CN108597563A - Dynamic random group technology and system - Google Patents

Abstract

The invention discloses a kind of dynamic random group technology and systems.Wherein, this method includes：Obtain the essential characteristic of target object, and distribution situation of the enrolled object between each group；According to the essential characteristic and the distribution situation, calculates the target object and be assigned to each group of total difference degree brought to system；The value of each total difference degree is ranked up, determines minimum value, and records the group where the minimum value；Judge whether the number of the group of the minimum value is unique；If the number of the group of the minimum value is unique, random number is taken out from preset random sequence, and according to the random number, distribute the target object；If the number of the group of the minimum value is not unique, a group is randomly selected in the group of the minimum value of identical total difference degree as target group, the target object is distributed to the target group.The present invention solves the technical issues of dynamic random group technology is without reproducibility.

Description

Dynamic random grouping method and system

technical field

The present invention relates to the field of clinical research random grouping, in particular to a dynamic random grouping method and system.

Background technique

A new drug clinical trial refers to any systematic study of a drug in humans (patients or healthy volunteers) to confirm or discover the clinical, pharmacological and/or other pharmacodynamic effects, adverse reactions and/or absorption of the experimental drug , distribution, metabolism and excretion, the purpose is to determine the safety and effectiveness of the experimental drug, and provide a basis for the marketing of innovative drugs (or generic drugs).

Randomization is an important part of clinical trials. The dynamic random grouping method, represented by the minimum random grouping method, has recently received widespread attention in the industry. According to the "Guiding Principles of Biostatistics for Drug Clinical Trials" issued by the State Food and Drug Administration in 2016, the random allocation table should be reproducible. However, since dynamic randomization is not like block randomization, a random allocation table cannot be generated before the start of the trial. The characteristics of the patients themselves and the chronological order of their enrollment will affect the results of the grouping. This is also one of the problems that hinder the large-scale application of this method in clinical trials of new drugs.

For the above problems, no effective solution has been proposed yet.

Contents of the invention

Embodiments of the present invention provide a dynamic random grouping method and system to at least solve the technical problem that the dynamic random grouping method does not have reproducibility.

According to an aspect of an embodiment of the present invention, a dynamic random grouping method is provided, including: obtaining the basic characteristics of the target object and the distribution of the objects that have been grouped among the groups; according to the basic characteristics and the distribution In this case, calculate the overall difference degree brought to the system by assigning the target object to each group; sort the values of each overall difference degree, determine the minimum value, and record the group where the minimum value is located; judge the minimum value Whether the number of the group is unique; if the number of the minimum group is unique, take a random number from the preset random sequence, and assign the target object according to the random number; if the minimum value The number of groups is not unique, and a group is randomly selected from groups with the same minimum value of the overall difference degree as the target group, and the target objects are assigned to the target group.

Optionally, the allocating the target object according to the random number includes: judging whether the random number is greater than the probability of completely random grouping; if the random number is greater than the probability of completely random grouping, assigning the target object To the target group, the target group is the group where the minimum value is located; if the random number is less than or equal to the complete random grouping probability, then the target object is allocated according to the complete random grouping method.

Optionally, when the random number is taken from the preset random sequence, the row where the random number is located is marked, and the ID number of the target object using the random number is associated.

Optionally, the basic characteristics of the target object include at least one of the following: prognostic factors and prognostic levels.

According to another aspect of the embodiment of the present invention, there is also provided a dynamic random grouping system, including: an acquisition unit, used to acquire the basic characteristics of the target object, and the distribution of the objects that have been included in the group among the groups; the calculation unit , used to calculate the overall difference degree brought to the system by assigning the target object to each group according to the basic characteristics and the distribution situation; the processing unit is used to sort the values of each overall difference degree, and determine the minimum value, and record the group where the minimum value is located; the judging unit is used to judge whether the number of the group of the minimum value is unique; the allocation unit is used for if the number of the group of the minimum value is unique, from the preset Random numbers are taken from the random sequence, and the target objects are assigned according to the random numbers; if the number of groups with the minimum value is not unique, a group is randomly selected from the group with the same minimum value of the overall difference degree As a target group, the target objects are assigned to the target group.

Optionally, the allocating unit is configured to perform the following steps to allocate the target object according to the random number: judging whether the random number is greater than the probability of completely random grouping; if the random number is greater than the probability of completely random grouping, Assigning the target object to a target group, where the target group is the group where the minimum value is located; if the random number is less than or equal to the completely random grouping probability, then assigning the target object according to a completely random grouping method.

Optionally, when the random number is taken from the preset random sequence, the row where the random number is located is marked, and the ID number of the target object using the random number is associated.

Optionally, the basic characteristics of the target object include at least one of the following: prognostic factors and prognostic levels.

In the embodiment of the present invention, the basic characteristics of the target object and the distribution of the objects that have been included in the group are obtained; according to the basic characteristics and distribution, the overall distribution of the target object to each group to the system is calculated. Degree of difference; sort the values of each overall difference degree, determine the minimum value, and record the group where the minimum value is located; judge whether the number of the minimum value group is unique; if the number of the minimum value group is unique, start from the preset Random numbers are taken out from the random sequence, and target objects are assigned according to the random numbers; if the number of groups with the minimum value is not unique, a group is randomly selected from the group with the same overall difference as the target group, and the target object The way of assigning to the target group is to use a "random seed" to automatically generate all random sequences. When the dynamic random grouping method needs to use random numbers, it is directly taken from the pre-generated "random sequence" to achieve dynamic randomness. The purpose of "reproducibility" of the grouping method, thereby realizing the technical effect of the dynamic random grouping method applied in the clinical trial of new drugs, and then solving the technical problem that the dynamic random grouping method does not have reproducibility.

Description of drawings

The accompanying drawings described here are used to provide a further understanding of the present invention and constitute a part of the application. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations to the present invention. In the attached picture:

Fig. 1 is a schematic flow diagram of an optional dynamic random grouping method according to an embodiment of the present invention;

FIG. 2 is a schematic flow diagram of another optional dynamic random grouping method according to an embodiment of the present invention;

Fig. 3 is a schematic structural diagram of an optional dynamic random grouping system according to an embodiment of the present invention.

Detailed ways

In order to enable those skilled in the art to better understand the solutions of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only It is an embodiment of a part of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

It should be noted that the terms "first" and "second" in the description and claims of the present invention and the above drawings are used to distinguish similar objects, but not necessarily used to describe a specific sequence or sequence. It is to be understood that the data so used are interchangeable under appropriate circumstances such that the embodiments of the invention described herein can be practiced in sequences other than those illustrated or described herein. Furthermore, the terms "comprising" and "having", as well as any variations thereof, are intended to cover a non-exclusive inclusion, for example, a process, method, system, product or device comprising a sequence of steps or elements is not necessarily limited to the expressly listed instead, may include other steps or elements not explicitly listed or inherent to the process, method, product or apparatus.

Example 1

According to an embodiment of the present invention, a method embodiment of a dynamic random grouping method is provided. It should be noted that the steps shown in the flow chart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and , although a logical order is shown in the flowcharts, in some cases the steps shown or described may be performed in an order different from that shown or described herein.

Fig. 1 is a dynamic random grouping method according to an embodiment of the present invention, as shown in Fig. 1, the method includes the following steps:

Step S101, acquiring the basic characteristics of the target object and the distribution of the objects that have been included in the group among the groups.

In the above step S101 of the present application, the target object may be a new patient, and the basic characteristics of the target object include at least one of the following: prognostic factors and prognostic levels. The basic characteristics of the target object may also include the chronological order of patients' enrollment.

Among them, prognosis refers to predicting the possible course and outcome of a disease.

Step S102, according to the basic characteristics and distribution, calculate the overall degree of difference brought to the system by assigning the target object to each group.

Among them, the calculation of the overall degree of difference brought to the system by assigning the target object to each group may include:

Calculate the degree of difference sq(n,p) brought to each layer if the target object is assigned to a certain group;

Calculate the standard deviation sa(n,p) brought to each layer if the target object is assigned to a certain group;

According to sa(n, p) and the weight value w(n) of each factor, the overall difference degree brought to the system by assigning the target object to each group is calculated respectively.

Step S103, sort the values of each overall difference degree, determine the minimum value, and record the group where the minimum value is located.

Among them, the group where the minimum value is located is taken as the target group to be assigned.

Step S104, judging whether the number of minimum value groups is unique.

Wherein, after the minimum value is determined from the overall difference degree, it is judged whether the number of groups of the minimum value is unique.

Step S105 , if the number of groups with the minimum value is unique, a random number is taken from a preset random sequence, and target objects are allocated according to the random number.

Optionally, according to the random number, assigning the target object includes:

Determine whether the random number is greater than the probability of completely random grouping;

If the random number is greater than the probability of completely random grouping, assign the target object to the target group, and the target group is the group where the minimum value is located;

If the random number is less than or equal to the probability of completely random grouping, the target objects will be assigned according to the completely random grouping method.

Among them, the completely randomized grouping method (also known as completely randomized design), refers to the use of a completely randomized method to assign homogeneous test subjects to each treatment group, and then observe the experimental effects of each group.

Wherein, when the random number is taken out from the preset random sequence, the row where the random number is located is marked, and the ID number of the target object using the random number is associated. Specifically as shown in Table 1:

Table 1

Step S106, if the number of groups with the minimum value is not unique, a group is randomly selected from the groups with the same overall difference degree of minimum value as the target group, and the target object is assigned to the target group.

As shown in Figure 2, the dynamic random grouping method of the present embodiment includes the following steps:

Step A, read the basic characteristics of the new patient.

Among them, the basic characteristics of new patients include important prognostic factors and levels.

Step B, the distribution of the enrolled patients among the treatment groups.

Step C, calculate the overall degree of difference brought to the system after the new patient is assigned to each treatment group.

Step D, sort all the differences, and record the group where the minimum value is located, and use it as the target group to be assigned.

Step E, judging whether the number of minimum value groups is unique.

If yes, perform step F;

If not, go to step I.

Step F, if the minimum value group is unique, a random number is taken from a preset random sequence.

In this embodiment, according to the number of patients enrolled in the trial, a sufficient number of random sequences are generated

Step G, judging whether it is greater than the probability of completely random grouping.

If yes, execute step J;

If not, go to step H.

Step H, allocate patients according to the method of complete random grouping (completely random allocation of patients is determined by the random number in the random sequence).

Step I, if the minimum value group is not unique, one of the minimum value groups with the same degree of difference is randomly selected as the target group (patient grouping is determined by random numbers in the random sequence).

Step J, assigning patients according to the target group.

In this example, after the test is completed, the random grouping process can be reproduced according to the basic characteristics of the patients and the time sequence of the patients' enrollment, combined with the "random sequence table".

Example 2

According to the embodiment of the present invention, a dynamic random grouping system is also provided, as shown in FIG. 3 , the dynamic random grouping system includes an acquisition unit 301, which is used to acquire the basic characteristics of the target object, and the objects that have been grouped in each group The distribution situation among them; the calculation unit 302 is used to calculate the overall difference degree that the target object is assigned to each group to the system according to the basic characteristics and the distribution situation; the processing unit 303 is used to calculate each overall The values of the degree of difference are sorted, the minimum value is determined, and the group where the minimum value is recorded; the judging unit 304 is used to judge whether the number of the group of the minimum value is unique; the allocation unit 305 is used to if the minimum value The number of value groups is unique, a random number is taken from the preset random sequence, and the target object is allocated according to the random number; if the number of the minimum value group is not unique, the same overall difference Randomly select a group from the group with the minimum value of degree as the target group, and assign the target object to the target group.

Optionally, the allocating unit is configured to perform the following steps to allocate the target object according to the random number: judging whether the random number is greater than the probability of completely random grouping; if the random number is greater than the probability of completely random grouping, Assigning the target object to a target group, where the target group is the group where the minimum value is located; if the random number is less than or equal to the completely random grouping probability, then assigning the target object according to a completely random grouping method.

Optionally, when the random number is taken from the preset random sequence, the row where the random number is located is marked, and the ID number of the target object using the random number is associated.

Optionally, the basic characteristics of the target object include at least one of the following: prognostic factors and prognostic levels.

The serial numbers of the above embodiments of the present invention are for description only, and do not represent the advantages and disadvantages of the embodiments.

In the above-mentioned embodiments of the present invention, the descriptions of each embodiment have their own emphases, and for parts not described in detail in a certain embodiment, reference may be made to relevant descriptions of other embodiments.

In the several embodiments provided in this application, it should be understood that the disclosed technical content can be realized in other ways. Wherein, the device embodiments described above are only illustrative. For example, the division of the units may be a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components may be combined or may be Integrate into another system, or some features may be ignored, or not implemented. In another point, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection of units or modules may be in electrical or other forms.

The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple units. Part or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, each unit may exist separately physically, or two or more units may be integrated into one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

If the integrated unit is realized in the form of a software function unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the essence of the technical solution of the present invention or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium , including several instructions to make a computer device (which may be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage media include: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes. .

The above is only a preferred embodiment of the present invention, and it should be pointed out that for those of ordinary skill in the art, some improvements and modifications can also be made without departing from the principles of the present invention. It should be regarded as the protection scope of the present invention.

Claims (8)

1. A dynamic random grouping method, characterized in that, comprising: Obtain the basic characteristics of the target object, and the distribution of the grouped objects among the groups; According to the basic characteristics and the distribution, calculate the overall degree of difference brought to the system by assigning the target object to each group; Sort the values of each overall difference degree, determine the minimum value, and record the group where the minimum value is located; Judging whether the number of groups of the minimum value is unique; If the number of the minimum group is unique, a random number is taken from a preset random sequence, and the target object is allocated according to the random number; If the number of groups with the minimum value is not unique, a group is randomly selected from groups with the same minimum value of the overall difference degree as the target group, and the target object is assigned to the target group. 2. The method according to claim 1, wherein said distributing said target object according to said random number comprises: Judging whether the random number is greater than the probability of completely random grouping; If the random number is greater than the probability of completely random grouping, assigning the target object to a target group, where the target group is the group where the minimum value is located; If the random number is less than or equal to the completely random grouping probability, the target object is assigned according to a completely random grouping method. 3. The method according to claim 1, wherein when the random number is taken out from the preset random sequence, the row where the random number is located is marked, and the random number is used The ID number of the target object is associated. 4. The method according to any one of claims 1 to 3, wherein the basic characteristics of the target object include at least one of the following: prognostic factors and prognostic levels. 5. A dynamic random grouping system, characterized in that it comprises: The acquisition unit is used to acquire the basic characteristics of the target object and the distribution of the objects that have been included in the group among the groups; A calculation unit, configured to calculate the overall degree of difference brought to the system by assigning the target object to each group according to the basic characteristics and the distribution; A processing unit, configured to sort the values of each overall difference degree, determine the minimum value, and record the group in which the minimum value is located; a judging unit, configured to judge whether the number of groups of the minimum value is unique; The allocation unit is used to take out a random number from a preset random sequence if the number of the group with the minimum value is unique, and allocate the target object according to the random number; if the number of the group with the minimum value If the number is not unique, a group is randomly selected as the target group from the group with the minimum value of the same overall difference degree, and the target object is assigned to the target group. 6. The system according to claim 5, wherein the allocation unit is configured to perform the following steps to allocate the target object according to the random number: Judging whether the random number is greater than the probability of completely random grouping; If the random number is greater than the probability of completely random grouping, assigning the target object to a target group, where the target group is the group where the minimum value is located; If the random number is less than or equal to the completely random grouping probability, the target object is assigned according to a completely random grouping method. 7. The system according to claim 5, wherein when the random number is taken out from the preset random sequence, the row where the random number is located is marked, and the random number is used The ID number of the target object is associated. 8. The system according to any one of claims 5 to 7, wherein the basic characteristics of the target object include at least one of the following: prognostic factors and prognostic levels.