Jon Deeks FMedSci Profile picture
Biostatistician trying to work out the best ways of evaluating medical tests. Views expressed are my own and do not necessarily reflect my employer or funders.

Jul 7, 2021, 11 tweets

Even more data on LFTs out today.

@dhscgovuk released report of studies of Innova and Orient Gene, and their interpretation of findings.

Includes unpublished studies

BUT Clear evidence of post hoc interpretation of results based on naïve definition of infectiousness.

1/10

Long link is here:

gov.uk/government/pub…

2/10

@dhscgov define

HIGH viral load as >1,000,000 RNA/ml and appear to consider that these are the only cases which matter.

10,000 to 1,000,000 is LOW (not moderate)

<10,000 MINIMAL.

This is despite acknowledging there is no cut-off that categorises people as infectious

3/10

So policy is based on EXPERT OPINION ignoring EVIDENCE AND DATA.

There is absolutely no step change at Ct=18.3 (which is 1,000,000) in their graph of risk of secondary cases

This categorisation is a post hoc subgroup definition which makes the tests look falsely good.

4/10

All graphs in the report show sensitivity results in these three categories.

5/10

New studies include a University pilot in asymptomatic students (is this Durham University from last autumn? ) - test identified 5 of 17 cases sensitivity of 29%.

Liverpool, Birmingham and this study are now the only three in people without symptoms.

6/10

There are also 5 studies done at Regional test and trace centres in people with symptoms.

Including three with self-use testing (two or Innova, one of Orient Gene).

Some suggestion that sensitivity drops with self-testing for Innova by ~10%

7/10

But

STILL No studies of self-use in people without symptoms

STILL No studies of use in children at all.

8/10

There is a shocking amount of detail missing from these reports. Little attempt to report in line with the STARD reporting criteria.

There is no reason not to do this and it makes it very difficult to assess the risk of bias and applicability of these findings.

9/10

Key issue is equating viral load>1,000,000 as infectious and (more importantly) viral load <1,000,000 as not infectious.
Use of such a high threshold falsely makes tests look good.
Implying everybody else has “little infectious virus” is wrong and puts our health at risk.
10/10

Also of interest to note that the report cites Beale S as the source of the one in three people being asymptomatic.
The data from this review are below. Looks more like on in four than one in three. Can anybody explain?

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