Ignite Creation Date:
2025-12-25 @ 1:33 AM
Ignite Modification Date:
2025-12-31 @ 5:39 PM
Study NCT ID:
NCT06856694
Status:
RECRUITING
Last Update Posted:
2025-12-11
First Post:
2025-02-14
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
RCT of NLP-Based Feedback for Improving SDM in Men With Localized Prostate Cancer
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D011471', 'term': 'Prostatic Neoplasms'}, {'id': 'D003142', 'term': 'Communication'}], 'ancestors': [{'id': 'D005834', 'term': 'Genital Neoplasms, Male'}, {'id': 'D014565', 'term': 'Urogenital Neoplasms'}, {'id': 'D009371', 'term': 'Neoplasms by Site'}, {'id': 'D009369', 'term': 'Neoplasms'}, {'id': 'D005832', 'term': 'Genital Diseases, Male'}, {'id': 'D000091662', 'term': 'Genital Diseases'}, {'id': 'D000091642', 'term': 'Urogenital Diseases'}, {'id': 'D011469', 'term': 'Prostatic Diseases'}, {'id': 'D052801', 'term': 'Male Urogenital Diseases'}, {'id': 'D001519', 'term': 'Behavior'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'RANDOMIZED', 'maskingInfo': {'masking': 'NONE'}, 'primaryPurpose': 'SUPPORTIVE_CARE', 'interventionModel': 'PARALLEL', 'interventionModelDescription': 'In this cluster randomized trial, an evaluable 259 patients with newly diagnosed clinically localized prostate cancer will be cluster randomized within an evaluable 24 physicians to:\n\n1. a control arm, in which they will receive standard of care treatment consultations along with AUA-endorsed educational materials on treatment risks and benefits (for patients) and on SDM (for physicians) or\n2. an experimental arm, in which patients and their physicians will receive NLP+AI-based feedback on what was said about key tradeoffs within approximately 72 hours of the consultation to assist with decision making.'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 283}}, 'statusModule': {'overallStatus': 'RECRUITING', 'startDateStruct': {'date': '2025-10-22', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-12', 'completionDateStruct': {'date': '2029-12', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-12-05', 'studyFirstSubmitDate': '2025-02-14', 'studyFirstSubmitQcDate': '2025-02-26', 'lastUpdatePostDateStruct': {'date': '2025-12-11', 'type': 'ESTIMATED'}, 'studyFirstPostDateStruct': {'date': '2025-03-04', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2029-05', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Decisional conflict', 'timeFrame': '2-4 weeks (from diagnosis and enrollment through the completion of post feedback survey)', 'description': 'Decisional conflict is a patient-level outcome between intervention and control and will be measured using the validated Decisional Conflict Scale (DCS) questionnaire, where participants will list if they strongly agree, agree, neither, disagree, or strongly disagree with the provided statements'}, {'measure': 'Shared decision-making', 'timeFrame': '2-4 weeks (from diagnosis and enrollment through the completion of post feedback survey', 'description': 'Shared decision making will be patient-reported and measured using the validated SDMP-4 questionnaire.'}, {'measure': 'Appropriateness of treatment choice', 'timeFrame': '2-4 weeks (from diagnosis and enrollment through the completion of post feedback survey)', 'description': 'Appropriateness of treatment choice will be determined a priori based on previously published measures determined by treatment guidelines.'}, {'measure': 'Quality of risk communication', 'timeFrame': '6-9 months (post study analysis)', 'description': 'Physician level outcome-that will measure the difference in composite quality of physician risk communication between the experimental and control arms. Quality of physician risk communication will be measured using a previously published hierarchical scale that is specific to communication of cancer prognosis, life expectancy, and treatment-related side effects.'}], 'secondaryOutcomes': [{'measure': 'Improvement of risk communication', 'timeFrame': '6-9 months (post study analysis)', 'description': 'Physician level outcome- improvement of risk communication in areas of deficiency in follow up calls between doctors and patients in the experimental arm. All of this information will be assessed retrospectively by qualitative analysis of treatment consultation transcripts.'}, {'measure': 'Risk Perception and Patient Satisfaction', 'timeFrame': '6-9 months (post study analysis)', 'description': 'Patients will fill out a REDCap questionnaire assessing risk perception and patient satisfaction with the intervention.'}]}, 'oversightModule': {'oversightHasDmc': True, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['prostate cancer', 'shared', 'decision', 'risk', 'communication', 'physician risk', 'natural language processing', 'NLP', 'artificial intelligence', 'AI', 'cluster', 'randomize', 'chatGPT'], 'conditions': ['Prostate Cancer', 'Shared Decision Making', 'Risk Communication']}, 'descriptionModule': {'briefSummary': 'The purpose of the research is to assess the impact of a natural language processing + artificial intelligence (NLP+AI)-based risk communication feedback system to improve quality of risk communication of key tradeoffs during prostate cancer consultations among physicians and to improve patient decision making. In this cluster randomized trial, an evaluable 259 patients with newly diagnosed clinically localized prostate cancer will be cluster randomized within an evaluable 24 physicians to:\n\n1. a control arm, in which patients will receive standard of care treatment consultations along with AUA-endorsed educational materials on treatment risks and benefits (for patients) and on SDM (for physicians) or\n2. an experimental arm, in which patients and participating physicians will receive NLP+AI-based feedback on what was said about key tradeoffs within approximately 72 hours of the consultation to assist with decision making. Physicians will additionally be provided with grading of their risk communication for each visit based on an a priori defined framework for quality of risk communication and recommendations for improvement.\n\nIn both study arms, there will be an audio-recorded follow-up phone or video call between the physician and patient to allow for further discussion of risk and clarifying any areas of ambiguity, which will be qualitatively analyzed to see if areas of poor communication were rectified. After the follow-up phone call, patients and participating physicians will be asked to complete a very brief survey about their experience.\n\nThe study plans to test whether receiving NLP+AI-based feedback improves decisional conflict, shared decision making, and appropriateness of treatment choice over the standard of care in patients undergoing treatment consultations for prostate cancer. Study staff will also test whether providing feedback and grading of risk communication to physicians affects quality of physician risk communication, since providing feedback will promote more accountability for the quality of information provided to patients. The study will also analyze data from the control arm of the randomized controlled trial to understand variation in risk communication of key tradeoffs in relevant subgroups of tumor risk (low-, intermediate-, and high-risk), provider specialty (Urology, Radiation Oncology, Medical Oncology), and patient sociodemographics.'}, 'eligibilityModule': {'sex': 'MALE', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'genderBased': True, 'genderDescription': 'cis-gendered men', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\nPhysician Inclusion Criteria\n\n(1) Physicians who typically counsel prostate cancer patients (Urology, Radiation Oncology, Medical Oncology)\n\nPatient Inclusion Criteria\n\n1. Patients undergoing initial treatment consultation for clinically localized prostate cancer;\n2. Patients with upgraded prostate cancer on active surveillance considering conversion to definitive local therapy;\n3. Ability to read and write in English.\n\nPatient Exclusion Criteria:\n\n1. Under 18 years of age;\n2. Subjects with difficulty communicating or dementia;\n3. Non-English speakers, given that our NLP-based tools cannot be used with languages other than English;\n4. Patients with locally advanced or metastatic prostate cancer;\n5. Patients who have already been treated for clinically localized prostate cancer.'}, 'identificationModule': {'nctId': 'NCT06856694', 'acronym': 'NLP RCT', 'briefTitle': 'RCT of NLP-Based Feedback for Improving SDM in Men With Localized Prostate Cancer', 'organization': {'class': 'OTHER', 'fullName': 'Cedars-Sinai Medical Center'}, 'officialTitle': 'Natural Language Processing-Based Feedback to Improve Physician Risk Communication and Informed Shared Decision Making in Men With Clinically Localized Prostate Cancer', 'orgStudyIdInfo': {'id': 'STUDY00003620'}, 'secondaryIdInfos': [{'id': '1R01CA290559-01A1', 'link': 'https://reporter.nih.gov/quickSearch/1R01CA290559-01A1', 'type': 'NIH'}]}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'NLP-Based Feedback Arm', 'interventionNames': ['Other: NLP+AI Report']}, {'type': 'NO_INTERVENTION', 'label': 'Standard of Care Arm', 'description': 'patients will receive standard of care treatment consultations along with AUA-endorsed educational materials on treatment risks and benefits (for patients) and on SDM (for physicians)'}], 'interventions': [{'name': 'NLP+AI Report', 'type': 'OTHER', 'description': 'A NLP model will extract key content from consultations and AI (Chat GPT) will summarize that information. Reports including the top sentences by NLP probability for key content areas will be generated and will be provided to patients and providers within approximately 72 hours after each case. In both arms, a follow up phone call will allow for clarification any concepts that was inadequately communicated during the consultation. This call will be audio recorded and qualitatively assessed to determine whether deficiencies in risk communication observed in the consultation were rectified.', 'armGroupLabels': ['NLP-Based Feedback Arm']}]}, 'contactsLocationsModule': {'locations': [{'zip': '90048', 'city': 'Los Angeles', 'state': 'California', 'status': 'RECRUITING', 'country': 'United States', 'facility': 'Cedars Sinai Medical Center', 'geoPoint': {'lat': 34.05223, 'lon': -118.24368}}], 'centralContacts': [{'name': 'Timothy Daskivich, MD', 'role': 'CONTACT', 'email': 'Timothy.Daskivich@cshs.org', 'phone': '310-423-4700'}, {'name': 'Ella Tetrault, AB', 'role': 'CONTACT', 'email': 'Ella.Tetrault@cshs.org', 'phone': '424-315-1311'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO', 'description': 'Concerns regarding identification of participating individuals with raw consultation transcripts.'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Cedars-Sinai Medical Center', 'class': 'OTHER'}, 'collaborators': [{'name': 'National Cancer Institute (NCI)', 'class': 'NIH'}], 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Staff Physician II', 'investigatorFullName': 'Timothy J. Daskivich', 'investigatorAffiliation': 'Cedars-Sinai Medical Center'}}}}