In multilevel settings such as individual participant data meta-analysis, a variable is ‘systematically missing’ if it is wholly missing in some clusters and ‘sporadically missing’ if it is partly ...missing in some clusters. Previously proposed methods to impute incomplete multilevel data handle either systematically or sporadically missing data, but frequently both patterns are observed. We describe a new multiple imputation by chained equations (MICE) algorithm for multilevel data with arbitrary patterns of systematically and sporadically missing variables. The algorithm is described for multilevel normal data but can easily be extended for other variable types. We first propose two methods for imputing a single incomplete variable: an extension of an existing method and a new two-stage method which conveniently allows for heteroscedastic data. We then discuss the difficulties of imputing missing values in several variables in multilevel data using MICE, and show that even the simplest joint multilevel model implies conditional models which involve cluster means and heteroscedasticity. However, a simulation study finds that the proposed methods can be successfully combined in a multilevel MICE procedure, even when cluster means are not included in the imputation models.
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Propensity score (PS) methods are increasingly used, even when sample sizes are small or treatments are seldom used. However, the relative performance of the two mainly recommended PS methods, namely ...PS-matching or inverse probability of treatment weighting (IPTW), have not been studied in the context of small sample sizes.
We conducted a series of Monte Carlo simulations to evaluate the influence of sample size, prevalence of treatment exposure, and strength of the association between the variables and the outcome and/or the treatment exposure, on the performance of these two methods.
Decreasing the sample size from 1,000 to 40 subjects did not substantially alter the Type I error rate, and led to relative biases below 10%. The IPTW method performed better than the PS-matching down to 60 subjects. When N was set at 40, the PS matching estimators were either similarly or even less biased than the IPTW estimators. Including variables unrelated to the exposure but related to the outcome in the PS model decreased the bias and the variance as compared to models omitting such variables. Excluding the true confounder from the PS model resulted, whatever the method used, in a significantly biased estimation of treatment effect. These results were illustrated in a real dataset.
Even in case of small study samples or low prevalence of treatment, PS-matching and IPTW can yield correct estimations of treatment effect unless the true confounders and the variables related only to the outcome are not included in the PS model.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract Circulating mixed cryoglobulins are detected in 40%–60% of patients with hepatitis C virus (HCV) infection, and overt cryoglobulinemia vasculitis (CryoVas) develops in about 15% of patients. ...Remission of vasculitis has been associated with viral clearance, but few studies have reported the effectiveness of direct acting antiviral drugs in these patients. We performed open-label, prospective, multi-center study of the effectiveness and tolerance of an all-oral, interferon- and ribavirin-free regimen of sofosbuvir plus daclatasvir in patients with HCV-associated CryoVas. Forty-one consecutive patients with active HCV-associated CryoVas (median age, 56 years; 53.6% women) were recruited from hospitals in Paris, France from 2014 through 2016. They received sofosbuvir (400 mg/day) plus daclatasvir (60 mg/day) for 12 weeks (n=32) or 24 weeks (n=9) and evaluated every 4 weeks until week 24 and at week 36. Blood samples were analyzed for complete blood count, serum chemistry profile, level of alanine aminotransferase, rheumatoid factor activity, C4 fraction of complement, and cryoglobulin; peripheral blood mononuclear cells were isolated for flow cytometry analysis. Thirty-seven patients (90.2%) had a complete clinical response (defined by improvement of all the affected organs involved at baseline and no clinical relapse) after a median time of 12 weeks’ therapy; all had a sustained virologic response (no detectable serum HCV RNA 12 weeks after the end of antiviral therapy). Patients’ mean cryoglobulin level decreased from 0.56±0.18 at baseline to 0.21±0.14 g/L at week 36, and no cryoglobulin was detected in 50% of patients at this time point. After antiviral therapy, patients had increased numbers of T-regulatory cells, IgM+CD21–/low memory B cells, CD4+CXCR5+ IL21+ cells, and T-helper 17 cells, compared with before therapy. After a median follow-up period of 26 months (interquartile range, 20–30 months), no patients had a serious adverse event or relapse of vasculitis.
In patients with convulsive status epilepticus, the addition of cooling to 32 to 34°C for 24 hours did not have a significant effect on the percentage of patients with good outcomes at 90 days as ...compared with standard seizure treatment alone.
Convulsive status epilepticus is among the most challenging life-threatening neurologic emergencies.
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Antiepileptic drug treatment is initiated rapidly and adjusted in response to clinical and electroencephalographic (EEG) findings.
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The in-hospital mortality associated with this condition is approximately 20% and, if status epilepticus remains refractory to treatment, can be as high as 40%.
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Functional impairments after status epilepticus may be due to the effect of seizures on cortical neurons or to cerebral damage due to the underlying process that caused the seizures. In a prospective, multicenter study, 50% of survivors of convulsive status epilepticus who were admitted to an intensive care . . .
Inverse probability of treatment weighting is a popular propensity score-based approach to estimate marginal treatment effects in observational studies at risk of confounding bias. A major issue when ...estimating the propensity score is the presence of partially observed covariates. Multiple imputation is a natural approach to handle missing data on covariates: covariates are imputed and a propensity score analysis is performed in each imputed dataset to estimate the treatment effect. The treatment effect estimates from each imputed dataset are then combined to obtain an overall estimate. We call this method MIte. However, an alternative approach has been proposed, in which the propensity scores are combined across the imputed datasets (MIps). Therefore, there are remaining uncertainties about how to implement multiple imputation for propensity score analysis: (a) should we apply Rubin’s rules to the inverse probability of treatment weighting treatment effect estimates or to the propensity score estimates themselves? (b) does the outcome have to be included in the imputation model? (c) how should we estimate the variance of the inverse probability of treatment weighting estimator after multiple imputation? We studied the consistency and balancing properties of the MIte and MIps estimators and performed a simulation study to empirically assess their performance for the analysis of a binary outcome. We also compared the performance of these methods to complete case analysis and the missingness pattern approach, which uses a different propensity score model for each pattern of missingness, and a third multiple imputation approach in which the propensity score parameters are combined rather than the propensity scores themselves (MIpar). Under a missing at random mechanism, complete case and missingness pattern analyses were biased in most cases for estimating the marginal treatment effect, whereas multiple imputation approaches were approximately unbiased as long as the outcome was included in the imputation model. Only MIte was unbiased in all the studied scenarios and Rubin’s rules provided good variance estimates for MIte. The propensity score estimated in the MIte approach showed good balancing properties. In conclusion, when using multiple imputation in the inverse probability of treatment weighting context, MIte with the outcome included in the imputation model is the preferred approach.
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Objective
To analyze the factors associated with response to anti–tumor necrosis factor (anti‐TNF) treatment and compare the efficacy and safety of infliximab (IFX) and adalimumab (ADA) in patients ...with refractory noninfectious uveitis.
Methods
This was a multicenter observational study of 160 patients (39% men and 61% women; median age 31 years interquartile range 21–42) with uveitis that had been refractory to other therapies, who were treated with anti‐TNF (IFX 5 mg/kg at weeks 0, 2, 6, and then every 5–6 weeks n = 98 or ADA 40 mg every 2 weeks n = 62). Factors associated with complete response were assessed by multivariate analysis. Efficacy and safety of IFX versus ADA were compared using a propensity score approach with baseline characteristics taken into account. Subdistribution hazard ratios (SHRs) and 95% confidence intervals (95% CIs) were calculated.
Results
The main etiologies of uveitis included Behçet's disease (BD) (36%), juvenile idiopathic arthritis (22%), spondyloarthropathy (10%), and sarcoidosis (6%). The overall response rate at 6 and 12 months was 87% (26% with complete response) and 93% (28% with complete response), respectively. The median time to complete response was 2 months. In multivariate analysis, BD and occurrence of >5 uveitis flares before anti‐TNF initiation were associated with complete response to anti‐TNF (SHR 2.52 95% CI 1.35–4.71, P = 0.004 and SHR 1.97 95% CI 1.02–3.84, P = 0.045, respectively). Side effects were reported in 28% of patients, including serious adverse events in 13%. IFX and ADA did not differ significantly in terms of occurrence of complete response (SHR 0.65 95% CI 0.25–1.71, P = 0.39), serious side effects (SHR 0.22 95% CI 0.04–1.25, P = 0.089), or event‐free survival (SHR 0.55 95% CI 0.28–1.08, P = 0.083).
Conclusion
Anti‐TNF treatment is highly effective in refractory inflammatory uveitis. BD is associated with increased odds of response. IFX and ADA appear to be equivalent in terms of efficacy.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Cluster analysis, commonly used to explore large biomedical datasets, can be challenging, notably due to missing data or left‐censored data induced by the sensitivity limits of the biochemical ...measurement method. Usually, complete‐case analysis, simple imputation, or stochastic simple imputation are applied before clustering. More recently, consensus methods following multiple imputation have been proposed. However, they ignore left‐censoring and do not allow the number of clusters to vary across the partitions of each imputed dataset. Here, we developed a consensus‐based clustering algorithm in which left‐censored data are taken into account using a modified multiple imputation method and the number of clusters is estimated for each imputed dataset. A simulation study was conducted to assess the performance in terms of the number of clusters, the percentage of unclassified observations, and the adjusted Rand index. The simulation results showed that the investigated method works well compared to several alternative approaches. A real‐world application in breast cancer patients showed that the proposed method may reveal novel clusters of patients.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Prognostic factors of coronavirus disease 2019 (COVID-19) patients among European population are lacking. Our objective was to identify early prognostic factors upon admission to optimize the ...management of COVID-19 patients hospitalized in a medical ward. This French single-center prospective cohort study evaluated 152 patients with positive severe acute respiratory syndrome coronavirus 2 real-time reverse transcriptase-polymerase chain reaction assay, hospitalized in the Internal Medicine and Clinical Immunology Department, at Pitié-Salpêtrière's Hospital, in Paris, France, a tertiary care university hospital. Predictive factors of intensive care unit (ICU) transfer or death at day 14 (D14), of being discharge alive and severe status at D14 (remaining with ventilation, or death) were evaluated in multivariable logistic regression models; models' performances, including discrimination and calibration, were assessed (C-index, calibration curve, R2, Brier score). A validation was performed on an external sample of 132 patients hospitalized in a French hospital close to Paris, in Aulnay-sous-Bois, Île-de-France. The probability of ICU transfer or death was 32% (47/147) (95% CI 25-40). Older age (OR 2.61, 95% CI 0.96-7.10), poorer respiratory presentation (OR 4.04 per 1-point increment on World Health Organization (WHO) clinical scale, 95% CI 1.76-9.25), higher CRP-level (OR 1.63 per 100mg/L increment, 95% CI 0.98-2.71) and lower lymphocytes count (OR 0.36 per 1000/mm3 increment, 95% CI 0.13-0.99) were associated with an increased risk of ICU requirement or death. A 9-point ordinal scale scoring system defined low (score 0-2), moderate (score 3-5), and high (score 6-8) risk patients, with predicted respectively 2%, 25% and 81% risk of ICU transfer or death at D14. Therefore, in this prospective cohort study of laboratory-confirmed COVID-19 patients hospitalized in a medical ward in France, a simplified scoring system at admission predicted the outcome at D14.
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Folliculitis decalvans (FD) is a chronic inflammatory disease of unknown aetiology. Although Staphylococcus aureus, frequently found on lesional skin, is thought to play a causal role, the importance ...of its involvement remains controversial. To examine the role of S aureus, we compared superficial and subepidermal microbiota in 20 FD patients who had S aureus on lesional skin and in 20 healthy controls using culture techniques and genomic identification, before and after an anti‐staphylococcal treatment; we also screened for S aureus virulence factors. When present on lesional skin, S aureus colonized non‐lesional and subepidermal skin in 80% of cases. These data imply a break in the epidermal barrier integrity and that an abnormal non‐lesional skin microbiota persists in FD. S aureus had no superantigenic toxin in 31% of cases and no toxin specificity. Clinical improvement obtained in most cases upon treatment was associated with the disappearance of S aureus in all studied areas, with an incomplete restoration of normal microbiota and a significant increase in negative bacterial samples. This persistent unbalanced, subepidermal microbiota may act as a reservoir of abnormal flora and explain the chronicity of FD, suggesting new avenues of research to restore normal microbiota.
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BFBNIB, DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UILJ, UKNU, UL, UM, UPUK
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