James Deardorff's guest appearances

James Deardorff

GeriPal

John Newman

Scott Bauer

BJ Miller

Andy Cohen

Aaron Kesselheim

Louise Aronson

Haider Warraich

Lewis Cohen

Stephanie Rogers

Tim Anderson

Jessica Zitter

Susan Block

John Mills

Katie Fitzgerald

John Nelson

OwlTail

Alex Lee

Sei Lee

Dr. Faith Fitzgerald once quipped that prognostic modeling is the “punctilious quantification of the amorphous.”  She has a point.  Prognosis is inherently uncertain.  As Alex Lee says on our podcast today, all prognostic models will be wrong (in some circumstances and for some patients); our job is to make prognostic models that are clinically useful.  As Sei Lee notes, the argument for developing prognostic models has won the day, and we increasingly use prognostic scores in clinical decision making.  What makes prognostic models for mortality different from models used for anticoagulation or risk of renal injury?  James Deardorff replies that there is something inherently different about predicting mortality.  Death is different.  For some reason clinicians who might be perfectly comfortable using an anticoagulation risk calculator might be skeptical of a mortality risk calculator (see this recent terrific  JAMA IM study from Nancy Shoenborn on this issue).  And yet, the only thing that may be worse than a prognostic calculator is a clinician relying solely on their clinical intuition. Today our guests Alex Lee, James Deardorff, and Sei Lee, talk to us about the uses, limitations, and clinical use cases for prognostic models.  As a springboard for this conversation we discuss new prognostic models developed to predict (simultaneously) mortality, disability, and mobility impairment (Alex Lee first author, JAGS) and mortality for people with dementia residing in the community (James Deardorff first author, JAMA IM).   Both new models are now available and free to use on ePrognosis.   And Sei and Eric reminisce about slow dancing to “Forever Young” by Alphaville in their teenage years. Enjoy! -AlexSmithMD

Dr. Faith Fitzgerald once <a href="https://www.nejm.org/doi/full/10.1056/nejmp1303295" rel="nofollow" target="_blank">quipped</a> that prognostic modeling is the “punctilious quantification of the amorphous.”  She has a point.  Prognosis is inherently uncertain.  As Alex Lee says on our podcast today, all prognostic models will be wrong (in some circumstances and for some patients); our job is to make prognostic models that are clinically useful.  As Sei Lee notes, the argument for developing prognostic models has won the day, and we increasingly use prognostic scores in clinical decision making.  What makes prognostic models for mortality different from models used for anticoagulation or risk of renal injury?  James Deardorff replies that there is something inherently different about predicting mortality.  Death is different.  For some reason clinicians who might be perfectly comfortable using an anticoagulation risk calculator might be skeptical of a mortality risk calculator (see this recent terrific <a href="https://jamanetwork.com/journals/jamainternalmedicine/fullarticle/2797395" rel="nofollow" target="_blank"> JAMA IM study</a> from Nancy Shoenborn on this issue).  And yet, the only thing that may be worse than a prognostic calculator is a clinician relying solely on their <a href="https://www.bmj.com/content/327/7408/195.short" rel="nofollow" target="_blank">clinical intuition</a>. Today our guests Alex Lee, James Deardorff, and Sei Lee, talk to us about the uses, limitations, and clinical use cases for prognostic models.  As a springboard for this conversation we discuss new prognostic models developed to predict (simultaneously) mortality, disability, and mobility impairment (<a href="https://agsjournals.onlinelibrary.wiley.com/doi/full/10.1111/jgs.17932" rel="nofollow" target="_blank">Alex Lee first author, JAGS</a>) and mortality for people with dementia residing in the community (<a href="https://jamanetwork.com/journals/jamainternalmedicine/article-abstract/2796662" rel="nofollow" target="_blank">James Deardorff first author, JAMA IM</a>).   Both new models are now available and free to use on <a href="https://eprognosis.ucsf.edu/calculators/" rel="nofollow" target="_blank">ePrognosis</a>.   And Sei and Eric reminisce about slow dancing to “Forever Young” by Alphaville in their teenage years. Enjoy! -AlexSmithMD

New Prognostic Models for Older Adults: Alex Lee, James Deardorff, Sei Lee

My mom is an Asian woman in her 70s with osteoporosis.  She tried an oral bisphosphonate and had horrible esophagitis.  She said never again, though she eventually tried an IV bisphosphonate.  She had terrible flu-like symptoms.  She said never again.  But based on reports that symptoms are worse the first time, she tried the IV again the next year and fortunately experienced no symptoms.  (Story used with permission, thanks mom!).   I tell this story because these issues don’t typically register as more than a nuisance for clinicians, who frequently don’t understand why their older patient with osteoporosis is not taking a bisphosphonate.  But our patients are walking with their feet, and adherence to bisphosphonates for osteoporosis is poor and decreases with time. When we have a medication with up front harms and downstream benefits, it’s critical that we consider the time to benefit, or how long it will take an individual to benefit from a test or treatment.  Think of the 10 years it takes to benefit from colon or breast cancer screening, which is designed to detect slow growing cancers.  For individuals with a life expectancy less than the time to benefit, the up front harms outweigh the downstream benefits.   In this context, we talked this week with James Deardorff and Sei Lee about their study of  time to benefit of bisphosphonates for osteoporosis, published in JAMA IM. What they found somewhat surprised us: it’s pretty short, about 1 year!   Which makes me feel better about urging my mom to get treatment.  Bisphosphonates are pretty darn effective, and act quickly. We also discuss discontinuing bispohsophantes, and if we can use the same logic we consider when starting them.   Toward the end we talk about the launch of ePrognosis’ new Time to Benefit tool.  This tool provides a clinical recommendation for starting/stopping medications and cancer screening based on the prognosis of the patient in front of you.  See screenshot below.  You can either access it directly here.  I you use the Lee Schonberg prognostic index for community dwelling older adults you will be directed to the tool, and it will automatically place the life expectancy at the calculated prognostic estimate.   James and Sei requested a terrific song - Bad to the Bone - much better than the Hannah Montana Bone Dance song they threatened me with (maybe next time). Enjoy! -@alexSmithMD

My mom is an Asian woman in her 70s with osteoporosis.  She tried an oral bisphosphonate and had horrible esophagitis.  She said never again, though she eventually tried an IV bisphosphonate.  She had terrible flu-like symptoms.  She said never again.  But based on reports that symptoms are worse the first time, she tried the IV again the next year and fortunately experienced no symptoms.  (Story used with permission, thanks mom!).   I tell this story because these issues don’t typically register as more than a nuisance for clinicians, who frequently don’t understand why their older patient with osteoporosis is not taking a bisphosphonate.  But our patients are walking with their feet, and <a href="https://bmjopen.bmj.com/content/9/4/e027049.abstract" rel="nofollow" target="_blank">adherence to bisphosphonates for osteoporosis is poor and decreases with time</a>. When we have a medication with up front harms and downstream benefits, it’s critical that we consider the time to benefit, or how long it will take an individual to benefit from a test or treatment.  Think of the 10 years it takes to benefit from colon or breast cancer screening, which is designed to detect slow growing cancers.  For individuals with a life expectancy less than the time to benefit, the up front harms outweigh the downstream benefits.   In this context, we talked this week with James Deardorff and Sei Lee about their study of <a href="https://jamanetwork.com/journals/jamainternalmedicine/fullarticle/2786013" rel="nofollow" target="_blank"> time to benefit of bisphosphonates for osteoporosis</a>, published in JAMA IM. What they found somewhat surprised us: it’s pretty short, about 1 year!   Which makes me feel better about urging my mom to get treatment.  Bisphosphonates are pretty darn effective, and act quickly. We also discuss discontinuing bispohsophantes, and if we can use the same logic we consider when starting them.   Toward the end we talk about the launch of ePrognosis’ new <a href="https://eprognosis.ucsf.edu/time_to_benefit.php" rel="nofollow" target="_blank">Time to Benefit tool</a>.  This tool provides a clinical recommendation for starting/stopping medications and cancer screening based on the prognosis of the patient in front of you.  See screenshot below.  You can either access it directly <a href="https://eprognosis.ucsf.edu/time_to_benefit.php" rel="nofollow" target="_blank">here</a>.  I you use the <a href="https://eprognosis.ucsf.edu/leeschonberg.php" rel="nofollow" target="_blank">Lee Schonberg prognostic index</a> for community dwelling older adults you will be directed to the tool, and it will automatically place the life expectancy at the calculated prognostic estimate.   James and Sei requested a terrific song - Bad to the Bone - much better than the Hannah Montana Bone Dance song they threatened me with (maybe next time). Enjoy! -@alexSmithMD

Bisphosphonates for Osteoporosis: Podcast with James Deardorff and Sei Lee