Practical delta check limits for tumour markers in different clinical settings

Author:

Yu Shinae1ORCID,Shin Kyung-Hwa2ORCID,Shin Sunghwan3ORCID,Lee Hyeyoung4ORCID,Yoo Soo Jin5ORCID,Jun Kyung Ran1ORCID,Shin Hangsik6ORCID,Kim Sollip7ORCID

Affiliation:

1. Department of Laboratory Medicine , Haeundae Paik Hospital, Inje University College of Medicine , Busan , Republic of Korea

2. Department of Laboratory Medicine and Biomedical Research Institute , Pusan National University Hospital , Busan , Republic of Korea

3. Department of Laboratory Medicine , Ilsan Paik Hospital, Inje University College of Medicine , Goyang , Republic of Korea

4. Department of Laboratory Medicine , International St. Mary’s Hospital, College of Medicine, Catholic Kwandong University , Incheon , Republic of Korea

5. Department of Laboratory Medicine , Sanggye Paik Hospital, Inje University College of Medicine , Seoul , Republic of Korea

6. Department of Digital Medicine , Asan Medical Center, University of Ulsan College of Medicine , Seoul , Republic of Korea

7. Department of Laboratory Medicine , Asan Medical Center, University of Ulsan College of Medicine , Seoul , Republic of Korea

Abstract

Abstract Objectives Few studies have reported on delta checks for tumour markers, even though these markers are often evaluated serially. Therefore, this study aimed to establish a practical delta check limit in different clinical settings for five tumour markers: alpha-fetoprotein, cancer antigen 19-9, cancer antigen 125, carcinoembryonic antigen, and prostate-specific antigen. Methods Pairs of patients’ results (current and previous) for five tumour markers between 2020 and 2021 were retrospectively collected from three university hospitals. The data were classified into three subgroups, namely: health check-up recipient (subgroup H), outpatient (subgroup O), and inpatient (subgroup I) clinics. The check limits of delta percent change (DPC), absolute DPC (absDPC), and reference change value (RCV) for each test were determined using the development set (the first 18 months, n=179,929) and then validated and simulated by applying the validation set (the last 6 months, n=66,332). Results The check limits of DPC and absDPC for most tests varied significantly among the subgroups. Likewise, the proportions of samples requiring further evaluation, calculated by excluding samples with both current and previous results within the reference intervals, were 0.2–2.9% (lower limit of DPC), 0.2–2.7% (upper limit of DPC), 0.3–5.6% (absDPC), and 0.8–35.3% (RCV99.9%). Furthermore, high negative predictive values >0.99 were observed in all subgroups in the in silico simulation. Conclusions Using real-world data, we found that DPC was the most appropriate delta-check method for tumour markers. Moreover, Delta-check limits for tumour markers should be applied based on clinical settings.

Funder

The Asan Institute for Life Sciences, Asan Medical Center, Seoul, Korea.

Publisher

Walter de Gruyter GmbH

Subject

Biochemistry (medical),Clinical Biochemistry,General Medicine

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Machine learning-based delta check method for detecting misidentification errors in tumor marker tests;Clinical Chemistry and Laboratory Medicine (CCLM);2023-12-14

2. Deep Learning-Based Sample Misidentification Error Detection in Clinical Chemistry Test;2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology;2023-12-07

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