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Role of inflammatory blood parameters from complete blood count in predicting ovarian follicular density in cancer patients undergoing ovarian tissue cryopreservation

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Journal of Ovarian Research 2025年第1期18卷 1-9页

作者： Ronchetti, Livia Terrenato, Irene Lobascio, Anna Maria Iacobelli, Marcello Ferretti, Margherita Setti Boubaker, Nouha Sperati, Francesca Mandoj, Chiara Mancini, Emanuela Carosi, Mariantonia Vizza, Enrico Corrado, Giacomo Pathology Unit IRCCS Regina Elena National Cancer Institute Via Elio Chianesi 53 Rome 00144 Italy Biostatistics & Bioinformatics IRCCS Regina Elena National Cancer Institute Rome Italy Gynecologic Oncology Unit IRCCS Regina Elena National Cancer Institute Rome Italy SAFU Unit IRCCS Regina Elena National Cancer Institute Rome Italy UOSD Clinical Trial Center and Biostatistics & Bioinformatics San Gallicano Dermatological Institute IRCCS Rome Italy Clinical Pathology Unit and Cancer Biobank IRCCS Regina Elena National Cancer Institute Rome Italy Department of Women and Child Health Division of Gynecologic Oncology Fondazione Policlinico Universitario A. Gemelli IRCCS Rome Italy

Background: Inflammation is a key feature of neoplastic diseases, especially cancer. Predicting follicular density (FD) in ovarian cortical tissue is essential for evaluating ovarian tissue cryopreservation (OTC) outcomes in fertility preservation. However, to date, no studies have explored the role of inflammatory markers in predicting FD in OTC patients. This study aims to investigate the relationship between blood inflammatory parameters and FD in this population. Methods: We conducted a retrospective observational study on 101 OTC patients. The primary goal was to assess whether parameters from Complete Blood Count (CBC) that include White Blood Cells (WBC), absolute neutrophil count, absolute lymphocyte count, Neutrophil/Lymphocyte Ratio (NLR), Mean Platelet Volume (MPV), Platelet Count (PC), MPV/PC and the Platelet/Lymphocyte Ratio (PLR) could predict FD. We also evaluated the impact of factors such as oncological diagnosis, smoking, Body Mass Index (BMI), and germline BRCA mutations. Spearman’s correlation coefficient and the Mann-Whitney test were used for analysis. Results: Significant correlations were found in patients aged between 27 and 31. In this group, NLR was inversely correlated with FD (Rho = -0.374, p = 0.032), while lymphocyte count (Rho = 0.371, p = 0.034) and MPV/PC (Rho = 0.365, p = 0.037) were positively correlated with FD. An inverse correlation was also found between PLR and FD (Rho = -0.38, p = 0.028). Conclusions: Our findings suggest that NLR, lymphocyte count, MPV/PC and PLR may be useful in predicting FD in a subgroup of OTC patients. Larger studies are needed to confirm these results. © The Author(s) 2025.

关键词： Cancer Fertility preservation Inflammatory parameters Ovarian follicular density Ovarian reserve Ovarian tissue cryopreservation (OTC)

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Factors affecting power in stepped wedge trials when the treatment effect varies with time

arXiv

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arXiv 2025年

作者： Kenny, Avi Voldal, Emily C. Xia, Fan Chan, Kwun Chuen Gary Heagerty, Patrick J. Hughes, James P. Department of Biostatistics & Bioinformatics Duke University United States Global Health Institute Duke University United States Vaccine and Infectious Disease Division Fred Hutch Cancer Center United States Department of Epidemiology and Biostatistics University of California San Francisco United States Department of Biostatistics University of Washington United States

Background Stepped wedge cluster randomized trials (SW-CRTs) have historically been analyzed using immediate treatment (IT) models, which assume the effect of the treatment is immediate after treatment initiation and subsequently remains constant over time. However, recent research has shown that this assumption can lead to severely misleading results if treatment effects vary with exposure time, i.e. time since the intervention started. Models that account for time-varying treatment effects, such as the exposure time indicator (ETI) model, allow researchers to target estimands such as the time-averaged treatment effect (TATE) over an interval of exposure time, or the point treatment effect (PTE) representing a treatment contrast at one time point. However, this increased flexibility results in reduced power. Methods In this paper, we use public power calculation software and simulation to characterize factors affecting SW-CRT power. Key elements include choice of estimand, study design considerations, and analysis model selection. Results For common SW-CRT designs, the sample size (individuals per cluster-period) must be increased by a factor of roughly 2.5 to 3 to maintain 90% power when switching from an IT model to an ETI model (targeting the TATE over the entire study). However, the inflation factor is lower when considering TATE estimands over shorter periods that exclude longer exposure times for which there is limited information. In general, SW-CRT designs (including the "staircase" variant) have much greater power for estimating "short-term effects" relative to "long-term effects". For an ETI model targeting a TATE estimand, substantial power can be gained by adding time points to the start of the study or increasing baseline sample size, but surprisingly little power is gained from adding time points to the end of the study. More restrictive choices for modeling the exposure time or calendar time trends (e.g., splines or linear terms) have little effect o

关键词： Design for testability

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ASO Visual Abstract: Medicaid Expansion is Associated with Differences in Local Therapy for Non-small Cell Lung Cancer

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Annals of Surgical Oncology 2025年 1-2页

作者： Madeka, Isheeta Mack, Shale J. Rshaidat, Hamza Ishwar, Anurag Koeneman, Scott Alaparthi, Sneha Whitehorn, Gregory L. Ho, Anie Grenda, Tyler R. Evans, Nathaniel R. Okusanya, Olugbenga T. Division of Thoracic Surgery Department of Surgery Thomas Jefferson University Hospital Philadelphia USA Sidney Kimmel Medical College at Thomas Jefferson University Philadelphia USA Department of Surgery University of Chicago Chicago USA Division of Biostatistics and Bioinformatics Thomas Jefferson University Philadelphia USA

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Peripheral intravascular lithotripsy to facilitate transfemoral transcatheter aortic valve replacement – Defining optimal treatable peripheral arterial disease burden

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Cardiovascular Revascularization Medicine 2025年 73卷 31-37页

作者： Tom, Stephanie Tully, Andy Kikuchi, Yuta Crawford, Kaylyn Binongo, José Wei, Jane Wenjing Gleason, Patrick Xie, Joe Devireddy, Chandan M. Grubb, Kendra J. Department of Surgery Emory University Atlanta GA United States University of Maryland Department of Surgery Baltimore MD United States Division of Cardiothoracic Surgery Emory University Atlanta GA United States Structural Heart and Valve Center Emory University Atlanta GA United States Emory University School of Medicine Atlanta GA United States Department of Biostatistics and Bioinformatics Rollins School of Public Health Emory University Atlanta GA United States Division of Cardiology Emory University Atlanta GA United States

Background: Transfemoral transcatheter aortic valve replacement (TF-TAVR) has proven superior to alternative access. However, some patients evaluated for TF-TAVR are unfit secondary to peripheral arterial disease (PAD). Peripheral intravascular lithotripsy (IVL) can facilitate femoral access. This study aimed to characterize optimal lesions that can be treated with IVL. Methods: Single-center, retrospective analysis of an institutional database, queried from 1/2018 through 7/2023 for all patients who underwent TAVR. Patients who received IVL-facilitated transfemoral access were analyzed. Results: Of 2862 TAVR cases identified, 92 (3.2 %) underwent lithotripsy. The IVL-facilitated cohort had a mean age of 78 ± 9.2 years and 45 % were female. The right common iliac artery was most treated (47). Most IVL was performed with 7-mm balloons (73.9 %). All cases were successful. 30-day mortality was 1.1 % (1/92). Conclusions: In our cohort, complications after IVL-facilitated TF-TAVR were more common with small vessel diameter (≤4.7 mm), significant luminal loss (>50 % stenosis), and heavy calcium burden (arc calcification >180°). The findings support the use of IVL to expand the population of patients who can undergo TF-TAVR without the increased risks associated with the various forms of alternative access. Summary for annotated table of contents: IVL-facilitated TF-TAVR is safe and feasible. Despite its introduction to TAVR clinical practice in 2018, IVL-facilitated TF-TAVR is not regularly performed and could increase the population of patients eligible for TF-TAVR. © 2024

关键词： Calcified iliofemoral access Intravascular lithotripsy PAD TAVR TAVR access

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Bayesian high-dimensional biological pathway-guided mediation analysis with application to metabolomics

arXiv

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arXiv 2025年

作者： Zhang, Yuzi Liang, Donghai Tan, Youran Dunlop, Anne L. Chang, Howard H. Division of Biostatistics The Ohio State University ColumbusOH United States Department of Environmental Health Emory University AtlantaGA United States Department of Gynecology and Obstetrics Emory University AtlantaGA United States Department of Biostatistics and Bioinformatics Emory University AtlantaGA United States

With advances in high-resolution mass spectrometry technologies, metabolomics data are increasingly used to investigate biological mechanisms underlying associations between exposures and health outcomes in clinical and epidemiological studies. Mediation analysis is a powerful framework for investigating a hypothesized causal chain and when applied to metabolomics data, a large number of correlated metabolites belonging to interconnected metabolic pathways need to be considered as mediators. To identify metabolic pathways as active mediators, existing approaches typically focus on first identifying individual metabolites as active mediators, followed by posthoc metabolic pathway determination. These multi-stage procedures make statistical inference challenging. We propose a Bayesian biological pathway-guided mediation analysis that aims to jointly analyze all metabolites together, identify metabolic pathways directly, and estimate metabolic pathway-specific indirect effects. This is accomplished by incorporating existing biological knowledge of metabolic pathways to account for correlations among mediators, along with variable selection and dimension reduction techniques. Advantages of the proposed method is demonstrated in extensive simulation studies with real-word metabolic pathway structure. We apply the proposed method to two studies examining the role of metabolism in mediating (1) the effect of Roux-en-Y gastric bypass on glycemic control, and (2) the effect of prenatal exposure to per- and polyfluoroalkyl substances (PFAS) on gestational age at birth. Our analyses confirm metabolic pathways previously identified and provide additional uncertainty quantification for the mediation effects. Copyright © 2025, The Authors. All rights reserved.

关键词： Metabolism

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Systematic Bias of Machine Learning Regression Models and Correction

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IEEE Transactions on Pattern Analysis and Machine Intelligence 2025年第6期47卷 4974-4983页

作者： Hwiyoung Lee Shuo Chen Division of Biostatistics and Bioinformatics Department of Epidemiology and Public Health University of Maryland School of Medicine Baltimore MD USA University of Maryland Institute for Health Computing (UM-IHC) North Bethesda MD USA Maryland Psychiatric Research Center (MPRC) University of Maryland School of Medicine Catonsville MD USA

Machine learning models for continuous outcomes often yield systematically biased predictions, particularly for values that largely deviate from the mean. Specifically, predictions for large-valued outcomes tend to be negatively biased (underestimating actual values), while those for small-valued outcomes are positively biased (overestimating actual values). We refer to this linear central tendency warped bias as the “systematic bias of machine learning regression”. In this paper, we first demonstrate that this systematic prediction bias persists across various machine learning regression models, and then delve into its theoretical underpinnings. To address this issue, we propose a general constrained optimization approach designed to correct this bias and develop computationally efficient implementation algorithms. Simulation results indicate that our correction method effectively eliminates the bias from the predicted outcomes. We apply the proposed approach to the prediction of brain age using neuroimaging data. In comparison to competing machine learning regression models, our method effectively addresses the longstanding issue of “systematic bias of machine learning regression” in neuroimaging-based brain age calculation, yielding unbiased predictions of brain age.

关键词： Machine learning Systematics Predictive models Linear programming Testing Brain modeling Neuroimaging Training Random forests Optimization

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CD19 CAR-T With Axicabtagene Ciloleucel in R/R Large B-Cell Lymphoma With/Without Prior Autologous Stem Cell Transplant

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Clinical Lymphoma, Myeloma and Leukemia 2025年第6期25卷 432-439页

作者： Chen, David T. Goloubeva, Olga Rapoport, Aaron P. Dahiya, Saurabh Atanackovic, Djordje Hardy, Nancy Kocoglu, Mehmet Lutfi, Forat Alkhaldi, Hanan Claiborne, John Preston Lee, Seung Tae Kline, Kathryn Law, Jennie Y. Yared, Jean A. Division of Hematology/Oncology Department of Medicine Greenebaum Comprehensive Cancer Center University of Maryland Medical Center University of Maryland School of Medicine Baltimore MD United States Department of Epidemiology and Public Health Division of Biostatistics and Bioinformatics University of Maryland Marlene and Stewart Greenebaum Comprehensive Cancer Center University of Maryland School of Medicine Baltimore MD United States Transplantation & Cellular Therapy Program Division of Hematology/Oncology Department of Internal Medicine Greenebaum Comprehensive Cancer Center University of Maryland Medical Center University of Maryland School of Medicine Baltimore MD United States Sidney Kimmel Comprehensive Cancer Center Johns Hopkins University School of Medicine Baltimore MD United States

Background: Anti-CD19 CAR-T therapy has been a breakthrough in treatment of primary refractory or relapsed large B-cell lymphoma (r/r LBCL) and is poised to supplant previous second line of high dose chemotherapy and autologous stem cell transplantation (HDT/ASCT). However, in clinical practice, high risk patients with chemoimmunotherapy sensitive disease continue to receive salvage chemoimmunotherapy or cannot access CAR-T in a timely manner and thus may still proceed to HDT/ASCT. Little is known about clinical outcomes of CAR-T in patients who receive HDT/ASCT compared to those who are transplant-naïve. Design: We conducted a retrospective study of patients with r/r LBCL who previously underwent HDT/ASCT or were transplant-naïve (n = 97) and received axicabtagene ciloleucel after at least 2 prior therapy lines between 1/1/2018 to 12/31/2021. Primary endpoint was progression-free survival (PFS). Secondary endpoints were overall survival (OS), nonrelapse mortality (NRM), and cumulative incidence of relapse/progression. Results: 82 (84.5%) patients were transplant-naïve and 15 (15.5%) previously received HDT/ASCT. No differences were found in the incidence of high-grade cytokine release syndrome or immune effector cell-associated neurotoxicity syndrome, length of hospital admission, or incidence of cytopenia at day 30. 90-day response, PFS, OS, cumulative incidence of relapse/progression, and NRM were not different. Factors that adversely affected outcomes were prior bridging therapy, elevated LDH or thrombocytopenia at time of lymphodepleting chemotherapy, and worse ECOG performance status. Conclusion: Prior treatment with HDT/ASCT does not compromise the safety and efficacy of anti-CD19 CAR-T therapy, suggesting a continued role for HDT/ASCT in treatment of select patients with r/r DLBCL. © 2024

关键词： Autologous HCT Axi-cel CAR-T DLBCL HSCT

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Long-term Update of a Phase 2 Study of Dose-Reduced Radiation in Diffuse Large B-Cell Lymphoma

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International Journal of Radiation Oncology Biology Physics 2025年

作者： Huang, Christina C. Wan, Zihan Niedzwiecki, Donna Prosnitz, Leonard R. Beaven, Anne W. Kelsey, Chris R. Department of Radiation Oncology Duke University Medical Center DurhamNC United States Department of Biostatistics and Bioinformatics Duke University Medical Center DurhamNC United States Department of Medicine Division of Medical Oncology University of North Carolina Medical Center Chapel HillNC United States

Purpose: Consolidation radiation therapy (RT) is often recommended in diffuse large B-cell lymphoma. The current recommended dose of 30 Gy was established in the pre-rituximab and PET-CT era. We hypothesized that following a complete response to modern systemic therapy, as determined by PET-CT, a lower dose of RT would be equally effective. Methods and Materials: Patients with diffuse large B-cell lymphoma or primary mediastinal B-cell lymphoma achieving a complete response by PET-CT (Deauville score 1-3) after ≥4 cycles of rituximab, cyclophosphamide, doxorubicin, vincristine, prednisone or rituximab, etoposide, prednisone, vincristine, cyclophosphamide, doxorubicin were eligible. Consolidation RT dose was 19.5-20 Gy. The primary endpoint of the original study was 5-year freedom from local recurrence. Results: From 2010 to 2016, 62 patients were enrolled. The stage distribution was as follows: I-II (n = 49, 79%) and III-IV (n = 13, 21%). Bulky disease (≥7.5 cm) was present in 24 patients (39%). Most (n = 58, 94%) received rituximab, cyclophosphamide, doxorubicin, vincristine, prednisone. Four cycles were administered to 34% of patients, whereas 66% received 5-6 cycles. A median follow-up was 9 years. Overall, 1 patient experienced local recurrence with freedom from local recurrence of 98% at both 5 and 10 years (95% CI, 88%-99%). Seven patients progressed outside of the RT field. Progression-free survival and overall survival at 10 years were 77% (95% CI, 62%-87%) and 80% (95% CI, 64%-89%), respectively. Conclusions: Long-term results of this phase 2 study, with a median follow-up of 9 years, did not demonstrate late local failures when patients received ∼20 Gy consolidation RT. A larger (n = 240) confirmatory study from the International Lymphoma Radiation Oncology Group evaluating ∼20 Gy of RT after ≥3 cycles of chemoimmunotherapy completed accrual in 2023. © 2025 Elsevier Inc.

关键词： Lung cancer

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Phase 1 trial of durvalumab (anti–PD-L1) combined with lenalidomide in relapsed/refractory cutaneous T-cell lymphoma

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Blood Advances 2025年第9期9卷 2247-2260页

作者： Querfeld, Christiane Palmer, Joycelynne Han, Zhen Wu, Xiwei Yuan, Yate-Ching Chen, Min-Hsuan Su, Chingyu Tsai, Ni-Chun Smith, D. Lynne Hammond, Samantha N. Crisan, Liliana Song, Joo Y. Pillai, Raju Rosen, Steven T. Zain, Jasmine Division of Dermatology Center for Informatics City of Hope Duarte CA United States Department of Pathology Center for Informatics City of Hope Duarte CA United States Department of Hematology and Hematopoietic Cell Transplantation Center for Informatics City of Hope Duarte CA United States Beckman Research Institute Center for Informatics City of Hope Duarte CA United States Division of Biostatistics Center for Informatics City of Hope Duarte CA United States Department of Computational and Quantitative Medicine Center for Informatics City of Hope Duarte CA United States Integrative Genomics Core Center for Informatics City of Hope Duarte CA United States Department of Translational Bioinformatics Center for Informatics City of Hope Duarte CA United States

Selective targeting of the functionally exhausted malignant T cells in cutaneous T-cell lymphoma (CTCL) and distinct cells within the tumor microenvironment (TME) via programmed cell death 1/programmed cell death ligand 1 blockade (durvalumab) may restore an antitumor immune response. The oral immunomodulator lenalidomide, which has activity in CTCL, may enhance durvalumab immune checkpoint blockade. Our phase 1/ 2 clinical trial of durvalumab and lenalidomide in patients with refractory/advanced CTCL sought to assess the safety and tolerability and to identify the maximum tolerated dose and recommended phase 2 dose (RP2D) of lenalidomide plus fixed-dose durvalumab. Secondary and tertiary objectives were to investigate the efficacy and effects on the TME. Thirteen patients were evaluable for toxicities and 12 for dose decisions and response. No serious adverse events (AEs) or dose-limiting toxicities (DLTs) were observed during cycles 1 to 3 (DLT evaluation period), and dose level 3 was identified as the RP2D. The most frequent AEs were tumor flare, fatigue, neutropenia, and leukopenia. Three patients developed grade 1 or 2 autoimmune thyroiditis that resolved with treatment. Best overall and skin response rates were 58.3% (95% confidence interval (95% CI), 27.7-84.8%) and 75% (95% CI: 42.8-94.5%), respectively. The median cycles of treatment were 11, and the median duration of response was 25.5 months. The combination showed clinical activity with 7 partial responses and 4 stable disease. Potentially predictive immune signatures were downregulation of -α signaling via NF-κB, interferon gamma, and phosphoinositide 3 kinase-AKT-mammalian target of rapamycin signaling pathways in responders and upregulation of MYC targets and proinflammatory pathways in nonresponders. Profiling of immune cell compositions revealed changes in individual immune cell clusters based on treatment response. © 2025 American Society of Hematology.

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Privacy-Preserving Machine Learning (PPML) Inference for Clinically Actionable Models

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IEEE Access 2025年 13卷 37431-37456页

作者： Balaban, Baris Magara, Seyma Selcan Yilgor, Caglar Yucekul, Altug Obeid, Ibrahim Pizones, Javier Kleinstueck, Frank Perez-Grueso, Francisco Javier Sanchez Pellise, Ferran Alanay, Ahmet Savas, Erkay Bagci, Cetin Sezerman, Osman Ugur Institute of Health Sciences Acibadem Mehmet Ali Aydinlar University Department of Biostatistics and Bioinformatics Istanbul34638 Turkey Sabanci University Department of Computer Science and Engineering Istanbul34956 Turkey University of Tübingen Department of Computer Science Tübingen72074 Germany Acibadem University School of Medicine Department of Orthopedics and Traumatology Istanbul34750 Turkey Clinique du Dos Elsan Jean Villar Private Hospital Bordeaux33520 France Hospital Universitario La Paz Spine Surgery Unit Madrid28046 Spain Schulthess Klinik Spine Center Division Department of Orthopedics and Neurosurgery Zürich8008 Switzerland Hospital Universitari Vall d'Hebron Spine Surgery Unit Barcelona08035 Spain Bilmed Computer and Software Company Istanbul34742 Turkey

Machine learning (ML) refers to algorithms (often models) that are learned directly from data, germane to past experience. As algorithms have constantly been evolving with the exponential increase of computing power and vastly generated data, privacy of algorithms as well as of data becomes extremely important due to regulations and IP rights. Therefore, it is vital to address privacy and security concerns of both data and model together with other performance metrics when commercializing machine learning models. Our aim is to show that privacy-preserving machine learning inference methods can safeguard the intellectual property of models and prevent plaintext models from disclosing information about the sensitive data employed in training these ML models. Additionally, these methods protect the confidentiality of model users' sensitive patient data. We accomplish this by performing a security analysis to determine an appropriate query limit for each user, using the European Spine Study Group's (ESSG) adult spinal deformity dataset. We implement a privacy-preserving tree-based machine learning inference and run two security scenarios (scenario A and scenario B) containing four parts with progressively increasing the number of synthetic data points, which are used to enhance the accuracy of the attacker's substitute model. A target model is generated with particular operation site(s) in each scenario, and substitute models are built with nine-time threefold cross-validation using the XGBoost algorithm with the remaining sites' data to assess the security of the target model. First, we create box plots of the test sets' accuracy, sensitivity, precision, and F-score metrics to compare the substitute models' performance with the target model. Second, we compare the gain values of the target and substitute models' features. Third, we provide an in-depth analysis to check the inclusion of target model split points in substitute models with a heatmap. Finally, we compare t

关键词： Adversarial machine learning

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