Implementation of a Prospective Index-Cluster Sampling Strategy for the Detection of Presymptomatic Viral Respiratory Infection in Undergraduate Students.

Background: Index-cluster studies may help characterize the spread of communicable infections in the presymptomatic state. We describe a prospective index-cluster sampling strategy (ICSS) to detect presymptomatic respiratory viral illness and its implementation in a college population. Methods: We enrolled an annual cohort of first-year undergraduates who completed daily electronic symptom diaries to identify index cases (ICs) with respiratory illness. Investigators then selected 5-10 potentially exposed, asymptomatic close contacts (CCs) who were geographically co-located to follow for infections. Symptoms and nasopharyngeal samples were collected for 5 days. Logistic regression model-based predictions for proportions of self-reported illness were compared graphically for the whole cohort sampling group and the CC group. Results: We enrolled 1379 participants between 2009 and 2015, including 288 ICs and 882 CCs. The median number of CCs per IC was 6 (interquartile range, 3-8). Among the 882 CCs, 111 (13%) developed acute respiratory illnesses. Viral etiology testing in 246 ICs (85%) and 719 CCs (82%) identified a pathogen in 57% of ICs and 15% of CCs. Among those with detectable virus, rhinovirus was the most common (IC: 18%; CC: 6%) followed by coxsackievirus/echovirus (IC: 11%; CC: 4%). Among 106 CCs with a detected virus, only 18% had the same virus as their associated IC. Graphically, CCs did not have a higher frequency of self-reported illness relative to the whole cohort sampling group. Conclusions: Establishing clusters by geographic proximity did not enrich for cases of viral transmission, suggesting that ICSS may be a less effective strategy to detect spread of respiratory infection.

A blood-based host gene expression assay for early detection of respiratory viral infection: an index-cluster prospective cohort study.

BACKGROUND: Early and accurate identification of individuals with viral infections is crucial for clinical management and public health interventions. We aimed to assess the ability of transcriptomic biomarkers to identify naturally acquired respiratory viral infection before typical symptoms are present. METHODS: In this index-cluster study, we prospectively recruited a cohort of undergraduate students (aged 18-25 years) at Duke University (Durham, NC, USA) over a period of 5 academic years. To identify index cases, we monitored students for the entire academic year, for the presence and severity of eight symptoms of respiratory tract infection using a daily web-based survey, with symptoms rated on a scale of 0-4. Index cases were defined as individuals who reported a 6-point increase in cumulative daily symptom score. Suspected index cases were visited by study staff to confirm the presence of reported symptoms of illness and to collect biospecimen samples. We then identified clusters of close contacts of index cases (ie, individuals who lived in close proximity to index cases, close friends, and partners) who were presumed to be at increased risk of developing symptomatic respiratory tract infection while under observation. We monitored each close contact for 5 days for symptoms and viral shedding and measured transcriptomic responses at each timepoint each day using a blood-based 36-gene RT-PCR assay. FINDINGS: Between Sept 1, 2009, and April 10, 2015, we enrolled 1465 participants. Of 264 index cases with respiratory tract infection symptoms, 150 (57%) had a viral cause confirmed by RT-PCR. Of their 555 close contacts, 106 (19%) developed symptomatic respiratory tract infection with a proven viral cause during the observation window, of whom 60 (57%) had the same virus as their associated index case. Nine viruses were detected in total. The transcriptomic assay accurately predicted viral infection at the time of maximum symptom severity (mean area under the receiver operating characteristic curve [AUROC] 0·94 [95% CI 0·92-0·96]), as well as at 1 day (0·87 [95% CI 0·84-0·90]), 2 days (0·85 [0·82-0·88]), and 3 days (0·74 [0·71-0·77]) before peak illness, when symptoms were minimal or absent and 22 (62%) of 35 individuals, 25 (69%) of 36 individuals, and 24 (82%) of 29 individuals, respectively, had no detectable viral shedding. INTERPRETATION: Transcriptional biomarkers accurately predict and diagnose infection across diverse viral causes and stages of disease and thus might prove useful for guiding the administration of early effective therapy, quarantine decisions, and other clinical and public health interventions in the setting of endemic and pandemic infectious diseases. FUNDING: US Defense Advanced Research Projects Agency.

Software for Administering the National Cancer Institute's Patient-Reported Outcomes Version of the Common Terminology Criteria for Adverse Events: Usability Study.

BACKGROUND: The US National Cancer Institute (NCI) developed software to gather symptomatic adverse events directly from patients participating in clinical trials. The software administers surveys to patients using items from the Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE) through Web-based or automated telephone interfaces and facilitates the management of survey administration and the resultant data by professionals (clinicians and research associates). OBJECTIVE: The purpose of this study was to iteratively evaluate and improve the usability of the PRO-CTCAE software. METHODS: Heuristic evaluation of the software functionality was followed by semiscripted, think-aloud protocols in two consecutive rounds of usability testing among patients with cancer, clinicians, and research associates at 3 cancer centers. We conducted testing with patients both in clinics and at home (remotely) for both Web-based and telephone interfaces. Furthermore, we refined the software between rounds and retested. RESULTS: Heuristic evaluation identified deviations from the best practices across 10 standardized categories, which informed initial software improvement. Subsequently, we conducted user-based testing among 169 patients and 47 professionals. Software modifications between rounds addressed identified issues, including difficulty using radio buttons, absence of survey progress indicators, and login problems (for patients) as well as scheduling of patient surveys (for professionals). The initial System Usability Scale (SUS) score for the patient Web-based interface was 86 and 82 (P=.22) before and after modifications, respectively, whereas the task completion score was 4.47, which improved to 4.58 (P=.39) after modifications. Following modifications for professional users, the SUS scores improved from 71 to 75 (P=.47), and the mean task performance improved significantly (4.40 vs 4.02; P=.001). CONCLUSIONS: Software modifications, informed by rigorous assessment, rendered a usable system, which is currently used in multiple NCI-sponsored multicenter cancer clinical trials. TRIAL REGISTRATION: ClinicalTrials.gov NCT01031641; https://clinicaltrials.gov/ct2/show/NCT01031641 (Archived by WebCite at http://www.webcitation.org/708hTjlTl).

A Genomic Signature of Influenza Infection Shows Potential for Presymptomatic Detection, Guiding Early Therapy, and Monitoring Clinical Responses.

Early, presymptomatic intervention with oseltamivir (corresponding to the onset of a published host-based genomic signature of influenza infection) resulted in decreased overall influenza symptoms (aggregate symptom scores of 23.5 vs 46.3), more rapid resolution of clinical disease (20 hours earlier), reduced viral shedding (total median tissue culture infectious dose [TCID50] 7.4 vs 9.7), and significantly reduced expression of several inflammatory cytokines (interferon-γ, tumor necrosis factor-α, interleukin-6, and others). The host genomic response to influenza infection is robust and may provide the means for early detection, more timely therapeutic interventions, a meaningful reduction in clinical disease, and an effective molecular means to track response to therapy.

Host gene expression classifiers diagnose acute respiratory illness etiology.

Acute respiratory infections caused by bacterial or viral pathogens are among the most common reasons for seeking medical care. Despite improvements in pathogen-based diagnostics, most patients receive inappropriate antibiotics. Host response biomarkers offer an alternative diagnostic approach to direct antimicrobial use. This observational cohort study determined whether host gene expression patterns discriminate noninfectious from infectious illness and bacterial from viral causes of acute respiratory infection in the acute care setting. Peripheral whole blood gene expression from 273 subjects with community-onset acute respiratory infection (ARI) or noninfectious illness, as well as 44 healthy controls, was measured using microarrays. Sparse logistic regression was used to develop classifiers for bacterial ARI (71 probes), viral ARI (33 probes), or a noninfectious cause of illness (26 probes). Overall accuracy was 87% (238 of 273 concordant with clinical adjudication), which was more accurate than procalcitonin (78%, P < 0.03) and three published classifiers of bacterial versus viral infection (78 to 83%). The classifiers developed here externally validated in five publicly available data sets (AUC, 0.90 to 0.99). A sixth publicly available data set included 25 patients with co-identification of bacterial and viral pathogens. Applying the ARI classifiers defined four distinct groups: a host response to bacterial ARI, viral ARI, coinfection, and neither a bacterial nor a viral response. These findings create an opportunity to develop and use host gene expression classifiers as diagnostic platforms to combat inappropriate antibiotic use and emerging antibiotic resistance.

Potential Cost-effectiveness of Early Identification of Hospital-acquired Infection in Critically Ill Patients.

RATIONALE: Limitations in methods for the rapid diagnosis of hospital-acquired infections often delay initiation of effective antimicrobial therapy. New diagnostic approaches offer potential clinical and cost-related improvements in the management of these infections. OBJECTIVES: We developed a decision modeling framework to assess the potential cost-effectiveness of a rapid biomarker assay to identify hospital-acquired infection in high-risk patients earlier than standard diagnostic testing. METHODS: The framework includes parameters representing rates of infection, rates of delayed appropriate therapy, and impact of delayed therapy on mortality, along with assumptions about diagnostic test characteristics and their impact on delayed therapy and length of stay. Parameter estimates were based on contemporary, published studies and supplemented with data from a four-site, observational, clinical study. Extensive sensitivity analyses were performed. The base-case analysis assumed 17.6% of ventilated patients and 11.2% of nonventilated patients develop hospital-acquired infection and that 28.7% of patients with hospital-acquired infection experience delays in appropriate antibiotic therapy with standard care. We assumed this percentage decreased by 50% (to 14.4%) among patients with true-positive results and increased by 50% (to 43.1%) among patients with false-negative results using a hypothetical biomarker assay. Cost of testing was set at $110/d. MEASUREMENTS AND MAIN RESULTS: In the base-case analysis, among ventilated patients, daily diagnostic testing starting on admission reduced inpatient mortality from 12.3 to 11.9% and increased mean costs by $1,640 per patient, resulting in an incremental cost-effectiveness ratio of $21,389 per life-year saved. Among nonventilated patients, inpatient mortality decreased from 7.3 to 7.1% and costs increased by $1,381 with diagnostic testing. The resulting incremental cost-effectiveness ratio was $42,325 per life-year saved. Threshold analyses revealed the probabilities of developing hospital-acquired infection in ventilated and nonventilated patients could be as low as 8.4 and 9.8%, respectively, to maintain incremental cost-effectiveness ratios less than $50,000 per life-year saved. CONCLUSIONS: Development and use of serial diagnostic testing that reduces the proportion of patients with delays in appropriate antibiotic therapy for hospital-acquired infections could reduce inpatient mortality. The model presented here offers a cost-effectiveness framework for future test development.

A novel diagnostic approach may reduce inappropriate antibiotic use for acute respiratory infections.

Respiratory infections can be due to a multitude of etiologies and are common throughout the world. Most are viral and self-limited, yet these infections are commonly treated with antibiotics thus contributing to the increase in resistance. Historically, infectious disease diagnostics have focused on identification of the microbial culprit at the site of infection but the specificity of host response as measured by the host transcriptome, now enables us to classify the etiology of infection agnostic to pathogen class. The ability to rapidly determine whether a similar set of symptoms is due to a virus, bacteria, or other agent from a common specimen (blood) will have far-reaching public health benefits, and further research is warranted to transfer this technology into the clinical setting.

Human T cell reconstitution in DiGeorge syndrome and HIV-1 infection.

The thymus is essential for proper development and maintenance of a broad T cell repertoire capable of recognizing a wide-range of foreign antigens. Recent advances in multicolor flow cytometry, non-invasive imaging techniques, and molecular assessments of thymic function have enabled a more comprehensive characterization of human thymic output in clinical settings than in the past. These techniques have been particularly valuable in monitoring human T cells after therapeutic thymic grafting for complete DiGeorge syndrome and during HIV-1 infection and AIDS. By defining the degree and mechanisms of T cell reconstitution in these settings, clinical investigators and primary caregivers have been able to better diagnose, treat and care for individuals with congenital or acquired immune deficiencies associated with loss of thymic function.

Association of Epstein-Barr virus with systemic lupus erythematosus: effect modification by race, age, and cytotoxic T lymphocyte-associated antigen 4 genotype.

OBJECTIVE: Epstein-Barr virus (EBV) is hypothesized to play a role in the development of systemic lupus erythematosus (SLE). Cytotoxic T lymphocyte-associated antigen 4 (CTLA-4) is important in regulating T cell-mediated immunity, encompassing the first line of response to viral infections, and genetic variation in CTLA-4 has been associated with SLE. This study examined the seroprevalence of EBV in a population-based study of SLE patients from the southeastern United States, and potential interactions with CTLA-4 polymorphisms were assessed. METHODS: Cases comprised 230 subjects recently diagnosed as having SLE (144 African American and 86 white) from university and community-based clinics, and controls comprised 276 age-, sex-, and state-matched subjects (72 African American and 204 white) recruited from driver's license registries. Antibodies to EBV capsid antigen were determined by enzyme-linked immunosorbent assay, with results expressed as positive or negative using the international standardized ratio (ISR) (a ratio of the sample absorbance to a known standard). CTLA-4 genotypes were identified by polymerase chain reaction-based methods. RESULTS: In African Americans, EBV-IgA seroprevalence was strongly associated with SLE (odds ratio [OR] 5.6, 95% confidence interval [95% CI] 3.0-10.6). In whites, the modest association of SLE with EBV-IgA (OR 1.6) was modified by age, in that the strongest association was observed in those older than age 50 years (OR 4.1, 95% CI 1.6-10.4). The seroprevalence of EBV-IgM and that of EBV-IgG were not associated with SLE. Higher EBV-IgG absorbance ratios were observed in SLE patients, with a significant dose response across units of the ISR in African Americans (P < 0.0001). Allelic variation in the CTLA-4 gene promoter (-1661A/G) significantly modified the association between SLE and EBV-IgA (P = 0.03), with a stronger association among those with the -1661AA genotype. CONCLUSION: These findings suggest that repeated or reactivated EBV infection, which results in increased EBV-IgA seroprevalence and higher IgG antibody titers, may be associated with SLE, and that the CTLA-4 genotype influences immune responsiveness to EBV in SLE patients. The observed patterns of effect modification by race, age, and CTLA-4 genotype should be examined in other studies and may help frame new hypotheses regarding the role of EBV in SLE etiology.

Ethnic differences in cytotoxic T lymphocyte associated antigen 4 genotype associations with systemic sclerosis.

OBJECTIVE: To determine the role of cytotoxic T lymphocyte associated antigen 4 (CTLA-4) genetic polymorphisms in susceptibility to systemic sclerosis (SSc, scleroderma). METHODS: The study population consisted of 293 African American and Caucasian patients with SSc and matched controls. Subjects were genotyped for allelic determinants at 4 polymorphic sites: 3 in the promoter region (positions -318, -1661, -1722) and one in the first exon (position +49) of the CTLA-4 gene, using polymerase chain reaction (PCR) restriction fragment length polymorphism (RFLP) methods. Genotype frequencies were compared using Pearson's chi-square or Fisher's exact test. RESULTS: In African American patients, the frequency of AG heterozygotes at position +49 was significantly higher than in controls (71% vs 36%, p = 0.003; OR = 4.37), while the frequency of AA homozygotes was significantly lower in patients than in controls (29% vs 61%, p = 0.007; OR = 0.26). The distribution of CTLA-4 alleles at other loci did not differ significantly between patients and controls. CTLA-4 genotypes were not associated with SSc in Caucasians. No differences in CTLA-4 genotype distributions were observed between patients with the limited and diffuse forms of the disease. CONCLUSION: Our data show that the exon 1 (+49) polymorphism of the CTLA-4 gene is associated with systemic sclerosis in African Americans.

CTLA-4 gene polymorphisms in systemic lupus erythematosus: a highly significant association with a determinant in the promoter region.

The cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4; CD 152) is a negative regulator of T-lymphocyte activation. Particular genotypes of the locus encoding the CTLA-4 glycoprotein have been associated with susceptibility to various autoimmune diseases. To determine their role in susceptibility to systemic lupus erythematosus (SLE), we genotyped 130 patients and 200 ethnically matched controls for allelic determinants at four polymorphic sites, viz., three in the promoter region at positions -1722 (T/C), -1661 (A/G), and -318 (C/T), and one within the first exon at position +49 (A/G), by restriction fragment length polymorphism methods. All genotype frequencies were in Hardy-Weinberg equilibrium. The genotypes at position -1722 were significantly associated with SLE. The frequency of T/T homozygotes was higher in patients than in controls (56% vs 33%, P=0.00003). Conversely, the frequencies of C/C homozygotes and C/T heterozygotes were higher in controls than in patients (15.5% vs 7%, P=0.019; 51.5% vs 37%, P=0.009). Genotypes at positions +49, -318, or -1661 were not significantly associated with SLE. These results show that allelic variation at the -1722 site influences susceptibility to SLE. This is the first report to our knowledge implicating CTLA-4 genotypes at the -1722 locus in susceptibility to any disease.