Evidence map›Paper›PMID 36733365›Full record

ArticleFrontiers in oncology2022

Landmark mediation survival analysis using longitudinal surrogate.

Jie Zhou, Xun Jiang, H Amy Xia, Brian P Hobbs, Peng Wei

Abstract read
In one paragraph

Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Robust evaluation of longitudinal surrogate markers with censored data.Journal of the Royal Statistical Society. Series B, Statistical methodology · 2025
    Article
  2. Article
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

5 authors.

Jie ZhouDepartment of Biostatistics and Pharmacometrics, Neuroscience Global Drug Development, Novartis, East Hanover, NJ, United States.
Xun JiangCenter for Design and Analysis, Amgen, Thousand Oaks, CA, United States.
H Amy XiaCenter for Design and Analysis, Amgen, Thousand Oaks, CA, United States.
Brian P HobbsDepartment of Population Health, The University of Texas, Austin, TX, United States.
Peng WeiDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clinical cancer trials are designed to collect radiographic measurements of each patient's baseline and residual tumor burden at regular intervals over the course of study. For solid tumors, the extent of reduction in tumor size following treatment is used as a measure of a drug's antitumor activity. Statistical estimation of treatment efficacy routinely reduce the longitudinal assessment of tumor burden to a binary outcome describing the presence versus absence of an objective tumor response as defined by RECIST criteria. The objective response rate (ORR) is the predominate method for evaluating an experimental therapy in a single-arm trial. Additionally, ORR is routinely compared against a control therapy in phase III randomized controlled trials. The longitudinal assessments of tumor burden are seldom integrated into a formal statistical model, nor integrated into mediation analysis to characterize the relationships among treatment, residual tumor burden, and survival. This article presents a frameworkfor landmark mediation survival analyses devised to incorporate longitudinal assessment of tumor burden.

Indexed as

functional principal component analysislandmark analysislongitudinal analysismediation analysisoncologyRECIST

Identifiers

PMID36733365
PMCPMC9887328

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.