Synthetic controls for survival data

Patent metadata

Field	Value
Publication number	US-2025174327-A1
Application number	US-202418592455-A
Country	US
Kind code	A1
Filing date	Feb 29, 2024
Priority date	Nov 29, 2023
Publication date	May 29, 2025
Grant date	—

Abstract

A computerized system and method for creating synthetic controls in survival analysis is provided. A target group of patients who are administered a drug and a control group of patients who are not administered the drug are created from real data of patients. A weight is applied to a common feature of each patient in the control group of patients so that a linear combination of the common feature of the patients in the control group of patients becomes similar to a particular patient in the target group of patients. A synthetic patient is created for each patient in the control group of patients. Because the common feature of the synthetic patient is similar to the particular patient in the target group, an efficacy of the drug may be determined by comparing the target group of patients with the synthetic patient.

First claim

What is claimed is:

1 . A system comprising:
a processor; and a memory comprising computer program code, the memory and the computer program code configured to cause the processor to: create a target group of patients and a control group of patients from data associated with a plurality of patients, the target group of patients comprising patients to whom a drug is to be administered, the control group of patients comprising patients to whom the drug is not administered, each patient in the target group of patients and the control group of patients having a common feature; apply a weight to the common feature of each patient in the control group of patients so that a linear combination of the common feature of the patients in the control group of patients becomes similar to a particular patient in the target group of patients, wherein applying the weight comprises:
minimizing a distance between the common feature of the particular patient in the target group of patients and the linear combination of the common feature of the patients in the control group of patients, the distance being minimized by penalizing the distance using a variance penalty; and
create a synthetic patient for each patient in the control group of patients, the synthetic patient having the common feature similar to the particular patient in the target group of patients.

2 . The system of claim 1 , wherein the memory and the computer program code are configured to further cause the processor to:
cause the drug to be administered to the target group of patients; compare the target group of patients who are administered the drug with the synthetic patient for each patient in the control group of patients; and based on the comparison, determine an efficacy of the drug.

3 . The system of claim 1 , wherein minimizing the distance between the common feature of the particular patient in the target group of patients and the linear combination of the common feature of the patients in the control group of patients further includes initializing the applied weight to correspond with the common feature of a nearest neighbor patient in the control group of patients to the particular patient.

4 . The system of claim 1 , wherein the data associated with the plurality of patients includes censored data;
wherein applying the weight to the common feature of each patient in the control group of patients so that a linear combination of the common feature of the patients in the control group of patients becomes similar to a particular patient in the target group of patients further includes applying the weight to censored time data and censored event indicators of the censored data; and wherein the created synthetic patients are heuristically censored based on the censored data.

5 . A computerized method for creating synthetic controls in survival analysis, the computerized method comprising:
creating a target group of patients and a control group of patients from data associated with a plurality of patients, the target group of patients comprising patients to whom a drug is to be administered, the control group of patients comprising patients to whom the drug is not administered, each patient in the target group of patients and the control group of patients having a common feature; applying a weight to the common feature of each patient in the control group of patients so that a linear combination of the common feature of the patients in the control group of patients becomes similar to a particular patient in the target group of patients, wherein applying the weight comprises:
minimizing a distance between the common feature of the particular patient in the target group of patients and the linear combination of the common feature of the patients in the control group of patients, the distance being minimized by penalizing the distance using a variance penalty; and
determining the weight to be applied based on the minimizing; and
creating a synthetic patient for each patient in the control group of patients, the synthetic patient having the common feature similar to the particular patient in the target group of patients.

6 . The computerized method of claim 5 , further comprising:
causing the drug to be administered to the target group of patients; comparing the target group of patients who are administered the drug with the synthetic patient for each patient in the control group of patients; and based on the comparison, determining an efficacy of the drug.

7 . The computerized method of claim 5 , further comprising creating another synthetic patient for each patient in the target group of patients, the other synthetic patient having the common feature similar to a particular patient in the control group of patients.

8 . The computerized method of claim 7 , further comprising:
administering the drug to a subset of the target group of patients; comparing the subset of the target group of patients who are administered the drug with the other synthetic patient for each patient in the subset of the target group of patients; and based on the comparison, determining an efficacy of the drug.

9 . The computerized method of claim 5 , further comprising determining a time to event outcome of the synthetic patient for each patient in the control group of patients.

10 . The computerized method of claim 5 , wherein the synthetic patient for each patient in the control group of patients is created on an outcome scale or on log scale.

11 . The computerized method of claim 5 , wherein the penalizing the distance comprises using the variance penalty and a covariance penalty.

12 . The computerized method of claim 5 , wherein the target group of patients and the control group of patients are created from data associated with the plurality of patients by following a biased sampling scheme, the biased sampling scheme comprising:
fitting a cox proportional hazards model using all covariates on the plurality of patients; predicting, using the cox proportional hazards model, an expected median survival time for each patient; and based on the expected median survival time, splitting the plurality of patients into the target group of patients and the control group of patients, wherein the target group of patients have the expected median survival time above a threshold.

13 . The computerized method of claim 5 , wherein minimizing the distance between the common feature of the particular patient in the target group of patients and the linear combination of the common feature of the patients in the control group of patients further includes initializing the applied weight to correspond with the common feature of a nearest neighbor patient in the control group of patients to the particular patient.

14 . The computerized method of claim 5 , wherein the data associated with the plurality of patients includes censored data;
wherein applying the weight to the common feature of each patient in the control group of patients so that a linear combination of the common feature of the patients in the control group of patients becomes similar to a particular patient in the target group of patients further includes applying the weight to censored time data and censored event indicators of the censored data; and wherein the created synthetic patients are heuristically censored based on the censored data.

15 . The computerized method of claim 5 , wherein creating the synthetic patient for each patient in the control group of patients includes at least one of the following:
creating the synthetic patient for each patient in the control group of patie

Assignees

• Microsoft Technology Licensing Llc

Inventors

• González Hernández Javier
• Curth Alicia Marie
• Poon Hoifung
• Nori Aditya Vithal

Classifications

• G16H70/40

  relating to drugs, e.g. their side effects or intended usage · CPC title

• G16H10/20

  for electronic clinical trials or questionnaires · CPC title

• G16H20/10 Primary

  relating to drugs or medications, e.g. for ensuring correct administration to patients · CPC title

• A61B5/4848

  Monitoring or testing the effects of treatment, e.g. of medication · CPC title