Category: Statistics

Cancer Med. 2024 Feb;13(4):e6948. doi: 10.1002/cam4.6948.

ABSTRACT

BACKGROUND: The purpose of this study was to investigate associations between self-reported distress (anxiety/depression) and satisfaction with and desire for virtual follow-up (VFU) care among cancer patients during and beyond the COVID-19 pandemic.

METHODS: Breast and prostate cancer patients receiving VFU at an urban cancer centre in Toronto, Canada completed an online survey on their sociodemographic, clinical, and technology, characteristics and experience with and views on VFU. EQ5D-5 L was used to assess distress. Statistical models adjusted for age, gender, education, income and Internet confidence.

RESULTS: Of 352 participants, average age was 65 years, 48% were women,79% were within 5 years of treatment completion, 84% had college/university education and 74% were confident Internet users. Nearly, all (98%) had a virtual visit via phone and 22% had a virtual visit via video. The majority of patients (86%) were satisfied with VFU and 70% agreed that they would like VFU options after the COVID-19 pandemic. Participants who reported distress and who were not confident using the Internet for health purposes were significantly less likely to be satisfied with VFU (OR = 0.4; 95% CI: 0.2-0.8 and OR = 0.19; 95% CI: 0.09-0.38, respectively) and were less likely to desire VFU option after the COVID-19 pandemic (OR = 0.49; 95% CI: 0.30-0.82 and OR = 0.41; 95% CI: 0.23-0.70, respectively).

CONCLUSIONS: The majority of respondents were satisfied with VFU and would like VFU options after the COVID-19 pandemic. Future research should determine how to optimize VFU options for cancer patients who are distressed and who are less confident using virtual care technology.

PMID:38466233 | DOI:10.1002/cam4.6948

Health Lit Res Pract. 2024 Jan;8(1):e38-e46. doi: 10.3928/24748307-20240220-01. Epub 2024 Mar 7.

ABSTRACT

BACKGROUND: Research suggests that younger adult African American people (age 18-35 years) have more than double the risk of having a stroke than White people. Stroke risk education is lacking for this cohort; there is a dearth of materials that are targeted and focused for young adult African Americans. There is also little research on developing and testing age and culturally appropriate health literate materials that may help this population better understand personal risk factors for stroke.

OBJECTIVE: The aim of this study was to understand factors to guide creating and disseminating plain language health messages about stroke risk awareness among young adult African Americans.

METHODS: African American participants age 18 years and older completed an online survey (N = 413). Descriptive statistics, one-way analysis of variance, and two-step cluster analyses were used to evaluate stroke risk awareness, perceived risk of stroke, message creation factors, and online health information seeking behavior. Open-ended survey items described modifiable and non-modifiable reasons for perceived risk of stroke.

KEY RESULTS: Participants reported differences on overall stroke risk factor awareness by perceived risk of stroke was significant (F[2, 409] = 4.91, p = .008) with the very low/low group (M = 1.66, p < .01), showing significantly lower overall stroke risk factor awareness compared to the moderate and high/very high groups. Both respondents who thought their stroke risk was very low/low and moderate/high/very high commented about family history (54.1% and 45.9%, respectively) as the reason and 88.2% of very low/low commented that they did not have risk factors for stroke because they were young. Cluster analysis indicated the Mostly Clear Preferences cluster was more likely to select mostly/very on positive, informational, and long-term messages and medical authority sources. The largest of three clusters reported medical sources as the highest rated source for both finding and trusting health information (47.2%, n = 195).

CONCLUSION: Young adult African Americans have a scarce understanding of modifiable stroke risk factors; health education materials should focus on positive information messaging that shows a long-term result and is presented by a medical authority. We did not observe any age or sex differences among the data, which suggests different message modalities may not be needed. [HLRP: Health Literacy Research and Practice. 2024;8(1):e38-e46.].

PMID:38466224 | DOI:10.3928/24748307-20240220-01

Anesthesiology. 2024 Mar 11. doi: 10.1097/ALN.0000000000004969. Online ahead of print.

ABSTRACT

BACKGROUND: Prospective interventional trials and retrospective observational analyses provide conflicting evidence regarding the relationship between propofol versus inhaled volatile general anesthesia and long-term survival after cancer surgery. In specific, bladder cancer surgery lacks prospective clinical trial evidence.

METHODS: Data on bladder cancer surgery performed under general anesthesia between 2014 and 2021 from The National Quality Registry for Urinary Tract and Bladder Cancer and the Swedish Perioperative Registry were record-linked. Overall survival was compared between patients receiving propofol or inhaled volatile for anesthesia maintenance. The minimum clinically important difference was defined as a five-percentage point difference in five-year survival.

RESULTS: Of 7,571 subjects, 4,519 (59.7%) received an inhaled volatile anesthetic and 3,052 (40.3%) received propofol for general anesthesia maintenance. The two groups were quite similar in most respects but differed in ASA physical status and tumor stage. Propensity score matching was used to address treatment bias. Survival did not differ during follow-up (median 45 months [interquartile range, 33 to 62]) in neither the full unmatched cohort, nor following 1:1 propensity score matching (3,052 matched pairs). The Kaplan-Meier adjusted five-year survival rates in the matched cohort were 898/3,052, 67.5% (65.7-69.3) for propofol and 852/3,052, 68.5% (66.7-70.4) for inhaled volatile general anesthesia, respectively (hazard ratio 1.05 [95% CI: 0.96 to 1.15], P = 0.332). A sensitivity analysis restricted to 1,766 propensity score matched pairs of patients who received only one general anesthetic during the study period did not demonstrate a difference in survival; Kaplan-Meier adjusted five-year-survival rates were 521/1,766, 67.1% (64.7-69.7) and 482/1,766, 68.9% (66.5-71.4) for propofol and inhaled volatile general anesthesia, respectively (hazard ratio 1.09 [95% CI: 0.97 to 1.23], P = 0.139).

CONCLUSIONS: Among patients undergoing bladder cancer surgery under general anesthesia, there was no statistically significant difference in long-term overall survival associated with the choice of propofol or an inhaled volatile maintenance.

PMID:38466217 | DOI:10.1097/ALN.0000000000004969

Am J Phys Med Rehabil. 2024 Feb 29. doi: 10.1097/PHM.0000000000002453. Online ahead of print.

ABSTRACT

OBJECTIVE: To investigate the effect of Sensorimotor Training (SMT) on gait, ankle joint proprioception, and quality of life in Diabetic Peripheral Neuropathy (DPN) patients.

DESIGN: A prospective, single-blind, randomized controlled experiment was performed. Forty patients with DPN aged 50 to 65 yrs were distributed randomly into two groups, the SMT group (n = 20) and the control group (n = 20). Both groups attended awareness sessions about diabetes and foot care for 30 minutes, every two weeks. Moreover, the SMT group received 6wk (3 days/week) of SMT. Spatiotemporal gait parameters, proprioception accuracy of the ankle joint, and quality of life were measured before and after 6 weeks of intervention.

RESULTS: Regarding baseline data, no significant differences were identified among groups (p > 0.05). After 6wk intervention, the SMT group exhibited significant improvements in all outcome variables (p < 0.001), while the control group showed significant changes in quality of life only (p = 0.03). Comparing groups after intervention reveals statistically significant differences in all measured variables in favor of the SMT group (p < 0.001).

CONCLUSIONS: Sensorimotor training may improve spatiotemporal gait parameters, ankle joint proprioception, and quality of life of patients with DPN.

PMID:38466203 | DOI:10.1097/PHM.0000000000002453

J Sep Sci. 2024 Mar;47(5):e2300923. doi: 10.1002/jssc.202300923.

ABSTRACT

Regorafenib is a small-molecule tyrosine kinase inhibitor with severe hepatotoxicity. It undergoes metabolism mainly by CYP3A4 to generate active metabolites regorafenib-N-oxide (M2) and N-desmethyl-regorafenib-N-oxide (M5). Wuzhi capsule (WZC) is an herbal preparation derived from Schisandra sphenanthera and is potentially used to prevent regorafenib-induced hepatotoxicity. This study aims to explore the effect of WZC on the pharmacokinetics of regorafenib in rats. An efficient and sensitive liquid chromatography-tandem mass spectrometry method was developed to quantitatively determine regorafenib and its main metabolites in rat plasma. The proposed method was applied to the pharmacokinetic study of regorafenib in rats, with or without WZC. Coadministration of regorafenib with WZC resulted in a prolonged mean residence time (MRT) of the parent drug but had no statistically significant difference in other pharmacokinetic parameters. While for the main metabolites of regorafenib, WZC decreased the area under the curve and maximum concentration (C_max ), delayed the time to reach C_max , and prolonged the MRT of M2 and M5. These results indicate that WZC delayed and inhibited the metabolism of regorafenib to M2 and M5 by suppressing CYP3A4. Our study provides implications for the rational use of the WZC-regorafenib combination in clinical practice.

PMID:38466147 | DOI:10.1002/jssc.202300923

J Head Trauma Rehabil. 2024 Mar 11. doi: 10.1097/HTR.0000000000000937. Online ahead of print.

ABSTRACT

OBJECTIVE: Cognitive behavioral therapy for insomnia (CBT-I) is the gold standard treatment for insomnia, but there is limited evidence on the treatment effect of CBT-I in individuals after a concussion. Therefore, the main purpose of this study was to evaluate the treatment effect of CBT-I on sleep outcomes and postconcussion symptoms.

SETTING: This study was conducted at an academic institution. The CBT-I sessions were conducted using a teleconferencing system (Zoom).

PARTICIPANTS: Participants were eligible to participate if they were at least 4 weeks post- concussion, aged 18 to 64 years, and scored 10 or more on the Insomnia Severity Index. A total of 40 people were enrolled; 32 participants were included in analyses.

DESIGN: This was a randomized controlled wait-list study. Participants were randomized into starting the CBT-I intervention immediately after the baseline assessment or into the wait-list group for 6 weeks before starting CBT-I. Assessments were performed at baseline, 6, 12, and 18 weeks.

MAIN MEASURES: The primary outcome was the Insomnia Severity Index. Secondary measures included the Pittsburg Sleep Quality Index, Post-Concussion Symptom Scale, and Beck Depression and Anxiety Inventories. Statistical analyses included a repeated-measures analysis of variance, t tests, and mixed linear regression modeling.

RESULTS: There was a group-by-time interaction for the sleep outcomes but not for the concussion or mood outcomes. Differences were seen between groups on sleep outcomes, symptom severity, and depression. The treatment effect was maintained following CBT-I for all outcomes. Improvement in sleep outcomes was predictive of improvement in postconcussion symptom severity and number of symptoms.

CONCLUSIONS: CBT-I reduces insomnia in individuals with concussions, and improved sleep was associated with lower postconcussion and mood symptoms. These effects were maintained 6 to 12 weeks following the intervention.

PMID:38466122 | DOI:10.1097/HTR.0000000000000937

Mol Biol Evol. 2024 Mar 11:msae053. doi: 10.1093/molbev/msae053. Online ahead of print.

ABSTRACT

Ancient DNA can directly reveal the contribution of natural selection to human genomic variation. However, while the analysis of ancient DNA has been successful at identifying genomic signals of selection, inferring the phenotypic consequences of that selection has been more difficult. Most trait-associated variants are non-coding, so we expect that a large proportion of the phenotypic effects of selection will also act through non-coding variation. Since we cannot measure gene expression directly in ancient individuals, we used an approach (Joint-Tissue Imputation; JTI) developed to predict gene expression from genotype data. We tested for changes in the predicted expression of 17,384 protein coding genes over a time transect of 4500 years using 91 present-day and 616 ancient individuals from Britain. We identified 28 genes at seven genomic loci with significant (FDR < 0.05) changes in predicted expression levels in this time period. We compared the results from our transcriptome-wide scan to a genome-wide scan based on estimating per-SNP selection coefficients from time series data. At five previously identified loci, our approach allowed us to highlight small numbers of genes with evidence for significant shifts in expression from peaks that in some cases span tens of genes. At two novel loci (SLC44A5 and NUP85), we identify selection on gene expression not captured by scans based on genomic signatures of selection. Finally we show how classical selection statistics (iHS and SDS) can be combined with JTI models to incorporate functional information into scans that use present-day data alone. These results demonstrate the potential of this type of information to explore both the causes and consequences of natural selection.

PMID:38466119 | DOI:10.1093/molbev/msae053

Cereb Cortex. 2024 Mar 1;34(3):bhae065. doi: 10.1093/cercor/bhae065.

ABSTRACT

Mild cognitive impairment plays a crucial role in predicting the early progression of Alzheimer’s disease, and it can be used as an important indicator of the disease progression. Currently, numerous studies have focused on utilizing the functional brain network as a novel biomarker for mild cognitive impairment diagnosis. In this context, we employed a graph convolutional neural network to automatically extract functional brain network features, eliminating the need for manual feature extraction, to improve the mild cognitive impairment diagnosis performance. However, previous graph convolutional neural network approaches have primarily concentrated on single modes of brain connectivity, leading to a failure to leverage the potential complementary information offered by diverse connectivity patterns and limiting their efficacy. To address this limitation, we introduce a novel method called the graph convolutional neural network with multimodel connectivity, which integrates multimode connectivity for the identification of mild cognitive impairment using fMRI data and evaluates the graph convolutional neural network with multimodel connectivity approach through a mild cognitive impairment diagnostic task on the Alzheimer’s Disease Neuroimaging Initiative dataset. Overall, our experimental results show the superiority of the proposed graph convolutional neural network with multimodel connectivity approach, achieving an accuracy rate of 92.2% and an area under the Receiver Operating Characteristic (ROC) curve of 0.988.

PMID:38466115 | DOI:10.1093/cercor/bhae065

Biol Open. 2024 Mar 11:bio.060286. doi: 10.1242/bio.060286. Online ahead of print.

ABSTRACT

Distinguishing clinical subgroups for patients suffering with diseases characterized by a wide phenotypic spectrum is essential for developing precision therapies. Patients with gain-of-function (GOF) variants in the SCN8A gene exhibit substantial clinical heterogeneity, viewed historically as a linear spectrum ranging from mild to severe. To test for hidden clinical subgroups, we applied two machine learning algorithms to analyze a dataset of patient features collected by the International SCN8A Patient Registry. We utilized two research methodologies: a supervised approach that incorporated feature severity cutoffs based on clinical conventions, and an unsupervised approach employing an entirely data-driven strategy. Both approaches found statistical support for three distinct subgroups and were validated by correlation analyses utilizing external variables. However, distinguishing features of the three subgroups within each approach were not concordant, suggesting a more complex phenotypic landscape. The unsupervised approach yielded strong support for a model involving three partially-ordered subgroups rather than a linear spectrum. Application of these machine-learning approaches may lead to improved prognosis and clinical management of individuals with SCN8A GOF variants and provide insights into the underlying mechanisms of the disease.

PMID:38466077 | DOI:10.1242/bio.060286

Altern Ther Health Med. 2024 Mar 8:AT9918. Online ahead of print.

ABSTRACT

BACKGROUND: Colon cancer is a common malignant tumor that often leads to intestinal obstruction, resulting in significant morbidity and mortality. Early and accurate diagnosis of colon cancer and associated ileus is crucial for timely treatment and improved patient outcomes. Various diagnostic methods, including MSCT and MRI, are currently used in clinical practice. However, the optimal imaging approach for accurate diagnosis remains uncertain.

OBJECTIVE: To study the value and accuracy of multi-slice spiral CT (MSCT) combined with magnetic resonance imaging (MRI) in diagnosing colon cancer obstruction.

METHODS: A retrospective analysis was performed on 100 cases of colon cancer and ileus patients admitted to the Hai’an Hospital of Chinese Medicine from January 2019 to July 2020. The cases were randomly divided into control and experimental groups, with 50 cases in each. The control group was diagnosed with MSCT, and the experimental group was diagnosed with MRI based on the control group. The positive and negative detection rates, test accuracy, sensitivity, and specificity were compared between the 2 groups. The area under the curve (AUC), quality of life (QOL) score, and mental status scale in non-psychiatric settings (MSSNS) score were calculated with the receiver operator characteristic curve (ROC) and compared between the 2 groups.

RESULTS: The test accuracy, positive detection rate, negative detection rate, test specificity, sensitivity, and AUC of the experimental group were significantly higher than those of the control group, and the results were statistically significant (P < .05). There was no significant difference in the QOL and the MSSNS scores between the 2 groups (P > .05).

CONCLUSION: MSCT combined with MRI has a high application value in diagnosing colon cancer obstruction patients, and can significantly improve the test’s accuracy, specificity and sensitivity.

PMID:38466066