Event Details
Agenda
Event Details
Clinical Considerations
There is concern regarding the clinical utility of biomarkers in kidney disease (Acute Kidney Injury [AKI], Chronic Kidney Disease [CKD], various forms of glomerulonephritis [GN], and polycystic kidney disease [PKD]) for prediction of diverse clinical outcomes (such as loss of renal function, development of cardiovascular disease, diminution of quality of life, death), as well as in drug development (for refinement of risk stratification or drug response). There is
dissatisfaction with the results of published biomarker studies and the lack of uptake of biomarkers in clinical practice in patients with kidney disease. Finally, we don’t know the answers to several key questions. Some of these are listed below.
- Of what use is this biomarker to me or my patient in the clinic?
- Has “context of use” or “fit purpose” been identified, or do the present studies evaluate biomarkers on convenience samples?
- How can we deal with the paradox of well-established but crude measures which biomarkers must enhance?
- Can we develop markers for kidney disease that are superior to S[Cr] and proteinuria?
- Does the Framingham study provide a better framework for the evaluation of biomarkers—or do biomarker studies have to be designed de novo for each context?
- How does biomarker science allow us to move from a population focus to individual considerations: the patient and the physician in the consultation room (or at the bedside)—considering a distinct outcome?
- Can we as biomarker scientists develop physician / patient perspectives—assessing risk for the individual, or outcome for the individual with drug therapy?
Statistical Considerations
Have we developed a true set of biomarker statistical analyses? Or are we fitting old techniques to new contexts / issues? What does a biomarker showing independent association with a distant outcome in a Cox regression mean? What are the key elements of design for a meaningful biomarker study? What metrics are appropriate for assessing incremental value of biomarkers?
- What does “prediction” mean?
- Is “prediction” different for present measures (eg eGFR) compared to future outcomes (risk of future decrement in renal function, need for ESRD treatment, or death)?
- How can we make predictive models in kidney disease patients more precise?
- Can causal links between biomarker levels or changes identified by present statistical methods be strengthened?
This workshop will grapple with these thorny questions. Breakout groups, composed of biostatisticians and clinical nephrologists, will consider the issues and put forth approaches for moving forward.
Agenda
December 2, 2014
- 8:00 a.m.
- Introduction
P. Kimmel & R. Star
Biomarkers, Clinical and Research Utility: Current State of the Art
(10 min followed by 15 min Q/A)
Moderators: H. Rodriguez, J. Lachin
- 8:10 a.m.
- Why we need kidney biomarkers for prognosis and diagnosis
C.-Y. Hsu
- Review of current methods to assess the prognostic/diagnostic value of kidney biomarkers
C. Parikh
- What not to do when evaluating the prognostic/diagnostic value of biomarkers
F. Harrell
- 9:25 a.m.
- Break
Towards better interpretation of prognostic/diagnostic value of biomarkers
(10 min followed by 15 min Q/A)
Moderators: A. Thompson, M.J. Pencina
- 9:45 a.m.
- Clinical perspective – What do we need?
R.S. Vasan
- Regulatory needs regarding biomarkers and drug development tools
M. Walton
- Statistical perspective – What is the state of the art?
R. D'Agostino
- Applied perspective – How are biomarkers used in practice and in research?
M. Gail
- Decision analysis – Hope or myth?
E. Steyerberg
- 11:50 a.m.
- Lunch
New Frontiers: Novel ways to look at/for biomarkers
(10 min followed by 15 min Q/A)
Moderators: K. Lemley, M.J. Pencina
- 12:20 p.m.
- Selection methods
K. Kerr
- Prognostic models of the future
A. Foulkes
- Use of biomarkers in combinations to enhance accuracy and clinical utility
R. Pfeiffer
- Use of biomarkers – Longitudinal measurement models
V. Chinchilli
- Combining cohorts and creating valid metanalyses
J. Coresh
- 2:25 p.m.
- Break
- 2:45 p.m.
- Breakout Sessions – 4 Groups:
- Models with biomarkers
- Assessment of added value of biomarkers
- Strategies and knowledge from combining existing studies/cohorts?
- Combining Biomarkers
- 4:45 p.m.
- Break
- 5:00 p.m.
- Breakout Reports
(15 min/each, including discussion)
- 6:00 p.m.
- Summary & Closing Remarks
P. Kimmel & R. Star
- 6:15 p.m.
- Adjourn
Breakout Groups
Overarching Question/Objective for All Groups
What are the key methodological advances needed for enhance biomarker research?
Group 1—Models with biomarkers
Foulkes/Parikh
- Better methods to construct risk prediction models
- Selection of cut-offs for biomarkers
- Multi-level outcomes for AKI and CKD
- Mediation analysis for prognostic model
Group 2—Assessment of added value of biomarkers
Cook/Lemley
- Statistical metrics and data summaries for model improvement with biomarkers
- Cost-effectiveness and cost-benefit analysis
- Cross-validation and external validation of biomarker results
Group 3—Strategies and knowledge from combining existing studies/cohorts?
Coresh/Gimmoty/Hsu
- Meta-analysis—study level vs. patient level
- Different assays, clinical settings, cohorts
- Center effects in multicenter biomarker studies
- Combining performance metrics
- Data sharing considerations
Group 4—Combining Biomarkers
Song/Feldman
- Correlation, biology or outcome-driven combinations
- Developing guidelines for combinations
- Which metrics to focus on in combination
- Longitudinal combination of biomarkers