Evidence map›Paper›PMID 37602779›Full record

ReviewJournal of comparative effectiveness research2023

Increasing transparency in indirect treatment comparisons: is selecting effect modifiers the missing part of the puzzle? A review of methodological approaches and critical considerations.

Andreas Freitag, Laura Gurskyte, Grammati Sarri

Abstract readReview
In one paragraph

Review in Journal of comparative effectiveness research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Review
  5. Article
  6. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Andreas FreitagCytel, Evidence Value & Access, London, WC2B 4HN, UK.ORCID 0000-0003-0265-9338
Laura GurskyteCytel, Evidence Value & Access, Rotterdam, 3012 NJ, The Netherlands.ORCID 0000-0001-5031-9886
Grammati SarriCytel, Real-World Advanced Analytics, London, WC2B 4HN, UK.ORCID 0000-0001-5536-8038

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Failure to adjust for effect modifiers (EMs) in indirect treatment comparisons (ITCs) can produce biased and uncertain effect estimates. This is particularly important for health technology assessments (HTAs), where the availability of new treatments is based on comparative effectiveness results. Much emphasis has been placed on advancing ITC methods to adjust for EMs, yet whether EMs are appropriately identified for the conduct of ITCs in the first place is unclear. To understand the extent of guidance and requirements for the selection of EMs for ITCs currently available and if and how this guidance is applied in practice, a series of pragmatic reviews of guidance documents from HTA and non-payer organizations, primary published ITC analyses, and prior HTA submissions in two indications (non-small cell lung cancer and psoriasis) was conducted. The reviews showed that current ITC guidance mainly focused on developing analytical methods to adjust for EMs. Some organizations, such as HTA bodies in the UK, France and Germany, recommended the use of literature reviews, expert opinion and statistical methods to identify EMs. No detailed guidance on the selection process or the appropriate literature review approach was found. Similar trends were identified through the database search and review of prior HTA submissions; only few published ITCs and submissions included information on the EM selection process which was either based on findings from the literature, trial subgroup analyses, or clinical input. No reference to a systematic selection approach was found. There is an urgent need to fill the guidance gap identified across the reviews by including a step in ITC guidelines on how EMs should be identified through systematic reviews, formal expert elicitation, and a quantitative assessment of the EM distribution. Researchers and manufacturers are also encouraged to improve transparent reporting and justification of their selection of EMs to allow for an independent review of the set of factors being considered for adjustment. Both will contribute toward reducing bias in the ITC results and ultimately increase confidence in decision-making.

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsFranceGermanyHumanscomparative effectivenesseffect modifierhealth technology assessmentindirect treatment comparisonliterature reviewmatching-adjusted indirect comparisonnetwork meta-analysisprognostic variablesimulated treatment comparison

Identifiers

PMID37602779
PMCPMC10690444

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.