Evidence map›Paper›PMID 41781344›Full record

ReviewHelicobacter

Optimizing Benefits-Harms of H. pylori Screen-and-Treat Programs Tailored to the Regional Settings.

Duco T Mülder, Yi-Chia Lee, Mario Dinis-Ribeiro, Melissa McLeod, Jin Young Park, Iris Lansdorp-Vogelaar

Abstract readReview
In one paragraph

Review in Helicobacter. 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. Review
  2. Review
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

6 authors.

Duco T MülderEarly Detection, Prevention and Infections Branch, International Agency for Research on Cancer, Lyon, France.ORCID https://orcid.org/0000-0001-7226-322X
Yi-Chia LeeDepartment of Internal Medicine, College of Medicine, National Taiwan University and Departments of Medical Research and Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan.ORCID https://orcid.org/0000-0002-8160-1216
Mario Dinis-RibeiroDepartment of Gastroenterology, Porto Comprehensive Cancer Center and RISE@CI-IPO (Health Research Network), 4200-072 Porto, Portugal & MEDCIDS (Department of Community Medicine, Health Information, and Decision), Faculty of Medicine, University of Porto, Porto, Portugal.
Melissa McLeodDepartment of Public Health, University of Otago, Wellington, New Zealand.
Jin Young ParkEarly Detection, Prevention and Infections Branch, International Agency for Research on Cancer, Lyon, France.ORCID https://orcid.org/0000-0003-2491-5099
Iris Lansdorp-VogelaarDepartment of Public Health, Erasmus Medical Center, Rotterdam, the Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This article outlines how decision modeling can be used to optimize the cost-effectiveness of H. pylori screen-and-treat programs. Decision models enable the translation of data from pilot studies into locally tailored strategies by adapting test modalities, treatment options, and the need to retest specific to the local setting. We summarize existing evidence from modeling studies, which consistently demonstrate that H. pylori screen-and-treat is cost-effective across diverse populations. In addition, we discuss how decision modeling can support resource allocation, promote health equity, and guide implementation planning. Integrating H. pylori screen-and-treat into established preventive programs, such as colorectal cancer screening, may further increase efficiency and feasibility. The article concludes with a proposed research agenda to advance efficient H. pylori screen-and-treat programs across the globe.

Indexed as

Helicobacter InfectionsHelicobacter pyloriMass ScreeningCost-Benefit AnalysisCost-Effectiveness AnalysisDecision Support TechniquesHumans

Identifiers

PMID41781344
PMCPMC12960071

What OpenQuestion holds

Textmetadata
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.