Accelerated clinical discovery using self-reported patient data collected online and a patient-matching algorithm
TL;DR: Analysis of data reported on the website PatientsLikeMe by patients with amyotrophic lateral sclerosis who experimented with lithium carbonate treatment found no effect of lithium on disease progression, 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.
Abstract: 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.
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TL;DR: Approaches used for drug repurposing (also known as drug repositioning) are presented, the challenges faced by the repurpose community are discussed, and innovative ways by which these challenges could be addressed are recommended to help realize the full potential of drugRepurposing.
Abstract: Given the high attrition rates, substantial costs and slow pace of new drug discovery and development, repurposing of 'old' drugs to treat both common and rare diseases is increasingly becoming an attractive proposition because it involves the use of de-risked compounds, with potentially lower overall development costs and shorter development timelines. Various data-driven and experimental approaches have been suggested for the identification of repurposable drug candidates; however, there are also major technological and regulatory challenges that need to be addressed. In this Review, we present approaches used for drug repurposing (also known as drug repositioning), discuss the challenges faced by the repurposing community and recommend innovative ways by which these challenges could be addressed to help realize the full potential of drug repurposing.
2,365 citations
TL;DR: The potential for furthering medical research and clinical care using EHR data and the challenges that must be overcome before this is a reality are considered.
Abstract: The adoption of electronic health records will provide a rich resource for biomedical researchers. This Review discusses the potential for their use in informed decision making in the clinic, for a finer understanding of genotype–phenotype relationships and for selection of research cohorts, along with the current challenges for their mining and use. Clinical data describing the phenotypes and treatment of patients represents an underused data source that has much greater research potential than is currently realized. Mining of electronic health records (EHRs) has the potential for establishing new patient-stratification principles and for revealing unknown disease correlations. Integrating EHR data with genetic data will also give a finer understanding of genotype–phenotype relationships. However, a broad range of ethical, legal and technical reasons currently hinder the systematic deposition of these data in EHRs and their mining. Here, we consider the potential for furthering medical research and clinical care using EHR data and the challenges that must be overcome before this is a reality.
1,376 citations
Book•
05 Jun 2013
TL;DR: The knowledge and tools exist to put the health system on the right course to achieve continuous improvement and better quality care at a lower cost, and a better use of data is a critical element of a continuously improving health system.
Abstract: America's health care system has become too complex and costly to continue business as usual. Best Care at Lower Cost explains that inefficiencies, an overwhelming amount of data, and other economic and quality barriers hinder progress in improving health and threaten the nation's economic stability and global competitiveness. According to this report, the knowledge and tools exist to put the health system on the right course to achieve continuous improvement and better quality care at a lower cost.The costs of the system's current inefficiency underscore the urgent need for a systemwide transformation. About 30 percent of health spending in 2009--roughly $750 billion--was wasted on unnecessary services, excessive administrative costs, fraud, and other problems. Moreover, inefficiencies cause needless suffering. By one estimate, roughly 75,000 deaths might have been averted in 2005 if every state had delivered care at the quality level of the best performing state. This report states that the way health care providers currently train, practice, and learn new information cannot keep pace with the flood of research discoveries and technological advances.About 75 million Americans have more than one chronic condition, requiring coordination among multiple specialists and therapies, which can increase the potential for miscommunication, misdiagnosis, potentially conflicting interventions, and dangerous drug interactions. Best Care at Lower Cost emphasizes that a better use of data is a critical element of a continuously improving health system, such as mobile technologies and electronic health records that offer significant potential to capture and share health data better. In order for this to occur, the National Coordinator for Health Information Technology, IT developers, and standard-setting organizations should ensure that these systems are robust and interoperable. Clinicians and care organizations should fully adopt these technologies, and patients should be encouraged to use tools, such as personal health information portals, to actively engage in their care.This book is a call to action that will guide health care providers; administrators; caregivers; policy makers; health professionals; federal, state, and local government agencies; private and public health organizations; and educational institutions.
1,324 citations
Cites methods from "Accelerated clinical discovery usin..."
...This research method, even with its drawbacks, has several advantages, including speed of data collection, low cost, patient engagement, the availability of control participants, and ease of patient access (Wicks et al., 2011)....
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TL;DR: A machine learning-based approach to extract mentions of adverse drug reactions (ADRs) from highly informal text in social media, suitable for social media mining, as it relies on large volumes of unlabeled data, thus diminishing the need for large, annotated training data sets.
495 citations
TL;DR: Overall, SNS interventions appeared to be effective in promoting changes in health-related behaviors, and further research regarding the application of these promising tools is warranted.
487 citations
Cites background from "Accelerated clinical discovery usin..."
...At the individual level, they are able to facilitate access to health-related information and social support,(7,17) promoting better-informed treatment decisions.(18,19) Given that lifestyle behaviors are...
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References
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TL;DR: A revised version of the ALSFRS, which incorporates additional assessments of dyspnea, orthopnea, and the need for ventilatory support is validated, indicating that the quality of function is a strong determinant of quality of life in ALS.
2,440 citations
TL;DR: In this article, the authors developed an efficient and effective implementation of the Newton-Raphson (NR) algorithm for estimating the parameters in mixed-effects models for repeated-measures data.
Abstract: We develop an efficient and effective implementation of the Newton—Raphson (NR) algorithm for estimating the parameters in mixed-effects models for repeated-measures data. We formulate the derivatives for both maximum likelihood and restricted maximum likelihood estimation and propose improvements to the algorithm discussed by Jennrich and Schluchter (1986) to speed convergence and ensure a positive-definite covariance matrix for the random effects at each iteration. We use matrix decompositions to develop efficient and computationally stable implementations of both the NR algorithm and an EM algorithm (Laird and Ware 1982) for this model. We compare the two methods (EM vs. NR) in terms of computational order and performance on two sample data sets and conclude that in most situations a well-implemented NR algorithm is preferable to the EM algorithm or EM algorithm with Aitken's acceleration. The term repeated measures refers to experimental designs where there are several individuals and several...
900 citations
"Accelerated clinical discovery usin..." refers methods in this paper
...One alternative method of analysis is to use a linear mixed-effects model to test whether the slope of the ALSFRS was different in the two group...
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Columbia University1, California Pacific Medical Center2, Washington University in St. Louis3, Mayo Clinic4, University of California, San Francisco5, University of Colorado Hospital6, University of California, Irvine7, University of Medicine and Dentistry of New Jersey8, Virginia Mason Medical Center9, Duke University10, University of California, Los Angeles11, University of Pennsylvania12, University of Kansas13, University of Vermont14
TL;DR: The finding that minocycline has a harmful effect on patients with ALS has implications for trials of minocyCline in patients with other neurological disorders, and for how potential neuroprotective agents are screened for use in Patients with ALS.
Abstract: Summary Background Minocycline has anti-apoptotic and anti-inflammatory effects in vitro, and extends survival in mouse models of some neurological conditions. Several trials are planned or are in progress to assess whether minocycline slows human neurodegeneration. We aimed to test the efficacy of minocycline as a treatment for amyotrophic lateral sclerosis (ALS). Methods We did a multicentre, randomised placebo-controlled phase III trial. After a 4-month lead-in phase, 412 patients were randomly assigned to receive placebo or minocycline in escalating doses of up to 400 mg/day for 9 months. The primary outcome measure was the difference in rate of change in the revised ALS functional rating scale (ALSFRS-R). Secondary outcome measures were forced vital capacity (FVC), manual muscle testing (MMT), quality of life, survival, and safety. Analysis was by intention to treat. This trial is registered with ClinicalTrials.gov, number NCT00047723. Findings ALSFRS-R score deterioration was faster in the minocycline group than in the placebo group (−1·30 vs −1·04 units/month, 95% CI for difference −0·44 to −0·08; p=0·005). Patients on minocycline also had non-significant tendencies towards faster decline in FVC (−3·48 vs −3·01, −1·03 to 0·11; p=0·11) and MMT score (−0·30 vs −0·26, −0·08 to 0·01; p=0·11), and greater mortality during the 9-month treatment phase (hazard ratio=1·32, 95% CI 0·83 to 2·10; p=0·23) than did patients on placebo. Quality-of-life scores did not differ between the treatment groups. Non-serious gastrointestinal and neurological adverse events were more common in the minocycline group than in the placebo group, but these events were not significantly related to the decline in ALSFRS-R score. Interpretation Our finding that minocycline has a harmful effect on patients with ALS has implications for trials of minocycline in patients with other neurological disorders, and for how potential neuroprotective agents are screened for use in patients with ALS.
610 citations
"Accelerated clinical discovery usin..." refers background in this paper
...However, minocycline was subsequently found to accelerate disease progression when tested in a multicenter randomized placebo-controlled phase 3 tria...
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TL;DR: It is established that members of the PatientsLikeMe community reported a range of benefits, and that these may be related to the extent of site use, and third party validation and longitudinal evaluation is an important next step in continuing to evaluate the potential of online data-sharing platforms.
Abstract: 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. [J Med Internet Res 2010;12(2):e19]
577 citations
"Accelerated clinical discovery usin..." refers methods in this paper
...Results Participants As of the date that our data set was finalized (28 February 2010), there were 4,318 ALS patients on PatientsLikeMe, all of whom were invited to report their FRS scores, symptoms, treatments (with start and stop dates), site of ALS onset and demographic data using online tools provided on the PatientsLikeMe websit...
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TL;DR: It is found that daily doses of lithium, leading to plasma levels ranging from 0.4 to 0.8 mEq/liter, delay disease progression in human patients affected by ALS, and a marked neuroprotection by lithium is found, which delayed disease onset and duration and augmented the life span.
Abstract: ALS is a devastating neurodegenerative disorder with no effective treatment. In the present study, we found that daily doses of lithium, leading to plasma levels ranging from 0.4 to 0.8 mEq/liter, delay disease progression in human patients affected by ALS. None of the patients treated with lithium died during the 15 months of the follow-up, and disease progression was markedly attenuated when compared with age-, disease duration-, and sex-matched control patients treated with riluzole for the same amount of time. In a parallel study on a genetic ALS animal model, the G93A mouse, we found a marked neuroprotection by lithium, which delayed disease onset and duration and augmented the life span. These effects were concomitant with activation of autophagy and an increase in the number of the mitochondria in motor neurons and suppressed reactive astrogliosis. Again, lithium reduced the slow necrosis characterized by mitochondrial vacuolization and increased the number of neurons counted in lamina VII that were severely affected in saline-treated G93A mice. After lithium administration in G93A mice, the number of these neurons was higher even when compared with saline-treated WT. All these mechanisms may contribute to the effects of lithium, and these results offer a promising perspective for the treatment of human patients affected by ALS.
541 citations
"Accelerated clinical discovery usin..." refers background in this paper
...In 2008, a study described the potential efficacy of lithium carbonate to slow the progression of ALS in a small, single-blind trial of 16 treated patients and 28 control...
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