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Late breast cancer survival probability prediction nomogram, survival probability prediction method and patient classification method

A technology of advanced breast cancer and survival probability, which is applied in the field of nomogram of survival probability prediction of advanced breast cancer, can solve the problem of missing nomogram of survival probability of advanced breast cancer and achieve the effect of improving accuracy

Pending Publication Date: 2020-06-30
SUN YAT SEN MEMORIAL HOSPITAL SUN YAT SEN UNIV
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  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0006] The present invention aims to overcome at least one defect of the above-mentioned prior art, and provides a nomogram for predicting the survival probability of advanced breast cancer, a method for predicting the survival probability and a patient classification method, which are used to solve the problem of the lack of the nomogram of the survival probability for advanced breast cancer in China , and combine with medical development to integrate more new indicators to improve the prediction of survival probability of patients with advanced breast cancer

Method used

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  • Late breast cancer survival probability prediction nomogram, survival probability prediction method and patient classification method
  • Late breast cancer survival probability prediction nomogram, survival probability prediction method and patient classification method
  • Late breast cancer survival probability prediction nomogram, survival probability prediction method and patient classification method

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Embodiment 1

[0048] Such as figure 1 As shown, this embodiment provides a nomogram for predicting the survival probability of advanced breast cancer. The nomogram has ten lines in total. The arrangement of the ten lines is provided in this embodiment as an example. It is not limited to the sorting manner provided in this embodiment.

[0049]In the nomogram, the first line is the score scale (Points), and its score ranges from 0 to 10; the independent variable in the second to sixth line of the nomogram is the prognostic variable, and the prognostic variable is a categorical variable; The second row is the breast cancer stage variable (TumorStage), which contains two variable values, which are breast cancer stage I / II (I / II) and breast cancer stage III / IV (III / IV); the third row is breast cancer Molecular typing variable (Subtype), which includes 3 variable values, which are HR+ / HER2-, HER2+ and TNBC; the fourth behavior is the disease recurrence-free time variable (DFS), which includes 3 ...

Embodiment 2

[0074] This embodiment provides a patient classification method based on the survival probability prediction nomogram of advanced breast cancer. Select a variable value among the prognostic variables in the sixth row, add the scores of all selected variable values ​​corresponding to the score scale to obtain the total score, and when the total score is less than 11, classify the patient as a low-risk patient , when the total score is greater than or equal to 11, the patient is classified as a high-risk patient.

[0075] Utilize the first experimental group in embodiment 1 and the second experimental group to analyze with regard to predicted survival months and predicted survival probability, as Figure 8 , 9 Shown is a Kaplan-Meier curve, with survival time (months) as the horizontal axis and predicted survival rate as the vertical axis, to illustrate the relationship between survival time and survival rate. Such as Figure 8 As shown, after classifying the first experimental...

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Abstract

The invention provides a late breast cancer survival probability prediction nomogram, a survival probability determination method and a patient classification method. The nomogram comprises a score scale and a plurality of prognostic variables, and the prognostic variables are classification variables and comprise a breast cancer staging variable, a breast cancer molecular typing variable, a patient disease-free recurrence time variable, a tumor load variable and a brain metastasis variable; each prognostic variable comprises a plurality of variable values, and each variable value correspondsto one score on the score scale; the nomogram also comprises a total score scale and patient survival probability variables which are continuous variables and comprise a one-year survival probabilityvariable, a two-year survival probability variable and a three-year survival probability variable, wherein each survival probability variable comprises a variable value range, and each variable valuerange has a score range corresponding to the total score scale; the development of medical science is considered, and meanwhile, the requirements of domestic patients are considered, so that the evaluation accuracy of the advanced breast cancer is improved.

Description

technical field [0001] The invention relates to the field of prognosis assessment of advanced breast cancer, and more specifically, to a nomogram for predicting survival probability of advanced breast cancer, a method for predicting survival probability and a method for classifying patients. Background technique [0002] Advanced breast cancer is a large group of heterogeneous diseases with different biological behaviors, response to treatment and prognosis. The treatment methods have developed from traditional palliative care to multidisciplinary diagnosis and treatment today. It is a very complicated diagnosis and treatment process and disease management Reliable assessment of the expected survival time and risk classification of newly diagnosed patients with advanced stage is an important basis for doctors to make treatment plans. Moreover, more than 90% of patients with advanced breast cancer believe that survival time is the most desired information in the treatment dec...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H50/20G16H50/30G16H50/70G06K9/62
CPCG16H50/20G16H50/30G16H50/70G06F18/2415Y02A90/10
Inventor 姚和瑞汪颖赵健丽余运芳
Owner SUN YAT SEN MEMORIAL HOSPITAL SUN YAT SEN UNIV
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