Data from capillary electrophoresis analysis of serum from patients with suspected multiple myeloma
SND-ID: 2023-180. Version: 1. DOI: https://doi.org/10.5878/a2aa-kt50
Associated documentation
Citation
Creator/Principal investigator(s)
Victoria Rotter Sopasakis - University of Gothenburg, Institute of Biomedicine
Lillemor Mattsson Hultén - University of Gothenburg, Institute of Medicine
Maria Nilsson - Sahlgrenska University Hospital, Region Västra Götaland, Clinical Chemistry
Research principal
University of Gothenburg - Institute of Biomedicine
Description
Data contains personal data
Yes
Sensitive personal data
Yes
Type of personal data
Sample ID number and date of samples, analysis of serum samples
Code key exists
Yes
Language
Unit of analysis
Population
For this study we used a total of 67,073 patient serum samples from 34,567 individuals of which 14,626 were positive for M-protein. The average age was 61±21.4 years. The gender distribution was 15,892 men and 18,675 women.
Time Method
Study design
Diagnostic study
Time period(s) investigated
2015 – 2020
Number of individuals/objects
34657
Data format / data structure
Geographic spread
Geographic location: Västra Götaland County
Responsible department/unit
Institute of Biomedicine
Other research principals
Ethics Review
Swedish Ethical Review Authority - Ref. 2021-03301
Research area
Mathematical analysis (Standard för svensk indelning av forskningsämnen 2011)
Computational mathematics (Standard för svensk indelning av forskningsämnen 2011)
Probability theory and statistics (Standard för svensk indelning av forskningsämnen 2011)
Analytical chemistry (Standard för svensk indelning av forskningsämnen 2011)
Medical laboratory and measurements technologies (Standard för svensk indelning av forskningsämnen 2011)
Cancer and oncology (Standard för svensk indelning av forskningsämnen 2011)
Clinical laboratory medicine (Standard för svensk indelning av forskningsämnen 2011)
Medication and treatment (CESSDA Topic Classification)
Signs and symptoms; pathological conditions (CESSDA Topic Classification)
Specific diseases, disorders and medical conditions (CESSDA Topic Classification)