NLP-Based Feedback for Prostate Cancer Communication
This study is testing a new way to improve how doctors and patients talk about prostate cancer. It uses "NLP-based Feedback" (Natural Language Processing), which is a computer program that analyzes recordings of your conversations with your doctor. The program identifies key sentences about your cancer, treatment options, and potential side effects like erectile dysfunction or urinary issues. Both you and your doctor will receive a report with these key sentences within two weeks of your consultation. The goal is to see if this feedback helps you feel more confident in your treatment decisions and if doctors find it useful. This study is for men with newly diagnosed prostate cancer or those on active surveillance considering treatment, who are Cedars-Sinai patients and can read and write in English. We are looking for 30 participants.
- Study design
- This is an interventional pilot study involving 30 men. It is not specified if it is randomized or blinded.
- What's involved
- You will have your treatment consultation audio recorded. You will receive NLP-based feedback and complete surveys about your decisions and risk perception. You will also participate in a 30-minute interview within two weeks of receiving the feedback.
- Compensation
- Not stated in the trial record.
- Follow-up
- Your decisional conflict and risk perception will be measured directly after your consultation and again after receiving the NLP-based feedback within two weeks. Interviews will also be conducted within two weeks of the intervention.
AI-generated from the public study record. Only the study team can confirm whether you're eligible — confirm details with them before making decisions.
NLP-Based Feedback to Improve Risk Comms and Informed Shared Decision Making
At a glance
Conditions
Where it's being run
1 sites across 1 statesStudy leadership
- Timothy Daskivich · PRINCIPAL_INVESTIGATOR · Cedars-Sinai Medical Center
Who to contact
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What this trial measures
- Change in Decisional Conflict Scale Scores before and after intervention (patient-level outcome)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)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)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)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)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 informationwithin 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