Recent quotes:

Capsule Commentary on Odineal et al., Effect of Mobile Device-Assisted N-of-1 Trial Participation on Analgesic Prescribing for Chronic Pain: Randomized Controlled Trial | SpringerLink

In this study, Odineal and colleagues1 examined changes in prescription analgesic prescribing for approximately 200 patients with chronic pain randomized to either a mobile app–enabled N-of-1 study (tailored, individualized pain-control interventions) or a control group. The app allowed patients to choose two treatment plans to compare over several short trials, selecting from a list of commonly prescribed analgesics or non-pharmaceutical therapies such as yoga or physical therapy. Among intervention patients, the authors found a clinically and statistically significant decrease in NSAID prescriptions relative to controls. Nearly one-quarter of intervention patients stopped NSAIDs during the study period, and the between-group difference was also significant.

N-of-1 Trials: FDA Plots Path to Regulation | RAPS

“At the very least, during the time needed to discover and develop an intervention, quantifiable, objective measures of the patient’s disease status should be identified and tracked, since, in an N-of-one experiment, evaluation of disease trends before and after treatment will usually be the primary method of assessing effectiveness,” Woodcock and Marks explained.

Living a longer, healthier life: A systems approach to medicine at WesternU's Pumerantz Lecture | Benzinga

"We think that clinical trials in the future ought to be done as N-of-1 (single subject) experiments," Hood said. "In a cancer trial we can use the individual data clouds to actually identify biomarkers that distinguish the responders from the non-responders. Then what we will do is a second trial of 50 patients with all responders. And if you get a 98 percent response rate, the FDA will approve your drug in the blink of an eye. You go from spending $1.5 billion on a clinical trial to spending hundreds of thousands of dollars on a clinical trial." Hood and his collaborators completed a study that used dynamic data clouds to improve wellness. "A wellness study of 108 individuals using personal, dense, dynamic data clouds," published in Nature Biotechnology in 2017, involved collecting the complete genome sequences of 108 volunteers, including Hood. The subjects each gave blood draws every three months to measure 1,200 analytes of three classes: clinical chemistries, metabolites and proteins. They measured gut microbiome every three months and used Fitbit and other devices for digital health measurements. "What these gave us for each individual was longitudinal data clouds that, when analyzed, led to actionable possibilities that if executed by the individual could either improve their wellness and/or let them ameliorate or avoid disease," Hood said. "The big question in all of this is: How do you change social behavior? What we used were wellness coaches, trained in psychology and nutrition and nursing, who were magnificent. They would elicit from the individual exactly what they wanted in their health objectives, and this is not easy to do."

The 'pathobiome' -- a new understanding of disease -- ScienceDaily

The concept acknowledges that all organisms are in fact complex communities of viruses, microbes and other small organisms (e.g. parasites) which can interact to affect health or disease status at any given time. These complex communities continually interact with their hosts, sometimes conferring benefits (e.g. "good" bacteria in the human gut microbiome), and at other times causing harm by contributing to disease. When these communities combine to cause disease they are termed "pathobiomes" -- a recognition of their collective shift away from the healthy-state "symbiome."

Pragmatic trials revisited: applicability is about individualization - Journal of Clinical Epidemiology

Classically, clinical research has centered on studying groups of individuals to extrapolate the findings to the general population. It is time to walk back from the population (the average patient) to the individual patient, understanding that population-oriented research is actually exploratory and individual-oriented research is confirmatory [24].

Pragmatic trials revisited: applicability is about individualization - Journal of Clinical Epidemiology

These designs represent an important step toward stratified therapy, but N-of-1 trials [14] are the purest form of pragmatic patient-centered design [15]. N-of-1 trials are multiple-period, crossover experiments comparing two or more treatments within individual patients. They are the optimal design to estimate individual treatment effects directly and to identify the best treatment for each individual patient in each specific setting. The Journal of Clinical Epidemiology has recently published a number of articles reviewing the main features and applications of N-of-1 trials [16].

Educate Your Patients…or They Will Take Medical Advice From Their Hairdresser |

“One of the bigger distractions in sports medicine practices is that patients often focus on what we do with professional athletes…everyone wants to try what worked for Kobe Bryant. But I tell them that is an n of 1, and what they should truly be basing their decision on is the result of a large prospective study where you are looking at efficacy of a specific dosage and formulary, for their particular type of orthopaedic problem. And this is our job to present that data in a fair fashion, particularly because of the appearance of conflict involved in these cash-based procedures that are rarely covered by insurance.  “Because medicine has become a consumer field we must focus on public education. If we were to poll the physicians who are performing most of these treatments, they will likely agree that the evidence is still pending but looking promising, and furthermore that the patients are asking for it.” I spend a good amount of time in my clinic talking to these patients about the current evidence (and lack of such) behind these treatments, and some still do choose to move forward with this option.

Statistical considerations for rare diseases drug development. - PubMed - NCBI

One of the most challenges for rare disease clinical trials is probably the availability of a small patient population. It is then a great concern on how to conduct clinical trials with a small number of subjects available for obtaining substantial evidence regarding safety and effectiveness for approval of the rare disease drug product under investigation. FDA, however, does not have the intention to create a statutory standard for approval of orphan drugs that are different from the standard for approval of drugs in common conditions. Thus, it is suggested that innovative trial designs such as a complete n-of-1 trial design or an adaptive design should be used for an accurate and reliable assessment of rare disease drug products under investigation. In this article, basic considerations, innovative trial designs, and statistical methods for data analysis are discussed. In addition, some innovative thinking for the evaluation of rare disease drug products is proposed.

Cost savings due to n-of-1

Omeprazole was the appropriate treatment in only 52% of these chronic users of acid-suppressing drugs. Eleven of 27 trials (41%) indicated that ranitidine was the preferred treatment. The SPT method proved acceptable to patients, feasible to administer, and reproducible. It can statistically discriminate effectiveness and adverse events and serve as a useful, prognostic tool in community practice by determining the least costly, evidence-based, appropriate treatment.

Industrial n-of-1

The N-of-1 trials propose replacing large-scale trials of whole groups with methodical study of individual patients. However, the requirement to provide specific treatment to different subgroups of patients will make clinical trials more complex, so the industry needs to redesign how it interacts with patients. CROs will need to establish expert teams to structure and run precision-medicine-oriented trials for their sponsor clients.