Hematologic NeoplasmsoncOPALNCT07519811
LLM-Generated Plain-Language Patient Synopses to Improve Comprehension in Hematology and Oncology (oncOPAL)
A study testing LLM-Generated Plain-Language Patient Synopsis in people with Hematologic Neoplasms and Oncologic Disorders, run by Technical University of Munich at 1 site in Germany.
Trial summary
This study tests whether patients with blood cancer or other cancers better understand their medical information when it is rewritten in plain language by an artificial intelligence (AI) system. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Hematologic Neoplasms, Oncologic Disorders
- What is being tested?
- LLM-Generated Plain-Language Patient Synopsis
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 150 participants
- Where
- 1 siteGermany
- Study dates
- 1 Apr 2026to 1 Apr 2027
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Age 18 years or older
- Inpatient of the Department of Medicine III (Hematology/Oncology) at TUM University Hospital (Klinikum rechts der Isar), Munich, Germany
- 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
Who cannot join
- Cognitive impairment precluding independent assessment of comprehension (e.g., dementia, severe encephalopathy)
- Participation in another study with potential influence on the study endpoints
- Lack of capacity to provide informed consent
- Refusal to participate in the study
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Germany1 site, 1 recruiting
- Recruiting
Technical University Munich
Munich, Bavaria, 81675
About this study
Official title: Prospective Randomized Controlled Trial to Evaluate Locally Implemented Large Language Models (LLMs) for Simplifying Patient Communication in Hematology and Oncology
This study tests whether patients with blood cancer or other cancers better understand their medical information when it is rewritten in plain language by an artificial intelligence (AI) system.
When patients are discharged from the hospital, they receive a medical letter summarizing their diagnosis, treatment, and next steps. These letters are often written in technical language that is difficult for patients to understand. In this study, an AI language model running on the hospital's own secure servers rewrites parts of this letter into simpler language. A physician checks the simplified version before the patient receives it.
Read more
Patients are randomly assigned to one of two groups. One group receives both the standard medical letter and the AI-simplified version. The other group receives the standard letter only. A separate group of patients who do not speak German well will receive a simplified and translated version.
After reading their letter, all participants fill out a short questionnaire about how well they understood the information. The study takes place at TUM University Hospital (Klinikum rechts der Isar) in Munich, Germany.
Read the detailed description
Background:
Studies show that up to 40-80% of medical information conveyed during physician consultations is not correctly recalled or understood by patients. This problem is particularly relevant in hematology and oncology, where treatment regimens, prognoses, and side-effect profiles are complex. Large language models (LLMs) have demonstrated the ability to convert medical texts into plain language with high accuracy. However, prospective randomized controlled trials evaluating the clinical benefit of LLM-simplified patient synopses in routine care are lacking.
Study Design:
Prospective, single-center, randomized controlled trial with parallel group design. Randomization is 2:1 (intervention : control) using permuted blocks of variable size (4-6). An additional non-randomized translation arm enrolls patients with insufficient German language proficiency.
Intervention:
The locally implemented LLM system (on-premise, no external data transmission) automatically simplifies the following sections of the discharge letter: Current Status, Medical History, Epicrisis, and Further Management. A study physician reviews and approves the simplified version before it is given to the patient. The system is not classified as a medical device and is not used for diagnosis or treatment decisions.
Endpoints:
The primary endpoint is a comprehension score measured by a 5-item scale (10-point Likert, based on PEMAT), assessing overall comprehension and comprehension of diagnosis, treatment, next steps, and medical terminology. Secondary endpoints include patient satisfaction (EORTC QLQ-INFO25 subscales), subjective uncertainty reduction, format preference, physician review time, correction rate, and translation quality.
Statistical Analysis:
The primary endpoint will be analyzed using a t-test or Mann-Whitney U-test. A clinically relevant difference of 1.5 points on the 10-point scale is assumed. With a standard deviation of 2.5, power of 80%, and alpha of 0.05 (two-sided), 136 randomized patients are required (91 intervention, 45 control). Accounting for a 10% dropout rate, 150 patients will be recruited for the randomized arms, plus 30 for the translation arm (total n=180).
Data Protection:
All data are pseudonymized and stored on secure hospital servers. No patient data are transmitted to external servers or cloud services. The study complies with GDPR.
- Conditions
- Hematologic Neoplasms, Oncologic Disorders
- Being tested
- LLM-Generated Plain-Language Patient Synopsis
- Keywords
- Patient-Provider Communication, Patient Health Literacy, Large Language Model
- Medical subject headings
- Hematologic Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
LLM-Generated Plain-Language Patient SynopsisOther
A locally implemented large language model (GPT-OSS, on-premise) automatically rewrites selected sections of the hospital discharge letter (Current Status, Medical History, Epicrisis, and Further Management) into plain language. A study physician reviews the output for accuracy before it is provided to the patient. The system is not classified as a medical device and is not used for diagnosis or treatment decisions. No patient data are transmitted to external servers.
| Study group | Role | What they receive |
|---|---|---|
| Intervention: LLM-Simplified Synopsis | Experimental | Participants receive the standard discharge letter synopsis plus an
LLM-generated plain-language version of the following sections:
Current Status, Medical History, Epicrisis, and Further Management. The simplified version is reviewed and approved by a study physician before being given to the patient. Receives: Other: LLM-Generated Plain-Language Patient Synopsis |
| Control: Standard Synopsis | No intervention | Participants receive the standard discharge letter synopsis only, as provided in routine clinical care. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Patient Comprehension Score
Comprehension of the patient synopsis measured using a 5-item scale based on the Patient Education Materials Assessment Tool (PEMAT; scores range from 1 to 10, with higher scores indicating better comprehension), assessing overall comprehension and comprehension of diagnosis, treatment, next steps, and medical terminology. The score is calculated as the mean of all five items (range 0-10; higher scores indicate better comprehension).
Measured: At the time of hospital discharge (Day 0), assessed immediately after reading the synopsis (approximately 15-30 minutes after receipt)
Secondary outcomes (5)
Patient Satisfaction with Information Received
Patient satisfaction (European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire - Information Module 25 [EORTC QLQ-INFO25] subscales; scores range from 0 to 100, with higher scores indicating better-perceived information)
Measured: Day 0, assessed immediately after reading the synopsis
Subjective Uncertainty Reduction
Single-item measure on a 0-10 scale, administered before and after reading the synopsis
Measured: Day 0, before and after reading the synopsis
Patient Preference for Synopsis Format
Categorical variable assessing which synopsis format the patient preferred
Measured: Day 0, assessed immediately after reading the synopsis
Physician Review Time
Time in minutes required for the study physician to review and approve the LLM-generated synopsis
Measured: Day 0, recorded at time of physician review
Physician Correction Rate
Rate of necessary corrections made by the study physician to the LLM-generated synopsis prior to patient handout
Measured: Day 0, recorded at time of physician review
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted9 Apr 2026
- Study start1 Apr 2026
- Primary completion31 Dec 2026 (estimated)
- Study completion1 Apr 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Hematologic NeoplasmsStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Model description
- 2:1 block randomization (intervention : control) with permuted blocks of variable size (4-6). A separate exploratory translation component may be conducted for patients with insufficient German language proficiency, subject to operational feasibility. This component is non-randomized and descriptive only.
- Masking
- Single blind
- Who is masked
- Participant
- Enrolment
- 150 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Technical University of Munich
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07519811
- Sponsor's protocol ID
- oncOPAL-V1.0
- Acronym
- oncOPAL
- Status last verified
- Apr 2026
- First submitted
- 22 Mar 2026
- Last updated
- 16 Apr 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Individual participant data will not be shared. All study data are pseudonymized and stored on secure hospital servers at TUM University Hospital (Klinikum rechts der Isar) in compliance with the General Data Protection Regulation (GDPR). The study protocol does not provide for disclosure of participant-level data to third parties. Aggregate, anonymized data will be made available through publication of results.
Study at a glance
From the registry record, last updated by the sponsor on 16 Apr 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Prospective Randomized Controlled Trial to Evaluate Locally Implemented Large Language Models (LLMs) for Simplifying Patient Communication in Hematology and Oncology
- ClinicalTrials.gov ID
- NCT07519811
- Acronym / sponsor ID
- oncOPAL / oncOPAL-V1.0
- Conditions
- Hematologic Neoplasms, Oncologic Disorders
- Keywords
- Patient-Provider Communication, Patient Health Literacy, Large Language Model
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 150 participants (estimated)
- Lead sponsor
- Technical University of MunichUniversity, hospital or other
- Study start
- 1 Apr 2026 (actual)
- Primary completion
- 31 Dec 2026 (estimated)
- Study completion
- 1 Apr 2027 (estimated)
- First posted
- 9 Apr 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This study tests whether patients with blood cancer or other cancers better understand their medical information when it is rewritten in plain language by an artificial intelligence (AI) system.
When patients are discharged from the hospital, they receive a medical letter summarizing their diagnosis, treatment, and next steps. These letters are often written in technical language that is difficult for patients to understand. In this study, an AI language model running on the hospital's own secure servers rewrites parts of this letter into simpler language. A physician checks the simplified version before the patient receives it.
Patients are randomly assigned to one of two groups. One group receives both the standard medical letter and the AI-simplified version. The other group receives the standard letter only. A separate group of patients who do not speak German well will receive a simplified and translated version.
After reading their letter, all participants fill out a short questionnaire about how well they understood the information. The study takes place at TUM University Hospital (Klinikum rechts der Isar) in Munich, Germany.
Detailed description
Background:
Studies show that up to 40-80% of medical information conveyed during physician consultations is not correctly recalled or understood by patients. This problem is particularly relevant in hematology and oncology, where treatment regimens, prognoses, and side-effect profiles are complex. Large language models (LLMs) have demonstrated the ability to convert medical texts into plain language with high accuracy. However, prospective randomized controlled trials evaluating the clinical benefit of LLM-simplified patient synopses in routine care are lacking.
Study Design:
Prospective, single-center, randomized controlled trial with parallel group design. Randomization is 2:1 (intervention : control) using permuted blocks of variable size (4-6). An additional non-randomized translation arm enrolls patients with insufficient German language proficiency.
Intervention:
The locally implemented LLM system (on-premise, no external data transmission) automatically simplifies the following sections of the discharge letter: Current Status, Medical History, Epicrisis, and Further Management. A study physician reviews and approves the simplified version before it is given to the patient. The system is not classified as a medical device and is not used for diagnosis or treatment decisions.
Endpoints:
The primary endpoint is a comprehension score measured by a 5-item scale (10-point Likert, based on PEMAT), assessing overall comprehension and comprehension of diagnosis, treatment, next steps, and medical terminology. Secondary endpoints include patient satisfaction (EORTC QLQ-INFO25 subscales), subjective uncertainty reduction, format preference, physician review time, correction rate, and translation quality.
Statistical Analysis:
The primary endpoint will be analyzed using a t-test or Mann-Whitney U-test. A clinically relevant difference of 1.5 points on the 10-point scale is assumed. With a standard deviation of 2.5, power of 80%, and alpha of 0.05 (two-sided), 136 randomized patients are required (91 intervention, 45 control). Accounting for a 10% dropout rate, 150 patients will be recruited for the randomized arms, plus 30 for the translation arm (total n=180).
Data Protection:
All data are pseudonymized and stored on secure hospital servers. No patient data are transmitted to external servers or cloud services. The study complies with GDPR.
Study design
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (participant)
- Number of arms
- 2
- Model description
- 2:1 block randomization (intervention : control) with permuted blocks of variable size (4-6). A separate exploratory translation component may be conducted for patients with insufficient German language proficiency, subject to operational feasibility. This component is non-randomized and descriptive only.
| Arm | Type | Receives |
|---|---|---|
| Intervention: LLM-Simplified Synopsis | Experimental | Other: LLM-Generated Plain-Language Patient SynopsisParticipants receive the standard discharge letter synopsis plus an LLM-generated plain-language version of the following sections: Current Status, Medical History, Epicrisis, and Further Management. The simplified version is reviewed and approved by a study physician before being given to the patient. |
| Control: Standard Synopsis | No intervention | –Participants receive the standard discharge letter synopsis only, as provided in routine clinical care. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (5 listed)
- Age 18 years or older
- Inpatient of the Department of Medicine III (Hematology/Oncology) at TUM University Hospital (Klinikum rechts der Isar), Munich, Germany
- 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
Key exclusion criteria (4 listed)
- Cognitive impairment precluding independent assessment of comprehension (e.g., dementia, severe encephalopathy)
- Participation in another study with potential influence on the study endpoints
- Lack of capacity to provide informed consent
- Refusal to participate in the study
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| LLM-Generated Plain-Language Patient SynopsisA locally implemented large language model (GPT-OSS, on-premise) automatically rewrites selected sections of the hospital discharge letter (Current Status, Medical History, Epicrisis, and Further Management) into plain language. A study physician reviews the output for accuracy before it is provided to the patient. The system is not classified as a medical device and is not used for diagnosis or treatment decisions. No patient data are transmitted to external servers. | Other | Intervention: LLM-Simplified Synopsis |
Primary outcome
Patient Comprehension Score
Time frame: At the time of hospital discharge (Day 0), assessed immediately after reading the synopsis (approximately 15-30 minutes after receipt)
Comprehension of the patient synopsis measured using a 5-item scale based on the Patient Education Materials Assessment Tool (PEMAT; scores range from 1 to 10, with higher scores indicating better comprehension), assessing overall comprehension and comprehension of diagnosis, treatment, next steps, and medical terminology. The score is calculated as the mean of all five items (range 0-10; higher scores indicate better comprehension).
5 secondary outcomes
Patient Satisfaction with Information Received
Time frame: Day 0, assessed immediately after reading the synopsis
Subjective Uncertainty Reduction
Time frame: Day 0, before and after reading the synopsis
Patient Preference for Synopsis Format
Time frame: Day 0, assessed immediately after reading the synopsis
Physician Review Time
Time frame: Day 0, recorded at time of physician review
Physician Correction Rate
Time frame: Day 0, recorded at time of physician review
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 16 Apr 2026.
- Individual participant dataSharing planned: No. Individual participant data will not be shared. All study data are pseudonymized and stored on secure hospital servers at TUM University Hospital (Klinikum rechts der Isar) in compliance with the General Data Protection Regulation (GDPR). The study protocol does not provide for disclosure of participant-level data to third parties. Aggregate, anonymized data will be made available through publication of results.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing LLM-Generated Plain-Language Patient Synopsis in people with Hematologic Neoplasms and Oncologic Disorders, run by Technical University of Munich at 1 site in Germany.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 5 inclusion and 4 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 16 Apr 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Germany. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Krischan Braitsch, MD (+49 089 4140 1268, krischan.braitsch@tum.de), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Patient Comprehension Score (time frame: At the time of hospital discharge (Day 0), assessed immediately after reading the synopsis (approximately 15-30 minutes after receipt)). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 16 Apr 2026.