Stan Shaw, Tianxi Cai, Raoul, Shawn, Zak, Susanne et al.,
Discussed whether to expand the data mart to include other hospitals.
Reviewed study design for measures of inflammation.
Stan Shaw, Tianxi Cai, Raoul, Shawn, Zak, Susanne et al.,
Discussed whether to expand the data mart to include other hospitals.
Reviewed study design for measures of inflammation.
Discussed how additional SHRINE influences future directions of i2b2. Then demonstrated the latest i2b2/SMART integration (quite impressive!).
(minutes courtesy Caitlin)
Attendance: Jordan Smoller, Roy Perlis, Shawn Murphy, Susanne Churchill, Isaac Kohane, Tianxi Cai, Victor Castro, Alison Hoffnagle, Patience Gallagher, Sydney Weill, Caitlin Clements
Minutes:
-ICCBDà Refresh: Victor has performed a preliminary refresh of the data mart; however, this did not include the NLP cohort. Victor will finish NLP classification and will perform another refresh by the end of the following week that includes this data. The current updated numbers for the other cohorts may change a bit as well when he performs this second refresh; however, they will not change by much.
Next Stepsà 1. Final refresh of data mart
2. The group needs to decide what we are going to do with the MRP and MRP-SV cohorts
StudyGroup |
Cohort |
ClassificationType |
N |
TP |
FP |
PPV |
PPV 95% CI Lower |
PPV 95% CI Upper |
Case |
95NLP |
NLP+EMR |
45 |
38 |
7 |
0.844 |
0.712 |
0.923 |
Case |
NoNLP |
EMR |
26 |
24 |
2 |
0.923 |
0.759 |
0.979 |
Case |
MRP |
EMR |
25 |
14 |
11 |
0.560 |
0.371 |
0.733 |
Case |
MRP-SV |
EMR |
5 |
1 |
4 |
0.200 |
0.036 |
0.624 |
StudyGroup |
Cohort |
ClassificationType |
N |
TN |
FN |
NPV |
NPV 95% CI Lower |
NPV 95% CI Upper |
Control |
MDD |
Advertising |
11 |
10 |
1 |
0.909 |
0.623 |
0.984 |
Control |
SCZ |
Advertising |
15 |
13 |
2 |
0.867 |
0.621 |
0.963 |
Control |
Control |
EMR |
13 |
13 |
0 |
1.000 |
0.772 |
1.000 |
Topic: Local i2b2-initiated federally funded spinoffs.
1.Kat Liao presented the RA DBP and the spinoff RA-CVD project. What is the relationship with risk for CAD/CVD risk in the general population (and the risk alleles) and that in RA. Our of 4453 in RA cohort (i2b2), 335 have CAD.
2. Jordan Smoller presented the Bipolar Disease NIMH grant. Reviewed the challenges of a very specific case definition. Claims codes alone seem to give positive predictive values (PPV) in the 20-50% range and the PPV of NLP is about 85% (with specificity of 95%).
3. Roy Perlis spoke about his R01 derived from the MDD-resistant-to-SSRI DBP. He is studying a MDD clinical and genetic risk risk algorithm/classifier. He is on the way to a 1500 population which represented 1/2 of all the drug response GWAS currently published in this particular domain?
4. Robert Plenge described the spinoff of the i2b2 RA DBP to the PGRN project. The project looks at genetic informants of treatment response and treatment toxicities. Involves Vanderbilt, Northwestern and Partners. Early result shows the portability of the NLP RA classifier.
Given intermittent recording of drug exposure and clinical events, there is going to be a lot of censoring in the EHR data stream. This kind of data censoring is a methodological challenge and we reviewed various heuristics and comparisons that can be used to correct/account for this censoring. A lot of focus on modeling the frequency of observations.
For the next generation of i2b2, we are trying to minimize how many cells have to be locally hosted. Even more crucially, how many cells have to be locally customized and supported and how many can be generic. In other words, can we or should we reposition any abstraction barriers?
Xia et al,
Very extensive discussion of randomization procedures in selecting patient samples.
Shaw, Cai, Churchill, Liao, Murphy, Kohane, Sordo, Savova
Reviewed the subsamples to see if we are getting the right DM rate.