Development and Validation of a User‐Friendly Predictive Model Using Demographic and Complete Blood Count Data to Facilitate Early Diagnosis on Suspicion of Myeloproliferative Neoplasms

We have developed and validated a prediction model for MPN based on demographics and CBC data. The model could assist general practitioners in quickly identifying patients with potential MPN and in initiating timely further investigations and referrals.

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Publication Details

Journal
International Journal of Laboratory Hematology
Published
2025-02-22
DOI
https://doi.org/10.1111/ijlh.14452
Primary Topic
Myeloproliferative Neoplasms: Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00
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article

Development and Validation of a User‐Friendly Predictive Model Using Demographic and Complete Blood Count Data to Facilitate Early Diagnosis on Suspicion of Myeloproliferative Neoplasms

Gang Cai, Lilan Jin, Lei Li, Yiyi Lu et al.
2 links
International Journal of Laboratory Hematology
Myeloproliferative Neoplasms: Diagnosis and Treatment
article

Development and Validation of a User‐Friendly Predictive Model Using Demographic and Complete Blood Count Data to Facilitate Early Diagnosis on Suspicion of Myeloproliferative Neoplasms

Gang Cai, Lilan Jin, Lei Li, Yiyi Lu, Lin Lin, Jiafei Lin
article en

Abstract

We have developed and validated a prediction model for MPN based on demographics and CBC data. The model could assist general practitioners in quickly identifying patients with potential MPN and in initiating timely further investigations and referrals.

International Journal of Laboratory HematologyVol. 47(4)
Shanghai Jiao Tong University (CN), Ruijin Hospital (CN)
Peace, Justice and strong institutions
Openalex Percentile: Top 95%
Myeloproliferative Neoplasms: Diagnosis and Treatment
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