Prospective Randomized Controlled Trial to Evaluate Locally Implemented Large Language Models (LLMs) for Simplifying Patient Communication in Hematology and Oncology
Phase: NA
Conditions: Hematologic Neoplasms, Oncologic Disorders
Sponsor: Technical University of Munich

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oncOPAL — Oncology Optimized Patient-Accessible 
Language
Study Protocol
Prospective Randomized Controlled Trial to Evaluate Locally Implemented Large Language 
Models (LLMs) for Simplifying Patient Communication in Hematology and Oncology 
Date: 18.03.2026 
Version: 1.0 
Study Code: oncOPAL 
Principal Investigators 
Dr. med. Krischan Braitsch 
PD Dr. med. Lisa C. Adams 
TUM University Hospital (Klinikum rechts der Isar) 
Ismaninger Str. 22, 81675 Munich 
1  Protocol Synopsis 
Short Title 
oncOPAL 
Title 
Prospective Randomized Controlled Trial to Evaluate Locally 
Implemented Large Language Models (LLMs) for Simplifying Patient 
Communication in Hematology and Oncology 
Study Center 
TUM University Hospital (Klinikum rechts der Isar) 
Study Design 
Prospective, randomized controlled trial with parallel group design. 
Block randomization 2:1 (intervention : control) with permuted blocks of 
variable size (4–6). Additionally, a non-randomized translation arm for 
non-German-speaking patients. 
Study Population 
Inpatients of the Department of Medicine III (Hematology/Oncology) at 
TUM University Hospital who receive a discharge letter including the 
sections Current Status, Medical History, Epicrisis, and Further 
Management as part of routine clinical care. 
Rationale 
Up to 40–80% of medical information is not correctly recalled or 
understood by patients. LLMs can convert medical texts into plain-
language versions with high accuracy. However, prospective RCTs 
evaluating the clinical benefit of LLM-simplified patient synopses are 
lacking. 
Primary Objective 
To evaluate the superiority of LLM-generated, simplified patient 
synopses over standard synopses with respect to patient 
comprehension. 
Intervention 
Intervention group: The following sections of the discharge letter are 
simplified by the LLM system: Current Status, Medical History, 
Epicrisis, and Further Management. The patient receives the LLM-

 
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simplified version in addition to the standard synopsis (after physician 
review). Control group: Standard synopsis only. Translation arm: LLM-
simplified and translated synopsis of the same sections. 
Sample Size 
180 patients (150 randomized: 100 intervention, 50 control; 30 
translation arm) 
Primary Endpoint 
Comprehension score (5-item scale, 10-point Likert, based on PEMAT) 
Secondary Endpoints 
Patient satisfaction (EORTC QLQ-INFO25 subscales), uncertainty 
reduction, format preference, physician review workload, correction 
rate, translation quality 
Statistical Analyses 
t-test / Mann-Whitney U-test for primary endpoint; chi-squared / Fisher 
for categorical endpoints; multivariate regression adjusted for 
educational level and further covariates; ITT analysis. Analysis with R 
or SPSS. 
Study Duration 
12 months recruitment (April 2026 – March 2027), data analysis 
complete June 2027 
 
2  Rationale 
2.1  Background 
Communicating complex medical information to patients represents a central challenge in 
oncology. Studies show that up to 40–80% of the medical information conveyed during a 
physician consultation is not correctly recalled or understood by patients (Kessels 2003). 
This is particularly relevant in hematology and oncology, where complex treatment regimens, 
prognoses, and side-effect profiles must be communicated, making comprehensible written 
summaries especially important. 
 
Large language models (LLMs) have made substantial progress in processing and 
generating natural language over recent years. Current studies demonstrate that LLMs can 
translate medical technical texts into plain language with high accuracy (Jeblick et al. 2024). 
A systematic review by Ayers et al. (2023) showed that LLM-generated responses to patient 
questions were in some cases rated higher in quality and empathy than responses from 
physicians. 
 
Local implementation of LLMs (on-premise) enables the processing of sensitive patient data 
in compliance with the GDPR, as no data are transmitted to external servers. 
2.2  Derivation of the Research Question 
Despite promising results in retrospective analyses, prospective, randomized controlled trials 
evaluating the benefit of LLM-simplified patient synopses in routine clinical practice are 
lacking. The present study addresses this research gap. In addition, a non-randomized arm 
will evaluate the feasibility and quality of LLM translations for patients with insufficient 
German language proficiency. 
3  Study Objectives 
3.1  Primary Objective 
To evaluate the superiority of LLM-generated, simplified patient synopses over standard 
synopses with respect to patient comprehension in hematology and oncology. 

 
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3.2  Secondary Objectives 
• 
Assessment of patient satisfaction with the information received 
• 
Evaluation of the subjective reduction in uncertainty and anxiety 
• 
Assessment of patient preference for synopsis format 
• 
Measurement of the time required for physician review of LLM-generated synopses 
• 
Documentation of the rate of necessary physician corrections 
• 
Qualitative assessment of LLM translations by native-speaker reviewers 
3.3  Endpoints 
Primary Endpoint: 
Comprehension score of the patient synopsis, measured using a 5-item scale (10-point 
Likert, based on PEMAT). The score is calculated as the mean of five items: overall 
comprehension, comprehension of the diagnosis, the treatment, the next steps, and medical 
terminology. 
 
Secondary Endpoints: 
• 
Patient satisfaction (EORTC QLQ-INFO25 subscales) 
• 
Subjective uncertainty reduction (single item, 0–10 scale, measured before and after 
reading the synopsis) 
• 
Preference for synopsis format (categorical variable) 
• 
Health literacy as a covariate (HLS-EU-Q6) 
• 
Time for physician review (in minutes) and correction rate 
• 
Translation quality (rated by native-speaker reviewers, 5-point scale) 
3.4  Hypotheses 
H1: LLM-simplified patient synopses achieve a significantly higher comprehension score 
(difference of at least 1.5 points on the 10-point scale) compared to standard synopses. 
 
H0: There is no difference or a difference of less than 1.5 points between the groups. 
4  Study Procedures 
4.1  Study Design 
Prospective, single-center, randomized controlled trial with parallel group design. 
Randomization is performed in a 2:1 ratio (intervention : control) using a computer-generated 
randomization list with permuted blocks of variable size (4–6). An additional non-randomized 
translation arm is conducted for non-German-speaking patients. 
 
Blinding is not possible, as the intervention group receives an additional, visibly different 
synopsis. However, questionnaire evaluation is performed blinded to group assignment. 
4.2  Study Procedures 
Potential participants are identified during inpatient stays in the Department of Medicine III. 
Following verification of inclusion and exclusion criteria, informed consent is obtained in 
writing (with a reflection period of at least 24 hours). Randomization or assignment to the 
translation arm then follows. 
 

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Day 0 (as part of the regular hospital visit): 
•
Informed consent procedure (approx. 10–15 minutes)
•
Randomization or assignment to the translation arm
•
Preparation of the synopsis as part of routine clinical care
•
LLM simplification and physician review where applicable
•
Distribution of synopsis/synopses with at least 15 minutes reading time
•
Completion of the questionnaire (approx. 5–10 minutes)
No further study visits are planned. Study participation is complete upon submission of the 
questionnaire. 
4.3  Intervention 
Intervention Group: 
The following sections of the discharge letter are automatically converted into a plain-
language version by the locally implemented LLM system (GPT-OSS, on-premise): Current 
Status, Medical History, Epicrisis, and Further Management. A study physician reviews the 
LLM-generated synopsis for content accuracy and makes corrections as necessary. The 
patient receives the simplified version in addition to the standard synopsis. 
Control Group: 
The patient receives the standard synopsis only. 
Translation Arm: 
The specified sections of the discharge letter (Current Status, Medical History, Epicrisis, 
Further Management) are simplified by the LLM system and translated into the patient's 
native language. The translation is reviewed by a native-speaker reviewer. 
4.4  Technical Implementation 
The LLM system (GPT-OSS) is operated locally on servers at the Klinikum rechts der Isar 
(on-premise). No data are transmitted to external servers or cloud services. The system is 
not classified as a medical device and is used solely to support text simplification, not for 
diagnosis or treatment decisions. 
5  Criteria for Early Study Termination 
Individual Discontinuation: 
•
Withdrawal of consent by the participant
•
Subsequent identification of an exclusion criterion
Termination of the Entire Study: 
•
Decision by the principal investigators for scientific or organizational reasons
•
Request by the responsible ethics committee or supervisory authority
•
Unexpected, serious safety concerns
6  Study Population 
6.1  Inclusion Criteria 

 
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• 
Age 18 years or older 
• 
Inpatients of the Department of Medicine III (Hematology/Oncology) at TUM 
University Hospital 
• 
Receipt of a discharge letter including the sections Current Status, Medical History, 
Epicrisis, and Further Management as part of routine clinical care 
• 
Capacity to provide informed consent 
• 
Written informed consent following the consent procedure 
 
Additional Inclusion Criteria for the Translation Arm: 
• 
Insufficient German language proficiency 
• 
Native language supported by the LLM system (English, Turkish, Arabic, Russian, 
Polish, Spanish, Italian, French, Portuguese, Vietnamese, Chinese) 
6.2  Exclusion Criteria 
• 
Cognitive impairments that preclude independent assessment of comprehension 
(e.g., dementia, severe encephalopathy) 
• 
Participation in another study with potential influence on the endpoints 
• 
Lack of capacity to provide informed consent 
• 
Refusal to participate in the study 
6.3  Patient Recruitment 
Recruitment proceeds consecutively during inpatient ward rounds in the Department of 
Medicine III. Potential participants are identified by the treating medical staff. No recruitment 
materials such as flyers or notices are used. 
7  Data Protection and Data Security 
7.1  Informed Consent 
Study participation requires prior written informed consent. The consent procedure is 
conducted by a study physician. Participants are given a reflection period of at least 24 
hours. Consent may be withdrawn at any time without giving reasons and without any 
disadvantage to further treatment. 
7.2  Legal Basis 
The legal basis for processing personal data is informed consent pursuant to Art. 6(1)(a) and 
Art. 9(2)(a) GDPR in conjunction with § 27 BDSG. 
7.3  Data Collection and Storage 
Data collected include: demographic data (age, sex, educational level, native language), 
clinical baseline data (diagnosis, treatment setting), questionnaire data, and interview data 
where applicable. All study data are pseudonymized (study code oncOPAL-XXXX) and 
stored in a password-protected electronic database on servers of the Klinikum rechts der 
Isar. Data transmission is encrypted (TLS 1.3). 
7.4  Pseudonymization 
Each participant is assigned a unique alphanumeric study code. The mapping list is stored 
separately from the study data in an encrypted document. Access is restricted to the 
principal investigator and a designated deputy. All analyses are performed exclusively with 
pseudonymized data. 

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7.5  Data Disclosure 
Personal data are not disclosed to third parties. Publications use exclusively aggregated, 
anonymized data. Transfer of data to non-EU countries is not planned. 
7.6  Withdrawal and Data Deletion 
In the event of withdrawal, no further data are collected. Already collected data may be 
deleted upon request, provided they have not yet been incorporated into the analysis in 
anonymized form. After expiry of the retention period (10 years), all study data will be fully 
deleted and the mapping list destroyed. 
7.7  Access Control 
Access to study data is protected by individual user accounts with strong passwords and is 
logged. Servers are located in a secured data center with access control. 
8  Benefit-Risk Assessment 
The benefit-risk ratio is favorable. Participants in the intervention group and translation arm 
receive an additional plain-language synopsis that can promote understanding of diagnosis 
and treatment. Study participation involves minimal burden (additional time requirement of 
approximately 5–15 minutes). There are no physical risks. Psychological risks are low; the 
risk of possible misunderstandings arising from the simplified presentation is mitigated by 
mandatory physician review. Routine clinical care remains completely unchanged. 
9  Sample Size and Power Analysis 
The sample size calculation is based on the following assumptions: a clinically relevant 
difference in the primary endpoint of 1.5 points, an expected standard deviation of 2.5 points, 
power of 80%, significance level α = 0.05 (two-sided), a randomization ratio of 2:1, and an 
expected dropout rate of 10%. 
For a two-sided t-test for independent samples, the required sample size is n = 136 (91 
intervention, 45 control). Accounting for the dropout rate, n = 150 patients will be recruited 
for the randomized part. 
For the translation arm, n = 30 patients will be enrolled. This sample size permits a 
descriptive evaluation of feasibility without a formal statistical comparison. 
10  Funding 
The study is funded through internal resources of the Institute for Diagnostic and 
Interventional Radiology and the Department of Medicine III at TUM University Hospital 
(Klinikum rechts der Isar). There are no conflicts of interest. 
11  References 
1. Kessels RPC. Patients' memory for medical information. J R Soc Med. 2003;96(5):219-
222.
2. Jeblick K, et al. ChatGPT Makes Medicine Easy to Swallow: An Exploratory Case Study
on Simplified Radiology Reports. Radiology. 2024;308(1):e230618.

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3. Ayers JW, et al. Comparing Physician and Artificial Intelligence Chatbot Responses to
Patient Questions Posted to a Public Social Media Forum. JAMA Intern Med.
2023;183(6):589-596.
4. Arraras JI, et al. The EORTC QLQ-INFO25: A questionnaire to assess information given
to cancer patients. Eur J Cancer. 2010;46(15):2726-2738.
5. Basch E, et al. Overall Survival Results of a Trial Assessing Patient-Reported Outcomes
for Symptom Monitoring During Routine Cancer Treatment. JAMA. 2017;318(2):197-198.