Evidence map›Paper›PMID 42780309›Full record

ArticleDialogues in health2026

Treatment switching in oncology evidence synthesis: a systematic review of meta-analytical practices incorporating time-dependent confounding, censoring bias, and patient-level variability.

Edward Kurnia Setiawan Limijadi

Abstract read
In one paragraph

Article in Dialogues in health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

1 author.

Edward Kurnia Setiawan LimijadiUniversitas Diponegoro, Indonesia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Treatment switching in the oncology trials introduced time-dependent confounding and informative censoring, which complicated the unbiased estimation of treatment effects in evidence synthesis. Objectives: To systematically assess the meta-analytical practices that are used for adjusting treatment switching in oncology, with an emphasis on handling time-dependent confounding, censoring bias, as well as patient-level variability. Methods: A systematic review was conducted using PRISMA 2020 guidelines. The databases searched systematically are MEDLINE, Embase, Cochrane Library and Web of Science, and the studies published between 2015 and the last search date were included (provide exact search date). The review was conducted with the reporting standards from the PRISMA 2020 statement, and because there was methodological heterogeneity, an analysis of the findings was conducted using a structured narrative synthesis. The eligible studies included randomized trials, simulation studies, observational studies, and health technology assessments, with the application of formal statistical methods to adjust for treatment switching. Results: Six studies had met the inclusion criteria. Common methods involved rank-preserving structural failure time models (RPSFTM), marginal structural models (MSMs), and inverse probability of censoring weighting (IPCW). The modeling assumptions, the specification of the model, the switching mechanisms, the method of dealing with time-dependent confounders, and the method of dealing with censoring were shown to vary across the included studies and affect the results and estimates of the treatment effects. The reporting practices were varying, and there was limited integration into the meta-analytical frameworks. Conclusion: Adjustment regarding the treatment switching is methodologically complex, having no universally optimal approach. Enhanced level of transparency, methodological standardization, along with the consideration of patient-level heterogeneity, is important to improve the validity of the oncology evidence synthesis.

Indexed as

And inverse probability of censoring weighting (IPCW)Marginal structural models (MSMs)OncologyRank-preserving structural failure time models (RPSFTM)Treatment switching

Identifiers

PMID42780309
PMCPMC13597185

What OpenQuestion holds

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Registered trials

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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.