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Nevin Manimala Statistics

Cash Transfers and Their Effect on Maternal and Young Children’s Health: A Randomized Clinical Trial

JAMA Pediatr. 2025 Jun 16. doi: 10.1001/jamapediatrics.2025.1612. Online ahead of print.

ABSTRACT

IMPORTANCE: Mothers and children in low-income households are more likely to experience worse mental and physical health than those from higher-income households.

OBJECTIVE: To determine the effect of 4 years of monthly unconditional cash transfers on the mental health of mothers with low-income and the physical health of mothers and children.

DESIGN, SETTING, AND PARTICIPANTS: This was a parallel-group, randomized clinical trial conducted from May 2018 to July 2023. Mother-infant dyads were recruited (May 2018-June 2019) from postpartum wards in 12 hospitals in 4 cities: Omaha, Nebraska; Minneapolis/St Paul, Minnesota; New Orleans, Louisiana; and New York, New York. Data were analyzed from September 2023 to February 2025.

INTERVENTIONS: Mothers were randomly assigned to receive either a high-cash gift ($333 per month) or a low-cash gift ($20 per month) on debit cards. The cash gifts continued for the first 6 years of their children’s lives. Data analyzed here were collected after 4 years of monthly transfers.

MAIN OUTCOMES AND MEASURES: Outcomes were preregistered and measured around the child’s fourth birthday. Maternal outcomes included depression, anxiety, and body mass index (BMI). Child outcomes included age- and sex-adjusted BMI percentile and maternal report of child health (overall health, times sick in the past year, and presence of chronic health conditions).

RESULTS: A total of 1000 mother-infant dyads (mean [SD] maternal age, 27.0 [5.8] years) were included in this study. Among those mothers, 400 were randomly assigned to receive the $333 high-cash gift and 600 received the $20 low-cash gift on debit cards. Data were available from 891 mother-child dyads. No statistically detectable group differences were found in maternal depressive symptoms (effect size [ES], 0.04; 95% CI, -0.08 to 0.17; P = .51), anxiety (ES, 0.12; 95% CI, -0.02 to 0.25; P = .09), or BMI (ES, -0.06; 95% CI, -0.21 to 0.09; P = .42). In addition, there were no statistically detectable group differences in child BMI percentile (ES, -0.03; 95% CI, -0.17 to 0.12; P = .73) or overall child health (ES, 0.08; 95% CI, -0.07 to 0.22; P = .30).

CONCLUSIONS AND RELEVANCE: Monthly unconditional cash transfers totaling approximately $15 000 over 4 years to mothers with low incomes did not improve maternal mental health, maternal or child BMI, or maternal report of children’s health. These results could reflect the absence of causal connections between cash transfers and health, the possibility that impacts of early childhood income may not appear until later in life, or that an 18% increase in income is insufficient to overcome the structural vulnerabilities associated with poverty that contribute to health.

TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03593356.

PMID:40522644 | DOI:10.1001/jamapediatrics.2025.1612

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Nevin Manimala Statistics

Life Expectancy of American Indian and Alaska Native Persons and Underreporting of Mortality in Vital Statistics

JAMA. 2025 Jun 16. doi: 10.1001/jama.2025.8126. Online ahead of print.

ABSTRACT

IMPORTANCE: Mortality of American Indian and Alaska Native (AI/AN) persons is known to be high but may be underreported in routine vital statistics.

OBJECTIVE: To estimate age-specific mortality rates and life expectancy for non-Hispanic AI/AN individuals and other racial and ethnic groups, using self-identified race and ethnicity data in a national cohort, circumventing errors due to racial misclassification on death certificates.

DESIGN, SETTING, AND PARTICIPANTS: This longitudinal cohort study used data from the Mortality Disparities in American Communities (MDAC) study, a nationally representative cohort created through the US Census Bureau’s linkage of the 2008 American Community Survey (ACS) with death records from the National Vital Statistics System through 2019. The cohort included 4 135 000 ACS respondents, including 30 500 who self-identified as AI/AN (alone) and 58 000 who self-identified as AI/AN alone or in combination with another race (AI/AN-AiC).

EXPOSURE: Self-identified race and ethnicity.

MAIN OUTCOMES AND MEASURES: Age-specific mortality rates and life expectancy, estimated using continuous time, nonparametric period survival curves by self-identified race and ethnicity; comparisons to estimates from the US Centers for Disease Control and Prevention (CDC) WONDER database based on race and ethnicity reported on death certificates; and classification ratios for self-reported vs death certificate-recorded AI/AN race among decedents in the MDAC. Analyses were stratified by time period, sociodemographic factors, and cause of death.

RESULTS: Life expectancy of self-identified AI/AN individuals was 72.7 years (73.9 for AI/AN-AiC individuals), 6.5 years less than the US-wide average of 79.2 years. The AI/AN vs US average life expectancy gap widened from 4.1 years in 2008 to 2010 to 8.0 years in 2017 to 2019. Among self-identified AI/AN and AI/AN-AiC decedents, only 59.0% and 39.8% had AI/AN race reported on their death certificates, yielding classification ratios of 1.26 and 1.81, respectively. AI/AN race was most frequently underreported for heart disease and cancer deaths and less frequently for deaths from violence, drugs, and alcohol. In CDC WONDER data (based on race and ethnicity from death certificates), age-standardized mortality was 5% higher for AI/AN individuals than the US average (1067 vs 1016 deaths per 100 000). In MDAC data, mortality for self-identified AI/AN individuals was 42% higher (1420 vs 999 deaths per 100 000). The AI/AN life expectancy gap was 2.9 times larger in the MDAC than in unadjusted official statistics.

CONCLUSIONS AND RELEVANCE: This longitudinal cohort study found that large life expectancy differences between AI/AN individuals and other US residents have been underestimated due to racial misclassification on death certificates, resulting in the statistical erasure of Indigenous people in routine vital statistics.

PMID:40522635 | DOI:10.1001/jama.2025.8126

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Nevin Manimala Statistics

Advanced Characterization of Vitreous Hyperreflective Dots via OCT-Derived Metrics: A Cross-Sectional Study

Ophthalmol Ther. 2025 Jun 16. doi: 10.1007/s40123-025-01182-3. Online ahead of print.

ABSTRACT

INTRODUCTION: The use of optical coherence tomography (OCT) as a potential tool for the measurement of vitreous inflammation has been previously described as a more objective and reproducible method when compared to historically known subjective scales. In this study, our objective is to evaluate OCT’s ability to characterize vitreous hyperreflective dots (VHDs) across eyes with varying conditions, including healthy controls, vitreous degenerations, intraocular inflammation, and others.

METHODS: We utilized a purpose built semiautomated software comprising an image binarization tool to segment OCT scans of 61 eyes, comprising 15 eyes with vitreous degenerations, 20 uveitic eyes, 17 healthy controls, and 9 with other eye conditions. The vitreous dot index (VDI) was computed by determining the number of dots (VDI-N) and the dot area (VDI-A). VHDs were identified as the hyperreflective shadows observed in OCT images within segmented areas of the vitreous, stratified as zones I, II, and III. We compared the difference between groups using analysis of variance (ANOVA). Intergrader reliability was evaluated by comparing results obtained by two trained independent graders, employing intraclass correlation coefficient (ICC) analysis.

RESULTS: When the medians of VDI-N and VDI-A were compared in healthy controls, patients with uveitis, patients with vitreous degeneration, and others, patients with vitreous degeneration had the highest VDI-N median (2.61 ± 2.76 mm3 p < 0.001) followed by healthy controls (0.48 ± 0.87 mm3 p < 0.001) in zone l. As for VDI-A in the same zone, healthy controls had the greatest median (0.71 ± 0.96, p < 0.001) among the different groups. In zone II, uveitis and the healthy control group had similar medians for VDI-N (0.03 ± 0.36 and 0.03 ± 0.29, p < 0.001 respectably) and VDI-A was greater in the vitreous degeneration group (0.40 ± 0.50 p < 0.001). Zone III had lower VDI-N and VDI-A; patients with uveitis and patients with vitreous degeneration had equal VDI-N (0.00 ± 0.03 p < 0.001) and patients with uveitis had the higher VDI-A among the rest of the groups (0.00 ± 0.65 p < 0.001). For the total vitreous (TV), the highest VDI-N was found in patients with vitreous degeneration (2.92 ± 2.85 p < 0.001) while the highest VDI-A was in the uveitis group patients (0.66 ± 1.31) p < 0.001. The average vitreous dot density index and the average vitreous dot reflectivity index (VDRI) in the TV were greater in patients with vitreous degeneration (2.15 × 10-5 ± 1.52 × 10-5) and patients with uveitis (0.13 ± 0.08), respectively. When comparing VDI markers using a Kruskal-Wallis nonparametric one-way ANOVA test, we found that only the average vitreous dot reflectivity index in zone I and VDI-A in TV were statistically significant. However, only the reflectivity index was significant when comparing patients with vitreous degeneration and healthy controls in a pairwise analysis.

CONCLUSION: While vitreous inflammation scales must evolve toward more objective metrics, our findings suggest that VHDs on OCT can act as confounders, as they may represent normal vitreous cells or even the presence of vitreous degeneration. The reflectivity index appears to have better reproducibility than simple count; however, when searching for a more objective parameter for measuring vitreous inflammation, vitreous degeneration must be considered.

PMID:40522626 | DOI:10.1007/s40123-025-01182-3

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Nevin Manimala Statistics

Estimating Risks of Central Nervous System Disturbance Associated with Medications for Herpes Zoster: Findings from a Regional Population-Based Cohort Study Using the Shizuoka Kokuho Database

Drugs Real World Outcomes. 2025 Jun 16. doi: 10.1007/s40801-025-00500-2. Online ahead of print.

ABSTRACT

BACKGROUND: Herpes zoster commonly occurs in older adults, whose renal function often declines, necessitating careful dosing of antivirals such as acyclovir, valacyclovir, and famciclovir. Insufficient dose adjustment can increase central nervous system (CNS) disturbance risk. Although previous reports show varying neurotoxic risk among these drugs, the safety profiles of these drugs remain underexplored. CNS disturbance significantly impacts quality of life, but it is rare and primarily documented through case reports, with little thorough investigation or comparison across drugs.

OBJECTIVE: This study aims to evaluate the potential risks of CNS disturbance associated with acyclovir and valacyclovir compared with famciclovir in patients with herpes zoster, highlighting the potential influence of renal function and dose adjustments.

METHODS: We conducted a population-based cohort study using data from the National Health Insurance and the Late-Stage Medical Care System for the Elderly in Japan, including patients diagnosed with herpes zoster and newly prescribed oral or intravenous antiviral drugs between April 2012 and September 2021. The outcome was defined as the occurrence of CNS disturbance within 1 month from the index date. Patients with neurological, infectious or psychiatric disorders during the 1-year baseline period were excluded. The incidence of CNS disturbance with 95% confidence intervals (CIs) was compared between dialysis and nondialysis patients, owing to incomplete renal function data. In addition, we compared the incidence of CNS disturbance among groups using propensity score matching to adjust for confounders, with famciclovir users as the control group. Postmatching, risk differences with 95% CIs, and number needed to harm (NNH) were calculated.

RESULTS: The final cohort consisted of 82,646 patients (8646 acyclovir, 46,643 valacyclovir, and 27,357 famciclovir users). Severe renal dysfunction was associated with CNS disturbance. The CNS disturbance incidence was 0.33% in nondialysis and 2.29% (risk difference 1.96%, 95% CI [0.39-3.53]) in dialysis patients using acyclovir/valacyclovir versus 0.18% and 0.60% (risk difference 0.42%, 95% CI [- 0.76 to 1.6]) for famciclovir, respectively. After propensity score matching, CNS disturbances were observed in 0.50% of patients in the acyclovir group versus 0.17% in the famciclovir group and in 0.29% of patients in the valacyclovir group versus 0.17% in the famciclovir group. The risk of CNS disturbance remained higher in both the acyclovir group (risk difference 0.33%, 95% CI [0.16-0.51], NNH 278) and the valacyclovir group (0.12%, [0.04-0.19], 833) compared with the famciclovir group.

CONCLUSIONS: Acyclovir and valacyclovir, when compared with famciclovir, are associated with an increased risk of CNS disturbance in patients with herpes zoster, particularly among those with severe renal dysfunction. These findings highlight the importance of careful consideration of renal function when determining antiviral dosing and support the development of clinical guidelines to enhance the safety of antiviral treatments, though further investigation into additional kidney function stages is needed.

PMID:40522612 | DOI:10.1007/s40801-025-00500-2

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Nevin Manimala Statistics

Reflections on Conducting a Large Replication Project in Sports and Exercise Science

Sports Med. 2025 Jun 16. doi: 10.1007/s40279-025-02200-x. Online ahead of print.

ABSTRACT

This review reflects on the lessons and limitations of the first large, collaborative replication project in sports and exercise science. We discuss the challenges and barriers faced, while also exploring the broader contribution of replication to the field. This project faced many practical challenges when preparing studies for replication, specifically the poor reporting of statistical information, the availability of original raw data and the prioritisation of feasibility at the risk of some bias. However, we believe these issues reflect the larger sports and exercise science field. Therefore, our research culture needs to change to minimise the active engagement in behaviours that reduce reproducibility and replicability, and enable collective evaluation of research in line with the foundations of scientific rigour. In addition, discourse with the original study authors was a challenging process as many were unwilling to engage and this indicates a problematic perception of replication. We also reflect on the contribution of replication to theory development in sports and exercise science so that this review can serve as a valuable resource for understanding replication and can aid future replication efforts.

PMID:40522611 | DOI:10.1007/s40279-025-02200-x

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Nevin Manimala Statistics

Estimating the Replicability of Sports and Exercise Science Research

Sports Med. 2025 Jun 16. doi: 10.1007/s40279-025-02201-w. Online ahead of print.

ABSTRACT

BACKGROUND: The replicability of sports and exercise research has not been assessed previously despite concerns about scientific practices within the field.

AIM: This study aims to provide an initial estimate of the replicability of applied sports and exercise science research published in quartile 1 journals (SCImago journal ranking for 2019 in the Sports Science subject category; www.scimagojr.com ) between 2016 and 2021.

METHODS: A formalised selection protocol for this replication project was previously published. Voluntary collaborators were recruited, and studies were allocated in a stratified and randomised manner on the basis of equipment and expertise. Original authors were contacted to provide deidentified raw data, to review preregistrations and to provide methodological clarifications. A multiple inferential strategy was employed to analyse the replication data. The same analysis (i.e. F test or t test) was used to determine whether the replication effect size was statistically significant and in the same direction as the original effect size. Z-tests were used to determine whether the original and replication effect size estimates were compatible or significantly different in magnitude.

RESULTS: In total, 25 replication studies were included for analysis. Of the 25, 10 replications used paired t tests, 1 used an independent t test and 14 used an analysis of variance (ANOVA) for the statistical analyses. In all, 7 (28%) studies demonstrated robust replicability, meeting all three validation criteria: achieving statistical significance (p < 0.05) in the same direction as the original study and showing compatible effect size magnitudes as per the Z test (p > 0.05).

CONCLUSION: There was a substantial decrease in the published effect size estimate magnitudes when replicated; therefore, sports and exercise science researchers should consider effect size uncertainty when conducting subsequent power analyses. Additionally, there were many barriers to conducting the replication studies, e.g., original author communication and poor data and reporting transparency.

PMID:40522610 | DOI:10.1007/s40279-025-02201-w

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Nevin Manimala Statistics

Health and Performance Challenges in the Era of Human Enhancement: Insights from Sport Medicine Professionals

Sports Med. 2025 Jun 16. doi: 10.1007/s40279-025-02258-7. Online ahead of print.

ABSTRACT

BACKGROUND: In the pursuit of sporting success, some elite athletes prioritise peak performance over long-term health, frequently resulting in significant and enduring health consequences. The Enhanced Games (TEG) position themselves as a bold experiment in transhumanism, advocating for the use of performance-enhancing drugs (PEDs), including methods banned by World Anti-Doping Agency (WADA), to push the boundaries of human athletic potential.

OBJECTIVES: The aim of this study is to explore the perspectives of sport physicians, sport scientists, physiotherapists and other allied healthcare professionals on treating and supporting “enhanced athletes”, with the view of informing future guidelines.

METHODS: Participants were invited via email and personal contacts within sport medicine communities to complete a brief anonymous survey via QuestionPro™. Descriptive statistics were performed using Excel™ and RStudio™.

RESULTS: A total of 323 healthcare professionals responded (82% were sport physicians), among whom 74% expressed a willingness to treat acute lesions and/or chronic diseases in “enhanced athletes”. In comparison, a considerable minority (30%) expressed support for assisting athletes in their use of PEDs and methods under medically supervised conditions, with high consistency across professional roles. A relatively high readiness was observed in sport physicians treating acute (77% versus 58%; p < 0.01) and chronic (75% versus 63%; p = 0.11) diseases for “enhanced athletes”. As far as WADA rules and/or national anti-doping laws apply, this support presupposes compliance with the code and the respective national laws to protect physicians from serious professional, legal and personal consequences.

CONCLUSION: The preliminary findings align with the broader goal of fostering a sport culture that values both peak performance and the short- and long-term health of all participants. These results emphasise the necessity of implementing professional guidelines and comprehensive support systems designed to safeguard the long-term well-being of all athletes and underscore the urgent need for further research into the impact of TEG on sport and its community.

PMID:40522609 | DOI:10.1007/s40279-025-02258-7

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Sizing It Up: Concordance between Breast Imaging and Pathologically Determined Tumor Measurement

Ann Surg Oncol. 2025 Jun 16. doi: 10.1245/s10434-025-17663-5. Online ahead of print.

ABSTRACT

BACKGROUND: Accurate preoperative imaging of breast tumor size is essential, as small measurement differences can influence the treatment strategy. This study evaluates the accuracy of tumor size estimation by mammography, ultrasound, and magnetic resonance imaging (MRI) compared with pathology and examines factors influencing imaging performance.

PATIENTS AND METHODS: We retrospectively analyzed patients with breast cancer treated from 2019 to 2024. Measurements were considered concordant if they fell within ±20% of the pathological size. Statistical analyses performed include paired t-tests, chi-squared tests, Lin’s concordance correlation coefficient (CCC), and logistic regression. Python-based framework was used to identify the most accurate weighted formula.

RESULTS: We included 460 patients with a median age of 57 (26-90) years. MRI had the highest concordance (62%), outperforming mammography (57%) and ultrasound (53%) (p = 0.004). Our alternative weighted average formula (0.66 × MRI size + 0.35 × US size) yielded the highest concordance rate (65.2%, CCC = 0.785). Average tumor size on pathology was 17.31 mm. MRI slightly overestimated the size (18.38 mm, p = 0.482), while mammography (14.8 mm, p = 0.06) and ultrasound (14.31 mm, p = 0.019) underestimated. MRI demonstrated the highest accuracy in T-stage classification (89%). Concordance was highest for masses without non-mass enhancement (NME) (CCC = 0.834) and declined with NME (CCC = 0.635). MRI accuracy improved in tumors > 15 mm (OR 2.47) and high-grade tumors (OR 1.75) but declined in extremely dense breasts (OR 0.42) and lobular histology (OR 0.46).

CONCLUSIONS: MRI demonstrated the highest concordance with tumor size and T stage. Its accuracy improved in larger and high-grade tumors but decreased with dense breasts, NME, and lobular histology. A combined imaging approach using MRI and ultrasound may enhance preoperative size estimation.

PMID:40522576 | DOI:10.1245/s10434-025-17663-5

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Predictors of prolonged length of stay in patients undergoing laser interstitial thermal therapy for intracranial tumors

J Neurooncol. 2025 Jun 16. doi: 10.1007/s11060-025-05101-1. Online ahead of print.

ABSTRACT

PURPOSE: Laser interstitial thermal therapy (LITT) offers a minimally invasive approach for treating intracranial pathologies while offering shorter length of stays (LOS) as compared to traditional craniotomies. Yet, some patients still face prolonged LOS (pLOS), highlighting the need to identify factors contributing to pLOS to improve outcomes.

METHODS: We retrospectively reviewed patients who underwent LITT for intracranial pathologies at our institution from 2012 to 2023. Patients with LOS ≥ 75th percentile formed the study group, while those with LOS < 75th percentile formed control group. Patient demographics and perioperative factors were analyzed. Bivariate statistical analyses included Fisher’s exact test, chi-square test, and t-tests. Univariate and multivariate logistic regression identified significant predictors of pLOS.

RESULTS: Of 294 patients in this study, 73 patients in the study group (mean age 62.14 ± 11.63 years, 54.8% males) with a median LOS of 4.12 [IQR: 3.01-6.67] days were compared to 221 controls (mean age 59.50 ± 14.01 years, 40.3% males) with a median LOS of 1.92 [IQR: 1.86-2.01] days. Upon multivariate analysis, higher mFI-5 scores (OR 1.80; 95% CI [1.31-2.47]; p < 0.001), preoperative neurologic deficits (OR 2.27; 95% CI [1.09-4.76]; p = 0.029), and preoperative tumor volume (OR 2.03; 95% CI [1.46-2.83]; p < 0.001) were significantly associated with pLOS. Operative time, number of pullbacks, and extent of ablation were not significantly associated with pLOS (p > 0.05).

CONCLUSION: To our knowledge, this is the first study to identify preoperative mFI-5 score, neurological deficit, and tumor volume as independent predictors of pLOS in patients undergoing LITT for intracranial pathologies.

PMID:40522561 | DOI:10.1007/s11060-025-05101-1

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Nevin Manimala Statistics

Automated feature learning and survival prognostication in grade 4 glioma using supervised machine learning models

J Neurooncol. 2025 Jun 16. doi: 10.1007/s11060-025-05099-6. Online ahead of print.

ABSTRACT

OBJECTIVE: WHO grade 4 glioma is the most common primary malignant brain tumor, with a median survival of only 14.6 months. Predicting survival outcomes remains challenging due to the tumor’s heterogeneity and the influence of multiple clinical factors. Machine learning (ML) techniques have demonstrated superior predictive performance compared to traditional statistical models. Embedded feature-selection techniques such as Lasso shrinkage or Random-Forest importance scores are widely used, yet grade-4-glioma prognostic models still rely on an initial clinician-curated variable list and on ad-hoc cut-offs (e.g., “top X features” or “above certain threshold”) when deciding how many ranked features to keep-choices that markedly influence model accuracy. We therefore developed a fully data-driven pipeline that begins with an unrestricted pool of clinical, functional, and biomarker variables, employs SHAP values for global importance ranking, and uses automated feature-subset optimization to identify the most optimal combination of predictors that maximizes survival-prediction performance in grade-4 glioma.

METHOD: We retrospectively analyzed clinical data from 764 patients who underwent grade 4 glioma resection at a single institution. Five ML models (XGBoost, AdaBoost, Random Forest, Decision Tree, and Neural Networks) were trained to predict survival time and classify into longer-term survival (≥ 12 months) and short-term survival (< 12 months). Feature selection was performed in two steps: (1) Shapley Additive Explanations (SHAPs) were used to identify the most important prognostic features influencing survival outcomes, and (2) feature-subset optimization was applied to determine the optimal number of top features to be included in each model. 5-fold cross-validation (CV) and holdout testing were performed to evaluate the models’ performance on unseen testing data. Model evaluation was conducted using root mean square error (RMSE) for regression and area under the receiver operating characteristic curve (AUROC) for classification. Decision Curve Analysis (DCA) was performed to evaluate the clinical utility of the models.

RESULTS: Feature selection and model optimization significantly enhanced predictive accuracy across both regression and classification tasks. In regression, AdaBoost achieved the lowest RMSE of 1.69 months after feature selection, outperforming other models. In classification, XGBoost demonstrated the highest AUROC (0.85) on holdout testing, though all ensemble models (XGBoost, Random Forest, and AdaBoost) achieved comparable performance with no statistical significance. DCA revealed that XGBoost and Random Forest achieved the most net benefit of 0.24 and 0.22, respectively. Key prognostic features consistently identified included patient age, tumor location, radiation dose, extent of resection, Karnofsky Performance Score, and MGMT promoter methylation status. Biomarkers such as Ki-67, ATRX, and TP53 also emerged as important predictors of survival outcomes. The model also uncovered several cognitive and functional deficits-including preoperative and postoperative language deficits, permanent motor deficits, and perioperative seizures-that were previously underutilized in survival prediction models.

CONCLUSION: ML-based feature selection enhances survival prediction in grade 4 glioma by systematically identifying the most relevant prognostic factors while minimizing human bias. Our findings suggest that ensemble models, and particularly AdaBoost, offer robust prognostic capabilities. These insights can aid clinicians in personalized treatment planning and patient counseling.

PMID:40522559 | DOI:10.1007/s11060-025-05099-6