Update text for prospective registration plot

[delwen]

For the prospective registration metric, we will include more recent trials using a dataset that Nico previously extracted from the AACT (15.03.2019). It includes trials with a start date between 2006 – 2018 (2018 still included completely but not 2019).

TODO: update the Methods text accordingly.

[maia-sh]

Prepping the IV exclusion variables now, so we can choose to use as needed. Looking at our filters at https://github.com/quest-bih/clinical-dashboard/blob/main/prep/prep-intovalue.R#L9

I think we only need:

• iv_status
• iv_interventional

Right?

Disregard:

• iv_completion → since we want more recent trials
• has_german_umc_lead → since should all be via manual checks (I emailed NR just now to confirm)
• !(is_dupe & iv_version == 1) → IV dupes are irrelevant here

[maia-sh]

While it's no problem to add the boolean flags, I'm not sure we should filter for iv_status since that excludes 545 trials that would still be eligible to be inspected for prospective reg...

    iv_status = if_else(
      recruitment_status %in% c("Completed" , "Terminated" , "Suspended", "Unknown status"), TRUE, FALSE
    )

[maia-sh]

While I'm here, I can also switch start date filter (by 2018) to another boolean in case we change our mind to include trials started after 2018 (22 trials) [or less logically, with na start date (1 trial)]

@bgcarlisle : may mean some minor tweaks on your end too

[maia-sh]

Ok, I made the updates to prospective reg dataset and pushed to the branch: https://github.com/maia-sh/intovalue-data/commit/88c1103e98dd5ae54b2a6fad61d804e825f79fcd

@bgcarlisle : for the dashboard you could now update to exclude based on start_by_2018 and iv_interventional. As said above, i would not exclude based on iv_status but open for counterarguments.

@delwen for the text, i reran the query to ctgov so use today's date for latest query. also updated in query.log

[delwen]

• iv_completion → agree to disregard
• iv_interventional → agree to keep
• iv_status → given that DRKS and CT.gov prospective reg data is displayed in the same plot (with toggle), it could be confusing if we apply different iv_status inclusion/exclusion criteria to these datasets. But I see the argument to extend beyond completed trials. Would suggest we either re-apply our iv_status filter to the updated CT.gov dataset (and lose trials) or disregard the iv_status filter in both datasets. Note that we probably couldn't drop this filter completely; we'd probably still need to filter out trials that are 'Not yet recruiting' and 'Withdrawn' (we'd need to check this again and check equivalence in DRKS).
• has_german_umc_lead → let's wait for update from Nico
• duplicates: I guess there aren't any duplicate trials in this dataset?

[maia-sh]

iv_status → ah I forgot about that! indeed could be confusing... no duplicated in this dataset (I check that assertion)

[maia-sh]

@maia-sh: check for start 2006; filter start_by_2018 and iv_interventional and iv_status and let @bgcarlisle know its ready.

[maia-sh]

Changes pushed. I checked for 2006 min (all good). @bgcarlisle here is the dataset with exclusions filtered so ready to use.

@delwen Here's some draft text just for content This dataset includes trials led by a German UMC (based on manual evaluation [checking with Nico]) and registered in ClinicalTrials.gov. Trials were started between 2006 and 2018 inclusive per registry data available on 2021-10-06. In line with the primary IntoValue dataset, all are interventional trials with the eligible statuses ("Completed" , "Terminated" , "Suspended", "Unknown status").

[delwen]

Just adding that we decided to keep the iv_status exclusions for both the CT.gov and DRKS datasets even though we don't strictly need to only focus on completed trials for prospective registration. This means we lose ~500 CT.gov trials, but we gain parity between the plots and avoid having too many separate data sources with different criteria.

We can revisit this later if requested.

[delwen]

Nico suggested we limit the range of the DRKS prospective registration plot to start from 2006 (in line with the CT.gov plot). We'd lose 10 trials. I tend to agree. Again, parity but also because the earlier dates might cause confusion. Thoughts?

[delwen]

@bgcarlisle @maia-sh agree?

[bgcarlisle]

Yeah agreed! This should do it! https://github.com/quest-bih/clinical-dashboard/commit/9cff831baf944b1786aabf814d6e77ad6a35cde7

[delwen]

TODO: detail the inclusion/exclusion criteria for the different prospective registration datasets in more detail in the dashboard methods/tooltips.

[delwen]

Done.