Late treatment initiation leads to reduced antiviral potency

A virologic marker, the number of HIV RNA copies or viral load, is currently used to evaluate anti-HIV therapies in AIDS clinical trials. This marker can be used to assess the antiviral potency of therapies, but is easily affected by noncompliance, drug resistance, toxicities, and other factors during the long-term treatment evaluation process. Recently it has been suggested to use viral dynamics to assess the potency of antiviral drugs and therapies, since viral decay rates in viral dynamic models have been shown to be related to the antiviral drug potency directly, and they need a shorter evaluation time. In this paper we first review the two statistical approaches for characterizing HIV dynamics and estimating viral decay rates: the individual nonlinear least squares regression (INLS) method and the population nonlinear mixed-effect model (PMEM) approach. To compare the viral decay rates between two treatment arms, parametric and nonparametric tests, based on the estimates of viral decay rates (the derived variables) from both the INLS and PMEM methods, are proposed and studied. We show, using the concept of exchangeability, that the test based on the empirical Bayes' estimates from the PMEM is valid, powerful and robust. This proposed method is very useful in most practical cases where the INLS-based tests and the general likelihood ratio test may not apply. We validate and compare various tests for finite samples using Monte Carlo simulations. Finally, we apply the proposed tests to an AIDS clinical trial to compare the antiviral potency between a 3-drug combination regimen and a 4-drug combination regimen. The proposed tests provide some significant evidence that the 4-drug regimen is more potent than the 3-drug regimen, while the naive methods fail to give a significant result.*To whom correspondence should be addressed.

Background: While facial neuromuscular retraining and chemodenervation are effective treatments for facial synkinesis, it is unclear if clinical outcomes are affected by the timing or sequence of treatment initiation. Objective: To compare outcomes between patients with facial synkinesis based on timing of treatment initiation with facial neuromuscular retraining and/or chemodenervation as measured by the Sunnybrook Facial Grading System. Methods: Retrospective review of patients with facial synkinesis. Patient data recorded include demographics, clinical information, and Sunnybrook scores. t-Tests, analysis of variance, and logistic regression were used for analysis. Results: A total of 78 adult patients were included in our study (73% female; median age 50 years with a range of 18-78 years). Median patient follow-up was 16 months (range of 1-56 months). Patients were divided into three groups based on time between paralysis onset and treatment initiation: <12 months, 12-36 months, and >36 months. The use of facial neuromuscular retraining and chemodenervation improved Sunnybrook scores for all patients. The time between paralysis onset to treatment initiation was not associated with a difference in Sunnybrook scores. Conclusion: The duration of facial palsy prior to initiation of facial neuromuscular retraining and/or chemodenervation was not associated with a difference in synkinesis outcomes as determined by Sunnybrook scores.

We describe the impact of early initiation of influenza antiviral treatment among pregnant women hospitalized with laboratory-confirmed influenza during the 2010-2014 influenza seasons. Severe influenza was defined as illness with ≥1 of the following: intensive care unit admission, need for mechanical ventilation, respiratory failure, pulmonary embolism, sepsis, or death. Within severity stratum, we used parametric survival analysis to compare length of stay by timing of antiviral treatment, adjusting for underlying conditions, influenza vaccination, and pregnancy trimester. Among 865 pregnant women, the median age was 27 years (interquartile range [IQR], 23-31 years). Most (68%) were healthy, and 85% received antiviral treatment. Sixty-three women (7%) had severe influenza, and 4 died. Severity was associated with preterm delivery and fetal loss. Women with severe influenza were less likely to be vaccinated than those without severe influenza (14% vs 26%; P = .03). Among women treated with antivirals ≤2 days versus those treated >2 days from illness onset, the median length of stay was 2.2 days (interquartile range [IQR], 0.9-5.8 days; n = 8) versus 7.8 days (IQR, 3.0-20.6 days; n = 7), respectively, for severe influenza (P = .03) and 2.4 days (IQR, 2.3-2.5 days; n = 153) versus 3.1 days (IQR, 2.8-3.5 days; n = 62), respectively, for nonsevere influenza (P < .01). Early initiation of influenza antiviral treatment to pregnant women hospitalized with influenza may reduce the length of stay, especially among those with severe influenza. Influenza during pregnancy is associated with maternal and infant morbidity, and annual influenza vaccination is warranted.

JSH Guidelines for the Management of Hepatitis C Virus Infection: A 2016 update for genotype 1 and 2.

Eigenvalue analysis is an important tool in economics and nonlinear physics to analyze industrial processes and instability phenomena, respectively. A model-based eigenvalue analysis of viral load data from eight symptomatic COVID-19 patients was conducted. The eigenvalues and eigenvectors of the instabilities were determined that give rise to COVID-19. For all eight patients, it was found that the virus dynamics followed the unstable eigenvectors until the viral load reached the respective peak values. At the peak virus values, the virus dynamics branched off from the directions specified by the eigenvectors. The temporal course of the unstable eigenvalues was determined as well. For all patients, it was found that the eigenvalues switched from positive to negative values just when the virus load reached peak values. These findings suggest that the fixed, instability-related eigenvalues and eigenvectors determine initial stages of SARS-CoV-2 infections during which virus load increases. In contrast, the time-dependent eigenvalues show a sign-switching phenomenon that indicates when the virus dynamics switches from the growth stage (increasing virus load) to the decay stage (decreasing virus load). The virus dynamics model was a standard three-variable virus dynamics model frequently used in the literature.

IL28B single nucleotide polymorphisms in the treatment of hepatitis C

BackgroundDevelopment of an effective antiviral drug for Coronavirus Disease 2019 (COVID-19) is a global health priority. Although several candidate drugs have been identified through in vitro and in vivo models, consistent and compelling evidence from clinical studies is limited. The lack of evidence from clinical trials may stem in part from the imperfect design of the trials. We investigated how clinical trials for antivirals need to be designed, especially focusing on the sample size in randomized controlled trials.Methods and findingsA modeling study was conducted to help understand the reasons behind inconsistent clinical trial findings and to design better clinical trials. We first analyzed longitudinal viral load data for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) without antiviral treatment by use of a within-host virus dynamics model. The fitted viral load was categorized into 3 different groups by a clustering approach. Comparison of the estimated parameters showed that the 3 distinct groups were characterized by different virus decay rates (p-value < 0.001). The mean decay rates were 1.17 d−1 (95% CI: 1.06 to 1.27 d−1), 0.777 d−1 (0.716 to 0.838 d−1), and 0.450 d−1 (0.378 to 0.522 d−1) for the 3 groups, respectively. Such heterogeneity in virus dynamics could be a confounding variable if it is associated with treatment allocation in compassionate use programs (i.e., observational studies).Subsequently, we mimicked randomized controlled trials of antivirals by simulation. An antiviral effect causing a 95% to 99% reduction in viral replication was added to the model. To be realistic, we assumed that randomization and treatment are initiated with some time lag after symptom onset. Using the duration of virus shedding as an outcome, the sample size to detect a statistically significant mean difference between the treatment and placebo groups (1:1 allocation) was 13,603 and 11,670 (when the antiviral effect was 95% and 99%, respectively) per group if all patients are enrolled regardless of timing of randomization. The sample size was reduced to 584 and 458 (when the antiviral effect was 95% and 99%, respectively) if only patients who are treated within 1 day of symptom onset are enrolled. We confirmed the sample size was similarly reduced when using cumulative viral load in log scale as an outcome.We used a conventional virus dynamics model, which may not fully reflect the detailed mechanisms of viral dynamics of SARS-CoV-2. The model needs to be calibrated in terms of both parameter settings and model structure, which would yield more reliable sample size calculation.ConclusionsIn this study, we found that estimated association in observational studies can be biased due to large heterogeneity in viral dynamics among infected individuals, and statistically significant effect in randomized controlled trials may be difficult to be detected due to small sample size. The sample size can be dramatically reduced by recruiting patients immediately after developing symptoms. We believe this is the first study investigated the study design of clinical trials for antiviral treatment using the viral dynamics model.

Background:Adolescents with newly diagnosed depression may not receive timely antidepressant therapy. Clinical and economic effects of early versus late treatment initiation are unclear.Objective:To compare effects of early versus late initiation of second-generation (SSRI/SNRI) antidepressants on emergency room (ER) visits, hospitalizations and healthcare costs in adolescents with depression.Methods:Patients aged 12–17 with a diagnosis of depression were identified in a claims database (1999–2007). Patients initiating antidepressants within 1 month of initial diagnosis were considered early initiators; patients initiating within 2–12 months were late initiators. Clinical resource use and healthcare costs were measured during the 6-month pre-index and 12-month post-index (study) periods and compared descriptively between groups. Logistic regression compared healthcare services utilization; a generalized linear model compared costs. All models were adjusted for baseline characteristics, including demographics, comorbidities, and healthcare services utilization.Results:A total of 7344 adolescents met study criteria. 4415 (60%) initiated antidepressant treatment within 1 month of diagnosis. At baseline, early initiators had more all-cause inpatient visits (14 vs. 7%) and all-cause ER visits than late initiators (25 vs. 21%, both p < 0.01). They had higher medical ($1434 vs. $1160) and total costs ($1565 vs. $1290) (both p < 0.01). In the study period, late initiators had higher risk of ER visits (OR = 1.13, p = 0.03). They incurred higher medical costs ($5415 vs. $4061) and higher total healthcare costs ($6001 vs. $4907), but lower adjusted drug costs ($767 vs. $888) (all p < 0.01).Limitations:Clinical data are scarce in the claims database, and the ability to observe disease severity and reasons for delayed treatment is limited. The definition of early and late initiation was based on empirical analysis, and no clear cutoff was identified beyond what was observed in the data.Conclusions:Adolescents who initiated SSRI/SNRI therapy earlier experienced lower risk of ER visits and had lower total costs compared to late initiators.

BackgroundHIV treatment and care services were scaled up in 2007 in India with objective to increase HIV-care coverage. CD4 count based criteria was mainly used for treatment initiation with increasing threshold in later years. Therefore, this paper aimed to evaluate the survival by varying CD4 criteria for antiretroviral treatment (ART) initiation among of HIV-positive patients, and independent factors associated with the mortality.MethodsThis retrospective cohort study included 127 949 HIV-positive patients aged ≥15 years, who initiated ART between 2007 and 2013 in Andhra Pradesh state, India. The patient’s demographic and clinical characteristics were extracted from the patient’s health records from electronic Computerized Management Information System Software (CMIS). Incidence of mortality/100 person-years was calculated for CD4 and treatment initiation categories. Kaplan-Meier and multivariable Cox-regression analyses were used to explore the association.ResultsMedian CD4 count was 172 (inter-quartile range (IQR) = 102-240) at the time of treatment initiation, and 19.3% of them had ≤ 100 CD4 count. Incidence of mortality for the period 2007-08 (CD4 ≤ 200 cells/mm3) was 8.5/100 person-years compared to 6.4/100 person-years at risk for the period 2012 onwards (CD4 ≤ 350 cells/mm3). Earlier thresholds for treatment initiation showed higher risk of mortality (2007-08 (CD4 ≤ 200 cells/mm3), adjusted hazard ratio (HR): 1.86, 95% confidence interval (CI): 1.68-2.07; 2009-11 (CD4 ≤ 250 cells/mm3), HR = 1.67, 95% CI = 1.51-1.85) compared to 2012 onwards (CD4 ≤ 350 cells/mm3) criteria for treatment initiation.ConclusionsIncreasing CD4 threshold for treatment initiation over time was independently associated with lower risk of mortality. More efforts are required to detect and treat early, monitoring of follow-ups, promote health education to improve ART adherence, and provide supportive environment that encourages HIV-infected patients to disclose their HIV status in confidence.

Safety and Efficacy of CMX001 as Salvage Therapy for Severe Adenovirus Infections in Immunocompromised Patients

Better design leads to better results - Importance of virological outcome design in clinical trials for antiviral treatment of coronavirus disease 2019.

To investigate whether the relation between estrogen-progestagen menopausal hormone therapy (EP-MHT) and breast cancer risk varies according to the delay between menopause onset and treatment initiation. Between 1992 and 2005, 1,726 invasive breast cancers were identified among 53,310 postmenopausal women from the French E3N cohort (mean duration of follow-up, 8.1 years). Hazard ratios (HRs) and CIs were estimated using Cox models, with MHT never users as the reference. Among recent users of EP-MHT, the risk of breast cancer varied according to the timing of treatment initiation. This variation was confined to short durations of use (< or = 2 years): the HR was 1.54 (95% CI, 1.28 to 1.86) for short treatments initiated in the 3-year period following menopause onset and 1.00 (95% CI, 0.68 to 1.47) for short treatments initiated later (P = .04 for homogeneity). However, this pattern of risks was not observed in users of EP-MHT containing progesterone, among whom there was no significantly increased risk associated with short duration of use (HR was 0.87 [95% CI, 0.57 to 1.32] for treatments initiated < or = 3 years after menopause, and HR was 0.90 [95% CI, 0.45 to 1.81] for treatments initiated later). Longer durations of EP-MHT use were generally associated with increases in breast cancer risk, whatever the gap time. Our results suggest that, for some EP-MHT, the timing of treatment initiation transiently modulates the risk of breast cancer and that, when initiated close to menopause, even short durations of use are associated with an increased breast cancer risk. Estrogen + progesterone combinations might be an exception in this regard.

Isoniazid and rifampicin heteroresistant Mycobacterium tuberculosis isolated from tuberculous meningitis patients in India

The scientific community is focused on developing antiviral therapies to mitigate the impacts of the ongoing novel coronavirus disease 2019 (COVID-19) outbreak. This will be facilitated by improved understanding of viral dynamics within infected hosts. Here, using a mathematical model in combination with published viral load data, we compare within-host viral dynamics of SARS-CoV-2 with analogous dynamics of MERS-CoV and SARS-CoV. Our quantitative analyses using a mathematical model revealed that the within-host reproduction number at symptom onset of SARS-CoV-2 was statistically significantly larger than that of MERS-CoV and similar to that of SARS-CoV. In addition, the time from symptom onset to the viral load peak for SARS-CoV-2 infection was shorter than those of MERS-CoV and SARS-CoV. These findings suggest the difficulty of controlling SARS-CoV-2 infection by antivirals. We further used the viral dynamics model to predict the efficacy of potential antiviral drugs that have different modes of action. The efficacy was measured by the reduction in the viral load area under the curve (AUC). Our results indicate that therapies that block de novo infection or virus production are likely to be effective if and only if initiated before the viral load peak (which appears 2–3 days after symptom onset), but therapies that promote cytotoxicity of infected cells are likely to have effects with less sensitivity to the timing of treatment initiation. Furthermore, combining a therapy that promotes cytotoxicity and one that blocks de novo infection or virus production synergistically reduces the AUC with early treatment. Our unique modeling approach provides insights into the pathogenesis of SARS-CoV-2 and may be useful for development of antiviral therapies.

Rethinking hepatitis C viral kinetics: Insights into host-virus interactions in ‘difficult-to-treat’ groups and implications for novel treatment approaches