MOSAIC: A cohort study of human mpox virus disease.

Background: Human mpox is a viral disease caused by an Orthopoxvirus, human mpox virus (hMPXV), typically causing fever and a rash. Mpox has historically been endemic to parts of Central and West Africa, with small numbers of imported cases reported elsewhere, but starting May 2022 an unprecedented global outbreak caused by clade IIb hMPXV was reported outside traditionally endemic countries. This prompted the initiation of MOSAIC, a cohort study implemented in Europe and Asia that aims to describe clinical and virologic outcomes of PCR-confirmed hMPXV disease, including those who receive antiviral therapy. The focus of this article, however, is on describing the study protocol itself with implementation process and operational challenges. Methods: MOSAIC recruits participants of any age with laboratory-confirmed mpox disease who provide informed consent. Participants enrol in the cohort for a total of six months. Blood, lesion and throat samples are collected at several timepoints from the day of diagnosis or the first day of treatment (Day 1) until Day 28 for PCR detection of hMPXV. Clinical data are collected by clinicians and participants (via a self-completion questionnaire) for six months to characterize the signs and symptoms associated with the illness, as well as short- and more long-term outcomes. Discussion: The design and prompt implementation of clinical research response is key in addressing emerging outbreaks. MOSAIC began enrolment within two months of the start of the international mpox epidemic. Enrolment has been stopped and the last follow-up visits are expected in January 2024. ICTRP registration: EU CT number: 2022-501132-42-00 (22/06/2022).

PupillOmetry for preDIction of DeliriUM in ICU (PODIUM): protocol for a prospective multicentre cohort study.

INTRODUCTION: Delirium is a severe complication that is associated with short-term adverse events, prolonged hospital stay and neurological sequelae in survivors. Automated pupillometry is an easy-to-use device that allows for accurate objective assessment of the pupillary light responses in comatose patients in the intensive care unit (ICU). Whether automated pupillometry might predict delirium in critically ill patients is not known. We hypothesise that automated pupillometry could predict the occurrence of delirium in critically ill patients without primary brain injury, requiring more than 48 hours of invasive mechanical ventilation in the ICU. METHODS AND ANALYSIS: The PupillOmetry for preDIction of DeliriUM in ICU (PODIUM) study is a prospective cohort study, which will be conducted in eight French ICUs in the Paris area. We aim to recruit 213 adult patients requiring invasive mechanical ventilation for more than 48 hours. Automated pupillometry (Neurological Pupil Index; NPi-200, Neuroptics) will be assessed two times per day for 7 days. Delirium will be assessed using the Confusion Assessment Method in ICU two times per day over 14 days in non-comatose patients (Richmond Agitation and Sedation Scale ≥-3).The predictive performances of the seven automated pupillometry parameters (ie, pupillary diameter, variation of the pupillary diameter, pupillary constriction speed, pupillary dilatation speed, photomotor reflex latency, NPi and symmetry of pupillary responses) measured to detect the delirium occurrence within 14 days will be the main outcomes. Secondary outcomes will be the predictive performances of the seven automated pupillometry parameters to detect complications related to delirium, ICU length of stay, mortality, functional and cognitive outcomes at 90 days. ETHICS AND DISSEMINATION: The PODIUM study has been approved by an independent ethics committee, the Comité de Protection des Personnes (CPP) OUEST IV-NANTES (CPP21.02.15.45239 32/21_3) on 06 April 2021). Participant recruitment started on 15 April 2022. Results will be published in international peer-reviewed medical journals and presented at conferences. TRIAL REGISTRATION NUMBER: NCT05248035; clinicaltrials.gov.

Evaluation of model-based bioequivalence approach for single sample pharmacokinetic studies.

In a traditional pharmacokinetic (PK) bioequivalence (BE) study, a two-way crossover study is conducted, PK parameters (namely the area under the time-concentration curve [AUC] and the maximal concentration [ C max ]) are obtained by noncompartmental analysis (NCA), and the BE analysis is performed using the two one-sided test (TOST) method. For ophthalmic drugs, however, only one sample of aqueous humor, in one eye, per eye can be obtained in each patient, which precludes the traditional BE analysis. To circumvent this issue, the U.S. Food and Drug Administration (FDA) has proposed an approach coupling NCA with either parametric or nonparametric bootstrap (NCA bootstrap). The model-based TOST (MB-TOST) has previously been proposed and evaluated successfully for various settings of sparse PK BE studies. In this paper, we evaluate, via simulations, MB-TOST in the specific setting of single sample PK BE study and compare its performance to NCA bootstrap. We performed BE study simulations using a published PK model and parameter values and evaluated multiple scenarios, including study design (parallel or crossover), sampling times (5 or 10 spread across the dosing interval), and geometric mean ratio (of 0.8, 0.9, 1, and 1.25). Using the simulated structural PK model, MB-TOST performed similarly to NCA bootstrap for AUC. For C max , the latter tended to be conservative and less powerful. Our research suggests that MB-TOST may be considered as an alternative BE approach for single sample PK studies, provided that the PK model is correctly specified and the test drug has the same structural model as the reference drug.

No increased prevalence of autoantibodies neutralizing type I IFNs in idiopathic pulmonary fibrosis patients.

SARS-CoV2 infection has a poor prognosis in patients affected of idiopathic pulmonary fibrosis (IPF). Autoantibodies (auto-Abs) neutralizing type I interferons (IFNs) are found in the blood of at least 15% of patients with life-threatening COVID-19 pneumonia. Because of the elevated prevalence of some auto-Abs in IPF patients, we hypothesize that the prevalence of auto-Abs neutralizing type I IFNs might be increased in the IPF population and then explained specific poor outcome after COVID-19. We screened the plasma of 247 consecutive IPF patients for the presence of auto-Abs neutralizing type I IFNs. Three patients displayed auto-Abs neutralizing type I IFNs. Among them, the only patient with documented SARS-CoV-2 infection experienced life threatening COVID-19 pneumonia. The prevalence of auto-Abs neutralizing type I IFNs in this cohort of IPF patients was not significantly different from the one of the general population. Overall, this study did not suggest any association between auto-Abs neutralizing type I IFNs and IPF.

Anti-mutated citrullinated vimentin antibodies are increased in IPF patients.

INTRO: An increased prevalence of serum anti-MCV antibody is observed in the serum of patients with idiopathic pulmonary fibrosis (IPF) but the clinical relevance of these antibodies is unknown. METHODS: Patients from our center with a diagnosis of IPF according to the 2018 ATS/ERS/JRS/ALAT guidelines and at least one anti-MCV assay available were selected. All patients were part of the prospective cohort European IPF registry and selected between 03/2010 and 03/2018. We constituted two groups of patients according to the anti-MCV status at baseline to compare their characteristics at baseline and the evolution of lung function, survival and/or transplantation status. RESULTS: Anti-MCV data were available for 101 patients, of whom 86 had complete clinical data available. Twenty-nine (34 %) patients had a positive anti-MCV assay (MCV+), at a low level in most patients (29 UI/mL [IQR 25-40]), and 57 (66 %) patients a negative assay (MCV-). MCV+ patients were 20 men and 9 women, with a median age of 73 years [IQR 67-78]. MCV- patients were 49 men and 8 women with a median age of 72 years [IQR 64-77]. Sixty-two (75 %) patients were ex-smokers and 5 (6 %) were active smokers. Median cumulative tobacco smoke exposure was 22.5 (15.0-38.6) and was similar in both groups. Lung function test results and HRCT pattern distribution was similar in both groups at baseline. The median duration of follow-up was 3.5 years [IQR 2.1-5.0]. Lung function decline was similar in both groups. During the study period, 31 (36 %) patients died or have been transplanted with no difference in transplant-free survival status between the two groups. CONCLUSION: Low level anti-MCV autoimmunity was prevalent in IPF patients.

Belief and adherence to COVID 19-lockdown restrictions in patients with asthma versus other chronic diseases: results from a cross-sectional survey nested in the ComPaRe e-cohort, in France.

BACKGROUND: Asthma patients are under-represented among patients with COVID-19. Their behavior during lockdown and associated restrictions is unknown, as well as whether it was influenced by coexistent cardiovascular conditions. METHODS: We conducted a cross-sectional survey in May 2020, in France, nested in ComPaRe, an e-cohort of adults with chronic diseases. A self-administered questionnaire was mailed to 10,859 people; 3701 fully completed questionnaires. The prevalence of self-reported asthma was 7%. Patients were classified in 4 categories: asthma with (n = 106) or without (n = 149) cardiovascular disease and other diseases with (n = 1186) or without (n = 2260) cardiovascular disease. RESULT: Adherence to movement restrictions during the lockdown was very strong: 89% of participants reported a frequency of outings of "less than once per week" and "once or twice per week" for errands and no family-related outings during the lockdown. This proportion and frequency of outings were similar whatever the chronic disease (p = 0.122). Most patients (96%) reported a high feeling of security during the lockdown, but 95% felt anxious or depressed, with no difference by disease. As compared with patients with controlled asthma, those with uncontrolled asthma more frequently reported complaints related to deteriorated medical follow-up, waived care, anxiety or depression. CONCLUSIONS: Behaviors during the lockdown in France among the asthma population did not differ from patients with other chronic diseases in this cohort, which strengthens hypotheses for specific disease-related susceptibility to explain the low representation of asthmatics among COVID-19 cases. Special attention should be paid to the subgroup of patients with uncontrolled asthma during lockdowns.

Severity of self-reported symptoms and psychological burden 6-months after hospital admission for COVID-19: a prospective cohort study.

OBJECTIVES: Few studies have reported clinical COVID-19 sequelae six months (M6) after hospital discharge, but none has studied symptom severity. METHODS: Prevalence and severity of 7 symptoms were estimated until M6 using the self-administered influenza severity scale in COVID-19 hospitalized patients enrolled in the French COVID cohort. Factors associated with severity were assessed by logistic regression. Anxiety, depression and health-related quality of life (HRQL) were also assessed. RESULTS: At M6, among the 324 patients (median age 61 years, 63% men, 19% admitted to intensive care during the acute phase), 187/324 (58%) reported at least one symptom, mostly fatigue (47%) and myalgia (23%). Symptom severity was scored, at most, mild in 125 (67%), moderate in 44 (23%) and severe in 18 (10%). Female gender was the sole factor associated with moderate/severe symptom reporting (OR = 1.98, 95%CI=1.13-3.47). Among the 225 patients with psychological assessment, 24 (11%) had anxiety, 18 (8%) depressive symptoms, and their physical HRQL was significantly poorer than the general population (p=0.0005). CONCLUSION: Even if 58% of patients reported ≥1 symptom at M6, less than 7% rated any symptom as severe. Assessing symptoms severity could be helpful to identify patients requiring appropriate medical care. Women may require special attention.

Modeling SARS-CoV-2 viral kinetics and association with mortality in hospitalized patients from the French COVID cohort.

The characterization of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral kinetics in hospitalized patients and its association with mortality is unknown. We analyzed death and nasopharyngeal viral kinetics in 655 hospitalized patients from the prospective French COVID cohort. The model predicted a median peak viral load that coincided with symptom onset. Patients with age ≥65 y had a smaller loss rate of infected cells, leading to a delayed median time to viral clearance occurring 16 d after symptom onset as compared to 13 d in younger patients (P < 10-4). In multivariate analysis, the risk factors associated with mortality were age ≥65 y, male gender, and presence of chronic pulmonary disease (hazard ratio [HR] > 2.0). Using a joint model, viral dynamics after hospital admission was an independent predictor of mortality (HR = 1.31, P < 10-3). Finally, we used our model to simulate the effects of effective pharmacological interventions on time to viral clearance and mortality. A treatment able to reduce viral production by 90% upon hospital admission would shorten the time to viral clearance by 2.0 and 2.9 d in patients of age <65 y and ≥65 y, respectively. Assuming that the association between viral dynamics and mortality would remain similar to that observed in our population, this could translate into a reduction of mortality from 19 to 14% in patients of age ≥65 y with risk factors. Our results show that viral dynamics is associated with mortality in hospitalized patients. Strategies aiming to reduce viral load could have an effect on mortality rate in this population.

Determinants of Kidney Function and Accuracy of Kidney Microcysts Detection in Patients Treated With Lithium Salts for Bipolar Disorder.

Objectives: Early kidney damage during lithium treatment in bipolar disorder is still hypothetical. We aimed at identifying the determinants of a decreased measured glomerular filtration rate (mGFR) and the accuracy of kidney MRI imaging in its detection. Methods: In this cross-sectional cohort study, 217 consecutive lithium-treated patients underwent mGFR and kidney MRI with half-Fourier turbo spin-echo and Single-shot with long echo time sequences. Results: Median age was 51 [27-62] years, and median lithium treatment duration was 5 [2-14] years. 52% of patients had a stage 2 CKD. In multivariable analysis, the determinants of a lower mGFR were a longer lithium treatment duration (ß -0.8 [-1; -0.6] ml/min/1.73 m2 GFR decrease for each year of treatment), a higher age (ß -0.4 [-0.6; -0.3] ml/min/1.73 m2 for each year of age, p < 0.001), albuminuria (ß -3.97 [-6.6; -1.3], p = 0.003), hypertension (ß -6.85 [-12.6; -1.1], p = 0.02) and hypothyroidism (ß -7.1 [-11.7; -2.5], p = 0.003). Serum lithium concentration was not associated with mGFR. Renal MRI displayed renal microcyst(s) in 51% of patients, detected as early as 1 year after lithium treatment initiation. mGFR and lithium treatment duration were strongly correlated in patients with microcyst(s) (r = -0.64, p < 0.001), but not in patients with no microcysts (r = -0.24, p = 0.09). The presence of microcysts was associated with the detection of an mGFR <45 ml/min/1.73 m2 (AUC 0.893, p < 0.001, sensitivity 80%, specificity 81% for a cut-off value of five microcysts). Conclusion: Lithium treatment duration and hypothyroidism strongly impacted mGFR independently of age, especially in patients with microcysts. MRI might help detect early lithium-induced kidney damage and inform preventive strategies.

Bayesian inference using Hamiltonian Monte-Carlo algorithm for nonlinear joint modeling in the context of cancer immunotherapy.

Treatment evaluation in advanced cancer mainly relies on overall survival and tumor size dynamics. Both markers and their association can be simultaneously analyzed by using joint models, and these approaches are supported by many softwares or packages. However, these approaches are essentially limited to linear models for the longitudinal part, which limit their biological interpretation. More biological models of tumor dynamics can be obtained by using nonlinear models, but they are limited by the fact that parameter identifiability require rich dataset. In that context Bayesian approaches are particularly suited to incorporate the biological knowledge and increase the information available, but they are limited by the high computing cost of Monte-Carlo by Markov Chains algorithms. Here, we aimed to assess the performances of the Hamiltonian Monte-Carlo (HMC) algorithm implemented in Stan for inference in a nonlinear joint model. The method was validated on simulated data where HMC provided proper posterior distributions and credibility intervals in a reasonable computational time. Then the association between tumor size dynamics and survival was assessed in patients with advanced or metastatic bladder cancer treated with atezolizumab, an immunotherapy agent. HMC confirmed limited sensitivity to prior distributions. A cross-validation approach was developed and identified the current slope of tumor size dynamics as the most relevant driver of survival. In summary, HMC is an efficient approach to perform nonlinear joint models in a Bayesian framework, and opens the way for the use of nonlinear models to characterize both the rapid dynamics and the intersubject variability observed during cancer immunotherapy treatment.

Association Between Tumor Size Kinetics and Survival in Patients With Urothelial Carcinoma Treated With Atezolizumab: Implication for Patient Follow-Up.

We characterized the association between tumor size kinetics and survival in patients with advanced urothelial carcinoma treated with atezolizumab (anti-programmed death-ligand 1, Tecentriq) using a joint model. The model, developed on data from 309 patients of a phase II clinical trial, identified the time-to-tumor growth and the instantaneous changes in tumor size as the best on-treatment predictors of survival. On the validation dataset containing data from 457 patients from a phase III study, the model predicted individual survival probability using 3-month or 6-month tumor size follow-up data with an area under the receptor-occupancy curve between 0.75 and 0.84, as compared with values comprised between 0.62 and 0.75 when the model included only information available at treatment initiation. Including tumor size kinetics in a relevant statistical framework improves the prediction of survival probability during immunotherapy treatment and may be useful to identify most-at-risk patients in "real-time."