Prostate CancerNCT05923684
NLP-Based Feedback to Improve Risk Comms and Informed Shared Decision Making
A study testing NLP-based Feedback in people with Prostate Cancer, run by Cedars-Sinai Medical Center at 1 site in United States.
Trial summary
In this pilot study, the investigators will show feasibility of the NLP-based feedback system in 20 consultations of men with newly diagnosed prostate cancer. The investigators will recruit from the practices of up to 10 physicians who typically see these patients. Read more about this study
- Who is it for?
- Ages 18 years and older, men only
- Conditions the study is for
- Prostate Cancer
- What is being tested?
- NLP-based Feedback
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 30 participants
- Where
- 1 siteUnited States
- Study dates
- 15 Nov 2023to 15 Jul 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
- Men only
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Men undergoing initial treatment consultation for clinically localized prostate cancer;
- Men with upgraded prostate cancer on active surveillance considering conversion to definitive local therapy.
- Cedars-Sinai patient.
- Ability to read and write in English.
Who cannot join
- Under 18 years of age;
- Subjects with difficulty communicating or dementia;
- Non-English speakers, given that our NLP-based tools cannot be used with languages other than English;
- Men with locally advanced or metastatic prostate cancer;
- Men who have already been treated for clinically localized prostate cancer
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
United States1 site, 1 recruiting
- Recruiting
Cedars-Sinai Medical Center
Los Angeles, California, 90048
Timothy Daskivich, MD, 3104230415, timothy.daskivich@cshs.org
Antwon Chaplin, BA, 3102486790, antwon.chaplin@cshs.org
About this study
Official title: Natural Language Processing-Based Feedback to Improve Physician Risk Communication and Informed Shared Decision Making in Men With Clinically Localized Prostate Cancer
In this pilot study, the investigators will show feasibility of the NLP-based feedback system in 20 consultations of men with newly diagnosed prostate cancer. The investigators will recruit from the practices of up to 10 physicians who typically see these patients. The investigators will report the top five sentences from each consultation across key content areas (cancer prognosis, life expectancy, erectile dysfunction, urinary incontinence, and irritative urinary symptoms) to both patients and physicians within 2 weeks of the consultation.
Read the detailed description
The primary research procedures are:
- Audio recording and transcribing treatment counseling discussions for 20 men with newly diagnosed clinically localized prostate cancers and utilize NLP to extract key content using the system described above.
- Reports including the top five sentences by NLP probability for key content areas will be generated and will be provided to patients and providers within 2 weeks after each case.
- For patients, decisional conflict and risk perception will be assessed before and after receiving the NLP-based feedback.
- For physicians, the investigators will assess baseline quality of risk communication, any changes in individual physician communication over time, and accuracy of risk estimates for key content areas.
- Within 2 weeks of receiving the NLP-based feedback, the investigators will conduct a 30-minute semi-structured interview with patients to obtain their opinions on the utility and ideal implementation strategy for the NLP-based feedback.
- At the conclusion of the pilot trial, the investigators will conduct 30-minute semi-structured interview with counseling physicians to obtain their opinions on the utility and ideal implementation strategy for the NLP-based feedback.
- Conditions
- Prostate Cancer
- Being tested
- NLP-based Feedback
- Keywords
- prostate, cancer, consultation, review, feedback, natural, process
- Medical subject headings
- Prostatic Neoplasms, Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
NLP-based FeedbackBehavioural
Audio recordings will be made using either digital recorders or telehealth platform-generated transcripts. Patient reports will include only the extracted sentences related to content areas. Physician reports will note the extracted statements across each content area, the quality scores for individual statements based on the pre-specified hierarchy, the statements that achieved the highest score across each content area, and feedback on what could be improved. For patients, decisional conflict and risk perception will be assessed before and after receiving the NLP-based feedback. For physicians, the investigators will assess baseline quality of risk communication by pre-specified hierarchy, any changes in individual physician communication over time, and accuracy of risk estimates for key content areas.
| Study group | Role | What they receive |
|---|---|---|
| NLP Intervention Experimental Arm | Experimental | 20 men with newly diagnosed clinically localized prostate cancers and utilize NLP to extract key content using the top five sentences by NLP probability for key content areas will be generated and will be provided to patients and providers within 2 weeks after each case. Receives: Behavioral: NLP-based Feedback |
What is being measured
The primary outcome is the main question the study is designed to answer.
Change in Decisional Conflict Scale Scores before and after intervention (patient-level outcome)
The investigators will employ the validated Decisional Conflict Scale (DCS), to estimate uncertainty associated with treatment choice. Effect sizes of 0.3 to 0.4 are considered meaningful. Variability (standard deviation) in DCS scores before and after receiving NLP-based feedback will be assessed and used in planning a larger trial.
Measured: Measured directly after treatment consultation and after NLP-based feedback given to patients within 2 weeks of consultation
Change in risk perception before and after intervention (patient-level outcome)
The investigators will evaluate concordance of cancer risk perception with actual cancer risk at the patient level before and after the intervention. Cancer risk perception will be assessed by multiple-choice questions. Concordance of patient answers with actual cancer risk as estimated by outcomes of the SPCG-4 randomized trial comparing surgery versus watchful waiting at the patient's PCCI-predicted life expectancy will be assessed as a binary outcome. Risk perception will be assessed before and after their consultation. Variability (standard deviation) in risk perception scores before and after receiving NLP-based feedback will be assessed and used in planning a larger trial.
Measured: Measured directly after treatment consultation and after NLP -based feedback given to patients within 2 weeks of consultation
Physician attitudes regarding integration of NLP-based information (physician-level outcome)
30-minute semi-structured interviews with counseling physicians will be conducted within 2 weeks of the intervention to obtain their opinions on the utility and ideal implementation strategy for the NLP-based feedback.
Measured: Interviews will be conducted within 2 weeks of the intervention.
Difference between reported risk of side effects and prognosis with gold standard (physician-level outcome)
The difference in reported risk estimates given by physicians during the consultation as compared with the gold standards for these risks (i.e. for side effects, estimates from the CAESAR study; for cancer risk with and without treatment, risks of cancer mortality in the WW group of SPCG-4 trial at the patient's life expectancy as determined by the prostate cancer comorbidity index). Variability (standard deviation) in accuracy of estimates will be assessed and used in planning a larger trial. Accuracy of estimates for the interventional period will be compared with physician-specific historical references from a previously conducted trial using the standard of care (i.e. no NLP-based intervention).
Measured: Data will be captured during the treatment consultation-for the duration of the study up to 1 year
Quality of composite physician risk communication score in treatment consultation (physician-level outcome)
Quality of risk communication scores will be calculated by qualitatively analyzing treatment consultation transcripts to assess the highest quality of communication used to transmit information regarding all key tradeoffs (cancer prognosis, life expectancy, erectile dysfunction, urinary incontinence, and irritative urinary symptoms). The quality of risk communication scale ranges from 0 to 5 for each outcome, with 0 representing the lowest score and 5 representing the highest score (Daskivich et al, J Urol 2022; Naser-Tavakolian et al, J Urol 2022). Scores for all key tradeoffs will be averaged to yield a composite quality of risk communication score. Variability (standard deviation) in quality scores will be assessed and used in planning a larger trial.
Measured: Data will be captured during the treatment consultation, for duration of the study up to 1 year
Patient attitudes regarding integration of NLP-based information
30-minute semi-structured interviews with patients will be conducted at the conclusion of the study period to obtain their opinions on the utility and ideal implementation strategy for the NLP-based feedback
Measured: within 4 weeks of patients using NLP system.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted28 Jun 2023
- Study start15 Nov 2023
- Primary completion15 Jul 2027 (estimated)
- Study completion15 Jul 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Prostate CancerStudies 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
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 30 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Cedars-Sinai Medical Center
- Sponsor type
- University, hospital or other
- Collaborators
- National Cancer Institute (NCI)
- Responsible party
- Principal investigator, Timothy J. Daskivich, Cedars-Sinai Medical Center
- Investigators
- Timothy Daskivich, Principal investigator, Cedars-Sinai Medical Center
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05923684
- Sponsor's protocol ID
- STUDY00002590
- Other IDs
- K08CA230155
- Status last verified
- Jul 2026
- First submitted
- 24 May 2023
- Last updated
- 12 Aug 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 12 Aug 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Natural Language Processing-Based Feedback to Improve Physician Risk Communication and Informed Shared Decision Making in Men With Clinically Localized Prostate Cancer
- ClinicalTrials.gov ID
- NCT05923684
- Acronym / sponsor ID
- STUDY00002590
- Conditions
- Prostate Cancer
- Keywords
- prostate, cancer, consultation, review, feedback, natural, process
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 30 participants (estimated)
- Lead sponsor
- Cedars-Sinai Medical CenterUniversity, hospital or other
- Collaborators
- National Cancer Institute (NCI)
- Study start
- 15 Nov 2023 (actual)
- Primary completion
- 15 Jul 2027 (estimated)
- Study completion
- 15 Jul 2027 (estimated)
- First posted
- 28 Jun 2023 (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.
In this pilot study, the investigators will show feasibility of the NLP-based feedback system in 20 consultations of men with newly diagnosed prostate cancer. The investigators will recruit from the practices of up to 10 physicians who typically see these patients. The investigators will report the top five sentences from each consultation across key content areas (cancer prognosis, life expectancy, erectile dysfunction, urinary incontinence, and irritative urinary symptoms) to both patients and physicians within 2 weeks of the consultation.
Detailed description
The primary research procedures are:
- Audio recording and transcribing treatment counseling discussions for 20 men with newly diagnosed clinically localized prostate cancers and utilize NLP to extract key content using the system described above.
- Reports including the top five sentences by NLP probability for key content areas will be generated and will be provided to patients and providers within 2 weeks after each case.
- For patients, decisional conflict and risk perception will be assessed before and after receiving the NLP-based feedback.
- For physicians, the investigators will assess baseline quality of risk communication, any changes in individual physician communication over time, and accuracy of risk estimates for key content areas.
- Within 2 weeks of receiving the NLP-based feedback, the investigators will conduct a 30-minute semi-structured interview with patients to obtain their opinions on the utility and ideal implementation strategy for the NLP-based feedback.
- At the conclusion of the pilot trial, the investigators will conduct 30-minute semi-structured interview with counseling physicians to obtain their opinions on the utility and ideal implementation strategy for the NLP-based feedback.
Study design
- Primary purpose
- Health services research
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| NLP Intervention Experimental Arm | Experimental | Behavioral: NLP-based Feedback20 men with newly diagnosed clinically localized prostate cancers and utilize NLP to extract key content using the top five sentences by NLP probability for key content areas will be generated and will be provided to patients and providers within 2 weeks after each case. |
Who may qualify
- Ages
- 18 years and older
- Sex
- Male only
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (4 listed)
- Men undergoing initial treatment consultation for clinically localized prostate cancer;
- Men with upgraded prostate cancer on active surveillance considering conversion to definitive local therapy.
- Cedars-Sinai patient.
- Ability to read and write in English.
Key exclusion criteria (5 listed)
- Under 18 years of age;
- Subjects with difficulty communicating or dementia;
- Non-English speakers, given that our NLP-based tools cannot be used with languages other than English;
- Men with locally advanced or metastatic prostate cancer;
- Men who have already been treated for clinically localized prostate cancer
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 |
|---|---|---|
| NLP-based FeedbackAudio recordings will be made using either digital recorders or telehealth platform-generated transcripts. Patient reports will include only the extracted sentences related to content areas. Physician reports will note the extracted statements across each content area, the quality scores for individual statements based on the pre-specified hierarchy, the statements that achieved the highest score across each content area, and feedback on what could be improved. For patients, decisional conflict and risk perception will be assessed before and after receiving the NLP-based feedback. For physicians, the investigators will assess baseline quality of risk communication by pre-specified hierarchy, any changes in individual physician communication over time, and accuracy of risk estimates for key content areas. | Behavioural | NLP Intervention Experimental Arm |
Primary outcome
Change in Decisional Conflict Scale Scores before and after intervention (patient-level outcome)
Time frame: Measured directly after treatment consultation and after NLP-based feedback given to patients within 2 weeks of consultation
The investigators will employ the validated Decisional Conflict Scale (DCS), to estimate uncertainty associated with treatment choice. Effect sizes of 0.3 to 0.4 are considered meaningful. Variability (standard deviation) in DCS scores before and after receiving NLP-based feedback will be assessed and used in planning a larger trial.
Change in risk perception before and after intervention (patient-level outcome)
Time frame: Measured directly after treatment consultation and after NLP -based feedback given to patients within 2 weeks of consultation
The investigators will evaluate concordance of cancer risk perception with actual cancer risk at the patient level before and after the intervention. Cancer risk perception will be assessed by multiple-choice questions. Concordance of patient answers with actual cancer risk as estimated by outcomes of the SPCG-4 randomized trial comparing surgery versus watchful waiting at the patient's PCCI-predicted life expectancy will be assessed as a binary outcome. Risk perception will be assessed before and after their consultation. Variability (standard deviation) in risk perception scores before and after receiving NLP-based feedback will be assessed and used in planning a larger trial.
Physician attitudes regarding integration of NLP-based information (physician-level outcome)
Time frame: Interviews will be conducted within 2 weeks of the intervention.
30-minute semi-structured interviews with counseling physicians will be conducted within 2 weeks of the intervention to obtain their opinions on the utility and ideal implementation strategy for the NLP-based feedback.
Difference between reported risk of side effects and prognosis with gold standard (physician-level outcome)
Time frame: Data will be captured during the treatment consultation-for the duration of the study up to 1 year
The difference in reported risk estimates given by physicians during the consultation as compared with the gold standards for these risks (i.e. for side effects, estimates from the CAESAR study; for cancer risk with and without treatment, risks of cancer mortality in the WW group of SPCG-4 trial at the patient's life expectancy as determined by the prostate cancer comorbidity index). Variability (standard deviation) in accuracy of estimates will be assessed and used in planning a larger trial. Accuracy of estimates for the interventional period will be compared with physician-specific historical references from a previously conducted trial using the standard of care (i.e. no NLP-based intervention).
Quality of composite physician risk communication score in treatment consultation (physician-level outcome)
Time frame: Data will be captured during the treatment consultation, for duration of the study up to 1 year
Quality of risk communication scores will be calculated by qualitatively analyzing treatment consultation transcripts to assess the highest quality of communication used to transmit information regarding all key tradeoffs (cancer prognosis, life expectancy, erectile dysfunction, urinary incontinence, and irritative urinary symptoms). The quality of risk communication scale ranges from 0 to 5 for each outcome, with 0 representing the lowest score and 5 representing the highest score (Daskivich et al, J Urol 2022; Naser-Tavakolian et al, J Urol 2022). Scores for all key tradeoffs will be averaged to yield a composite quality of risk communication score. Variability (standard deviation) in quality scores will be assessed and used in planning a larger trial.
Patient attitudes regarding integration of NLP-based information
Time frame: within 4 weeks of patients using NLP system.
30-minute semi-structured interviews with patients will be conducted at the conclusion of the study period to obtain their opinions on the utility and ideal implementation strategy for the NLP-based feedback
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 12 Aug 2026.
- Individual participant dataSharing planned: No
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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.
Timothy Daskivich principal investigator
Cedars-Sinai Medical Center
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing NLP-based Feedback in people with Prostate Cancer, run by Cedars-Sinai Medical Center at 1 site in United States.
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 4 inclusion and 5 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 12 Aug 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 United States. 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 Timothy Daskivich, MD (3104230415, timothy.daskivich@cshs.org), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Change in Decisional Conflict Scale Scores before and after intervention (patient-level outcome) (time frame: Measured directly after treatment consultation and after NLP-based feedback given to patients within 2 weeks of consultation). The study lists 6 primary outcomes in all. 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 12 Aug 2026.