Evidence map›Paper›PMID 40853930›Full record

ArticlePloS one2025

Average annual costs of Rheumatoid Arthritis estimated by inverse probability weighting and their influence factors: A cross-sectional study based on Chinese Registry of Rheumatoid arthritis (CREDIT) Cohort.

Bing Yu, Lin Qiao, Lu Li, Keying Zuo, Liangming Li, Li Wang, Nan Jiang, Qian Wang, Mengtao Li, Yanhong Wang and 1 more

Abstract readMulticenter Study
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

11 authors.

Bing YuDepartment of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences & School of Basic Medicine Peking Union Medical College, Beijing, China.ORCID https://orcid.org/0009-0003-8531-1675
Lin QiaoDepartment of Rheumatology and Clinical Immunology, Chinese Academy of Medical Sciences & Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases (NCRC-DID), Ministry of Science & Technology, Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital (PUMCH), Beijing, China.
Lu LiDepartment of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences & School of Basic Medicine Peking Union Medical College, Beijing, China.
Keying ZuoDepartment of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences & School of Basic Medicine Peking Union Medical College, Beijing, China.
Liangming LiDepartment of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences & School of Basic Medicine Peking Union Medical College, Beijing, China.
Li WangDepartment of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences & School of Basic Medicine Peking Union Medical College, Beijing, China.
Nan JiangDepartment of Rheumatology and Clinical Immunology, Chinese Academy of Medical Sciences & Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases (NCRC-DID), Ministry of Science & Technology, Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital (PUMCH), Beijing, China.
Qian WangDepartment of Rheumatology and Clinical Immunology, Chinese Academy of Medical Sciences & Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases (NCRC-DID), Ministry of Science & Technology, Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital (PUMCH), Beijing, China.
Mengtao LiDepartment of Rheumatology and Clinical Immunology, Chinese Academy of Medical Sciences & Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases (NCRC-DID), Ministry of Science & Technology, Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital (PUMCH), Beijing, China.
Yanhong WangDepartment of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences & School of Basic Medicine Peking Union Medical College, Beijing, China.ORCID https://orcid.org/0000-0003-3436-4673
Xinping TianDepartment of Rheumatology and Clinical Immunology, Chinese Academy of Medical Sciences & Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases (NCRC-DID), Ministry of Science & Technology, Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital (PUMCH), Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo date, the evidences of economic burden for the RA individual in the real-world clinical practice were still limited in China. This study aimed to estimate average annual costs of rheumatoid arthritis (RA) patients using inverse probability weighting (IPW) and their influence factors.

methodsA multicenter, cross-sectional study was conducted and the RA patients who met inclusion criteria on CREDIT cohort were invited to participate the survey. After they signed the informed confirm form, the information of outpatient and inpatient expenditures in the past year were collected through online questionnaires. Medical records were retrieved from the Chinese Rheumatology Information System (CRIS). Propensity scores for sample using the Generalized Boosted Model (GBM) method were used to calculate IPW, so that we produced the weighted population similar to the target of RA patients on CREDIT. Bootstrap methods were used to estimate average costs and 95% confidence intervals with 1,000 samples. Indirect costs were estimated using the human capital approach. Weighted multivariate regression identified factors influencing average annual costs.

resultsIn this study, a total of 18,507 patients from the CREDIT database met the recruitment criteria. Among them, 1,293 patients from 152 hospitals across 29 provinces in China completed the questionnaire and were included in our analysis. The average annual total costs per patient by the Bootstrap method on the weighted population was about 41,971 CNY (Bootstrap 95%CI: 37,107-47,046 CNY), in which more than 75% were the direct costs. Moreover, in the direct costs, the medical costs accounted for nearly 89% and even half of them (approximately 59.7%) was medication expense. The moderate or high disease activity status, hospitalization in last year, history of comorbidity, the treatment of biologics or glucocorticoids were also found to substantially increase average annual costs of RA in our study.

conclusionsThis study provided reliable insight into evaluating the economic burden of RA for the individuals and their families in the real-world clinical practice of China.

Indexed as

Arthritis, RheumatoidCost of IllnessHealth Care CostsAdultAgedChinaCohort StudiesCross-Sectional StudiesEast Asian PeopleFemaleHumansMaleMiddle AgedProbabilityRegistriesSurveys and Questionnaires

Identifiers

PMID40853930
PMCPMC12377572

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.