Replication Study to Analyze the Surgical Treatment of Proximal Humeral Fracture
Conditions: Proximal Humeral Fracture
Sponsor: University Hospital Muenster

 
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Replication study to analyze the surgical treatment of 
proximal humeral fracture 
 
Short Study Protocol 
Version 1.1 
Date: March 08, 2023 
 
Coordinating Investigators: 
Prof. Dr. med. J. Christoph Katthagen 
University Hospital Münster 
Klinik für Unfall-, Hand- und Wiederherstellungschirurgie 
Albert-Schweitzer-Campus 1, Building W1 
D-48149 Münster 
Dr. rer. nat. Jeanette Köppe, M. Sc.  
University of Münster 
Institute of Biostatistics and Clinical Research 
Schmeddingstraße 56 
D-48149 Münster 
Biostatistician:  
Karen Fischhuber, M.Sc. 
University of Münster 
Institute of Biostatistics and Clinical Research 
Schmeddingstraße 56 
D-48149 Münster 
 
 

 
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Signatures 
 
Coordinating Investigators 
 
Prof. Dr. med. J. Christoph Katthagen 
  
________________________________________
Place, date 
 
 
________________________________________ 
Signature 
 
Dr. rer. nat. Jeanette Köppe, M. Sc. 
________________________________________
Place, date 
 
 
________________________________________ 
Signature 
 
Biostatistician  
 
Karen Fischhuber, M. Sc. 
________________________________________
Place, date 
 
 
________________________________________ 
Signature 
 
 
 
 

 
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Table of Contents 
 ................................................................................................................................................................. 1 
1. 
Background of the Study ................................................................................................................. 4 
2. 
Population ....................................................................................................................................... 4 
2.1. 
Treatment Groups and study population cohorts ................................................................... 4 
3. 
Endpoints and Variables .................................................................................................................. 5 
3.1. 
Variables .................................................................................................................................. 5 
3.2. 
Endpoints ............................................................................................................................... 10 
3.2.1. Primary Endpoints ............................................................................................................... 10 
3.2.2. Secondary Endpoints ........................................................................................................... 10 
4. 
Statistical Methods ........................................................................................................................ 10 
4.1. 
Descriptive Statistics of Baseline Variables ........................................................................... 10 
4.2. 
Analysis of Primary Endpoints ............................................................................................... 10 
4.2.1 Short-term outcomes ........................................................................................................... 11 
4.2.1 long-term outcomes ............................................................................................................. 11 
4.3. Analyzing replicability ................................................................................................................. 11 
5. Treatment of Missing Values ............................................................................................................. 12 
6. Software ............................................................................................................................................ 12 
7. References ......................................................................................................................................... 12 
 
 
 

 
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1. Background of the Study 
Age-related fragility fractures are responsible for the loss of over one million quality-adjusted life years 
across Europe per year, and are thus ahead of stroke and chronic lung disease. In Europe, this results 
in annual treatment costs of more than 1 billion euros [1]. The proximal humeral fracture is the third 
most common age related fracture with an incidence of approx. 290 per 100.000 population years in 
elderly patients [2]. Within the last decades, an increase in the use of reverse total shoulder 
arthroplasty was observed (RTSA) [3]. However, to date, there is no consent about the optimal surgical 
treatment strategy, which is also due to the fact of missing evidence for different treatment options. 
Only a few randomized controlled trials (RTCs) comparing RTSA with an internal fixation using locked 
plate fixation (LPF; most common treatment) based small sample size are available, having partly 
contradictory results. Based on real world data (RWD) including more than 50,000 patients, two studies 
analyzing the outcome after both therapies are available in the literature.  
The study at hand aimed to analyze the replicability of the observed treatment effects in these studies 
published by Köppe et al. [3] and Stolberg-Stolberg et al. [4]. 
2. Population 
The German reimbursement system governs the remuneration of health care services subject to 
encoded diagnoses (International Statistical Classification of Diseases, German Modification; ICD-10 
GM) and procedures (German procedure classification – Operationen- und Prozedurenschluessel; OPS) 
by means of the  ‘German Diagnosis Related Groups’ taxonomy (GDRG). This obligatory documentation 
and accounting system is specified and further regulated in detail by mandatory coding instructions. 
The database consists of retrospective health claims data of the German BARMER health insurance 
company. This includes anonymized data from following sectors: 
- 
Inpatient data (§301 SGB V): In addition to information on costs, duration of hospitalization 
and information about treating hospital, standardized information on diagnoses (coded 
according to ICD-10 GM) and procedures (coded according to OPS) are available. 
- 
Outpatient data (§295 SGB V): In addition to information on costs, diagnoses (ICD-10 GM) and 
procedures (OPS). 
- 
Pharmaceutical therapies (§300 SGB V): Information on medication (coded via ATC 
classification), as well as costs and DDD (Defined Daily Dose). 
2.1. 
Treatment Groups and study population cohorts 
The study design is in accordance to the original study with patient selection and exclusion criteria as 
described in Köppe et al. [3]. Thus, within an index period from January 2011 to September 2022, all 
patients will be included, who had an inpatient coded treatment using LPF (OPS: 5-794.21, 5-794.k1) 
or RTSA (OPS: 5-824.21) and no exclusion criterion as given in table 1.  
Table 1: Exclusion criteria 
Exclusion Criteria 
Incomplete insurance status within two years before index 
Incomplete basic information 
Age<65 years 

 
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Missing diagnosis of PHF (ICD: S42.2) within two years before surgery 
Previous surgical treatment (RTSA, LPF or other fracture fixation) 
Coded polytrauma 
Bone tumors/ bone metastasis 
Both sides or missing information of surgery side 
COVID-19 infection during index hospitalization 
 
Patients were grouped into two treatment groups: LPF (reference group) or RTSA depending on 
which therapy was performed first. If RTSA and LPF were coded at the same day, patients were 
assigned to RTSA group. Two different analysis sets were defined as follows: 
• 
Short-term set: including all patients. 
• 
Long-term set: including all patients, which were discharged alive and had an index 
surgery before 2022 (to guarantee a possible follow-up time of a least one year). 
3. Endpoints and Variables 
3.1. 
Variables 
The following table lists all variables relevant to the analysis along with their ICD, OPS or ATC codes. 
For each patient, possible comorbidities will be recorded at baseline by including all outpatient and 
inpatient information coded within two years prior to the index event (index admission). The "minor 
outpatient complications" defined below (see the last two rows of the following table) will be based 
exclusively on outpatient information coded after discharge. All other variables will be collected 
exclusively from inpatient information. Corresponding data sources are additionally marked in the 
table and explained in the footnotes.  
Variable 
Classification Code 
Proximal humeral fracture 
ICD 
S42.2 
Multi-fragmented LPF 
OPS 
5-794.21, 5-794.k1 
RTSA 
OPS 
5-824.21 
Comorbidities at Baseline1 
Alcohol abuses 
ICD 
E24.4, F10, G31.2, G62.1, G72.1, I42.6, K29.2, K70, K85.2, 
K86.0, T51.0, T51.9 
Atherosclerosis  
ICD 
I70 
Atrial fibrillation and flutter 
ICD 
I48 
Bone tumor/metastasis 
ICD 
C40.0, C79.5, C79.86, C79.9 
Cancer 
ICD 
C 
Chronic kidney disease 
ICD 
N18, N19 
Chronic polyarthritis 
ICD 
M05, M06 
Congestive heart failure  
ICD 
I50 
Coronary heart disease  
ICD 
I25 
Dementia 
ICD 
F00, F01, F02, F051, G30, G31.1 
Diabetes mellitus 
ICD 
E10-E14 
                                                          
1 Data collection based on outpatient and inpatient information in the period of two years before the index 
surgery. Exception: Rotator cuff rupture. 

 
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Hypertension  
ICD 
I10-I15 
Infection 
ICD 
M86.01, M86.11, M86.21, M86.31, M86.41, M86.51, 
M86.61, M86.81, M86.91, T84.5, T84.6, T84.7 
Nicotine abuses 
ICD 
F17 
Obesity 
ICD 
E66 
Osteoporosis 
ICD 
M80-M85 
Parkinson 
ICD 
G20 
Polytrauma  
ICD, OPS, 
DRG 
ICD: T07, 
OPS: 5-982,  
or coded DRG started with “W” 
Rotator cuff rupture2 
ICD 
M75.1, S46.0 
Omarthrosis 
ICD 
M25.51 
Previous stroke 
ICD 
I60-I69 
Other fracture fixation  
OPS 
5-790.01, 5-790.11, 5-790.21, 5-790.31, 5-790.41, 5-790.51, 
5-790.61, 5-790.71, 5-790.81, 5-790.91, 5-790.d1, 5-790.m1, 
5-790.n1, 5-790.p1, 5-790.x1, 5-793.11, 5-793.21, 5-793.31, 
5-793.41, 5-793.51, 5-793.61, 5-793.71, 5-793.81, 5-793.91, 
5-793.a1, 5-793.b1, 5-793.c1, 5-793.g1, 5-793.k1, 5-793.m1, 
5-793.n1, 5-793.x1, 5-794.01, 5-794.11,5-794.31, 5-794.41, 5-
794.51, 5-794.61, 5-794.71, 5-794.81, 5-794.a1, 5-794.b1, 5-
794.c1, 5-794.g1, 5-794.m1, 5-794.n1, 5-794.x1, 5-824.00, 5-
824.01, 5-824.0x, 5-824.20 
Pharmaceutical therapy at baseline3 
Analgesics4 
ATC 
N02 
Antibiotics5 
ATC 
J01 
Any anticoagulant 
ATC 
B01AA, B01AB, B01AC, B01AE, B01AF, B01AX 
Vitamin D or calcium 
ATC 
A11CC 
Bisphosphonates 
ATC 
M05BA, M05BB 
Any osteoporosis 
pharmacotherapy 
ATC 
Vitamin D/Calcium or Bisphosphonates 
General Complications 
Acute liver failure 
ICD 
K72.0, K72.7, K72.9 
Acute myocardial infarction 
ICD 
I21, I22 
Acute renal failure 
ICD 
N17 
Acute respiratory distress 
syndrome 
ICD 
J80 
Cardiac arrest 
ICD 
I46 
Deep vein thrombosis 
ICD 
I80.1, I80.2, I82.2, I82.3 
Pulmonary embolism 
ICD 
I26 
Sepsis 
ICD 
A41, A40, B37.7, R65.0, R65.1, R65.9, R57.2 
Hemorrhagic stroke 
ICD 
I60-I62 
Ischemic stroke 
ICD  
I63-I64 
                                                          
2 If only coded during index hospitalization. 
3 Data collection based medication information in the period of two years before the index surgery. 
4 Only including 14 days before admission. 
5 Only including 14 days before admission. 

 
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Delirium 
ICD 
F05 
Resuscitation 
OPS 
8-77 
Need of intensive care unit 
OPS 
8-980, 8-98f 
Surgical complications  
Osteonecrosis 
ICD 
M87.21, M87.22, M87.32, M87.82, M87.92 
Vascular injury  
OPS 
5-388.11, 5-388.12, 5-395.11, 5-395.12, 5-397.11, 5-397.12 
ICD (only in-
hospital) 
S45.0, S45.1, S55.0, S55.1 
Nerve injury 
OPS 
5-040.1, 5-040.2, 5-040.3, 5-041.1, 5-041.2, 5-041.3, 5-044.1,  
5-044.2, 5-044.3, 5-045.1, 5-045.2, 5-045.3, 5-046.1, 5-046.2,  
5-046.3, 5-047.1, 5-047.2, 5-047.3, 5-048.1, 5-048.2, 5-048.3,  
5-049.1, 5-049.2, 5-049.3, 5-04b.1, 5-04b.2, 5-04b.3, 5-050.1,  
5-050.2, 5-050.3, 5-051.1, 5-051.2, 5-051.3, 5-052.1, 5-052.2,  
5-052.3, 5-053.1, 5-053.2, 5-053.3, 5-054.1, 5-054.2, 5-054.3,  
5-055.1, 5-055.2, 5-055.3, 5-056.1, 5-056.2, 5-056.3, 5-057.1,  
5-057.2, 5-057.3 
ICD (only in-
hospital) 
S44, G45.0, S14.3 
Joint damage / cartilage 
damage (LPF) 
OPS 
5-780.31, 5-784.51, 5-784.61, 5-800.80, 5-810.40, 5-812.00, 
5-812.30, 5-812.90, 5-812.a0, 5-812.e0, 5-812.f0, 5-812.g0, 
5-812.h0, 5-812.k0, 5-812.m0 
Upper limb amputation, 
ipsilateral (shoulder or 
upper arm) 
 
OPS 
 
5-862.1, 5-862.2 
Infection 
 
OPS 
 
5-780.41, 5-780.51, 5-780.61, 5-780.71, 5-780.81, 5-780.91, 
5-800.20, 5-800.30, 5-800.a0, 5-800.b0, 5-810.10, 5-810.70, 
5-810.80, 8-989, 8-989.0, 8-989.1, 8-989.2, 8-989.3, 8-989.4, 
8-989.5, 8-989.6 
ICD (only in-
hospital) 
T84.5, T84.6, T84.7, M86.01, M86.11, M86.21, M86.31, 
M86.41, M86.51, M86.61, M86.81, M86.91  
Haematoma after surgery 
ICD (only in-
hospital) 
T81.0 
Surgical incidents  
ICD (only in-
hospital) 
Y69!, Y84.9, Y82.8 
Consequences of injury of 
the upper extremity 
ICD (only in-
hospital) 
T92.1 
Secondary surgery, open 
(LPF) 
OPS 
5-780.01, 5-780.11, 5-780.21, 5-780.31, 5-780.61, 5-780.x1,  
5-782.11, 5-782.21, 5-782.31, 5-782.41, 5-782.51, 5-782.62, 
5-782.72, 5-782.82, 5-782.92, 5-782.a1, 5-784.01, 5-784.11,  
5-784.21, 5-784.31, 5-784.41, 5-784.51, 5-784.61, 5-784.71, 
5-784.81, 5-784.a1, 5-784.b1, 5-785.01, 5-785.11, 5-785.21, 
5-785.31, 5-785.41, 5-785.51, 5-785.61, 5-785.71, 5-789.b1,  
5-789.c1, 5-794.01, 5-794.11, 5-794.21, 5-794.31, 5-794.41, 
5-794.71, 5-794.81, 5-794.k1, 5-800.10, 5-800.30, 5-800.40, 
5-800.50, 5-800.70, 5-800.80, 5-800.90, 5-800.x0, 5-801.00, 
5-801.30, 5-801.40, 5-801.b0, 5-801.c0, 5-801.g0, 5-801.h0, 
5-801.k0, 5-801.m0, 5-801.n0, 5-801.p0, 5-805.0, 5-805.1, 
5-805.2, 5-805.3, 5-805.4, 5-805.5, 5-805.6, 5-805.7, 5-805.8, 
5-805.9, 5-805.a, 5-850.01,5-850.11, 5-850.21, 5-850.31, 

 
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5-850.41, 5-850.51, 5-850.61, 5-850.71, 5-850.81, 5-850.91, 
5-850.a1, 5-850.b1, 5-850.c1, 5-850.d1, 5-850.e1, 5-850.f1, 
5-850.g1, 5-850.h1, 5-850.j1, 5-850.x1, 5-851.11, 5-851.21, 
5-852.01, 5-852.11, 5-853.01, 5-853.11, 5-855.01, 5-855.11, 
5-855.21, 5-855.51, 5-855.61, 5-855.71, 5-855.81, 5-855.91, 
5-855.a1, 5-859.01, 5-859.11, 5-862.1, 5-862.2, 5-892.06, 
5-892.07, 5-892.16, 5-892.17, 5-896.06, 5-896.16, 5-896.26 
Secondary arthroscopy (LPF) 
OPS 
5-782.b1, 5-784.c1, 5-784.d1, 5-784.e1, 5-784.f1, 5-810.00, 
5-810.10, 5-810.20, 5-810.40, 5-810.50, 5-810.70, 5-810.80,  
Revision (LPF) 
OPS 
5-785.01, 5-785.11, 5-785.21, 5-785.51, 5-785.61, 5-785.71 
5-789.31, 5-78a.01, 5-78a.11, 5-78a.21, 5-78a.31,  5-78a.41, 
5-78a.51, 5-78a.61, 5-78a.71, 5-78a.90, 5-78a.c1, 5-78a.g1, 
Secondary arthroplasty (LPF) 
OPS 
5 824.0, 5 824.20, 5 824.21 
Arthrolysis (LPF) 
OPS 
5 800.60, 5 810.20, 5 810.90 
Decompression of 
subacromial space (LPF) 
OPS 
5 814.3 
Debridement (LPF) 
OPS 
5 819.10 
Secondary surgery, open 
(RTSA) 
OPS 
5-780.01, 5-780.11, 5-780.21, 5-780.31, 5-780.61, 5-780.x1, 
5-782.11, 5-782.21, 5-782.31, 5-782.41, 5-782.51, 5-782.62, 
5-782.72, 5-782.82, 5-782.92, 5-782.a1, 5-785.01, 5-785.11,  
5-785.21, 5-785.31, 5-785.41, 5-785.51, 5-785.61, 5-785.71,  
5-789.b1, 5-791.02, 5-791.12, 5-791.22, 5-792.02, 5-792.12, 
5-792.22, 5-792.k2, 5-800.10, 5-800.30, 5-800.40, 5-800.50, 
5-800.70, 5-800.80, 5-800.90, 5-800.x0, 5-850.01, 5-850.11, 
5-850.21, 5-850.31, 5-850.41, 5-850.51, 5-850.61, 5-850.71, 
5-850.81, 5-850.91, 5-850.a1, 5-850.b1, 5-850.c1, 5-850.d1, 
5-850.e1, 5-850.f1, 5-850.g1, 5-850.h1, 5-850.j1, 5-850.x1,  
5-859.01, 5-859.11, 5-862.1, 5-862.2, 5-892.06, 5-892.07,  
5-892.16, 5-892.17, 5-896.06, 5-896.16, 5-896.26 
Secondary arthroscopy 
(RTSA) 
OPS 
5-782.b1, 5-810.00, 5-810.10, 5-810.20, 5-810.40, 5-810.50, 
5-810.70, 5-810.80, 5-810.90, 5-811.20, 5-811.30, 5-811.40, 
5-814.b, 5-814.c, 5-814.d, 5-814.e, 5-819.00, 5-819.10,  
5-819.20 
Revision (RTSA) 
OPS 
5-785.01, 5-785.11, 5-787.01, 5-787.11, 5-787.21, 5-787.31, 
5-787.k1, 5-789.31, 5-78a.01, 5-78a.11, 5-78a.21,  5-78a.k1, 
5-810.40, 5-824.21, 5-825.00, 5-825.1 (only 2010-2012), 
5-825.21, 5-825.8, 5-825.k, 5-825.k0, 5-825.k1, 5-825.kx 
Resection arthroplasty (for 
spacer placement) 
OPS 
5 829.3 
Impingement 
ICD (only in-
hospital) 
M75.4 
Implant dislocation 
ICD (only in-
hospital) 
T84.10, T84.00 
Bursitis 
ICD (only in-
hospital) 
M75.5 
Compartment syndrome 
ICD (only in-
hospital) 
S41.86! 
Consequences of injury of 
the upper extremity 
ICD (only in-
hospital) 
T92.1 

 
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Minor outpatient 
complications (LPF) 6 
ICD 
G56.1, G56.2, G56.3, I80.80, I80.81, M00.01, M00.11, 
M00.21, M00.81, M00.91, M13.11, M13.81, M13.91, 
M19.11, M24.01, M24.11, M24.21, M24.41, M24.31, 
M24.51, M24.61, M25.11, M25.21, M25.31, M25.41, 
M25.51, M25.61, M25.71, M61.01, M62.21, M62.22,  
M62.41, M62.51, M62.61, M65.81, M65.91, M75.0, M75.1, 
M75.2, M75.4, M75.5, M84.21, M84.31, M86.01, M86.11, 
M86.21, M86.31, M86.41, M86.51, M86.61, M86.81, 
M86.91, M87.21, M87.22M87.31, M87.81, M87.91, M89.51, 
M96.6, T79.60, T84.10, T84.5, T84.6, T84.7 
Minor outpatient 
complications (RTSA) 7 
ICD 
G56.1, G56.2, G56.3, I80.80, I80.81, M00.01, M00.11, 
M00.21, M00.81, M00.91, M24.21, M24.41, M24.31, 
M24.51, M24.61, M25.11, M25.21, M25.31, M25.41, 
M25.51, M25.61, M25.71, M61.01, M62.21, M62.41, 
M62.51, M62.61, M65.81, M65.91, M75.0, M75.1, M75.2, 
M75.4, M75.5, M84.31, M86.01, M86.11, M86.21, M86.31, 
M86.41, M86.51, M86.61, M86.81, M86.91, M96.6, T79.60, 
T81.4, T84.5, T84.6, T84.7, T84.00 
Classification of complications  
General complications 
during hospital stay 
Myocardial infarction, thrombo-embolic events, acute renal failure, acute 
liver failure, ARDS, sepsis, delirium, need of intensive care, resuscitation 
Surgical complications 
during hospital stay 
Infection, bursitis, compartment syndrome 
Consequences of injury of the upper extremity, haematoma after surgery, 
impingement, implant dislocation, mechanical malfunction or material 
failure/loosening, peri-prosthetic or peri-implant fracture nerve injury, 
vascular trauma 
Implant-associated 
complications during 
hospital stay 
Impingement, bursitis, mechanical malfunction or material failure/loosening, 
peri-prosthetic or peri-implant fracture 
Non-implant associated 
complications during 
hospital stay 
Infection, infection with antibiotic-resistant germs, haematoma after surgery 
Major adverse event (MAE) 
resuscitation, cardiac arrest, myocardial infarction, stroke, acute renal 
failure, acute liver failure, acute respiratory distress syndrome, sepsis or 
death from any case 
Thromboembolic event 
Deep vein thrombosis, pulmonary embolism, ischemic stroke 
Surgical complications after 
discharge 
Adhesive capsulitis, arthrolysis, debridement, decompression of subacromial 
space, frozen shoulder, infection, infection with antibiotic-resistant germs, 
joint damage/cartilage damage, luxation, delayed union, non-union/ 
pseudoarthrosis, malunion, nerve injury, vascular injury, osteonecrosis, 
postoperative stiffness, secondary arthroplasty, secondary arthroscopy, 
secondary surgery (open) including revision surgery, upper limb amputation 
                                                          
6 Data collection exclusively based on outpatient information coded after discharge. 
7 Data collection exclusively based on outpatient information coded after discharge. 

 
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3.2. 
Endpoints 
The following two sub-chapters list the primary and secondary endpoints to be analyzed together 
with their definition. For more information, as well as underlying ICP, OPS and ATC codes, see 
Chapter 3.1. 
3.2.1. Primary Endpoints 
Variable  
Definition 
30-day mortality 
Death from any cause during the first 30-days after surgery. 
Overall survival (OS) 
- 
Time from discharge of index hospitalization to 
death of any case. 
- 
Death will be determined using the coded death as 
the reason for withdrawal in the BARMER database. 
In addition, all inpatient cases will be reviewed 
during follow-up, to determine whether death was 
reported as the reason for discharge. 
Major adverse events during index case 
See above, only events during hospitalization 
Major adverse events after discharge 
- 
Time from discharge of index hospitalization to MAE 
as defined above 
Thromboembolic events during index case 
See above, only events during hospitalization 
Thromboembolic events (or death) after 
discharge 
- 
Time from discharge of index hospitalization to a 
thromboembolic event or death of any case. 
Surgical complications during index case 
See above, only events during hospitalization 
Surgical complications after discharge 
- 
Time from discharge of index hospitalization to 
surgical complications, with death being considered 
as a competing risk event. 
3.2.2. Secondary Endpoints 
Implant-associated 
complication 
during 
index 
See above, only events during hospitalization 
Non-Implant-associated 
complication 
during index 
See above, only events during hospitalization 
Minor 
outpatient 
complications 
after 
discharge 
- 
Time from discharge of index hospitalization to 
minor outpatient complications, with death being 
considered as a competing risk event. 
4. Statistical Methods 
4.1. 
Descriptive Statistics of Baseline Variables 
Baseline variables as given by patients comorbidities, prior medications and general demographic data 
will be analyzed descriptively using absolute values and ratio for categorical variables and standard 
measures (median, mean, variance, 25%-quartile, 75%-quartile, minimum and maximum) for 
continuous variables).   
4.2. 
Analysis of Primary Endpoints 
To avoid bias due to differences in the distribution of insurance holders of both companies (BARMER 
cohort is older and had a higher proportion of women compared to German population), a propensity 
score matching (1:1) will be made to define the analysis set for all primary and secondary endpoints. 

 
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Matching will include year of surgery, sex, age at surgery and all listed comorbidities at baseline. Risk 
differences between treatment group (RTSA) and control (LPF), Z differences and sum of squared Z-
differences will be reported to evaluate the balance between both treatment groups. The dependence 
of the matching pairs will be considered via stratified analyses for all endpoints.  
4.2.1 Short-term outcomes 
For all endpoints, absolute number of complications and the proportion in percent will be determined 
and presented. Furthermore, a 95% Clopper-Pearson confidence interval will be estimated for the 
proportions. However, no tests will be performed for the univariate differences between LPF and RTSA. 
In accordance to the models presented in Köppe et al. [3], a multivariable logistic regression model 
including age, sex, year of surgery, treatment group, comorbidities at baseline and prior medication 
will be performed to determine treatment effect of the replication cohort. For short-term analysis, all 
patients will be included.  
4.2.1 long-term outcomes 
As stated above, long-term endpoints will only considered using long-term analysis set. Patients will 
be observed from discharge to the end of study. Only complete matching pairs will be included to the 
analysis, i.e. if one of the matching partners will be excluded due to in-hospital death, the related 
partner will be also excluded from long-term analysis. For all endpoints, event rates one and five years 
after discharge will be determined by cumulative incidence function using Aalen-Johansen estimate. 
Rates will be presented with related 95% confidence interval. Multivariable Cox regression models will 
analyze the impact of baseline variables on the endpoints. The resulting hazard ratios will be presented 
along with the related 95% confidence intervals. In the case of competing risks, cumulative incidence 
function determined by Aalen-Johansen estimate and sub-distributional hazards using Fine & Gray Cox 
models will be calculated. Multivariable models will include the treatment group, age, sex, year of 
surgery, comorbidities (listed in chapter 3.1), previous medications and in-hospital outcome 
parameter. Moreover, two time-dependent variables were included to account for COVID-19 
pandemic (variable one: represent the start of pandemic situation in Germany, variable two: coded 
COVID-19 infection). 
Moreover, as sensitivity analysis further analysis will be performed: 
- 
Considering a COVID-19 infection as a competing risk event for all long-term endpoints.  
- 
Using a subset of patients, given by those with an index surgery up to 2019 and an end of 
follow-up defined as 31.12.2019. 
4.3. Analyzing replicability 
To check the replicability of the observed treatment effects by Köppe et al. [3] and Stolberg-Stolberg 
et al. [4] the following agreements metrics will be analyzed: 
- 
Regulatory agreement (also known as two-trial rule): fulfilled, if original effect and replication 
effect have the same direction and the same significance. For an original null effect, the 
replication effect must also not have reached significance. 
- 
Analyzing standardized differences. 
- 
One-sided skeptical p-values [5]. 
- 
Meta-analysis: a meta-analysis using fixed-effects models will be performed. Even if the inter-
study heterogeneity is very high (with disjoint confidence intervals of the individual studies 
this is the case), a meta-analysis allowing random effects does not provide any useful insights. 
As the inter-study variance is calculated using only two studies (OES and RES), it leads to a very 

 
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high, uninformative dispersion of the estimate. The joint effect combing original effect size 
(OES) and replication effect size (RES) has to be significant to fulfill statistical agreement. For 
an original null effect, the joint effect must also not have reached significance. 
- 
Grade of replication as recommend by Errington et al. [6]: Five criteria will be checked and the 
grade of replication (0 – 5) will be presented. There are defined as: 
o Direction and significance: A null hypothesis is used to test, if the replication effect 
would unlikely occur under null. This property is equivalent to regulatory agreement. 
o RES is enclosed to the 95% CI of OES, also called estimated agreement. 
o OES is enclosed to the 95% CI of RES.  
o RES is enclosed to the 95% prediction interval. 
o Meta-analysis combing both is significant (or also not significant for original null 
effects). 
5. Treatment of Missing Values 
Missing values or inconsistent data in sex, day of birth, exit date of database lead to exclusion from 
study. Missing values are possible for the primary endpoint “30-day mortality”, since no information 
about death for patients with shorter follow-up period without event (censored within 30-days after 
surgery) will be available. Analysis will be made using all patients without missing values; an imputation 
will not be performed.  
For all other variables, no missing data will occur in the study, since all variables are defined by existing 
ICD/OPS or ATC codes. If no related code will be found, the according variable will be set to zero. Since 
the considered comorbidities are highly relevant for any imbursement, it is very unlikely that they are 
not coded in the database. However, there could be a bias by setting all the variables as known 
variables. 
6. Software 
All statistical analyses will be performed using SAS (SAS Enterprise Guide Version 8.3, SAS Institute 
Inc., Cary, NC, USA) and R version 4.2.1, R foundation, Vienna, Austria. 
7. References 
1 F. Borgström et al. Arch Osteoporos 15(1):59–21, 2020. 
2 M. Rupp et al.Dtsch Arztebl Int. 118(40):665-669, 2021. 
3J. Köppe et al. Clin. Orthop. Relat. Res. 479(10): 2284–2292, 2021. 
4 J. Stolberg-Stolberg et al. Dtsch. Arztebl. Int. 118(48): 817–823, 2021. 
5 L. Held: J. R. Statist. Soc. A 183 (2): 431–448, 2020.  
6 T.M. Errington et al. Elife. 10:e71601, 2021.