James Heywood

Sharing Health Data for Better Outcomes on PatientsLikeMe

Background PatientsLikeMe is an online quantitative personal research platform for patients with life-changing illnesses to share their experience using patient-reported outcomes, find other patients like them matched on demographic and clinical characteristics, and learn from the aggregated data reports of others to improve their outcomes. The goal of the website is to help patients answer the question: “Given my status, what is the best outcome I can hope to achieve, and how do I get there?” Objective Using a cross-sectional online survey, we sought to describe the potential benefits of PatientsLikeMe in terms of treatment decisions, symptom management, clinical management, and outcomes. Methods Almost 7,000 members from six PatientsLikeMe communities (amyotrophic lateral sclerosis [ALS], Multiple Sclerosis [MS], Parkinson’s Disease, human immunodeficiency virus [HIV], fibromyalgia, and mood disorders) were sent a survey invitation using an internal survey tool (PatientsLikeMe Lens). Results Complete responses were received from 1323 participants (19% of invited members). Between-group demographics varied according to disease community. Users perceived the greatest benefit in learning about a symptom they had experienced; 72% (952 of 1323) rated the site “moderately” or “very helpful.” Patients also found the site helpful for understanding the side effects of their treatments (n = 757, 57%). Nearly half of patients (n = 559, 42%) agreed that the site had helped them find another patient who had helped them understand what it was like to take a specific treatment for their condition. More patients found the site helpful with decisions to start a medication (n = 496, 37%) than to change a medication (n = 359, 27%), change a dosage (n = 336, 25%), or stop a medication (n = 290, 22%). Almost all participants (n = 1,249, 94%) were diagnosed when they joined the site. Most (n = 824, 62%) experienced no change in their confidence in that diagnosis or had an increased level of confidence (n = 456, 34%). Use of the site was associated with increasing levels of comfort in sharing personal health information among those who had initially been uncomfortable. Overall, 12% of patients (n = 151 of 1320) changed their physician as a result of using the site; this figure was doubled in patients with fibromyalgia (21%, n = 33 of 150). Patients reported community-specific benefits: 41% of HIV patients (n = 72 of 177) agreed they had reduced risky behaviors and 22% of mood disorders patients (n = 31 of 141) agreed they needed less inpatient care as a result of using the site. Analysis of the Web access logs showed that participants who used more features of the site (eg, posted in the online forum) perceived greater benefit. Conclusions We have established that members of the community reported a range of benefits, and that these may be related to the extent of site use. Third party validation and longitudinal evaluation is an important next step in continuing to evaluate the potential of online data-sharing platforms.

Design, power, and interpretation of studies in the standard murine model of ALS

Identification of SOD1 as the mutated protein in a significant subset of familial amyotrophic lateral sclerosis (FALS) cases has led to the generation of transgenic rodent models of autosomal dominant SOD1 FALS. Mice carrying 23 copies of the human SOD1G93A transgene are considered the standard model for FALS and ALS therapeutic studies. To date, there have been at least 50 publications describing therapeutic agents that extend the lifespan of this mouse. However, no therapeutic agent besides riluzole has shown corresponding clinical efficacy. We used computer modeling and statistical analysis of 5429 SOD1G93A mice from our efficacy studies to quantify the impact of several critical confounding biological variables that must be appreciated and should be controlled for when designing and interpreting efficacy studies. Having identified the most critical of these biological variables, we subsequently instituted parameters for optimal study design in the SOD1G93A mouse model. We retested several compounds reported in major animal studies (minocycline, creatine, celecoxib, sodium phenylbutyrate, ceftriaxone, WHI‐P131, thalidomide, and riluzole) using this optimal study design and found no survival benefit in the SOD1G93A mouse for any compounds (including riluzole) administered by their previously reported routes and doses. The presence of these uncontrolled confounding variables in the screening system, and the failure of these several drugs to demonstrate efficacy in adequately designed and powered repeat studies, leads us to conclude that the majority of published effects are most likely measurements of noise in the distribution of survival means as opposed to actual drug effect. We recommend a minimum study design for this mouse model to best address and manage this inherent noise and to facilitate more significant and reproducible results among all laboratories employing the SOD1G93A mouse.

Accelerated clinical discovery using self-reported patient data collected online and a patient-matching algorithm

Patients with serious diseases may experiment with drugs that have not received regulatory approval. Online patient communities structured around quantitative outcome data have the potential to provide an observational environment to monitor such drug usage and its consequences. Here we describe an analysis of data reported on the website PatientsLikeMe by patients with amyotrophic lateral sclerosis (ALS) who experimented with lithium carbonate treatment. To reduce potential bias owing to lack of randomization, we developed an algorithm to match 149 treated patients to multiple controls (447 total) based on the progression of their disease course. At 12 months after treatment, we found no effect of lithium on disease progression. Although observational studies using unblinded data are not a substitute for double-blind randomized control trials, this study reached the same conclusion as subsequent randomized trials, suggesting that data reported by patients over the internet may be useful for accelerating clinical discovery and evaluating the effectiveness of drugs already in use.

The power of social networking in medicine

AcknowleDgemenTS We would like to acknowledge the valuable comments of Z. Lynch, B. Booth, K. Perampaladas and H. Masum in shaping the overall study design and G. Williams for study data. This study was supported by New Enterprise Associates. J.C. is funded by a grant from the Bill and Melinda Gates Foundation through the Grand Challenges in Global Health initiative. We also graciously thank all the venture capital firms for participating in our qualitative and quantitative analysis.

Patient-reported outcomes as a source of evidence in off-label prescribing: analysis of data from PatientsLikeMe.

Background Evaluating a new use for an existing drug can be expensive and time consuming. Providers and patients must all too often rely upon their own individual-level experience to inform clinical practice, which generates only anecdotal and unstructured data. While academic-led clinical trials are occasionally conducted to test off-label uses of drugs with expired patents, this is relatively rare. In this work, we explored how a patient-centered online research platform could supplement traditional trials to create a richer understanding of medical products postmarket by efficiently aggregating structured patient-reported data. PatientsLikeMe is a tool for patients, researchers, and caregivers (currently 82,000 members across 11 condition-based communities) that helps users make treatment decisions, manage symptoms, and improve outcomes. Members enter demographic information, longitudinal treatment, symptoms, outcome data, and treatment evaluations. These are reflected back as longitudinal health profiles and aggregated reports. Over the last 3 years, patients have entered treatment histories and evaluations on thousands of medical products. These data may aid in evaluating the effectiveness and safety of some treatments more efficiently and over a longer period of time course than is feasible through traditional trials. Objective The objective of our study was to examine the illustrative cases of amitriptyline and modafinil – drugs commonly used off-label. Methods We analyzed patient-reported treatment histories and drug evaluations for each drug, examining prevalence, treatment purpose, and evaluations of effectiveness, side effects, and burden. Results There were 1948 treatment histories for modafinil and 1394 treatment reports for amitriptyline reported across five PatientsLikeMe communities (multiple sclerosis, Parkinsons disease, mood conditions, fibromyalgia/chronic fatigue syndrome, and amyotrophic lateral sclerosis). In these reports, the majority of members reported taking the drug for off-label uses. Only 34 of the 1755 (1%) reporting purpose used modafinil for an approved purpose (narcolepsy or sleep apnea). Only 104 out of 1197 members (9%) reported taking amitriptyline for its approved indication, depression. Members taking amitriptyline for off-label purposes rated the drug as more effective than those who were taking it for its approved indication. While dry mouth is a commonly reported side effect of amitriptyline for most patients, 88 of 220 (40%) of people with amyotrophic lateral sclerosis on the drug reported taking advantage of this side effect to treat their symptom of excess saliva. Conclusions Patient-reported outcomes, like those entered within PatientsLikeMe, offer a unique real-time approach to understand utilization and performance of treatments across many conditions. These patient-reported data can provide a new source of evidence about secondary uses and potentially identify targets for treatments to be studied systematically in traditional efficacy trials.

Perceived benefits of sharing health data between people with epilepsy on an online platform

An epilepsy community was developed on PatientsLikeMe.com to share data between patients to improve their outcomes by finding other patients like them. In a 14-day response period, 221 patients with epilepsy (mean age: 40 years, SD: 12, range: 17-72, 66% female) completed a survey about benefits they perceived. Prior to using the site, a third of respondents (30%) did not know anyone else with epilepsy with whom they could talk; of these, 63% now had at least one other patient with whom they could connect. Perceived benefits included: finding another patient experiencing the same symptoms (59%), gaining a better understanding of seizures (58%), and learning more about symptoms or treatments (55%). Number of benefits was associated with number of relationships with other patients, F(4,216)=8.173, P<0.001). Patients with epilepsy reported an array of perceived benefits similar to those reported by populations with other diseases. Controlled sharing of health data may have the potential to improve disease self-management of people with epilepsy.

Measuring function in advanced ALS: validation of ALSFRS-EX extension items

Background:  With the aid of assistive technology, some patients with amyotrophic lateral sclerosis (ALS) are able to live for several years past the lowest measurable level of function on the Amyotrophic Lateral Sclerosis Functional Rating Scale – Revised (ALSFRS‐R), a widely used end‐point in ALS assessment. There is a research need to monitor patient function at the end of life, particularly in the face of severe impairment or ‘locked in syndrome’.

Subjects no more: what happens when trial participants realize they hold the power?

Patients will hold us all accountable in new and necessary ways

ALS untangled no. 20: The Deanna protocol

ISSN 2167-8421 print/ISSN 2167-9223 online

Modifiable barriers to enrollment in American ALS research studies.

Abstract Enrollment in ALS research studies is surprisingly low. Here we report on two online patient surveys that help identify some of the reasons. These include failure to invite patients to enroll, especially patients who have already participated in prior studies. Also included are patient concerns about the cost of participation, and confusion about several aspects of studies being offered. Along with prior work, these data suggest specific steps that can be taken to improve enrollment.