Nevin Manimala

Breast Cancer Res Treat. 2022 Jun 29. doi: 10.1007/s10549-022-06657-6. Online ahead of print.

ABSTRACT

PURPOSE: The purpose of this study was to identify oncologist-reported barriers and motivators in addressing long-term effects with breast cancer survivors.

METHODS: This study is a secondary analysis of data from a survey of U.S. medical oncologists (n = 217) about breast cancer survivorship care in clinical practice. Using both closed- and open-ended questions, we asked oncologists to report barriers and motivators they perceived in addressing long-term effects with breast cancer patients. Descriptive statistics were used to summarize and rank items endorsed by oncologists in analyses of quantitative data; content analysis was used to identify salient categories of barriers and motivators in qualitative data.

RESULTS: Key barriers to managing physical long-term effects included lack of time during appointments (n = 128 oncologists, 59%) and perceived lack of evidence-based interventions (n = 89, 41%). With respect to psychosocial effects, oncologists reported lack of knowledge (n = 88, 40.6%) and challenges making referrals to mental health providers (n = 115, 53%). From the qualitative data, three distinct barrier categories emerged: “Competing priorities during brief appointments;” “Discussing long-term effects-Who? What? When?;” and “Beyond my expertise and comfort level.” Two motivator categories emerged: “I owe it to them;” and “Giving people a life worth living.”

CONCLUSION: Oncologists’ key motivators for addressing long-term effects were focused on professional values, relationships with survivors, and their commitment to prioritizing patients’ quality of life. Future efforts should leverage oncologists’ professional and interpersonal motivators to enhance the delivery of survivorship care for breast cancer.

PMID:35767127 | DOI:10.1007/s10549-022-06657-6

Eur Spine J. 2022 Jun 29. doi: 10.1007/s00586-022-07277-w. Online ahead of print.

ABSTRACT

PURPOSE: To measure the pedicle dimensions in high grade lytic spondylolisthesis (HGL) and to classify them, which helps the spine surgeon in proper selection of pedicle screws.

METHODS: A study of CT scans in 100 consecutive patients between Jan 2017 and April 2021 diagnosed as single-level HGL on standing radiographs. Pedicle height (PH), Pedicle width (PW), Differential pedicle height (DPH), Screw length (SL) and Transverse pedicle angle (TPA) were measured and analyzed. PH and PW were classified into four grades as-grade A less than 5.0 mm, grade B between 5.0 and 6.0 mm, grade C between 6.0 and 7.0 mm, and grade D above 7.0 mm.

RESULTS: 5 males and 95 females with mean age of 49.1 years. PH in 44% lytic vertebra were grade A, B (less than 6 mm) and the rest 56% had grade C, D (greater than 6 mm). PH averaged 6.6 mm in grade 3 HGL, 5.61 mm in grade 4 HGL. Change in PW, SL and TPA was not statistically significant with regards to grade or level of listhesis. A total of 37 cases were noted to have DPH (25 cases had a difference < 2 mm and 12 had a difference > 2 mm).

CONCLUSION: 44% of the PH in lytic vertebra was grade A and B (less than 6 mm) that stresses the importance of pre-op CT assessment and planning the appropriate screw dimensions. Change in PH was statistically significant with regards to the grade of listhesis (P-value < 0.01). Differential pedicle height also need to be looked for.

PMID:35767112 | DOI:10.1007/s00586-022-07277-w

Support Care Cancer. 2022 Jun 29. doi: 10.1007/s00520-022-07245-6. Online ahead of print.

ABSTRACT

PURPOSE: The aim of this study was to study the nutritional profile of node-negative and node-positive patients undergoing treatment for head and neck squamous cell cancer (HNSCC).

METHODS: This prospective cohort study was conducted between 2018 and 2020. Patients diagnosed with HNSCC, planned for treatment, were enrolled after written informed consent. In node-negative (N0) and node-positive (N +) cohorts of patients, nutritional status was determined using anthropometric measures and Subjective Global Assessment (SGA) scale pre-treatment, and during and after treatment. Statistical analysis was performed using SPSS version 22. Data was analyzed using parametric and non-parametric tests, and p value of 0.05 was considered significant.

RESULTS: In total, 161 patients were analyzed, 73 N0 and 88 N + cohorts. Pre-treatment, 9.6 to 20.4% patients in N0 and 23.9 to 32.8% patients in N + cohorts were malnourished. Incidence of malnutrition at completion of treatment was 40.8 to 52.5% overall, 20.5 to 41.1% N0, and 39.5 to 62.8% N + . Mean reduction in weight (11.1% ± 7.82 vs 6.26% ± 8.3, p = 0.000), mean reduction in BMI (2.57 ± 1.87 vs 1.29 ± 1.62, p = 0.000), median reduction in MUAC (2 cm vs 1 cm, p = 0.000), and median increase in SGA score (13 vs 6, p = 0.000) were higher in multi-modality as compared to those in a single-modality treatment. Similar findings were noted in N0 and N + cohorts.

CONCLUSION: As compared to N0, N + patients had higher burden of malnutrition at diagnosis, and more worsening of nutritional parameters during treatment. More decline in nutritional status was seen in patients receiving multi-modality as compared to single-modality treatment.

PMID:35767086 | DOI:10.1007/s00520-022-07245-6

Curr Microbiol. 2022 Jun 29;79(8):230. doi: 10.1007/s00284-022-02918-1.

ABSTRACT

In healthy women at reproductive age, the vaginal microbiota is mainly dominated by Lactobacillus bacteria during pregnancy and non-pregnancy stages. However, little is known about longitudinal changes within the vaginal microbiota composition from the third trimester of pregnancy to childbirth in healthy women. Thus, we conducted an exploratory longitudinal study of vaginal microbiota composition of 10 Mexican pregnant women, sampling from the same volunteer at two-time points: third trimester of pregnancy and active childbirth. Vaginal bacterial microbiota was characterized by V3-16S rDNA libraries by high-throughput sequencing and bioinformatics methods. Out of ten, vaginal microbiota from eight women was dominated by the Lactobacillus genus at both time points, whereas the other two women showed vaginal microbiota composition with high abundance of genera Gardnerella, Prevotella, and members of the Atopobiaceae family, without any preterm birth correlation. Importantly, we found no statistically significant differences in relative abundances, absolute reads count, alpha and beta diversity between the third trimester of pregnancy, and active childbirth time points. However, compared to the third trimester of pregnancy, we observed a trend with higher absolute reads counts for Gardnerella, Faecalibaculum, Ileibacterium, and Lactococcus genus at active childbirth and lower absolute reads count of Lactobacillus genus. Our results suggest that the vaginal microbiota composition is stable, and Lactobacillus genus is the dominant taxa in Mexican women’s vagina at the third trimester of pregnancy and childbirth.

PMID:35767085 | DOI:10.1007/s00284-022-02918-1

J Math Biol. 2022 Jun 29;85(1):1. doi: 10.1007/s00285-022-01772-w.

ABSTRACT

An intraguild predation model with intraguild predator diffusion is proposed and studied in this work. It is shown that the local system can have four boundary equilibria and at most two interior equilibria. The interior equilibria may exist even when the system is not uniformly persistent. When only intraguild predator diffusion is incorporated into our three-species model, the resulting model is a partially degenerate reaction-diffusion system. For this partially degenerate system, we show that the solution semiflow is bounded dissipative and the positive orbits of bounded sets are bounded. We also demonstrate that intraguild predator diffusion can lead to the occurrence of spatially nonhomogeneous oscillations and spatiotemporal chaos. Further, we show that intraguild predator diffusion can induce transitions between spatially homogeneous oscillations, spatially nonhomogeneous oscillations and chaos.

PMID:35767083 | DOI:10.1007/s00285-022-01772-w

Pharm Stat. 2022 Jun 29. doi: 10.1002/pst.2248. Online ahead of print.

ABSTRACT

There is an increasing interest in the use of win ratio with composite time-to-event due to its flexibility in combining component endpoints. Exploring this flexibility further, one interesting question is in assessing the impact when there is a difference in treatment effect in the component endpoints. For example, the active treatment may prolong the time to occurrence of the negative event such as death or ventilation; meanwhile, the treatment effect may also shorten the time to achieving positive events, such as recovery or improvement. Notably, this portrays a situation where the treatment effect on time to recovery is in a different direction of benefit compared to the time to ventilation or death. Under such circumstances, if a single endpoint is used, the benefit gained for other individual outcomes is not counted and is diminished. As consequence, the study may need a larger sample size to detect a significant effect of treatment. Such a scenario can be handled by win ratio in a novel way by ranking component events, which is different from the usual composite endpoint approach such as time-to-first event. To evaluate how the different directions of treatment effect on component endpoints will impact the win ratio analysis, we use a Clayton copula-based bivariate survival simulation to investigate the correlation of component time-to-event. Through simulation, we found that compared to the marginal model using single endpoints, the win ratio analysis on composite endpoint performs better, especially when the correlation between two events is weak. Then, we applied the methodology to an infectious disease progression simulated study motivated by COVID-19. The application demonstrates that the win ratio approach offers advantages in empirical power compared to the traditional Cox proportional hazard approach when there is a difference in treatment effect in the marginal events.

PMID:35766113 | DOI:10.1002/pst.2248

Orbit. 2022 Jun 29:1-4. doi: 10.1080/01676830.2022.2092156. Online ahead of print.

ABSTRACT

PURPOSE: We aimed to perform a review of facial and periorbital squamous cell carcinoma (SCC) cases to assess the relative incidence of eyelid margin involvement.

METHODS: This is a retrospective review of all patients with biopsy-proven SCC who were evaluated at a single oculoplastic surgery practice from 2007 to 2019. The charts were reviewed for the anatomical location of the malignancy, and those involving the eyelid were further divided into marginal and non-marginal lesions. Statistical analysis was performed using a one proportion z-test.

RESULTS: A total of 76 patients with a diagnosis of biopsy-proven periorbital and facial SCC were identified, 67 involved the ocular adnexa. Thirty-nine (58.2%) patients had lesions located on the eyelid. Of these, 33 (84.6% p < 0.0001, 95% CI 69.45-94.13) had lesions located at the margin, six of the 39 lesions were non-marginal. The remaining lesions were present within the brow (n = 10, 14.9%), medial canthus (n = 10, 14.9%), palpebral conjunctiva (n = 1, 1.5%), or orbit (n = 1, 1.5%). In six patients (8.9%) lesions involved multiple anatomic subunits.

CONCLUSION: We present our investigation of the incidence of SCC of the marginal vs. non-marginal eyelid, revealing a statistically significant increased involvement of the eyelid margin. Future investigations are necessary to further elucidate the vulnerability of the eyelid margin to the development of SCC in particular in regards to the role of the unique genetic expression profile of eyelash follicular stem cells.

PMID:35766103 | DOI:10.1080/01676830.2022.2092156

Ann Biol Clin (Paris). 2022 Mar 1;80(2):148-155. doi: 10.1684/abc.2022.1723.

ABSTRACT

BACKGROUND: Numerous studies have shown that thrombin generation test (TG) allows a better evaluation of the hemorrhagic and the thrombotic risks. The ST Genesia® is a benchtop, fully automated TG device. However, standardization of the technique and establishment of usual values are essential for its implementation in the routine laboratory.

OBJECTIVES: We evaluated the fully automated TG analyzer ST Genesia ® and we aimed to determine usual values with special attention to the pediatric population.

METHODS: Two ST Genesia® reagents were evaluated (BleedscreenTM and ThromboscreenTM). Precision, stability, practicability and usual values according to age were established as well as the impact of freezing samples. The comparison between calibrated automated thrombogram (CAT) method and ST Genesia® was performed. TG parameters (ETP, peak, velocity, lag time, time to peak) were analyzed on both instruments. All the results were normalized toward a reference plasma.

RESULTS: Coefficient of variation associated with the repeatability and reproducibility of the QC norm low, and norm were less than 5% with both Thromboscreen and Bleedscreen reagents. We did not observe any statistical difference between results obtained on fresh or frozen samples. Usual values according to age and sex were established with special attention to the pediatric population.

CONCLUSION: This technique provides a fully automated system, a strict control of temperature and the use of a reference plasma to obtain normalized results. This study is a prerequisite to future use of ST Genesia® in clinical application.

PMID:35766075 | DOI:10.1684/abc.2022.1723

Genet Epidemiol. 2022 Jun 29. doi: 10.1002/gepi.22491. Online ahead of print.

ABSTRACT

Transcriptome-Wide Association Studies (TWASs) have become increasingly popular in identifying genes (or other endophenotypes or exposures) associated with complex traits. In TWAS, one first builds a predictive model for gene expressions using an expression quantitative trait loci (eQTL) data set in stage 1, then tests the association between the predicted gene expression and a trait based on a large, independent genome-wide association study (GWAS) data set in stage 2. However, since the sample size of the eQTL data set is usually small and the coefficient of multiple determination (i.e., R2${R}^{2}$ ) of the model for many genes is also small, a question of interest is to what extent these factors affect the statistical power of TWAS. In addition, in contrast to a standard (univariate) TWAS (UV-TWAS) considering only a single gene at a time, multivariate TWAS (MV-TWAS) methods have recently emerged to account for the effects of multiple genes, or a gene’s nonlinear effects, simultaneously. With the absence of the power analysis for these MV-TWAS methods, it would be of interest to investigate whether one can gain or lose power by using the newly proposed MV-TWAS instead of UV-TWAS. In this paper, we first outline a general method for sample size/power calculations for two-sample TWAS, then use real data-the Alzheimer’s Disease Neuroimaging Initiative (ADNI) expression quantitative trait loci (eQTL) data and the Genotype-Tissue Expression (GTEx) eQTL data for stage 1, the International Genomics of Alzheimer’s Project Alzheimer’s disease (AD) GWAS summary data and UK Biobank (UKB) individual-level data for stage 2-to empirically address these questions. Our most important conclusions are the following. First, a sample size of a few thousands (~8000) would suffice in stage 1, where the power of TWAS would be more determined by cis-heritability of gene expression. Second, as in the general case of simple regression versus multiple regression, the power of MV-TWAS may be higher or lower than that of UV-TWAS, depending on the specific relationships among the GWAS trait and multiple genes (or linear and nonlinear terms of the same gene’s expression levels), such as their correlations and effect sizes. Interestingly, several top genes with large power gains in MV-TWAS (over that in UV-TWAS) were known to be (and in our data more significantly) associated with AD. We also reached similar conclusions in an application to the GTEx whole blood gene expression data and UKB GWAS data of high-density lipoprotein cholesterol. The proposed method and the conclusions are expected to be useful in planning and designing future TWAS and other related studies (e.g., Proteome- or Metabolome-Wide Association Studies) when determining the sample sizes for the two stages.

PMID:35766062 | DOI:10.1002/gepi.22491

Genet Epidemiol. 2022 Jun 29. doi: 10.1002/gepi.22461. Online ahead of print.

ABSTRACT

Penalized variable selection for high-dimensional longitudinal data has received much attention as it can account for the correlation among repeated measurements while providing additional and essential information for improved identification and prediction performance. Despite the success, in longitudinal studies, the potential of penalization methods is far from fully understood for accommodating structured sparsity. In this article, we develop a sparse group penalization method to conduct the bi-level gene-environment (G ×$times $ E) interaction study under the repeatedly measured phenotype. Within the quadratic inference function framework, the proposed method can achieve simultaneous identification of main and interaction effects on both the group and individual levels. Simulation studies have shown that the proposed method outperforms major competitors. In the case study of asthma data from the Childhood Asthma Management Program, we conduct G ×$times $ E study by using high-dimensional single nucleotide polymorphism data as genetic factors and the longitudinal trait, forced expiratory volume in 1 s, as the phenotype. Our method leads to improved prediction and identification of main and interaction effects with important implications.

PMID:35766061 | DOI:10.1002/gepi.22461