Isolated pulmonary nodule malignant risk prediction system based on logistic regression model

A logistic regression model and risk prediction technology, applied in the field of medical diagnosis, can solve the problems of overestimating the risk of lung cancer, poor matching, poor malignant risk prediction accuracy, etc. Effect

Pending Publication Date: 2021-09-28
WEST CHINA HOSPITAL SICHUAN UNIV
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Problems solved by technology

And its matching with the population targeted by this application (Chinese population with solitary pulmonary nodules requiring surgical evaluation or biopsy) is still poor, and it overestimates the risk of lung cancer in the population targeted by this application
[0008] In summary, due to the relevance of...

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Embodiment 1

[0049] Example 1: Logistic Regression Model

[0050] The data of 721 subjects were used for modeling, of which malignant and benign cases were 522 and 199, respectively. The modeling group and the validation group were allocated 3:1. There were 541 cases in the modeling group (392 malignant cases and 149 benign cases) and 180 cases in the validation group (130 malignant cases and 50 benign cases).

[0051] Logistic regression was used to screen for risk factors, and since all parameters in the training group were tested by univariate analysis, we directly employed stepwise logistic regression to identify independent predictors of malignant nodules. Finally, the established model formula is:

[0052] Nodule malignancy probability f(x)=e x / (1+e x );

[0053] Among them, x=-2.8107+(1.2454×with or without smoking history)+(-1.4055×CT nodule with smooth border)+(0.0771×age)+(-1.0728×sex)+(-0.6228×CT nodule with clear border) +(-1.3319×CT nodule calcification)+(0.6890×whether ...

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Abstract

The invention belongs to the technical field of medical diagnosis, and particularly relates to an isolated pulmonary nodule malignant risk prediction system based on a logistic regression model. The invention provides an isolated pulmonary nodule malignant risk prediction system, and the system comprises: a data collection module which is used for acquiring and/or inputting variable data of an isolated pulmonary nodule patient; a data operation module which is used for substituting the variable data into the logistic regression model for calculation to obtain a nodule malignancy probability and/or a judgment conclusion about whether the nodule is malignant; and a data output module which is used for outputting a nodule malignancy probability and/or a judgment conclusion about whether the nodule is malignant or not. The model provided by the invention is suitable for diagnosing whether nodules of SPN patients in Chinese population are malignant or not.

Description

technical field [0001] The invention belongs to the technical field of medical diagnosis, and in particular relates to a system for predicting the malignant risk of isolated pulmonary nodules based on a logistic regression model. Background technique [0002] Worldwide, lung cancer is still the number one killer of cancer-related deaths (Al-Ameri et al. 2015). The widespread use of low-dose CT in cancer screening has enabled early detection of lung cancer in many patients, resulting in improved mortality in the screened population (Bach et al. 2012; Criss et al. 2018; Henschke et al. 2006). At the same time, lung nodules, one of the imaging manifestations of lung cancer, can be found. A solitary pulmonary nodule is defined as a round-like lesion less than 30 mm in diameter surrounded by lung parenchyma, and approximately 1–12% of solitary pulmonary nodules are malignant on pathology (Khan et al. 2019). The current overall management of solitary pulmonary nodules is a chal...

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Application Information

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IPC IPC(8): G16H50/20G16H50/70G06F17/18
CPCG16H50/30G06N5/01
Inventor 陈勃江邬祚虹李为民
Owner WEST CHINA HOSPITAL SICHUAN UNIV
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