Category: Statistics

Am J Cancer Res. 2024 Dec 15;14(12):5851-5862. doi: 10.62347/ZWAM1063. eCollection 2024.

ABSTRACT

OBJECTIVE: To analyze the clinical characteristics and molecular biomarkers of adult T-cell lymphoblastic lymphoma (T-LBL) to identify prognostic factors, and to evaluate the efficacy of different chemotherapy regimens, providing a basis for optimizing treatment strategies for T-LBL.

METHODS: A total of 89 Patients aged 18-72 years with T-LBL, confirmed via histopathological examination of lymph nodes, extranodal tissues, or bone marrow, were retrospectively included. Clinical data, treatment details, and mutational profiles were collected. Prognostic factors were assessed based on clinical and molecular characteristics, and the efficacy and safety of two chemotherapy regimens were compared. Descriptive statistics were used to analyze the disease spectrum.

RESULTS: Most patients (84.00%) presented with advanced disease (stages III-IV). Mediastinal invasion was observed in 63 patients (70.80%), and 59 patients (66.30%) exhibited B symptoms. Bone marrow involvement occurred in 19 patients (21.20%), and bulky mediastinum (>10 cm) was present in 50 patients (56.18%). Mutations were detected in 29 patients, with NOTCH1 being the most frequently mutated gene, followed by PHF-6, JAK-1, JAK-3, IL-7R, and TP53. The complete response (CR) rate was 51.69%. The 3-year overall survival (OS) and progression-free survival (PFS) rates were 74.9% and 58.80%, respectively. Multivariate analysis identified female sex, lack of CR, and elevated lactate dehydrogenase (LDH) levels (>2× normal) as independent predictors of poor OS (58.25%). Chemotherapy regimens, LDH levels, and sex were independent prognostic factors for PFS (21.24%).

CONCLUSION: T-LBL is characterized by high-frequency gene mutations across multiple signaling pathways. Mediastinal invasion (70.80%) and extranodal involvement (39.33%) were prevalent in Chinese patients and were associated with poor prognosis. Combined assessment of clinical and molecular features allows for improved prognostic stratification and facilitates the development of targeted therapies for high-risk patients.

PMID:39803658 | PMC:PMC11711535 | DOI:10.62347/ZWAM1063

Am J Cancer Res. 2024 Dec 15;14(12):5628-5643. doi: 10.62347/ILIJ7959. eCollection 2024.

ABSTRACT

Breast cancer is one of the malignant tumors that seriously threaten women’s health, and early diagnosis and detection of breast cancer are crucial for effective treatment. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is an important diagnostic tool that allows for the dynamic observation of blood flow characteristics of breast tumors, including small lesions within the affected tissue. Currently, it is widely used in clinical practice and has been shown promising prospects. This study included a total of 1,987 patients who underwent breast surgery at Huangpu Branch, Shanghai Ninth People’s Hospital, Shanghai Jiaotong University School of Medicine from January 1, 2019 to December 31, 2019. Comprehensive patient information was collected, including ultrasound, mammography findings, physical examination details, age, family history, and pathological diagnoses. The least absolute shrinkage and selection operator (LASSO) algorithm was employed to assign values to the x variables, facilitating the construction and validation of the LASSO model group. Receiver operating characteristic curves were generated using support vector machines to determine the area under the curve (AUC), as well as to assess sensitivity and specificity. There were no statistically significant differences (P>0.05) in average age, body mass index, tumor location, or tumor benignity/malignancy between the training and test sets. The AUC, sensitivity, and specificity of mammography for predicting the benignity or malignancy of breast tumors were 0.83, 86.96%, and 76%, respectively. In comparison, the AUC, sensitivity, and specificity of DCE-MRI for the same predictions were 0.91, 91.3%, and 88%, respectively. The predictive performance of DCE-MRI was significantly higher than that of mammography (P<0.05). In conclusion, both mammography and DCE-MRI demonstrated high AUC, sensitivity, and specificity in predicting the benignity or malignancy of breast tumors. However, DCE-MRI showed superior predictive performance, making it a valuable tool for the early detection of clinical breast cancer with potential for broader clinical application.

PMID:39803643 | PMC:PMC11711528 | DOI:10.62347/ILIJ7959

Heart Rhythm O2. 2024 Oct 5;5(12):951-956. doi: 10.1016/j.hroo.2024.09.018. eCollection 2024 Dec.

ABSTRACT

BACKGROUND: Atrial fibrillation (AF) has a significant impact on health and quality of life. The relationship of AF burden and temporal patterns of AF on patient symptoms, outcomes, and healthcare utilization is unknown. Insertable cardiac monitors (ICMs) are a strategic and as yet untapped, tool to investigate these relationships.

OBJECTIVE: The DEFINE Atrial Fibrillation (DEFINE AFib) study will evaluate how AF burden and patterns are associated with changes in AF-related healthcare utilization (AFHCU) and patient-reported quality of life.

METHODS: This is a prospective, observational, multicenter study with a unique design that supports a complete method of assessing AF as a multifactorial disease. Patients with AF implanted with an ICM will be enrolled in the study and managed through an app-based research platform on their smartphone. Patients will be remotely monitored and patient-reported outcomes will be collected via the app. AFHCU will be confirmed via the participant’s medical record.

RESULTS: The primary analysis will evaluate whether summary and episodic measurements collected by ICMs are associated with changes in AFHCU. Secondary analyses will determine the relationship between AF characteristics and quality of life, timing and severity of AF-related complications, patient engagement, reliability of patient-reported outcomes, data from other digital rhythm detectors, and heterogeneity in care quality and AFHCU.

CONCLUSION: The DEFINE AFib study will provide valuable insights into the association between dynamic measures of AF and AFHCU in a patient population with known AF. The results may demonstrate the impact of ICM-detected AF on patient outcomes and help isolate novel AF patterns predictive of clinical risk.

PMID:39803627 | PMC:PMC11721724 | DOI:10.1016/j.hroo.2024.09.018

Heart Rhythm O2. 2024 Sep 26;5(12):942-950. doi: 10.1016/j.hroo.2024.09.011. eCollection 2024 Dec.

ABSTRACT

BACKGROUND: There is consensus on the safety of standard dose direct oral anticoagulants (DOACs) for stroke prevention in patients undergoing cardioversion of atrial fibrillation (AF), but outcomes of reduced dose DOACs in this setting remain unclear.

OBJECTIVE: This systematic review and meta-analysis aimed to compare the rate of cardioversion-associated thromboembolic events between patients taking reduced dose DOACs and those receiving standard dose anticoagulation.

METHODS: A systematic search was conducted for studies published between January 1, 2009, and February 16, 2024 in PubMed, Embase, and Cochrane Central Register of Controlled Trials. The included studies compared the rate of thromboembolic events in patients with AF undergoing cardioversion on reduced dose DOACs with the rate in those on standard dose anticoagulation. Odds ratios were pooled with a random effects model.

RESULTS: We identified 2 randomized controlled trials and 8 cohort studies, which included 5212 patients with AF who underwent cardioversion on anticoagulation (1010 patients on reduced dose DOACs and 4202 patients on standard dose anticoagulation). Follow-up ranged from 3 hours to 90 days after cardioversion. There was a numerically higher rate of thromboembolic events in patients undergoing cardioversion on reduced dose DOACs than in those on standard dose anticoagulation (0.69% vs 0.29%; odds ratio 1.98; 95% confidence interval 0.72-5.45; P = .19; I² = 0%); however, the difference was not statistically significant.

CONCLUSION: Our systematic review and meta-analysis suggests that there is a numerically higher risk of thromboembolic events in patients with AF undergoing cardioversion on reduced dose DOACs than in those on standard dose anticoagulation. However, the difference was not statistically significant. These findings raise concern about the safety of reduced dose DOACs in patients undergoing cardioversion.

PMID:39803618 | PMC:PMC11721732 | DOI:10.1016/j.hroo.2024.09.011

Heart Rhythm O2. 2024 Sep 26;5(12):925-935. doi: 10.1016/j.hroo.2024.09.010. eCollection 2024 Dec.

ABSTRACT

BACKGROUND: Prediction models for atrial fibrillation (AF) may enable earlier detection and guideline-directed treatment decisions. However, model bias may lead to inaccurate predictions and unintended consequences.

OBJECTIVE: The purpose of this study was to validate, assess bias, and improve generalizability of “UNAFIED-10,” a 2-year, 10-variable predictive model of undiagnosed AF in a national data set (originally developed using the Indiana Network for Patient Care regional data).

METHODS: UNAFIED-10 was validated and optimized using Optum de-identified electronic health record data set. AF diagnoses were recorded in the January 2018-December 2019 period (outcome period), with January 2016-December 2017 as the baseline period. Validation cohorts (patients with AF and non-AF controls, aged ≥40 years) comprised the full imbalanced and randomly sampled balanced data sets. Model performance and bias in patient subpopulations based on sex, insurance, race, and region were evaluated.

RESULTS: Of the 6,058,657 eligible patients (mean age 60 ± 12 years), 4.1% (n = 246,975) had their first AF diagnosis within the outcome period. The validated UNAFIED-10 model achieved a higher C-statistic (0.85 [95% confidence interval 0.85-0.86] vs 0.81 [0.80-0.81]) and sensitivity (86% vs 74%) but lower specificity (66% vs 74%) than the original UNAFIED-10 model. During retraining and optimization, the variables insurance, shock, and albumin were excluded to address bias and improve generalizability. This generated an 8-variable model (UNAFIED-8) with consistent performance.

CONCLUSION: UNAFIED-10, developed using regional patient data, displayed consistent performance in a large national data set. UNAFIED-8 is more parsimonious and generalizable for using advanced analytics for AF detection. Future directions include validation on additional data sets.

PMID:39803613 | PMC:PMC11721729 | DOI:10.1016/j.hroo.2024.09.010

Curr Epidemiol Rep. 2024 Jun;11(2):120-130. doi: 10.1007/s40471-024-00342-6. Epub 2024 Mar 20.

ABSTRACT

PURPOSE OF REVIEW: Our review critically examines research on trends in mental health among US adults following the COVID-19 pandemic’s onset and makes recommendations for research on the topic.

RECENT FINDINGS: Studies comparing pre-pandemic nationally representative government surveys (“benchmark surveys”) with pandemic-era non-benchmark surveys generally estimated 3-4-fold increases in the prevalence of adverse mental-health outcomes following the pandemic’s onset. However, studies analyzing trends in repeated waves of a single survey, which may carry a lower risk of bias, generally estimated much smaller increases in adverse outcomes. Likewise in our analysis of benchmark surveys, we estimated <1% increases in the prevalence of adverse outcomes from 2018/2019-2021. Finally, studies analyzing vital-statistics data estimated spiking fatal-overdose rates, but stable suicide rates.

SUMMARY: Although fatal-overdose rates increased substantially following the pandemic’s onset, evidence suggests the population prevalence of other adverse mental-health outcomes may have departed minimally from prior years’ trends, at least through 2021. Future research on trends through the pandemic’s later stages should prioritize leveraging repeated waves of benchmark surveys to minimize risk of bias.

PMID:39803610 | PMC:PMC11720142 | DOI:10.1007/s40471-024-00342-6

Drug Des Devel Ther. 2025 Jan 8;19:97-110. doi: 10.2147/DDDT.S500253. eCollection 2025.

ABSTRACT

BACKGROUND: YYD601 is a new dual delayed-release formulation of esomeprazole, developed to enhance plasma exposure and prolong the duration of acid suppression.

PURPOSE: This study aimed to evaluate the safety, pharmacokinetic (PK), and pharmacodynamic (PD) profiles of YYD601 20 mg following single and multiple oral administrations in healthy, fasting adult Koreans, and to compare these outcomes to those of the conventional esomeprazole 20 mg capsule.

METHODS: A randomized, open-label, two-period crossover study was conducted in 28 participants, who were divided into two treatment groups: one group received YYD601 20 mg, and the other received conventional esomeprazole 20 mg, once daily for five consecutive days. Blood samples for PK analysis were collected pre-dose and up to 24 hours post-dose. The primary PK parameters (AUC_last and AUC_τ) were evaluated. PD endpoints included integrated gastric acidity, percentage of time with intragastric pH > 4 over 24-hour and nighttime intervals, and percent change in serum gastrin levels after multiple dosing.

RESULTS: A total of 22 participants completed the study. YYD601 displayed more prolonged plasma concentration-time profiles than the conventional formulation, although the extent of the systemic exposure (AUC values) showed no statistically significant difference between the two formulations. With regard to the 24-hour gastric acid inhibition, YYD601 was comparable to the conventional formulation. The YYD601 showed a greater tendency for acid inhibition at night, as indicated by the percentage change of time with nocturnal acid breakthrough and other PD parameters. Both treatments were well tolerated, with no serious adverse events reported.

CONCLUSION: Through extended systemic exposure of esomeprazole, YYD601 produces gastric acid suppression that is comparable to that of the conventional esomeprazole formulation, with a greater tendency to suppress acid at night. YYD601 20 mg was safe and well tolerated following single and multiple oral administrations, supporting its use as an effective alternative to conventional esomeprazole therapy.

CLINICAL TRIAL REGISTRY: http://clinicaltrials.gov, NCT03985319 (Date of registration: May 29, 2019; Study period: between July 2019 and March 2020).

PMID:39803609 | PMC:PMC11725257 | DOI:10.2147/DDDT.S500253

Drug Des Devel Ther. 2025 Jan 6;19:65-66. doi: 10.2147/DDDT.S512114. eCollection 2025.

NO ABSTRACT

PMID:39803608 | PMC:PMC11721147 | DOI:10.2147/DDDT.S512114

Stat Probab Lett. 2025 Mar;218:110295. doi: 10.1016/j.spl.2024.110295. Epub 2024 Nov 22.

ABSTRACT

We introduce a generalized Bayesian credible set that can achieve any preassigned credible level, addressing a limitation of the current credible sets. This is achieved by exploiting a connection between the highest posterior density set and the Neyman-Pearson lemma.

PMID:39803594 | PMC:PMC11722005 | DOI:10.1016/j.spl.2024.110295

bioRxiv [Preprint]. 2024 Dec 30:2024.12.30.630778. doi: 10.1101/2024.12.30.630778.

ABSTRACT

A significant advancement in synthetic biology is the development of synthetic gene circuits with predictive Boolean logic. However, there is no universally accepted or applied statistical test to analyze the performance of these circuits. Many basic statistical tests fail to capture the predicted logic (OR, AND, etc.) and most studies neglect statistical analysis entirely. As synthetic gene circuits shift toward advanced applications, primarily in computing, biosensing, and human health, it is critical to standardize the statistical methods used to evaluate gate success. Here, we propose the application of a linear mixed effects model to analyze and quantify genetic Boolean logic gate performance. First, we analyzed 144 currently published Boolean logic gates for trends and used unsupervised machine learning (k-means clustering) to validate the statistical model. Next, we utilized the model to generate estimates for the fixed effect of the ON state, β, as a general descriptor of the Boolean nature of a circuit and used Monte Carlo simulations to recommend sample sizes for evaluating gate performance. Finally, we examined β as a holistic metric for circuit performance using a series of nested repressor OR gates with intentionally degraded performance. We observed a linear correlation between β and the predicted translation rate, highlighting the use of β for the forward design of new Boolean gates. In summary, we utilized a linear mixed effects model to describe synthetic gene circuits and determined that the fixed effect, β, is an appropriate descriptor of gate behavior that can be used to statistically evaluate performance.

PMID:39803539 | PMC:PMC11722350 | DOI:10.1101/2024.12.30.630778