Evidence map›Paper›PMID 34511103›Full record

ArticleBMC musculoskeletal disorders2021

Novel nomogram for predicting the progression of osteoarthritis based on 3D-MRI bone shape: data from the FNIH OA biomarkers consortium.

Yingwei Sun, Chunbo Deng, Zhan Zhang, Xun Ma, Fenghua Zhou, Xueyong Liu

Abstract read
In one paragraph

Article in BMC musculoskeletal disorders, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

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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

7 citing papers in PubMed.

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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.

Yingwei Sun *Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, Liaoning Province, China.
Chunbo Deng *Department of Orthopedics, Shengjing Hospital of China Medical University, Shenyang, Liaoning Province, China.
Zhan ZhangDepartment of Orthopedics, Shengjing Hospital of China Medical University, Shenyang, Liaoning Province, China.
Xun MaDepartment of Rehabilitation, Shengjing Hospital of China Medical University, No.16, Puhe Street, Shenyang North New Area, Liaoning Province, 110134, Shenyang, China.
Fenghua ZhouDepartment of Rehabilitation, Shengjing Hospital of China Medical University, No.16, Puhe Street, Shenyang North New Area, Liaoning Province, 110134, Shenyang, China. Zhoufh@sj-hospital.org.
Xueyong LiuDepartment of Rehabilitation, Shengjing Hospital of China Medical University, No.16, Puhe Street, Shenyang North New Area, Liaoning Province, 110134, Shenyang, China. liusjh@sj-hospital.org.

Funding

Natural Science Foundation of Liaoning Province of China No. 20180530044The Joint Program of Key Research and Development of Liaoning Province of China No. 2020JH2/10300138
6 · The paper itself

Abstract

backgroundOsteoarthritis(OA) is a major source of pain, disability, and socioeconomic cost in worldwide. However, there is no effective means for the early diagnosis of OA, nor can it accurately predict the progress of OA. To develop and validate a novel nomogram to predict the radiographic progression of mild to moderate OA based on three-dimensional(3D)-MRI bone shape and bone shape change during 24 months.

methodAnalysis of publicly available data from the Foundation for the National Institutes of Health (FNIH) OA Biomarkers Consortium. Radiographic progression was defined as minimum radiographic narrowing of the medial tibiofemoral joint space of ≥ 0.7 mm from baseline at 24, 36, or 48 months. There were 297 knees with radiographic progression and 303 without. The bone shapes of the tibia, femur, and patella were evaluated by 3D-MRI at the baseline and at 24 months. Two nomograms were separately established by multivariate logistic regression analysis using clinical risk factors, bone shape at baseline (nomogram 0), or bone shape change at 24 months (nomogram Δ24). The discrimination, calibration, and usefulness were selected to evaluate the nomograms.

resultsThere were significant differences between groups in baseline Kellgren-Lawrence (KL) grade, gender, age, and tibia, femur, and patella shape. The areas under the curve (AUC) of nomogram 0 and nomogram Δ24 were 0.66 and 0.75 (p < 0.05), with accuracy of 0.62 and 0.69, respectively. Both nomograms had good calibration. The decision curve analysis ( DCA) showed that nomogram Δ24 had greater clinical usefulness than nomogram 0 when the risk threshold ranged from 0.04 to 0.86.

conclusionsNomograms based on 3D-MRI bone shape change were useful for predicting the radiographic progression of mild to moderate OA.

Indexed as

NomogramsOsteoarthritis, KneeBiomarkersDisease ProgressionHumansMagnetic Resonance ImagingNational Institutes of Health (U.S.)United StatesBiomarkersBone shapeNomogramOsteoarthritis

Identifiers

PMID34511103
PMCPMC8436553

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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 Socratic graph.