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National Cardiovascular Disease Management Capability Assessment and Improvement Project——CDQI (Cardiovascular Disease Quality Initiative) , jointly carried out by the National Clinical Research Center for Cardiovascular Diseases and the Cardiovascular Branch of the Chinese Medical Association. The goal is to launch a new model of heart disease treatment that is nationwide, information sharing, hierarchical diagnosis and treatment, and regional coordination, and becomes an important driving force for promoting “Healthy China” in an all-round way.
03month31day 14:00-14:40, the second phase of clinical scientific research training invited Professor Du Xin from Beijing Anzhen Hospital Affiliated to Capital Medical University as a keynote speaker, bringing wonderful popular science education content! The content of the conference is now organized as follows for readers to learn and communicate!
Professor Du Xin explained the four elements in the clinical research process in the last course:PICO , in this course, Prof. Du discusses the most important element in PICO——O (Outcome), is the endpoint selection of randomised controlled trials, and made a wonderful interpretation.
Fig.1
Professor Du Xin said that in setting the endpoints of randomized controlled trials, the first principle is to clarify whether the endpoints of the study are important to patients, and the second is to clarify the clinical significance to patients. . If the research end point has no clear meaning to the patient and the doctor, it is generally called “not patient-centered research end point”. When conducting clinical research, one of the most important principles is to select “patient-centered research endpoints”, which are more instructive to patients. For example, in clinical studies of patients with heart failure, after treatment, whether the patient’s survival time is prolonged, whether the number of hospitalizations is reduced, whether the interval between hospitalizations can be prolonged, and the change in 6-minute walking distance are all meaningful clinical endpoints. The most important thing in clinical trials is to monitor the endpoints that are very important to patients. It is not enough to only observe indirect indicators (for example, the number of premature beats is a commonly used surrogate endpoint). At the same time, it is also necessary to observe the correlation between the surrogate endpoint and the clinical endpoint. sex.
The third principle of conducting RCTs is that the endpoint of a clinical trial must include the end of every aspect. For example, clinical studies using chemotherapeutic agents in cancer not only focus on the important clinical endpoint of prolonging long-term survival of patients with surgery, but also report on perioperative risks. The life-extending effects of chemotherapeutics need to be focused on, but the effects of chemotherapeutics on patients’ quality of life also need to be reported. When conducting clinical research, it is necessary to fully understand and comprehensively consider the impact of all aspects of clinical intervention.
Fig.2
Professor Du then said that the selection of clinical endpoints is mainly divided into two categories: the first category is “counting the number of people”, that is, the 5-year survival rate of patients is calculated, which is calculated by the number of patients To calculate the ratio, the disease progression process of the patient is not taken into account, as shown in Figure 2, a significant difference in the changes in mortality of aortic dissection (A) and lung cancer (B) can be observed; the second category is “measurement” (measurement) )”, such as measuring the patient’s blood pressure, the number of premature beats, cholesterol levels and other basic physiological indicators, so as to obtain a continuous variable. The length of a patient’s hospital stay is also a measurable indicator, such as the time from discharge to the first cardiovascular event in patients with heart failure after discharge, which may be 3 months, 2 months, 1.5 months, or 20 days after readmission. Called “Time-to-event” data, it can provide more information. When conducting clinical research, it is necessary to clarify the selection of clinical endpoints.
Figure 3
in clinical research In order to ensure that the study has sufficient clinical significance, it is necessary to accumulate enough endpoint events. This requires that the type II error is sufficiently small, and the sample size needs to be increased, or multiple endpoints should be selected to reduce the possibility of type II errors. The more common cardiovascular composite endpoints are cardiovascular death, non-fatal stroke, and non-fatal myocardial infarction. For patients, the severity and importance of these endpoints are similar. The premise of selecting composite endpoints is that, The importance of the components of the composite endpoint should be of similar importance. In addition, the interventions in this study had similar effects on the components of the composite endpoint. In Figure 3 (left), the study intervention on the patient’s risk of death The magnitude of reduction and the magnitude of reduction in non-fatal stroke and non-fatal myocardial infarction are very similar, and in this case, it is feasible to combine these endpoints into a composite endpoint. However, in Figure 3 (right), it can be observed Given that the impact of interventions on several clinical endpoints is quite different, and the magnitude of reduction of interventions on each endpoint is also different, this situation is not suitable for combining each endpoint event into a composite endpoint. In addition, cardiovascular death must be considered A problem that needs to be used as one of the components of the composite endpoint.
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Afterwards, Prof. Du Xin took a clinical study on IIb/IIIa receptor antagonists as an example to make more For detailed interpretation, it can be seen from Figure 4 that the study set cardiovascular death, myocardial infarction, refractory angina, etc. as composite endpoints, but the effects of each component of the composite endpoint are different, and the benefits of the interventions in this study Mainly derived from the effect on the end point of the study on refractory angina pectoris, but Combined with the effect on individual endpoints, the effect of the drug on death was very slight, and the meta-analysis did not find an effect on death. Therefore, although the benefit of the drug was found in the observation of the clinical composite endpoint, it is necessary to clearly report the component of the benefit, especially the effect on cardiovascular death and myocardial infarction.
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Professor Du went on to say that if p<0.05 in clinical research, it means that the type I error in the research is acceptable. Taking the CRPRICORN study as an example, the primary endpoint was all-cause mortality. However, when the study progressed to the mid-term, the data safety committee found that although the enrolled population was patients with poor cardiac function, the patients were relatively healthy, and the endpoint events were far from expectations. This will lead to an increase in the possibility of type II errors, that is, an increase in the probability of false negative results. Therefore, at the recommendation of the Steering Committee, the study endpoint was changed to the composite endpoint: all-cause mortality or cardiovascular hospitalization, p<0.045, and all-cause mortality, p<0.005. The results of the study were: all-cause mortality, p=0.03; the new composite endpoint, p=0.30, was not significant. Assuming that the study endpoints are not modified, positive results can be obtained, but after the study endpoints are modified, positive results cannot be obtained, which is in line with the dilution effect during the end-point event process, which suggests that when choosing the study endpoints, it is necessary to avoid the research that has less impact on the study. event.
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However, when choosing composite endpoints, it should also be noted that it is not that the more the composite endpoints, the better. Taking a study of the hypoglycemic drug pioglitazone in the treatment of type 2 diabetes as an example, the incidence of death, non-fatal myocardial infarction, and stroke caused by pioglitazone was lower than that of placebo. Benefit effect. However, after the composite endpoint was formed, p=0.08, no positive result was obtained, which was inconsistent with the conclusion drawn from a single endpoint. Therefore, it is not necessary to have more composite endpoints, and to avoid adding too many factors that may not be affected by the intervention, which may dilute the original findings.
Fig.7
Figure 8
As mentioned above, in the selection of composite endpoints, it is necessary to assign the same weight to individual endpoints, but theoretically, this is unfair, such as myocardial infarction and death, although both are serious, but the severity There is still a certain gap. In response to this problem, Professor Du introduced a statistical method: win ratio. This method compares each patient in the treatment group with each patient in the control group, and the total number of comparison pairs is N, where N=Nt×Nc, and win rate=T wins/T loses. In most heart failure studies, the time to first event question is based on selection from enrollment to the occurrence of the first event, and the impact of cardiovascular death on the study endpoint is approximately two-thirds. In a study of ARNI in heart failure shown in Figure 8B, it was observed that ARNI had a similar effect on cardiovascular death and heart failure hospitalization, with similar magnitude of benefit, but with time, the success rate (Figure A) is stable. However, in the study of digoxin in the treatment of heart failure (Figure 8D), it was observed that digoxin had no effect on mortality, and had a greater effect on heart failure rehospitalization, taking into account the important effect of cardiovascular death on clinical endpoints. , it can be found that the initial winning rate is relatively high, but with the extension of time, the winning rate gradually approaches 1, which cannot reflect the advantages of digoxin in the treatment of heart failure. Using the win rate to reflect the therapeutic effect of the drug may reflect the specific difference more objectively.
The question of endpoint selection in randomized controlled trials , Prof. Du Xin explained in a eloquent way, from the simple to the deep, and made a very detailed interpretation in this lecture, leading the audience to review the past and learn new things, which benefited the participants a lot. Clinical research is a grand subject that requires more study and communication. Welcome more scholars to participate in the follow-up lectures to learn the relevant knowledge of clinical research together!
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CDQI
National Cardiovascular Disease Management Capability Assessment and Improvement Project