System for evaluating prognosis of patient with spinal glioma based on peripheral blood cells
A glioma, prognostic technology, applied in the field of biomedicine, can solve the problems of large differences in the prognosis of diffuse spinal glioma and unclear prognostic factors of diffuse spinal glioma, and achieve rapid and accurate evaluation and detection. The effect of low operation complexity and simple acquisition process
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Embodiment 1
[0051] This embodiment is used to illustrate the establishment of the evaluation model of the present disclosure.
[0052] 88 cases of diffuse spinal glioma samples were collected using the operation in accordance with the standards of the medical ethics committee, and the pathological characteristics of each diffuse spinal glioma sample were judged. Among them, each patient who collects samples has obtained the consent of himself and his therapist before collecting samples, and has written certification materials. Diffuse spinal cord glioma was diagnosed by pathological diagnosis method, and the peripheral blood cell count index of each sample was detected and calculated by a blood cell analyzer. The prognosis of the diffuse spinal glioma sample was evaluated according to the survival period of the patients corresponding to the diffuse spinal glioma sample. The longer the survival period of the patient, the better the prognosis of the diffuse spinal glioma. The gender, age, ...
Embodiment 2
[0063] This embodiment is used to verify the evaluation model of the present disclosure
[0064] According to the method of Example 1, 88 samples of diffuse glioma were recollected, including 46 samples of lower grade glioma (WHO grade II / III) and 42 samples of WHO grade IV glioma. All diffuse spinal glioma samples were used as the first validation set, lower-grade spinal glioma samples (WHO grade II / III) were used as the second validation set, and WHO grade IV spinal glioma samples were used as the third validation set. Use a blood cell analyzer to detect and calculate the white blood cell count, neutrophil count, platelet count and lymphocyte count of each sample, and based on the above detection data, and use formula (2) to calculate the prognosis score of each sample respectively, the prognosis Samples with a score <3.85 were classified into the low-risk group, and samples with a prognostic score ≥3.85 were classified into the high-risk group. Each sample was followed up ...
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Abstract
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