhalation-based biomarkers in positive LDCT cases 
with subsequent biopsy on the positive predictive value of the LDCT test: 
Liquid Biopsy: 
- 
Epigenetic Signature Profile from cell free DNA (currently 835 loci), a more specific 
description is possible after patent approval. 
Exhaled Breath Condensates: 
- 
RNA Analysis of the genes TUBA1A and HPRT, followed by analysis for GATA6 Em, 
GATA6 Ad, NKX2-1 Em, NKX2-Ad. 
12. Cost-effectiveness analysis 
a. Cost-effectiveness modeling to investigate the impact of different components of LDCT lung 
cancer screening on the log-term all-cause mortality and cost-effectiveness: Key components 
include risk score-based selection criteria, nodule management protocols, threshold values of 
imaging biomarkers for cardio-vascular diseases and COPD, and inclusion of smoking cessation 
programs (CHERH).       
b. Comparison of patient recruitment strategies: Cost-effectiveness of register-based mailing 
campaign vs. GP referrals in terms of recruitment of qualified screening subjects (CHERH). 
 
4.3 
Other Variables and Covariates 
Additional primary endpoint (longitudinal follow up, not part of this study - 
application for additional funding after successful completion of the 2nd screening 
round):  
1. All cause mortality rates and major adverse cardiovascular event (MACE: nonfatal 
stroke, nonfatal myocardial infarction, and cardiovascular death) rate in the reporting 
group vs. non-reporting group at year 5 and year 10. 
 
2. Long-term smoking cessation rates in the emphysema reporting group vs. non-reporting 
group at year 5 and year 10. 

Study Protocol 
Study ESR Code ESR-20-20770  
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Date 09-Feb-2021 
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5. 
STATISTICAL ANALYSIS PLAN 
5.1 
Statistical Methods – General Aspects 
5.1.1 
Primary and key-secondary Objective(s):   
The primary and key-secondary endpoints of this study will be calculated from the following two 
fourfold tables summarizing the distribution of included patients and patients with detected lung 
cancer: 
 
 
 

Study Protocol 
Study ESR Code ESR-20-20770  
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Date 09-Feb-2021 
27 
Table 1 
Number of Participants by Screening Eligibility 
 
 
NELSON 
 
 
+ 
- 
PLCOm2012 
+ 
A 
B 
- 
C 
D* 
 
Table 2 
Number of detected lung cancers by Screening 
Eligibility 
 
 
NELSON 
 
 
+ 
- 
PLCOm2012 
+ 
a 
b 
- 
c 
d* 
 
Please note that * indicates patients with a low risk score, which are both PLCO and LLP negative at 
inclusion. 
 
PPV 
PPV NELSON = (a+c) / (A+C); PPV PLCO = (a+b) / (A+B).  
 
Proportion of lung cancer detected 
Secondarily, proportion of lung cancers detected will be calculated as prop_lung(PLCO) = (a+b) / 
(a+b+c+d*) and prop_lung(NELSON) = (a+c) / (a+b+c+d*). 
 
Additionally, also the proportion of lung cancers detected in the identified high-risk population (PLCO 
or NELSON positive) will be calculated, using (a+b+c) as denominator and the proportion of individuals 
selected for screening within the low-risk population will also be calculated using (A+B+C+D*) as a 
denominator. 
Proportion of individuals selected for screening 
The proportion of individuals selected for screening (within the high-risk population) will be calculated 
as prop_screening(PLCO) = (A+B) / (A+B+C) and prop_screening(NELSON) = (A+C) / (A+B+C) . 
 
Specificity  
Specificities of the risk scores will be calculated as spec(PLCO)=(C+D* – c-d)/(A+B+C+D* – a –b-c-
d*) and spec(LLP)=(B+D* – b-d*)/(A+B+C+D* – a –b-c-d*). 
 
Sensitivity 
The sensitivities correspond to the proportions of lung cancer detected in the overall population. 
 
The primary and key-secondary endpoints will be compared between PLCO score and NELSON 
inclusion criteria in a hierarchical at a two-sided type-I-error of 5% to control the overall type-I-error at 
5% (according to the hierarchy of endpoints outlined above). As the primary analysis, for testing the 
null-hypothesis of no difference between the risk scores regarding the proportion of lung cancers 
detected, McNemar’s Test will be used.  

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Statistical testing 
For testing the null-hypothesis of equal positive predictive values, the weighted generalized score 
statistic developed by Kosinski et al. (20) will be used.  
For testing the null-hypothesis of no difference between the risk scores regarding the proportion of 
individuals selected for screening, McNemar’s Test will be used.  
 
Description of the primary analysis and population: 
The primary analysis will be conducted of all volunteers within the overall study population after 2 
LDCT screening rounds. 
 
5.1.2 
Secondary Objective(s):  Calculation of Epidemiological Measure(s) of Interest 
(e.g. hazard ratios, incidence rates, test/retest reliability) 
1. 
Rate/rate ratio of initiation of cardiovascular treatments (in particular lipid-lowering) in 
the calcium score reporting group vs. the non-reporting group after year 1 of study:  
2. 
Efficiency of nodule management algorithms: 
Based on the two alternative management algorithms (LungRads1.1 alone or LungRads1.1 + 
PanCan) patients are sorted into three management groups: (a) next surveillance scan, (b) early 
recall scan, or (c) diagnostic evaluation recommended. For one algorithm to be more efficient, 
the following criteria most both be fulfilled 
i. 
The number of patients without cancer sorted in the category (a) is higher AND 
ii. 
The number of patients with lung cancer sorted into category (b) or (c) is higher. 
3. 
Success of screening program. Based on all individuals enrolled. Definition of success 
is calculated using: 
a. 
Response rate (number of responses/overall number contacted), number of drop-outs, 
effectiveness of patient recruitment via mailings vs. GPs referrals (individual response rates) 
b. 
Percentage of subjects meeting all inclusion/exclusion criteria 
c. 
Repeatability of the PLCO score 
d. 
Percentage of subjects receiving an adequate low-dose CT scan according to DRG 
guidelines (number of diagnostic CTs/number of all CTs) 
4. 
Quality of screening program.  
a. 
CT reading performance (2nd reader vs. CAD vs. AI) 
b. 
Frequency of detection and management of incidental findings from low dose chest CT 
(emphysema, coronary heart disease, etc.) 

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c. 
Subsequent identification of biomarkers with predictive value / correlation with positive 
LDCT findings / cancer risk 
5. 
Smoking cessation 
a. 
Success of smoking cessation counseling based on number of participants quitting with 
or without revealing additional health risks (emphysema score, coronary calcium score or both). 
6.  
Blood-based and exhalation- based biomarkers 
a. Evaluation of various blood-based or exhalation- based biomarkers in positive LDCT cases 
with subsequent biopsy on the positive predictive value of the LDCT test. 
7. 
Cost-effectiveness analysis 
a. 
Cost-effectiveness modeling comparing screening costs and mortality benefits from 
lung cancer, cardiovascular and all-cause mortality (performed by Center for Health Economics 
Research Hannover (CHERH, DZL funding) 
b. 
Comparison of patient recruitment strategies: Cost-effectiveness of register-based 
mailing campaign vs. GP referrals in terms of recruitment of qualified screening subjects 
(CHERH, DZL funding). 
 
5.1.3 
Exploratory Objective(s):  Calculation of Epidemiological Measure(s) of 
Interest (e.g. hazard ratios, incidence rates, test/retest reliability) 
Additional primary endpoint (longitudinal follow up, not part of this study - application for 
additional funding after successful completion of the 2nd screening round):  
1. 
Mortality rates and major adverse cardiovascular event (MACE) rate in the reporting 
group vs. non-reporting group at year 5 and year 10 (not part of this funding period). 
2. 
Long-term smoking cessation rates in the emphysema reporting group vs. non-reporting 
group at year 5 and year 10 (not part of this funding period). 
 
 

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5.2 
Bias 
5.2.1 
Methods to Minimize Bias 
Randomization: Subjects included in the screening study will be randomized prior to receiving the 
initial LDCT scan. Randomization will not affect the procedure and the schedule of the cancer screening 
process but only determine the allocation of the participants of the coronary calcium score and 
emphysema score to the reporting and the non-reporting group. Randomization ratio of 1:1 and a 2-
factorial design (¼ calcium score only; ¼ emphysema score only, ¼ both; ¼ none) will provide equally 
sized groups of patients in both groups including age and sex stratification. 
Sampling bias: To minimize sampling bias we randomly select volunteers in the age group 55-
79 from the local general population registry database (“Einwohnermeldeämter”) to be 
contacted via mail at each study center. Additional recruitment efforts via GP or public media 
may introduce a sampling bias; however, this recruitment strategy reflects the real world setting 
of a future German national lung cancer-screening program. Additionally, we will track and 
analyze the recruitment pathways in the HANSE study. 
 
5.2.2 
Adjustment for Multiple Comparisons 
The primary end key-secondary endpoints will be tested in a hierarchical order, thereby 
controlling the overall type-I error rate at 5%. Therefore, no correction of p-values for multiple 
testing needs to be performed. All secondary parameters will be considered explorative.  
 
Strengths and Limitations 
Strengths 
Importantly, the results and the innovative workflow infrastructure of this study should pave the 
way for an effective comprehensive screening program in Germany. Especially, novel results 
about the definition of the high-risk population, the inclusion of cardiovascular and lung 
comorbidity, smoking cessation and cost-effectiveness will guide the future German lung cancer 
screening program. 
Limitations: 
This study is designed as a reference case for a nationwide lung cancer screening program, 
which both suffer from limitations.  The voluntary participation may introduce a certain bias 
and may not reveal all high-risk cases. In addition, clinically not apparent lung cancer cases in 
the low-risk population will be missed, since this group will not receive a LDCT. However, we 
follow-up smokers, who did not meet the risk score inclusion criteria and were willing to 
participate in the study, after 5 years to calculate the proportion of clinically detected lung 

Study Protocol 
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31 
cancers, which were missed due to non-inclusion in the high risk group. This will generate 
important data for the ethical and economical discussion of risk-based inclusion for lung cancer 
screening. 
The assessment of coronary calcium scores is usually performed on normal dose ECG-gated 
CT. However, recently it has been shown that coronary artery calcium scoring is feasible on 
non-ECG-gated LDCT. Furthermore, the used Coreline software has an innovative and fully 
automated algorithm especially developed for non-ECG gated Coronary calcium score on 
LDCT. 
Due to the 36 month time horizon of the study, the endpoint ‘initiation of cv treatment’ was 
selected, rather than a clinically more meaningful endpoint, such as 10 year cardiovascular 
mortality, for example. However, the investigators will seek additional funding to continue the 
coronary calcium part of the study in order to evaluate cardiovascular and all-cause mortality at 
year 10 follow-up. 
 
5.3 
Sample Size and Power Calculations 
To be assessed for eligibility: n = 350 000 
To be allocated to trial:           n = 5500 + all recruited volunteers with low risk scores/low 
NELSON criteria (low risk group) 
To be analysed:                      n = 5000 + 7100 low risk group 
 
(i) 
Power calculation for the primary endpoint 
Sample size calculation is based on data from the German Health Update study (GEDA; 
“Gesundheit in Deutschland aktuell”) - a health monitoring program consisting of cross-
sectional surveys conducted by the Robert Koch Institute to provide data on health and disease, 
health determinants and health behaviors from nationally representative samples of adults in 
Germany (20). Between 2008 and 2013, three GEDA studies were carried out, in 2008–2009, 
2009–2010 and 2012–2013, involving a total of 62,606 computer assisted telephone interviews 
(23, 24). Based on this dataset the PLCO risk score was adjusted to a level (5-year risk of 
1.314%, or 6-year risk of 1.58% [rounded]) were the NELSON inclusion criteria and the PCLO 
risk score are equally weighted in the German population aged 55-79 to include the same 
amount of volunteers in each group  (table 3) 
 
Table 3: 

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32 
 
Number of ever smokers (predicted cancers) GEDA dataset (23, 24). 
Between parentheses are the 5-year case numbers predicted by the PLCO model.  
In a study by Hüsing & Kaaks (24) this model was found to accurately predict absolute lung 
cancer incidence compared to incidence actually observed (cancer registry data). 
However, for power calculations one cannot directly assume that predicted 5-year incidence 
corresponds to the number of LC cases that will be detected by two CT screenings over a 1-
year interval. 
To estimate the number of expected CT-detected cases (two screens, 1-year interval) we 
extrapolated from observations in the LUSI trial. LUSI included participants 50-69 years of 
age who met the smoking criteria of NELSON. In a total of 2029 participants in the screening 
arm, 34 LC cases were detected in the first two screening rounds (22 at prevalence screen, and 
12 at the first incidence screen).  
From GEDA data, using the PLCO model, we estimated that, compared to individuals who 
meet the inclusion criteria of LUSI (age 50-69, and smoking criteria identical as in NELSON) 
the (5-year) LC incidence is 1.72 times higher for individuals in the higher age range (55-79, 
+ NELSON smoking criteria) chosen for the present study. 
For the present study, we thus estimated an expected overall number of CT-detected cases of 
144:34 x 5000/2029 x 1.72 = 144 
We assume that these 144 CT-detected cases will be proportionally distributed as those in 
Table 3 (i.e., as with predicted 5-year incidence without screening). 
 
The numbers in Table 3 suggest that the PPV of the PLCO (risk-based, with 6-year risk 
threshold of 1.58%) will be 14% higher than the PPV of NELSON. 
 
For comparing positive predictive values from a paired diagnostic study, the weighted 
generalized score statistic proposed by Kosinski (20) will be used to test the Null-hypothesis of 
the PPVs being equal for Nelson and PLCO.  
Using a two-sided type-I error rate of 5%, the power of the primary comparison was estimated 
with a simulation study based on the above described proportions. Assuming an overall number 
of 5000 patients who are selected by the Nelson or the PCLO criterion, and number of patients 
which are positive by Nelson or PLCO only are simulated as a realization of a multivariate 
variable with n=5000 and proportions (2857/5000, 1070/5000 and 1072/5000 respectively) as 

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*&

Study Protocol 
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33 
n_both, n_Nelson and n_PLCO. Subsequently, the number of cancers detected was calculated 
from independent Binominal variables for each of the following conditions.   
 
Number of cancers in the group of patients who are Nelson and PLCO positive: Bin(n_both, 
(144/149)*(112/2857)) 
Number of cancers in the group of patients who are Nelson positive and PLCO negative: 
Bin(n_Nelson, (144/149)* (10/1070)) 
Number of cancers in the group of patients who are Nelson negative and PLCO positive: 
Bin(n_PLCO, (144/149)* (27/1072)) 
 
The empirical power was estimated as the proportion of 10,000 simulation runs, where the 
weighted generalized score statistic (20) applied to the simulated data showed a p-value smaller 
than 5%.  
 
Based on the above procedure, the estimated power to reject the null-hypothesis of equal PPVs 
between the NELSON and the PLCO score is 80,3%. 
 
For the HANSE study the calibrated  threshold for the PLCO 5 year risk score of 1,314% was 
converted to a 6year threshold of 1,58% , because the original PLCO risk score calculates the 
6year risk and thus the original calculators by Tammemägi et al. can be used for the HANSE 
study (13).For this conversion linearity between year 5 and 6 was assumed. 
 
(ii) Sample size for the evaluation of initiation of cardiovascular therapy within 1 year after 
randomization has been calculated using Chi-Square Test and two-sided type-I-error rate of 5% 
based on the results of the ITALUNG study (15,16), where for 44% of all patients coronary 
artery calcification (CAC) was detected. In the ITALUNG study, 63% of patients with CAC 
were on cardiovascular treatment without receiving results of their low dose CT screening. For 
this study, where the patients are randomized to either reporting or non-reporting of CT 
screening results, we conservatively assume that the non-reporting group shows a rate of 
cardiovascular treatment of 68%. In contrast, as an effect of reporting the screening results, we 
assume that in the reporting group 73% of patients receive cardiovascular treatment, so the 
effect of reporting the CT results is assumed to be an increase of 5 percentage points in the 
cardiovascular treatment rate. Acknowledging that only 44% of all patients are assumed to show 
CAC on low dose CT, the expected difference between the reporting and non-reporting group 
is (73%-68%) * 44% = 2.2%. Equivalently, the assumed rate ratio between the reporting and 
non-reporting group is (73% * 44%) / (68% *44%) = 1.07.   With 2,500 patients randomized to 
each arm and using a Chi-Square Test with a two-sided type-I-error rate of 5% for testing the 
null-hypothesis of no difference between the groups, the statistical power is 97%.  
  
(iii) To evaluate the power of potential longitudinal follow-up studies based on this screening 
trial, the power for the 10 year mortality endpoint has been calculated based on the results of 
the NELSON study using a Chi-Square Test with a two-sided type-I-error rate of 5% for testing 
the null-hypothesis of no difference in 10-year cardiovascular mortality rates between the 

Study Protocol 
Study ESR Code ESR-20-20770  
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34 
reporting and non-reporting groups. In line with the results of the NELSON study, we assume 
a 10 year cardiovascular mortality rate in the non-reporting group of 2.7%. 
 
Assuming a rate ratio of 0.6 between the reporting and non-reporting group (or equivalently, a 
10-year mortality rate of 1.6%), the difference between the reporting and non-reporting group 
can be shown with a power of 75%.  
 
 
 

Study Protocol 
Study ESR Code ESR-20-20770  
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Date 09-Feb-2021 
35 
Conclusion: With an overall sample size of 5,000 subjects (and 2,500 volunteers 
randomized to the reporting and non-reporting group) the study is well-powered to 
investigate the primary hypothesis, evaluate potential cardiovascular benefit and provide 
the basis to investigate mortality in a follow-up study. 
 

Study Protocol 
Study ESR Code ESR-20-20770  
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Date 09-Feb-2021 
36 
6. 
STUDY CONDUCT AND REGULATORY DETAILS 
6.1 
Data Management 
6.1.1 
Study Flow Chart and Plan 
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Figure 1: Flow diagram of the HANSE study. 

Study Protocol 
Study ESR Code ESR-20-20770  
Version: final 2.1 
Date 09-Feb-2021 
37 
6.1.2 
Procedures 
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Figure 2: Procedure workflow of the Hanse Study 
1. Recruitment 
 
 Population will be contacted by mail (address data of individuals in the age group 
obtained from local population registries) with an individually tailored invitation 
letter and response element (paper and website) to assess their overall qualification and 
willingness to participate.  Additional recruitment efforts via local physicians (GPs), 
and via public media using the study website.  
Table 5: Variables for risk scoring, applicable for PLCO model 
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Study Protocol 
Study ESR Code ESR-20-20770  
Version: final 2.1 
Date 09-Feb-2021 
38 
 
Initial eligibility assessment based on self-reported data (age, smoking history and 
parameters required for the NELSON inclusion criteria and PLCO scores, table 5) in 
return letter, based on individuals’ input in study website, or according to GP 
assessment. Data of eligible subjects will be stored in CRO database. Eligible subjects 
(based on initial assessment of risk) will receive an invitation for participation in the 
screening program with additional background information. 
 
On site validation of variables required for risk scoring models and accompanying 
assessment of medical condition, medical history, current medication by qualified 
medical staff.  
 
Data will be stored in database (CRO) and PLCOM2012 risk score and NELSON 
inclusion criteria will be determined. Individuals with PLCOM2012 risk score 1.58% (6 
yrs.) or NELSON inclusion criteria will be included in the study.  
 
Non-qualifying subjects (who did not meet the NELSON inclusion criteria or PLCO 
criteria) will be asked to volunteer by contributing long-term outcome data informing 
of the development of lung cancer or death from lung cancer.  In addition NELSON 
and PLCO non-qualified subjects with a smoking history, who volunteered to 
participate in the HANSE study, will be contacted via mail after 5 years to inquire if 
they developed lung cancer in the time between their recruitment and present. Non-
responders will be followed by local cancer registries and by phone. 
2. LDCT - 1. Screening round 
 
Lung function test: All included participants will receive a lung function test prior to 
undergoing LDCT.  
 
Cardiovascular health: All participants will be questioned whether they receive 
treatment for any cardiovascular conditions. Blood pressure, heart rate and BMI data 
(height and weight) will be obtained.  
 
Assessment of current COPD treatment medication. 
 
Randomization: Subjects included in the screening study will be randomized prior to 
receiving the initial LDCT scan. Randomization will not affect the procedure and the 
schedule of the cancer screening process but only determine the allocation of the 
participants of the coronary calcium score and emphysema score to the reporting and 
the non-reporting group. Randomization ratio of 1:1 and a 2-factorial design (¼ 
calcium score only; ¼ emphysema score only, ¼ both; ¼ none) will provide equally 
sized groups of patients in both groups including age (5 year groups) and sex 
stratification . 
 
 

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Lung LDCT assessment:  
 
Standardized and quality-assured image analysis will be conducted using state-of-
the-art artificial intelligence (AI)-based detection and nodule measurement software 
(Coreline) to support the radiologist. CT assessment of lung nodules will be performed 
according to LungRADS 1.1 criteria (see Appendix), as well as volume doubling time 
according to the European position statement on lung cancer screening (14).  
 
Inspection of lungs for nodules will be carried out for all subjects, independent of the 
assigned groups (reporting or non-reporting).  
 
An independent 2nd read by an additional radiologist using the same reading software 
algorithm will be performed. 
 
Subjects with no nodules or those of LungRADS grades 1, 2, 3, 4a will be scheduled 
for follow-up scans at intervals according to LungRADS schedule (see Appendix).  
 
Findings categorized as LungRADS Cat. 4b or 4X nodules will be presented to the 
local Multidisciplinary Tumor Board (MDT) for further assessment and treatment 
decisions in the clinical routine workflow.  
 
Emphysema severity as a measure for tobacco related lung destruction will be 
quantitatively assessed on the LDCT images using the fully automated artificial 
intelligence (AI)-based algorithm of the Coreline software (Coreline, Seoul South 
Korea). The data will either be reported to study participants and treating physicians or 
not according to the allocation of the individual to the two randomized experimental 
groups.  
 
Coronary calcium scores (Agatston score) will be assessed using the fully automated 
artificial intelligence (AI)-based algorithm of the Coreline software (Coreline, Seoul 
South Korea). However, only the reporting group will receive the results of the score, 
together with an explanation of potential consequences of these findings for their 
cardiovascular health and with recommendation to seek specific consultation with their 
general practitioner or specialist. In this group a report is sent to the participants’ GP. 
 
The LDCT image data, the coronary calcium score and % emphysema of the non-
reporting group will remain confidential and will be stored for further assessment at 
year 1 (follow-up CT screen) and for evaluation of endpoints at year 5 and 10 (not part 
of this funding period). 
 
Apart from the randomized reporting of coronary artery calcium score and % 
emphysema clinically relevant incidental findings will be categorized in emergent 
(within 1-30 days),  timely (within 1-6 months) or regular (>6 months) follow up. They 
will always be included in the CT report for the study participants.  

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For emergent findings the study participant will be contacted directly by the local study 
team. 
 
Clinically non-relevant CT findings (i.e. liver or kidney cysts) not requiring physician 
consultation will not be included in the report. 
Smoking cessation program:  
 
Prior to obtaining the chest CT, all participants are counselled for smoking cessation and 
referred to a smoking cessation program, according to the requirements defined by the 
Joint Statement of the German Radiological Society. Specifically, participation in local 
certified smoking cessation programs such as “Das Rauchfrei Programm” 
(https://www.mhh.de/pneumologie/rauchfrei) is encouraged. In addition, an information 
brochure about smoking cessation and available local certified smoking cessation 
programs and further online information material will be given to each participant. 
Biomarker program: 
 
All patients undergoing tissue sampling according to the LungRADS 1.1. criteria will 
be invited to participate in the translational biomarker program using a separate 
informed consent form. For the program, a blood sample for epigenetic profiling will be 
required, together with an exhalation sample for assessment of specific exhalatory 
transition markers. The findings of the Biomarker analysis will be correlated to the 
pathological results of the radiological finding. The exact biomarkers will be determined 
before the study start and included in the appendix of the protocol. 
 
Optionally, blood samples will be collected from the high-risk group at the 1st and 2nd 
screening round visit and stored in the DZL biobank for future research. 
Long-term performance and cost-effectiveness: 
 
The Center for Health Economics Research Hannover (CHERH) develops a 
comprehensive microsimulation platform for the assessment of long-term performance 
and cost-effectiveness of nationwide lung cancer screening with LDCT based on the 
HANSE study data. Main objectives of the modelling study are to investigate the impact 
of different components of LDCT lung cancer screening on the log-term all-cause 
mortality and cost-effectiveness. Key components include risk score-based selection 
criteria, nodule management protocols, threshold values of imaging biomarkers for 
cardio-vascular diseases and COPD, and inclusion of smoking cessation programs.       
 
Model concept: The stochastic microsimulation model simulates virtual life histories of 
the HANSE study, which represents a representative sample of the German population 
in northern Germany. For each individual, it creates different life histories: no LC-
screening, LC-screening focussing on lung cancer only, LC-screening including 
cardiovascular and lung comorbidity assessment, comprehensive LC-screening plus 

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smoking cessation program. A team of clinical and health economic experts will define 
the detailed structure of the model.  
 
Outcome analyses: For each screening scenario, a Monte Carlo simulation (MCS) with 
1,000 iterations will be performed to estimate expected outcomes and MSC-based 
confidence intervals. Primary outcomes of the analysis are long-term all-cause mortality, 
additional costs per quality-adjusted life year (QALY) gained, per life year (LY) gained 
or per death averted. Efficiency frontiers will be constructed for each primary outcome 
to identify efficient screening scenarios and calculate the incremental cost-effectiveness 
of these scenarios. The impact of variations in the values of key input parameters 
(adherence to screening, smoking cessation etc.) on model outcomes will be tested in 
sensitivity analyses. 
Consequences of screening:  
 
All screened individuals will ask to participate in a ‘Consequences of Screening’ survey 
in order to evaluate their emotional and psychological condition during the screening 
process. Survey will be based on the psychological consequences questionnaire, adapted 
for lung cancer screening (19).  
 
In addition, the patient questionnaire will evaluate the socioeconomic background, 
smoking cessation, lung and cardiovascular health. 
 
The exact questions of the questionnaire will be determined before the study start and 
included in the appendix of the protocol. 
 
GP contact information is recorded. 
 
Current medication is recorded. 
 
3. LDCT 1 year - 2. Screening round 
 
Timing of the follow-up chest CT according to LungRADS 1.1 schedule. 
Chest LDCT scan procedure and image analysis as in the 1st screening round. 
 
Lung LDCT assessment: Assessment of newly identified lung nodules will be done 
according to LungRADS 1.1 criteria. Follow-up radiographic assessment of solid 
nodules will be based upon volume doubling time (VDT) as a key driver for 
recommendations on further course of action. 
 
Lung function test: All included participants will receive a lung function test prior to 
undergoing LDCT.  

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Cardiovascular health: All participants will be questioned whether they initiated 
treatment for any cardiovascular conditions during the study. Blood pressure, heart rate, 
and BMI data will be obtained.  
 
Additionally, the study is designed to analyze cardiovascular events and mortality in a 
follow-up study at year 5 and 10 (not part of the current funding period). 
 
Assessment of smoking status: Success of the smoking cessation program will be 
evaluated using a questionnaire, combined with a urine cotinine check (in quitters).  
 
Initiation of COPD treatment: Assessment of COPD treatment initiation during the 
study. 
 
Consequences of screening:  Questionnaire ‘Consequences of Screening’ as above. 
 

	 
Evaluation 
Lung cancer screening:  
 
The percentage of subjects receiving an adequate low-dose CT scan according to DRG 
guidelines will be assessed. 
 
For all included participants, detection rate of lung cancers will be evaluated and 
categorized according to LungRADS 1.1 categories.  
 
Detected (proven by histopathology) lung cancers will be categorized whether they 
were predicted by PLCO or NELSON or both. Statistical analysis will reveal potential 
advantages of either risk scoring methodology. 
 
A retrospective analysis will compare this algorithm to the PanCan nodule algorithm 
vs. AI for management efficiency. Based on the two alternative management 
algorithms patients are sorted into three management groups: (a) next surveillance scan, 
(b) early recall scan, or (c) diagnostic evaluation recommended. For one algorithm to 
be more efficient, the following criteria most both be fulfilled 
• The number of patients without lung cancer sorted in the category (a) is higher AND 
• The number of patients with lung cancer sorted into category (b) or (c) is higher. 
 
Coronary calcium score / cardio-vascular treatment initiation:  

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 
At the 1-year follow-up visit, the rate of initiation of cardiovascular treatment (in particular 
lipid-lowering) will be determined, together with BMI, and blood pressure data. Data for 
the calcium score reporting group will be compared to those of the non-reporting group.  
 
Smoking cessation:  
 
Success of smoking cessation counseling will be based on the number of participants 
quitting (% quitters) within study period. 
 
Allocation of the participants to the different experimental groups will allow 
determining the influence of ‘reporting’ of prognostic markers (percent emphysema 
and coronary calcium score) on smoking cessation. 
 
All methods will be performed according to study site SOPs. 
 
CT analysis software (Coreline) specifications: 
1. Viewer function 
- LCS (Lung Cancer Screening) viewer functions 
 Image display with axial, sagittal and coronal images and 3D rendering. 
 Virtual slice thickness control display function for MPR (Multi-Planar Reformat) images. 
 Semi-automatic nodule segmentation and measurement. 
 Follow-up nodule comparison, using automatic nodule position registration. 
 Quantitative feature calculation from the nodule segmentation. 
 Calculation of VDT (volume doubling time) and cancer-risk probability based on PANCAN 
model (Brock model). 
 Structured reporting UI based on Lung RADS v1.1, with incidental findings (S Modifier) 
(Can be modified to conform to German requirements) 
 Form-based report generation 
 
 

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- LAA (Lower Attenuation Area) viewer functions 
 Lobe-based quantitative emphysema analysis, such as LAA-950HU and Perc15. 
 Image display of axial, sagittal, coronal and 3D rendering, with LAA mask overlaid. 
 Bull’s eye chart for displaying LAA distribution in lobes, which are automatically segmented. 
 Histogram analysis of lung parenchymal densities. 
 Form-based report generation 
 
- CAC (Coronary Artery Calcification) viewer functions 
 Automatic calcification labeling and manual correction. 
 AGATSTON scoring and isotropic volume scoring. 
 Form-based report generation 
 
- Automatic processing server (APS) engines 
 Lung nodule detection engine (CADe, for research purpose only till CE certification) 
 Lung/lobe segmentation engine for automatic nodule position determination. 
 LAA analysis engine 
 CAC analysis engine 
 
- Worklist functions 
 Display the important results in separate columns; (Lung-RADS category, LAA-950HU, 
CAC, etc.) 
 Workflow management to enable double-reading capability. 
 Automatic notification of high-risk (critical) reading results. 
 Exporting results in CSV format (MS-Excel compatible) 
 

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2. Central registry function 
- Anonymization of uploaded patient data. 
- Web-based questionnaire (Specific requirements must be determined.) 
- Collects all the reading results in the CLOUD database. 
- CT dose management, using dose report from CT devices.  
- Dashboard view to display all participating hospitals’ information (charts and tables). 
 
3. Additional function support further research work 
- Radiomics feature generation from the segmented nodules. 
- Exporting all the collected information in CSV format (MS-Excel compatible). 
- Exporting nodule segmentation masks. 
- Interface with 3rd-party research modules, such as nodule malignancy estimation. 
 
4. Function be customized in the preparation phase of the HANSE study 
- German language support. 
- Customization to reflect German workflow. 
- Customization of structured reporting for incidental findings. 
- Development of web-based questionnaire system. 
- Development of nodule management system including dashboard 
- Interface with existing PACS, RIS and EMR 
 
6.1.3 
Quality Control 
Monitoring 
Offsite Monitoring using plausibility checks during data entry will be performed. 

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Training of Study Site Personnel 
All study personnel will be trained according to the study SOPs prior to the study start. 
 
6.1.4 
Storage and Retention 
Pseudonymized volunteer data will be stored in a password protected eCRF in a secure 
environment of the Alcedis Platform. Pseudonymized image data will be stored in a secure 
password protected cloud environment in Germany. Only the password secured Alcedis TRUST 
center has access to the clear name and the study pseudonym (Figure 2).  
 
Figure 3. 
For Image postprocessing and analysis the following Hybrid system from Coreline will be used 
(figure 3): 
- Workstations will be installed in each hospital. 
- All the DICOM CT images will be stored in the workstation of each hospital. 

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- Preprocessing, such as lung/lobe segmentation and nodule detection, will be done in each 
workstation. 
- Reading doctors access their images in the workstation through their web browsers. 
- Prior exams taken at a different hospital can be accessed (with one-click) in the follow-up 
mode from DICOM CT images in the CLOUD center. 
- All the reading results (reports) are stored in the workstation first. 
- All the reading results (reports) will be pseudonymized and uploaded to the secured CLOUD.  
- All the DICOM CT images will be uploaded to the CLOUD (Option 1). 
 
6.2 
Protection of Human Subjects 
This study will be performed in accordance with ethical principles that are consistent with the 
Declaration of Helsinki, ICH GCPs, GPP and the applicable legislation.  
For the study procedures a patient insurance will be obtained. Once the study participant enters 
the clinical routine, she/he is covered by the insurance of the hospital. 
6.2.1 
Subject Informed Consent 
Before documentation of any data, informed consent (DZL broad consent) is obtained by the 
patient in writing.  
An unconditional prerequisite for a patient participating in the study is his/her written informed 
consent. Adequate information must therefore be given to the subject by the investigator before 
informed consent is obtained. A person designated by the investigator may give the information, 
if permitted by local regulations. A patient information sheet in the local language will be 
provided for the purpose of obtaining informed consent. In addition to this written information, 
the investigator or his designate will inform the patient verbally. In doing so, the wording used 
will be chosen so that the information can be fully and readily understood by laypersons. 
The patient information sheet will be revised whenever important new information becomes 
available that may be relevant to the consent of patients.  
The written informed consent of the patient to participate in the clinical study has to be given 
before any study-related activities are carried out. It must be signed and personally dated by the 
patient and by the investigator / person designated by the investigator to conduct the informed 
consent discussion. Patients are also asked to give consent to additional analysis of tumor, blood 
or urine material. This approval is not a precondition for participation in the study. 

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Provision of consent will be confirmed in the CRF by the investigator. The signed and dated 
declaration of informed consent will remain at the investigator's site and must be safely archived 
by the investigator so that the forms can be retrieved at any time for monitoring, auditing and 
inspection purposes. A copy of the signed and dated information and consent should be provided 
to the subject prior to participation. 
At any time during or after the HANSE study a volunteer can withdraw from the study without 
any reason. In this case all collected study data will be deleted. 
 
6.2.2 
Confidentiality of Study/Subject Data 
All data collected in this study will be strictly confidential in accordance with all appropriate 
legislation. Access to the participant files will not be permitted to anyone other than the study 
staff, monitors and auditors. Only the study staff involved in data collection will know the 
identity of the participants. Study staff will be instructed to maintain complete confidentiality 
of all collected data. Patient files will be kept on secure servers. The study report will not contain 
any patient identifying information. Participants will be assigned a unique participant number 
to ensure confidentiality and anonymity. Interview transcripts will be identified by this unique 
participant number and will not have any identifiers associated with the individual. 
6.3 
Management and Report of Adverse Events/Adverse Drug Reactions 
6.3.1 
Definition of Adverse Events (AE) 
This is a population-based screening study without using medication. Low dose CT imaging 
will be conducted without use of contrast media, thus adverse drug reactions are not associated 
with the procedure.  Once tissue sampling is recommended by the CT results possible adverse 
events due to a lung biopsy for example are part of the clinical routine workflow. Any adverse 
event that may have been caused by the imaging procedure or any follow-up procedure during 
the study will be captured and documented in the eCRF. Finally, after closure of the study, all 
documented events will be summarized in a line listing by the investigator. 
6.3.2 
Definition of Serious Adverse Events (SAE) 
A serious adverse event is an AE occurring during any study phase (i.e., run-in, treatment, 
washout, follow-up), that fulfils one or more of the following criteria: 
• 
Results in death 
• 
Is immediately life-threatening 
• 
Requires in-patient hospitalisation or prolongation of existing hospitalisation  
• 
Results in persistent or significant disability/incapacity or substantial disruption of the 
ability to conduct normal life functions 

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• 
Is a congenital abnormality or birth defect 
• 
Is an important medical event that may jeopardise the subject or may require medical 
intervention to prevent one of the outcomes listed above. 
6.3.3 
Definition of Adverse Drug Reactions (ADR) 
An ADR is the development of an undesirable medical condition or the deterioration of a pre-
existing medical condition following or during exposure to a medicinal product, suspected to 
be causally related to the product. 
6.3.4 
Collection of Adverse Events 
Record all AEs with a fatal outcome in the eCRF. 
For each AE the following variables will be collected; 
• 
AE (verbatim) 
• 
The date when the AE started and stopped 
• 
Whether the AE is serious or not 
• 
Investigator causality rating against the medicinal product (yes or no) 
• 
Action taken with regard to medicinal product 
• 
Outcome 
It is important to distinguish between serious and severe AEs.  Severity is a measure of intensity 
whereas seriousness is defined by the criteria in Sections 6.3.1 to 6.3.3 above.  An AE of severe 
intensity need not necessarily be considered serious. For example, nausea that persists for 
several hours may be considered severe nausea, but not a SAE unless it meets one of the criteria 
shown in Section 6.3.2. On the other hand, a stroke that results in only a limited degree of 
disability may be considered a mild stroke but would be a SAE if it satisfies one of the criteria 
shown in Section 6.3.2. 
Any AE which is not required to be collected, as specified in the protocol, can be reported 
according to local regulations. 
Causality collection 
The Investigator will assess the causal relationship between study procedures and each Adverse 
Event, and answer ‘yes’ or ‘no’ to the question ‘Do you consider that there is a reasonable 
possibility that the event may have been caused by the study procedure?’ 
Time period for collection of adverse events 
Adverse Events will be collected from time of the 1st screening round visit and during any 
follow-up period specified in the protocol.  

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6.3.5 
Reporting of Adverse Events 
All SAEs will be reported, whether or not considered causally related to the study procedure(s). 
The reporting period for SAEs is the period immediately following the time that written 
informed consent until the end of the HANSE study (eCRF closure). The investigator is 
responsible for informing the Ethics Committee and/or the Regulatory Authority of the SAE as 
per local requirements. 
 
6.4 
Communication Plan 
The results of the study will be published in peer-reviewed journals shortly after study-
finalization, independently of a positive or negative overall study result. All scientifically 
involved participants of the study will be considered as authors in the respective trial 
publications according to the guidelines of the International Committee of Medical Journal 
editors (http://www.icmje.org/). 
Importantly, the results and the innovative workflow infrastructure of this study should pave the 
way for an effective comprehensive screening program in Germany. Especially, novel results 
about the definition of the high-risk population, the inclusion of cardiovascular and lung 
comorbidity, smoking cessation and cost-effectiveness will guide the future German lung cancer 
screening program. 
Outreach to the general public and smokers a study web presence will be designed and 
implemented during the first 3 months of project commencement and updated regularly and 
augmented via the use of social media. This public website will act as an information point for 
the work of the project providing details of all innovative, scientific, translational and 
socioeconomic aspects of the HANSE study, thus benefitting future studies in respiratory 
medicine, cardiology and oncology. Information will be communicated both on a general and a 
specialized level in order to specifically address different target groups. It is planned to link the 
site to patient smoking cessation groups and regional general practitioner networks. A leaflet 
including basic information about the project will be produced and used for both digital and 
printed communication/information material. The general public will also be addressed via 
publications/press releases, videos and social media. 
Targeted stakeholder information  
In order to enable a two-way dialogue with stakeholders on objectives and results of the 
HANSE-study, these will be presented to physicians at conferences such as the annual meetings 
of the Deutsche Gesellschaft für Hämatologie und Medizinische Onkologie, Deutsche 
Gesellschaft für Pneumologie, Deutsche Röntgengesellschaft. Importantly, the Gemeinsamer 
Bundesausschuss (GBA) will be approached with the results of the HANSE study in order to 
initiate and improve a national cost effective and holistic interdisciplinary lung cancer-screening 
program in Germany. 

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6.4.1 
Publication Plan 
2021 Study design paper 
2022 Radiology paper (s) 
2023 HANSE study paper, Cost effectiveness modelling paper 
 
6.4.2 
Compliance with Study Registration and Results Posting Requirements 
Study information from this study protocol will be posted on clinicaltrials.gov before enrolment 
of subjects begins. 
A permission to use LDCT in this study protocol will be obtained from the Bundesamt für 
Strahlenschutz (BfS). 
In Germany where reference to an Independent Ethics Committee (IEC) is required, 
documented approval from appropriate IECs will be obtained prior to study start. When 
necessary, an extension, amendment or renewal of the IEC approval must be obtained. 
6.4.3 
Compliance with Financial Disclosure Requirements 
All investigators will comply with the financial disclosure requirements. 

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7. 
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	 Lange C, Jentsch F, Allen J, Hoebel J, Kratz AL, von der Lippe E, et al. Data resource 
profile: German health update (GEDA)—the health interview survey for adults in 
Germany. Int J Epidemiol. 2015;44(2):442–50. https ://doi.org/10.1093/ije/dyv06 7. 

	 Hüsing A, Kaaks R. Risk prediction models versus simplified selection criteria to 
determine eligibility for lung cancer screening: an analysis of German federal-wide survey 
and incidence data. Eur J Epidemiol. 2020 Oct;35(10):899-912. doi: 10.1007/s10654-020-
00657-w. Epub 2020 Jun 27. 
 

Study Protocol 
Study ESR Code ESR-20-20770  
Version: final 2.1 
Date 09-Feb-2021 
54 
8. 
APPENDICES 
LungRADS 1.1 Classification system 
https://www.acr.org/-/media/ACR/Files/RADS/Lung-
RADS/LungRADSAssessmentCategoriesv1-1.pdf 

 
LungRADS 1.1 classification will be used, except for the “Growth” definition. Lung nodule 
growth in the HANSE study will be defined according to the NELSON study (6) as:1. Volume 
doubling time (VDT) < 400 days (positive) is suspicious for malignancy with further nodule 
workup as per MDT decision. 
2. VDT of 400-600 days (intermediate) results in repeat LDCT scan in 3 months. 
3. VDT>600 days: continue annual screening. 
 
9. 
ATTACHMENTS 
Patient information sheets / informed consent forms will be submitted as stand-alone 
documents. 
Patient questionnaires will also be submitted as stand-alone documents.