Evidence map›Paper›PMID 35357077›Full record

ArticlePharmaceutical statistics2022

A treatment-specific marginal structural Cox model for the effect of treatment discontinuation.

Dana Johnson, Karen Pieper, Shu Yang

Abstract read
In one paragraph

Article in Pharmaceutical statistics, 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. Estimating the causal effects of multiple intermittent treatments with application to COVID-19.Journal of the Royal Statistical Society. Series C, Applied statistics · 2023
    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

3 authors.

Dana JohnsonBiostatistics, United Therapeutics Corp., Silver Spring, North Carolina, USA.
Karen PieperStatistics, Thrombosis Research Institute, London, UK.
Shu YangDepartment of Statistics, North Carolina State University, Raleigh, North Carolina, USA.ORCID 0000-0001-7703-707X

Funding

Statistical Methods for Cancer Clinical TrialsP01CA142538 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI DAVIDIAN, MARIE, KOSOROK, MICHAEL R · 2010 to 2019
$21.3M
Integrated Biostatistical Training for CVD ResearchT32HL079896 · NHLBI · NORTH CAROLINA STATE UNIVERSITY RALEIGH · PI Sean M O'Brien, Ana-Maria Staicu · 2006 to 2026
$4.1M
Transforming Clinical Trials for Elderly and Rare Cancers through Intelligent and Robust Information BorrowingR01AG066883 · NIA · NORTH CAROLINA STATE UNIVERSITY RALEIGH · PI Xiaofei Wang, Shu Yang · 2020 to 2026
$2.0M
Spatial Causal Inference for Wildland Fire Smoke Effects on Air Pollution and HealthR01ES031651 · NIEHS · NORTH CAROLINA STATE UNIVERSITY RALEIGH · PI REICH, BRIAN J., YANG, SHU · 2020 to 2024
$1.2M
NCI NIH HHS P01 CA142538NHLBI NIH HHS T32 HL079896NIA NIH HHS R01 AG066883NIEHS NIH HHS R01 ES031651
6 · The paper itself

Abstract

Patients taking a prescribed medication often discontinue their treatment; however, this may negatively impact their health outcomes. If doctors had statistical evidence that discontinuing some prescribed medication shortened, on average, the time to a clinical event (e.g., death), they could use that knowledge to encourage their patients to stay on the prescribed treatment. We describe a treatment-specific marginal structural Cox model for estimation of the causal effect of treatment discontinuation on a survival endpoint. The effect of treatment discontinuation is quantified by the hazard ratio of the event hazard rate had the population followed the regime "take treatment

Indexed as

AnticoagulantsAtrial FibrillationAdministration, OralHumansProbabilityProportional Hazards ModelsAnticoagulantsarticifial censoringcausal inferencediscontinuationinverse probability weightingtime-dependent confounding

Identifiers

PMID35357077
PMCPMC9481666

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.