Year Distribution of Competing Renewal (Type 2) Grants from 1995-2014

Feb 25 2015 Published by under Uncategorized

R01 grants may be renewed, typically every 4-5 years. These are called "competing renewals" or "Type 2" grants. In the context of discussions of the "Emeritus Award" discussion, I examined the distribution of R01 grants that had been renewed over a long period of time. Here, I look at the distribution of Type 2 grants over the period from 1995 to 2014.

Data for Type 2 R01 grants (as well as the corresponding but much smaller number of R37 MERIT awards) for each year were compiled from NIH RePORTER. Note that these grants only include grants that were competitively renewed in a given year and not non-competing continuations (Type 5 awards). The distributions of the 2653 Type 2 awards from FY1995 and 1532 Type 2 awards from FY2014 over the Support Year are shown below:

1995-2014 plot

The distribution for FY1995 shows peaks at Year 4, Year 6 corresponding to renewals of initial (Type 1) grants of 3 and 5 years, respectively. There are additional peaks at Year 9 and Year 14. These correspond primarily to grants that initially made for a period of 3 years and then were renewed for 5 year periods.

The distribution for FY2014 is similar but shows some important differences. First, the overall amplitude is smaller as there were 58% as many Type 2 R01 grants awarded in FY2014 compared to FY1995. Second, the FY2014 shows peaks at Year 6 and Year 11. These correspond to grants awarded initially for a period of 5 years and then renewed for an additional 5 year period. Third, the FY2014 distribution shows a longer tail extended to Year 40 and beyond, corresponding to long-running grants.

The distributions are shown in normalized and integrated form below:

1995-2014 frac plot

These curves show more clearly the tail extending longer grant durations. For FY1995, 20% of the grants are in Years 13 or beyond whereas for FY2014, 20% of the grants are in Years 18 and beyond.

The distribution of Type 2 grants can be seen more clearly by looking are the distribution summed over all of the years from FY1995 to FY2014 as shown below.

Overall Type 2 distribution

This shows peaks from Years 5-6 and Years 10-11 and then the tail extending from Year 15 and beyond.

The structure of this tail can be seen more clearly by replotting the data on a log (base 10) scale as shown below:

Log plot-2-60

The portion of this graph corresponding to the extended tail is very nearly linear with a slight downward curvature. This indicates the tail that is approximately exponential. Fitting this curve reveals an exponent of approximately -0.064/year. This corresponds to a half-life 0f 4.7 years. In order words, the chance that a long-standing grant is renewed every 4-5 years is approximately 50%. The NIH reported success rate for all competing renewal Grants averaged 38% from FY2001 to 2014. Thus, it appears that the likelihood that a longstanding R01 is competitively renewed is slightly, but not dramatically, higher than that for R01 grants overall. The slight downward curvature of the log plot likely reflects that fact that there were a smaller number of longstanding grants in the earlier years in this analysis.

An alternative approach to examining trends the duration of these grants involves looking at the fraction of A0 applications among the funded Type 2 grants. I have previously examined this parameter in other contexts. A plot of the fraction of A0 applications among funded Type 2 grants as a function of the Year of the grant is shown below:

Fraction A0 plot

 

This fraction dips slightly for grant years from 4-7 (corresponding to the first renewal) and then reaches a relatively stable level extending out to 40 years. This suggests there is not a major increase in the likelihood of application success as the year of the grant increases.

Overall, these observations are consistent with the notion that R01 grants reach longstanding status through the perseverance of the principal investigators. Over time, these investigators continue to execute research programs that are sufficiently productive that they compete for renewal with a success rate close to 50% (at least historically). There does not appear to be a substantial advantage for longstanding grant applications above the general advantage for Type 2 versus Type 1 applications based on these publicly available data.

15 responses so far

  • Drugmonkey says:

    Oh cool. You've data confirmed my occasional assertion that 3 yr R01s used to be seen as a valid Exploratory/Developmental strategy. Not so much anymore.

  • AScientist says:

    I'm surprised by the big drop-off from first renewal (at year 6) vs second renewal (~year 10) but I guess that's due to exponential function and the "sharpness" of those first two renewals (later renewals stagger more?). Or are many grants not renewed a second time?

    Also, how do no-cost extensions fit in? do they count as 'year 6' of the grant?

  • datahound says:

    I think several factors are at work here. First, as you note, subsequent renewals do stagger more so the peak is broader and less apparent. Second, many investigators submit new grants rather than renewals for a variety of reasons including that they have move on to different problems or have written other grants that were funded in the meantime.

    No-cost extensions add to the years of the grant so, for example, they would count as year 6 and any subsequent competing renewal would count as year 7.

  • lurker says:

    DH- am I correct in interpreting the sheer # of Type 2's are fewer now than they were in 1994? 2014 (N=1536) versus 1994 (N=2653)? A 42% drop in Type 2 grants?

    Does this reflect much more churn, many more instances a lab can't keep the same "project" renewed but instead keeps the lab funded via a "new" project?

    Another indicator that times right now are way more cut-throat than they used to be, just a decade ago?

    • datahound says:

      lurker: Yes, you are correct about the drop. I will have to do more work to figure out what happened to folks who did not renew grants. In the meantime, I have posted more data on the trends.

  • Comradde PhysioProffe says:

    KILL ALL TJOSE OTHER FICKERS!! NOT MEEEEEEEEEEEEEEEE!

  • […] has a cool new analysis posted on the distribution of competing continuation R01/R37 awards (Type 2 in NIH grant […]

  • drugmonkey says:

    I don't think NCE years are counted, DH.

  • […] my recent post, I noted in passing that the number of Type 2 (Competing Renewal) awards (R01s and R37s) fell from […]

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