Methods And Systems Of Dynamic Screening Of Disease

• US 20090088981A1
• Filed: 04/25/2008
• Published: 04/02/2009
• Est. Priority Date: 04/26/2007
• Status: Abandoned Application

• Current Assignee: Soar Through Life, Ltd.
• Original Assignee: Soar Through Life, Ltd.
• Inventors: Kaminski, David, Neville, Thomas B.
• Application Number:
  US12/109,757
• Publication Number:
  US 20090088981A1
• Time in Patent Office: Days
• US Class Current: 702/19
• CPC Class Codes: G06N 7/01 Probabilistic graphical models, e.g. probabilistic networks
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

The present invention provides methods and systems for dynamic screening of disease in a subject. The information provided by the methods and systems can be used for many purposes including disease diagnosis and screening, disease treatment, and education the subject of life choices.

Claims

1. A method of assessing a disease in a subject comprising:

obtaining data from a subject corresponding to a biomarker for a disease at least two different times, wherein the data corresponding to the at least two different times form a first trend;

removing data from said first trend that has a value outside a tolerance, thereby forming a second trend, and

determining a relationship between said second trend and a historical trend, wherein the historical trend corresponds to the biomarker for the disease.

3. The method of claim 1, wherein the velocity of the second trend is used to determine the relationship between said second trend and said historical trend.

4. The method of claim 1, wherein the relationship is determined by a probability calculation.

5. The method of claim 4, wherein the probability calculation is a Bayesian method.

6. The method of claim 1 or 2, wherein the data comprises a ratio of two biomarkers for the disease.

7. The method of claim 1 or 2, wherein the disease is prostate cancer and wherein at least one biomarker is selected from the group consisting of fPSA and PSA.

8. The method of claim 1 or 2, wherein the tolerance is determined by a feedback iteration process.

9. A system for assessing a disease in a subject comprising a Monte Carlo calculation engine, wherein the engine executes the method of claim 1.

18. A method of delivering medical treatment to a subject with a disease comprising:

obtaining information provided from executing a method of claim 1, 2, 10, 11, or 12;

determining a course of medical action based on said information; and

delivering medical treatment by following the course of medical action.

19. The method of claim 18, wherein the course of medical action comprises administration of medical tests.

20. The method of claim 18, wherein the course of medical action comprises a specific time for delivering medical treatment.

21. The method of claim 18, wherein the course of medical action comprises calculation of a Life Score.

22. A method of diagnosing a disease in a subject comprising:

obtaining information provided from executing a method of claim 1, 2, 10, 11, or 12; and

diagnosing the disease in the subject using said information.

23. A computer readable medium comprising computer readable instructions, wherein the computer readable instructions when executed cause a processor to execute a method of claim 1, 2, 10, 11, or 12.

24. The computer readable medium of claim 23, wherein the instructions operate in a software runtime environment.

25. A data signal that is transmitted using a network, wherein the data signal comprises information provided from a method of claim 1, 2, 10, 11, or 12.

26. The data signal of claim 25 further comprising packetized data that is transmitted through a carrier wave across the network.

28. A method of assessing a disease in a subject comprising

collecting data from the subject corresponding to a biomarker for the disease at least two different times, wherein the data corresponding to the at least two different times form a trend;

exporting said data for manipulation of said data by executing a method of claim 1, 2, 10, 11, or 12; and

importing the results of said manipulation to an end user.

2. A method of assessing a disease in a subject comprising:

obtaining data from a subject corresponding to a biomarker for a disease at least two different times, wherein the data corresponding to the at least two different times form a first trend;

removing data from the first trend that has a value outside a tolerance, thereby forming a second trend; and

estimating future values for the biomarker using the second trend.

10. A method to assess the probability of progressing disease in a subject comprising:

obtaining data from a subject corresponding to a biomarker for a disease at least two different times, wherein the data corresponding to the at least two different times form a trend;

assessing a prior probability of progressing disease at more than one time point; and

determining the probability of said trend relating to the prior probability of progressing disease, thereby assessing the probability of progressing disease.

13. The method of claim 10, 11, or 12, wherein the disease is prostate cancer and wherein a biomarker is selected from the group consisting of fPSA and PSA.

14. The method of claim 10 or 12 further comprising removing data that has a value outside a tolerance from the trend.

11. A method for screening for progressing cancer comprising:

estimating two trends over at least two time points corresponding to data from two biomarkers and the ratio between the two biomarkers;

determining prior probabilities of progressing cancer at different times; and

estimating the probability of progressing cancer by performing a Bayesian method with said trend and said prior probabilities, thereby screening for progressing cancer.

15. The method of claim 11 further comprising removing data that has a value outside a tolerance from the two trends.

12. A method of assessing disease progression comprising:

determining prior probabilities of cancer occurrence at more than one time;

obtaining data from a subject corresponding to a biomarker for a disease at least two different times, wherein the data corresponding to the at least two different times form a trend;

determining a probability of an observation of the trend conditional on no progressing disease;

determining a probability of an observation of the trend conditional on progressing disease; and

assessing disease progression by performing a Bayesian method with the prior probabilities, the probability of an observation conditional on no progressing disease, and the probability of an observation conditional on progressing disease.

16. The method of claim 12, wherein the probability of an observation of the trend conditional on no progressing disease is calculated using Monte Carlo methods.

17. The method of claim 12, wherein the probability of an observation of the trend conditional on progressing disease is calculated using Monte Carlo methods.

27. A medical information system for assessing a disease of a subject comprising:

an input device for receiving subject data corresponding to a biomarker for the disease at least two different times, wherein the data corresponding to the at least two different times form a first trend;

a processor that assesses a probability of said trend relating to historical data;

a storage unit in communication with the processor having a database for;

(i) storing the subject data;

(ii) storing historical data related to the disease; and

an output device that transmits information relating to the probability of said trend relating to historical data to an end user.