Clinical trials are most often performed in the controlled trial sites and treatment guidelines are advocated based on outcomes of these clinical trials. However, a physician sitting in his clinic, far away from the clinical trial sites, feels disconnected and does not relate easily to these trials. Also, in a busy practice, it is hard for physicians to keep up with the rapidly evolving literature and changing practice paradigms. Hence, most derive information from attending meetings and listening to speakers. However, lets understand that the final application of clinical trials and advising a particular treatment for a patient in your clinic happens on a one to one basis. You own up to the decisions you make and face the consequences. Hence, the onus is on you to apply clinical trials to your patients.
Let us first understand how clinical trials differ from the real world scenario. In one word, the answer is “Variability”. Clinical trials limit variability and are performed in a controlled environment. Hence statistics can be applied and conclusions drawn in a robust manner. But when you are with your patient, there is no control on variability in their age, disease characteristics, socio-economic status, follow up patterns etc. So how do you adjust for these before applying clinical trials data to the patient sitting in front of you? I present a simple stepwise approach on how I go about doing this.
Step 1: Inclusion criteria:
Look at the inclusion criteria used to enroll patients in the clinical trials and see whether your patient meets these. If your patient is a good match, only then can you expect them to get results similar to the trials data.
Step 2: Variability:
It will be extremely difficult to have every patient exactly fit the inclusion criteria of a clinical trial. Try and assess how your patients’ characteristics differ from those enrolled in the clinical trial. Doing a quick math in your mind and assessing how different your patient is from the inclusion criteria is a good approach. I find that if patients vary by more than 25% from those in the clinical trial, you should not expect them to get results as promised by the trial.
Step 3: Intervention:
Choose the arm of treatment from the clinical trial that shows the best outcome as far as possible. Trials often state non-inferiority designs and say that both drugs are equally effective. It takes a lot of subgroup analysis and statistical prowess to tease out data and advocate one drug over another. In such a case, use the variability of your patient and try to find a best fit. After choosing the drug, follow the frequency of drug dosage, follow up regimen and tests to be performed at every visit as far as possible.
Step 4: Assess outcomes:
This is the most important part as far as a physician treating his patient goes. You will need to judge whether outcomes mentioned in the trial are being replicated in your clinical environment. You will be surprised that despite following all the above steps, you may not get outcomes as published in clinical trial reports. That is again because of the variability and uncontrolled environment in which your data has been collected.
Step 5: Collect your own data:
In my opinion, every physician can contribute in his/her own small or big way to literature. Make it a practice to collect your own data and after treating a good number of patients, analyze how your results obtained in the real world, differ from the clinical trials data. You may find subgroups of patients that respond well and some who do not respond as expected. This will help you refine your practice patterns and get optimum results.
Finally, application of clinical trials data to your practice depends on how closely you follow the above-mentioned steps. You will see that these will help you adopt evidence-based medicine in daily life, optimize your outcomes, boost your own confidence and ultimately benefit your patients a great deal. Some analytic minds will also come up with newer questions and try and publish their results. Many such questions and publications pile up in literature and culminate into clinical trials in the future. So do not underestimate your contribution to literature and try to walk the extra mile to publish your own results.