As you will recall, the Hoppe et al. 2019 report [blogpost] both replicated Ginther et al 2011 with a subsequent slice of grant applications, demonstrating that after the news of Ginther, with a change in scoring procedures and changes in permissible revisions, applications with Black PIs still suffered a huge funding disparity. Applications with white PIs are 1.7 times more likely to be funded. Hoppe et al also identified a new culprit for the funding disparity to applications with African-American / Black PIs. TOPIC! “Aha”, they crowed, “it isn’t that applications with Black PIs are discriminated against on that basis, no. It’s that the applications with Black PIs just so happen to be disproportionately focused on topics that just so happen to have lower funding / success rates”. Of course it also was admitted very quietly by Hoppe et al that:

WH applicants also experienced lower award rates in these clusters, but the disparate outcomes between AA/B and WH applicants remained, regardless of whether the topic was among the higher- or lower-success clusters (fig. S6).

Hoppe et al., Science Advances, 2019 Oct 9;5(10):eaaw7238. doi: 10.1126/sciadv.aaw7238

If you go to the Supplement Figure S6 you can see that for each of the five quintiles of topic clusters (ranked by award rates) applications with Black PIs fare worse than applications with white PIs. In fact, in the least-awarded quintile, which has the highest proportion of the applications with Black PIs, the white PI apps enjoy a 1.87 fold advantage, higher than the overall mean of the 1.65 fold advantage.

Record scratch: As usual I find something new every time I go back to one of these reports on the NIH funding disparity. The overall award rate disparity was 10.7% for applications with Black PIs versus 17.7% for those with white PIs. The take away from Hoppe et al. 2019 is reflected in the left side of Figure S6 where it shows that the percentage of applications with Black PIs is lowest (<10%) in the topic domains with the highest award rates and highest (~28%) in the domains with the lowest award rates. The percentages are more similar for apps with white PIs, approximately 20% per quintile. But the right side lists the award rates by quintile. And here we see that in the second highest award-rate topic quintile, the disparity is similar to the mean (12.6% vs 18.9%) but in the top quintile it is greater (13.4% vs 24.2% or a 10.8%age point gap vs the 7%age point gap overall). So if Black PIs followed Director Collins’ suggestion that they work on the right topics with the right methodologies, they would fare even worse due to the 1.81 fold advantage for applications with white PIs in the top most-awarded topic quintile!

Okay but what I really started out to discuss today was a new tiny tidbit provided by a blog post on the Open Mike blog. It reports the topic clusters by IC. This is cool to see since the word clusters presented in Hoppe (Figure 4) don’t map cleanly onto any sort of IC assumptions.

All we are really concerned with here is the ranking along the X axis. From the blog post:

17 topics (out of 148), representing 40,307 R01 applications, accounted for 50% of the submissions from African American and Black (AAB) PIs. We refer to these topics as “AAB disproportionate” as these are topics to which AAB PIs disproportionately apply.

Note the extreme outliers. One (MD) is the National Institute on Minority Health and Health Disparities. I mean… seriously. The other (NR) is the National Institute on Nursing Research which is also really interesting. Did I mention that these two Is get 0.8% and 0.4% of the NIH budget, respectively? The NIH mission statement reads: “NIH’s mission is to seek fundamental knowledge about the nature and behavior of living systems and the application of that knowledge to enhance health, lengthen life, and reduce illness and disability.” Emphasis added. The next one (TW) is the Fogerty International Center which focuses on global health issues (hello global pandemics!) and gets 0.2% of the NIH budget.

Then we get into the real meat. At numbers 4-6 on the AAB Disproportionate list of ICs we reach the National Institute on Child Health and Development (HD, 3.7% of the budget), NIDA (DA, 3.5%) and NIAAA (AA, 1.3%). And clocking in at 7 and 9 we have National Institute on Aging (AG, 8.5%) and the NIMH (MH, 4.9%).

These are a lot of NIH dollars being expended in ICs of central interest to me and a lot of my audience. We could have made some guesses based on the word clusters in Hoppe et al 2019 but this gets us closer.

Yes, we now need to get deeper and more specific. What is the award disparity for applications with Black vs white PIs within each of these ICs? How much of that disparity, if it exists, accounted for by the topic choices within IC?

And lets consider the upside. If, by some miracle, a given IC is doing particularly well with respect to funding applications with Black PIs fairly….how are they accomplishing this variance from the NIH average? What can the NIH adopt from such an IC to improve things?

Oh, and NINR and NIMHHD really need a boost to their budgets. Maybe NIH Director Collins could put a 10% cut prior to award to the other ICs to improve investment in the applying-knowledge-to-enhance-health goals of the mission statement?