Systems and methods for determining the probability of a pregnancy at a selected point in time

• US 10,162,800 B2
• Filed: 10/11/2013
• Issued: 12/25/2018
• Est. Priority Date: 10/17/2012
• Status: Active Grant

• Current Assignee: Celmatix Inc.
• Original Assignee: Celmatix Inc.
• Inventors: Elashoff, Michael, Karvir, Hrishikesh, Yurttas Beim, Piraye
• Primary Examiner(s): Lin, Jerry
• Application Number:
  US14/051,716
• Publication Number:
  US 20140107934A1
• Time in Patent Office: 1,901 Days
• Field of Search: 702 19
• CPC Class Codes: G06F 17/18 for evaluating statistical data , e.g. average values, frequency distributions, probability functions, regression analysis forecasting specially adapted for a specific administrative, business or logistic context G06Q10/04
• CPC Class Codes: G16H 10/20 for electronic clinical trials or questionnaires
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment

Abstract

The present invention generally relates to systems and methods for determining the probability of a pregnancy at a selected point in time. Systems and methods of the invention employ an algorithm that has been trained on a reference set of data from a plurality of women for whom at least one of fertility-associated phenotypic traits, fertility-associated medical interventions, or pregnancy outcomes are known, in which the algorithm accounts for any woman who ceases pregnancy attempts prior to reaching a live birth outcome.

Claims

1. A system for determining a probability of achieving a pregnancy at a selected point in time, the system comprising:

a central processing unit (CPU); and

storage coupled to said CPU for storing instructions that when executed by the CPU cause the CPU to;

accept as input, data representative of a plurality of fertility-associated phenotypic traits of a female subject;

analyze the input data using a prognosis predictor generated by;

obtaining a reference set of data from a plurality of women across one or more reproductive cycles, the reference set of data comprising fertility-associated phenotypic traits and known pregnancy outcomes, wherein the plurality of women accounts for a dropout population of women who ceased pregnancy attempts prior to reaching a live birth outcome and a non-dropout population of women who continued pregnancy attempts until live birth;

determining one or more correlations between the at least one of the fertility-associated phenotypic traits and the known pregnancy outcomes at a plurality of time points across the reproductive cycles, wherein the dropout population is accounted for by estimating a likelihood of dropout for each subject at each reproductive cycle and weighing the women in the non-dropout population proportionally to the likelihood of dropout; and

training the prognosis predictor on the reference set of data;

provide a probability of achieving a pregnancy for the female subject at a selected point in time as a result of running the prognosis predictor on said input data; and

treating the female subject with a fertility treatment based on the probability of achieving a pregnancy.

2. The system of claim 1, wherein the probability of achieving pregnancy comprises the probability of achieving pregnancy that results in a live birth.

3. The system of claim 1, wherein the correlations for said fertility-associated phenotypic traits are adjusted at each time point across the plurality of reproductive cycles.

4. The system of claim 1, wherein said input data are obtained from at least one selected from the group consisting of a questionnaire, a medical history of said female subject, a family medical history of said female subject, and a combination thereof.

5. The system of claim 1, wherein said data are obtained by analyzing a sample collected from a person selected from the group consisting of:

said female subject, intimate partners of said female subject, blood-related relatives of said female subject, gamete donors, embryo donors, gestational carriers, and a combination thereof.

6. The system of claim 5, wherein said sample is a human tissue or bodily fluid.

7. The system of claim 1, wherein the input data of the female subject further comprises fertility-associated genotypic traits of the female subject.

8. The system of claim 7, wherein the reference set of data from the plurality of women further comprises fertility-associated genotypic traits.

9. The system of claim 7, wherein the genotypic traits of the subject are obtained by conducting an assay on a sample from the subject to determine the presence or absence of a genetic variation that is associated with infertility.

10. The system according to claim 9, wherein the assay is selected from the group consisting of sequencing, hybridization to an array, and an amplification reaction.

11. The system of claim 9, wherein the genetic variation is selected from the group consisting of a single nucleotide polymorphism, a deletion, an insertion, a rearrangement, a copy number variation, and a combination thereof.

12. The system of claim 7, wherein the genotype traits are reflective of expression levels of one or more fertility-associated genes.

13. The system of claim 1, wherein the fertility-associated phenotypic trait is a trait selected from Table 1.

14. The system of claim 1, wherein the prognosis predictor is stored at a remote location and the CPU communicates across a network to access said prognosis predictor.

15. The system of claim 1, wherein the prognosis predictor is stored locally within the CPU and the CPU accesses the prognosis predictor within the CPU.

16. The system of claim 1, wherein the data further comprises a plurality of fertility-associated phenotypic traits of a male subject.

17. A method for determining a probability of achieving a pregnancy at a selected point in time, the method comprising:

accepting as input, data representative of a plurality of fertility-associated phenotypic traits of a female subject;

analyzing the input data using a prognosis predictor generated by;

obtaining a reference set of data from a plurality of women across one or more reproductive cycles, the reference set of data comprising fertility-associated phenotypic traits and known pregnancy outcomes, wherein the plurality of women accounts for a dropout population of women who ceased pregnancy attempts prior to reaching a live birth outcome and a non-dropout population of women who continued pregnancy attempts until live birth;

determining one or more correlations between the at least one of the fertility-associated phenotypic traits and the known pregnancy outcomes at a plurality of time points across the reproductive cycles, wherein the dropout population is accounted for by estimating a likelihood of dropout for each subject at each reproductive cycle and weighing the women in the non-dropout population proportionally to the likelihood of dropout; and

training the prognosis predictor on the reference set of data;

providing a probability of achieving a pregnancy for the female subject at a selected point in time as a result of running the prognosis predictor on said input data; and

treating the female subject with a fertility treatment based on the probability of achieving a pregnancy.

18. The method of claim 17, wherein the probability of achieving pregnancy comprises the probability of achieving pregnancy that results in a live birth.

19. The method of claim 17, wherein the correlations for said fertility-associated phenotypic traits are adjusted at each time point across the plurality of reproductive cycles.

20. The method of claim 17, wherein said input data are obtained from at least one selected from the group consisting of a questionnaire, a medical history of said female subject, a family medical history of said female subject, and a combination thereof.

21. The method of claim 17, wherein said data are obtained by analyzing a sample collected from a person selected from the group consisting of:

said female subject, intimate partners of said female subject, blood-related relatives of said female subject, gamete donors, embryo donors, gestational carriers, and a combination thereof.

22. The method of claim 21, wherein said sample is a human tissue or bodily fluid.

23. The method of claim 17, wherein the input data of the female subject further comprises fertility-associated genotypic traits of the female subject.

24. The method of claim 23, wherein the reference set of data from the plurality of women further comprises fertility-associated genotypic traits.

25. The method of claim 23, wherein the genotypic traits of the subject are obtained by conducting an assay on a sample from the subject to determine the presence or absence of a genetic variation that is associated with infertility.

26. The method of claim 25, wherein the assay is selected from the group consisting of:

sequencing, hybridization to an array, and an amplification reaction.

27. The method of claim 26, wherein the genetic variation is selected from the group consisting of:

a single nucleotide polymorphism, a deletion, an insertion, a rearrangement, a copy number variation, and a combination thereof.

28. The method of claim 23, wherein the genotype traits are reflective of expression levels of one or more fertility-associated genes.

29. The method of claim 17, wherein the fertility-associated phenotypic trait is a trait selected from Table 1.

30. The method of claim 17, wherein the data further comprises a plurality of fertility-associated phenotypic traits of a male subject.

31. A method for determining a probability of achieving a pregnancy at a selected point in time, the method comprising, the method comprising:

inputting data representative of a plurality of fertility-associated phenotypic traits of a female subject into a computer;

causing the computer to;

analyze the input data using a prognosis predictor generated by;

obtaining a reference set of data from a plurality of women across one or more reproductive cycles, the reference set of data comprising fertility-associated phenotypic traits and known pregnancy outcomes, wherein the plurality of women accounts for a dropout population of women who ceased pregnancy attempts prior to reaching a live birth outcome and a non-dropout population of women who continued pregnancy attempts until live birth;

determining one or more correlations between the at least one of the fertility-associated phenotypic traits and the known pregnancy outcomes at a plurality of time points across the reproductive cycles, wherein the dropout population is accounted for by estimating a likelihood of dropout for each subject at each reproductive cycle and weighing the women in the non-dropout population proportionally to the likelihood of dropout; and

training the prognosis predictor on the reference set of data; and

provide a probability of achieving a pregnancy for the female subject at a selected point in time as a result of running an algorithm on the inputted data; and

treating the female subject with a fertility treatment based on the probability of achieving a pregnancy.

32. The method of claim 31, wherein the probability of achieving pregnancy comprises the probability of achieving pregnancy that results in a live birth.

33. The method of claim 31, wherein the correlations for said fertility-associated phenotypic traits are adjusted at each time point across the plurality of reproductive cycles.

34. The method of claim 33, wherein both the reference set of data from the plurality of women and the inputted data from the female subject further comprises fertility-associated genotypic traits.

35. The method of claim 33, wherein the genotypic traits of at least one of the subject and the plurality of women from the reference set of data are obtained by conducting an assay on a sample from the subject to determine the presence or absence of a genetic variation that is associated with infertility.

36. The method of claim 31, wherein the prognosis predictor is stored at a remote location and the computer communicates across a network to access said prognosis predictor.

37. The method of claim 31, wherein the prognosis predictor is stored locally within the computer and the computer accesses the prognosis predictor within the computer.

38. The method of claim 31, wherein the data further comprises a plurality of fertility-associated phenotypic traits of a male subject.