Evidence map›Paper›PMID 38637815›Full record

ArticleBMC medicine2024

Variability in the prevalence of depression among adults with chronic pain: UK Biobank analysis through clinical prediction models.

Lingxiao Chen, Claire E Ashton-James, Baoyi Shi, Maja R Radojčić, David B Anderson, Yujie Chen, David B Preen, John L Hopper, Shuai Li, Minh Bui and 6 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC medicine, 2024. 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
4.0field-weighted citation impact, top 7% of its field
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

7 citing papers in PubMed, 9 citations in OpenAlex.

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  7. Editorial: Musculoskeletal pain phenotypes and personalised pain medicine.Frontiers in pain research (Lausanne, Switzerland) · 2024
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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

16 authors at 9 institutions in 5 countries.

Lingxiao Chen *Department of Orthopaedics, Qilu Hospital of Shandong University, Shandong University Centre for Orthopaedics, Advanced Medical Research Institute, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, People's Republic of China.
Claire E Ashton-James *Sydney Medical School, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia.
Baoyi ShiDepartment of Biostatistics, Mailman School of Public Health, Columbia University, New York, USA.
Maja R RadojčićDivision of Psychology and Mental Health, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.
David B AndersonSchool of Health Sciences, Faculty of Medicine and Health, University of Sydney, Sydney, Australia.
Yujie ChenProgram in Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, ON, Canada.
David B PreenSchool of Population and Global Health, The University of Western Australia, Perth, Australia.
John L HopperCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia.
Shuai LiCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia.
Minh BuiCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia.
Paula R BeckenkampSchool of Health Sciences, Faculty of Medicine and Health, University of Sydney, Sydney, Australia.
Nigel K ArdenNuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK.
Paulo H FerreiraSchool of Health Sciences, Faculty of Medicine and Health, University of Sydney, Sydney, Australia.
Hengxing ZhouDepartment of Orthopaedics, Qilu Hospital of Shandong University, Shandong University Centre for Orthopaedics, Advanced Medical Research Institute, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, People's Republic of China. zhouhengxing@sdu.edu.cn.
Shiqing FengDepartment of Orthopaedics, Qilu Hospital of Shandong University, Shandong University Centre for Orthopaedics, Advanced Medical Research Institute, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, People's Republic of China. shiqingfeng@sdu.edu.cn.
Manuela L FerreiraSydney Musculoskeletal Health, The Kolling Institute, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia.
University of Sydney · AUUniversity of Melbourne · AUSecond Hospital of Shandong University · CNColumbia University · USNuffield Orthopaedic Centre · GBQilu Hospital of Shandong University · CNUniversity of Manchester · GBUniversity of Toronto · CAUniversity of Western Australia · AU

Funding

Taishan Scholars Program of Shandong Province- Pandeng Taishan Scholars tspd20210320Taishan Scholars Program of Shandong Province-Young Taishan Scholars tsqn201909197
6 · The paper itself

Abstract

backgroundThe prevalence of depression among people with chronic pain remains unclear due to the heterogeneity of study samples and definitions of depression. We aimed to identify sources of variation in the prevalence of depression among people with chronic pain and generate clinical prediction models to estimate the probability of depression among individuals with chronic pain.

methodsParticipants were from the UK Biobank. The primary outcome was a "lifetime" history of depression. The model's performance was evaluated using discrimination (optimism-corrected C statistic) and calibration (calibration plot).

resultsAnalyses included 24,405 patients with chronic pain (mean age 64.1 years). Among participants with chronic widespread pain, the prevalence of having a "lifetime" history of depression was 45.7% and varied (25.0-66.7%) depending on patient characteristics. The final clinical prediction model (optimism-corrected C statistic: 0.66; good calibration on the calibration plot) included age, BMI, smoking status, physical activity, socioeconomic status, gender, history of asthma, history of heart failure, and history of peripheral artery disease. Among participants with chronic regional pain, the prevalence of having a "lifetime" history of depression was 30.2% and varied (21.4-70.6%) depending on patient characteristics. The final clinical prediction model (optimism-corrected C statistic: 0.65; good calibration on the calibration plot) included age, gender, nature of pain, smoking status, regular opioid use, history of asthma, pain location that bothers you most, and BMI.

conclusionsThere was substantial variability in the prevalence of depression among patients with chronic pain. Clinically relevant factors were selected to develop prediction models. Clinicians can use these models to assess patients' treatment needs. These predictors are convenient to collect during daily practice, making it easy for busy clinicians to use them.

Indexed as

AsthmaChronic PainAdultBiological Specimen BanksDepressionHumansMiddle AgedModels, StatisticalPrevalencePrognosisUK BiobankBig dataChronic painClinical prediction modelDepressionPrevalenceVariability

Identifiers

PMID38637815
PMCPMC11027372
OpenAlexW4394909513

What OpenQuestion holds

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LicenceCC BY
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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.