Medical Device Clinical Trials
The medical device industry constitutes a significant sector of the entire healthcare industry in the US. Roughly 42% of the world’s total health care industry works on the medical device industry. However, the medical device industries are comparatively small from pharmaceutical companies.
The medical device research is essential in the overall development of pharmaceutical research. It acts as a primary tool for the aid of the alternative life-saving options at severe health conditions and diagnostic testing. The clinical studies are usually carried out in the form of phases such as “Phase 2 study of any new drug” and other phases. The clinical trials for medical devices are similar to the pharmaceuticals, but there is a slight difference in the carrying out the trial and the design of the trial. The clinical trials may not be even required for the medical devices in few cases. Few examples of medical devices range from tongue depressors and elastic bandages to heart stent and instruments for blood screening which show the existence of HIV.
Medical devices are a lot different from most of the pharmaceutical products in accordance with the terms of FDA approval process, duration and pace of respective study. The clinical trials on drugs mainly focus on the usage of drugs and dosage, but the medical device clinical trials work on prototype development. It employs all types of interrelated statistical analysis and studies. The medical devices are strictly classified into Class 1, 2 and 3. In accordance with the regulatory requirements, class 3 controls the most and class 1 control the least of all. Class 1 is usually the simple devices which pose minimal risk to the users like elastic bandages, bedpans and more. Class 2 are those devices which pose a moderate risk level like sutures, inflatable blood pressure cuffs, and intravenous administration sets. The Class 3 devices are considered to be the most high-risk devices which can pose a serious risk of injury or illness to the patients. The most common examples of class 3 devices are blood vessel stents, breast implants, implantable pacemakers and more. The class 3 devices usually necessitate Premarket Approval (PMA) for the usage.
There are mainly two types of studies in the medical device research namely clinical utility and reproducibility. Reproducibility study is conducted to prove the precision and accuracy of a device. For instance, a quantitative diagnostic test uses the coefficient of variation, the precision analysis uses linear mixed models, and qualitative diagnostic test utilizes hit rates to verify reproducibility. A clinical utility is executed to show the practical usage of the device in clinical practice. The diagnostic studies for medical devices are much shorter than the usual duration as compared to pharmaceutical studies.
Handling Missing Data
During the execution of the clinical trial, there may be a lot of missing data which may cause problems in future. Handling of the missing data can be a challenging task. The missing data may be caused due to many reasons including the patients lost due follow up with the relocation of the trial, closing of centers before the completion of the study, and patients withdrawing the consent and dropping out. The missing data can affect the outcomes of the study and even cause biased treatment comparisons. Tipping point analysis can be used in the medical device clinical trials. A tipping point analysis fills up the missing data space with the values so that the p-value is equal to or more than the pre-specified significance level.
Measures of Diagnostic Accuracy
The accuracy of the clinical test is identified by comparing the outcome from the diagnostic test(negative or positive) to the true condition(absence or presence of disease) of the respective patient. The basic measures for accuracy are mainly specificity and sensitivity. Specificity focuses on the specific area of the test, excluding the disease or condition from which the patient is not suffering. It is the probability of the negative result as the patient is not suffering from the condition of interest. Sensitivity is the ability to test or detect the current condition or status when the disease is present. There will be a probability of the positive test given to the patient actually suffering from the condition or disease. In medical clinical trials, the accuracy of the results is most important to know about the true positive of the test by the predictive values. The negative predictive value (NPV) is the probability of the patient not suffering from the condition or disease. The positive predictive value (PPV) is the probability that the diagnosed patient is suffering from the tested condition or disease.
Adaptive designs use the data to determine the adjustments to the aspects of the trial according to the plan. One of the most common notions is the early stoppage of the trial. To curb the following possibility of the early stoppage, an interim analysis should be performed before the final analysis. It is planned to assess if the following accumulated evidence at the interim study is enough to land to an appropriate inference. The adaptive design has a great ability to adjust the size of the same according to the needs of the study at the time of course of the trial. The adaptive trial designs are much easier to implement by the help of Bayesian methods rather than using the frequentist method. By implementing the Bayesian method, the trials are more adaptive and flexible in design and study. From the analysis to the designs of medical device data, a great experience is required in the technical field for the ease and accuracy of the study.
The medical device clinical trial industry is growing at a decent pace. The clinical research is necessary for assessing the effectiveness and safety of the various medical devices available in the development process and markets. The high-quality precision and accuracy is the main key of the medical device clinical trial. It has also become a vital element in most of the pharmaceutical researches like the devices used to deliver diagnostic images or drugs to monitoring therapies.