Category: Statistics

J Clin Immunol. 2022 Jun 18. doi: 10.1007/s10875-022-01298-2. Online ahead of print.

ABSTRACT

Pathogenic RIPK1 variants have been described as the cause of two different inborn errors of immunity. Biallelic loss-of-function variants cause the recessively inherited RIPK1 deficiency, while monoallelic variants impairing the caspase-8-mediated RIPK1 cleavage provoke a novel autoinflammatory disease (AID) called cleavage-resistant RIPK1-induced autoinflammatory (CRIA) syndrome. The aim of this study was to characterize the pathogenicity of two novel RIPK1 variants located at the cleavage site of caspase-8 detected in patients with dominantly-inherited, early-onset undefined AID. RIPK1 genotyping was performed by Sanger and next-generation sequencing. Clinical and analytical data were collected from medical charts, and in silico and in vitro assays were performed to evaluate the functional consequences. Genetic analyses identified two novel heterozygous RIPK1 variants at the caspase-8 cleavage site (p.Leu321Arg and p.Asp324Gly), which displayed a perfect intrafamilial phenotype-genotype segregation following a dominant inheritance pattern. Structural analyses suggested that these variants disrupt the normal RIPK1 structure, probably making it less accessible to and/or less cleavable by caspase-8. In vitro experiments confirmed that the p.Leu321Arg and p.Asp324Gly RIPK1 variants were resistant to caspase-8-mediated cleavage and induced a constitutive activation of necroptotic pathway in a similar manner that previously characterized RIPK1 variants causing CRIA syndrome. All these results strongly supported the pathogenicity of the two novel RIPK1 variants and the diagnosis of CRIA syndrome in all enrolled patients. Moreover, the evidences here collected expand the phenotypic and genetic diversity of this recently described AID, and provide interesting data about effectiveness of treatments that may benefit future patients.

PMID:35716229 | DOI:10.1007/s10875-022-01298-2

J Comput Aided Mol Des. 2022 Jun 18. doi: 10.1007/s10822-022-00460-7. Online ahead of print.

ABSTRACT

The main protease (M^pro) of SARS-Cov-2 is the essential enzyme for maturation of functional proteins implicated in viral replication and transcription. The peculiarity of its specific cleavage site joint with its high degree of conservation among all coronaviruses promote it as an attractive target to develop broad-spectrum inhibitors, with high selectivity and tolerable safety profile. Herein is reported a combination of three-dimensional quantitative structure-activity relationships (3-D QSAR) and comparative molecular binding energy (COMBINE) analysis to build robust and predictive ligand-based and structure-based statistical models, respectively. Models were trained on experimental binding poses of co-crystallized M^pro-inhibitors and validated on available literature data. By means of deep optimization both models’ goodness and robustness reached final statistical values of r²/q² values of 0.97/0.79 and 0.93/0.79 for the 3-D QSAR and COMBINE approaches respectively, and an overall predictiveness values of 0.68 and 0.57 for the SDEP_PRED and AAEP metrics after application to a test set of 60 compounds covered by the training set applicability domain. Despite the different nature (ligand-based and structure-based) of the employed methods, their outcome fully converged. Furthermore, joint ligand- and structure-based structure-activity relationships were found in good agreement with nirmatrelvir chemical features properties, a novel oral M^pro-inhibitor that has recently received U.S. FDA emergency use authorization (EUA) for the oral treatment of mild-to-moderate COVID-19 infected patients. The obtained results will guide future rational design and/or virtual screening campaigns with the aim of discovering new potential anti-coronavirus lead candidates, minimizing both time and financial resources. Moreover, as most of calculation were performed through the well-established web portal 3d-qsar.com the results confirm the portal as a useful tool for drug design.

PMID:35716228 | DOI:10.1007/s10822-022-00460-7

Qual Life Res. 2022 Jun 18. doi: 10.1007/s11136-022-03169-0. Online ahead of print.

ABSTRACT

PURPOSE: Mixture item response theory (MixIRT) models can be used to uncover heterogeneity in responses to items that comprise patient-reported outcome measures (PROMs). This is accomplished by identifying relatively homogenous latent subgroups in heterogeneous populations. Misspecification of the number of latent subgroups may affect model accuracy. This study evaluated the impact of specifying too many latent subgroups on the accuracy of MixIRT models.

METHODS: Monte Carlo methods were used to assess MixIRT accuracy. Simulation conditions included number of items and latent classes, class size ratio, sample size, number of non-invariant items, and magnitude of between-class difference in item parameters. Bias and mean square error in item parameters and accuracy of latent class recovery were assessed.

RESULTS: When the number of latent classes was correctly specified, the average bias and MSE in model parameters decreased as the number of items and latent classes increased, but specification of too many latent classes resulted in modest decrease (i.e., < 10%) in the accuracy of latent class recovery.

CONCLUSION: The accuracy of MixIRT model is largely influenced by the overspecification of the number of latent classes. Appropriate choice of goodness-of-fit measures, study design considerations, and a priori contextual understanding of the degree of sample heterogeneity can guide model selection.

PMID:35716223 | DOI:10.1007/s11136-022-03169-0

Breast Cancer Res Treat. 2022 Jun 18. doi: 10.1007/s10549-022-06641-0. Online ahead of print.

ABSTRACT

PURPOSE: To evaluate the clinical role of tumor-associated macrophages, including foamy (FM) and hemosiderin-laden macrophages (HLM) in the tumor bed (TB) of triple-negative breast cancer (TNBC) post-neoadjuvant chemotherapy (NACT).

METHODS: We conducted a pathologic review of 129 women, diagnosed with TNBC between 2002 and 2016 at our institute. The residual cancer burden (RCB) was calculated. We estimated the percentage of tumor-infiltrating lymphocytes (TILs) in the core needle biopsy (CNB), and FM, HLM, and TILs (in TB) [the combined cells are designated as tumor-associated mononuclear cells (TAMNC)]. The information on patient demographics, chemotherapy regimen, recurrence-free survival (RFS), and overall survival (OS) was extracted from the medical records.

RESULTS: Pathologic complete response (pCR) was achieved in 34.1% of the women. TILs (10% increment in CNB) only were associated with pCR in the multivariable analysis [odds ratio 1.04 (1.02, 1.06) (p = 0.0003)]. Immune cells associated with better OS included TAMNC (≤ 30%) [hazard ratio (HR) 4.32 (1.93, 9.66) (p = 0.0004)], and FM (0%) [HR 2.30 (1.06, 4.98) (p = 0.036)]. While increased HLM (10% increment) was statistically significant with HR 0.93 and 95% CI (0.88 to 0.98) (p = 0.0061), using a cutoff of 0%, HLM (0%: negative vs. ≥ 1%: positive) achieved only borderline significance with HR 2.05 (0.98, 4.31) (p = 0.058). Similarly, these immune cells were also associated with better RFS: TAMNC (≤ 30%) [HR 4.57 (2.04, 10.21) (p = 0.0002)], FM (0%) [HR 2.80 (1.23, 6.35) (p = 0.014)], and HLM (0%) [HR 2.34 (1.07, 5.11) (p = 0.03)]. TILs (in TB) were not associated with any clinical outcomes.

CONCLUSIONS: Although TILs may play a role in the response to NACT, they may not be critical to the prognosis after NACT. Instead, FM and HLM may assume this role. More studies are warranted.

PMID:35716216 | DOI:10.1007/s10549-022-06641-0

J Ophthalmic Inflamm Infect. 2022 Jun 18;12(1):18. doi: 10.1186/s12348-022-00297-z.

ABSTRACT

OBJECTIVES: This study aimed to evaluate the retinal and choroidal changes in the macular region of patients with Coronavirus Disease 2019 (COVID-19) using structural spectral-domain optical coherence tomography (SD-OCT) analysis.

METHODS: This cross-sectional observational case-control study included patients recovered from COVID-19. The COVID-19 in all participants was confirmed using the reverse transcription-polymerase chain reaction (RT-PCR) technique. The participants had mild to moderate degree of disease without a history of hospitalization, steroid usage, or blood saturation below 92%. Macular SD-OCT was performed at least two weeks and up to one month after recovery from systemic COVID-19. Quantitative and qualitative changes detected by macular SD-OCT imaging were evaluated in COVID-19 recovered patients and compared with the results of age-matched normal controls.

RESULTS: Participants in this study included 30 cases (60 eyes) and 60 healthy controls (120 eyes). In total, 17 (28.3%) eyes in patient group showed at least one abnormal finding indicated by macular SD-OCT imaging included hyperreflective lesions in different retinal layers. In addition, dilated choroidal vessels and retinal pigment epitheliopathy were evident in 41 (68.3.6%) and 4 (6.6%) eyes in patient group, respectively, and their OCT findings resembled those with pachychoroid spectrum. No statistically significant differences were observed in retinal layers or retinal volume between the two groups. The mean ± SD subfoveal choroidal thickness (SFCT) was determined at 380.3 ± 12.40 μm, which was significantly thicker than that in control group (310.7 ± 57.5 μm) (P < 0.001).

CONCLUSION: Regarding retinal thickness, no significant change was observed in different retina layers of patients with COVID-19; however, there were striking qualitative changes, such as hyperreflective lesions in different retinal layers. The evaluation of choroidal structure and thickness demonstrated remarkable abnormal pachyvessels and significant thickening of the SFCT but the clinical significance of these findings is unknown.

PMID:35716213 | DOI:10.1186/s12348-022-00297-z

Int Urogynecol J. 2022 Jun 18. doi: 10.1007/s00192-022-05278-3. Online ahead of print.

ABSTRACT

INTRODUCTION AND HYPOTHESIS: Increased post-voiding residual volume (PVRV), known as covert postpartum urinary retention (PUR), is an asymptomatic condition with unknown long-term adverse effects. The objectives were to determine the frequency of this phenomenon 3 days after delivery and to examine the associated risk factors and consequences of the increased residuum on women´s health 6 weeks postpartum.

METHODS: We carried out a prospective observational study including a total of 926 primiparous women, giving birth to singletons. All participants underwent ultrasound determination of PVRV on day 3 postpartum. Then, risk factors were determined using logistic regression analysis. After 6 weeks, participants were invited to return for PVRV determination and to complete urogynecological and general health questionnaires. Using these data, the consequences of increased PVRV were determined.

RESULTS: A total of n=90 women were diagnosed with abnormal PVRV. Mean age in the studied population was 30.4 years, BMI prior to delivery 27.8, weight of the newborn 3,420 g, and percentage of cesarean sections 15.9%. Gestational week (p=0.043), vaginal tear (p=0.032), and induction of labor (p=0.003) were risk factors for covert PUR. Puerperal incidence of urinary tract infection was 1.1% (6 out of 526) and of urinary incontinence 29.2% (155 out of 530), with no differences between the groups. In the second examination, covert PUR was no longer present, and the values of residual urine decreased for all patients in the case group. No statistically significant differences were observed in questionnaire scores in general health and wellbeing perceptions between the groups.

CONCLUSIONS: We have found a few significant obstetrical-pediatric risk factors for abnormal PVRVs. Data from the follow-up suggest that covert PUR has no impact on morbidity and quality of life 6 weeks postpartum. Therefore, abnormal PVRV is a self-limited phenomenon with a tendency toward self-correction. Our findings support those of previous studies that advocate against screening for asymptomatic retention in the postpartum period, despite some similar previous recommendations.

PMID:35716199 | DOI:10.1007/s00192-022-05278-3

Stat Med. 2022 Jun 18. doi: 10.1002/sim.9501. Online ahead of print.

ABSTRACT

Counterfactual-model-based mediation analysis can yield substantial insight into the causal mechanism through the assessment of natural direct effects (NDEs) and natural indirect effects (NIEs). However, the assumptions regarding unmeasured mediator-outcome confounding and intermediate mediator-outcome confounding that are required for the determination of NDEs and NIEs present practical challenges. To address this problem, we introduce an instrumental blocker, a novel quasi-instrumental variable, to relax both of these assumptions, and we define a swapped direct effect (SDE) and a swapped indirect effect (SIE) to assess the mediation. We show that the SDE and SIE are identical to the NDE and NIE, respectively, based on a causal interpretation. Moreover, the empirical expressions of the SDE and SIE are derived with and without an intermediate mediator-outcome confounder. Then, a multiply robust estimation method is derived to mitigate the model misspecification problem. We prove that the proposed estimator is consistent, asymptotically normal, and achieves the semiparametric efficiency bound. As an illustration, we apply the proposed method to genomic datasets of lung cancer to investigate the potential role of the epidermal growth factor receptor in the treatment of lung cancer.

PMID:35716042 | DOI:10.1002/sim.9501

Stat Med. 2022 Jun 18. doi: 10.1002/sim.9498. Online ahead of print.

ABSTRACT

The existence of items not susceptible to the event of interest is of both theoretical and practical importance. Although researchers may provide, for example, biological, medical, or sociological evidence for the presence of such items (cured), statistical models performing well under the existence or not of a cured proportion, frequently offer a necessary flexibility. This work introduces a new reparameterization of a flexible family of cure models, which not only includes among its special cases, the most studied cure models (such as the mixture, bounded cumulative hazard, and negative binomial cure model) but also classical survival models (ie, without cured items). One of the main properties of the proposed family, apart from its computationally tractable closed form, is that the case of zero cured proportion is not found at the boundary of the parameter space, as it typically happens to other families. A simulation study examines the (finite) performance of the suggested methodology, focusing to the estimation through EM algorithm and model discrimination, by the aid of the likelihood ratio test and Akaike information criterion; for illustrative purposes, analysis of two real life datasets (on recidivism and cutaneous melanoma) is also carried out.

PMID:35716033 | DOI:10.1002/sim.9498

Stat Med. 2022 Jun 18. doi: 10.1002/sim.9491. Online ahead of print.

ABSTRACT

In precision medicine, the ultimate goal is to recommend the most effective treatment to an individual patient based on patient-specific molecular and clinical profiles, possibly high-dimensional. To advance cancer treatment, large-scale screenings of cancer cell lines against chemical compounds have been performed to help better understand the relationship between genomic features and drug response; existing machine learning approaches use exclusively supervised learning, including penalized regression and recommender systems. However, it would be more efficient to apply reinforcement learning to sequentially learn as data accrue, including selecting the most promising therapy for a patient given individual molecular and clinical features and then collecting and learning from the corresponding data. In this article, we propose a novel personalized ranking system called Proximal Policy Optimization Ranking (PPORank), which ranks the drugs based on their predicted effects per cell line (or patient) in the framework of deep reinforcement learning (DRL). Modeled as a Markov decision process, the proposed method learns to recommend the most suitable drugs sequentially and continuously over time. As a proof-of-concept, we conduct experiments on two large-scale cancer cell line data sets in addition to simulated data. The results demonstrate that the proposed DRL-based PPORank outperforms the state-of-the-art competitors based on supervised learning. Taken together, we conclude that novel methods in the framework of DRL have great potential for precision medicine and should be further studied.

PMID:35716038 | DOI:10.1002/sim.9491

Muscle Nerve. 2022 Jun 18. doi: 10.1002/mus.27662. Online ahead of print.

ABSTRACT

INTRODUCTION/AIMS: Pulmonary decline is an important issue in patients with Duchenne muscular dystrophy (DMD). Eteplirsen is a US-approved treatment for patients with DMD and exon 51 skip-amenable mutations. Previous analyses have shown that eteplirsen is associated with statistically significant attenuation of pulmonary decline. This study evaluates the effect of eteplirsen treatment from newly available data sources on pulmonary function over time in patients with DMD.

METHODS: This study uses a post hoc pooled analysis to compare the percentage of predicted forced vital capacity (FVC%p) and projected time to pulmonary function milestones in patients with DMD and exon 51 skip-amenable mutations receiving eteplirsen (Studies 204 and 301) or standard of care (SoC; Cooperative International Neuromuscular Research Group Duchenne Natural History Study). A mixed model for repeated measures framework was applied to evaluate the impact of eteplirsen.

RESULTS: An average annual rate of FVC%p decline for eteplirsen-treated patients was estimated to be 3.47%, which was a statistically significant attenuation from the 5.95% rate of decline estimated in SoC patients (P = 0.0001). Using linear extrapolations of the model-estimated decline in FVC%p, the attenuation in FVC%p decline for eteplirsen-treated patients corresponded to a delay of 5.72 years in time to needing continuous ventilation, 3.31 years in time to needing nighttime ventilation, and 2.11 years in time to needing a cough assist device compared with SoC patients.

DISCUSSION: The attenuation of FVC%p decline suggests that eteplirsen-treated patients experienced statistically significant and clinically meaningful attenuations in pulmonary decline compared with SoC patients. This article is protected by copyright. All rights reserved.

PMID:35715998 | DOI:10.1002/mus.27662