Preliminary evaluation of the therapeutic effect and safety of drugs on patients with target indications

Provide a basis for the study design and dosage regimen determination of phase III clinical trials

Further verify the therapeutic effect and safety of the drug on patients with target indications, evaluate the relationship between benefits and risks, and ultimately provide sufficient basis for the review of drug registration applications.

Examine drug efficacy and adverse reactions under widespread use

Evaluate the benefits and risks of drug use in general or special populations, and improve dosage, etc.

Evaluate drugs of unknown or questionable effect

Study the dose-effect relationship of a drug

Compare the effects of different administration methods

Evaluate the effectiveness of new uses of old drugs

Compare the effects of different drugs

Study drug-drug interactions

Determine the effectiveness of a drug in a specific patient or setting

Repeat important research

Try to choose subjects with obvious symptoms and signs

The people who are likely to benefit the most and suffer the least harm from this treatment are also the people in whom the effects are most likely to be detected.

Populations of particular interest to the researcher, such as children or the elderly

People for whom the treatment effect is unclear or doubtful

Try to choose research subjects with good compliance

Diagnostic criteria

Inclusion criteria

Exclusion criteria

standard constrain

Exclusion criteria

Possible magnitude of adverse reactions

Are there any indications that should not be treated?

compliance with treatment

Possibility of dropout and loss to follow-up

The size of the effect that the study is likely to detect, i.e., its statistical power

Other factors that may affect study quality

The size of the difference between the experimental group and the control group is the main factor that determines the sample size

If the observation indicator is count data, the lower the frequency of the outcome event in the population, the larger the sample size required.

If the observation indicator is measurement data, the greater the difference (i.e. variance or standard deviation) between individuals, the greater the sample size required.

The significance level α of the test (probability of type I error)

Test power 1-β (β is the probability of type II error)

The smaller α and β are specified, the larger the sample size required.

Factors affecting sample size

Calculation of sample size for count data

Calculation of measurement data sample size

Is the size of a group of people (experimental group or control group)

If the two groups have equal numbers of people, the sample size required for all experiments is 2N

In experiments, the α and β values ​​are generally determined by the researcher according to needs. If you want the results to be more reliable, you can choose smaller α and β values, and the sample size will be larger.

Based on the calculated sample size, increase 10% to 15% to prevent loss to follow-up

Eliminate confounding and bias caused by non-experimental factors

Helps identify side effects of treatment or complications of the disease itself

unpredictable ending

natural history of disease

regression to the mean

Hawthorne Effect*

placebo effect*

Standard control or positive control

placebo control or negative control

cross control

Compare each other

self control

Randomization means that all subjects are assigned to the experimental group or the control group according to a preset probability, regardless of the subjective wishes or objective reasons of the researcher or subject.

Make groups comparable, balance known and unknown confounding factors, reduce selection bias caused by human factors, and improve the authenticity of research results.

Before grouping, subjects and researchers cannot predict or speculate on the grouping situation in advance.

Random ≠ random, each subject has an equal chance to be assigned to any group

simple randomization

block randomization

stratified randomization

single blind trial

double blind trial

triple blind trial

ARR = event rate in the control group - event rate in the experimental group

Research subjects were lost to follow-up due to migration or death from other diseases, thus destroying the representativeness of the original sample.

It means that the experimental group received additional treatment measures that are consistent with the experimental effect, thus creating the illusion of artificially exaggerating the therapeutic effect.

It refers to the phenomenon that patients in the control group receive additional drugs from the experimental group, resulting in artificial exaggeration of the efficacy of the control group and thus underestimation of the effect.

Before randomly allocating research subjects, research subjects should be further screened. All subjects with contraindications to treatment or intervention, those who cannot be traced, those who may be lost to follow-up, those who refuse to participate, and those who do not meet the criteria should be excluded.

Clinical compliance refers to the extent to which patients implement medical instructions in clinical trials. Those who fully implement medical instructions are considered to have good compliance, and vice versa are considered to be non-compliance or poor compliance.

Patients in the experimental group who do not comply with the experimental protocols are equivalent to withdrawing from the experimental group; patients in the control group who do not comply with the control protocols and receive intervention measures in private are equivalent to joining the experimental group

Minimize loss to follow-up, generally requiring the loss-to-follow-up rate not to exceed 10%