A Useful and Sustainable Role for N-of-1 Trials in the Healthcare Ecosystem.

Clinicians and patients often try a treatment for an initial period to inform longer-term therapeutic decisions. A more rigorous approach involves N-of-1 trials. In these single-patient crossover trials, typically conducted in patients with chronic conditions, individual patients are given candidate treatments in a double-blinded, random sequence of alternating periods to determine the most effective treatment for that patient. However, to date, these trials are rarely done outside of research settings and have not been integrated into general care where they could offer substantial benefit. Designating this classical, N-of-1 trial design as type 1, there also are new and evolving uses of N-of-1 trials that we designate as type 2. In these, rather than focusing on optimizing treatment for chronic diseases when multiple approved choices are available, as is typical of type 1, a type 2 N-of-1 trial tests treatments designed specifically for a patient with a rare disease, to facilitate personalized medicine. While the aims differ, both types face the challenge of collecting individual-patient evidence using standard, trusted, widely accepted methods. To fulfill their potential for producing both clinical and research benefits, and to be available for wide use, N-of-1 trials will have to fit into the current healthcare ecosystem. This will require generalizable and accepted processes, platforms, methods, and standards. This also will require sustainable value-based arrangements among key stakeholders. In this article, we review opportunities, stakeholders, issues, and possible approaches that could support general use of N-of-1 trials and deliver benefit to patients and the healthcare enterprise. To assess and expand the benefits of N-of-1 trials, we propose multistakeholder meetings, workshops, and the generation of methods, standards, and platforms that would support wider availability and the value of N-of-1 trials.

A concept-wide association study to identify potential risk factors for nonadherence among prevalent users of antihypertensives.

PURPOSE: We sought to determine whether an association study using information contained in clinical notes could identify known and potentially novel risk factors for nonadherence to antihypertensive medications. METHODS: We conducted a retrospective concept-wide association study (CWAS) using clinical notes to identify potential risk factors for medication nonadherence, adjusting for age, sex, race, baseline blood pressure, estimated glomerular filtration rate, and a combined comorbidity score. Participants included Medicare beneficiaries 65 years and older receiving care at the Harvard Vanguard Medical Associates network from 2010-2012 and enrolled in a Medicare Advantage program. Concepts were extracted from clinical notes in the year prior to the index prescription date for each patient. We tested associations with the outcome for 5013 concepts extracted from clinical notes in a derivation cohort (4382 patients) and accounted for multiple hypothesis testing by using a false discovery rate threshold of less than 5% (q < .05). We then confirmed the associations in a validation cohort (3836 patients). Medication nonadherence was defined using a proportion of days covered (PDC) threshold less than 0.8 using pharmacy claims data. RESULTS: We found 415 concepts associated with nonadherence, which we organized into 11 clusters using a hierarchical clustering approach. Volume depletion and overload, assessment of needs at the point of discharge, mood disorders, neurological disorders, complex coordination of care, and documentation of noncompliance were some of the factors associated with nonadherence. CONCLUSIONS: This approach was successful in identifying previously described and potentially new risk factors for antihypertensive nonadherence using the clinical narrative.

Efficacy and Effectiveness Too Trials: Clinical Trial Designs to Generate Evidence on Efficacy and on Effectiveness in Wide Practice.

Efficacy trials, designed to gain regulatory marketing approval, evaluate drugs in optimally selected patients under advantageous conditions for relatively short time periods. Effectiveness trials, designed to evaluate use in usual practice, assess treatments among more typical patients in real-world conditions with longer follow-up periods. In "efficacy-to-effectiveness (E2E) trials," if the initial efficacy trial component is positive, the trial seamlessly transitions to an effectiveness trial component to efficiently yield both types of evidence. Yet more time could be saved by simultaneously addressing efficacy and effectiveness in an "efficacy and effectiveness too (EE2) trial." Additionally, hybrids of the E2E and EE2 approaches with differing degrees of overlap of the two components could allow flexibility for specific drug development needs. In planning EE2 trials, each stakeholder's current and future needs, incentives, and perspective must be considered. Although challenging, the ultimate benefits to stakeholders, the health system, and the public should justify this effort.

Author Correction: Checkpoint blockade immunotherapy reshapes the high-dimensional phenotypic heterogeneity of murine intratumoural neoantigen-specific CD8+ T cells.

The original version of this Article omitted a declaration from the competing interests statement, which should have included the following: 'R.D.S. is a cofounder, stock holder, and scientific advisory board member of Jounce Therapeutics and Neon Therapeutics, and a member of the scientific advisory boards of BioLegend, Constellation, Lytix, and NGM. He also received research funding from Janssen and Agios.'. This has now been corrected in both the PDF and HTML versions of the Article.

The relative benefits of claims and electronic health record data for predicting medication adherence trajectory.

BACKGROUND: Healthcare providers are increasingly encouraged to improve their patients' adherence to chronic disease medications. Prediction of adherence can identify patients in need of intervention, but most prediction efforts have focused on claims data, which may be unavailable to providers. Electronic health records (EHR) are readily available and may provide richer information with which to predict adherence than is currently available through claims. METHODS: In a linked database of complete Medicare Advantage claims and comprehensive EHR from a multi-specialty outpatient practice, we identified patients who filled a prescription for a statin, antihypertensive, or oral antidiabetic during 2011 to 2012. We followed patients to identify subsequent medication filling patterns and used group-based trajectory models to assign patients to adherence trajectories. We then identified potential predictors from both claims and EHR data and fit a series of models to evaluate the accuracy of each data source in predicting medication adherence. RESULTS: Claims were highly predictive of patients in the worst adherence trajectory (C=0.78), but EHR data also provided good predictions (C=0.72). Among claims predictors, presence of a prior gap in filling of at least 6 days was by far the most influential predictor. In contrast, good predictions from EHR data required complex models with many variables. CONCLUSION: EHR data can provide good predictions of adherence trajectory and therefore may be useful for providers seeking to deploy resource-intensive interventions. However, prior adherence information derived from claims is most predictive, and can supplement EHR data when it is available.

Multiplex peptide-MHC tetramer staining using mass cytometry for deep analysis of the influenza-specific T-cell response in mice.

Antigen-specific T cells play a crucial role for the host protective immunity against viruses and other diseases. The use of mass cytometry together with a combinatorial multiplex tetramer staining has successfully been applied for probing and characterization of multiple antigen-specific CD8+ T cells in human blood samples. The present study shows that this approach can also be used to rapidly assess the magnitude of influenza-specific CD8+ T cell epitope dominance across lymph nodes and lungs in a murine model of a highly pathological influenza infection. Moreover, we show feasibility of extending this approach to include concurrent identification of virus-specific CD4+ T cells. By using a double coding approach, we probed for five influenza-specific MHCI-peptide complexes as well as one influenza-specific MHCII-peptide complex in the presence of irrelevant control peptides and show that this approach is capable of tracking antigen-specific T cells across individual lymph nodes and lungs. The simultaneous staining with 26 surface maker molecules further facilitated an in-depth characterization of T cells reacting with influenza epitopes and revealed tissue specific phenotypic differences between CD4+ T cells targeting the same pathogenic epitope. In conclusion, this approach provides the possibility for a rapid and comprehensive analysis of antigen-specific CD8+ and CD4+ T cells in different disease settings that might be advantageous for subsequent vaccine formulation strategies.

Checkpoint blockade immunotherapy reshapes the high-dimensional phenotypic heterogeneity of murine intratumoural neoantigen-specific CD8+ T cells.

The analysis of neoantigen-specific CD8+ T cells in tumour-bearing individuals is challenging due to the small pool of tumour antigen-specific T cells. Here we show that mass cytometry with multiplex combinatorial tetramer staining can identify and characterize neoantigen-specific CD8+ T cells in mice bearing T3 methylcholanthrene-induced sarcomas that are susceptible to checkpoint blockade immunotherapy. Among 81 candidate antigens tested, we identify T cells restricted to two known neoantigens simultaneously in tumours, spleens and lymph nodes in tumour-bearing mice. High-dimensional phenotypic profiling reveals that antigen-specific, tumour-infiltrating T cells are highly heterogeneous. We further show that neoantigen-specific T cells display a different phenotypic profile in mice treated with anti-CTLA-4 or anti-PD-1 immunotherapy, whereas their peripheral counterparts are not affected by the treatments. Our results provide insights into the nature of neoantigen-specific T cells and the effects of checkpoint blockade immunotherapy.Immune checkpoint blockade (ICB) therapies can unleash anti-tumour T-cell responses. Here the authors show, by integrating MHC tetramer multiplexing, mass cytometry and high-dimensional analyses, that neoantigen-specific, tumour-infiltrating T cells are highly heterogeneous and are subjected to ICB modulations.

Deep Profiling Human T Cell Heterogeneity by Mass Cytometry.

Advances of mass cytometry and high-dimensional single-cell data analysis have brought cellular immunological research into a new generation. By coupling these two powerful technology platforms, immunologists now have more tools to resolve the tremendous diversity of immune cell subsets, and their heterogeneous functionality. Since the first introduction of mass cytometry, many reports have been published using this novel technology to study a range of cell types. At the outset, studies of human hematopoietic stem cell and peripheral CD8(+) T cells using mass cytometry have shad the light of future experimental approach in interrogating immune cell phenotypic and functional diversity. Here, we briefly revisit the past and present understanding of T cell heterogeneity, and the technologies that facilitate this knowledge. In addition, we review the current progress of mass cytometry and high-dimensional cytometric analysis, including the methodology, panel design, experimental procedure, and choice of computational algorithms with a special focus on their utility in exploration of human T cell immunology.

High-dimensional immune profiling of total and rotavirus VP6-specific intestinal and circulating B cells by mass cytometry.

In-depth phenotyping of human intestinal antibody secreting cells (ASCs) and their precursors is important for developing improved mucosal vaccines. We used single-cell mass cytometry to simultaneously analyze 34 differentiation and trafficking markers on intestinal and circulating B cells. In addition, we labeled rotavirus (RV) double-layered particles with a metal isotope and characterized B cells specific to the RV VP6 major structural protein. We describe the heterogeneity of the intestinal B-cell compartment, dominated by ASCs with some phenotypic and transcriptional characteristics of long-lived plasma cells. Using principal component analysis, we visualized the phenotypic relationships between major B-cell subsets in the intestine and blood, and revealed that IgM(+) memory B cells (MBCs) and naive B cells were phenotypically related as were CD27(-) MBCs and switched MBCs. ASCs in the intestine and blood were highly clonally related, but associated with distinct trajectories of phenotypic development. VP6-specific B cells were present among diverse B-cell subsets in immune donors, including naive B cells, with phenotypes representative of the overall B-cell pool. These data provide a high dimensional view of intestinal B cells and the determinants regulating humoral memory to a ubiquitous, mucosal pathogen at steady-state.

CD161(int)CD8+ T cells: a novel population of highly functional, memory CD8+ T cells enriched within the gut.

The C-type lectin-like receptor CD161 is expressed by lymphocytes found in human gut and liver, as well as blood, especially natural killer (NK) cells, T helper 17 (Th17) cells, and a population of unconventional T cells known as mucosal-associated invariant T (MAIT) cells. The association of high CD161 expression with innate T-cell populations including MAIT cells is established. Here we show that CD161 is also expressed, at intermediate levels, on a prominent subset of polyclonal CD8+ T cells, including antiviral populations that display a memory phenotype. These memory CD161(int)CD8+ T cells are enriched within the colon and express both CD103 and CD69, markers associated with tissue residence. Furthermore, this population was characterized by enhanced polyfunctionality, increased levels of cytotoxic mediators, and high expression of the transcription factors T-bet and eomesodermin (EOMES). Such populations were induced by novel vaccine strategies based on adenoviral vectors, currently in trial against hepatitis C virus. Thus, intermediate CD161 expression marks potent polyclonal, polyfunctional tissue-homing CD8+ T-cell populations in humans. As induction of such responses represents a major aim of T-cell prophylactic and therapeutic vaccines in viral disease and cancer, analysis of these populations could be of value in the future.

Scanning laser Doppler imaging may predict disease progression of localized scleroderma in children and young adults.

BACKGROUND: Localized scleroderma is a rare but potentially disfiguring and disabling condition. Systemic treatment should be started early in those with active disease in key functional and cosmetic sites, but disease activity is difficult to determine clinically. Superficial blood flow has been shown to correlate with disease activity in localized scleroderma. OBJECTIVES: To examine whether superficial blood flow measured by laser Doppler imaging (LDI) has the potential to predict disease progression and therefore select patients for early systemic treatment. METHODS: A group of 20 individuals had clinical assessment and scanning LDI blood-flow measurements of 32 affected body sites. After a mean follow-up of 8.7 months their clinical outcome was compared with the results of the initial LDI assessment. RESULTS: Eleven out of 15 patients with an assessment of active LDI had progressed clinically, and 16 out of the 17 scans with inactive LDI assessment had not progressed, giving a positive predictive value of 73% and a negative predictive value of 94%. CONCLUSIONS: We believe that LDI can be a useful tool in predicting disease progression in localized scleroderma, and it may help clinicians to decide which patients to treat early.