Evidence map›Paper›PMID 42689061›Full record

ArticleJournal of dental sciences2026

Development of a risk scoring system for predicting post-extraction medication-related osteonecrosis of jaws: A derivation and validation cohort study.

Ling-Ying Wei, Ching-Ming Chiu, Sang-Heng Kok, Hung-Ying Lin, Wei-Yih Chiu, Hao-Hong Chang, Shih-Jung Cheng, Jang-Jaer Lee

Abstract read
In one paragraph

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

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0citing papers in PubMed
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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

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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

8 authors.

Ling-Ying WeiDivision of Oral and Maxillofacial Surgery, Department of Dentistry, National Taiwan University Hospital, Taipei, Taiwan.
Ching-Ming ChiuDepartment of Family Medicine, National Taiwan University Hospital, Taipei, Taiwan.
Sang-Heng KokDivision of Oral and Maxillofacial Surgery, Department of Dentistry, National Taiwan University Hospital, Taipei, Taiwan.
Hung-Ying LinDivision of Oral and Maxillofacial Surgery, Department of Dentistry, National Taiwan University Hospital, Taipei, Taiwan.
Wei-Yih ChiuDivision of Endocrinology and Metabolism, Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan.
Hao-Hong ChangDivision of Oral and Maxillofacial Surgery, Department of Dentistry, National Taiwan University Hospital, Taipei, Taiwan.
Shih-Jung ChengDivision of Oral and Maxillofacial Surgery, Department of Dentistry, National Taiwan University Hospital, Taipei, Taiwan.
Jang-Jaer LeeDivision of Oral and Maxillofacial Surgery, Department of Dentistry, National Taiwan University Hospital, Taipei, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background/purpose: Although risk factors for medication-related osteonecrosis of the jaw (MRONJ) are known, clinical assessment prior to dental extraction remains largely subjective. We aimed to develop and externally validate a simple clinical risk scoring system to predict post-extraction MRONJ in osteoporotic patients receiving antiresorptive therapy (ART) and support evidence-based clinical decision-making. Materials and methods: This retrospective cohort study used a derivation cohort (N = 1067 extractions, 2003-2022) to develop a 5- to 16-point risk score system based on five predictors (age ≥75, ART duration ≥24 months, bisphosphonate use, drug interruption Results: MRONJ prevalence was lower in the validation cohort (2.2% vs. 24.5%; Conclusion: The model demonstrates good discrimination and excellent "rule-out" utility in a real-world, low-prevalence setting, identifying low-risk patients (

Indexed as

Medication-related osteonecrosis of the jaws (MRONJ)OsteoporosisRisk scoreRisk stratificationTooth extraction

Identifiers

PMID42689061
PMCPMC13536377

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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.