Evidence map›Paper›PMID 38418448›Full record

ArticleScientific reports2024

Quantitative risk factor analysis of prior disease condition and socioeconomic status with the multiple myeloma development: nationwide cohort study.

Suein Choi, Eunjin Kim, Jinhee Jung, Sung-Soo Park, Chang-Ki Min, Seunghoon Han

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.4field-weighted citation impact, top 20% 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

5 citing papers in PubMed, 3 citations in OpenAlex.

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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 at 2 institutions in 1 country.

Suein Choi *Department of Pharmacology, College of Medicine, The Catholic University of Korea, 222 Banpodaero, Seochogu, Seoul, Republic of Korea.
Eunjin Kim *Department of Pharmacology, College of Medicine, The Catholic University of Korea, 222 Banpodaero, Seochogu, Seoul, Republic of Korea.
Jinhee JungDepartment of Pharmacology, College of Medicine, The Catholic University of Korea, 222 Banpodaero, Seochogu, Seoul, Republic of Korea.
Sung-Soo ParkDepartment of Hematology, Seoul St. Mary's Hematology Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
Chang-Ki MinDepartment of Hematology, Seoul St. Mary's Hematology Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
Seunghoon HanDepartment of Pharmacology, College of Medicine, The Catholic University of Korea, 222 Banpodaero, Seochogu, Seoul, Republic of Korea. waystolove@catholic.ac.kr.
Catholic University of Korea · KRThe Catholic University of Korea Seoul St. Mary's Hospital · KR

Funding

Ministry of Health and Welfare HA21C0013
6 · The paper itself

Abstract

Early diagnosis and following management are important determinants of the prognosis of multiple myeloma (MM). However, screening for MM is not routinely performed because it is rare disease. In this study, we evaluated the association of prior disease condition and socioeconomic status (SES) with MM diagnosis and developed a simple predictive model that can identify patients at high risk of developing MM who may need screening using nationwide database from South Korea. According to multivariate logistic regression analysis, eight prior disease conditions and SES before diagnosis were shown to be predictors of MM development and selected for score development. Total prediction scores were categorized into four groups: patients without any risk (≤ 0) intermediate-1 (0.5-9), intermediate-2 (9-14), and high risk (> 14). The odds ratios for developing MM in the intermediate-1, intermediate-2, and high-risk groups were 1.29, 3.07, and 4.62, respectively. The association of prior disease conditions and SES with MM diagnosis were demonstrated and the simple scoring system to predict the MM risk was developed. This scoring system is also provided by web-based application and could be a useful tool to support clinicians in identifying potential candidates for MM screening.

Indexed as

Multiple MyelomaCohort StudiesHumansRisk AssessmentRisk FactorsSocial Class

Identifiers

PMID38418448
PMCPMC10902317
OpenAlexW4392240478

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.