Breast cancer prognosis survival rate prediction method based on dynamic Cox model

A prediction method and survival rate technology, applied in the fields of medical data mining, health index calculation, medical informatics, etc., to achieve the effect of improving prediction accuracy and accurate prediction effect

Inactive Publication Date: 2018-11-30
NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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Problems solved by technology

However, in the above studies, the survival analysis method used is the traditional Cox proportional hazards model

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  • Breast cancer prognosis survival rate prediction method based on dynamic Cox model
  • Breast cancer prognosis survival rate prediction method based on dynamic Cox model
  • Breast cancer prognosis survival rate prediction method based on dynamic Cox model

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Embodiment Construction

[0026] The present invention provides a method for predicting the prognosis and survival rate of breast cancer based on a dynamic Cox model. The present invention will be described below in conjunction with the accompanying drawings and embodiments.

[0027] The specific implementation method is as figure 1 As shown; the model is based on the LNR and the patient's survival data, cancer-related information and patient age and other indicators, using the Cox proportional hazards model based on the Bayesian method for dynamically estimating parameters; using the logarithmic probability regression algorithm, the LNR correlation The eigenvalues ​​of include the tumor size, location, number of positive lymph nodes and the total number of lymph nodes tested as input, and the observed LNR is used as the output training model; the specific implementation method includes the following steps:

[0028] Step 1: First delete the obviously unreasonable data samples, and then normalize the di...

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Abstract

The invention discloses a breast cancer prognosis survival rate prediction method based on a dynamic Cox model, and belongs to the technical field of a tumor mortality risk regression model algorithm.The method includes: using a log probability regression model to estimate the patient's positive lymph node ratio LNR level; combining the ratio with other features to fit a Cox regression model of Bayesian method based dynamical estimation model parameters; and predicting a survival rate-time characteristic curve of the patient. The simulation results show that the Cox regression model of the Bayesian method based dynamical estimation model parameters of two logarithmic pseudo-marginal LPML indexes of the combined model is superior to the conventional Cox proportional risk model using LNR index features; and the Cox regression model of the dynamical estimation parameters can further improve the prediction precision of a survival analysis model, the computational complexity is within an acceptable range, and the prediction effect is relatively accurate.

Description

technical field [0001] The invention belongs to the technical field of tumor mortality risk regression model algorithm; in particular, it relates to a method for predicting the prognosis and survival rate of breast cancer based on a dynamic Cox model. Specifically, the Cox proportional hazards regression model based on dynamic estimated parameters is an input logarithmic probability regression estimation using the positive lymph node ratio and other related features to realize accurate prediction of prognosis and survival of breast cancer patients based on the dynamic Cox proportional hazards regression model algorithm rate method. Background technique [0002] Cancer is a risk factor that seriously affects the health of residents. In my country, tumor death accounts for nearly a quarter of all causes of death, ranking first among the causes of death. Among them, although the incidence and mortality rate of female breast cancer in China are at a relatively low level in the...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H50/70G16H50/30
CPCG16H50/30G16H50/70
Inventor 滕婧杜婧马卞周蓉
Owner NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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