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Cancer screening in hospitalized ischemic stroke patients: a multicenter study focused on multiparametric analysis to improve management of occult cancers

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Abstract

Background/aims

The reciprocal promotion of cancer and stroke occurs due to changes in shared risk factors, such as metabolic pathways and molecular targets, creating a “vicious cycle.” Cancer plays a direct or indirect role in the pathogenesis of ischemic stroke (IS), along with the reactive medical approach used in the treatment and clinical management of IS patients, resulting in clinical challenges associated with occult cancer in these patients. The lack of reliable and simple tools hinders the effectiveness of the predictive, preventive, and personalized medicine (PPPM/3PM) approach. Therefore, we conducted a multicenter study that focused on multiparametric analysis to facilitate early diagnosis of occult cancer and personalized treatment for stroke associated with cancer.

Methods

Admission routine clinical examination indicators of IS patients were retrospectively collated from the electronic medical records. The training dataset comprised 136 IS patients with concurrent cancer, matched at a 1:1 ratio with a control group. The risk of occult cancer in IS patients was assessed through logistic regression and five alternative machine-learning models. Subsequently, select the model with the highest predictive efficacy to create a nomogram, which is a quantitative tool for predicting diagnosis in clinical practice. Internal validation employed a ten-fold cross-validation, while external validation involved 239 IS patients from six centers. Validation encompassed receiver operating characteristic (ROC) curves, calibration curves, decision curve analysis (DCA), and comparison with models from prior research.

Results

The ultimate prediction model was based on logistic regression and incorporated the following variables: regions of ischemic lesions, multiple vascular territories, hypertension, D-dimer, fibrinogen (FIB), and hemoglobin (Hb). The area under the ROC curve (AUC) for the nomogram was 0.871 in the training dataset and 0.834 in the external test dataset. Both calibration curves and DCA underscored the nomogram’s strong performance.

Conclusions

The nomogram enables early occult cancer diagnosis in hospitalized IS patients and helps to accurately identify the cause of IS, while the promotion of IS stratification makes personalized treatment feasible. The online nomogram based on routine clinical examination indicators of IS patients offered a cost-effective platform for secondary care in the framework of PPPM.

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Data availability

The datasets upholding the outcomes of this study can be accessed through a judicious solicitation to the corresponding author.

Code availability

All software applications used are included in this article.

Abbreviations

AUC:

Area under the ROC curve

AUC-ROC:

Area under the receiver operating characteristic curves

BBB:

Blood-brain barrier

CA:

Carbohydrate antigen

CI:

Confidence interval

DALYs:

Disability-adjusted life years

DCA:

Decision curve analysis

DWI:

Diffusion-weighted imaging

FIB:

Fibrinogen

Hb:

Hemoglobin

ICA:

Internal carotid artery

IS:

Ischemic stroke

LDA:

Linear discriminant analysis

LDH:

Lactic dehydrogenase

MRI:

Magnetic resonance imaging

ORs:

Odds ratios

PLT:

Platelet count

PPPM/3PM:

Predictive, preventive, and personalized medicine

ROC:

Receiver operating characteristic

SBI:

Silent brain microinfarction

SVM:

Support vector machine

VBA:

Vertebral-basilar artery

WSO:

World Stroke Organization

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Funding

We acknowledge the substantial support rendered by the Natural Science Foundation of China (Grants nos. 82072777), the Key Project of Natural Science Foundation of Fujian Province (Grants nos. 2021J02057), and the Natural Science Foundation of Fujian Province (Grants nos. 2022J011358, 2022J011365, 2020J02063). Additionally, we extend our gratitude to the Medical and Health Key Project of Xiamen (Grants nos. 3502Z20204006), as well as the Xiamen Municipal Health Commission and the Xiamen Municipal Bureau of Science and Technology (Grants nos. 3502Z20209005).

Author information

Author notes

  1. Jie Fang and Jielong Wu contributed equally to this work.

Authors and Affiliations

  1. Department of Neurology and Department of Neuroscience, School of Medicine, The First Affiliated Hospital of Xiamen University, Xiamen University, 55 Zhenhai Road, Xiamen, 361003, China

    Jie Fang, Jielong Wu, Liangcheng Zheng, Qing Lin, Chuya Jing, Qiuhong Zhang, Chen Wang, Quan Lan & Qilin Ma

  2. Fujian Key Laboratory of Brain Tumors Diagnosis and Precision Treatment, Xiamen, China

    Jie Fang, Liangcheng Zheng, Qing Lin, Chuya Jing, Qiuhong Zhang, Chen Wang, Quan Lan, Zhanxiang Wang & Qilin Ma

  3. Xiamen Key Laboratory of Brain Center, Xiamen, China

    Jie Fang, Liangcheng Zheng, Qing Lin, Chuya Jing, Qiuhong Zhang, Chen Wang, Quan Lan, Zhanxiang Wang & Qilin Ma

  4. Xiamen Medical Quality Control Center for Neurology, Xiamen, China

    Jie Fang, Liangcheng Zheng, Qing Lin, Chuya Jing, Qiuhong Zhang, Chen Wang, Quan Lan, Zhanxiang Wang & Qilin Ma

  5. Fujian Provincial Clinical Research Center for Brain Diseases, Xiamen, China

    Jie Fang, Liangcheng Zheng, Qing Lin, Chuya Jing, Qiuhong Zhang, Chen Wang, Quan Lan, Zhanxiang Wang & Qilin Ma

  6. Xiamen Clinical Research Center for Neurological Diseases, Xiamen, China

    Jie Fang, Liangcheng Zheng, Qing Lin, Chuya Jing, Qiuhong Zhang, Chen Wang, Quan Lan, Zhanxiang Wang & Qilin Ma

  7. School of Medicine, Xiamen University, Xiamen, China

    Jie Fang, Jielong Wu, Lingsheng Kong, Zhanxiang Wang & Qilin Ma

  8. National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, China

    Jielong Wu, Zhanxiang Wang & Qilin Ma

  9. Cerebrovascular Interventional Department, Zhangzhou Hospital of Fujian Province, Zhangzhou, China

    Ganji Hong

  10. Department of Neurology, Changxing People’s Hospital, Huzhou, China

    Lu Yu

  11. Department of Neurology, The Jilin Center Hospital, Jilin, China

    Xiuping Liu

  12. Department of Neurology, The Second Hospital of Longyan City, Longyan, China

    Pan Lin

  13. Department of Neurology, The Second Affiliated Hospital of Xiamen Medical College, Xiamen, China

    Zhenzhen Yu

  14. Department of Neurology, Xiamen Haicang Hospital, Xiamen, China

    Dan Chen

  15. School of Clinical Medicine, Fujian Medical University, Fuzhou, China

    Jiedong Zhao

  16. Department of Gynecology of Xiamen Maternal and Child Health Care Hospital, Xiamen, China

    Xiaodong Yuan

  17. Department of Neurology, Huaihe Hospital, Henan University, Huaihe, China

    Chunfang Wu

  18. Department of Neurology, Kaifeng Hospital of Traditional Chinese Medicine, Kaifeng, China

    Zhaojie Zhang

  19. Department of Neurology, First Affiliated Hospital of Gannan Medical University, Gannan, China

    Mingwei Guo & Junde Zhang

  20. Department of Neurology, Ningde Municipal Hospital of Ningde Normal University, Ningde, China

    Jingjing Zheng

  21. Department of Neurology, The Fifth Hospital of Xiamen, Xiamen, China

    Aidi Lei & Tengkun Zhang

  22. NHC Key Laboratory of Technical Evaluation of Fertility Regulation for Non-Human Primate (Fujian Maternity and Child Health Hospital), No. 19 Jinjishan Road, Jin’an District, Fuzhou, 350013, China

    Xinrui Wang

  23. Medical Research Center, College of Clinical Medicine for Obstetrics and Gynecology and Pediatrics, Fujian Maternityand Child Health Hospital, Fujian Medical University, Fuzhou, China

    Xinrui Wang

  24. Department of Neurosurgery and Department of Neuroscience, School of Medicine, The First Affiliated Hospital of Xiamen University, Xiamen University, 55 Zhenhai Road, Xiamen, 361003, China

    Zhanxiang Wang

Authors
  1. Jie Fang
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  2. Jielong Wu
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  3. Ganji Hong
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  4. Liangcheng Zheng
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  5. Lu Yu
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  6. Xiuping Liu
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  7. Pan Lin
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  8. Zhenzhen Yu
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  9. Dan Chen
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  10. Qing Lin
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  27. Qilin Ma
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Contributions

We present a comprehensive summary of the roles undertaken by the authors in this scholarly endeavor. The conceptualization was primarily orchestrated by J.F. and Q.M., whereas the study design was meticulously crafted by J.F. and J.W. In consonance, data collection and quality control were executed by the entire team. The analytical facet of data was proficiently managed by J.W. Subsequently, the initial manuscript draft was skillfully composed by J.W., with subsequent iterations and editing being jointly administered by J.F. and J.W. Lastly, the ultimate manuscript was reviewed and endorsed by all authors, underscoring their collective commitment. This collaborative effort underscores their involvement in writing, substantiates their engagement with the manuscript, and attests to their consensus on its finalization.

Corresponding authors

Correspondence to Xinrui Wang, Zhanxiang Wang or Qilin Ma.

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Ethics approval

Approval for the study was duly granted by the Ethics Committee of the First Affiliated Hospital of Xiamen University (ID: XMYY-2021KYSB074).

Consent to participate

Given the retrospective, non-interventional nature of this study wherein the personal data of patients were not gathered, the requirement for informed consent was duly obviated.

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Not applicable.

Conflict of interest

The authors declare no competing interests.

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It is pertinent to note that the funders played no role in shaping the study’s inception and execution, encompassing aspects such as design, data collection, analysis, and manuscript preparation, review, and final endorsement.

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Fang, J., Wu, J., Hong, G. et al. Cancer screening in hospitalized ischemic stroke patients: a multicenter study focused on multiparametric analysis to improve management of occult cancers. EPMA Journal 15, 53–66 (2024). https://doi.org/10.1007/s13167-024-00354-8

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