Assessing at the participant level the applicability of clinical trials to a specific patient

Assessing at the participant level the applicability of clinical trials to a specific patient

Dr. Cahan was supported by an appointment to the Research Participation Program for the Centers for Disease Control and Prevention: National Center for Environmental Health, Division of Laboratory Sciences, administered by the Oak Ridge Institute for Science and Education through an agreement between the Department of Energy and DLS. Dr. Cimino is supported in part by research funds from the National Library of Medicine and the NIH Clinical Center.

When making clinical decisions concerning an individual patient based on a clinical trial, we have to assess the applicability of the trial’s results to the patient in question. In order for us to extrapolate from a trial to a patient, it is said that the patient has to be sufficiently similar to the trial population.

However, considerable variability usually is found among a trial’s participants in their reaction to the trial intervention. Whereas some participants may benefit from an intervention, others may actually be harmed by it. Yet trials almost invariably report aggregate-level results, which may mask such between-participant variability. As a result, with few exceptions, similarity can only be assessed between a patient and the trial’s population as a whole.

Comparing a patient to a study population based on all coded patients’ characteristics may enhance clinicians’ ability to answer the question so commonly asked: Do the results of this clinical trial apply to my patient?

All available baseline characteristics, including demographics, past medical history, social history, physical exam findings, and lab tests will be used. One participant at a time will be compared to a reference patient and a score indicating the degree of similarity between them will be computed. Trial participants will then be ranked by their degree of similarity to the reference patient. A subpopulation analysis of the outcome of only those participants who are most similar to the reference patient will be conducted. Using reference patients whose outcome is known, we could assess the prediction based on similar participants compared to prediction based on the entire study population.

The kind of analysis we suggest could be applied on any clinical trial. If proven to better predict patients’ outcome, it would almost certainly be widely used would have bearings on management decisions regarding many, many patients.

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Medicine: belimumab, Condition: Systemic Lupus Erythematosus, Phase: 3, Clinical Study ID: HGS1006-C1057, Sponsor: GSK" }]

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