Evidence map›Paper›PMID 40401462›Full record

ArticleAnnals of medicine2025

Construction of a predictive model for relapse of primary autoimmune hemolytic anemia: a retrospective cohort study.

Pan Li, Chuanqi Zhong, Xianjun Huang, Zhi Cai, Tianhong Guo

Abstract read
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Article in Annals of medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Pan LiDepartment of Oncology, Xuyong County People's Hospital, Luzhou, Sichuan, China.
Chuanqi ZhongClinical Laboratory, Luzhou Second People's Hospital, Luzhou, Sichuan, China.
Xianjun HuangDepartment of Transfusion, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China.
Zhi CaiClinical Laboratory Diagnostics, the Southwest Medical University, Luzhou, Sichuan, China.
Tianhong GuoDepartment of Transfusion, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China.ORCID 0009-0004-9164-4668

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo develop a machine learning-based model to predict the relapse risk of Primary Autoimmune Haemolytic Anaemia (AIHA) after the last remission.

methodsA retrospective study was conducted on primary AIHA cases who visited the Affiliated Hospital of Southwest Medical University and Xuyong County People's Hospital from May 2017 to May 2022. Cases were categorized as relapsed or non-relapsed based on the 1-year outcomes. Twenty-two features were analyzed to identify relapse risk factors. The least absolute shrinkage and selection operator (LASSO) regression model and multivariate logistic regression analysis were used to establish a predictive model. The

resultsA total of 232 cases of primary AIHA were included, and five potential variables including 'DAT results', 'Hb', 'Multiline therapy', 'Complicating ITP', and 'Complicating infection', have been screened for constructing a 1-year relapse risk prediction nomogram for primary AIHA. The nomogram has a

conclusionsBy following the current diagnostic and treatment criteria for AIHA in China, we retrospectively collect a multitude of medical records and analyze several relevant variables of AIHA, construct a predictive model by machine learning. Using this 1-year relapse risk nomogram can effectively predict the risk of relapse within 1 year after remission of primary AIHA.

Indexed as

Anemia, Hemolytic, AutoimmuneAdultAgedFemaleHumansMachine LearningMaleMiddle AgedNomogramsRecurrenceRetrospective StudiesRisk AssessmentRisk FactorsROC CurveYoung AdultAutoimmune haemolytic anemiamachine learningnomogramsrelapse

Identifiers

PMID40401462
PMCPMC12100961

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