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Nevin Manimala Statistics

AJGM: Joint Learning of Heterogeneous Gene Networks with Adaptive Graphical Model

Bioinformatics. 2025 Mar 12:btaf096. doi: 10.1093/bioinformatics/btaf096. Online ahead of print.

ABSTRACT

MOTIVATION: Inferring gene networks provides insights into biological pathways and functional relationships among genes. When gene expression samples exhibit heterogeneity, they may originate from unknown subtypes, prompting the utilization of mixture Gaussian graphical model for simultaneous subclassification and gene network inference. However, this method overlooks the heterogeneity of network relationships across subtypes and does not sufficiently emphasize shared relationships. Additionally, GGM assumes data follows a multivariate Gaussian distribution, which is often not the case with zero-inflated scRNA-seq data.

RESULTS: We propose an Adaptive Joint Graphical Model (AJGM) for estimating multiple gene networks from single-cell or bulk data with unknown heterogeneity. In AJGM, an overall network is introduced to capture relationships shared by all samples. The model establishes connections between the subtype networks and the overall network through adaptive weights, enabling it to focus more effectively on gene relationships shared across all networks, thereby enhancing the accuracy of network estimation. On synthetic data, the proposed approach outperforms existing methods in terms of sample classification and network inference, particularly excelling in the identification of shared relationships. Applying this method to gene expression data from triple-negative breast cancer confirms known gene pathways and hub genes, while also revealing novel biological insights.

AVAILABILITY AND IMPLEMENTATION: The Python code and demonstrations of the proposed approaches are available at https://github.com/yyytim/AJGM, and the software is archived in Zenodo with DOI: 10.5281/zenodo.14740972.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:40073230 | DOI:10.1093/bioinformatics/btaf096

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Nevin Manimala Statistics

A statistical framework for analysis of trial-level temporal dynamics in fiber photometry experiments

Elife. 2025 Mar 12;13:RP95802. doi: 10.7554/eLife.95802.

ABSTRACT

Fiber photometry has become a popular technique to measure neural activity in vivo, but common analysis strategies can reduce the detection of effects because they condense within-trial signals into summary measures, and discard trial-level information by averaging across-trials. We propose a novel photometry statistical framework based on functional linear mixed modeling, which enables hypothesis testing of variable effects at every trial time-point, and uses trial-level signals without averaging. This makes it possible to compare the timing and magnitude of signals across conditions while accounting for between-animal differences. Our framework produces a series of plots that illustrate covariate effect estimates and statistical significance at each trial time-point. By exploiting signal autocorrelation, our methodology yields joint 95% confidence intervals that account for inspecting effects across the entire trial and improve the detection of event-related signal changes over common multiple comparisons correction strategies. We reanalyze data from a recent study proposing a theory for the role of mesolimbic dopamine in reward learning, and show the capability of our framework to reveal significant effects obscured by standard analysis approaches. For example, our method identifies two dopamine components with distinct temporal dynamics in response to reward delivery. In simulation experiments, our methodology yields improved statistical power over common analysis approaches. Finally, we provide an open-source package and analysis guide for applying our framework.

PMID:40073228 | DOI:10.7554/eLife.95802

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Nevin Manimala Statistics

Assisted Reproductive Technologies in Latin America: the Latin American Registry, 2021

JBRA Assist Reprod. 2025 Mar 12;29(1):167-190. doi: 10.5935/1518-0557.20240107.

ABSTRACT

RESEARCH QUESTION: What are the trends and impact of new technologies on the effectiveness and safety of assisted reproductive technology (ART) performed in Latin America during 2021?

DESIGN: This was a retrospective collection of cycle-based multinational data obtained from ART procedures performed by 204 accredited institutions in 16 countries.

RESULTS: In total 127,351 initiated cycles resulted in 20,032 deliveries and 22,708 births. ART utilization showed great variability, from 623.5 cycles/million inhabitants in Uruguay to fewer than 35 in Guatemala and El Salvador. The proportion of women aged ≥40 years increased to 35.8%, while that of women ≤34 years dropped to 23.9%. Nonetheless, the proportion of single-embryo transfers (SET) increased from 11.9% in the previous decade to 42.4% in 2021. Of 22,708 babies born, 76.8% were singletons, 22.3% twins and 1.0% triplets or more. Intracytoplasmic sperm injection represented 84.5% of fertilization techniques, and blastocyst transfer increased from 49.6% in 2016 to 79.3% in 2021. The delivery rate after fresh blastocyst elective SET was significantly higher than after the transfer of one frozen embryo from a freeze-all cycle (p<0.0001). The number of aspirations leading to preimplantation genetic testing has increased 2.8 times in 5 years and significantly increased delivery rates/transfer at all ages, including in oocyte donation (p≤0.002), and reduced miscarriage in women ≥35 years old. In oocyte donation, delivery rates after the fresh transfer of embryos from vitrified-warmed oocyte cycles generated similar outcomes to frozen embryo transfer. Perinatal mortality increased from 7.7 ‰ in singletons to 21.3 ‰ in twins.

CONCLUSIONS: The systematic collection of cycle-based multinational data contributes to cooperative sustained development and helps implement evidence-based reproductive decisions.

PMID:40073223 | DOI:10.5935/1518-0557.20240107

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Nevin Manimala Statistics

Global prevalence of post-COVID-19 condition: a systematic review and meta-analysis of prospective evidence

Health Promot Chronic Dis Prev Can. 2025 Mar;45(3):112-138. doi: 10.24095/hpcdp.45.3.02.

ABSTRACT

INTRODUCTION: We investigated the prevalence of new or persistent manifestations experienced by COVID-19 survivors at 3 or more months after their initial infection, collectively known as post-COVID-19 condition (PCC).

METHODS: We searched four electronic databases and major grey literature resources for prospective studies, systematic reviews, authoritative reports and population surveys. A random-effects meta-analysis pooled the prevalence data of 22 symptoms and outcomes. The GRADE approach was used to assess the certainty of evidence. PROSPERO CRD42021231476.

RESULTS: Of 20 731 identified references, 194 met our inclusion criteria. These studies followed 483 531 individuals with confirmed COVID-19 diagnosis over periods of up to 2 years. Most focused on adults, nearly two-thirds were conducted in Europe and 63% were of high or moderate quality. The supplementary search identified 17 systematic reviews, five authoritative reports and four population surveys that reported on PCC prevalence. Our analysis revealed that more than half of COVID-19 survivors experienced one or more symptoms more than a year after their initial infection. The most common symptoms were fatiguedyspneamemory, sleep or concentration disturbances; depressionand pain. Limitation in returning to work was the most common outcome. Prevalence tended to be higher among females, individuals hospitalized during their initial infection and those who experienced severe COVID-19 illness.

CONCLUSION: PCC presents a significant health burden, affecting some groups more than others. This information will help inform health care system policies and services for people living with PCC and those caring for them.

PMID:40073162 | DOI:10.24095/hpcdp.45.3.02

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Nevin Manimala Statistics

The Dermatologist is Out? Assessment of Dermatologists in Ontario Accepting Ontario Health Insurance Plan (OHIP) Referrals for Hair Loss Evaluation

J Cutan Med Surg. 2025 Mar 12:12034754251324941. doi: 10.1177/12034754251324941. Online ahead of print.

ABSTRACT

BACKGROUND: The Ontario Health Insurance Plan (OHIP) insures appointments for the assessment and diagnosis of hair loss, or alopecia. Although anecdotal, discussion suggests that, increasingly, dermatologists decline to see referrals of this nature. There has been a lack of objective surveillance to determine the proportion of dermatologists in practice who accept referrals for this concern.

OBJECTIVES: This study investigated the proportion of dermatologists in Ontario accepting OHIP referrals for hair loss. Secondary objectives included wait times, consultation fees for non-OHIP visits, and factors affecting referral acceptance or rejection.

METHODS: A cross-sectional telephone survey was conducted, in which 284 dermatologists’ offices listed by the College of Physicians and Surgeons of Ontario (CPSO) were contacted. The study investigated the acceptance of OHIP referrals for hair loss, wait times, additional referral requirements, and private consultation fees. Descriptive statistics were employed to summarize data.

RESULTS: Of the 284 offices contacted, 38.38% (109/284) accepted OHIP referrals for hair loss, 48.59% (138/284) did not, and 13.03% (37/284) were unavailable for contact. The average wait time for offices that accepted referrals was 4.51 ± 4.07 months. Non-OHIP consultation fees ranged from $135 to $299 CAD. Some offices limited acceptance to specific conditions such as alopecia areata and male androgenetic alopecia.

CONCLUSION: A total of 48.59% of dermatologists in Ontario do not accept OHIP referrals for hair loss, while the status of 13.03% remains unknown. This reality raises concerns about accessibility to care. Further research is needed to investigate factors influencing referral acceptance.

PMID:40072492 | DOI:10.1177/12034754251324941

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Nevin Manimala Statistics

Statistical inference on change points in generalized semiparametric segmented models

Biometrics. 2025 Jan 7;81(1):ujaf022. doi: 10.1093/biomtc/ujaf022.

ABSTRACT

The segmented model has significant applications in scientific research when the change-point effect exists. In this article, we propose a comprehensive semiparametric framework in segmented models to test the existence and estimate the location of change points in the generalized outcome setting. The proposed framework is based on a semismooth estimating equation for the change-point estimation and an average score-type test for hypothesis testing. The root-n consistency, asymptotic normality, and asymptotic efficiency of estimators for all parameters in the segmented model are rigorously studied. The distribution of the average score-type test statistics under the null hypothesis is rigorously derived. Extensive simulation studies are conducted to assess the numerical performance of the proposed change-point estimation method and the average score-type test. We investigate change-point effects of baseline glomerular filtration rate and body mass index on bleeding after intervention using data from Blue Cross Blue Shield. This application study successfully identifies statistically significant change-point effects, with the estimated values providing clinically meaningful insights.

PMID:40072490 | DOI:10.1093/biomtc/ujaf022

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Nevin Manimala Statistics

Long-term safety and effectiveness of fenfluramine in children and adults with Dravet syndrome

Epilepsia. 2025 Mar 12. doi: 10.1111/epi.18342. Online ahead of print.

ABSTRACT

OBJECTIVE: We analyzed the long-term safety and effectiveness of fenfluramine (FFA) in patients with Dravet syndrome (DS) in an open-label extension (OLE) study after participating in randomized controlled trials (RCTs) or commencing FFA de novo as adults.

METHODS: Patients with DS who participated in one of three RCTs or were 19 to 35 years of age and started FFA de novo were included. Key endpoints were: incidence of treatment-emergent adverse events (TEAEs) in the safety population, and median percentage change in monthly convulsive seizure frequency (MCSF) from the RCT baseline to end of study (EOS) in the modified intent-to-treat (mITT) population. Post hoc analyses compared effectiveness in patients on concomitant stiripentol (STP) vs those not taking STP, and assessed safety (TEAEs) and effectiveness (Clinical Global Impression-Improvement [CGI-I] scale ratings) in patients enrolled as adults.

RESULTS: A total of 374 patients, including 45 adults, received ≥1 FFA dose. Median FFA exposure was 824 days (range, 7-1280). TEAEs occurring in ≥10% of patients were pyrexia, nasopharyngitis, decreased appetite, seizure, decreased blood glucose, diarrhea, abnormal echocardiography (only physiologic regurgitation), upper respiratory tract infection, influenza, vomiting, and ear infection; no valvular heart disease or pulmonary arterial hypertension was observed over the OLE. In the mITT population (n = 324), median percentage change in MCSF from baseline to EOS was -66.8% (p < .001). The post hoc analyses of MCSF change from baseline to EOS in patients on concomitant STP (n = 75) was -36.2% vs -71.6% in those not on concomitant STP (n = 234) (p < .0001). In adult patients, 29 of 41 (70.7%) and 29 of 42 patients (69.1%) demonstrated clinically meaningful improvement on CGI-I at last visit as rated by caregivers and investigators, respectively.

SIGNIFICANCE: Our OLE study of FFA in patients with DS confirmed previous positive findings and extended the exposure up to 3.5 years. No new or unexpected safety signals were observed and FFA demonstrated sustained and clinically meaningful reduction in MCSF.

PMID:40072476 | DOI:10.1111/epi.18342

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Nevin Manimala Statistics

Novel Controlled Metabolic Accelerator for Obesity-Related HFpEF: The HuMAIN-HFpEF Randomized Clinical Trial

JAMA Cardiol. 2025 Mar 12. doi: 10.1001/jamacardio.2025.0103. Online ahead of print.

ABSTRACT

IMPORTANCE: Excess body fat plays a pivotal role in the pathogenesis of heart failure with preserved ejection fraction (HFpEF). HU6 is a novel, controlled metabolic accelerator that enhances mitochondrial uncoupling resulting in increased metabolism and fat-specific weight loss.

OBJECTIVE: To assess efficacy and safety of HU6 in reducing body weight, improving peak volume of oxygen consumption (VO2) and body composition among patients with obesity-related HFpEF.

DESIGN, SETTING, AND PARTICIPANTS: The Exploratory Phase 2A, Double-Blind, Placebo-Controlled Dose Escalation Study of Safety, Tolerability, Pharmacodynamics, and Pharmacokinetics of HU6 for Subjects With Obese HFpEF (HuMAIN-HFpEF) trial was a multicenter, dose-escalation randomized clinical trial among patients with chronic stable HFpEF and obesity. Data were analyzed from July to October 2024.

INTERVENTION: HU6 treatment for 19 weeks, starting at 150 mg per day and potentially up titrated to 450 mg per day based on safety and tolerability vs placebo.

MAIN OUTCOMES AND MEASURES: The primary end point was change in body weight.

RESULTS: Of 66 participants randomized (mean [SD] age, 64.5 [12] years; 38 female [58%]; mean [SD] weight, 110.9 [22.4] kg), 56 completed the trial. HU6 (vs placebo) significantly decreased weight (between-group difference, -2.86 kg; 95% CI, -4.68 to -1.04 kg; P = .003), total fat mass (between-group difference, -2.96 kg; 95% CI, -4.50 to -1.42 kg; P < .001), and percentage visceral fat (between-group difference,-1.3%; 95% CI, -2.1 to -0.5%; P = .003), with no significant loss of muscle mass. There were no statistically significant changes in peak VO2, 6-minute walk distance, Kansas City Cardiomyopathy Questionnaire score, high-sensitivity C-reactive protein level, N-terminal pro-brain natriuretic peptide level, or diastolic function. Serious adverse events were noted in 5 participants (4 in the HU6 group; 1 in the placebo group), including 1 death, all judged unrelated to treatment.

CONCLUSIONS AND RELEVANCE: Among patients with obesity-related HFpEF, treatment with HU6 for 19 weeks led to modest but statistically significant weight loss without significant changes in peak VO2. Larger trials of longer duration are warranted to determine whether longer-term administration of HU6 can improve exercise function, quality of life, and cardiovascular outcomes in this increasingly common disorder.

TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT05284617.

PMID:40072462 | DOI:10.1001/jamacardio.2025.0103

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Nevin Manimala Statistics

Expectancy Effects, Failure of Blinding Integrity, and Placebo Response in Trials of Treatments for Psychiatric Disorders: A Narrative Review

JAMA Psychiatry. 2025 Mar 12. doi: 10.1001/jamapsychiatry.2025.0085. Online ahead of print.

ABSTRACT

IMPORTANCE: Expectancy effects are significant confounding factors in psychiatric randomized clinical trials (RCTs), potentially affecting the interpretation of study results. This narrative review is the first, to our knowledge, to explore the relationship between expectancy effects, compromised blinding integrity, and the effects of active treatment/placebo in psychiatric RCTs. Additionally, we present statistical and experimental approaches that may help mitigate the confounding impact of expectancy effects. The review concludes with recommendations to enhance the reliability of RCTs in psychiatry.

OBSERVATIONS: The placebo response comprises both specific and nonspecific elements, with expectation being a key specific component. Evidence from experimental and clinical studies suggests that expectancy can influence treatment responses in RCTs. Blinding integrity may be compromised by perceived treatment efficacy and adverse effects, introducing bias into outcome assessments. Treatment expectations can lead to unblinding during RCTs, and meta-analytic data from studies in the fields of psychedelics and anxiety disorders indicate that this can influence effect sizes. Therefore, controlling for expectancy effects is essential when interpreting RCT results. Novel statistical methods, though still in need of further validation, offer strategies to address this issue. Another approach may involve experimental medicine models, which aim to develop objective improvement markers (readouts) less affected by expectancy effects.

CONCLUSIONS AND RELEVANCE: Expectancy effects represent a significant confound in psychiatric RCTs. We recommend collecting data on treatment expectations alongside monitoring blinding integrity to more accurately interpret study results. Additionally, developing objective readouts that are less confounded by expectancy effects offers another promising avenue for mitigating these confounding influences in psychiatric RCTs.

PMID:40072447 | DOI:10.1001/jamapsychiatry.2025.0085

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Nevin Manimala Statistics

Risk Prediction Models for Sentinel Node Positivity in Melanoma: A Systematic Review and Meta-Analysis

JAMA Dermatol. 2025 Mar 12. doi: 10.1001/jamadermatol.2025.0113. Online ahead of print.

ABSTRACT

IMPORTANCE: There is a need to identify the best performing risk prediction model for sentinel lymph node biopsy (SLNB) positivity in melanoma.

OBJECTIVE: To comprehensively review the characteristics and discriminative performance of existing risk prediction models for SLNB positivity in melanoma.

DATA SOURCES: Embase and MEDLINE were searched from inception to May 1, 2024, for English language articles.

STUDY SELECTION: All studies that either developed or validated a risk prediction model (defined as any calculator that combined more than 1 variable to provide a patient estimate for probability of melanoma SLNB positivity) with a corresponding measure of model discrimination were considered for inclusion by 2 reviewers, with disagreements adjudicated by a third reviewer.

DATA EXTRACTION AND SYNTHESIS: Data were extracted in duplicate according to Data Extraction for Systematic Reviews of Prediction Modeling Studies, Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis, and Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guidelines. Effects were pooled using random-effects meta-analysis.

MAIN OUTCOME AND MEASURES: The primary outcome was the mean pooled C statistic. Heterogeneity was assessed using the I2 statistic.

RESULTS: In total, 23 articles describing the development of 21 different risk prediction models for SLNB positivity, 20 external validations of 8 different risk prediction models, and 9 models that included sufficient information to obtain individualized patient risk estimates in routine preprocedural clinical practice were identified. Among all risk prediction models, the pooled weighted C statistic was 0.78 (95% CI, 0.74-0.81) with significant heterogeneity (I2 = 97.4%) that was not explained in meta-regression. The Memorial Sloan Kettering Cancer Center and Melanoma Institute of Australia models were most frequently externally validated with both having strong and comparable discriminative performance (pooled weighted C statistic, 0.73; 95% CI, 0.69-0.78 vs pooled weighted C statistic, 0.70; 95% CI, 0.66-0.74). Discrimination was not significantly different between models that included gene expression profiles (pooled C statistic, 0.83; 95% CI, 0.76-0.90) and those that only used clinicopathologic features (pooled C statistic, 0.77; 95% CI, 0.73-0.81) (P = .11).

CONCLUSIONS AND RELEVANCE: This systematic review and meta-analysis found several risk prediction models that have been externally validated with strong discriminative performance. Further research is needed to evaluate the associations of their implementation with preprocedural care.

PMID:40072444 | DOI:10.1001/jamadermatol.2025.0113