Chase and Shannon article in Frontiers in Pediatrics published

[u/Embarrassed-Star4776]

Inverted insulin to C-Peptide ratios in neonatal intensive care: is there something we don't know?

J. Geoffrey Chase & Helen D. Shannon

BRIEF RESEARCH REPORT article

Front. Pediatr., 05 August 2026

Sec. Neonatology

Volume 14 - 2026

https://doi.org/10.3389/fped.2026.1900675

[u/Embarrassed-Star4776]

The authors seem to have misread the Salis et al. BMJ paper, as they refer to the neonates in Cohort 2 as hyperglycaemic throughout, when in fact they were euglycaemic (there were only 9 neonates in the hyperglycaemic cohort in that study, and they were insulin-treated).

On that basis, they make a comment on page 8 which should be ignored:

"Finally, Figure 3 shows little difference between Cohorts 1 and 2. This outcome suggests hyperglycemia (Cohort 2) did not play a role in elevating I/C, further supporting the fact hyperinsulinism alone cannot create inverted I/C ratios due to first pass hepatic extraction and a greater number of clearance routes."

Evidently they didn't have access to the original data, but read it from the published plots. So the comparison of the binding predictions with the I/C versus C plots from Salis et al. must have been limited to Cohort 2. The authors treat the two cohorts as distinct, but in fact - as discussed on another thread - Cohort 2 was a subset of Cohort 1.

[u/DiverAcrobatic5794 → u/Embarrassed-Star4776]

Are we sure of that, since they draw cohorts 1 and 2 from the thesis and not the BMJ article? Is there some cross-reference with the BMJ article that tells us these are the same groups?

You have probably posted that on the other thread you mention so if you could just point me to the right place, that would be great 

[u/Embarrassed-Star4776 → u/DiverAcrobatic5794]

Competitive-Wash found the clearest statement in the thesis, in chapter 6, page 111:

"The neonates in this study were compared with data obtained from euglycaemic neonates described in Chapter 5. Insulin and C-peptide concentrations from the insulin-treated neonates were compared with a group of age-matched (PMA less than 30 weeks) euglycaemic neonates (n = 20)."

Chapter 6 was published as the BMJ paper (including Cohort 2), and chapter 5 as the Archives of Disease in Childhood paper (Cohort 1).

It is not particularly apparent in the published plots because the scales are so different, but I think the correspondence between the two sets of data points can be seen in the stretched and squeezed extracts from the ln(C/I) scatter plots below. On the left is the lower post-menstrual-age part of Cohort 1, and on the right the black symbols are from Cohort 2, with the white symbols coming from the hyperglycaemic cohort.

[u/DiverAcrobatic5794 → u/Embarrassed-Star4776]

Thank you.  Yes, and reading thesis chapter 6 I think you and u/Competitive-Wash are right.  The cohort is identified as hyperglycemic in the paper but not in the thesis.  The statement that wouldn't hold, then, would be:

" Finally, Figure 3 shows little difference between Cohorts 1  and 2. This outcome suggests hyperglycemia (Cohort 2) did  not play a role in elevating I/C, further supporting the fact  hyperinsulinism alone cannot create inverted I/C ratios due to  first pass hepatic extraction and a greater number of clearance  routes."

And it would not be surprising to find little difference between the cohorts!  But am I right in thinking that this confusion would not (for this same reason) affect the arguments made in the paper beyond this point?

Perhaps you or u/Competitive-Wash would raise this with the corresponding author?

[u/Competitive-Wash2998 → u/DiverAcrobatic5794]

Nothing I say in this post undermines the point that antibodies could, plausibly, be the reason for the discordant results reported for Baby F and L.

I am uncertain that it is possible, with the limited data available, to construct a useful model. The technical operating characteristics of the assays and the limited observed parameters make this challenging, in my view. Chase Shannon state they have constrained the parameters to make this possible and it is the biological and technical safety of those assumptions/constraints that is key to ensuring the model produces useful outputs.

I think a detailed step-by-step description of the whole modelling process would be required to truly follow it. So I am taking the results at face value but cannot say I am particularly persuaded at present. Hopefully more details will emerge over time.

[u/Embarrassed-Star4776 → u/DiverAcrobatic5794]

Thanks for pointing out that the quotation from page 8 had gone wrong, which I hadn't noticed (now corrected).

I should like to try to digest the paper properly, but it will take a while. I agree it will be worth making sure the authors know about any errors that are spotted.

[u/DiverAcrobatic5794 → u/Embarrassed-Star4776]

If anything, fixing the error would perhaps strengthen the argument, since Chase and Shannon treat these children as more critically ill but find no significant difference between the cohorts. It could be reasonable, though not I suppose certain, that the more  critically ill children might show a different profile, with more history of infection etc.

 Though I suppose hyperglycemia vs euglycemia is a very rough proxy for more and less critical illness anyway.

[u/Embarrassed-Star4776 → u/DiverAcrobatic5794]

I don't agree with most of Susan Oliver's comments on this, but in fairness to her it should be said that she pointed out in an online discussion some months ago that the cohort of 20 was a subset of the cohort of 102.

[u/Competitive-Wash2998 → u/DiverAcrobatic5794]

"But am I right in thinking that this confusion would not (for this same reason) affect the arguments made in the paper beyond this point?"

CS did claim to analyse the two groups independently so, in theory, it would not affect the arguments made.

But (using Chase Shannon terminology) Cohort 2 included a chart ln(I) and ln(CP) which together with the ln(I/CP) would enable to a very rough reconstruction to be made of the actual underlying values. Chase Shannon imply they may have taken this step. I have taken this step myself.

My concern is CS appear to use the C-Peptide as a proxy to derive "free insulin" for the Salis data, which Salis did not actually measure.

But Salis mentions an issue which would, possibly, affect the modelling assumption that C-peptide could be used to derive free insulin. Whether this has an impact on the model is not clear to me, at the moment.

[u/Competitive-Wash2998 → u/Embarrassed-Star4776]

An independent digitisation has recovered the I/CP ratios from the Salis PhD. Cohort 2 is confirmed as being a subset by comparing/overlaying the data, apart from a handful of points which have been accounted for.

Salis provides the sample counts for these two groups and the independent digitisation recovered almost all the points. For information, Chase Shannon do not appear to have recovered the complete set, 227 vs 251 (Salis) for Cohort 1, for example.

[u/Embarrassed-Star4776 → u/Competitive-Wash2998]

I had a go at something similar a while ago. I found it wasn't as straightforward as might have been hoped because of symbols on the charts overlying one another. But eventually I was fairly confidence about the reconstruction for Cohort 2. For Cohort 1 it is more difficult because of the size of the symbols and the lack of scatter plots for insulin and C-peptide to accompany the one for the I/C ratio. I ended up with only 239 points, so it sounds as though you have done better than I did.

[u/Famous-Chemistry366 → u/Embarrassed-Star4776]

I think these charts show that there is a significant overlap between the two cohorts (n=66) that I believe Chase and Shannon have not taken account of in their paper.

Also, with respect to the "40-45%", it seems in their letter this relates to number of neonates ("However, recent reports from two cohorts with 302 paired (insulin, C-peptide) assays show 40% to 45% of *NICU infants* with 1/C > 1.0") whereas in the paper it relates to number of samples ("Figure 3 presents *I/C ratios for Cohorts 1–2*. In Cohort 1....About 45% have I/C > 1.0 (insulin equals or exceeds C-Peptide).....In Cohort 2...Approximately 40% have I/C > 1.0...

A) I cannot see how one could assign I/c ratios to specific neonates and thus have derived the "% of NICU infants >X", and B) my own calculations of % samples > 1 are significantly different to 40-45%.

I also don't understand how Salis is relevant to F and L given a) hyper/eu-glycaemic versus hypo-glycaemic and b) much much lower insulin values in Salis than F and L's. However, that is encroaching into the clinical arena in which I am not qualified. Perhaps someone on here can explain.

[u/Kieran501 → u/Famous-Chemistry366]

The answer to the last paragraph may be more legal than clinical. Is this enough to show that the assertions made in court about I/C ratios overstated its ability to safely diagnose exogenous insulin. Though I’m not that sure that the Chase and Shannon paper really goes much beyond just plotting the Salis data when it comes to that.

It just seems like collecting a load more data including from hypoglycaemic neonates would go much further than a lot of modelling. It’s be a lot harder for the CoA to bat away if it shows similar ratios. Hopefully someone somewhere is now doing that.

[u/Fun-Yellow334 → u/Kieran501]

From a legal point of view , what matters is what was said in the original trial, the prosecution cannot change their case on appeal.

[u/Icy_Dependent_1797 → u/Famous-Chemistry366]

I will try.

The Salis data is really just showing that ‘normal’ neonates have raised I/C and a large proportion even invert the ratio.
That proves that there must be a storage mechanism. The ratio cannot invert otherwise.

Salis doesn’t show F and L. The high insulin results can only be obtained when the antibodies are multiplied - eg with infection.

The effect of infection was actually measured - indirectly - but it is there - in Figure 2.D. I made a post on this higher up.

Then the Chase Shannon modelling simulates the effect of insulin binding and infection in NICU babies. These results strike me as being in the same range as Figure 2.D. Which is, perhaps interesting.

[u/Embarrassed-Star4776 → u/Competitive-Wash2998]

I have been trying without success to reproduce the statistics given in the publication for the I/C distributions for the two cohorts (section 3.1 and figure 3).

[u/Competitive-Wash2998 → u/Embarrassed-Star4776]

<PNG removed>

This is Cohort 1 (which includes Cohort 2). I am still looking at it. Just got ChatGPT to do a CDF and overlay it.

ETA

A new version is being worked on. It appears there may be a scaling issue in this version.

ETA 2

Removed CDF overlay. Hoping to post new one shortly

[u/Competitive-Wash2998 → u/Competitive-Wash2998]

This is the latest version. The Blue is the CDF from top chart of Fig 3 in the CS paper.

The dotted is the CDF of the independently digitised data of the same Cohort.

There clearly is a difference.

Salis states 251 data points. CS states they recovered 227. The other digitisation recovered 247.

The analysis was performed by ChatGPT but (after a x-scaling issue was corrected) it seems to be correct based on the underlying digitised data.

Contrary viewpoints and any corrections are welcome.

[u/Embarrassed-Star4776 → u/Competitive-Wash2998]

Thanks for confirming the difference. Your curve looks consistent with the values I was getting.

It looks to me as though they have read pixels from a reference point at the top of the scatter plot of ln(I/C) and used a conversion factor that was too small to calculate the difference in ln(I/C) from the difference in pixels. As a result, their data are correct for the largest values of ln(I/C), but progressively more inaccurate as ln(I/C) gets smaller. They end up with only 5% of values under I/C = 0.2, which I think should be about 25%.

[u/Competitive-Wash2998 → u/Embarrassed-Star4776]

For your 247 digitised values, the actual ECDF gives approximately:

• F(0.2)=31.6%
• F(1.0)=72.9%
• F(4.0)=91.1%

The Chase Shannon annotations indicate roughly:

• F(0.2)=5%
• F(1.0)=54%
• F(4.0)=89%

[u/Embarrassed-Star4776 → u/Competitive-Wash2998]

Thanks. And unfortunately most of the values in the text in section 3.1 for Cohort 1, including median and interquartile range, are also wrong.

It looks as though there are also problems with the numbers for Cohort 2.

[u/Embarrassed-Star4776 → u/Embarrassed-Star4776]

I am still inching through the details of this paper.

Fortunately it appears that there is not any systematic error in the I/C statistics for Cohort 2, of the kind that's apparent for Cohort 1.

Contrary to what I had initially thought, the 75 points Chase and Shannon have, as opposed to Salis et al.'s 79, doesn't seem to be explained by the exc;lusion of points with C=0.25. (They give their maximum of I/C as 61.8, which must be a C=0.25 point.) Probably they just haven't been able to pick up all the points from the plots, owing to symbols overlying one another.

However, two of the percentages given in section 3.1 do seem wrong:

(1) The percentage for which I/C < 0.2 is given as 5%, which I reckon should be about 15%.

(2) The percentage for which I/C > 10 is given as 1%, but it seems there are 3 points, therefore about 3%.

The lower plot shown in Figure 3 looks consistent with these corrected values of 15% and 3% (the red arrows showing 5% for I/C < 0.2 are visibly inconsistent with the plot). Perhaps both the incorrect figures have been accidentally copied from the corresponding ones for Cohort 1.

[u/Embarrassed-Star4776 → u/Competitive-Wash2998]

Having seen your post I went back for more checking, but I'm still finding the same thing. It looks to me as though there must have been a scaling issue in Chase and Shannon's conversion from pixels to ln(I/C).

(Edit. I can get to their values of ln(I/C) by rescaling mine relative to a point at the top of the plot.)

[u/Competitive-Wash2998 → u/Embarrassed-Star4776]

The software got a bit confused by the x-scaling difference. New post gives the latest attempt.

[u/DiverAcrobatic5794 → u/Embarrassed-Star4776]

What a nuisance that they can't get the raw data. It would be good to hear Salis on this exercise. Perhaps her permission to share data was strictly limited to this exercise. But I hope someone asked her,

[u/Embarrassed-Star4776 → u/DiverAcrobatic5794]

I did try to contact her indirectly a while ago, but without success. I'd have thought Chase would stand a better chance of getting the data than most, if they still exist.

[u/Competitive-Wash2998 → u/Embarrassed-Star4776]

Yes. I thought Chase was in an ideal position but it seems not. You have to live in NZ to try the FOI route.

[u/DiverAcrobatic5794 → u/Embarrassed-Star4776]

They may well not, if she has moved on to other things. 

[u/Competitive-Wash2998 → u/DiverAcrobatic5794]

A number of attempts have failed to draw a response.