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Statistical Design and Analytic Considerations for N-of-1 Trials (Chapter 4)
Boca Raton, Fla. Design of experiments.
Scientific experiment Statistical design Control Internal and external validity Experimental unit Blinding Optimal design : Bayesian Random assignment Randomization Restricted randomization Replication versus subsampling Sample size. Glossary Category Mathematics portal Statistical outline Statistical topics.
Outline Index. Descriptive statistics. Mean arithmetic geometric harmonic Median Mode. Central limit theorem Moments Skewness Kurtosis L-moments. Index of dispersion. Grouped data Frequency distribution Contingency table. Pearson product-moment correlation Rank correlation Spearman's rho Kendall's tau Partial correlation Scatter plot.
Data collection. Sampling stratified cluster Standard error Opinion poll Questionnaire. Scientific control Randomized experiment Randomized controlled trial Random assignment Blocking Interaction Factorial experiment.
Adaptive clinical trial Up-and-Down Designs Stochastic approximation. Cross-sectional study Cohort study Natural experiment Quasi-experiment. Statistical inference. Z -test normal Student's t -test F -test. Bayesian probability prior posterior Credible interval Bayes factor Bayesian estimator Maximum posterior estimator. It includes more background material, greater coverage of important statistical techniques, including Bayesian methods, and discussion of analysis using a number of statistical software packages.
Primarily aimed at statisticians and researchers working in the pharmaceutical industry, the book will also appeal to physicians involved in clinical research and students of medical statistics. Some basic considerations concerning estimation. Other outcomes and the ABBA design. Normal data from designs with three or more.
Neither the patient nor the doctor knew the order of treatments. At the end of the study, rather than simply computing results per individual, the researchers also aggregated data for the 38 patients who completed at least two rounds of each treatment. The use of N-of-1 trials as a tool for clinical research, as opposed to purely for patient care, is attracting new interest as the scientific community grapples with disappointments in the field of precision medicine. Promises that approaches such as genome screening would identify the right drugs for the right people have been fulfilled in only a handful of cases, and much of the problem seems to stem from unseen sources of variability in treatment responses—both between patients, and, perhaps less appreciated, within the same patient over time.
Although originally framed as a way to move away from population-level averages, N-of-1 trials could help tackle both intra- and interindividual variation, as researchers collect multiple, detailed measures on each person. You can use. Nikles notes that, provided effort is made to include a representative sample of patients, an N-of-1 series could provide more information for less effort compared to an RCT, making it an attractive approach for studying drug responses in rare diseases. One group in the Netherlands recently demonstrated this principle with a study of mexiletine, a sodium-channel blocker that has for decades been used as a local anesthetic and antiarrhythmic agent.
A RCT of around 60 people found that the drug was also effective for treating muscle stiffness in a disorder known as nondystrophic myotonia; last year, the Netherlands team found a comparable level of statistical support for efficacy after analyzing aggregated data from just 11 N-of-1 trials. Researchers are still working out how to properly combine data from trials specifically designed to be run independently.
Aggregating data consisting of repeated measures per individual, potentially taken over different durations and with an eye toward different patient-specified goals, necessitates a careful statistical approach. Bayesian techniques weight data from each new patient against existing data from previous patients and provide results in terms of probabilities of efficacy, rather than a more-limited conclusion based on p-values. Roustit, whose team incorporated Bayesian techniques in its analysis of responses to sildenafil, says the method takes some getting used to for clinicians more familiar with RCT data.
The first is the development of technology such as cloud-connected activity monitors that could minimize the effort needed to carry out the trials, says Schork.
Crossover study - Wikipedia
More than , health-related mobile apps are available worldwide, while Fitbit, a company offering activity-monitoring wristbands, reported that its number of active users exceeded 27 million at the end of last year. Back in Queensland, Payze describes her experience in the melatonin trial in a similar way, noting that she enjoyed being proactive about her sleep problems and happily used a sleep-monitoring watch for part of the study.
In fact, the program is conducting and planning several further projects. COM, Varijanta F or a few months in the first half of , Chris Payze started each morning at home in Queensland, Australia, by jotting down answers to a series of questions. A patient works with her physician to develop a study design with the primary goal of finding the best course of treatment for her.
She alternates between taking a drug and a placebo during the course of the trial. The drug and placebo are made into identical capsules, which she takes in treatment blocks of several days or weeks at a time in a randomized sequence. The patient receives detailed feedback at the end of the study about her results, plus a recommended treatment plan based on that information.