ArticleSupportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer2025
Predictive risk model of mild cognitive impairment in patients with malignant haematological diseases after haematopoietic stem cell transplantation.
Article in Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 2 of them syntheses that pooled it.
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Who cites it
4 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Longitudinal Neurocognitive Changes for Patients With Hematologic Malignancies Undergoing Hematopoietic Stem Cell Transplantation: A Systematic Review With Structured Narrative Synthesis.European journal of haematology · 2026Pooled it
- Addressing the evidence gap: exploratory insights into dual challenges of mild cognitive impairment and hematologic cancer in older adults through mixed methods and social listening study.European geriatric medicine · 2026Pooled it
- Evidence-Based Strategies for Addressing Cancer- and Treatment-Related Cognitive Impairment: A Review.Biomolecules & therapeutics · 2026Review
- Symptom Cluster Trajectories of Cough, Shortness of Breath, and Disturbed Sleep in Patients Undergoing Lung Cancer Surgery: A Longitudinal Study.Annals of surgical oncology · 2026Article
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Authors and funding
9 authors.
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Abstract
objectiveThis study is to develop and validate a robust risk prediction model for mild cognitive impairment (MCI) in patients with malignant haematological diseases after haematopoietic stem cell transplantation (HSCT).
methodsIn this study, we analysed the clinical data of the included patients. Logistic regression analysis was used to identify independent risk factors for cognitive impairment after HSCT in patients with malignant haematological diseases, and a risk prediction model was constructed. Multiple cohorts of patients with haematological malignancies after HSCT (282 cases) from the Affiliated Hospital of Xuzhou Medical University and the First People's Hospital of Yancheng City between April 2019 and February 2022, and patients from the Affiliated Huaian No.1 People's Hospital of Nanjing Medical University between March 2022 and July 2023 were used for external validation. Logistic regression analysis was performed to develop the predictive model. The predictive value and consistency of the model were evaluated using the area under the curve (AUC) and calibration method, respectively. Decision curve analysis (DCA) was performed to access the utility of the model.
resultsApproximately half (52.26%) of the patients in the study developed mild cognitive impairment (MCI). Older age, allogeneic HSCT, anxiety, graft-versus-host disease, and longer hospital stay were associated with a higher risk of developing MCI. ROC curve analysis confirmed the sound performance of the predictive model and external validation, with AUC of 0.897 and 0.789 respectively. The direction of the calibration curves of the training and validation sets is closer to the diagonal (ideal curve), indicating good model consistency; the DCA curves also show that the model has good predictive ability and stability.
conclusionsWe conclude that it is possible to predict mild cognitive impairment with readily available, mostly pretransplant predictors. The accuracy of the risk prediction models can be improved for use in clinical practice, possibly by adding pretransplant patient-reported functioning and comorbidities.
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