Best Case/Worst Case (BC/WC) Geriatric Oncology (GeriOnc) communication tool for Cancer, Advanced

Phase-Based Progress Estimates
1
Effectiveness
1
Safety
San Francisco Veterans Medical Center, San Francisco, CA
Cancer, Advanced
Best Case/Worst Case (BC/WC) Geriatric Oncology (GeriOnc) communication tool - Other
Eligibility
65+
All Sexes
What conditions do you have?
Select

Study Summary

This is a minimal risk, pilot cluster randomized controlled trial (CRT) to determine the feasibility and acceptability of training medical oncologists to use the Best Case/Worst Case-Geriatric Oncology (BC/WC-GeriOnc) communication tool in clinical practice with older adults with advanced cancer.

Treatment Effectiveness

Effectiveness Progress

1 of 3

Study Objectives

5 Primary · 5 Secondary · Reporting Duration: Completed once at the end of study participation (approximately 18 months)

1 day
Enrollment rate
3 months
Retention rate
Month 18
Practitioner Opinion Survey (Lead-In and BC/WC-GeriOnc Intervention Groups Only)
Qualitative oncologist-reported feasibility (Lead-In and BC/WC-GeriOnc Intervention Groups Only)
Week 2
Acceptability of Intervention Measure (Lead-In and BC/WC-GeriOnc Intervention Groups Only)
BC/WC-GeriOnc Intervention Adherence (Lead-In and BC/WC-GeriOnc Intervention Groups Only)
BC/WC-GeriOnc Intervention Fidelity (Lead-In and BC/WC-GeriOnc Intervention Groups Only)
Duration of audio-recorded decision-making discussions
Feasibility of Intervention Measure (Lead-In and BC/WC-GeriOnc Intervention Groups Only)
Intervention Appropriateness Measure (Lead-In and BC/WC-GeriOnc Intervention Groups Only)

Trial Safety

Safety Progress

1 of 3

Trial Design

3 Treatment Groups

Waitlist Control
1 of 3
Lead-In (BC/WC-GeriOnc)
1 of 3
Intervention (BC/WC-GeriOnc)
1 of 3
Active Control
Experimental Treatment

96 Total Participants · 3 Treatment Groups

Primary Treatment: Best Case/Worst Case (BC/WC) Geriatric Oncology (GeriOnc) communication tool · No Placebo Group · N/A

Lead-In (BC/WC-GeriOnc)
Other
Experimental Group · 1 Intervention: Best Case/Worst Case (BC/WC) Geriatric Oncology (GeriOnc) communication tool · Intervention Types: Other
Intervention (BC/WC-GeriOnc)
Other
Experimental Group · 1 Intervention: Best Case/Worst Case (BC/WC) Geriatric Oncology (GeriOnc) communication tool · Intervention Types: Other
Waitlist ControlNoIntervention Group · 1 Intervention: Waitlist Control · Intervention Types:

Trial Logistics

Trial Timeline

Approximate Timeline
Screening: ~3 weeks
Treatment: Varies
Reporting: completed once at the end of study participation (approximately 18 months)
Closest Location: San Francisco Veterans Medical Center · San Francisco, CA
Photo of San Francisco 1Photo of San Francisco 2Photo of San Francisco 3
2016First Recorded Clinical Trial
1 TrialsResearching Cancer, Advanced
1 CompletedClinical Trials

Who is running the clinical trial?

National Institute on Aging (NIA)NIH
1,348 Previous Clinical Trials
3,261,801 Total Patients Enrolled
1 Trials studying Cancer, Advanced
80 Patients Enrolled for Cancer, Advanced
University of California, San FranciscoLead Sponsor
2,246 Previous Clinical Trials
11,473,578 Total Patients Enrolled
1 Trials studying Cancer, Advanced
6,400 Patients Enrolled for Cancer, Advanced
Melisa L Wong, MD, MASPrincipal InvestigatorUniversity of California, San Francisco

Eligibility Criteria

Age 65+ · All Participants · 10 Total Inclusion Criteria

Mark “yes” if the following statements are true for you:
You have a solid tumor malignancy that is currently in the stage IV (per AJCC 8th Edition) or stage III (per AJCC 7th Edition) and has not been treated with curative intent.
You are a physician who has completed an oncology fellowship and is independently practicing.
You are a current or former faculty member of the Helen Diller Family Comprehensive Cancer Center (HDFCCC) affiliated site.

About The Reviewer

Michael Gill preview

Michael Gill - B. Sc.

First Published: October 9th, 2021

Last Reviewed: August 12th, 2022

Michael Gill holds a Bachelors of Science in Integrated Science and Mathematics from McMaster University. During his degree he devoted considerable time modeling the pharmacodynamics of promising drug candidates. Since then, he has leveraged this knowledge of the investigational new drug ecosystem to help his father navigate clinical trials for multiple myeloma, an experience which prompted him to co-found Power Life Sciences: a company that helps patients access randomized controlled trials.