Cervical cancer postoperative recurrence risk prediction method and system

A technology for risk prediction and cervical cancer, applied in the medical field, to achieve the effect of rigorous screening of high-risk factors, precise scope of application, and improved accuracy

Pending Publication Date: 2020-09-08
SHANDONG UNIV QILU HOSPITAL
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

In addition, the inventors found that there is currently no literature report on evaluating and predicting postope...

Method used

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  • Cervical cancer postoperative recurrence risk prediction method and system
  • Cervical cancer postoperative recurrence risk prediction method and system
  • Cervical cancer postoperative recurrence risk prediction method and system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0076] 1. Cervical cancer patients identified as stage IA2-IIA2 according to the 2009 FIGO staging system;

[0077] 2. No neoadjuvant chemotherapy or radiotherapy before operation;

[0078] 3. The surgical method is modified or radical hysterectomy and pelvic lymph node dissection;

[0079] 4. Postoperative pathological results do not include the three pathological high-risk factors of lymph node metastasis, parametrial invasion, and positive surgical margin;

[0080] 5. Not combined with other primary malignant tumors at the same time;

[0081] 6. Postoperative follow-up time of at least 2 years.

[0082] (1) Number of patients enrolled: more than 400 cases.

[0083] (2) Patient grouping: the above-mentioned patients were randomly divided into a modeling group and a verification group in a ratio of 3:1.

[0084](3) Collection of clinical data for modeling: collect the basic clinical data of the above-mentioned patients, including: age, pregnancy and childbirth history, HP...

Embodiment 2

[0094] A postoperative recurrence risk prediction system for cervical cancer, said system comprising:

[0095] Clinical data acquisition and processing module: acquire clinical data of postoperative patients with cervical cancer and perform preprocessing;

[0096] Risk factor screening module: take the postoperative progression-free survival (DFS) of the patient as the outcome, and perform single-factor COX regression analysis on the above-mentioned processed clinical data to obtain risk factors;

[0097] Model building block: take the patient's progression-free survival (DFS) as the outcome, and combine the screened risk factors (preferably with a p value less than 0.10) with the intermediate-risk pathological factors in the Sedlis criteria and postoperative adjuvant treatment options , to construct predictive models using multivariate Cox regression analysis.

[0098] Among them, in the clinical data acquisition and processing module,

[0099] The clinical data of postoper...

Embodiment 3

[0106] An electronic device, including a memory, a processor, and computer instructions stored in the memory and run on the processor. When the computer instructions are run by the processor, each operation in the method of Embodiment 1 is completed. For brevity, here No longer.

[0107] Described electronic device can be mobile terminal and non-mobile terminal, and non-mobile terminal comprises desktop computer, and mobile terminal comprises smart phone (Smart Phone, such as Android mobile phone, IOS mobile phone etc.), smart glasses, smart watch, smart bracelet, tablet computer , laptops, personal digital assistants and other mobile Internet devices that can communicate wirelessly.

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Abstract

The invention provides a cervical cancer postoperative recurrence risk prediction method and system, and belongs to the technical field of medicine. The invention provides a prediction model based onmedium-risk pathological factors. The effect of predicting the postoperative disease recurrence risk of a early cervical cancer patient is achieved and the foothold is postoperative disease recurrencerisk assessment of early cervical cancer patients without high-risk pathological factors; therefore, the disease recurrence risk prediction of cervical cancer patients at any time point after the operation can be realized; and meanwhile, two model verification methods of data of a verification group and a machine learning algorithm are used, external verification is performed on the obtained model, and the prediction accuracy of the constructed model is further ensured, so that the method has a good practical application value.

Description

technical field [0001] The invention belongs to the field of medical technology, and in particular relates to a method and system for predicting recurrence risk after cervical cancer surgery. Background technique [0002] The information disclosed in this background section is only intended to increase the understanding of the general background of the present invention, and is not necessarily taken as an acknowledgment or any form of suggestion that the information constitutes the prior art already known to those skilled in the art. [0003] Worldwide, more than half a million women are diagnosed with cervical cancer each year and more than 300,000 die from the disease. Although cervical cancer screening has reduced the incidence of cervical cancer, global data on cervical cancer show that the survival rate of patients has not improved significantly in the past few decades. Furthermore, nearly 90% of cervical cancer deaths occur in developing and resource-poor countries. ...

Claims

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Application Information

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IPC IPC(8): G16H50/50G16H10/60G06F17/18G06N20/00
CPCG06F17/18G16H10/60G16H50/50G06N20/00
Inventor 宋坤褚然李莉谯旭苏绚涛解琳陈威姚舒苑存忠孔北华
Owner SHANDONG UNIV QILU HOSPITAL
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